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ug(e)||ug(e[0])||ug(t)||ug(t[0])?GI(e,n,(function(e,t){return e==t})):GI(e,t,(function(e,t){return HI(e,t,0)}))},expectNumbersClose:jI,expectValuesInRange:function(e,t,n){for(var r=0;r<e.length;r++)if(e[r]<t||e[r]>n)throw new Error("Value out of range:"+e[r]+" low: "+t+", high: "+n)},expectArrayBuffersEqual:function(e,t){var n=new Float32Array(e),r=new Float32Array(t);if(n.length!==r.length)throw new Error("Expected ArrayBuffer to be of length "+r.length+", but it was "+n.length);for(var a=0;a<r.length;a++)if(n[a]!==r[a])throw new Error("Expected ArrayBuffer value at "+a+" to be "+r[a]+" but got "+n[a]+" instead")},encodeStrings:function e(t){for(var n=0;n<t.length;n++){var r=t[n];Array.isArray(r)?e(r):t[n]=Ow(r)}return t}},KI="3.16.0";function XI(e){Rg().getBool("DEPRECATION_WARNINGS_ENABLED")&&console.warn(e+" You can disable deprecation warnings with tf.disableDeprecationWarnings().")}function YI(){return mk}function JI(){return mk.memory()}function ZI(e,t){return mk.tidy(e,t)}function QI(e){sk(e).forEach((function(e){return e.dispose()}))}function $I(e){return mk.keep(e)}function eS(e){return mk.setBackend(e)}function tS(e,t,n){return void 0===n&&(n=1),mk.registerBackend(e,t,n)}function nS(){return mk.backend}var rS=Ek({add_:function(e,t){var n=Ik(e,"a","add"),r=Ik(t,"b","add"),a=ak(n,r),i={a:n=a[0],b:r=a[1]};return mk.runKernel(Mg,i)}});var aS=Ek({floorDiv_:function(e,t){var n=Ik(e,"a","floorDiv"),r=Ik(t,"b","floorDiv"),a=ak(n,r),i={a:n=a[0],b:r=a[1]};return mk.runKernel(Wy,i)}});var iS=Ek({div_:function(e,t){var n=Ik(e,"a","div"),r=Ik(t,"b","div"),a=ak(n,r);if(n=a[0],r=a[1],"int32"===n.dtype&&"int32"===r.dtype)return aS(n,r);var i={a:n,b:r};return mk.runKernel(Ey,i,{})}});var oS=Ek({mul_:function(e,t){var n=Ik(e,"a","mul"),r=Ik(t,"b","mul"),a=ak(n,r),i={a:n=a[0],b:r=a[1]};return mk.runKernel(Nb,i)}});var sS=Ek({abs_:function(e){var t=Ik(e,"x","abs");if("complex64"===t.dtype){var n={x:t};return mk.runKernel(iy,n)}var r={x:t};return 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s,u=TS(t),l=u[0],c=u[1];if("channelsLast"===o)s=[l,c,e[3],e[3]];else{if("channelsFirst"!==o)throw new Error("Unknown dataFormat "+o);s=[l,c,e[1],e[1]]}return NS(e,s,n,r,a,i,!1,o)}function kS(e,t,n,r,a,i,o){void 0===o&&(o="NDHWC");var s,u,l=ES(t),c=l[0],p=l[1],h=l[2];if("NDHWC"===o)u="channelsLast",s=[c,p,h,e[4],e[4]];else{if("NCDHW"!==o)throw new Error("Unknown dataFormat "+o);u="channelsFirst",s=[c,p,h,e[1],e[1]]}return IS(e,s,n,r,a,!1,u,i)}function NS(e,t,n,r,a,i,o,s){void 0===o&&(o=!1),void 0===s&&(s="channelsLast");var u=-1,l=-1,c=-1,p=-1;if("channelsLast"===s)u=e[0],l=e[1],c=e[2],p=e[3];else{if("channelsFirst"!==s)throw new Error("Unknown dataFormat "+s);u=e[0],p=e[1],l=e[2],c=e[3]}var h,f=t[0],d=t[1],m=t[3],v=TS(n),g=v[0],y=v[1],b=TS(r),x=b[0],w=b[1],k=CS(f,x),N=CS(d,w),I=function(e,t,n,r,a,i,o,s,u){var l,c,p;if("number"==typeof e){l={top:e,bottom:e,left:e,right:e,type:0===e?"VALID":"NUMBER"};var h=function(e,t,n,r,a){null==r&&(r=SS(e,t,n));var i=e[0],o=e[1],s=RS((i-t+2*r)/n+1,a),u=RS((o-t+2*r)/n+1,a);return[s,u]}([t,n],i,r,e,s);c=h[0],p=h[1]}else if("same"===e){c=Math.ceil(t/r),p=Math.ceil(n/a);var f=Math.max(0,(c-1)*r+i-t),d=Math.max(0,(p-1)*a+o-n),m=Math.floor(f/2),v=f-m,g=Math.floor(d/2);l={top:m,bottom:v,left:g,right:d-g,type:"SAME"}}else if("valid"===e)l={top:0,bottom:0,left:0,right:0,type:"VALID"},c=Math.ceil((t-i+1)/r),p=Math.ceil((n-o+1)/a);else{if("object"!=typeof e)throw Error("Unknown padding parameter: "+e);var y="channelsLast"===u?e[1][0]:e[2][0],b="channelsLast"===u?e[1][1]:e[2][1],x="channelsLast"===u?e[2][0]:e[3][0],w="channelsLast"===u?e[2][1]:e[3][1];l={top:y,bottom:b,left:x,right:w,type:0===y&&0===b&&0===x&&0===w?"VALID":"EXPLICIT"},c=RS((t-i+y+b)/r+1,s),p=RS((n-o+x+w)/a+1,s)}return{padInfo:l,outHeight:c,outWidth:p}}(a,l,c,g,y,k,N,i,s),S=I.padInfo,T=I.outHeight,E=I.outWidth,C=o?m*p:m;return"channelsFirst"===s?h=[u,C,T,E]:"channelsLast"===s&&(h=[u,T,E,C]),{batchSize:u,dataFormat:s,inHeight:l,inWidth:c,inChannels:p,outHeight:T,outWidth:E,outChannels:C,padInfo:S,strideHeight:g,strideWidth:y,filterHeight:f,filterWidth:d,effectiveFilterHeight:k,effectiveFilterWidth:N,dilationHeight:x,dilationWidth:w,inShape:e,outShape:h,filterShape:t}}function IS(e,t,n,r,a,i,o,s){void 0===i&&(i=!1),void 0===o&&(o="channelsLast");var u=-1,l=-1,c=-1,p=-1,h=-1;if("channelsLast"===o)u=e[0],l=e[1],c=e[2],p=e[3],h=e[4];else{if("channelsFirst"!==o)throw new Error("Unknown dataFormat "+o);u=e[0],h=e[1],l=e[2],c=e[3],p=e[4]}var f,d=t[0],m=t[1],v=t[2],g=t[4],y=ES(n),b=y[0],x=y[1],w=y[2],k=ES(r),N=k[0],I=k[1],S=k[2],T=CS(d,N),E=CS(m,I),C=CS(v,S),R=function(e,t,n,r,a,i,o,s,u,l,c){var p,h,f,d;if("number"==typeof e){p={top:e,bottom:e,left:e,right:e,front:e,back:e,type:0===e?"VALID":"NUMBER"};var m=function(e,t,n,r,a,i){null==a&&(a=SS(e,t,r));var o=e[0],s=e[1],u=e[2],l=RS((o-t+2*a)/r+1,i),c=RS((s-t+2*a)/r+1,i),p=RS((u-t+2*a)/r+1,i);return[l,c,p,n]}([t,n,r,1],s,1,a,e,c);h=m[0],f=m[1],d=m[2]}else if("same"===e){var v=((h=Math.ceil(t/a))-1)*a+s-t,g=((f=Math.ceil(n/i))-1)*i+u-n,y=((d=Math.ceil(r/o))-1)*o+l-r,b=Math.floor(v/2),x=v-b,w=Math.floor(g/2),k=g-w,N=Math.floor(y/2);p={top:w,bottom:k,left:N,right:y-N,front:b,back:x,type:"SAME"}}else{if("valid"!==e)throw Error("Unknown padding parameter: "+e);p={top:0,bottom:0,left:0,right:0,front:0,back:0,type:"VALID"},h=Math.ceil((t-s+1)/a),f=Math.ceil((n-u+1)/i),d=Math.ceil((r-l+1)/o)}return{padInfo:p,outDepth:h,outHeight:f,outWidth:d}}(a,l,c,p,b,x,w,T,E,C,s),A=R.padInfo,_=R.outDepth,F=R.outHeight,D=R.outWidth,O=i?g*h:g;return"channelsFirst"===o?f=[u,O,_,F,D]:"channelsLast"===o&&(f=[u,_,F,D,O]),{batchSize:u,dataFormat:o,inDepth:l,inHeight:c,inWidth:p,inChannels:h,outDepth:_,outHeight:F,outWidth:D,outChannels:O,padInfo:A,strideDepth:b,strideHeight:x,strideWidth:w,filterDepth:d,filterHeight:m,filterWidth:v,effectiveFilterDepth:T,effectiveFilterHeight:E,effectiveFilterWidth:C,dilationDepth:N,dilationHeight:I,dilationWidth:S,inShape:e,outShape:f,filterShape:t}}function SS(e,t,n,r){void 0===r&&(r=1);var a=CS(t,r);return Math.floor((e[0]*(n-1)-n+a)/2)}function TS(e){return"number"==typeof e?[e,e,e]:2===e.length?[e[0],e[1],1]:e}function ES(e){return"number"==typeof e?[e,e,e]:e}function CS(e,t){return t<=1?e:e+(e-1)*(t-1)}function RS(e,t){if(!t)return Math.trunc(e);switch(t){case"round":return Math.round(e);case"ceil":return Math.ceil(e);case"floor":return Math.floor(e);default:throw new Error("Unknown roundingMode "+t)}}function AS(e){var t=TS(e),n=t[0],r=t[1],a=t[2];return 1===n&&1===r&&1===a}function _S(e,t){return AS(e)||AS(t)}function FS(e){if("NHWC"===e)return"channelsLast";if("NCHW"===e)return"channelsFirst";throw new Error("Unknown dataFormat "+e)}function DS(e,t,n){if(null!=n){if("string"==typeof t)throw Error("Error in "+e+": pad must be an integer when using dimRoundingMode "+n+" but got pad "+t+".");if("number"==typeof t)Uv(Kv(t),(function(){return"Error in "+e+": pad must be an integer when using dimRoundingMode "+n+" but got pad "+t+"."}));else{if("object"!=typeof t)throw Error("Error in "+e+": Unknown padding parameter: "+t);t.forEach((function(t){t.forEach((function(t){Uv(Kv(t),(function(){return"Error in "+e+": pad must be an integer when using dimRoundingMode "+n+" but got pad "+t+"."}))}))}))}}}var OS=Ek({reshape_:function(e,t){var n={x:Ik(e,"x","reshape","string_or_numeric")},r={shape:t};return mk.runKernel(Wb,n,r)}});var MS=Ek({avgPool_:function(e,t,n,r,a){var i=Ik(e,"x","avgPool","float32");Uv(_S(n,1),(function(){return"Error in avgPool: Either strides or dilations must be 1. Got strides "+n+" and dilations '1'"}));var o=i,s=!1;3===i.rank&&(s=!0,o=OS(i,[1,i.shape[0],i.shape[1],i.shape[2]])),Uv(4===o.rank,(function(){return"Error in avgPool: x must be rank 4 but got rank "+o.rank+"."})),DS("avgPool",r,a);var u={x:o},l={filterSize:t,strides:n,pad:r,dimRoundingMode:a},c=mk.runKernel(qg,u,l);return c=DN(c,i.dtype),s?OS(c,[c.shape[1],c.shape[2],c.shape[3]]):c}});var LS=Ek({avgPool3d_:function(e,t,n,r,a,i){void 0===i&&(i="NDHWC");var o=Ik(e,"x","avgPool3d","float32"),s=o,u=!1;4===o.rank&&(u=!0,s=OS(o,[1,o.shape[0],o.shape[1],o.shape[2],o.shape[3]])),Uv(5===s.rank,(function(){return"Error in avgPool3d: x must be rank 5 but got rank "+s.rank+"."})),Uv("NDHWC"===i,(function(){return"Error in avgPool3d: Only NDHWC is currently supported, but got dataFormat of "+i})),DS("avgPool3d",r,a);var l={x:s},c={filterSize:t,strides:n,pad:r,dimRoundingMode:a,dataFormat:i},p=mk.runKernel(Xg,l,c);return p=DN(p,s.dtype),u?OS(p,[p.shape[1],p.shape[2],p.shape[3],p.shape[4]]):p}});var zS=Ek({concat_:function(e,t){void 0===t&&(t=0),Uv(e.length>=1,(function(){return"Pass at least one tensor to concat"}));var n=Sk(e,"tensors","concat","string_or_numeric");if("complex64"===n[0].dtype&&n.forEach((function(e){if("complex64"!==e.dtype)throw new Error("Cannot concatenate complex64 tensors with a tensor\n with dtype "+e.dtype+". ")})),1===n.length)return ON(n[0]);var r=n,a={axis:t};return mk.runKernel(oy,r,a)}});var PS=Ek({sigmoid_:function(e){var t={x:Ik(e,"x","sigmoid","float32")};return mk.runKernel(nx,t)}});var BS=Ek({slice_:function(e,t,n){var r=Ik(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 mk.runKernel(Qb,a,i)}});var WS=Ek({tanh_:function(e){var t={x:Ik(e,"x","tanh","float32")};return mk.runKernel(kx,t)}});var US=Ek({basicLSTMCell_:function(e,t,n,r,a,i){var o=Ik(e,"forgetBias","basicLSTMCell"),s=Ik(t,"lstmKernel","basicLSTMCell"),u=Ik(n,"lstmBias","basicLSTMCell"),l=Ik(r,"data","basicLSTMCell"),c=Ik(a,"c","basicLSTMCell"),p=Ik(i,"h","basicLSTMCell"),h=zS([l,p],1),f=eI(h,s),d=rS(f,u),m=d.shape[0],v=d.shape[1]/4,g=[m,v],y=BS(d,[0,0],g),b=BS(d,[0,v],g),x=BS(d,[0,2*v],g),w=BS(d,[0,3*v],g),k=rS(oS(PS(y),WS(b)),oS(c,PS(rS(o,x))));return[k,oS(WS(k),PS(w))]}});var VS=Ek({batchToSpaceND_:function(e,t,n){var r=Ik(e,"x","batchToSpaceND"),a=t.reduce((function(e,t){return e*t}));Uv(r.rank>=1+t.length,(function(){return"input rank is "+r.rank+" but should be > than blockShape.length "+t.length})),Uv(n.length===t.length,(function(){return"crops.length is "+n.length+" but should be equal to blockShape.length "+t.length})),Uv(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 mk.runKernel(Zg,i,o)}});var GS=Ek({batchNorm_:function(e,t,n,r,a,i){null==i&&(i=.001);var o,s,u=Ik(e,"x","batchNorm"),l=Ik(t,"mean","batchNorm"),c=Ik(n,"variance","batchNorm");null!=a&&(o=Ik(a,"scale","batchNorm")),null!=r&&(s=Ik(r,"offset","batchNorm")),Uv(l.rank===c.rank,(function(){return"Batch normalization gradient requires mean and variance to have equal ranks."})),Uv(null==s||l.rank===s.rank,(function(){return"Batch normalization gradient requires mean and offset to have equal ranks."})),Uv(null==o||l.rank===o.rank,(function(){return"Batch normalization gradient requires mean and scale to have equal ranks."}));var p={x:function(e){return 0===e.rank||1===e.rank?OS(e,[1,1,1,e.size]):2===e.rank?OS(e,[1,1,e.shape[0],e.shape[1]]):3===e.rank?OS(e,[1,e.shape[0],e.shape[1],e.shape[2]]):e}(u),scale:o,offset:s,mean:l,variance:c},h={varianceEpsilon:i},f=mk.runKernel(Uy,p,h);return OS(f,u.shape)}});var jS=Ek({batchNorm2d_:function(e,t,n,r,a,i){var o,s,u=Ik(e,"x","batchNorm"),l=Ik(t,"mean","batchNorm"),c=Ik(n,"variance","batchNorm");return null!=a&&(o=Ik(a,"scale","batchNorm")),null!=r&&(s=Ik(r,"offset","batchNorm")),Uv(2===u.rank,(function(){return"Error in batchNorm2D: x must be rank 2 but got rank "+u.rank+"."})),Uv(2===l.rank||1===l.rank,(function(){return"Error in batchNorm2D: mean must be rank 2 or rank 1 but got rank "+l.rank+"."})),Uv(2===c.rank||1===c.rank,(function(){return"Error in batchNorm2D: variance must be rank 2 or rank 1 but got rank "+c.rank+"."})),null!=o&&Uv(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&&Uv(2===s.rank||1===s.rank,(function(){return"Error in batchNorm2D: offset must be rank 2 or rank 1 but got rank "+s.rank+"."})),GS(u,l,c,s,o,i)}});var HS=Ek({batchNorm3d_:function(e,t,n,r,a,i){var o,s,u=Ik(e,"x","batchNorm"),l=Ik(t,"mean","batchNorm"),c=Ik(n,"variance","batchNorm");return null!=a&&(o=Ik(a,"scale","batchNorm")),null!=r&&(s=Ik(r,"offset","batchNorm")),Uv(3===u.rank,(function(){return"Error in batchNorm3D: x must be rank 3 but got rank "+u.rank+"."})),Uv(3===l.rank||1===l.rank,(function(){return"Error in batchNorm3D: mean must be rank 3 or rank 1 but got rank "+l.rank+"."})),Uv(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&&Uv(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&&Uv(3===s.rank||1===s.rank,(function(){return"Error in batchNorm3D: offset must be rank 3 or rank 1 but got rank "+s.rank+"."})),GS(u,l,c,s,o,i)}});var qS=Ek({batchNorm4d_:function(e,t,n,r,a,i){var o,s,u=Ik(e,"x","batchNorm"),l=Ik(t,"mean","batchNorm"),c=Ik(n,"variance","batchNorm");return null!=a&&(o=Ik(a,"scale","batchNorm")),null!=r&&(s=Ik(r,"offset","batchNorm")),Uv(4===u.rank,(function(){return"Error in batchNorm4D: x must be rank 4 but got rank "+u.rank+"."})),Uv(4===l.rank||1===l.rank,(function(){return"Error in batchNorm4D: mean must be rank 4 or rank 1 but got rank "+l.rank+"."})),Uv(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&&Uv(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&&Uv(4===s.rank||1===s.rank,(function(){return"Error in batchNorm4D: offset must be rank 4 or rank 1 but got rank "+s.rank+"."})),GS(u,l,c,s,o,i)}});var KS=Ek({bincount_:function(e,t,n){var r=Ik(e,"x","bincount"),a=Ik(t,"weights","bincount");Uv("int32"===r.dtype,(function(){return"Error in bincount: input dtype must be int32, but got "+r.dtype})),Uv(n>=0,(function(){return"size must be non-negative, but got "+n+"."})),Uv(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 mk.runKernel(Qg,i,o)}});var XS=Ek({broadcastArgs_:function(e,t){var n=Ik(e,"s0","broadcastArgs","int32"),r=Ik(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 mk.runKernel(ey,a)}});var YS=Ek({broadcastTo_:function(e,t){var n=Ik(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=OS(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 ON(n);var u={x:n},l={reps:o};return mk.runKernel(Nx,u,l)}});var JS=Ek({ceil_:function(e){var t={x:Ik(e,"x","ceil","float32")};return mk.runKernel(ny,t)}});var ZS=Ek({clipByValue_:function(e,t,n){var r=Ik(e,"x","clipByValue");Uv(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 mk.runKernel(ry,a,i)}});var QS=Ek({concat1d_:function(e){return zS(e,0)}});var $S=Ek({concat2d_:function(e,t){return zS(e,t)}});var eT=Ek({concat3d_:function(e,t){return zS(e,t)}});var tT=Ek({concat4d_:function(e,t){return zS(e,t)}});var nT=Ek({conv2d_:function(e,t,n,r,a,i,o){void 0===a&&(a="NHWC"),void 0===i&&(i=[1,1]);var s=Ik(e,"x","conv2d","float32"),u=Ik(t,"filter","conv2d","float32"),l=s,c=!1;3===s.rank&&(c=!0,l=OS(s,[1,s.shape[0],s.shape[1],s.shape[2]])),Uv(4===l.rank,(function(){return"Error in conv2d: input must be rank 4, but got rank "+l.rank+"."})),Uv(4===u.rank,(function(){return"Error in conv2d: filter must be rank 4, but got rank "+u.rank+"."})),DS("conv2d",r,o);var p="NHWC"===a?l.shape[3]:l.shape[1];Uv(p===u.shape[2],(function(){return"Error in conv2d: depth of input ("+p+") must match input depth for filter "+u.shape[2]+"."})),Uv(_S(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=mk.runKernel(sy,h,f);return c?OS(d,[d.shape[1],d.shape[2],d.shape[3]]):d}});var rT=Ek({conv1d_:function(e,t,n,r,a,i,o){void 0===a&&(a="NWC"),void 0===i&&(i=1);var s=Ik(e,"x","conv1d"),u=Ik(t,"filter","conv1d"),l=s,c=!1;2===s.rank&&(c=!0,l=OS(s,[1,s.shape[0],s.shape[1]])),Uv(3===l.rank,(function(){return"Error in conv1d: input must be rank 3, but got rank "+l.rank+"."})),Uv(3===u.rank,(function(){return"Error in conv1d: filter must be rank 3, but got rank "+u.rank+"."})),DS("conv1d",r,o),Uv(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]+"."})),Uv(_S(n,i),(function(){return"Error in conv1D: Either stride or dilation must be 1. Got stride "+n+" and dilation '"+i+"'"})),Uv("NWC"===a,(function(){return"Error in conv1d: got dataFormat of "+a+" but only NWC is currently supported."}));var p=OS(u,[1,u.shape[0],u.shape[1],u.shape[2]]),h=OS(l,[l.shape[0],1,l.shape[1],l.shape[2]]),f=nT(h,p,[1,n],r,"NHWC",[1,i],o);return OS(f,c?[f.shape[2],f.shape[3]]:[f.shape[0],f.shape[2],f.shape[3]])}});var aT=Ek({conv2DBackpropInput_:function(e,t,n,r,a,i,o){void 0===i&&(i="NHWC"),Uv(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=OS(t,[1,t.shape[0],t.shape[1],t.shape[2]]),s=[1,e[0],e[1],e[2]]),Uv(4===s.length,(function(){return"Error in conv2dDerInput: inShape must be length 4, but got length "+s.length+"."})),Uv(4===u.rank,(function(){return"Error in conv2dDerInput: dy must be rank 4, but got rank "+u.rank})),Uv(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];Uv(c===n.shape[2],(function(){return"Error in conv2dDerInput: depth of input ("+c+") must match input depth for filter "+n.shape[2]+"."})),Uv(p===n.shape[3],(function(){return"Error in conv2dDerInput: depth of output ("+p+") must match output depth for filter "+n.shape[3]+"."})),DS("conv2dDerInput",a,o);var h={dy:u,filter:n},f={strides:r,pad:a,dataFormat:i,dimRoundingMode:o,inputShape:s},d=mk.runKernel(ly,h,f);return l?OS(d,[d.shape[1],d.shape[2],d.shape[3]]):d}});var iT=Ek({conv2dTranspose_:function(e,t,n,r,a,i){var o=Ik(e,"x","conv2dTranspose"),s=Ik(t,"filter","conv2dTranspose");return aT(n,o,s,r,a,"NHWC",i)}});var oT=Ek({conv3d_:function(e,t,n,r,a,i){void 0===a&&(a="NDHWC"),void 0===i&&(i=[1,1,1]);var o=Ik(e,"x","conv3d"),s=Ik(t,"filter","conv3d"),u=o,l=!1;4===o.rank&&(l=!0,u=OS(o,[1,o.shape[0],o.shape[1],o.shape[2],o.shape[3]])),Uv(5===u.rank,(function(){return"Error in conv3d: input must be rank 5, but got rank "+u.rank+"."})),Uv(5===s.rank,(function(){return"Error in conv3d: filter must be rank 5, but got rank "+s.rank+"."})),Uv(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]+"."})),Uv(_S(n,i),(function(){return"Error in conv3D: Either strides or dilations must be 1. Got strides "+n+" and dilations '"+i+"'"})),Uv("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=mk.runKernel(cy,c,p);return l?OS(h,[h.shape[1],h.shape[2],h.shape[3],h.shape[4]]):h}});var sT=Ek({conv3DBackpropInput_:function(e,t,n,r,a){Uv(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=OS(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];Uv(5===i.length,(function(){return"Error in conv3dDerInput: inShape must be length 5, but got length "+i.length+"."})),Uv(5===o.rank,(function(){return"Error in conv3dDerInput: dy must be rank 5, but got rank "+o.rank})),Uv(5===n.rank,(function(){return"Error in conv3dDerInput: filter must be rank 5, but got rank "+n.rank})),Uv(u===n.shape[3],(function(){return"Error in conv3dDerInput: depth of input ("+u+") must match input depth for filter "+n.shape[3]+"."})),Uv(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=mk.runKernel(hy,c,p);return s?OS(h,[h.shape[1],h.shape[2],h.shape[3],h.shape[4]]):h}});var uT=Ek({conv3dTranspose_:function(e,t,n,r,a){var i=Ik(e,"x","conv3dTranspose"),o=Ik(t,"filter","conv3dTranspose");return sT(n,i,o,r,a)}});var lT=Ek({cos_:function(e){var t={x:Ik(e,"x","cos","float32")};return mk.runKernel(fy,t)}});var cT=Ek({cosh_:function(e){var t={x:Ik(e,"x","cosh","float32")};return mk.runKernel(dy,t)}});var pT=Ek({cumprod_:function(e,t,n,r){void 0===t&&(t=0),void 0===n&&(n=!1),void 0===r&&(r=!1);var a={x:Ik(e,"x","cumprod")},i={axis:t,exclusive:n,reverse:r};return mk.runKernel(my,a,i)}});var hT=Ek({cumsum_:function(e,t,n,r){void 0===t&&(t=0),void 0===n&&(n=!1),void 0===r&&(r=!1);var a={x:Ik(e,"x","cumsum")},i={axis:t,exclusive:n,reverse:r};return mk.runKernel(vy,a,i)}});var fT=Ek({denseBincount_:function(e,t,n,r){void 0===r&&(r=!1);var a=Ik(e,"x","denseBincount"),i=Ik(t,"weights","denseBincount");Uv("int32"===a.dtype,(function(){return"Error in denseBincount: input dtype must be int32, but got "+a.dtype})),Uv(a.rank<=2,(function(){return"Error in denseBincount: input must be at most rank 2, but got rank "+a.rank+"."})),Uv(n>=0,(function(){return"size must be non-negative, but got "+n+"."})),Uv(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 mk.runKernel(yy,o,s)}});var dT=Ek({depthToSpace_:function(e,t,n){void 0===n&&(n="NHWC");var r=Ik(e,"x","depthToSpace","float32"),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];Uv(t>1,(function(){return"blockSize should be > 1 for depthToSpace, but was: "+t})),Uv(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})),Uv(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})),Uv(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 mk.runKernel(by,s,u)}});var mT=Ek({depthwiseConv2d_:function(e,t,n,r,a,i,o){void 0===a&&(a="NHWC"),void 0===i&&(i=[1,1]);var s=Ik(e,"x","depthwiseConv2d","float32"),u=Ik(t,"filter","depthwiseConv2d","float32"),l=s,c=!1;3===s.rank&&(c=!0,l=OS(s,[1,s.shape[0],s.shape[1],s.shape[2]])),Uv(4===l.rank,(function(){return"Error in depthwiseConv2d: input must be rank 4, but got rank "+l.rank+"."})),Uv(4===u.rank,(function(){return"Error in depthwiseConv2d: filter must be rank 4, but got rank "+u.rank+"."})),Uv(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]+"."})),DS("depthwiseConv2d",r,o);var p={x:l,filter:u},h={strides:n,pad:r,dataFormat:a,dilations:i,dimRoundingMode:o},f=mk.runKernel(xy,p,h);return c?OS(f,[f.shape[1],f.shape[2],f.shape[3]]):f}});var vT=Ek({diag_:function(e){var t={x:Ik(e,"x","diag")};return mk.runKernel(Ny,t)}});var gT=Ek({dilation2d_:function(e,t,n,r,a,i){void 0===a&&(a=[1,1]),void 0===i&&(i="NHWC");var o=Ik(e,"x","dilation2d"),s=Ik(t,"filter","dilation2d");Uv(3===o.rank||4===o.rank,(function(){return"Error in dilation2d: input must be rank 3 or 4, but got rank "+o.rank+"."})),Uv(3===s.rank,(function(){return"Error in dilation2d: filter must be rank 3, but got rank "+s.rank+"."})),Uv("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=OS(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=mk.runKernel(Iy,c,p);return l?OS(h,[h.shape[1],h.shape[2],h.shape[3]]):h}});var yT=Ek({equal_:function(e,t){var n=Ik(e,"a","equal","string_or_numeric"),r=Ik(t,"b","equal","string_or_numeric"),a=ak(n,r);n=a[0],r=a[1],oI(n.shape,r.shape);var i={a:n,b:r};return mk.runKernel(Fy,i)}});var bT=Ek({where_:function(e,t,n){var r=Ik(t,"a","where"),a=Ik(n,"b","where"),i=Ik(e,"condition","where","bool"),o=oI(oI(i.shape,r.shape),a.shape),s={condition:YS(i,o),t:YS(r,o),e:YS(a,o)};return mk.runKernel(Jb,s)}});var xT=Ek({zerosLike_:function(e){var t={x:Ik(e,"x","zerosLike")};return mk.runKernel(Ax,t)}});var wT=Ek({divNoNan_:function(e,t){var n=Ik(e,"a","div"),r=Ik(t,"b","div"),a=ak(n,r);n=a[0],r=a[1];var i=iS(n,r),o=xT(i),s=yT(r,o);return bT(s,o,i)}});var kT=Ek({dot_:function(e,t){var n=Ik(e,"t1","dot"),r=Ik(t,"t2","dot");Uv(!(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(Uv(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=OS(n,[1,-1]),s=OS(r,[-1,1]),u=eI(o,s);return OS(u,[])}if(1===n.rank&&2===r.rank){var l=OS(n,[1,-1]),c=OS(r,[r.shape[0],r.shape[1]]),p=eI(l,c);return OS(p,[p.size])}if(2===n.rank&&1===r.rank){var h=OS(r,[-1,1]),f=eI(n,h);return OS(f,[f.size])}var d=OS(r,[r.shape[0],r.shape[1]]);return eI(n,d)}});var NT=Ek({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 Ik(e,"tensors"+t,"einsum")})),i={equation:e};return mk.runKernel(Cy,a,i)}});var IT=Ek({elu_:function(e){var t={x:Ik(e,"x","elu","float32")};return mk.runKernel(Ry,t)}});var ST=Ek({erf_:function(e){var t=Ik(e,"x","erf");Uv("int32"===t.dtype||"float32"===t.dtype,(function(){return"Input dtype must be `int32` or `float32`."})),"int32"===t.dtype&&(t=DN(t,"float32"));var n={x:t};return mk.runKernel(_y,n)}});var TT=Ek({exp_:function(e){var t={x:Ik(e,"x","exp")};return mk.runKernel(Dy,t)}});var ET=Ek({expandDims_:function(e,t){void 0===t&&(t=0);var n=Ik(e,"x","expandDims","string_or_numeric");Uv(t<=n.rank,(function(){return"Axis must be <= rank of the tensor"}));var r={input:n},a={dim:t};return mk.runKernel(Oy,r,a)}});var CT=Ek({expm1_:function(e){var t={x:Ik(e,"x","expm1")};return mk.runKernel(My,t)}});var RT=Ek({tile_:function(e,t){var n=Ik(e,"x","tile","string_or_numeric");Uv(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 mk.runKernel(Nx,r,a)}});var AT=Ek({eye_:function(e,t,n,r){void 0===r&&(r="float32"),null==t&&(t=e);for(var a=FN([e,t],r),i=e<=t?e:t,o=0;o<i;++o)a.set(1,o,o);var s=OS(a.toTensor(),[e,t]);if(null==n)return s;if(1===n.length)return RT(ET(s,0),[n[0],1,1]);if(2===n.length)return RT(ET(ET(s,0),0),[n[0],n[1],1,1]);if(3===n.length)return RT(ET(ET(ET(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 _T(e,t,n){var r={shape:e,value:t,dtype:n};return mk.runKernel(zy,{},r)}var FT=Ek({floor_:function(e){var t={x:Ik(e,"x","floor","float32")};return mk.runKernel(By,t)}});var DT=Ek({gather_:function(e,t,n,r){void 0===n&&(n=0),void 0===r&&(r=0);var a={x:Ik(e,"x","gather"),indices:Ik(t,"indices","gather","int32")},i={axis:n,batchDims:r};return mk.runKernel(Vy,a,i)}});var OT=Ek({greater_:function(e,t){var n=Ik(e,"a","greater","string_or_numeric"),r=Ik(t,"b","greater","string_or_numeric"),a=ak(n,r);n=a[0],r=a[1],oI(n.shape,r.shape);var i={a:n,b:r};return mk.runKernel(jy,i)}});var MT=Ek({greaterEqual_:function(e,t){var n=Ik(e,"a","greaterEqual","string_or_numeric"),r=Ik(t,"b","greaterEqual","string_or_numeric"),a=ak(n,r);n=a[0],r=a[1],oI(n.shape,r.shape);var i={a:n,b:r};return mk.runKernel(Hy,i)}});var LT=Ek({imag_:function(e){var t={input:Ik(e,"input","imag")};return mk.runKernel(Xy,t)}});var zT=Ek({isFinite_:function(e){var t={x:Ik(e,"x","isFinite")};return mk.runKernel(Yy,t)}});var PT=Ek({isInf_:function(e){var t={x:Ik(e,"x","isInf")};return mk.runKernel(Jy,t)}});var BT=Ek({isNaN_:function(e){var t={x:Ik(e,"x","isNaN")};return mk.runKernel(Zy,t)}});var WT=Ek({leakyRelu_:function(e,t){void 0===t&&(t=.2);var n={x:Ik(e,"x","leakyRelu")},r={alpha:t};return mk.runKernel(Qy,n,r)}});var UT=Ek({less_:function(e,t){var n=Ik(e,"a","less","string_or_numeric"),r=Ik(t,"b","less","string_or_numeric"),a=ak(n,r);n=a[0],r=a[1],oI(n.shape,r.shape);var i={a:n,b:r};return mk.runKernel($y,i)}});var VT=Ek({lessEqual_:function(e,t){var n=Ik(e,"a","lessEqual","string_or_numeric"),r=Ik(t,"b","lessEqual","string_or_numeric"),a=ak(n,r);n=a[0],r=a[1],oI(n.shape,r.shape);var i={a:n,b:r};return mk.runKernel(eb,i)}});function GT(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 mk.runKernel(tb,{},r)}var jT=Ek({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=Ik(e,"x","localResponseNormalization");Uv(4===i.rank||3===i.rank,(function(){return"Error in localResponseNormalization: x must be rank 3 or 4 but got\n rank "+i.rank+"."})),Uv(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=OS(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=mk.runKernel(ub,u,l);return s?OS(c,[c.shape[1],c.shape[2],c.shape[3]]):c}});var HT=Ek({log_:function(e){var t={x:Ik(e,"x","log","float32")};return mk.runKernel(nb,t)}});var qT=Ek({log1p_:function(e){var t={x:Ik(e,"x","log1p")};return mk.runKernel(rb,t)}});function KT(e,t){Uv(hg(e),(function(){return"The f passed in variableGrads(f) must be a function"})),Uv(null==t||Array.isArray(t)&&t.every((function(e){return e instanceof ek})),(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=[],mk.registeredVariables)t.push(mk.registeredVariables[r]);var a=n?t.filter((function(e){return!e.trainable})):null,i=t.length;Uv((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=mk.gradients(e,t,null,!0),s=o.value,u=o.grads;Uv(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). Please make sure the operations that use variables are inside the function f passed to minimize()."})),Uv(0===s.rank,(function(){return"The f passed in variableGrads(f) must return a scalar, but it returned a rank-"+s.rank+" tensor"}));var l={};return t.forEach((function(e,t){null!=u[t]&&(l[e.name]=u[t])})),null!=a&&a.forEach((function(e){return l[e.name]=null})),{value:s,grads:l}}function XT(e){return mk.customGrad(e)}function YT(e){if(e.filter((function(e){return null==e})).length>0)throw new Error("Cannot compute gradient of y=f(x) with respect to x. Make sure that\n the f you passed encloses all operations that lead from x to y.")}var JT=Ek({neg_:function(e){var t={x:Ik(e,"x","neg")};return mk.runKernel(Ib,t)}});var ZT=Ek({softplus_:function(e){var t={x:Ik(e,"x","softplus")};return mk.runKernel(rx,t)}});var QT=Ek({logSigmoid_:function(e){var t=Ik(e,"x","logSigmoid");return XT((function(e){return{value:JT(ZT(JT(e))),gradFunc:function(t){return oS(t,PS(JT(e)))}}}))(t)}});var $T=Ek({max_:function(e,t,n){void 0===t&&(t=null),void 0===n&&(n=!1);var r={x:Ik(e,"x","max")},a={reductionIndices:t,keepDims:n};return mk.runKernel(cb,r,a)}});var eE=Ek({sub_:function(e,t){var n=Ik(e,"a","sub"),r=Ik(t,"b","sub"),a=ak(n,r),i={a:n=a[0],b:r=a[1]};return mk.runKernel(xx,i)}});var tE=Ek({sum_:function(e,t,n){void 0===t&&(t=null),void 0===n&&(n=!1);var r=Ik(e,"x","sum");"bool"===r.dtype&&(r=DN(r,"int32"));var a={x:r},i={axis:t,keepDims:n};return mk.runKernel(ix,a,i)}});var nE=Ek({logSoftmax_:function(e,t){void 0===t&&(t=-1);var n=Ik(e,"logits","logSoftmax");if(-1===t&&(t=n.rank-1),t!==n.rank-1)throw Error("Log Softmax along a non-last dimension is not yet supported. Logits was rank "+n.rank+" and axis was "+t);return XT((function(e,n){var r=$T(e,t,!0),a=eE(e,r),i=eE(DN(a,"float32"),HT(tE(TT(a),t,!0)));n([i]);return{value:i,gradFunc:function(e,n){var r=n[0],a=TT(r);return eE(e,oS(tE(e,t,!0),a))}}}))(n)}});function rE(e,t){for(var n=0;n<e.length;++n)if(e[e.length-n-1]!==t-1-n)return!1;return!0}function aE(e,t,n){for(var r=e.length+t.length,a=[],i=0,o=0,s=0;s<r;s++)-1===n.indexOf(s)?a.push(e[i++]):a.push(t[o++]);return a}function iE(e,t){for(var n=[],r=e.length,a=0;a<r;a++)-1===t.indexOf(a)&&n.push(e[a]);return[n,t.map((function(t){return e[t]}))]}function oE(e,t){return aE(e,t.map((function(e){return 1})),t)}function sE(e,t,n){Uv(rE(t,n),(function(){return e+" supports only inner-most axes for now. 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Got strides "+n+" and dilations '1'"})),DS("maxPool",r,a);var u={x:o},l={filterSize:t,strides:n,pad:r,dimRoundingMode:a},c=mk.runKernel(hb,u,l);return s?OS(c,[c.shape[1],c.shape[2],c.shape[3]]):c}});var gE=Ek({maxPool3d_:function(e,t,n,r,a,i){void 0===t&&(t=[1,1,1]),void 0===i&&(i="NDHWC");var o=Ik(e,"x","maxPool3d"),s=o,u=!1;4===o.rank&&(u=!0,s=OS(o,[1,o.shape[0],o.shape[1],o.shape[2],o.shape[3]])),Uv(5===s.rank,(function(){return"Error in maxPool3d: x must be rank 5 but got rank "+s.rank+"."})),Uv("NDHWC"===i,(function(){return"Error in maxPool3d: Only NDHWC is currently supported, but got dataFormat of "+i})),DS("maxPool3d",r,a);var l={x:s},c={filterSize:t,strides:n,pad:r,dimRoundingMode:a,dataFormat:i},p=mk.runKernel(db,l,c);return u?OS(p,[p.shape[1],p.shape[2],p.shape[3],p.shape[4]]):p}});var yE=Ek({maxPoolWithArgmax_:function(e,t,n,r,a){void 0===a&&(a=!1);var i={x:Ik(e,"x","maxPoolWithArgmax")},o={filterSize:t,strides:n,pad:r,includeBatchInIndex:a},s=mk.runKernel(vb,i,o);return{result:s[0],indexes:s[1]}}});var bE=Ek({maximum_:function(e,t){var n=Ik(e,"a","maximum"),r=Ik(t,"b","maximum"),a=ak(n,r);n=a[0],r=a[1],"bool"===n.dtype&&(n=DN(n,"int32"),r=DN(r,"int32")),oI(n.shape,r.shape);var i={a:n,b:r};return mk.runKernel(pb,i)}});var xE=Ek({mean_:function(e,t,n){void 0===t&&(t=null),void 0===n&&(n=!1);var r={x:Ik(e,"x","mean")},a={axis:t,keepDims:n};return mk.runKernel(gb,r,a)}});function wE(e,t){if(void 0===t&&(t="float32"),"complex64"===t){var n=wE(e,"float32"),r=wE(e,"float32");return Ck(n,r)}var a=yg(Hv(e),t);return mk.makeTensor(a,e,t)}function kE(e,t){if(void 0===t&&(t="float32"),"complex64"===t){var n=kE(e,"float32"),r=wE(e,"float32");return Ck(n,r)}var a=gg(Hv(e),t);return mk.makeTensor(a,e,t)}function NE(e,t,n){var r=(void 0===n?{}:n).indexing,a=void 0===r?"xy":r;if("xy"!==a&&"ij"!==a)throw new TypeError(a+" is not a valid third argument to meshgrid");if(void 0===e)return[];var i=Ik(e,"x","meshgrid",e instanceof Kw?e.dtype:"float32");if(void 0===t)return[i];var o=Ik(t,"y","meshgrid",t instanceof Kw?t.dtype:"float32"),s=Hv(i.shape),u=Hv(o.shape);return"xy"===a?(i=OS(i,[1,-1]),o=OS(o,[-1,1]),[eI(kE([u,1],i.dtype),i),eI(o,kE([1,s],o.dtype))]):(i=OS(i,[-1,1]),o=OS(o,[1,-1]),[eI(i,kE([1,u],i.dtype)),eI(kE([s,1],o.dtype),o)])}var IE=Ek({min_:function(e,t,n){void 0===t&&(t=null),void 0===n&&(n=!1);var r={x:Ik(e,"x","min")},a={axis:t,keepDims:n};return mk.runKernel(yb,r,a)}});var SE=Ek({minimum_:function(e,t){var n=Ik(e,"a","minimum"),r=Ik(t,"b","minimum"),a=ak(n,r);n=a[0],r=a[1],"bool"===n.dtype&&(n=DN(n,"int32"),r=DN(r,"int32")),oI(n.shape,r.shape);var i={a:n,b:r};return mk.runKernel(bb,i)}});var TE=Ek({mirrorPad_:function(e,t,n){Uv("reflect"===n||"symmetric"===n,(function(){return"Invalid mode. Mode must be either reflect or symmetric. Got "+n+"."}));var r=Ik(e,"x","mirrorPad");if(0===r.rank)throw new Error("mirrorPad(scalar) is not defined. Pass non-scalar to mirrorPad");Uv(t.length===r.rank,(function(){return"Padding doesn't match input. Must be "+r.rank+". Got "+t.length+"."}));for(var a="reflect"===n?1:0,i=function(e){Uv(2===t[e].length,(function(){return"Invalid number of paddings. Must be length of 2 each."})),Uv(t[e][0]>=0&&t[e][0]<=r.shape[e]-a&&t[e][1]>=0&&t[e][1]<=r.shape[e]-a,(function(){return"Padding in dimension "+e+" cannot be greater than or equal to "+(r.shape[e]-a)+" or less than 0 for input of shape "+r.shape}))},o=0;o<r.rank;o++)i(o);var s={paddings:t,mode:n},u={x:r};return mk.runKernel(xb,u,s)}});var EE=Ek({mod_:function(e,t){var n=Ik(e,"a","mod"),r=Ik(t,"b","mod"),a=ak(n,r),i={a:n=a[0],b:r=a[1]};return mk.runKernel(wb,i)}});var CE=Ek({square_:function(e){var t=Ik(e,"x","square");return mk.runKernel("Square",{x:t},{})}});var RE=Ek({moments_:function(e,t,n){void 0===t&&(t=null),void 0===n&&(n=!1);var r=Qv(t,(e=Ik(e,"x","moments")).shape),a=xE(e,r,n),i=a.shape;n||(i=oE(a.shape,r));var o=CE(eE(DN(e,"float32"),OS(a,i)));return{mean:a,variance:xE(o,r,n)}}});var AE=Ek({multiRNNCell_:function(e,t,n,r){for(var a=Ik(t,"data","multiRNNCell"),i=Sk(n,"c","multiRNNCell"),o=Sk(r,"h","multiRNNCell"),s=a,u=[],l=0;l<e.length;l++){var c=e[l](s,i[l],o[l]);u.push(c[0]),u.push(c[1]),s=c[1]}for(var p=[],h=[],f=0;f<u.length;f+=2)p.push(u[f]),h.push(u[f+1]);return[p,h]}});var _E=Ek({multinomial_:function(e,t,n,r){void 0===r&&(r=!1);var a=Ik(e,"logits","multinomial"),i=a.size,o=a.rank;if(i<2)throw new Error("Error in multinomial: you need at least 2 outcomes, but got "+i+".");if(o>2)throw new Error("Rank of probabilities must be 1 or 2, but is "+o);n=n||Math.random();var s={logits:1===o?OS(a,[1,-1]):a},u={numSamples:t,seed:n,normalized:r},l=mk.runKernel(kb,s,u);return 1===o?OS(l,[l.size]):l}});var FE=Ek({notEqual_:function(e,t){var n=Ik(e,"a","notEqual","string_or_numeric"),r=Ik(t,"b","notEqual","string_or_numeric"),a=ak(n,r);n=a[0],r=a[1],oI(n.shape,r.shape);var i={a:n,b:r};return mk.runKernel(Sb,i)}});var DE=Ek({onesLike_:function(e){var t={x:Ik(e,"x","onesLike")};return mk.runKernel(Rb,t)}});var OE=Ek({outerProduct_:function(e,t){var n=Ik(e,"v1","outerProduct"),r=Ik(t,"v2","outerProduct");Uv(1===n.rank&&1===r.rank,(function(){return"Error in outerProduct: inputs must be rank 1, but got ranks "+n.rank+" and "+r.rank+"."}));var a=OS(n,[-1,1]),i=OS(r,[1,-1]);return eI(a,i)}});var ME=Ek({pad_:function(e,t,n){void 0===n&&(n=0);var r=Ik(e,"x","pad");if(0===r.rank)throw new Error("pad(scalar) is not defined. Pass non-scalar to pad");var a={paddings:t,constantValue:n},i={x:r};return mk.runKernel(Fb,i,a)}});var LE=Ek({pad1d_:function(e,t,n){return void 0===n&&(n=0),Uv(2===t.length,(function(){return"Invalid number of paddings. Must be length of 2."})),ME(e,[t],n)}});var zE=Ek({pad2d_:function(e,t,n){return void 0===n&&(n=0),Uv(2===t.length&&2===t[0].length&&2===t[1].length,(function(){return"Invalid number of paddings. Must be length of 2 each."})),ME(e,t,n)}});var PE=Ek({pad3d_:function(e,t,n){return void 0===n&&(n=0),Uv(3===t.length&&2===t[0].length&&2===t[1].length&&2===t[2].length,(function(){return"Invalid number of paddings. Must be length of 2 each."})),ME(e,t,n)}});var BE=Ek({pad4d_:function(e,t,n){return void 0===n&&(n=0),Uv(4===t.length&&2===t[0].length&&2===t[1].length&&2===t[2].length&&2===t[3].length,(function(){return"Invalid number of paddings. Must be length of 2 each."})),ME(e,t,n)}});var WE=Ek({spaceToBatchND_:function(e,t,n){var r=Ik(e,"x","spaceToBatchND");Uv(r.rank>=1+t.length,(function(){return"input rank "+r.rank+" should be > than [blockShape] "+t.length})),Uv(n.length===t.length,(function(){return"paddings.shape[0] "+n.length+" must be equal to [blockShape] "+t.length})),Uv(r.shape.reduce((function(e,r,a){return a>0&&a<=t.length?e&&(r+n[a-1][0]+n[a-1][1])%t[a-1]==0:e}),!0),(function(){return"input spatial dimensions "+r.shape.slice(1)+" with paddings "+n.toString()+" must be divisible by blockShapes "+t.toString()}));var a={x:r},i={blockShape:t,paddings:n};return mk.runKernel(ox,a,i)}});var UE=Ek({pool_:function(e,t,n,r,a,i,o){null==a&&(a=[1,1]),null==i&&(i=1),0===r&&(r="valid");var s=Ik(e,"x","maxPool"),u=s,l=!1;3===s.rank&&(l=!0,u=OS(s,[1,s.shape[0],s.shape[1],s.shape[2]])),Uv(_S(i,a),(function(){return"Error in pool: Either strides or dilations must be 1. 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18:case"end":return e.stop()}}),e)})))).apply(this,arguments)}var $R=function(e,t,n,r,a,i){return QR.apply(this,arguments)};var eA=Ek({resizeBilinear_:function(e,t,n,r){void 0===n&&(n=!1),void 0===r&&(r=!1);var a=Ik(e,"images","resizeBilinear");Uv(3===a.rank||4===a.rank,(function(){return"Error in resizeBilinear: x must be rank 3 or 4, but got rank "+a.rank+"."})),Uv(2===t.length,(function(){return"Error in resizeBilinear: new shape must 2D, but got shape "+t+"."})),Uv(!1===r||!1===n,(function(){return"Error in resizeBilinear: If halfPixelCenters is true, alignCorners must be false."}));var i=a,o=!1;3===a.rank&&(o=!0,i=OS(a,[1,a.shape[0],a.shape[1],a.shape[2]]));var s={images:i},u={alignCorners:n,halfPixelCenters:r,size:t},l=mk.runKernel(Gb,s,u);return o?OS(l,[l.shape[1],l.shape[2],l.shape[3]]):l}});var tA=Ek({resizeNearestNeighbor_:function(e,t,n,r){void 0===n&&(n=!1),void 0===r&&(r=!1);var a=Ik(e,"images","resizeNearestNeighbor");Uv(3===a.rank||4===a.rank,(function(){return"Error in resizeNearestNeighbor: x must be rank 3 or 4, but got rank "+a.rank+"."})),Uv(2===t.length,(function(){return"Error in resizeNearestNeighbor: new shape must 2D, but got shape "+t+"."})),Uv("float32"===a.dtype||"int32"===a.dtype,(function(){return"`images` must have `int32` or `float32` as dtype"})),Uv(!1===r||!1===n,(function(){return"Error in resizeNearestNeighbor: If halfPixelCenters is true, alignCorners must be false."}));var i=a,o=!1;3===a.rank&&(o=!0,i=OS(a,[1,a.shape[0],a.shape[1],a.shape[2]]));var s={images:i},u={alignCorners:n,halfPixelCenters:r,size:t},l=mk.runKernel(Ub,s,u);return o?OS(l,[l.shape[1],l.shape[2],l.shape[3]]):l}});var nA=Ek({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=Ik(e,"image","threshold"),l=u.shape[0]*u.shape[1],c=oS(GC([r]),255);if(Uv(3===u.rank,(function(){return"Error in threshold: image must be rank 3,but got rank "+u.rank+"."})),Uv(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]+"."})),Uv("int32"===u.dtype||"float32"===u.dtype,(function(){return"Error in dtype: image dtype must be int32 or float32,but got dtype "+u.dtype+"."})),Uv("otsu"===t||"binary"===t,(function(){return"Method must be binary or otsu, but was "+t})),3===u.shape[2]){var p=OC(u,[1,1,1],-1);a=p[0],i=p[1],o=p[2];var h=oS(a,.2989),f=oS(i,.587),d=oS(o,.114);s=rS(rS(h,f),d)}else s=e;"otsu"===t&&(c=function(e,t){for(var n,r,a,i,o,s,u=GC([-1]),l=GC([0]),c=GC([0]),p=0;p<e.size-1;p++){n=BS(e,0,p+1),r=BS(e,p+1),o=iS(tE(n),t),s=iS(tE(r),t);var h=tE(oS(n,oC(0,n.size)));a=iS(h,tE(n));var f=_T(r.shape,n.size),d=rS(oC(0,r.size),f),m=oS(r,d);i=iS(tE(m),tE(r));var v=eE(a,i),g=eE(a,i),y=oS(o,s);c=oS(oS(y,v),g);var b=OT(c,l);l=bT(b,c,l),u=bT(b,GC([p]),u)}return u}(KS(DN(vC(s),"int32"),Ak([]),256),l));var m=n?VT(s,c):OT(s,c);return DN(oS(m,255),"int32")}});var rA=Ek({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=Ik(e,"image","transform","float32"),s=Ik(t,"transforms","transform","float32");Uv(4===o.rank,(function(){return"Error in transform: image must be rank 4,but got rank "+o.rank+"."})),Uv(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"})),Uv(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 mk.runKernel(Sx,u,l)}});var aA=Ek({bandPart_:function(e,t,n){Uv(t%1==0,(function(){return"bandPart(): numLower must be an integer, got "+t+"."})),Uv(n%1==0,(function(){return"bandPart(): numUpper must be an integer, got "+n+"."}));var r=Ik(e,"a","bandPart");Uv(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=OS(oC(0,o,1,"int32"),[-1,1]),l=oC(0,s,1,"int32"),c=eE(u,l),p=hE(VT(c,yC(+t,"int32")),MT(c,yC(-n,"int32"))),h=wE([o,s],r.dtype);return OS(BC(QC(OS(r,[-1,o,s])).map((function(e){return bT(p,e,h)}))),a)}});var iA=Ek({gramSchmidt_:function(e){var t;Array.isArray(e)?function(){t=!1,Uv(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){Uv(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=OC(e,e.shape[0],0).map((function(e){return PC(e,[0])}))),Uv(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(mk.tidy((function(){var t=r[e];if(e>0)for(var a=0;a<e;++a){var i=oS(tE(oS(n[a],t)),n[a]);t=eE(t,i)}return iS(t,oR(t,"euclidean"))})))},i=0;i<e.length;++i)a(i);return t?BC(n,0):n}});function oA(e,t){return void 0===t&&(t=!1),mk.tidy((function(){Uv(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=AT(n),i=ON(e),o=jC([[1]],[1,1]),s=ON(o),u=n>=r?r:n,l=function(e){var t=i,u=s,l=a,c=mk.tidy((function(){var t=BS(i,[e,e],[n-e,1]),u=oR(t),l=BS(i,[e,e],[1,1]),c=bT(OT(l,0),jC([[-1]]),jC([[1]])),p=eE(l,oS(c,u)),h=iS(t,p);s=1===h.shape[0]?ON(o):zS([o,BS(h,[1,0],[h.shape[0]-1,h.shape[1]])],0);var f=JT(iS(eI(c,p),u)),d=BS(i,[e,0],[n-e,r]),m=oS(f,s),v=nI(s);if(0===e)i=eE(d,eI(m,eI(v,d)));else{var 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0===r&&(r=e.Reduction.SUM_BY_NONZERO_WEIGHTS);var a=Ik(t,"losses","computeWeightedLoss"),i=null;null!=n&&(i=Ik(n,"weights","computeWeightedLoss"));var o=null==i?a:oS(a,i);if(r===e.Reduction.NONE)return o;if(r===e.Reduction.SUM)return tE(o);if(r===e.Reduction.MEAN){if(null==i)return xE(o);var s=a.size/i.size,u=iS(tE(o),tE(i));return s>1?iS(u,yC(s)):u}if(r===e.Reduction.SUM_BY_NONZERO_WEIGHTS){if(null==i)return iS(tE(o),yC(a.size));var l=oS(i,kE(a.shape)),c=DN(tE(FE(l,yC(0))),"float32");return iS(tE(o),c)}throw Error("Unknown reduction: "+r)}});var cA=Ek({absoluteDifference_:function(t,n,r,a){void 0===a&&(a=e.Reduction.SUM_BY_NONZERO_WEIGHTS);var i=Ik(t,"labels","absoluteDifference"),o=Ik(n,"predictions","absoluteDifference"),s=null;null!=r&&(s=Ik(r,"weights","absoluteDifference")),Vv(i.shape,o.shape,"Error in absoluteDifference: ");var u=sS(eE(i,o));return lA(u,s,a)}});var pA=Ek({cosineDistance_:function(t,n,r,a,i){void 0===i&&(i=e.Reduction.SUM_BY_NONZERO_WEIGHTS);var o=Ik(t,"labels","cosineDistance"),s=Ik(n,"predictions","cosineDistance"),u=null;null!=a&&(u=Ik(a,"weights","cosineDistance")),Vv(o.shape,s.shape,"Error in cosineDistance: ");var l=yC(1),c=eE(l,tE(oS(o,s),r,!0));return lA(c,u,i)}});var hA=Ek({hingeLoss_:function(t,n,r,a){void 0===a&&(a=e.Reduction.SUM_BY_NONZERO_WEIGHTS);var i=Ik(t,"labels","hingeLoss"),o=Ik(n,"predictions","hingeLoss"),s=null;null!=r&&(s=Ik(r,"weights","hingeLoss")),Vv(i.shape,o.shape,"Error in hingeLoss: ");var u=yC(1);i=eE(oS(yC(2),i),u);var l=lC(eE(u,oS(i,o)));return lA(l,s,a)}});var fA=Ek({huberLoss_:function(t,n,r,a,i){void 0===a&&(a=1),void 0===i&&(i=e.Reduction.SUM_BY_NONZERO_WEIGHTS);var o=Ik(t,"labels","huberLoss"),s=Ik(n,"predictions","huberLoss"),u=null;null!=r&&(u=Ik(r,"weights","huberLoss")),Vv(o.shape,s.shape,"Error in huberLoss: ");var l=yC(a),c=sS(eE(s,o)),p=SE(c,l),h=eE(c,p),f=rS(oS(yC(.5),CE(p)),oS(l,h));return lA(f,u,i)}});var dA=Ek({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=Ik(t,"labels","logLoss"),s=Ik(n,"predictions","logLoss"),u=null;null!=r&&(u=Ik(r,"weights","logLoss")),Vv(o.shape,s.shape,"Error in logLoss: ");var l=yC(1),c=yC(a),p=JT(oS(o,HT(rS(s,c)))),h=oS(eE(l,o),HT(rS(eE(l,s),c))),f=eE(p,h);return lA(f,u,i)}});var mA=Ek({meanSquaredError_:function(t,n,r,a){void 0===a&&(a=e.Reduction.SUM_BY_NONZERO_WEIGHTS);var i=Ik(t,"labels","meanSquaredError"),o=Ik(n,"predictions","meanSquaredError"),s=null;null!=r&&(s=Ik(r,"weights","meanSquaredError")),Vv(i.shape,o.shape,"Error in meanSquaredError: ");var u=zC(i,o);return lA(u,s,a)}});var vA=Ek({sigmoidCrossEntropy_:function(t,n,r,a,i){void 0===a&&(a=0),void 0===i&&(i=e.Reduction.SUM_BY_NONZERO_WEIGHTS);var o=Ik(t,"multiClassLabels","sigmoidCrossEntropy"),s=Ik(n,"logits","sigmoidCrossEntropy"),u=null;if(null!=r&&(u=Ik(r,"weights","sigmoidCrossEntropy")),Vv(o.shape,s.shape,"Error in sigmoidCrossEntropy: "),a>0){var l=yC(a),c=yC(1),p=yC(.5);o=rS(oS(o,eE(c,l)),oS(p,l))}var h=function(e,t){var n=Ik(e,"labels","sigmoidCrossEntropyWithLogits"),r=Ik(t,"logits","sigmoidCrossEntropyWithLogits");Vv(n.shape,r.shape,"Error in sigmoidCrossEntropyWithLogits: ");var a=lC(r),i=oS(r,n),o=qT(TT(JT(sS(r))));return rS(eE(a,i),o)}(o,s);return lA(h,u,i)}});var gA=Ek({softmaxCrossEntropy_:function(t,n,r,a,i){void 0===a&&(a=0),void 0===i&&(i=e.Reduction.SUM_BY_NONZERO_WEIGHTS);var o=Ik(t,"onehotLabels","softmaxCrossEntropy"),s=Ik(n,"logits","softmaxCrossEntropy"),u=null;if(null!=r&&(u=Ik(r,"weights","softmaxCrossEntropy")),Vv(o.shape,s.shape,"Error in softmaxCrossEntropy: "),a>0){var l=yC(a),c=yC(1),p=yC(o.shape[1]);o=rS(oS(o,eE(c,l)),iS(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. Labels / logits was rank "+t.rank+" and dim was "+n);return XT((function(e,t,r){var a=pE(t,[n],!0),i=eE(DN(t,"float32"),a);r([e,i]);var o=JT(oS(i,e));return{value:tE(o,[n]),gradFunc:function(e,t){var r=t[0],a=t[1],i=oE(e.shape,[n]);return[oS(OS(e,i),eE(DN(r,"float32"),TT(a))),oS(OS(e,i),eE(TT(a),DN(r,"float32")))]}}}))(e,t)}(o,s);return lA(h,u,i)}});var yA=Ek({sparseFillEmptyRows_:function(e,t,n,r){var a=Ik(e,"indices","sparseFillEmptyRows","int32"),i=Ik(t,"values","sparseFillEmptyRows"),o=Ik(n,"denseShape","sparseFillEmptyRows","int32"),s=Ik(r,"defaultValue","sparseFillEmptyRows",i.dtype);if(2!==a.rank)throw new Error("Indices should be Tensor2D but received shape\n "+a.shape);if(1!==i.rank)throw new Error("Values should be Tensor1D but received shape "+i.shape);if(1!==o.rank)throw new Error("Dense shape should be Tensor1D but received shape "+o.shape);if(0!==s.rank)throw new Error("Default value should be a scalar but received shape "+s.shape);var u={indices:a,values:i,denseShape:o,defaultValue:s},l=mk.runKernel(lx,u);return{outputIndices:l[0],outputValues:l[1],emptyRowIndicator:l[2],reverseIndexMap:l[3]}}});var bA=Ek({sparseReshape_:function(e,t,n){var r=Ik(e,"inputIndices","sparseReshape","int32"),a=Ik(t,"inputShape","sparseReshape","int32"),i=Ik(n,"newShape","sparseReshape","int32");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=mk.runKernel(cx,o);return{outputIndices:s[0],outputShape:s[1]}}});var xA=Ek({sparseSegmentMean_:function(e,t,n){var r=Ik(e,"data","sparseSegmentMean"),a=Ik(t,"indices","sparseSegmentMean","int32"),i=Ik(n,"segmentIds","sparseSegmentMean","int32");if(r.rank<1)throw new Error("Data should be at least 1 dimensional but received 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Build it first by calling build(batchInputShape).");return UO(this.weights)},n.build=function(e){this.built=!0},n.getWeights=function(e){return void 0===e&&(e=!1),jO(e?this.trainableWeights:this.weights)},n.setWeights=function(e){var t=this;ZI((function(){var n=t.weights;if(n.length!==e.length)throw new iD('You called setWeights(weights) on layer "'+t.name+'" with a weight list of length '+e.length+", but the layer was expecting "+n.length+" weights. Provided weights: "+e+"...");if(0!==n.length){for(var r=[],a=jO(n),i=0;i<a.length;++i){var o=a[i],s=n[i],u=e[i];if(!qv(o.shape,u.shape))throw new iD("Layer weight shape "+o.shape+" not compatible with provided weight shape "+u.shape);r.push([s,u])}HO(r)}}))},n.addWeight=function(e,t,n,r,a,i,o,s){if(-1!==this._addedWeightNames.indexOf(e))throw new iD("Duplicate weight name "+e+" for layer "+this.name);this._addedWeightNames.push(e),null==n&&(n="float32"),this.fastWeightInitDuringBuild&&(r=null!=s?s():LO("zeros"));var u=r.apply(t,n),l=new GO(u,n,e,i,o);return u.dispose(),null!=a&&this.addLoss((function(){return a.apply(l.read())})),null==i&&(i=!0),i?this._trainableWeights.push(l):this._nonTrainableWeights.push(l),l},n.setFastWeightInitDuringBuild=function(e){this.fastWeightInitDuringBuild=e},n.addLoss=function(e){var t;null==e||Array.isArray(e)&&0===e.length||(e=fD(e),void 0!==this._losses&&null!==this._losses&&(t=this.losses).push.apply(t,e))},n.computeOutputShape=function(e){return e},n.computeMask=function(e,t){var n=this;if(!this.supportsMasking){if(null!=t){if(!Array.isArray(t))throw new TypeError("Layer "+this.name+" does not support masking, but was passed an inputMask.");t.forEach((function(e){if(null!=e)throw new TypeError("Layer "+n.name+" does not support masking, but was passed an inputMask.")}))}return null}return t},n.addInboundNode=function(e,t,n,r,a,i,o){void 0===o&&(o=null);var s=fD(e);t=fD(t),n=fD(n),r=fD(r),a=PO(a),i=PO(i);for(var u,l=[],c=[],p=[],h=Fv(s);!(u=h()).done;){var f=u.value;l.push(f.sourceLayer),c.push(f.nodeIndex),p.push(f.tensorIndex)}new YO({outboundLayer:this,inboundLayers:l,nodeIndices:c,tensorIndices:p,inputTensors:s,outputTensors:t,inputMasks:n,outputMasks:r,inputShapes:a,outputShapes:i},o);for(var d=0;d<t.length;d++)t[d].sourceLayer=this,t[d].nodeIndex=this.inboundNodes.length-1,t[d].tensorIndex=d},n.getConfig=function(){var e={name:this.name,trainable:this.trainable};return null!=this.batchInputShape&&(e.batchInputShape=this.batchInputShape),null!=this.dtype&&(e.dtype=this.dtype),e},n.disposeWeights=function(){return this.weights.forEach((function(e){return e.dispose()})),this.weights.length},n.assertNotDisposed=function(){if(0===this._refCount)throw new Error("Layer '"+this.name+"' is already disposed.")},n.dispose=function(){if(!this.built)throw new Error("Cannot dispose Layer "+this.name+" because it has not been built yet.");if(null===this._refCount)throw new Error("Cannot dispose Layer "+this.name+" because it has not been used yet.");this.assertNotDisposed();var e=0;return 0==--this._refCount&&(e=this.disposeWeights()),{refCountAfterDispose:this._refCount,numDisposedVariables:e}},kv(t,[{key:"input",get:function(){if(this.inboundNodes.length>1)throw new rD("Layer "+this.name+' has multiple inbound nodes, hence the notion of "layer input" is ill-defined. Use `getInputAt(nodeIndex)` instead.');if(0===this.inboundNodes.length)throw new rD("Layer "+this.name+" is not connected, no input to return.");return hD(this.getNodeAtIndex(0,"input").inputTensors)}},{key:"output",get:function(){if(0===this.inboundNodes.length)throw new rD("Layer "+this.name+" has no inbound nodes.");if(this.inboundNodes.length>1)throw new rD("Layer "+this.name+' has multiple inbound nodes, hence the notion of "layer output" is ill-defined. Use `getOutputAt(nodeIndex)` instead.');return hD(this.getNodeAtIndex(0,"output").outputTensors)}},{key:"losses",get:function(){return this._losses}},{key:"updates",get:function(){return this._updates}},{key:"built",get:function(){return this._built},set:function(e){this._built=e}},{key:"trainable",get:function(){return this.trainable_},set:function(e){this._trainableWeights.forEach((function(t){return t.trainable=e})),this.trainable_=e}},{key:"trainableWeights",get:function(){return this.trainable_?this._trainableWeights.filter((function(e){return e.trainable})):[]},set:function(e){this._trainableWeights=e}},{key:"nonTrainableWeights",get:function(){return this.trainable?this._trainableWeights.filter((function(e){return!e.trainable})).concat(this._nonTrainableWeights):this._trainableWeights.concat(this._nonTrainableWeights)},set:function(e){this._nonTrainableWeights=e}},{key:"weights",get:function(){return this.trainableWeights.concat(this.nonTrainableWeights)}},{key:"stateful",get:function(){return this._stateful}},{key:"outputShape",get:function(){if(null==this.inboundNodes||0===this.inboundNodes.length)throw new rD("The layer "+this.name+" has never been called and thus has no defined output shape.");for(var e,t=[],n=Fv(this.inboundNodes);!(e=n()).done;){var r=e.value,a=JSON.stringify(r.outputShapes);-1===t.indexOf(a)&&t.push(a)}if(1===t.length){var i=this.inboundNodes[0].outputShapes;return Array.isArray(i)&&Array.isArray(i[0])&&1===i.length?i[0]:i}throw new rD("The layer "+this.name+' has multiple inbound nodes with different output shapes. Hence the notion of "output shape" is ill-defined for the layer.')}}]),t}(PI);function QO(e,t,n){if((null==t||null!=n&&n>0)&&(t=e.sourceLayer,n=e.nodeIndex),0===t.inboundNodes.length)return[e];var r=t.inboundNodes[n];if(0===r.inboundLayers.length)return r.inputTensors;for(var a=[],i=0;i<r.inboundLayers.length;i++)for(var o,s=Fv(QO(r.inputTensors[i],r.inboundLayers[i],r.nodeIndices[i]));!(o=s()).done;){var u=o.value;-1===a.indexOf(u)&&a.push(u)}return a}var $O=function(e){function t(t){var n;if(n=e.call(this,{dtype:t.dtype,name:null!=t.name?t.name:_D("input").toString()})||this,null==t.batchSize&&(t.batchSize=null),null==t.sparse&&(t.sparse=!1),n.trainable=!1,n.built=!0,n.sparse=t.sparse,null!=t.inputShape&&null!=t.batchInputShape)throw new iD("Only provide the inputShape OR batchInputShape argument to inputLayer, not both at the same time.");var r=t.batchInputShape;if(null==r){if(null==t.inputShape)throw new iD("An InputLayer should be passed either a `batchInputShape` or an `inputShape`.");r=[t.batchSize].concat(t.inputShape)}else if(null!=t.batchSize)throw new iD("Cannot specify batchSize if batchInputShape is specified when creating an InputLayer.");var a=t.dtype||"float32";n.batchInputShape=r,n.dtype=a,n.inputSpec=[{shape:r}];var i=new KO(n.dtype,n.batchInputShape,Rv(n),[],{},n.name);return i.nodeIndex=0,i.tensorIndex=0,new YO({outboundLayer:Rv(n),inboundLayers:[],nodeIndices:[],tensorIndices:[],inputTensors:[i],outputTensors:[i],inputMasks:[null],outputMasks:[null],inputShapes:[r],outputShapes:[r]}),n}Nv(t,e);var n=t.prototype;return n.apply=function(e,t){throw new iD("Cannot pass any input to an InputLayer's apply() method. 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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;RL(r);var a=this.standardizeUserDataXY(e,t,!0,r);try{var i=a[0].concat(a[1]);this.makeTestFunction();var o=this.testFunction;return hD(this.testLoop(o,i,r,n.verbose,n.steps))}finally{PL(a[0],e),PL(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",EL(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 iD("If "+r+" is set, batchSize must be null or undefined.Got batchSize = "+t)}else{if(null==e)throw new iD("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 iD("`outputs` is an empty Array, which is not allowed.");var n=Array.isArray(t),r=n?t:[t],a=this.retrieveSymbolicTensors(r),i=new tM;if(e instanceof Kw&&(e=[e]),Array.isArray(e)){if(e.length!==this.inputs.length)throw new iD("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 iD("No value is provided for the model's input "+l.name);i.add(l,c)}var p=aM(a,i);return n?p:p[0]},n.retrieveSymbolicTensors=function(e){for(var t,n=lD(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 iD("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),ZI((function(){var a=r.checkNumSamples(e);if(n)throw new oD("Verbose predictLoop() is not implemented yet.");for(var i=FL(a,t),o=r.outputs.map((function(e){return[]})),s=function(t){ZI((function(){var n=i[t][0],a=i[t][1],o=AL(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 tM(s);return aM(r.outputs,l)})).forEach((function(e,t){return o[t].push(e)}))},u=0;u<i.length;++u)s(u);return hD(o.map((function(e){return zS(e,0)})))}))},n.predict=function(e,t){void 0===t&&(t={});var n=zL(e);VL(n,this.inputNames,this.feedInputShapes,!1);try{var r=null==t.batchSize?32:t.batchSize;return RL(r),this.predictLoop(n,r)}finally{PL(n,e)}},n.predictOnBatch=function(e){VL(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 aD("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]===BM?a.push(o.slice(0,o.length-1).concat([1])):a.push(o)}if(function(e,t,n){var r=wD(e.map((function(e){return e.shape[0]})));r.sort();var a=wD(t.map((function(e){return e.shape[0]})));if(a.sort(),r.length>1)throw new iD("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 iD("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 iD("Input Tensors should have the same number of samples as target Tensors. 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'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 iD("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 iD("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=mL(a,this.outputNames),c=[],h=0;case 9:if(!(h<p.length)){e.next=18;break}return e.t0=c,e.next=13,vL(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),ZI((function(){var o=i.checkNumSamples(t,n,a,"steps"),s=[];if(r>0)throw new oD("Verbose mode is not implemented yet.");if(null!=a)throw new oD("steps mode 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h=(0,e.lossFunctions[p])(a[p],c[p]);null!=i[p]&&(h=yL(h,i[p]));var f=xE(h);n.push(f),u=0===p?h:rS(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=xE(v(a[g],c[g]))}$I(m),o.push(m)}return u=xE(u),e.calculateLosses().forEach((function(e){u=rS(u,e)})),u}),!0,s)].concat(o)}},n.makeTestFunction=function(){var e=this;this.testFunction=function(t){return ZI((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 tM(o),l=aM(e.outputs,u),c=0;c<e.lossFunctions.length;++c){var p=e.lossFunctions[c],h=xE(p(i[c],l[c]));n=0===c?h:rS(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=xE(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",ML(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",kL(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 QI(s),PL(r[0],t),PL(r[1],n),e.abrupt("return",hD(u));case 21: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=JI().numTensors;this.optimizer_.dispose(),t.numDisposedVariables+=n-JI().numTensors}return t},n.getLossIdentifiers=function(){var e;if("string"==typeof this.loss)e=dD(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 dD(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]=dD(a[s])}}return e},n.getMetricIdentifiers=function(){if("string"==typeof this.metrics||"function"==typeof this.metrics)return[dD(nL(this.metrics))];if(Array.isArray(this.metrics))return this.metrics.map((function(e){return dD(nL(e))}));var e={};for(var t in this.metrics)e[t]=dD(nL(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 yet.");var t,n,r=FM(pL(e.optimizer_config));if("string"==typeof e.loss)t=mD(e.loss);else if(Array.isArray(e.loss))t=e.loss.map((function(e){return mD(e)}));else if(null!=e.loss)for(var a in t={},e.loss)t[a]=mD(e.loss[a]);if(Array.isArray(e.metrics))n=e.metrics.map((function(e){return mD(e)}));else if(null!=e.metrics)for(var i in n={},e.metrics)n[i]=mD(e.metrics[i]);this.compile({loss:t,metrics:n,optimizer:r})},n.save=function(){var e=xv(regeneratorRuntime.mark((function e(t,n){var r,a,i,o,s,u,l,c,p;return regeneratorRuntime.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:if("string"!=typeof t){e.next=9;break}if(0!==(r=Xk(t)).length){e.next=6;break}throw new iD("Cannot find any save handlers for URL '"+t+"'");case 6:if(!(r.length>1)){e.next=8;break}throw new iD("Found more than one ("+r.length+") save handlers for URL '"+t+"'");case 8:t=r[0];case 9:if(null!=t.save){e.next=11;break}throw new iD("LayersModel.save() cannot proceed because the IOHandler provided does not have the 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e.apply(this,arguments)}}(),n.setUserDefinedMetadata=function(e){aL(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=_D(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],wD(r.inputs).length!==r.inputs.length)throw new iD("The list of inputs passed to the model is redundant. 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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 iD("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 iD("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(cD("kernelSize"in e,"required key 'kernelSize' not in config"),"number"!=typeof e.kernelSize&&!ID(e.kernelSize,"number",1,3))throw new iD("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:fz(this.activation),useBias:this.useBias,biasInitializer:MO(this.biasInitializer),biasRegularizer:xz(this.biasRegularizer),activityRegularizer:xz(this.activityRegularizer),biasConstraint:mM(this.biasConstraint)},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(ZO),Pz=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,SD(a.filters,"filters"),a.kernelInitializer=LO(r.kernelInitializer||a.DEFAULT_KERNEL_INITIALIZER),a.kernelConstraint=gM(r.kernelConstraint),a.kernelRegularizer=kz(r.kernelRegularizer),a}Nv(t,e);var n=t.prototype;return n.build=function(e){var t;e=WO(e);var n="channelsFirst"===this.dataFormat?1:e.length-1;if(null==e[n])throw new iD("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 ZI((function(){var t;e=BO(e);var r=null==n.bias?null:n.bias.read(),a=ED(n.activation.getClassName());if(null!=a&&2===n.rank)t=Mz(e,n.kernel.read(),r,n.strides,n.padding,n.dataFormat,n.dilationRate,a);else{if(1===n.rank)t=Oz(e,n.kernel.read(),r,n.strides[0],n.padding,n.dataFormat,n.dilationRate[0]);else if(2===n.rank)t=Mz(e,n.kernel.read(),r,n.strides,n.padding,n.dataFormat,n.dilationRate);else{if(3!==n.rank)throw new oD("convolutions greater than 3D are not implemented yet.");t=Lz(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=WO(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=Az(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:MO(this.kernelInitializer),kernelRegularizer:xz(this.kernelRegularizer),kernelConstraint:mM(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 iD("Convolution layer expected config.filters to be a 'number' > 0 but got "+JSON.stringify(e.filters))},t}(zz),Bz=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&&!ID(e.kernelSize,"number",1,2))throw new iD("Conv2D expects config.kernelSize to be number or number[] with length 1 or 2, but received "+JSON.stringify(e.kernelSize)+".")},t}(Pz);Bz.className="Conv2D",WI(Bz);var Wz=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 iD("Conv3D expects config.kernelSize to be number or [number, number, number], but received "+JSON.stringify(e.kernelSize)+".")},t}(Pz);Wz.className="Conv3D",WI(Wz);var Uz=function(e){function t(t){var n;if((n=e.call(this,t)||this).inputSpec=[new qO({ndim:4})],"same"!==n.padding&&"valid"!==n.padding)throw new iD("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=WO(e)).length)throw new iD("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 iD("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 qO({ndim:4,axes:(t={},t[n]=r,t)})],this.built=!0},n.call=function(e,t){var n=this;return ZI((function(){var t=BO(e);if(4!==t.shape.length)throw new iD("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,_z(s,p,l,n.padding),_z(u,h,c,n.padding),n.filters];"channelsLast"!==n.dataFormat&&(t=nI(t,[0,2,3,1]));var d=iT(t,n.kernel.read(),f,n.strides,n.padding);return"channelsLast"!==n.dataFormat&&(d=nI(d,[0,3,1,2])),null!=n.bias&&(d=hO(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=WO(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]=_z(a[n],s,i,this.padding),a[r]=_z(a[r],u,o,this.padding),a},n.getConfig=function(){var t=e.prototype.getConfig.call(this);return delete t.dilationRate,t},t}(Bz);Uz.className="Conv2DTranspose",WI(Uz);var Vz=function(e){function t(t){var n;if((n=e.call(this,t)||this).inputSpec=[new qO({ndim:5})],"same"!==n.padding&&"valid"!==n.padding)throw new iD("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=WO(e)).length)throw new iD("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 iD("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 qO({ndim:5,axes:(t={},t[n]=r,t)})],this.built=!0},n.call=function(e,t){var n=this;return ZI((function(){var t=BO(e);if(5!==t.shape.length)throw new iD("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,_z(u,d,p,n.padding),_z(l,m,h,n.padding),_z(c,v,f,n.padding),n.filters];"channelsLast"!==n.dataFormat&&(t=nI(t,[0,2,3,4,1]));var y=uT(t,n.kernel.read(),g,n.strides,n.padding);return"channelsLast"!==n.dataFormat&&(y=nI(y,[0,4,1,2,3])),null!==n.bias&&(y=hO(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=WO(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]=_z(i[n],l,o,this.padding),i[r]=_z(i[r],c,s,this.padding),i[a]=_z(i[a],p,u,this.padding),i},n.getConfig=function(){var t=e.prototype.getConfig.call(this);return delete t.dilationRate,t},t}(Wz);Vz.className="Conv3DTranspose",WI(Vz);var Gz=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 iD("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(null!=n.kernelInitializer||null!=n.kernelRegularizer||null!=n.kernelConstraint)throw new iD("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 iD("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=LO(n.depthwiseInitializer||r.DEFAULT_DEPTHWISE_INITIALIZER),r.depthwiseRegularizer=kz(n.depthwiseRegularizer),r.depthwiseConstraint=gM(n.depthwiseConstraint),r.pointwiseInitializer=LO(n.depthwiseInitializer||r.DEFAULT_POINTWISE_INITIALIZER),r.pointwiseRegularizer=kz(n.pointwiseRegularizer),r.pointwiseConstraint=gM(n.pointwiseConstraint),r}Nv(t,e);var n=t.prototype;return n.build=function(e){var t;if((e=WO(e)).length<this.rank+2)throw new iD("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 iD("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 qO({ndim:this.rank+2,axes:(t={},t[n]=r,t)})],this.built=!0},n.call=function(e,t){var n=this;return ZI((function(){var t;if(e=BO(e),1===n.rank)throw new oD("1D separable convolution is not implemented yet.");return 2===n.rank&&("channelsFirst"===n.dataFormat&&(e=nI(e,[0,2,3,1])),t=xC(e,n.depthwiseKernel.read(),n.pointwiseKernel.read(),n.strides,n.padding,n.dilationRate,"NHWC")),n.useBias&&(t=hO(t,n.bias.read(),n.dataFormat)),null!=n.activation&&(t=n.activation.apply(t)),"channelsFirst"===n.dataFormat&&(t=nI(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=MO(this.depthwiseInitializer),t.pointwiseInitializer=MO(this.pointwiseInitializer),t.depthwiseRegularizer=xz(this.depthwiseRegularizer),t.pointwiseRegularizer=xz(this.pointwiseRegularizer),t.depthwiseConstraint=mM(this.depthwiseConstraint),t.pointwiseConstraint=mM(this.pointwiseConstraint),t},t}(Pz);Gz.className="SeparableConv";var jz=function(e){function t(t){return e.call(this,2,t)||this}return Nv(t,e),t}(Gz);jz.className="SeparableConv2D",WI(jz);var Hz=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&&!ID(e.kernelSize,"number",1,1))throw new iD("Conv1D expects config.kernelSize to be number or number[] with length 1, but received "+JSON.stringify(e.kernelSize)+".")},t}(Pz);Hz.className="Conv1D",WI(Hz);var qz=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 ZI((function(){if(e=BO(e),"channelsLast"===n.dataFormat){var t=rO(e,n.cropping[0][0],e.shape[1]-n.cropping[0][0]-n.cropping[0][1],2);return rO(t,n.cropping[1][0],e.shape[2]-n.cropping[1][1]-n.cropping[1][0],3)}var r=rO(e,n.cropping[0][0],e.shape[2]-n.cropping[0][0]-n.cropping[0][1],3);return rO(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}(ZO);qz.className="Cropping2D",WI(qz);var Kz=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,PD(n.dataFormat),n.interpolation=null==t.interpolation?"nearest":t.interpolation,r=n.interpolation,ND(DD,"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 ZI((function(){var t=BO(e),r=t.shape;if("channelsFirst"===n.dataFormat){t=nI(t,[0,2,3,1]);var a=n.size[0]*r[2],i=n.size[1]*r[3],o="nearest"===n.interpolation?EA.resizeNearestNeighbor(t,[a,i]):EA.resizeBilinear(t,[a,i]);return nI(o,[0,3,1,2])}var s=n.size[0]*r[1],u=n.size[1]*r[2];return"nearest"===n.interpolation?EA.resizeNearestNeighbor(t,[s,u]):EA.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}(ZO);Kz.className="UpSampling2D",WI(Kz);var Xz=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=LO(t.depthwiseInitializer||n.DEFAULT_KERNEL_INITIALIZER),n.depthwiseConstraint=gM(t.depthwiseConstraint),n.depthwiseRegularizer=kz(t.depthwiseRegularizer),n}Nv(t,e);var n=t.prototype;return n.build=function(e){if((e=WO(e)).length<4)throw new iD("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 iD("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 ZI((function(){e=BO(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"),ZI((function(){null==o&&(o="channelsLast"),PD(o);var e=Fz(t,o);if(4!==t.rank)throw new iD("Input for depthwiseConv2d is required to be 4-D, but is instead "+t.rank+"-D");if(4!==r.rank)throw new iD("depthwiseKernel is required to be 4-D, but is instead "+r.rank+"-D");return e=mT(e,r,a,"same"===i?"same":"valid","NHWC",s),"channelsFirst"===o&&(e=nI(e,[0,3,1,2])),e})));return n.useBias&&(u=hO(u,n.bias.read(),n.dataFormat)),null!=n.activation&&(u=n.activation.apply(u)),u}))},n.computeOutputShape=function(e){e=WO(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=Az(t,this.kernelSize[0],this.padding,this.strides[0]),i=Az(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=MO(this.depthwiseInitializer),t.depthwiseRegularizer=xz(this.depthwiseRegularizer),t.depthwiseConstraint=mM(this.depthwiseRegularizer),t},t}(zz);function Yz(e,t,n,r){if(Array.isArray(e)){if(null!=t||null!=n)throw new iD("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 Jz(e,t,n,r,a,i,o,s){return void 0===r&&(r=!1),void 0===o&&(o=!1),void 0===s&&(s=!1),ZI((function(){var u=t.shape.length;if(u<3)throw new iD("Input should be at least 3D, but is "+u+"D.");var l=[1,0].concat(ZD(2,u));if(t=nI(t,l),null!=i)throw new oD("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=DN(DN(a,"bool"),"float32")).rank===u-1&&(a=ET(a,-1)),a=nI(a,l)),r&&(t=pC(t,0),null!=a&&(a=pC(a,0)));var c,p,h=[],f=n,d=t.shape[0],m=QC(t);null!=a&&(p=QC(a));for(var v,g=function(t){var n=m[t],r=ZI((function(){return e(n,f)}));if(null==a)c=r[0],f=r[1];else{var i=ZI((function(){var e=p[t],n=eE(DE(e),e);return{output:rS(oS(r[0],e),oS(f[0],n)),newStates:f.map((function(t,a){return rS(oS(r[1][a],e),oS(t,n))}))}}));c=i.output,f=i.newStates}s&&h.push(c)},y=0;y<d;++y)g(y);if(s){v=BC(h,1)}return[c,v,f]}))}Xz.className="DepthwiseConv2D",WI(Xz);var Zz=function(e){function t(t){var n,r;if(n=e.call(this,t)||this,null==t.cell)throw new iD("cell property is missing for the constructor of RNN.");if(null==(r=Array.isArray(t.cell)?new iP({cells:t.cell}):t.cell).stateSize)throw new iD("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 qO({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_?ZD(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){zO(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 ZI((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 oD("Constants support is not implemented in RNN yet.");zO(e)&&(e=e[0]),e=e;var t=this.stateful?e[0]:null,n=e.slice(2);this.inputSpec[0]=new qO({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 iD("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 qO({shape:[null,e]})}));this.stateful&&this.resetStates()},n.resetStates=function(e,t){var n=this;void 0===t&&(t=!1),ZI((function(){if(!n.stateful)throw new rD("Cannot call resetStates() on an RNN Layer that is not stateful.");var r=n.inputSpec[0].shape[0];if(null==r)throw new iD("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 wE([r,e])})):n.states_=[wE([r,n.cell.stateSize])];else if(null==e)QI(n.states_),null!=n.keptStates&&(QI(n.keptStates),n.keptStates=[]),Array.isArray(n.cell.stateSize)?n.states_=n.cell.stateSize.map((function(e){return wE([r,e])})):n.states_[0]=wE([r,n.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==n.states_.length)throw new iD("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()):QI(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 iD("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 $I(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=Yz(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 qO({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 KO){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 ZI((function(){var r=null==t?null:t.mask,a=null==t?null:t.training,i=null==t?null:t.initialState;e=BO(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 iD("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=Jz((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 ZI((function(){var n=wE(e.shape);return n=eO(n=tE(n,[1,2])),Array.isArray(t.cell.stateSize)?t.cell.stateSize.map((function(e){return e>1?oO(n,[1,e]):n})):t.cell.stateSize>1?[oO(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=FM(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}(ZO);Zz.className="RNN",WI(Zz);var Qz=function(e){function t(){return e.apply(this,arguments)||this}return Nv(t,e),t}(ZO),$z=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,SD(n.units,"units"),n.activation=mz(null==t.activation?n.DEFAULT_ACTIVATION:t.activation),n.useBias=null==t.useBias||t.useBias,n.kernelInitializer=LO(t.kernelInitializer||n.DEFAULT_KERNEL_INITIALIZER),n.recurrentInitializer=LO(t.recurrentInitializer||n.DEFAULT_RECURRENT_INITIALIZER),n.biasInitializer=LO(t.biasInitializer||n.DEFAULT_BIAS_INITIALIZER),n.kernelRegularizer=kz(t.kernelRegularizer),n.recurrentRegularizer=kz(t.recurrentRegularizer),n.biasRegularizer=kz(t.biasRegularizer),n.kernelConstraint=gM(t.kernelConstraint),n.recurrentConstraint=gM(t.recurrentConstraint),n.biasConstraint=gM(t.biasConstraint),n.dropout=YD([1,JD([0,null==t.dropout?0:t.dropout])]),n.recurrentDropout=YD([1,JD([0,null==t.recurrentDropout?0:t.recurrentDropout])]),n.dropoutFunc=t.dropoutFunc,n.stateSize=n.units,n.dropoutMask=null,n.recurrentDropoutMask=null,n}Nv(t,e);var n=t.prototype;return n.build=function(e){e=WO(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 ZI((function(){if(2!==(e=e).length)throw new iD("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=oP({ones:function(){return DE(e)},rate:n.dropout,training:i,dropoutFunc:n.dropoutFunc})),0<n.recurrentDropout&&n.recurrentDropout<1&&null==n.recurrentDropoutMask&&(n.recurrentDropoutMask=oP({ones:function(){return DE(r)},rate:n.recurrentDropout,training:i,dropoutFunc:n.dropoutFunc}));var o=n.dropoutMask,s=n.recurrentDropoutMask;a=uO(null!=o?oS(e,o):e,n.kernel.read()),null!=n.bias&&(a=hO(a,n.bias.read())),null!=s&&(r=oS(r,s));var u=rS(a,uO(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:fz(this.activation),useBias:this.useBias,kernelInitializer:MO(this.kernelInitializer),recurrentInitializer:MO(this.recurrentInitializer),biasInitializer:MO(this.biasInitializer),kernelRegularizer:xz(this.kernelRegularizer),recurrentRegularizer:xz(this.recurrentRegularizer),biasRegularizer:xz(this.biasRegularizer),activityRegularizer:xz(this.activityRegularizer),kernelConstraint:mM(this.kernelConstraint),recurrentConstraint:mM(this.recurrentConstraint),biasConstraint:mM(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign({},t,n)},t}(Qz);$z.className="SimpleRNNCell",WI($z);var eP=function(e){function t(t){return t.cell=new $z(t),e.call(this,t)||this}return Nv(t,e),t.prototype.call=function(t,n){var r=this;return ZI((function(){null!=r.cell.dropoutMask&&(QI(r.cell.dropoutMask),r.cell.dropoutMask=null),null!=r.cell.recurrentDropoutMask&&(QI(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}(Zz);eP.className="SimpleRNN",WI(eP);var tP=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 iD("GRUCell does not support reset_after parameter set to true.");return n.units=t.units,SD(n.units,"units"),n.activation=mz(void 0===t.activation?n.DEFAULT_ACTIVATION:t.activation),n.recurrentActivation=mz(void 0===t.recurrentActivation?n.DEFAULT_RECURRENT_ACTIVATION:t.recurrentActivation),n.useBias=null==t.useBias||t.useBias,n.kernelInitializer=LO(t.kernelInitializer||n.DEFAULT_KERNEL_INITIALIZER),n.recurrentInitializer=LO(t.recurrentInitializer||n.DEFAULT_RECURRENT_INITIALIZER),n.biasInitializer=LO(t.biasInitializer||n.DEFAULT_BIAS_INITIALIZER),n.kernelRegularizer=kz(t.kernelRegularizer),n.recurrentRegularizer=kz(t.recurrentRegularizer),n.biasRegularizer=kz(t.biasRegularizer),n.kernelConstraint=gM(t.kernelConstraint),n.recurrentConstraint=gM(t.recurrentConstraint),n.biasConstraint=gM(t.biasConstraint),n.dropout=YD([1,JD([0,null==t.dropout?0:t.dropout])]),n.recurrentDropout=YD([1,JD([0,null==t.recurrentDropout?0:t.recurrentDropout])]),n.dropoutFunc=t.dropoutFunc,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=WO(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 ZI((function(){if(2!==(e=e).length)throw new iD("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=oP({ones:function(){return DE(e)},rate:n.dropout,training:r,count:3,dropoutFunc:n.dropoutFunc})),0<n.recurrentDropout&&n.recurrentDropout<1&&null==n.recurrentDropoutMask&&(n.recurrentDropoutMask=oP({ones:function(){return DE(a)},rate:n.recurrentDropout,training:r,count:3,dropoutFunc:n.dropoutFunc}));var i,o,s,u=n.dropoutMask,l=n.recurrentDropoutMask;0<n.dropout&&n.dropout<1&&(e=oS(e,u[0]));var c=uO(e,n.kernel.read());n.useBias&&(c=hO(c,n.bias.read())),0<n.recurrentDropout&&n.recurrentDropout<1&&(a=oS(a,l[0]));var p=n.recurrentKernel.read(),h=OC(p,[2*n.units,n.units],p.rank-1),f=h[0],d=h[1],m=uO(a,f),v=OC(c,3,c.rank-1),g=v[0],y=v[1],b=v[2],x=OC(m,2,m.rank-1),w=x[0],k=x[1];i=n.recurrentActivation.apply(rS(g,w)),o=n.recurrentActivation.apply(rS(y,k));var N=uO(oS(o,a),d);s=n.activation.apply(rS(b,N));var I=rS(oS(i,a),oS(rS(1,JT(i)),s));return[I,I]}))},n.getConfig=function(){var t=e.prototype.getConfig.call(this),n={units:this.units,activation:fz(this.activation),recurrentActivation:fz(this.recurrentActivation),useBias:this.useBias,kernelInitializer:MO(this.kernelInitializer),recurrentInitializer:MO(this.recurrentInitializer),biasInitializer:MO(this.biasInitializer),kernelRegularizer:xz(this.kernelRegularizer),recurrentRegularizer:xz(this.recurrentRegularizer),biasRegularizer:xz(this.biasRegularizer),activityRegularizer:xz(this.activityRegularizer),kernelConstraint:mM(this.kernelConstraint),recurrentConstraint:mM(this.recurrentConstraint),biasConstraint:mM(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign({},t,n)},t}(Qz);tP.className="GRUCell",WI(tP);var nP=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 tP(t),e.call(this,t)||this}return Nv(t,e),t.prototype.call=function(t,n){var r=this;return ZI((function(){null!=r.cell.dropoutMask&&(QI(r.cell.dropoutMask),r.cell.dropoutMask=null),null!=r.cell.recurrentDropoutMask&&(QI(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}(Zz);nP.className="GRU",WI(nP);var rP=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,SD(n.units,"units"),n.activation=mz(void 0===t.activation?n.DEFAULT_ACTIVATION:t.activation),n.recurrentActivation=mz(void 0===t.recurrentActivation?n.DEFAULT_RECURRENT_ACTIVATION:t.recurrentActivation),n.useBias=null==t.useBias||t.useBias,n.kernelInitializer=LO(t.kernelInitializer||n.DEFAULT_KERNEL_INITIALIZER),n.recurrentInitializer=LO(t.recurrentInitializer||n.DEFAULT_RECURRENT_INITIALIZER),n.biasInitializer=LO(t.biasInitializer||n.DEFAULT_BIAS_INITIALIZER),n.unitForgetBias=t.unitForgetBias,n.kernelRegularizer=kz(t.kernelRegularizer),n.recurrentRegularizer=kz(t.recurrentRegularizer),n.biasRegularizer=kz(t.biasRegularizer),n.kernelConstraint=gM(t.kernelConstraint),n.recurrentConstraint=gM(t.recurrentConstraint),n.biasConstraint=gM(t.biasConstraint),n.dropout=YD([1,JD([0,null==t.dropout?0:t.dropout])]),n.recurrentDropout=YD([1,JD([0,null==t.recurrentDropout?0:t.recurrentDropout])]),n.dropoutFunc=t.dropoutFunc,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=WO(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 bO).apply([i]),o=a.apply([2*i]);return iO(iO(n,r),o)},t}(gO)).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 ZI((function(){var r=null!=t.training&&t.training;if(3!==(e=e).length)throw new iD("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=oP({ones:function(){return DE(e)},rate:n.dropout,training:r,count:4,dropoutFunc:n.dropoutFunc})),0<n.recurrentDropout&&n.recurrentDropout<1&&null==n.recurrentDropoutMask&&(n.recurrentDropoutMask=oP({ones:function(){return DE(a)},rate:n.recurrentDropout,training:r,count:4,dropoutFunc:n.dropoutFunc}));var o,s,u,l,c=n.dropoutMask,p=n.recurrentDropoutMask;0<n.dropout&&n.dropout<1&&(e=oS(e,c[0]));var h=uO(e,n.kernel.read());0<n.recurrentDropout&&n.recurrentDropout<1&&(a=oS(a,p[0])),h=rS(h,uO(a,n.recurrentKernel.read())),n.useBias&&(h=hO(h,n.bias.read()));var f=OC(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=rS(oS(s,i),oS(o,n.activation.apply(v))),l=n.recurrentActivation.apply(g);var y=oS(l,n.activation.apply(u));return[y,y,u]}))},n.getConfig=function(){var t=e.prototype.getConfig.call(this),n={units:this.units,activation:fz(this.activation),recurrentActivation:fz(this.recurrentActivation),useBias:this.useBias,kernelInitializer:MO(this.kernelInitializer),recurrentInitializer:MO(this.recurrentInitializer),biasInitializer:MO(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:xz(this.kernelRegularizer),recurrentRegularizer:xz(this.recurrentRegularizer),biasRegularizer:xz(this.biasRegularizer),activityRegularizer:xz(this.activityRegularizer),kernelConstraint:mM(this.kernelConstraint),recurrentConstraint:mM(this.recurrentConstraint),biasConstraint:mM(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return Object.assign({},t,n)},t}(Qz);rP.className="LSTMCell",WI(rP);var aP=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 rP(t),e.call(this,t)||this}return Nv(t,e),t.prototype.call=function(t,n){var r=this;return ZI((function(){null!=r.cell.dropoutMask&&(QI(r.cell.dropoutMask),r.cell.dropoutMask=null),null!=r.cell.recurrentDropoutMask&&(QI(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}(Zz);aP.className="LSTM",WI(aP);var iP=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 ZI((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;zO(e)&&(e=e[0]),e=e,this.cells.forEach((function(n,r){VD("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(FM(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 jO(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]]);HO(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}(Qz);function oP(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=e.dropoutFunc,u=function(){return null!=s?s(t(),n):fO(t(),n)},l=function(){return dO(u,t,a)};return!o||o<=1?$I(l().clone()):Array(o).fill(void 0).map(l).map((function(e){return $I(e.clone())}))}iP.className="StackedRNNCells",WI(iP);var sP=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},uP=function(e){function t(t){var n;if(t.unroll)throw new oD("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(t.cell))throw new oD("It is not possible at the moment to stack convolutional cells.");return(n=e.call(this,t)||this).inputSpec=[new qO({ndim:5})],n}Nv(t,e);var n=t.prototype;return n.call=function(t,n){var r=this;return ZI((function(){if(null!=r.cell.dropoutMask&&(QI(r.cell.dropoutMask),r.cell.dropoutMask=null),null!=r.cell.recurrentDropoutMask&&(QI(r.cell.recurrentDropoutMask),r.cell.recurrentDropoutMask=null),n&&n.constants)throw new iD("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 ZI((function(){var n=t.cell.stateSize,r=e.shape,a=t.computeSingleOutputShape(r),i=wE([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),ZI((function(){if(!n.stateful)throw new rD("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 iD("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 wE(i)})):n.states_=[wE(i)];else if(null==e)QI(n.states_),null!=n.keptStates&&(QI(n.keptStates),n.keptStates=[]),Array.isArray(n.cell.stateSize)?n.states_=n.cell.stateSize.map((function(){return wE(i)})):n.states_[0]=wE(i);else{if(Array.isArray(e)||(e=[e]),e.length!==n.states_.length)throw new iD("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()):QI(n.states_);for(var o=0;o<n.states_.length;++o){var s=e[o],u=i;if(!qv(s.shape,u))throw new iD("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 $I(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=Az(l,a[0],i,o[0],s[0]),h=Az(c,a[1],i,o[1],s[1]);return[].concat(e.slice(0,2),u?[r,p,h]:[p,h,r])},t}(Zz);uP.className="ConvRNN2D";var lP=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,SD(n.filters,"filters"),n.kernelSize=Rz(a,2,"kernelSize"),n.kernelSize.forEach((function(e){return SD(e,"kernelSize")})),n.strides=Rz(i||1,2,"strides"),n.strides.forEach((function(e){return SD(e,"strides")})),n.padding=o||"valid",BD(n.padding),n.dataFormat=s||"channelsLast",PD(n.dataFormat),n.dilationRate=Rz(u||1,2,"dilationRate"),n.dilationRate.forEach((function(e){return SD(e,"dilationRate")})),n}Nv(t,e);var n=t.prototype;return n.build=function(e){var t;e=WO(e);var n="channelsFirst"===this.dataFormat?1:e.length-1;if(null==e[n])throw new iD("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 aO([s.apply([u]),kE([u]),s.apply([2*u])])},t}(gO)).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 ZI((function(){if(3!==e.length)throw new iD("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=oP({ones:function(){return DE(a)},rate:n.dropout,training:r,count:4,dropoutFunc:n.dropoutFunc}));var s=n.dropoutMask,u=function(e,t,n){return t&&t[n]?oS(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=oP({ones:function(){return DE(i)},rate:n.recurrentDropout,training:r,count:4,dropoutFunc:n.dropoutFunc}));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=OC(n.kernel.read(),4,3),b=y[0],x=y[1],w=y[2],k=y[3],N=n.useBias?OC(n.bias.read(),4):[null,null,null,null],I=N[0],S=N[1],T=N[2],E=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,E,n.padding);var C=OC(n.recurrentKernel.read(),4,3),R=C[0],A=C[1],_=C[2],F=C[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(rS(l,d)),O=n.recurrentActivation.apply(rS(c,m)),M=rS(oS(O,o),oS(D,n.activation.apply(rS(p,v)))),L=oS(n.recurrentActivation.apply(rS(h,g)),n.activation.apply(M));return[L,L,M]}))},n.getConfig=function(){var t=e.prototype.getConfig.call(this),n=(t.units,sP(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=nT(e,t,this.strides,r||"valid","channelsFirst"===this.dataFormat?"NCHW":"NHWC",this.dilationRate);return n?hO(a,n,this.dataFormat):a},n.recurrentConv=function(e,t){return nT(e,t,1,"same","channelsFirst"===this.dataFormat?"NCHW":"NHWC")},t}(rP);lP.className="ConvLSTM2DCell",WI(lP);var cP=function(e){function t(t){var n=new lP(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}(uP);cP.className="ConvLSTM2D",WI(cP);var pP=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 ZI((function(){n.invokeCallHook(e,t);var r=BO(e);if(0<n.rate&&n.rate<1){var a=null!=t.training&&t.training,i=n.getNoiseShape(r);return dO((function(){return fO(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}(ZO);pP.className="Dropout",WI(pP);var hP=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}(pP);hP.className="SpatialDropout1D",WI(hP);var fP=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,SD(n.units,"units"),n.activation=mz(t.activation),null!=t.useBias&&(n.useBias=t.useBias),n.kernelInitializer=LO(t.kernelInitializer||n.DEFAULT_KERNEL_INITIALIZER),n.biasInitializer=LO(t.biasInitializer||n.DEFAULT_BIAS_INITIALIZER),n.kernelConstraint=gM(t.kernelConstraint),n.biasConstraint=gM(t.biasConstraint),n.kernelRegularizer=kz(t.kernelRegularizer),n.biasRegularizer=kz(t.biasRegularizer),n.activityRegularizer=kz(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=WO(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=WO(e)).slice();return t[t.length-1]=this.units,t},n.call=function(e,t){var n=this;return ZI((function(){n.invokeCallHook(e,t);var r,a=BO(e),i=ED(n.activation.getClassName());return null!=i?r=uO(a,n.kernel.read(),i,n.bias?n.bias.read():null):(r=uO(a,n.kernel.read()),null!=n.bias&&(r=hO(r,n.bias.read())),null!=n.activation&&(r=n.activation.apply(r))),r}))},n.getConfig=function(){var t={units:this.units,activation:fz(this.activation),useBias:this.useBias,kernelInitializer:MO(this.kernelInitializer),biasInitializer:MO(this.biasInitializer),kernelRegularizer:xz(this.kernelRegularizer),biasRegularizer:xz(this.biasRegularizer),activityRegularizer:xz(this.activityRegularizer),kernelConstraint:mM(this.kernelConstraint),biasConstraint:mM(this.biasConstraint)},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(ZO);fP.className="Dense",WI(fP);var dP=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=WO(e)).slice(1));!(t=n()).done;){if(null==t.value)throw new iD('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],XD(e,1)]},n.call=function(e,t){var n=this;return ZI((function(){n.invokeCallHook(e,t);var r=BO(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=nI(r,a)}return function(e){if(e.rank<=1)throw new iD("batchFlatten requires a minimum rank of 2. 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e=BO(e),t=e,r=n.n,ZI((function(){if(2!==t.shape.length)throw new iD("repeat() expects a rank-2 tensor, but received a rank-"+t.shape.length+" tensor.");return oO(eO(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}(ZO);vP.className="RepeatVector",WI(vP);var gP=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 iD("Can only specifiy one unknown dimension.");i=o}else a*=s}var u=XD(e);if(null!==i){if(0===a||u%a!=0)throw new iD(n);r[i]=u/a}else if(u!==a)throw new iD(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 ZI((function(){n.invokeCallHook(e,t);var r=BO(e),a=r.shape,i=a.slice(0,1).concat(n.fixUnknownDimension(a.slice(1),n.targetShape));return OS(r,i)}))},n.getConfig=function(){var t={targetShape:this.targetShape},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(ZO);gP.className="Reshape",WI(gP);var yP=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=ZD(1,t.dims.length+1);if(!qv(t.dims.slice().sort(),r))throw new Error("Invalid permutation `dims`: 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hS(FE(n,this.maskValue),-1)},n.call=function(e,t){var n=this;return ZI((function(){n.invokeCallHook(e,t);var r=BO(e),a=hS(FE(r,n.maskValue),-1,!0);return oS(r,DN(a,r.dtype))}))},t}(ZO);bP.className="Masking",WI(bP);var xP=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(fD(t.inputLength))}return n.inputDim=t.inputDim,SD(n.inputDim,"inputDim"),n.outputDim=t.outputDim,SD(n.outputDim,"outputDim"),n.embeddingsInitializer=LO(t.embeddingsInitializer||n.DEFAULT_EMBEDDINGS_INITIALIZER),n.embeddingsRegularizer=kz(t.embeddingsRegularizer),n.activityRegularizer=kz(t.activityRegularizer),n.embeddingsConstraint=gM(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 ZI((function(){return n.maskZero?(e=BO(e),FE(e,xT(e))):null}))},n.computeOutputShape=function(e){if(e=WO(e),null==this.inputLength)return[].concat(e,[this.outputDim]);var t=fD(this.inputLength);if(t.length!==e.length-1)throw new iD('"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 iD('"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 ZI((function(){n.invokeCallHook(e,t);var r=BO(e);"int32"!==r.dtype&&(r=$D(r,"int32"));var a=lO(n.embeddings.read(),OS(r,[r.size]));return OS(a,WO(n.computeOutputShape(r.shape)))}))},n.getConfig=function(){var t={inputDim:this.inputDim,outputDim:this.outputDim,embeddingsInitializer:MO(this.embeddingsInitializer),embeddingsRegularizer:xz(this.embeddingsRegularizer),activityRegularizer:xz(this.activityRegularizer),embeddingsConstraint:mM(this.embeddingsConstraint),maskZero:this.maskZero,inputLength:this.inputLength},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(ZO);xP.className="Embedding",WI(xP);var wP=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 oD},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 iD("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=[WO(e)]),(e=e).length<2)throw new iD("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=wD(n)).length>1)throw new iD("Can not merge tensors with different batch sizes. 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Got input shapes: "+JSON.stringify(e))}},n.mergeFunction=function(e){var t=this;return ZI((function(){return aO(e,t.axis)}))},n.computeOutputShape=function(e){if(!Array.isArray(e)||!Array.isArray(e[0]))throw new iD("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 iD("`mask` should be an array for Concatenate");if(!Array.isArray(e))throw new iD("`inputs` should be an array for Concatenate");if(t.length!==e.length)throw new iD("Mismatch in the length of mask ("+t.length+") and the legnth of inputs ("+e.length+")");return ZI((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(DN(DE(e[i]),"bool")):t[i].rank<e[i].rank?a.push(ET(t[i],-1)):a.push(t[i]);var o=zS(a,n.axis);return pS(o,-1,!1)}))},n.getConfig=function(){var t={axis:this.axis},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(wP);function CP(e,t){for(;e<0;)e+=t;return e}EP.className="Concatenate",WI(EP);var RP=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){Uv(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 oD("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 iD("Dimension incompatibility: "+t[r[0]]+" !== "+n[r[1]])},n.mergeFunction=function(e){if(2!==e.length)throw new iD("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=DM(n,t[0]),r=DM(r,t[1])),function(e,t,n){if(e.shape.length>3||t.shape.length>3)throw new oD("batchDot is not implemented for tensors of 4D or higher rank yet");if(Uv(e.shape.length>=2,(function(){return"batchDot requires the rank of x to be >= 2, but got "+e.shape.length})),Uv(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 oD("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 ZI((function(){var n,o;if(r>a){n=r-a;for(var s=[],u=0;u<n;++u)s.push(1);t=OS(t,t.shape.concat(s))}else if(a>r){n=a-r;for(var l=[],c=0;c<n;++c)l.push(1);e=OS(e,e.shape.concat(l))}else n=0;if(2===e.shape.length&&2===t.shape.length)o=i[0]===i[1]?tE(oS(e,t),i[0]):tE(oS(nI(e,[1,0]),t),i[1]);else{var p=i[0]!==e.shape.length-1,h=i[1]===t.shape.length-1;o=eI(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=PC(o,d)}return 1===o.shape.length&&(o=ET(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){Uv(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 oD("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}(wP);RP.className="Dot",WI(RP);var AP=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 ZI((function(){n.invokeCallHook(e,t);var r=BO(e);return dO((function(){return rS(sO(r.shape,0,n.stddev),r)}),(function(){return r}),t.training||!1)}))},t}(ZO);AP.className="GaussianNoise",WI(AP);var _P=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 ZI((function(){n.invokeCallHook(e,t);var r=BO(e);if(n.rate>0&&n.rate<1){return dO((function(){var e=Math.sqrt(n.rate/(1-n.rate));return oS(r,sO(r.shape,1,e))}),(function(){return r}),t.training||!1)}return r}))},t}(ZO);_P.className="GaussianDropout",WI(_P);var FP=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||BO(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 ZI((function(){if(n.rate<1&&n.rate>0){var r=n._getNoiseShape(e);return dO((function(){var t=BO(e),a=-1.7580993408473766,i=MT(iC(r),n.rate);i=$D(i,"float32");var o=Math.pow((1-n.rate)*(1+n.rate*Math.pow(a,2)),-.5),s=-o*a*n.rate,u=rS(oS(t,i),oS(rS(i,-1),a));return rS(oS(u,o),s)}),(function(){return BO(e)}),t.training||!1)}return e}))},t}(ZO);function DP(e,t,n,r,a,i){var o;if(void 0===i&&(i=.001),2===e.rank)o=jS(e,t,n,r,a,i);else if(3===e.rank)o=HS(e,t,n,r,a,i);else{if(4!==e.rank)throw new oD("batchNormalization is not implemented for array of rank "+e.rank+" yet");o=qS(e,t,n,r,a,i)}return o}function OP(e,t,n,r,a){return void 0===a&&(a=.001),qv(r.slice().sort(),ZD(0,e.rank-1))?function(e,t,n,r,a){return void 0===a&&(a=.001),ZI((function(){var i=RE(e,r),o=i.mean,s=i.variance;return[DP(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),ZI((function(){for(var i,o=RE(e,r),s=o.mean,u=o.variance,l=[],c=Fv(ZD(0,e.rank));!(i=c()).done;){var p=i.value;-1!==r.indexOf(p)?l.push(1):l.push(e.shape[p])}var h=OS(s,l),f=OS(u,l),d=null==t?null:OS(t,l),m=null==n?null:OS(n,l);return[DP(e,h,f,m,d,a),s,u]}))}(e,t,n,r,a)}FP.className="AlphaDropout",WI(FP);var MP=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=LO(t.betaInitializer||"zeros"),n.gammaInitializer=LO(t.gammaInitializer||"ones"),n.movingMeanInitializer=LO(t.movingMeanInitializer||"zeros"),n.movingVarianceInitializer=LO(t.movingVarianceInitializer||"ones"),n.betaConstraint=gM(t.betaConstraint),n.gammaConstraint=gM(t.gammaConstraint),n.betaRegularizer=kz(t.betaRegularizer),n.gammaRegularizer=kz(t.gammaRegularizer),n}Nv(t,e);var n=t.prototype;return n.build=function(e){var t;e=WO(e);var n=this.axis>=0?this.axis:this.axis+e.length,r=e[n];if(null==r)throw new iD("Axis "+n+" of input tensor should have a defined dimension but the layer received an input with shape "+JSON.stringify(e)+".");this.inputSpec=[new qO({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 ZI((function(){var r=null!=t.training&&t.training,a=BO(e),i=a.shape,o=i.length,s=ZD(0,o),u=n.axis>=0?n.axis:n.axis+o;s.splice(u,1);var l=lD(1,o);l[u]=i[u];var c=s.slice();c.sort();var p=!qv(c,ZD(0,o).slice(0,o-1));if(!r)return function(){if(p){var e=OS(n.movingMean.read(),l),t=OS(n.movingVariance.read(),l),r=n.center?OS(n.beta.read(),l):null,i=n.scale?OS(n.gamma.read(),l):null;return DP(a,e,t,r,i,n.epsilon)}return DP(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=OP(a,n.gamma.read(),n.beta.read(),s,n.epsilon),f=h[0],d=h[1],m=h[2],v=function(e,t,n){ZI((function(){var r=1-n,a=e.read(),i=oS(eE(a,t),r);e.write(eE(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:MO(this.betaInitializer),gammaInitializer:MO(this.gammaInitializer),movingMeanInitializer:MO(this.movingMeanInitializer),movingVarianceInitializer:MO(this.movingVarianceInitializer),betaRegularizer:xz(this.betaRegularizer),gammaRegularizer:xz(this.gammaRegularizer),betaConstraint:mM(this.betaConstraint),gammaConstraint:mM(this.gammaConstraint)},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(ZO);MP.className="BatchNormalization",WI(MP);var LP=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=LO(t.betaInitializer||"zeros"),n.gammaInitializer=LO(t.gammaInitializer||"ones"),n.betaRegularizer=kz(t.betaRegularizer),n.gammaRegularizer=kz(t.gammaRegularizer),n.supportsMasking=!0,n}Nv(t,e);var n=t.prototype;return n.build=function(e){var t=(e=WO(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!==wD(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=BO(e),a=r.shape,i=a.length;return ZI((function(){for(var e,t=RE(r,n.axis,!0),o=t.mean,s=t.variance,u=lD(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?OS(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=RT(o,d),s=RT(s,d),h=RT(h,m),f=RT(f,m),DP(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:MO(this.betaInitializer),gammaInitializer:MO(this.gammaInitializer),betaRegularizer:xz(this.betaRegularizer),gammaRegularizer:xz(this.gammaRegularizer)},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(ZO);LP.className="LayerNormalization",WI(LP);var zP=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 iD("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 iD("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 iD("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 qO({ndim:4})],n}Nv(t,e);var n=t.prototype;return n.computeOutputShape=function(e){var t,n;return e=WO(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 ZI((function(){return t=BO(e),r=n.padding,a=n.dataFormat,ZI((function(){if(4!==t.rank)throw new iD("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 iD("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 iD("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]],ME(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}(ZO);function PP(e,t,n,r,a,i){return ZI((function(){var o;PD(a),WD(i),BD(r),null==n&&(n=[1,1]),null==r&&(r="valid"),null==a&&(a="channelsLast"),null==i&&(i="max"),e=Fz(e,a);var s="same"===r?"same":"valid";return o="max"===i?vE(e,t,n,s):MS(e,t,n,s),"channelsFirst"===a&&(o=nI(o,[0,3,1,2])),o}))}function BP(e,t,n,r,a,i){return ZI((function(){var o;PD(a),WD(i),BD(r),null==n&&(n=[1,1,1]),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?gE(e,t,n,s):LS(e,t,n,s),"channelsFirst"===a&&(o=nI(o,[0,4,1,2,3])),o}))}zP.className="ZeroPadding2D",WI(zP);var WP=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 iD("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(SD(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 iD("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 SD(n.strides,"strides"),n.padding=null==t.padding?"valid":t.padding,BD(n.padding),n.inputSpec=[new qO({ndim:3})],n}Nv(t,e);var n=t.prototype;return n.computeOutputShape=function(e){var t=Az((e=WO(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 ZI((function(){n.invokeCallHook(e,t),e=eO(BO(e),2);var r=n.poolingFunction(BO(e),[n.poolSize[0],1],[n.strides[0],1],n.padding,"channelsLast");return PC(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}(ZO),UP=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 PD(a),BD(r),PP(e,t,n,r,a,"max")},t}(WP);UP.className="MaxPooling1D",WI(UP);var VP=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 PD(a),BD(r),PP(e,t,n,r,a,"avg")},t}(WP);VP.className="AveragePooling1D",WI(VP);var GP=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 iD("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 SD(n.poolSize,"poolSize"),SD(n.strides,"strides"),n.padding=null==t.padding?"valid":t.padding,n.dataFormat=null==t.dataFormat?"channelsLast":t.dataFormat,PD(n.dataFormat),BD(n.padding),n.inputSpec=[new qO({ndim:4})],n}Nv(t,e);var n=t.prototype;return n.computeOutputShape=function(e){e=WO(e);var t="channelsFirst"===this.dataFormat?e[2]:e[1],n="channelsFirst"===this.dataFormat?e[3]:e[2];return t=Az(t,this.poolSize[0],this.padding,this.strides[0]),n=Az(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 ZI((function(){return n.invokeCallHook(e,t),n.poolingFunction(BO(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}(ZO),jP=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 PD(a),BD(r),PP(e,t,n,r,a,"max")},t}(GP);jP.className="MaxPooling2D",WI(jP);var HP=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 PD(a),BD(r),PP(e,t,n,r,a,"avg")},t}(GP);HP.className="AveragePooling2D",WI(HP);var qP=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 iD("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 SD(n.poolSize,"poolSize"),SD(n.strides,"strides"),n.padding=null==t.padding?"valid":t.padding,n.dataFormat=null==t.dataFormat?"channelsLast":t.dataFormat,PD(n.dataFormat),BD(n.padding),n.inputSpec=[new qO({ndim:5})],n}Nv(t,e);var n=t.prototype;return n.computeOutputShape=function(e){e=WO(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=Az(t,this.poolSize[0],this.padding,this.strides[0]),n=Az(n,this.poolSize[1],this.padding,this.strides[1]),r=Az(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 ZI((function(){return n.invokeCallHook(e,t),n.poolingFunction(BO(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}(ZO),KP=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 PD(a),BD(r),BP(e,t,n,r,a,"max")},t}(qP);KP.className="MaxPooling3D",WI(KP);var XP=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 PD(a),BD(r),BP(e,t,n,r,a,"avg")},t}(qP);XP.className="AveragePooling3D",WI(XP);var YP=function(e){function t(t){var n;return(n=e.call(this,t)||this).inputSpec=[new qO({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 oD},t}(ZO),JP=function(e){function t(t){return e.call(this,t||{})||this}return Nv(t,e),t.prototype.call=function(e,t){return ZI((function(){var t=BO(e);return xE(t,1)}))},t}(YP);JP.className="GlobalAveragePooling1D",WI(JP);var ZP=function(e){function t(t){return e.call(this,t||{})||this}return Nv(t,e),t.prototype.call=function(e,t){return ZI((function(){var t=BO(e);return $T(t,1)}))},t}(YP);ZP.className="GlobalMaxPooling1D",WI(ZP);var QP=function(e){function t(t){var n;return(n=e.call(this,t)||this).dataFormat=null==t.dataFormat?"channelsLast":t.dataFormat,PD(n.dataFormat),n.inputSpec=[new qO({ndim:4})],n}Nv(t,e);var n=t.prototype;return n.computeOutputShape=function(e){return e=e,"channelsLast"===this.dataFormat?[e[0],e[3]]:[e[0],e[1]]},n.call=function(e,t){throw new oD},n.getConfig=function(){var t={dataFormat:this.dataFormat},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(ZO),$P=function(e){function t(){return e.apply(this,arguments)||this}return Nv(t,e),t.prototype.call=function(e,t){var n=this;return ZI((function(){var t=BO(e);return"channelsLast"===n.dataFormat?xE(t,[1,2]):xE(t,[2,3])}))},t}(QP);$P.className="GlobalAveragePooling2D",WI($P);var eB=function(e){function t(){return e.apply(this,arguments)||this}return Nv(t,e),t.prototype.call=function(e,t){var n=this;return ZI((function(){var t=BO(e);return"channelsLast"===n.dataFormat?$T(t,[1,2]):$T(t,[2,3])}))},t}(QP);eB.className="GlobalMaxPooling2D",WI(eB);var tB=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=FM(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}(ZO),nB=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.build=function(t){if((t=WO(t)).length<3)throw new iD("TimeDistributed layer expects an input shape >= 3D, but received input shape "+JSON.stringify(t));this.inputSpec=[{shape:t}];var n=[t[0]].concat(t.slice(2));this.layer.built||(this.layer.build(n),this.layer.built=!0),e.prototype.build.call(this,t)},n.computeOutputShape=function(e){var t=[(e=WO(e))[0]].concat(e.slice(2)),n=this.layer.computeOutputShape(t),r=e[1];return[n[0],r].concat(n.slice(1))},n.call=function(e,t){var n=this;return ZI((function(){return Jz((function(e,r){return[BO(n.layer.call(e,t)),[]]}),e=BO(e),[],!1,null,null,!1,!0)[1]}))},t}(tB);nB.className="TimeDistributed",WI(nB);var rB=function(e){function t(t){var n;n=e.call(this,t)||this;var r=t.layer.getConfig(),a={};a.className=t.layer.getClassName(),a.config=r,n.forwardLayer=FM(a),r.goBackwards=!0!==r.goBackwards;var 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e.t2=e.sent,e.abrupt("return",[e.t2]);case 24:return v=IB("tableHandle",t,n,r,a),g=a.getHashTableById(v.id),e.abrupt("return",[g.tensorSize()]);case 27:throw TypeError("Node type "+t.op+" is not implemented");case 28:case"end":return e.stop()}}),e)})));return function(t,n,r,a){return e.apply(this,arguments)}}();function RW(e,t,n,r){var a=function(e,t,n){switch(e.category){case"arithmetic":return ZI((function(){return function(e,t,n){switch(e.op){case"BiasAdd":case"AddV2":case"Add":return[rS(IB("a",e,t,n),IB("b",e,t,n))];case"AddN":return[cS(IB("tensors",e,t,n))];case"FloorMod":case"Mod":return[EE(IB("a",e,t,n),IB("b",e,t,n))];case"Mul":return[oS(IB("a",e,t,n),IB("b",e,t,n))];case"RealDiv":case"Div":return[iS(IB("a",e,t,n),IB("b",e,t,n))];case"DivNoNan":return[wT(IB("a",e,t,n),IB("b",e,t,n))];case"FloorDiv":return[aS(IB("a",e,t,n),IB("b",e,t,n))];case"Sub":return[eE(IB("a",e,t,n),IB("b",e,t,n))];case"Minimum":return[SE(IB("a",e,t,n),IB("b",e,t,n))];case"Maximum":return[bE(IB("a",e,t,n),IB("b",e,t,n))];case"Pow":return[VE(IB("a",e,t,n),IB("b",e,t,n))];case"SquaredDifference":return[zC(IB("a",e,t,n),IB("b",e,t,n))];default:throw TypeError("Node type "+e.op+" is not implemented")}}(e,t,n)}));case"basic_math":return ZI((function(){return function(e,t,n){switch(e.op){case"Abs":case"ComplexAbs":return[sS(IB("x",e,t,n))];case"Acos":return[uS(IB("x",e,t,n))];case"Acosh":return[lS(IB("x",e,t,n))];case"Asin":return[mS(IB("x",e,t,n))];case"Asinh":return[vS(IB("x",e,t,n))];case"Atan":return[gS(IB("x",e,t,n))];case"Atan2":return[yS(IB("x",e,t,n),IB("y",e,t,n))];case"Atanh":return[bS(IB("x",e,t,n))];case"Ceil":return[JS(IB("x",e,t,n))];case"Complex":return[Ck(IB("real",e,t,n),IB("imag",e,t,n))];case"Cos":return[lT(IB("x",e,t,n))];case"Cosh":return[cT(IB("x",e,t,n))];case"Elu":return[IT(IB("x",e,t,n))];case"Erf":return[ST(IB("x",e,t,n))];case"Exp":return[TT(IB("x",e,t,n))];case"Expm1":return[CT(IB("x",e,t,n))];case"Floor":return[FT(IB("x",e,t,n))];case"Log":return[HT(IB("x",e,t,n))];case"Log1p":return[qT(IB("x",e,t,n))];case"Imag":return[LT(IB("x",e,t,n))];case"Neg":return[JT(IB("x",e,t,n))];case"Reciprocal":return[uC(IB("x",e,t,n))];case"Real":return[sC(IB("x",e,t,n))];case"Relu":return[lC(IB("x",e,t,n))];case"Round":return[vC(IB("x",e,t,n))];case"Selu":return[bC(IB("x",e,t,n))];case"Sigmoid":return[PS(IB("x",e,t,n))];case"Sin":return[IC(IB("x",e,t,n))];case"Sign":return[NC(IB("x",e,t,n))];case"Sinh":return[SC(IB("x",e,t,n))];case"Softplus":return[ZT(IB("x",e,t,n))];case"Sqrt":return[LC(IB("x",e,t,n))];case"Square":return[CE(IB("x",e,t,n))];case"Tanh":return[WS(IB("x",e,t,n))];case"Tan":return[VC(IB("x",e,t,n))];case"ClipByValue":return[ZS(IB("x",e,t,n),IB("clipValueMin",e,t,n),IB("clipValueMax",e,t,n))];case"Relu6":return[cC(IB("x",e,t,n))];case"Rsqrt":return[gC(SB(e.inputNames[0],t,n))];case"Prod":return[jE(IB("x",e,t,n),IB("axes",e,t,n))];case"LeakyRelu":return[WT(IB("x",e,t,n),IB("alpha",e,t,n))];case"Prelu":return[GE(IB("x",e,t,n),IB("alpha",e,t,n))];case"IsNan":return[BT(SB(e.inputNames[0],t,n))];default:throw TypeError("Node type "+e.op+" is not implemented")}}(e,t,n)}));case"control":return NW(e,t,n);case"convolution":return ZI((function(){return function(e,t,n){switch(e.op){case"Conv1D":var r=IB("stride",e,t,n),a=IB("pad",e,t,n),i=IB("dataFormat",e,t,n).toUpperCase(),o=IB("dilation",e,t,n);return[rT(IB("x",e,t,n),IB("filter",e,t,n),r,a,i,o)];case"Conv2D":var s=IB("strides",e,t,n),u=RB(e,t,n),l=IB("dataFormat",e,t,n).toUpperCase(),c=IB("dilations",e,t,n);return[nT(IB("x",e,t,n),IB("filter",e,t,n),[s[1],s[2]],u,l,[c[1],c[2]])];case"_FusedConv2D":var p=IW(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[wR({x:IB("x",e,t,n),filter:IB("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=IW(e,t,n),w=x.stride,k=x.pad,N=x.dataFormat,I=x.dilations,S=x.biasArg,T=x.preluArg,E=x.activationFunc,C=x.leakyreluAlpha;return[IR({x:IB("x",e,t,n),filter:IB("filter",e,t,n),strides:[w[1],w[2]],pad:k,dataFormat:N,dilations:[I[1],I[2]],bias:S,activation:E,preluActivationWeights:T,leakyreluAlpha:C})];case"Conv2DBackpropInput":case"Conv2dTranspose":var R=IB("outputShape",e,t,n),A=IB("strides",e,t,n),_=RB(e,t,n);return[iT(IB("x",e,t,n),IB("filter",e,t,n),R,[A[1],A[2]],_)];case"DepthwiseConv2dNative":case"DepthwiseConv2d":var F=IB("strides",e,t,n),D=RB(e,t,n),O=IB("dilations",e,t,n),M=IB("dataFormat",e,t,n).toUpperCase();return[mT(IB("input",e,t,n),IB("filter",e,t,n),[F[1],F[2]],D,M,[O[1],O[2]])];case"Conv3D":var L=IB("strides",e,t,n),z=IB("pad",e,t,n),P=IB("dataFormat",e,t,n).toUpperCase(),B=IB("dilations",e,t,n);return[oT(IB("x",e,t,n),IB("filter",e,t,n),[L[1],L[2],L[3]],z,P,[B[1],B[2],B[3]])];case"AvgPool":var W=IB("strides",e,t,n),U=IB("pad",e,t,n),V=IB("kernelSize",e,t,n);return[MS(IB("x",e,t,n),[V[1],V[2]],[W[1],W[2]],U)];case"MaxPool":var G=IB("strides",e,t,n),j=IB("pad",e,t,n),H=IB("kernelSize",e,t,n);return[vE(IB("x",e,t,n),[H[1],H[2]],[G[1],G[2]],j)];case"MaxPoolWithArgmax":var q=IB("strides",e,t,n),K=IB("pad",e,t,n),X=IB("kernelSize",e,t,n),Y=IB("includeBatchInIndex",e,t,n),J=yE(IB("x",e,t,n),[X[1],X[2]],[q[1],q[2]],K,Y);return[J.result,J.indexes];case"AvgPool3D":var Z=IB("strides",e,t,n),Q=IB("pad",e,t,n),$=IB("kernelSize",e,t,n);return[LS(IB("x",e,t,n),[$[1],$[2],$[3]],[Z[1],Z[2],Z[3]],Q)];case"MaxPool3D":var ee=IB("strides",e,t,n),te=IB("pad",e,t,n),ne=IB("kernelSize",e,t,n);return[gE(IB("x",e,t,n),[ne[1],ne[2],ne[3]],[ee[1],ee[2],ee[3]],te)];case"Dilation2D":var re=IB("strides",e,t,n),ae=IB("pad",e,t,n),ie=IB("dilations",e,t,n),oe=re[1],se=re[2],ue=ie[1],le=ie[2];return[gT(IB("x",e,t,n),IB("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 ZI((function(){return function(e,t,n){switch(e.op){case"Fill":var r=IB("shape",e,t,n),a=IB("dtype",e,t,n);return[_T(r,IB("value",e,t,n),a)];case"LinSpace":return[GT(IB("start",e,t,n),IB("stop",e,t,n),IB("num",e,t,n))];case"Multinomial":var i=IB("logits",e,t,n),o=IB("numSamples",e,t,n),s=IB("seed",e,t,n);return[_E(i,o,s)];case"OneHot":var u=IB("indices",e,t,n),l=IB("depth",e,t,n),c=IB("onValue",e,t,n),p=IB("offValue",e,t,n);return[tI(u,l,c,p)];case"Ones":return[kE(IB("shape",e,t,n),IB("dtype",e,t,n))];case"OnesLike":return[DE(IB("x",e,t,n))];case"RandomUniform":return[iC(IB("shape",e,t,n),IB("minval",e,t,n),IB("maxval",e,t,n),IB("dtype",e,t,n))];case"Range":return[oC(IB("start",e,t,n),IB("stop",e,t,n),IB("step",e,t,n),IB("dtype",e,t,n))];case"TruncatedNormal":var h=IB("shape",e,t,n),f=IB("mean",e,t,n),d=IB("stdDev",e,t,n),m=IB("seed",e,t,n);return[YC(h,f,d,IB("dtype",e,t,n),m)];case"Zeros":return[wE(IB("shape",e,t,n),IB("dtype",e,t,n))];case"ZerosLike":return[xT(IB("x",e,t,n))];default:throw TypeError("Node type "+e.op+" is not implemented")}}(e,t,n)}));case"dynamic":return TW(e,t,n);case"evaluation":return ZI((function(){return function(e,t,n){switch(e.op){case"TopKV2":var r=IB("x",e,t,n),a=IB("k",e,t,n),i=IB("sorted",e,t,n),o=XC(r,a,i);return[o.values,o.indices];case"Unique":var s=IB("x",e,t,n),u=JC(s);return[u.values,u.indices];case"UniqueV2":var l=IB("x",e,t,n),c=IB("axis",e,t,n),p=JC(l,c);return[p.values,p.indices];default:throw TypeError("Node type "+e.op+" is not implemented")}}(e,t,n)}));case"image":return ZI((function(){return function(e,t,n){switch(e.op){case"ResizeBilinear":var r=IB("images",e,t,n),a=IB("size",e,t,n),i=IB("alignCorners",e,t,n),o=IB("halfPixelCenters",e,t,n);return[EA.resizeBilinear(r,[a[0],a[1]],i,o)];case"ResizeNearestNeighbor":var s=IB("images",e,t,n),u=IB("size",e,t,n),l=IB("alignCorners",e,t,n),c=IB("halfPixelCenters",e,t,n);return[EA.resizeNearestNeighbor(s,[u[0],u[1]],l,c)];case"CropAndResize":var p=IB("image",e,t,n),h=IB("boxes",e,t,n),f=IB("boxInd",e,t,n),d=IB("cropSize",e,t,n),m=IB("method",e,t,n),v=IB("extrapolationValue",e,t,n);return[EA.cropAndResize(p,h,f,d,m,v)];case"ImageProjectiveTransformV3":var g=IB("images",e,t,n),y=IB("transforms",e,t,n),b=IB("outputShape",e,t,n),x=IB("fillValue",e,t,n),w=IB("interpolation",e,t,n),k=IB("fillMode",e,t,n);return[EA.transform(g,y,w.toLowerCase(),k.toLowerCase(),x,b)];default:throw TypeError("Node type "+e.op+" is not implemented")}}(e,t,n)}));case"graph":return ZI((function(){return function(e,t,n){switch(e.op){case"Const":return t[e.name];case"PlaceholderWithDefault":var r=IB("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[AB(IB("x",e,t,n))];case"IdentityN":return IB("x",e,t,n).map((function(e){return AB(e)}));case"Snapshot":return[AB(IB("x",e,t,n))];case"Shape":return[GC(IB("x",e,t,n).shape,"int32")];case"ShapeN":return IB("x",e,t,n).map((function(e){return GC(e.shape)}));case"Size":return[yC(IB("x",e,t,n).size,"int32")];case"Rank":return[yC(IB("x",e,t,n).rank,"int32")];case"NoOp":return[yC(1)];case"Print":var a=IB("x",e,t,n),i=IB("data",e,t,n),o=IB("message",e,t,n),s=IB("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 ZI((function(){return function(e,t,n){switch(e.op){case"Equal":return[yT(IB("a",e,t,n),IB("b",e,t,n))];case"NotEqual":return[FE(IB("a",e,t,n),IB("b",e,t,n))];case"Greater":return[OT(IB("a",e,t,n),IB("b",e,t,n))];case"GreaterEqual":return[MT(IB("a",e,t,n),IB("b",e,t,n))];case"Less":return[UT(IB("a",e,t,n),IB("b",e,t,n))];case"LessEqual":return[VT(IB("a",e,t,n),IB("b",e,t,n))];case"LogicalAnd":return[hE(IB("a",e,t,n),IB("b",e,t,n))];case"LogicalNot":return[fE(IB("a",e,t,n))];case"LogicalOr":return[dE(IB("a",e,t,n),IB("b",e,t,n))];case"Select":case"SelectV2":return[bT(IB("condition",e,t,n),IB("a",e,t,n),IB("b",e,t,n))];default:throw TypeError("Node type "+e.op+" is not implemented")}}(e,t,n)}));case"matrices":return ZI((function(){return function(e,t,n){switch(e.op){case"BatchMatMul":case"BatchMatMulV2":case"MatMul":return[eI(IB("a",e,t,n),IB("b",e,t,n),IB("transposeA",e,t,n),IB("transposeB",e,t,n))];case"Einsum":return[NT.apply(hW,[IB("equation",e,t,n)].concat(IB("tensors",e,t,n)))];case"Transpose":return[nI(IB("x",e,t,n),IB("perm",e,t,n))];case"_FusedMatMul":var r=IB("fusedOps",e,t,n),a=r[0],i=r[1],o="biasadd"===a,s="prelu"===i,u=IB("numArgs",e,t,n),l=IB("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=IB("args",e,t,n),p=c[0],h=c[1];return[SR({a:IB("a",e,t,n),b:IB("b",e,t,n),transposeA:IB("transposeA",e,t,n),transposeB:IB("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 ZI((function(){return function(e,t,n){switch(e.op){case"FusedBatchNorm":case"FusedBatchNormV2":case"FusedBatchNormV3":return[GS(IB("x",e,t,n),IB("mean",e,t,n),IB("variance",e,t,n),IB("offset",e,t,n),IB("scale",e,t,n),IB("epsilon",e,t,n))];case"LRN":return[jT(IB("x",e,t,n),IB("radius",e,t,n),IB("bias",e,t,n),IB("alpha",e,t,n),IB("beta",e,t,n))];case"Softmax":return[AC(IB("x",e,t,n))];case"LogSoftmax":return[nE(IB("x",e,t,n))];case"SparseToDense":return[lR(IB("sparseIndices",e,t,n),IB("outputShape",e,t,n),IB("sparseValues",e,t,n),IB("defaultValue",e,t,n))];default:throw TypeError("Node type "+e.op+" is not implemented")}}(e,t,n)}));case"reduction":return ZI((function(){return function(e,t,n){switch(e.op){case"Max":var r=IB("axis",e,t,n),a=IB("keepDims",e,t,n);return[$T(IB("x",e,t,n),r,a)];case"Mean":var i=IB("axis",e,t,n),o=IB("keepDims",e,t,n);return[xE(IB("x",e,t,n),i,o)];case"Min":var s=IB("axis",e,t,n),u=IB("keepDims",e,t,n);return[IE(IB("x",e,t,n),s,u)];case"Sum":var l=IB("axis",e,t,n),c=IB("keepDims",e,t,n);return[tE(IB("x",e,t,n),l,c)];case"All":var p=IB("axis",e,t,n),h=IB("keepDims",e,t,n);return[pS(IB("x",e,t,n),p,h)];case"Any":var f=IB("axis",e,t,n),d=IB("keepDims",e,t,n);return[hS(IB("x",e,t,n),f,d)];case"ArgMax":var m=IB("axis",e,t,n);return[fS(IB("x",e,t,n),m)];case"ArgMin":var v=IB("axis",e,t,n);return[dS(IB("x",e,t,n),v)];case"Prod":var g=IB("axis",e,t,n),y=IB("keepDims",e,t,n);return[jE(IB("x",e,t,n),g,y)];case"Cumprod":var b=IB("axis",e,t,n),x=IB("exclusive",e,t,n),w=IB("reverse",e,t,n);return[pT(IB("x",e,t,n),b,x,w)];case"Cumsum":var k=IB("axis",e,t,n),N=IB("exclusive",e,t,n),I=IB("reverse",e,t,n);return[hT(IB("x",e,t,n),k,N,I)];case"Bincount":var S=IB("x",e,t,n),T=IB("weights",e,t,n),E=IB("size",e,t,n);return[KS(S,T,E)];case"DenseBincount":var C=IB("x",e,t,n),R=IB("weights",e,t,n),A=IB("size",e,t,n),_=IB("binaryOutput",e,t,n);return[fT(C,R,A,_)];default:throw TypeError("Node type "+e.op+" is not implemented")}}(e,t,n)}));case"slice_join":return ZI((function(){return function(e,t,n){switch(e.op){case"ConcatV2":case"Concat":var r=IB("n",e,t,n),a=IB("axis",e,t,n),i=IB("tensors",e,t,n);return i=i.slice(0,r),[zS(i,a)];case"Gather":var o=IB("x",e,t,n),s=IB("indices",e,t,n);return[DT(o,DN(s,"int32"),0)];case"GatherV2":var u=IB("axis",e,t,n),l=IB("batchDims",e,t,n),c=IB("x",e,t,n),p=IB("indices",e,t,n);return[DT(c,DN(p,"int32"),u,l)];case"Reverse":for(var h=IB("dims",e,t,n),f=[],d=0;d<h.length;d++)h[d]&&f.push(d);var m=IB("x",e,t,n);return[pC(m,f)];case"ReverseV2":var v=IB("axis",e,t,n),g=IB("x",e,t,n);return[pC(g,v)];case"Slice":var y=IB("begin",e,t,n),b=IB("size",e,t,n);return[BS(IB("x",e,t,n),y,b)];case"StridedSlice":var x=IB("begin",e,t,n),w=IB("end",e,t,n),k=IB("strides",e,t,n),N=IB("beginMask",e,t,n),I=IB("endMask",e,t,n),S=IB("ellipsisMask",e,t,n),T=IB("newAxisMask",e,t,n),E=IB("shrinkAxisMask",e,t,n),C=IB("x",e,t,n);return[UC(C,x,w,k,N,I,S,T,E)];case"Pack":return ZI((function(){var r=IB("axis",e,t,n),a=IB("tensors",e,t,n),i=a[0].shape,o=PC(a[0]).shape,s=a.map((function(e){var t=qv(e.shape,i);if(!t&&!qv(PC(e).shape,o))throw new Error("the input tensors shape does not match");return t?e:OS(e,i)}));return[BC(s,r)]}));case"Unpack":var R=IB("axis",e,t,n),A=IB("tensor",e,t,n);return QC(A,R);case"Tile":var _=IB("reps",e,t,n);return[RT(IB("x",e,t,n),_)];case"Split":case"SplitV":var F=IB("axis",e,t,n),D=IB("numOrSizeSplits",e,t,n),O=IB("x",e,t,n);return OC(O,D,F);case"ScatterNd":var M=IB("indices",e,t,n),L=IB("values",e,t,n),z=IB("shape",e,t,n);return[uR(M,L,z)];case"GatherNd":var P=IB("x",e,t,n),B=IB("indices",e,t,n);return[cR(P,B)];case"SparseToDense":var W=IB("sparseIndices",e,t,n),U=IB("outputShape",e,t,n),V=IB("sparseValues",e,t,n),G=IB("defaultValue",e,t,n);return[lR(W,V,U,V.dtype===G.dtype?G:DN(G,V.dtype))];default:throw TypeError("Node type "+e.op+" is not implemented")}}(e,t,n)}));case"sparse":return ZI((function(){return function(e,t,n){switch(e.op){case"SparseFillEmptyRows":var r=AA.sparseFillEmptyRows(IB("indices",e,t,n),IB("values",e,t,n),IB("denseShape",e,t,n),IB("defaultValue",e,t,n));return[r.outputIndices,r.outputValues,r.emptyRowIndicator,r.reverseIndexMap];case"SparseReshape":var a=AA.sparseReshape(IB("inputIndices",e,t,n),IB("inputShape",e,t,n),IB("newShape",e,t,n));return[a.outputIndices,a.outputShape];case"SparseSegmentMean":return[AA.sparseSegmentMean(IB("data",e,t,n),IB("indices",e,t,n),IB("segmentIds",e,t,n))];case"SparseSegmentSum":return[AA.sparseSegmentSum(IB("data",e,t,n),IB("indices",e,t,n),IB("segmentIds",e,t,n))];default:throw TypeError("Node type "+e.op+" is not implemented")}}(e,t,n)}));case"spectral":return ZI((function(){return function(e,t,n){switch(e.op){case"FFT":return[_C(IB("x",e,t,n))];case"IFFT":return[FC(IB("x",e,t,n))];case"RFFT":return[MC(IB("x",e,t,n))];case"IRFFT":return[DC(IB("x",e,t,n))];default:throw TypeError("Node type "+e.op+" is not 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b=s?[g,f,p]:[g,p,f],x=xj({inputs:{x:a},backend:n,attrs:{shape:o?[v,c,h]:[v,h,c]}}),w=xj({inputs:{x:i},backend:n,attrs:{shape:b}}),k=o?x.shape[1]:x.shape[2],N=o?x.shape[2]:x.shape[1],I=s?w.shape[1]:w.shape[2],S=Math.max(v,g),T=n.data.get(x.dataId).values,E=n.data.get(w.dataId).values,C=dg(x.shape),R=dg(w.shape),A=o?[C[0],1,C[1]]:[C[0],C[1],1],_=A[0],F=A[1],D=A[2],O=s?[1,R[1],R[0]]:[R[1],1,R[0]],M=O[0],L=O[1],z=O[2],P=N*I,B=FN([S,N,I],x.dtype),W=B.values,U=n.blockSize,V=0;V<S;V++)for(var G=0;G<N;G+=U)for(var j=0;j<I;j+=U)for(var H=0;H<k;H+=U)for(var q=Math.min(G+U,N),K=Math.min(j+U,I),X=Math.min(H+U,k),Y=G;Y<q;Y++)for(var J=j;J<K;J++){for(var Z=0,Q=H;Q<X;Q++){var $=Math.min(V,v-1)*_,ee=Math.min(V,g-1)*z;Z+=T[$+Y*F+Q*D]*E[Q*M+J*L+ee]}W[V*P+(Y*I+J)]+=Z}return n.disposeIntermediateTensorInfo(x),n.disposeIntermediateTensorInfo(w),n.makeTensorInfo(y,B.dtype,B.values)}var Nj={kernelName:Jg,backendName:"cpu",kernelFunc:kj};var Ij={kernelName:Ox,backendName:"cpu",kernelFunc:function(e){var t,n,r,a=e.inputs,i=e.backend,o=e.attrs,s=a.a,u=a.b,l=a.bias,c=a.preluActivationWeights,p=o.transposeA,h=o.transposeB,f=o.activation,d=o.leakyreluAlpha,m=[];t=kj({inputs:{a:s,b:u},attrs:{transposeA:p,transposeB:h},backend:i}),l&&(n=xV({inputs:{a:t,b:l},backend:i}),m.push(t),t=n),f&&(r=bj(i,t,f,c,d),m.push(t),t=r);for(var v=0,g=m;v<g.length;v++){var y=g[v];i.disposeIntermediateTensorInfo(y)}return t}},Sj=SV(Dg,(function(e){return Math.acos(e)})),Tj={kernelName:Dg,backendName:"cpu",kernelFunc:Sj},Ej=SV(Og,(function(e){return Math.acosh(e)})),Cj={kernelName:Og,backendName:"cpu",kernelFunc:Ej};var Rj={kernelName:Lg,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=t;tV(t,"addN");for(var a=r.map((function(e){return n.data.get(e.dataId).values})),i=FN(r[0].shape,r[0].dtype),o=i.values,s=0;s<r.length;s++)for(var u=a[s],l=0;l<o.length;l++)o[l]+=u[l];return n.makeTensorInfo(i.shape,i.dtype,i.values)}};var Aj={kernelName:zg,backendName:"cpu",kernelFunc:function(e){var 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p=iE(c.shape,u),h=p[0],f=Hv(p[1]),d=yg(Hv(h),c.dtype),m=n.data.get(c.dataId).values,v=0;v<d.length;++v){for(var g=v*f,y=m[g],b=0;b<f;++b){var x=m[g+b];y=y||x}d[v]=y}null!=l&&n.disposeIntermediateTensorInfo(c);var w=n.makeTensorInfo(h,c.dtype,d);if(o){var k=xj({inputs:{x:w},backend:n,attrs:{shape:oE(h,s)}});return n.disposeIntermediateTensorInfo(w),k}return w}};var Fj={kernelName:Bg,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=r.axis;tV(a,"argMax");var o=Qv(i,a.shape),s=uE(o,a.shape.length),u=a,l=[];null!=s&&(u=IG({inputs:{x:a},backend:n,attrs:{perm:s}}),l.push(u),o=cE(o.length,u.shape.length)),sE("argMax",o=[o[0]],u.shape.length);for(var c=iE(u.shape,o),p=c[0],h=c[1],f=yg(Hv(p),"int32"),d=Hv(h),m=n.data.get(u.dataId).values,v=0;v<f.length;++v){for(var g=v*d,y=m[g],b=0,x=0;x<d;++x){var w=m[g+x];w>y&&(y=w,b=x)}f[v]=b}return l.forEach((function(e){return n.disposeIntermediateTensorInfo(e)})),n.makeTensorInfo(p,"int32",f)}};var 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o=a.strideDepth,s=a.strideHeight,u=a.strideWidth,l=a.dilationDepth,c=a.dilationHeight,p=a.dilationWidth,h=a.effectiveFilterDepth,f=a.effectiveFilterHeight,d=a.effectiveFilterWidth,m=a.padInfo.front,v=a.padInfo.top,g=a.padInfo.left,y="max"===i?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,b=FN(a.outShape,n),x=b.values,w=a.outShape[1]*a.outShape[2]*a.outShape[3]*a.outShape[4],k=a.outShape[2]*a.outShape[3]*a.outShape[4],N=a.outShape[3]*a.outShape[4],I=a.outShape[4],S=0;S<a.batchSize;++S)for(var T=S*w,E=S*r[0],C=0;C<a.inChannels;++C)for(var R=0;R<a.outDepth;++R){for(var A=R*o-m,_=A;_<0;)_+=l;for(var F=Math.min(a.inDepth,h+A),D=T+R*k,O=0;O<a.outHeight;++O){for(var M=O*s-v,L=M;L<0;)L+=c;for(var z=Math.min(a.inHeight,f+M),P=D+O*N,B=0;B<a.outWidth;++B){for(var W=B*u-g,U=W;U<0;)U+=p;for(var V=Math.min(a.inWidth,d+W),G=P+B*I,j=y,H=0,q=0,K=_;K<F;K+=l){for(var X=E+K*r[1],Y=L;Y<z;Y+=c){for(var J=X+Y*r[2],Z=U;Z<V;Z+=p){var 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c=kS(i.shape,o,s,1,u,l),p=c.strideDepth,h=c.strideHeight,f=c.strideWidth,d=c.filterDepth,m=c.filterHeight,v=c.filterWidth,g=c.dilationDepth,y=c.dilationHeight,b=c.dilationWidth,x=c.effectiveFilterDepth,w=c.effectiveFilterHeight,k=c.effectiveFilterWidth,N=x-1-c.padInfo.front,I=k-1-c.padInfo.left,S=w-1-c.padInfo.top,T=FN(i.shape,"float32"),E=1/(d*m*v),C=n.bufferSync(a),R=0;R<c.batchSize;++R)for(var A=0;A<c.inChannels;++A)for(var _=0;_<c.inDepth;++_)for(var F=0;F<c.inHeight;++F)for(var D=0;D<c.inWidth;++D){for(var O=_-N,M=F-S,L=D-I,z=0,P=0;P<x;P+=g){var B=(O+P)/p;if(!(B<0||B>=c.outDepth||Math.floor(B)!==B))for(var W=0;W<w;W+=y){var U=(M+W)/h;if(!(U<0||U>=c.outHeight||Math.floor(U)!==U))for(var V=0;V<k;V+=b){var G=(L+V)/f;if(!(G<0||G>=c.outWidth||Math.floor(G)!==G))z+=C.get(R,B,U,G,A)}}}T.set(z*E,R,_,F,D,A)}return n.makeTensorInfo(T.shape,T.dtype,T.values)}};var Zj={kernelName:Kg,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.dy,i=t.input,o=i;tV([a,i],"avgPoolGrad");for(var s=r.filterSize,u=r.strides,l=r.pad,c=wS(o.shape,s,u,1,l),p=c.strideHeight,h=c.strideWidth,f=c.filterHeight,d=c.filterWidth,m=c.dilationHeight,v=c.dilationWidth,g=c.effectiveFilterHeight,y=c.effectiveFilterWidth,b=y-1-c.padInfo.left,x=g-1-c.padInfo.top,w=FN(o.shape,"float32"),k=1/(f*d),N=n.data.get(a.dataId).values,I=FN(a.shape,"float32",N),S=0;S<c.batchSize;++S)for(var T=0;T<c.inChannels;++T)for(var E=0;E<c.inHeight;++E)for(var C=0;C<c.inWidth;++C){for(var R=E-x,A=C-b,_=0,F=0;F<g;F+=m){var D=(R+F)/p;if(!(D<0||D>=c.outHeight||Math.floor(D)!==D))for(var O=0;O<y;O+=v){var M=(A+O)/h;if(!(M<0||M>=c.outWidth||Math.floor(M)!==M))_+=I.get(S,D,M,T)}}w.set(_*k,S,E,C,T)}return n.makeTensorInfo(w.shape,w.dtype,w.values)}};var Qj={kernelName:Uy,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=t.scale,o=t.offset,s=t.mean,u=t.variance;Uv(s.shape.length===u.shape.length,(function(){return"Batch normalization gradient requires mean and variance to have equal ranks."})),Uv(null==o||s.shape.length===o.shape.length,(function(){return"Batch normalization gradient requires mean and offset to have equal ranks."})),Uv(null==i||s.shape.length===i.shape.length,(function(){return"Batch normalization gradient requires mean and scale to have equal ranks."})),tV([a,s,u,i,o],"batchNorm");var l=r.varianceEpsilon;null==l&&(l=.001);for(var c=n.data.get(a.dataId).values,p=n.data.get(s.dataId).values,h=n.data.get(u.dataId).values,f=i?n.data.get(i.dataId).values:new Float32Array([1]),d=o?n.data.get(o.dataId).values:new Float32Array([0]),m=new Float32Array(c.length),v=d.length,g=f.length,y=h.length,b=p.length,x=0,w=0,k=0,N=0,I=0;I<c.length;++I)m[I]=d[x++]+(c[I]-p[w++])*f[k++]/Math.sqrt(h[N++]+l),x>=v&&(x=0),w>=b&&(w=0),k>=g&&(k=0),N>=y&&(N=0);return n.makeTensorInfo(a.shape,a.dtype,m)}};var $j={kernelName:Zg,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=r.blockShape,o=r.crops;tV([a],"batchToSpaceND");var s=i.reduce((function(e,t){return e*t})),u=XA(a.shape,i,s),l=YA(u.length,i.length),c=JA(a.shape,i,s),p=ZA(o,i.length),h=QA(c,o,i.length),f=xj({inputs:{x:a},backend:n,attrs:{shape:u}}),d=IG({inputs:{x:f},backend:n,attrs:{perm:l}}),m=xj({inputs:{x:d},backend:n,attrs:{shape:c}}),v=LG({inputs:{x:m},backend:n,attrs:{begin:p,size:h}});return n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(m),v}};var eH={kernelName:Qg,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=t.weights,o=r.size,s=kV(n.data.get(a.dataId).values,n.data.get(i.dataId).values,i.dtype,i.shape,o);return n.makeTensorInfo([o],i.dtype,s)}};var tH={kernelName:ey,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=t.s0,a=t.s1,i=n.data.get(r.dataId).values,o=n.data.get(a.dataId).values,s=oI(Array.from(i),Array.from(o));return n.makeTensorInfo([s.length],"int32",Int32Array.from(s))}},nH=SV(ry,(function(e,t){var n=t;return e>n.clipValueMax?n.clipValueMax:e<n.clipValueMin?n.clipValueMin:e})),rH={kernelName:ry,backendName:"cpu",kernelFunc:nH},aH={kernelName:iy,backendName:"cpu",kernelFunc:function(e){for(var t=e.inputs.x,n=e.backend,r=new Float32Array(Hv(t.shape)),a=n.data.get(t.dataId),i=a.complexTensorInfos.real,o=a.complexTensorInfos.imag,s=n.data.get(i.dataId).values,u=n.data.get(o.dataId).values,l=0;l<s.length;l++){var c=s[l],p=u[l];r[l]=Math.hypot(c,p)}return n.makeOutput(r,t.shape,"float32")}};function iH(e){var t=e.inputs,n=e.backend,r=t.input,a=n.data.get(r.dataId).complexTensorInfos.imag,i=n.data.get(a.dataId).values;return n.makeTensorInfo(a.shape,a.dtype,i)}var oH={kernelName:Xy,backendName:"cpu",kernelFunc:iH};function sH(e){var t=e.inputs,n=e.backend,r=Qv(e.attrs.axis,t[0].shape)[0],a=HA(t.map((function(e){return e.shape})),r);if(0===Hv(a))return n.makeTensorInfo(a,t[0].dtype,[]);var i=t.filter((function(e){return Hv(e.shape)>0}));if(1===i.length)return cV({inputs:{x:i[0]},backend:n});if(jA(i.map((function(e){return e.shape})),r),"complex64"===i[0].dtype){var o=i.map((function(e){return hV({inputs:{input:e},backend:n})})),s=i.map((function(e){return iH({inputs:{input:e},backend:n})})),u=sH({inputs:o,backend:n,attrs:{axis:r}}),l=sH({inputs:s,backend:n,attrs:{axis:r}}),c=sV({inputs:{real:u,imag:l},backend:n});return o.forEach((function(e){return n.disposeIntermediateTensorInfo(e)})),s.forEach((function(e){return n.disposeIntermediateTensorInfo(e)})),n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(l),c}var p=i.map((function(e){var t=Hv(e.shape.slice(r));return 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p=FS(u),h=NS(a.shape,c,o,1,s,l,!1,p),f=h.strideHeight,d=h.strideWidth,m=h.filterHeight,v=h.filterWidth,g="channelsLast"===h.dataFormat,y=new jw(h.filterShape,"float32"),b=h.padInfo.left,x=h.padInfo.top,w=n.data.get(a.dataId).values,k=n.data.get(i.dataId).values,N=new jw(a.shape,a.dtype,w),I=new jw(i.shape,i.dtype,k),S=0;S<m;++S)for(var T=Math.max(0,Math.ceil((x-S)/f)),E=Math.min(h.outHeight,(h.inHeight+x-S)/f),C=0;C<v;++C)for(var R=Math.max(0,Math.ceil((b-C)/d)),A=Math.min(h.outWidth,(h.inWidth+b-C)/d),_=0;_<h.inChannels;++_)for(var F=0;F<h.outChannels;++F){for(var D=0,O=0;O<h.batchSize;++O)for(var M=T;M<E;++M)for(var L=S+M*f-x,z=R;z<A;++z){var P=C+z*d-b;D+=g?N.get(O,L,P,_)*I.get(O,M,z,F):N.get(O,_,L,P)*I.get(O,F,M,z)}y.set(D,S,C,_,F)}return n.makeTensorInfo(y.shape,y.dtype,y.values)}};var hH={kernelName:ly,backendName:"cpu",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;tV([a,i],"conv2dBackpropInput");var p=dg(i.shape),h=dg(a.shape),f=FS(l),d=NS(o,i.shape,s,1,u,c,!1,f),m=new jw(d.inShape,"float32"),v=m.values,g=n.data.get(a.dataId).values,y=n.data.get(i.dataId).values,b=p[0],x=p[1],w=p[2],k=d.batchSize,N=d.filterHeight,I=d.filterWidth,S=d.inChannels,T=d.inHeight,E=d.inWidth,C=d.outChannels,R=d.outHeight,A=d.outWidth,_=d.strideHeight,F=d.strideWidth;f=d.dataFormat;for(var D=N-1-d.padInfo.top,O=I-1-d.padInfo.left,M="channelsLast"===f,L=m.strides[0],z=M?m.strides[1]:m.strides[2],P=M?m.strides[2]:1,B=M?1:m.strides[1],W=h[0],U=M?h[1]:h[2],V=M?h[2]:1,G=M?1:h[1],j=0;j<k;++j)for(var H=0;H<S;++H)for(var q=0;q<T;++q)for(var K=q-D,X=Math.max(0,Math.ceil(K/_)),Y=Math.min(R,(N+K)/_),J=0;J<E;++J){for(var Z=J-O,Q=Math.max(0,Math.ceil(Z/F)),$=Math.min(A,(I+Z)/F),ee=0,te=X;te<Y;++te)for(var ne=te*_-K,re=Q;re<$;++re)for(var ae=W*j+U*te+V*re,ie=b*(N-1-ne)+x*(I-1-(re*F-Z))+w*H,oe=0;oe<C;++oe){ee+=g[ae+G*oe]*y[ie+oe]}v[L*j+z*q+P*J+B*H]=ee}return n.makeTensorInfo(m.shape,m.dtype,m.values)}};var fH={kernelName:cy,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=t.filter,o=r.strides,s=r.pad,u=r.dilations;tV([a,i],"conv3d");for(var l=IS(a.shape,i.shape,o,u,s),c=l.filterDepth,p=l.filterHeight,h=l.filterWidth,f=l.dilationDepth,d=l.dilationHeight,m=l.dilationWidth,v=l.padInfo,g=v.front,y=v.left,b=v.top,x=new jw(l.outShape,a.dtype),w=n.data.get(a.dataId).values,k=n.data.get(i.dataId).values,N=x.values,I=dg(a.shape),S=dg(i.shape),T=0;T<l.batchSize;++T)for(var E=T*I[0],C=T*x.strides[0],R=0;R<l.outDepth;++R)for(var A=C+R*x.strides[1],_=R*l.strideDepth-g,F=0;F<c;++F){var D=_+F*f;if(!(D<0||D>=l.inDepth))for(var O=F*S[0],M=E+D*I[1],L=0;L<l.outHeight;++L)for(var z=A+L*x.strides[2],P=L*l.strideHeight-b,B=0;B<p;++B){var W=P+B*d;if(!(W<0||W>=l.inHeight))for(var U=O+B*S[1],V=M+W*I[2],G=0;G<l.outWidth;++G)for(var j=z+G*l.outChannels,H=G*l.strideWidth-y,q=0;q<h;++q){var K=H+q*m;if(!(K<0||K>=l.inWidth))for(var X=U+q*S[2],Y=V+K*l.inChannels,J=X,Z=0;Z<l.inChannels;++Z){for(var Q=w[Y+Z],$=0;$<l.outChannels;++$)N[j+$]+=Q*k[J+$];J+=l.outChannels}}}}return n.makeTensorInfo(x.shape,x.dtype,x.values)}};var dH={kernelName:py,backendName:"cpu",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;tV([a,i],"conv3dBackpropFilterV2");for(var l=dg(a.shape),c=dg(i.shape),p=IS(a.shape,u,o,1,s),h=p.strideDepth,f=p.strideHeight,d=p.strideWidth,m=p.filterDepth,v=p.filterHeight,g=p.filterWidth,y=new jw(p.filterShape,"float32"),b=y.values,x=y.strides,w=x[0],k=x[1],N=x[2],I=x[3],S=n.data.get(i.dataId).values,T=c[0],E=c[1],C=c[2],R=c[3],A=n.data.get(a.dataId).values,_=l[0],F=l[1],D=l[2],O=l[3],M=p.padInfo.front,L=p.padInfo.left,z=p.padInfo.top,P=0;P<m;++P)for(var 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n.makeTensorInfo(h.shape,h.dtype,h.values)}},vH=SV(fy,(function(e){return Math.cos(e)})),gH={kernelName:fy,backendName:"cpu",kernelFunc:vH},yH=SV(dy,(function(e){return Math.cosh(e)})),bH={kernelName:dy,backendName:"cpu",kernelFunc:yH};var xH={kernelName:gy,backendName:"cpu",kernelFunc:function(e){for(var t=e.inputs,n=e.backend,r=e.attrs,a=t.image,i=t.boxes,o=t.boxInd,s=r.cropSize,u=r.method,l=r.extrapolationValue,c=a.shape,p=c[0],h=c[1],f=c[2],d=c[3],m=i.shape[0],v=s[0],g=s[1],y=FN([m,v,g,d],"float32"),b=n.data.get(i.dataId).values,x=n.data.get(o.dataId).values,w=n.data.get(a.dataId).values,k=dg(a.shape),N=dg(y.shape),I=0;I<m;I++){var S=4*I,T=b[S],E=b[S+1],C=b[S+2],R=b[S+3],A=x[I];if(!(A>=p))for(var _=v>1?(C-T)*(h-1)/(v-1):0,F=g>1?(R-E)*(f-1)/(g-1):0,D=0;D<v;D++){var O=v>1?T*(h-1)+D*_:.5*(T+C)*(h-1);if(O<0||O>h-1)for(var M=0;M<g;M++)for(var L=0;L<d;L++){var z=L+M*N[2]+D*N[1]+I*N[0];y.values[z]=l}else if("bilinear"===u)for(var P=Math.floor(O),B=Math.ceil(O),W=O-P,U=0;U<g;U++){var V=g>1?E*(f-1)+U*F:.5*(E+R)*(f-1);if(V<0||V>f-1)for(var G=0;G<d;G++){var j=G+U*N[2]+D*N[1]+I*N[0];y.values[j]=l}else for(var H=Math.floor(V),q=Math.ceil(V),K=V-H,X=0;X<d;X++){var Y=X+H*k[2]+P*k[1]+A*k[0],J=w[Y],Z=w[Y=X+q*k[2]+P*k[1]+A*k[0]],Q=w[Y=X+H*k[2]+B*k[1]+A*k[0]],$=J+(Z-J)*K,ee=Q+(w[Y=X+q*k[2]+B*k[1]+A*k[0]]-Q)*K;Y=X+U*N[2]+D*N[1]+I*N[0],y.values[Y]=$+(ee-$)*W}}else for(var te=0;te<g;++te){var ne=g>1?E*(f-1)+te*F:.5*(E+R)*(f-1);if(ne<0||ne>f-1)for(var re=0;re<d;re++){var ae=re+te*N[2]+D*N[1]+I*N[0];y.values[ae]=l}else for(var ie=Math.round(ne),oe=Math.round(O),se=0;se<d;se++){var ue=se+ie*k[2]+oe*k[1]+A*k[0],le=se+te*N[2]+D*N[1]+I*N[0];y.values[le]=w[ue]}}}}return n.makeTensorInfo(y.shape,y.dtype,y.values)}};var wH={kernelName:my,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=r.axis,o=r.exclusive,s=r.reverse;tV(a,"cumprod");var u=uE([i],a.shape.length),l=a;null!=u&&(l=IG({inputs:{x:a},backend:n,attrs:{perm:u}}));var c=cE(1,a.shape.length)[0];if(c!==l.shape.length-1)throw new Error("backend.cumprod in CPU expects an inner-most axis="+(l.shape.length-1)+" but got axis="+c);for(var p=nk(l.dtype,"int32"),h=gg(Hv(l.shape),p),f=n.data.get(l.dataId).values,d=l.shape[l.shape.length-1],m=s?function(e,t){return e+d-t-1}:function(e,t){return e+t},v=0;v<f.length;v+=d)for(var g=0;g<d;g++){var y=m(v,g);if(0===g)h[y]=o?1:f[y];else{var b=m(v,g-1);h[y]=o?f[b]*h[b]:f[y]*h[b]}}var x=n.makeTensorInfo(l.shape,p,h);if(null!=u){var w=IG({inputs:{x:x},backend:n,attrs:{perm:lE(u)}});return n.disposeIntermediateTensorInfo(x),n.disposeIntermediateTensorInfo(l),w}return x}};var kH={kernelName:vy,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=r.axis,o=r.exclusive,s=r.reverse;tV(a,"cumsum");var u=uE([i],a.shape.length),l=a;null!=u&&(l=IG({inputs:{x:a},backend:n,attrs:{perm:u}}));var c=cE(1,a.shape.length)[0];if(c!==l.shape.length-1)throw new Error("backend.cumsum in CPU expects an 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t=e.inputs,n=e.backend,r=e.attrs,a=t.dy,i=t.filter,o=r.strides,s=r.dilations,u=r.pad,l=r.dimRoundingMode,c=r.inputShape;tV([a,i],"depthwiseConv2DNativeBackpropInput");for(var p=dg(a.shape),h=dg(i.shape),f=NS(c,i.shape,o,s,u,l,!0),d=new jw(f.inShape,"float32"),m=d.values,v=d.strides,g=v[0],y=v[1],b=v[2],x=n.data.get(a.dataId).values,w=p[0],k=p[1],N=p[2],I=n.data.get(i.dataId).values,S=h[0],T=h[1],E=h[2],C=f.batchSize,R=f.filterHeight,A=f.filterWidth,_=f.inChannels,F=f.inHeight,D=f.inWidth,O=f.outChannels,M=f.outHeight,L=f.outWidth,z=f.strideHeight,P=f.strideWidth,B=R-1-f.padInfo.top,W=A-1-f.padInfo.left,U=O/_,V=0;V<C;++V)for(var G=0;G<_;++G)for(var j=0;j<F;++j)for(var H=j-B,q=Math.max(0,Math.ceil(H/z)),K=Math.min(M,(R+H)/z),X=0;X<D;++X){for(var Y=X-W,J=Math.max(0,Math.ceil(Y/P)),Z=Math.min(L,(A+Y)/P),Q=0,$=q;$<K;++$)for(var ee=$*z-H,te=J;te<Z;++te)for(var ne=w*V+k*$+N*te,re=S*(R-1-ee)+T*(A-1-(te*P-Y))+E*G,ae=0;ae<U;++ae){Q+=x[ne+(G*U+ae)]*I[re+ae]}m[g*V+y*j+b*X+G]=Q}return 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C=vg(E,c.data.get(o.dataId).values),R=bg(i.shape,i.dtype),A=0;A<d;++A)for(var _=0;_<y;++_)for(var F=_*w-x.top,D=0;D<b;++D)for(var O=D*k-x.left,M=0;M<g;++M){for(var L=Number.MIN_SAFE_INTEGER,z=0,P=0,B=0;B<N;++B){var W=F+B*S;if(W>=0&&W<m)for(var U=0;U<I;++U){var V=O+U*T;if(V>=0&&V<v){var G=p[A][W][V][M]+h[B][U][M];G>L&&(L=G,z=B,P=U)}}}R[z][P][M]+=C[A][_][D][M]}return{dataId:c.write(_w(R,a.dtype),i.shape,i.dtype),shape:i.shape,dtype:i.dtype}}},FH={kernelName:Sy,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=t.filter,o=t.dy,s=r.strides,u=r.pad,l=r.dilations,c=n,p=vg(a.shape,c.data.get(a.dataId).values),h=vg(i.shape,c.data.get(i.dataId).values),f=xS(a.shape,i.shape,s,u,"NHWC",l),d=f.batchSize,m=f.inHeight,v=f.inWidth,g=f.inChannels,y=f.outHeight,b=f.outWidth,x=f.padInfo,w=f.strideHeight,k=f.strideWidth,N=f.filterHeight,I=f.filterWidth,S=f.dilationHeight,T=f.dilationWidth,E=f.outShape;Uv(o.rank===E.length,(function(){return"Error in 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f=iE(h.shape,p),d=f[0],m=f[1],v=lV(r,d,nk(h.dtype,"int32")),g=Hv(m),y=r.data.get(v.dataId).values,b=r.data.get(h.dataId).values,x=0;x<y.length;++x){for(var w=x*g,k=0,N=0;N<g;++N)k+=b[w+N];y[x]=k}if(s){var I=v;v=xj({inputs:{x:v},backend:r,attrs:{shape:oE(v.shape,l)}}),r.disposeIntermediateTensorInfo(I)}return r.disposeIntermediateTensorInfo(t),null!=c&&r.disposeIntermediateTensorInfo(h),v}var OH={kernelName:ix,backendName:"cpu",kernelFunc:DH};var MH={kernelName:Cy,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=t,a=g_(e.attrs.equation,r.length),i=a.allDims,o=a.summedDims,s=a.idDims;b_(i.length,s,r);for(var u=x_(o,s),l=u.path,c=u.steps,p=c.length,h=null,f=i.length,d=[],m=0;m<p;++m){for(var v,g=Fv(c[m]);!(v=g()).done;){var y=v.value,b=y_(f,s[y]),x=b.permutationIndices,w=b.expandDims,k=void 0;w_(x)?k=r[y]:(k=IG({inputs:{x:r[y]},backend:n,attrs:{perm:x}}),d.push(k));for(var N=k.shape.slice(),I=0;I<w.length;++I)N.splice(w[I],0,1);qv(k.shape,N)||(k=xj({inputs:{x:k},backend:n,attrs:{shape:N}}),d.push(k)),null===h?h=k:(h=vG({inputs:{a:k,b:h},backend:n}),d.push(h))}m<p-1&&(l[m]>=0&&(h=DH({inputs:{x:h},backend:n,attrs:{axis:l[m]-(i.length-f),keepDims:!1}}),d.push(h)),f--)}for(var S=0,T=d;S<T.length;S++){var E=T[S];E!==h&&n.disposeIntermediateTensorInfo(E)}return h}};var LH={kernelName:Ay,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=t.dy,a=t.y;tV([r,a],"eluGrad");for(var i=new Float32Array(Hv(a.shape)),o=n.data.get(a.dataId).values,s=n.data.get(r.dataId).values,u=0;u<o.length;++u){var l=o[u];i[u]=l>=1?s[u]:s[u]*(l+1)}return n.makeTensorInfo(a.shape,"float32",i)}},zH=SV(_y,(function(e){var t=Math.sign(e),n=Math.abs(e),r=1/(1+.3275911*n);return t*(1-((((1.061405429*r-1.453152027)*r+1.421413741)*r-.284496736)*r+.254829592)*r*Math.exp(-n*n))})),PH={kernelName:_y,backendName:"cpu",kernelFunc:zH};function BH(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.input,i=r.dim,o=a.shape.length,s=a.shape.slice(),u=i;return i<0&&(Uv(-(o+1)<=i,(function(){return"Axis must be in the interval ["+-(o+1)+", "+o+"]"})),u=o+i+1),s.splice(u,0,1),xj({inputs:{x:a},backend:n,attrs:{shape:s}})}var WH={kernelName:Oy,backendName:"cpu",kernelFunc:BH},UH=oV((function(e,t){return e/t})),VH=vV(Ey,UH),GH={kernelName:Ey,backendName:"cpu",kernelFunc:VH};function jH(e,t,n){for(var r=e.shape,a=r[0],i=r[1],o=n.data.get(e.dataId),s=o.complexTensorInfos.real,u=o.complexTensorInfos.imag,l=[a,i],c=Hv(l),p=eg("float32",c),h=eg("float32",c),f=0;f<a;f++){for(var d=LG({inputs:{x:s},backend:n,attrs:{begin:[f,0],size:[1,i]}}),m=LG({inputs:{x:u},backend:n,attrs:{begin:[f,0],size:[1,i]}}),v=sV({inputs:{real:d,imag:m},backend:n}),g=HH(v,t,n),y=s_(g.real,g.imag),b=0;b<i;b++){var x=p_(y,b);p[f*i+b]=x.real,h[f*i+b]=x.imag}n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(v)}var w=n.makeTensorInfo(l,"float32",p),k=n.makeTensorInfo(l,"float32",h),N=sV({inputs:{real:w,imag:k},backend:n});return n.disposeIntermediateTensorInfo(w),n.disposeIntermediateTensorInfo(k),N}function HH(e,t,n){var r,a=Hv(e.shape),i=n.data.get(e.dataId),o=n.data.get(i.complexTensorInfos.real.dataId).values,s=n.data.get(i.complexTensorInfos.imag.dataId).values;if(0==((r=a)&r-1)){var u=qH(o,s,a,t,n),l=[e.shape[0],e.shape[1]];if(t){var c=n.makeTensorInfo(l,"float32",u.real),p=n.makeTensorInfo(l,"float32",u.imag),h=n.makeTensorInfo([],"float32",Aw(a,"float32")),f=cV({inputs:{x:h},backend:n}),d=GH.kernelFunc({inputs:{a:c,b:h},backend:n}),m=GH.kernelFunc({inputs:{a:p,b:f},backend:n}),v=n.data.get(d.dataId).values,g=n.data.get(m.dataId).values;return n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(m),{real:v,imag:g}}return u}return u_(function(e,t,n){for(var r=new Float32Array(2*t),a=0;a<t;a++){for(var i=0,o=0,s=0;s<t;s++){var u=d_(a*s,t,n),l=p_(e,s);i+=l.real*u.real-l.imag*u.imag,o+=l.real*u.imag+l.imag*u.real}n&&(i/=t,o/=t),h_(r,i,o,a)}return r}(s_(o,s),a,t))}function qH(e,t,n,r,a){if(1===n)return{real:e,imag:t};var i=s_(e,t),o=n/2,s=l_(i),u=s.real,l=s.imag,c=[u.length],p=a.makeTensorInfo(c,"float32",u),h=a.makeTensorInfo(c,"float32",l),f=sV({inputs:{real:p,imag:h},backend:a}),d=c_(i),m=d.real,v=d.imag,g=[m.length],y=a.makeTensorInfo(g,"float32",m),b=a.makeTensorInfo(g,"float32",v),x=sV({inputs:{real:y,imag:b},backend:a}),w=qH(u,l,o,r,a),k=w.real,N=w.imag,I=[k.length],S=a.makeTensorInfo(I,"float32",k),T=a.makeTensorInfo(I,"float32",N),E=sV({inputs:{real:S,imag:T},backend:a}),C=qH(m,v,o,r,a),R=C.real,A=C.imag,_=[R.length],F=a.makeTensorInfo(_,"float32",R),D=a.makeTensorInfo(_,"float32",A),O=sV({inputs:{real:F,imag:D},backend:a}),M=f_(n,r),L=[M.real.length],z=a.makeTensorInfo(L,"float32",M.real),P=a.makeTensorInfo(L,"float32",M.imag),B=sV({inputs:{real:z,imag:P},backend:a}),W=vG({inputs:{a:B,b:O},backend:a}),U=xV({inputs:{a:E,b:W},backend:a}),V=tj({inputs:{a:E,b:W},backend:a}),G=hV({inputs:{input:U},backend:a}),j=hV({inputs:{input:V},backend:a}),H=iH({inputs:{input:U},backend:a}),q=iH({inputs:{input:V},backend:a}),K=sH({inputs:[G,j],backend:a,attrs:{axis:0}}),X=sH({inputs:[H,q],backend:a,attrs:{axis:0}}),Y=a.data.get(K.dataId).values,J=a.data.get(X.dataId).values;return a.disposeIntermediateTensorInfo(p),a.disposeIntermediateTensorInfo(h),a.disposeIntermediateTensorInfo(f),a.disposeIntermediateTensorInfo(y),a.disposeIntermediateTensorInfo(b),a.disposeIntermediateTensorInfo(x),a.disposeIntermediateTensorInfo(S),a.disposeIntermediateTensorInfo(T),a.disposeIntermediateTensorInfo(E),a.disposeIntermediateTensorInfo(F),a.disposeIntermediateTensorInfo(D),a.disposeIntermediateTensorInfo(O),a.disposeIntermediateTensorInfo(z),a.disposeIntermediateTensorInfo(P),a.disposeIntermediateTensorInfo(B),a.disposeIntermediateTensorInfo(W),a.disposeIntermediateTensorInfo(U),a.disposeIntermediateTensorInfo(V),a.disposeIntermediateTensorInfo(G),a.disposeIntermediateTensorInfo(H),a.disposeIntermediateTensorInfo(j),a.disposeIntermediateTensorInfo(q),a.disposeIntermediateTensorInfo(K),a.disposeIntermediateTensorInfo(X),{real:Y,imag:J}}var KH={kernelName:Ly,backendName:"cpu",kernelFunc:function(e){var 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Fq={kernelName:yb,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=r.axis,o=r.keepDims;tV(a,"min");var s=Qv(i,a.shape),u=s,l=uE(u,a.shape.length),c=a;null!=l&&(c=IG({inputs:{x:a},backend:n,attrs:{perm:l}}),u=cE(u.length,a.shape.length)),sE("min",u,c.shape.length);for(var p=iE(c.shape,u),h=p[0],f=Hv(p[1]),d=yg(Hv(h),c.dtype),m=n.data.get(c.dataId).values,v=0;v<d.length;++v){for(var g=v*f,y=m[g],b=0;b<f;++b){var x=m[g+b];(Number.isNaN(x)||x<y)&&(y=x)}d[v]=y}null!=l&&n.disposeIntermediateTensorInfo(c);var w=n.makeTensorInfo(h,c.dtype,d);if(o){var k=xj({inputs:{x:w},backend:n,attrs:{shape:oE(h,s)}});return n.disposeIntermediateTensorInfo(w),k}return w}};var Dq={kernelName:xb,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=r.paddings,o=r.mode;tV(a,"mirrorPad");for(var s=i.map((function(e,t){return e[0]+a.shape[t]+e[1]})),u=i.map((function(e){return e[0]})),l=i.map((function(e,t){return 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e-t<.5?Math.floor(e):e-t>.5?Math.ceil(e):t%2==0?t:t+1})),hK={kernelName:Kb,backendName:"cpu",kernelFunc:pK};function fK(e,t,n,r,a,i,o,s,u,l){var c=[r/a,a],p=e.values,h=t.values;if(0===r)return FN(n,t.dtype);var f=FN(c,t.dtype);f.values.fill(u);for(var d=0;d<i;d++){for(var m=[],v=0,g=0;g<o;g++){var y=p[d*o+g];m.push(y),v+=y*s[g]}if(v<0||v>=r/a)throw new Error("Invalid indices: "+m+" does not index into "+n);for(var b=0;b<a;b++)l?f.values[v*a+b]+=h[d*a+b]:f.values[v*a+b]=0===t.rank?h[0]:h[d*a+b]}return f}var dK={kernelName:Yb,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.indices,i=t.updates,o=r.shape,s=xI(0,a,o),u=s.sliceRank,l=s.numUpdates,c=s.sliceSize,p=s.strides,h=s.outputSize,f=fK(n.bufferSync(a),n.bufferSync(i),o,h,c,l,u,p,0,!0);return n.makeTensorInfo(o,f.dtype,f.values)}};var mK={kernelName:Jb,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=t.condition,a=t.t,i=t.e;tV([r,a,i],"select");for(var 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=nk(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)}},vK=SV(Zb,(function(e){return e>=0?1.0507009873554805*e:1.7580993408473768*(Math.exp(e)-1)})),gK={kernelName:Zb,backendName:"cpu",kernelFunc:vK},yK=SV(tx,(function(e){return e<0?-1:e>0?1:0})),bK={kernelName:tx,backendName:"cpu",kernelFunc:yK},xK=SV($b,(function(e){return Math.sin(e)})),wK={kernelName:$b,backendName:"cpu",kernelFunc:xK},kK=SV(ex,(function(e){return Math.sinh(e)})),NK={kernelName:ex,backendName:"cpu",kernelFunc:kK},IK=Math.log(1.1920928955078125e-7)+2,SK=SV(rx,(function(e){var t=e>-IK,n=e<IK,r=Math.exp(e);return n?r:t?e:Math.log(1+r)})),TK={kernelName:rx,backendName:"cpu",kernelFunc:SK};var EK={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;tV([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=Qq.kernelFunc({inputs:{x:a},backend:n,attrs:{paddings:u,constantValue:0}}),p=XA(c.shape,i,s,!1),h=YA(p.length,i.length,!1),f=JA(c.shape,i,s,!1),d=xj({inputs:{x:c},backend:n,attrs:{shape:p}}),m=IG({inputs:{x:d},backend:n,attrs:{perm:h}}),v=xj({inputs:{x:m},backend:n,attrs:{shape:f}});return n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(m),v}};var CK={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=BG(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 AK={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);if(a.shape[0]!==i.shape[0])throw new Error("segmentIds and indices should have same size.");var o=n.data.get(r.dataId).values,s=n.data.get(a.dataId).values,u=n.data.get(i.dataId).values,l=WG(o,r.shape,r.dtype,s,u,!0),c=l[0],p=l[1];return n.makeTensorInfo(p,r.dtype,c)}};var 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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 "+OX(["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 "+OX(["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+=HX),[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=qX(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 "+KX(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=qX(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=$v(n),u=s.newShape,l=s.keptDims,c=u;if(c.length<n.length){var p=["row","col"];return"\n "+WX(JX(e,c),t)+"\n float "+a+"(int row, int col) {\n return "+a+"("+ZX(p,l)+");\n }\n "}if(e.shapeInfo.isUniform)return"\n float "+a+"(int row, int col) {\n int index = round(dot(vec2(row, col), vec2("+n[1]+", 1)));\n "+KX(e)+"\n }\n ";var h=i[0],f=i[1],d=qX(r);if(1===f)return t?"\n float "+a+"(int row, int col) {\n float index = dot(vec3(row, col, "+d+"), vec3("+r+"Shape[1], 1, 1));\n vec2 uv = vec2(0.5, (index + 0.5) / float("+r+"TexShape[0]));\n return sampleTexture("+r+", uv);\n }\n ":"\n float "+a+"(int row, int col) {\n float index = dot(vec3(row, col, "+d+"), vec3("+n[1]+", 1, 1));\n vec2 uv = vec2(0.5, (index + 0.5) / "+h+".0);\n return sampleTexture("+r+", uv);\n }\n ";if(1===h)return t?"\n float "+a+"(int row, int col) {\n float index = dot(vec3(row, col, "+d+"), vec3("+r+"Shape[1], 1, 1));\n vec2 uv = vec2((index + 0.5) / float("+r+"TexShape[1]), 0.5);\n return sampleTexture("+r+", uv);\n }\n ":"\n float "+a+"(int row, int col) {\n float index = dot(vec3(row, col, "+d+"), vec3("+n[1]+", 1, 1));\n vec2 uv = vec2((index + 0.5) / "+f+".0, 0.5);\n return sampleTexture("+r+", uv);\n }\n ";if(t)return"\n float "+a+"(int row, int col) {\n // Explicitly use integer operations as dot() only works on floats.\n int index = row * "+r+"Shape[1] + col + "+d+";\n vec2 uv = uvFromFlat("+r+"TexShape[0], "+r+"TexShape[1], index);\n return sampleTexture("+r+", uv);\n }\n ";return"\n float "+a+"(int row, int col) {\n // Explicitly use integer operations as dot() only works on floats.\n int index = row * "+n[1]+" + col + "+d+";\n vec2 uv = uvFromFlat("+h+", "+f+", index);\n return sampleTexture("+r+", uv);\n }\n"}(e,t);case 3:return function(e,t){var n=e.shapeInfo.logicalShape,r=e.name,a="get"+r.charAt(0).toUpperCase()+r.slice(1),i=n[1]*n[2],o=n[2],s=$v(n),u=s.newShape,l=s.keptDims,c=u;if(c.length<n.length){var p=["row","col","depth"];return"\n "+WX(JX(e,c),t)+"\n float "+a+"(int row, int col, int depth) {\n return "+a+"("+ZX(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 "+KX(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=qX(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(JX(e,l),t)+"\n float "+a+"(int row, int col, int depth, int depth2) {\n return "+a+"("+ZX(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 "+KX(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=qX(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(JX(e,l))+"\n float "+r+"(int row, int col, int depth, int depth2, int depth3) {\n return "+r+"("+ZX(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 "+KX(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=qX(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(JX(e,i))+"\n float "+r+"(int row, int col, int depth,\n int depth2, int depth3, int depth4) {\n return "+r+"("+ZX(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 "+KX(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=qX(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 UX(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 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= packedUVfrom2D("+c+", "+l[0]+", "+l[1]+", row, col);\n return "+u.texture2D+"("+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=e.shapeInfo.texShape,o=[Math.ceil(i[0]/2),Math.ceil(i[1]/2)];if(1===n[0]){var s=[1,2],u=["b","row","col"];return"\n "+UX(JX(e,n.slice(1)),t)+"\n vec4 "+a+"(int b, int row, int col) {\n return "+a+"("+ZX(u,s)+");\n }\n "}var l=FX();if(t)return"\n vec4 "+a+"(int b, 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[2]) / 2.0));\n int texelsInBatch = valuesPerRow * int(ceil(float("+r+"Shape[1]) / 2.0));\n vec2 uv = packedUVfrom3D(\n packedTexShape[0], packedTexShape[1], texelsInBatch, valuesPerRow, b, row, col);\n return "+l.texture2D+"("+r+", uv);\n }\n ";var c=o[0],p=o[1],h=Math.ceil(n[2]/2),f=h*Math.ceil(n[1]/2);return"\n vec4 "+a+"(int b, int row, 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 VX="\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",GX="\nvec2 packedUVfrom2D(int 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KX(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 XX(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 YX(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 JX(e,t){var n=JSON.parse(JSON.stringify(e));return n.shapeInfo.logicalShape=t,n}function ZX(e,t){return t.map((function(t){return e[t]})).join(", ")}function QX(e,t,n,r){var a=n.map((function(e,n){var r={logicalShape:e.shape,texShape:e.isUniform?null:e.texData.texShape,isUniform:e.isUniform,isPacked:!e.isUniform&&e.texData.isPacked,flatOffset:null};return 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t.enableShapeUniforms&&(r=e.getUniformLocation(n,"outShape",h),i=e.getUniformLocation(n,"outShapeStrides",h),a=e.getUniformLocation(n,"outTexShape",h)),t.customUniforms&&t.customUniforms.forEach((function(t,r){c[r]=e.getUniformLocation(n,t.name,h)})),{uniformLocations:s,customUniformLocations:c,infLoc:p,nanLoc:o,inShapesLocations:u,inTexShapesLocations:l,outShapeLocation:r,outShapeStridesLocation:i,outTexShapeLocation:a}}function eY(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 than the current args. 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. Shape "+o+" and "+s+" must match")}}))}function tY(e){return Rg().getBool("WEBGL_USE_SHAPES_UNIFORMS")&&e<=4}var nY=function(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=JK.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];var t=FX();this.outputShape=e,this.enableShapeUniforms=tY(this.outputShape.length),this.userCode="\n ivec3 outCoordsFromFlatIndex(int index) {\n "+(this.enableShapeUniforms?OX(["r","c","d"],e):DX(["r","c","d"],e))+"\n return ivec3(r, c, d);\n }\n\n void main() {\n ivec2 resTexRC = ivec2(resultUV.yx * vec2(texShape[0], texShape[1]));\n int index = 4 * (resTexRC.x * texShape[1] + resTexRC.y);\n\n vec4 result = vec4(0.);\n\n for (int i=0; i<4; i++) {\n int flatIndex = index + i;\n ivec3 rc = outCoordsFromFlatIndex(flatIndex);\n result[i] = getA(rc.x, rc.y, rc.z);\n }\n\n "+t.output+" = result;\n }\n 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encode_float(x);\n }\n "},iY=function(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=ZK.DOWNLOAD;var t=FX();this.outputShape=e,this.userCode="\n "+zX+"\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 "},oY=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=tY(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":LX(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 "},sY=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=tY(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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t=uJ("rc",this.rank),n=XX(this.rank),r=this.getOutOfBoundsCondition(t),a=this.getSetup(t),i=this.getOutput(t);this.userCode="\n void main() {\n "+n+" rc = getOutputCoords();\n\n if("+r+") {\n setOutput(vec4(0));\n } else {\n "+a+"\n\n setOutput(vec4("+i+"));\n }\n }\n "}}var t=e.prototype;return t.getSourceCoordsArr=function(e){for(var t=[],n=0;n<=1;n++)for(var r=0;r<=1;r++){for(var a=(0===n?"r":"rp1")+", "+(0===r?"c":"cp1"),i=2;i<this.rank;i++)a=e[e.length-1-i]+","+a;t.push(a)}return t},t.getOutOfBoundsCondition=function(e){if(1===this.rank)return"rc > "+(this.enableShapeUniforms?"outShape":this.outputShape[0]);for(var t="",n=this.rank-2;n<this.rank;n++)t+=e[n]+" >= "+(this.enableShapeUniforms?"outShape["+n+"]":this.outputShape[n]),n<this.rank-1&&(t+="||");return t},t.getSetup=function(e){if(1===this.rank)return"";var t=e.slice(-2),n=this.enableShapeUniforms?"outShape["+this.rank+" - 1]":this.outputShape[this.rank-1],r=this.enableShapeUniforms?"outShape["+this.rank+" - 2]":this.outputShape[this.rank-2];return"\n int r = "+t[0]+";\n int c = "+t[1]+";\n int rp1 = r + 1;\n int cp1 = c + 1;\n\n bool cEdge = cp1 >= "+n+";\n bool rEdge = rp1 >= "+r+";\n "},t.getOutput=function(e){var t=this.getSourceCoordsArr(e);return 1===this.rank?"getA(rc), (rc + 1 >= "+(this.enableShapeUniforms?"outShape":this.outputShape[0])+" ? 0. : getA(rc + 1)), 0, 0":"getA("+t[0]+"),\n cEdge ? 0. : getA("+t[1]+"),\n rEdge ? 0. : getA("+t[2]+"),\n rEdge || cEdge ? 0. : getA("+t[3]+")"},e}(),cJ=function(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"inputShape",type:"ivec3"}],this.outputShape=e,this.enableShapeUniforms=tY(this.outputShape.length);for(var n,r="",a=0;a<4;a++){var i="thisRC = rc;";a%2==1&&(i+="thisRC.z += 1;"),a>1&&(i+="thisRC.y += 1;"),r+="\n "+i+"\n "+(a>0?"if(thisRC.y < rows && thisRC.z < cols){":"")+"\n int flatIndex = getFlatIndex(thisRC);\n\n ivec3 inputRC = inputCoordsFromReshapedOutCoords(flatIndex);\n vec2 inputRCInnerDims = vec2(float(inputRC.y),float(inputRC.z));\n\n result["+a+"] =\n getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);\n "+(a>0?"}":"")+"\n "}this.userCode="\n "+(n=t,"\n ivec3 inputCoordsFromReshapedOutCoords(int index) {\n "+(this.enableShapeUniforms?MX(["r","c","d"],"inputShape"):DX(["r","c","d"],n))+"\n return ivec3(r, c, d);\n }\n \n ")+(this.enableShapeUniforms?"\n int getFlatIndex(ivec3 coords) {\n return coords.x * outShapeStrides[0] + coords.y * outShapeStrides[1] + coords.z;\n }\n":LX(e))+"\n\n void main() {\n ivec3 rc = getOutputCoords();\n\n vec4 result = vec4(0.);\n\n ivec3 thisRC;\n int rows = "+(this.enableShapeUniforms?"outShape[1]":e[1])+";\n int cols = "+(this.enableShapeUniforms?"outShape[2]":e[2])+";\n\n "+r+"\n\n setOutput(result);\n }\n "};var pJ=function(){function e(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}var t=e.prototype;return t.acquireTexture=function(e,t,n){var r=fJ(t,n),a=dJ(e,r,n);a in this.freeTextures||(this.freeTextures[a]=[]),a in this.usedTextures||(this.usedTextures[a]=[]);var i,o=hJ(e,r,this.gpgpu.gl,this.gpgpu.textureConfig,n);if(this.freeTextures[a].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=o,this.log();var s=this.freeTextures[a].shift();return this.usedTextures[a].push(s),s}return r===QK.PACKED_2X2_FLOAT32?i=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):r===QK.PACKED_2X2_FLOAT16?i=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):r===QK.UNPACKED_FLOAT32?i=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):r===QK.UNPACKED_FLOAT16?i=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):r===QK.PACKED_4X1_UNSIGNED_BYTE&&(i=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[a].push(i),this.numUsedTextures++,this._numBytesAllocated+=o,this.log(),i},t.releaseTexture=function(e,t,n,r){if(null!=this.freeTextures){var a=fJ(n,r),i=dJ(t,a,r);i in this.freeTextures||(this.freeTextures[i]=[]);var o=hJ(t,a,this.gpgpu.gl,this.gpgpu.textureConfig,r),s=Rg().get("WEBGL_DELETE_TEXTURE_THRESHOLD");-1!==s&&this._numBytesAllocated>s?(this.gpgpu.deleteMatrixTexture(e.texture),this._numBytesAllocated-=o):(this.freeTextures[i].push(e),this.numFreeTextures++,this._numBytesFree+=o),this.numUsedTextures--;var u=this.usedTextures[i],l=u.indexOf(e);if(l<0)throw new Error("Cannot release a texture that was never provided by this texture manager");u.splice(l,1),this.log()}},t.log=function(){if(this.logEnabled){var e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",this.numFreeTextures+" / "+this.numUsedTextures,"("+e+")");var t=this._numBytesFree/this._numBytesAllocated;console.log("Bytes allocated: "+this._numBytesAllocated),console.log("Bytes unused: "+this._numBytesFree+" ("+Math.round(100*t)+"%)")}},t.getNumUsedTextures=function(){return this.numUsedTextures},t.getNumFreeTextures=function(){return this.numFreeTextures},t.dispose=function(){var e=this;if(null!=this.freeTextures){for(var t in this.freeTextures)this.freeTextures[t].forEach((function(t){e.gpgpu.deleteMatrixTexture(t.texture)}));for(var n in this.usedTextures)this.usedTextures[n].forEach((function(t){e.gpgpu.deleteMatrixTexture(t.texture)}));this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}},kv(e,[{key:"numBytesAllocated",get:function(){return this._numBytesAllocated}},{key:"numBytesFree",get:function(){return this._numBytesFree}}]),e}();function hJ(e,t,n,r,a){var i,o=function(e,t){switch(e){case QK.PACKED_2X2_FLOAT32:return mY(t);case QK.PACKED_2X2_FLOAT16:return vY(t);case QK.UNPACKED_FLOAT32:return hY(t);case QK.UNPACKED_FLOAT16:return fY(t);case QK.PACKED_4X1_UNSIGNED_BYTE:return dY(t);default:throw new Error("Unknown physical texture type "+e)}}(t,r);if(a){var s=aX(e[0],e[1]);i=s[0]*s[1]}else{var u=nX(e[0],e[1]);i=u[0]*u[1]}return i*function(e,t){var n=e;if(t===n.R32F)return 4;if(t===n.R16F)return 2;if(t===n.RGBA32F)return 16;if(t===e.RGBA)return 16;if(t===n.RGBA16F)return 8;if(t===n.RGBA8)return 4;throw new Error("Unknown 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Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'");throw Error("The value "+n+" cannot be represented on this device.")}}},n.getValuesFromTexture=function(e){var t=this.texData.get(e),n=t.shape,r=t.dtype,a=t.isPacked,i=Hv(n);if(Rg().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){var o,s=this.decode(e),u=this.texData.get(s.dataId),l=(o=this.gpgpu).downloadMatrixFromPackedTexture.apply(o,[u.texture.texture].concat(rX(n))).subarray(0,i);return this.disposeIntermediateTensorInfo(s),l}var c=Rg().getBool("WEBGL_PACK")&&!0===a,p=c?NX(n):n,h=c?new iY(p):new aY(p),f=this.runWebGLProgram(h,[{shape:p,dtype:r,dataId:e}],"float32"),d=this.texData.get(f.dataId),m=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(d.texture.texture,d.texShape[0],d.texShape[1]).subarray(0,i);return this.disposeIntermediateTensorInfo(f),m},n.timerAvailable=function(){return Rg().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0},n.time=function(e){var t=this,n=this.activeTimers,r=[],a=!1;null==this.programTimersStack?(this.programTimersStack=r,a=!0):this.activeTimers.push(r),this.activeTimers=r,e();var i=jv(this.activeTimers.map((function(e){return e.query}))).filter((function(e){return null!=e})),o=jv(this.activeTimers.map((function(e){return e.name}))).filter((function(e){return null!=e}));this.activeTimers=n,a&&(this.programTimersStack=null);var s={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};return xv(regeneratorRuntime.mark((function e(){var n;return regeneratorRuntime.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:if(!(Rg().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)){e.next=8;break}return e.next=3,Promise.all(i);case 3:n=e.sent,s.kernelMs=Wv(n),s.getExtraProfileInfo=function(){return n.map((function(e,t){return{name:o[t],ms:e}})).map((function(e){return e.name+": "+e.ms})).join(", ")},e.next=9;break;case 8:s.kernelMs={error:"WebGL query timers are not supported in this environment."};case 9:return t.uploadWaitMs=0,t.downloadWaitMs=0,e.abrupt("return",s);case 12:case"end":return e.stop()}}),e)})))()},n.memory=function(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}},n.startTimer=function(){return Rg().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:Fw(),endMs:null}},n.endTimer=function(e){return Rg().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=Fw(),e)},n.getQueryTime=function(){var e=xv(regeneratorRuntime.mark((function e(t){var n;return regeneratorRuntime.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:if(!(Rg().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)){e.next=2;break}return e.abrupt("return",this.gpgpu.waitForQueryAndGetTime(t));case 2:return n=t,e.abrupt("return",n.endMs-n.startMs);case 4:case"end":return e.stop()}}),e,this)})));return function(t){return e.apply(this,arguments)}}(),n.disposeData=function(e,t){if(void 0===t&&(t=!1),this.pendingDisposal.has(e))return!1;if(!this.texData.has(e))return!0;if(t?this.texData.get(e).refCount=0:this.texData.get(e).refCount--,!t&&this.texData.get(e).refCount>0)return!1;if(this.pendingRead.has(e))return this.pendingDisposal.add(e),this.pendingDeletes++,!1;this.releaseGPUData(e);var n=this.texData.get(e).complexTensorInfos;return null!=n&&(this.disposeData(n.real.dataId,t),this.disposeData(n.imag.dataId,t)),this.texData.delete(e),!0},n.releaseGPUData=function(e){var t=this.texData.get(e),n=t.texture,r=t.dtype,a=t.texShape,i=t.usage,o=t.isPacked,s=t.slice,u=s&&s.origDataId||e,l=this.dataRefCount.get(u);l>1?this.dataRefCount.set(u,l-1):(this.dataRefCount.delete(u),null!=n&&(this.numBytesInGPU-=this.computeBytes(a,r),this.textureManager.releaseTexture(n,a,i,o)));var c=this.texData.get(e);c.texture=null,c.texShape=null,c.isPacked=!1,c.slice=null},n.getTexture=function(e){return this.uploadToGPU(e),this.texData.get(e).texture.texture},n.getDataInfo=function(e){return this.texData.get(e)},n.shouldExecuteOnCPU=function(e,t){var n=this;return void 0===t&&(t=NJ),Rg().getBool("WEBGL_CPU_FORWARD")&&e.every((function(e){return null==n.texData.get(e.dataId).texture&&Hv(e.shape)<t}))},n.getGPGPUContext=function(){return this.gpgpu},n.where=function(e){zx("tf.where() in webgl locks the UI thread. 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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=Rg().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&null!=n?new bJ(u.shape,n):new mJ(u.shape,t),l.runWebGLProgram(i,[u],c)}}function PJ(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 SJ(t,l.shape,c.shape);return p.runWebGLProgram(o,[a,i],nk(n.dtype,r.dtype))})),m=d[0],v=d[1],g=RJ({inputs:{real:m,imag:v},backend:p});return p.disposeIntermediateTensorInfo(m),p.disposeIntermediateTensorInfo(v),g}var y,b=u||nk(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?B_(x):x,N="string"===l.dtype?B_(w):w,I=s(l.shape,c.shape,k,N,b),S=I[0],T=I[1],E=p.makeTensorInfo(T,b);return p.texData.get(E.dataId).values=S,E}return y=Rg().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&null!=n?new TJ(n,l.shape,c.shape,a):new SJ(t,l.shape,c.shape),p.runWebGLProgram(y,[l,c],b)}}function BJ(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 ? x.a : result.a;\n\n return result;\n":"if (isnan(x)) return x;\n return (x < 0.0) ? 0.0 : x;\n";if("elu"===e)return t?"\n vec4 result;\n\n result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);\n result.g = (x.g >= 0.0) ? x.g : (exp(x.g) - 1.0);\n result.b = (x.b >= 0.0) ? x.b : (exp(x.b) - 1.0);\n result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);\n\n return result;\n":"return (x >= 0.0) ? x : (exp(x) - 1.0);";if("relu6"===e)return t?"\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":"if (isnan(x)) return x;\n return (x < 0.0) ? 0.0 : min(6.0, x);\n";if("prelu"===e)return t?MJ:OJ;if("leakyrelu"===e)return t?FJ:_J;if("sigmoid"===e)return"return 1.0 / (1.0 + exp(-1.0 * x));";throw new Error("Activation "+e+" has not been implemented for the WebGL backend.")}var WJ=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=tY(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), "+(e[0]-1)+".))":t[0]<e[0]&&(b="int(min(float(rc.x), "+(t[0]-1)+".))"),this.userCode="\n "+m+"\n // Don't use uniform for sharedDimensionPacked for performance.\n const float sharedDimension = "+c+".0;\n\n vec4 dot2x2ARowBCol(ivec3 rc) {\n vec4 result = vec4(0);\n for (int i = 0; i < "+c+"; i++) {\n int batchA = "+y+";\n int batchB = "+b+";\n vec4 a = getMatrixA(batchA, "+p+");\n vec4 b = getMatrixB(batchB, "+h+");\n\n // These swizzled products need to be separately added.\n // See: https://github.com/tensorflow/tfjs/issues/1735\n result += ("+f[0]+" * "+d[0]+");\n result += ("+f[1]+" * "+d[1]+");\n }\n return result;\n }\n\n void main() {\n ivec3 rc = getOutputCoords();\n vec4 result = dot2x2ARowBCol(rc);\n\n "+g+"\n\n "+v+"\n\n setOutput(result);\n }\n "},UJ="return areal * breal - aimag * bimag;",VJ="return areal * bimag + aimag * breal;",GJ=function(e,t,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=oI(t,n),this.userCode="\n float binaryOpComplex(\n float areal, float aimag, float breal, float bimag) {\n "+e+"\n }\n\n void main() {\n float areal = 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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=BY(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=Rg().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new TJ(jJ,a.shape,i.shape):new SJ(jJ,a.shape,i.shape),r.runWebGLProgram(t,[a,i],o)}var qJ={kernelName:Nb,backendName:"webgl",kernelFunc:HJ};function KJ(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);Uv(s===l,(function(){return"The new shape ("+u+") has "+l+" elements and the old shape ("+a.shape+") has "+s+" elements. 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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 "},JJ=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 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}\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 ZJ(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=qA(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 YJ({windowSize:c,inSize:l,batchSize:e.shape[0],outSize:p},l):new YJ({windowSize:c,inSize:l,batchSize:e.shape[0],outSize:p}):new JJ({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 QJ=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=XX(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 $J=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=XX(this.rank),i=sJ("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 eZ(e,t,n){var r=Rg().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new $J(e.shape,t):new QJ(e.shape,t);return n.runWebGLProgram(r,[e],e.dtype)}function tZ(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=uE(s,i),l=null!=u,c=e;l&&(c=eZ(e,u,r),s=cE(s.length,i)),sE("sum",s,i);var p=iE(c.shape,s),h=p[0],f=p[1],d=h;n&&(d=oE(h,o));var m=Hv(f),v=KJ({inputs:{x:c},attrs:{shape:[Hv(e.shape)/m,m]},backend:r}),g=ZJ(v,rk(e.dtype),"sum",r),y=KJ({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 nZ={kernelName:ix,backendName:"webgl",kernelFunc:tZ};function rZ(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=iJ(p,i.shape,i.dtype,o,l);t=s.makeTensorInfo(l,i.dtype),s.texData.get(t.dataId).values=h}else t=eZ(i,o,s);return t}var aZ={kernelName:Tx,backendName:"webgl",kernelFunc:rZ};function iZ(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 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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 "}},BZ=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. 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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) > 0.0) {\n continue;\n }\n int idyD = int(dyD);\n\n for (int wR = 0; wR < "+p+";\n wR += "+u+") {\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 for (int wC = 0; wC < "+h+";\n wC += "+l+") {\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 float dyValue = getDy(batch, idyD, idyR, idyC, ch);\n\n dotProd += dyValue * avgMultiplier;\n }\n }\n }\n setOutput(dotProd);\n }\n "};var jZ={kernelName:Yg,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=kS(i.shape,o,s,[1,1,1],u,l),p=new GZ(c);return n.runWebGLProgram(p,[a],i.dtype)}};var HZ={kernelName:Kg,backendName:"webgl",kernelFunc:function(e){var 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nQ={kernelName:Qg,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=t.weights,o=r.size,s=n.readSync(a.dataId),u=n.readSync(i.dataId),l=xY(s,u,i.dtype,i.shape,o);return n.makeTensorInfo([o],i.dtype,l)}};var rQ={kernelName:ey,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=t.s0,a=t.s1,i=n.readSync(r.dataId),o=n.readSync(a.dataId),s=oI(Array.from(i),Array.from(o));return n.makeTensorInfo([s.length],"int32",Int32Array.from(s))}},aQ=PJ({opSnippet:"return float(a != b);",cpuKernelImpl:UY,dtype:"bool"}),iQ={kernelName:Sb,backendName:"webgl",kernelFunc:aQ};function oQ(e){var t=e.inputs,n=e.backend,r=t.input;return EJ({inputs:{x:n.texData.get(r.dataId).complexTensorInfos.real},backend:n})}var sQ={kernelName:zb,backendName:"webgl",kernelFunc:oQ};var uQ={kernelName:ty,backendName:"webgl",kernelFunc:function e(t){var n=t.inputs,r=t.backend,a=t.attrs,i=n.x,o=a.dtype;if("complex64"===o){if("complex64"===i.dtype)return EJ({inputs:{x:i},backend:r});var s=wE(i.shape),u=e({inputs:{x:i},backend:r,attrs:{dtype:"float32"}}),l=RJ({inputs:{real:u,imag:s},backend:r});return s.dispose(),r.disposeIntermediateTensorInfo(u),l}if("complex64"===i.dtype){var c=oQ({inputs:{input:i},backend:r}),p=e({inputs:{x:c},backend:r,attrs:{dtype:o}});return r.disposeIntermediateTensorInfo(c),p}if(!ag(i.dtype,o)){var h=EJ({inputs:{x:i},backend:r});return{dataId:h.dataId,shape:h.shape,dtype:o}}if("int32"===o)return function(e,t){var n=new mJ(e.shape,"return float(int(x));"),r=t.runWebGLProgram(n,[e],"int32");return{dataId:r.dataId,shape:r.shape,dtype:r.dtype}}(i,r);if("bool"===o){var f=r.makeTensorInfo([],"bool",eg("bool",1)),d=aQ({inputs:{a:i,b:f},backend:r});return r.disposeIntermediateTensorInfo(f),d}throw new Error("Error in Cast: failed to cast "+i.dtype+" to "+o)}},lQ="return 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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 "},EQ=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 "},CQ=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=tY(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 RQ(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]++,Uv(SX(m.shape,k.shape),(function(){return"packed reshape "+m.shape+" to "+k.shape+" isn't free"}));var I=KJ({inputs:{x:r},backend:i,attrs:{shape:[1,a.inChannels,a.outChannels]}});x.push(I);var S=iZ({a:k,b:I,backend:i,transposeA:false,transposeB:false,bias:s,activation:f,preluActivationWeights:l,leakyreluAlpha:p}),T=i.texData.get(S.dataId);Uv(T.isPacked,(function(){return"batchMatMul result is expected to be packed"})),m.shape=N,T.shape=a.outShape,(t=EJ({inputs:{x:S},backend:i})).shape=a.outShape,x.push(S)}else{var E=KJ({inputs:{x:n},backend:i,attrs:{shape:[1,b?d[0]*d[1]*d[2]:d[0]*d[2]*d[3],a.inChannels]}}),C=KJ({inputs:{x:r},backend:i,attrs:{shape:[1,a.inChannels,a.outChannels]}}),R=iZ({a:E,b:C,transposeA:false,transposeB:false,backend:i,bias:s,activation:f,preluActivationWeights:l,leakyreluAlpha:p});t=KJ({inputs:{x:R},backend:i,attrs:{shape:a.outShape}}),x.push(E),x.push(C),x.push(R)}for(var A=0,_=x;A<_.length;A++){var F=_[A];i.disposeIntermediateTensorInfo(F)}return t}function AQ(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=KJ({inputs:{x:t},backend:a,attrs:{shape:t.shape.slice(1)}}),I=KJ({inputs:{x:n},backend:a,attrs:{shape:[1,b,Hv(n.shape)/b]}});k.push(N),k.push(I);var S=new CQ(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]],E=a.runWebGLProgram(S,[N],"float32",T),C=KJ({inputs:{x:E},backend:a,attrs:{shape:[1,w[0],w[1]]}});k.push(E),k.push(C);var R=null!=o,A=null!=u,_="leakyrelu"===h,F=h?BJ(h,!0):null,D=new WJ(C.shape,I.shape,[1,x,r.outChannels],!0,!1,R,F,A,_),O=[C,I];if(o&&O.push(o),A&&O.push(u),_){var M=a.makeTensorInfo([],"float32",Aw(c,"float32"));O.push(M),k.push(M)}var L=a.runWebGLProgram(D,O,"float32"),z=KJ({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 _Q={kernelName:sy,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=FS(l),f=NS(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(Rg().getBool("WEBGL_CONV_IM2COL")&&1===i.shape[0])t=AQ({x:i,filter:o,convInfo:f,backend:r});else{var d=new TQ(f);t=r.runWebGLProgram(d,[i,o],"float32")}else t=RQ({x:i,filter:o,convInfo:f,backend:r});var m=KJ({inputs:{x:t},backend:r,attrs:{shape:f.outShape}});return r.disposeIntermediateTensorInfo(t),m}},FQ=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 "},DQ=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 "},OQ=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+" - 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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 LQ={kernelName:uy,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=FS(u),h=NS(a.shape,c,o,1,s,l,!1,p),f=new FQ(h);return n.runWebGLProgram(f,[a,i],"float32")}};var zQ={kernelName:ly,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=FS(l),h=NS(o,i.shape,s,1,u,c,!1,p),f=new DQ(h);return n.runWebGLProgram(f,[a,i],"float32")}};var PQ={kernelName:cy,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=IS(a.shape,i.shape,o,u,s),c=new EQ(l);return n.runWebGLProgram(c,[a,i],"float32")}};var BQ={kernelName:py,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=IS(a.shape,u,o,1,s),c=new OQ(l);return n.runWebGLProgram(c,[a,i],"float32")}};var WQ={kernelName:hy,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=IS(r.inputShape,i.shape,s,1,o),l=new MQ(u);return n.runWebGLProgram(l,[a,i],"float32")}},UQ=zJ({opSnippet:"if (isnan(x)) return x;\n return cos(x);\n"}),VQ={kernelName:fy,backendName:"webgl",kernelFunc:UQ},GQ=zJ({opSnippet:"\n float e2x = exp(-x);\n return (e2x + 1.0 / e2x) / 2.0;\n"}),jQ={kernelName:dy,backendName:"webgl",kernelFunc:GQ},HQ=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 "},i$=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=tY(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+";";h+="\n for (int r = 0; r < "+l+"; r++) {\n ";for(var d=0;d<c;d++)h+="\n xTexelC"+2*d+" = vec4(0.0);\n xTexelC"+2*d+"Ready = 0;\n xTexelC"+(2*d+1)+" = vec4(0.0);\n xTexelC"+(2*d+1)+"Ready = 0;\n xC"+d+" = vec4(0.0);";h+="\n xR = xRCorner + r * dilations[0];\n if (xR >=0 && xR < inDims[0]) {\n ";for(var m=0;m<(p+1)/2;m++){var v=2*m;if(h+="\n xC = xCCorner + "+v*u+";\n ",1===s){if(v<c&&(o%2==1?(h+="\n xCOffset = xC + 1;\n if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC"+v+"Ready == 0) {\n xTexelC"+v+" = 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"+v+".zw = vec2(0.0);\n }\n xTexelC"+v+"Ready = 1;\n }\n ",h+=1===u&&v>0?"\n xC"+v+" = vec4(xTexelC"+(v-2)+".zw, xTexelC"+v+".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"+v+" = vec4(previous.zw, xTexelC"+v+".xy);\n } else {\n xC"+v+" = vec4(0.0, 0.0, xTexelC"+v+".xy);\n }\n "):h+="\n if (xC >= 0 && xC < inDims[1] && xTexelC"+v+"Ready == 0) {\n xTexelC"+v+" = getX(batch, xR, xC, d1);\n if (xC + 1 >= inDims[1]) {\n xTexelC"+v+".zw = vec2(0.0);\n }\n xTexelC"+v+"Ready = 1;\n }\n\n xC"+v+" = xTexelC"+v+";\n ",v+1<c)){var g=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) + "+g+";\n\n if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC"+(v+1)+"Ready == 0) {\n xTexelC"+(v+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"+(v+1)+".zw = vec2(0.0);\n }\n xTexelC"+(v+1)+"Ready = 1;\n }\n ",u>1&&(h+="\n xCOffset -= 2;\n if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC"+v+"Ready == 0) {\n xTexelC"+v+" = getX(batch, xR, xCOffset, d1);\n xTexelC"+v+"Ready = 1;\n }\n "),h+="\n xC"+(v+1)+" = vec4(xTexelC"+v+".zw, xTexelC"+(v+1)+".xy);\n "):h+=1===g?"\n xC"+(v+1)+" = xTexelC"+v+";\n ":"\n xCOffset = xC + "+g+";\n\n if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC"+(v+1)+"Ready == 0) {\n xTexelC"+(v+1)+" = getX(batch, xR, xCOffset, d1);\n if (xCOffset + 1 >= inDims[1]) {\n xTexelC"+(v+1)+".zw = vec2(0.0);\n }\n xTexelC"+(v+1)+"Ready = 1;\n }\n\n xC"+(v+1)+" = xTexelC"+(v+1)+";\n "}}else v<c&&(o%2==1?(h+="\n xCOffset = xC + 1 - strides[1];\n if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC"+v+"Ready == 0) {\n xTexelC"+v+" = 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"+v+".zw = vec2(0.0);\n }\n xTexelC"+v+"Ready = 1;\n }\n\n if(xC + 1 >= 0 && xC + 1 < inDims[1] && xTexelC"+(v+1)+"Ready == 0) {\n xTexelC"+(v+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"+(v+1)+".zw = vec2(0.0);\n }\n xTexelC"+(v+1)+"Ready = 1;\n }\n\n xC"+v+" = vec4(xTexelC"+v+".zw, xTexelC"+(v+1)+".zw);\n ",v+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"+(v+1)+" = vec4(xTexelC"+(v+1)+".xy, final.xy);\n ")):(h+="\n if(xC >= 0 && xC < inDims[1] && xTexelC"+v+"Ready == 0) {\n xTexelC"+v+" = getX(batch, xR, xC, d1);\n if (xC + 1 >= inDims[1]) {\n xTexelC"+v+".zw = vec2(0.0);\n }\n xTexelC"+v+"Ready = 1;\n }\n\n xCOffset = xC + strides[1];\n if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC"+(v+1)+"Ready == 0) {\n xTexelC"+(v+1)+" = getX(batch, xR, xCOffset, d1);\n if (xCOffset + 1 >= inDims[1]) {\n xTexelC"+(v+1)+".zw = vec2(0.);\n }\n xTexelC"+(v+1)+"Ready = 1;\n }\n\n xC"+v+" = vec4(\n xTexelC"+v+".xy, xTexelC"+(v+1)+".xy);\n ",v+1<c&&(h+="\n xC"+(v+1)+" = vec4(xTexelC"+v+".zw, xTexelC"+(v+1)+".zw);\n ")));v<c&&(h+="\n wTexel = getW(r, "+v+", d1, q);\n dotProd += xC"+v+" * vec4(wTexel.xz, wTexel.xz);\n ",v+1<c&&(h+="\n wTexel = getW(r, "+(v+1)+", d1, q);\n dotProd += xC"+(v+1)+" * vec4(wTexel.xz, wTexel.xz);\n "))}h+="\n }\n ",h+="\n }\n ";var y="",b="";n&&(y=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 }",b="result = activation(result);");var x=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode="\n "+y+"\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 "+x+"\n "+b+"\n setOutput(result);\n }\n "};var o$={kernelName:xy,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=t.filter,o=r.strides,s=r.pad,u=r.dilations,l=r.dimRoundingMode,c=u;null==c&&(c=[1,1]),Uv(_S(o,c),(function(){return"Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides "+o+" and dilations '"+c+"'"}));var p,h=NS(a.shape,i.shape,o,c,s,l,!0);p=Rg().getBool("WEBGL_PACK_DEPTHWISECONV")&&h.strideWidth<=2&&h.outChannels/h.inChannels==1?new i$(h):new a$(h);var f=[[h.padInfo.top,h.padInfo.left],[h.strideHeight,h.strideWidth],[h.dilationHeight,h.dilationWidth],[h.inHeight,h.inWidth]];return n.runWebGLProgram(p,[a,i],"float32",f)}},s$=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 "},u$=function(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;var t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,i=t-1-e.padInfo.top,o=n-1-e.padInfo.left,s=e.outChannels/e.inChannels;this.userCode="\n const ivec2 pads = ivec2("+i+", "+o+");\n\n void main() {\n ivec4 coords = getOutputCoords();\n int batch = coords[0];\n int d1 = coords[3];\n ivec2 dyCorner = coords.yz - pads;\n int dyRCorner = dyCorner.x;\n int dyCCorner = dyCorner.y;\n\n float dotProd = 0.0;\n\n for (int wR = 0; wR < "+t+"; wR++) {\n float dyR = float(dyRCorner + wR) / "+r+".0;\n\n if (dyR < 0.0 || dyR >= "+e.outHeight+".0 || fract(dyR) > 0.0) {\n continue;\n }\n int idyR = int(dyR);\n\n int wRPerm = "+t+" - 1 - wR;\n\n for (int wC = 0; 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i < "+r+"; i++) {\n // x = (-2|2 * PI / N) * index * i;\n float x = exponentMultiplierTimesIndexRatio * float(i);\n float expR = cos(x);\n float expI = sin(x);\n float real = getReal(batch, i);\n float imag = getImag(batch, i);\n\n result +=\n unaryOpComplex(real, expR, imag, expI) / "+o+";\n }\n\n return result;\n }\n\n void main() {\n ivec2 coords = getOutputCoords();\n setOutput(mulMatDFT(coords[0], coords[1]));\n }\n "};function _$(e,t,n){var r=n.texData.get(e.dataId),a=Hv(e.shape),i=e.shape[e.shape.length-1],o=KJ({inputs:{x:e},backend:n,attrs:{shape:[a/i,i]}}),s=o.shape,u=new A$("real",s,t),l=new A$("imag",s,t),c=[{dataId:r.complexTensorInfos.real.dataId,dtype:r.complexTensorInfos.real.dtype,shape:s},{dataId:r.complexTensorInfos.imag.dataId,dtype:r.complexTensorInfos.imag.dtype,shape:s}],p=n.runWebGLProgram(u,c,"float32"),h=n.runWebGLProgram(l,c,"float32"),f=RJ({inputs:{real:p,imag:h},backend:n});n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(h);var d=KJ({inputs:{x:f},backend:n,attrs:{shape:e.shape}});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(f),d}var F$={kernelName:Ly,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend;return _$(t.input,!1,n)}},D$=function(e,t){this.outputShape=[],this.customUniforms=[{name:"value",type:"float"}],this.variableNames=["x"],this.outputShape=e,this.userCode="\n void main() {\n // Input can be obtained from uniform value.\n setOutput(value);\n }\n "};function O$(e){var t=e.backend,n=e.attrs,r=n.shape,a=n.value,i=n.dtype;if("string"===(i=i||pg(a))){var o=tg(i,Hv(r));return o.fill(a),t.makeTensorInfo(r,i,o)}var s=new D$(r,a),u=[[a]];return t.runWebGLProgram(s,[],i,u)}var M$,L$={kernelName:zy,backendName:"webgl",kernelFunc:O$},z$=function(e){this.variableNames=["Image"],this.outputShape=[];var t=e[2];this.outputShape=e,this.userCode="\n void main() {\n ivec4 coords = getOutputCoords();\n int x = coords[2];\n\n int coordX = "+t+" - x - 1;\n float outputValue;\n if(coordX >= 0 && coordX < "+t+") {\n outputValue = getImage(coords[0], coords[1], coordX, coords[3]);\n } else {\n outputValue = getImage(coords[0], coords[1], coords[2], coords[3]);\n }\n setOutput(outputValue);\n }\n "},P$={kernelName:Py,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=t.image,a=n,i=new z$(r.shape);return a.runWebGLProgram(i,[r],r.dtype)}},B$="return floor(x);",W$=zJ({opSnippet:B$,packedOpSnippet:B$,cpuKernelImpl:EY}),U$={kernelName:By,backendName:"webgl",kernelFunc:W$},V$=PJ({opSnippet:"\n float s = sign(a) * sign(b);\n int ia = round(a);\n int ib = round(b);\n if (ib != 0) {\n // Windows (D3D) wants guaranteed non-zero int division at compile-time.\n return float(idiv(ia, ib, s));\n } else {\n return NAN;\n }\n",packedOpSnippet:"\n ivec4 ia = round(a);\n ivec4 ib = round(b);\n bvec4 cond = notEqual(ib, ivec4(0));\n ivec4 result = ivec4(0);\n vec4 s = sign(a) * sign(b);\n\n // Windows (D3D) wants guaranteed non-zero int division at compile-time.\n if (cond[0]) {\n result[0] = idiv(ia[0], ib[0], s[0]);\n }\n if (cond[1]) {\n result[1] = idiv(ia[1], ib[1], s[1]);\n }\n if (cond[2]) {\n result[2] = idiv(ia[2], ib[2], s[2]);\n }\n if (cond[3]) {\n result[3] = idiv(ia[3], ib[3], s[3]);\n }\n return vec4(result);\n",dtype:"int32"}),G$={kernelName:Wy,backendName:"webgl",kernelFunc:V$},j$=function(e){this.variableNames=["A"];var t=FX(),n=e[0],r=e[1];this.outputShape=e,this.userCode="\n void main() {\n ivec3 coords = getOutputCoords();\n int texR = coords[0];\n int texC = coords[1];\n int depth = coords[2];\n vec2 uv = (vec2(texC, texR) + halfCR) / vec2("+r+".0, "+n+".0);\n\n vec4 values = "+t.texture2D+"(A, uv);\n float value;\n if (depth == 0) {\n value = values.r;\n } else if (depth == 1) {\n value = values.g;\n } else if (depth == 2) {\n value = values.b;\n } else if (depth == 3) {\n value = values.a;\n }\n\n setOutput(floor(value * 255.0 + 0.5));\n }\n "},H$=function(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;var t=FX(),n=e[0],r=e[1];this.outputShape=e,this.userCode="\n void main() {\n ivec3 coords = getOutputCoords();\n int texR = coords[0];\n int texC = coords[1];\n int depth = coords[2];\n\n vec4 result = vec4(0.);\n\n for(int row=0; 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n=["resRC.x","resRC.y","resRC.z","resRC.w"],r=[],a=0;a<e.length;a++)2===a?r.push("index"):r.push(""+n[a]);return r.join()}(e);this.userCode="\n void main() {\n "+n+" resRC = getOutputCoords();\n int index = int(getIndices(resRC.x, resRC.z));\n float inBounds = (index >= 0) && (index < "+e[2]+") ? 1.0 : 0.0;\n setOutput(inBounds * getA("+r+"));\n }\n "};function Q$(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=t.indices,o=r.axis,s=r.batchDims,u=Qv(o,a.shape)[0];Rg().get("DEBUG")&&function(){for(var e=n.readSync(i.dataId),t=a.shape[u],r=function(n){var r=e[n];Uv(r<=t-1&&r>=0,(function(){return"GatherV2: the index value "+r+" is not in [0, "+(t-1)+"]"}))},o=0;o<e.length;++o)r(o)}();var l=P_(a,i,u,s),c=Hv(i.shape),p=[],h=KJ({inputs:{x:a},backend:n,attrs:{shape:[l.batchSize,l.outerSize,l.dimSize,l.sliceSize]}}),f=KJ({inputs:{x:i},backend:n,attrs:{shape:[l.batchSize,c/l.batchSize]}});p.push(h),p.push(f);var d=[l.batchSize,l.outerSize,c/l.batchSize,l.sliceSize];if(n.shouldExecuteOnCPU([a,i])||"string"===a.dtype){var m=n.bufferSync(f),v=n.bufferSync(h),g=RY(v,m,d);return p.forEach((function(e){return n.disposeIntermediateTensorInfo(e)})),n.makeTensorInfo(l.outputShape,g.dtype,g.values)}var y=new Z$(h.shape,d),b=n.runWebGLProgram(y,[h,f],h.dtype);p.push(b);var x=KJ({inputs:{x:b},backend:n,attrs:{shape:l.outputShape}});return p.forEach((function(e){return n.disposeIntermediateTensorInfo(e)})),x}var $$={kernelName:Vy,backendName:"webgl",kernelFunc:Q$},e0=PJ({opSnippet:"return float(a > b);",packedOpSnippet:"\n return vec4(greaterThan(a, b));\n",cpuKernelImpl:AY,dtype:"bool"}),t0={kernelName:jy,backendName:"webgl",kernelFunc:e0},n0=PJ({opSnippet:"return float(a >= b);",packedOpSnippet:"\n return vec4(greaterThanEqual(a, b));\n",dtype:"bool",cpuKernelImpl:_Y}),r0={kernelName:Hy,backendName:"webgl",kernelFunc:n0};var a0={kernelName:Ky,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend;return _$(t.input,!0,n)}},i0=zJ({opSnippet:"return float(!isnan(x) && !isinf(x));",dtype:"bool"}),o0={kernelName:Yy,backendName:"webgl",kernelFunc:i0},s0=zJ({opSnippet:"return float(isinf(x));",dtype:"bool"}),u0={kernelName:Jy,backendName:"webgl",kernelFunc:s0},l0=zJ({opSnippet:"return float(isnan(x));",dtype:"bool"}),c0={kernelName:Zy,backendName:"webgl",kernelFunc:l0},p0=PJ({opSnippet:"return float(a < b);",packedOpSnippet:"\n return vec4(lessThan(a, b));\n",cpuKernelImpl:FY,dtype:"bool"}),h0={kernelName:$y,backendName:"webgl",kernelFunc:p0},f0=PJ({opSnippet:"return float(a <= b);",packedOpSnippet:"\n return vec4(lessThanEqual(a, b));\n",cpuKernelImpl:DY,dtype:"bool"}),d0={kernelName:eb,backendName:"webgl",kernelFunc:f0};var m0={kernelName:tb,backendName:"webgl",kernelFunc:function(e){var t=e.backend,n=e.attrs,r=n.start,a=n.stop,i=n.num,o=OY(r,a,i);return t.makeTensorInfo([o.length],"float32",o)}},v0=zJ({opSnippet:"if (isnan(x)) return x;\n return x < 0.0 ? 0./0. : log(x);\n",packedOpSnippet:"\n vec4 result = log(x);\n bvec4 isNaN = isnan(x);\n result.r = isNaN.r ? x.r : (x.r < 0.0 ? 0./0. : result.r);\n result.g = isNaN.g ? x.g : (x.g < 0.0 ? 0./0. : result.g);\n result.b = isNaN.b ? x.b : (x.b < 0.0 ? 0./0. : result.b);\n result.a = isNaN.a ? x.a : (x.a < 0.0 ? 0./0. : result.a);\n return result;\n",cpuKernelImpl:MY}),g0={kernelName:nb,backendName:"webgl",kernelFunc:v0},y0=zJ({opSnippet:"if (isnan(x)) return x;\n return log(1.0 + x);\n"}),b0={kernelName:rb,backendName:"webgl",kernelFunc:y0},x0=PJ({opSnippet:"return float(a >= 1.0 && b >= 1.0);",packedOpSnippet:"\n return vec4(\n vec4(greaterThanEqual(a, vec4(1.0))) *\n vec4(greaterThanEqual(b, vec4(1.0))));\n",dtype:"bool"}),w0={kernelName:ab,backendName:"webgl",kernelFunc:x0},k0=zJ({opSnippet:"return float(!(x >= 1.0));"}),N0={kernelName:ib,backendName:"webgl",kernelFunc:k0},I0=PJ({opSnippet:"return float(a >= 1.0 || b >= 1.0);",packedOpSnippet:"\n return min(\n vec4(greaterThanEqual(a, vec4(1.0))) +\n vec4(greaterThanEqual(b, vec4(1.0))),\n vec4(1.0));\n",dtype:"bool"}),S0={kernelName:ob,backendName:"webgl",kernelFunc:I0},T0=function(e,t,n,r,a){this.variableNames=["x"],this.outputShape=[];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[0];\n int r = coords[1];\n int c = coords[2];\n int d = coords[3];\n float x = getX(b, r, c, d);\n float sum = 0.0;\n for (int j = -"+o+"; j <= "+o+"; j++) {\n int idx = d + j;\n if (idx >= 0 && idx <= "+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 "},E0=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 "},C0={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=Rg().getBool("WEBGL_PACK_NORMALIZATION")?new E0(a.shape,i,o,s,u):new T0(a.shape,i,o,s,u);return n.runWebGLProgram(l,[a],a.dtype)}},R0=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 "},A0={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 R0(a.shape,s,u,l,c);return n.runWebGLProgram(p,[a,i,o],a.dtype)}};function _0(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=uE(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=iJ(d,a.shape,a.dtype,c,m);f=n.makeTensorInfo(m,a.dtype),n.texData.get(f.dataId).values=g}else f=eZ(a,c,n);l=cE(l.length,s)}sE("max",l,s);var y,b=iE(f.shape,l),x=b[0],w=b[1],k=x;if(o&&(k=oE(x,u)),h){var N=n.texData.get(f.dataId).values,I=LY(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=KJ({inputs:{x:e},attrs:{shape:[Hv(e.shape)/a,a]},backend:r}),o=ZJ(i,e.dtype,"max",r),s=KJ({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 F0={kernelName:cb,backendName:"webgl",kernelFunc:_0},D0=PJ({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. ? 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:zY}),O0={kernelName:pb,backendName:"webgl",kernelFunc:D0};var M0={kernelName:hb,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x;AX(a,"maxPool");var i=r.filterSize,o=r.strides,s=r.pad,u=r.dimRoundingMode;Uv(_S(o,1),(function(){return"Error in maxPool: Either strides or dilations must be 1. Got strides "+o+" and dilations '1'"}));var l=wS(a.shape,i,o,1,s,u);if(1===l.filterWidth&&1===l.filterHeight&&qv(l.inShape,l.outShape))return EJ({inputs:{x:a},backend:n});var c=new PZ(l,"max",!1);return n.runWebGLProgram(c,[a],a.dtype)}};var L0={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=kS(a.shape,i,o,[1,1,1],s,l,u),p=new BZ(c,"max",!1);return n.runWebGLProgram(p,[a],a.dtype)}},z0=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 "},P0=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 B0={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=kS(i.shape,o,s,[1,1,1],u,l),p=new BZ(c,"max",!0),h=n.runWebGLProgram(p,[i],i.dtype),f=new P0(c),d=n.runWebGLProgram(f,[a,h],i.dtype);return n.disposeIntermediateTensorInfo(h),d}};var W0={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;AX([i,t.output],"maxPoolGrad");var s=r.filterSize,u=r.strides,l=r.pad,c=r.dimRoundingMode,p=wS(o.shape,s,u,1,l,c),h=new PZ(p,"max",!0),f=n.runWebGLProgram(h,[o],o.dtype),d=new z0(p),m=n.runWebGLProgram(d,[a,f],o.dtype);return n.disposeIntermediateTensorInfo(f),m}};var U0={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;Uv(4===a.shape.length,(function(){return"Error in maxPool: input must be rank 4 but got rank "+a.shape.length+"."}));var c=[1,1];Uv(_S(o,c),(function(){return"Error in maxPool: Either strides or dilations must be 1. 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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. ? 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NAN : result.a;\n\n return result;\n"}),I1={kernelName:Db,backendName:"webgl",kernelFunc:N1};var S1={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=uE(p,u),f=i;if(null!=h&&(f=rZ({inputs:{x:i},backend:r,attrs:{perm:h}}),p=cE(p.length,u),l.push(f)),sE("prod",p,u),r.shouldExecuteOnCPU([f])){var d=r.texData.get(f.dataId).values,m=VY(f.shape,f.dtype,d,p),v=m.outVals,g=m.outShape,y=m.outDtype;t=r.makeTensorInfo(g,y,v)}else{var b=iE(f.shape,p),x=b[0],w=Hv(b[1]),k=KJ({inputs:{x:f},backend:r,attrs:{shape:[-1,w]}}),N=ZJ(k,rk(i.dtype),"prod",r);t=KJ({inputs:{x:N},backend:r,attrs:{shape:x}}),l.push(k),l.push(N)}if(s){l.push(t);var I=oE(t.shape,c);t=KJ({inputs:{x:t},backend:r,attrs:{shape:I}})}return l.forEach((function(e){return r.disposeIntermediateTensorInfo(e)})),t}},T1=function(e){var t=e.backend,n=e.attrs,r=n.start,a=n.stop,i=n.step,o=n.dtype,s=GY(r,a,i,o);return t.makeTensorInfo([s.length],o,s)},E1={kernelName:Lb,backendName:"webgl",kernelFunc:T1},C1=zJ({opSnippet:"return 1.0 / x;"}),R1={kernelName:Pb,backendName:"webgl",kernelFunc:C1},A1=zJ({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"}),_1={kernelName:Bb,backendName:"webgl",kernelFunc:A1},F1=zJ({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"}),D1={kernelName:Hb,backendName:"webgl",kernelFunc:F1},O1=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 "},M1=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 L1={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=Rg().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new M1(a.shape,u,l,i,o):new O1(a.shape,u,l,i,o);return n.runWebGLProgram(c,[a],"float32")}},z1=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 P1={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 z1(i.shape,a.shape,o);return n.runWebGLProgram(s,[i],i.dtype)}},B1=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 "},W1=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 U1={kernelName:Ub,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=Rg().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new W1(a.shape,u,l,i,o):new B1(a.shape,u,l,i,o);return n.runWebGLProgram(c,[a],a.dtype)}},V1=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 G1={kernelName:Vb,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 V1(i.shape,a.shape,o);return n.runWebGLProgram(s,[i],i.dtype)}},j1=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=XX(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 "},H1=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=uJ("rc",n),a=r[n-1]+" + 1 < "+this.outputShape[n-1],i=r[n-2]+" + 1 < "+this.outputShape[n-2],o=XX(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 q1={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 EJ({inputs:{x:a},backend:n});var u=Rg().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new H1(a.shape,s):new j1(a.shape,s);return n.runWebGLProgram(u,[a],a.dtype)}},K1=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 "},X1={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 K1(a.shape,o),c=KA(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)}},Y1=zJ({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 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> 0.0 ? 1.0 : float("+n.alpha+");\n ",o=new mJ(a.shape,i);return r.runWebGLProgram(o,[a],a.dtype)}},A2=function(e,t,n){this.variableNames=["x"],this.outputShape=n;var r=n.length,a=XX(n.length),i=XX(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 _2={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=MI(i.shape,o,s,u,l,c,p,h,f),m=d.finalShapeSparse,v=d.finalShape,g=d.isIdentity,y=d.sliceDim0,b=d.isSimpleSlice,x=d.begin,w=d.end,k=d.strides;if(g)t=KJ({inputs:{x:i},backend:r,attrs:{shape:v}});else if(y||b){Uv(i.shape.length>=1,(function(){return"Input must have rank at least 1, got: "+i.shape.length}));var N=NI(x,w,k),I=$Z({inputs:{x:i},backend:r,attrs:{begin:x,size:N}});t=KJ({inputs:{x:I},backend:r,attrs:{shape:v}}),r.disposeIntermediateTensorInfo(I)}else{if(r.shouldExecuteOnCPU([i])){var S=r.readSync(i.dataId),T=FN(i.shape,i.dtype,S),E=QY(m,T,k,x);t=r.makeTensorInfo(v,i.dtype,E.values)}else{var C=new A2(x,k,m);t=r.runWebGLProgram(C,[i],i.dtype)}}var R=KJ({inputs:{x:t},backend:r,attrs:{shape:v}});return r.disposeIntermediateTensorInfo(t),R}};var F2={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=$Y(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 D2={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=eJ(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 O2={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=tJ(i,r);return n.makeTensorInfo(a.shape,"int32",o)}},M2=zJ({opSnippet:"return tan(x);"}),L2={kernelName:wx,backendName:"webgl",kernelFunc:M2},z2=zJ({opSnippet:"\n float e2x = exp(-2.0 * abs(x));\n return sign(x) * (1.0 - e2x) / (1.0 + e2x);\n"}),P2=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=XX(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 B2(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 Mw(e)})):o,u=FN(a.shape,a.dtype,s),l=rJ(u,i);return n.makeTensorInfo(l.shape,l.dtype,l.values)}var c=new P2(a.shape,i);return n.runWebGLProgram(c,[a],a.dtype)}var W2=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. 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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 V2(e,t){null!==t&&e.disposeIntermediateTensorInfo(t)}function G2(e){for(var t=1;t<e;)t*=2;return t}var j2=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 } 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H2=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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