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Agriculture-front-end/dist/libs/tensorflow/3.9.0/tf.min.js
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/**
* @license
* Copyright 2021 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
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")})),1===n.length)return FN(n[0]);var r=n,a={axis:t};return fk.runKernel(sy,r,a)}});var FS=Sk({sigmoid_:function(e){var t={x:kk(e,"x","sigmoid")};return fk.runKernel(nx,t)}});var DS=Sk({slice_:function(e,t,n){var r=kk(e,"x","slice","string_or_numeric");if(0===r.rank)throw new Error("Slicing scalar is not possible");var a={x:r},i={begin:t,size:n};return fk.runKernel(Qb,a,i)}});var OS=Sk({tanh_:function(e){var t={x:kk(e,"x","tanh")};return fk.runKernel(kx,t)}});var MS=Sk({basicLSTMCell_:function(e,t,n,r,a,i){var o=kk(e,"forgetBias","basicLSTMCell"),s=kk(t,"lstmKernel","basicLSTMCell"),u=kk(n,"lstmBias","basicLSTMCell"),l=kk(r,"data","basicLSTMCell"),c=kk(a,"c","basicLSTMCell"),p=kk(i,"h","basicLSTMCell"),h=_S([l,p],1),f=QN(h,s),d=QI(f,u),m=d.shape[0],v=d.shape[1]/4,g=[m,v],y=DS(d,[0,0],g),b=DS(d,[0,v],g),x=DS(d,[0,2*v],g),w=DS(d,[0,3*v],g),k=QI(tS(FS(y),OS(b)),tS(c,FS(QI(o,x))));return[k,tS(OS(k),FS(w))]}});var LS=Sk({batchToSpaceND_:function(e,t,n){var r=kk(e,"x","batchToSpaceND"),a=t.reduce((function(e,t){return e*t}));Vv(r.rank>=1+t.length,(function(){return"input rank is "+r.rank+" but should be > than blockShape.length "+t.length})),Vv(n.length===t.length,(function(){return"crops.length is "+n.length+" but should be equal to blockShape.length "+t.length})),Vv(r.shape[0]%a==0,(function(){return"input tensor batch is "+r.shape[0]+" but is not divisible by the product of the elements of blockShape "+t.join(" * ")+" === "+a}));var i={x:r},o={blockShape:t,crops:n};return fk.runKernel(Qg,i,o)}});var zS=Sk({batchNorm_:function(e,t,n,r,a,i){null==i&&(i=.001);var o,s,u=kk(e,"x","batchNorm"),l=kk(t,"mean","batchNorm"),c=kk(n,"variance","batchNorm");null!=a&&(o=kk(a,"scale","batchNorm")),null!=r&&(s=kk(r,"offset","batchNorm")),Vv(l.rank===c.rank,(function(){return"Batch normalization gradient requires mean and variance to have equal ranks."})),Vv(null==s||l.rank===s.rank,(function(){return"Batch normalization gradient requires mean and 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rank "+c.rank+"."})),null!=o&&Vv(2===o.rank||1===o.rank,(function(){return"Error in batchNorm2D: scale must be rank 2 or rank 1 but got rank "+o.rank+"."})),null!=s&&Vv(2===s.rank||1===s.rank,(function(){return"Error in batchNorm2D: offset must be rank 2 or rank 1 but got rank "+s.rank+"."})),zS(u,l,c,s,o,i)}});var BS=Sk({batchNorm3d_:function(e,t,n,r,a,i){var o,s,u=kk(e,"x","batchNorm"),l=kk(t,"mean","batchNorm"),c=kk(n,"variance","batchNorm");return null!=a&&(o=kk(a,"scale","batchNorm")),null!=r&&(s=kk(r,"offset","batchNorm")),Vv(3===u.rank,(function(){return"Error in batchNorm3D: x must be rank 3 but got rank "+u.rank+"."})),Vv(3===l.rank||1===l.rank,(function(){return"Error in batchNorm3D: mean must be rank 3 or rank 1 but got rank "+l.rank+"."})),Vv(3===c.rank||1===c.rank,(function(){return"Error in batchNorm3D: variance must be rank 3 or rank 1 but got rank "+c.rank+"."})),null!=o&&Vv(3===o.rank||1===o.rank,(function(){return"Error in batchNorm3D: scale must be rank 3 or rank 1 but got rank "+o.rank+"."})),null!=s&&Vv(3===s.rank||1===s.rank,(function(){return"Error in batchNorm3D: offset must be rank 3 or rank 1 but got rank "+s.rank+"."})),zS(u,l,c,s,o,i)}});var WS=Sk({batchNorm4d_:function(e,t,n,r,a,i){var o,s,u=kk(e,"x","batchNorm"),l=kk(t,"mean","batchNorm"),c=kk(n,"variance","batchNorm");return null!=a&&(o=kk(a,"scale","batchNorm")),null!=r&&(s=kk(r,"offset","batchNorm")),Vv(4===u.rank,(function(){return"Error in batchNorm4D: x must be rank 4 but got rank "+u.rank+"."})),Vv(4===l.rank||1===l.rank,(function(){return"Error in batchNorm4D: mean must be rank 4 or rank 1 but got rank "+l.rank+"."})),Vv(4===c.rank||1===c.rank,(function(){return"Error in batchNorm4D: variance must be rank 4 or rank 1 but got rank "+c.rank+"."})),null!=o&&Vv(4===o.rank||1===o.rank,(function(){return"Error in batchNorm4D: scale must be rank 4 or rank 1 but got rank "+o.rank+"."})),null!=s&&Vv(4===s.rank||1===s.rank,(function(){return"Error in batchNorm4D: offset must be rank 4 or rank 1 but got rank "+s.rank+"."})),zS(u,l,c,s,o,i)}});var VS=Sk({bincount_:function(e,t,n){var r=kk(e,"x","bincount"),a=kk(t,"weights","bincount");Vv("int32"===r.dtype,(function(){return"Error in bincount: input dtype must be int32, but got "+r.dtype})),Vv(n>=0,(function(){return"size must be non-negative, but got "+n+"."})),Vv(a.size===r.size||0===a.size,(function(){return"Error in bincount: weights must have the same size as input or0-length, but got input shape: "+r.shape+", weights shape: "+a.shape+"."}));var i={x:r,weights:a},o={size:n};return fk.runKernel($g,i,o)}});var US=Sk({broadcastArgs_:function(e,t){var n=kk(e,"s0","broadcastArgs","int32"),r=kk(t,"s1","broadcastArgs","int32");if(1!==n.rank)throw new Error("broadcastArgs(): first input must be a vector (rank=1). Has rank "+n.rank);if(1!==r.rank)throw new Error("broadcastArgs(): second input must be a vector (rank=1). Has rank "+r.rank);var a={s0:n,s1:r};return fk.runKernel(ty,a)}});var GS=Sk({broadcastTo_:function(e,t){var n=kk(e,"broadcastTo","x"),r=n.shape;if(t.some((function(e){return!(e>0)||e%1!=0})))throw new Error("broadcastTo(): Invalid broadcast shape ["+t+"].");if(t.length<n.rank)throw new Error("broadcastTo(): shape.length="+t.length+" < input.rank="+n.rank+".");if(t.length>n.rank){for(var a=n.shape.slice();a.length<t.length;)a.unshift(1);n=ES(n,a)}for(var i=n.shape,o=Array.from(t),s=t.length-1;s>=0;s--)if(i[s]===t[s])o[s]=1;else if(1!==n.shape[s])throw new Error("broadcastTo(): ["+r+"] cannot be broadcast to ["+t+"].");if(0===o.map((function(e,t){return e>1?t:-1})).filter((function(e){return e>=0})).length)return FN(n);var u={x:n},l={reps:o};return fk.runKernel(Nx,u,l)}});var jS=Sk({ceil_:function(e){var t={x:kk(e,"x","ceil")};return fk.runKernel(ry,t)}});var HS=Sk({clipByValue_:function(e,t,n){var r=kk(e,"x","clipByValue");Vv(t<=n,(function(){return"Error in clip: min ("+t+") must be less than or equal to max ("+n+")."}));var a={x:r},i={clipValueMin:t,clipValueMax:n};return fk.runKernel(ay,a,i)}});var qS=Sk({concat1d_:function(e){return _S(e,0)}});var KS=Sk({concat2d_:function(e,t){return _S(e,t)}});var XS=Sk({concat3d_:function(e,t){return _S(e,t)}});var YS=Sk({concat4d_:function(e,t){return _S(e,t)}});var JS=Sk({conv2d_:function(e,t,n,r,a,i,o){void 0===a&&(a="NHWC"),void 0===i&&(i=[1,1]);var s=kk(e,"x","conv2d"),u=kk(t,"filter","conv2d"),l=s,c=!1;3===s.rank&&(c=!0,l=ES(s,[1,s.shape[0],s.shape[1],s.shape[2]])),Vv(4===l.rank,(function(){return"Error in conv2d: input must be rank 4, but got rank "+l.rank+"."})),Vv(4===u.rank,(function(){return"Error in conv2d: filter must be rank 4, but got rank "+u.rank+"."})),null!=o&&Vv(Kv(r),(function(){return"Error in conv2d: pad must be an integer when using, dimRoundingMode "+o+" but got pad "+r+"."}));var p="NHWC"===a?l.shape[3]:l.shape[1];Vv(p===u.shape[2],(function(){return"Error in conv2d: depth of input ("+p+") must match input depth for filter "+u.shape[2]+"."})),Vv(TS(n,i),(function(){return"Error in conv2D: Either strides or dilations must be 1. Got strides "+n+" and dilations '"+i+"'"}));var h={x:l,filter:u},f={strides:n,pad:r,dataFormat:a,dilations:i,dimRoundingMode:o},d=fk.runKernel(uy,h,f);return c?ES(d,[d.shape[1],d.shape[2],d.shape[3]]):d}});var ZS=Sk({conv1d_:function(e,t,n,r,a,i,o){void 0===a&&(a="NWC"),void 0===i&&(i=1);var s=kk(e,"x","conv1d"),u=kk(t,"filter","conv1d"),l=s,c=!1;2===s.rank&&(c=!0,l=ES(s,[1,s.shape[0],s.shape[1]])),Vv(3===l.rank,(function(){return"Error in conv1d: input must be rank 3, but got rank "+l.rank+"."})),Vv(3===u.rank,(function(){return"Error in conv1d: filter must be rank 3, but got rank "+u.rank+"."})),null!=o&&Vv(Kv(r),(function(){return"Error in conv1d: pad must be an integer when using, dimRoundingMode "+o+" but got pad "+r+"."})),Vv(l.shape[2]===u.shape[1],(function(){return"Error in conv1d: depth of input ("+l.shape[2]+") must match input depth for filter "+u.shape[1]+"."})),Vv(TS(n,i),(function(){return"Error in conv1D: Either stride or dilation must be 1. Got stride "+n+" and dilation '"+i+"'"})),Vv("NWC"===a,(function(){return"Error in conv1d: got dataFormat of "+a+" but only NWC is currently supported."}));var p=ES(u,[1,u.shape[0],u.shape[1],u.shape[2]]),h=ES(l,[l.shape[0],1,l.shape[1],l.shape[2]]),f=JS(h,p,[1,n],r,"NHWC",[1,i],o);return ES(f,c?[f.shape[2],f.shape[3]]:[f.shape[0],f.shape[2],f.shape[3]])}});var QS=Sk({conv2DBackpropInput_:function(e,t,n,r,a,i,o){void 0===i&&(i="NHWC"),Vv(e.length===t.rank,(function(){return"Length of inShape ("+e.length+") and rank of dy ("+t.rank+") must match"}));var s=e,u=t,l=!1;3===t.rank&&(l=!0,u=ES(t,[1,t.shape[0],t.shape[1],t.shape[2]]),s=[1,e[0],e[1],e[2]]),Vv(4===s.length,(function(){return"Error in conv2dDerInput: inShape must be length 4, but got length "+s.length+"."})),Vv(4===u.rank,(function(){return"Error in conv2dDerInput: dy must be rank 4, but got rank "+u.rank})),Vv(4===n.rank,(function(){return"Error in conv2dDerInput: filter must be rank 4, but got rank "+n.rank}));var c="NHWC"===i?s[3]:s[1],p="NHWC"===i?u.shape[3]:u.shape[1];Vv(c===n.shape[2],(function(){return"Error in conv2dDerInput: depth of input ("+c+") must match input depth for filter "+n.shape[2]+"."})),Vv(p===n.shape[3],(function(){return"Error in conv2dDerInput: depth of output ("+p+") must match output depth for filter "+n.shape[3]+"."})),null!=o&&Vv(Kv(a),(function(){return"Error in conv2dDerInput: pad must be an integer when using, dimRoundingMode "+o+" but got pad "+a+"."}));var h={dy:u,filter:n},f={strides:r,pad:a,dataFormat:i,dimRoundingMode:o,inputShape:s},d=fk.runKernel(cy,h,f);return l?ES(d,[d.shape[1],d.shape[2],d.shape[3]]):d}});var $S=Sk({conv2dTranspose_:function(e,t,n,r,a,i){var o=kk(e,"x","conv2dTranspose"),s=kk(t,"filter","conv2dTranspose");return QS(n,o,s,r,a,"NHWC",i)}});var eT=Sk({conv3d_:function(e,t,n,r,a,i){void 0===a&&(a="NDHWC"),void 0===i&&(i=[1,1,1]);var o=kk(e,"x","conv3d"),s=kk(t,"filter","conv3d"),u=o,l=!1;4===o.rank&&(l=!0,u=ES(o,[1,o.shape[0],o.shape[1],o.shape[2],o.shape[3]])),Vv(5===u.rank,(function(){return"Error in conv3d: input must be rank 5, but got rank "+u.rank+"."})),Vv(5===s.rank,(function(){return"Error in conv3d: filter must be rank 5, but got rank "+s.rank+"."})),Vv(u.shape[4]===s.shape[3],(function(){return"Error in conv3d: depth of input ("+u.shape[4]+") must match input depth for filter "+s.shape[3]+"."})),Vv(TS(n,i),(function(){return"Error in conv3D: Either strides or dilations must be 1. Got strides "+n+" and dilations '"+i+"'"})),Vv("NDHWC"===a,(function(){return"Error in conv3d: got dataFormat of "+a+" but only NDHWC is currently supported."}));var c={x:u,filter:s},p={strides:n,pad:r,dataFormat:a,dilations:i},h=fk.runKernel(py,c,p);return l?ES(h,[h.shape[1],h.shape[2],h.shape[3],h.shape[4]]):h}});var tT=Sk({conv3DBackpropInput_:function(e,t,n,r,a){Vv(e.length===t.rank,(function(){return"Length of inShape ("+e.length+") and rank of dy ("+t.rank+") must match"}));var i=e,o=t,s=!1;4===t.rank&&(s=!0,o=ES(t,[1,t.shape[0],t.shape[1],t.shape[2],t.shape[3]]),i=[1,e[0],e[1],e[2],e[3]]);var u=i[4],l=o.shape[4];Vv(5===i.length,(function(){return"Error in conv3dDerInput: inShape must be length 5, but got length "+i.length+"."})),Vv(5===o.rank,(function(){return"Error in conv3dDerInput: dy must be rank 5, but got rank "+o.rank})),Vv(5===n.rank,(function(){return"Error in conv3dDerInput: filter must be rank 5, but got rank "+n.rank})),Vv(u===n.shape[3],(function(){return"Error in conv3dDerInput: depth of input ("+u+") must match input depth for filter "+n.shape[3]+"."})),Vv(l===n.shape[4],(function(){return"Error in conv3dDerInput: depth of output ("+l+") must match output depth for filter "+n.shape[4]+"."}));var c={dy:o,filter:n},p={pad:a,strides:r,inputShape:i},h=fk.runKernel(fy,c,p);return s?ES(h,[h.shape[1],h.shape[2],h.shape[3],h.shape[4]]):h}});var nT=Sk({conv3dTranspose_:function(e,t,n,r,a){var i=kk(e,"x","conv3dTranspose"),o=kk(t,"filter","conv3dTranspose");return tT(n,i,o,r,a)}});var rT=Sk({cos_:function(e){var t={x:kk(e,"x","cos")};return fk.runKernel(dy,t)}});var aT=Sk({cosh_:function(e){var t={x:kk(e,"x","cosh")};return fk.runKernel(my,t)}});var iT=Sk({cumsum_:function(e,t,n,r){void 0===t&&(t=0),void 0===n&&(n=!1),void 0===r&&(r=!1);var a={x:kk(e,"x","cumsum")},i={axis:t,exclusive:n,reverse:r};return fk.runKernel(vy,a,i)}});var oT=Sk({denseBincount_:function(e,t,n,r){void 0===r&&(r=!1);var a=kk(e,"x","denseBincount"),i=kk(t,"weights","denseBincount");Vv("int32"===a.dtype,(function(){return"Error in denseBincount: input dtype must be int32, but got "+a.dtype})),Vv(a.rank<=2,(function(){return"Error in denseBincount: input must be at most rank 2, but got rank "+a.rank+"."})),Vv(n>=0,(function(){return"size must be non-negative, but got "+n+"."})),Vv(i.size===a.size||0===i.size,(function(){return"Error in denseBincount: weights must have the same shape as x or 0-length, but got x shape: "+a.shape+", weights shape: "+i.shape+"."}));var o={x:a,weights:i},s={size:n,binaryOutput:r};return fk.runKernel(yy,o,s)}});var sT=Sk({depthToSpace_:function(e,t,n){void 0===n&&(n="NHWC");var r=kk(e,"x","depthToSpace"),a="NHWC"===n?r.shape[1]:r.shape[2],i="NHWC"===n?r.shape[2]:r.shape[3],o="NHWC"===n?r.shape[3]:r.shape[1];Vv(a*t>=0,(function(){return"Negative dimension size caused by overflow when multiplying\n "+a+" and "+t+" for depthToSpace with input shape\n "+r.shape})),Vv(i*t>=0,(function(){return"Negative dimension size caused by overflow when multiplying\n "+i+" and "+t+" for depthToSpace with input shape\n "+r.shape})),Vv(o%(t*t)==0,(function(){return"Dimension size must be evenly divisible by "+t*t+" but is "+o+" for depthToSpace with input shape "+r.shape}));var s={x:r},u={blockSize:t,dataFormat:n};return fk.runKernel(by,s,u)}});var uT=Sk({depthwiseConv2d_:function(e,t,n,r,a,i,o){void 0===a&&(a="NHWC"),void 0===i&&(i=[1,1]);var s=kk(e,"x","depthwiseConv2d"),u=kk(t,"filter","depthwiseConv2d"),l=s,c=!1;3===s.rank&&(c=!0,l=ES(s,[1,s.shape[0],s.shape[1],s.shape[2]])),Vv(4===l.rank,(function(){return"Error in depthwiseConv2d: input must be rank 4, but got rank "+l.rank+"."})),Vv(4===u.rank,(function(){return"Error in depthwiseConv2d: filter must be rank 4, but got rank "+u.rank+"."})),Vv(l.shape[3]===u.shape[2],(function(){return"Error in depthwiseConv2d: number of input channels ("+l.shape[3]+") must match the inChannels dimension in filter "+u.shape[2]+"."})),null!=o&&Vv(Kv(r),(function(){return"Error in depthwiseConv2d: pad must be an integer when using, dimRoundingMode "+o+" but got pad "+r+"."}));var p={x:l,filter:u},h={strides:n,pad:r,dataFormat:a,dilations:i,dimRoundingMode:o},f=fk.runKernel(xy,p,h);return c?ES(f,[f.shape[1],f.shape[2],f.shape[3]]):f}});var lT=Sk({diag_:function(e){var t={x:kk(e,"x","diag")};return fk.runKernel(Ny,t)}});var cT=Sk({dilation2d_:function(e,t,n,r,a,i){void 0===a&&(a=[1,1]),void 0===i&&(i="NHWC");var o=kk(e,"x","dilation2d"),s=kk(t,"filter","dilation2d");Vv(3===o.rank||4===o.rank,(function(){return"Error in dilation2d: input must be rank 3 or 4, but got rank "+o.rank+"."})),Vv(3===s.rank,(function(){return"Error in dilation2d: filter must be rank 3, but got rank "+s.rank+"."})),Vv("NHWC"===i,(function(){return"Error in dilation2d: Only NHWC is currently supported, but got dataFormat of "+i}));var u=o,l=!1;3===o.rank&&(u=ES(o,[1,o.shape[0],o.shape[1],o.shape[2]]),l=!0);var c={x:u,filter:s},p={strides:n,pad:r,dilations:a},h=fk.runKernel(Iy,c,p);return l?ES(h,[h.shape[1],h.shape[2],h.shape[3]]):h}});function pT(e,t){for(var n=e.length,r=[],a=0;a<n;a++){var i=n-1-a,o=e[i]||1;(t[t.length-1-a]||1)>1&&1===o&&r.unshift(i)}return r}function hT(e,t){for(var n=[],r=0;r<t.length;r++){var a=e[e.length-r-1],i=t.length-r-1,o=t[i];(null==a||1===a&&o>1)&&n.unshift(i)}return n}function fT(e,t){for(var n=[],r=Math.max(e.length,t.length),a=0;a<r;a++){var i=e[e.length-a-1];null==i&&(i=1);var o=t[t.length-a-1];if(null==o&&(o=1),1===i)n.unshift(o);else if(1===o)n.unshift(i);else{if(i!==o)throw Error("Operands could not be broadcast together with shapes "+e+" and "+t+".");n.unshift(i)}}return n}var dT=Sk({equal_:function(e,t){var n=kk(e,"a","equal","string_or_numeric"),r=kk(t,"b","equal","string_or_numeric"),a=rk(n,r);n=a[0],r=a[1],fT(n.shape,r.shape);var i={a:n,b:r};return fk.runKernel(Fy,i)}});var mT=Sk({where_:function(e,t,n){var r=kk(t,"a","where"),a=kk(n,"b","where"),i=kk(e,"condition","where","bool"),o=fT(fT(i.shape,r.shape),a.shape),s={condition:GS(i,o),t:GS(r,o),e:GS(a,o)};return fk.runKernel(Jb,s)}});var vT=Sk({zerosLike_:function(e){var t={x:kk(e,"x","zerosLike")};return fk.runKernel(Ax,t)}});var gT=Sk({divNoNan_:function(e,t){var n=kk(e,"a","div"),r=kk(t,"b","div"),a=rk(n,r);n=a[0],r=a[1];var i=eS(n,r),o=vT(i),s=dT(r,o);return mT(s,o,i)}});var yT=Sk({dot_:function(e,t){var n=kk(e,"t1","dot"),r=kk(t,"t2","dot");Vv(!(1!==n.rank&&2!==n.rank||1!==r.rank&&2!==r.rank),(function(){return"Error in dot: inputs must all be rank 1 or 2, but got ranks "+n.rank+" and "+r.rank+"."}));var a=1===n.rank?n.size:n.shape[1],i=1===r.rank?r.size:r.shape[0];if(Vv(a===i,(function(){return"Error in dot: inner dimensions of inputs must match, but got "+a+" and "+i+"."})),1===n.rank&&1===r.rank){var o=ES(n,[1,-1]),s=ES(r,[-1,1]),u=QN(o,s);return ES(u,[])}if(1===n.rank&&2===r.rank){var l=ES(n,[1,-1]),c=ES(r,[r.shape[0],r.shape[1]]),p=QN(l,c);return ES(p,[p.size])}if(2===n.rank&&1===r.rank){var h=ES(r,[-1,1]),f=QN(n,h);return ES(f,[f.size])}var d=ES(r,[r.shape[0],r.shape[1]]);return QN(n,d)}});var bT=Sk({einsum_:function(e){for(var t=arguments.length,n=new Array(t>1?t-1:0),r=1;r<t;r++)n[r-1]=arguments[r];var a=n.map((function(e,t){return kk(e,"tensors"+t,"einsum")})),i={equation:e};return fk.runKernel(Ey,a,i)}});var xT=Sk({elu_:function(e){var t={x:kk(e,"x","elu")};return fk.runKernel(Ry,t)}});var wT=Sk({erf_:function(e){var t=kk(e,"x","erf");Vv("int32"===t.dtype||"float32"===t.dtype,(function(){return"Input dtype must be `int32` or `float32`."})),"int32"===t.dtype&&(t=_N(t,"float32"));var n={x:t};return fk.runKernel(_y,n)}});var kT=Sk({exp_:function(e){var t={x:kk(e,"x","exp")};return fk.runKernel(Dy,t)}});var NT=Sk({expandDims_:function(e,t){void 0===t&&(t=0);var n=kk(e,"x","expandDims","string_or_numeric");Vv(t<=n.rank,(function(){return"Axis must be <= rank of the tensor"}));var r={input:n},a={dim:t};return fk.runKernel(Oy,r,a)}});var IT=Sk({expm1_:function(e){var t={x:kk(e,"x","expm1")};return fk.runKernel(My,t)}});var ST=Sk({tile_:function(e,t){var n=kk(e,"x","tile","string_or_numeric");Vv(n.rank===t.length,(function(){return"Error in transpose: rank of input "+n.rank+" must match length of reps "+t+"."}));var r={x:n},a={reps:t};return fk.runKernel(Nx,r,a)}});var TT=Sk({eye_:function(e,t,n,r){void 0===r&&(r="float32"),null==t&&(t=e);for(var a=AN([e,t],r),i=e<=t?e:t,o=0;o<i;++o)a.set(1,o,o);var s=ES(a.toTensor(),[e,t]);if(null==n)return s;if(1===n.length)return ST(NT(s,0),[n[0],1,1]);if(2===n.length)return ST(NT(NT(s,0),0),[n[0],n[1],1,1]);if(3===n.length)return ST(NT(NT(NT(s,0),0),0),[n[0],n[1],n[2],1,1]);throw new Error("eye() currently supports only 1D and 2D batchShapes, but received "+n.length+"D.")}});function CT(e,t,n){var r={shape:e,value:t,dtype:n};return fk.runKernel(zy,{},r)}var ET=Sk({floor_:function(e){var t={x:kk(e,"x","floor")};return fk.runKernel(By,t)}});var RT=Sk({gather_:function(e,t,n,r){void 0===n&&(n=0),void 0===r&&(r=0);var a={x:kk(e,"x","gather"),indices:kk(t,"indices","gather","int32")},i={axis:n,batchDims:r};return fk.runKernel(Uy,a,i)}});var AT=Sk({greater_:function(e,t){var n=kk(e,"a","greater","string_or_numeric"),r=kk(t,"b","greater","string_or_numeric"),a=rk(n,r);n=a[0],r=a[1],fT(n.shape,r.shape);var i={a:n,b:r};return fk.runKernel(jy,i)}});var _T=Sk({greaterEqual_:function(e,t){var n=kk(e,"a","greaterEqual","string_or_numeric"),r=kk(t,"b","greaterEqual","string_or_numeric"),a=rk(n,r);n=a[0],r=a[1],fT(n.shape,r.shape);var i={a:n,b:r};return fk.runKernel(Hy,i)}});var FT=Sk({imag_:function(e){var t={input:kk(e,"input","imag")};return fk.runKernel(Xy,t)}});var DT=Sk({isFinite_:function(e){var t={x:kk(e,"x","isFinite")};return fk.runKernel(Yy,t)}});var OT=Sk({isInf_:function(e){var t={x:kk(e,"x","isInf")};return fk.runKernel(Jy,t)}});var MT=Sk({isNaN_:function(e){var t={x:kk(e,"x","isNaN")};return fk.runKernel(Zy,t)}});var LT=Sk({leakyRelu_:function(e,t){void 0===t&&(t=.2);var n={x:kk(e,"x","leakyRelu")},r={alpha:t};return fk.runKernel(Qy,n,r)}});var zT=Sk({less_:function(e,t){var n=kk(e,"a","less","string_or_numeric"),r=kk(t,"b","less","string_or_numeric"),a=rk(n,r);n=a[0],r=a[1],fT(n.shape,r.shape);var i={a:n,b:r};return fk.runKernel($y,i)}});var PT=Sk({lessEqual_:function(e,t){var n=kk(e,"a","lessEqual","string_or_numeric"),r=kk(t,"b","lessEqual","string_or_numeric"),a=rk(n,r);n=a[0],r=a[1],fT(n.shape,r.shape);var i={a:n,b:r};return fk.runKernel(eb,i)}});function BT(e,t,n){if(n<=0)throw new Error("The number of values should be positive.");var r={start:e,stop:t,num:n};return fk.runKernel(tb,{},r)}var WT=Sk({localResponseNormalization_:function(e,t,n,r,a){void 0===t&&(t=5),void 0===n&&(n=1),void 0===r&&(r=1),void 0===a&&(a=.5);var i=kk(e,"x","localResponseNormalization");Vv(4===i.rank||3===i.rank,(function(){return"Error in localResponseNormalization: x must be rank 3 or 4 but got\n rank "+i.rank+"."})),Vv(Kv(t),(function(){return"Error in localResponseNormalization: depthRadius must be an integer but got depthRadius "+t+"."}));var o=i,s=!1;3===i.rank&&(s=!0,o=ES(i,[1,i.shape[0],i.shape[1],i.shape[2]]));var u={x:o},l={depthRadius:t,bias:n,alpha:r,beta:a},c=fk.runKernel(ub,u,l);return s?ES(c,[c.shape[1],c.shape[2],c.shape[3]]):c}});var VT=Sk({log_:function(e){var t={x:kk(e,"x","log")};return fk.runKernel(nb,t)}});var UT=Sk({log1p_:function(e){var t={x:kk(e,"x","log1p")};return fk.runKernel(rb,t)}});function GT(e,t){Vv(hg(e),(function(){return"The f passed in variableGrads(f) must be a function"})),Vv(null==t||Array.isArray(t)&&t.every((function(e){return e instanceof $w})),(function(){return"The varList passed in variableGrads(f, varList) must be an array of variables"}));var n=null!=t;if(!n)for(var r in t=[],fk.registeredVariables)t.push(fk.registeredVariables[r]);var a=n?t.filter((function(e){return!e.trainable})):null,i=t.length;Vv((t=t.filter((function(e){return e.trainable}))).length>0,(function(){return"variableGrads() expects at least one of the input variables to be trainable, but none of the "+i+" variables is trainable."}));var o=fk.gradients(e,t,null,!0),s=o.value,u=o.grads;Vv(u.some((function(e){return null!=e})),(function(){return"Cannot find a connection between any variable and the result of the loss function y=f(x). 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s={images:i},u={alignCorners:n,halfPixelCenters:r,size:t},l=fk.runKernel(Vb,s,u);return o?ES(l,[l.shape[1],l.shape[2],l.shape[3]]):l}});var QR=Sk({threshold_:function(e,t,n,r){void 0===t&&(t="binary"),void 0===n&&(n=!1),void 0===r&&(r=.5);var a,i,o,s,u=kk(e,"image","threshold"),l=u.shape[0]*u.shape[1],c=tS(BE([r]),255);if(Vv(3===u.rank,(function(){return"Error in threshold: image must be rank 3,but got rank "+u.rank+"."})),Vv(3===u.shape[2]||1===u.shape[2],(function(){return"Error in threshold: image color channel must be equal to 3 or 1but got "+u.shape[2]+"."})),Vv("int32"===u.dtype||"float32"===u.dtype,(function(){return"Error in dtype: image dtype must be int32 or float32,but got dtype "+u.dtype+"."})),Vv("otsu"===t||"binary"===t,(function(){return"Method must be binary or otsu, but was "+t})),3===u.shape[2]){var p=AE(u,[1,1,1],-1);a=p[0],i=p[1],o=p[2];var h=tS(a,.2989),f=tS(i,.587),d=tS(o,.114);s=QI(QI(h,f),d)}else s=e;"otsu"===t&&(c=function(e,t){for(var n,r,a,i,o,s,u=BE([-1]),l=BE([0]),c=BE([0]),p=0;p<e.size-1;p++){n=DS(e,0,p+1),r=DS(e,p+1),o=eS(ZT(n),t),s=eS(ZT(r),t);var h=ZT(tS(n,nE(0,n.size)));a=eS(h,ZT(n));var f=CT(r.shape,n.size),d=QI(nE(0,r.size),f),m=tS(r,d);i=eS(ZT(m),ZT(r));var v=JT(a,i),g=JT(a,i),y=tS(o,s);c=tS(tS(y,v),g);var b=AT(c,l);l=mT(b,c,l),u=mT(b,BE([p]),u)}return u}(VS(_N(hE(s),"int32"),Ek([]),256),l));var m=n?PT(s,c):AT(s,c);return _N(tS(m,255),"int32")}});var $R=Sk({transform_:function(e,t,n,r,a,i){void 0===n&&(n="nearest"),void 0===r&&(r="constant"),void 0===a&&(a=0);var o=kk(e,"image","transform","float32"),s=kk(t,"transforms","transform","float32");Vv(4===o.rank,(function(){return"Error in transform: image must be rank 4,but got rank "+o.rank+"."})),Vv(2===s.rank&&(s.shape[0]===o.shape[0]||1===s.shape[0])&&8===s.shape[1],(function(){return"Error in transform: Input transform should be batch x 8 or 1 x 8"})),Vv(null==i||2===i.length,(function(){return"Error in transform: outputShape must be [height, width] or null, but got "+i+"."}));var u={image:o,transforms:s},l={interpolation:n,fillMode:r,fillValue:a,outputShape:i};return fk.runKernel(Sx,u,l)}});var eA=Sk({bandPart_:function(e,t,n){Vv(t%1==0,(function(){return"bandPart(): numLower must be an integer, got "+t+"."})),Vv(n%1==0,(function(){return"bandPart(): numUpper must be an integer, got "+n+"."}));var r=kk(e,"a","bandPart");Vv(r.rank>=2,(function(){return"bandPart(): Rank must be at least 2, got "+r.rank+"."}));var a=r.shape,i=r.shape.slice(-2),o=i[0],s=i[1];if(!(t<=o))throw new Error("bandPart(): numLower ("+t+") must not be greater than the number of rows ("+o+").");if(!(n<=s))throw new Error("bandPart(): numUpper ("+n+") must not be greater than the number of columns ("+s+").");t<0&&(t=o),n<0&&(n=s);var u=ES(nE(0,o,1,"int32"),[-1,1]),l=nE(0,s,1,"int32"),c=JT(u,l),p=uC(PT(c,dE(+t,"int32")),_T(c,dE(-n,"int32"))),h=gC([o,s],r.dtype);return ES(ME(XE(ES(r,[-1,o,s])).map((function(e){return mT(p,e,h)}))),a)}});var tA=Sk({gramSchmidt_:function(e){var t;Array.isArray(e)?function(){t=!1,Vv(null!=e&&e.length>0,(function(){return"Gram-Schmidt process: input must not be null, undefined, or empty"}));for(var n=e[0].shape[0],r=function(t){Vv(e[t].shape[0]===n,(function(){return"Gram-Schmidt: Non-unique lengths found in the input vectors: ("+e[t].shape[0]+" vs. "+n+")"}))},a=1;a<e.length;++a)r(a)}():(t=!0,e=AE(e,e.shape[0],0).map((function(e){return OE(e,[0])}))),Vv(e.length<=e[0].shape[0],(function(){return"Gram-Schmidt: Number of vectors ("+e.length+") exceeds number of dimensions ("+e[0].shape[0]+")."}));for(var n=[],r=e,a=function(e){n.push(fk.tidy((function(){var t=r[e];if(e>0)for(var a=0;a<e;++a){var i=tS(ZT(tS(n[a],t)),n[a]);t=JT(t,i)}return eS(t,nR(t,"euclidean"))})))},i=0;i<e.length;++i)a(i);return t?ME(n,0):n}});function nA(e,t){return void 0===t&&(t=!1),fk.tidy((function(){Vv(2===e.shape.length,(function(){return"qr2d() requires a 2D Tensor, but got a "+e.shape.length+"D Tensor."}));for(var n=e.shape[0],r=e.shape[1],a=TT(n),i=FN(e),o=WE([[1]],[1,1]),s=FN(o),u=n>=r?r:n,l=function(e){var t=i,u=s,l=a,c=fk.tidy((function(){var t=DS(i,[e,e],[n-e,1]),u=nR(t),l=DS(i,[e,e],[1,1]),c=mT(AT(l,0),WE([[-1]]),WE([[1]])),p=JT(l,tS(c,u)),h=eS(t,p);s=1===h.shape[0]?FN(o):_S([o,DS(h,[1,0],[h.shape[0]-1,h.shape[1]])],0);var f=qT(eS(QN(c,p),u)),d=DS(i,[e,0],[n-e,r]),m=tS(f,s),v=eI(s);if(0===e)i=JT(d,QN(m,QN(v,d)));else{var g=JT(d,QN(m,QN(v,d)));i=_S([DS(i,[0,0],[e,r]),g],0)}var y=eI(m),b=DS(a,[0,e],[n,a.shape[1]-e]);if(0===e)a=JT(b,QN(QN(b,s),y));else{var x=JT(b,QN(QN(b,s),y));a=_S([DS(a,[0,0],[n,e]),x],1)}return[s,i,a]}));s=c[0],i=c[1],a=c[2],KI([t,u,l])},c=0;c<u;++c)l(c);return!t&&n>r&&(a=DS(a,[0,0],[n,r]),i=DS(i,[0,0],[r,r])),[a,i]}))}var rA,aA=Sk({qr_:function(e,t){if(void 0===t&&(t=!1),Vv(e.rank>=2,(function(){return"qr() requires input tensor to have a rank >= 2, but got rank "+e.rank})),2===e.rank)return nA(e,t);var n=e.shape.slice(0,e.shape.length-2).reduce((function(e,t){return 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oA=Sk({absoluteDifference_:function(t,n,r,a){void 0===a&&(a=e.Reduction.SUM_BY_NONZERO_WEIGHTS);var i=kk(t,"labels","absoluteDifference"),o=kk(n,"predictions","absoluteDifference"),s=null;null!=r&&(s=kk(r,"weights","absoluteDifference")),Uv(i.shape,o.shape,"Error in absoluteDifference: ");var u=nS(JT(i,o));return iA(u,s,a)}});var sA=Sk({cosineDistance_:function(t,n,r,a,i){void 0===i&&(i=e.Reduction.SUM_BY_NONZERO_WEIGHTS);var o=kk(t,"labels","cosineDistance"),s=kk(n,"predictions","cosineDistance"),u=null;null!=a&&(u=kk(a,"weights","cosineDistance")),Uv(o.shape,s.shape,"Error in cosineDistance: ");var l=dE(1),c=JT(l,ZT(tS(o,s),r,!0));return iA(c,u,i)}});var uA=Sk({hingeLoss_:function(t,n,r,a){void 0===a&&(a=e.Reduction.SUM_BY_NONZERO_WEIGHTS);var i=kk(t,"labels","hingeLoss"),o=kk(n,"predictions","hingeLoss"),s=null;null!=r&&(s=kk(r,"weights","hingeLoss")),Uv(i.shape,o.shape,"Error in hingeLoss: ");var u=dE(1);i=JT(tS(dE(2),i),u);var l=iE(JT(u,tS(i,o)));return iA(l,s,a)}});var lA=Sk({huberLoss_:function(t,n,r,a,i){void 0===a&&(a=1),void 0===i&&(i=e.Reduction.SUM_BY_NONZERO_WEIGHTS);var o=kk(t,"labels","huberLoss"),s=kk(n,"predictions","huberLoss"),u=null;null!=r&&(u=kk(r,"weights","huberLoss")),Uv(o.shape,s.shape,"Error in huberLoss: ");var l=dE(a),c=nS(JT(s,o)),p=wC(c,l),h=JT(c,p),f=QI(tS(dE(.5),IC(p)),tS(l,h));return iA(f,u,i)}});var cA=Sk({logLoss_:function(t,n,r,a,i){void 0===a&&(a=1e-7),void 0===i&&(i=e.Reduction.SUM_BY_NONZERO_WEIGHTS);var o=kk(t,"labels","logLoss"),s=kk(n,"predictions","logLoss"),u=null;null!=r&&(u=kk(r,"weights","logLoss")),Uv(o.shape,s.shape,"Error in logLoss: ");var l=dE(1),c=dE(a),p=qT(tS(o,VT(QI(s,c)))),h=tS(JT(l,o),VT(QI(JT(l,s),c))),f=JT(p,h);return iA(f,u,i)}});var pA=Sk({meanSquaredError_:function(t,n,r,a){void 0===a&&(a=e.Reduction.SUM_BY_NONZERO_WEIGHTS);var i=kk(t,"labels","meanSquaredError"),o=kk(n,"predictions","meanSquaredError"),s=null;null!=r&&(s=kk(r,"weights","meanSquaredError")),Uv(i.shape,o.shape,"Error in 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o=kk(t,"onehotLabels","softmaxCrossEntropy"),s=kk(n,"logits","softmaxCrossEntropy"),u=null;if(null!=r&&(u=kk(r,"weights","softmaxCrossEntropy")),Uv(o.shape,s.shape,"Error in softmaxCrossEntropy: "),a>0){var l=dE(a),c=dE(1),p=dE(o.shape[1]);o=QI(tS(o,JT(c,l)),eS(l,p))}var h=function(e,t,n){if(void 0===n&&(n=-1),-1===n&&(n=t.rank-1),n!==t.rank-1)throw Error("Softmax cross entropy along a non-last dimension is not yet supported. 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u={indices:a,values:i,denseShape:o,defaultValue:s},l=fk.runKernel(lx,u);return{outputIndices:l[0],outputValues:l[1],emptyRowIndicator:l[2],reverseIndexMap:l[3]}}});var mA=Sk({sparseReshape_:function(e,t,n){var r=kk(e,"inputIndices","sparseReshape"),a=kk(t,"inputShape","sparseReshape"),i=kk(n,"newShape","sparseReshape");if(2!==r.rank)throw new Error("Input indices should be Tensor2D but received shape\n "+r.shape);if(1!==a.rank)throw new Error("Input shape should be Tensor1D but received shape "+a.shape);if(1!==i.rank)throw new Error("New shape should be Tensor1D but received shape "+i.shape);var o={inputIndices:r,inputShape:a,newShape:i},s=fk.runKernel(cx,o);return{outputIndices:s[0],outputShape:s[1]}}});var vA=Sk({sparseSegmentMean_:function(e,t,n){var r=kk(e,"data","sparseSegmentMean"),a=kk(t,"indices","sparseSegmentMean"),i=kk(n,"segmentIds","sparseSegmentMean");if(r.rank<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(1!==a.rank)throw new 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l=kk(t,"dataSplits","stringNGrams");if("int32"!==l.dtype)throw new Error("Data splits must be of datatype int32");var c={separator:n,nGramWidths:r,leftPad:a,rightPad:i,padWidth:o,preserveShortSequences:s},p={data:u,dataSplits:l},h=fk.runKernel(gx,p,c);return{nGrams:h[0],nGramsSplits:h[1]}}});var bA=Sk({stringSplit_:function(e,t,n){void 0===n&&(n=!0);var r=kk(e,"input","stringSplit","string"),a=kk(t,"delimiter","stringSplit","string");if(1!==r.rank)throw new Error("Input should be Tensor1D but received shape "+r.shape);if(0!==a.rank)throw new Error("Delimiter should be a scalar but received shape "+a.shape);var i={skipEmpty:n},o={input:r,delimiter:a},s=fk.runKernel(yx,o,i);return{indices:s[0],values:s[1],shape:s[2]}}});var xA=Sk({stringToHashBucketFast_:function(e,t){var n=kk(e,"input","stringToHashBucketFast","string"),r={numBuckets:t};if(t<=0)throw new Error("Number of buckets must be at least 1");var a={input:n};return 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Did you set `model.trainable` without calling `model.compile()` afterwards?")},n.evaluate=function(e,t,n){void 0===n&&(n={});var r=null==n.batchSize?32:n.batchSize;pL(r);var a=this.standardizeUserDataXY(e,t,!0,r);try{var i=a[0].concat(a[1]);this.makeTestFunction();var o=this.testFunction;return JF(this.testLoop(o,i,r,n.verbose,n.steps))}finally{xL(a[0],e),xL(a[1],t)}},n.evaluateDataset=function(){var e=xv(regeneratorRuntime.mark((function e(t,n){return regeneratorRuntime.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:return this.makeTestFunction(),e.abrupt("return",lL(this,t,n));case 2:case"end":return e.stop()}}),e,this)})));return function(t,n){return e.apply(this,arguments)}}(),n.checkNumSamples=function(e,t,n,r){var a;if(void 0===r&&(r="steps"),null!=n){if(a=null,null!=t)throw new jF("If "+r+" is set, batchSize must be null or undefined.Got batchSize = "+t)}else{if(null==e)throw new jF("Either the input data should have a defined shape, or "+r+" shoud be specified.");a=Array.isArray(e)?e[0].shape[0]:e.shape[0]}return a},n.execute=function(e,t){if(Array.isArray(t)&&0===t.length)throw new jF("`outputs` is an empty Array, which is not allowed.");var n=Array.isArray(t),r=n?t:[t],a=this.retrieveSymbolicTensors(r),i=new GM;if(e instanceof qw&&(e=[e]),Array.isArray(e)){if(e.length!==this.inputs.length)throw new jF("The number of inputs provided ("+e.length+") does not match the number of inputs of this model ("+this.inputs.length+").");for(var o=0;o<this.inputs.length;++o)i.add(this.inputs[o],e[o])}else for(var s,u=Fv(this.inputs);!(s=u()).done;){var l=s.value,c=e[l.name];if(null==c)throw new jF("No value is provided for the model's input "+l.name);i.add(l,c)}var p=qM(a,i);return n?p:p[0]},n.retrieveSymbolicTensors=function(e){for(var t,n=KF(null,e.length),r=e.length,a=Fv(this.layers);!(t=a()).done;){for(var i=t.value,o=Array.isArray(i.output)?i.output:[i.output],s=o.map((function(e){return e.name})),u=0;u<e.length;++u){var l=s.indexOf(e[u]);if(-1!==l&&(n[u]=o[l],r--),0===r)break}if(0===r)break}if(r>0){var c=[];throw n.forEach((function(t,n){null==t&&c.push(e[n])})),new jF("Cannot find SymbolicTensors for output name(s): "+JSON.stringify(c))}return n},n.predictLoop=function(e,t,n){var r=this;return void 0===t&&(t=32),void 0===n&&(n=!1),qI((function(){var a=r.checkNumSamples(e);if(n)throw new HF("Verbose predictLoop() is not implemented yet.");for(var i=dL(a,t),o=r.outputs.map((function(e){return[]})),s=function(t){qI((function(){var n=i[t][0],a=i[t][1],o=hL(e,n,a),s=[];if(Array.isArray(o))for(var u=0;u<o.length;++u)s.push({key:r.inputs[u],value:o[u]});else s.push({key:r.inputs[0],value:o});var l=new GM(s);return qM(r.outputs,l)})).forEach((function(e,t){return o[t].push(e)}))},u=0;u<i.length;++u)s(u);return JF(o.map((function(e){return _S(e,0)})))}))},n.predict=function(e,t){void 0===t&&(t={});var n=bL(e);IL(n,this.inputNames,this.feedInputShapes,!1);try{var r=null==t.batchSize?32:t.batchSize;return pL(r),this.predictLoop(n,r)}finally{xL(n,e)}},n.predictOnBatch=function(e){IL(e,this.inputNames,this.feedInputShapes,!0);var t=(Array.isArray(e)?e[0]:e).shape[0];return this.predictLoop(e,t)},n.standardizeUserDataXY=function(e,t,n,r){if(void 0===n&&(n=!0),null==this.optimizer_)throw new GF("You must compile a model before training/testing. Use LayersModel.compile(modelCompileArgs).");for(var a=[],i=0;i<this.feedOutputShapes.length;++i){var o=this.feedOutputShapes[i];this.feedLossFns[i]===dM?a.push(o.slice(0,o.length-1).concat([1])):a.push(o)}if(function(e,t,n){var r=iD(e.map((function(e){return e.shape[0]})));r.sort();var a=iD(t.map((function(e){return e.shape[0]})));if(a.sort(),r.length>1)throw new jF("All input Tensors (x) should have the same number of samples. Got array shapes: "+JSON.stringify(e.map((function(e){return e.shape}))));if(a.length>1)throw new jF("All target Tensors (y) should have the same number of samples. Got array shapes: "+JSON.stringify(t.map((function(e){return e.shape}))));if(r.length>0&&a.length>0&&!qv(r,a))throw new jF("Input Tensors should have the same number of samples as target Tensors. Found "+r[0]+" input sample(s) and "+a[0]+" target sample(s).")}(e=NL(e,this.feedInputNames,this.feedInputShapes,!1,"input"),t=NL(t,this.feedOutputNames,a,!1,"target")),function(e,t,n){for(var r=[lM,mM,fM],a=0;a<e.length;++a){var i=e[a],o=t[a],s=n[a];if(null!=o){if(o===fM&&1===i.shape[i.shape.length-1])throw new jF("You are passing a target array of shape "+i.shape+" while using a loss 'categorical_crossentropy'. 'categorical_crossentropy'expects targets to be binary matrices (1s and 0s) of shape [samples, classes].");if(-1!==r.indexOf(o))for(var u=i.shape.slice(1),l=s.slice(1),c=0;c<u.length;++c){var p=u[c],h=l[c];if(null!=h&&p!==h)throw new jF("A target Tensor with shape "+i.shape+" was passed for an output of shape "+s+", while using a loss function that expects targets to have the same shape as the output.")}}}}(t,this.feedLossFns,this.feedOutputShapes),this.stateful&&null!=r&&r>0&&e[0].shape[0]%r!=0)throw new jF("In a stateful network, you should only pass inputs with a number of samples that is divisible by the batch size "+r+". Found: "+e[0].shape[0]+" sample(s).");return[e,t]},n.standardizeUserData=function(){var e=xv(regeneratorRuntime.mark((function e(t,n,r,a,i,o){var s,u,l,c,p,h;return regeneratorRuntime.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:if(void 0===i&&(i=!0),s=this.standardizeUserDataXY(t,n,i,o),u=s[0],l=s[1],null==r){e.next=4;break}throw new Error("sample weight is not supported yet.");case 4:if(c=null,null==a){e.next=18;break}p=ZM(a,this.outputNames),c=[],h=0;case 9:if(!(h<p.length)){e.next=18;break}return e.t0=c,e.next=13,QM(l[h],null,p[h]);case 13:e.t1=e.sent,e.t0.push.call(e.t0,e.t1);case 15:++h,e.next=9;break;case 18:return e.abrupt("return",[u,l,c]);case 19:case"end":return e.stop()}}),e,this)})));return function(t,n,r,a,i,o){return e.apply(this,arguments)}}(),n.testLoop=function(e,t,n,r,a){var i=this;return void 0===r&&(r=0),qI((function(){var o=i.checkNumSamples(t,n,a,"steps"),s=[];if(r>0)throw new HF("Verbose mode is not implemented yet.");if(null!=a)throw new HF("steps mode in testLoop() is not implemented yet");for(var u=dL(o,n),l=BE(VD(0,o)),c=0;c<u.length;++c){var p=u[c][0],h=u[c][1],f=jD(l,p,h-p),d=fL(t,f),m=e(d);if(0===c)for(var v=0;v<m.length;++v)s.push(dE(0));for(var g=0;g<m.length;++g){var y=m[g];s[g]=QI(s[g],tS(h-p,y))}}for(var b=0;b<s.length;++b)s[b]=eS(s[b],o);return s}))},n.getDedupedMetricsNames=function(){for(var e=this.metricsNames,t=[],n=0;n<e.length;++n){var r=e[n],a=r;if(YF(e,r)>1)a+="_"+YF(e.slice(0,n),r);t.push(a)}return t},n.makeTrainFunction=function(){var e=this;return function(t){var n=[],r=t.slice(0,e.inputs.length),a=t.slice(e.inputs.length,e.inputs.length+e.outputs.length),i=t.slice(e.inputs.length+e.outputs.length,e.inputs.length+2*e.outputs.length),o=[],s=e.collectedTrainableWeights.map((function(e){return e.read()}));return[e.optimizer_.minimize((function(){for(var t=[],s=0;s<e.inputs.length;++s)t.push({key:e.inputs[s],value:r[s]});for(var u,l=new GM(t),c=qM(e.outputs,l,{training:!0}),p=0;p<e.lossFunctions.length;++p){var h=(0,e.lossFunctions[p])(a[p],c[p]);null!=i[p]&&(h=eL(h,i[p]));var f=vC(h);n.push(f),u=0===p?h:QI(u,h)}for(var d=0;d<e.metricsTensors.length;++d){var m=void 0;if(e.outputs.length>1&&d<e.outputs.length)m=n[d];else{var v=e.metricsTensors[d][0],g=e.metricsTensors[d][1];m=vC(v(a[g],c[g]))}XI(m),o.push(m)}return u=vC(u),e.calculateLosses().forEach((function(e){u=QI(u,e)})),u}),!0,s)].concat(o)}},n.makeTestFunction=function(){var e=this;this.testFunction=function(t){return qI((function(){for(var n,r=[],a=t.slice(0,e.inputs.length),i=t.slice(e.inputs.length,e.inputs.length+e.outputs.length),o=[],s=0;s<e.inputs.length;++s)o.push({key:e.inputs[s],value:a[s]});for(var u=new GM(o),l=qM(e.outputs,u),c=0;c<e.lossFunctions.length;++c){var p=e.lossFunctions[c],h=vC(p(i[c],l[c]));n=0===c?h:QI(n,h),r.push(n)}for(var f=0;f<e.metricsTensors.length;++f){var d=e.metricsTensors[f][0],m=e.metricsTensors[f][1],v=vC(d(i[m],l[m]));r.push(v)}return r}))}},n.fit=function(){var e=xv(regeneratorRuntime.mark((function e(t,n,r){return regeneratorRuntime.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:return void 0===r&&(r={}),e.abrupt("return",gL(this,t,n,r));case 2:case"end":return e.stop()}}),e,this)})));return function(t,n,r){return e.apply(this,arguments)}}(),n.fitDataset=function(){var e=xv(regeneratorRuntime.mark((function e(t,n){return regeneratorRuntime.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:return e.abrupt("return",aL(this,t,n));case 1:case"end":return e.stop()}}),e,this)})));return function(t,n){return e.apply(this,arguments)}}(),n.trainOnBatch=function(){var e=xv(regeneratorRuntime.mark((function e(t,n){var r,a,i,o,s,u,l,c,p,h;return regeneratorRuntime.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:return e.next=2,this.standardizeUserData(t,n);case 2:r=e.sent,a=r[0],i=r[1],o=this.makeTrainFunction(),s=o(a.concat(i)),u=[],l=Fv(s);case 9:if((c=l()).done){e.next=17;break}return p=c.value,e.next=13,p.data();case 13:h=e.sent,u.push(h[0]);case 15:e.next=9;break;case 17:return KI(s),e.abrupt("return",JF(u));case 19:case"end":return e.stop()}}),e,this)})));return function(t,n){return e.apply(this,arguments)}}(),n.getNamedWeights=function(e){for(var t=[],n=null!=e&&e.trainableOnly,r=n?this.trainableWeights:this.weights,a=this.getWeights(n),i=0;i<r.length;++i)n&&!r[i].trainable||t.push({name:r[i].originalName,tensor:a[i]});return t},n.dispose=function(){var t=e.prototype.dispose.call(this);if(0===t.refCountAfterDispose&&null!=this.optimizer&&this.isOptimizerOwned){var n=HI().numTensors;this.optimizer_.dispose(),t.numDisposedVariables+=n-HI().numTensors}return t},n.getLossIdentifiers=function(){var e;if("string"==typeof this.loss)e=QF(this.loss);else if(Array.isArray(this.loss)){for(var t,n=Fv(this.loss);!(t=n()).done;){if("string"!=typeof t.value)throw new Error("Serialization of non-string loss is not supported.")}e=this.loss.map((function(e){return QF(e)}))}else{var r=Object.keys(this.loss);e={};for(var a=this.loss,i=0,o=r;i<o.length;i++){var s=o[i];if("string"!=typeof a[s])throw new Error("Serialization of non-string loss is not supported.");e[s]=QF(a[s])}}return e},n.getMetricIdentifiers=function(){if("string"==typeof this.metrics||"function"==typeof this.metrics)return[QF(_M(this.metrics))];if(Array.isArray(this.metrics))return this.metrics.map((function(e){return QF(_M(e))}));var e={};for(var t in this.metrics)e[t]=QF(_M(this.metrics[t]));return e},n.getTrainingConfig=function(){return{loss:this.getLossIdentifiers(),metrics:this.getMetricIdentifiers(),optimizer_config:{class_name:this.optimizer.getClassName(),config:this.optimizer.getConfig()}}},n.loadTrainingConfig=function(e){if(null!=e.weighted_metrics)throw new Error("Loading weight_metrics is not supported yet.");if(null!=e.loss_weights)throw new Error("Loading loss_weights is not supported yet.");if(null!=e.sample_weight_mode)throw new Error("Loading sample_weight_mode is not supported 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e.apply(this,arguments)}}(),n.setUserDefinedMetadata=function(e){DM(e,this.name),this.userDefinedMetadata=e},n.getUserDefinedMetadata=function(){return this.userDefinedMetadata},kv(t,[{key:"stopTraining",get:function(){return this.stopTraining_},set:function(e){this.stopTraining_=e}},{key:"optimizer",get:function(){return this.optimizer_},set:function(e){this.optimizer_!==e&&(this.optimizer_=e,this.isOptimizerOwned=!1)}}]),t}(function(e){function t(n){var r;if((r=e.call(this,{})||this).containerNodes=new Set,r.name=n.name,null==r.name){var a=r.getClassName().toLowerCase();r.name=AO(a)}if(r.supportsMasking=!1,r.trainable_=!0,Array.isArray(n.inputs)?r.inputs=n.inputs.slice():r.inputs=[n.inputs],Array.isArray(n.outputs)?r.outputs=n.outputs.slice():r.outputs=[n.outputs],iD(r.inputs).length!==r.inputs.length)throw new jF("The list of inputs passed to the model is redundant. 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n,r=Fv(this.sharedAxes);!(n=r()).done;){t[n.value-1]=1}this.alpha=this.addWeight("alpha",t,"float32",this.alphaInitializer,this.alphaRegularizer,!0,this.alphaConstraint);var a={};if(null!=this.sharedAxes)for(var i=1;i<e.length;++i)a[i]=e[i];this.inputSpec=[new WO({ndim:e.length,axes:a})],this.built=!0},n.call=function(e,t){return e=DO(e),BC(e,this.alpha.read())},n.getConfig=function(){var t={alphaInitializer:IO(this.alphaInitializer),alphaRegularizer:nz(this.alphaRegularizer),alphaConstraint:bD(this.alphaConstraint),sharedAxes:this.sharedAxes},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(HO);sz.className="PReLU",MI(sz);var uz=function(e){function t(t){var n;if((n=e.call(this,null==t?{}:t)||this).DEFAULT_ALPHA=1,null==t&&(t={}),null!=t.alpha&&t.alpha!==n.DEFAULT_ALPHA)throw new HF("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}Nv(t,e);var n=t.prototype;return n.call=function(e,t){var n=DO(e);return xT(n)},n.computeOutputShape=function(e){return e},n.getConfig=function(){var t={alpha:this.alpha},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(HO);uz.className="ELU",MI(uz);var lz=function(e){function t(t){var n;return(n=e.call(this,null==t?{}:t)||this).DEFAULT_THETA=1,null==t&&(t={}),n.theta=null==t.theta?n.DEFAULT_THETA:t.theta,n}Nv(t,e);var n=t.prototype;return n.call=function(e,t){var n=DO(e);return tS(n,_N(AT(n,this.theta),"float32"))},n.computeOutputShape=function(e){return e},n.getConfig=function(){var t={theta:this.theta},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(HO);lz.className="ThresholdedReLU",MI(lz);var cz=function(e){function t(t){var n;return(n=e.call(this,null==t?{}:t)||this).DEFAULT_AXIS=1,null==t&&(t={}),n.softmax=(new HL).apply,n.axis=null==t.axis?n.DEFAULT_AXIS:t.axis,n}Nv(t,e);var n=t.prototype;return n.call=function(e,t){var n=DO(e);return 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single number for 1D convolution, but received "+JSON.stringify(a.dilationRate));if(2===a.rank){if("number"==typeof a.dilationRate)a.dilationRate=[a.dilationRate,a.dilationRate];else if(2!==a.dilationRate.length)throw new jF("dilationRate must be a number or array of two numbers for 2D convolution, but received "+JSON.stringify(a.dilationRate))}else if(3===a.rank)if("number"==typeof a.dilationRate)a.dilationRate=[a.dilationRate,a.dilationRate,a.dilationRate];else if(3!==a.dilationRate.length)throw new jF("dilationRate must be a number or array of three numbers for 3D convolution, but received "+JSON.stringify(a.dilationRate));return a}return Nv(t,e),t.verifyArgs=function(e){if(XF("kernelSize"in e,"required key 'kernelSize' not in config"),"number"!=typeof e.kernelSize&&!uD(e.kernelSize,"number",1,3))throw new jF("BaseConv expects config.kernelSize to be number or number[] with length 1, 2, or 3, but received "+JSON.stringify(e.kernelSize)+".")},t.prototype.getConfig=function(){var t={kernelSize:this.kernelSize,strides:this.strides,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,activation:YL(this.activation),useBias:this.useBias,biasInitializer:IO(this.biasInitializer),biasRegularizer:nz(this.biasRegularizer),activityRegularizer:nz(this.activityRegularizer),biasConstraint:bD(this.biasConstraint)},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(HO),xz=function(e){function t(n,r){var a;return(a=e.call(this,n,r)||this).kernel=null,t.verifyArgs(r),a.filters=r.filters,lD(a.filters,"filters"),a.kernelInitializer=SO(r.kernelInitializer||a.DEFAULT_KERNEL_INITIALIZER),a.kernelConstraint=wD(r.kernelConstraint),a.kernelRegularizer=az(r.kernelRegularizer),a}Nv(t,e);var n=t.prototype;return n.build=function(e){var t;e=OO(e);var n="channelsFirst"===this.dataFormat?1:e.length-1;if(null==e[n])throw new jF("The channel dimension of the input should be defined. Found "+e[n]);var r=e[n],a=this.kernelSize.concat([r,this.filters]);this.kernel=this.addWeight("kernel",a,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:(t={},t[n]=r,t)}],this.built=!0},n.call=function(e,t){var n=this;return qI((function(){var t;e=DO(e);var r=null==n.bias?null:n.bias.read(),a=pD(n.activation.getClassName());if(null!=a&&2===n.rank)t=gz(e,n.kernel.read(),r,n.strides,n.padding,n.dataFormat,n.dilationRate,a);else{if(1===n.rank)t=vz(e,n.kernel.read(),r,n.strides[0],n.padding,n.dataFormat,n.dilationRate[0]);else if(2===n.rank)t=gz(e,n.kernel.read(),r,n.strides,n.padding,n.dataFormat,n.dilationRate);else{if(3!==n.rank)throw new HF("convolutions greater than 3D are not implemented yet.");t=yz(e,n.kernel.read(),r,n.strides,n.padding,n.dataFormat,n.dilationRate)}null!=n.activation&&(t=n.activation.apply(t))}return t}))},n.computeOutputShape=function(e){e=OO(e);for(var t=[],n="channelsLast"===this.dataFormat?e.slice(1,e.length-1):e.slice(2),r=0;r<n.length;++r){var a=hz(n[r],this.kernelSize[r],this.padding,this.strides[r],"number"==typeof this.dilationRate?this.dilationRate:this.dilationRate[r]);t.push(a)}var i=[e[0]];return"channelsLast"===this.dataFormat?(i=i.concat(t)).push(this.filters):(i.push(this.filters),i=i.concat(t)),i},n.getConfig=function(){var t={filters:this.filters,kernelInitializer:IO(this.kernelInitializer),kernelRegularizer:nz(this.kernelRegularizer),kernelConstraint:bD(this.kernelConstraint)},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t.verifyArgs=function(e){if(!("filters"in e)||"number"!=typeof e.filters||e.filters<1)throw new jF("Convolution layer expected config.filters to be a 'number' > 0 but got "+JSON.stringify(e.filters))},t}(bz),wz=function(e){function t(n){var r;return r=e.call(this,2,n)||this,t.verifyArgs(n),r}return Nv(t,e),t.prototype.getConfig=function(){var t=e.prototype.getConfig.call(this);return delete t.rank,t},t.verifyArgs=function(e){if("number"!=typeof e.kernelSize&&!uD(e.kernelSize,"number",1,2))throw new jF("Conv2D expects config.kernelSize to be number or number[] with length 1 or 2, but received "+JSON.stringify(e.kernelSize)+".")},t}(xz);wz.className="Conv2D",MI(wz);var kz=function(e){function t(n){var r;return r=e.call(this,3,n)||this,t.verifyArgs(n),r}return Nv(t,e),t.prototype.getConfig=function(){var t=e.prototype.getConfig.call(this);return delete t.rank,t},t.verifyArgs=function(e){if("number"!=typeof e.kernelSize&&(!Array.isArray(e.kernelSize)||1!==e.kernelSize.length&&3!==e.kernelSize.length))throw new jF("Conv3D expects config.kernelSize to be number or [number, number, number], but received "+JSON.stringify(e.kernelSize)+".")},t}(xz);kz.className="Conv3D",MI(kz);var Nz=function(e){function t(t){var n;if((n=e.call(this,t)||this).inputSpec=[new WO({ndim:4})],"same"!==n.padding&&"valid"!==n.padding)throw new jF("Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode "+n.padding);return n}Nv(t,e);var n=t.prototype;return n.build=function(e){var t;if(4!==(e=OO(e)).length)throw new jF("Input should have rank 4; Received input shape: "+JSON.stringify(e));var n="channelsFirst"===this.dataFormat?1:e.length-1;if(null==e[n])throw new jF("The channel dimension of the inputs should be defined. Found `None`.");var r=e[n],a=this.kernelSize.concat([this.filters,r]);this.kernel=this.addWeight("kernel",a,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new WO({ndim:4,axes:(t={},t[n]=r,t)})],this.built=!0},n.call=function(e,t){var n=this;return qI((function(){var t=DO(e);if(4!==t.shape.length)throw new jF("Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-"+t.shape.length);var r,a,i=t.shape,o=i[0];"channelsFirst"===n.dataFormat?(r=2,a=3):(r=1,a=2);var s=i[r],u=i[a],l=n.kernelSize[0],c=n.kernelSize[1],p=n.strides[0],h=n.strides[1],f=[o,fz(s,p,l,n.padding),fz(u,h,c,n.padding),n.filters];"channelsLast"!==n.dataFormat&&(t=eI(t,[0,2,3,1]));var d=$S(t,n.kernel.read(),f,n.strides,n.padding);return"channelsLast"!==n.dataFormat&&(d=eI(d,[0,3,1,2])),null!=n.bias&&(d=tO(d,n.bias.read(),n.dataFormat)),null!=n.activation&&(d=n.activation.apply(d)),d}))},n.computeOutputShape=function(e){var t,n,r,a=(e=OO(e)).slice();"channelsFirst"===this.dataFormat?(t=1,n=2,r=3):(t=3,n=1,r=2);var i=this.kernelSize[0],o=this.kernelSize[1],s=this.strides[0],u=this.strides[1];return a[t]=this.filters,a[n]=fz(a[n],s,i,this.padding),a[r]=fz(a[r],u,o,this.padding),a},n.getConfig=function(){var t=e.prototype.getConfig.call(this);return delete t.dilationRate,t},t}(wz);Nz.className="Conv2DTranspose",MI(Nz);var Iz=function(e){function t(t){var n;if((n=e.call(this,t)||this).inputSpec=[new WO({ndim:5})],"same"!==n.padding&&"valid"!==n.padding)throw new jF("Conv3DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode "+n.padding);return n}Nv(t,e);var n=t.prototype;return n.build=function(e){var t;if(5!==(e=OO(e)).length)throw new jF("Input should have rank 5; Received input shape: "+JSON.stringify(e));var n="channelsFirst"===this.dataFormat?1:e.length-1;if(null==e[n])throw new jF("The channel dimension of the inputs should be defined. Found `None`.");var r=e[n],a=this.kernelSize.concat([this.filters,r]);this.kernel=this.addWeight("kernel",a,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new WO({ndim:5,axes:(t={},t[n]=r,t)})],this.built=!0},n.call=function(e,t){var n=this;return qI((function(){var t=DO(e);if(5!==t.shape.length)throw new jF("Conv3DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-"+t.shape.length);var r,a,i,o=t.shape,s=o[0];"channelsFirst"===n.dataFormat?(i=2,r=3,a=4):(i=1,r=2,a=3);var u=o[i],l=o[r],c=o[a],p=n.kernelSize[0],h=n.kernelSize[1],f=n.kernelSize[2],d=n.strides[0],m=n.strides[1],v=n.strides[2],g=[s,fz(u,d,p,n.padding),fz(l,m,h,n.padding),fz(c,v,f,n.padding),n.filters];"channelsLast"!==n.dataFormat&&(t=eI(t,[0,2,3,4,1]));var y=nT(t,n.kernel.read(),g,n.strides,n.padding);return"channelsLast"!==n.dataFormat&&(y=eI(y,[0,4,1,2,3])),null!==n.bias&&(y=tO(y,n.bias.read(),n.dataFormat)),null!==n.activation&&(y=n.activation.apply(y)),y}))},n.computeOutputShape=function(e){var t,n,r,a,i=(e=OO(e)).slice();"channelsFirst"===this.dataFormat?(t=1,n=2,r=3,a=4):(t=4,n=1,r=2,a=3);var o=this.kernelSize[0],s=this.kernelSize[1],u=this.kernelSize[2],l=this.strides[0],c=this.strides[1],p=this.strides[2];return i[t]=this.filters,i[n]=fz(i[n],l,o,this.padding),i[r]=fz(i[r],c,s,this.padding),i[a]=fz(i[a],p,u,this.padding),i},n.getConfig=function(){var t=e.prototype.getConfig.call(this);return delete t.dilationRate,t},t}(kz);Iz.className="Conv3DTranspose",MI(Iz);var Sz=function(e){function t(t,n){var r;if((r=e.call(this,t,n)||this).DEFAULT_DEPTHWISE_INITIALIZER="glorotUniform",r.DEFAULT_POINTWISE_INITIALIZER="glorotUniform",r.depthwiseKernel=null,r.pointwiseKernel=null,null==n.filters)throw new jF("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(null!=n.kernelInitializer||null!=n.kernelRegularizer||null!=n.kernelConstraint)throw new jF("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 jF("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=SO(n.depthwiseInitializer||r.DEFAULT_DEPTHWISE_INITIALIZER),r.depthwiseRegularizer=az(n.depthwiseRegularizer),r.depthwiseConstraint=wD(n.depthwiseConstraint),r.pointwiseInitializer=SO(n.depthwiseInitializer||r.DEFAULT_POINTWISE_INITIALIZER),r.pointwiseRegularizer=az(n.pointwiseRegularizer),r.pointwiseConstraint=wD(n.pointwiseConstraint),r}Nv(t,e);var n=t.prototype;return n.build=function(e){var t;if((e=OO(e)).length<this.rank+2)throw new jF("Inputs to SeparableConv"+this.rank+"D should have rank "+(this.rank+2)+", but received input shape: "+JSON.stringify(e));var n="channelsFirst"===this.dataFormat?1:e.length-1;if(null==e[n]||e[n]<0)throw new jF("The channel dimension of the inputs should be defined, but found "+JSON.stringify(e[n]));for(var r=e[n],a=this.kernelSize.concat([r,this.depthMultiplier]),i=[],o=0;o<this.rank;++o)i.push(1);i.push(r*this.depthMultiplier,this.filters);var s=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",a,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,s,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",i,"float32",this.pointwiseInitializer,this.pointwiseRegularizer,s,this.pointwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,s,this.biasConstraint):this.bias=null,this.inputSpec=[new WO({ndim:this.rank+2,axes:(t={},t[n]=r,t)})],this.built=!0},n.call=function(e,t){var n=this;return qI((function(){var t;if(e=DO(e),1===n.rank)throw new HF("1D separable convolution is not implemented yet.");return 2===n.rank&&("channelsFirst"===n.dataFormat&&(e=eI(e,[0,2,3,1])),t=vE(e,n.depthwiseKernel.read(),n.pointwiseKernel.read(),n.strides,n.padding,n.dilationRate,"NHWC")),n.useBias&&(t=tO(t,n.bias.read(),n.dataFormat)),null!=n.activation&&(t=n.activation.apply(t)),"channelsFirst"===n.dataFormat&&(t=eI(t,[0,3,1,2])),t}))},n.getConfig=function(){var t=e.prototype.getConfig.call(this);return delete t.rank,delete t.kernelInitializer,delete t.kernelRegularizer,delete t.kernelConstraint,t.depthwiseInitializer=IO(this.depthwiseInitializer),t.pointwiseInitializer=IO(this.pointwiseInitializer),t.depthwiseRegularizer=nz(this.depthwiseRegularizer),t.pointwiseRegularizer=nz(this.pointwiseRegularizer),t.depthwiseConstraint=bD(this.depthwiseConstraint),t.pointwiseConstraint=bD(this.pointwiseConstraint),t},t}(xz);Sz.className="SeparableConv";var Tz=function(e){function t(t){return e.call(this,2,t)||this}return Nv(t,e),t}(Sz);Tz.className="SeparableConv2D",MI(Tz);var Cz=function(e){function t(n){var r;return r=e.call(this,1,n)||this,t.verifyArgs(n),r.inputSpec=[{ndim:3}],r}return Nv(t,e),t.prototype.getConfig=function(){var t=e.prototype.getConfig.call(this);return delete t.rank,delete t.dataFormat,t},t.verifyArgs=function(e){if("number"!=typeof e.kernelSize&&!uD(e.kernelSize,"number",1,1))throw new jF("Conv1D expects config.kernelSize to be number or number[] with length 1, but received "+JSON.stringify(e.kernelSize)+".")},t}(xz);Cz.className="Conv1D",MI(Cz);var Ez=function(e){function t(t){var n;return n=e.call(this,t)||this,"number"==typeof t.cropping?n.cropping=[[t.cropping,t.cropping],[t.cropping,t.cropping]]:"number"==typeof t.cropping[0]?n.cropping=[[t.cropping[0],t.cropping[0]],[t.cropping[1],t.cropping[1]]]:n.cropping=t.cropping,n.dataFormat=void 0===t.dataFormat?"channelsLast":t.dataFormat,n.inputSpec=[{ndim:4}],n}Nv(t,e);var n=t.prototype;return n.computeOutputShape=function(e){return"channelsFirst"===this.dataFormat?[e[0],e[1],e[2]-this.cropping[0][0]-this.cropping[0][1],e[3]-this.cropping[1][0]-this.cropping[1][1]]:[e[0],e[1]-this.cropping[0][0]-this.cropping[0][1],e[2]-this.cropping[1][0]-this.cropping[1][1],e[3]]},n.call=function(e,t){var n=this;return qI((function(){if(e=DO(e),"channelsLast"===n.dataFormat){var t=qD(e,n.cropping[0][0],e.shape[1]-n.cropping[0][0]-n.cropping[0][1],2);return qD(t,n.cropping[1][0],e.shape[2]-n.cropping[1][1]-n.cropping[1][0],3)}var r=qD(e,n.cropping[0][0],e.shape[2]-n.cropping[0][0]-n.cropping[0][1],3);return qD(r,n.cropping[1][0],e.shape[3]-n.cropping[1][1]-n.cropping[1][0],4)}))},n.getConfig=function(){var t={cropping:this.cropping,dataFormat:this.dataFormat},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(HO);Ez.className="Cropping2D",MI(Ez);var Rz=function(e){function t(t){var n,r;return(n=e.call(this,t)||this).DEFAULT_SIZE=[2,2],n.inputSpec=[{ndim:4}],n.size=null==t.size?n.DEFAULT_SIZE:t.size,n.dataFormat=null==t.dataFormat?"channelsLast":t.dataFormat,RD(n.dataFormat),n.interpolation=null==t.interpolation?"nearest":t.interpolation,r=n.interpolation,sD(ID,"InterpolationFormat",r),n}Nv(t,e);var n=t.prototype;return n.computeOutputShape=function(e){if("channelsFirst"===this.dataFormat){var t=null==e[2]?null:this.size[0]*e[2],n=null==e[3]?null:this.size[1]*e[3];return[e[0],e[1],t,n]}var r=null==e[1]?null:this.size[0]*e[1],a=null==e[2]?null:this.size[1]*e[2];return[e[0],r,a,e[3]]},n.call=function(e,t){var n=this;return qI((function(){var t=DO(e),r=t.shape;if("channelsFirst"===n.dataFormat){t=eI(t,[0,2,3,1]);var a=n.size[0]*r[2],i=n.size[1]*r[3],o="nearest"===n.interpolation?NA.resizeNearestNeighbor(t,[a,i]):NA.resizeBilinear(t,[a,i]);return eI(o,[0,3,1,2])}var s=n.size[0]*r[1],u=n.size[1]*r[2];return"nearest"===n.interpolation?NA.resizeNearestNeighbor(t,[s,u]):NA.resizeBilinear(t,[s,u])}))},n.getConfig=function(){var t={size:this.size,dataFormat:this.dataFormat},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(HO);Rz.className="UpSampling2D",MI(Rz);var Az=function(e){function t(t){var n;return(n=e.call(this,2,t)||this).depthwiseKernel=null,n.depthMultiplier=null==t.depthMultiplier?1:t.depthMultiplier,n.depthwiseInitializer=SO(t.depthwiseInitializer||n.DEFAULT_KERNEL_INITIALIZER),n.depthwiseConstraint=wD(t.depthwiseConstraint),n.depthwiseRegularizer=az(t.depthwiseRegularizer),n}Nv(t,e);var n=t.prototype;return n.build=function(e){if((e=OO(e)).length<4)throw new jF("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 jF("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},n.call=function(e,t){var n=this;return qI((function(){e=DO(e);var t,r,a,i,o,s,u=(t=e,r=n.depthwiseKernel.read(),a=n.strides,i=n.padding,o=n.dataFormat,s=null,void 0===a&&(a=[1,1]),void 0===i&&(i="valid"),qI((function(){null==o&&(o="channelsLast"),RD(o);var e=dz(t,o);if(4!==t.rank)throw new jF("Input for depthwiseConv2d is required to be 4-D, but is instead "+t.rank+"-D");if(4!==r.rank)throw new jF("depthwiseKernel is required to be 4-D, but is instead "+r.rank+"-D");return e=uT(e,r,a,"same"===i?"same":"valid","NHWC",s),"channelsFirst"===o&&(e=eI(e,[0,3,1,2])),e})));return n.useBias&&(u=tO(u,n.bias.read(),n.dataFormat)),null!=n.activation&&(u=n.activation.apply(u)),u}))},n.computeOutputShape=function(e){e=OO(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,a=hz(t,this.kernelSize[0],this.padding,this.strides[0]),i=hz(n,this.kernelSize[1],this.padding,this.strides[1]);return"channelsFirst"===this.dataFormat?[e[0],r,a,i]:[e[0],a,i,r]},n.getConfig=function(){var t=e.prototype.getConfig.call(this);return t.depthMultiplier=this.depthMultiplier,t.depthwiseInitializer=IO(this.depthwiseInitializer),t.depthwiseRegularizer=nz(this.depthwiseRegularizer),t.depthwiseConstraint=bD(this.depthwiseRegularizer),t},t}(bz);function _z(e,t,n,r){if(Array.isArray(e)){if(null!=t||null!=n)throw new jF("When inputs is an array, neither initialState or constants should be provided");null!=r&&(n=e.slice(e.length-r,e.length),e=e.slice(0,e.length-r)),e.length>1&&(t=e.slice(1,e.length)),e=e[0]}function a(e){return null==e||Array.isArray(e)?e:[e]}return{inputs:e,initialState:t=a(t),constants:n=a(n)}}function Fz(e,t,n,r,a,i,o,s){return void 0===r&&(r=!1),void 0===o&&(o=!1),void 0===s&&(s=!1),qI((function(){var u=t.shape.length;if(u<3)throw new jF("Input should be at least 3D, but is "+u+"D.");var l=[1,0].concat(VD(2,u));if(t=eI(t,l),null!=i)throw new HF("The rnn() functoin of the deeplearn.js backend does not support constants yet.");o&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),null!=a&&((a=_N(_N(a,"bool"),"float32")).rank===u-1&&(a=NT(a,-1)),a=eI(a,l)),r&&(t=sE(t,0),null!=a&&(a=sE(a,0)));var c,p,h=[],f=n,d=t.shape[0],m=XE(t);null!=a&&(p=XE(a));for(var v,g=function(t){var n=m[t],r=qI((function(){return e(n,f)}));if(null==a)c=r[0],f=r[1];else{var i=qI((function(){var e=p[t],n=JT(RC(e),e);return{output:QI(tS(r[0],e),tS(f[0],n)),newStates:f.map((function(t,a){return QI(tS(r[1][a],e),tS(t,n))}))}}));c=i.output,f=i.newStates}s&&h.push(c)},y=0;y<d;++y)g(y);if(s){v=ME(h,1)}return[c,v,f]}))}Az.className="DepthwiseConv2D",MI(Az);var Dz=function(e){function t(t){var n,r;if(n=e.call(this,t)||this,null==t.cell)throw new jF("cell property is missing for the constructor of RNN.");if(null==(r=Array.isArray(t.cell)?new Vz({cells:t.cell}):t.cell).stateSize)throw new jF("The RNN cell should have an attribute `stateSize` (tuple of integers, one integer per RNN state).");return n.cell=r,n.returnSequences=null!=t.returnSequences&&t.returnSequences,n.returnState=null!=t.returnState&&t.returnState,n.goBackwards=null!=t.goBackwards&&t.goBackwards,n._stateful=null!=t.stateful&&t.stateful,n.unroll=null!=t.unroll&&t.unroll,n.supportsMasking=!0,n.inputSpec=[new WO({ndim:3})],n.stateSpec=null,n.states_=null,n.numConstants=null,n.keptStates=[],n}Nv(t,e);var n=t.prototype;return n.getStates=function(){return null==this.states_?VD(0,Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1).map((function(e){return null})):this.states_},n.setStates=function(e){this.states_=e},n.computeOutputShape=function(e){_O(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 a,i=[],o=Fv(t);!(a=o()).done;){var s=a.value;i.push([e[0],s])}return[n].concat(i)}return n},n.computeMask=function(e,t){var n=this;return qI((function(){Array.isArray(t)&&(t=t[0]);var e=n.returnSequences?t:null;if(n.returnState){var r=n.states.map((function(e){return null}));return[e].concat(r)}return e}))},n.build=function(e){if(null!=this.numConstants)throw new HF("Constants support is not implemented in RNN yet.");_O(e)&&(e=e[0]),e=e;var t=this.stateful?e[0]:null,n=e.slice(2);this.inputSpec[0]=new WO({shape:[t,null].concat(n)});var r,a=[e[0]].concat(e.slice(2));if(this.cell.build(a),r=Array.isArray(this.cell.stateSize)?this.cell.stateSize:[this.cell.stateSize],null!=this.stateSpec){if(!qv(this.stateSpec.map((function(e){return e.shape[e.shape.length-1]})),r))throw new jF("An initialState was passed that is not compatible with cell.stateSize. Received stateSpec="+this.stateSpec+"; However cell.stateSize is "+this.cell.stateSize)}else this.stateSpec=r.map((function(e){return new WO({shape:[null,e]})}));this.stateful&&this.resetStates()},n.resetStates=function(e,t){var n=this;void 0===t&&(t=!1),qI((function(){if(!n.stateful)throw new UF("Cannot call resetStates() on an RNN Layer that is not stateful.");var r=n.inputSpec[0].shape[0];if(null==r)throw new jF("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==n.states_)Array.isArray(n.cell.stateSize)?n.states_=n.cell.stateSize.map((function(e){return gC([r,e])})):n.states_=[gC([r,n.cell.stateSize])];else if(null==e)KI(n.states_),null!=n.keptStates&&(KI(n.keptStates),n.keptStates=[]),Array.isArray(n.cell.stateSize)?n.states_=n.cell.stateSize.map((function(e){return gC([r,e])})):n.states_[0]=gC([r,n.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==n.states_.length)throw new jF("Layer "+n.name+" expects "+n.states_.length+" state(s), but it received "+e.length+" state value(s). Input received: "+e);!0===t?n.keptStates.push(n.states_.slice()):KI(n.states_);for(var a=0;a<n.states_.length;++a){var i=e[a],o=Array.isArray(n.cell.stateSize)?n.cell.stateSize[a]:n.cell.stateSize,s=[r,o];if(!qv(i.shape,s))throw new jF("State "+a+" is incompatible with layer "+n.name+": expected shape="+s+", received shape="+i.shape);n.states_[a]=i}}n.states_=n.states_.map((function(e){return XI(e.clone())}))}))},n.apply=function(t,n){var r=null==n?null:n.initialState,a=null==n?null:n.constants;null==n&&(n={});var i=_z(t,r,a,this.numConstants);t=i.inputs,r=i.initialState,a=i.constants;var o=[],s=[];if(null!=r){n.initialState=r,o=o.concat(r),this.stateSpec=[];for(var u,l=Fv(r);!(u=l()).done;){var c=u.value;this.stateSpec.push(new WO({shape:c.shape}))}s=s.concat(this.stateSpec)}if(null!=a&&(n.constants=a,o=o.concat(a),this.numConstants=a.length),o[0]instanceof VO){var p=[t].concat(o),h=this.inputSpec.concat(s),f=this.inputSpec;this.inputSpec=h;var d=e.prototype.apply.call(this,p,n);return this.inputSpec=f,d}return e.prototype.apply.call(this,t,n)},n.call=function(e,t){var n=this;return qI((function(){var r=null==t?null:t.mask,a=null==t?null:t.training,i=null==t?null:t.initialState;e=DO(e),null==i&&(i=n.stateful?n.states_:n.getInitialState(e));var o=Array.isArray(n.cell.stateSize)?n.cell.stateSize.length:1;if(i.length!==o)throw new jF("RNN Layer has "+o+" state(s) but was passed "+i.length+" initial state(s).");n.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");var s={training:a},u=Fz((function(e,t){var r=n.cell.call([e].concat(t),s);return[r[0],r.slice(1)]}),e,i,n.goBackwards,r,null,n.unroll,n.returnSequences),l=u[0],c=u[1],p=u[2];n.stateful&&n.resetStates(p,a);var h=n.returnSequences?c:l;return n.returnState?[h].concat(p):h}))},n.getInitialState=function(e){var t=this;return qI((function(){var n=gC(e.shape);return n=GD(n=ZT(n,[1,2])),Array.isArray(t.cell.stateSize)?t.cell.stateSize.map((function(e){return e>1?YD(n,[1,e]):n})):t.cell.stateSize>1?[YD(n,[1,t.cell.stateSize])]:[n]}))},n.setFastWeightInitDuringBuild=function(t){e.prototype.setFastWeightInitDuringBuild.call(this,t),null!=this.cell&&this.cell.setFastWeightInitDuringBuild(t)},n.getConfig=function(){var n=e.prototype.getConfig.call(this),r={returnSequences:this.returnSequences,returnState:this.returnState,goBackwards:this.goBackwards,stateful:this.stateful,unroll:this.unroll};null!=this.numConstants&&(r.numConstants=this.numConstants);var a=this.cell.getConfig();return this.getClassName()===t.className&&(r.cell={className:this.cell.getClassName(),config:a}),Object.assign({},a,n,r)},t.fromConfig=function(e,t,n){void 0===n&&(n={});var r=sM(t.cell,n);return new e(Object.assign(t,{cell:r}))},kv(t,[{key:"states",get:function(){if(null==this.states_){for(var e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1,t=[],n=0;n<e;++n)t.push(null);return t}return this.states_},set:function(e){this.states_=e}},{key:"trainableWeights",get:function(){return this.trainable?this.cell.trainableWeights:[]}},{key:"nonTrainableWeights",get:function(){return this.trainable?this.cell.nonTrainableWeights:this.cell.weights}}]),t}(HO);Dz.className="RNN",MI(Dz);var Oz=function(e){function t(){return e.apply(this,arguments)||this}return Nv(t,e),t}(HO),Mz=function(e){function t(t){var n;return(n=e.call(this,t)||this).DEFAULT_ACTIVATION="tanh",n.DEFAULT_KERNEL_INITIALIZER="glorotNormal",n.DEFAULT_RECURRENT_INITIALIZER="orthogonal",n.DEFAULT_BIAS_INITIALIZER="zeros",n.units=t.units,lD(n.units,"units"),n.activation=ZL(null==t.activation?n.DEFAULT_ACTIVATION:t.activation),n.useBias=null==t.useBias||t.useBias,n.kernelInitializer=SO(t.kernelInitializer||n.DEFAULT_KERNEL_INITIALIZER),n.recurrentInitializer=SO(t.recurrentInitializer||n.DEFAULT_RECURRENT_INITIALIZER),n.biasInitializer=SO(t.biasInitializer||n.DEFAULT_BIAS_INITIALIZER),n.kernelRegularizer=az(t.kernelRegularizer),n.recurrentRegularizer=az(t.recurrentRegularizer),n.biasRegularizer=az(t.biasRegularizer),n.kernelConstraint=wD(t.kernelConstraint),n.recurrentConstraint=wD(t.recurrentConstraint),n.biasConstraint=wD(t.biasConstraint),n.dropout=BD([1,WD([0,null==t.dropout?0:t.dropout])]),n.recurrentDropout=BD([1,WD([0,null==t.recurrentDropout?0:t.recurrentDropout])]),n.stateSize=n.units,n.dropoutMask=null,n.recurrentDropoutMask=null,n}Nv(t,e);var n=t.prototype;return n.build=function(e){e=OO(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},n.call=function(e,t){var n=this;return qI((function(){if(2!==(e=e).length)throw new jF("SimpleRNNCell expects 2 input Tensors, got "+e.length+".");var r=e[1];e=e[0];var a,i=null!=t.training&&t.training;0<n.dropout&&n.dropout<1&&null==n.dropoutMask&&(n.dropoutMask=Uz({ones:function(){return RC(e)},rate:n.dropout,training:i})),0<n.recurrentDropout&&n.recurrentDropout<1&&null==n.recurrentDropoutMask&&(n.recurrentDropoutMask=Uz({ones:function(){return RC(r)},rate:n.recurrentDropout,training:i}));var o=n.dropoutMask,s=n.recurrentDropoutMask;a=ZD(null!=o?tS(e,o):e,n.kernel.read()),null!=n.bias&&(a=tO(a,n.bias.read())),null!=s&&(r=tS(r,s));var u=QI(a,ZD(r,n.recurrentKernel.read()));return null!=n.activation&&(u=n.activation.apply(u)),[u,u]}))},n.getConfig=function(){var t=e.prototype.getConfig.call(this),n={units:this.units,activation:YL(this.activation),useBias:this.useBias,kernelInitializer:IO(this.kernelInitializer),recurrentInitializer:IO(this.recurrentInitializer),biasInitializer:IO(this.biasInitializer),kernelRegularizer:nz(this.kernelRegularizer),recurrentRegularizer:nz(this.recurrentRegularizer),biasRegularizer:nz(this.biasRegularizer),activityRegularizer:nz(this.activityRegularizer),kernelConstraint:bD(this.kernelConstraint),recurrentConstraint:bD(this.recurrentConstraint),biasConstraint:bD(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign({},t,n)},t}(Oz);Mz.className="SimpleRNNCell",MI(Mz);var Lz=function(e){function t(t){return t.cell=new Mz(t),e.call(this,t)||this}return Nv(t,e),t.prototype.call=function(t,n){var r=this;return qI((function(){null!=r.cell.dropoutMask&&(KI(r.cell.dropoutMask),r.cell.dropoutMask=null),null!=r.cell.recurrentDropoutMask&&(KI(r.cell.recurrentDropoutMask),r.cell.recurrentDropoutMask=null);var a=null==n?null:n.mask,i=null==n?null:n.training,o=null==n?null:n.initialState;return e.prototype.call.call(r,t,{mask:a,training:i,initialState:o})}))},t.fromConfig=function(e,t){return new e(t)},t}(Dz);Lz.className="SimpleRNN",MI(Lz);var zz=function(e){function t(t){var n;if((n=e.call(this,t)||this).DEFAULT_ACTIVATION="tanh",n.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",n.DEFAULT_KERNEL_INITIALIZER="glorotNormal",n.DEFAULT_RECURRENT_INITIALIZER="orthogonal",n.DEFAULT_BIAS_INITIALIZER="zeros",t.resetAfter)throw new jF("GRUCell does not support reset_after parameter set to true.");return n.units=t.units,lD(n.units,"units"),n.activation=ZL(void 0===t.activation?n.DEFAULT_ACTIVATION:t.activation),n.recurrentActivation=ZL(void 0===t.recurrentActivation?n.DEFAULT_RECURRENT_ACTIVATION:t.recurrentActivation),n.useBias=null==t.useBias||t.useBias,n.kernelInitializer=SO(t.kernelInitializer||n.DEFAULT_KERNEL_INITIALIZER),n.recurrentInitializer=SO(t.recurrentInitializer||n.DEFAULT_RECURRENT_INITIALIZER),n.biasInitializer=SO(t.biasInitializer||n.DEFAULT_BIAS_INITIALIZER),n.kernelRegularizer=az(t.kernelRegularizer),n.recurrentRegularizer=az(t.recurrentRegularizer),n.biasRegularizer=az(t.biasRegularizer),n.kernelConstraint=wD(t.kernelConstraint),n.recurrentConstraint=wD(t.recurrentConstraint),n.biasConstraint=wD(t.biasConstraint),n.dropout=BD([1,WD([0,null==t.dropout?0:t.dropout])]),n.recurrentDropout=BD([1,WD([0,null==t.recurrentDropout?0:t.recurrentDropout])]),n.implementation=t.implementation,n.stateSize=n.units,n.dropoutMask=null,n.recurrentDropoutMask=null,n}Nv(t,e);var n=t.prototype;return n.build=function(e){var t=(e=OO(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},n.call=function(e,t){var n=this;return qI((function(){if(2!==(e=e).length)throw new jF("GRUCell expects 2 input Tensors (inputs, h, c), got "+e.length+".");var r=null!=t.training&&t.training,a=e[1];e=e[0],0<n.dropout&&n.dropout<1&&null==n.dropoutMask&&(n.dropoutMask=Uz({ones:function(){return RC(e)},rate:n.dropout,training:r,count:3})),0<n.recurrentDropout&&n.recurrentDropout<1&&null==n.recurrentDropoutMask&&(n.recurrentDropoutMask=Uz({ones:function(){return RC(a)},rate:n.recurrentDropout,training:r,count:3}));var i,o,s,u=n.dropoutMask,l=n.recurrentDropoutMask;0<n.dropout&&n.dropout<1&&(e=tS(e,u[0]));var c=ZD(e,n.kernel.read());n.useBias&&(c=tO(c,n.bias.read())),0<n.recurrentDropout&&n.recurrentDropout<1&&(a=tS(a,l[0]));var p=n.recurrentKernel.read(),h=AE(p,[2*n.units,n.units],p.rank-1),f=h[0],d=h[1],m=ZD(a,f),v=AE(c,3,c.rank-1),g=v[0],y=v[1],b=v[2],x=AE(m,2,m.rank-1),w=x[0],k=x[1];i=n.recurrentActivation.apply(QI(g,w)),o=n.recurrentActivation.apply(QI(y,k));var N=ZD(tS(o,a),d);s=n.activation.apply(QI(b,N));var I=QI(tS(i,a),tS(QI(1,qT(i)),s));return[I,I]}))},n.getConfig=function(){var t=e.prototype.getConfig.call(this),n={units:this.units,activation:YL(this.activation),recurrentActivation:YL(this.recurrentActivation),useBias:this.useBias,kernelInitializer:IO(this.kernelInitializer),recurrentInitializer:IO(this.recurrentInitializer),biasInitializer:IO(this.biasInitializer),kernelRegularizer:nz(this.kernelRegularizer),recurrentRegularizer:nz(this.recurrentRegularizer),biasRegularizer:nz(this.biasRegularizer),activityRegularizer:nz(this.activityRegularizer),kernelConstraint:bD(this.kernelConstraint),recurrentConstraint:bD(this.recurrentConstraint),biasConstraint:bD(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign({},t,n)},t}(Oz);zz.className="GRUCell",MI(zz);var Pz=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 zz(t),e.call(this,t)||this}return Nv(t,e),t.prototype.call=function(t,n){var r=this;return qI((function(){null!=r.cell.dropoutMask&&(KI(r.cell.dropoutMask),r.cell.dropoutMask=null),null!=r.cell.recurrentDropoutMask&&(KI(r.cell.recurrentDropoutMask),r.cell.recurrentDropoutMask=null);var a=null==n?null:n.mask,i=null==n?null:n.training,o=null==n?null:n.initialState;return e.prototype.call.call(r,t,{mask:a,training:i,initialState:o})}))},t.fromConfig=function(e,t){return 0===t.implmentation&&(t.implementation=1),new e(t)},t}(Dz);Pz.className="GRU",MI(Pz);var Bz=function(e){function t(t){var n;return(n=e.call(this,t)||this).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,lD(n.units,"units"),n.activation=ZL(void 0===t.activation?n.DEFAULT_ACTIVATION:t.activation),n.recurrentActivation=ZL(void 0===t.recurrentActivation?n.DEFAULT_RECURRENT_ACTIVATION:t.recurrentActivation),n.useBias=null==t.useBias||t.useBias,n.kernelInitializer=SO(t.kernelInitializer||n.DEFAULT_KERNEL_INITIALIZER),n.recurrentInitializer=SO(t.recurrentInitializer||n.DEFAULT_RECURRENT_INITIALIZER),n.biasInitializer=SO(t.biasInitializer||n.DEFAULT_BIAS_INITIALIZER),n.unitForgetBias=t.unitForgetBias,n.kernelRegularizer=az(t.kernelRegularizer),n.recurrentRegularizer=az(t.recurrentRegularizer),n.biasRegularizer=az(t.biasRegularizer),n.kernelConstraint=wD(t.kernelConstraint),n.recurrentConstraint=wD(t.recurrentConstraint),n.biasConstraint=wD(t.biasConstraint),n.dropout=BD([1,WD([0,null==t.dropout?0:t.dropout])]),n.recurrentDropout=BD([1,WD([0,null==t.recurrentDropout?0:t.recurrentDropout])]),n.implementation=t.implementation,n.stateSize=[n.units,n.units],n.dropoutMask=null,n.recurrentDropoutMask=null,n}Nv(t,e);var n=t.prototype;return n.build=function(e){var t,n,r=(e=OO(e))[e.length-1];if(this.kernel=this.addWeight("kernel",[r,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),this.useBias){if(this.unitForgetBias){var a=this.biasInitializer,i=this.units;n=new((t=function(e){function t(){return e.apply(this,arguments)||this}return Nv(t,e),t.prototype.apply=function(e,t){var n=a.apply([i]),r=(new uO).apply([i]),o=a.apply([2*i]);return XD(XD(n,r),o)},t}(oO)).className="CustomInit",t)}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},n.call=function(e,t){var n=this;return qI((function(){var r=null!=t.training&&t.training;if(3!==(e=e).length)throw new jF("LSTMCell expects 3 input Tensors (inputs, h, c), got "+e.length+".");var a=e[1],i=e[2];e=e[0],0<n.dropout&&n.dropout<1&&null==n.dropoutMask&&(n.dropoutMask=Uz({ones:function(){return RC(e)},rate:n.dropout,training:r,count:4})),0<n.recurrentDropout&&n.recurrentDropout<1&&null==n.recurrentDropoutMask&&(n.recurrentDropoutMask=Uz({ones:function(){return RC(a)},rate:n.recurrentDropout,training:r,count:4}));var o,s,u,l,c=n.dropoutMask,p=n.recurrentDropoutMask;0<n.dropout&&n.dropout<1&&(e=tS(e,c[0]));var h=ZD(e,n.kernel.read());0<n.recurrentDropout&&n.recurrentDropout<1&&(a=tS(a,p[0])),h=QI(h,ZD(a,n.recurrentKernel.read())),n.useBias&&(h=tO(h,n.bias.read()));var f=AE(h,4,h.rank-1),d=f[0],m=f[1],v=f[2],g=f[3];o=n.recurrentActivation.apply(d),s=n.recurrentActivation.apply(m),u=QI(tS(s,i),tS(o,n.activation.apply(v))),l=n.recurrentActivation.apply(g);var y=tS(l,n.activation.apply(u));return[y,y,u]}))},n.getConfig=function(){var t=e.prototype.getConfig.call(this),n={units:this.units,activation:YL(this.activation),recurrentActivation:YL(this.recurrentActivation),useBias:this.useBias,kernelInitializer:IO(this.kernelInitializer),recurrentInitializer:IO(this.recurrentInitializer),biasInitializer:IO(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:nz(this.kernelRegularizer),recurrentRegularizer:nz(this.recurrentRegularizer),biasRegularizer:nz(this.biasRegularizer),activityRegularizer:nz(this.activityRegularizer),kernelConstraint:bD(this.kernelConstraint),recurrentConstraint:bD(this.recurrentConstraint),biasConstraint:bD(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return Object.assign({},t,n)},t}(Oz);Bz.className="LSTMCell",MI(Bz);var Wz=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 Bz(t),e.call(this,t)||this}return Nv(t,e),t.prototype.call=function(t,n){var r=this;return qI((function(){null!=r.cell.dropoutMask&&(KI(r.cell.dropoutMask),r.cell.dropoutMask=null),null!=r.cell.recurrentDropoutMask&&(KI(r.cell.recurrentDropoutMask),r.cell.recurrentDropoutMask=null);var a=null==n?null:n.mask,i=null==n?null:n.training,o=null==n?null:n.initialState;return e.prototype.call.call(r,t,{mask:a,training:i,initialState:o})}))},t.fromConfig=function(e,t){return 0===t.implmentation&&(t.implementation=1),new e(t)},t}(Dz);Wz.className="LSTM",MI(Wz);var Vz=function(e){function t(t){var n;return(n=e.call(this,t)||this).cells=t.cells,n}Nv(t,e);var n=t.prototype;return n.call=function(e,t){var n=this;return qI((function(){for(var r,a=(e=e).slice(1),i=[],o=Fv(n.cells.slice().reverse());!(r=o()).done;){var s=r.value;Array.isArray(s.stateSize)?i.push(a.splice(0,s.stateSize.length)):i.push(a.splice(0,1))}i.reverse();for(var u,l=[],c=0;c<n.cells.length;++c){var p=n.cells[c];a=i[c],u=0===c?[e[0]].concat(a):[u[0]].concat(a),u=p.call(u,t),l.push(u.slice(1))}a=[];for(var h,f=Fv(l.slice().reverse());!(h=f()).done;){var d,m=h.value;(d=a).push.apply(d,m)}return[u[0]].concat(a)}))},n.build=function(e){var t;_O(e)&&(e=e[0]),e=e,this.cells.forEach((function(n,r){DD("RNNCell_"+r,(function(){n.build(e),t=Array.isArray(n.stateSize)?n.stateSize[0]:n.stateSize,e=[e[0],t]}))})),this.built=!0},n.getConfig=function(){var t=e.prototype.getConfig.call(this),n={cells:this.cells.map((function(e){return{className:e.getClassName(),config:e.getConfig()}}))};return Object.assign({},t,n)},t.fromConfig=function(e,t,n){void 0===n&&(n={});for(var r,a=[],i=Fv(t.cells);!(r=i()).done;){var o=r.value;a.push(sM(o,n))}return new e({cells:a})},n.getWeights=function(){for(var e,t=[],n=Fv(this.cells);!(e=n()).done;){var r=e.value;t.push.apply(t,r.weights)}return PO(t)},n.setWeights=function(e){for(var t,n=[],r=Fv(this.cells);!(t=r()).done;)for(var a=t.value,i=a.weights.length,o=e.splice(i),s=0;s<a.weights.length;++s)n.push([a.weights[s],o[s]]);BO(n)},kv(t,[{key:"stateSize",get:function(){for(var e,t=[],n=Fv(this.cells.slice().reverse());!(e=n()).done;){var r=e.value;Array.isArray(r.stateSize)?t.push.apply(t,r.stateSize):t.push(r.stateSize)}return t}},{key:"trainableWeights",get:function(){if(!this.trainable)return[];for(var e,t=[],n=Fv(this.cells);!(e=n()).done;){var r=e.value;t.push.apply(t,r.trainableWeights)}return t}},{key:"nonTrainableWeights",get:function(){for(var e,t=[],n=Fv(this.cells);!(e=n()).done;){var r=e.value;t.push.apply(t,r.nonTrainableWeights)}if(!this.trainable){for(var a,i=[],o=Fv(this.cells);!(a=o()).done;){var s=a.value;i.push.apply(i,s.trainableWeights)}return i.concat(t)}return t}}]),t}(Oz);function Uz(e){var t=e.ones,n=e.rate,r=e.training,a=void 0!==r&&r,i=e.count,o=void 0===i?1:i,s=function(){return nO(t(),n)},u=function(){return rO(s,t,a)};return!o||o<=1?XI(u().clone()):Array(o).fill(void 0).map(u).map((function(e){return XI(e.clone())}))}Vz.className="StackedRNNCells",MI(Vz);var Gz=function(e,t){var n={};for(var r in e)Object.prototype.hasOwnProperty.call(e,r)&&t.indexOf(r)<0&&(n[r]=e[r]);if(null!=e&&"function"==typeof Object.getOwnPropertySymbols){var a=0;for(r=Object.getOwnPropertySymbols(e);a<r.length;a++)t.indexOf(r[a])<0&&Object.prototype.propertyIsEnumerable.call(e,r[a])&&(n[r[a]]=e[r[a]])}return n},jz=function(e){function t(t){var n;if(t.unroll)throw new HF("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(t.cell))throw new HF("It is not possible at the moment to stack convolutional cells.");return(n=e.call(this,t)||this).inputSpec=[new WO({ndim:5})],n}Nv(t,e);var n=t.prototype;return n.call=function(t,n){var r=this;return qI((function(){if(null!=r.cell.dropoutMask&&(KI(r.cell.dropoutMask),r.cell.dropoutMask=null),null!=r.cell.recurrentDropoutMask&&(KI(r.cell.recurrentDropoutMask),r.cell.recurrentDropoutMask=null),n&&n.constants)throw new jF("ConvRNN2D cell does not support constants");var a=null==n?null:n.mask,i=null==n?null:n.training,o=null==n?null:n.initialState;return e.prototype.call.call(r,t,{mask:a,training:i,initialState:o})}))},n.computeOutputShape=function(e){var t=this.computeSingleOutputShape(e);return this.returnSequences||(t=[t[0]].concat(t.slice(2))),this.returnState&&(t=[t].concat(Array(2).fill([e[0]].concat(t.slice(-3))))),t},n.getInitialState=function(e){var t=this;return qI((function(){var n=t.cell.stateSize,r=e.shape,a=t.computeSingleOutputShape(r),i=gC([a[0]].concat(a.slice(2)));return Array.isArray(n)?Array(n.length).fill(i):[i]}))},n.resetStates=function(e,t){var n=this;void 0===t&&(t=!1),qI((function(){if(!n.stateful)throw new UF("Cannot call resetStates() on an RNN Layer that is not stateful.");var r=n.inputSpec[0].shape,a=n.computeSingleOutputShape(r),i=[a[0]].concat(a.slice(2));if(null==r[0])throw new jF("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==n.getStates())Array.isArray(n.cell.stateSize)?n.states_=n.cell.stateSize.map((function(){return gC(i)})):n.states_=[gC(i)];else if(null==e)KI(n.states_),null!=n.keptStates&&(KI(n.keptStates),n.keptStates=[]),Array.isArray(n.cell.stateSize)?n.states_=n.cell.stateSize.map((function(){return gC(i)})):n.states_[0]=gC(i);else{if(Array.isArray(e)||(e=[e]),e.length!==n.states_.length)throw new jF("Layer "+n.name+" expects "+n.states_.length+" state(s), but it received "+e.length+" state value(s). Input received: "+e);t?n.keptStates.push(n.states_.slice()):KI(n.states_);for(var o=0;o<n.states_.length;++o){var s=e[o],u=i;if(!qv(s.shape,u))throw new jF("State "+o+" is incompatible with layer "+n.name+": expected shape="+u+", received shape="+s.shape);n.states_[o]=s}}n.states_=n.states_.map((function(e){return XI(e.clone())}))}))},n.computeSingleOutputShape=function(e){var t=this.cell,n=t.dataFormat,r=t.filters,a=t.kernelSize,i=t.padding,o=t.strides,s=t.dilationRate,u="channelsFirst"===n,l=e[u?3:2],c=e[u?4:3],p=hz(l,a[0],i,o[0],s[0]),h=hz(c,a[1],i,o[1],s[1]);return[].concat(e.slice(0,2),u?[r,p,h]:[p,h,r])},t}(Dz);jz.className="ConvRNN2D";var Hz=function(e){function t(t){var n,r=t.filters,a=t.kernelSize,i=t.strides,o=t.padding,s=t.dataFormat,u=t.dilationRate;return(n=e.call(this,Object.assign({},t,{units:r}))||this).filters=r,lD(n.filters,"filters"),n.kernelSize=pz(a,2,"kernelSize"),n.kernelSize.forEach((function(e){return lD(e,"kernelSize")})),n.strides=pz(i||1,2,"strides"),n.strides.forEach((function(e){return lD(e,"strides")})),n.padding=o||"valid",AD(n.padding),n.dataFormat=s||"channelsLast",RD(n.dataFormat),n.dilationRate=pz(u||1,2,"dilationRate"),n.dilationRate.forEach((function(e){return lD(e,"dilationRate")})),n}Nv(t,e);var n=t.prototype;return n.build=function(e){var t;e=OO(e);var n="channelsFirst"===this.dataFormat?1:e.length-1;if(null==e[n])throw new jF("The channel dimension of the input should be defined. Found "+e[n]);var r=e[n],a=this.kernelSize.concat([r,4*this.filters]);this.kernel=this.addWeight("kernel",a,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);var i=this.kernelSize.concat([this.filters,4*this.filters]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",i,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){var o;if(this.unitForgetBias){var s=this.biasInitializer,u=this.filters;o=new((t=function(e){function t(){return e.apply(this,arguments)||this}return Nv(t,e),t.prototype.apply=function(e,t){return KD([s.apply([u]),yC([u]),s.apply([2*u])])},t}(oO)).className="CustomInit",t)}else o=this.biasInitializer;this.bias=this.addWeight("bias",[4*this.filters],null,o,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0},n.call=function(e,t){var n=this;return qI((function(){if(3!==e.length)throw new jF("ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got "+e.length+".");var r=t.training||!1,a=e[0],i=e[1],o=e[2];0<n.dropout&&n.dropout<1&&null==n.dropoutMask&&(n.dropoutMask=Uz({ones:function(){return RC(a)},rate:n.dropout,training:r,count:4}));var s=n.dropoutMask,u=function(e,t,n){return t&&t[n]?tS(t[n],e):e},l=u(a,s,0),c=u(a,s,1),p=u(a,s,2),h=u(a,s,3);0<n.recurrentDropout&&n.recurrentDropout<1&&null==n.recurrentDropoutMask&&(n.recurrentDropoutMask=Uz({ones:function(){return RC(i)},rate:n.recurrentDropout,training:r,count:4}));var f=n.recurrentDropoutMask,d=u(i,f,0),m=u(i,f,1),v=u(i,f,2),g=u(i,f,3),y=AE(n.kernel.read(),4,3),b=y[0],x=y[1],w=y[2],k=y[3],N=n.useBias?AE(n.bias.read(),4):[null,null,null,null],I=N[0],S=N[1],T=N[2],C=N[3];l=n.inputConv(l,b,I,n.padding),c=n.inputConv(c,x,S,n.padding),p=n.inputConv(p,w,T,n.padding),h=n.inputConv(h,k,C,n.padding);var E=AE(n.recurrentKernel.read(),4,3),R=E[0],A=E[1],_=E[2],F=E[3];d=n.recurrentConv(d,R),m=n.recurrentConv(m,A),v=n.recurrentConv(v,_),g=n.recurrentConv(g,F);var D=n.recurrentActivation.apply(QI(l,d)),O=n.recurrentActivation.apply(QI(c,m)),M=QI(tS(O,o),tS(D,n.activation.apply(QI(p,v)))),L=tS(n.recurrentActivation.apply(QI(h,g)),n.activation.apply(M));return[L,L,M]}))},n.getConfig=function(){var t=e.prototype.getConfig.call(this),n=(t.units,Gz(t,["units"])),r={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign({},n,r)},n.inputConv=function(e,t,n,r){var a=JS(e,t,this.strides,r||"valid","channelsFirst"===this.dataFormat?"NCHW":"NHWC",this.dilationRate);return n?tO(a,n,this.dataFormat):a},n.recurrentConv=function(e,t){return JS(e,t,1,"same","channelsFirst"===this.dataFormat?"NCHW":"NHWC")},t}(Bz);Hz.className="ConvLSTM2DCell",MI(Hz);var qz=function(e){function t(t){var n=new Hz(t);return e.call(this,Object.assign({},t,{cell:n}))||this}return Nv(t,e),t.fromConfig=function(e,t){return new e(t)},t}(jz);qz.className="ConvLSTM2D",MI(qz);var Kz=function(e){function t(t){var n;return(n=e.call(this,t)||this).rate=Math.max(Math.min(t.rate,1),0),n.noiseShape=t.noiseShape,n.seed=t.seed,n.supportsMasking=!0,n}Nv(t,e);var n=t.prototype;return n.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},n.call=function(e,t){var n=this;return qI((function(){n.invokeCallHook(e,t);var r=DO(e);if(0<n.rate&&n.rate<1){var a=null!=t.training&&t.training,i=n.getNoiseShape(r);return rO((function(){return nO(r,n.rate,i,n.seed)}),(function(){return r}),a)}return e}))},n.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},n.dispose=function(){return e.prototype.dispose.call(this)},t}(HO);Kz.className="Dropout",MI(Kz);var Xz=function(e){function t(t){var n;return(n=e.call(this,t)||this).inputSpec=[{ndim:3}],n}return Nv(t,e),t.prototype.getNoiseShape=function(e){var t=e.shape;return[t[0],1,t[2]]},t}(Kz);Xz.className="SpatialDropout1D",MI(Xz);var Yz=function(e){function t(t){var n;if((n=e.call(this,t)||this).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,lD(n.units,"units"),n.activation=ZL(t.activation),null!=t.useBias&&(n.useBias=t.useBias),n.kernelInitializer=SO(t.kernelInitializer||n.DEFAULT_KERNEL_INITIALIZER),n.biasInitializer=SO(t.biasInitializer||n.DEFAULT_BIAS_INITIALIZER),n.kernelConstraint=wD(t.kernelConstraint),n.biasConstraint=wD(t.biasConstraint),n.kernelRegularizer=az(t.kernelRegularizer),n.biasRegularizer=az(t.biasRegularizer),n.activityRegularizer=az(t.activityRegularizer),n.supportsMasking=!0,n.inputSpec=[{minNDim:2}],n}Nv(t,e);var n=t.prototype;return n.build=function(e){var t,n=(e=OO(e))[e.length-1];null==this.kernel&&(this.kernel=this.addWeight("kernel",[n,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:(t={},t[-1]=n,t)}],this.built=!0},n.computeOutputShape=function(e){var t=(e=OO(e)).slice();return t[t.length-1]=this.units,t},n.call=function(e,t){var n=this;return qI((function(){n.invokeCallHook(e,t);var r,a=DO(e),i=pD(n.activation.getClassName());return null!=i?r=ZD(a,n.kernel.read(),i,n.bias?n.bias.read():null):(r=ZD(a,n.kernel.read()),null!=n.bias&&(r=tO(r,n.bias.read())),null!=n.activation&&(r=n.activation.apply(r))),r}))},n.getConfig=function(){var t={units:this.units,activation:YL(this.activation),useBias:this.useBias,kernelInitializer:IO(this.kernelInitializer),biasInitializer:IO(this.biasInitializer),kernelRegularizer:nz(this.kernelRegularizer),biasRegularizer:nz(this.biasRegularizer),activityRegularizer:nz(this.activityRegularizer),kernelConstraint:bD(this.kernelConstraint),biasConstraint:bD(this.biasConstraint)},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(HO);Yz.className="Dense",MI(Yz);var Jz=function(e){function t(t){var n;return t=t||{},(n=e.call(this,t)||this).inputSpec=[{minNDim:3}],n.dataFormat=t.dataFormat,n}Nv(t,e);var n=t.prototype;return n.computeOutputShape=function(e){for(var t,n=Fv((e=OO(e)).slice(1));!(t=n()).done;){if(null==t.value)throw new jF('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],PD(e,1)]},n.call=function(e,t){var n=this;return qI((function(){n.invokeCallHook(e,t);var r=DO(e);if("channelsFirst"===n.dataFormat&&r.rank>1){for(var a=[0],i=2;i<r.rank;++i)a.push(i);a.push(1),r=eI(r,a)}return function(e){if(e.rank<=1)throw new jF("batchFlatten requires a minimum rank of 2. 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e=DO(e),t=e,r=n.n,qI((function(){if(2!==t.shape.length)throw new jF("repeat() expects a rank-2 tensor, but received a rank-"+t.shape.length+" tensor.");return YD(GD(t,1),[1,r,1])}));var t,r}))},n.getConfig=function(){var t={n:this.n},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(HO);Qz.className="RepeatVector",MI(Qz);var $z=function(e){function t(t){var n;(n=e.call(this,t)||this).targetShape=t.targetShape;for(var r=0;r<n.targetShape.length;++r)n.isUnknown(n.targetShape[r])&&(n.targetShape[r]=null);return n}Nv(t,e);var n=t.prototype;return n.isUnknown=function(e){return e<0||null==e},n.fixUnknownDimension=function(e,t){for(var n="Total size of new array must be unchanged.",r=t.slice(),a=1,i=null,o=0;o<r.length;++o){var s=r[o];if(this.isUnknown(s)){if(null!==i)throw new jF("Can only specifiy one unknown dimension.");i=o}else a*=s}var u=PD(e);if(null!==i){if(0===a||u%a!=0)throw new jF(n);r[i]=u/a}else if(u!==a)throw new jF(n);return r},n.computeOutputShape=function(e){for(var t=!1,n=0;n<e.length;++n)if(this.isUnknown(e[n])){t=!0;break}return t?e.slice(0,1).concat(this.targetShape):e.slice(0,1).concat(this.fixUnknownDimension(e.slice(1),this.targetShape))},n.call=function(e,t){var n=this;return qI((function(){n.invokeCallHook(e,t);var r=DO(e),a=r.shape,i=a.slice(0,1).concat(n.fixUnknownDimension(a.slice(1),n.targetShape));return ES(r,i)}))},n.getConfig=function(){var t={targetShape:this.targetShape},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(HO);$z.className="Reshape",MI($z);var eP=function(e){function t(t){var n;if(n=e.call(this,t)||this,null==t.dims)throw new Error("Required configuration field `dims` is missing during Permute constructor call.");if(!Array.isArray(t.dims))throw new Error("Permute constructor requires `dims` to be an Array, but received "+t.dims+" instead.");var r=VD(1,t.dims.length+1);if(!qv(t.dims.slice().sort(),r))throw new Error("Invalid permutation `dims`: "+JSON.stringify(t.dims)+" `dims` must contain consecutive integers starting from 1.");return n.dims=t.dims,n.dimsIncludingBatch=[0].concat(n.dims),n.inputSpec=[new WO({ndim:n.dims.length+1})],n}Nv(t,e);var n=t.prototype;return n.computeOutputShape=function(e){var t=(e=OO(e)).slice();return this.dims.forEach((function(n,r){t[r+1]=e[n]})),t},n.call=function(e,t){return eI(DO(e),this.dimsIncludingBatch)},n.getConfig=function(){var t={dims:this.dims},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(HO);eP.className="Permute",MI(eP);var tP=function(e){function t(t){var n;return(n=e.call(this,null==t?{}:t)||this).supportsMasking=!0,n.maskValue=null!=t?null==t.maskValue?0:t.maskValue:0,n}Nv(t,e);var n=t.prototype;return n.computeOutputShape=function(e){return e},n.getConfig=function(){var t=e.prototype.getConfig.call(this),n={maskValue:this.maskValue};return Object.assign(n,t),n},n.computeMask=function(e,t){var n=DO(e);return sS(EC(n,this.maskValue),-1)},n.call=function(e,t){var n=this;return qI((function(){n.invokeCallHook(e,t);var r=DO(e),a=sS(EC(r,n.maskValue),-1,!0);return tS(r,_N(a,r.dtype))}))},t}(HO);tP.className="Masking",MI(tP);var nP=function(e){function t(t){var n;if((n=e.call(this,t)||this).embeddings=null,n.DEFAULT_EMBEDDINGS_INITIALIZER="randomUniform",null==t.batchInputShape&&null==t.inputShape){var r=null;null!=t.batchSize&&(r=t.batchSize),null==t.inputLength?n.batchInputShape=[r,null]:n.batchInputShape=[r].concat(ZF(t.inputLength))}return n.inputDim=t.inputDim,lD(n.inputDim,"inputDim"),n.outputDim=t.outputDim,lD(n.outputDim,"outputDim"),n.embeddingsInitializer=SO(t.embeddingsInitializer||n.DEFAULT_EMBEDDINGS_INITIALIZER),n.embeddingsRegularizer=az(t.embeddingsRegularizer),n.activityRegularizer=az(t.activityRegularizer),n.embeddingsConstraint=wD(t.embeddingsConstraint),n.maskZero=t.maskZero,n.supportsMasking=t.maskZero,n.inputLength=t.inputLength,n}Nv(t,e);var n=t.prototype;return n.build=function(e){this.embeddings=this.addWeight("embeddings",[this.inputDim,this.outputDim],this.dtype,this.embeddingsInitializer,this.embeddingsRegularizer,!0,this.embeddingsConstraint),this.built=!0},n.warnOnIncompatibleInputShape=function(e){},n.computeMask=function(e,t){var n=this;return qI((function(){return n.maskZero?(e=DO(e),EC(e,vT(e))):null}))},n.computeOutputShape=function(e){if(e=OO(e),null==this.inputLength)return[].concat(e,[this.outputDim]);var t=ZF(this.inputLength);if(t.length!==e.length-1)throw new jF('"inputLength" is '+this.inputLength+", but received input shape has shape "+e);for(var n=0,r=0;r<t.length;++r){var a=t[r],i=e[r+1];if(null!=a&&null!=i&&a!==i)throw new jF('"inputLength" is '+this.inputLength+", but received input shape has shape "+e);null==a&&(t[n]=i),n++}return[e[0]].concat(t,[this.outputDim])},n.call=function(e,t){var n=this;return qI((function(){n.invokeCallHook(e,t);var r=DO(e);"int32"!==r.dtype&&(r=UD(r,"int32"));var a=QD(n.embeddings.read(),ES(r,[r.size]));return ES(a,OO(n.computeOutputShape(r.shape)))}))},n.getConfig=function(){var t={inputDim:this.inputDim,outputDim:this.outputDim,embeddingsInitializer:IO(this.embeddingsInitializer),embeddingsRegularizer:nz(this.embeddingsRegularizer),activityRegularizer:nz(this.activityRegularizer),embeddingsConstraint:bD(this.embeddingsConstraint),maskZero:this.maskZero,inputLength:this.inputLength},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(HO);nP.className="Embedding",MI(nP);var rP=function(e){function t(t){var n;return(n=e.call(this,t||{})||this).supportsMasking=!0,n}Nv(t,e);var n=t.prototype;return n.mergeFunction=function(e){throw new HF},n.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 a=e[e.length-t.length+r],i=t[r];if(null==a||null==i||a<0||i<0)n.push(null);else if(1===a)n.push(i);else if(1===i)n.push(a);else{if(a!==i)throw new jF("Operands could not be broadcast together with shapes "+JSON.stringify(e)+" "+JSON.stringify(t));n.push(a)}}return n},n.build=function(e){if(Array.isArray(e)&&!Array.isArray(e[0])&&(e=[OO(e)]),(e=e).length<2)throw new jF("A merge layer should be called on an Array of at least 2 inputs. Got "+e.length+" input(s).");for(var t,n=[],r=Fv(e);!(t=r()).done;){var a=t.value;null!=a&&null!==a[0]&&n.push(a[0])}if((n=iD(n)).length>1)throw new jF("Can not merge tensors with different batch sizes. Got tensors with shapes: "+JSON.stringify(e)+".");for(var i=null==e[0]?null:e[0].slice(1),o=1;o<e.length;++o){var s=null==e[o]?null:e[o].slice(1);i=this.computeElementwiseOpOutputShape(i,s)}var u=e.map((function(e){return e.length}));-1===e.indexOf(null)&&1===iD(u).length?this.reshapeRequired=!1:this.reshapeRequired=!0},n.call=function(e,t){var n=this;return qI((function(){if(e=e,n.reshapeRequired){var t=[],r=e.map((function(e){return e.rank}));if(-1===r.indexOf(null)){for(var a,i=WD(r),o=Fv(e);!(a=o()).done;){for(var s=a.value,u=s.rank,l=0;l<i-u;++l)s=GD(s,1);t.push(s)}return n.mergeFunction(t)}for(var c,p=!1,h=Fv(e);!(c=h()).done;){var f=c.value,d=f.rank;if(null==d){var m=f.shape,v=m[0],g=m.slice(1).concat([v]),y=ES(f,[v].concat(PD(m.slice(1))));y=eI(y,[1,0]),y=ES(y,g),t.push(y),p=!0}else if(d>1){var b=VD(1,d).concat([0]);t.push(eI(f,b)),p=!0}else t.push(f)}var x=n.mergeFunction(t),w=x.rank;if(p)if(null==w){var k=x.shape,N=k[k.length-1],I=[N].concat(k.slice(0,k.length-1));x=ES(eI(ES(x,[-1,N]),[1,0]),I)}else if(w>1){var S=[w-1].concat(VD(0,w-1));x=eI(x,S)}return x}return n.mergeFunction(e)}))},n.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,i=[],o=Fv(e);!(a=o()).done;){var s=a.value;null!=s&&null!==s[0]&&i.push(s[0])}return t=1===(i=iD(i)).length?i.concat(t):[null].concat(t)},n.computeMask=function(e,t){return qI((function(){if(null==t)return null;if(!Array.isArray(t))throw new jF("`mask` should be an Array");if(!Array.isArray(e))throw new jF("`inputs` should be an Array");if(t.length!==e.length)throw new jF("The Array 'inputs' and 'mask' are expected to have the same length, but have different lengths ("+e.length+" vs "+t.length+")");if(t.every((function(e){return null==e})))return null;for(var n=(t=t.map((function(e){return null==e?e:NT(e,0)})))[0],r=1;r<t.length-1;++r)n=uC(n,t[r]);return n}))},t}(HO),aP=function(e){function t(t){return e.call(this,t)||this}return Nv(t,e),t.prototype.mergeFunction=function(e){return qI((function(){for(var t=e[0].clone(),n=1;n<e.length;++n)t=QI(t,e[n]);return t}))},t}(rP);aP.className="Add",MI(aP);var iP=function(e){function t(t){return e.call(this,t)||this}return Nv(t,e),t.prototype.mergeFunction=function(e){return qI((function(){for(var t=e[0].clone(),n=1;n<e.length;++n)t=tS(t,e[n]);return t}))},t}(rP);iP.className="Multiply",MI(iP);var oP=function(e){function t(t){return e.call(this,t)||this}return Nv(t,e),t.prototype.mergeFunction=function(e){return qI((function(){for(var t=e[0].clone(),n=1;n<e.length;++n)t=QI(t,e[n]);return tS(1/e.length,t)}))},t}(rP);oP.className="Average",MI(oP);var sP=function(e){function t(t){return e.call(this,t)||this}return Nv(t,e),t.prototype.mergeFunction=function(e){return qI((function(){for(var t=e[0],n=1;n<e.length;++n)t=mC(t,e[n]);return t}))},t}(rP);sP.className="Maximum",MI(sP);var uP=function(e){function t(t){return e.call(this,t)||this}return Nv(t,e),t.prototype.mergeFunction=function(e){return qI((function(){for(var t=e[0],n=1;n<e.length;++n)t=wC(t,e[n]);return t}))},t}(rP);uP.className="Minimum",MI(uP);var lP=function(e){function t(t){var n;return(n=e.call(this,t)||this).DEFAULT_AXIS=-1,null==t&&(t={}),n.axis=null==t.axis?n.DEFAULT_AXIS:t.axis,n.supportsMasking=!0,n.reshapeRequired=!1,n}Nv(t,e);var n=t.prototype;return n.build=function(e){if(!Array.isArray(e)||!Array.isArray(e[0])||1===e.length)throw new jF("A `Concatenate` layer should be called on a list of at least 2 inputs");for(var t,n=!0,r=Fv(e=e);!(t=r()).done;){if(null!=t.value){n=!1;break}}if(!n){for(var a=[],i=0;i<e.length;++i){var o=e[i].slice();o.splice(this.axis,1);for(var s,u=!1,l=Fv(a);!(s=l()).done;){if(qv(s.value,o)){u=!0;break}}u||a.push(o)}if(a.length>1)throw new jF("A `Concatenate` layer requires inputs with matching shapes except for the concat axis. Got input shapes: "+JSON.stringify(e))}},n.mergeFunction=function(e){var t=this;return qI((function(){return KD(e,t.axis)}))},n.computeOutputShape=function(e){if(!Array.isArray(e)||!Array.isArray(e[0]))throw new jF("A `Concatenate` layer should be called on a list of inputs.");for(var t,n=e,r=n[0].slice(),a=this.axis<0?r.length+this.axis:this.axis,i=Fv(n.slice(1));!(t=i()).done;){var o=t.value;if(null==r[a]||null==o[a]){r[a]=null;break}r[a]+=o[a]}return r},n.computeMask=function(e,t){var n=this;if(null==t)return null;if(!Array.isArray(t))throw new jF("`mask` should be an array for Concatenate");if(!Array.isArray(e))throw new jF("`inputs` should be an array for Concatenate");if(t.length!==e.length)throw new jF("Mismatch in the length of mask ("+t.length+") and the legnth of inputs ("+e.length+")");return qI((function(){var r=!0;if(t.forEach((function(e){null==e||(r=!1)})),r)return null;for(var a=[],i=0;i<e.length;++i)null==t[i]?a.push(_N(RC(e[i]),"bool")):t[i].rank<e[i].rank?a.push(NT(t[i],-1)):a.push(t[i]);var o=_S(a,n.axis);return oS(o,-1,!1)}))},n.getConfig=function(){var t={axis:this.axis},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(rP);function cP(e,t){for(;e<0;)e+=t;return e}lP.className="Concatenate",MI(lP);var pP=function(e){function t(t){var n;return(n=e.call(this,t)||this).axes=t.axes,n.normalize=null!=t.normalize&&t.normalize,n.supportsMasking=!0,n.reshapeRequired=!1,n}Nv(t,e);var n=t.prototype;return n.build=function(e){Vv(Array.isArray(e)&&2===e.length&&Array.isArray(e[0])&&Array.isArray(e[1]),(function(){return"A `Dot` layer should be called on a list of exactly 2 inputs."}));var t=e[0],n=e[1];if(t.length>3||n.length>3)throw new HF("Dot layer does not support tensors of 4D or higher rank yet.");var r=this.interpretAxes(t,n);if(t[r[0]]!==n[r[1]])throw new jF("Dimension incompatibility: "+t[r[0]]+" !== "+n[r[1]])},n.mergeFunction=function(e){if(2!==e.length)throw new jF("A `Dot` layer must be called on exactly 2 inputs, but received "+e.length+" input(s).");var t,n=e[0],r=e[1];return t=Array.isArray(this.axes)?this.axes.map((function(t,n){return cP(t,e[n].shape.length)})):[cP(this.axes,n.shape.length),cP(this.axes,r.shape.length)],this.normalize&&(n=uM(n,t[0]),r=uM(r,t[1])),function(e,t,n){if(e.shape.length>3||t.shape.length>3)throw new HF("batchDot is not implemented for tensors of 4D or higher rank yet");if(Vv(e.shape.length>=2,(function(){return"batchDot requires the rank of x to be >= 2, but got "+e.shape.length})),Vv(e.shape.length>=2,(function(){return"batchDot requires the rank of y to be >= 2, but got "+t.shape.length})),"number"==typeof n&&(n=[n,n]),"complex64"===e.dtype||"complex64"===t.dtype)throw new HF("batchDot is not implemented for complex64-type Tensors yet.");var r=e.shape.length,a=t.shape.length;null==n&&(n=[r-1,a-2]);var i=n;return qI((function(){var n,o;if(r>a){n=r-a;for(var s=[],u=0;u<n;++u)s.push(1);t=ES(t,t.shape.concat(s))}else if(a>r){n=a-r;for(var l=[],c=0;c<n;++c)l.push(1);e=ES(e,e.shape.concat(l))}else n=0;if(2===e.shape.length&&2===t.shape.length)o=i[0]===i[1]?ZT(tS(e,t),i[0]):ZT(tS(eI(e,[1,0]),t),i[1]);else{var p=i[0]!==e.shape.length-1,h=i[1]===t.shape.length-1;o=QN(e,t,p,h)}if(n>0){for(var f,d=[],m=f=r>a?r+a-3:r-1;m<f+n;++m)d.push(m);o=OE(o,d)}return 1===o.shape.length&&(o=NT(o,1)),o}))}(n,r,t)},n.interpretAxes=function(e,t){return Array.isArray(this.axes)?this.axes:[cP(this.axes,e.length),cP(this.axes,t.length)]},n.computeOutputShape=function(e){Vv(Array.isArray(e)&&2===e.length&&Array.isArray(e[0])&&Array.isArray(e[1]),(function(){return"A `Dot` layer should be called on a list of exactly 2 inputs."}));var t=e[0].slice(),n=e[1].slice();if(t.length>3||n.length>3)throw new HF("Dot layer does not support tensors of 4D or higher rank yet.");var r=this.interpretAxes(t,n);t.splice(r[0],1),n.splice(r[1],1),n.splice(0,1);var a=t.concat(n);return 1===a.length&&a.push(1),a},n.computeMask=function(e,t){return null},n.getConfig=function(){var t={axes:this.axes,normalize:this.normalize},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(rP);pP.className="Dot",MI(pP);var hP=function(e){function t(t){var n;return(n=e.call(this,t)||this).supportsMasking=!0,n.stddev=t.stddev,n}Nv(t,e);var n=t.prototype;return n.computeOutputShape=function(e){return e},n.getConfig=function(){var t=e.prototype.getConfig.call(this),n={stddev:this.stddev};return Object.assign(n,t),n},n.call=function(e,t){var n=this;return qI((function(){n.invokeCallHook(e,t);var r=DO(e);return rO((function(){return QI(JD(r.shape,0,n.stddev),r)}),(function(){return r}),t.training||!1)}))},t}(HO);hP.className="GaussianNoise",MI(hP);var fP=function(e){function t(t){var n;return(n=e.call(this,t)||this).supportsMasking=!0,n.rate=t.rate,n}Nv(t,e);var n=t.prototype;return n.computeOutputShape=function(e){return e},n.getConfig=function(){var t=e.prototype.getConfig.call(this),n={rate:this.rate};return Object.assign(n,t),n},n.call=function(e,t){var n=this;return qI((function(){n.invokeCallHook(e,t);var r=DO(e);if(n.rate>0&&n.rate<1){return rO((function(){var e=Math.sqrt(n.rate/(1-n.rate));return tS(r,JD(r.shape,1,e))}),(function(){return r}),t.training||!1)}return r}))},t}(HO);fP.className="GaussianDropout",MI(fP);var dP=function(e){function t(t){var n;return(n=e.call(this,t)||this).supportsMasking=!0,n.rate=t.rate,n.noiseShape=t.noiseShape,n}Nv(t,e);var n=t.prototype;return n._getNoiseShape=function(e){return this.noiseShape||DO(e).shape},n.computeOutputShape=function(e){return e},n.getConfig=function(){var t=e.prototype.getConfig.call(this),n={rate:this.rate};return Object.assign(n,t),n},n.call=function(e,t){var n=this;return qI((function(){if(n.rate<1&&n.rate>0){var r=n._getNoiseShape(e);return rO((function(){var t=DO(e),a=-1.7580993408473766,i=_T(tE(r),n.rate);i=UD(i,"float32");var o=Math.pow((1-n.rate)*(1+n.rate*Math.pow(a,2)),-.5),s=-o*a*n.rate,u=QI(tS(t,i),tS(QI(i,-1),a));return QI(tS(u,o),s)}),(function(){return DO(e)}),t.training||!1)}return e}))},t}(HO);function mP(e,t,n,r,a,i){var o;if(void 0===i&&(i=.001),2===e.rank)o=PS(e,t,n,r,a,i);else if(3===e.rank)o=BS(e,t,n,r,a,i);else{if(4!==e.rank)throw new HF("batchNormalization is not implemented for array of rank "+e.rank+" yet");o=WS(e,t,n,r,a,i)}return o}function vP(e,t,n,r,a){return void 0===a&&(a=.001),qv(r.slice().sort(),VD(0,e.rank-1))?function(e,t,n,r,a){return void 0===a&&(a=.001),qI((function(){var i=SC(e,r),o=i.mean,s=i.variance;return[mP(e,o,s,n,t,a),o,s]}))}(e,t,n,r,a):function(e,t,n,r,a){return void 0===a&&(a=.001),qI((function(){for(var i,o=SC(e,r),s=o.mean,u=o.variance,l=[],c=Fv(VD(0,e.rank));!(i=c()).done;){var p=i.value;-1!==r.indexOf(p)?l.push(1):l.push(e.shape[p])}var h=ES(s,l),f=ES(u,l),d=null==t?null:ES(t,l),m=null==n?null:ES(n,l);return[mP(e,h,f,m,d,a),s,u]}))}(e,t,n,r,a)}dP.className="AlphaDropout",MI(dP);var gP=function(e){function t(t){var n;return null==t&&(t={}),(n=e.call(this,t)||this).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=SO(t.betaInitializer||"zeros"),n.gammaInitializer=SO(t.gammaInitializer||"ones"),n.movingMeanInitializer=SO(t.movingMeanInitializer||"zeros"),n.movingVarianceInitializer=SO(t.movingVarianceInitializer||"ones"),n.betaConstraint=wD(t.betaConstraint),n.gammaConstraint=wD(t.gammaConstraint),n.betaRegularizer=az(t.betaRegularizer),n.gammaRegularizer=az(t.gammaRegularizer),n}Nv(t,e);var n=t.prototype;return n.build=function(e){var t;e=OO(e);var n=this.axis>=0?this.axis:this.axis+e.length,r=e[n];if(null==r)throw new jF("Axis "+n+" of input tensor should have a defined dimension but the layer received an input with shape "+JSON.stringify(e)+".");this.inputSpec=[new WO({ndim:e.length,axes:(t={},t[n]=r,t)})];var a=[r];this.scale&&(this.gamma=this.addWeight("gamma",a,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",a,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",a,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",a,null,this.movingVarianceInitializer,null,!1),this.built=!0},n.call=function(e,t){var n=this;return qI((function(){var r=null!=t.training&&t.training,a=DO(e),i=a.shape,o=i.length,s=VD(0,o),u=n.axis>=0?n.axis:n.axis+o;s.splice(u,1);var l=KF(1,o);l[u]=i[u];var c=s.slice();c.sort();var p=!qv(c,VD(0,o).slice(0,o-1));if(!r)return function(){if(p){var e=ES(n.movingMean.read(),l),t=ES(n.movingVariance.read(),l),r=n.center?ES(n.beta.read(),l):null,i=n.scale?ES(n.gamma.read(),l):null;return mP(a,e,t,r,i,n.epsilon)}return mP(a,n.movingMean.read(),n.movingVariance.read(),null==n.beta?null:n.beta.read(),null==n.gamma?null:n.gamma.read(),n.epsilon)}();var h=vP(a,n.gamma.read(),n.beta.read(),s,n.epsilon),f=h[0],d=h[1],m=h[2],v=function(e,t,n){qI((function(){var r=1-n,a=e.read(),i=tS(JT(a,t),r);e.write(JT(a,i))}))};return v(n.movingMean,d,n.momentum),v(n.movingVariance,m,n.momentum),f}))},n.getConfig=function(){var t={axis:this.axis,momentum:this.momentum,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:IO(this.betaInitializer),gammaInitializer:IO(this.gammaInitializer),movingMeanInitializer:IO(this.movingMeanInitializer),movingVarianceInitializer:IO(this.movingVarianceInitializer),betaRegularizer:nz(this.betaRegularizer),gammaRegularizer:nz(this.gammaRegularizer),betaConstraint:bD(this.betaConstraint),gammaConstraint:bD(this.gammaConstraint)},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(HO);gP.className="BatchNormalization",MI(gP);var yP=function(e){function t(t){var n;if(null==t&&(t={}),(n=e.call(this,t)||this).axis=null==t.axis?-1:t.axis,"number"==typeof n.axis){if(!Number.isInteger(n.axis))throw new Error("Expected axis to be an integer, but received "+n.axis)}else{if(!Array.isArray(n.axis))throw new Error("Expected axis to be an integer or an array of integers, but received "+JSON.stringify(n.axis));for(var r,a=Fv(n.axis);!(r=a()).done;){var i=r.value;if(!Number.isInteger(i))throw new Error("Expected axis to be an array of integers, but received "+JSON.stringify(n.axis))}}return n.epsilon=null==t.epsilon?.001:t.epsilon,n.center=null==t.center||t.center,n.scale=null==t.scale||t.scale,n.betaInitializer=SO(t.betaInitializer||"zeros"),n.gammaInitializer=SO(t.gammaInitializer||"ones"),n.betaRegularizer=az(t.betaRegularizer),n.gammaRegularizer=az(t.gammaRegularizer),n.supportsMasking=!0,n}Nv(t,e);var n=t.prototype;return n.build=function(e){var t=(e=OO(e)).length;"number"==typeof this.axis&&(this.axis=[this.axis]);for(var n=0;n<this.axis.length;++n)this.axis[n]<0&&(this.axis[n]+=t);for(var r,a=Fv(this.axis);!(r=a()).done;){var i=r.value;if(i<0||i>=t)throw new Error("Invalid axis: "+i)}if(this.axis.length!==iD(this.axis).length)throw new Error("Found duplicate axes in: "+this.axis);var o=this.axis.map((function(t){return e[t]}));this.scale?this.gamma=this.addWeight("gamma",o,"float32",this.gammaInitializer,this.gammaRegularizer,true):this.gamma=null,this.center?this.beta=this.addWeight("beta",o,"float32",this.betaInitializer,this.betaRegularizer,true):this.beta=null,this.built=!0},n.call=function(e,t){var n=this,r=DO(e),a=r.shape,i=a.length;return qI((function(){for(var e,t=SC(r,n.axis,!0),o=t.mean,s=t.variance,u=KF(1,i),l=Fv(n.axis);!(e=l()).done;){var c=e.value;u[c]=a[c]}for(var p=function(e){return null!=e&&e.shape.length!==i&&n.axis!==[i-1]?ES(e,u):e},h=p(n.gamma.read()),f=p(n.beta.read()),d=[],m=[],v=0;v<i;++v)-1!==n.axis.indexOf(v)?(d.push(a[v]),m.push(1)):(d.push(1),m.push(a[v]));return o=ST(o,d),s=ST(s,d),h=ST(h,m),f=ST(f,m),mP(r,o,s,f,h,n.epsilon)}))},n.getConfig=function(){var t={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:IO(this.betaInitializer),gammaInitializer:IO(this.gammaInitializer),betaRegularizer:nz(this.betaRegularizer),gammaRegularizer:nz(this.gammaRegularizer)},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(HO);yP.className="LayerNormalization",MI(yP);var bP=function(e){function t(t){var n;if(null==t&&(t={}),(n=e.call(this,t)||this).dataFormat=null==t.dataFormat?"channelsLast":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 jF("ZeroPadding2D expects padding to be a length-2 array, but received a length-"+t.padding.length+" array.");var r,a;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 jF("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 jF("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 WO({ndim:4})],n}Nv(t,e);var n=t.prototype;return n.computeOutputShape=function(e){var t,n;return e=OO(e),"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]])},n.call=function(e,t){var n=this;return qI((function(){return t=DO(e),r=n.padding,a=n.dataFormat,qI((function(){if(4!==t.rank)throw new jF("temporalPadding expects input tensor to be 4-D, but received a "+t.rank+"-D tensor.");if(null==r&&(r=[[1,1],[1,1]]),2!==r.length||2!==r[0].length||2!==r[1].length)throw new jF("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(null==a&&(a="channelsLast"),"channelsLast"!==a&&"channelsFirst"!==a)throw new jF("Unknown data format: "+a+". Supported data formats are 'channelsLast' and 'channelsFirst.");var e;return e="channelsFirst"===a?[[0,0],[0,0],r[0],r[1]]:[[0,0],r[0],r[1],[0,0]],_C(t,e)}));var t,r,a}))},n.getConfig=function(){var t={padding:this.padding,dataFormat:this.dataFormat},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(HO);function xP(e,t,n,r,a,i){return qI((function(){var o;RD(a),_D(i),AD(r),null==n&&(n=[1,1]),null==r&&(r="valid"),null==a&&(a="channelsLast"),null==i&&(i="max"),e=dz(e,a);var s="same"===r?"same":"valid";return o="max"===i?hC(e,t,n,s):RS(e,t,n,s),"channelsFirst"===a&&(o=eI(o,[0,3,1,2])),o}))}function wP(e,t,n,r,a,i){return qI((function(){var o;RD(a),_D(i),AD(r),null==n&&(n=[1,1,1]),null==r&&(r="valid"),null==a&&(a="channelsLast"),null==i&&(i="max"),e=mz(e,a);var s="same"===r?"same":"valid";return o="max"===i?fC(e,t,n,s):AS(e,t,n,s),"channelsFirst"===a&&(o=eI(o,[0,4,1,2,3])),o}))}bP.className="ZeroPadding2D",MI(bP);var kP=function(e){function t(t){var n;if(null==t.poolSize&&(t.poolSize=2),n=e.call(this,t)||this,"number"==typeof t.poolSize)n.poolSize=[t.poolSize];else{if(!Array.isArray(t.poolSize)||1!==t.poolSize.length||"number"!=typeof t.poolSize[0])throw new jF("poolSize for 1D convolutional layer must be a number or an Array of a single number, but received "+JSON.stringify(t.poolSize));n.poolSize=t.poolSize}if(lD(n.poolSize,"poolSize"),null==t.strides)n.strides=n.poolSize;else if("number"==typeof t.strides)n.strides=[t.strides];else{if(!Array.isArray(t.strides)||1!==t.strides.length||"number"!=typeof t.strides[0])throw new jF("strides for 1D convolutional layer must be a number or an Array of a single number, but received "+JSON.stringify(t.strides));n.strides=t.strides}return lD(n.strides,"strides"),n.padding=null==t.padding?"valid":t.padding,AD(n.padding),n.inputSpec=[new WO({ndim:3})],n}Nv(t,e);var n=t.prototype;return n.computeOutputShape=function(e){var t=hz((e=OO(e))[1],this.poolSize[0],this.padding,this.strides[0]);return[e[0],t,e[2]]},n.call=function(e,t){var n=this;return qI((function(){n.invokeCallHook(e,t),e=GD(DO(e),2);var r=n.poolingFunction(DO(e),[n.poolSize[0],1],[n.strides[0],1],n.padding,"channelsLast");return OE(r,[2])}))},n.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}(HO),NP=function(e){function t(t){return e.call(this,t)||this}return Nv(t,e),t.prototype.poolingFunction=function(e,t,n,r,a){return RD(a),AD(r),xP(e,t,n,r,a,"max")},t}(kP);NP.className="MaxPooling1D",MI(NP);var IP=function(e){function t(t){return e.call(this,t)||this}return Nv(t,e),t.prototype.poolingFunction=function(e,t,n,r,a){return RD(a),AD(r),xP(e,t,n,r,a,"avg")},t}(kP);IP.className="AveragePooling1D",MI(IP);var SP=function(e){function t(t){var n;if(null==t.poolSize&&(t.poolSize=[2,2]),(n=e.call(this,t)||this).poolSize=Array.isArray(t.poolSize)?t.poolSize:[t.poolSize,t.poolSize],null==t.strides)n.strides=n.poolSize;else if(Array.isArray(t.strides)){if(2!==t.strides.length)throw new jF("If the strides property of a 2D pooling layer is an Array, it is expected to have a length of 2, but received length "+t.strides.length+".");n.strides=t.strides}else n.strides=[t.strides,t.strides];return lD(n.poolSize,"poolSize"),lD(n.strides,"strides"),n.padding=null==t.padding?"valid":t.padding,n.dataFormat=null==t.dataFormat?"channelsLast":t.dataFormat,RD(n.dataFormat),AD(n.padding),n.inputSpec=[new WO({ndim:4})],n}Nv(t,e);var n=t.prototype;return n.computeOutputShape=function(e){e=OO(e);var t="channelsFirst"===this.dataFormat?e[2]:e[1],n="channelsFirst"===this.dataFormat?e[3]:e[2];return t=hz(t,this.poolSize[0],this.padding,this.strides[0]),n=hz(n,this.poolSize[1],this.padding,this.strides[1]),"channelsFirst"===this.dataFormat?[e[0],e[1],t,n]:[e[0],t,n,e[3]]},n.call=function(e,t){var n=this;return qI((function(){return n.invokeCallHook(e,t),n.poolingFunction(DO(e),n.poolSize,n.strides,n.padding,n.dataFormat)}))},n.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}(HO),TP=function(e){function t(t){return e.call(this,t)||this}return Nv(t,e),t.prototype.poolingFunction=function(e,t,n,r,a){return RD(a),AD(r),xP(e,t,n,r,a,"max")},t}(SP);TP.className="MaxPooling2D",MI(TP);var CP=function(e){function t(t){return e.call(this,t)||this}return Nv(t,e),t.prototype.poolingFunction=function(e,t,n,r,a){return RD(a),AD(r),xP(e,t,n,r,a,"avg")},t}(SP);CP.className="AveragePooling2D",MI(CP);var EP=function(e){function t(t){var n;if(null==t.poolSize&&(t.poolSize=[2,2,2]),(n=e.call(this,t)||this).poolSize=Array.isArray(t.poolSize)?t.poolSize:[t.poolSize,t.poolSize,t.poolSize],null==t.strides)n.strides=n.poolSize;else if(Array.isArray(t.strides)){if(3!==t.strides.length)throw new jF("If the strides property of a 3D pooling layer is an Array, it is expected to have a length of 3, but received length "+t.strides.length+".");n.strides=t.strides}else n.strides=[t.strides,t.strides,t.strides];return lD(n.poolSize,"poolSize"),lD(n.strides,"strides"),n.padding=null==t.padding?"valid":t.padding,n.dataFormat=null==t.dataFormat?"channelsLast":t.dataFormat,RD(n.dataFormat),AD(n.padding),n.inputSpec=[new WO({ndim:5})],n}Nv(t,e);var n=t.prototype;return n.computeOutputShape=function(e){e=OO(e);var t="channelsFirst"===this.dataFormat?e[2]:e[1],n="channelsFirst"===this.dataFormat?e[3]:e[2],r="channelsFirst"===this.dataFormat?e[4]:e[3];return t=hz(t,this.poolSize[0],this.padding,this.strides[0]),n=hz(n,this.poolSize[1],this.padding,this.strides[1]),r=hz(r,this.poolSize[2],this.padding,this.strides[2]),"channelsFirst"===this.dataFormat?[e[0],e[1],t,n,r]:[e[0],t,n,r,e[4]]},n.call=function(e,t){var n=this;return qI((function(){return n.invokeCallHook(e,t),n.poolingFunction(DO(e),n.poolSize,n.strides,n.padding,n.dataFormat)}))},n.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}(HO),RP=function(e){function t(t){return e.call(this,t)||this}return Nv(t,e),t.prototype.poolingFunction=function(e,t,n,r,a){return RD(a),AD(r),wP(e,t,n,r,a,"max")},t}(EP);RP.className="MaxPooling3D",MI(RP);var AP=function(e){function t(t){return e.call(this,t)||this}return Nv(t,e),t.prototype.poolingFunction=function(e,t,n,r,a){return RD(a),AD(r),wP(e,t,n,r,a,"avg")},t}(EP);AP.className="AveragePooling3D",MI(AP);var _P=function(e){function t(t){var n;return(n=e.call(this,t)||this).inputSpec=[new WO({ndim:3})],n}Nv(t,e);var n=t.prototype;return n.computeOutputShape=function(e){return[e[0],e[2]]},n.call=function(e,t){throw new HF},t}(HO),FP=function(e){function t(t){return e.call(this,t||{})||this}return Nv(t,e),t.prototype.call=function(e,t){return qI((function(){var t=DO(e);return vC(t,1)}))},t}(_P);FP.className="GlobalAveragePooling1D",MI(FP);var DP=function(e){function t(t){return e.call(this,t||{})||this}return Nv(t,e),t.prototype.call=function(e,t){return qI((function(){var t=DO(e);return YT(t,1)}))},t}(_P);DP.className="GlobalMaxPooling1D",MI(DP);var OP=function(e){function t(t){var n;return(n=e.call(this,t)||this).dataFormat=null==t.dataFormat?"channelsLast":t.dataFormat,RD(n.dataFormat),n.inputSpec=[new WO({ndim:4})],n}Nv(t,e);var n=t.prototype;return n.computeOutputShape=function(e){return e=e,"channelsLast"===this.dataFormat?[e[0],e[3]]:[e[0],e[1]]},n.call=function(e,t){throw new HF},n.getConfig=function(){var t={dataFormat:this.dataFormat},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(HO),MP=function(e){function t(){return e.apply(this,arguments)||this}return Nv(t,e),t.prototype.call=function(e,t){var n=this;return qI((function(){var t=DO(e);return"channelsLast"===n.dataFormat?vC(t,[1,2]):vC(t,[2,3])}))},t}(OP);MP.className="GlobalAveragePooling2D",MI(MP);var LP=function(e){function t(){return e.apply(this,arguments)||this}return Nv(t,e),t.prototype.call=function(e,t){var n=this;return qI((function(){var t=DO(e);return"channelsLast"===n.dataFormat?YT(t,[1,2]):YT(t,[2,3])}))},t}(OP);LP.className="GlobalMaxPooling2D",MI(LP);var zP=function(e){function t(t){var n;return(n=e.call(this,t)||this).layer=t.layer,n}Nv(t,e);var n=t.prototype;return n.build=function(e){this.built=!0},n.getWeights=function(){return this.layer.getWeights()},n.setWeights=function(e){this.layer.setWeights(e)},n.getConfig=function(){var t={layer:{className:this.layer.getClassName(),config:this.layer.getConfig()}},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},n.setFastWeightInitDuringBuild=function(t){e.prototype.setFastWeightInitDuringBuild.call(this,t),null!=this.layer&&this.layer.setFastWeightInitDuringBuild(t)},t.fromConfig=function(e,t,n){void 0===n&&(n={});var r=sM(t.layer,n);delete t.layer;var a={layer:r};return Object.assign(a,t),new e(a)},kv(t,[{key:"trainable",get:function(){return null!=this.layer&&this.layer.trainable},set:function(e){null!=this.layer&&(this.layer.trainable=e)}},{key:"trainableWeights",get:function(){return this.layer.trainableWeights}},{key:"nonTrainableWeights",get:function(){return this.layer.nonTrainableWeights}},{key:"updates",get:function(){return this.layer._updates}},{key:"losses",get:function(){return this.layer.losses}}]),t}(HO),PP=function(e){function t(t){var n;return(n=e.call(this,t)||this).supportsMasking=!0,n}Nv(t,e);var n=t.prototype;return 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implemented")}}(e,t,n)}));case"basic_math":return qI((function(){return function(e,t,n){switch(e.op){case"Abs":case"ComplexAbs":return[nS(oB("x",e,t,n))];case"Acos":return[rS(oB("x",e,t,n))];case"Acosh":return[aS(oB("x",e,t,n))];case"Asin":return[cS(oB("x",e,t,n))];case"Asinh":return[pS(oB("x",e,t,n))];case"Atan":return[hS(oB("x",e,t,n))];case"Atan2":return[fS(oB("x",e,t,n),oB("y",e,t,n))];case"Atanh":return[dS(oB("x",e,t,n))];case"Ceil":return[jS(oB("x",e,t,n))];case"Complex":return[Tk(oB("real",e,t,n),oB("imag",e,t,n))];case"Cos":return[rT(oB("x",e,t,n))];case"Cosh":return[aT(oB("x",e,t,n))];case"Elu":return[xT(oB("x",e,t,n))];case"Erf":return[wT(oB("x",e,t,n))];case"Exp":return[kT(oB("x",e,t,n))];case"Expm1":return[IT(oB("x",e,t,n))];case"Floor":return[ET(oB("x",e,t,n))];case"Log":return[VT(oB("x",e,t,n))];case"Log1p":return[UT(oB("x",e,t,n))];case"Imag":return[FT(oB("x",e,t,n))];case"Neg":return[qT(oB("x",e,t,n))];case"Reciprocal":return[aE(oB("x",e,t,n))];case"Real":return[rE(oB("x",e,t,n))];case"Relu":return[iE(oB("x",e,t,n))];case"Round":return[hE(oB("x",e,t,n))];case"Selu":return[mE(oB("x",e,t,n))];case"Sigmoid":return[FS(oB("x",e,t,n))];case"Sin":return[xE(oB("x",e,t,n))];case"Sign":return[bE(oB("x",e,t,n))];case"Sinh":return[wE(oB("x",e,t,n))];case"Softplus":return[KT(oB("x",e,t,n))];case"Sqrt":return[FE(oB("x",e,t,n))];case"Square":return[IC(oB("x",e,t,n))];case"Tanh":return[OS(oB("x",e,t,n))];case"Tan":return[PE(oB("x",e,t,n))];case"ClipByValue":return[HS(oB("x",e,t,n),oB("clipValueMin",e,t,n),oB("clipValueMax",e,t,n))];case"Relu6":return[oE(oB("x",e,t,n))];case"Rsqrt":return[fE(sB(e.inputNames[0],t,n))];case"Prod":return[WC(oB("x",e,t,n),oB("axes",e,t,n))];case"LeakyRelu":return[LT(oB("x",e,t,n),oB("alpha",e,t,n))];case"Prelu":return[BC(oB("x",e,t,n),oB("alpha",e,t,n))];case"IsNan":return[MT(sB(e.inputNames[0],t,n))];default:throw TypeError("Node type "+e.op+" is not implemented")}}(e,t,n)}));case"control":return iW(e,t,n);case"convolution":return qI((function(){return function(e,t,n){switch(e.op){case"Conv1D":var r=oB("stride",e,t,n),a=oB("pad",e,t,n),i=oB("dataFormat",e,t,n).toUpperCase(),o=oB("dilation",e,t,n);return[ZS(oB("x",e,t,n),oB("filter",e,t,n),r,a,i,o)];case"Conv2D":var s=oB("strides",e,t,n),u=pB(e,t,n),l=oB("dataFormat",e,t,n).toUpperCase(),c=oB("dilations",e,t,n);return[JS(oB("x",e,t,n),oB("filter",e,t,n),[s[1],s[2]],u,l,[c[1],c[2]])];case"_FusedConv2D":var p=oW(e,t,n),h=p.stride,f=p.pad,d=p.dataFormat,m=p.dilations,v=p.biasArg,g=p.preluArg,y=p.activationFunc,b=p.leakyreluAlpha;return[gR({x:oB("x",e,t,n),filter:oB("filter",e,t,n),strides:[h[1],h[2]],pad:f,dataFormat:d,dilations:[m[1],m[2]],bias:v,activation:y,preluActivationWeights:g,leakyreluAlpha:b})];case"FusedDepthwiseConv2dNative":var x=oW(e,t,n),w=x.stride,k=x.pad,N=x.dataFormat,I=x.dilations,S=x.biasArg,T=x.preluArg,C=x.activationFunc,E=x.leakyreluAlpha;return[xR({x:oB("x",e,t,n),filter:oB("filter",e,t,n),strides:[w[1],w[2]],pad:k,dataFormat:N,dilations:[I[1],I[2]],bias:S,activation:C,preluActivationWeights:T,leakyreluAlpha:E})];case"Conv2DBackpropInput":case"Conv2dTranspose":var R=oB("outputShape",e,t,n),A=oB("strides",e,t,n),_=pB(e,t,n);return[$S(oB("x",e,t,n),oB("filter",e,t,n),R,[A[1],A[2]],_)];case"DepthwiseConv2dNative":case"DepthwiseConv2d":var F=oB("strides",e,t,n),D=pB(e,t,n),O=oB("dilations",e,t,n),M=oB("dataFormat",e,t,n).toUpperCase();return[uT(oB("input",e,t,n),oB("filter",e,t,n),[F[1],F[2]],D,M,[O[1],O[2]])];case"Conv3D":var L=oB("strides",e,t,n),z=oB("pad",e,t,n),P=oB("dataFormat",e,t,n).toUpperCase(),B=oB("dilations",e,t,n);return[eT(oB("x",e,t,n),oB("filter",e,t,n),[L[1],L[2],L[3]],z,P,[B[1],B[2],B[3]])];case"AvgPool":var W=oB("strides",e,t,n),V=oB("pad",e,t,n),U=oB("kernelSize",e,t,n);return[RS(oB("x",e,t,n),[U[1],U[2]],[W[1],W[2]],V)];case"MaxPool":var G=oB("strides",e,t,n),j=oB("pad",e,t,n),H=oB("kernelSize",e,t,n);return[hC(oB("x",e,t,n),[H[1],H[2]],[G[1],G[2]],j)];case"MaxPoolWithArgmax":var q=oB("strides",e,t,n),K=oB("pad",e,t,n),X=oB("kernelSize",e,t,n),Y=oB("includeBatchInIndex",e,t,n),J=dC(oB("x",e,t,n),[X[1],X[2]],[q[1],q[2]],K,Y);return[J.result,J.indexes];case"AvgPool3D":var Z=oB("strides",e,t,n),Q=oB("pad",e,t,n),$=oB("kernelSize",e,t,n);return[AS(oB("x",e,t,n),[$[1],$[2],$[3]],[Z[1],Z[2],Z[3]],Q)];case"MaxPool3D":var ee=oB("strides",e,t,n),te=oB("pad",e,t,n),ne=oB("kernelSize",e,t,n);return[fC(oB("x",e,t,n),[ne[1],ne[2],ne[3]],[ee[1],ee[2],ee[3]],te)];case"Dilation2D":var re=oB("strides",e,t,n),ae=oB("pad",e,t,n),ie=oB("dilations",e,t,n),oe=re[1],se=re[2],ue=ie[1],le=ie[2];return[cT(oB("x",e,t,n),oB("filter",e,t,n),[oe,se],ae,[ue,le],"NHWC")];default:throw TypeError("Node type "+e.op+" is not implemented")}}(e,t,n)}));case"creation":return qI((function(){return function(e,t,n){switch(e.op){case"Fill":var r=oB("shape",e,t,n),a=oB("dtype",e,t,n);return[CT(r,oB("value",e,t,n),a)];case"LinSpace":return[BT(oB("start",e,t,n),oB("stop",e,t,n),oB("num",e,t,n))];case"Multinomial":var i=oB("logits",e,t,n),o=oB("numSamples",e,t,n),s=oB("seed",e,t,n);return[CC(i,o,s)];case"OneHot":var u=oB("indices",e,t,n),l=oB("depth",e,t,n),c=oB("onValue",e,t,n),p=oB("offValue",e,t,n);return[$N(u,l,c,p)];case"Ones":return[yC(oB("shape",e,t,n),oB("dtype",e,t,n))];case"OnesLike":return[RC(oB("x",e,t,n))];case"RandomUniform":return[tE(oB("shape",e,t,n),oB("minval",e,t,n),oB("maxval",e,t,n),oB("dtype",e,t,n))];case"Range":return[nE(oB("start",e,t,n),oB("stop",e,t,n),oB("step",e,t,n),oB("dtype",e,t,n))];case"TruncatedNormal":var h=oB("shape",e,t,n),f=oB("mean",e,t,n),d=oB("stdDev",e,t,n),m=oB("seed",e,t,n);return[HE(h,f,d,oB("dtype",e,t,n),m)];case"Zeros":return[gC(oB("shape",e,t,n),oB("dtype",e,t,n))];case"ZerosLike":return[vT(oB("x",e,t,n))];default:throw TypeError("Node type "+e.op+" is not implemented")}}(e,t,n)}));case"dynamic":return uW(e,t,n);case"evaluation":return qI((function(){return function(e,t,n){switch(e.op){case"TopKV2":var r=oB("x",e,t,n),a=oB("k",e,t,n),i=oB("sorted",e,t,n),o=jE(r,a,i);return[o.values,o.indices];case"Unique":var s=oB("x",e,t,n),u=qE(s);return[u.values,u.indices];case"UniqueV2":var l=oB("x",e,t,n),c=oB("axis",e,t,n),p=qE(l,c);return[p.values,p.indices];default:throw TypeError("Node type "+e.op+" is not implemented")}}(e,t,n)}));case"image":return qI((function(){return function(e,t,n){switch(e.op){case"ResizeBilinear":var r=oB("images",e,t,n),a=oB("size",e,t,n),i=oB("alignCorners",e,t,n),o=oB("halfPixelCenters",e,t,n);return[NA.resizeBilinear(r,[a[0],a[1]],i,o)];case"ResizeNearestNeighbor":var s=oB("images",e,t,n),u=oB("size",e,t,n),l=oB("alignCorners",e,t,n),c=oB("halfPixelCenters",e,t,n);return[NA.resizeNearestNeighbor(s,[u[0],u[1]],l,c)];case"CropAndResize":var p=oB("image",e,t,n),h=oB("boxes",e,t,n),f=oB("boxInd",e,t,n),d=oB("cropSize",e,t,n),m=oB("method",e,t,n),v=oB("extrapolationValue",e,t,n);return[NA.cropAndResize(p,h,f,d,m,v)];default:throw TypeError("Node type "+e.op+" is not implemented")}}(e,t,n)}));case"graph":return qI((function(){return function(e,t,n){switch(e.op){case"Const":return t[e.name];case"PlaceholderWithDefault":var r=oB("default",e,t,n);return[sB(e.name,t,n)||r];case"Placeholder":return[sB(e.name,t,n)];case"Identity":case"StopGradient":case"FakeQuantWithMinMaxVars":return[hB(oB("x",e,t,n))];case"IdentityN":return oB("x",e,t,n).map((function(e){return hB(e)}));case"Snapshot":return[hB(oB("x",e,t,n))];case"Shape":return[BE(oB("x",e,t,n).shape,"int32")];case"ShapeN":return oB("x",e,t,n).map((function(e){return BE(e.shape)}));case"Size":return[dE(oB("x",e,t,n).size,"int32")];case"Rank":return[dE(oB("x",e,t,n).rank,"int32")];case"NoOp":return[dE(1)];case"Print":var a=oB("x",e,t,n),i=oB("data",e,t,n),o=oB("message",e,t,n),s=oB("summarize",e,t,n);console.warn("The graph has a tf.print() operation,usually used for debugging, which slows down performance."),console.log(o);for(var u=0;u<i.length;u++)console.log(Array.prototype.slice.call(i[u].dataSync()).slice(0,s));return[a];default:throw TypeError("Node type "+e.op+" is not implemented")}}(e,t,n)}));case"logical":return qI((function(){return function(e,t,n){switch(e.op){case"Equal":return[dT(oB("a",e,t,n),oB("b",e,t,n))];case"NotEqual":return[EC(oB("a",e,t,n),oB("b",e,t,n))];case"Greater":return[AT(oB("a",e,t,n),oB("b",e,t,n))];case"GreaterEqual":return[_T(oB("a",e,t,n),oB("b",e,t,n))];case"Less":return[zT(oB("a",e,t,n),oB("b",e,t,n))];case"LessEqual":return[PT(oB("a",e,t,n),oB("b",e,t,n))];case"LogicalAnd":return[uC(oB("a",e,t,n),oB("b",e,t,n))];case"LogicalNot":return[lC(oB("a",e,t,n))];case"LogicalOr":return[cC(oB("a",e,t,n),oB("b",e,t,n))];case"Select":case"SelectV2":return[mT(oB("condition",e,t,n),oB("a",e,t,n),oB("b",e,t,n))];default:throw TypeError("Node type "+e.op+" is not implemented")}}(e,t,n)}));case"matrices":return qI((function(){return function(e,t,n){switch(e.op){case"BatchMatMul":case"BatchMatMulV2":case"MatMul":return[QN(oB("a",e,t,n),oB("b",e,t,n),oB("transposeA",e,t,n),oB("transposeB",e,t,n))];case"Einsum":return[bT.apply(XB,[oB("equation",e,t,n)].concat(oB("tensors",e,t,n)))];case"Transpose":return[eI(oB("x",e,t,n),oB("perm",e,t,n))];case"_FusedMatMul":var r=oB("fusedOps",e,t,n),a=r[0],i=r[1],o="biasadd"===a,s="prelu"===i,u=oB("numArgs",e,t,n),l=oB("leakyreluAlpha",e,t,n);if(o){if(s&&2!==u)throw new Error("Fused MatMul with BiasAdd and Prelu must have two extra arguments: bias and alpha.");if(!s&&1!==u)throw new Error("Fused MatMul with BiasAdd must have one extra argument: bias.")}var c=oB("args",e,t,n),p=c[0],h=c[1];return[wR({a:oB("a",e,t,n),b:oB("b",e,t,n),transposeA:oB("transposeA",e,t,n),transposeB:oB("transposeB",e,t,n),bias:p,activation:i,preluActivationWeights:h,leakyreluAlpha:l})];default:throw TypeError("Node type "+e.op+" is not implemented")}}(e,t,n)}));case"normalization":return qI((function(){return function(e,t,n){switch(e.op){case"FusedBatchNorm":case"FusedBatchNormV2":case"FusedBatchNormV3":return[zS(oB("x",e,t,n),oB("mean",e,t,n),oB("variance",e,t,n),oB("offset",e,t,n),oB("scale",e,t,n),oB("epsilon",e,t,n))];case"LRN":return[WT(oB("x",e,t,n),oB("radius",e,t,n),oB("bias",e,t,n),oB("alpha",e,t,n),oB("beta",e,t,n))];case"Softmax":return[TE(oB("x",e,t,n))];case"LogSoftmax":return[QT(oB("x",e,t,n))];case"SparseToDense":return[iR(oB("sparseIndices",e,t,n),oB("outputShape",e,t,n),oB("sparseValues",e,t,n),oB("defaultValue",e,t,n))];default:throw TypeError("Node type "+e.op+" is not implemented")}}(e,t,n)}));case"reduction":return qI((function(){return function(e,t,n){switch(e.op){case"Max":var r=oB("axis",e,t,n),a=oB("keepDims",e,t,n);return[YT(oB("x",e,t,n),r,a)];case"Mean":var i=oB("axis",e,t,n),o=oB("keepDims",e,t,n);return[vC(oB("x",e,t,n),i,o)];case"Min":var s=oB("axis",e,t,n),u=oB("keepDims",e,t,n);return[xC(oB("x",e,t,n),s,u)];case"Sum":var l=oB("axis",e,t,n),c=oB("keepDims",e,t,n);return[ZT(oB("x",e,t,n),l,c)];case"All":var p=oB("axis",e,t,n),h=oB("keepDims",e,t,n);return[oS(oB("x",e,t,n),p,h)];case"Any":var f=oB("axis",e,t,n),d=oB("keepDims",e,t,n);return[sS(oB("x",e,t,n),f,d)];case"ArgMax":var m=oB("axis",e,t,n);return[uS(oB("x",e,t,n),m)];case"ArgMin":var v=oB("axis",e,t,n);return[lS(oB("x",e,t,n),v)];case"Prod":var g=oB("axis",e,t,n),y=oB("keepDims",e,t,n);return[WC(oB("x",e,t,n),g,y)];case"Cumsum":var b=oB("axis",e,t,n),x=oB("exclusive",e,t,n),w=oB("reverse",e,t,n);return[iT(oB("x",e,t,n),b,x,w)];case"Bincount":var k=oB("x",e,t,n),N=oB("weights",e,t,n),I=oB("size",e,t,n);return[VS(k,N,I)];case"DenseBincount":var S=oB("x",e,t,n),T=oB("weights",e,t,n),C=oB("size",e,t,n),E=oB("binaryOutput",e,t,n);return[oT(S,T,C,E)];default:throw TypeError("Node type "+e.op+" is not implemented")}}(e,t,n)}));case"slice_join":return qI((function(){return function(e,t,n){switch(e.op){case"ConcatV2":case"Concat":var r=oB("n",e,t,n),a=oB("axis",e,t,n),i=oB("tensors",e,t,n);return i=i.slice(0,r),[_S(i,a)];case"Gather":var o=oB("x",e,t,n),s=oB("indices",e,t,n);return[RT(o,_N(s,"int32"),0)];case"GatherV2":var u=oB("axis",e,t,n),l=oB("batchDims",e,t,n),c=oB("x",e,t,n),p=oB("indices",e,t,n);return[RT(c,_N(p,"int32"),u,l)];case"Reverse":for(var h=oB("dims",e,t,n),f=[],d=0;d<h.length;d++)h[d]&&f.push(d);var m=oB("x",e,t,n);return[sE(m,f)];case"ReverseV2":var v=oB("axis",e,t,n),g=oB("x",e,t,n);return[sE(g,v)];case"Slice":var y=oB("begin",e,t,n),b=oB("size",e,t,n);return[DS(oB("x",e,t,n),y,b)];case"StridedSlice":var x=oB("begin",e,t,n),w=oB("end",e,t,n),k=oB("strides",e,t,n),N=oB("beginMask",e,t,n),I=oB("endMask",e,t,n),S=oB("ellipsisMask",e,t,n),T=oB("newAxisMask",e,t,n),C=oB("shrinkAxisMask",e,t,n),E=oB("x",e,t,n);return[zE(E,x,w,k,N,I,S,T,C)];case"Pack":return qI((function(){var r=oB("axis",e,t,n),a=oB("tensors",e,t,n),i=a[0].shape,o=OE(a[0]).shape,s=a.map((function(e){var t=qv(e.shape,i);if(!t&&!qv(OE(e).shape,o))throw new Error("the input tensors shape does not match");return t?e:ES(e,i)}));return[ME(s,r)]}));case"Unpack":var R=oB("axis",e,t,n),A=oB("tensor",e,t,n);return XE(A,R);case"Tile":var _=oB("reps",e,t,n);return[ST(oB("x",e,t,n),_)];case"Split":case"SplitV":var F=oB("axis",e,t,n),D=oB("numOrSizeSplits",e,t,n),O=oB("x",e,t,n);return AE(O,D,F);case"ScatterNd":var M=oB("indices",e,t,n),L=oB("values",e,t,n),z=oB("shape",e,t,n);return[aR(M,L,z)];case"GatherNd":var P=oB("x",e,t,n),B=oB("indices",e,t,n);return[oR(P,B)];case"SparseToDense":var W=oB("sparseIndices",e,t,n),V=oB("outputShape",e,t,n),U=oB("sparseValues",e,t,n),G=oB("defaultValue",e,t,n);return[iR(W,U,V,U.dtype===G.dtype?G:_N(G,U.dtype))];default:throw TypeError("Node type "+e.op+" is not implemented")}}(e,t,n)}));case"sparse":return qI((function(){return function(e,t,n){switch(e.op){case"SparseFillEmptyRows":var r=TA.sparseFillEmptyRows(oB("indices",e,t,n),oB("values",e,t,n),oB("denseShape",e,t,n),oB("defaultValue",e,t,n));return[r.outputIndices,r.outputValues,r.emptyRowIndicator,r.reverseIndexMap];case"SparseReshape":var a=TA.sparseReshape(oB("inputIndices",e,t,n),oB("inputShape",e,t,n),oB("newShape",e,t,n));return[a.outputIndices,a.outputShape];case"SparseSegmentMean":return[TA.sparseSegmentMean(oB("data",e,t,n),oB("indices",e,t,n),oB("segmentIds",e,t,n))];case"SparseSegmentSum":return[TA.sparseSegmentSum(oB("data",e,t,n),oB("indices",e,t,n),oB("segmentIds",e,t,n))];default:throw TypeError("Node type "+e.op+" is not implemented")}}(e,t,n)}));case"spectral":return qI((function(){return function(e,t,n){switch(e.op){case"FFT":return[CE(oB("x",e,t,n))];case"IFFT":return[EE(oB("x",e,t,n))];case"RFFT":return[_E(oB("x",e,t,n))];case"IRFFT":return[RE(oB("x",e,t,n))];default:throw TypeError("Node type "+e.op+" is not implemented")}}(e,t,n)}));case"string":return qI((function(){return function(e,t,n){switch(e.op){case"StringNGrams":var r=CA.stringNGrams(oB("data",e,t,n),oB("dataSplits",e,t,n),oB("separator",e,t,n),oB("nGramWidths",e,t,n),oB("leftPad",e,t,n),oB("rightPad",e,t,n),oB("padWidth",e,t,n),oB("preserveShortSequences",e,t,n));return[r.nGrams,r.nGramsSplits];case"StringSplit":var a=CA.stringSplit(oB("input",e,t,n),oB("delimiter",e,t,n),oB("skipEmpty",e,t,n));return[a.indices,a.values,a.shape];case"StringToHashBucketFast":return[CA.stringToHashBucketFast(oB("input",e,t,n),oB("numBuckets",e,t,n))];default:throw TypeError("Node type "+e.op+" is not implemented")}}(e,t,n)}));case"transformation":return qI((function(){return function(e,t,n){switch(e.op){case"Cast":return[_N(oB("x",e,t,n),oB("dtype",e,t,n))];case"ExpandDims":var r=oB("axis",e,t,n);return[NT(oB("x",e,t,n),r)];case"Squeeze":var 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YG({inputs:{x:t,alpha:r},backend:e});if("leakyrelu"===n)return qG({inputs:{x:t},backend:e,attrs:{alpha:a}});if("sigmoid"===n)return mG({inputs:{x:t},backend:e});throw new Error("Activation "+n+" has not been implemented for the CPU backend.")}function nj(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=r.shape,o=Hv(a.shape),s=Zv(i,o),u=Hv(s);Vv(o===u,(function(){return"The new shape ("+s+") has "+u+" elements and the old shape ("+a.shape+") has "+o+" elements. 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l=iU(n.bufferSync(a),n.bufferSync(i),o,s);return n.makeTensorInfo(l.shape,i.dtype,l.values)}throw new Error("Error in denseBincount: input must be at most rank 2, but got rank"+a.shape.length+".")}};var iH={kernelName:by,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=r.blockSize,o=r.dataFormat;Vv("NHWC"===o,(function(){return"Only NHWC dataFormat supported on CPU for depthToSpace. 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u=s?a:yq({inputs:{logits:a},backend:n,attrs:{dim:-1}}),l=u.shape[0],c=u.shape[1],p=n.data.get(u.dataId).values,h=[l,i],f=yg(Hv(h),"int32"),d=0;d<l;++d){var m=d*c,v=new Float32Array(c-1);v[0]=p[m];for(var g=1;g<v.length;++g)v[g]=v[g-1]+p[m+g];for(var y=YC(o.toString()),b=d*i,x=0;x<i;++x){var w=y();f[b+x]=v.length;for(var k=0;k<v.length;k++)if(w<v[k]){f[b+x]=k;break}}}return s||n.disposeIntermediateTensorInfo(u),n.makeTensorInfo(h,"int32",f)}},wq=MR;var kq={kernelName:Tb,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.boxes,i=t.scores,o=r.maxOutputSize,s=r.iouThreshold,u=r.scoreThreshold;zV(a,"NonMaxSuppression");var l=n.data.get(a.dataId).values,c=n.data.get(i.dataId).values,p=wq(l,c,o,s,u).selectedIndices;return n.makeTensorInfo([p.length],"int32",new Int32Array(p))}},Nq=LR;var Iq={kernelName:Cb,backendName:"cpu",kernelFunc:function(e){var 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t=e.inputs,n=e.backend,r=e.attrs,a=t.indices,i=r.depth,o=r.onValue,s=r.offValue;zV(a,"oneHot");var u=Hv(a.shape),l=new Float32Array(u*i);l.fill(s);for(var c=n.data.get(a.dataId).values,p=0;p<u;++p)c[p]>=0&&c[p]<i&&(l[p*i+c[p]]=o);return n.makeTensorInfo([].concat(a.shape,[i]),"int32",l)}};function Eq(e){var t=e.inputs,n=e.backend,r=t.x;if("string"===r.dtype)throw new Error("zerosLike is not supported for string tensors");if("complex64"===r.dtype){var a=XV({inputs:{input:r},backend:n}),i=Eq({inputs:{x:a},backend:n}),o=Vj({inputs:{input:r},backend:n}),s=Eq({inputs:{x:o},backend:n}),u=GV({inputs:{real:i,imag:s},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(s),u}return RH({backend:n,attrs:{shape:r.shape,value:0,dtype:r.dtype}})}var Rq={kernelName:Ax,backendName:"cpu",kernelFunc:Eq};var Aq={kernelName:Rb,backendName:"cpu",kernelFunc:function e(t){var n=t.inputs,r=t.backend,a=n.x;if("string"===a.dtype)throw new Error("onesLike is not supported for string tensors");if("complex64"===a.dtype){var i=XV({inputs:{input:a},backend:r}),o=e({inputs:{x:i},backend:r}),s=Vj({inputs:{input:a},backend:r}),u=Eq({inputs:{x:s},backend:r}),l=GV({inputs:{real:o,imag:u},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),r.disposeIntermediateTensorInfo(s),r.disposeIntermediateTensorInfo(u),l}return RH({backend:r,attrs:{shape:a.shape,value:1,dtype:a.dtype}})}};function _q(e){var t=e.inputs,n=e.backend,r=e.attrs.axis;if(1===t.length)return xH({inputs:{input:t[0]},backend:n,attrs:{dim:r}});var a=t[0].shape,i=t[0].dtype;t.forEach((function(e){Uv(a,e.shape,"All tensors passed to stack must have matching shapes"),Vv(i===e.dtype,(function(){return"All tensors passed to stack must have matching dtypes"}))}));var o=[],s=Gj({inputs:t.map((function(e){var t=xH({inputs:{input:e},backend:n,attrs:{dim:r}});return 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Vq={kernelName:jb,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.images,i=t.dy,o=r.alignCorners;zV([i,a],"resizeBilinearGrad");for(var s=dg(a.shape),u=a.shape,l=u[0],c=u[1],p=u[2],h=u[3],f=i.shape,d=f[1],m=f[2],v=new Float32Array(l*c*p*h),g=[o&&d>1?c-1:c,o&&m>1?p-1:p],y=[o&&d>1?d-1:d,o&&m>1?m-1:m],b=g[0]/y[0],x=g[1]/y[1],w=n.data.get(i.dataId).values,k=0,N=0;N<l;N++)for(var I=N*s[0],S=0;S<d;S++)for(var T=S*b,C=Math.floor(T),E=Math.min(Math.ceil(T),c-1),R=I+C*s[1],A=I+E*s[1],_=T-C,F=1-_,D=0;D<m;D++)for(var O=D*x,M=Math.floor(O),L=Math.min(Math.ceil(O),p-1),z=O-M,P=1-z,B=R+M*s[2],W=R+L*s[2],V=A+M*s[2],U=A+L*s[2],G=F*P,j=F*z,H=_*P,q=_*z,K=0;K<h;K++){var X=w[k++];v[B+K]+=X*G,v[W+K]+=X*j,v[V+K]+=X*H,v[U+K]+=X*q}return n.makeTensorInfo([l,p,c,h],"float32",v)}};var Uq={kernelName:Vb,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.images,i=r.alignCorners,o=r.halfPixelCenters,s=r.size;zV(a,"resizeNearestNeighbor");for(var u=dg(a.shape),l=s[0],c=s[1],p=a.shape,h=p[0],f=p[1],d=p[2],m=p[3],v=n.data.get(a.dataId).values,g=new Float32Array(h*l*c*m),y=[i&&l>1?f-1:f,i&&c>1?d-1:d],b=[i&&l>1?l-1:l,i&&c>1?c-1:c],x=y[0]/b[0],w=y[1]/b[1],k=0,N=0;N<h;N++)for(var I=N*u[0],S=0;S<l;S++){var T=o?x*(S+.5):x*S,C=Math.min(f-1,i?Math.round(T):Math.floor(T));o&&(C=Math.max(0,C));for(var E=I+C*u[1],R=0;R<c;R++){var A=o?w*(R+.5):w*R,_=Math.min(d-1,i?Math.round(A):Math.floor(A));o&&(_=Math.max(0,_));for(var F=E+_*u[2],D=0;D<m;D++){var O=v[F+D];g[k++]=O}}}return n.makeTensorInfo([h,l,c,m],a.dtype,g)}};var Gq={kernelName:Ub,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.images,i=t.dy,o=r.alignCorners;zV([i,a],"resizeNearestNeighborGrad");for(var s=dg(a.shape),u=dg(i.shape),l=a.shape,c=l[0],p=l[1],h=l[2],f=l[3],d=i.shape,m=d[1],v=d[2],g=new 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o=r.shape.length,s=n.data.get(r.dataId).values,u=n.data.get(a.dataId).values,l=n.data.get(i.dataId).values,c=tk(a.dtype,i.dtype),p=yg(Hv(a.shape),c),h=0,f=0===o||o>1||1===a.shape.length?1:Hv(a.shape.slice(1)),d=0;d<s.length;d++)for(var m=0;m<f;m++)1===s[d]?p[h++]=u[d]:p[h++]=l[d];return n.makeTensorInfo(a.shape,c,p)}},Zq=sU(Zb,(function(e){return e>=0?1.0507009873554805*e:1.7580993408473768*(Math.exp(e)-1)})),Qq={kernelName:Zb,backendName:"cpu",kernelFunc:Zq},$q=sU(tx,(function(e){return e<0?-1:e>0?1:0})),eK={kernelName:tx,backendName:"cpu",kernelFunc:$q},tK=sU($b,(function(e){return Math.sin(e)})),nK={kernelName:$b,backendName:"cpu",kernelFunc:tK},rK=sU(ex,(function(e){return Math.sinh(e)})),aK={kernelName:ex,backendName:"cpu",kernelFunc:rK},iK=Math.log(1.1920928955078125e-7)+2,oK=sU(rx,(function(e){var t=e>-iK,n=e<iK,r=Math.exp(e);return n?r:t?e:Math.log(1+r)})),sK={kernelName:rx,backendName:"cpu",kernelFunc:oK};var uK={kernelName:ox,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=r.blockShape,o=r.paddings;zV([a],"spaceToBatchND");var s=Hv(i),u=[[0,0]];u.push.apply(u,o);for(var l=1+i.length;l<a.shape.length;++l)u.push([0,0]);var c=Dq.kernelFunc({inputs:{x:a},backend:n,attrs:{paddings:u,constantValue:0}}),p=jA(c.shape,i,s,!1),h=HA(p.length,i.length,!1),f=qA(c.shape,i,s,!1),d=nj({inputs:{x:c},backend:n,attrs:{shape:p}}),m=oG({inputs:{x:d},backend:n,attrs:{perm:h}}),v=nj({inputs:{x:m},backend:n,attrs:{shape:f}});return n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(m),v}};var lK={kernelName:lx,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=t.indices,a=t.values,i=t.denseShape,o=t.defaultValue;if(1!==i.shape.length)throw new Error("Dense shape must be a vector, saw:\n "+i.shape);if(2!==r.shape.length)throw new Error("Indices must be a matrix, saw:\n "+r.shape);if(1!==a.shape.length)throw new Error("Values must be a vector, saw:\n 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o=Array.from(n.data.get(a.dataId).values),s=n.data.get(r.dataId).values,u=Array.from(n.data.get(i.dataId).values),l=wG(s,r.shape,r.dtype,o,u),c=l[0],p=l[1],h=l[2];return[n.makeTensorInfo(p,r.dtype,c),n.makeTensorInfo([h.length],i.dtype,new Int32Array(h))]}};var pK={kernelName:px,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=t.data,a=t.indices,i=t.segmentIds;if(r.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(1!==a.shape.length)throw new Error("Indices should be a vector but received shape\n "+a.shape);if(1!==i.shape.length)throw new Error("Segment ids should be a vector but received shape\n "+i.shape);var o=n.data.get(r.dataId).values,s=n.data.get(a.dataId).values,u=n.data.get(i.dataId).values,l=kG(o,r.shape,r.dtype,s,u,!0),c=l[0],p=l[1];return n.makeTensorInfo(p,r.dtype,c)}};var hK={kernelName:hx,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=t.data,a=t.indices,i=t.segmentIds;if(r.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(1!==a.shape.length)throw new Error("Indices should be a vector but received shape\n "+a.shape);if(1!==i.shape.length)throw new Error("Segment ids should be a vector but received shape\n "+i.shape);var o=n.data.get(r.dataId).values,s=n.data.get(a.dataId).values,u=n.data.get(i.dataId).values,l=kG(o,r.shape,r.dtype,s,u),c=l[0],p=l[1];return n.makeTensorInfo(p,r.dtype,c)}};var fK={kernelName:fx,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.sparseIndices,i=t.sparseValues,o=t.defaultValue,s=r.outputShape,u=dI(0,a,s),l=u.sliceRank,c=u.numUpdates,p=u.sliceSize,h=u.strides,f=u.outputSize,d=Xq(n.bufferSync(a),n.bufferSync(i),s,f,p,c,l,h,n.data.get(o.dataId).values[0],!1);return n.makeTensorInfo(s,d.dtype,d.values)}};var dK={kernelName:sx,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=r.numOrSizeSplits,o=Qv(r.axis,a.shape)[0],s=b_(a,i,o),u=new Array(a.shape.length).fill(0),l=a.shape.slice();return s.map((function(e){var t=[].concat(l);t[o]=e;var r=yG({inputs:{x:a},backend:n,attrs:{begin:u,size:t}});return u[o]+=e,r}))}},mK={kernelName:mx,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=t.x,a=n;zV(r,"square");for(var i=a.data.get(r.dataId).values,o=new Float32Array(i.length),s=0;s<i.length;++s){var u=i[s];o[s]=u*u}return{dataId:a.write(o,r.shape,r.dtype),shape:r.shape,dtype:r.dtype}}},vK=sU(_x,(function(e,t){var n=t;return isNaN(e)?NaN:e>0?1:n.alpha})),gK={kernelName:_x,backendName:"cpu",kernelFunc:vK};var yK={kernelName:vx,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=r.begin,o=r.end,s=r.strides,u=r.beginMask,l=r.endMask,c=r.ellipsisMask,p=r.newAxisMask,h=r.shrinkAxisMask;zV(a,"stridedSlice");var 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hX.getBool("WEBGL_PACK")})),hX.registerFlag("WEBGL_PACK_REDUCE",(function(){return hX.getBool("WEBGL_PACK")})),hX.registerFlag("WEBGL_LAZILY_UNPACK",(function(){return hX.getBool("WEBGL_PACK")})),hX.registerFlag("WEBGL_CONV_IM2COL",(function(){return hX.getBool("WEBGL_PACK")})),hX.registerFlag("WEBGL_MAX_TEXTURE_SIZE",(function(){return function(e){if(null==HK){var t=LK(e);HK=t.getParameter(t.MAX_TEXTURE_SIZE)}return HK}(hX.getNumber("WEBGL_VERSION"))})),hX.registerFlag("WEBGL_MAX_TEXTURES_IN_SHADER",(function(){return function(e){if(null==qK){var t=LK(e);qK=t.getParameter(t.MAX_TEXTURE_IMAGE_UNITS)}return Math.min(16,qK)}(hX.getNumber("WEBGL_VERSION"))})),hX.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION",(function(){var e=hX.getNumber("WEBGL_VERSION");return 0===e?0:function(e){if(0===e)return 0;var t=LK(e);return sX(t,"EXT_disjoint_timer_query_webgl2")&&2===e?2:sX(t,"EXT_disjoint_timer_query")?1:0}(e)})),hX.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE",(function(){return hX.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0&&!mk()})),hX.registerFlag("WEBGL_RENDER_FLOAT32_CAPABLE",(function(){return function(e){if(0===e)return!1;var t=LK(e);if(1===e){if(!sX(t,"OES_texture_float"))return!1}else if(!sX(t,"EXT_color_buffer_float"))return!1;return cX(t)}(hX.getNumber("WEBGL_VERSION"))})),hX.registerFlag("WEBGL_RENDER_FLOAT32_ENABLED",(function(){return!hX.getBool("WEBGL_FORCE_F16_TEXTURES")&&hX.getBool("WEBGL_RENDER_FLOAT32_CAPABLE")})),hX.registerFlag("WEBGL_DOWNLOAD_FLOAT_ENABLED",(function(){return lX(hX.getNumber("WEBGL_VERSION"))})),hX.registerFlag("WEBGL_FENCE_API_ENABLED",(function(){return 2===(e=hX.getNumber("WEBGL_VERSION"))&&null!=LK(e).fenceSync;var e})),hX.registerFlag("WEBGL_SIZE_UPLOAD_UNIFORM",(function(){return hX.getBool("WEBGL_RENDER_FLOAT32_ENABLED")?4:0})),hX.registerFlag("WEBGL_DELETE_TEXTURE_THRESHOLD",(function(){return-1}),(function(e){if(e<0&&-1!==e)throw new Error("WEBGL_DELETE_TEXTURE_THRESHOLD must be -1 (indicating never delete) or at least 0, but got "+e+".")})),hX.registerFlag("WEBGL_FLUSH_THRESHOLD",(function(){return mk()&&hX.getBool("IS_CHROME")?1:-1}),(function(e){if(e<0&&-1!==e)throw new Error("WEBGL_FLUSH_THRESHOLD must be -1 (indicating never manual flush) or at least 0, but got "+e+".")})),hX.registerFlag("CPU_HANDOFF_SIZE_THRESHOLD",(function(){return 128})),hX.registerFlag("WEBGL_USE_SHAPES_UNIFORMS",(function(){return!1})),hX.registerFlag("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD",(function(){return 1e5})),hX.registerFlag("TOPK_K_CPU_HANDOFF_THRESHOLD",(function(){return 128}));var yX="\n const float FLOAT_MAX = 1.70141184e38;\n const float FLOAT_MIN = 1.17549435e-38;\n\n lowp vec4 encode_float(highp float v) {\n if (isnan(v)) {\n return vec4(255, 255, 255, 255);\n 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offset"+e.name+";")),n.enableShapeUniforms){switch(AX(n.packedInputs,e.shapeInfo.logicalShape,e.shapeInfo.texShape).uniformShape.length){case 1:r.push("uniform int "+e.name+"Shape;");break;case 2:r.push("uniform ivec2 "+e.name+"Shape;");break;case 3:r.push("uniform ivec3 "+e.name+"Shape;");break;case 4:r.push("uniform ivec4 "+e.name+"Shape;")}r.push("uniform ivec2 "+e.name+"TexShape;")}})),n.enableShapeUniforms){switch(t.logicalShape.length){case 1:r.push("uniform int outShape;");break;case 2:r.push("uniform ivec2 outShape;"),r.push("uniform int outShapeStrides;");break;case 3:r.push("uniform ivec3 outShape;"),r.push("uniform ivec2 outShapeStrides;");break;case 4:r.push("uniform ivec4 outShape;"),r.push("uniform ivec3 outShapeStrides;")}r.push("uniform ivec2 outTexShape;")}n.customUniforms&&n.customUniforms.forEach((function(e){r.push("uniform "+e.type+" "+e.name+(e.arrayIndex?"["+e.arrayIndex+"]":"")+";")}));var a,i,o=r.join("\n"),s=e.map((function(e){return function(e,t,n,r){void 0===n&&(n=!1);var a="";a+=n?kX(e,r):wX(e,r);var i=e.shapeInfo.logicalShape,o=t.logicalShape;i.length<=o.length&&(a+=n?function(e,t){var n,r=e.name,a=r.charAt(0).toUpperCase()+r.slice(1),i="get"+a+"AtOutCoords",o=e.shapeInfo.logicalShape.length,s=t.logicalShape.length,u=bX(e.shapeInfo.logicalShape,t.logicalShape),l=RX(s),c=s-o,p=["x","y","z","w","u","v"];n=0===o?"":s<2&&u.length>=1?"coords = 0;":u.map((function(e){return"coords."+p[e+c]+" = 0;"})).join("\n");var h="";h=s<2&&o>0?"coords":e.shapeInfo.logicalShape.map((function(e,t){return"coords."+p[t+c]})).join(", ");var f="return outputValue;",d=1===Hv(e.shapeInfo.logicalShape),m=1===Hv(t.logicalShape);if(1!==o||d||m){if(d&&!m)f=1===s?"\n return vec4(outputValue.x, outputValue.x, 0., 0.);\n ":"\n return vec4(outputValue.x);\n ";else if(u.length){var v=o-2,g=o-1;u.indexOf(v)>-1&&u.indexOf(g)>-1?f="return vec4(outputValue.x);":u.indexOf(v)>-1?f="return vec4(outputValue.x, outputValue.y, outputValue.x, 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get"+r+"("+d+");\n }\n "}(e,t));return a}(e,t,n.packedInputs,n.enableShapeUniforms)})).join("\n"),u=t.texShape,l=fX(),c=function(e){return"\n float sampleTexture(sampler2D textureSampler, vec2 uv) {\n return "+e.texture2D+"(textureSampler, uv).r;\n }\n "}(l),p=function(e){return e.version+"\n precision highp float;\n precision highp int;\n precision highp sampler2D;\n "+e.varyingFs+" vec2 resultUV;\n "+e.defineOutput+"\n const vec2 halfCR = vec2(0.5, 0.5);\n\n struct ivec5\n {\n int x;\n int y;\n int z;\n int w;\n int u;\n };\n\n struct ivec6\n {\n int x;\n int y;\n int z;\n int w;\n int u;\n int v;\n };\n\n uniform float NAN;\n "+e.defineSpecialNaN+"\n "+e.defineSpecialInf+"\n "+e.defineRound+"\n\n int imod(int x, int y) {\n return x - y * (x / y);\n }\n\n int idiv(int a, int b, float sign) {\n int res = a / b;\n int mod = imod(a, b);\n if (sign < 0. && mod != 0) {\n res -= 1;\n }\n return res;\n }\n\n //Based on the work of Dave Hoskins\n //https://www.shadertoy.com/view/4djSRW\n #define HASHSCALE1 443.8975\n float random(float seed){\n vec2 p = resultUV * seed;\n vec3 p3 = fract(vec3(p.xyx) * HASHSCALE1);\n p3 += dot(p3, p3.yzx + 19.19);\n return fract((p3.x + p3.y) * p3.z);\n }\n\n "+NX+"\n "+IX+"\n "+SX+"\n "}(l);return t.isPacked?(a=function(e,t,n){switch(e.length){case 0:return"\n int getOutputCoords() {\n return 0;\n }\n ";case 1:return function(e,t,n){var r=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(1===r[0])return n?"\n int getOutputCoords() {\n return 2 * int(resultUV.x * ceil(float(outTexShape[1]) / 2.0));\n }\n ":"\n int getOutputCoords() {\n return 2 * int(resultUV.x * "+r[1]+".0);\n }\n ";if(1===r[1])return n?"\n int getOutputCoords() {\n return 2 * int(resultUV.y * ceil(float(outTexShape[0]) / 2.0));\n }\n ":"\n int getOutputCoords() {\n return 2 * int(resultUV.y * "+r[0]+".0);\n }\n ";if(n)return"\n int getOutputCoords() {\n ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));\n ivec2 resTexRC = ivec2(resultUV.yx *\n vec2(packedTexShape[0], packedTexShape[1]));\n return 2 * (resTexRC.x * packedTexShape[1] + resTexRC.y);\n }\n ";return"\n int getOutputCoords() {\n ivec2 resTexRC = ivec2(resultUV.yx *\n vec2("+r[0]+", "+r[1]+"));\n return 2 * (resTexRC.x * "+r[1]+" + resTexRC.y);\n }\n "}(0,t,n);case 2:return function(e,t,n){var r=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(qv(e,t))return n?"\n ivec2 getOutputCoords() {\n ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));\n return 2 * ivec2(resultUV.yx * vec2(packedTexShape[0], packedTexShape[1]));\n }\n ":"\n ivec2 getOutputCoords() {\n return 2 * ivec2(resultUV.yx * vec2("+r[0]+", "+r[1]+"));\n }\n ";var a=Math.ceil(e[1]/2);if(n)return"\n ivec2 getOutputCoords() {\n ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));\n int texelsInLogicalRow = int(ceil(float(outShape[1]) / 2.0));\n ivec2 resTexRC = ivec2(resultUV.yx *\n vec2(packedTexShape[0], packedTexShape[1]));\n\n int index = resTexRC.x * packedTexShape[1] + resTexRC.y;\n int r = 2 * (index / texelsInLogicalRow);\n int c = imod(index, texelsInLogicalRow) * 2;\n\n return ivec2(r, c);\n }\n ";return"\n ivec2 getOutputCoords() {\n ivec2 resTexRC = ivec2(resultUV.yx *\n vec2("+r[0]+", "+r[1]+"));\n\n int index = resTexRC.x * "+r[1]+" + resTexRC.y;\n int r = 2 * (index / "+a+");\n int c = imod(index, "+a+") * 2;\n\n return ivec2(r, c);\n }\n "}(e,t,n);case 3:return function(e,t,n){if(n)return"\n ivec3 getOutputCoords() {\n ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));\n int texelsInLogicalRow = int(ceil(float(outShape[2]) / 2.0));\n int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[1]) / 2.0));\n ivec2 resTexRC = ivec2(resultUV.yx *\n vec2(packedTexShape[0], packedTexShape[1]));\n int index = resTexRC.x * packedTexShape[1] + resTexRC.y;\n\n int b = index / texelsInBatch;\n index -= b * texelsInBatch;\n\n int r = 2 * (index / texelsInLogicalRow);\n int c = imod(index, texelsInLogicalRow) * 2;\n\n return ivec3(b, r, c);\n }\n ";var r=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],a=Math.ceil(e[2]/2),i=a*Math.ceil(e[1]/2);return"\n ivec3 getOutputCoords() {\n ivec2 resTexRC = ivec2(resultUV.yx *\n vec2("+r[0]+", "+r[1]+"));\n int index = resTexRC.x * "+r[1]+" + resTexRC.y;\n\n int b = index / "+i+";\n index -= b * "+i+";\n\n int r = 2 * (index / "+a+");\n int c = imod(index, "+a+") * 2;\n\n return ivec3(b, r, c);\n }\n "}(e,t,n);default:return function(e,t,n){if(n)return"\n ivec4 getOutputCoords() {\n ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));\n ivec2 resTexRC = ivec2(resultUV.yx *\n vec2(packedTexShape[0], packedTexShape[1]));\n int index = resTexRC.x * packedTexShape[1] + resTexRC.y;\n\n int texelsInLogicalRow = int(ceil(float(outShape[3]) / 2.0));\n int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[2]) / 2.0));\n int texelsInBatchN = texelsInBatch * outShape[1];\n\n int b2 = index / texelsInBatchN;\n index -= b2 * texelsInBatchN;\n\n int b = index / texelsInBatch;\n index -= b * texelsInBatch;\n\n int r = 2 * (index / texelsInLogicalRow);\n int c = imod(index, texelsInLogicalRow) * 2;\n\n return ivec4(b2, b, r, c);\n }\n ";for(var r=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],a=Math.ceil(e[e.length-1]/2),i=a*Math.ceil(e[e.length-2]/2),o=i,s="",u="b, r, c",l=2;l<e.length-1;l++)s="\n int b"+l+" = index / "+(o*=e[e.length-l-1])+";\n index -= b"+l+" * "+o+";\n "+s,u="b"+l+", "+u;return"\n ivec"+e.length+" getOutputCoords() {\n ivec2 resTexRC = ivec2(resultUV.yx *\n vec2("+r[0]+", "+r[1]+"));\n int index = resTexRC.x * "+r[1]+" + resTexRC.y;\n\n "+s+"\n\n int b = index / "+i+";\n index -= b * "+i+";\n\n int r = 2 * (index / "+a+");\n int c = imod(index, "+a+") * 2;\n\n return ivec"+e.length+"("+u+");\n }\n "}(e,t,n)}}(t.logicalShape,u,n.enableShapeUniforms),i=function(e){return"\n void setOutput(vec4 val) {\n "+e.output+" = val;\n }\n "}(l)):(a=function(e,t,n){switch(e.length){case 0:return"\n int getOutputCoords() {\n return 0;\n }\n ";case 1:return function(e,t,n){if(1===t[0])return n?"\n int getOutputCoords() {\n return int(resultUV.x * float(outTexShape[1]));\n }\n ":"\n int getOutputCoords() {\n return int(resultUV.x * "+t[1]+".0);\n }\n ";if(1===t[1])return n?"\n int getOutputCoords() {\n return int(resultUV.y * float(outTexShape[0]));\n }\n ":"\n int getOutputCoords() {\n return int(resultUV.y * "+t[0]+".0);\n }\n ";if(n)return"\n int getOutputCoords() {\n ivec2 resTexRC = ivec2(resultUV.yx *\n vec2(outTexShape[0], outTexShape[1]));\n return resTexRC.x * outTexShape[1] + resTexRC.y;\n }\n ";return"\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 "}(0,t,n);case 2:return function(e,t,n){if(qv(e,t))return n?"\n ivec2 getOutputCoords() {\n return ivec2(resultUV.yx * vec2(outTexShape[0], outTexShape[1]));\n }\n ":"\n ivec2 getOutputCoords() {\n return ivec2(resultUV.yx * vec2("+t[0]+", "+t[1]+"));\n }\n ";if(1===e[1])return n?"\n ivec2 getOutputCoords() {\n ivec2 resTexRC = ivec2(resultUV.yx *\n vec2(outTexShape[0], outTexShape[1]));\n int index = resTexRC.x * outTexShape[1] + resTexRC.y;\n return ivec2(index, 0);\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 return ivec2(index, 0);\n }\n ";if(1===e[0])return n?"\n ivec2 getOutputCoords() {\n ivec2 resTexRC = ivec2(resultUV.yx *\n vec2(outTexShape[0], outTexShape[1]));\n int index = resTexRC.x * outTexShape[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 return ivec2(0, index);\n }\n ";if(n)return"\n ivec2 getOutputCoords() {\n ivec2 resTexRC = ivec2(resultUV.yx *\n vec2(outTexShape[0], outTexShape[1]));\n int index = resTexRC.x * outTexShape[1] + resTexRC.y;\n int r = index / outShape[1];\n int c = index - r * outShape[1];\n return ivec2(r, c);\n }\n ";return"\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 "}(e,t,n);case 3:return function(e,t,n){if(n){return"\n ivec3 getOutputCoords() {\n ivec2 resTexRC = ivec2(resultUV.yx *\n vec2(outTexShape[0], outTexShape[1]));\n int index = resTexRC.x * outTexShape[1] + resTexRC.y;\n "+mX(["r","c","d"],e)+"\n return ivec3(r, c, d);\n }\n"}var r=dX(["r","c","d"],e);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 "+r+"\n return ivec3(r, c, d);\n }\n "}(e,t,n);case 4:return function(e,t,n){if(n){return"\n ivec4 getOutputCoords() {\n ivec2 resTexRC = ivec2(resultUV.yx *\n vec2(outTexShape[0], outTexShape[1]));\n int index = resTexRC.x * outTexShape[1] + resTexRC.y;\n "+mX(["r","c","d","d2"],e)+"\n return ivec4(r, c, d, d2);\n }\n "}var r=dX(["r","c","d","d2"],e);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 "+r+"\n return ivec4(r, c, d, d2);\n }\n "}(e,t,n);case 5:return r=t,a=dX(["r","c","d","d2","d3"],e),"\n ivec5 getOutputCoords() {\n ivec2 resTexRC = ivec2(resultUV.yx * vec2("+r[0]+",\n "+r[1]+"));\n\n int index = resTexRC.x * "+r[1]+" + resTexRC.y;\n\n "+a+"\n\n ivec5 outShape = ivec5(r, c, d, d2, d3);\n return outShape;\n }\n ";case 6:return function(e,t){var n=dX(["r","c","d","d2","d3","d4"],e);return"\n ivec6 getOutputCoords() {\n ivec2 resTexRC = ivec2(resultUV.yx *\n vec2("+t[0]+", "+t[1]+"));\n int index = resTexRC.x * "+t[1]+" + resTexRC.y;\n\n "+n+"\n\n ivec6 result = ivec6(r, c, d, d2, d3, d4);\n return result;\n }\n "}(e,t);default:throw new Error(e.length+"-D output sampling is not yet supported")}var r,a}(t.logicalShape,u,n.enableShapeUniforms),i=function(e){return"\n void setOutput(float val) {\n "+e.output+" = vec4(val, 0, 0, 0);\n }\n "}(l)),n.packedInputs&&(p+=TX),[p,c,i,o,a,s,n.userCode].join("\n")}function wX(e,t){void 0===t&&(t=!1);var n=e.shapeInfo.logicalShape;switch(n.length){case 0:return function(e,t){var n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1);if(e.shapeInfo.isUniform)return"float "+r+"() {return "+n+";}";var a=e.shapeInfo.texShape,i=a[0],o=a[1];if(1===i&&1===o)return"\n float "+r+"() {\n return sampleTexture("+n+", halfCR);\n }\n ";var s=CX(n);if(t)return"\n float "+r+"() {\n vec2 uv = uvFromFlat("+n+"TexShape[0], "+n+"TexShape[1], "+s+");\n return sampleTexture("+n+", uv);\n }\n ";var u=e.shapeInfo.texShape,l=u[0],c=u[1];return"\n float "+r+"() {\n vec2 uv = uvFromFlat("+l+", "+c+", "+s+");\n return sampleTexture("+n+", uv);\n }\n "}(e,t);case 1:return function(e,t){var n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1);if(e.shapeInfo.isUniform)return"\n float "+r+"(int index) {\n "+EX(e)+"\n }\n ";var a=e.shapeInfo.texShape,i=a[0],o=a[1];if(1===o&&1===i)return"\n float "+r+"(int index) {\n return sampleTexture("+n+", halfCR);\n }\n ";var s=CX(n);if(1===o)return t?"\n float "+r+"(int index) {\n vec2 uv = vec2(0.5, (float(index + "+s+") + 0.5) / float("+n+"TexShape[0]));\n return sampleTexture("+n+", uv);\n }\n ":"\n float "+r+"(int index) {\n vec2 uv = vec2(0.5, (float(index + "+s+") + 0.5) / "+i+".0);\n return sampleTexture("+n+", uv);\n }\n ";if(1===i)return t?"\n float "+r+"(int index) {\n vec2 uv = vec2((float(index + "+s+") + 0.5) / float("+n+"TexShape[1]), 0.5);\n return sampleTexture("+n+", uv);\n }\n ":"\n float "+r+"(int index) {\n vec2 uv = vec2((float(index + "+s+") + 0.5) / "+o+".0, 0.5);\n return sampleTexture("+n+", uv);\n }\n ";if(t)return"\n float "+r+"(int index) {\n vec2 uv = uvFromFlat("+n+"TexShape[0], "+n+"TexShape[1], index + "+s+");\n return sampleTexture("+n+", uv);\n }\n ";return"\n float "+r+"(int index) {\n vec2 uv = uvFromFlat("+i+", "+o+", index + "+s+");\n return sampleTexture("+n+", uv);\n }\n "}(e,t);case 2:return function(e,t){var n=e.shapeInfo.logicalShape,r=e.name,a="get"+r.charAt(0).toUpperCase()+r.slice(1),i=e.shapeInfo.texShape;if(null!=i&&qv(n,i)){if(t)return"\n float "+a+"(int row, int col) {\n vec2 uv = (vec2(col, row) + halfCR) / vec2("+r+"TexShape[1], "+r+"TexShape[0]);\n return sampleTexture("+r+", uv);\n }\n ";var o=i[0];return"\n float "+a+"(int row, int col) {\n vec2 uv = (vec2(col, row) + halfCR) / vec2("+i[1]+".0, "+o+".0);\n return sampleTexture("+r+", uv);\n }\n "}var s=$v(n),u=s.newShape,l=s.keptDims,c=u;if(c.length<n.length){var p=["row","col"];return"\n "+wX(_X(e,c),t)+"\n float "+a+"(int row, int col) {\n return "+a+"("+FX(p,l)+");\n }\n "}if(e.shapeInfo.isUniform)return"\n float "+a+"(int row, int col) {\n int index = round(dot(vec2(row, col), vec2("+n[1]+", 1)));\n "+EX(e)+"\n }\n ";var h=i[0],f=i[1],d=CX(r);if(1===f)return t?"\n float "+a+"(int row, int col) {\n float index = dot(vec3(row, col, "+d+"), vec3("+r+"Shape[1], 1, 1));\n vec2 uv = vec2(0.5, (index + 0.5) / float("+r+"TexShape[0]));\n return sampleTexture("+r+", uv);\n }\n ":"\n float "+a+"(int row, int col) {\n float index = dot(vec3(row, col, "+d+"), vec3("+n[1]+", 1, 1));\n vec2 uv = vec2(0.5, (index + 0.5) / "+h+".0);\n return sampleTexture("+r+", uv);\n }\n ";if(1===h)return t?"\n float "+a+"(int row, int col) {\n float index = dot(vec3(row, col, "+d+"), vec3("+r+"Shape[1], 1, 1));\n vec2 uv = vec2((index + 0.5) / float("+r+"TexShape[1]), 0.5);\n return sampleTexture("+r+", uv);\n }\n ":"\n float "+a+"(int row, int col) {\n float index = dot(vec3(row, col, "+d+"), vec3("+n[1]+", 1, 1));\n vec2 uv = vec2((index + 0.5) / "+f+".0, 0.5);\n return sampleTexture("+r+", uv);\n }\n ";if(t)return"\n float "+a+"(int row, int col) {\n // Explicitly use integer operations as dot() only works on floats.\n int index = row * "+r+"Shape[1] + col + "+d+";\n vec2 uv = uvFromFlat("+r+"TexShape[0], "+r+"TexShape[1], index);\n return sampleTexture("+r+", uv);\n }\n ";return"\n float "+a+"(int row, int col) {\n // Explicitly use integer operations as dot() only works on floats.\n int index = row * "+n[1]+" + col + "+d+";\n vec2 uv = uvFromFlat("+h+", "+f+", index);\n return sampleTexture("+r+", uv);\n }\n"}(e,t);case 3:return function(e,t){var n=e.shapeInfo.logicalShape,r=e.name,a="get"+r.charAt(0).toUpperCase()+r.slice(1),i=n[1]*n[2],o=n[2],s=$v(n),u=s.newShape,l=s.keptDims,c=u;if(c.length<n.length){var p=["row","col","depth"];return"\n "+wX(_X(e,c),t)+"\n float "+a+"(int row, int col, int depth) {\n return "+a+"("+FX(p,l)+");\n }\n "}if(e.shapeInfo.isUniform)return"\n float "+a+"(int row, int col, int depth) {\n int index = round(dot(vec3(row, col, depth),\n vec3("+i+", "+o+", 1)));\n "+EX(e)+"\n }\n ";var h=e.shapeInfo.texShape,f=h[0],d=h[1],m=e.shapeInfo.flatOffset;if(d===i&&null==m)return t?"\n float "+a+"(int row, int col, int depth) {\n int stride1 = "+r+"Shape[2];\n float texR = float(row);\n float texC = dot(vec2(col, depth), vec2(stride1, 1));\n vec2 uv = (vec2(texC, texR) + halfCR) /\n vec2("+r+"TexShape[1], "+r+"TexShape[0]);\n return sampleTexture("+r+", uv);\n }\n ":"\n float "+a+"(int row, int col, int depth) {\n float texR = float(row);\n float texC = dot(vec2(col, depth), vec2("+o+", 1));\n vec2 uv = (vec2(texC, texR) + halfCR) /\n vec2("+d+".0, "+f+".0);\n return sampleTexture("+r+", uv);\n }\n ";if(d===o&&null==m)return t?"\n float "+a+"(int row, int col, int depth) {\n float texR = dot(vec2(row, col), vec2("+r+"Shape[1], 1));\n float texC = float(depth);\n vec2 uv = (vec2(texC, texR) + halfCR) / vec2("+r+"TexShape[1], "+r+"TexShape[0]);\n return sampleTexture("+r+", uv);\n }\n ":"\n float "+a+"(int row, int col, int depth) {\n float texR = dot(vec2(row, col), vec2("+n[1]+", 1));\n float texC = float(depth);\n vec2 uv = (vec2(texC, texR) + halfCR) / vec2("+d+".0, "+f+".0);\n return sampleTexture("+r+", uv);\n }\n ";var v=CX(r);if(t)return"\n float "+a+"(int row, int col, int depth) {\n // Explicitly use integer operations as dot() only works on floats.\n int stride0 = "+r+"Shape[1] * "+r+"Shape[2];\n int stride1 = "+r+"Shape[2];\n int index = row * "+i+" + col * "+o+" + depth + "+v+";\n vec2 uv = uvFromFlat("+r+"TexShape[0], "+r+"TexShape[1], index);\n return sampleTexture("+r+", uv);\n }\n ";return"\n float "+a+"(int row, int col, int depth) {\n // Explicitly use integer operations as dot() only works on floats.\n int index = row * "+i+" + col * "+o+" + depth + "+v+";\n vec2 uv = uvFromFlat("+f+", "+d+", index);\n return sampleTexture("+r+", uv);\n }\n "}(e,t);case 4:return function(e,t){var n=e.shapeInfo.logicalShape,r=e.name,a="get"+r.charAt(0).toUpperCase()+r.slice(1),i=n[3],o=n[2]*i,s=n[1]*o,u=$v(n),l=u.newShape,c=u.keptDims;if(l.length<n.length){var p=["row","col","depth","depth2"];return"\n "+wX(_X(e,l),t)+"\n float "+a+"(int row, int col, int depth, int depth2) {\n return "+a+"("+FX(p,c)+");\n }\n "}if(e.shapeInfo.isUniform)return"\n float "+a+"(int row, int col, int depth, int depth2) {\n int index = round(dot(vec4(row, col, depth, depth2),\n vec4("+s+", "+o+", "+i+", 1)));\n "+EX(e)+"\n }\n ";var h=e.shapeInfo.flatOffset,f=e.shapeInfo.texShape,d=f[0],m=f[1],v="int stride2 = "+r+"Shape[3];",g="int stride1 = "+r+"Shape[2] * stride2;",y="int stride0 = "+r+"Shape[1] * stride1;";if(m===s&&null==h)return t?"\n float "+a+"(int row, int col, int depth, int depth2) {\n "+v+"\n "+g+"\n float texR = float(row);\n float texC =\n dot(vec3(col, depth, depth2),\n vec3(stride1, stride2, 1));\n vec2 uv = (vec2(texC, texR) + halfCR) /\n vec2("+r+"TexShape[1], "+r+"TexShape[0]);\n return sampleTexture("+r+", uv);\n }\n ":"\n float "+a+"(int row, int col, int depth, int depth2) {\n float texR = float(row);\n float texC =\n dot(vec3(col, depth, depth2),\n vec3("+o+", "+i+", 1));\n vec2 uv = (vec2(texC, texR) + halfCR) /\n vec2("+m+".0, "+d+".0);\n return sampleTexture("+r+", uv);\n }\n ";if(m===i&&null==h)return t?"\n float "+a+"(int row, int col, int depth, int depth2) {\n float texR = dot(vec3(row, col, depth),\n vec3("+r+"Shape[1] * "+r+"Shape[2], "+r+"Shape[2], 1));\n float texC = float(depth2);\n vec2 uv = (vec2(texC, texR) + halfCR) /\n vec2("+r+"TexShape[1], "+r+"TexShape[0]);\n return sampleTexture("+r+", uv);\n }\n ":"\n float "+a+"(int row, int col, int depth, int depth2) {\n float texR = dot(vec3(row, col, depth),\n vec3("+n[1]*n[2]+", "+n[2]+", 1));\n float texC = float(depth2);\n vec2 uv = (vec2(texC, texR) + halfCR) /\n vec2("+m+".0, "+d+".0);\n return sampleTexture("+r+", uv);\n }\n ";var b=CX(r);if(t)return"\n float "+a+"(int row, int col, int depth, int depth2) {\n // Explicitly use integer operations as dot() only works on floats.\n "+v+"\n "+g+"\n "+y+"\n int index = row * stride0 + col * stride1 +\n depth * stride2 + depth2;\n vec2 uv = uvFromFlat("+r+"TexShape[0], "+r+"TexShape[1], index + "+b+");\n return sampleTexture("+r+", uv);\n }\n ";return"\n float "+a+"(int row, int col, int depth, int depth2) {\n // Explicitly use integer operations as dot() only works on floats.\n int index = row * "+s+" + col * "+o+" +\n depth * "+i+" + depth2;\n vec2 uv = uvFromFlat("+d+", "+m+", index + "+b+");\n return sampleTexture("+r+", uv);\n }\n "}(e,t);case 5:return function(e){var t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[4],i=t[3]*a,o=t[2]*i,s=t[1]*o,u=$v(t),l=u.newShape,c=u.keptDims;if(l.length<t.length){var p=["row","col","depth","depth2","depth3"];return"\n "+wX(_X(e,l))+"\n float "+r+"(int row, int col, int depth, int depth2, int depth3) {\n return "+r+"("+FX(p,c)+");\n }\n "}if(e.shapeInfo.isUniform)return"\n float "+r+"(int row, int col, int depth, int depth2, int depth3) {\n float index = dot(\n vec4(row, col, depth, depth2),\n vec4("+s+", "+o+", "+i+", "+a+")) +\n depth3;\n "+EX(e)+"\n }\n ";var h=e.shapeInfo.flatOffset,f=e.shapeInfo.texShape,d=f[0],m=f[1];if(m===s&&null==h)return"\n float "+r+"(int row, int col, int depth, int depth2, int depth3) {\n int texR = row;\n float texC = dot(vec4(col, depth, depth2, depth3),\n vec4("+o+", "+i+", "+a+", 1));\n vec2 uv = (vec2(texC, texR) + halfCR) /\n vec2("+m+".0, "+d+".0);\n return sampleTexture("+n+", uv);\n }\n ";if(m===a&&null==h)return"\n float "+r+"(int row, int col, int depth, int depth2, int depth3) {\n float texR = dot(\n vec4(row, col, depth, depth2),\n vec4("+t[1]*t[2]*t[3]+",\n "+t[2]*t[3]+", "+t[3]+", 1));\n int texC = depth3;\n vec2 uv = (vec2(texC, texR) + halfCR) /\n vec2("+m+".0, "+d+".0);\n return sampleTexture("+n+", uv);\n }\n ";var v=CX(n);return"\n float "+r+"(int row, int col, int depth, int depth2, int depth3) {\n // Explicitly use integer operations as dot() only works on floats.\n int index = row * "+s+" + col * "+o+" + depth * "+i+" +\n depth2 * "+a+" + depth3 + "+v+";\n vec2 uv = uvFromFlat("+d+", "+m+", index);\n return sampleTexture("+n+", uv);\n }\n "}(e);case 6:return function(e){var t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=$v(t),i=a.newShape,o=a.keptDims;if(i.length<t.length){var s=["row","col","depth","depth2","depth3","depth4"];return"\n "+wX(_X(e,i))+"\n float "+r+"(int row, int col, int depth,\n int depth2, int depth3, int depth4) {\n return "+r+"("+FX(s,o)+");\n }\n "}var u=t[5],l=t[4]*u,c=t[3]*l,p=t[2]*c,h=t[1]*p;if(e.shapeInfo.isUniform)return"\n float "+r+"(int row, int col, int depth,\n int depth2, int depth3, int depth4) {\n int index = round(dot(\n vec4(row, col, depth, depth2),\n vec4("+h+", "+p+", "+c+", "+l+")) +\n dot(\n vec2(depth3, depth4),\n vec2("+u+", 1)));\n "+EX(e)+"\n }\n ";var f=e.shapeInfo.flatOffset,d=e.shapeInfo.texShape,m=d[0],v=d[1];if(v===h&&null==f)return"\n float "+r+"(int row, int col, int depth,\n int depth2, int depth3, int depth4) {\n int texR = row;\n float texC = dot(vec4(col, depth, depth2, depth3),\n vec4("+p+", "+c+", "+l+", "+u+")) +\n float(depth4);\n vec2 uv = (vec2(texC, texR) + halfCR) /\n vec2("+v+".0, "+m+".0);\n return sampleTexture("+n+", uv);\n }\n ";if(v===u&&null==f)return"\n float "+r+"(int row, int col, int depth,\n int depth2, int depth3, int depth4) {\n float texR = dot(vec4(row, col, depth, depth2),\n vec4("+t[1]*t[2]*t[3]*t[4]+",\n "+t[2]*t[3]*t[4]+",\n "+t[3]*t[4]+",\n "+t[4]+")) + float(depth3);\n int texC = depth4;\n vec2 uv = (vec2(texC, texR) + halfCR) /\n vec2("+v+".0, "+m+".0);\n return sampleTexture("+n+", uv);\n }\n ";var g=CX(n);return"\n float "+r+"(int row, int col, int depth,\n int depth2, int depth3, int depth4) {\n // Explicitly use integer operations as dot() only works on floats.\n int index = row * "+h+" + col * "+p+" + depth * "+c+" +\n depth2 * "+l+" + depth3 * "+u+" + depth4 + "+g+";\n vec2 uv = uvFromFlat("+m+", "+v+", index);\n return sampleTexture("+n+", uv);\n }\n "}(e);default:throw new Error(n.length+"-D input sampling is not yet supported")}}function kX(e,t){var n,r,a;switch(e.shapeInfo.logicalShape.length){case 0:return n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=fX(),"\n vec4 "+r+"() {\n return "+a.texture2D+"("+n+", halfCR);\n }\n ";case 1:return function(e,t){var n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape,i=fX();if(t)return"\n vec4 "+r+"(int index) {\n ivec2 packedTexShape = ivec2(ceil(float("+n+"TexShape[0]) / 2.0), ceil(float("+n+"TexShape[1]) / 2.0));\n vec2 uv = packedUVfrom1D(\n packedTexShape[0], packedTexShape[1], index);\n return "+i.texture2D+"("+n+", uv);\n }\n ";var o=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)];return"\n vec4 "+r+"(int index) {\n vec2 uv = packedUVfrom1D(\n "+o[0]+", "+o[1]+", index);\n return "+i.texture2D+"("+n+", uv);\n }\n "}(e,t);case 2:return function(e,t){var n=e.shapeInfo.logicalShape,r=e.name,a="get"+r.charAt(0).toUpperCase()+r.slice(1),i=e.shapeInfo.texShape,o=i[0],s=i[1],u=fX();if(null!=i&&qv(n,i))return t?"\n vec4 "+a+"(int row, int col) {\n vec2 uv = (vec2(col, row) + halfCR) / vec2("+r+"TexShape[1], "+r+"TexShape[0]);\n\n return "+u.texture2D+"("+r+", uv);\n }\n ":"\n vec4 "+a+"(int row, int col) {\n vec2 uv = (vec2(col, row) + halfCR) / vec2("+s+".0, "+o+".0);\n\n return "+u.texture2D+"("+r+", uv);\n }\n ";if(t)return"\n vec4 "+a+"(int row, int col) {\n ivec2 packedTexShape = ivec2(ceil(float("+r+"TexShape[0]) / 2.0), ceil(float("+r+"TexShape[1]) / 2.0));\n int valuesPerRow = int(ceil(float("+r+"Shape[1]) / 2.0));\n vec2 uv = packedUVfrom2D(valuesPerRow, packedTexShape[0], packedTexShape[1], row, col);\n return "+u.texture2D+"("+r+", uv);\n }\n ";var l=[Math.ceil(i[0]/2),Math.ceil(i[1]/2)],c=Math.ceil(n[1]/2);return"\n vec4 "+a+"(int row, int col) {\n vec2 uv 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int col) {\n vec2 uv = packedUVfrom3D(\n "+c+", "+p+", "+f+", "+h+", b, row, col);\n return "+l.texture2D+"("+r+", uv);\n }\n "}(e,t);default:return function(e,t){var n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=fX();if(t)return"\n vec4 "+r+"(int b2, int b, int row, int col) {\n int valuesPerRow = int(ceil(float("+n+"Shape[3]) / 2.0));\n int texelsInBatch = valuesPerRow * int(ceil(float("+n+"Shape[2]) / 2.0));\n int index = b * texelsInBatch + (row / 2) * valuesPerRow + (col / 2);\n texelsInBatch *= "+n+"Shape[1];\n index = b2 * texelsInBatch + index;\n ivec2 packedTexShape = ivec2(ceil(float("+n+"TexShape[0]) / 2.0), ceil(float("+n+"TexShape[1]) / 2.0));\n int texR = index / packedTexShape[1];\n int texC = index - texR * packedTexShape[1];\n vec2 uv = (vec2(texC, texR) + halfCR) / vec2(packedTexShape[1], packedTexShape[0]); return "+a.texture2D+"("+n+", uv);\n }\n ";for(var i=e.shapeInfo.logicalShape,o=i.length,s=e.shapeInfo.texShape,u=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)],l=u[0],c=u[1],p=Math.ceil(i[o-1]/2),h=p*Math.ceil(i[o-2]/2),f="int b, int row, int col",d="b * "+h+" + (row / 2) * "+p+" + (col / 2)",m=2;m<o-1;m++)f="int b"+m+", "+f,d="b"+m+" * "+(h*=i[o-m-1])+" + "+d;return"\n vec4 "+r+"("+f+") {\n int index = "+d+";\n int texR = index / "+c+";\n int texC = index - texR * "+c+";\n vec2 uv = (vec2(texC, texR) + halfCR) / vec2("+c+", "+l+");\n return "+a.texture2D+"("+n+", uv);\n }\n "}(e,t)}}var NX="\nvec2 uvFromFlat(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}\nvec2 packedUVfrom1D(int texNumR, int texNumC, int index) {\n int texelIndex = index / 2;\n int texR = texelIndex / texNumC;\n int texC = texelIndex - texR * texNumC;\n return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n",IX="\nvec2 packedUVfrom2D(int 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EX(e){var t=e.name,n=Hv(e.shapeInfo.logicalShape);return n<2?"return "+t+";":"\n for (int i = 0; i < "+n+"; i++) {\n if (i == index) {\n return "+t+"[i];\n }\n }\n "}function RX(e){if(e<=1)return"int";if(2===e)return"ivec2";if(3===e)return"ivec3";if(4===e)return"ivec4";if(5===e)return"ivec5";if(6===e)return"ivec6";throw Error("GPU for rank "+e+" is not yet supported")}function AX(e,t,n){var r=$v(t),a=r.newShape,i=r.keptDims,o=t.length,s=e&&3===o&&1===t[0],u=s?t.slice(1):a,l=!e&&o>1&&!qv(t,n)&&a.length<o||s;return{useSqueezeShape:l,uniformShape:l?u:t,keptDims:i}}function _X(e,t){var n=JSON.parse(JSON.stringify(e));return n.shapeInfo.logicalShape=t,n}function FX(e,t){return t.map((function(t){return e[t]})).join(", ")}function DX(e,t){if(e.length!==t.length)throw Error("Binary was compiled with "+e.length+" inputs, but was executed with "+t.length+" inputs");e.forEach((function(e,n){var r=e.logicalShape,a=t[n],i=a.shape;if(!qv(r,i))throw Error("Binary was compiled with different shapes 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Shapes "+r+" and "+i+" must match");if(!e.isUniform||!a.isUniform){var o=e.texShape,s=a.isUniform?null:a.texData.texShape;if(!qv(o,s))throw Error("Binary was compiled with different texture shapes than the current args. 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encode_float(x);\n }\n "},PX=function(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=FK.DOWNLOAD;var t=fX();this.outputShape=e,this.userCode="\n "+yX+"\n\n void main() {\n ivec3 coords = getOutputCoords();\n float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));\n "+t.output+" = encode_float(x);\n }\n "},BX=function(e,t){void 0===t&&(t=!1),this.variableNames=["A"],this.customUniforms=[{name:"texShape",type:"ivec2"}];var n=fX();this.outputShape=e,this.enableShapeUniforms=OX(this.outputShape.length);var r="result";t&&(r="floor(result * 255. + 0.5)"),this.userCode="\n "+(this.enableShapeUniforms?"\n int getFlatIndex(ivec3 coords) {\n return coords.x * outShapeStrides[0] + coords.y * outShapeStrides[1] + coords.z;\n }\n":gX(e))+"\n\n void main() {\n ivec3 coords = getOutputCoords();\n\n int flatIndex = getFlatIndex(coords);\n int offset = imod(flatIndex, 4);\n\n flatIndex = idiv(flatIndex, 4, 1.);\n\n int r = flatIndex / texShape[1];\n int c = imod(flatIndex, texShape[1]);\n vec2 uv = (vec2(c, r) + halfCR) / vec2(texShape[1], texShape[0]);\n vec4 values = "+n.texture2D+"(A, uv);\n\n float result;\n\n if(offset == 0) {\n result = values[0];\n } else if(offset == 1) {\n result = values[1];\n } else if(offset == 2) {\n result = values[2];\n } else {\n result = values[3];\n }\n\n "+n.output+" = vec4("+r+", 0., 0., 0.);\n }\n "},WX=function(e,t){void 0===t&&(t=!1),this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.customUniforms=[{name:"texShape",type:"ivec2"}];var n=fX();this.outputShape=e,this.enableShapeUniforms=OX(this.outputShape.length);var r="",a="result";t&&(a="floor(result * 255. + 0.5)");for(var i=0;i<=1;i++)for(var o=0;o<=1;o++){var s=2*i+o;r+="\n localCoords = coords;\n if(localCoords[2] + "+o+" < "+(this.enableShapeUniforms?"outShape[2]":""+e[2])+") {\n localCoords[2] += "+o+";\n if (localCoords[1] + "+i+" < "+(this.enableShapeUniforms?"outShape[1]":""+e[1])+") {\n localCoords[1] += 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0===a&&(a=!1),n=n||t[0].dtype,this.runWebGLProgram(e,t,n,r,a)},n.getAndSaveBinary=function(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]},n.getTextureManager=function(){return this.textureManager},n.dispose=function(){var e=this;if(!this.disposed){if(!Ag().getBool("IS_TEST"))Object.keys(this.binaryCache).forEach((function(t){e.gpgpu.deleteProgram(e.binaryCache[t].webGLProgram),delete e.binaryCache[t]}));this.textureManager.dispose(),null!=this.canvas&&"undefined"!=typeof HTMLCanvasElement&&this.canvas instanceof HTMLCanvasElement?this.canvas.remove():this.canvas=null,this.gpgpuCreatedLocally&&(this.gpgpu.program=null,this.gpgpu.dispose()),this.disposed=!0}},n.floatPrecision=function(){var e=this;return null==this.floatPrecisionValue&&(this.floatPrecisionValue=qI((function(){if(!Ag().get("WEBGL_RENDER_FLOAT32_ENABLED")){var t=Ag().getBool("DEBUG");Ag().set("DEBUG",!1);var n=e.abs(dE(1e-8)).dataSync()[0];if(Ag().set("DEBUG",t),n>0)return 32}return 16}))),this.floatPrecisionValue},n.epsilon=function(){return 32===this.floatPrecision()?1e-7:1e-4},n.uploadToGPU=function(e){var t=this.texData.get(e),n=t.shape,r=t.dtype,a=t.values,i=t.texture,o=t.usage,s=t.isPacked;if(null==i){var u,l=null!=this.activeTimers;l&&(u=_w());var c=t.texShape;if(null==c&&(c=function(e,t){void 0===t&&(t=!1);var n=Ag().getNumber("WEBGL_MAX_TEXTURE_SIZE");if(t&&(n*=2,1===(e=e.map((function(t,n){return n>=e.length-2?Pv(e[n]):e[n]}))).length&&(e=[2,e[0]])),2!==e.length){var r=$v(e);e=r.newShape}var a=Hv(e);if(e.length<=1&&a<=n)return[1,a];if(2===e.length&&e[0]<=n&&e[1]<=n)return e;if(3===e.length&&e[0]*e[1]<=n&&e[2]<=n)return[e[0]*e[1],e[2]];if(3===e.length&&e[0]<=n&&e[1]*e[2]<=n)return[e[0],e[1]*e[2]];if(4===e.length&&e[0]*e[1]*e[2]<=n&&e[3]<=n)return[e[0]*e[1]*e[2],e[3]];if(4===e.length&&e[0]<=n&&e[1]*e[2]*e[3]<=n)return[e[0],e[1]*e[2]*e[3]];if(t){var i=nX(e),o=2,s=2;if(e.length){var u=rX(e);o=u[0],s=u[1]}return Xv(a=i*(o/2)*(s/2)).map((function(e){return 2*e}))}return Xv(a)}(n,s),t.texShape=c),null!=a){var p,h=aX(n),f=c[1],d=c[0],m=a instanceof Uint8Array;if(s){var v=BK(c[0],c[1]);f=v[0],d=v[1],p=new WX(h,m)}else p=new BX(h,m);var g=this.makeTensorInfo([d,f],r);this.texData.get(g.dataId).usage=m?FK.PIXELS:FK.UPLOAD,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(g.dataId),f,d,a);var y=[[d,f]],b=this.runWebGLProgram(p,[g],r,y,!0),x=this.texData.get(b.dataId);t.texture=x.texture,t.texShape=x.texShape,t.isPacked=x.isPacked,t.usage=x.usage,this.disposeIntermediateTensorInfo(g),this.texData.delete(b.dataId),t.values=null,l&&(this.uploadWaitMs+=_w()-u)}else{var w=this.acquireTexture(c,o,r,s);t.texture=w}}},n.convertAndCacheOnCPU=function(e,t){var n=this.texData.get(e),r=n.dtype;return this.releaseGPUData(e),null!=t&&(n.values=function(e,t){if("float32"===t||"complex64"===t)return e;if("int32"===t||"bool"===t){for(var n="int32"===t?new Int32Array(e.length):new Uint8Array(e.length),r=0;r<n.length;++r)n[r]=Math.round(e[r]);return n}throw new Error("Unknown dtype "+t)}(t,r)),n.values},n.acquireTexture=function(e,t,n,r){if(this.numBytesInGPU+=this.computeBytes(e,n),!this.warnedAboutMemory&&this.numBytesInGPU>1024*this.numMBBeforeWarning*1024){var a=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn("High memory usage in GPU: "+a+" MB, most likely due to a memory leak")}return this.textureManager.acquireTexture(e,t,r)},n.computeBytes=function(e,t){return e[0]*e[1]*og(t)},t}(Ov);rJ.nextDataId=0;vk()&&JI("webgl",(function(){return new rJ}),2);var aJ=function(e,t,n){this.variableNames=["A","B"],this.outputShape=fT(t,n),this.enableShapeUniforms=OX(this.outputShape.length),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 "},iJ=function(e,t,n,r){void 0===r&&(r=!1),this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=fT(t,n);var a=this.outputShape.length;this.enableShapeUniforms=OX(a);var i="";if(r)if(0===a||1===Hv(this.outputShape))i="\n result.y = 0.;\n result.z = 0.;\n result.w = 0.;\n ";else if(i="\n "+RX(a)+" coords = getOutputCoords();\n ",1===a)this.enableShapeUniforms?i+="\n result.y = (coords + 1) >= outShape ? 0. : result.y;\n result.z = 0.;\n result.w = 0.;\n ":i+="\n result.y = (coords + 1) >= "+this.outputShape[0]+" ? 0. : result.y;\n result.z = 0.;\n result.w = 0.;\n ";else{var o=VY("coords",a);this.enableShapeUniforms?i+="\n bool nextRowOutOfBounds =\n ("+o[a-2]+" + 1) >= outShape["+a+" - 2];\n bool nextColOutOfBounds =\n ("+o[a-1]+" + 1) >= outShape["+a+" - 1];\n result.y = nextColOutOfBounds ? 0. : result.y;\n result.z = nextRowOutOfBounds ? 0. : result.z;\n result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;\n ":i+="\n bool nextRowOutOfBounds =\n ("+o[a-2]+" + 1) >= "+this.outputShape[a-2]+";\n bool nextColOutOfBounds =\n ("+o[a-1]+" + 1) >= "+this.outputShape[a-1]+";\n result.y = nextColOutOfBounds ? 0. : result.y;\n result.z = nextRowOutOfBounds ? 0. : result.z;\n result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;\n "}this.userCode="\n vec4 binaryOperation(vec4 a, vec4 b) {\n "+e+"\n }\n\n void main() {\n vec4 a = getAAtOutCoords();\n vec4 b = getBAtOutCoords();\n\n vec4 result = binaryOperation(a, b);\n "+i+"\n\n setOutput(result);\n }\n "};function oJ(e){var t=e.inputs,n=e.backend,r=t.x;return n.incRef(r.dataId),{dataId:r.dataId,shape:r.shape,dtype:r.dtype}}var sJ={kernelName:qy,backendName:"webgl",kernelFunc:oJ};function uJ(e){var t=e.inputs,n=e.backend,r=t.real,a=t.imag,i=n.makeTensorInfo(r.shape,"complex64"),o=n.texData.get(i.dataId),s=oJ({inputs:{x:r},backend:n}),u=oJ({inputs:{x:a},backend:n});return o.complexTensorInfos={real:s,imag:u},i}var lJ={kernelName:iy,backendName:"webgl",kernelFunc:uJ},cJ="return (a < 0.) ? b * a : a;",pJ="\n vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));\n return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);\n";var hJ={kernelName:Qy,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=r.alpha,o=n.makeTensorInfo([],"float32",Rw(i,"float32")),s=Ag().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new iJ(pJ,a.shape,o.shape):new aJ(cJ,a.shape,o.shape),u=n.runWebGLProgram(s,[a,o],a.dtype);return n.disposeIntermediateTensorInfo(o),u}},fJ="return (a < 0.) ? b * a : a;",dJ="\n vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));\n return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);\n";var mJ={kernelName:Ob,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=t.x,a=t.alpha,i=Ag().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new iJ(dJ,r.shape,a.shape):new aJ(fJ,r.shape,a.shape);return n.runWebGLProgram(i,[r,a],r.dtype)}};function vJ(e){var t=e.opSnippet,n=e.packedOpSnippet,r=e.cpuKernelImpl,a=e.dtype;return function(e){var i,o=e.inputs,s=e.backend,u=o.x,l=s,c=a||u.dtype;if(l.shouldExecuteOnCPU([u])&&null!=r){var p=l.texData.get(u.dataId),h=r(p.values,c);return l.makeTensorInfo(u.shape,c,h)}return i=Ag().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&null!=n?new QY(u.shape,n):new XY(u.shape,t),l.runWebGLProgram(i,[u],c)}}function gJ(e){var t=e.opSnippet,n=e.packedOpSnippet,r=e.checkOutOfBounds,a=void 0!==r&&r,i=e.supportsComplex,o=void 0!==i&&i,s=e.cpuKernelImpl,u=e.dtype;return function(e){var r=e.inputs,i=e.backend,l=r.a,c=r.b,p=i;if(o&&"complex64"===l.dtype){var h=p.texData.get(l.dataId),f=p.texData.get(c.dataId),d=[[h.complexTensorInfos.real,f.complexTensorInfos.real],[h.complexTensorInfos.imag,f.complexTensorInfos.imag]].map((function(e){var n=e[0],r=e[1],a={dataId:n.dataId,dtype:n.dtype,shape:l.shape},i={dataId:r.dataId,dtype:r.dtype,shape:c.shape},o=new aJ(t,l.shape,c.shape);return p.runWebGLProgram(o,[a,i],tk(n.dtype,r.dtype))})),m=d[0],v=d[1],g=uJ({inputs:{real:m,imag:v},backend:p});return p.disposeIntermediateTensorInfo(m),p.disposeIntermediateTensorInfo(v),g}var y,b=u||tk(l.dtype,c.dtype);if(("string"===l.dtype||"string"===c.dtype||p.shouldExecuteOnCPU([l,c]))&&null!=s){var x=p.texData.get(l.dataId).values,w=p.texData.get(c.dataId).values,k="string"===l.dtype?N_(x):x,N="string"===l.dtype?N_(w):w,I=s(l.shape,c.shape,k,N,b),S=I[0],T=I[1],C=p.makeTensorInfo(T,b);return p.texData.get(C.dataId).values=S,C}return y=Ag().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&null!=n?new iJ(n,l.shape,c.shape,a):new aJ(t,l.shape,c.shape),p.runWebGLProgram(y,[l,c],b)}}function yJ(e,t){if(void 0===t&&(t=!1),"linear"===e)return"return x;";if("relu"===e)return t?"\n vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));\n bvec4 isNaN = isnan(x);\n\n result.r = isNaN.r ? x.r : result.r;\n result.g = isNaN.g ? x.g : result.g;\n result.b = isNaN.b ? x.b : result.b;\n result.a = isNaN.a ? 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bJ=function(e,t,n,r,a,i,o,s,u){void 0===r&&(r=!1),void 0===a&&(a=!1),void 0===i&&(i=!1),void 0===o&&(o=null),void 0===s&&(s=!1),void 0===u&&(u=!1),this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=n,this.enableShapeUniforms=OX(this.outputShape.length);var l=r?e[1]:e[2],c=Math.ceil(l/2),p=r?"i * 2, rc.y":"rc.y, i * 2",h=a?"rc.z, i * 2":"i * 2, rc.z",f=r?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],d=a?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],m="",v="";o&&(m=s?"vec4 activation(vec4 a) {\n vec4 b = getPreluActivationWeightsAtOutCoords();\n "+o+"\n }":u?"vec4 activation(vec4 a) {\n vec4 b = getLeakyreluAlphaAtOutCoords();\n "+o+"\n }":"vec4 activation(vec4 x) {\n "+o+"\n }",v="result = activation(result);");var g=i?"result += getBiasAtOutCoords();":"";i&&this.variableNames.push("bias"),s&&this.variableNames.push("preluActivationWeights"),u&&this.variableNames.push("leakyreluAlpha");var y="rc.x",b="rc.x";e[0]<t[0]?y="int(min(float(rc.x), 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areal, float aimag, float breal, float bimag) {\n "+e+"\n }\n\n void main() {\n float areal = getARealAtOutCoords();\n float aimag = getAImagAtOutCoords();\n float breal = getBRealAtOutCoords();\n float bimag = getBImagAtOutCoords();\n setOutput(binaryOpComplex(areal, aimag, breal, bimag));\n }\n "},NJ="return a * b;";function IJ(e){var t,n=e.inputs,r=e.backend,a=n.a,i=n.b,o=tk(a.dtype,i.dtype);if("complex64"===a.dtype){var s=r.texData.get(a.dataId),u=r.texData.get(i.dataId),l=new kJ(xJ,a.shape,i.shape),c=new kJ(wJ,a.shape,i.shape),p=[{dataId:s.complexTensorInfos.real.dataId,dtype:s.complexTensorInfos.real.dtype,shape:a.shape},{dataId:s.complexTensorInfos.imag.dataId,dtype:s.complexTensorInfos.imag.dtype,shape:a.shape},{dataId:u.complexTensorInfos.real.dataId,dtype:u.complexTensorInfos.real.dtype,shape:i.shape},{dataId:u.complexTensorInfos.imag.dataId,dtype:u.complexTensorInfos.imag.dtype,shape:i.shape}],h=r.runWebGLProgram(l,p,"float32"),f=r.runWebGLProgram(c,p,"float32"),d=uJ({inputs:{real:h,imag:f},backend:r});return r.disposeIntermediateTensorInfo(h),r.disposeIntermediateTensorInfo(f),d}if(r.shouldExecuteOnCPU([a,i])){var m=r.texData.get(a.dataId),v=r.texData.get(i.dataId),g=yY(a.shape,i.shape,m.values,v.values,o),y=g[0],b=g[1],x=r.makeTensorInfo(b,o);return r.texData.get(x.dataId).values=y,x}return t=Ag().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new iJ(NJ,a.shape,i.shape):new aJ(NJ,a.shape,i.shape),r.runWebGLProgram(t,[a,i],o)}var SJ={kernelName:Nb,backendName:"webgl",kernelFunc:IJ};function TJ(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=r.shape,o=n,s=Hv(a.shape),u=Zv(i,s),l=Hv(u);Vv(s===l,(function(){return"The new shape ("+u+") has "+l+" elements and the old shape ("+a.shape+") has "+s+" elements. The new shape and old shape must have the same number of elements."}));var c=o.texData.get(a.dataId);return!c.isPacked||oX(a.shape,u)||null!==c.texture&&oX(c.shape,u)?(o.incRef(a.dataId),{dataId:a.dataId,shape:u,dtype:a.dtype}):function(e,t,n){var r=[nX(e.shape)].concat(rX(e.shape)),a={dtype:e.dtype,shape:r,dataId:e.dataId},i=[nX(t)].concat(rX(t)),o=new GY(i,r),s=[r],u=n.runWebGLProgram(o,[a],e.dtype,s,!0);return{dataId:u.dataId,shape:t,dtype:u.dtype}}(a,u,o)}var CJ={kernelName:Wb,backendName:"webgl",kernelFunc:TJ},EJ=function(e,t){this.variableNames=["x"];var n=e.windowSize,r=e.batchSize,a=e.inSize,i=e.outSize;this.outputShape=[r,i];var o=4*Math.floor(n/4),s=n%4,u="sumValue += dot(values, ones);";if(null!=t){var l=1/t;u="sumValue += dot(values * "+(Kv(l)?l.toPrecision(2):l)+", ones);"}var c="";a%n>0&&(c="\n if (inIdx < 0 || inIdx >= "+a+") {\n return 0.0;\n }\n "),this.userCode="\n const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n float getValue(int batch, int inIdx) {\n "+c+"\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 float sumValue = 0.0;\n\n for (int i = 0; i < "+o+"; 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 "+u+"\n }\n\n int inIdx = inOffset + "+o+";\n if ("+(1===s)+") {\n vec4 values = vec4(getValue(batch, inIdx), 0.0, 0.0, 0.0);\n\n "+u+"\n } else if ("+(2===s)+") {\n vec4 values = vec4(\n getValue(batch, inIdx),\n getValue(batch, inIdx + 1), 0.0, 0.0);\n\n "+u+"\n } else if ("+(3===s)+") {\n vec4 values = vec4(\n getValue(batch, inIdx),\n getValue(batch, inIdx + 1),\n getValue(batch, inIdx + 2), 0.0);\n\n "+u+"\n }\n setOutput(sumValue);\n }\n "},RJ=function(e,t){this.variableNames=["x"];var n=e.windowSize,r=e.batchSize,a=e.inSize,i=e.outSize;this.outputShape=[r,i];var o="0.0",s="";"prod"===t?o="1.0":"min"===t?(o="1.0 / 1e-20",s="min"):"max"===t&&(o="-1.0 / 1e-20",s="max");var u=t+"("+t+"("+t+"(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";"sum"===t?u="sumValue":"prod"===t?u="prodValue":"all"===t?u="allValue":"any"===t&&(u="anyValue");var l=4*Math.floor(n/4),c=n%4,p="\n if ("+("sum"===t)+") {\n sumValue += dot(values, ones);\n } else if ("+("prod"===t)+") {\n vec2 tmp = vec2(values[0], values[1]) * vec2(values[2], values[3]);\n prodValue *= tmp[0] * tmp[1];\n } else {\n minMaxValue = "+s+"(values, minMaxValue);\n if ("+("min"===t)+" || "+("max"===t)+") {\n minMaxValue = "+s+"(values, minMaxValue);\n bvec4 isNaN = isnan(values);\n if (isNaN.r || isNaN.g || isNaN.b || isNaN.a) {\n minMaxValue = vec4(NAN);\n }\n }\n }\n ",h="vec4";"all"===t?(o="1.0",p="\n bool reducedAllValue = all(values);\n float floatedReducedAllValue = float(reducedAllValue);\n allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0);\n ",h="bvec4"):"any"===t&&(o="0.0",p="\n bool reducedAnyValue = any(values);\n float floatedReducedAnyValue = float(reducedAnyValue);\n anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);\n ",h="bvec4");var f="";a%n>0&&(f="\n if (inIdx < 0 || inIdx >= "+a+") {\n return initializationValue;\n }\n "),this.userCode="\n const float initializationValue = "+o+";\n const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n float getValue(int batch, int inIdx) {\n "+f+"\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("+o+");\n float prodValue = 1.0;\n float sumValue = 0.0;\n float allValue = 1.0;\n float anyValue = 0.0;\n\n for (int i = 0; i < "+l+"; i += 4) {\n int inIdx = inOffset + i;\n "+h+" values = "+h+"(\n getValue(batch, inIdx),\n getValue(batch, inIdx + 1),\n getValue(batch, inIdx + 2),\n getValue(batch, inIdx + 3)\n );\n\n "+p+"\n }\n\n int inIdx = inOffset + "+l+";\n if ("+(1===c)+") {\n "+h+" values = "+h+"(\n getValue(batch, inIdx),\n initializationValue,\n initializationValue,\n initializationValue\n );\n\n "+p+"\n } else if ("+(2===c)+") {\n "+h+" values = "+h+"(\n getValue(batch, inIdx),\n getValue(batch, inIdx + 1),\n initializationValue,\n initializationValue\n );\n\n "+p+"\n } else if ("+(3===c)+") {\n "+h+" values = "+h+"(\n getValue(batch, inIdx),\n getValue(batch, inIdx + 1),\n getValue(batch, inIdx + 2),\n initializationValue\n );\n\n "+p+"\n }\n setOutput("+u+");\n }\n "};function AJ(e,t,n,r){for(var a=function(e){for(var t=[];0===t.length||1!==t[t.length-1].outSize;){var n=t.length?t[t.length-1].outSize:e[1],r=UA(n);t.push({inSize:n,windowSize:r,outSize:Math.ceil(n/r)})}return t}(e.shape),i=e,o=0;o<a.length;o++){var s,u=a[o],l=u.inSize,c=u.windowSize,p=u.outSize,h=void 0;h="mean"===n?0===o?new EJ({windowSize:c,inSize:l,batchSize:e.shape[0],outSize:p},l):new EJ({windowSize:c,inSize:l,batchSize:e.shape[0],outSize:p}):new RJ({windowSize:c,inSize:l,batchSize:e.shape[0],outSize:p},n),s=i,i=r.runWebGLProgram(h,[i],t),s.dataId!==e.dataId&&r.disposeIntermediateTensorInfo(s)}return i}var _J=function(e,t){this.variableNames=["A"];for(var n=new Array(e.length),r=0;r<n.length;r++)n[r]=e[t[r]];this.outputShape=n,this.rank=n.length;var a=RX(this.rank),i=function(e){var t=e.length;if(t>6)throw Error("Transpose for rank "+t+" is not yet supported");for(var n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],r=new Array(t),a=0;a<e.length;a++)r[e[a]]=n[a];return r.join()}(t);this.userCode="\n void main() {\n "+a+" resRC = getOutputCoords();\n setOutput(getA("+i+"));\n }\n "};var FJ=function(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;for(var n=new Array(e.length),r=0;r<n.length;r++)n[r]=e[t[r]];if(this.outputShape=n,this.rank=n.length,this.rank>6)throw Error("Packed transpose for rank "+this.rank+" is not yet supported.");for(var a=RX(this.rank),i=WY("rc",this.rank),o=new Array(this.rank),s=0;s<t.length;s++)o[t[s]]=i[s];var u="vec2("+o.slice(-2).join()+")",l="++"+i[this.rank-1]+" < "+n[this.rank-1],c="getChannel(getA("+o.join()+"), "+u+")";this.userCode="\n void main() {\n "+a+" rc = getOutputCoords();\n vec4 result = vec4(0.);\n result[0] = "+c+";\n if("+l+") {\n result[1] = "+c+";\n }\n --"+i[this.rank-1]+";\n if(++"+i[this.rank-2]+" < "+n[this.rank-2]+") {\n result[2] = "+c+";\n if("+l+") {\n result[3] = "+c+";\n }\n }\n setOutput(result);\n }\n "};function DJ(e,t,n){var r=Ag().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new FJ(e.shape,t):new _J(e.shape,t);return n.runWebGLProgram(r,[e],e.dtype)}function OJ(e){var t=e.inputs,n=e.backend,r=e.attrs;return function(e,t,n,r){var a=t,i=e.shape.length,o=Qv(a,e.shape),s=o,u=aC(s,i),l=null!=u,c=e;l&&(c=DJ(e,u,r),s=oC(s.length,i)),rC("sum",s,i);var p=tC(c.shape,s),h=p[0],f=p[1],d=h;n&&(d=nC(h,o));var m=Hv(f),v=TJ({inputs:{x:c},attrs:{shape:[Hv(e.shape)/m,m]},backend:r}),g=AJ(v,nk(e.dtype),"sum",r),y=TJ({inputs:{x:g},attrs:{shape:d},backend:r});return r.disposeIntermediateTensorInfo(v),r.disposeIntermediateTensorInfo(g),l&&r.disposeIntermediateTensorInfo(c),y}(t.x,r.axis,r.keepDims,n)}var MJ={kernelName:ix,backendName:"webgl",kernelFunc:OJ};function LJ(e){for(var t,n=e.inputs,r=e.backend,a=e.attrs,i=n.x,o=a.perm,s=r,u=i.shape.length,l=new Array(u),c=0;c<l.length;c++)l[c]=i.shape[o[c]];if(s.shouldExecuteOnCPU([i])){var p=s.texData.get(i.dataId).values,h=PY(p,i.shape,i.dtype,o,l);t=s.makeTensorInfo(l,i.dtype),s.texData.get(t.dataId).values=h}else t=DJ(i,o,s);return t}var zJ={kernelName:Tx,backendName:"webgl",kernelFunc:LJ};function PJ(e){var t=e.a,n=e.b,r=e.transposeA,a=e.transposeB,i=e.backend,o=e.bias,s=void 0===o?null:o,u=e.preluActivationWeights,l=void 0===u?null:u,c=e.leakyreluAlpha,p=void 0===c?0:c,h=e.activation,f=void 0===h?null:h,d=t.shape.length,m=n.shape.length,v=r?t.shape[d-2]:t.shape[d-1],g=a?n.shape[m-1]:n.shape[m-2],y=r?t.shape[d-1]:t.shape[d-2],b=a?n.shape[m-2]:n.shape[m-1],x=t.shape.slice(0,-2),w=n.shape.slice(0,-2),k=Hv(x),N=Hv(w);Vv(d>=2&&m>=2&&(k===N||1===k||1===N),(function(){return"Error in matMul: the input batch dimensions must either be the same or at least one input batch dimension must be 1. 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G=IJ({inputs:{a:W,b:U},backend:i});S=OJ({inputs:{x:G},backend:i,attrs:{axis:V,keepDims:!0}}),A.push(G)}else{var j=tk(t.dtype,n.dtype),H=new bJ(T,C,[_,y,b],r,a,D,L,O,M),q=[E,R];if(null!=s&&q.push(s),O&&q.push(l),M){var K=i.makeTensorInfo([],"float32",Rw(p,"float32"));q.push(K),A.push(K)}S=i.runWebGLProgram(H,q,j)}var X=TJ({inputs:{x:S},backend:i,attrs:{shape:I}});A.push(S);for(var Y=0,J=A;Y<J.length;Y++){var Z=J[Y];i.disposeIntermediateTensorInfo(Z)}return X}var BJ={kernelName:Ox,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.a,i=t.b,o=t.bias,s=t.preluActivationWeights,u=r.transposeA,l=r.transposeB,c=r.activation;return PJ({a:a,b:i,transposeA:u,transposeB:l,backend:n,bias:o,preluActivationWeights:s,leakyreluAlpha:r.leakyreluAlpha,activation:c})}},WJ="return abs(x);";var VJ={kernelName:Dg,backendName:"webgl",kernelFunc:function(e){var t,n=e.inputs,r=e.backend,a=n.x;if(r.shouldExecuteOnCPU([a])&&"complex64"!==a.dtype){var i=r.texData.get(a.dataId),o=SY(i.values);return r.makeTensorInfo(a.shape,a.dtype,o)}return t=Ag().getBool("WEBGL_PACK_UNARY_OPERATIONS")?new QY(a.shape,WJ):new XY(a.shape,WJ),r.runWebGLProgram(t,[a],a.dtype)}},UJ=vJ({opSnippet:"if (isnan(x)) return x;\n if (abs(x) > 1.) {\n return NAN;\n }\n return acos(x);\n"}),GJ={kernelName:Og,backendName:"webgl",kernelFunc:UJ},jJ=vJ({opSnippet:"if (isnan(x)) return x;\n if (x < 1.0) return NAN;\nreturn log(x + sqrt(x * x - 1.0));"}),HJ={kernelName:Mg,backendName:"webgl",kernelFunc:jJ},qJ="return a + b;",KJ=gJ({opSnippet:qJ,packedOpSnippet:qJ,supportsComplex:!0,cpuKernelImpl:QX}),XJ={kernelName:Lg,backendName:"webgl",kernelFunc:KJ},YJ=function(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((function(e,t){return"T"+t}));var n=[];this.variableNames.forEach((function(e){n.push("float v"+e+" = get"+e+"AtOutCoords();")}));var r=this.variableNames.map((function(e){return"v"+e})).join(" + ");this.userCode="\n void main() {\n "+n.join("\n ")+"\n\n float result = "+r+";\n setOutput(result);\n }\n "},JJ=function(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((function(e,t){return"T"+t}));var n=[];this.variableNames.forEach((function(e){n.push("vec4 v"+e+" = get"+e+"AtOutCoords();")}));var r=this.variableNames.map((function(e){return"v"+e})).join(" + ");this.userCode="\n void main() {\n "+n.join("\n ")+"\n\n vec4 result = "+r+";\n setOutput(result);\n }\n "};var ZJ={kernelName:zg,backendName:"webgl",kernelFunc:function e(t){var n=t.inputs,r=t.backend,a=n;if(1===a.length)return oJ({inputs:{x:a[0]},backend:r});if(a.length>Ag().get("WEBGL_MAX_TEXTURES_IN_SHADER")){var i=Math.floor(a.length/2),o=e({inputs:a.slice(0,i),backend:r}),s=e({inputs:a.slice(i),backend:r});return e({inputs:[o,s],backend:r})}var u=a.map((function(e){return e.dtype})).reduce((function(e,t){return tk(e,t)})),l=a.map((function(e){return e.shape})),c=Ag().getBool("WEBGL_PACK")?new JJ(a[0].shape,l):new YJ(a[0].shape,l);return r.runWebGLProgram(c,a,u)}};var QJ={kernelName:Pg,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=r.axis,o=r.keepDims,s=a.shape.length,u=Qv(i,a.shape),l=u,c=aC(l,s),p=a;null!=c&&(p=LJ({inputs:{x:a},backend:n,attrs:{perm:c}}),l=oC(l.length,s)),rC("all",l,s);var h,f=tC(p.shape,l),d=f[0],m=TJ({inputs:{x:p},backend:n,attrs:{shape:[-1,Hv(f[1])]}}),v=AJ(m,m.dtype,"all",n);return h=TJ(o?{inputs:{x:v},backend:n,attrs:{shape:nC(d,u)}}:{inputs:{x:v},backend:n,attrs:{shape:d}}),n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(v),null!=c&&n.disposeIntermediateTensorInfo(p),h}};var $J={kernelName:Bg,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=r.axis,o=r.keepDims,s=a.shape.length,u=Qv(i,a.shape),l=u,c=aC(l,s),p=a;null!=c&&(p=LJ({inputs:{x:a},backend:n,attrs:{perm:c}}),l=oC(l.length,s)),rC("any",l,s);var h,f=tC(p.shape,l),d=f[0],m=TJ({inputs:{x:p},backend:n,attrs:{shape:[-1,Hv(f[1])]}}),v=AJ(m,m.dtype,"any",n);return h=TJ(o?{inputs:{x:v},backend:n,attrs:{shape:nC(d,u)}}:{inputs:{x:v},backend:n,attrs:{shape:d}}),n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(v),null!=c&&n.disposeIntermediateTensorInfo(p),h}},eZ=function(e,t,n){this.variableNames=["A"];var r=e.windowSize,a=e.batchSize,i=e.outSize;n||this.variableNames.push("bestIndicesA"),this.outputShape=[a,i];var o="max"===t?">":"<",s=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 = inOffset;\n float bestValue = getA(batch, bestIndex);\n\n for (int i = 0; i < "+r+"; i++) {\n int inIdx = "+s+";\n float candidate = getA(batch, inIdx);\n if (candidate "+o+" bestValue) {\n bestValue = candidate;\n bestIndex = inIdx;\n }\n }\n setOutput(float(bestIndex));\n }\n "},tZ=function(e,t,n,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,Vv(e.length>2,(function(){return"Packed arg"+(n.charAt(0).toUpperCase()+n.slice(1))+" supports only inputs with rank above 2."}));var a=e[e.length-1],i=Math.ceil(a/t);this.outputShape=e.slice(0,-1),i>1&&this.outputShape.push(i),r||this.variableNames.push("bestIndicesA");var o,s,u=this.outputShape,l=u.length,c=RX(l),p=VY("coords",l);if(1===i){var h=RX(s=l+1);o="\n "+h+" sourceLocR = "+h+"("+p.join()+", 0);\n ++"+p[l-1]+";\n "+h+" sourceLocG = "+h+"("+p.join()+", 0);\n ++"+p[l-2]+";\n "+h+" sourceLocA = "+h+"("+p.join()+", 0);\n --"+p[l-1]+";\n "+h+" sourceLocB = "+h+"("+p.join()+", 0);\n --"+p[l-2]+";"}else s=l,o="\n "+c+" sourceLocR = coords;\n ++"+p[l-1]+";\n "+c+" sourceLocG = coords;\n ++"+p[l-2]+";\n "+c+" sourceLocA = coords;\n --"+p[l-1]+";\n "+c+" sourceLocB = coords;\n --"+p[l-2]+";";var f=["x","y","z","w","u","v"].slice(0,s),d="."+f[s-1],m=f.map((function(e){return"int "+e})),v=VY("sourceLocR",s-1).concat("inIdx.r"),g=VY("sourceLocG",s-1).concat("inIdx.g"),y=VY("sourceLocB",s-1).concat("inIdx.b"),b=VY("sourceLocA",s-1).concat("inIdx.a"),x="max"===n?"greaterThan":"lessThan",w=r?"":"\n inIdx = round(vec4(getBestIndicesAChannel("+v.join()+"),\n getBestIndicesAChannel("+g.join()+"),\n getBestIndicesAChannel("+y.join()+"),\n getBestIndicesAChannel("+b.join()+")));",k="vec4(\n getAChannel("+v.join()+"),\n hasNextCol ? getAChannel("+g.join()+") : 0.,\n hasNextRow ? getAChannel("+y.join()+") : 0.,\n hasNextRow && hasNextCol ? getAChannel("+b.join()+") : 0.)",N=r?"":"\n float getBestIndicesAChannel("+m.join()+") {\n return getChannel(getBestIndicesA("+f.join()+"),\n vec2("+f.slice(-2).join()+"));\n }";this.userCode="\n float getAChannel("+m.join()+") {\n return getChannel(getA("+f.join()+"),\n vec2("+f.slice(-2).join()+"));\n }\n "+N+"\n void main() {\n "+c+" coords = getOutputCoords();\n bool hasNextCol = "+p[l-1]+" < "+(u[l-1]-1)+";\n bool hasNextRow = "+p[l-2]+" < "+(u[l-2]-1)+";\n "+o+"\n ivec4 srcIdx = ivec4(sourceLocR"+d+", sourceLocG"+d+",\n sourceLocB"+d+", sourceLocA"+d+") * "+t+";\n ivec4 inIdx = srcIdx;\n vec4 bestIndex = vec4(inIdx);\n vec4 bestValue = "+k+";\n\n for (int i = 0; i < "+t+"; i++) {\n inIdx = srcIdx;\n "+w+"\n vec4 candidate = "+k+";\n bvec4 nan = isnan(candidate);\n bvec4 replace = bvec4(\n vec4("+x+"(candidate, bestValue)) * (vec4(1.0) - vec4(nan)));\n\n bestValue = vec4(replace.x ? candidate.x : bestValue.x,\n replace.y ? candidate.y : bestValue.y,\n replace.z ? candidate.z : bestValue.z,\n replace.w ? candidate.w : bestValue.w);\n bestIndex = mix(bestIndex, vec4(inIdx), vec4(replace));\n srcIdx++;\n }\n setOutput(bestIndex);\n }\n "};function nZ(e,t,n,r){void 0===r&&(r=null);var a=t.shape[0],i=t.shape[1];null!=r&&(a=r.shape[0],i=r.shape[1]);var o=UA(i),s={windowSize:o,inSize:i,batchSize:a,outSize:Math.ceil(i/o)},u=new eZ(s,n,null==r),l=[t];null!=r&&l.push(r);var c=e.runWebGLProgram(u,l,"int32");if(1===c.shape[1])return c;var p=nZ(e,t,n,c);return e.disposeIntermediateTensorInfo(c),p}function rZ(e,t,n,r){void 0===r&&(r=null);var a=null!=r?r.shape:t.shape,i=UA(a[a.length-1]),o=new tZ(a,i,n,null==r),s=null==r?[t]:[t,r],u=e.runWebGLProgram(o,s,"int32");if(u.shape.length===t.shape.length){var l=rZ(e,t,n,u);return e.disposeIntermediateTensorInfo(u),l}return u}function aZ(e,t,n,r){var a=[n];if(rC("arg"+r.charAt(0).toUpperCase()+r.slice(1),a,t.shape.length),!Ag().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){var i=[],o=e.texData.get(t.dataId),s=t;null!==o&&o.isPacked&&(s=e.unpackTensor(t),i.push(s));var u=tC(s.shape,a),l=u[0],c=Hv(u[1]),p=TJ({inputs:{x:s},backend:e,attrs:{shape:[-1,c]}});i.push(p);var h=nZ(e,p,r);i.push(h);var f=TJ({inputs:{x:h},backend:e,attrs:{shape:l}});return i.forEach((function(t){return e.disposeIntermediateTensorInfo(t)})),f}return rZ(e,t,r)}var iZ={kernelName:Wg,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=Qv(r.axis,a.shape),o=aC(i,a.shape.length),s=a,u=[];null!=o&&(s=LJ({inputs:{x:a},backend:n,attrs:{perm:o}}),u.push(s),i=oC(i.length,s.shape.length)),rC("argMax",[i[0]],s.shape.length);var l=aZ(n,s,i[0],"max");return u.forEach((function(e){return n.disposeIntermediateTensorInfo(e)})),l}};var oZ={kernelName:Vg,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=Qv(r.axis,a.shape),o=aC(i,a.shape.length),s=a,u=[];null!=o&&(s=LJ({inputs:{x:a},backend:n,attrs:{perm:o}}),u.push(s),i=oC(i.length,s.shape.length)),rC("argMin",[i[0]],s.shape.length);var l=aZ(n,s,i[0],"min");return u.forEach((function(e){return n.disposeIntermediateTensorInfo(e)})),l}},sZ=vJ({opSnippet:"if (isnan(x)) return x;\n if (abs(x) > 1.) {\n return NAN;\n }\n return asin(x);\n"}),uZ={kernelName:Ug,backendName:"webgl",kernelFunc:sZ},lZ=vJ({opSnippet:"if (isnan(x)) return x;return log(x 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NAN : result.r;\n result.g = isNaN.g > 0. ? NAN : result.g;\n result.b = isNaN.b > 0. ? NAN : result.b;\n result.a = isNaN.a > 0. ? NAN : result.a;\n\n return result;\n"}),dZ={kernelName:qg,backendName:"webgl",kernelFunc:fZ},mZ=vJ({opSnippet:"if (isnan(x)) return x;\n if ((x < -1.0) || (x > 1.0)) return NAN;\nreturn (log(1.0 + x) - log(1.0 - x)) / 2.0;"}),vZ={kernelName:Hg,backendName:"webgl",kernelFunc:mZ},gZ=function(e,t,n,r,a){if(void 0===r&&(r=!1),void 0===a&&(a=!1),this.variableNames=["x"],"avg"===t&&n)throw new Error("Cannot compute positions for average pool.");var i=e.filterWidth,o=e.strideHeight,s=e.strideWidth,u=e.dilationHeight,l=e.dilationWidth,c=e.effectiveFilterHeight,p=e.effectiveFilterWidth,h=e.padInfo.top,f=e.padInfo.left;this.outputShape=e.outShape;var d="avg"===t,m="((batch * "+e.inHeight+" + xR) * "+e.inWidth+" + xC) * "+e.inChannels+" + d",v="(xR * "+e.inWidth+" + xC) * "+e.inChannels+" + d",g="0.0";if(d||(g="-1.0 / 1e-20"),n){this.userCode="\n const ivec2 strides = ivec2("+o+", "+s+");\n const ivec2 pads = ivec2("+h+", "+f+");\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 < "+c+";\n wR += "+u+") {\n int xR = xRCorner + wR;\n\n if (xR < 0 || xR >= "+e.inHeight+") {\n continue;\n }\n\n for (int wC = 0; wC < "+p+";\n wC += "+l+") {\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 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 >= currMinMaxValue) {\n minMaxValue = value;\n minMaxValueFound = 1.0;\n minMaxPosition = "+(r?a?m:v:"wR * "+p+" + wC")+";\n }\n }\n }\n setOutput(float(minMaxPosition));\n }\n "}else{var y=t+"("+t+"("+t+"(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";"avg"===t&&(y="avgValue / count");var b=4*Math.floor(i/4),x=i%4,w="\n if ("+d+") {\n avgValue += dot(values, ones);\n } else {\n minMaxValue = max(values, minMaxValue);\n }\n ";this.userCode="\n const ivec2 strides = ivec2("+o+", "+s+");\n const ivec2 pads = ivec2("+h+", "+f+");\n const float initializationValue = "+g+";\n const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n float count = 0.0;\n\n float getValue(int batch, int xR, int xC, int d) {\n if (xC < 0 || xC >= "+e.inWidth+") {\n return initializationValue;\n }\n count += 1.0;\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("+g+");\n float avgValue = 0.0;\n count = 0.0;\n\n for (int wR = 0; wR < "+c+";\n wR += "+u+") {\n int xR = xRCorner + wR;\n\n if (xR < 0 || xR >= "+e.inHeight+") {\n continue;\n }\n\n for (int wC = 0; wC < "+b+"; wC += 4) {\n int xC = xCCorner + wC * "+l+";\n\n vec4 values = vec4(\n getValue(batch, xR, xC, d),\n getValue(batch, xR, xC + "+l+", d),\n getValue(batch, xR, xC + 2 * "+l+", d),\n getValue(batch, xR, xC + 3 * "+l+", d)\n );\n\n "+w+"\n }\n\n int xC = xCCorner + "+b+";\n if ("+(1===x)+") {\n vec4 values = vec4(\n getValue(batch, xR, xC, d),\n initializationValue,\n initializationValue,\n initializationValue\n );\n\n "+w+"\n } else if ("+(2===x)+") {\n vec4 values = vec4(\n getValue(batch, xR, xC, d),\n getValue(batch, xR, xC + "+l+", d),\n initializationValue,\n initializationValue\n );\n\n "+w+"\n } else if ("+(3===x)+") {\n vec4 values = vec4(\n getValue(batch, xR, xC, d),\n getValue(batch, xR, xC + "+l+", d),\n getValue(batch, xR, xC + 2 * "+l+", d),\n initializationValue\n );\n\n "+w+"\n }\n }\n setOutput("+y+");\n }\n "}},yZ=function(e,t,n,r,a){if(void 0===r&&(r=!1),void 0===a&&(a=!1),this.variableNames=["x"],"avg"===t&&n)throw new Error("Cannot compute positions for average pool.");var i=e.filterWidth,o=e.strideDepth,s=e.strideHeight,u=e.strideWidth,l=e.dilationDepth,c=e.dilationHeight,p=e.dilationWidth,h=e.effectiveFilterDepth,f=e.effectiveFilterHeight,d=e.effectiveFilterWidth,m=e.padInfo.front,v=e.padInfo.top,g=e.padInfo.left;this.outputShape=e.outShape;var y="avg"===t,b="0.0";if(y||(b="-1.0 / 1e-20"),n){this.userCode="\n const ivec3 strides =\n ivec3("+o+", "+s+", "+u+");\n const ivec3 pads = ivec3("+m+", "+v+", "+g+");\n\n void main() {\n ivec5 coords = getOutputCoords();\n int batch = coords.x;\n int ch = coords.u;\n\n ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n int xDCorner = xCorner.x;\n int xRCorner = xCorner.y;\n int xCCorner = xCorner.z;\n\n // max/min x(?, ?, ?, ch) to get y(yD, yR, yC, ch).\n // ? = to be determined\n float minMaxValue = 0.0;\n float minMaxValueFound = 0.0;\n int minMaxPosition = 0;\n\n for (int wD = 0; wD < "+h+";\n wD += "+l+") {\n int xD = xDCorner + wD;\n\n if (xD < 0 || xD >= "+e.inDepth+") {\n continue;\n }\n\n for (int wR = 0; wR < "+f+";\n wR += "+c+") {\n int xR = xRCorner + wR;\n\n if (xR < 0 || xR >= "+e.inHeight+") {\n continue;\n }\n\n for (int wC = 0; wC < "+d+";\n wC += "+p+") {\n int xC = xCCorner + wC;\n\n if (xC < 0 || xC >= "+e.inWidth+") {\n continue;\n }\n\n float value = getX(batch, xD, xR, xC, ch);\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 >= currMinMaxValue) {\n minMaxValue = value;\n minMaxValueFound = 1.0;\n minMaxPosition = "+(r?a?"(((batch * "+e.inDepth+" + xD) * "+e.inHeight+" + xR) * "+e.inWidth+" + xC) * "+e.inChannels+" + ch":"((xD * "+e.inHeight+" + xR) * "+e.inWidth+" + xC) * "+e.inChannels+" + ch":"wD * "+f+" * "+d+" +\n wR * "+d+" + wC")+";\n }\n }\n }\n }\n setOutput(float(minMaxPosition));\n }\n "}else{var x=t+"("+t+"("+t+"(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";"avg"===t&&(x="avgValue / count");var w=4*Math.floor(i/4),k=i%4,N="\n if ("+y+") {\n avgValue += dot(values, ones);\n } else {\n minMaxValue = max(values, minMaxValue);\n }\n ";this.userCode="\n const ivec3 strides =\n ivec3("+o+", "+s+", "+u+");\n const ivec3 pads = ivec3("+m+", "+v+", "+g+");\n const float initializationValue = "+b+";\n const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n float count = 0.0;\n\n float getValue(int batch, int xD, int xR, int xC, int ch) {\n if (xC < 0 || xC >= "+e.inWidth+") {\n return initializationValue;\n }\n count += 1.0;\n return getX(batch, xD, xR, xC, ch);\n }\n\n void main() {\n ivec5 coords = getOutputCoords();\n int batch = coords.x;\n int ch = coords.u;\n\n ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n int xDCorner = xCorner.x;\n int xRCorner = xCorner.y;\n int xCCorner = xCorner.z;\n\n // max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).\n // ? = to be determined\n vec4 minMaxValue = vec4("+b+");\n float avgValue = 0.0;\n count = 0.0;\n\n for (int wD = 0; wD < "+h+";\n wD += "+l+") {\n int xD = xDCorner + wD;\n\n if (xD < 0 || xD >= "+e.inDepth+") {\n continue;\n }\n\n for (int wR = 0; wR < "+f+";\n wR += "+c+") {\n int xR = xRCorner + wR;\n\n if (xR < 0 || xR >= "+e.inHeight+") {\n continue;\n }\n\n for (int wC = 0; wC < "+w+"; wC += 4) {\n int xC = xCCorner + wC * "+p+";\n\n vec4 values = vec4(\n getValue(batch, xD, xR, xC, ch),\n getValue(batch, xD, xR, xC + "+p+", ch),\n getValue(batch, xD, xR, xC + 2 * "+p+", ch),\n getValue(batch, xD, xR, xC + 3 * "+p+", ch)\n );\n\n "+N+"\n }\n\n int xC = xCCorner + "+w+";\n if ("+(1===k)+") {\n vec4 values = vec4(\n getValue(batch, xD, xR, xC, ch),\n initializationValue,\n initializationValue,\n initializationValue\n );\n\n "+N+"\n } else if ("+(2===k)+") {\n vec4 values = vec4(\n getValue(batch, xD, xR, xC, ch),\n getValue(batch, xD, xR, xC + "+p+", ch),\n initializationValue,\n initializationValue\n );\n\n "+N+"\n } else if ("+(3===k)+") {\n vec4 values = vec4(\n getValue(batch, xD, xR, xC, ch),\n getValue(batch, xD, xR, xC + "+p+", ch),\n getValue(batch, xD, xR, xC + 2 * "+p+", ch),\n initializationValue\n );\n\n "+N+"\n }\n }\n setOutput("+x+");\n }\n }\n "}};var bZ={kernelName:Kg,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x;pX(a,"avgPool");var i=r.filterSize,o=r.strides,s=r.pad,u=r.dimRoundingMode;Vv(TS(o,1),(function(){return"Error in avgPool: Either strides or dilations must be 1. Got strides "+o+" and dilations '1'"}));var l=vS(a.shape,i,o,1,s,u);if(1===l.filterWidth&&1===l.filterHeight&&qv(l.inShape,l.outShape))return oJ({inputs:{x:a},backend:n});var c=new gZ(l,"avg",!1);return n.runWebGLProgram(c,[a],"float32")}};var xZ={kernelName:Yg,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=r.filterSize,o=r.strides,s=r.pad,u=r.dimRoundingMode,l=r.dataFormat,c=gS(a.shape,i,o,[1,1,1],s,u,l),p=new yZ(c,"avg",!1);return n.runWebGLProgram(p,[a],"float32")}},wZ=function(e){this.variableNames=["dy"],this.outputShape=e.inShape;var t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,i=e.dilationHeight,o=e.dilationWidth,s=e.effectiveFilterHeight,u=e.effectiveFilterWidth,l=s-1-e.padInfo.top,c=u-1-e.padInfo.left,p=1/(t*n);this.userCode="\n const ivec2 pads = ivec2("+l+", "+c+");\n const float avgMultiplier = float("+p+");\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 < "+s+";\n wR += "+i+") {\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 < "+u+";\n wC+= "+o+") {\n float dyC = float(dyCCorner + wC) / "+a+".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 "},kZ=function(e){this.variableNames=["dy"],this.outputShape=e.inShape;var t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,i=e.strideHeight,o=e.strideWidth,s=e.dilationDepth,u=e.dilationHeight,l=e.dilationWidth,c=e.effectiveFilterDepth,p=e.effectiveFilterHeight,h=e.effectiveFilterWidth,f=c-1-e.padInfo.front,d=p-1-e.padInfo.top,m=h-1-e.padInfo.left,v=1/(t*n*r);this.userCode="\n const ivec3 pads = ivec3("+f+", "+d+", "+m+");\n const float avgMultiplier = float("+v+");\n\n void main() {\n ivec5 coords = getOutputCoords();\n int batch = coords.x;\n int ch = coords.u;\n\n ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n int dyDCorner = dyCorner.x;\n int dyRCorner = dyCorner.y;\n int dyCCorner = dyCorner.z;\n\n // Convolve dy(?, ?, ?, d) with pos mask(:, :, :, ch) to get\n // dx(xD, xR, xC, ch).\n // ? = to be determined. : = across all values in that axis.\n float dotProd = 0.0;\n\n for (int wD = 0; wD < "+c+";\n wD += "+s+") {\n float dyD = float(dyDCorner + wD) / "+a+".0;\n\n if (dyD < 0.0 || dyD >= "+e.outDepth+".0 || fract(dyD) > 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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 < "+p+"; wR++) {\n int xR = xRCorner + wR * "+l+";\n\n if (xR < 0 || xR >= "+e.inHeight+") {\n continue;\n }\n\n for (int wC = 0; wC < "+h+"; wC++) {\n int xC = xCCorner + wC * "+c+";\n\n if (xC < 0 || xC >= "+e.inWidth+") {\n continue;\n }\n\n for (int d1 = 0; d1 < "+f+"; d1 += 4) {\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 if ("+m+") {\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 dotProd += dot(xValues, wValues);\n } else {\n vec4 xValues = vec4(\n getX(batch, d1, xR, xC),\n getX(batch, d1 + 1, xR, xC),\n getX(batch, d1 + 2, xR, xC),\n getX(batch, d1 + 3, xR, xC)\n );\n dotProd += dot(xValues, wValues);\n }\n }\n\n if ("+(1===d)+") {\n\n if ("+m+") {\n dotProd +=\n getX(batch, xR, xC, "+f+") *\n getW(wR, wC, "+f+", d2);\n } else {\n dotProd +=\n getX(batch, "+f+", xR, xC) *\n getW(wR, wC, "+f+", d2);\n }\n\n } else if ("+(2===d)+") {\n vec2 wValues = vec2(\n getW(wR, wC, "+f+", d2),\n getW(wR, wC, "+f+" + 1, d2)\n );\n\n if ("+m+") {\n vec2 xValues = vec2(\n getX(batch, xR, xC, "+f+"),\n getX(batch, xR, xC, "+f+" + 1)\n );\n dotProd += dot(xValues, wValues);\n } else {\n vec2 xValues = vec2(\n getX(batch, "+f+", xR, xC),\n getX(batch, "+f+" + 1, xR, xC)\n );\n dotProd += dot(xValues, wValues);\n }\n\n } else if ("+(3===d)+") {\n vec3 wValues = vec3(\n getW(wR, wC, "+f+", d2),\n getW(wR, wC, "+f+" + 1, d2),\n getW(wR, wC, "+f+" + 2, d2)\n );\n\n if ("+m+") {\n vec3 xValues = vec3(\n getX(batch, xR, xC, "+f+"),\n getX(batch, xR, xC, "+f+" + 1),\n getX(batch, xR, xC, "+f+" + 2)\n );\n dotProd += dot(xValues, wValues);\n } else {\n vec3 xValues = vec3(\n getX(batch, "+f+", xR, xC),\n getX(batch, "+f+" + 1, xR, xC),\n getX(batch, "+f+" + 2, xR, xC)\n );\n dotProd += dot(xValues, wValues);\n }\n\n }\n }\n }\n\n float result = dotProd;\n "+w+"\n "+x+"\n setOutput(result);\n }\n "},iQ=function(e){this.variableNames=["x","W"],this.outputShape=e.outShape;var t=e.padInfo.front,n=e.padInfo.top,r=e.padInfo.left,a=e.strideDepth,i=e.strideHeight,o=e.strideWidth,s=e.dilationDepth,u=e.dilationHeight,l=e.dilationWidth,c=e.filterDepth,p=e.filterHeight,h=e.filterWidth,f=4*Math.floor(e.inChannels/4),d=e.inChannels%4;this.userCode="\n const ivec3 strides = ivec3("+a+", "+i+", "+o+");\n const ivec3 pads = ivec3("+t+", "+n+", "+r+");\n\n void main() {\n ivec5 coords = getOutputCoords();\n int batch = coords.x;\n int d2 = coords.u;\n\n ivec3 xFRCCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n int xFCorner = xFRCCorner.x;\n int xRCorner = xFRCCorner.y;\n int xCCorner = xFRCCorner.z;\n\n // Convolve x(?, ?, ?, d1) with w(:, :, :, d1, d2) to get\n // y(yF, yR, yC, d2). ? = to be determined. : = across all\n // values in that axis.\n float dotProd = 0.0;\n for (int wF = 0; wF < "+c+"; wF++) {\n int xF = xFCorner + wF * "+s+";\n\n if (xF < 0 || xF >= "+e.inDepth+") {\n continue;\n }\n\n for (int wR = 0; wR < "+p+"; wR++) {\n int xR = xRCorner + wR * "+u+";\n\n if (xR < 0 || xR >= "+e.inHeight+") {\n continue;\n }\n\n for (int wC = 0; wC < "+h+"; wC++) {\n int xC = xCCorner + wC * "+l+";\n\n if (xC < 0 || xC >= "+e.inWidth+") {\n continue;\n }\n\n for (int d1 = 0; d1 < "+f+"; d1 += 4) {\n vec4 xValues = vec4(\n getX(batch, xF, xR, xC, d1),\n getX(batch, xF, xR, xC, d1 + 1),\n getX(batch, xF, xR, xC, d1 + 2),\n getX(batch, xF, xR, xC, d1 + 3)\n );\n vec4 wValues = vec4(\n getW(wF, wR, wC, d1, d2),\n getW(wF, wR, wC, d1 + 1, d2),\n getW(wF, wR, wC, d1 + 2, d2),\n getW(wF, wR, wC, d1 + 3, d2)\n );\n\n dotProd += dot(xValues, wValues);\n }\n\n if ("+(1===d)+") {\n dotProd +=\n getX(batch, xF, xR, xC, "+f+") *\n getW(wF, wR, wC, "+f+", d2);\n } else if ("+(2===d)+") {\n vec2 xValues = vec2(\n getX(batch, xF, xR, xC, "+f+"),\n getX(batch, xF, xR, xC, "+f+" + 1)\n );\n vec2 wValues = vec2(\n getW(wF, wR, wC, "+f+", d2),\n getW(wF, wR, wC, "+f+" + 1, d2)\n );\n dotProd += dot(xValues, wValues);\n } else if ("+(3===d)+") {\n vec3 xValues = vec3(\n getX(batch, xF, xR, xC, "+f+"),\n getX(batch, xF, xR, xC, "+f+" + 1),\n getX(batch, xF, xR, xC, "+f+" + 2)\n );\n vec3 wValues = vec3(\n getW(wF, wR, wC, "+f+", d2),\n getW(wF, wR, wC, "+f+" + 1, d2),\n getW(wF, wR, wC, "+f+" + 2, d2)\n );\n dotProd += dot(xValues, wValues);\n }\n }\n }\n }\n setOutput(dotProd);\n }\n "},oQ=function(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"inputShape",type:"ivec3"},{name:"pad",type:"ivec2"},{name:"stride",type:"ivec2"},{name:"dilation",type:"ivec2"},{name:"inChannels",type:"int"},{name:"itemsPerBlockRow",type:"int"},{name:"outWidth",type:"int"}],this.outputShape=e,this.enableShapeUniforms=OX(this.outputShape.length);for(var n=t.dataFormat,r=fX(),a="channelsLast"===n,i=a?0:1,o=a?1:2,s=this.enableShapeUniforms?"if(blockIndex < outShape[1] && pos < outShape[0]) {":"if(blockIndex < "+e[1]+" && pos < "+e[0]+") {",u="",l=0;l<=1;l++)for(var c=0;c<=1;c++)u+="\n blockIndex = rc.y + "+c+";\n pos = rc.x + "+l+";\n\n "+s+"\n offsetY = int(blockIndex / outWidth) * stride[0] - pad[0];\n d0 = offsetY + dilation[0] * (pos / itemsPerBlockRow);\n\n if(d0 < inputShape["+i+"] && d0 >= 0) {\n // Use custom imod instead mod. On Intel GPU, mod may generate\n // unexpected value.\n // https://github.com/tensorflow/tfjs/issues/5447\n offsetX = imod(blockIndex, outWidth) * stride[1] - pad[1];\n d1 = offsetX + dilation[1] * (imod(pos, itemsPerBlockRow) /\n inChannels);\n\n if(d1 < inputShape["+o+"] && d1 >= 0) {\n\n ch = imod(pos, inChannels);\n\n if ("+a+") {\n innerDims = vec2(d1, ch);\n result["+(2*l+c)+"] = getChannel(\n getA(d0, int(innerDims.x),\n int(innerDims.y)), innerDims);\n } else {\n innerDims = vec2(d0, d1);\n result["+(2*l+c)+"] = getChannel(\n getA(ch, int(innerDims.x),\n int(innerDims.y)), innerDims);\n }\n }\n }\n }\n ";this.userCode="\n void main() {\n ivec2 rc = getOutputCoords();\n\n vec4 result = vec4(0);\n\n int blockIndex, pos, offsetY, d0, offsetX, d1, ch;\n vec2 innerDims;\n\n "+u+"\n\n "+r.output+" = result;\n }\n "};function sQ(e){var t,n=e.x,r=e.filter,a=e.convInfo,i=e.backend,o=e.bias,s=void 0===o?null:o,u=e.preluActivationWeights,l=void 0===u?null:u,c=e.leakyreluAlpha,p=void 0===c?0:c,h=e.activation,f=void 0===h?null:h,d=n.shape,m=i.texData.get(n.dataId),v=a.inChannels,g=d[0]*d[1]*d[2],y=a.outChannels,b="channelsLast"===a.dataFormat,x=[];if(!((1===g||1===y)&&v>1e3)&&m.isPacked&&b&&null!=m.texture&&d[2]%2!=0&&qv(m.shape.slice(-3),d.slice(-3))){var w=d[0]*d[1]*(d[2]+1),k={dataId:n.dataId,shape:[1,w,a.inChannels],dtype:n.dtype},N=m.shape;m.shape=m.shape.slice(),m.shape[m.shape.length-2]++,Vv(oX(m.shape,k.shape),(function(){return"packed reshape "+m.shape+" to "+k.shape+" isn't free"}));var I=TJ({inputs:{x:r},backend:i,attrs:{shape:[1,a.inChannels,a.outChannels]}});x.push(I);var S=PJ({a:k,b:I,backend:i,transposeA:false,transposeB:false,bias:s,activation:f,preluActivationWeights:l,leakyreluAlpha:p}),T=i.texData.get(S.dataId);Vv(T.isPacked,(function(){return"batchMatMul result is expected to be packed"})),m.shape=N,T.shape=a.outShape,(t=oJ({inputs:{x:S},backend:i})).shape=a.outShape,x.push(S)}else{var C=TJ({inputs:{x:n},backend:i,attrs:{shape:[1,b?d[0]*d[1]*d[2]:d[0]*d[2]*d[3],a.inChannels]}}),E=TJ({inputs:{x:r},backend:i,attrs:{shape:[1,a.inChannels,a.outChannels]}}),R=PJ({a:C,b:E,transposeA:false,transposeB:false,backend:i,bias:s,activation:f,preluActivationWeights:l,leakyreluAlpha:p});t=TJ({inputs:{x:R},backend:i,attrs:{shape:a.outShape}}),x.push(C),x.push(E),x.push(R)}for(var A=0,_=x;A<_.length;A++){var F=_[A];i.disposeIntermediateTensorInfo(F)}return t}function uQ(e){var t=e.x,n=e.filter,r=e.convInfo,a=e.backend,i=e.bias,o=void 0===i?null:i,s=e.preluActivationWeights,u=void 0===s?null:s,l=e.leakyreluAlpha,c=void 0===l?0:l,p=e.activation,h=void 0===p?null:p,f=r.filterWidth,d=r.filterHeight,m=r.inChannels,v=r.outWidth,g=r.outHeight,y="channelsLast"===r.dataFormat,b=f*d*m,x=g*v,w=[b,x],k=[],N=TJ({inputs:{x:t},backend:a,attrs:{shape:t.shape.slice(1)}}),I=TJ({inputs:{x:n},backend:a,attrs:{shape:[1,b,Hv(n.shape)/b]}});k.push(N),k.push(I);var S=new oQ(w,r),T=[N.shape,[r.padInfo.top,r.padInfo.left],[r.strideHeight,r.strideWidth],[r.dilationHeight,r.dilationWidth],[r.inChannels],[r.filterWidth*r.inChannels],[r.outWidth]],C=a.runWebGLProgram(S,[N],"float32",T),E=TJ({inputs:{x:C},backend:a,attrs:{shape:[1,w[0],w[1]]}});k.push(C),k.push(E);var R=null!=o,A=null!=u,_="leakyrelu"===h,F=h?yJ(h,!0):null,D=new bJ(E.shape,I.shape,[1,x,r.outChannels],!0,!1,R,F,A,_),O=[E,I];if(o&&O.push(o),A&&O.push(u),_){var M=a.makeTensorInfo([],"float32",Rw(c,"float32"));O.push(M),k.push(M)}var L=a.runWebGLProgram(D,O,"float32"),z=TJ({inputs:{x:L},backend:a,attrs:{shape:y?[1,g,v,r.outChannels]:[1,r.outChannels,g,v]}});k.push(L);for(var P=0,B=k;P<B.length;P++){var W=B[P];a.disposeIntermediateTensorInfo(W)}return z}var lQ={kernelName:uy,backendName:"webgl",kernelFunc:function(e){var t,n=e.inputs,r=e.backend,a=e.attrs,i=n.x,o=n.filter,s=a.strides,u=a.pad,l=a.dataFormat,c=a.dilations,p=a.dimRoundingMode,h=CS(l),f=yS(i.shape,o.shape,s,c,u,p,!1,h);if(1!==f.filterHeight||1!==f.filterWidth||1!==f.dilationHeight||1!==f.dilationWidth||1!==f.strideHeight||1!==f.strideWidth||"SAME"!==f.padInfo.type&&"VALID"!==f.padInfo.type)if(Ag().getBool("WEBGL_CONV_IM2COL")&&1===i.shape[0])t=uQ({x:i,filter:o,convInfo:f,backend:r});else{var d=new aQ(f);t=r.runWebGLProgram(d,[i,o],"float32")}else t=sQ({x:i,filter:o,convInfo:f,backend:r});var m=TJ({inputs:{x:t},backend:r,attrs:{shape:f.outShape}});return r.disposeIntermediateTensorInfo(t),m}},cQ=function(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;var t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,a=e.padInfo.left,i="channelsLast"===e.dataFormat;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+" - "+a+";\n\n if (xC < 0 || xC >= "+e.inWidth+") {\n continue;\n }\n\n if ("+i+") {\n float dyValue = getDy(b, yR, yC, d2);\n float xValue = getX(b, xR, xC, d1);\n dotProd += (xValue * dyValue);\n } else {\n float dyValue = getDy(b, d2, yR, yC);\n float xValue = getX(b, d1, xR, xC);\n dotProd += (xValue * dyValue);\n }\n\n }\n }\n }\n setOutput(dotProd);\n }\n "},pQ=function(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;var t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,i="channelsLast"===e.dataFormat,o=t-1-e.padInfo.top,s=n-1-e.padInfo.left,u=i?1:2,l=i?2:3,c=i?3:1;this.userCode="\n const ivec2 pads = ivec2("+o+", "+s+");\n\n void main() {\n ivec4 coords = getOutputCoords();\n int batch = coords[0];\n int d1 = coords["+c+"];\n\n ivec2 dyCorner = ivec2(coords["+u+"], coords["+l+"]) - 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) / "+a+".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\n if ("+i+") {\n float xValue = getDy(batch, idyR, idyC, d2);\n float wValue = getW(wRPerm, wCPerm, d1, d2);\n dotProd += xValue * wValue;\n } else {\n float xValue = getDy(batch, d2, idyR, idyC);\n float wValue = getW(wRPerm, wCPerm, d1, d2);\n dotProd += xValue * wValue;\n }\n\n }\n }\n }\n setOutput(dotProd);\n }\n "},hQ=function(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;var t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,a=e.padInfo.front,i=e.padInfo.top,o=e.padInfo.left;this.userCode="\n void main() {\n ivec5 coords = getOutputCoords();\n int wF = coords.x;\n int wR = coords.y;\n int wC = coords.z;\n int d1 = coords.w;\n int d2 = coords.u;\n\n float dotProd = 0.0;\n\n for (int b = 0; b < "+e.batchSize+"; b++) {\n for (int yF = 0; yF < "+e.outDepth+"; yF++) {\n int xF = wF + yF * "+t+" - "+a+";\n\n if (xF < 0 || xF >= "+e.inDepth+") {\n continue;\n }\n\n for (int yR = 0; yR < "+e.outHeight+"; yR++) {\n int xR = wR + yR * "+n+" - "+i+";\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 * "+r+" - "+o+";\n\n if (xC < 0 || xC >= "+e.inWidth+") {\n continue;\n }\n\n float dyValue = getDy(b, yF, yR, yC, d2);\n float xValue = getX(b, xF, xR, xC, d1);\n dotProd += (xValue * dyValue);\n }\n }\n }\n }\n setOutput(dotProd);\n }\n "},fQ=function(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;var t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,i=e.strideHeight,o=e.strideWidth,s=t-1-e.padInfo.front,u=n-1-e.padInfo.top,l=r-1-e.padInfo.left;this.userCode="\n const ivec3 pads = ivec3("+s+", "+u+", "+l+");\n\n void main() {\n ivec5 coords = getOutputCoords();\n int batch = coords.x;\n int d1 = coords.u;\n\n\n ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n int dyFCorner = dyCorner.x;\n int dyRCorner = dyCorner.y;\n int dyCCorner = dyCorner.z;\n\n float dotProd = 0.0;\n for (int wF = 0; wF < "+t+"; wF++) {\n float dyF = float(dyFCorner + wF) / "+a+".0;\n\n if (dyF < 0.0 || dyF >= "+e.outDepth+".0 || fract(dyF) > 0.0) {\n continue;\n }\n int idyF = int(dyF);\n\n int wFPerm = "+t+" - 1 - wF;\n\n for (int wR = 0; wR < "+n+"; wR++) {\n float dyR = float(dyRCorner + wR) / "+i+".0;\n\n if (dyR < 0.0 || dyR >= "+e.outHeight+".0 ||\n fract(dyR) > 0.0) {\n continue;\n }\n int idyR = int(dyR);\n\n int wRPerm = "+n+" - 1 - wR;\n\n for (int wC = 0; wC < "+r+"; wC++) {\n float dyC = float(dyCCorner + wC) / "+o+".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 = "+r+" - 1 - wC;\n\n for (int d2 = 0; d2 < "+e.outChannels+"; d2++) {\n float xValue = getDy(batch, idyF, idyR, idyC, d2);\n float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);\n dotProd += xValue * wValue;\n }\n }\n }\n }\n setOutput(dotProd);\n }\n "};var dQ={kernelName:ly,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=t.dy,o=r.strides,s=r.pad,u=r.dataFormat,l=r.dimRoundingMode,c=r.filterShape,p=CS(u),h=yS(a.shape,c,o,1,s,l,!1,p),f=new cQ(h);return n.runWebGLProgram(f,[a,i],"float32")}};var mQ={kernelName:cy,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.dy,i=t.filter,o=r.inputShape,s=r.strides,u=r.pad,l=r.dataFormat,c=r.dimRoundingMode,p=CS(l),h=yS(o,i.shape,s,1,u,c,!1,p),f=new pQ(h);return n.runWebGLProgram(f,[a,i],"float32")}};var vQ={kernelName:py,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=t.filter,o=r.strides,s=r.pad,u=r.dilations,l=bS(a.shape,i.shape,o,u,s),c=new iQ(l);return n.runWebGLProgram(c,[a,i],"float32")}};var gQ={kernelName:hy,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=t.dy,o=r.strides,s=r.pad,u=r.filterShape,l=bS(a.shape,u,o,1,s),c=new hQ(l);return n.runWebGLProgram(c,[a,i],"float32")}};var yQ={kernelName:fy,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.dy,i=t.filter,o=r.pad,s=r.strides,u=bS(r.inputShape,i.shape,s,1,o),l=new fQ(u);return n.runWebGLProgram(l,[a,i],"float32")}},bQ=vJ({opSnippet:"if (isnan(x)) return x;\n return cos(x);\n"}),xQ={kernelName:dy,backendName:"webgl",kernelFunc:bQ},wQ=vJ({opSnippet:"\n float e2x = exp(-x);\n return (e2x + 1.0 / e2x) / 2.0;\n"}),kQ={kernelName:my,backendName:"webgl",kernelFunc:wQ},NQ=function(e,t,n,r,a){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];var i=e[0],o=e[1],s=e[2],u=e[3],l=t[0],c=n[0],p=n[1];this.outputShape=[l,c,p,u];var h="bilinear"===r?1:0,f=o-1+".0",d=s-1+".0",m=c>1?[""+(o-1)/(c-1),"(y2-y1) * height_ratio","y1*"+f+" + float(y)*(height_scale)"]:["0.0","0.0","0.5 * (y1+y2) * "+f],v=m[0],g=m[1],y=m[2],b=p>1?[""+(s-1)/(p-1),"(x2-x1) * width_ratio","x1*"+d+" + float(x)*(width_scale)"]:["0.0","0.0","0.5 * (x1+x2) * "+d],x=b[0],w=b[1],k=b[2];this.userCode="\n const float height_ratio = float("+v+");\n const float width_ratio = float("+x+");\n void main() {\n ivec4 coords = getOutputCoords();\n int b = coords[0];\n int y = coords[1];\n int x = coords[2];\n int d = coords[3];\n\n // get box vals\n float y1 = getBoxes(b,0);\n float x1 = getBoxes(b,1);\n float y2 = getBoxes(b,2);\n float x2 = getBoxes(b,3);\n\n // get image in batch index\n int bInd = round(getBoxInd(b));\n if(bInd < 0 || bInd >= "+i+") {\n return;\n }\n\n float height_scale = "+g+";\n float width_scale = "+w+";\n\n float in_y = "+y+";\n if( in_y < 0.0 || in_y > "+f+" ) {\n setOutput(float("+a+"));\n return;\n }\n float in_x = "+k+";\n if( in_x < 0.0 || in_x > "+d+" ) {\n setOutput(float("+a+"));\n return;\n }\n\n vec2 sourceFracIndexCR = vec2(in_x,in_y);\n if("+h+" == 1) {\n // Compute the four integer indices.\n ivec2 sourceFloorCR = ivec2(sourceFracIndexCR);\n ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR));\n\n float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d);\n float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d);\n float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);\n float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);\n\n vec2 fracCR = sourceFracIndexCR - 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pads;\n int d2 = coords.w;\n int d1 = d2 / "+s+";\n int q = d2 - d1 * "+s+";\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 // TO DO(dsmilkov): Flatten the two for loops and vec4 the operations.\n for (int wR = 0; wR < "+i+"; wR++) {\n int xR = xRCorner + wR * dilations[0];\n\n if (xR < 0 || xR >= inDims[0]) {\n continue;\n }\n\n for (int wC = 0; wC < "+o+"; wC++) {\n int xC = xCCorner + wC * dilations[1];\n\n if (xC < 0 || xC >= inDims[1]) {\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\n float result = dotProd;\n "+c+"\n "+l+"\n setOutput(result);\n }\n "},DQ=function(e,t,n,r,a){void 0===t&&(t=!1),void 0===n&&(n=null),void 0===r&&(r=!1),void 0===a&&(a=!1),this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=OX(this.outputShape.length);for(var i=e.outChannels/e.inChannels,o=e.padInfo.left,s=e.strideWidth,u=e.dilationWidth,l=e.filterHeight,c=e.filterWidth,p=c,h="\n int xR; int xC; int xCOffset;\n vec4 wTexel; vec4 previous; vec4 final;",f=0;f<c;f++)h+="\n vec4 xTexelC"+2*f+";\n int xTexelC"+2*f+"Ready;\n vec4 xTexelC"+(2*f+1)+";\n int xTexelC"+(2*f+1)+"Ready;\n vec4 xC"+f+";";for(var d=0;d<l;d++){for(var m=0;m<c;m++)h+="\n xTexelC"+2*m+" = vec4(0.0);\n xTexelC"+2*m+"Ready = 0;\n xTexelC"+(2*m+1)+" = vec4(0.0);\n xTexelC"+(2*m+1)+"Ready = 0;\n xC"+m+" = vec4(0.0);";h+="\n xR = xRCorner + "+d+" * dilations[0];\n if (xR >=0 && xR < inDims[0]) {\n ";for(var v=0;v<(p+1)/2;v++){var g=2*v;if(h+="\n xC = xCCorner + "+g*u+";\n ",1===s){if(g<c&&(o%2==1?(h+="\n xCOffset = xC + 1;\n if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC"+g+"Ready == 0) {\n xTexelC"+g+" = getX(batch, xR, xCOffset, d1);\n\n // Need to manually clear unused channels in case\n // we're reading from recycled texture.\n if (xCOffset + 1 >= inDims[1]) {\n xTexelC"+g+".zw = vec2(0.0);\n }\n xTexelC"+g+"Ready = 1;\n }\n ",h+=1===u&&g>0?"\n xC"+g+" = vec4(xTexelC"+(g-2)+".zw, xTexelC"+g+".xy);\n ":"\n xCOffset = xC + 1 - 2;\n\n if (xCOffset >= 0 && xCOffset < inDims[1]) {\n previous = getX(batch, xR, xCOffset, d1);\n\n // Need to manually clear unused channels in case\n // we're reading from recycled texture.\n if (xCOffset + 1 >= inDims[1]) {\n previous.zw = vec2(0.0);\n }\n\n xC"+g+" = vec4(previous.zw, xTexelC"+g+".xy);\n } else {\n xC"+g+" = vec4(0.0, 0.0, xTexelC"+g+".xy);\n }\n "):h+="\n if (xC >= 0 && xC < inDims[1] && xTexelC"+g+"Ready == 0) {\n xTexelC"+g+" = getX(batch, xR, xC, d1);\n if (xC + 1 >= inDims[1]) {\n xTexelC"+g+".zw = vec2(0.0);\n }\n xTexelC"+g+"Ready = 1;\n }\n\n xC"+g+" = xTexelC"+g+";\n ",g+1<c)){var y=o%2==0?Pv(u):u;u%2==0&&o%2==1||u%2!=0&&o%2!=1?(h+="\n xCOffset = xC + imod(pads[1], 2) + "+y+";\n\n if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC"+(g+1)+"Ready == 0) {\n xTexelC"+(g+1)+" = getX(batch, xR, xCOffset, d1);\n\n // Need to manually clear unused channels in case\n // we're reading from recycled texture.\n if (xCOffset + 1 >= inDims[1]) {\n xTexelC"+(g+1)+".zw = vec2(0.0);\n }\n xTexelC"+(g+1)+"Ready = 1;\n }\n ",u>1&&(h+="\n xCOffset -= 2;\n if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC"+g+"Ready == 0) {\n xTexelC"+g+" = getX(batch, xR, xCOffset, d1);\n xTexelC"+g+"Ready = 1;\n }\n "),h+="\n xC"+(g+1)+" = vec4(xTexelC"+g+".zw, xTexelC"+(g+1)+".xy);\n "):h+=1===y?"\n xC"+(g+1)+" = xTexelC"+g+";\n ":"\n xCOffset = xC + "+y+";\n\n if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC"+(g+1)+"Ready == 0) {\n xTexelC"+(g+1)+" = getX(batch, xR, xCOffset, d1);\n if (xCOffset + 1 >= inDims[1]) {\n xTexelC"+(g+1)+".zw = vec2(0.0);\n }\n xTexelC"+(g+1)+"Ready = 1;\n }\n\n xC"+(g+1)+" = xTexelC"+(g+1)+";\n "}}else g<c&&(o%2==1?(h+="\n xCOffset = xC + 1 - strides[1];\n if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC"+g+"Ready == 0) {\n xTexelC"+g+" = getX(batch, xR, xCOffset, d1);\n // Need to manually clear unused channels in case\n // we're reading from recycled texture.\n if (xCOffset + 1 >= inDims[1]) {\n xTexelC"+g+".zw = vec2(0.0);\n }\n xTexelC"+g+"Ready = 1;\n }\n\n if(xC + 1 >= 0 && xC + 1 < inDims[1] && xTexelC"+(g+1)+"Ready == 0) {\n xTexelC"+(g+1)+" = getX(batch, xR, xC + 1, d1);\n // Need to manually clear unused channels in case\n // we're reading from recycled texture.\n if (xC + 2 >= inDims[1]) {\n xTexelC"+(g+1)+".zw = vec2(0.0);\n }\n xTexelC"+(g+1)+"Ready = 1;\n }\n\n xC"+g+" = vec4(xTexelC"+g+".zw, xTexelC"+(g+1)+".zw);\n ",g+1<c&&(h+="\n final = vec4(0.0);\n xCOffset = xC + 1 + strides[1];\n if(xCOffset >= 0 && xCOffset < inDims[1]) {\n final = getX(batch, xR, xCOffset, d1);\n }\n xC"+(g+1)+" = vec4(xTexelC"+(g+1)+".xy, final.xy);\n ")):(h+="\n if(xC >= 0 && xC < inDims[1] && xTexelC"+g+"Ready == 0) {\n xTexelC"+g+" = getX(batch, xR, xC, d1);\n if (xC + 1 >= inDims[1]) {\n xTexelC"+g+".zw = vec2(0.0);\n }\n xTexelC"+g+"Ready = 1;\n }\n\n xCOffset = xC + strides[1];\n if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC"+(g+1)+"Ready == 0) {\n xTexelC"+(g+1)+" = getX(batch, xR, xCOffset, d1);\n if (xCOffset + 1 >= inDims[1]) {\n xTexelC"+(g+1)+".zw = vec2(0.);\n }\n xTexelC"+(g+1)+"Ready = 1;\n }\n\n xC"+g+" = vec4(\n xTexelC"+g+".xy, xTexelC"+(g+1)+".xy);\n ",g+1<c&&(h+="\n xC"+(g+1)+" = vec4(xTexelC"+g+".zw, xTexelC"+(g+1)+".zw);\n ")));g<c&&(h+="\n wTexel = getW("+d+", "+g+", d1, q);\n dotProd += xC"+g+" * vec4(wTexel.xz, wTexel.xz);\n ",g+1<c&&(h+="\n wTexel = getW("+d+", "+(g+1)+", d1, q);\n dotProd += xC"+(g+1)+" * vec4(wTexel.xz, wTexel.xz);\n "))}h+="\n }\n "}var b="",x="";n&&(b=r?"vec4 activation(vec4 a) {\n vec4 b = getPreluActivationWeightsAtOutCoords();\n "+n+"\n }":a?"vec4 activation(vec4 a) {\n vec4 b = getLeakyreluAlphaAtOutCoords();\n "+n+"\n }":"vec4 activation(vec4 x) {\n "+n+"\n }",x="result = activation(result);");var w=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode="\n "+b+"\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 / "+i+";\n int q = d2 - d1 * "+i+";\n int xRCorner = xRCCorner.x;\n int xCCorner = xRCCorner.y;\n\n //intialize dotProd with a small epsilon seems to reduce GPU accuracy loss.\n vec4 dotProd = vec4(0.000000000000001);\n\n "+h+"\n\n vec4 result = dotProd - vec4(0.000000000000001);\n "+w+"\n "+x+"\n setOutput(result);\n }\n "};var OQ={kernelName:xy,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=t.filter,o=r.strides,s=r.pad,u=r.dilations,l=r.dimRoundingMode,c=u;null==c&&(c=[1,1]),Vv(TS(o,c),(function(){return"Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides "+o+" and dilations '"+c+"'"}));var p,h=yS(a.shape,i.shape,o,c,s,l,!0);p=Ag().getBool("WEBGL_PACK_DEPTHWISECONV")&&h.strideWidth<=2&&h.outChannels/h.inChannels==1?new DQ(h):new FQ(h);var f=[[h.padInfo.top,h.padInfo.left],[h.strideHeight,h.strideWidth],[h.dilationHeight,h.dilationWidth],[h.inHeight,h.inWidth]];return n.runWebGLProgram(p,[a,i],"float32",f)}},MQ=function(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;var t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,a=e.padInfo.left,i=e.outChannels/e.inChannels;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 dm = coords.w;\n int d2 = d1 * "+i+" + dm;\n\n float dotProd = 0.0;\n\n // TO DO: Vec4 over the batch size\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+" - "+a+";\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 "},LQ=function(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;var t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,i=t-1-e.padInfo.top,o=n-1-e.padInfo.left,s=e.outChannels/e.inChannels;this.userCode="\n const ivec2 pads = ivec2("+i+", "+o+");\n\n void main() {\n ivec4 coords = getOutputCoords();\n int batch = coords[0];\n int d1 = coords[3];\n ivec2 dyCorner = coords.yz - pads;\n int dyRCorner = dyCorner.x;\n int dyCCorner = dyCorner.y;\n\n float dotProd = 0.0;\n\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; 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j <= "+o+"; j++) {\n int idx = d + j;\n if (idx >= 0 && idx <= "+s+") {\n float z = getX(b, r, c, idx);\n sum += z * z;\n }\n }\n float val = x * "+i+";\n setOutput(val);\n }\n "},n0=function(e,t,n,r,a){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;var i,o=t,s=e[3]-1;this.outputShape=e;var u="float("+n+") + float("+r+") * sum";i=.5===a?"inversesqrt("+u+")":1===a?"1.0/("+u+")":"exp(log("+u+") * float(-"+a+"));",this.userCode="\n void main() {\n ivec4 coords = getOutputCoords();\n int b = coords.x;\n int r = coords.y;\n int c = coords.z;\n int d = coords.w;\n\n bool hasNextCol = d < "+this.outputShape[3]+";\n bool hasNextRow = c < "+this.outputShape[2]+";\n\n vec4 sum = vec4(0.);\n vec4 xFragAtOutputCoords = getX(b, r, c, d);\n\n vec4 xAtOutputCoords = vec4(\n getChannel(xFragAtOutputCoords, vec2(c, d)),\n hasNextCol ?\n getChannel(xFragAtOutputCoords, vec2(c, d + 1)) : 0.0,\n hasNextRow ?\n getChannel(xFragAtOutputCoords , vec2(c + 1, d)) : 0.0,\n (hasNextRow && hasNextCol) ?\n getChannel(xFragAtOutputCoords, vec2(c + 1, d + 1)) : 0.0\n );\n\n int firstChannel = d - "+o+";\n vec2 cache = vec2(0.);\n if(firstChannel >= 0){\n vec4 firstChannelFrag = getX(b, r, c, firstChannel);\n cache.x = getChannel(firstChannelFrag, vec2(c, firstChannel));\n if(hasNextRow){\n cache.y = getChannel(firstChannelFrag, vec2(c + 1, firstChannel));\n }\n }\n\n ivec2 depth = ivec2(d, d + 1);\n for (int j = - "+o+"; j <= "+o+"; j++) {\n ivec2 idx = depth + j;\n bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));\n bvec2 belowUpperBound = lessThanEqual(idx, ivec2("+s+"));\n\n bool depthInRange = aboveLowerBound.x && belowUpperBound.x;\n bool depthPlusOneInRange = aboveLowerBound.y && belowUpperBound.y;\n\n if(depthInRange || depthPlusOneInRange){\n vec4 z = vec4(0.);\n vec4 xFragAtCurrentDepth;\n z.xz = cache.xy;\n if(depthPlusOneInRange && hasNextCol){\n xFragAtCurrentDepth = idx.y != d ?\n getX(b, r, c, idx.y) : xFragAtOutputCoords;\n z.y = getChannel(xFragAtCurrentDepth, vec2(c, idx.y));\n if(hasNextRow){\n z.w = getChannel(xFragAtCurrentDepth, vec2(c + 1, idx.y));\n }\n }\n cache.xy = z.yw;\n sum += z * z;\n }\n }\n vec4 result = xAtOutputCoords * "+i+";\n setOutput(result);\n }\n "},r0={kernelName:ub,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=r.depthRadius,o=r.bias,s=r.alpha,u=r.beta,l=Ag().getBool("WEBGL_PACK_NORMALIZATION")?new n0(a.shape,i,o,s,u):new t0(a.shape,i,o,s,u);return n.runWebGLProgram(l,[a],a.dtype)}},a0=function(e,t,n,r,a){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=n,this.alpha=r,this.beta=a,this.userCode="\n void main() {\n ivec4 coords = getOutputCoords();\n int b = coords[0];\n int r = coords[1];\n int c = coords[2];\n\n float result = 0.0;\n for (int d = 0; d < "+this.depth+"; ++d) {\n int depthBegin = int(max(0.0, float(d - "+t+")));\n int depthEnd = int(min(float("+this.depth+"),\n float(d + "+t+" + 1)));\n\n const int MIN_DEPTH_BEGIN = 0;\n const int MAX_DEPTH_END = "+this.depth+";\n\n float norm = 0.0;\n for (int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k) {\n if (k < depthBegin){\n continue;\n }\n else if (k >= depthBegin && k < depthEnd) {\n norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k);\n }\n else {\n break;\n }\n }\n\n norm = float("+r+") * norm + float("+n+");\n\n for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){\n if (k < depthBegin){\n continue;\n }\n else if (k >= depthBegin && k < depthEnd){\n float dyi = -2.0 * float("+r+")\n * float("+a+")\n * getInputImage(b ,r ,c, k) * getOutputImage(b, r, c, d)\n / norm;\n if (k == d) {\n dyi += pow(norm, -1.0 * "+a+");\n }\n if (k == coords[3]) {\n dyi *= getDy(b, r, c, d);\n result += dyi;\n }\n }\n else {\n break;\n }\n }\n }\n setOutput(result);\n }\n "},i0={kernelName:lb,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=t.y,o=t.dy,s=r.depthRadius,u=r.bias,l=r.alpha,c=r.beta,p=new a0(a.shape,s,u,l,c);return n.runWebGLProgram(p,[a,i,o],a.dtype)}};function o0(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=r.reductionIndices,o=r.keepDims,s=a.shape.length,u=Qv(i,a.shape),l=u,c=aC(l,s),p=null!=c,h=n.shouldExecuteOnCPU([a]),f=a;if(p){if(h){for(var d=n.texData.get(f.dataId).values,m=new Array(s),v=0;v<m.length;v++)m[v]=a.shape[c[v]];var g=PY(d,a.shape,a.dtype,c,m);f=n.makeTensorInfo(m,a.dtype),n.texData.get(f.dataId).values=g}else f=DJ(a,c,n);l=oC(l.length,s)}rC("max",l,s);var y,b=tC(f.shape,l),x=b[0],w=b[1],k=x;if(o&&(k=nC(x,u)),h){var N=n.texData.get(f.dataId).values,I=mY(N,Hv(w),k,a.dtype);y=n.makeTensorInfo(k,a.dtype),n.texData.get(y.dataId).values=I}else y=function(e,t,n,r){var a=Hv(t),i=TJ({inputs:{x:e},attrs:{shape:[Hv(e.shape)/a,a]},backend:r}),o=AJ(i,e.dtype,"max",r),s=TJ({inputs:{x:o},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),s}(f,w,k,n);return p&&n.disposeIntermediateTensorInfo(f),y}var s0={kernelName:cb,backendName:"webgl",kernelFunc:o0},u0=gJ({opSnippet:"\n if (isnan(a)) return a;\n if (isnan(b)) return b;\n\n return max(a, b);\n",packedOpSnippet:"\n vec4 result = vec4(max(a, b));\n vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\n \n result.r = isNaN.r > 0. ? 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Got strides "+o+" and dilations '1'"}));var l=vS(a.shape,i,o,1,s,u);if(1===l.filterWidth&&1===l.filterHeight&&qv(l.inShape,l.outShape))return oJ({inputs:{x:a},backend:n});var c=new gZ(l,"max",!1);return n.runWebGLProgram(c,[a],a.dtype)}};var p0={kernelName:db,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=r.filterSize,o=r.strides,s=r.pad,u=r.dataFormat,l=r.dimRoundingMode,c=gS(a.shape,i,o,[1,1,1],s,l,u),p=new yZ(c,"max",!1);return n.runWebGLProgram(p,[a],a.dtype)}},h0=function(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;var t=e.strideHeight,n=e.strideWidth,r=e.dilationHeight,a=e.effectiveFilterHeight,i=e.effectiveFilterWidth,o=a-1-e.padInfo.top,s=i-1-e.padInfo.left,u=a*i-1;this.userCode="\n const ivec2 pads = ivec2("+o+", "+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 < "+a+";\n wR += "+r+") {\n float dyR = float(dyRCorner + wR) / "+t+".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 < "+i+"; wC++) {\n float dyC = float(dyCCorner + wC) / "+n+".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 = "+u+" - 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 * "+i+" + wC;\n float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);\n\n dotProd += dyValue * mask;\n }\n }\n setOutput(dotProd);\n }\n "},f0=function(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;var t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,a=e.dilationDepth,i=e.dilationHeight,o=e.dilationWidth,s=e.effectiveFilterDepth,u=e.effectiveFilterHeight,l=e.effectiveFilterWidth,c=s-1-e.padInfo.front,p=u-1-e.padInfo.top,h=l-1-e.padInfo.left,f=s*u*l-1;this.userCode="\n const ivec3 pads = ivec3("+c+", "+p+", "+h+");\n\n void main() {\n ivec5 coords = getOutputCoords();\n int batch = coords.x;\n int ch = coords.u;\n\n ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n int dyDCorner = dyCorner.x;\n int dyRCorner = dyCorner.y;\n int dyCCorner = dyCorner.z;\n\n // Convolve dy(?, ?, ?, ch) with pos mask(:, :, :, d) to get\n // dx(xD, xR, xC, ch).\n // ? = to be determined. : = across all values in that axis.\n float dotProd = 0.0;\n\n for (int wD = 0; wD < "+s+";\n wD += "+a+") {\n float dyD = float(dyDCorner + wD) / "+t+".0;\n\n if (dyD < 0.0 || dyD >= "+e.outDepth+".0 || fract(dyD) > 0.0) {\n continue;\n }\n int idyD = int(dyD);\n\n for (int wR = 0; wR < "+u+";\n wR += "+i+") {\n float dyR = float(dyRCorner + wR) / "+n+".0;\n\n if (dyR < 0.0 || dyR >= "+e.outHeight+".0 ||\n fract(dyR) > 0.0) {\n continue;\n }\n int idyR = int(dyR);\n\n for (int wC = 0; wC < "+l+";\n wC += "+o+") {\n float dyC = float(dyCCorner + wC) / "+r+".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(batch, idyD, idyR, idyC, ch);\n int maxPosValue = "+f+" -\n int(getMaxPos(batch, idyD, idyR, idyC, ch));\n\n // Get the current value, check it against the value from the\n // position matrix.\n int curPosValue =\n wD * "+u+" * "+l+" +\n wR * "+l+" + wC;\n float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);\n\n dotProd += dyValue * mask;\n }\n }\n }\n setOutput(dotProd);\n }\n "};var d0={kernelName:mb,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.dy,i=t.input,o=r.filterSize,s=r.strides,u=r.pad,l=r.dimRoundingMode,c=gS(i.shape,o,s,[1,1,1],u,l),p=new yZ(c,"max",!0),h=n.runWebGLProgram(p,[i],i.dtype),f=new f0(c),d=n.runWebGLProgram(f,[a,h],i.dtype);return n.disposeIntermediateTensorInfo(h),d}};var m0={kernelName:fb,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.dy,i=t.input,o=i;pX([i,t.output],"maxPoolGrad");var s=r.filterSize,u=r.strides,l=r.pad,c=r.dimRoundingMode,p=vS(o.shape,s,u,1,l,c),h=new gZ(p,"max",!0),f=n.runWebGLProgram(h,[o],o.dtype),d=new h0(p),m=n.runWebGLProgram(d,[a,f],o.dtype);return n.disposeIntermediateTensorInfo(f),m}};var v0={kernelName:vb,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.attrs,r=e.backend,a=t.x,i=n.filterSize,o=n.strides,s=n.pad,u=n.includeBatchInIndex,l=r;Vv(4===a.shape.length,(function(){return"Error in maxPool: input must be rank 4 but got rank "+a.shape.length+"."}));var c=[1,1];Vv(TS(o,c),(function(){return"Error in maxPool: Either strides or dilations must be 1. Got strides "+o+" and dilations '"+c+"'"}));var p=vS(a.shape,i,o,c,s),h=function(e,t,n,r){var a=new gZ(n,"max",!1),i=r.runWebGLProgram(a,[e],"float32");return a=new gZ(n,"max",!0,!0,t),[i,r.runWebGLProgram(a,[e],"float32")]}(a,u,p,l);return[h[0],h[1]]}};var g0={kernelName:gb,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.attrs,r=e.backend,a=t.x,i=n.keepDims,o=n.axis,s=r,u=a.shape.length,l=Qv(o,a.shape),c=l,p=aC(c,u),h=null!=p,f=s.shouldExecuteOnCPU([a]),d=[],m=a;if(h){if(f){for(var v=s.texData.get(m.dataId).values,g=new Array(u),y=0;y<g.length;y++)g[y]=a.shape[p[y]];var b=PY(v,a.shape,a.dtype,p,g);m=s.makeTensorInfo(g,a.dtype),s.texData.get(m.dataId).values=b}else m=DJ(a,p,s);d.push(m),c=oC(c.length,u)}rC("sum",c,u);var x=tC(m.shape,c),w=x[0],k=x[1],N=w;i&&(N=nC(w,l));for(var I=function(e,t,n,r){var a=Hv(t),i=TJ({inputs:{x:e},attrs:{shape:[Hv(e.shape)/a,a]},backend:r}),o=AJ(i,"float32","mean",r),s=TJ({inputs:{x:o},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),s}(m,k,N,s),S=0,T=d;S<T.length;S++){var C=T[S];s.disposeIntermediateTensorInfo(C)}return I}};var y0={kernelName:yb,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=r.axis,o=r.keepDims,s=a.shape.length,u=Qv(i,a.shape),l=u,c=aC(l,s),p=a;null!=c&&(p=LJ({inputs:{x:a},backend:n,attrs:{perm:c}}),l=oC(l.length,a.shape.length)),rC("min",l,s);var h,f=tC(p.shape,l),d=f[0],m=TJ({inputs:{x:p},backend:n,attrs:{shape:[-1,Hv(f[1])]}}),v=AJ(m,m.dtype,"min",n);return h=TJ(o?{inputs:{x:v},backend:n,attrs:{shape:nC(d,u)}}:{inputs:{x:v},backend:n,attrs:{shape:d}}),n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(v),null!=c&&n.disposeIntermediateTensorInfo(p),h}},b0=gJ({opSnippet:"\n if (isnan(a)) return a;\n if (isnan(b)) return b;\n\n return min(a, b);\n",packedOpSnippet:"\n vec4 result = vec4(min(a, b));\n vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\n \n result.r = isNaN.r > 0. ? NAN : result.r;\n result.g = isNaN.g > 0. ? NAN : result.g;\n result.b = isNaN.b > 0. ? NAN : result.b;\n result.a = isNaN.a > 0. ? NAN : result.a;\n\n return result;\n",cpuKernelImpl:gY}),x0={kernelName:bb,backendName:"webgl",kernelFunc:b0},w0=function(e,t,n){this.variableNames=["x"],this.outputShape=t.map((function(t,n){return t[0]+e[n]+t[1]}));var r=e.length,a=RX(r),i=t.map((function(e){return e[0]})).join(","),o=t.map((function(t,n){return t[0]+e[n]})).join(","),s=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r),u="reflect"===n?0:1;this.userCode=1!==r?"\n "+a+" start = "+a+"("+i+");\n "+a+" end = "+a+"("+o+");\n\n void main() {\n "+a+" outC = getOutputCoords();\n for (int i = 0; i < "+r+"; i++) {\n if (outC[i] < start[i]) {\n outC[i] = start[i] * 2 - outC[i] - "+u+";\n } else if(outC[i] >= end[i]) {\n outC[i] = (end[i] - 1) * 2 - outC[i] + "+u+";\n }\n }\n "+a+" coords = outC - start;\n setOutput(getX("+s+"));\n }\n ":"\n int start = "+i+";\n int end = "+o+";\n\n void main() {\n int outC = getOutputCoords();\n if (outC < start) {\n outC = start * 2 - outC - "+u+";\n } else if(outC >= end) {\n outC = (end - 1) * 2 - outC + "+u+";\n }\n setOutput(getX(outC - start));\n }\n "},k0=function(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((function(t,n){return t[0]+e[n]+t[1]}));var r=e.length,a=RX(r),i=t.map((function(e){return e[0]})).join(","),o=t.map((function(t,n){return t[0]+e[n]})).join(","),s=VY("rc",r),u=VY("source",r),l=s[r-1]+" < "+this.outputShape[r-1],c=1===r?"source":"vec2("+u.slice(-2).join()+")",p="reflect"===n?0:1,h="";if(1===r){var f="\n "+a+" source = rc;\n if (source < start) {\n source = start * 2 - source - "+p+";\n } else if (source >= end) {\n source = (end - 1) * 2 - source + "+p+";\n }\n source -= start;\n ";h="\n "+a+" rc = outputLoc;\n "+f+"\n result[0] = getChannel(getX("+u.join()+"), "+c+");\n "+s[r-1]+" += 1;\n if("+l+") {\n "+f+"\n result[1] = getChannel(getX("+u.join()+"), "+c+");\n }\n "}else{var d="\n "+a+" source = rc;\n "+a+" lt = "+a+"(lessThan(source, start));\n "+a+" gte = "+a+"(greaterThanEqual(source, end));\n "+a+" orig = 1 - (lt + gte);\n source = orig * source +\n lt * (start * 2 - source - "+p+") +\n gte * ((end - 1) * 2 - source + "+p+");\n source -= start;\n ";h="\n "+a+" rc = outputLoc;\n "+d+"\n result[0] = getChannel(getX("+u.join()+"), "+c+");\n "+s[r-1]+" += 1;\n if("+l+") {\n "+d+"\n result[1] = getChannel(getX("+u.join()+"), "+c+");\n }\n rc = outputLoc;\n "+s[r-2]+" += 1;\n if("+s[r-2]+" < "+this.outputShape[r-2]+") {\n "+d+"\n result[2] = getChannel(getX("+u.join()+"), "+c+");\n "+s[r-1]+" += 1;\n if("+l+") {\n "+d+"\n result[3] = getChannel(getX("+u.join()+"), "+c+");\n }\n }\n "}this.userCode="\n const "+a+" start = "+a+"("+i+");\n const "+a+" end = "+a+"("+o+");\n\n void main() {\n "+a+" outputLoc = getOutputCoords();\n vec4 result = vec4(0.);\n "+h+"\n setOutput(result);\n }\n "},N0={kernelName:xb,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=r.paddings,o=r.mode,s=Ag().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new k0(a.shape,i,o):new w0(a.shape,i,o);return n.runWebGLProgram(s,[a],a.dtype)}},I0=gJ({opSnippet:"if (b == 0.0) return NAN;\n return mod(a, b);",packedOpSnippet:"\n vec4 result = mod(a, b);\n vec4 isNaN = vec4(equal(b, vec4(0.0)));\n \n result.r = isNaN.r > 0. ? NAN : result.r;\n result.g = isNaN.g > 0. ? NAN : result.g;\n result.b = isNaN.b > 0. ? NAN : result.b;\n result.a = isNaN.a > 0. ? NAN : result.a;\n\n return result;\n"}),S0={kernelName:wb,backendName:"webgl",kernelFunc:I0},T0=function(e,t,n){this.variableNames=["probs"],this.customUniforms=[{name:"seed",type:"float"}],this.outputShape=[e,n],this.userCode="\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 "},C0=gJ({opSnippet:"\nif (a == b) {\n return 1.0;\n};\nreturn a / b;",packedOpSnippet:"\n // vec4 one = vec4(equal(a, b));\n // return one + (vec4(1.0) - one) * a / b;\n vec4 result = a / b;\n if(a.x == b.x) {\n result.x = 1.;\n }\n if(a.y == b.y) {\n result.y = 1.;\n }\n if(a.z == b.z) {\n result.z = 1.;\n }\n if(a.w == b.w) {\n result.w = 1.;\n }\n\n return result;\n",checkOutOfBounds:!0}),E0={kernelName:Cy,backendName:"webgl",kernelFunc:C0},R0="return a - b;",A0=gJ({opSnippet:R0,packedOpSnippet:R0,supportsComplex:!0,cpuKernelImpl:MY}),_0={kernelName:xx,backendName:"webgl",kernelFunc:A0};function F0(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.logits,i=Qv([r.dim],a.shape),o=o0({inputs:{x:a},backend:n,attrs:{reductionIndices:i,keepDims:!1}}),s=nC(o.shape,i),u=TJ({inputs:{x:o},backend:n,attrs:{shape:s}}),l=A0({inputs:{a:a,b:u},backend:n}),c=QQ({inputs:{x:l},backend:n}),p=OJ({inputs:{x:c},backend:n,attrs:{axis:i,keepDims:!1}}),h=TJ({inputs:{x:p},backend:n,attrs:{shape:s}}),f=C0({inputs:{a:c,b:h},backend:n});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(l),n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(h),f}var D0={kernelName:ux,backendName:"webgl",kernelFunc:F0};var O0={kernelName:kb,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.logits,i=r.numSamples,o=r.seed,s=r.normalized,u=s?a:F0({inputs:{logits:a},backend:n,attrs:{dim:a.shape.length-1}}),l=u.shape[0],c=u.shape[1],p=new T0(l,c,i),h=[[o]],f=n.runWebGLProgram(p,[u],"int32",h);return s||n.disposeIntermediateTensorInfo(u),f}},M0="return -x;";var L0={kernelName:Ib,backendName:"webgl",kernelFunc:function(e){var t,n=e.inputs,r=e.backend,a=n.x;if(r.shouldExecuteOnCPU([a])){var i=r.texData.get(a.dataId),o=bY(i.values,a.shape,a.dtype),s=o[0],u=o[1];return r.makeTensorInfo(u,a.dtype,s)}return t=Ag().getBool("WEBGL_PACK_UNARY_OPERATIONS")?new QY(a.shape,M0):new XY(a.shape,M0),r.runWebGLProgram(t,[a],a.dtype)}},z0=MR;var P0={kernelName:Tb,backendName:"webgl",kernelFunc:function(e){Ig("tf.nonMaxSuppression() in webgl locks the UI thread. 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Call tf.nonMaxSuppressionAsync() instead");var t=e.inputs,n=e.backend,r=e.attrs,a=t.boxes,i=t.scores,o=r.maxOutputSize,s=r.iouThreshold,u=r.scoreThreshold,l=r.softNmsSigma,c=n.readSync(a.dataId),p=n.readSync(i.dataId),h=V0(c,p,o,s,u,l),f=h.selectedIndices,d=h.selectedScores;return[n.makeTensorInfo([f.length],"int32",new Int32Array(f)),n.makeTensorInfo([d.length],"float32",new Float32Array(d))]}},G0=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 "},j0={kernelName:Ab,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.indices,i=r.depth,o=r.onValue,s=r.offValue,u=Hv(a.shape),l=new G0(u,i,o,s),c=TJ({inputs:{x:a},backend:n,attrs:{shape:[u]}}),p=n.runWebGLProgram(l,[c],a.dtype);n.disposeIntermediateTensorInfo(c);var h=TJ({inputs:{x:p},backend:n,attrs:{shape:[].concat(a.shape,[i])}});return n.disposeIntermediateTensorInfo(p),h}};function H0(e){var t=e.inputs,n=e.backend,r=t.x;if("complex64"===r.dtype){var a=PZ({inputs:{input:r},backend:n}),i=H0({inputs:{x:a},backend:n}),o=$Z({inputs:{input:r},backend:n}),s=H0({inputs:{x:o},backend:n}),u=uJ({inputs:{real:i,imag:s},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(s),u}return l$({attrs:{shape:r.shape,dtype:r.dtype,value:"string"===r.dtype?"":0},backend:n})}var q0={kernelName:Ax,backendName:"webgl",kernelFunc:H0};var K0={kernelName:Rb,backendName:"webgl",kernelFunc:function e(t){var n=t.inputs,r=t.backend,a=n.x;if("string"===a.dtype)throw new Error("onesLike is not supported under string dtype");if("complex64"===a.dtype){var i=PZ({inputs:{input:a},backend:r}),o=e({inputs:{x:i},backend:r}),s=$Z({inputs:{input:a},backend:r}),u=H0({inputs:{x:s},backend:r}),l=uJ({inputs:{real:o,imag:u},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),r.disposeIntermediateTensorInfo(s),r.disposeIntermediateTensorInfo(u),l}return l$({attrs:{shape:a.shape,dtype:a.dtype,value:1},backend:r})}};var X0={kernelName:_b,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs.axis;if(1===t.length)return e$({inputs:{input:t[0]},backend:n,attrs:{dim:r}});var a=t[0].shape,i=t[0].dtype;t.forEach((function(e){Uv(a,e.shape,"All tensors passed to stack must have matching shapes"),Vv(i===e.dtype,(function(){return"All tensors passed to stack must have matching dtypes"}))}));var o=[],s=nQ({inputs:t.map((function(e){var t=e$({inputs:{input:e},backend:n,attrs:{dim:r}});return o.push(t),t})),backend:n,attrs:{axis:r}});return o.forEach((function(e){return n.disposeIntermediateTensorInfo(e)})),s}},Y0=function(e,t,n){this.variableNames=["x"],this.customUniforms=[{name:"value",type:"float"}],this.outputShape=t.map((function(t,n){return t[0]+e[n]+t[1]}));var r=e.length,a=RX(r),i=t.map((function(e){return e[0]})).join(","),o=t.map((function(t,n){return t[0]+e[n]})).join(","),s=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r);this.userCode=1!==r?"\n "+a+" start = "+a+"("+i+");\n "+a+" end = "+a+"("+o+");\n\n void main() {\n "+a+" outC = getOutputCoords();\n if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {\n setOutput(value);\n } else {\n "+a+" coords = outC - start;\n setOutput(getX("+s+"));\n }\n }\n ":"\n int start = "+i+";\n int end = "+o+";\n\n void main() {\n int outC = getOutputCoords();\n if (outC < start || outC >= end) {\n setOutput(value);\n } else {\n setOutput(getX(outC - start));\n }\n }\n "},J0=function(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"value",type:"float"}],this.outputShape=t.map((function(t,n){return t[0]+e[n]+t[1]}));for(var r=e.length,a=RX(r),i=t.map((function(e){return e[0]})).join(","),o=t.map((function(t,n){return t[0]+e[n]})).join(","),s=VY("rc",r),u=VY("source",r),l=s[r-1]+" < "+this.outputShape[r-1],c=1===r?"source":"vec2("+u.slice(-2).join()+")",p=[a+" rc = outputLoc;",s[r-1]+" += 1;\n if("+l+") {\n ",1===r?"":"}\n rc = outputLoc;\n "+s[r-2]+" += 1;\n if("+s[r-2]+" < "+this.outputShape[r-2]+") {",1===r?"":" "+s[r-1]+" += 1;\n if("+l+") {"],h=1===r?"rc < start || rc >= end":"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))",f="",d=0,m=1===r?2:4;d<m;d++)f+="\n "+p[d]+"\n if ("+h+") {\n result["+d+"] = float(value);\n } else {\n "+a+" source = rc - start;\n result["+d+"] = getChannel(getX("+u.join()+"), "+c+");\n }\n ";f+=1===r?"} ":"}}",this.userCode="\n const "+a+" start = "+a+"("+i+");\n const "+a+" end = "+a+"("+o+");\n\n void main() {\n "+a+" outputLoc = getOutputCoords();\n vec4 result = vec4(0.);\n "+f+"\n setOutput(result);\n }\n "},Z0=function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=r.paddings,o=r.constantValue;if(0===Hv(a.shape))return l$({backend:n,attrs:{shape:i.map((function(e,t){return e[0]+a.shape[t]+e[1]})),value:o,dtype:a.dtype}});var s=Ag().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new J0(a.shape,i,o):new Y0(a.shape,i,o),u=[[o]];return n.runWebGLProgram(s,[a],a.dtype,u)},Q0={kernelName:Fb,backendName:"webgl",kernelFunc:Z0},$0=gJ({opSnippet:"\n if(a < 0.0 && floor(b) < b){\n return NAN;\n }\n if (b == 0.0) {\n return 1.0;\n }\n return (round(mod(b, 2.0)) != 1) ?\n pow(abs(a), b) : sign(a) * pow(abs(a), b);\n",packedOpSnippet:"\n // isModRound1 has 1 for components with round(mod(b, 2.0)) == 1, 0 otherwise.\n vec4 isModRound1 = vec4(equal(round(mod(b, 2.0)), ivec4(1)));\n vec4 multiplier = sign(a) * isModRound1 + (vec4(1.0) - isModRound1);\n vec4 result = multiplier * pow(abs(a), b);\n\n // Ensure that a^0 = 1, including 0^0 = 1 as this correspond to TF and JS\n bvec4 isExpZero = equal(b, vec4(0.0));\n result.r = isExpZero.r ? 1.0 : result.r;\n result.g = isExpZero.g ? 1.0 : result.g;\n result.b = isExpZero.b ? 1.0 : result.b;\n result.a = isExpZero.a ? 1.0 : result.a;\n\n vec4 isNaN = vec4(lessThan(a, vec4(0.0))) * vec4(lessThan(floor(b), b));\n \n result.r = isNaN.r > 0. ? NAN : result.r;\n result.g = isNaN.g > 0. ? NAN : result.g;\n result.b = isNaN.b > 0. ? NAN : result.b;\n result.a = isNaN.a > 0. ? NAN : result.a;\n\n return result;\n"}),e1={kernelName:Db,backendName:"webgl",kernelFunc:$0};var t1={kernelName:Mb,backendName:"webgl",kernelFunc:function(e){var t,n=e.inputs,r=e.backend,a=e.attrs,i=n.x,o=a.axis,s=a.keepDims,u=i.shape.length,l=[],c=Qv(o,i.shape),p=c,h=aC(p,u),f=i;if(null!=h&&(f=LJ({inputs:{x:i},backend:r,attrs:{perm:h}}),p=oC(p.length,u),l.push(f)),rC("prod",p,u),r.shouldExecuteOnCPU([f])){var d=r.texData.get(f.dataId).values,m=wY(f.shape,f.dtype,d,p),v=m.outVals,g=m.outShape,y=m.outDtype;t=r.makeTensorInfo(g,y,v)}else{var b=tC(f.shape,p),x=b[0],w=Hv(b[1]),k=TJ({inputs:{x:f},backend:r,attrs:{shape:[-1,w]}}),N=AJ(k,nk(i.dtype),"prod",r);t=TJ({inputs:{x:N},backend:r,attrs:{shape:x}}),l.push(k),l.push(N)}if(s){l.push(t);var I=nC(t.shape,c);t=TJ({inputs:{x:t},backend:r,attrs:{shape:I}})}return l.forEach((function(e){return r.disposeIntermediateTensorInfo(e)})),t}},n1=function(e){var t=e.backend,n=e.attrs,r=n.start,a=n.stop,i=n.step,o=n.dtype,s=kY(r,a,i,o);return t.makeTensorInfo([s.length],o,s)},r1={kernelName:Lb,backendName:"webgl",kernelFunc:n1},a1=vJ({opSnippet:"return 1.0 / x;"}),i1={kernelName:Pb,backendName:"webgl",kernelFunc:a1},o1=vJ({opSnippet:"if (isnan(x)) return x;\n return (x < 0.0) ? 0.0 : x;\n",packedOpSnippet:"\n vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));\n bvec4 isNaN = isnan(x);\n\n result.r = isNaN.r ? x.r : result.r;\n result.g = isNaN.g ? x.g : result.g;\n result.b = isNaN.b ? x.b : result.b;\n result.a = isNaN.a ? x.a : result.a;\n\n return result;\n"}),s1={kernelName:Bb,backendName:"webgl",kernelFunc:o1},u1=vJ({opSnippet:"if (isnan(x)) return x;\n return (x < 0.0) ? 0.0 : min(6.0, x);\n",packedOpSnippet:"\n vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));\n bvec4 isNaN = isnan(x);\n\n result.r = isNaN.r ? x.r : result.r;\n result.g = isNaN.g ? x.g : result.g;\n result.b = isNaN.b ? x.b : result.b;\n result.a = isNaN.a ? x.a : result.a;\n\n return result;\n"}),l1={kernelName:Hb,backendName:"webgl",kernelFunc:u1},c1=function(e,t,n,r,a){this.variableNames=["A"],this.outputShape=[];var i=e[0],o=e[1],s=e[2],u=e[3];this.outputShape=[i,t,n,u];var l,c=[r&&t>1?o-1:o,r&&n>1?s-1:s],p=[r&&t>1?t-1:t,r&&n>1?n-1:n];l=a?"(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":"vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode="\n const vec2 effectiveInputOverOutputRatioRC = vec2(\n "+c[0]/p[0]+",\n "+c[1]/p[1]+");\n const vec2 inputShapeRC = vec2("+o+".0, "+s+".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 = "+l+";\n\n // Compute the four integer indices.\n ivec2 sourceFloorRC = ivec2(max(sourceFracIndexRC, vec2(0.0)));\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 "},p1=function(e,t,n,r,a){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];var i=e[0],o=e[1],s=e[2],u=e[3];this.outputShape=[i,t,n,u];var l,c=[r&&t>1?o-1:o,r&&n>1?s-1:s],p=[r&&t>1?t-1:t,r&&n>1?n-1:n];l=a?"(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":"vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode="\n const vec3 effectiveInputOverOutputRatioRC = vec3(\n "+c[0]/p[0]+",\n "+c[1]/p[1]+",\n "+c[1]/p[1]+");\n const vec3 inputShapeRC = vec3("+o+".0, "+s+".0,\n "+s+".0);\n\n float getAValue(int b, int r, int c, int d) {\n return getChannel(getA(b, r, c, d), vec2(c, d));\n }\n\n void main() {\n ivec4 coords = getOutputCoords();\n int b = coords[0];\n int d = coords[3];\n // Calculate values for next column in yRC.z.\n ivec3 yRC = coords.yzz + ivec3(0, 0, 1);\n\n // Fractional source index.\n vec3 sourceFracIndexRC = "+l+";\n\n // Compute the four integer indices.\n ivec3 sourceFloorRC = ivec3(max(sourceFracIndexRC, vec3(0.0)));\n ivec3 sourceCeilRC = ivec3(\n min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));\n\n // Should we calculate next column and row elements in 2x2 packed cell.\n bool hasNextCol = d < "+(u-1)+";\n bool hasNextRow = coords.z < "+(n-1)+";\n\n // In parallel, construct four corners for all four components in\n // packed 2x2 cell.\n vec4 topLeft = vec4(\n getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d),\n hasNextCol ? getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d + 1)\n : 0.0,\n hasNextRow ? getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d)\n : 0.0,\n (hasNextRow && hasNextCol) ?\n getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d + 1) : 0.0);\n\n vec4 bottomLeft = vec4(\n getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d),\n hasNextCol ? getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d + 1)\n : 0.0,\n hasNextRow ? getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d)\n : 0.0,\n (hasNextRow && hasNextCol) ?\n getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d + 1) : 0.0);\n\n vec4 topRight = vec4(\n getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d),\n hasNextCol ? getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d + 1)\n : 0.0,\n hasNextRow ? getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d)\n : 0.0,\n (hasNextRow && hasNextCol) ?\n getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d + 1) : 0.0);\n\n vec4 bottomRight = vec4(\n getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d),\n hasNextCol ? getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d + 1)\n : 0.0,\n hasNextRow ? getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d)\n : 0.0,\n (hasNextRow && hasNextCol) ?\n getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d + 1) : 0.0);\n\n vec3 fracRC = sourceFracIndexRC - vec3(sourceFloorRC);\n\n vec4 top = mix(topLeft, topRight, fracRC.yyzz);\n vec4 bottom = mix(bottomLeft, bottomRight, fracRC.yyzz);\n vec4 newValue = mix(top, bottom, fracRC.x);\n\n setOutput(newValue);\n }\n "};var h1={kernelName:Gb,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.images,i=r.alignCorners,o=r.halfPixelCenters,s=r.size,u=s[0],l=s[1],c=Ag().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new p1(a.shape,u,l,i,o):new c1(a.shape,u,l,i,o);return n.runWebGLProgram(c,[a],"float32")}},f1=function(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;var r=t[1],a=t[2],i=e[1],o=e[2],s=[n&&i>1?r-1:r,n&&o>1?a-1:a],u=[n&&i>1?i-1:i,n&&o>1?o-1:o],l=s[0]/u[0],c=s[1]/u[1],p=1/l,h=1/c,f=2*Math.ceil(p)+2,d=2*Math.ceil(h)+2;this.userCode="\n void main() {\n ivec4 coords = getOutputCoords();\n int b = coords[0];\n int d = coords[3];\n int r = coords[1];\n int c = coords[2];\n\n float accumulator = 0.0;\n\n const float heightScale = float("+l+");\n const float widthScale = float("+c+");\n\n const float invHeightScale = float("+p+");\n const float invWidthScale = float("+h+");\n\n const int winHeight = int("+f+");\n const int winWidth = int("+d+");\n\n // Compute bounds for where in dy we will look\n float startRLerp = floor(float(r) * invHeightScale);\n int startDyR = int(startRLerp - float(winHeight / 2));\n\n float startCLerp = floor(float(c) * invWidthScale);\n int startDyC = int(startCLerp - float(winWidth / 2));\n\n // Loop over dy\n for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {\n int dyR = dyROffset + startDyR;\n\n // Guard against the window exceeding the bounds of dy\n if (dyR < 0 || dyR >= "+i+") {\n continue;\n }\n\n for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {\n int dyC = dyCOffset + startDyC;\n\n // Guard against the window exceeding the bounds of dy\n if (dyC < 0 || dyC >= "+o+") {\n continue;\n }\n\n float dxR = float(dyR) * heightScale;\n int topDxRIndex = int(floor(dxR));\n int bottomDxRIndex = int(min(ceil(dxR), "+(r-1)+".0));\n float dxRLerp = dxR - float(topDxRIndex);\n float inverseDxRLerp = 1.0 - dxRLerp;\n\n float dxC = float(dyC) * widthScale;\n int leftDxCIndex = int(floor(dxC));\n int rightDxCIndex = int(min(ceil(dxC), "+(a-1)+".0));\n float dxCLerp = dxC - float(leftDxCIndex);\n float inverseDxCLerp = 1.0 - dxCLerp;\n\n if (r == topDxRIndex && c == leftDxCIndex) {\n // topLeft\n accumulator +=\n getDy(b, dyR, dyC, d) * inverseDxRLerp * inverseDxCLerp;\n }\n\n if (r == topDxRIndex && c == rightDxCIndex) {\n // topRight\n accumulator += getDy(b, dyR, dyC, d) * inverseDxRLerp * dxCLerp;\n }\n\n if (r == bottomDxRIndex && c == leftDxCIndex) {\n // bottomLeft\n accumulator += getDy(b, dyR, dyC, d) * dxRLerp * inverseDxCLerp;\n }\n\n if (r == bottomDxRIndex && c == rightDxCIndex) {\n // bottomRight\n accumulator += getDy(b, dyR, dyC, d) * dxRLerp * dxCLerp;\n }\n }\n }\n // End loop over dy\n\n setOutput(accumulator);\n }\n "};var d1={kernelName:jb,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.images,i=t.dy,o=r.alignCorners,s=new f1(i.shape,a.shape,o);return n.runWebGLProgram(s,[i],i.dtype)}},m1=function(e,t,n,r,a){this.variableNames=["A"],this.outputShape=[];var i=e[0],o=e[1],s=e[2],u=e[3];this.outputShape=[i,t,n,u];var l,c=[r&&t>1?o-1:o,r&&n>1?s-1:s],p=[r&&t>1?t-1:t,r&&n>1?n-1:n],h=r?"0.5":"0.0";l=a?"max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":"vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode="\n const vec2 effectiveInputOverOutputRatioRC = vec2(\n "+c[0]/p[0]+",\n "+c[1]/p[1]+");\n const vec2 inputShapeRC = vec2("+o+".0, "+s+".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 = "+l+";\n\n // Compute the coordinators of nearest neighbor point.\n ivec2 sourceNearestRC = ivec2(\n min(inputShapeRC - 1.0, floor(sourceFracIndexRC + "+h+")));\n float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d);\n\n setOutput(newValue);\n }\n "},v1=function(e,t,n,r,a){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];var i=e[0],o=e[1],s=e[2],u=e[3];this.outputShape=[i,t,n,u];var l,c=[r&&t>1?o-1:o,r&&n>1?s-1:s],p=[r&&t>1?t-1:t,r&&n>1?n-1:n],h=r?"0.5":"0.0";l=a?"max((vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC, vec3(0.0))":"vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode="\n const vec3 effectiveInputOverOutputRatioRC = vec3(\n "+c[0]/p[0]+",\n "+c[1]/p[1]+",\n "+c[1]/p[1]+");\n const vec3 inputShapeRC = vec3("+o+".0, "+s+".0,\n "+s+".0);\n\n float getAValue(int b, int r, int c, int d) {\n return getChannel(getA(b, r, c, d), vec2(c, d));\n }\n\n void main() {\n ivec4 coords = getOutputCoords();\n int b = coords[0];\n int d = coords[3];\n // Calculate values for next column in yRC.z.\n ivec3 yRC = coords.yzz + ivec3(0, 0, 1);\n\n // Fractional source index.\n vec3 sourceFracIndexRC = "+l+";\n\n // Compute the coordinators of nearest neighbor point.\n ivec3 sourceNearestRC = ivec3(\n min(inputShapeRC - 1.0, floor(sourceFracIndexRC + "+h+")));\n\n // Should we calculate next column and row elements in 2x2 packed cell.\n bool hasNextCol = d < "+(u-1)+";\n bool hasNextRow = coords.z < "+(n-1)+";\n\n vec4 newValue = vec4(\n getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d),\n hasNextCol ? getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d + 1)\n : 0.0,\n hasNextRow ? getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d)\n : 0.0,\n (hasNextRow && hasNextCol) ?\n getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d + 1) : 0.0);\n\n setOutput(newValue);\n }\n "};var g1={kernelName:Vb,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.images,i=r.alignCorners,o=r.halfPixelCenters,s=r.size,u=s[0],l=s[1],c=Ag().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new v1(a.shape,u,l,i,o):new m1(a.shape,u,l,i,o);return n.runWebGLProgram(c,[a],a.dtype)}},y1=function(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;var r=t[1],a=t[2],i=e[1],o=e[2],s=[n&&i>1?r-1:r,n&&o>1?a-1:a],u=[n&&i>1?i-1:i,n&&o>1?o-1:o],l=s[0]/u[0],c=s[1]/u[1],p=1/l,h=1/c,f=2*Math.ceil(p)+2,d=2*Math.ceil(h)+2;this.userCode="\n void main() {\n ivec4 coords = getOutputCoords();\n int b = coords[0];\n int d = coords[3];\n int r = coords[1];\n int c = coords[2];\n\n float accumulator = 0.0;\n\n const float heightScale = float("+l+");\n const float widthScale = float("+c+");\n\n const float invHeightScale = float("+p+");\n const float invWidthScale = float("+h+");\n\n const int winHeight = int("+f+");\n const int winWidth = int("+d+");\n\n // Compute bounds for where in dy we will look\n float startRLerp = floor(float(r) * invHeightScale);\n int startDyR = int(floor(startRLerp - float(winHeight / 2)));\n\n float startCLerp = floor(float(c) * invWidthScale);\n int startDyC = int(floor(startCLerp - float(winWidth / 2)));\n\n // Loop over dy\n for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {\n int dyR = dyROffset + startDyR;\n\n // Guard against the window exceeding the bounds of dy\n if (dyR < 0 || dyR >= "+i+") {\n continue;\n }\n\n for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {\n int dyC = dyCOffset + startDyC;\n\n // Guard against the window exceeding the bounds of dy\n if (dyC < 0 || dyC >= "+o+") {\n continue;\n }\n\n float sourceFracRow =\n float("+s[0]+") *\n (float(dyR) / float("+u[0]+"));\n\n float sourceFracCol =\n float("+s[1]+") *\n (float(dyC) / float("+u[1]+"));\n\n int sourceNearestRow = int(min(\n float(int("+r+") - 1),\n "+n+" ? float(round(sourceFracRow)) :\n float(floor(sourceFracRow))));\n\n int sourceNearestCol = int(min(\n float(int("+a+") - 1),\n "+n+" ? float(round(sourceFracCol)) :\n float(floor(sourceFracCol))));\n\n if (r == sourceNearestRow && c == sourceNearestCol) {\n accumulator += getDy(b, dyR, dyC, d);\n }\n }\n }\n // End loop over dy\n\n setOutput(accumulator);\n }\n "};var b1={kernelName:Ub,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.images,i=t.dy,o=r.alignCorners,s=new y1(i.shape,a.shape,o);return n.runWebGLProgram(s,[i],i.dtype)}},x1=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 r=e.map((function(n,r){return function(n){return-1!==t.indexOf(n)&&1!==e[n]?e[n]+" - coords["+n+"] - 1":"coords["+n+"]"}(r)})).join(","),a=RX(n);this.userCode="\n void main() {\n "+a+" coords = getOutputCoords();\n setOutput(getX("+r+"));\n }\n "}else this.userCode="\n void main() {\n int coord = getOutputCoords();\n setOutput(getX("+e[0]+" - coord - 1));\n }\n "},w1=function(e,t){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;var n=e.length;if(n>4)throw new Error("WebGL backend: Reverse of rank-"+n+" tensor is not yet supported");this.outputShape=e;var r=VY("rc",n),a=r[n-1]+" + 1 < "+this.outputShape[n-1],i=r[n-2]+" + 1 < "+this.outputShape[n-2],o=RX(n);function s(n){var r=e.map((function(r,a){return function(n,r){return-1!==t.indexOf(n)&&1!==e[n]?e[n]+" - "+r[n]+" - 1":""+r[n]}(a,n)}));return"getChannel(getX("+r.join(",")+"), vec2("+r.slice(-2).join(",")+"))"}this.userCode=1===n?"\n void main(){\n int rc = getOutputCoords();\n vec4 result = vec4(0.);\n result.r = getChannel(getX("+e[0]+" - rc - 1),\n "+e[0]+" - rc - 1);\n if("+a+"){\n result.g = getChannel(getX("+e[0]+" - (rc + 1) - 1),\n "+e[0]+" - (rc + 1) - 1);\n }\n setOutput(result);\n }\n ":"\n void main() {\n "+o+" rc = getOutputCoords();\n vec4 result = vec4(0.);\n result.r = "+function(e){return s(e)}(r.slice())+";\n if("+a+"){\n result.g = "+function(e){return e[n-1]="("+e[n-1]+" + 1)",s(e)}(r.slice())+";\n }\n if("+i+") {\n result.b = "+function(e){return e[n-2]="("+e[n-2]+" + 1)",s(e)}(r.slice())+";\n if("+a+") {\n result.a = "+function(e){return e[n-1]="("+e[n-1]+" + 1)",e[n-2]="("+e[n-2]+" + 1)",s(e)}(r.slice())+";\n }\n }\n setOutput(result);\n }\n "};var k1={kernelName:qb,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=r.dims,o=a.shape.length,s=Qv(i,a.shape);if(0===o)return oJ({inputs:{x:a},backend:n});var u=Ag().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new w1(a.shape,s):new x1(a.shape,s);return n.runWebGLProgram(u,[a],a.dtype)}},N1=function(e,t){this.variableNames=["Image"],this.outputShape=[],this.customUniforms=[{name:"params",type:"vec4"}];var n=e[1],r=e[2];this.outputShape=e;var a="";a="number"==typeof t?"float outputValue = "+t.toFixed(2)+";":"\n vec3 fill = vec3("+t.join(",")+");\n float outputValue = fill[coords[3]];",this.userCode="\n void main() {\n ivec4 coords = getOutputCoords();\n int x = coords[2];\n int y = coords[1];\n float coordXFloat = (float(x) - params[0]) * params[3] -\n (float(y) - params[1]) * params[2];\n float coordYFloat = (float(x) - params[0]) * params[2] +\n (float(y) - params[1]) * params[3];\n int coordX = int(round(coordXFloat + params[0]));\n int coordY = int(round(coordYFloat + params[1]));\n "+a+"\n if(coordX >= 0 && coordX < "+r+" && coordY >= 0 && coordY < "+n+") {\n outputValue = getImage(coords[0], coordY, coordX, coords[3]);\n }\n setOutput(outputValue);\n }\n "},I1={kernelName:Dx,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.attrs,r=e.backend,a=t.image,i=n.radians,o=n.fillValue,s=n.center,u=r,l=new N1(a.shape,o),c=GA(s,a.shape[1],a.shape[2]),p=[[c[0],c[1],Math.sin(i),Math.cos(i)]];return u.runWebGLProgram(l,[a],a.dtype,p)}},S1=vJ({opSnippet:"\n // OpenGL ES does not support round function.\n // The algorithm is based on banker's rounding.\n float base = floor(x);\n if ((x - base) < 0.5) {\n return floor(x);\n } else if ((x - base) > 0.5) {\n return ceil(x);\n } else {\n if (mod(base, 2.0) == 0.0) {\n return base;\n } else {\n return base + 1.0;\n }\n }\n"}),T1={kernelName:Kb,backendName:"webgl",kernelFunc:S1},C1=vJ({opSnippet:"return inversesqrt(x);",cpuKernelImpl:NY}),E1={kernelName:Xb,backendName:"webgl",kernelFunc:C1},R1=function(e,t,n,r,a,i,o){void 0===o&&(o=!0),this.variableNames=["updates","indices","defaultValue"],this.outputShape=i;var s=RX(a.length),u=RX(i.length),l="";1===n?l="i":2===n&&(l="i, j");var c="getIndices("+l+")",p="";1===r?p="i":2===r&&(p="i, coords[1]");var h="getUpdates("+p+")",f=t>1?"strides[j]":"strides";this.userCode="\n "+s+" strides = "+s+"("+a+");\n\n void main() {\n "+u+" coords = getOutputCoords();\n float sum = 0.0;\n bool found = false;\n for (int i = 0; i < "+e+"; i++) {\n int flattenedIndex = 0;\n for (int j = 0; j < "+t+"; j++) {\n int index = round("+c+");\n flattenedIndex += index * "+f+";\n }\n if (flattenedIndex == coords[0]) {\n sum += "+h+";\n found = true;\n }\n }\n setOutput(mix(getDefaultValue(), sum, float(found)));\n }\n "};var A1={kernelName:Yb,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.indices,i=t.updates,o=r.shape,s=dI(0,a,o),u=s.sliceRank,l=s.numUpdates,c=s.sliceSize,p=s.strides,h=s.outputSize,f=[h/c,c];if(0===h)return n.makeTensorInfo(o,a.dtype);var d=TJ({inputs:{x:a},backend:n,attrs:{shape:[l,u]}}),m=TJ({inputs:{x:i},backend:n,attrs:{shape:[l,c]}}),v=n.makeTensorInfo([],"float32",new Float32Array([0])),g=new R1(l,u,d.shape.length,m.shape.length,p,f),y=n.runWebGLProgram(g,[m,d,v],m.dtype),b=TJ({inputs:{x:y},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(v),b}},_1=function(e,t,n){var r,a;if(this.variableNames=["c","a","b"],this.outputShape=t,n>4)throw Error("Where for rank "+n+" is not yet supported");if(1===n)a="resRC",r="resRC";else{for(var i=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[],s=[],u=0;u<t.length;u++)s.push(""+i[u]),u<e&&o.push(""+i[u]);r=o.join(),a=s.join()}var l=RX(n);this.userCode="\n void main() {\n "+l+" resRC = getOutputCoords();\n float cVal = getC("+r+");\n if (cVal >= 1.0) {\n setOutput(getA("+a+"));\n } else {\n setOutput(getB("+a+"));\n }\n }\n "};var F1={kernelName:Jb,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=t.condition,a=t.t,i=t.e,o=new _1(r.shape.length,a.shape,a.shape.length);return n.runWebGLProgram(o,[r,a,i],tk(a.dtype,i.dtype))}},D1=vJ({opSnippet:"\n // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.\n // see: https://arxiv.org/abs/1706.02515\n float scaleAlpha = 1.7580993408473768;\n float scale = 1.0507009873554805;\n return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);\n"}),O1={kernelName:Zb,backendName:"webgl",kernelFunc:D1},M1="return 1.0 / (1.0 + exp(-1.0 * x));",L1=vJ({opSnippet:M1,packedOpSnippet:M1,cpuKernelImpl:IY}),z1={kernelName:nx,backendName:"webgl",kernelFunc:L1},P1=vJ({opSnippet:"\n if (isnan(x)) { return 0.0; }\n return sign(x);\n"}),B1={kernelName:tx,backendName:"webgl",kernelFunc:P1},W1=vJ({opSnippet:"if (isnan(x)) return x;\n return sin(x);\n"}),V1={kernelName:$b,backendName:"webgl",kernelFunc:W1},U1=vJ({opSnippet:"\n float e2x = exp(x);\n return (e2x - 1.0 / e2x) / 2.0;\n"}),G1={kernelName:ex,backendName:"webgl",kernelFunc:U1},j1=vJ({opSnippet:"\n float epsilon = 1.1920928955078125e-7;\n float threshold = log(epsilon) + 2.0;\n\n bool too_large = x > -threshold;\n bool too_small = x < threshold;\n\n float result;\n float exp_x = exp(x);\n\n if (too_large){\n result = x;\n }\n else if (too_small){\n result = exp_x;\n }\n else{\n result = log(exp_x + 1.0);\n }\n return result;\n"}),H1={kernelName:rx,backendName:"webgl",kernelFunc:j1},q1={kernelName:ox,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=r.blockShape,o=r.paddings;Vv(a.shape.length<=4,(function(){return"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet"}));var s=i.reduce((function(e,t){return e*t})),u=[[0,0]];u.push.apply(u,o);for(var l=1+i.length;l<a.shape.length;++l)u.push([0,0]);var c=[],p=Z0({inputs:{x:a},backend:n,attrs:{paddings:u,constantValue:0}}),h=jA(p.shape,i,s,!1),f=HA(h.length,i.length,!1),d=qA(p.shape,i,s,!1),m=TJ({inputs:{x:p},backend:n,attrs:{shape:h}}),v=LJ({inputs:{x:m},backend:n,attrs:{perm:f}}),g=TJ({inputs:{x:v},backend:n,attrs:{shape:d}});return c.push(p),c.push(m),c.push(v),c.forEach((function(e){return n.disposeIntermediateTensorInfo(e)})),g}};var K1={kernelName:lx,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=t.indices,a=t.values,i=t.denseShape,o=t.defaultValue;if(1!==i.shape.length)throw new Error("Dense shape must be a vector, saw:\n "+i.shape);if(2!==r.shape.length)throw new Error("Indices must be a matrix, saw:\n "+r.shape);if(1!==a.shape.length)throw new Error("Values must be a vector, saw:\n "+a.shape);if(0!==o.shape.length)throw new Error("Default value must be a scalar, saw:\n "+o.shape);var s=n.readSync(r.dataId),u=n.readSync(a.dataId),l=n.readSync(i.dataId),c=n.readSync(o.dataId)[0],p=CY(s,r.shape,r.dtype,u,a.dtype,l,c),h=p[0],f=p[1],d=p[2],m=p[3],v=p[4];return[n.makeTensorInfo(f,r.dtype,h),n.makeTensorInfo([f[0]],a.dtype,d),n.makeTensorInfo([m.length],"bool",new Uint8Array(m.map((function(e){return Number(e)})))),n.makeTensorInfo([v.length],r.dtype,new Int32Array(v))]}};var X1={kernelName:cx,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=t.inputIndices,a=t.inputShape,i=t.newShape;if(2!==r.shape.length)throw new Error("Input indices should be a matrix but received shape "+r.shape);if(1!==a.shape.length)throw new Error("Input shape should be a vector but received shape "+a.shape);if(1!==i.shape.length)throw new Error("Target shape should be a vector but received shape "+i.shape);var o=Array.from(n.readSync(a.dataId)),s=n.readSync(r.dataId),u=Array.from(n.readSync(i.dataId)),l=EY(s,r.shape,r.dtype,o,u),c=l[0],p=l[1],h=l[2];return[n.makeTensorInfo(p,r.dtype,c),n.makeTensorInfo([h.length],i.dtype,new Int32Array(h))]}};var Y1={kernelName:px,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=t.data,a=t.indices,i=t.segmentIds;if(r.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(1!==a.shape.length)throw new Error("Indices should be a vector but received shape\n "+a.shape);if(1!==i.shape.length)throw new Error("Segment ids should be a vector but received shape\n "+i.shape);var o=n.readSync(r.dataId),s=n.readSync(a.dataId),u=n.readSync(i.dataId),l=RY(o,r.shape,r.dtype,s,u,!0),c=l[0],p=l[1];return n.makeTensorInfo(p,r.dtype,c)}};var J1={kernelName:hx,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=t.data,a=t.indices,i=t.segmentIds;if(r.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(1!==a.shape.length)throw new Error("Indices should be a vector but received shape\n "+a.shape);if(1!==i.shape.length)throw new Error("Segment ids should be a vector but received shape\n "+i.shape);var o=n.readSync(r.dataId),s=n.readSync(a.dataId),u=n.readSync(i.dataId),l=RY(o,r.shape,r.dtype,s,u),c=l[0],p=l[1];return n.makeTensorInfo(p,r.dtype,c)}};var Z1={kernelName:fx,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.sparseIndices,i=t.sparseValues,o=t.defaultValue,s=r.outputShape,u=dI(0,a,s),l=u.sliceRank,c=u.numUpdates,p=u.strides,h=u.outputSize,f=new R1(c,l,a.shape.length,i.shape.length,p,[h,1],!1),d=n.runWebGLProgram(f,[i,a,o],i.dtype),m=TJ({inputs:{x:d},backend:n,attrs:{shape:s}});return n.disposeIntermediateTensorInfo(d),m}};var Q1={kernelName:sx,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=r.numOrSizeSplits,o=Qv(r.axis,a.shape)[0],s=b_(a,i,o),u=a.shape.length,l=new Array(u).fill(0),c=a.shape.slice();return s.map((function(e){var t=[].concat(c);t[o]=e;var r=FZ({inputs:{x:a},backend:n,attrs:{begin:l,size:t}});return l[o]+=e,r}))}},$1="return sqrt(x);",e2=vJ({opSnippet:$1,packedOpSnippet:$1,cpuKernelImpl:AY}),t2={kernelName:ax,backendName:"webgl",kernelFunc:e2},n2={kernelName:mx,backendName:"webgl",kernelFunc:vJ({opSnippet:"return x * x;"})},r2="return (a - b) * (a - b);",a2=gJ({opSnippet:r2,packedOpSnippet:r2}),i2={kernelName:dx,backendName:"webgl",kernelFunc:a2};var o2={kernelName:_x,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.attrs,r=e.backend,a=t.x,i=YY+"\n return x > 0.0 ? 1.0 : float("+n.alpha+");\n ",o=new XY(a.shape,i);return r.runWebGLProgram(o,[a],a.dtype)}},s2=function(e,t,n){this.variableNames=["x"],this.outputShape=n;var r=n.length,a=RX(n.length),i=RX(n.length),o="";if(1===r)o="coords * strides + begin";else{var s=0;o=n.map((function(e,t){return s++,1===n.length?"coords * strides["+t+"] + begin["+t+"]":"coords["+(s-1)+"] * strides["+t+"] + begin["+t+"]"})).join(",")}this.userCode="\n "+a+" begin = "+a+"("+e+");\n "+a+" strides = "+a+"("+t+");\n\n void main() {\n "+i+" coords = getOutputCoords();\n setOutput(getX("+o+"));\n }\n "};var u2={kernelName:vx,backendName:"webgl",kernelFunc:function(e){var t,n=e.inputs,r=e.backend,a=e.attrs,i=n.x,o=a.begin,s=a.end,u=a.strides,l=a.beginMask,c=a.endMask,p=a.ellipsisMask,h=a.newAxisMask,f=a.shrinkAxisMask,d=_I(i.shape,o,s,u,l,c,p,h,f),m=d.nonStrided,v=d.$begin,g=d.$strides,y=d.size,b=d.newShape,x=d.outShape,w=TJ({inputs:{x:i},backend:r,attrs:{shape:b}});if(m){var k=FZ({inputs:{x:w},backend:r,attrs:{begin:v,size:y}});t=TJ({inputs:{x:k},backend:r,attrs:{shape:x}}),r.disposeIntermediateTensorInfo(k)}else if(x.some((function(e){return 0===e})))t=r.makeTensorInfo(x,i.dtype,[]);else{if(r.shouldExecuteOnCPU([w])){var N=r.texData.get(w.dataId).values,I=AN(w.shape,w.dtype,N),S=_Y(x,I,g,v);t=r.makeTensorInfo(x,w.dtype,S.values)}else{var T=new s2(v,g,x);t=r.runWebGLProgram(T,[w],w.dtype)}}var C=TJ({inputs:{x:t},backend:r,attrs:{shape:x}});return r.disposeIntermediateTensorInfo(w),r.disposeIntermediateTensorInfo(t),C}};var l2={kernelName:gx,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=r.separator,i=r.nGramWidths,o=r.leftPad,s=r.rightPad,u=r.padWidth,l=r.preserveShortSequences,c=t.data,p=t.dataSplits,h=n.readSync(c.dataId),f=n.readSync(p.dataId),d=FY(h,f,a,i,o,s,u,l),m=d[0],v=d[1];return[n.makeTensorInfo([m.length],"string",m),n.makeTensorInfo(p.shape,"int32",v)]}};var c2={kernelName:yx,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs.skipEmpty,a=t.input,i=t.delimiter;if("string"!==a.dtype)throw new Error("Input must be of datatype string");if(1!==a.shape.length)throw new Error("Input must be a vector, got shape: "+a.shape);if(0!==i.shape.length)throw new Error("Delimiter must be a scalar, got shape: "+i.shape);var o=n.readSync(a.dataId),s=n.readSync(i.dataId)[0],u=DY(o,s,r),l=u[0],c=u[1],p=u[2],h=c.length;return[n.makeTensorInfo([h,2],"int32",l),n.makeTensorInfo([h],"string",c),n.makeTensorInfo([2],"int32",new Int32Array(p))]}};var p2={kernelName:bx,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs.numBuckets,a=t.input;if("string"!==a.dtype)throw new Error("Input must be of datatype string");if(r<=0)throw new Error("Number of buckets must be at least 1");var i=n.readSync(a.dataId),o=OY(i,r);return n.makeTensorInfo(a.shape,"int32",o)}},h2=vJ({opSnippet:"return tan(x);"}),f2={kernelName:wx,backendName:"webgl",kernelFunc:h2},d2=vJ({opSnippet:"\n float e2x = exp(-2.0 * abs(x));\n return sign(x) * (1.0 - e2x) / (1.0 + e2x);\n"}),m2=function(e,t){this.variableNames=["A"];for(var n=new Array(e.length),r=0;r<n.length;r++)n[r]=e[r]*t[r];this.outputShape=n,this.rank=n.length;var a=RX(this.rank),i=function(e){var t=e.length;if(t>5)throw Error("Tile for rank "+t+" is not yet supported");if(1===t)return"imod(resRC, "+e[0]+")";for(var n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],r=[],a=0;a<e.length;a++)r.push("imod("+n[a]+", "+e[a]+")");return r.join()}(e);this.userCode="\n void main() {\n "+a+" resRC = getOutputCoords();\n setOutput(getA("+i+"));\n }\n "};function v2(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=r.reps;if("string"===a.dtype||a.shape.length>5){var o=n.readSync(a.dataId),s="string"===a.dtype?o.map((function(e){return Ow(e)})):o,u=AN(a.shape,a.dtype,s),l=LY(u,i);return n.makeTensorInfo(l.shape,l.dtype,l.values)}var c=new m2(a.shape,i);return n.runWebGLProgram(c,[a],a.dtype)}var g2=function(e){this.variableNames=["x","indices"],this.customUniforms=[{name:"n",type:"int"},{name:"firstPass",type:"int"},{name:"negativeInf",type:"float"},{name:"dir",type:"int"},{name:"inc",type:"int"}],this.outputShape=e,this.userCode="\n void main() {\n ivec2 coords = getOutputCoords();\n int batch = coords[0];\n int elemIdx = coords[1];\n\n // We compare elements pair-wise within a group of size 2 * inc.\n // The comparing rule for each group alternates between ascending\n // and descending. Within each group, we compare each pair at\n // positions i and i+inc. To decide whether an element at position i\n // is x0 or x1, we mod it by 2 * inc, if the result is smaller than\n // inc, it is in the first half of the group, we denote it as x0,\n // otherwise we denote it as x1.\n // For example, as shown in the Bitonic top K paper referenced above,\n // Figure5(a) shows that element[1] is in the\n // second half of the group when group size is 2, but it is in the\n // first half of the group when group size is 4.\n\n bool isFirstInPair = imod(elemIdx, 2 * inc) < inc;\n int i = isFirstInPair ? elemIdx : elemIdx - inc;\n\n int i0 = firstPass == 1 ? i : int(getIndices(batch, i));\n int i1 = firstPass == 1 ? i + inc : int(getIndices(batch, i + inc));\n float x0 = i0 < n ? getX(batch, i0) : negativeInf;\n float x1 = i1 < n ? getX(batch, i1) : negativeInf;\n\n // Denotes which direction indices are in (ascending or descending).\n bool reverse = imod(elemIdx, 2 * dir) >= dir;\n bool isGreater = x0 > x1 || (x0 == x1 && i1 > i0);\n if (reverse == isGreater) { // Elements in opposite order of direction\n int iTemp = i0;\n i0 = i1;\n i1 = iTemp;\n }\n if (isFirstInPair) {\n setOutput(float(i0));\n } else {\n setOutput(float(i1));\n }\n }\n "},y2=function(e){this.variableNames=["x","indices"],this.customUniforms=[{name:"n",type:"int"},{name:"firstPass",type:"int"},{name:"k",type:"int"}],this.outputShape=e,this.userCode="\n void main() {\n // Takes max of indices (0, k), (1, k + 1), (2, k + 2) ...\n ivec2 coords = getOutputCoords();\n int batch = coords[0];\n int elemIdx = coords[1];\n\n // The output size is half of the previous size.\n // If the previous sequence is | | | | _ _ _ _ | | | | _ _ _ _ (k=4),\n // we only need to output the indices at positions |, the indices at\n // positions _ can be thrown away, see Figure5(b) After Phase 2\n // (Merge phase) in the Bitonic Top K paper referenced above.\n // For example, the paper shows we only need to output the orange bars.\n // The output sequence should look like this | | | | | | | |.\n // Because the sequence is halved, to map the output index back\n // to the previous sequence to find the corresponding value,\n // we need to double the index. When we double the index,\n // we basically interpolate a position, so 2i looks like\n // | _ | _ | _ | _ | _ | _ | _. We move the | to the first k position\n // of each 2k positions by - elemIdx % k. E.g. for output at\n // index 4,5,6,7, we want to get the corresponding element at\n // original index 8,9,10,11, for output at index 8,9,10,11,\n // we want to get the corresponding element at original index\n // 16,17,18,19, so on and so forth.\n\n int i = elemIdx < k ? elemIdx : (elemIdx * 2 - imod(elemIdx, k));\n int i0 = firstPass == 1 ? i : int(getIndices(batch, i));\n int i1 = firstPass == 1 ? i + k : int(getIndices(batch, i + k));\n\n float x0 = getX(batch, i0);\n float x1 = i1 < n ? getX(batch, i1) : x0;\n\n setOutput(x0 >= x1 ? float(i0) : float(i1));\n }\n "};function b2(e,t){null!==t&&e.disposeIntermediateTensorInfo(t)}function x2(e){for(var t=1;t<e;)t*=2;return t}var w2=function(e,t,n,r,a,i){this.variableNames=["Image","Transforms"],this.outputShape=i;var o,s="nearest"===n?1:2;switch(r){case"constant":o=1;break;case"reflect":o=2;break;case"wrap":o=3;break;case"nearest":o=4;break;default:o=1}this.userCode="\n float mapCoord(float outCoord, float len) {\n float inCoord = outCoord;\n if("+o+" == 2) {\n if (inCoord < 0.0) {\n if (len <= 1.0) {\n inCoord = 0.0;\n } else {\n float sz2 = 2.0 * len;\n if (inCoord < sz2) {\n inCoord = sz2 * float(int(float(-inCoord / sz2))) +\n inCoord;\n }\n inCoord = inCoord < -len ? inCoord + sz2 : -inCoord - 1.0;\n }\n } else if (inCoord > len - 1.0) {\n if (len <= 1.0) {\n inCoord = 0.0;\n } else {\n float sz2 = 2.0 * len;\n inCoord -= sz2 * float(int(float(inCoord / sz2)));\n if (inCoord >= len) {\n inCoord = sz2 - inCoord - 1.0;\n }\n }\n }\n return clamp(inCoord, 0.0, len - 1.0);\n } else if ("+o+" == 3) {\n if (inCoord < 0.0) {\n if (len <= 1.0) {\n inCoord = 0.0;\n } else {\n float sz = len - 1.0;\n inCoord += len * (float(int(float(-inCoord / sz))) + 1.0);\n }\n } else if (inCoord > len - 1.0) {\n if (len <= 1.0) {\n inCoord = 0.0;\n } else {\n float sz = len - 1.0;\n inCoord -= len * float(int(float(inCoord / sz)));\n }\n }\n return clamp(inCoord, 0.0, len - 1.0);\n } else if ("+o+" == 4) {\n return clamp(outCoord, 0.0, len - 1.0);\n } else {\n return outCoord;\n }\n }\n\n float readWithFillValue(int batch, int coordY, int coordX,\n int channel) {\n float outputValue;\n if (0 <= coordY && coordY < "+e+" && 0 <= coordX && coordX < "+t+") {\n outputValue = getImage(batch, coordY, coordX, channel);\n } else {\n outputValue = float("+a+");\n }\n return outputValue;\n }\n\n void main() {\n ivec4 coords = getOutputCoords();\n float outputValue;\n int batch = coords[0];\n int x = coords[2];\n int y = coords[1];\n int channel = coords[3];\n float xf = float(x);\n float yf = float(y);\n float a1 = getTransforms(batch, 0);\n float a2 = getTransforms(batch, 1);\n float a3 = getTransforms(batch, 2);\n float b1 = getTransforms(batch, 3);\n float b2 = getTransforms(batch, 4);\n float b3 = getTransforms(batch, 5);\n float c1 = getTransforms(batch, 6);\n float c2 = getTransforms(batch, 7);\n float projection = c1 * xf + c2 * yf + 1.0;\n if (projection == 0.0) {\n outputValue = float("+a+");\n } else {\n float inX = (a1 * xf + a2 * yf + a3) / projection;\n float inY = (b1 * xf + b2 * yf + b3) / projection;\n float mapX = mapCoord(inX, float("+t+"));\n float mapY = mapCoord(inY, float("+e+"));\n\n if ("+s+" == 1) {\n int coordY = int(round(mapY));\n int coordX = int(round(mapX));\n outputValue = readWithFillValue(batch, coordY, coordX,\n channel);\n } else {\n float yFloor = floor(mapY);\n float xFloor = floor(mapX);\n float yCeil = yFloor + 1.0;\n float xCeil = xFloor + 1.0;\n float valueYFloor = (xCeil - mapX) *\n readWithFillValue(batch, int(yFloor), int(xFloor), channel) +\n (mapX - xFloor) *\n readWithFillValue(batch, int(yFloor), int(xCeil), channel);\n float valueYCeil = (xCeil - mapX) *\n readWithFillValue(batch, int(yCeil), int(xFloor), channel) +\n (mapX - xFloor) *\n readWithFillValue(batch, int(yCeil), int(xCeil), channel);\n outputValue = (yCeil - mapY) * valueYFloor +\n (mapY - yFloor) * valueYCeil;\n }\n }\n setOutput(outputValue);\n }\n "};var k2=function(e,t){this.variableNames=["x","segmentIds"];var n=e.windowSize,r=e.batchSize,a=e.inSize,i=e.numSegments,o=i*Math.ceil(a/n);this.outputShape=[r,o];var s=4*Math.floor(n/4),u=n%4,l="\n sumValue += dot(values, segFilter);\n ",c="";a%n>0&&(c="\n if (inIdx < 0 || inIdx >= "+a+") {\n return initializationValue;\n }\n ");var p="";a%n>0&&(p="\n if (inIdx < 0 || inIdx >= "+a+") {\n return -1.0;\n }\n "),this.userCode="\n const float initializationValue = 0.0;\n\n float getValue(int batch, int inIdx) {\n "+c+"\n return getX(batch, inIdx);\n }\n\n float getSegmentIdAtIndex(int inIdx) {\n "+p+"\n return getSegmentIds(inIdx);\n }\n\n void main() {\n ivec2 coords = getOutputCoords();\n int batch = coords[0];\n int outIdx = coords[1];\n int inOffset = int(floor(float(outIdx) / float(\n "+i+")) * float("+n+"));\n int currentSeg = int(mod(float(outIdx), float("+i+")));\n\n float sumValue = 0.0;\n\n for (int i = 0; i < "+s+"; 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 vec4 segFilter = vec4(\n int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\n int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,\n int(getSegmentIdAtIndex(inIdx + 3)) == currentSeg ? 1 : 0\n );\n\n "+l+"\n }\n\n int inIdx = inOffset + "+s+";\n if ("+(1===u)+") {\n vec4 values = vec4(\n getValue(batch, inIdx),\n initializationValue,\n initializationValue,\n initializationValue\n );\n\n int inIdxSeg = int(getSegmentIdAtIndex(inIdx));\n\n vec4 segFilter = vec4(\n int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n 0,\n 0,\n 0\n );\n\n "+l+"\n } else if ("+(2===u)+") {\n vec4 values = vec4(\n getValue(batch, inIdx),\n getValue(batch, inIdx + 1),\n initializationValue,\n initializationValue\n );\n\n vec4 segFilter = vec4(\n int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\n 0,\n 0\n );\n\n "+l+"\n } else if ("+(3===u)+") {\n vec4 values = vec4(\n getValue(batch, inIdx),\n getValue(batch, inIdx + 1),\n getValue(batch, inIdx + 2),\n initializationValue\n );\n\n vec4 segFilter = vec4(\n int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\n int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,\n 0\n );\n\n "+l+"\n }\n setOutput(sumValue);\n }\n "};for(var 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