/*
  Human
  homepage: <https://github.com/vladmandic/human>
  author: <https://github.com/vladmandic>'
*/

"use strict";var Human=(()=>{var jc=Object.defineProperty;var MC=Object.getOwnPropertyDescriptor;var $C=Object.getOwnPropertyNames;var PC=Object.prototype.hasOwnProperty;var Gx=e=>{throw TypeError(e)};var _C=(e,t,a)=>t in e?jc(e,t,{enumerable:!0,configurable:!0,writable:!0,value:a}):e[t]=a;var Ar=(e,t)=>{for(var a in t)jc(e,a,{get:t[a],enumerable:!0})},FC=(e,t,a,n)=>{if(t&&typeof t=="object"||typeof t=="function")for(let r of $C(t))!PC.call(e,r)&&r!==a&&jc(e,r,{get:()=>t[r],enumerable:!(n=MC(t,r))||n.enumerable});return e};var DC=e=>FC(jc({},"__esModule",{value:!0}),e);var he=(e,t,a)=>_C(e,typeof t!="symbol"?t+"":t,a),Hx=(e,t,a)=>t.has(e)||Gx("Cannot "+a);var qa=(e,t,a)=>(Hx(e,t,"read from private field"),a?a.call(e):t.get(e)),Kn=(e,t,a)=>t.has(e)?Gx("Cannot add the same private member more than once"):t instanceof WeakSet?t.add(e):t.set(e,a),br=(e,t,a,n)=>(Hx(e,t,"write to private field"),n?n.call(e,a):t.set(e,a),a);var dye={};Ar(dye,{Env:()=>nc,Human:()=>Mx,default:()=>Mx,defaults:()=>pl,draw:()=>C0,empty:()=>hr,env:()=>ne,match:()=>em,models:()=>Ex});var Ke={};Ar(Ke,{Abs:()=>ou,Acos:()=>oi,Acosh:()=>li,AdadeltaOptimizer:()=>Zg,AdagradOptimizer:()=>Jg,AdamOptimizer:()=>Qg,AdamaxOptimizer:()=>e3,Add:()=>ls,AddN:()=>ui,All:()=>di,Any:()=>pi,ArgMax:()=>lu,ArgMin:()=>uu,Asin:()=>ci,Asinh:()=>hi,Atan:()=>mi,Atan2:()=>gi,Atanh:()=>fi,AvgPool:()=>yi,AvgPool3D:()=>du,AvgPool3DGrad:()=>pp,AvgPoolGrad:()=>dp,BackendWasm:()=>Ik,BatchMatMul:()=>xi,BatchToSpaceND:()=>pu,Bincount:()=>Ai,BitwiseAnd:()=>cu,BroadcastArgs:()=>hu,BroadcastTo:()=>TT,Cast:()=>bi,Ceil:()=>vi,ClipByValue:()=>us,Complex:()=>cp,ComplexAbs:()=>hp,Concat:()=>mu,Conv2D:()=>wi,Conv2DBackpropFilter:()=>mp,Conv2DBackpropInput:()=>ki,Conv3D:()=>Ii,Conv3DBackpropFilterV2:()=>fu,Conv3DBackpropInputV2:()=>Si,Cos:()=>Ci,Cosh:()=>Ti,CropAndResize:()=>Ei,Cumprod:()=>Ni,Cumsum:()=>Ri,DataStorage:()=>op,DenseBincount:()=>gu,DepthToSpace:()=>Mi,DepthwiseConv2dNative:()=>$i,DepthwiseConv2dNativeBackpropFilter:()=>fp,DepthwiseConv2dNativeBackpropInput:()=>gp,Diag:()=>yu,Dilation2D:()=>Pi,Dilation2DBackpropFilter:()=>Xl,Dilation2DBackpropInput:()=>ql,Draw:()=>yp,ENV:()=>eg,Einsum:()=>xp,Elu:()=>Fi,EluGrad:()=>xu,Environment:()=>TA,Equal:()=>Oi,Erf:()=>Di,Exp:()=>zi,ExpandDims:()=>Au,Expm1:()=>Li,FFT:()=>Ap,Fill:()=>bu,FlipLeftRight:()=>Wi,Floor:()=>Bi,FloorDiv:()=>Vi,FromPixels:()=>Wd,FusedBatchNorm:()=>Ui,FusedConv2D:()=>Jr,FusedDepthwiseConv2D:()=>Qr,GPGPUContext:()=>Hl,GatherNd:()=>Gi,GatherV2:()=>vu,GraphModel:()=>Xp,Greater:()=>Hi,GreaterEqual:()=>ji,IFFT:()=>bp,Identity:()=>qi,Imag:()=>vp,IsFinite:()=>Xi,IsInf:()=>Ki,IsNan:()=>Yi,KernelBackend:()=>su,LRN:()=>io,LRNGrad:()=>wu,LeakyRelu:()=>Zi,Less:()=>Ji,LessEqual:()=>Qi,LinSpace:()=>eo,Log:()=>to,Log1p:()=>ao,LogSoftmax:()=>NT,LogicalAnd:()=>no,LogicalNot:()=>ro,LogicalOr:()=>so,LogicalXor:()=>RA,LowerBound:()=>RT,MathBackendCPU:()=>p3,MathBackendWebGL:()=>Jp,MatrixBandPart:()=>ET,Max:()=>oo,MaxPool:()=>uo,MaxPool3D:()=>ku,MaxPool3DGrad:()=>kp,MaxPoolGrad:()=>wp,MaxPoolWithArgmax:()=>Iu,Maximum:()=>lo,Mean:()=>po,Min:()=>co,Minimum:()=>ho,MirrorPad:()=>mo,Mod:()=>fo,MomentumOptimizer:()=>t3,Multinomial:()=>go,Multiply:()=>yo,Neg:()=>Su,NonMaxSuppressionV3:()=>Ao,NonMaxSuppressionV4:()=>Cu,NonMaxSuppressionV5:()=>bo,NotEqual:()=>xo,OP_SCOPE_SUFFIX:()=>sg,OneHot:()=>vo,OnesLike:()=>Tu,Optimizer:()=>hs,OptimizerConstructors:()=>U7,Pack:()=>Nu,PadV2:()=>wo,Pool:()=>MT,Pow:()=>ko,Prelu:()=>Io,Prod:()=>So,RMSPropOptimizer:()=>a3,RaggedGather:()=>$h,RaggedRange:()=>Ph,RaggedTensorToTensor:()=>_h,Range:()=>Ru,Rank:()=>n1,Real:()=>Ip,RealDiv:()=>_i,Reciprocal:()=>Co,Reduction:()=>wa,Relu:()=>To,Relu6:()=>Eo,Reshape:()=>Eu,ResizeBilinear:()=>Ro,ResizeBilinearGrad:()=>$u,ResizeNearestNeighbor:()=>No,ResizeNearestNeighborGrad:()=>Mu,Reverse:()=>Mo,RotateWithOffset:()=>el,Round:()=>$o,Rsqrt:()=>Po,SGDOptimizer:()=>Qh,ScatterNd:()=>_o,SearchSorted:()=>Do,Select:()=>Pu,Selu:()=>Oo,Sigmoid:()=>Bo,Sign:()=>Wo,Sin:()=>zo,Sinh:()=>Lo,Slice:()=>_u,Softmax:()=>Ho,Softplus:()=>Vo,SpaceToBatchND:()=>Fu,SparseFillEmptyRows:()=>Sp,SparseReshape:()=>Ou,SparseSegmentMean:()=>zu,SparseSegmentSum:()=>Lu,SparseToDense:()=>jo,SplitV:()=>Du,Sqrt:()=>Uo,Square:()=>Cp,SquaredDifference:()=>qo,StaticRegexReplace:()=>Tp,Step:()=>ps,StridedSlice:()=>Xo,StringNGrams:()=>Wu,StringSplit:()=>Np,StringToHashBucketFast:()=>Rp,Sub:()=>Ko,Sum:()=>Go,Tan:()=>Yo,Tanh:()=>Zo,Tensor:()=>yt,TensorBuffer:()=>Vt,TensorScatterUpdate:()=>Fo,Tile:()=>ds,TopK:()=>Jo,Transform:()=>Qo,Transpose:()=>Ir,Unique:()=>Ep,Unpack:()=>Bu,UnsortedSegmentSum:()=>Mp,UpperBound:()=>$T,Variable:()=>Gd,WebGPUBackend:()=>X3,ZerosLike:()=>Vu,_FusedMatMul:()=>Zr,abs:()=>Za,acos:()=>ab,acosh:()=>nb,add:()=>we,addN:()=>Dh,all:()=>rb,any:()=>sb,argMax:()=>ir,argMin:()=>ib,asin:()=>ob,asinh:()=>lb,atan:()=>ub,atan2:()=>db,atanh:()=>pb,avgPool:()=>hg,avgPool3d:()=>fb,backend:()=>Vn,backend_util:()=>C,basicLSTMCell:()=>gb,batchNorm:()=>Wp,batchNorm2d:()=>yb,batchNorm3d:()=>xb,batchNorm4d:()=>Ab,batchToSpaceND:()=>mg,bincount:()=>fg,bitwiseAnd:()=>bb,booleanMaskAsync:()=>r7,broadcastArgs:()=>vb,broadcastTo:()=>Gl,broadcast_util:()=>nl,browser:()=>Un,buffer:()=>_e,cast:()=>Ue,ceil:()=>wb,clipByValue:()=>kb,clone:()=>Ia,complex:()=>Tr,concat:()=>lt,concat1d:()=>Ib,concat2d:()=>Uu,concat3d:()=>Sb,concat4d:()=>Cb,conv1d:()=>Tb,conv2d:()=>Bp,conv2dTranspose:()=>Rb,conv3d:()=>Eb,conv3dTranspose:()=>Mb,copyRegisteredKernels:()=>OT,cos:()=>$b,cosh:()=>Pb,cosineWindow:()=>Xh,cumprod:()=>_b,cumsum:()=>Fb,customGrad:()=>nr,denseBincount:()=>Db,deprecationWarn:()=>og,depthToSpace:()=>Ob,depthwiseConv2d:()=>Oh,deregisterOp:()=>LD,device_util:()=>Fp,diag:()=>zb,dilation2d:()=>Lb,disableDeprecationWarnings:()=>mN,dispose:()=>J,disposeVariables:()=>fN,div:()=>ve,divNoNan:()=>Bb,dot:()=>Vb,dropout:()=>u7,einsum:()=>Vs,elu:()=>xg,enableDebugMode:()=>hN,enableProdMode:()=>ig,enclosingPowerOfTwo:()=>Xg,engine:()=>It,ensureShape:()=>Ub,env:()=>B,equal:()=>yg,erf:()=>Gb,euclideanNorm:()=>qb,exp:()=>rs,expandDims:()=>Wt,expm1:()=>Xb,eye:()=>bg,fft:()=>Gh,fill:()=>or,findBackend:()=>lg,findBackendFactory:()=>bN,floor:()=>vg,floorDiv:()=>zp,forceHalfFloat:()=>x8,fused:()=>Kg,gather:()=>wg,gatherND:()=>l7,gather_util:()=>s3,getBackend:()=>ea,getGradient:()=>t1,getKernel:()=>Vd,getKernelsForBackend:()=>er,getThreadsCount:()=>dle,gpgpu_util:()=>Kv,grad:()=>aM,grads:()=>nM,greater:()=>Gp,greaterEqual:()=>kg,ifft:()=>Jd,imag:()=>Hp,image:()=>fe,inTopKAsync:()=>d7,io:()=>Zn,irfft:()=>Vg,isFinite:()=>Kb,isInf:()=>Yb,isNaN:()=>Zb,keep:()=>Ln,kernel_impls:()=>En,leakyRelu:()=>Ig,less:()=>mh,lessEqual:()=>zh,linalg:()=>x7,linspace:()=>Jb,loadGraphModel:()=>d3,loadGraphModelSync:()=>HO,localResponseNormalization:()=>Qb,log:()=>Zl,log1p:()=>Sg,logSigmoid:()=>t4,logSoftmax:()=>a4,logSumExp:()=>Tg,logicalAnd:()=>Kd,logicalNot:()=>Ng,logicalOr:()=>Rg,logicalXor:()=>n4,losses:()=>A7,lowerBound:()=>r4,matMul:()=>pt,math:()=>M7,max:()=>ga,maxPool:()=>Eg,maxPool3d:()=>s4,maxPoolWithArgmax:()=>i4,maximum:()=>Mg,mean:()=>Yd,memory:()=>gN,meshgrid:()=>o4,min:()=>ns,minimum:()=>Zd,mirrorPad:()=>l4,mod:()=>Gu,moments:()=>u4,movingAverage:()=>s7,mul:()=>te,multiRNNCell:()=>d4,multinomial:()=>p4,neg:()=>Wn,nextFrame:()=>G7,node:()=>Q3,norm:()=>Up,notEqual:()=>$g,oneHot:()=>fh,ones:()=>jr,onesLike:()=>c4,op:()=>z,outerProduct:()=>h4,pad:()=>Rn,pad1d:()=>m4,pad2d:()=>f4,pad3d:()=>g4,pad4d:()=>y4,pool:()=>x4,pow:()=>Yl,prelu:()=>_g,print:()=>pg,prod:()=>A4,profile:()=>yN,raggedGather:()=>b4,raggedRange:()=>v4,raggedTensorToTensor:()=>w4,rand:()=>k4,randomGamma:()=>T4,randomNormal:()=>Lg,randomStandardNormal:()=>N4,randomUniform:()=>Bh,randomUniformInt:()=>R4,range:()=>Jl,ready:()=>tl,real:()=>Ql,reciprocal:()=>E4,registerBackend:()=>al,registerGradient:()=>_T,registerKernel:()=>xn,registerOp:()=>zD,relu:()=>jp,relu6:()=>Wg,removeBackend:()=>AN,reshape:()=>Q,reverse:()=>ss,reverse1d:()=>M4,reverse2d:()=>$4,reverse3d:()=>P4,reverse4d:()=>_4,rfft:()=>Hh,round:()=>Bg,rsqrt:()=>F4,scalar:()=>Ge,scatterND:()=>i7,scatter_util:()=>jh,searchSorted:()=>Wh,selu:()=>D4,separableConv2d:()=>O4,serialization:()=>w7,setBackend:()=>Dp,setPlatform:()=>vN,setThreadsCount:()=>ule,setWasmPath:()=>lle,setWasmPaths:()=>u0,setWebGLContext:()=>n0,setdiff1dAsync:()=>z4,shared:()=>t0,sigmoid:()=>za,sign:()=>L4,signal:()=>y7,sin:()=>W4,sinh:()=>B4,slice:()=>Fe,slice1d:()=>V4,slice2d:()=>U4,slice3d:()=>qp,slice4d:()=>Vh,slice_util:()=>Nt,softmax:()=>Uh,softplus:()=>Cg,spaceToBatchND:()=>Pg,sparse:()=>b7,sparseToDense:()=>o7,spectral:()=>g7,split:()=>Sa,sqrt:()=>ar,square:()=>Tn,squaredDifference:()=>Ug,squeeze:()=>Oe,stack:()=>ha,step:()=>Gg,stridedSlice:()=>G4,string:()=>v7,sub:()=>xe,sum:()=>ot,sumOutType:()=>_p,tan:()=>H4,tanh:()=>hh,tensor:()=>Ve,tensor1d:()=>Bt,tensor2d:()=>Qn,tensor3d:()=>Hg,tensor4d:()=>j4,tensor5d:()=>q4,tensor6d:()=>X4,tensorScatterUpdate:()=>Y4,tensor_util:()=>FA,test_util:()=>I4,tidy:()=>De,tile:()=>Kr,time:()=>xN,topk:()=>Z4,train:()=>FF,transpose:()=>Qs,truncatedNormal:()=>J4,unique:()=>Q4,unregisterGradient:()=>DT,unregisterKernel:()=>FT,unsortedSegmentSum:()=>e7,unstack:()=>Na,upcastType:()=>ca,upperBound:()=>t7,util:()=>v,valueAndGrad:()=>rM,valueAndGrads:()=>sM,variable:()=>a7,variableGrads:()=>e4,version:()=>ac,version_converter:()=>qO,version_core:()=>i3,version_cpu:()=>oL,version_wasm:()=>ple,version_webgl:()=>Yj,webgl:()=>Zj,webgl_util:()=>Av,webgpu_util:()=>Tk,where:()=>Sr,whereAsync:()=>qg,zeros:()=>yn,zerosLike:()=>Qa});var OC=Object.create,Z1=Object.defineProperty,zC=Object.getOwnPropertyDescriptor,LC=Object.getOwnPropertyNames,WC=Object.getPrototypeOf,BC=Object.prototype.hasOwnProperty,Xt=(e,t)=>()=>(t||e((t={exports:{}}).exports,t),t.exports),Ze=(e,t)=>{for(var a in t)Z1(e,a,{get:t[a],enumerable:!0})},VC=(e,t,a,n)=>{if(t&&typeof t=="object"||typeof t=="function")for(let r of LC(t))!BC.call(e,r)&&r!==a&&Z1(e,r,{get:()=>t[r],enumerable:!(n=zC(t,r))||n.enumerable});return e},ru=(e,t,a)=>(a=e!=null?OC(WC(e)):{},VC(t||!e||!e.__esModule?Z1(a,"default",{value:e,enumerable:!0}):a,e)),UC=Xt((e,t)=>{t.exports=n;var a=null;try{a=new WebAssembly.Instance(new WebAssembly.Module(new Uint8Array([0,97,115,109,1,0,0,0,1,13,2,96,0,1,127,96,4,127,127,127,127,1,127,3,7,6,0,1,1,1,1,1,6,6,1,127,1,65,0,11,7,50,6,3,109,117,108,0,1,5,100,105,118,95,115,0,2,5,100,105,118,95,117,0,3,5,114,101,109,95,115,0,4,5,114,101,109,95,117,0,5,8,103,101,116,95,104,105,103,104,0,0,10,191,1,6,4,0,35,0,11,36,1,1,126,32,0,173,32,1,173,66,32,134,132,32,2,173,32,3,173,66,32,134,132,126,34,4,66,32,135,167,36,0,32,4,167,11,36,1,1,126,32,0,173,32,1,173,66,32,134,132,32,2,173,32,3,173,66,32,134,132,127,34,4,66,32,135,167,36,0,32,4,167,11,36,1,1,126,32,0,173,32,1,173,66,32,134,132,32,2,173,32,3,173,66,32,134,132,128,34,4,66,32,135,167,36,0,32,4,167,11,36,1,1,126,32,0,173,32,1,173,66,32,134,132,32,2,173,32,3,173,66,32,134,132,129,34,4,66,32,135,167,36,0,32,4,167,11,36,1,1,126,32,0,173,32,1,173,66,32,134,132,32,2,173,32,3,173,66,32,134,132,130,34,4,66,32,135,167,36,0,32,4,167,11])),{}).exports}catch(S){}function n(S,_,O){this.low=S|0,this.high=_|0,this.unsigned=!!O}n.prototype.__isLong__,Object.defineProperty(n.prototype,"__isLong__",{value:!0});function r(S){return(S&&S.__isLong__)===!0}n.isLong=r;var s={},i={};function o(S,_){var O,W,P;return _?(S>>>=0,(P=0<=S&&S<256)&&(W=i[S],W)?W:(O=u(S,(S|0)<0?-1:0,!0),P&&(i[S]=O),O)):(S|=0,(P=-128<=S&&S<128)&&(W=s[S],W)?W:(O=u(S,S<0?-1:0,!1),P&&(s[S]=O),O))}n.fromInt=o;function l(S,_){if(isNaN(S))return _?b:A;if(_){if(S<0)return b;if(S>=g)return M}else{if(S<=-y)return $;if(S+1>=y)return N}return S<0?l(-S,_).neg():u(S%f|0,S/f|0,_)}n.fromNumber=l;function u(S,_,O){return new n(S,_,O)}n.fromBits=u;var p=Math.pow;function c(S,_,O){if(S.length===0)throw Error("empty string");if(S==="NaN"||S==="Infinity"||S==="+Infinity"||S==="-Infinity")return A;if(typeof _=="number"?(O=_,_=!1):_=!!_,O=O||10,O<2||36<O)throw RangeError("radix");var W;if((W=S.indexOf("-"))>0)throw Error("interior hyphen");if(W===0)return c(S.substring(1),_,O).neg();for(var P=l(p(O,8)),U=A,G=0;G<S.length;G+=8){var q=Math.min(8,S.length-G),H=parseInt(S.substring(G,G+q),O);if(q<8){var V=l(p(O,q));U=U.mul(V).add(l(H))}else U=U.mul(P),U=U.add(l(H))}return U.unsigned=_,U}n.fromString=c;function d(S,_){return typeof S=="number"?l(S,_):typeof S=="string"?c(S,_):u(S.low,S.high,typeof _=="boolean"?_:S.unsigned)}n.fromValue=d;var h=65536,m=1<<24,f=h*h,g=f*f,y=g/2,x=o(m),A=o(0);n.ZERO=A;var b=o(0,!0);n.UZERO=b;var w=o(1);n.ONE=w;var I=o(1,!0);n.UONE=I;var T=o(-1);n.NEG_ONE=T;var N=u(-1,2147483647,!1);n.MAX_VALUE=N;var M=u(-1,-1,!0);n.MAX_UNSIGNED_VALUE=M;var $=u(0,-2147483648,!1);n.MIN_VALUE=$;var E=n.prototype;E.toInt=function(){return this.unsigned?this.low>>>0:this.low},E.toNumber=function(){return this.unsigned?(this.high>>>0)*f+(this.low>>>0):this.high*f+(this.low>>>0)},E.toString=function(S){if(S=S||10,S<2||36<S)throw RangeError("radix");if(this.isZero())return"0";if(this.isNegative())if(this.eq($)){var _=l(S),O=this.div(_),W=O.mul(_).sub(this);return O.toString(S)+W.toInt().toString(S)}else return"-"+this.neg().toString(S);for(var P=l(p(S,6),this.unsigned),U=this,G="";;){var q=U.div(P),H=U.sub(q.mul(P)).toInt()>>>0,V=H.toString(S);if(U=q,U.isZero())return V+G;for(;V.length<6;)V="0"+V;G=""+V+G}},E.getHighBits=function(){return this.high},E.getHighBitsUnsigned=function(){return this.high>>>0},E.getLowBits=function(){return this.low},E.getLowBitsUnsigned=function(){return this.low>>>0},E.getNumBitsAbs=function(){if(this.isNegative())return this.eq($)?64:this.neg().getNumBitsAbs();for(var S=this.high!=0?this.high:this.low,_=31;_>0&&!(S&1<<_);_--);return this.high!=0?_+33:_+1},E.isZero=function(){return this.high===0&&this.low===0},E.eqz=E.isZero,E.isNegative=function(){return!this.unsigned&&this.high<0},E.isPositive=function(){return this.unsigned||this.high>=0},E.isOdd=function(){return(this.low&1)===1},E.isEven=function(){return(this.low&1)===0},E.equals=function(S){return r(S)||(S=d(S)),this.unsigned!==S.unsigned&&this.high>>>31===1&&S.high>>>31===1?!1:this.high===S.high&&this.low===S.low},E.eq=E.equals,E.notEquals=function(S){return!this.eq(S)},E.neq=E.notEquals,E.ne=E.notEquals,E.lessThan=function(S){return this.comp(S)<0},E.lt=E.lessThan,E.lessThanOrEqual=function(S){return this.comp(S)<=0},E.lte=E.lessThanOrEqual,E.le=E.lessThanOrEqual,E.greaterThan=function(S){return this.comp(S)>0},E.gt=E.greaterThan,E.greaterThanOrEqual=function(S){return this.comp(S)>=0},E.gte=E.greaterThanOrEqual,E.ge=E.greaterThanOrEqual,E.compare=function(S){if(r(S)||(S=d(S)),this.eq(S))return 0;var _=this.isNegative(),O=S.isNegative();return _&&!O?-1:!_&&O?1:this.unsigned?S.high>>>0>this.high>>>0||S.high===this.high&&S.low>>>0>this.low>>>0?-1:1:this.sub(S).isNegative()?-1:1},E.comp=E.compare,E.negate=function(){return!this.unsigned&&this.eq($)?$:this.not().add(w)},E.neg=E.negate,E.add=function(S){r(S)||(S=d(S));var _=this.high>>>16,O=this.high&65535,W=this.low>>>16,P=this.low&65535,U=S.high>>>16,G=S.high&65535,q=S.low>>>16,H=S.low&65535,V=0,Z=0,X=0,re=0;return re+=P+H,X+=re>>>16,re&=65535,X+=W+q,Z+=X>>>16,X&=65535,Z+=O+G,V+=Z>>>16,Z&=65535,V+=_+U,V&=65535,u(X<<16|re,V<<16|Z,this.unsigned)},E.subtract=function(S){return r(S)||(S=d(S)),this.add(S.neg())},E.sub=E.subtract,E.multiply=function(S){if(this.isZero())return A;if(r(S)||(S=d(S)),a){var _=a.mul(this.low,this.high,S.low,S.high);return u(_,a.get_high(),this.unsigned)}if(S.isZero())return A;if(this.eq($))return S.isOdd()?$:A;if(S.eq($))return this.isOdd()?$:A;if(this.isNegative())return S.isNegative()?this.neg().mul(S.neg()):this.neg().mul(S).neg();if(S.isNegative())return this.mul(S.neg()).neg();if(this.lt(x)&&S.lt(x))return l(this.toNumber()*S.toNumber(),this.unsigned);var O=this.high>>>16,W=this.high&65535,P=this.low>>>16,U=this.low&65535,G=S.high>>>16,q=S.high&65535,H=S.low>>>16,V=S.low&65535,Z=0,X=0,re=0,ee=0;return ee+=U*V,re+=ee>>>16,ee&=65535,re+=P*V,X+=re>>>16,re&=65535,re+=U*H,X+=re>>>16,re&=65535,X+=W*V,Z+=X>>>16,X&=65535,X+=P*H,Z+=X>>>16,X&=65535,X+=U*q,Z+=X>>>16,X&=65535,Z+=O*V+W*H+P*q+U*G,Z&=65535,u(re<<16|ee,Z<<16|X,this.unsigned)},E.mul=E.multiply,E.divide=function(S){if(r(S)||(S=d(S)),S.isZero())throw Error("division by zero");if(a){if(!this.unsigned&&this.high===-2147483648&&S.low===-1&&S.high===-1)return this;var _=(this.unsigned?a.div_u:a.div_s)(this.low,this.high,S.low,S.high);return u(_,a.get_high(),this.unsigned)}if(this.isZero())return this.unsigned?b:A;var O,W,P;if(this.unsigned){if(S.unsigned||(S=S.toUnsigned()),S.gt(this))return b;if(S.gt(this.shru(1)))return I;P=b}else{if(this.eq($)){if(S.eq(w)||S.eq(T))return $;if(S.eq($))return w;var U=this.shr(1);return O=U.div(S).shl(1),O.eq(A)?S.isNegative()?w:T:(W=this.sub(S.mul(O)),P=O.add(W.div(S)),P)}else if(S.eq($))return this.unsigned?b:A;if(this.isNegative())return S.isNegative()?this.neg().div(S.neg()):this.neg().div(S).neg();if(S.isNegative())return this.div(S.neg()).neg();P=A}for(W=this;W.gte(S);){O=Math.max(1,Math.floor(W.toNumber()/S.toNumber()));for(var G=Math.ceil(Math.log(O)/Math.LN2),q=G<=48?1:p(2,G-48),H=l(O),V=H.mul(S);V.isNegative()||V.gt(W);)O-=q,H=l(O,this.unsigned),V=H.mul(S);H.isZero()&&(H=w),P=P.add(H),W=W.sub(V)}return P},E.div=E.divide,E.modulo=function(S){if(r(S)||(S=d(S)),a){var _=(this.unsigned?a.rem_u:a.rem_s)(this.low,this.high,S.low,S.high);return u(_,a.get_high(),this.unsigned)}return this.sub(this.div(S).mul(S))},E.mod=E.modulo,E.rem=E.modulo,E.not=function(){return u(~this.low,~this.high,this.unsigned)},E.and=function(S){return r(S)||(S=d(S)),u(this.low&S.low,this.high&S.high,this.unsigned)},E.or=function(S){return r(S)||(S=d(S)),u(this.low|S.low,this.high|S.high,this.unsigned)},E.xor=function(S){return r(S)||(S=d(S)),u(this.low^S.low,this.high^S.high,this.unsigned)},E.shiftLeft=function(S){return r(S)&&(S=S.toInt()),(S&=63)===0?this:S<32?u(this.low<<S,this.high<<S|this.low>>>32-S,this.unsigned):u(0,this.low<<S-32,this.unsigned)},E.shl=E.shiftLeft,E.shiftRight=function(S){return r(S)&&(S=S.toInt()),(S&=63)===0?this:S<32?u(this.low>>>S|this.high<<32-S,this.high>>S,this.unsigned):u(this.high>>S-32,this.high>=0?0:-1,this.unsigned)},E.shr=E.shiftRight,E.shiftRightUnsigned=function(S){if(r(S)&&(S=S.toInt()),S&=63,S===0)return this;var _=this.high;if(S<32){var O=this.low;return u(O>>>S|_<<32-S,_>>>S,this.unsigned)}else return S===32?u(_,0,this.unsigned):u(_>>>S-32,0,this.unsigned)},E.shru=E.shiftRightUnsigned,E.shr_u=E.shiftRightUnsigned,E.toSigned=function(){return this.unsigned?u(this.low,this.high,!1):this},E.toUnsigned=function(){return this.unsigned?this:u(this.low,this.high,!0)},E.toBytes=function(S){return S?this.toBytesLE():this.toBytesBE()},E.toBytesLE=function(){var S=this.high,_=this.low;return[_&255,_>>>8&255,_>>>16&255,_>>>24,S&255,S>>>8&255,S>>>16&255,S>>>24]},E.toBytesBE=function(){var S=this.high,_=this.low;return[S>>>24,S>>>16&255,S>>>8&255,S&255,_>>>24,_>>>16&255,_>>>8&255,_&255]},n.fromBytes=function(S,_,O){return O?n.fromBytesLE(S,_):n.fromBytesBE(S,_)},n.fromBytesLE=function(S,_){return new n(S[0]|S[1]<<8|S[2]<<16|S[3]<<24,S[4]|S[5]<<8|S[6]<<16|S[7]<<24,_)},n.fromBytesBE=function(S,_){return new n(S[4]<<24|S[5]<<16|S[6]<<8|S[7],S[0]<<24|S[1]<<16|S[2]<<8|S[3],_)}}),GC=Xt(()=>{}),HC=Xt(()=>{}),jC=Xt((e,t)=>{(function(a,n,r){function s(u){var p=this,c=l();p.next=function(){var d=2091639*p.s0+p.c*23283064365386963e-26;return p.s0=p.s1,p.s1=p.s2,p.s2=d-(p.c=d|0)},p.c=1,p.s0=c(" "),p.s1=c(" "),p.s2=c(" "),p.s0-=c(u),p.s0<0&&(p.s0+=1),p.s1-=c(u),p.s1<0&&(p.s1+=1),p.s2-=c(u),p.s2<0&&(p.s2+=1),c=null}function i(u,p){return p.c=u.c,p.s0=u.s0,p.s1=u.s1,p.s2=u.s2,p}function o(u,p){var c=new s(u),d=p&&p.state,h=c.next;return h.int32=function(){return c.next()*4294967296|0},h.double=function(){return h()+(h()*2097152|0)*11102230246251565e-32},h.quick=h,d&&(typeof d=="object"&&i(d,c),h.state=function(){return i(c,{})}),h}function l(){var u=4022871197,p=function(c){c=String(c);for(var d=0;d<c.length;d++){u+=c.charCodeAt(d);var h=.02519603282416938*u;u=h>>>0,h-=u,h*=u,u=h>>>0,h-=u,u+=h*4294967296}return(u>>>0)*23283064365386963e-26};return p}n&&n.exports?n.exports=o:r&&r.amd?r(function(){return o}):this.alea=o})(e,typeof t=="object"&&t,typeof define=="function"&&define)}),qC=Xt((e,t)=>{(function(a,n,r){function s(l){var u=this,p="";u.x=0,u.y=0,u.z=0,u.w=0,u.next=function(){var d=u.x^u.x<<11;return u.x=u.y,u.y=u.z,u.z=u.w,u.w^=u.w>>>19^d^d>>>8},l===(l|0)?u.x=l:p+=l;for(var c=0;c<p.length+64;c++)u.x^=p.charCodeAt(c)|0,u.next()}function i(l,u){return u.x=l.x,u.y=l.y,u.z=l.z,u.w=l.w,u}function o(l,u){var p=new s(l),c=u&&u.state,d=function(){return(p.next()>>>0)/4294967296};return d.double=function(){do var h=p.next()>>>11,m=(p.next()>>>0)/4294967296,f=(h+m)/(1<<21);while(f===0);return f},d.int32=p.next,d.quick=d,c&&(typeof c=="object"&&i(c,p),d.state=function(){return i(p,{})}),d}n&&n.exports?n.exports=o:r&&r.amd?r(function(){return o}):this.xor128=o})(e,typeof t=="object"&&t,typeof define=="function"&&define)}),XC=Xt((e,t)=>{(function(a,n,r){function s(l){var u=this,p="";u.next=function(){var d=u.x^u.x>>>2;return u.x=u.y,u.y=u.z,u.z=u.w,u.w=u.v,(u.d=u.d+362437|0)+(u.v=u.v^u.v<<4^(d^d<<1))|0},u.x=0,u.y=0,u.z=0,u.w=0,u.v=0,l===(l|0)?u.x=l:p+=l;for(var c=0;c<p.length+64;c++)u.x^=p.charCodeAt(c)|0,c==p.length&&(u.d=u.x<<10^u.x>>>4),u.next()}function i(l,u){return u.x=l.x,u.y=l.y,u.z=l.z,u.w=l.w,u.v=l.v,u.d=l.d,u}function o(l,u){var p=new s(l),c=u&&u.state,d=function(){return(p.next()>>>0)/4294967296};return d.double=function(){do var h=p.next()>>>11,m=(p.next()>>>0)/4294967296,f=(h+m)/(1<<21);while(f===0);return f},d.int32=p.next,d.quick=d,c&&(typeof c=="object"&&i(c,p),d.state=function(){return i(p,{})}),d}n&&n.exports?n.exports=o:r&&r.amd?r(function(){return o}):this.xorwow=o})(e,typeof t=="object"&&t,typeof define=="function"&&define)}),KC=Xt((e,t)=>{(function(a,n,r){function s(l){var u=this;u.next=function(){var c=u.x,d=u.i,h,m,f;return h=c[d],h^=h>>>7,m=h^h<<24,h=c[d+1&7],m^=h^h>>>10,h=c[d+3&7],m^=h^h>>>3,h=c[d+4&7],m^=h^h<<7,h=c[d+7&7],h=h^h<<13,m^=h^h<<9,c[d]=m,u.i=d+1&7,m};function p(c,d){var h,m,f=[];if(d===(d|0))m=f[0]=d;else for(d=""+d,h=0;h<d.length;++h)f[h&7]=f[h&7]<<15^d.charCodeAt(h)+f[h+1&7]<<13;for(;f.length<8;)f.push(0);for(h=0;h<8&&f[h]===0;++h);for(h==8?m=f[7]=-1:m=f[h],c.x=f,c.i=0,h=256;h>0;--h)c.next()}p(u,l)}function i(l,u){return u.x=l.x.slice(),u.i=l.i,u}function o(l,u){l==null&&(l=+new Date);var p=new s(l),c=u&&u.state,d=function(){return(p.next()>>>0)/4294967296};return d.double=function(){do var h=p.next()>>>11,m=(p.next()>>>0)/4294967296,f=(h+m)/(1<<21);while(f===0);return f},d.int32=p.next,d.quick=d,c&&(c.x&&i(c,p),d.state=function(){return i(p,{})}),d}n&&n.exports?n.exports=o:r&&r.amd?r(function(){return o}):this.xorshift7=o})(e,typeof t=="object"&&t,typeof define=="function"&&define)}),YC=Xt((e,t)=>{(function(a,n,r){function s(l){var u=this;u.next=function(){var c=u.w,d=u.X,h=u.i,m,f;return u.w=c=c+1640531527|0,f=d[h+34&127],m=d[h=h+1&127],f^=f<<13,m^=m<<17,f^=f>>>15,m^=m>>>12,f=d[h]=f^m,u.i=h,f+(c^c>>>16)|0};function p(c,d){var h,m,f,g,y,x=[],A=128;for(d===(d|0)?(m=d,d=null):(d=d+"\0",m=0,A=Math.max(A,d.length)),f=0,g=-32;g<A;++g)d&&(m^=d.charCodeAt((g+32)%d.length)),g===0&&(y=m),m^=m<<10,m^=m>>>15,m^=m<<4,m^=m>>>13,g>=0&&(y=y+1640531527|0,h=x[g&127]^=m+y,f=h==0?f+1:0);for(f>=128&&(x[(d&&d.length||0)&127]=-1),f=127,g=4*128;g>0;--g)m=x[f+34&127],h=x[f=f+1&127],m^=m<<13,h^=h<<17,m^=m>>>15,h^=h>>>12,x[f]=m^h;c.w=y,c.X=x,c.i=f}p(u,l)}function i(l,u){return u.i=l.i,u.w=l.w,u.X=l.X.slice(),u}function o(l,u){l==null&&(l=+new Date);var p=new s(l),c=u&&u.state,d=function(){return(p.next()>>>0)/4294967296};return d.double=function(){do var h=p.next()>>>11,m=(p.next()>>>0)/4294967296,f=(h+m)/(1<<21);while(f===0);return f},d.int32=p.next,d.quick=d,c&&(c.X&&i(c,p),d.state=function(){return i(p,{})}),d}n&&n.exports?n.exports=o:r&&r.amd?r(function(){return o}):this.xor4096=o})(e,typeof t=="object"&&t,typeof define=="function"&&define)}),ZC=Xt((e,t)=>{(function(a,n,r){function s(l){var u=this,p="";u.next=function(){var d=u.b,h=u.c,m=u.d,f=u.a;return d=d<<25^d>>>7^h,h=h-m|0,m=m<<24^m>>>8^f,f=f-d|0,u.b=d=d<<20^d>>>12^h,u.c=h=h-m|0,u.d=m<<16^h>>>16^f,u.a=f-d|0},u.a=0,u.b=0,u.c=-1640531527,u.d=1367130551,l===Math.floor(l)?(u.a=l/4294967296|0,u.b=l|0):p+=l;for(var c=0;c<p.length+20;c++)u.b^=p.charCodeAt(c)|0,u.next()}function i(l,u){return u.a=l.a,u.b=l.b,u.c=l.c,u.d=l.d,u}function o(l,u){var p=new s(l),c=u&&u.state,d=function(){return(p.next()>>>0)/4294967296};return d.double=function(){do var h=p.next()>>>11,m=(p.next()>>>0)/4294967296,f=(h+m)/(1<<21);while(f===0);return f},d.int32=p.next,d.quick=d,c&&(typeof c=="object"&&i(c,p),d.state=function(){return i(p,{})}),d}n&&n.exports?n.exports=o:r&&r.amd?r(function(){return o}):this.tychei=o})(e,typeof t=="object"&&t,typeof define=="function"&&define)}),JC=Xt(()=>{}),QC=Xt((e,t)=>{(function(a,n,r){var s=256,i=6,o=52,l="random",u=r.pow(s,i),p=r.pow(2,o),c=p*2,d=s-1,h;function m(w,I,T){var N=[];I=I==!0?{entropy:!0}:I||{};var M=x(y(I.entropy?[w,b(n)]:w==null?A():w,3),N),$=new f(N),E=function(){for(var S=$.g(i),_=u,O=0;S<p;)S=(S+O)*s,_*=s,O=$.g(1);for(;S>=c;)S/=2,_/=2,O>>>=1;return(S+O)/_};return E.int32=function(){return $.g(4)|0},E.quick=function(){return $.g(4)/4294967296},E.double=E,x(b($.S),n),(I.pass||T||function(S,_,O,W){return W&&(W.S&&g(W,$),S.state=function(){return g($,{})}),O?(r[l]=S,_):S})(E,M,"global"in I?I.global:this==r,I.state)}function f(w){var I,T=w.length,N=this,M=0,$=N.i=N.j=0,E=N.S=[];for(T||(w=[T++]);M<s;)E[M]=M++;for(M=0;M<s;M++)E[M]=E[$=d&$+w[M%T]+(I=E[M])],E[$]=I;(N.g=function(S){for(var _,O=0,W=N.i,P=N.j,U=N.S;S--;)_=U[W=d&W+1],O=O*s+U[d&(U[W]=U[P=d&P+_])+(U[P]=_)];return N.i=W,N.j=P,O})(s)}function g(w,I){return I.i=w.i,I.j=w.j,I.S=w.S.slice(),I}function y(w,I){var T=[],N=typeof w,M;if(I&&N=="object")for(M in w)try{T.push(y(w[M],I-1))}catch($){}return T.length?T:N=="string"?w:w+"\0"}function x(w,I){for(var T=w+"",N,M=0;M<T.length;)I[d&M]=d&(N^=I[d&M]*19)+T.charCodeAt(M++);return b(I)}function A(){try{var w;return h&&(w=h.randomBytes)?w=w(s):(w=new Uint8Array(s),(a.crypto||a.msCrypto).getRandomValues(w)),b(w)}catch(N){var I=a.navigator,T=I&&I.plugins;return[+new Date,a,T,a.screen,b(n)]}}function b(w){return String.fromCharCode.apply(0,w)}if(x(r.random(),n),typeof t=="object"&&t.exports){t.exports=m;try{h=JC()}catch(w){}}else typeof define=="function"&&define.amd?define(function(){return m}):r["seed"+l]=m})(typeof self!="undefined"?self:e,[],Math)}),mA=Xt((e,t)=>{var a=jC(),n=qC(),r=XC(),s=KC(),i=YC(),o=ZC(),l=QC();l.alea=a,l.xor128=n,l.xorwow=r,l.xorshift7=s,l.xor4096=i,l.tychei=o,t.exports=l}),fA=Xt(()=>{}),gA=Xt(()=>{}),eT=Xt(()=>{}),tT=Xt(()=>{}),aT=Xt(()=>{}),nT=Xt((e,t)=>{var a=(()=>{var n=typeof document!="undefined"&&document.currentScript?document.currentScript.src:void 0;return typeof __filename!="undefined"&&(n=n||__filename),function(r){r=r||{};function s(){return ie.buffer!=He&&ht(ie.buffer),xt}function i(){return ie.buffer!=He&&ht(ie.buffer),Ha}function o(){return ie.buffer!=He&&ht(ie.buffer),zt}function l(){return ie.buffer!=He&&ht(ie.buffer),ua}function u(){return ie.buffer!=He&&ht(ie.buffer),_a}function p(){return ie.buffer!=He&&ht(ie.buffer),dn}function c(){return ie.buffer!=He&&ht(ie.buffer),Fa}var d=typeof r!="undefined"?r:{},h,m;d.ready=new Promise(function(D,j){h=D,m=j});var f;typeof process!="undefined"&&process.listeners&&(f={uncaughtException:process.listeners("uncaughtException"),unhandledRejection:process.listeners("unhandledRejection")});var g=Object.assign({},d),y=[],x="./this.program",A=(D,j)=>{throw j},b=typeof window=="object",w=typeof importScripts=="function",I=typeof process=="object"&&typeof process.versions=="object"&&typeof process.versions.node=="string",T=d.ENVIRONMENT_IS_PTHREAD||!1,N="";function M(D){return d.locateFile?d.locateFile(D,N):N+D}var $,E,S,_;function O(D){D instanceof Fs||H("exiting due to exception: "+D)}if(I){var W=fA(),P=gA();w?N=P.dirname(N)+"/":N=__dirname+"/",$=(j,oe)=>(j=Rl(j)?new URL(j):P.normalize(j),W.readFileSync(j,oe?void 0:"utf8")),S=j=>{var oe=$(j,!0);return oe.buffer||(oe=new Uint8Array(oe)),oe},E=(j,oe,Me)=>{j=Rl(j)?new URL(j):P.normalize(j),W.readFile(j,function(je,Be){je?Me(je):oe(Be.buffer)})},process.argv.length>1&&(x=process.argv[1].replace(/\\/g,"/")),y=process.argv.slice(2),process.on("uncaughtException",function(j){if(!(j instanceof Fs))throw j}),process.on("unhandledRejection",function(j){throw j}),A=(j,oe)=>{if(In())throw process.exitCode=j,oe;O(oe),process.exit(j)},d.inspect=function(){return"[Emscripten Module object]"};let D;try{D=eT()}catch(j){throw console.error('The "worker_threads" module is not supported in this node.js build - perhaps a newer version is needed?'),j}global.Worker=D.Worker}else(b||w)&&(w?N=self.location.href:typeof document!="undefined"&&document.currentScript&&(N=document.currentScript.src),typeof n!="undefined"&&n&&(N=n),N.indexOf("blob:")!==0?N=N.substr(0,N.replace(/[?#].*/,"").lastIndexOf("/")+1):N="",I||($=D=>{var j=new XMLHttpRequest;return j.open("GET",D,!1),j.send(null),j.responseText},w&&(S=D=>{var j=new XMLHttpRequest;return j.open("GET",D,!1),j.responseType="arraybuffer",j.send(null),new Uint8Array(j.response)}),E=(D,j,oe)=>{var Me=new XMLHttpRequest;Me.open("GET",D,!0),Me.responseType="arraybuffer",Me.onload=()=>{if(Me.status==200||Me.status==0&&Me.response){j(Me.response);return}oe()},Me.onerror=oe,Me.send(null)}),_=D=>document.title=D);I&&typeof performance=="undefined"&&(global.performance=tT().performance);var U=console.log.bind(console),G=console.warn.bind(console);I&&(U=D=>W.writeSync(1,D+`
`),G=D=>W.writeSync(2,D+`
`));var q=d.print||U,H=d.printErr||G;Object.assign(d,g),g=null,d.arguments&&(y=d.arguments),d.thisProgram&&(x=d.thisProgram),d.quit&&(A=d.quit);var V=4,Z=Atomics.load,X=Atomics.store,re=Atomics.compareExchange,ee;d.wasmBinary&&(ee=d.wasmBinary);var ge=d.noExitRuntime||!0;typeof WebAssembly!="object"&&_s("no native wasm support detected");var ie,be,Ce=!1,Re;function Le(D,j){D||_s(j)}var qe=typeof TextDecoder!="undefined"?new TextDecoder("utf8"):void 0;function gt(D,j,oe){j>>>=0;for(var Me=j+oe,je=j;D[je]&&!(je>=Me);)++je;if(je-j>16&&D.buffer&&qe)return qe.decode(D.buffer instanceof SharedArrayBuffer?D.slice(j,je):D.subarray(j,je));for(var Be="";j<je;){var ye=D[j++];if(!(ye&128)){Be+=String.fromCharCode(ye);continue}var Ne=D[j++]&63;if((ye&224)==192){Be+=String.fromCharCode((ye&31)<<6|Ne);continue}var Tt=D[j++]&63;if((ye&240)==224?ye=(ye&15)<<12|Ne<<6|Tt:ye=(ye&7)<<18|Ne<<12|Tt<<6|D[j++]&63,ye<65536)Be+=String.fromCharCode(ye);else{var cn=ye-65536;Be+=String.fromCharCode(55296|cn>>10,56320|cn&1023)}}return Be}function dt(D,j){return D>>>=0,D?gt(i(),D,j):""}function st(D,j,oe,Me){if(oe>>>=0,!(Me>0))return 0;for(var je=oe,Be=oe+Me-1,ye=0;ye<D.length;++ye){var Ne=D.charCodeAt(ye);if(Ne>=55296&&Ne<=57343){var Tt=D.charCodeAt(++ye);Ne=65536+((Ne&1023)<<10)|Tt&1023}if(Ne<=127){if(oe>=Be)break;j[oe++>>>0]=Ne}else if(Ne<=2047){if(oe+1>=Be)break;j[oe++>>>0]=192|Ne>>6,j[oe++>>>0]=128|Ne&63}else if(Ne<=65535){if(oe+2>=Be)break;j[oe++>>>0]=224|Ne>>12,j[oe++>>>0]=128|Ne>>6&63,j[oe++>>>0]=128|Ne&63}else{if(oe+3>=Be)break;j[oe++>>>0]=240|Ne>>18,j[oe++>>>0]=128|Ne>>12&63,j[oe++>>>0]=128|Ne>>6&63,j[oe++>>>0]=128|Ne&63}}return j[oe>>>0]=0,oe-je}function it(D,j,oe){return st(D,i(),j,oe)}var He,xt,Ha,zt,un,ua,_a,dn,Fa;T&&(He=d.buffer);function ht(D){He=D,d.HEAP8=xt=new Int8Array(D),d.HEAP16=zt=new Int16Array(D),d.HEAP32=ua=new Int32Array(D),d.HEAPU8=Ha=new Uint8Array(D),d.HEAPU16=un=new Uint16Array(D),d.HEAPU32=_a=new Uint32Array(D),d.HEAPF32=dn=new Float32Array(D),d.HEAPF64=Fa=new Float64Array(D)}var Da=d.INITIAL_MEMORY||16777216;if(T)ie=d.wasmMemory,He=d.buffer;else if(d.wasmMemory)ie=d.wasmMemory;else if(ie=new WebAssembly.Memory({initial:Da/65536,maximum:65536,shared:!0}),!(ie.buffer instanceof SharedArrayBuffer))throw H("requested a shared WebAssembly.Memory but the returned buffer is not a SharedArrayBuffer, indicating that while the browser has SharedArrayBuffer it does not have WebAssembly threads support - you may need to set a flag"),I&&H("(on node you may need: --experimental-wasm-threads --experimental-wasm-bulk-memory and/or recent version)"),Error("bad memory");ie&&(He=ie.buffer),Da=He.byteLength,ht(He);var ja,fr=[],Tl=[],Xn=[],fd=!1;function In(){return ge}function Or(){if(d.preRun)for(typeof d.preRun=="function"&&(d.preRun=[d.preRun]);d.preRun.length;)pm(d.preRun.shift());yd(fr)}function Zt(){fd=!0,!T&&yd(Tl)}function xc(){if(!T){if(d.postRun)for(typeof d.postRun=="function"&&(d.postRun=[d.postRun]);d.postRun.length;)$x(d.postRun.shift());yd(Xn)}}function pm(D){fr.unshift(D)}function cm(D){Tl.unshift(D)}function $x(D){Xn.unshift(D)}var zr=0,Nl=null,gr=null;function hm(D){zr++,d.monitorRunDependencies&&d.monitorRunDependencies(zr)}function Ac(D){if(zr--,d.monitorRunDependencies&&d.monitorRunDependencies(zr),zr==0&&(Nl!==null&&(clearInterval(Nl),Nl=null),gr)){var j=gr;gr=null,j()}}function _s(D){d.onAbort&&d.onAbort(D),D="Aborted("+D+")",H(D),Ce=!0,Re=1,D+=". Build with -sASSERTIONS for more info.";var j=new WebAssembly.RuntimeError(D);throw m(j),j}var mm="data:application/octet-stream;base64,";function bc(D){return D.startsWith(mm)}function Rl(D){return D.startsWith("file://")}var fa;fa="tfjs-backend-wasm-threaded-simd.wasm",bc(fa)||(fa=M(fa));function vc(D){try{if(D==fa&&ee)return new Uint8Array(ee);if(S)return S(D);throw"both async and sync fetching of the wasm failed"}catch(j){_s(j)}}function fm(){if(!ee&&(b||w)){if(typeof fetch=="function"&&!Rl(fa))return fetch(fa,{credentials:"same-origin"}).then(function(D){if(!D.ok)throw"failed to load wasm binary file at '"+fa+"'";return D.arrayBuffer()}).catch(function(){return vc(fa)});if(E)return new Promise(function(D,j){E(fa,function(oe){D(new Uint8Array(oe))},j)})}return Promise.resolve().then(function(){return vc(fa)})}function gm(){var D={env:_c,wasi_snapshot_preview1:_c};function j(ye,Ne){var Tt=ye.exports;if(d.asm=Tt,Sm(d.asm._emscripten_tls_init),ja=d.asm.__indirect_function_table,cm(d.asm.__wasm_call_ctors),be=Ne,!T){var cn=We.unusedWorkers.length;We.unusedWorkers.forEach(function(xr){We.loadWasmModuleToWorker(xr,function(){--cn||Ac("wasm-instantiate")})})}}T||hm("wasm-instantiate");function oe(ye){j(ye.instance,ye.module)}function Me(ye){return fm().then(function(Ne){return WebAssembly.instantiate(Ne,D)}).then(function(Ne){return Ne}).then(ye,function(Ne){H("failed to asynchronously prepare wasm: "+Ne),_s(Ne)})}function je(){return!ee&&typeof WebAssembly.instantiateStreaming=="function"&&!bc(fa)&&!Rl(fa)&&!I&&typeof fetch=="function"?fetch(fa,{credentials:"same-origin"}).then(function(ye){var Ne=WebAssembly.instantiateStreaming(ye,D);return Ne.then(oe,function(Tt){return H("wasm streaming compile failed: "+Tt),H("falling back to ArrayBuffer instantiation"),Me(oe)})}):Me(oe)}if(d.instantiateWasm)try{var Be=d.instantiateWasm(D,j);return Be}catch(ye){H("Module.instantiateWasm callback failed with error: "+ye),m(ye)}return je().catch(m),{}}var Px,_x,wc={};function Fs(D){this.name="ExitStatus",this.message="Program terminated with exit("+D+")",this.status=D}function ym(D){var j=We.pthreads[D];delete We.pthreads[D],j.terminate(),V2(D),We.runningWorkers.splice(We.runningWorkers.indexOf(j),1),j.pthread_ptr=0}function xm(D){var j=We.pthreads[D];j.postMessage({cmd:"cancel"})}function gd(D){var j=We.pthreads[D];Le(j),We.returnWorkerToPool(j)}function Am(D){var j=We.getNewWorker();if(!j)return 6;We.runningWorkers.push(j),We.pthreads[D.pthread_ptr]=j,j.pthread_ptr=D.pthread_ptr;var oe={cmd:"run",start_routine:D.startRoutine,arg:D.arg,pthread_ptr:D.pthread_ptr};return j.runPthread=()=>{I&&j.ref(),j.postMessage(oe,D.transferList),delete j.runPthread},j.loaded&&j.runPthread(),0}var kc={varargs:void 0,get:function(){kc.varargs+=4;var D=l()[kc.varargs-4>>>2];return D},getStr:function(D){var j=dt(D);return j}};function Ic(D){if(T)return Lr(1,1,D);Re=D,In()||(We.terminateAllThreads(),d.onExit&&d.onExit(D),Ce=!0),A(D,new Fs(D))}function bm(D,j){if(Re=D,!j&&T)throw Cc(D),"unwind";Ic(D)}var Sc=bm;function vm(D){if(D instanceof Fs||D=="unwind")return Re;A(1,D)}var We={unusedWorkers:[],runningWorkers:[],tlsInitFunctions:[],pthreads:{},init:function(){T?We.initWorker():We.initMainThread()},initMainThread:function(){for(var D=8;D--;)We.allocateUnusedWorker()},initWorker:function(){ge=!1},setExitStatus:function(D){Re=D},terminateAllThreads:function(){for(var D of Object.values(We.pthreads))We.returnWorkerToPool(D);for(var D of We.unusedWorkers)D.terminate();We.unusedWorkers=[]},returnWorkerToPool:function(D){var j=D.pthread_ptr;delete We.pthreads[j],We.unusedWorkers.push(D),We.runningWorkers.splice(We.runningWorkers.indexOf(D),1),D.pthread_ptr=0,I&&D.unref(),V2(j)},receiveObjectTransfer:function(D){},threadInitTLS:function(){We.tlsInitFunctions.forEach(D=>D())},loadWasmModuleToWorker:function(D,j){D.onmessage=Be=>{var ye=Be.data,Ne=ye.cmd;if(D.pthread_ptr&&(We.currentProxiedOperationCallerThread=D.pthread_ptr),ye.targetThread&&ye.targetThread!=Wc()){var Tt=We.pthreads[ye.targetThread];Tt?Tt.postMessage(ye,ye.transferList):H('Internal error! Worker sent a message "'+Ne+'" to target pthread '+ye.targetThread+", but that thread no longer exists!"),We.currentProxiedOperationCallerThread=void 0;return}Ne==="processProxyingQueue"?xd(ye.queue):Ne==="spawnThread"?Am(ye):Ne==="cleanupThread"?gd(ye.thread):Ne==="killThread"?ym(ye.thread):Ne==="cancelThread"?xm(ye.thread):Ne==="loaded"?(D.loaded=!0,I&&D.unref(),j&&j(D),D.runPthread&&D.runPthread()):Ne==="print"?q("Thread "+ye.threadId+": "+ye.text):Ne==="printErr"?H("Thread "+ye.threadId+": "+ye.text):Ne==="alert"?alert("Thread "+ye.threadId+": "+ye.text):ye.target==="setimmediate"?D.postMessage(ye):Ne==="callHandler"?d[ye.handler](...ye.args):Ne&&H("worker sent an unknown command "+Ne),We.currentProxiedOperationCallerThread=void 0},D.onerror=Be=>{var ye="worker sent an error!";throw H(ye+" "+Be.filename+":"+Be.lineno+": "+Be.message),Be},I&&(D.on("message",function(Be){D.onmessage({data:Be})}),D.on("error",function(Be){D.onerror(Be)}),D.on("detachedExit",function(){}));var oe=[],Me=["onExit","onAbort","print","printErr"];for(var je of Me)d.hasOwnProperty(je)&&oe.push(je);D.postMessage({cmd:"load",handlers:oe,urlOrBlob:d.mainScriptUrlOrBlob||n,wasmMemory:ie,wasmModule:be})},allocateUnusedWorker:function(){var D,j=M("tfjs-backend-wasm-threaded-simd.worker.js");D=new Worker(j),We.unusedWorkers.push(D)},getNewWorker:function(){return We.unusedWorkers.length==0&&(We.allocateUnusedWorker(),We.loadWasmModuleToWorker(We.unusedWorkers[0])),We.unusedWorkers.pop()}};d.PThread=We;function yd(D){for(;D.length>0;)D.shift()(d)}function wm(){var D=Wc(),j=l()[D+52>>>2],oe=l()[D+56>>>2],Me=j-oe;Wx(j,Me),Bc(j)}d.establishStackSpace=wm;function Cc(D){if(T)return Lr(2,0,D);try{Sc(D)}catch(j){vm(j)}}var El=[];function km(D){var j=El[D];return j||(D>=El.length&&(El.length=D+1),El[D]=j=ja.get(D)),j}function Im(D,j){var oe=km(D)(j);In()?We.setExitStatus(oe):Lx(oe)}d.invokeEntryPoint=Im;function Sm(D){We.tlsInitFunctions.push(D)}function Cm(D){Dx(D,!w,1,!b),We.threadInitTLS()}function Tm(D){T?postMessage({cmd:"cleanupThread",thread:D}):gd(D)}function Tc(D,j,oe,Me){return T?Lr(3,1,D,j,oe,Me):Nc(D,j,oe,Me)}function Nc(D,j,oe,Me){if(typeof SharedArrayBuffer=="undefined")return H("Current environment does not support SharedArrayBuffer, pthreads are not available!"),6;var je=[],Be=0;if(T&&(je.length===0||Be))return Tc(D,j,oe,Me);if(Be)return Be;var ye={startRoutine:oe,pthread_ptr:D,arg:Me,transferList:je};return T?(ye.cmd="spawnThread",postMessage(ye,je),0):Am(ye)}function Nm(){return 65536}var Rm=!0;function Em(){return Rm}function xd(D){Atomics.store(l(),D>>2,1),Wc()&&zx(D),Atomics.compareExchange(l(),D>>2,1,0)}d.executeNotifiedProxyingQueue=xd;function Mm(D,j,oe,Me){if(D==j)setTimeout(()=>xd(Me));else if(T)postMessage({targetThread:D,cmd:"processProxyingQueue",queue:Me});else{var je=We.pthreads[D];if(!je)return;je.postMessage({cmd:"processProxyingQueue",queue:Me})}return 1}function $m(D,j,oe){return-1}function Pm(){_s("")}function Ds(D){Ds.shown||(Ds.shown={}),Ds.shown[D]||(Ds.shown[D]=1,I&&(D="warning: "+D),H(D))}function _m(){I||w||Ds("Blocking on the main thread is very dangerous, see https://emscripten.org/docs/porting/pthreads.html#blocking-on-the-main-browser-thread")}function Fm(){return Date.now()}function Rc(){return 4294901760}function Dm(){return Rc()}var Ad;I?Ad=()=>{var D=process.hrtime();return D[0]*1e3+D[1]/1e6}:Ad=()=>performance.timeOrigin+performance.now();function Om(D,j,oe){i().copyWithin(D>>>0,j>>>0,j+oe>>>0)}function zm(){return I?aT().cpus().length:navigator.hardwareConcurrency}function Lm(D){var j=U2(),oe=D();return Bc(j),oe}function Lr(D,j){var oe=arguments.length-2,Me=arguments;return Lm(()=>{for(var je=oe,Be=Vc(je*8),ye=Be>>3,Ne=0;Ne<oe;Ne++){var Tt=Me[2+Ne];c()[ye+Ne>>>0]=Tt}return Ox(D,je,Be,j)})}var bd=[];function Wm(D,j,oe){bd.length=j;for(var Me=oe>>3,je=0;je<j;je++)bd[je]=c()[Me+je>>>0];var Be=D<0,ye=Be?wc[-D-1]:Km[D];return ye.apply(null,bd)}function Bm(D){try{return ie.grow(D-He.byteLength+65535>>>16),ht(ie.buffer),1}catch(j){}}function Vm(D){var j=i().length;if(D=D>>>0,D<=j)return!1;var oe=Rc();if(D>oe)return!1;let Me=(Tt,cn)=>Tt+(cn-Tt%cn)%cn;for(var je=1;je<=4;je*=2){var Be=j*(1+.2/je);Be=Math.min(Be,D+100663296);var ye=Math.min(oe,Me(Math.max(D,Be),65536)),Ne=Bm(ye);if(Ne)return!0}return!1}function Um(){throw"unwind"}function Ec(D){return T?Lr(4,1,D):52}function Mc(D,j,oe,Me,je){return T?Lr(5,1,D,j,oe,Me,je):70}var Gm=[null,[],[]];function Hm(D,j){var oe=Gm[D];j===0||j===10?((D===1?q:H)(gt(oe,0)),oe.length=0):oe.push(j)}function $c(D,j,oe,Me){if(T)return Lr(6,1,D,j,oe,Me);for(var je=0,Be=0;Be<oe;Be++){var ye=u()[j>>>2],Ne=u()[j+4>>>2];j+=8;for(var Tt=0;Tt<Ne;Tt++)Hm(D,i()[ye+Tt>>>0]);je+=Ne}return u()[Me>>>2]=je,0}function Pc(D){var j=d["_"+D];return j}function jm(D,j){s().set(D,j>>>0)}function qm(D,j,oe,Me,je){var Be={string:hn=>{var _l=0;if(hn!=null&&hn!==0){var Ux=(hn.length<<2)+1;_l=Vc(Ux),it(hn,_l,Ux)}return _l},array:hn=>{var _l=Vc(hn.length);return jm(hn,_l),_l}};function ye(hn){return j==="string"?dt(hn):j==="boolean"?!!hn:hn}var Ne=Pc(D),Tt=[],cn=0;if(Me)for(var xr=0;xr<Me.length;xr++){var Vx=Be[oe[xr]];Vx?(cn===0&&(cn=U2()),Tt[xr]=Vx(Me[xr])):Tt[xr]=Me[xr]}var G2=Ne.apply(null,Tt);function EC(hn){return cn!==0&&Bc(cn),ye(hn)}return G2=EC(G2),G2}function Xm(D,j,oe,Me){oe=oe||[];var je=oe.every(ye=>ye==="number"||ye==="boolean"),Be=j!=="string";return Be&&je&&!Me?Pc(D):function(){return qm(D,j,oe,arguments,Me)}}We.init();var Km=[null,Ic,Cc,Tc,Ec,Mc,$c],_c={__emscripten_init_main_thread_js:Cm,__emscripten_thread_cleanup:Tm,__pthread_create_js:Nc,_emscripten_default_pthread_stack_size:Nm,_emscripten_get_now_is_monotonic:Em,_emscripten_notify_task_queue:Mm,_emscripten_set_offscreencanvas_size:$m,abort:Pm,emscripten_check_blocking_allowed:_m,emscripten_date_now:Fm,emscripten_get_heap_max:Dm,emscripten_get_now:Ad,emscripten_memcpy_big:Om,emscripten_num_logical_cores:zm,emscripten_receive_on_main_thread_js:Wm,emscripten_resize_heap:Vm,emscripten_unwind_to_js_event_loop:Um,exit:Sc,fd_close:Ec,fd_seek:Mc,fd_write:$c,memory:ie||d.wasmMemory},Fx=gm(),Ym=d.___wasm_call_ctors=function(){return(Ym=d.___wasm_call_ctors=d.asm.__wasm_call_ctors).apply(null,arguments)},Zm=d._init=function(){return(Zm=d._init=d.asm.init).apply(null,arguments)},Jm=d._init_with_threads_count=function(){return(Jm=d._init_with_threads_count=d.asm.init_with_threads_count).apply(null,arguments)},Qm=d._get_threads_count=function(){return(Qm=d._get_threads_count=d.asm.get_threads_count).apply(null,arguments)},ef=d._register_tensor=function(){return(ef=d._register_tensor=d.asm.register_tensor).apply(null,arguments)},tf=d._dispose_data=function(){return(tf=d._dispose_data=d.asm.dispose_data).apply(null,arguments)},af=d._dispose=function(){return(af=d._dispose=d.asm.dispose).apply(null,arguments)},nf=d._Abs=function(){return(nf=d._Abs=d.asm.Abs).apply(null,arguments)},rf=d._Acos=function(){return(rf=d._Acos=d.asm.Acos).apply(null,arguments)},sf=d._Acosh=function(){return(sf=d._Acosh=d.asm.Acosh).apply(null,arguments)},of=d._Add=function(){return(of=d._Add=d.asm.Add).apply(null,arguments)},lf=d._AddN=function(){return(lf=d._AddN=d.asm.AddN).apply(null,arguments)},uf=d._All=function(){return(uf=d._All=d.asm.All).apply(null,arguments)},df=d._Any=function(){return(df=d._Any=d.asm.Any).apply(null,arguments)},pf=d._ArgMax=function(){return(pf=d._ArgMax=d.asm.ArgMax).apply(null,arguments)},cf=d._ArgMin=function(){return(cf=d._ArgMin=d.asm.ArgMin).apply(null,arguments)},hf=d._Asin=function(){return(hf=d._Asin=d.asm.Asin).apply(null,arguments)},mf=d._Asinh=function(){return(mf=d._Asinh=d.asm.Asinh).apply(null,arguments)},ff=d._Atan=function(){return(ff=d._Atan=d.asm.Atan).apply(null,arguments)},gf=d._Atan2=function(){return(gf=d._Atan2=d.asm.Atan2).apply(null,arguments)},yf=d._Atanh=function(){return(yf=d._Atanh=d.asm.Atanh).apply(null,arguments)},xf=d._AvgPool=function(){return(xf=d._AvgPool=d.asm.AvgPool).apply(null,arguments)},Af=d._AvgPool3D=function(){return(Af=d._AvgPool3D=d.asm.AvgPool3D).apply(null,arguments)},bf=d._AvgPool3DGrad=function(){return(bf=d._AvgPool3DGrad=d.asm.AvgPool3DGrad).apply(null,arguments)},vf=d._AvgPoolGrad=function(){return(vf=d._AvgPoolGrad=d.asm.AvgPoolGrad).apply(null,arguments)},wf=d._BatchMatMul=function(){return(wf=d._BatchMatMul=d.asm.BatchMatMul).apply(null,arguments)},kf=d._Bincount=function(){return(kf=d._Bincount=d.asm.Bincount).apply(null,arguments)},If=d._BitwiseAnd=function(){return(If=d._BitwiseAnd=d.asm.BitwiseAnd).apply(null,arguments)},Sf=d._Ceil=function(){return(Sf=d._Ceil=d.asm.Ceil).apply(null,arguments)},Cf=d._ClipByValue=function(){return(Cf=d._ClipByValue=d.asm.ClipByValue).apply(null,arguments)},Tf=d._Conv2D=function(){return(Tf=d._Conv2D=d.asm.Conv2D).apply(null,arguments)},Nf=d._Conv2DBackpropInput=function(){return(Nf=d._Conv2DBackpropInput=d.asm.Conv2DBackpropInput).apply(null,arguments)},Rf=d._Conv3D=function(){return(Rf=d._Conv3D=d.asm.Conv3D).apply(null,arguments)},Ef=d._Conv3DBackpropFilterV2=function(){return(Ef=d._Conv3DBackpropFilterV2=d.asm.Conv3DBackpropFilterV2).apply(null,arguments)},Mf=d._Conv3DBackpropInputV2=function(){return(Mf=d._Conv3DBackpropInputV2=d.asm.Conv3DBackpropInputV2).apply(null,arguments)},$f=d._Cos=function(){return($f=d._Cos=d.asm.Cos).apply(null,arguments)},Pf=d._Cosh=function(){return(Pf=d._Cosh=d.asm.Cosh).apply(null,arguments)},_f=d._CropAndResize=function(){return(_f=d._CropAndResize=d.asm.CropAndResize).apply(null,arguments)},Ff=d._Cumprod=function(){return(Ff=d._Cumprod=d.asm.Cumprod).apply(null,arguments)},Df=d._Cumsum=function(){return(Df=d._Cumsum=d.asm.Cumsum).apply(null,arguments)},Of=d._DenseBincount=function(){return(Of=d._DenseBincount=d.asm.DenseBincount).apply(null,arguments)},zf=d._DepthToSpace=function(){return(zf=d._DepthToSpace=d.asm.DepthToSpace).apply(null,arguments)},Lf=d._DepthwiseConv2dNative=function(){return(Lf=d._DepthwiseConv2dNative=d.asm.DepthwiseConv2dNative).apply(null,arguments)},Wf=d._Diag=function(){return(Wf=d._Diag=d.asm.Diag).apply(null,arguments)},Bf=d._Dilation2D=function(){return(Bf=d._Dilation2D=d.asm.Dilation2D).apply(null,arguments)},Vf=d._Dilation2DBackpropFilter=function(){return(Vf=d._Dilation2DBackpropFilter=d.asm.Dilation2DBackpropFilter).apply(null,arguments)},Uf=d._Dilation2DBackpropInput=function(){return(Uf=d._Dilation2DBackpropInput=d.asm.Dilation2DBackpropInput).apply(null,arguments)},Gf=d._Elu=function(){return(Gf=d._Elu=d.asm.Elu).apply(null,arguments)},Hf=d._EluGrad=function(){return(Hf=d._EluGrad=d.asm.EluGrad).apply(null,arguments)},jf=d._Equal=function(){return(jf=d._Equal=d.asm.Equal).apply(null,arguments)},qf=d._Erf=function(){return(qf=d._Erf=d.asm.Erf).apply(null,arguments)},Xf=d._Exp=function(){return(Xf=d._Exp=d.asm.Exp).apply(null,arguments)},Kf=d._Expm1=function(){return(Kf=d._Expm1=d.asm.Expm1).apply(null,arguments)},Yf=d._FlipLeftRight=function(){return(Yf=d._FlipLeftRight=d.asm.FlipLeftRight).apply(null,arguments)},Zf=d._Floor=function(){return(Zf=d._Floor=d.asm.Floor).apply(null,arguments)},Jf=d._FloorDiv=function(){return(Jf=d._FloorDiv=d.asm.FloorDiv).apply(null,arguments)},Qf=d._FusedBatchNorm=function(){return(Qf=d._FusedBatchNorm=d.asm.FusedBatchNorm).apply(null,arguments)},e2=d._FusedConv2D=function(){return(e2=d._FusedConv2D=d.asm.FusedConv2D).apply(null,arguments)},t2=d._FusedDepthwiseConv2D=function(){return(t2=d._FusedDepthwiseConv2D=d.asm.FusedDepthwiseConv2D).apply(null,arguments)},a2=d._Gather=function(){return(a2=d._Gather=d.asm.Gather).apply(null,arguments)},n2=d._GatherNd=function(){return(n2=d._GatherNd=d.asm.GatherNd).apply(null,arguments)},r2=d._Greater=function(){return(r2=d._Greater=d.asm.Greater).apply(null,arguments)},s2=d._GreaterEqual=function(){return(s2=d._GreaterEqual=d.asm.GreaterEqual).apply(null,arguments)},i2=d._IsFinite=function(){return(i2=d._IsFinite=d.asm.IsFinite).apply(null,arguments)},o2=d._IsInf=function(){return(o2=d._IsInf=d.asm.IsInf).apply(null,arguments)},l2=d._IsNan=function(){return(l2=d._IsNan=d.asm.IsNan).apply(null,arguments)},u2=d._LRN=function(){return(u2=d._LRN=d.asm.LRN).apply(null,arguments)},d2=d._LRNGrad=function(){return(d2=d._LRNGrad=d.asm.LRNGrad).apply(null,arguments)},p2=d._LeakyRelu=function(){return(p2=d._LeakyRelu=d.asm.LeakyRelu).apply(null,arguments)},c2=d._Less=function(){return(c2=d._Less=d.asm.Less).apply(null,arguments)},h2=d._LessEqual=function(){return(h2=d._LessEqual=d.asm.LessEqual).apply(null,arguments)},m2=d._LinSpace=function(){return(m2=d._LinSpace=d.asm.LinSpace).apply(null,arguments)},f2=d._Log=function(){return(f2=d._Log=d.asm.Log).apply(null,arguments)},g2=d._Log1p=function(){return(g2=d._Log1p=d.asm.Log1p).apply(null,arguments)},y2=d._LogicalAnd=function(){return(y2=d._LogicalAnd=d.asm.LogicalAnd).apply(null,arguments)},x2=d._LogicalNot=function(){return(x2=d._LogicalNot=d.asm.LogicalNot).apply(null,arguments)},A2=d._LogicalOr=function(){return(A2=d._LogicalOr=d.asm.LogicalOr).apply(null,arguments)},b2=d._LogicalXor=function(){return(b2=d._LogicalXor=d.asm.LogicalXor).apply(null,arguments)},v2=d._Max=function(){return(v2=d._Max=d.asm.Max).apply(null,arguments)},w2=d._MaxPool=function(){return(w2=d._MaxPool=d.asm.MaxPool).apply(null,arguments)},k2=d._MaxPool3D=function(){return(k2=d._MaxPool3D=d.asm.MaxPool3D).apply(null,arguments)},I2=d._MaxPool3DGrad=function(){return(I2=d._MaxPool3DGrad=d.asm.MaxPool3DGrad).apply(null,arguments)},S2=d._MaxPoolGrad=function(){return(S2=d._MaxPoolGrad=d.asm.MaxPoolGrad).apply(null,arguments)},C2=d._MaxPoolWithArgmax=function(){return(C2=d._MaxPoolWithArgmax=d.asm.MaxPoolWithArgmax).apply(null,arguments)},T2=d._Maximum=function(){return(T2=d._Maximum=d.asm.Maximum).apply(null,arguments)},N2=d._Mean=function(){return(N2=d._Mean=d.asm.Mean).apply(null,arguments)},R2=d._Min=function(){return(R2=d._Min=d.asm.Min).apply(null,arguments)},E2=d._Minimum=function(){return(E2=d._Minimum=d.asm.Minimum).apply(null,arguments)},M2=d._MirrorPad=function(){return(M2=d._MirrorPad=d.asm.MirrorPad).apply(null,arguments)},$2=d._Mod=function(){return($2=d._Mod=d.asm.Mod).apply(null,arguments)},P2=d._Multinomial=function(){return(P2=d._Multinomial=d.asm.Multinomial).apply(null,arguments)},_2=d._Multiply=function(){return(_2=d._Multiply=d.asm.Multiply).apply(null,arguments)},F2=d._Neg=function(){return(F2=d._Neg=d.asm.Neg).apply(null,arguments)},D2=d._NonMaxSuppressionV3=function(){return(D2=d._NonMaxSuppressionV3=d.asm.NonMaxSuppressionV3).apply(null,arguments)},O2=d._NonMaxSuppressionV4=function(){return(O2=d._NonMaxSuppressionV4=d.asm.NonMaxSuppressionV4).apply(null,arguments)},Fc=d._NonMaxSuppressionV5=function(){return(Fc=d._NonMaxSuppressionV5=d.asm.NonMaxSuppressionV5).apply(null,arguments)},Dc=d._NotEqual=function(){return(Dc=d._NotEqual=d.asm.NotEqual).apply(null,arguments)},vd=d._OneHot=function(){return(vd=d._OneHot=d.asm.OneHot).apply(null,arguments)},z2=d._PadV2=function(){return(z2=d._PadV2=d.asm.PadV2).apply(null,arguments)},L2=d._Pow=function(){return(L2=d._Pow=d.asm.Pow).apply(null,arguments)},Ml=d._Prelu=function(){return(Ml=d._Prelu=d.asm.Prelu).apply(null,arguments)},Oc=d._Prod=function(){return(Oc=d._Prod=d.asm.Prod).apply(null,arguments)},$l=d._RealDiv=function(){return($l=d._RealDiv=d.asm.RealDiv).apply(null,arguments)},Pl=d._Reciprocal=function(){return(Pl=d._Reciprocal=d.asm.Reciprocal).apply(null,arguments)},W2=d._Relu=function(){return(W2=d._Relu=d.asm.Relu).apply(null,arguments)},Y=d._Relu6=function(){return(Y=d._Relu6=d.asm.Relu6).apply(null,arguments)},se=d._ResizeBilinear=function(){return(se=d._ResizeBilinear=d.asm.ResizeBilinear).apply(null,arguments)},Ee=d._ResizeBilinearGrad=function(){return(Ee=d._ResizeBilinearGrad=d.asm.ResizeBilinearGrad).apply(null,arguments)},et=d._ResizeNearestNeighbor=function(){return(et=d._ResizeNearestNeighbor=d.asm.ResizeNearestNeighbor).apply(null,arguments)},wt=d._ResizeNearestNeighborGrad=function(){return(wt=d._ResizeNearestNeighborGrad=d.asm.ResizeNearestNeighborGrad).apply(null,arguments)},kt=d._Reverse=function(){return(kt=d._Reverse=d.asm.Reverse).apply(null,arguments)},Je=d._RotateWithOffset=function(){return(Je=d._RotateWithOffset=d.asm.RotateWithOffset).apply(null,arguments)},Ye=d._Round=function(){return(Ye=d._Round=d.asm.Round).apply(null,arguments)},Lt=d._Rsqrt=function(){return(Lt=d._Rsqrt=d.asm.Rsqrt).apply(null,arguments)},pn=d._ScatterNd=function(){return(pn=d._ScatterNd=d.asm.ScatterNd).apply(null,arguments)},yr=d._SearchSorted=function(){return(yr=d._SearchSorted=d.asm.SearchSorted).apply(null,arguments)},zc=d._SelectV2=function(){return(zc=d._SelectV2=d.asm.SelectV2).apply(null,arguments)},wd=d._Selu=function(){return(wd=d._Selu=d.asm.Selu).apply(null,arguments)},B2=d._Sigmoid=function(){return(B2=d._Sigmoid=d.asm.Sigmoid).apply(null,arguments)},Oa=d._Sign=function(){return(Oa=d._Sign=d.asm.Sign).apply(null,arguments)},Wr=d._Sin=function(){return(Wr=d._Sin=d.asm.Sin).apply(null,arguments)},Lc=d._Sinh=function(){return(Lc=d._Sinh=d.asm.Sinh).apply(null,arguments)},JS=d._Softmax=function(){return(JS=d._Softmax=d.asm.Softmax).apply(null,arguments)},QS=d._Softplus=function(){return(QS=d._Softplus=d.asm.Softplus).apply(null,arguments)},eC=d._SparseFillEmptyRows=function(){return(eC=d._SparseFillEmptyRows=d.asm.SparseFillEmptyRows).apply(null,arguments)},tC=d._SparseReshape=function(){return(tC=d._SparseReshape=d.asm.SparseReshape).apply(null,arguments)},aC=d._SparseSegmentReduction=function(){return(aC=d._SparseSegmentReduction=d.asm.SparseSegmentReduction).apply(null,arguments)},nC=d._SparseToDense=function(){return(nC=d._SparseToDense=d.asm.SparseToDense).apply(null,arguments)},rC=d._Sqrt=function(){return(rC=d._Sqrt=d.asm.Sqrt).apply(null,arguments)},sC=d._Square=function(){return(sC=d._Square=d.asm.Square).apply(null,arguments)},iC=d._SquaredDifference=function(){return(iC=d._SquaredDifference=d.asm.SquaredDifference).apply(null,arguments)},oC=d._Step=function(){return(oC=d._Step=d.asm.Step).apply(null,arguments)},lC=d._StridedSlice=function(){return(lC=d._StridedSlice=d.asm.StridedSlice).apply(null,arguments)},uC=d._Sub=function(){return(uC=d._Sub=d.asm.Sub).apply(null,arguments)},dC=d._Sum=function(){return(dC=d._Sum=d.asm.Sum).apply(null,arguments)},pC=d._Tan=function(){return(pC=d._Tan=d.asm.Tan).apply(null,arguments)},cC=d._Tanh=function(){return(cC=d._Tanh=d.asm.Tanh).apply(null,arguments)},hC=d._TensorScatterUpdate=function(){return(hC=d._TensorScatterUpdate=d.asm.TensorScatterUpdate).apply(null,arguments)},mC=d._Tile=function(){return(mC=d._Tile=d.asm.Tile).apply(null,arguments)},fC=d._TopK=function(){return(fC=d._TopK=d.asm.TopK).apply(null,arguments)},gC=d._Transform=function(){return(gC=d._Transform=d.asm.Transform).apply(null,arguments)},yC=d._Transpose=function(){return(yC=d._Transpose=d.asm.Transpose).apply(null,arguments)},xC=d.__FusedMatMul=function(){return(xC=d.__FusedMatMul=d.asm._FusedMatMul).apply(null,arguments)},AC=d._malloc=function(){return(AC=d._malloc=d.asm.malloc).apply(null,arguments)},bC=d._free=function(){return(bC=d._free=d.asm.free).apply(null,arguments)},vC=d.__emscripten_tls_init=function(){return(vC=d.__emscripten_tls_init=d.asm._emscripten_tls_init).apply(null,arguments)},Wc=d._pthread_self=function(){return(Wc=d._pthread_self=d.asm.pthread_self).apply(null,arguments)},wC=d.___errno_location=function(){return(wC=d.___errno_location=d.asm.__errno_location).apply(null,arguments)},Dx=d.__emscripten_thread_init=function(){return(Dx=d.__emscripten_thread_init=d.asm._emscripten_thread_init).apply(null,arguments)},kC=d.__emscripten_thread_crashed=function(){return(kC=d.__emscripten_thread_crashed=d.asm._emscripten_thread_crashed).apply(null,arguments)},IC=d._emscripten_main_thread_process_queued_calls=function(){return(IC=d._emscripten_main_thread_process_queued_calls=d.asm.emscripten_main_thread_process_queued_calls).apply(null,arguments)},SC=d._emscripten_main_browser_thread_id=function(){return(SC=d._emscripten_main_browser_thread_id=d.asm.emscripten_main_browser_thread_id).apply(null,arguments)},Ox=d._emscripten_run_in_main_runtime_thread_js=function(){return(Ox=d._emscripten_run_in_main_runtime_thread_js=d.asm.emscripten_run_in_main_runtime_thread_js).apply(null,arguments)},CC=d._emscripten_dispatch_to_thread_=function(){return(CC=d._emscripten_dispatch_to_thread_=d.asm.emscripten_dispatch_to_thread_).apply(null,arguments)},zx=d.__emscripten_proxy_execute_task_queue=function(){return(zx=d.__emscripten_proxy_execute_task_queue=d.asm._emscripten_proxy_execute_task_queue).apply(null,arguments)},V2=d.__emscripten_thread_free_data=function(){return(V2=d.__emscripten_thread_free_data=d.asm._emscripten_thread_free_data).apply(null,arguments)},Lx=d.__emscripten_thread_exit=function(){return(Lx=d.__emscripten_thread_exit=d.asm._emscripten_thread_exit).apply(null,arguments)},Wx=d._emscripten_stack_set_limits=function(){return(Wx=d._emscripten_stack_set_limits=d.asm.emscripten_stack_set_limits).apply(null,arguments)},U2=d.stackSave=function(){return(U2=d.stackSave=d.asm.stackSave).apply(null,arguments)},Bc=d.stackRestore=function(){return(Bc=d.stackRestore=d.asm.stackRestore).apply(null,arguments)},Vc=d.stackAlloc=function(){return(Vc=d.stackAlloc=d.asm.stackAlloc).apply(null,arguments)},TC=d.dynCall_iijjiiii=function(){return(TC=d.dynCall_iijjiiii=d.asm.dynCall_iijjiiii).apply(null,arguments)},NC=d.dynCall_jiji=function(){return(NC=d.dynCall_jiji=d.asm.dynCall_jiji).apply(null,arguments)};d.keepRuntimeAlive=In,d.wasmMemory=ie,d.cwrap=Xm,d.ExitStatus=Fs,d.PThread=We;var Uc;gr=function D(){Uc||Bx(),Uc||(gr=D)};function Bx(D){if(D=D||y,zr>0)return;if(T){h(d),Zt(),startWorker(d);return}if(Or(),zr>0)return;function j(){Uc||(Uc=!0,d.calledRun=!0,!Ce&&(Zt(),h(d),d.onRuntimeInitialized&&d.onRuntimeInitialized(),xc()))}d.setStatus?(d.setStatus("Running..."),setTimeout(function(){setTimeout(function(){d.setStatus("")},1),j()},1)):j()}if(d.preInit)for(typeof d.preInit=="function"&&(d.preInit=[d.preInit]);d.preInit.length>0;)d.preInit.pop()();Bx();var Gc;f&&(Gc={uncaughtException:process.listeners("uncaughtException").filter(function(D){return!f.uncaughtException.indexOf(D)>-1}),unhandledRejection:process.listeners("unhandledRejection").filter(function(D){return!f.unhandledRejection.indexOf(D)>-1})});var Hc;if(typeof WasmBackendModule!="undefined")Hc=WasmBackendModule;else if(typeof r!="undefined")Hc=r;else throw new Error("Could not find wasm module in post.js");if(Gc){var RC=Hc._dispose;Hc._dispose=function(){RC(),Gc.uncaughtException.forEach(function(D){process.removeListener("uncaughtException",D)}),Gc.unhandledRejection.forEach(function(D){process.removeListener("unhandledRejection",D)})}}return r.ready}})();typeof e=="object"&&typeof t=="object"?t.exports=a:typeof define=="function"&&define.amd?define([],function(){return a}):typeof e=="object"&&(e.WasmBackendModuleThreadedSimd=a)}),rT=Xt((e,t)=>{t.exports.wasmWorkerContents=`"use strict";var Module={};var ENVIRONMENT_IS_NODE=typeof process=="object"&&typeof process.versions=="object"&&typeof process.versions.node=="string";if(ENVIRONMENT_IS_NODE){var nodeWorkerThreads=require("worker_threads");var parentPort=nodeWorkerThreads.parentPort;parentPort.on("message",data=>onmessage({data:data}));var fs=require("fs");Object.assign(global,{self:global,require:require,Module:Module,location:{href:__filename},Worker:nodeWorkerThreads.Worker,importScripts:function(f){(0,eval)(fs.readFileSync(f,"utf8")+"//# sourceURL="+f)},postMessage:function(msg){parentPort.postMessage(msg)},performance:global.performance||{now:function(){return Date.now()}}})}var initializedJS=false;var pendingNotifiedProxyingQueues=[];function threadPrintErr(){var text=Array.prototype.slice.call(arguments).join(" ");if(ENVIRONMENT_IS_NODE){fs.writeSync(2,text+"
");return}console.error(text)}function threadAlert(){var text=Array.prototype.slice.call(arguments).join(" ");postMessage({cmd:"alert",text:text,threadId:Module["_pthread_self"]()})}var err=threadPrintErr;self.alert=threadAlert;Module["instantiateWasm"]=(info,receiveInstance)=>{var instance=new WebAssembly.Instance(Module["wasmModule"],info);receiveInstance(instance);Module["wasmModule"]=null;return instance.exports};self.onunhandledrejection=e=>{throw e.reason??e};self.startWorker=instance=>{Module=instance;postMessage({"cmd":"loaded"})};self.onmessage=e=>{try{if(e.data.cmd==="load"){Module["wasmModule"]=e.data.wasmModule;for(const handler of e.data.handlers){Module[handler]=function(){postMessage({cmd:"callHandler",handler:handler,args:[...arguments]})}}Module["wasmMemory"]=e.data.wasmMemory;Module["buffer"]=Module["wasmMemory"].buffer;Module["ENVIRONMENT_IS_PTHREAD"]=true;if(typeof e.data.urlOrBlob=="string"){importScripts(e.data.urlOrBlob)}else{var objectUrl=URL.createObjectURL(e.data.urlOrBlob);importScripts(objectUrl);URL.revokeObjectURL(objectUrl)}WasmBackendModuleThreadedSimd(Module)}else if(e.data.cmd==="run"){Module["__emscripten_thread_init"](e.data.pthread_ptr,0,0,1);Module["establishStackSpace"]();Module["PThread"].receiveObjectTransfer(e.data);Module["PThread"].threadInitTLS();if(!initializedJS){pendingNotifiedProxyingQueues.forEach(queue=>{Module["executeNotifiedProxyingQueue"](queue)});pendingNotifiedProxyingQueues=[];initializedJS=true}try{Module["invokeEntryPoint"](e.data.start_routine,e.data.arg)}catch(ex){if(ex!="unwind"){if(ex instanceof Module["ExitStatus"]){if(Module["keepRuntimeAlive"]()){}else{Module["__emscripten_thread_exit"](ex.status)}}else{throw ex}}}}else if(e.data.cmd==="cancel"){if(Module["_pthread_self"]()){Module["__emscripten_thread_exit"](-1)}}else if(e.data.target==="setimmediate"){}else if(e.data.cmd==="processProxyingQueue"){if(initializedJS){Module["executeNotifiedProxyingQueue"](e.data.queue)}else{pendingNotifiedProxyingQueues.push(e.data.queue)}}else if(e.data.cmd){err("worker.js received unknown command "+e.data.cmd);err(e.data)}}catch(ex){if(Module["__emscripten_thread_crashed"]){Module["__emscripten_thread_crashed"]()}throw ex}};`}),sT=Xt((e,t)=>{var a=(()=>{var n=typeof document!="undefined"&&document.currentScript?document.currentScript.src:void 0;return typeof __filename!="undefined"&&(n=n||__filename),function(r){r=r||{};var s=typeof r!="undefined"?r:{},i,o;s.ready=new Promise(function(Y,se){i=Y,o=se});var l;typeof process!="undefined"&&process.listeners&&(l={uncaughtException:process.listeners("uncaughtException"),unhandledRejection:process.listeners("unhandledRejection")});var u=Object.assign({},s),p=[],c="./this.program",d=(Y,se)=>{throw se},h=typeof window=="object",m=typeof importScripts=="function",f=typeof process=="object"&&typeof process.versions=="object"&&typeof process.versions.node=="string",g="";function y(Y){return s.locateFile?s.locateFile(Y,g):g+Y}var x,A,b,w;function I(Y){Y instanceof Nl||$("exiting due to exception: "+Y)}if(f){var T=fA(),N=gA();m?g=N.dirname(g)+"/":g=__dirname+"/",x=(Y,se)=>(Y=Or(Y)?new URL(Y):N.normalize(Y),T.readFileSync(Y,se?void 0:"utf8")),b=Y=>{var se=x(Y,!0);return se.buffer||(se=new Uint8Array(se)),se},A=(Y,se,Ee)=>{Y=Or(Y)?new URL(Y):N.normalize(Y),T.readFile(Y,function(et,wt){et?Ee(et):se(wt.buffer)})},process.argv.length>1&&(c=process.argv[1].replace(/\\/g,"/")),p=process.argv.slice(2),process.on("uncaughtException",function(Y){if(!(Y instanceof Nl))throw Y}),process.on("unhandledRejection",function(Y){throw Y}),d=(Y,se)=>{if(Ha())throw process.exitCode=Y,se;I(se),process.exit(Y)},s.inspect=function(){return"[Emscripten Module object]"}}else(h||m)&&(m?g=self.location.href:typeof document!="undefined"&&document.currentScript&&(g=document.currentScript.src),n&&(g=n),g.indexOf("blob:")!==0?g=g.substr(0,g.replace(/[?#].*/,"").lastIndexOf("/")+1):g="",x=Y=>{var se=new XMLHttpRequest;return se.open("GET",Y,!1),se.send(null),se.responseText},m&&(b=Y=>{var se=new XMLHttpRequest;return se.open("GET",Y,!1),se.responseType="arraybuffer",se.send(null),new Uint8Array(se.response)}),A=(Y,se,Ee)=>{var et=new XMLHttpRequest;et.open("GET",Y,!0),et.responseType="arraybuffer",et.onload=()=>{if(et.status==200||et.status==0&&et.response){se(et.response);return}Ee()},et.onerror=Ee,et.send(null)},w=Y=>document.title=Y);var M=s.print||console.log.bind(console),$=s.printErr||console.warn.bind(console);Object.assign(s,u),u=null,s.arguments&&(p=s.arguments),s.thisProgram&&(c=s.thisProgram),s.quit&&(d=s.quit);var E=4,S;s.wasmBinary&&(S=s.wasmBinary);var _=s.noExitRuntime||!0;typeof WebAssembly!="object"&&Xn("no native wasm support detected");var O,W=!1,P;function U(Y,se){Y||Xn(se)}var G=typeof TextDecoder!="undefined"?new TextDecoder("utf8"):void 0;function q(Y,se,Ee){se>>>=0;for(var et=se+Ee,wt=se;Y[wt]&&!(wt>=et);)++wt;if(wt-se>16&&Y.buffer&&G)return G.decode(Y.subarray(se,wt));for(var kt="";se<wt;){var Je=Y[se++];if(!(Je&128)){kt+=String.fromCharCode(Je);continue}var Ye=Y[se++]&63;if((Je&224)==192){kt+=String.fromCharCode((Je&31)<<6|Ye);continue}var Lt=Y[se++]&63;if((Je&240)==224?Je=(Je&15)<<12|Ye<<6|Lt:Je=(Je&7)<<18|Ye<<12|Lt<<6|Y[se++]&63,Je<65536)kt+=String.fromCharCode(Je);else{var pn=Je-65536;kt+=String.fromCharCode(55296|pn>>10,56320|pn&1023)}}return kt}function H(Y,se){return Y>>>=0,Y?q(ee,Y,se):""}function V(Y,se,Ee,et){if(Ee>>>=0,!(et>0))return 0;for(var wt=Ee,kt=Ee+et-1,Je=0;Je<Y.length;++Je){var Ye=Y.charCodeAt(Je);if(Ye>=55296&&Ye<=57343){var Lt=Y.charCodeAt(++Je);Ye=65536+((Ye&1023)<<10)|Lt&1023}if(Ye<=127){if(Ee>=kt)break;se[Ee++>>>0]=Ye}else if(Ye<=2047){if(Ee+1>=kt)break;se[Ee++>>>0]=192|Ye>>6,se[Ee++>>>0]=128|Ye&63}else if(Ye<=65535){if(Ee+2>=kt)break;se[Ee++>>>0]=224|Ye>>12,se[Ee++>>>0]=128|Ye>>6&63,se[Ee++>>>0]=128|Ye&63}else{if(Ee+3>=kt)break;se[Ee++>>>0]=240|Ye>>18,se[Ee++>>>0]=128|Ye>>12&63,se[Ee++>>>0]=128|Ye>>6&63,se[Ee++>>>0]=128|Ye&63}}return se[Ee>>>0]=0,Ee-wt}function Z(Y,se,Ee){return V(Y,ee,se,Ee)}var X,re,ee,ge,ie,be,Ce,Re,Le;function qe(Y){X=Y,s.HEAP8=re=new Int8Array(Y),s.HEAP16=ge=new Int16Array(Y),s.HEAP32=be=new Int32Array(Y),s.HEAPU8=ee=new Uint8Array(Y),s.HEAPU16=ie=new Uint16Array(Y),s.HEAPU32=Ce=new Uint32Array(Y),s.HEAPF32=Re=new Float32Array(Y),s.HEAPF64=Le=new Float64Array(Y)}var gt=s.INITIAL_MEMORY||16777216,dt,st=[],it=[],He=[],xt=!1;function Ha(){return _}function zt(){if(s.preRun)for(typeof s.preRun=="function"&&(s.preRun=[s.preRun]);s.preRun.length;)_a(s.preRun.shift());gr(st)}function un(){xt=!0,gr(it)}function ua(){if(s.postRun)for(typeof s.postRun=="function"&&(s.postRun=[s.postRun]);s.postRun.length;)Fa(s.postRun.shift());gr(He)}function _a(Y){st.unshift(Y)}function dn(Y){it.unshift(Y)}function Fa(Y){He.unshift(Y)}var ht=0,Da=null,ja=null;function fr(Y){ht++,s.monitorRunDependencies&&s.monitorRunDependencies(ht)}function Tl(Y){if(ht--,s.monitorRunDependencies&&s.monitorRunDependencies(ht),ht==0&&(Da!==null&&(clearInterval(Da),Da=null),ja)){var se=ja;ja=null,se()}}function Xn(Y){s.onAbort&&s.onAbort(Y),Y="Aborted("+Y+")",$(Y),W=!0,P=1,Y+=". Build with -sASSERTIONS for more info.";var se=new WebAssembly.RuntimeError(Y);throw o(se),se}var fd="data:application/octet-stream;base64,";function In(Y){return Y.startsWith(fd)}function Or(Y){return Y.startsWith("file://")}var Zt;Zt="tfjs-backend-wasm.wasm",In(Zt)||(Zt=y(Zt));function xc(Y){try{if(Y==Zt&&S)return new Uint8Array(S);if(b)return b(Y);throw"both async and sync fetching of the wasm failed"}catch(se){Xn(se)}}function pm(){if(!S&&(h||m)){if(typeof fetch=="function"&&!Or(Zt))return fetch(Zt,{credentials:"same-origin"}).then(function(Y){if(!Y.ok)throw"failed to load wasm binary file at '"+Zt+"'";return Y.arrayBuffer()}).catch(function(){return xc(Zt)});if(A)return new Promise(function(Y,se){A(Zt,function(Ee){Y(new Uint8Array(Ee))},se)})}return Promise.resolve().then(function(){return xc(Zt)})}function cm(){var Y={env:gd,wasi_snapshot_preview1:gd};function se(Je,Ye){var Lt=Je.exports;s.asm=Lt,O=s.asm.memory,qe(O.buffer),dt=s.asm.__indirect_function_table,dn(s.asm.__wasm_call_ctors),Tl("wasm-instantiate")}fr("wasm-instantiate");function Ee(Je){se(Je.instance)}function et(Je){return pm().then(function(Ye){return WebAssembly.instantiate(Ye,Y)}).then(function(Ye){return Ye}).then(Je,function(Ye){$("failed to asynchronously prepare wasm: "+Ye),Xn(Ye)})}function wt(){return!S&&typeof WebAssembly.instantiateStreaming=="function"&&!In(Zt)&&!Or(Zt)&&!f&&typeof fetch=="function"?fetch(Zt,{credentials:"same-origin"}).then(function(Je){var Ye=WebAssembly.instantiateStreaming(Je,Y);return Ye.then(Ee,function(Lt){return $("wasm streaming compile failed: "+Lt),$("falling back to ArrayBuffer instantiation"),et(Ee)})}):et(Ee)}if(s.instantiateWasm)try{var kt=s.instantiateWasm(Y,se);return kt}catch(Je){$("Module.instantiateWasm callback failed with error: "+Je),o(Je)}return wt().catch(o),{}}var $x,zr;function Nl(Y){this.name="ExitStatus",this.message="Program terminated with exit("+Y+")",this.status=Y}function gr(Y){for(;Y.length>0;)Y.shift()(s)}function hm(){Xn("")}function Ac(){return 4294901760}function _s(){return Ac()}function mm(Y,se,Ee){ee.copyWithin(Y>>>0,se>>>0,se+Ee>>>0)}function bc(Y){try{return O.grow(Y-X.byteLength+65535>>>16),qe(O.buffer),1}catch(se){}}function Rl(Y){var se=ee.length;Y=Y>>>0;var Ee=Ac();if(Y>Ee)return!1;let et=(Lt,pn)=>Lt+(pn-Lt%pn)%pn;for(var wt=1;wt<=4;wt*=2){var kt=se*(1+.2/wt);kt=Math.min(kt,Y+100663296);var Je=Math.min(Ee,et(Math.max(Y,kt),65536)),Ye=bc(Je);if(Ye)return!0}return!1}var fa={varargs:void 0,get:function(){fa.varargs+=4;var Y=be[fa.varargs-4>>>2];return Y},getStr:function(Y){var se=H(Y);return se}};function vc(Y){return 52}function fm(Y,se,Ee,et,wt){return 70}var gm=[null,[],[]];function Px(Y,se){var Ee=gm[Y];se===0||se===10?((Y===1?M:$)(q(Ee,0)),Ee.length=0):Ee.push(se)}function _x(Y,se,Ee,et){for(var wt=0,kt=0;kt<Ee;kt++){var Je=Ce[se>>>2],Ye=Ce[se+4>>>2];se+=8;for(var Lt=0;Lt<Ye;Lt++)Px(Y,ee[Je+Lt>>>0]);wt+=Ye}return Ce[et>>>2]=wt,0}function wc(Y){var se=s["_"+Y];return se}function Fs(Y,se){re.set(Y,se>>>0)}function ym(Y,se,Ee,et,wt){var kt={string:Oa=>{var Wr=0;if(Oa!=null&&Oa!==0){var Lc=(Oa.length<<2)+1;Wr=vd(Lc),Z(Oa,Wr,Lc)}return Wr},array:Oa=>{var Wr=vd(Oa.length);return Fs(Oa,Wr),Wr}};function Je(Oa){return se==="string"?H(Oa):se==="boolean"?!!Oa:Oa}var Ye=wc(Y),Lt=[],pn=0;if(et)for(var yr=0;yr<et.length;yr++){var zc=kt[Ee[yr]];zc?(pn===0&&(pn=Fc()),Lt[yr]=zc(et[yr])):Lt[yr]=et[yr]}var wd=Ye.apply(null,Lt);function B2(Oa){return pn!==0&&Dc(pn),Je(Oa)}return wd=B2(wd),wd}function xm(Y,se,Ee,et){Ee=Ee||[];var wt=Ee.every(Je=>Je==="number"||Je==="boolean"),kt=se!=="string";return kt&&wt&&!et?wc(Y):function(){return ym(Y,se,Ee,arguments,et)}}var gd={abort:hm,emscripten_get_heap_max:_s,emscripten_memcpy_big:mm,emscripten_resize_heap:Rl,fd_close:vc,fd_seek:fm,fd_write:_x},Am=cm(),kc=s.___wasm_call_ctors=function(){return(kc=s.___wasm_call_ctors=s.asm.__wasm_call_ctors).apply(null,arguments)},Ic=s._init=function(){return(Ic=s._init=s.asm.init).apply(null,arguments)},bm=s._init_with_threads_count=function(){return(bm=s._init_with_threads_count=s.asm.init_with_threads_count).apply(null,arguments)},Sc=s._get_threads_count=function(){return(Sc=s._get_threads_count=s.asm.get_threads_count).apply(null,arguments)},vm=s._register_tensor=function(){return(vm=s._register_tensor=s.asm.register_tensor).apply(null,arguments)},We=s._dispose_data=function(){return(We=s._dispose_data=s.asm.dispose_data).apply(null,arguments)},yd=s._dispose=function(){return(yd=s._dispose=s.asm.dispose).apply(null,arguments)},wm=s._Abs=function(){return(wm=s._Abs=s.asm.Abs).apply(null,arguments)},Cc=s._Acos=function(){return(Cc=s._Acos=s.asm.Acos).apply(null,arguments)},El=s._Acosh=function(){return(El=s._Acosh=s.asm.Acosh).apply(null,arguments)},km=s._Add=function(){return(km=s._Add=s.asm.Add).apply(null,arguments)},Im=s._AddN=function(){return(Im=s._AddN=s.asm.AddN).apply(null,arguments)},Sm=s._All=function(){return(Sm=s._All=s.asm.All).apply(null,arguments)},Cm=s._Any=function(){return(Cm=s._Any=s.asm.Any).apply(null,arguments)},Tm=s._ArgMax=function(){return(Tm=s._ArgMax=s.asm.ArgMax).apply(null,arguments)},Tc=s._ArgMin=function(){return(Tc=s._ArgMin=s.asm.ArgMin).apply(null,arguments)},Nc=s._Asin=function(){return(Nc=s._Asin=s.asm.Asin).apply(null,arguments)},Nm=s._Asinh=function(){return(Nm=s._Asinh=s.asm.Asinh).apply(null,arguments)},Rm=s._Atan=function(){return(Rm=s._Atan=s.asm.Atan).apply(null,arguments)},Em=s._Atan2=function(){return(Em=s._Atan2=s.asm.Atan2).apply(null,arguments)},xd=s._Atanh=function(){return(xd=s._Atanh=s.asm.Atanh).apply(null,arguments)},Mm=s._AvgPool=function(){return(Mm=s._AvgPool=s.asm.AvgPool).apply(null,arguments)},$m=s._AvgPool3D=function(){return($m=s._AvgPool3D=s.asm.AvgPool3D).apply(null,arguments)},Pm=s._AvgPool3DGrad=function(){return(Pm=s._AvgPool3DGrad=s.asm.AvgPool3DGrad).apply(null,arguments)},Ds=s._AvgPoolGrad=function(){return(Ds=s._AvgPoolGrad=s.asm.AvgPoolGrad).apply(null,arguments)},_m=s._BatchMatMul=function(){return(_m=s._BatchMatMul=s.asm.BatchMatMul).apply(null,arguments)},Fm=s._Bincount=function(){return(Fm=s._Bincount=s.asm.Bincount).apply(null,arguments)},Rc=s._BitwiseAnd=function(){return(Rc=s._BitwiseAnd=s.asm.BitwiseAnd).apply(null,arguments)},Dm=s._Ceil=function(){return(Dm=s._Ceil=s.asm.Ceil).apply(null,arguments)},Ad=s._ClipByValue=function(){return(Ad=s._ClipByValue=s.asm.ClipByValue).apply(null,arguments)},Om=s._Conv2D=function(){return(Om=s._Conv2D=s.asm.Conv2D).apply(null,arguments)},zm=s._Conv2DBackpropInput=function(){return(zm=s._Conv2DBackpropInput=s.asm.Conv2DBackpropInput).apply(null,arguments)},Lm=s._Conv3D=function(){return(Lm=s._Conv3D=s.asm.Conv3D).apply(null,arguments)},Lr=s._Conv3DBackpropFilterV2=function(){return(Lr=s._Conv3DBackpropFilterV2=s.asm.Conv3DBackpropFilterV2).apply(null,arguments)},bd=s._Conv3DBackpropInputV2=function(){return(bd=s._Conv3DBackpropInputV2=s.asm.Conv3DBackpropInputV2).apply(null,arguments)},Wm=s._Cos=function(){return(Wm=s._Cos=s.asm.Cos).apply(null,arguments)},Bm=s._Cosh=function(){return(Bm=s._Cosh=s.asm.Cosh).apply(null,arguments)},Vm=s._CropAndResize=function(){return(Vm=s._CropAndResize=s.asm.CropAndResize).apply(null,arguments)},Um=s._Cumprod=function(){return(Um=s._Cumprod=s.asm.Cumprod).apply(null,arguments)},Ec=s._Cumsum=function(){return(Ec=s._Cumsum=s.asm.Cumsum).apply(null,arguments)},Mc=s._DenseBincount=function(){return(Mc=s._DenseBincount=s.asm.DenseBincount).apply(null,arguments)},Gm=s._DepthToSpace=function(){return(Gm=s._DepthToSpace=s.asm.DepthToSpace).apply(null,arguments)},Hm=s._DepthwiseConv2dNative=function(){return(Hm=s._DepthwiseConv2dNative=s.asm.DepthwiseConv2dNative).apply(null,arguments)},$c=s._Diag=function(){return($c=s._Diag=s.asm.Diag).apply(null,arguments)},Pc=s._Dilation2D=function(){return(Pc=s._Dilation2D=s.asm.Dilation2D).apply(null,arguments)},jm=s._Dilation2DBackpropFilter=function(){return(jm=s._Dilation2DBackpropFilter=s.asm.Dilation2DBackpropFilter).apply(null,arguments)},qm=s._Dilation2DBackpropInput=function(){return(qm=s._Dilation2DBackpropInput=s.asm.Dilation2DBackpropInput).apply(null,arguments)},Xm=s._Elu=function(){return(Xm=s._Elu=s.asm.Elu).apply(null,arguments)},Km=s._EluGrad=function(){return(Km=s._EluGrad=s.asm.EluGrad).apply(null,arguments)},_c=s._Equal=function(){return(_c=s._Equal=s.asm.Equal).apply(null,arguments)},Fx=s._Erf=function(){return(Fx=s._Erf=s.asm.Erf).apply(null,arguments)},Ym=s._Exp=function(){return(Ym=s._Exp=s.asm.Exp).apply(null,arguments)},Zm=s._Expm1=function(){return(Zm=s._Expm1=s.asm.Expm1).apply(null,arguments)},Jm=s._FlipLeftRight=function(){return(Jm=s._FlipLeftRight=s.asm.FlipLeftRight).apply(null,arguments)},Qm=s._Floor=function(){return(Qm=s._Floor=s.asm.Floor).apply(null,arguments)},ef=s._FloorDiv=function(){return(ef=s._FloorDiv=s.asm.FloorDiv).apply(null,arguments)},tf=s._FusedBatchNorm=function(){return(tf=s._FusedBatchNorm=s.asm.FusedBatchNorm).apply(null,arguments)},af=s._FusedConv2D=function(){return(af=s._FusedConv2D=s.asm.FusedConv2D).apply(null,arguments)},nf=s._FusedDepthwiseConv2D=function(){return(nf=s._FusedDepthwiseConv2D=s.asm.FusedDepthwiseConv2D).apply(null,arguments)},rf=s._Gather=function(){return(rf=s._Gather=s.asm.Gather).apply(null,arguments)},sf=s._GatherNd=function(){return(sf=s._GatherNd=s.asm.GatherNd).apply(null,arguments)},of=s._Greater=function(){return(of=s._Greater=s.asm.Greater).apply(null,arguments)},lf=s._GreaterEqual=function(){return(lf=s._GreaterEqual=s.asm.GreaterEqual).apply(null,arguments)},uf=s._IsFinite=function(){return(uf=s._IsFinite=s.asm.IsFinite).apply(null,arguments)},df=s._IsInf=function(){return(df=s._IsInf=s.asm.IsInf).apply(null,arguments)},pf=s._IsNan=function(){return(pf=s._IsNan=s.asm.IsNan).apply(null,arguments)},cf=s._LRN=function(){return(cf=s._LRN=s.asm.LRN).apply(null,arguments)},hf=s._LRNGrad=function(){return(hf=s._LRNGrad=s.asm.LRNGrad).apply(null,arguments)},mf=s._LeakyRelu=function(){return(mf=s._LeakyRelu=s.asm.LeakyRelu).apply(null,arguments)},ff=s._Less=function(){return(ff=s._Less=s.asm.Less).apply(null,arguments)},gf=s._LessEqual=function(){return(gf=s._LessEqual=s.asm.LessEqual).apply(null,arguments)},yf=s._LinSpace=function(){return(yf=s._LinSpace=s.asm.LinSpace).apply(null,arguments)},xf=s._Log=function(){return(xf=s._Log=s.asm.Log).apply(null,arguments)},Af=s._Log1p=function(){return(Af=s._Log1p=s.asm.Log1p).apply(null,arguments)},bf=s._LogicalAnd=function(){return(bf=s._LogicalAnd=s.asm.LogicalAnd).apply(null,arguments)},vf=s._LogicalNot=function(){return(vf=s._LogicalNot=s.asm.LogicalNot).apply(null,arguments)},wf=s._LogicalOr=function(){return(wf=s._LogicalOr=s.asm.LogicalOr).apply(null,arguments)},kf=s._LogicalXor=function(){return(kf=s._LogicalXor=s.asm.LogicalXor).apply(null,arguments)},If=s._Max=function(){return(If=s._Max=s.asm.Max).apply(null,arguments)},Sf=s._MaxPool=function(){return(Sf=s._MaxPool=s.asm.MaxPool).apply(null,arguments)},Cf=s._MaxPool3D=function(){return(Cf=s._MaxPool3D=s.asm.MaxPool3D).apply(null,arguments)},Tf=s._MaxPool3DGrad=function(){return(Tf=s._MaxPool3DGrad=s.asm.MaxPool3DGrad).apply(null,arguments)},Nf=s._MaxPoolGrad=function(){return(Nf=s._MaxPoolGrad=s.asm.MaxPoolGrad).apply(null,arguments)},Rf=s._MaxPoolWithArgmax=function(){return(Rf=s._MaxPoolWithArgmax=s.asm.MaxPoolWithArgmax).apply(null,arguments)},Ef=s._Maximum=function(){return(Ef=s._Maximum=s.asm.Maximum).apply(null,arguments)},Mf=s._Mean=function(){return(Mf=s._Mean=s.asm.Mean).apply(null,arguments)},$f=s._Min=function(){return($f=s._Min=s.asm.Min).apply(null,arguments)},Pf=s._Minimum=function(){return(Pf=s._Minimum=s.asm.Minimum).apply(null,arguments)},_f=s._MirrorPad=function(){return(_f=s._MirrorPad=s.asm.MirrorPad).apply(null,arguments)},Ff=s._Mod=function(){return(Ff=s._Mod=s.asm.Mod).apply(null,arguments)},Df=s._Multinomial=function(){return(Df=s._Multinomial=s.asm.Multinomial).apply(null,arguments)},Of=s._Multiply=function(){return(Of=s._Multiply=s.asm.Multiply).apply(null,arguments)},zf=s._Neg=function(){return(zf=s._Neg=s.asm.Neg).apply(null,arguments)},Lf=s._NonMaxSuppressionV3=function(){return(Lf=s._NonMaxSuppressionV3=s.asm.NonMaxSuppressionV3).apply(null,arguments)},Wf=s._NonMaxSuppressionV4=function(){return(Wf=s._NonMaxSuppressionV4=s.asm.NonMaxSuppressionV4).apply(null,arguments)},Bf=s._NonMaxSuppressionV5=function(){return(Bf=s._NonMaxSuppressionV5=s.asm.NonMaxSuppressionV5).apply(null,arguments)},Vf=s._NotEqual=function(){return(Vf=s._NotEqual=s.asm.NotEqual).apply(null,arguments)},Uf=s._OneHot=function(){return(Uf=s._OneHot=s.asm.OneHot).apply(null,arguments)},Gf=s._PadV2=function(){return(Gf=s._PadV2=s.asm.PadV2).apply(null,arguments)},Hf=s._Pow=function(){return(Hf=s._Pow=s.asm.Pow).apply(null,arguments)},jf=s._Prelu=function(){return(jf=s._Prelu=s.asm.Prelu).apply(null,arguments)},qf=s._Prod=function(){return(qf=s._Prod=s.asm.Prod).apply(null,arguments)},Xf=s._RealDiv=function(){return(Xf=s._RealDiv=s.asm.RealDiv).apply(null,arguments)},Kf=s._Reciprocal=function(){return(Kf=s._Reciprocal=s.asm.Reciprocal).apply(null,arguments)},Yf=s._Relu=function(){return(Yf=s._Relu=s.asm.Relu).apply(null,arguments)},Zf=s._Relu6=function(){return(Zf=s._Relu6=s.asm.Relu6).apply(null,arguments)},Jf=s._ResizeBilinear=function(){return(Jf=s._ResizeBilinear=s.asm.ResizeBilinear).apply(null,arguments)},Qf=s._ResizeBilinearGrad=function(){return(Qf=s._ResizeBilinearGrad=s.asm.ResizeBilinearGrad).apply(null,arguments)},e2=s._ResizeNearestNeighbor=function(){return(e2=s._ResizeNearestNeighbor=s.asm.ResizeNearestNeighbor).apply(null,arguments)},t2=s._ResizeNearestNeighborGrad=function(){return(t2=s._ResizeNearestNeighborGrad=s.asm.ResizeNearestNeighborGrad).apply(null,arguments)},a2=s._Reverse=function(){return(a2=s._Reverse=s.asm.Reverse).apply(null,arguments)},n2=s._RotateWithOffset=function(){return(n2=s._RotateWithOffset=s.asm.RotateWithOffset).apply(null,arguments)},r2=s._Round=function(){return(r2=s._Round=s.asm.Round).apply(null,arguments)},s2=s._Rsqrt=function(){return(s2=s._Rsqrt=s.asm.Rsqrt).apply(null,arguments)},i2=s._ScatterNd=function(){return(i2=s._ScatterNd=s.asm.ScatterNd).apply(null,arguments)},o2=s._SearchSorted=function(){return(o2=s._SearchSorted=s.asm.SearchSorted).apply(null,arguments)},l2=s._SelectV2=function(){return(l2=s._SelectV2=s.asm.SelectV2).apply(null,arguments)},u2=s._Selu=function(){return(u2=s._Selu=s.asm.Selu).apply(null,arguments)},d2=s._Sigmoid=function(){return(d2=s._Sigmoid=s.asm.Sigmoid).apply(null,arguments)},p2=s._Sign=function(){return(p2=s._Sign=s.asm.Sign).apply(null,arguments)},c2=s._Sin=function(){return(c2=s._Sin=s.asm.Sin).apply(null,arguments)},h2=s._Sinh=function(){return(h2=s._Sinh=s.asm.Sinh).apply(null,arguments)},m2=s._Softmax=function(){return(m2=s._Softmax=s.asm.Softmax).apply(null,arguments)},f2=s._Softplus=function(){return(f2=s._Softplus=s.asm.Softplus).apply(null,arguments)},g2=s._SparseFillEmptyRows=function(){return(g2=s._SparseFillEmptyRows=s.asm.SparseFillEmptyRows).apply(null,arguments)},y2=s._SparseReshape=function(){return(y2=s._SparseReshape=s.asm.SparseReshape).apply(null,arguments)},x2=s._SparseSegmentReduction=function(){return(x2=s._SparseSegmentReduction=s.asm.SparseSegmentReduction).apply(null,arguments)},A2=s._SparseToDense=function(){return(A2=s._SparseToDense=s.asm.SparseToDense).apply(null,arguments)},b2=s._Sqrt=function(){return(b2=s._Sqrt=s.asm.Sqrt).apply(null,arguments)},v2=s._Square=function(){return(v2=s._Square=s.asm.Square).apply(null,arguments)},w2=s._SquaredDifference=function(){return(w2=s._SquaredDifference=s.asm.SquaredDifference).apply(null,arguments)},k2=s._Step=function(){return(k2=s._Step=s.asm.Step).apply(null,arguments)},I2=s._StridedSlice=function(){return(I2=s._StridedSlice=s.asm.StridedSlice).apply(null,arguments)},S2=s._Sub=function(){return(S2=s._Sub=s.asm.Sub).apply(null,arguments)},C2=s._Sum=function(){return(C2=s._Sum=s.asm.Sum).apply(null,arguments)},T2=s._Tan=function(){return(T2=s._Tan=s.asm.Tan).apply(null,arguments)},N2=s._Tanh=function(){return(N2=s._Tanh=s.asm.Tanh).apply(null,arguments)},R2=s._TensorScatterUpdate=function(){return(R2=s._TensorScatterUpdate=s.asm.TensorScatterUpdate).apply(null,arguments)},E2=s._Tile=function(){return(E2=s._Tile=s.asm.Tile).apply(null,arguments)},M2=s._TopK=function(){return(M2=s._TopK=s.asm.TopK).apply(null,arguments)},$2=s._Transform=function(){return($2=s._Transform=s.asm.Transform).apply(null,arguments)},P2=s._Transpose=function(){return(P2=s._Transpose=s.asm.Transpose).apply(null,arguments)},_2=s.__FusedMatMul=function(){return(_2=s.__FusedMatMul=s.asm._FusedMatMul).apply(null,arguments)},F2=s._malloc=function(){return(F2=s._malloc=s.asm.malloc).apply(null,arguments)},D2=s._free=function(){return(D2=s._free=s.asm.free).apply(null,arguments)},O2=s.___errno_location=function(){return(O2=s.___errno_location=s.asm.__errno_location).apply(null,arguments)},Fc=s.stackSave=function(){return(Fc=s.stackSave=s.asm.stackSave).apply(null,arguments)},Dc=s.stackRestore=function(){return(Dc=s.stackRestore=s.asm.stackRestore).apply(null,arguments)},vd=s.stackAlloc=function(){return(vd=s.stackAlloc=s.asm.stackAlloc).apply(null,arguments)},z2=s.dynCall_iijjiiii=function(){return(z2=s.dynCall_iijjiiii=s.asm.dynCall_iijjiiii).apply(null,arguments)},L2=s.dynCall_jiji=function(){return(L2=s.dynCall_jiji=s.asm.dynCall_jiji).apply(null,arguments)};s.cwrap=xm;var Ml;ja=function Y(){Ml||Oc(),Ml||(ja=Y)};function Oc(Y){if(Y=Y||p,ht>0||(zt(),ht>0))return;function se(){Ml||(Ml=!0,s.calledRun=!0,!W&&(un(),i(s),s.onRuntimeInitialized&&s.onRuntimeInitialized(),ua()))}s.setStatus?(s.setStatus("Running..."),setTimeout(function(){setTimeout(function(){s.setStatus("")},1),se()},1)):se()}if(s.preInit)for(typeof s.preInit=="function"&&(s.preInit=[s.preInit]);s.preInit.length>0;)s.preInit.pop()();Oc();var $l;l&&($l={uncaughtException:process.listeners("uncaughtException").filter(function(Y){return!l.uncaughtException.indexOf(Y)>-1}),unhandledRejection:process.listeners("unhandledRejection").filter(function(Y){return!l.unhandledRejection.indexOf(Y)>-1})});var Pl;if(typeof r!="undefined")Pl=r;else if(typeof WasmBackendModuleThreadedSimd!="undefined")Pl=WasmBackendModuleThreadedSimd;else throw new Error("Could not find wasm module in post.js");if($l){var W2=Pl._dispose;Pl._dispose=function(){W2(),$l.uncaughtException.forEach(function(Y){process.removeListener("uncaughtException",Y)}),$l.unhandledRejection.forEach(function(Y){process.removeListener("unhandledRejection",Y)})}}return r.ready}})();typeof e=="object"&&typeof t=="object"?t.exports=a:typeof define=="function"&&define.amd?define([],function(){return a}):typeof e=="object"&&(e.WasmBackendModule=a)}),op=class{constructor(e,t){this.backend=e,this.dataMover=t,this.data=new WeakMap,this.dataIdsCount=0}get(e){return this.data.has(e)||this.dataMover.moveData(this.backend,e),this.data.get(e)}set(e,t){this.dataIdsCount++,this.data.set(e,t)}has(e){return this.data.has(e)}delete(e){return this.dataIdsCount--,this.data.delete(e)}numDataIds(){return this.dataIdsCount}},su=class{refCount(e){return Xa("refCount")}incRef(e){return Xa("incRef")}timerAvailable(){return!0}time(e){return Xa("time")}read(e){return Xa("read")}readSync(e){return Xa("readSync")}readToGPU(e,t){return Xa("readToGPU")}numDataIds(){return Xa("numDataIds")}disposeData(e,t){return Xa("disposeData")}write(e,t,a){return Xa("write")}move(e,t,a,n,r){return Xa("move")}createTensorFromGPUData(e,t,a){return Xa("createTensorFromGPUData")}memory(){return Xa("memory")}floatPrecision(){return Xa("floatPrecision")}epsilon(){return this.floatPrecision()===32?1e-7:1e-4}dispose(){return Xa("dispose")}};function Xa(e){throw new Error(`'${e}' not yet implemented or not found in the registry. This kernel may not be supported by the tfjs backend you have chosen`)}function yA(e){let t=e.length,a=0;for(;t>0;)a=Math.random()*t|0,t--,uh(e,t,a)}function iT(e,t){if(e.length!==t.length)throw new Error(`Array sizes must match to be shuffled together First array length was ${e.length}Second array length was ${t.length}`);let a=e.length,n=0;for(;a>0;)n=Math.random()*a|0,a--,uh(e,a,n),uh(t,a,n)}function Ld(e,t,a){return Math.max(e,Math.min(t,a))}function oT(e){return e%2===0?e:e+1}function uh(e,t,a){let n=e[t];e[t]=e[a],e[a]=n}function lT(e){let t=0;for(let a=0;a<e.length;a++)t+=e[a];return t}function uT(e,t){let a=Math.random();return t*a+(1-a)*e}function dT(e,t){let a=0;for(let n=0;n<e.length;n++){let r=Number(e[n])-Number(t[n]);a+=r*r}return a}function F(e,t){if(!e)throw new Error(typeof t=="string"?t:t())}function Ta(e,t,a=""){F(Nr(e,t),()=>a+` Shapes ${e} and ${t} must match`)}function ii(e){F(e!=null,()=>"The input to the tensor constructor must be a non-null value.")}function mt(e){if(e.length===0)return 1;let t=e[0];for(let a=1;a<e.length;a++)t*=e[a];return t}function pT(e){return e.length===0}function xA(e,t){if(e===t)return!0;if(e==null||t==null||e.length!==t.length)return!1;for(let a=0;a<e.length;a++)if(e[a]!==null&&t[a]!==null&&e[a]!==t[a])return!1;return!0}function Nr(e,t){if(e===t)return!0;if(e==null||t==null||e.length!==t.length)return!1;for(let a=0;a<e.length;a++)if(e[a]!==t[a])return!1;return!0}function jl(e){return e%1===0}function cT(e){if(Math.tanh!=null)return Math.tanh(e);if(e===1/0)return 1;if(e===-1/0)return-1;{let t=Math.exp(2*e);return(t-1)/(t+1)}}function hT(e){let t=Math.ceil(Math.sqrt(e));return[t,Math.ceil(e/t)]}function mT(e){let t=new Uint32Array(e);for(let a=0;a<e;++a)t[a]=a;return yA(t),t}function Fd(e,t){return t<=e.length?e:e+" ".repeat(t-e.length)}function fT(e,t=r=>0,a,n){return new Promise((r,s)=>{let i=0,o=()=>{if(e()){r();return}i++;let l=t(i);if(a!=null&&i>=a){s();return}n!=null?n(o,l):setTimeout(o,l)};o()})}function gT(e,t){let a=1,n=-1;for(let s=0;s<e.length;++s)if(e[s]>=0)a*=e[s];else if(e[s]===-1){if(n!==-1)throw Error(`Shapes can only have 1 implicit size. Found -1 at dim ${n} and dim ${s}`);n=s}else if(e[s]<0)throw Error(`Shapes can not be < 0. Found ${e[s]} at dim ${s}`);if(n===-1){if(t>0&&t!==a)throw Error(`Size(${t}) must match the product of shape ${e}`);return e}if(a===0)throw Error(`Cannot infer the missing size in [${e}] when there are 0 elements`);if(t%a!==0)throw Error(`The implicit shape can't be a fractional number. Got ${t} / ${a}`);let r=e.slice();return r[n]=t/a,r}function lp(e,t){let a=t.length;return e=e==null?t.map((n,r)=>r):[].concat(e),F(e.every(n=>n>=-a&&n<a),()=>`All values in axis param must be in range [-${a}, ${a}) but got axis ${e}`),F(e.every(n=>jl(n)),()=>`All values in axis param must be integers but got axis ${e}`),e.map(n=>n<0?a+n:n)}function AA(e,t){let a=[],n=[],r=t!=null&&Array.isArray(t)&&t.length===0,s=t==null||r?null:lp(t,e).sort(),i=0;for(let o=0;o<e.length;++o){if(s!=null){if(s[i]===o&&e[o]!==1)throw new Error(`Can't squeeze axis ${o} since its dim '${e[o]}' is not 1`);(s[i]==null||s[i]>o)&&e[o]===1&&(a.push(e[o]),n.push(o)),s[i]<=o&&i++}e[o]!==1&&(a.push(e[o]),n.push(o))}return{newShape:a,keptDims:n}}function bA(e,t){return J1(e,t)}function J1(e,t){let a=null;if(e==null||e==="float32")a=new Float32Array(t);else if(e==="int32")a=new Int32Array(t);else if(e==="bool")a=new Uint8Array(t);else if(e==="string")a=new Array(t);else throw new Error(`Unknown data type ${e}`);return a}function vA(e,t){for(let a=0;a<e.length;a++){let n=e[a];if(isNaN(n)||!isFinite(n))throw Error(`A tensor of type ${t} being uploaded contains ${n}.`)}}function wA(e){return e==="bool"||e==="complex64"||e==="float32"||e==="int32"||e==="string"}function yT(e,t){return!(t==="complex64"||t==="float32"&&e!=="complex64"||t==="int32"&&e!=="float32"&&e!=="complex64"||t==="bool"&&e==="bool")}function dh(e){if(e==="float32"||e==="int32")return 4;if(e==="complex64")return 8;if(e==="bool")return 1;throw new Error(`Unknown dtype ${e}`)}function kA(e){if(e==null)return 0;let t=0;return e.forEach(a=>t+=a.length),t}function Gr(e){return typeof e=="string"||e instanceof String}function IA(e){return typeof e=="boolean"}function SA(e){return typeof e=="number"}function up(e){return Array.isArray(e)?up(e[0]):e instanceof Float32Array?"float32":e instanceof Int32Array||e instanceof Uint8Array||e instanceof Uint8ClampedArray?"int32":SA(e)?"float32":Gr(e)?"string":IA(e)?"bool":"float32"}function Yr(e){return!!(e&&e.constructor&&e.call&&e.apply)}function ph(e,t){for(let a=t;a<e;++a)if(e%a===0)return a;return e}function iu(e){let t=e.length;if(t<2)return[];let a=new Array(t-1);a[t-2]=e[t-1];for(let n=t-3;n>=0;--n)a[n]=a[n+1]*e[n+1];return a}function CA(e,t,a,n=!1){let r=new Array;if(t.length===1){let s=t[0]*(n?2:1);for(let i=0;i<s;i++)r[i]=a[e+i]}else{let s=t[0],i=t.slice(1),o=i.reduce((l,u)=>l*u)*(n?2:1);for(let l=0;l<s;l++)r[l]=CA(e+l*o,i,a,n)}return r}function Bl(e,t,a=!1){if(e.length===0)return t[0];let n=e.reduce((r,s)=>r*s)*(a?2:1);if(n===0)return[];if(n!==t.length)throw new Error(`[${e}] does not match the input size ${t.length}${a?" for a complex tensor":""}.`);return CA(0,e,t,a)}function xT(e,t){if(Array.isArray(e))return e;if(t==="float32")return e instanceof Float32Array?e:new Float32Array(e);if(t==="int32")return e instanceof Int32Array?e:new Int32Array(e);if(t==="bool"||t==="string")return Uint8Array.from(new Int32Array(e));throw new Error(`Unknown dtype ${t}`)}function Q1(e,t){let a=Eh(e,t);for(let n=0;n<a.length;n++)a[n]=1;return a}function Eh(e,t){if(t==null||t==="float32"||t==="complex64")return new Float32Array(e);if(t==="int32")return new Int32Array(e);if(t==="bool")return new Uint8Array(e);throw new Error(`Unknown data type ${t}`)}function AT(e,t){let a=e.reduce((n,r)=>n*r,1);if(t==null||t==="float32")return Bl(e,new Float32Array(a));if(t==="int32")return Bl(e,new Int32Array(a));if(t==="bool")return Bl(e,new Uint8Array(a));throw new Error(`Unknown data type ${t}`)}function an(e){e.forEach(t=>{F(Number.isInteger(t)&&t>=0,()=>`Tensor must have a shape comprised of positive integers but got shape [${e}].`)})}function bT(e,t,a){if(t===0)return 0;if(t===1)return e[0];let n=e[e.length-1];for(let r=0;r<e.length-1;++r)n+=a[r]*e[r];return n}function vT(e,t,a){if(t===0)return[];if(t===1)return[e];let n=new Array(t);for(let r=0;r<n.length-1;++r)n[r]=Math.floor(e/a[r]),e-=n[r]*a[r];return n[n.length-1]=e,n}function Mh(e){return e&&e.then&&typeof e.then=="function"}var jx="tfjsflags",TA=class{constructor(e){this.global=e,this.flags={},this.flagRegistry={},this.urlFlags={},this.getQueryParams=wT,this.populateURLFlags()}setPlatform(e,t){this.platform!=null&&(B().getBool("IS_TEST")||B().getBool("PROD")||console.warn(`Platform ${this.platformName} has already been set. Overwriting the platform with ${e}.`)),this.platformName=e,this.platform=t}registerFlag(e,t,a){if(this.flagRegistry[e]={evaluationFn:t,setHook:a},this.urlFlags[e]!=null){let n=this.urlFlags[e];B().getBool("IS_TEST")||B().getBool("PROD")||console.warn(`Setting feature override from URL ${e}: ${n}.`),this.set(e,n)}}async getAsync(e){return e in this.flags?this.flags[e]:(this.flags[e]=await this.evaluateFlag(e),this.flags[e])}get(e){if(e in this.flags)return this.flags[e];let t=this.evaluateFlag(e);if(Mh(t))throw new Error(`Flag ${e} cannot be synchronously evaluated. Please use getAsync() instead.`);return this.flags[e]=t,this.flags[e]}getNumber(e){return this.get(e)}getBool(e){return this.get(e)}getString(e){return this.get(e)}getFlags(){return this.flags}get features(){return this.flags}set(e,t){if(this.flagRegistry[e]==null)throw new Error(`Cannot set flag ${e} as it has not been registered.`);this.flags[e]=t,this.flagRegistry[e].setHook!=null&&this.flagRegistry[e].setHook(t)}evaluateFlag(e){if(this.flagRegistry[e]==null)throw new Error(`Cannot evaluate flag '${e}': no evaluation function found.`);return this.flagRegistry[e].evaluationFn()}setFlags(e){this.flags=Object.assign({},e)}reset(){this.flags={},this.urlFlags={},this.populateURLFlags()}populateURLFlags(){if(typeof this.global=="undefined"||typeof this.global.location=="undefined"||typeof this.global.location.search=="undefined")return;let e=this.getQueryParams(this.global.location.search);jx in e&&e[jx].split(",").forEach(t=>{let[a,n]=t.split(":");this.urlFlags[a]=IT(a,n)})}};function wT(e){let t={};return e.replace(/[?&]([^=?&]+)(?:=([^&]*))?/g,(a,...n)=>(kT(t,n[0],n[1]),n.join("="))),t}function kT(e,t,a){e[decodeURIComponent(t)]=decodeURIComponent(a||"")}function IT(e,t){let a=t.toLowerCase();return a==="true"||a==="false"?a==="true":`${+a}`===a?+a:t}function B(){return eg}var eg=null;function ST(e){eg=e}var H2;function NA(){if(H2==null){let e;if(typeof window!="undefined")e=window;else if(typeof global!="undefined")e=global;else if(typeof process!="undefined")e=process;else if(typeof self!="undefined")e=self;else throw new Error("Could not find a global object");H2=e}return H2}function CT(){let e=NA();return e._tfGlobals==null&&(e._tfGlobals=new Map),e._tfGlobals}function tg(e,t){let a=CT();if(a.has(e))return a.get(e);{let n=t();return a.set(e,n),a.get(e)}}var ou="Abs",oi="Acos",li="Acosh",ls="Add",ui="AddN",di="All",pi="Any",lu="ArgMax",uu="ArgMin",ci="Asin",hi="Asinh",mi="Atan",fi="Atanh",gi="Atan2",yi="AvgPool",dp="AvgPoolGrad",du="AvgPool3D",pp="AvgPool3DGrad",xi="BatchMatMul",pu="BatchToSpaceND",Ai="Bincount",cu="BitwiseAnd",TT="BroadcastTo",hu="BroadcastArgs",bi="Cast",vi="Ceil",us="ClipByValue",cp="Complex",hp="ComplexAbs",mu="Concat",wi="Conv2D",mp="Conv2DBackpropFilter",ki="Conv2DBackpropInput",Ii="Conv3D",fu="Conv3DBackpropFilterV2",Si="Conv3DBackpropInputV2",Ci="Cos",Ti="Cosh",Ni="Cumprod",Ri="Cumsum",Ei="CropAndResize",gu="DenseBincount",Mi="DepthToSpace",$i="DepthwiseConv2dNative",fp="DepthwiseConv2dNativeBackpropFilter",gp="DepthwiseConv2dNativeBackpropInput",yu="Diag",Pi="Dilation2D",ql="Dilation2DBackpropInput",Xl="Dilation2DBackpropFilter",yp="Draw",_i="RealDiv",xp="Einsum",Fi="Elu",xu="EluGrad",Di="Erf",Oi="Equal",zi="Exp",Au="ExpandDims",Li="Expm1",Ap="FFT",bu="Fill",Wi="FlipLeftRight",Bi="Floor",Vi="FloorDiv",Ui="FusedBatchNorm",vu="GatherV2",Gi="GatherNd",Hi="Greater",ji="GreaterEqual",qi="Identity",bp="IFFT",vp="Imag",Xi="IsFinite",Ki="IsInf",Yi="IsNan",Zi="LeakyRelu",Ji="Less",Qi="LessEqual",eo="LinSpace",to="Log",ao="Log1p",no="LogicalAnd",ro="LogicalNot",so="LogicalOr",RA="LogicalXor",NT="LogSoftmax",RT="LowerBound",io="LRN",wu="LRNGrad",ET="MatrixBandPart",oo="Max",lo="Maximum",uo="MaxPool",wp="MaxPoolGrad",ku="MaxPool3D",kp="MaxPool3DGrad",Iu="MaxPoolWithArgmax",po="Mean",co="Min",ho="Minimum",mo="MirrorPad",fo="Mod",go="Multinomial",yo="Multiply",Su="Neg",xo="NotEqual",Ao="NonMaxSuppressionV3",Cu="NonMaxSuppressionV4",bo="NonMaxSuppressionV5",Tu="OnesLike",vo="OneHot",Nu="Pack",wo="PadV2",MT="Pool",ko="Pow",Io="Prelu",So="Prod",$h="RaggedGather",Ph="RaggedRange",_h="RaggedTensorToTensor",Ru="Range",Ip="Real",Co="Reciprocal",To="Relu",Eu="Reshape",No="ResizeNearestNeighbor",Mu="ResizeNearestNeighborGrad",Ro="ResizeBilinear",$u="ResizeBilinearGrad",Eo="Relu6",Mo="Reverse",$o="Round",Po="Rsqrt",_o="ScatterNd",Fo="TensorScatterUpdate",Do="SearchSorted",Pu="Select",Oo="Selu",_u="Slice",zo="Sin",Lo="Sinh",Wo="Sign",Bo="Sigmoid",Vo="Softplus",Uo="Sqrt",Go="Sum",Fu="SpaceToBatchND",Du="SplitV",Ho="Softmax",Sp="SparseFillEmptyRows",Ou="SparseReshape",zu="SparseSegmentMean",Lu="SparseSegmentSum",jo="SparseToDense",qo="SquaredDifference",Cp="Square",Tp="StaticRegexReplace",Xo="StridedSlice",Wu="StringNGrams",Np="StringSplit",Rp="StringToHashBucketFast",Ko="Sub",Yo="Tan",Zo="Tanh",ds="Tile",Jo="TopK",Qo="Transform",Ir="Transpose",Ep="Unique",Bu="Unpack",Mp="UnsortedSegmentSum",$T="UpperBound",Vu="ZerosLike",ps="Step",Wd="FromPixels",el="RotateWithOffset",Zr="_FusedMatMul",Jr="FusedConv2D",Qr="FusedDepthwiseConv2D";function Ur(...e){B().getBool("IS_TEST")||B().getBool("PROD")||console.warn(...e)}function PT(...e){B().getBool("IS_TEST")||B().getBool("PROD")||console.log(...e)}var Kl=tg("kernelRegistry",()=>new Map),Bd=tg("gradRegistry",()=>new Map);function Vd(e,t){let a=ag(e,t);return Kl.get(a)}function t1(e){return Bd.get(e)}function er(e){let t=Kl.entries(),a=[];for(;;){let{done:n,value:r}=t.next();if(n)break;let[s,i]=r,[o]=s.split("_");o===e&&a.push(i)}return a}function xn(e){let{kernelName:t,backendName:a}=e,n=ag(t,a);Kl.has(n)&&Ur(`The kernel '${t}' for backend '${a}' is already registered`),Kl.set(n,e)}function _T(e){let{kernelName:t}=e;Bd.has(t)&&B().getBool("DEBUG")&&Ur(`Overriding the gradient for '${t}'`),Bd.set(t,e)}function FT(e,t){let a=ag(e,t);if(!Kl.has(a))throw new Error(`The kernel '${e}' for backend '${t}' is not registered`);Kl.delete(a)}function DT(e){if(!Bd.has(e))throw new Error(`The gradient '${e}' for backend is not registered`);Bd.delete(e)}function OT(e,t){er(e).forEach(a=>{let n=Object.assign({},a,{backendName:t});xn(n)})}function ag(e,t){return`${t}_${e}`}var v={};Ze(v,{arraysEqual:()=>Nr,arraysEqualWithNull:()=>xA,assert:()=>F,assertNonNegativeIntegerDimensions:()=>an,assertNonNull:()=>ii,assertShapesMatch:()=>Ta,bytesFromStringArray:()=>kA,bytesPerElement:()=>dh,checkConversionForErrors:()=>vA,clamp:()=>Ld,computeStrides:()=>iu,convertBackendValuesAndArrayBuffer:()=>xT,createScalarValue:()=>UT,createShuffledIndices:()=>mT,decodeString:()=>ch,distSquared:()=>dT,encodeString:()=>Pp,fetch:()=>HT,fingerPrint64:()=>VT,flatten:()=>es,getArrayFromDType:()=>J1,getTypedArrayFromDType:()=>bA,hasEncodingLoss:()=>yT,hexToLong:()=>$p,indexToLoc:()=>vT,inferDtype:()=>up,inferFromImplicitShape:()=>gT,isBoolean:()=>IA,isFunction:()=>Yr,isInt:()=>jl,isNumber:()=>SA,isPromise:()=>Mh,isScalarShape:()=>pT,isString:()=>Gr,isTypedArray:()=>Qt,isValidDtype:()=>wA,locToIndex:()=>bT,makeOnesTypedArray:()=>Q1,makeZerosNestedTypedArray:()=>AT,makeZerosTypedArray:()=>Eh,nearestDivisor:()=>ph,nearestLargerEven:()=>oT,now:()=>Ud,parseAxisParam:()=>lp,randUniform:()=>uT,repeatedTry:()=>fT,rightPad:()=>Fd,shuffle:()=>yA,shuffleCombo:()=>iT,sizeFromShape:()=>mt,sizeToSquarishShape:()=>hT,squeezeShape:()=>AA,sum:()=>lT,swap:()=>uh,tanh:()=>cT,toNestedArray:()=>Bl,toTypedArray:()=>Fh});function EA(e){return e instanceof Float32Array||e instanceof Int32Array||e instanceof Uint8Array||e instanceof Uint8ClampedArray}var qx=ru(UC()),Bs=qx.default||qx;function $p(e){return Bs.fromString(e,!0,16)}var MA=$p("c3a5c85c97cb3127"),Ls=$p("b492b66fbe98f273"),va=$p("9ae16a3b2f90404f");function a1(e){return e.xor(e.shru(47))}function $A(e,t,a){let n=e.slice(t,t+a);return Bs.fromBytes(Array.from(n),!0,!0)}function At(e,t){return $A(e,t,8)}function Xx(e,t){return $A(e,t,4)}function Jt(e,t){return t===0?e:e.shru(t).or(e.shl(64-t))}function Xr(e,t,a=$p("9ddfea08eb382d69")){let n=e.xor(t).mul(a);n=n.xor(n.shru(47));let r=t.xor(n).mul(a);return r=r.xor(r.shru(47)),r=r.mul(a),r}function zT(e,t,a,n,r,s){r=r.add(e),s=Jt(s.add(r).add(n),21);let i=r;return r=r.add(t),r=r.add(a),s=s.add(Jt(r,44)),[r.add(n),s.add(i)]}function qc(e,t,a,n){return zT(At(e,t),At(e,t+8),At(e,t+16),At(e,t+24),a,n)}function LT(e,t=e.length){if(t>=8){let a=va.add(t*2),n=At(e,0).add(va),r=At(e,t-8),s=Jt(r,37).mul(a).add(n),i=Jt(n,25).add(r).mul(a);return Xr(s,i,a)}if(t>=4){let a=va.add(t*2),n=Xx(e,0);return Xr(n.shl(3).add(t),Xx(e,t-4),a)}if(t>0){let a=e[0],n=e[t>>1],r=e[t-1],s=a+(n<<8),i=t+(r<<2);return a1(va.mul(s).xor(MA.mul(i))).mul(va)}return va}function WT(e,t=e.length){let a=va.add(t*2),n=At(e,0).mul(Ls),r=At(e,8),s=At(e,t-8).mul(a),i=At(e,t-16).mul(va);return Xr(Jt(n.add(r),43).add(Jt(s,30)).add(i),n.add(Jt(r.add(va),18)).add(s),a)}function BT(e,t=e.length){let a=va.add(t*2),n=At(e,0).mul(va),r=At(e,8),s=At(e,t-8).mul(a),i=At(e,t-16).mul(va),o=Jt(n.add(r),43).add(Jt(s,30)).add(i),l=Xr(o,n.add(Jt(r.add(va),18)).add(s),a),u=At(e,16).mul(a),p=At(e,24),c=o.add(At(e,t-32)).mul(a),d=l.add(At(e,t-24)).mul(a);return Xr(Jt(u.add(p),43).add(Jt(c,30)).add(d),u.add(Jt(p.add(n),18)).add(c),a)}function VT(e,t=e.length){let a=Bs.fromNumber(81,!0);if(t<=32)return t<=16?LT(e,t):WT(e,t);if(t<=64)return BT(e,t);let n=a,r=a.mul(Ls).add(113),s=a1(r.mul(va).add(113)).mul(va),i=[Bs.UZERO,Bs.UZERO],o=[Bs.UZERO,Bs.UZERO];n=n.mul(va).add(At(e,0));let l=0,u=(t-1>>6)*64,p=u+(t-1&63)-63;do n=Jt(n.add(r).add(i[0]).add(At(e,l+8)),37).mul(Ls),r=Jt(r.add(i[1]).add(At(e,l+48)),42).mul(Ls),n=n.xor(o[1]),r=r.add(i[0]).add(At(e,l+40)),s=Jt(s.add(o[0]),33).mul(Ls),i=qc(e,l,i[1].mul(Ls),n.add(o[0])),o=qc(e,l+32,s.add(o[1]),r.add(At(e,l+16))),[s,n]=[n,s],l+=64;while(l!==u);let c=Ls.add(s.and(255).shl(1));return l=p,o[0]=o[0].add(t-1&63),i[0]=i[0].add(o[0]),o[0]=o[0].add(i[0]),n=Jt(n.add(r).add(i[0]).add(At(e,l+8)),37).mul(c),r=Jt(r.add(i[1]).add(At(e,l+48)),42).mul(c),n=n.xor(o[1].mul(9)),r=r.add(i[0].mul(9).add(At(e,l+40))),s=Jt(s.add(o[0]),33).mul(c),i=qc(e,l,i[1].mul(c),n.add(o[0])),o=qc(e,l+32,s.add(o[1]),r.add(At(e,l+16))),[s,n]=[n,s],Xr(Xr(i[0],o[0],c).add(a1(r).mul(MA)).add(s),Xr(i[1],o[1],c).add(n),c)}function UT(e,t){return t==="string"?Pp(e):Fh([e],t)}function GT(e,t){return e instanceof Float32Array&&t==="float32"||e instanceof Int32Array&&t==="int32"||e instanceof Uint8Array&&t==="bool"}function Fh(e,t){if(t==="string")throw new Error("Cannot convert a string[] to a TypedArray");if(Array.isArray(e)&&(e=es(e)),B().getBool("DEBUG")&&vA(e,t),GT(e,t))return e;if(t==null||t==="float32"||t==="complex64")return new Float32Array(e);if(t==="int32")return new Int32Array(e);if(t==="bool"){let a=new Uint8Array(e.length);for(let n=0;n<a.length;++n)Math.round(e[n])!==0&&(a[n]=1);return a}else throw new Error(`Unknown data type ${t}`)}function Ud(){return B().platform.now()}function HT(e,t){return B().platform.fetch(e,t)}function Pp(e,t="utf-8"){return t=t||"utf-8",B().platform.encode(e,t)}function ch(e,t="utf-8"){return t=t||"utf-8",B().platform.decode(e,t)}function Qt(e){return B().platform.isTypedArray!=null?B().platform.isTypedArray(e):EA(e)}function es(e,t=[],a=!1){if(t==null&&(t=[]),typeof e=="boolean"||typeof e=="number"||typeof e=="string"||Mh(e)||e==null||Qt(e)&&a)t.push(e);else if(Array.isArray(e)||Qt(e))for(let n=0;n<e.length;++n)es(e[n],t,a);else{let n=-1;for(let r of Object.keys(e))/^([1-9]+[0-9]*|0)$/.test(r)&&(n=Math.max(n,Number(r)));for(let r=0;r<=n;r++)es(e[r],t,a)}return t}var jT=class{constructor(e,t){this.backendTimer=e,this.logger=t,t==null&&(this.logger=new XT)}profileKernel(e,t,a){let n,r=()=>{n=a()},s,i=Ud();if(this.backendTimer.timerAvailable())s=this.backendTimer.time(r);else{r();for(let o of n)o.dataSync();s=Promise.resolve({kernelMs:Ud()-i})}if(B().getBool("CHECK_COMPUTATION_FOR_ERRORS"))for(let o=0;o<n.length;o++){let l=n[o];l.data().then(u=>{qT(u,l.dtype,e)})}return{kernelName:e,outputs:n,inputs:t,timeMs:s.then(o=>o.kernelMs),extraInfo:s.then(o=>o.getExtraProfileInfo!=null?o.getExtraProfileInfo():"")}}logKernelProfile(e){let{kernelName:t,outputs:a,timeMs:n,inputs:r,extraInfo:s}=e;a.forEach(i=>{Promise.all([i.data(),n,s]).then(o=>{this.logger.logKernelProfile(t,i,o[0],o[1],r,o[2])})})}};function qT(e,t,a){if(t!=="float32")return!1;for(let n=0;n<e.length;n++){let r=e[n];if(isNaN(r)||!isFinite(r))return console.warn(`Found ${r} in the result of '${a}'`),!0}return!1}var XT=class{logKernelProfile(e,t,a,n,r,s){let i=typeof n=="number"?Fd(`${n}ms`,9):n.error,o=Fd(e,25),l=t.rank,u=t.size,p=Fd(t.shape.toString(),14),c="";for(let d in r){let h=r[d];if(h!=null){let m=h.shape||t.shape,f=m.length;c+=`${d}: ${f}D ${f>0?m:""} `}}console.log(`%c${o}	%c${i}	%c${l}D ${p}	%c${u}	%c${c}	%c${s}`,"font-weight:bold","color:red","color:blue","color: orange","color: green","color: steelblue")}};function KT(e,t,a){let n={},r={};for(let l=0;l<t.length;l++)n[t[l].id]=!0;for(let l=0;l<e.length;l++){let u=e[l],p=u.inputs;for(let c in p){let d=p[c],h=!1;for(let m=0;m<t.length;m++)if(n[d.id]){u.outputs.forEach(f=>n[f.id]=!0),h=!0,r[u.id]=!0;break}if(h)break}}let s={};s[a.id]=!0;let i={};for(let l=e.length-1;l>=0;l--){let u=e[l],p=u.inputs;for(let c=0;c<u.outputs.length;c++)if(s[u.outputs[c].id]){for(let d in p)s[p[d].id]=!0,i[u.id]=!0;break}}let o=[];for(let l=0;l<e.length;l++){let u=e[l];if(r[u.id]&&i[u.id]){let p={};for(let d in u.inputs){let h=u.inputs[d];n[h.id]&&(p[d]=h)}let c=Object.assign({},u);c.inputs=p,c.outputs=u.outputs,o.push(c)}}return o}function YT(e,t,a,n){for(let r=t.length-1;r>=0;r--){let s=t[r],i=[];if(s.outputs.forEach(l=>{let u=e[l.id];u!=null?i.push(u):i.push(null)}),s.gradient==null)throw new Error(`Cannot compute gradient: gradient function not found for ${s.kernelName}.`);let o=s.gradient(i);for(let l in s.inputs){if(!(l in o))throw new Error(`Cannot backprop through input ${l}. Available gradients found: ${Object.keys(o)}.`);let u=a(()=>o[l]());if(u.dtype!=="float32")throw new Error(`Error in gradient for op ${s.kernelName}. The gradient of input ${l} must have 'float32' dtype, but has '${u.dtype}'`);let p=s.inputs[l];if(!Nr(u.shape,p.shape))throw new Error(`Error in gradient for op ${s.kernelName}. The gradient of input '${l}' has shape '${u.shape}', which does not match the shape of the input '${p.shape}'`);if(e[p.id]==null)e[p.id]=u;else{let c=e[p.id];e[p.id]=n(c,u),c.dispose()}}}}var Kx=20,kd=3,j2=7;function ZT(e,t,a,n){let r=iu(t),s=JT(e,t,a,r),i=t.length,o=eh(e,t,a,r,s),l=["Tensor"];return n&&(l.push(`  dtype: ${a}`),l.push(`  rank: ${i}`),l.push(`  shape: [${t}]`),l.push("  values:")),l.push(o.map(u=>"    "+u).join(`
`)),l.join(`
`)}function JT(e,t,a,n){let r=mt(t),s=n[n.length-1],i=new Array(s).fill(0),o=t.length,l=a==="complex64"?Cd(e):e;if(o>1)for(let u=0;u<r/s;u++){let p=u*s;for(let c=0;c<s;c++)i[c]=Math.max(i[c],Sd(l[p+c],0,a).length)}return i}function Sd(e,t,a){let n;return Array.isArray(e)?n=`${parseFloat(e[0].toFixed(j2))} + ${parseFloat(e[1].toFixed(j2))}j`:Gr(e)?n=`'${e}'`:a==="bool"?n=PA(e):n=parseFloat(e.toFixed(j2)).toString(),Fd(n,t)}function PA(e){return e===0?"false":"true"}function eh(e,t,a,n,r,s=!0){let i=a==="complex64"?2:1,o=t[0],l=t.length;if(l===0){if(a==="complex64"){let f=Cd(e);return[Sd(f[0],0,a)]}return a==="bool"?[PA(e[0])]:[e[0].toString()]}if(l===1){if(o>Kx){let f=kd*i,g=Array.from(e.slice(0,f)),y=Array.from(e.slice((o-kd)*i,o*i));return a==="complex64"&&(g=Cd(g),y=Cd(y)),["["+g.map((x,A)=>Sd(x,r[A],a)).join(", ")+", ..., "+y.map((x,A)=>Sd(x,r[o-kd+A],a)).join(", ")+"]"]}return["["+(a==="complex64"?Cd(e):Array.from(e)).map((f,g)=>Sd(f,r[g],a)).join(", ")+"]"]}let u=t.slice(1),p=n.slice(1),c=n[0]*i,d=[];if(o>Kx){for(let f=0;f<kd;f++){let g=f*c,y=g+c;d.push(...eh(e.slice(g,y),u,a,p,r,!1))}d.push("...");for(let f=o-kd;f<o;f++){let g=f*c,y=g+c;d.push(...eh(e.slice(g,y),u,a,p,r,f===o-1))}}else for(let f=0;f<o;f++){let g=f*c,y=g+c;d.push(...eh(e.slice(g,y),u,a,p,r,f===o-1))}let h=l===2?",":"";d[0]="["+(o>0?d[0]+h:"");for(let f=1;f<d.length-1;f++)d[f]=" "+d[f]+h;let m=`,
`;for(let f=2;f<l;f++)m+=`
`;return d[d.length-1]=" "+d[d.length-1]+"]"+(s?"":m),d}function Cd(e){let t=[];for(let a=0;a<e.length;a+=2)t.push([e[a],e[a+1]]);return t}var Vt=class{constructor(e,t,a){if(this.dtype=t,this.shape=e.slice(),this.size=mt(e),a!=null){let n=a.length;F(n===this.size,()=>`Length of values '${n}' does not match the size inferred by the shape '${this.size}'.`)}if(t==="complex64")throw new Error("complex64 dtype TensorBuffers are not supported. Please create a TensorBuffer for the real and imaginary parts separately and call tf.complex(real, imag).");this.values=a||J1(t,this.size),this.strides=iu(e)}set(e,...t){t.length===0&&(t=[0]),F(t.length===this.rank,()=>`The number of provided coordinates (${t.length}) must match the rank (${this.rank})`);let a=this.locToIndex(t);this.values[a]=e}get(...e){e.length===0&&(e=[0]);let t=0;for(let n of e){if(n<0||n>=this.shape[t]){let r=`Requested out of range element at ${e}.   Buffer shape=${this.shape}`;throw new Error(r)}t++}let a=e[e.length-1];for(let n=0;n<e.length-1;++n)a+=this.strides[n]*e[n];return this.values[a]}locToIndex(e){if(this.rank===0)return 0;if(this.rank===1)return e[0];let t=e[e.length-1];for(let a=0;a<e.length-1;++a)t+=this.strides[a]*e[a];return t}indexToLoc(e){if(this.rank===0)return[];if(this.rank===1)return[e];let t=new Array(this.shape.length);for(let a=0;a<t.length-1;++a)t[a]=Math.floor(e/this.strides[a]),e-=t[a]*this.strides[a];return t[t.length-1]=e,t}get rank(){return this.shape.length}toTensor(){return zn().makeTensor(this.values,this.shape,this.dtype)}},zn=null,zl=null,QT=null;function eN(e){zn=e}function tN(e){zl=e}function aN(e){QT=e}var yt=class{constructor(e,t,a,n){this.kept=!1,this.isDisposedInternal=!1,this.shape=e.slice(),this.dtype=t||"float32",this.size=mt(e),this.strides=iu(e),this.dataId=a,this.id=n,this.rankType=this.rank<5?this.rank.toString():"higher"}get rank(){return this.shape.length}async buffer(){let e=await this.data();return zl.buffer(this.shape,this.dtype,e)}bufferSync(){return zl.buffer(this.shape,this.dtype,this.dataSync())}async array(){let e=await this.data();return Bl(this.shape,e,this.dtype==="complex64")}arraySync(){return Bl(this.shape,this.dataSync(),this.dtype==="complex64")}async data(){this.throwIfDisposed();let e=zn().read(this.dataId);if(this.dtype==="string"){let t=await e;try{return t.map(a=>ch(a))}catch(a){throw new Error("Failed to decode the string bytes into utf-8. To get the original bytes, call tensor.bytes().")}}return e}dataToGPU(e){return this.throwIfDisposed(),zn().readToGPU(this.dataId,e)}dataSync(){this.throwIfDisposed();let e=zn().readSync(this.dataId);if(this.dtype==="string")try{return e.map(t=>ch(t))}catch(t){throw new Error("Failed to decode the string bytes into utf-8. To get the original bytes, call tensor.bytes().")}return e}async bytes(){this.throwIfDisposed();let e=await zn().read(this.dataId);return this.dtype==="string"?e:new Uint8Array(e.buffer)}dispose(){this.isDisposed||(this.kerasMask&&this.kerasMask.dispose(),zn().disposeTensor(this),this.isDisposedInternal=!0)}get isDisposed(){return this.isDisposedInternal}throwIfDisposed(){if(this.isDisposed)throw new Error("Tensor is disposed.")}print(e=!1){return zl.print(this,e)}clone(){return this.throwIfDisposed(),zl.clone(this)}toString(e=!1){let t=this.dataSync();return ZT(t,this.shape,this.dtype,e)}cast(e){return this.throwIfDisposed(),zl.cast(this,e)}variable(e=!0,t,a){return this.throwIfDisposed(),zn().makeVariable(this,e,t,a)}};Object.defineProperty(yt,Symbol.hasInstance,{value:e=>!!e&&e.data!=null&&e.dataSync!=null&&e.throwIfDisposed!=null});function _A(){return tg("Tensor",()=>yt)}_A();var Gd=class extends yt{constructor(e,t,a,n){super(e.shape,e.dtype,e.dataId,n),this.trainable=t,this.name=a}assign(e){if(e.dtype!==this.dtype)throw new Error(`dtype of the new value (${e.dtype}) and previous value (${this.dtype}) must match`);if(!Nr(e.shape,this.shape))throw new Error(`shape of the new value (${e.shape}) and previous value (${this.shape}) must match`);zn().disposeTensor(this),this.dataId=e.dataId,zn().incRef(this,null)}dispose(){zn().disposeVariable(this),this.isDisposedInternal=!0}};Object.defineProperty(Gd,Symbol.hasInstance,{value:e=>e instanceof yt&&e.assign!=null&&e.assign instanceof Function});var FA={};Ze(FA,{assertTypesMatch:()=>zA,getTensorsInContainer:()=>ng,isTensorInList:()=>rN,makeTypesMatch:()=>Rt});var n1;(function(e){e.R0="R0",e.R1="R1",e.R2="R2",e.R3="R3",e.R4="R4",e.R5="R5",e.R6="R6"})(n1||(n1={}));var r1;(function(e){e.float32="float32",e.int32="int32",e.bool="int32",e.complex64="complex64"})(r1||(r1={}));var s1;(function(e){e.float32="float32",e.int32="int32",e.bool="bool",e.complex64="complex64"})(s1||(s1={}));var i1;(function(e){e.float32="float32",e.int32="float32",e.bool="float32",e.complex64="complex64"})(i1||(i1={}));var o1;(function(e){e.float32="complex64",e.int32="complex64",e.bool="complex64",e.complex64="complex64"})(o1||(o1={}));var nN={float32:i1,int32:r1,bool:s1,complex64:o1};function ca(e,t){if(e==="string"||t==="string"){if(e==="string"&&t==="string")return"string";throw new Error(`Can not upcast ${e} with ${t}`)}return nN[e][t]}function _p(e){return ca(e,"int32")}function DA(e){return e!=null&&typeof e=="object"&&"texture"in e&&e.texture instanceof WebGLTexture}function OA(e){return typeof GPUBuffer!="undefined"&&e!=null&&typeof e=="object"&&"buffer"in e&&e.buffer instanceof GPUBuffer}function Rt(e,t){if(e.dtype===t.dtype)return[e,t];let a=ca(e.dtype,t.dtype);return[e.cast(a),t.cast(a)]}function zA(e,t){F(e.dtype===t.dtype,()=>`The dtypes of the first(${e.dtype}) and second(${t.dtype}) input must match`)}function rN(e,t){return t.some(a=>a.id===e.id)}function ng(e){let t=[];return LA(e,t,new Set),t}function LA(e,t,a){if(e==null)return;if(e instanceof yt){t.push(e);return}if(!sN(e))return;let n=e;for(let r in n){let s=n[r];a.has(s)||(a.add(s),LA(s,t,a))}}function sN(e){return Array.isArray(e)||typeof e=="object"}function q2(e){return e.kernelName!=null}var Yx=class{constructor(){this.registeredVariables={},this.nextTapeNodeId=0,this.numBytes=0,this.numTensors=0,this.numStringTensors=0,this.numDataBuffers=0,this.gradientDepth=0,this.kernelDepth=0,this.scopeStack=[],this.numDataMovesStack=[],this.nextScopeId=0,this.tensorInfo=new WeakMap,this.profiling=!1,this.activeProfile={newBytes:0,newTensors:0,peakBytes:0,kernels:[],result:null,get kernelNames(){return Array.from(new Set(this.kernels.map(e=>e.name)))}}}dispose(){for(let e in this.registeredVariables)this.registeredVariables[e].dispose()}},rg=class l1{constructor(t){this.ENV=t,this.registry={},this.registryFactory={},this.pendingBackendInitId=0,this.state=new Yx}async ready(){if(this.pendingBackendInit!=null)return this.pendingBackendInit.then(()=>{});if(this.backendInstance!=null)return;let t=this.getSortedBackends();for(let a=0;a<t.length;a++){let n=t[a];if(await this.initializeBackend(n).success){await this.setBackend(n);return}}throw new Error("Could not initialize any backends, all backend initializations failed.")}get backend(){if(this.pendingBackendInit!=null)throw new Error(`Backend '${this.backendName}' has not yet been initialized. Make sure to await tf.ready() or await tf.setBackend() before calling other methods`);if(this.backendInstance==null){let{name:t,asyncInit:a}=this.initializeBackendsAndReturnBest();if(a)throw new Error(`The highest priority backend '${t}' has not yet been initialized. Make sure to await tf.ready() or await tf.setBackend() before calling other methods`);this.setBackend(t)}return this.backendInstance}backendNames(){return Object.keys(this.registryFactory)}findBackend(t){if(!(t in this.registry))if(t in this.registryFactory){let{asyncInit:a}=this.initializeBackend(t);if(a)return null}else return null;return this.registry[t]}findBackendFactory(t){return t in this.registryFactory?this.registryFactory[t].factory:null}registerBackend(t,a,n=1){return t in this.registryFactory?(Ur(`${t} backend was already registered. Reusing existing backend factory.`),!1):(this.registryFactory[t]={factory:a,priority:n},!0)}async setBackend(t){if(this.registryFactory[t]==null)throw new Error(`Backend name '${t}' not found in registry`);if(this.backendName=t,this.registry[t]==null){this.backendInstance=null;let{success:a,asyncInit:n}=this.initializeBackend(t);if(!(n?await a:a))return!1}return this.backendInstance=this.registry[t],this.setupRegisteredKernels(),this.profiler=new jT(this.backendInstance),!0}setupRegisteredKernels(){er(this.backendName).forEach(t=>{t.setupFunc!=null&&t.setupFunc(this.backendInstance)})}disposeRegisteredKernels(t){er(t).forEach(a=>{a.disposeFunc!=null&&a.disposeFunc(this.registry[t])})}initializeBackend(t){let a=this.registryFactory[t];if(a==null)throw new Error(`Cannot initialize backend ${t}, no registration found.`);try{let n=a.factory();if(n&&!(n instanceof su)&&typeof n.then=="function"){let r=++this.pendingBackendInitId,s=n.then(i=>r<this.pendingBackendInitId?!1:(this.registry[t]=i,this.pendingBackendInit=null,!0)).catch(i=>(r<this.pendingBackendInitId||(this.pendingBackendInit=null,Ur(`Initialization of backend ${t} failed`),Ur(i.stack||i.message)),!1));return this.pendingBackendInit=s,{success:s,asyncInit:!0}}else return this.registry[t]=n,{success:!0,asyncInit:!1}}catch(n){return Ur(`Initialization of backend ${t} failed`),Ur(n.stack||n.message),{success:!1,asyncInit:!1}}}removeBackend(t){if(!(t in this.registryFactory))throw new Error(`${t} backend not found in registry`);this.backendName===t&&this.pendingBackendInit!=null&&this.pendingBackendInitId++,t in this.registry&&(this.disposeRegisteredKernels(t),this.registry[t].dispose(),delete this.registry[t]),delete this.registryFactory[t],this.backendName===t&&(this.pendingBackendInit=null,this.backendName=null,this.backendInstance=null)}getSortedBackends(){if(Object.keys(this.registryFactory).length===0)throw new Error("No backend found in registry.");return Object.keys(this.registryFactory).sort((t,a)=>this.registryFactory[a].priority-this.registryFactory[t].priority)}initializeBackendsAndReturnBest(){let t=this.getSortedBackends();for(let a=0;a<t.length;a++){let n=t[a],{success:r,asyncInit:s}=this.initializeBackend(n);if(s||r)return{name:n,asyncInit:s}}throw new Error("Could not initialize any backends, all backend initializations failed.")}moveData(t,a){let n=this.state.tensorInfo.get(a),r=n.backend,s=this.readSync(a),i=r.refCount(a);r.disposeData(a,!0),n.backend=t,t.move(a,s,n.shape,n.dtype,i),this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack[this.state.numDataMovesStack.length-1]++}tidy(t,a){let n=null;if(a==null){if(typeof t!="function")throw new Error("Please provide a function to tidy()");a=t}else{if(typeof t!="string"&&!(t instanceof String))throw new Error("When calling with two arguments, the first argument to tidy() must be a string");if(typeof a!="function")throw new Error("When calling with two arguments, the 2nd argument to tidy() must be a function");n=t}let r;return this.scopedRun(()=>this.startScope(n),()=>this.endScope(r),()=>(r=a(),r instanceof Promise&&console.error("Cannot return a Promise inside of tidy."),r))}scopedRun(t,a,n){t();try{let r=n();return a(),r}catch(r){throw a(),r}}nextTensorId(){return l1.nextTensorId++}nextVariableId(){return l1.nextVariableId++}clone(t){let a=L.runKernel(qi,{x:t}),n={x:t},r=i=>({x:()=>{let o="float32",l={x:i},u={dtype:o};return L.runKernel(bi,l,u)}}),s=[];return this.addTapeNode(this.state.activeScope.name,n,[a],r,s,{}),a}runKernel(t,a,n){if(this.backendName==null&&this.backend,Vd(t,this.backendName)==null)throw new Error(`Kernel '${t}' not registered for backend '${this.backendName}'`);return this.runKernelFunc({kernelName:t,inputs:a,attrs:n})}shouldCheckForMemLeaks(){return this.ENV.getBool("IS_TEST")}checkKernelForMemLeak(t,a,n){let r=this.backend.numDataIds(),s=0;n.forEach(l=>{s+=l.dtype==="complex64"?3:1});let i=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],o=r-a-s-i;if(o>0)throw new Error(`Backend '${this.backendName}' has an internal memory leak (${o} data ids) after running '${t}'`)}runKernelFunc(t){let a,n=[],r=this.isTapeOn(),s=this.state.numBytes,i=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);let o;this.backendName==null&&this.backend;let l,u=q2(t)?t.kernelName:this.state.activeScope!=null?this.state.activeScope.name:"";if(q2(t)){let{kernelName:m,inputs:f,attrs:g}=t;this.backendName==null&&this.backend;let y=Vd(m,this.backendName);F(y!=null,()=>`Cannot find registered kernel '${m}' for backend '${this.backendName}'`),o=()=>{let x=this.backend.numDataIds();l=y.kernelFunc({inputs:f,attrs:g,backend:this.backend});let A=Array.isArray(l)?l:[l];this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(m,x,A);let b=A.map(w=>w.rank!=null?w:this.makeTensorFromTensorInfo(w));if(r){let w=this.getTensorsForGradient(m,f,b);n=this.saveTensorsForBackwardMode(w)}return b}}else{let{forwardFunc:m}=t,f=g=>{r&&(n=g.map(y=>this.keep(this.clone(y))))};o=()=>{let g=this.backend.numDataIds();l=this.tidy(()=>m(this.backend,f));let y=Array.isArray(l)?l:[l];return this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(u,g,y),y}}let{inputs:p,attrs:c}=t,d=q2(t)?null:t.backwardsFunc,h;return this.scopedRun(()=>this.state.kernelDepth++,()=>this.state.kernelDepth--,()=>{!this.ENV.getBool("DEBUG")&&!this.state.profiling?a=o():(h=this.profiler.profileKernel(u,p,()=>o()),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(h),a=h.outputs)}),r&&this.addTapeNode(u,p,a,d,n,c),this.state.profiling&&this.state.activeProfile.kernels.push({name:u,bytesAdded:this.state.numBytes-s,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-i,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(p).map(m=>p[m]!=null?p[m].shape:null),outputShapes:a.map(m=>m.shape),kernelTimeMs:h.timeMs,extraInfo:h.extraInfo}),Array.isArray(l)?a:a[0]}saveTensorsForBackwardMode(t){return t.map(a=>this.keep(this.clone(a)))}getTensorsForGradient(t,a,n){let r=t1(t);if(r!=null){let s=r.inputsToSave||[],i=r.outputsToSave||[],o;r.saveAllInputs?(F(Array.isArray(a),()=>"saveAllInputs is true, expected inputs to be an array."),o=Object.keys(a).map(u=>a[u])):o=s.map(u=>a[u]);let l=n.filter((u,p)=>i[p]);return o.concat(l)}return[]}makeTensor(t,a,n,r){if(t==null)throw new Error("Values passed to engine.makeTensor() are null");n=n||"float32",r=r||this.backend;let s=t;n==="string"&&Gr(t[0])&&(s=t.map(l=>Pp(l)));let i=r.write(s,a,n),o=new yt(a,n,i,this.nextTensorId());if(this.trackTensor(o,r),n==="string"){let l=this.state.tensorInfo.get(i),u=kA(s);this.state.numBytes+=u-l.bytes,l.bytes=u}return o}makeTensorFromDataId(t,a,n,r){n=n||"float32";let s={dataId:t,shape:a,dtype:n};return this.makeTensorFromTensorInfo(s,r)}makeTensorFromTensorInfo(t,a){let{dataId:n,shape:r,dtype:s}=t,i=new yt(r,s,n,this.nextTensorId());return this.trackTensor(i,a),i}makeVariable(t,a=!0,n,r){n=n||this.nextVariableId().toString(),r!=null&&r!==t.dtype&&(t=t.cast(r));let s=new Gd(t,a,n,this.nextTensorId());if(this.state.registeredVariables[s.name]!=null)throw new Error(`Variable with name ${s.name} was already registered`);return this.state.registeredVariables[s.name]=s,this.incRef(s,this.backend),s}trackTensor(t,a){this.state.numTensors++,t.dtype==="string"&&this.state.numStringTensors++;let n=0;t.dtype!=="complex64"&&t.dtype!=="string"&&(n=t.size*dh(t.dtype)),this.state.numBytes+=n,this.state.tensorInfo.has(t.dataId)||(this.state.numDataBuffers++,this.state.tensorInfo.set(t.dataId,{backend:a||this.backend,dtype:t.dtype,shape:t.shape,bytes:n})),t instanceof Gd||this.track(t)}incRef(t,a){this.trackTensor(t,a),this.backend.incRef(t.dataId)}removeDataId(t,a){this.state.tensorInfo.has(t)&&this.state.tensorInfo.get(t).backend===a&&(this.state.tensorInfo.delete(t),this.state.numDataBuffers--)}disposeTensor(t){if(!this.state.tensorInfo.has(t.dataId))return;let a=this.state.tensorInfo.get(t.dataId);if(this.state.numTensors--,t.dtype==="string"&&(this.state.numStringTensors--,this.state.numBytes-=a.bytes),t.dtype!=="complex64"&&t.dtype!=="string"){let n=t.size*dh(t.dtype);this.state.numBytes-=n}a.backend.disposeData(t.dataId)&&this.removeDataId(t.dataId,a.backend)}disposeVariables(){for(let t in this.state.registeredVariables){let a=this.state.registeredVariables[t];this.disposeVariable(a)}}disposeVariable(t){this.disposeTensor(t),this.state.registeredVariables[t.name]!=null&&delete this.state.registeredVariables[t.name]}memory(){let t=this.backend.memory();return t.numTensors=this.state.numTensors,t.numDataBuffers=this.state.numDataBuffers,t.numBytes=this.state.numBytes,this.state.numStringTensors>0&&(t.unreliable=!0,t.reasons==null&&(t.reasons=[]),t.reasons.push("Memory usage by string tensors is approximate (2 bytes per character)")),t}async profile(t){this.state.profiling=!0;let a=this.state.numBytes,n=this.state.numTensors;this.state.activeProfile.kernels=[],this.state.activeProfile.result=await t(),this.state.profiling=!1,this.state.activeProfile.peakBytes=Math.max(...this.state.activeProfile.kernels.map(r=>r.totalBytesSnapshot)),this.state.activeProfile.newBytes=this.state.numBytes-a,this.state.activeProfile.newTensors=this.state.numTensors-n;for(let r of this.state.activeProfile.kernels)r.kernelTimeMs=await r.kernelTimeMs,r.extraInfo=await r.extraInfo;return this.state.activeProfile}isTapeOn(){return this.state.gradientDepth>0&&this.state.kernelDepth===0}addTapeNode(t,a,n,r,s,i){let o={id:this.state.nextTapeNodeId++,kernelName:t,inputs:a,outputs:n,saved:s},l=t1(t);l!=null&&(r=l.gradFunc),r!=null&&(o.gradient=u=>(u=u.map((p,c)=>{if(p==null){let d=n[c],h=Eh(d.size,d.dtype);return this.makeTensor(h,d.shape,d.dtype)}return p}),r(u.length>1?u:u[0],s,i))),this.state.activeTape.push(o)}keep(t){return t.kept=!0,t}startTape(){this.state.gradientDepth===0&&(this.state.activeTape=[]),this.state.gradientDepth++}endTape(){this.state.gradientDepth--}startScope(t){let a={track:[],name:"unnamed scope",id:this.state.nextScopeId++};t&&(a.name=t),this.state.scopeStack.push(a),this.state.activeScope=a}endScope(t){let a=ng(t),n=new Set(a.map(s=>s.id));for(let s=0;s<this.state.activeScope.track.length;s++){let i=this.state.activeScope.track[s];!i.kept&&!n.has(i.id)&&i.dispose()}let r=this.state.scopeStack.pop();this.state.activeScope=this.state.scopeStack.length===0?null:this.state.scopeStack[this.state.scopeStack.length-1],a.forEach(s=>{!s.kept&&s.scopeId===r.id&&this.track(s)})}gradients(t,a,n,r=!1){if(F(a.length>0,()=>"gradients() received an empty list of xs."),n!=null&&n.dtype!=="float32")throw new Error(`dy must have 'float32' dtype, but has '${n.dtype}'`);let s=this.scopedRun(()=>this.startTape(),()=>this.endTape(),()=>this.tidy("forward",t));F(s instanceof yt,()=>"The result y returned by f() must be a tensor.");let i=KT(this.state.activeTape,a,s);if(!r&&i.length===0&&a.length>0)throw new Error("Cannot compute gradient of y=f(x) with respect to x. Make sure that the f you passed encloses all operations that lead from x to y.");return this.tidy("backward",()=>{let o={};o[s.id]=n==null?iN(s.shape):n,YT(o,i,u=>this.tidy(u),oN);let l=a.map(u=>o[u.id]);return this.state.gradientDepth===0&&(this.state.activeTape.forEach(u=>{for(let p of u.saved)p.dispose()}),this.state.activeTape=null),{value:s,grads:l}})}customGrad(t){return F(Yr(t),()=>"The f passed in customGrad(f) must be a function."),(...a)=>{F(a.every(o=>o instanceof yt),()=>"The args passed in customGrad(f)(x1, x2,...) must all be tensors");let n,r={};a.forEach((o,l)=>{r[l]=o});let s=(o,l)=>(n=t(...a,l),F(n.value instanceof yt,()=>"The function f passed in customGrad(f) must return an object where `obj.value` is a tensor"),F(Yr(n.gradFunc),()=>"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function."),n.value),i=(o,l)=>{let u=n.gradFunc(o,l),p=Array.isArray(u)?u:[u];F(p.length===a.length,()=>"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns the same number of tensors as inputs passed to f(...)."),F(p.every(d=>d instanceof yt),()=>"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns a list of only tensors.");let c={};return p.forEach((d,h)=>{c[h]=()=>d}),c};return this.runKernelFunc({forwardFunc:s,backwardsFunc:i,inputs:r})}}readSync(t){return this.state.tensorInfo.get(t).backend.readSync(t)}read(t){return this.state.tensorInfo.get(t).backend.read(t)}readToGPU(t,a){return this.state.tensorInfo.get(t).backend.readToGPU(t,a)}async time(t){let a=Ud(),n=await this.backend.time(t);return n.wallMs=Ud()-a,n}track(t){return this.state.activeScope!=null&&(t.scopeId=this.state.activeScope.id,this.state.activeScope.track.push(t)),t}get registeredVariables(){return this.state.registeredVariables}reset(){this.pendingBackendInitId++,this.state.dispose(),this.ENV.reset(),this.state=new Yx;for(let t in this.registry)this.disposeRegisteredKernels(t),this.registry[t].dispose(),delete this.registry[t];this.backendName=null,this.backendInstance=null,this.pendingBackendInit=null}};rg.nextTensorId=0;rg.nextVariableId=0;function iN(e){let t=Q1(mt(e),"float32");return L.makeTensor(t,e,"float32")}function WA(){let e=NA();if(e._tfengine==null){let t=new TA(e);e._tfengine=new rg(t)}return ST(e._tfengine.ENV),eN(()=>e._tfengine),e._tfengine}var L=WA();function oN(e,t){let a={a:e,b:t};return L.runKernel(ls,a)}var Fp={};Ze(Fp,{isBrowser:()=>BA,isMobile:()=>dN,mockIsMobile:()=>uN});function lN(){return typeof navigator!="undefined"&&navigator!=null}var u1;function uN(e){u1=e}function dN(e){if(u1!==void 0)return u1;if(e||lN()){if(e||(e=navigator),e.product==="ReactNative")return!0;let t=e.userAgent||e.vendor||(typeof window!="undefined"?window.opera:"");if(!t){let a=e;return a.userAgentData&&a.userAgentData.mobile}return/(android|bb\d+|meego).+mobile|avantgo|bada\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)\/|plucker|pocket|psp|series(4|6)0|symbian|treo|up\.(browser|link)|vodafone|wap|windows ce|xda|xiino/i.test(t)||/1207|6310|6590|3gso|4thp|50[1-6]i|770s|802s|a wa|abac|ac(er|oo|s\-)|ai(ko|rn)|al(av|ca|co)|amoi|an(ex|ny|yw)|aptu|ar(ch|go)|as(te|us)|attw|au(di|\-m|r |s )|avan|be(ck|ll|nq)|bi(lb|rd)|bl(ac|az)|br(e|v)w|bumb|bw\-(n|u)|c55\/|capi|ccwa|cdm\-|cell|chtm|cldc|cmd\-|co(mp|nd)|craw|da(it|ll|ng)|dbte|dc\-s|devi|dica|dmob|do(c|p)o|ds(12|\-d)|el(49|ai)|em(l2|ul)|er(ic|k0)|esl8|ez([4-7]0|os|wa|ze)|fetc|fly(\-|_)|g1 u|g560|gene|gf\-5|g\-mo|go(\.w|od)|gr(ad|un)|haie|hcit|hd\-(m|p|t)|hei\-|hi(pt|ta)|hp( i|ip)|hs\-c|ht(c(\-| |_|a|g|p|s|t)|tp)|hu(aw|tc)|i\-(20|go|ma)|i230|iac( |\-|\/)|ibro|idea|ig01|ikom|im1k|inno|ipaq|iris|ja(t|v)a|jbro|jemu|jigs|kddi|keji|kgt( |\/)|klon|kpt |kwc\-|kyo(c|k)|le(no|xi)|lg( g|\/(k|l|u)|50|54|\-[a-w])|libw|lynx|m1\-w|m3ga|m50\/|ma(te|ui|xo)|mc(01|21|ca)|m\-cr|me(rc|ri)|mi(o8|oa|ts)|mmef|mo(01|02|bi|de|do|t(\-| |o|v)|zz)|mt(50|p1|v )|mwbp|mywa|n10[0-2]|n20[2-3]|n30(0|2)|n50(0|2|5)|n7(0(0|1)|10)|ne((c|m)\-|on|tf|wf|wg|wt)|nok(6|i)|nzph|o2im|op(ti|wv)|oran|owg1|p800|pan(a|d|t)|pdxg|pg(13|\-([1-8]|c))|phil|pire|pl(ay|uc)|pn\-2|po(ck|rt|se)|prox|psio|pt\-g|qa\-a|qc(07|12|21|32|60|\-[2-7]|i\-)|qtek|r380|r600|raks|rim9|ro(ve|zo)|s55\/|sa(ge|ma|mm|ms|ny|va)|sc(01|h\-|oo|p\-)|sdk\/|se(c(\-|0|1)|47|mc|nd|ri)|sgh\-|shar|sie(\-|m)|sk\-0|sl(45|id)|sm(al|ar|b3|it|t5)|so(ft|ny)|sp(01|h\-|v\-|v )|sy(01|mb)|t2(18|50)|t6(00|10|18)|ta(gt|lk)|tcl\-|tdg\-|tel(i|m)|tim\-|t\-mo|to(pl|sh)|ts(70|m\-|m3|m5)|tx\-9|up(\.b|g1|si)|utst|v400|v750|veri|vi(rg|te)|vk(40|5[0-3]|\-v)|vm40|voda|vulc|vx(52|53|60|61|70|80|81|83|85|98)|w3c(\-| )|webc|whit|wi(g |nc|nw)|wmlb|wonu|x700|yas\-|your|zeto|zte\-/i.test(t.substr(0,4))}return!1}function BA(){return typeof window!="undefined"&&window.document!=null||typeof WorkerGlobalScope!="undefined"}var Ba=B();Ba.registerFlag("DEBUG",()=>!1,e=>{e&&console.warn("Debugging mode is ON. The output of every math call will be downloaded to CPU and checked for NaNs. This significantly impacts performance.")});Ba.registerFlag("IS_BROWSER",()=>BA());Ba.registerFlag("IS_NODE",()=>typeof process!="undefined"&&typeof process.versions!="undefined"&&typeof process.versions.node!="undefined");Ba.registerFlag("IS_CHROME",()=>typeof navigator!="undefined"&&navigator!=null&&navigator.userAgent!=null&&/Chrome/.test(navigator.userAgent)&&/Google Inc/.test(navigator.vendor));Ba.registerFlag("IS_SAFARI",()=>typeof navigator!="undefined"&&navigator!=null&&navigator.userAgent!=null&&/Safari/.test(navigator.userAgent)&&/Apple/.test(navigator.vendor));Ba.registerFlag("PROD",()=>!1);Ba.registerFlag("TENSORLIKE_CHECK_SHAPE_CONSISTENCY",()=>Ba.getBool("DEBUG"));Ba.registerFlag("DEPRECATION_WARNINGS_ENABLED",()=>!0);Ba.registerFlag("IS_TEST",()=>!1);Ba.registerFlag("CHECK_COMPUTATION_FOR_ERRORS",()=>Ba.getBool("DEBUG"));Ba.registerFlag("WRAP_TO_IMAGEBITMAP",()=>!1);Ba.registerFlag("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU",()=>!1);Ba.registerFlag("USE_SETTIMEOUTCUSTOM",()=>!1);function tr(e,t){let a=e;if(Qt(e))return t==="string"?[]:[e.length];if(DA(e)){let r=e.channels||"RGBA";return[e.height,e.width*r.length]}else if(OA(e))return[e.buffer.size/(t==null?4:dh(t))];if(!Array.isArray(e))return[];let n=[];for(;Array.isArray(a)||Qt(a)&&t!=="string";)n.push(a.length),a=a[0];return Array.isArray(e)&&B().getBool("TENSORLIKE_CHECK_SHAPE_CONSISTENCY")&&VA(e,n,[]),n}function VA(e,t,a){if(a=a||[],!Array.isArray(e)&&!Qt(e)){F(t.length===0,()=>`Element arr[${a.join("][")}] is a primitive, but should be an array/TypedArray of ${t[0]} elements`);return}F(t.length>0,()=>`Element arr[${a.join("][")}] should be a primitive, but is an array of ${e.length} elements`),F(e.length===t[0],()=>`Element arr[${a.join("][")}] should have ${t[0]} elements, but has ${e.length} elements`);let n=t.slice(1);for(let r=0;r<e.length;++r)VA(e[r],n,a.concat(r))}function Zx(e,t,a,n){if(e!=="string_or_numeric"){if(e==null)throw new Error("Expected dtype cannot be null.");if(e!=="numeric"&&e!==t||e==="numeric"&&t==="string")throw new Error(`Argument '${a}' passed to '${n}' must be ${e} tensor, but got ${t} tensor`)}}function R(e,t,a,n="numeric"){if(e instanceof _A())return Zx(n,e.dtype,t,a),e;let r=up(e);if(r!=="string"&&["bool","int32","float32"].indexOf(n)>=0&&(r=n),Zx(n,r,t,a),e==null||!Qt(e)&&!Array.isArray(e)&&typeof e!="number"&&typeof e!="boolean"&&typeof e!="string"){let o=e==null?"null":e.constructor.name;throw new Error(`Argument '${t}' passed to '${a}' must be a Tensor or TensorLike, but got '${o}'`)}let s=tr(e,r);!Qt(e)&&!Array.isArray(e)&&(e=[e]);let i=r!=="string"?Fh(e,r):es(e,[],!0);return L.makeTensor(i,s,r)}function Hd(e,t,a,n="numeric"){if(!Array.isArray(e))throw new Error(`Argument ${t} passed to ${a} must be a \`Tensor[]\` or \`TensorLike[]\``);return e.map((r,s)=>R(r,`${t}[${s}]`,a,n))}var sg="__op";function z(e){let t=Object.keys(e);if(t.length!==1)throw new Error(`Please provide an object with a single key (operation name) mapping to a function. Got an object with ${t.length} keys.`);let a=t[0],n=e[a];a.endsWith("_")&&(a=a.substring(0,a.length-1)),a=a+sg;let r=(...s)=>{L.startScope(a);try{let i=n(...s);return Mh(i)&&console.error("Cannot return a Promise inside of tidy."),L.endScope(i),i}catch(i){throw L.endScope(null),i}};return Object.defineProperty(r,"name",{value:a,configurable:!0}),r}function pN(e,t){let a=R(e,"real","complex"),n=R(t,"imag","complex");Ta(a.shape,n.shape,`real and imag shapes, ${a.shape} and ${n.shape}, must match in call to tf.complex().`);let r={real:a,imag:n};return L.runKernel(cp,r)}var Tr=z({complex_:pN});function cs(e,t,a,n){if(n==null)n=up(e);else if(n==="complex64")throw new Error("Cannot construct a complex64 tensor directly. Please use tf.complex(real, imag).");if(OA(e)||DA(e)){if(n!=="float32"&&n!=="int32")throw new Error(`Creating tensor from GPU data only supports 'float32'|'int32' dtype, while the dtype is ${n}.`);return L.backend.createTensorFromGPUData(e,t||a,n)}if(!Qt(e)&&!Array.isArray(e)&&typeof e!="number"&&typeof e!="boolean"&&typeof e!="string")throw new Error("values passed to tensor(values) must be a number/boolean/string or an array of numbers/booleans/strings, or a TypedArray");if(t!=null){an(t);let r=mt(t),s=mt(a);F(r===s,()=>`Based on the provided shape, [${t}], the tensor should have ${r} values but has ${s}`);for(let i=0;i<a.length;++i){let o=a[i],l=i===a.length-1?o!==mt(t.slice(i)):!0;F(a[i]===t[i]||!l,()=>`Error creating a new Tensor. Inferred shape (${a}) does not match the provided shape (${t}). `)}}return!Qt(e)&&!Array.isArray(e)&&(e=[e]),t=t||a,e=n!=="string"?Fh(e,n):es(e,[],!0),L.makeTensor(e,t,n)}function Ve(e,t,a){let n=tr(e,a);return cs(e,t,n,a)}var Ks={float32:4,float16:2,int32:4,uint16:2,uint8:1,bool:1,complex64:8},Rr=class UA{static join(t){return new UA(t).slice()}constructor(t){if(this.shards=[],this.previousShardIndex=0,t==null||(t instanceof Array||(t=[t]),t=t.map(n=>Qt(n)?n.buffer:n),t.length===0))return;this.bufferUniformSize=t[0].byteLength;let a=0;for(let n=0;n<t.length;n++){let r=t[n];n!==t.length-1&&r.byteLength!==this.bufferUniformSize&&(this.bufferUniformSize=void 0);let s=a+r.byteLength;this.shards.push({buffer:r,start:a,end:s}),a=s}this.shards.length===0&&(this.byteLength=0),this.byteLength=this.shards[this.shards.length-1].end}slice(t=0,a=this.byteLength){if(this.shards.length===0)return new ArrayBuffer(0);if(t=isNaN(Number(t))?0:t,a=isNaN(Number(a))?0:a,t=Math.max(0,t),a=Math.min(this.byteLength,a),a<=t)return new ArrayBuffer(0);let n=this.findShardForByte(t);if(n===-1)throw new Error(`Could not find start shard for byte ${t}`);let r=a-t,s=new ArrayBuffer(r),i=new Uint8Array(s),o=0;for(let l=n;l<this.shards.length;l++){let u=this.shards[l],p=t+o-u.start,c=o,d=Math.min(a,u.end)-u.start,h=new Uint8Array(u.buffer,p,d-p);if(i.set(h,c),o+=h.length,a<u.end)break}return s}findShardForByte(t){if(this.shards.length===0||t<0||t>=this.byteLength)return-1;if(this.bufferUniformSize!=null)return this.previousShardIndex=Math.floor(t/this.bufferUniformSize),this.previousShardIndex;function a(r){return t<r.start?-1:t>=r.end?1:0}if(a(this.shards[this.previousShardIndex])===0)return this.previousShardIndex;let n=cN(this.shards,a);return n===-1?-1:(this.previousShardIndex=n,this.previousShardIndex)}};function cN(e,t){let a=0,n=e.length;for(;a<=n;){let r=Math.floor((n-a)/2)+a,s=t(e[r]);if(s===0)return r;s<0?n=r:a=r+1}return-1}function ig(){B().set("PROD",!0)}function hN(){B().set("DEBUG",!0)}function mN(){B().set("DEPRECATION_WARNINGS_ENABLED",!1),console.warn("TensorFlow.js deprecation warnings have been disabled.")}function og(e){B().getBool("DEPRECATION_WARNINGS_ENABLED")&&console.warn(e+" You can disable deprecation warnings with tf.disableDeprecationWarnings().")}aN(og);function fN(){L.disposeVariables()}function It(){return L}function gN(){return L.memory()}function yN(e){return L.profile(e)}function De(e,t){return L.tidy(e,t)}function J(e){ng(e).forEach(t=>t.dispose())}function Ln(e){return L.keep(e)}function xN(e){return L.time(e)}function Dp(e){return L.setBackend(e)}function tl(){return L.ready()}function ea(){return L.backendName}function AN(e){L.removeBackend(e)}function lg(e){return L.findBackend(e)}function bN(e){return L.findBackendFactory(e)}function al(e,t,a=1){return L.registerBackend(e,t,a)}function Vn(){return L.backend}function vN(e,t){B().setPlatform(e,t)}var ts=4;async function wN(e,t){let a=[],n=[],r=Array.isArray(e)?e.map(i=>i.name):Object.keys(e);for(let i=0;i<r.length;++i){let o=r[i],l=Array.isArray(e)?e[i].tensor:e[o];if(l.dtype!=="float32"&&l.dtype!=="int32"&&l.dtype!=="bool"&&l.dtype!=="string"&&l.dtype!=="complex64")throw new Error(`Unsupported dtype in weight '${o}': ${l.dtype}`);let u={name:o,shape:l.shape,dtype:l.dtype};if(l.dtype==="string"){let p=new Promise(async c=>{let d=await l.bytes(),h=d.reduce((g,y)=>g+y.length,0)+ts*d.length,m=new Uint8Array(h),f=0;for(let g=0;g<d.length;g++){let y=d[g],x=new Uint8Array(new Uint32Array([y.length]).buffer);m.set(x,f),f+=ts,m.set(y,f),f+=y.length}c(m)});n.push(p)}else n.push(l.data());t!=null&&(u.group=t),a.push(u)}let s=await Promise.all(n);return{data:SN(s),specs:a}}function GA(e,t){let a=new Rr(e),n={},r=0;for(let s of t){let i=kN(s,(o,l)=>a.slice(r+o,r+l));n[s.name]=HA(s,a.slice(r,r+i)),r+=i}return n}function kN(e,t){let a=mt(e.shape),n;if("quantization"in e){let r=e.quantization;n=Ks[r.dtype]}else if(e.dtype==="string"){let r=0;for(let s=0;s<a;s++)r+=ts+new Uint32Array(t(r,r+ts))[0];return r}else n=Ks[e.dtype];return a*n}async function IN(e,t){let a=mt(e.shape),n;if("quantization"in e){let r=e.quantization;n=Ks[r.dtype]}else if(e.dtype==="string"){let r=0;for(let s=0;s<a;s++)r+=ts+new Uint32Array(await t(r,r+ts))[0];return r}else n=Ks[e.dtype];return a*n}function HA(e,t){let a=e.name,n=e.dtype,r=e.shape,s=mt(r),i,o=0;if("quantization"in e){let l=e.quantization;if(l.dtype==="uint8"||l.dtype==="uint16"){if(!("min"in l&&"scale"in l))throw new Error(`Weight ${e.name} with quantization ${l.dtype} doesn't have corresponding metadata min and scale.`)}else if(l.dtype==="float16"){if(n!=="float32")throw new Error(`Weight ${e.name} is quantized with ${l.dtype} which only supports weights of type float32 not ${n}.`)}else throw new Error(`Weight ${e.name} has unknown quantization dtype ${l.dtype}. Supported quantization dtypes are: 'uint8', 'uint16', and 'float16'.`);let u=Ks[l.dtype],p=l.dtype==="uint8"?new Uint8Array(t):new Uint16Array(t);if(n==="float32")if(l.dtype==="uint8"||l.dtype==="uint16"){i=new Float32Array(p.length);for(let c=0;c<p.length;c++){let d=p[c];i[c]=d*l.scale+l.min}}else if(l.dtype==="float16")i=$N()(p);else throw new Error(`Unsupported quantization type ${l.dtype} for weight type float32.`);else if(n==="int32"){if(l.dtype!=="uint8"&&l.dtype!=="uint16")throw new Error(`Unsupported quantization type ${l.dtype} for weight type int32.`);i=new Int32Array(p.length);for(let c=0;c<p.length;c++){let d=p[c];i[c]=Math.round(d*l.scale+l.min)}}else throw new Error(`Unsupported dtype in weight '${a}': ${n}`);o+=s*u}else if(n==="string"){let l=mt(e.shape);i=[];for(let u=0;u<l;u++){let p=new Uint32Array(t.slice(o,o+ts))[0];o+=ts;let c=new Uint8Array(t.slice(o,o+p));i.push(c),o+=p}}else{let l=Ks[n];if(n==="float32")i=new Float32Array(t);else if(n==="int32")i=new Int32Array(t);else if(n==="bool")i=new Uint8Array(t);else if(n==="complex64"){i=new Float32Array(t);let u=new Float32Array(i.length/2),p=new Float32Array(i.length/2);for(let m=0;m<u.length;m++)u[m]=i[m*2],p[m]=i[m*2+1];let c=Ve(u,r,"float32"),d=Ve(p,r,"float32"),h=Tr(c,d);return c.dispose(),d.dispose(),h}else throw new Error(`Unsupported dtype in weight '${a}': ${n}`);o+=s*l}return Ve(i,r,n)}async function Jx(e,t,a){let n=new Uint8Array(t);for(;n.byteLength<a;){let{done:r,value:s}=await e.read();if(r&&s==null){let o=a-n.byteLength;throw new Error(`Reader is done but ${o} bytes are still expected`)}let i=new Uint8Array(n.length+s.byteLength);i.set(n,0),i.set(new Uint8Array(s),n.length),n=i}return n.buffer}async function jA(e,t){let a={},n=e.getReader(),r=new ArrayBuffer(0);for(let s of t){let i=await IN(s,async(u,p)=>(r=await Jx(n,r,p),r.slice(u,p)));r=await Jx(n,r,i);let o=r.slice(0,i);r=r.slice(i);let l=HA(s,o);if(a[s.name]=l,ea()==="webgpu"){let u=Vn();"uploadToGPU"in u&&mt(l.shape)>=B().get("WEBGPU_CPU_HANDOFF_SIZE_THRESHOLD")&&u.uploadToGPU(l.dataId)}}return a}function SN(e){if(e===null)throw new Error(`Invalid input value: ${JSON.stringify(e)}`);let t=0,a=[];e.forEach(s=>{if(t+=s.byteLength,a.push(s.byteLength===s.buffer.byteLength?s:new s.constructor(s)),!(s instanceof Float32Array||s instanceof Int32Array||s instanceof Uint8Array))throw new Error(`Unsupported TypedArray subtype: ${s.constructor.name}`)});let n=new Uint8Array(t),r=0;return a.forEach(s=>{n.set(new Uint8Array(s.buffer),r),r+=s.byteLength}),n.buffer}var ug=typeof Buffer!="undefined"&&(typeof Blob=="undefined"||typeof atob=="undefined"||typeof btoa=="undefined");function Qx(e){return ug?Buffer.byteLength(e,"utf8"):new Blob([e]).size}function CN(e){if(ug)return Buffer.from(e).toString("base64");let t=new Uint8Array(e),a="";for(let n=0,r=t.length;n<r;n++)a+=String.fromCharCode(t[n]);return btoa(a)}function TN(e){if(ug){let n=Buffer.from(e,"base64");return n.buffer.slice(n.byteOffset,n.byteOffset+n.byteLength)}let t=atob(e),a=new Uint8Array(t.length);for(let n=0;n<t.length;++n)a.set([t.charCodeAt(n)],n);return a.buffer}function NN(e){return Rr.join(e)}function e5(e){let t="/";for(e=e.trim();e.endsWith(t);)e=e.slice(0,e.length-1);let a=e.split(t);return a[a.length-1]}function qA(e,t){let a={modelTopology:e.modelTopology,format:e.format,generatedBy:e.generatedBy,convertedBy:e.convertedBy,weightsManifest:t};return e.signature!=null&&(a.signature=e.signature),e.userDefinedMetadata!=null&&(a.userDefinedMetadata=e.userDefinedMetadata),e.modelInitializer!=null&&(a.modelInitializer=e.modelInitializer),e.initializerSignature!=null&&(a.initializerSignature=e.initializerSignature),e.trainingConfig!=null&&(a.trainingConfig=e.trainingConfig),a}function XA(e,t,a){let n={modelTopology:e.modelTopology,format:e.format,generatedBy:e.generatedBy,convertedBy:e.convertedBy};if(e.trainingConfig!=null&&(n.trainingConfig=e.trainingConfig),e.weightsManifest!=null){if(!t)throw new Error("modelJSON has weightsManifest but weightSpecs is null");if(!a)throw new Error("modelJSON has weightsManifest but weightData is null");n.weightSpecs=t,n.weightData=a}return e.signature!=null&&(n.signature=e.signature),e.userDefinedMetadata!=null&&(n.userDefinedMetadata=e.userDefinedMetadata),e.modelInitializer!=null&&(n.modelInitializer=e.modelInitializer),e.initializerSignature!=null&&(n.initializerSignature=e.initializerSignature),n}async function dg(e,t){let a,n;return e.weightsManifest!=null&&([a,n]=await t(e.weightsManifest)),XA(e,a,n)}function Op(e){if(e.modelTopology instanceof ArrayBuffer)throw new Error("Expected JSON model topology, received ArrayBuffer.");return{dateSaved:new Date,modelTopologyType:"JSON",modelTopologyBytes:e.modelTopology==null?0:Qx(JSON.stringify(e.modelTopology)),weightSpecsBytes:e.weightSpecs==null?0:Qx(JSON.stringify(e.weightSpecs)),weightDataBytes:e.weightData==null?0:new Rr(e.weightData).byteLength}}function d1(e){let t=[];for(let a of e)t.push(...a.weights);return t}function RN(){let e=a=>{let n=a<<13,r=0;for(;!(n&8388608);)r-=8388608,n<<=1;return n&=-8388609,r+=947912704,n|r},t=new Uint32Array(2048);t[0]=0;for(let a=1;a<1024;a++)t[a]=e(a);for(let a=1024;a<2048;a++)t[a]=939524096+(a-1024<<13);return t}function EN(){let e=new Uint32Array(64);e[0]=0,e[31]=1199570944,e[32]=2147483648,e[63]=3347054592;for(let t=1;t<31;t++)e[t]=t<<23;for(let t=33;t<63;t++)e[t]=2147483648+(t-32<<23);return e}function MN(){let e=new Uint32Array(64);for(let t=0;t<64;t++)e[t]=1024;return e[0]=e[32]=0,e}function $N(){let e=RN(),t=EN(),a=MN();return n=>{let r=new ArrayBuffer(4*n.length),s=new Uint32Array(r);for(let i=0;i<n.length;i++){let o=n[i],l=e[a[o>>10]+(o&1023)]+t[o>>10];s[i]=l}return new Float32Array(r)}}var gn=class Dn{constructor(){this.saveRouters=[],this.loadRouters=[]}static getInstance(){return Dn.instance==null&&(Dn.instance=new Dn),Dn.instance}static registerSaveRouter(t){Dn.getInstance().saveRouters.push(t)}static registerLoadRouter(t){Dn.getInstance().loadRouters.push(t)}static getSaveHandlers(t){return Dn.getHandlers(t,"save")}static getLoadHandlers(t,a){return Dn.getHandlers(t,"load",a)}static getHandlers(t,a,n){let r=[];return(a==="load"?Dn.getInstance().loadRouters:Dn.getInstance().saveRouters).forEach(s=>{let i=s(t,n);i!==null&&r.push(i)}),r}},PN=e=>gn.registerSaveRouter(e),_N=e=>gn.registerLoadRouter(e),FN=e=>gn.getSaveHandlers(e),DN=(e,t)=>gn.getLoadHandlers(e,t),p1="tensorflowjs",c1=1,js="models_store",Hr="model_info_store";function KA(){if(!B().getBool("IS_BROWSER"))throw new Error("Failed to obtain IndexedDB factory because the current environmentis not a web browser.");let e=typeof window=="undefined"?self:window,t=e.indexedDB||e.mozIndexedDB||e.webkitIndexedDB||e.msIndexedDB||e.shimIndexedDB;if(t==null)throw new Error("The current browser does not appear to support IndexedDB.");return t}function h1(e){let t=e.result;t.createObjectStore(js,{keyPath:"modelPath"}),t.createObjectStore(Hr,{keyPath:"modelPath"})}var Ys=class{constructor(e){if(this.indexedDB=KA(),e==null||!e)throw new Error("For IndexedDB, modelPath must not be null, undefined or empty.");this.modelPath=e}async save(e){if(e.modelTopology instanceof ArrayBuffer)throw new Error("BrowserLocalStorage.save() does not support saving model topology in binary formats yet.");return this.databaseAction(this.modelPath,e)}async load(){return this.databaseAction(this.modelPath)}databaseAction(e,t){return new Promise((a,n)=>{let r=this.indexedDB.open(p1,c1);r.onupgradeneeded=()=>h1(r),r.onsuccess=()=>{let s=r.result;if(t==null){let i=s.transaction(js,"readonly"),o=i.objectStore(js).get(this.modelPath);o.onsuccess=()=>{if(o.result==null)return s.close(),n(new Error(`Cannot find model with path '${this.modelPath}' in IndexedDB.`));a(o.result.modelArtifacts)},o.onerror=l=>(s.close(),n(o.error)),i.oncomplete=()=>s.close()}else{t.weightData=Rr.join(t.weightData);let i=Op(t),o=s.transaction(Hr,"readwrite"),l=o.objectStore(Hr),u;try{u=l.put({modelPath:this.modelPath,modelArtifactsInfo:i})}catch(c){return n(c)}let p;u.onsuccess=()=>{p=s.transaction(js,"readwrite");let c=p.objectStore(js),d;try{d=c.put({modelPath:this.modelPath,modelArtifacts:t,modelArtifactsInfo:i})}catch(h){return n(h)}d.onsuccess=()=>a({modelArtifactsInfo:i}),d.onerror=h=>{l=o.objectStore(Hr);let m=l.delete(this.modelPath);m.onsuccess=()=>(s.close(),n(d.error)),m.onerror=f=>(s.close(),n(d.error))}},u.onerror=c=>(s.close(),n(u.error)),o.oncomplete=()=>{p==null?s.close():p.oncomplete=()=>s.close()}}},r.onerror=s=>n(r.error)})}};Ys.URL_SCHEME="indexeddb://";var YA=e=>B().getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(Ys.URL_SCHEME)?ON(e.slice(Ys.URL_SCHEME.length)):null;gn.registerSaveRouter(YA);gn.registerLoadRouter(YA);function ON(e){return new Ys(e)}function zN(e){return e.startsWith(Ys.URL_SCHEME)?e.slice(Ys.URL_SCHEME.length):e}var LN=class{constructor(){this.indexedDB=KA()}async listModels(){return new Promise((e,t)=>{let a=this.indexedDB.open(p1,c1);a.onupgradeneeded=()=>h1(a),a.onsuccess=()=>{let n=a.result,r=n.transaction(Hr,"readonly"),s=r.objectStore(Hr).getAll();s.onsuccess=()=>{let i={};for(let o of s.result)i[o.modelPath]=o.modelArtifactsInfo;e(i)},s.onerror=i=>(n.close(),t(s.error)),r.oncomplete=()=>n.close()},a.onerror=n=>t(a.error)})}async removeModel(e){return e=zN(e),new Promise((t,a)=>{let n=this.indexedDB.open(p1,c1);n.onupgradeneeded=()=>h1(n),n.onsuccess=()=>{let r=n.result,s=r.transaction(Hr,"readwrite"),i=s.objectStore(Hr),o=i.get(e),l;o.onsuccess=()=>{if(o.result==null)return r.close(),a(new Error(`Cannot find model with path '${e}' in IndexedDB.`));{let u=i.delete(e),p=()=>{l=r.transaction(js,"readwrite");let c=l.objectStore(js).delete(e);c.onsuccess=()=>t(o.result.modelArtifactsInfo),c.onerror=d=>a(o.error)};u.onsuccess=p,u.onerror=c=>(p(),r.close(),a(o.error))}},o.onerror=u=>(r.close(),a(o.error)),s.oncomplete=()=>{l==null?r.close():l.oncomplete=()=>r.close()}},n.onerror=r=>a(n.error)})}},kr="/",Ll="tensorflowjs_models",ZA="info",WN="model_topology",BN="weight_specs",VN="weight_data",UN="model_metadata";function JA(e){return{info:[Ll,e,ZA].join(kr),topology:[Ll,e,WN].join(kr),weightSpecs:[Ll,e,BN].join(kr),weightData:[Ll,e,VN].join(kr),modelMetadata:[Ll,e,UN].join(kr)}}function QA(e){for(let t of Object.values(e))window.localStorage.removeItem(t)}function GN(e){let t=e.split(kr);if(t.length<3)throw new Error(`Invalid key format: ${e}`);return t.slice(1,t.length-1).join(kr)}function HN(e){return e.startsWith(Zs.URL_SCHEME)?e.slice(Zs.URL_SCHEME.length):e}var Zs=class{constructor(e){if(!B().getBool("IS_BROWSER")||typeof window=="undefined"||typeof window.localStorage=="undefined")throw new Error("The current environment does not support local storage.");if(this.LS=window.localStorage,e==null||!e)throw new Error("For local storage, modelPath must not be null, undefined or empty.");this.modelPath=e,this.keys=JA(this.modelPath)}async save(e){if(e.modelTopology instanceof ArrayBuffer)throw new Error("BrowserLocalStorage.save() does not support saving model topology in binary formats yet.");{let t=JSON.stringify(e.modelTopology),a=JSON.stringify(e.weightSpecs),n=Op(e),r=Rr.join(e.weightData);try{this.LS.setItem(this.keys.info,JSON.stringify(n)),this.LS.setItem(this.keys.topology,t),this.LS.setItem(this.keys.weightSpecs,a),this.LS.setItem(this.keys.weightData,CN(r));let s={format:e.format,generatedBy:e.generatedBy,convertedBy:e.convertedBy,signature:e.signature!=null?e.signature:void 0,userDefinedMetadata:e.userDefinedMetadata!=null?e.userDefinedMetadata:void 0,modelInitializer:e.modelInitializer!=null?e.modelInitializer:void 0,initializerSignature:e.initializerSignature!=null?e.initializerSignature:void 0,trainingConfig:e.trainingConfig!=null?e.trainingConfig:void 0};return this.LS.setItem(this.keys.modelMetadata,JSON.stringify(s)),{modelArtifactsInfo:n}}catch(s){throw QA(this.keys),new Error(`Failed to save model '${this.modelPath}' to local storage: size quota being exceeded is a possible cause of this failure: modelTopologyBytes=${n.modelTopologyBytes}, weightSpecsBytes=${n.weightSpecsBytes}, weightDataBytes=${n.weightDataBytes}.`)}}}async load(){let e=JSON.parse(this.LS.getItem(this.keys.info));if(e==null)throw new Error(`In local storage, there is no model with name '${this.modelPath}'`);if(e.modelTopologyType!=="JSON")throw new Error("BrowserLocalStorage does not support loading non-JSON model topology yet.");let t={},a=JSON.parse(this.LS.getItem(this.keys.topology));if(a==null)throw new Error(`In local storage, the topology of model '${this.modelPath}' is missing.`);t.modelTopology=a;let n=JSON.parse(this.LS.getItem(this.keys.weightSpecs));if(n==null)throw new Error(`In local storage, the weight specs of model '${this.modelPath}' are missing.`);t.weightSpecs=n;let r=this.LS.getItem(this.keys.modelMetadata);if(r!=null){let i=JSON.parse(r);t.format=i.format,t.generatedBy=i.generatedBy,t.convertedBy=i.convertedBy,i.signature!=null&&(t.signature=i.signature),i.userDefinedMetadata!=null&&(t.userDefinedMetadata=i.userDefinedMetadata),i.modelInitializer!=null&&(t.modelInitializer=i.modelInitializer),i.initializerSignature!=null&&(t.initializerSignature=i.initializerSignature),i.trainingConfig!=null&&(t.trainingConfig=i.trainingConfig)}let s=this.LS.getItem(this.keys.weightData);if(s==null)throw new Error(`In local storage, the binary weight values of model '${this.modelPath}' are missing.`);return t.weightData=TN(s),t}};Zs.URL_SCHEME="localstorage://";var eb=e=>B().getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(Zs.URL_SCHEME)?jN(e.slice(Zs.URL_SCHEME.length)):null;gn.registerSaveRouter(eb);gn.registerLoadRouter(eb);function jN(e){return new Zs(e)}var qN=class{constructor(){F(B().getBool("IS_BROWSER"),()=>"Current environment is not a web browser"),F(typeof window=="undefined"||typeof window.localStorage!="undefined",()=>"Current browser does not appear to support localStorage"),this.LS=window.localStorage}async listModels(){let e={},t=Ll+kr,a=kr+ZA;for(let n=0;n<this.LS.length;++n){let r=this.LS.key(n);if(r.startsWith(t)&&r.endsWith(a)){let s=GN(r);e[s]=JSON.parse(this.LS.getItem(r))}}return e}async removeModel(e){e=HN(e);let t=JA(e);if(this.LS.getItem(t.info)==null)throw new Error(`Cannot find model at path '${e}'`);let a=JSON.parse(this.LS.getItem(t.info));return QA(t),a}},Vl="://",as=class Br{constructor(){this.managers={}}static getInstance(){return Br.instance==null&&(Br.instance=new Br),Br.instance}static registerManager(t,a){F(t!=null,()=>"scheme must not be undefined or null."),t.endsWith(Vl)&&(t=t.slice(0,t.indexOf(Vl))),F(t.length>0,()=>"scheme must not be an empty string.");let n=Br.getInstance();F(n.managers[t]==null,()=>`A model store manager is already registered for scheme '${t}'.`),n.managers[t]=a}static getManager(t){let a=Br.getInstance().managers[t];if(a==null)throw new Error(`Cannot find model manager for scheme '${t}'`);return a}static getSchemes(){return Object.keys(Br.getInstance().managers)}};function th(e){if(e.indexOf(Vl)===-1)throw new Error(`The url string provided does not contain a scheme. Supported schemes are: ${as.getSchemes().join(",")}`);return{scheme:e.split(Vl)[0],path:e.split(Vl)[1]}}async function tb(e,t,a=!1){F(e!==t,()=>`Old path and new path are the same: '${e}'`);let n=gn.getLoadHandlers(e);F(n.length>0,()=>`Copying failed because no load handler is found for source URL ${e}.`),F(n.length<2,()=>`Copying failed because more than one (${n.length}) load handlers for source URL ${e}.`);let r=n[0],s=gn.getSaveHandlers(t);F(s.length>0,()=>`Copying failed because no save handler is found for destination URL ${t}.`),F(s.length<2,()=>`Copying failed because more than one (${n.length}) save handlers for destination URL ${t}.`);let i=s[0],o=th(e).scheme,l=th(e).path,u=o===th(e).scheme,p=await r.load();a&&u&&await as.getManager(o).removeModel(l);let c=await i.save(p);return a&&!u&&await as.getManager(o).removeModel(l),c.modelArtifactsInfo}async function XN(){let e=as.getSchemes(),t={};for(let a of e){let n=await as.getManager(a).listModels();for(let r in n){let s=a+Vl+r;t[s]=n[r]}}return t}async function KN(e){let t=th(e);return as.getManager(t.scheme).removeModel(t.path)}async function YN(e,t){return tb(e,t,!1)}async function ZN(e,t){return tb(e,t,!0)}var JN=class{constructor(){this.messageName="setTimeoutCustom",this.functionRefs=[],this.handledMessageCount=0,this.hasEventListener=!1}fetch(e,t){return fetch(e,t)}now(){return performance.now()}encode(e,t){if(t!=="utf-8"&&t!=="utf8")throw new Error(`Browser's encoder only supports utf-8, but got ${t}`);return this.textEncoder==null&&(this.textEncoder=new TextEncoder),this.textEncoder.encode(e)}decode(e,t){return new TextDecoder(t).decode(e)}setTimeoutCustom(e,t){if(typeof window=="undefined"||!B().getBool("USE_SETTIMEOUTCUSTOM")){setTimeout(e,t);return}this.functionRefs.push(e),setTimeout(()=>{window.postMessage({name:this.messageName,index:this.functionRefs.length-1},"*")},t),this.hasEventListener||(this.hasEventListener=!0,window.addEventListener("message",a=>{if(a.source===window&&a.data.name===this.messageName){a.stopPropagation();let n=this.functionRefs[a.data.index];n(),this.handledMessageCount++,this.handledMessageCount===this.functionRefs.length&&(this.functionRefs=[],this.handledMessageCount=0)}},!0))}isTypedArray(e){return EA(e)}};if(B().get("IS_BROWSER")){B().setPlatform("browser",new JN);try{as.registerManager(Zs.URL_SCHEME,new qN)}catch(e){}try{as.registerManager(Ys.URL_SCHEME,new LN)}catch(e){}}var QN={importFetch:()=>GC()},X2,eR=class{constructor(){this.util=HC(),this.textEncoder=new this.util.TextEncoder}fetch(e,t){return B().global.fetch!=null?B().global.fetch(e,t):(X2==null&&(X2=QN.importFetch()),X2(e,t))}now(){let e=process.hrtime();return e[0]*1e3+e[1]/1e6}encode(e,t){if(t!=="utf-8"&&t!=="utf8")throw new Error(`Node built-in encoder only supports utf-8, but got ${t}`);return this.textEncoder.encode(e)}decode(e,t){return e.length===0?"":new this.util.TextDecoder(t).decode(e)}isTypedArray(e){return this.util.types.isFloat32Array(e)||this.util.types.isInt32Array(e)||this.util.types.isUint8Array(e)||this.util.types.isUint8ClampedArray(e)}};B().get("IS_NODE")&&!B().get("IS_BROWSER")&&B().setPlatform("node",new eR);function _e(e,t="float32",a){return t=t||"float32",an(e),new Vt(e,t,a)}function tR(e,t){let a=R(e,"x","cast");if(!wA(t))throw new Error(`Failed to cast to unknown dtype ${t}`);if(t==="string"&&a.dtype!=="string"||t!=="string"&&a.dtype==="string")throw new Error("Only strings can be casted to strings");let n={x:a},r={dtype:t};return L.runKernel(bi,n,r)}var Ue=z({cast_:tR});function aR(e){let t={x:R(e,"x","clone","string_or_numeric")};return L.runKernel(qi,t)}var Ia=z({clone_:aR});function pg(e,t=!1){console.log(e.toString(t))}WA();var nR={buffer:_e,cast:Ue,clone:Ia,print:pg};tN(nR);function rR(e,t){let a=R(e,"a","add"),n=R(t,"b","add");[a,n]=Rt(a,n);let r={a,b:n};return L.runKernel(ls,r)}var we=z({add_:rR});function sR(e,t){let a=R(e,"a","floorDiv"),n=R(t,"b","floorDiv");[a,n]=Rt(a,n);let r={a,b:n};return L.runKernel(Vi,r)}var zp=z({floorDiv_:sR});function iR(e,t){let a=R(e,"a","div"),n=R(t,"b","div");if([a,n]=Rt(a,n),a.dtype==="int32"&&n.dtype==="int32")return zp(a,n);let r={a,b:n},s={};return L.runKernel(_i,r,s)}var ve=z({div_:iR});function oR(e,t){let a=R(e,"a","mul"),n=R(t,"b","mul");[a,n]=Rt(a,n);let r={a,b:n};return L.runKernel(yo,r)}var te=z({mul_:oR});function lR(e){let t=R(e,"x","abs");if(t.dtype==="complex64"){let a={x:t};return L.runKernel(hp,a)}else{let a={x:t};return L.runKernel(ou,a)}}var Za=z({abs_:lR});function uR(e){let t={x:R(e,"x","acos")};return L.runKernel(oi,t)}var ab=z({acos_:uR});function dR(e){let t={x:R(e,"x","acosh")};return L.runKernel(li,t)}var nb=z({acosh_:dR});function pR(e){F(Array.isArray(e),()=>"The argument passed to tf.addN() must be a list of tensors"),F(e.length>=1,()=>`Must pass at least one tensor to tf.addN(), but got ${e.length}`);let t=e.map((r,s)=>R(r,`tensors${s}`,"addN")),a=t[0];t.forEach(r=>{if(r.dtype!==a.dtype)throw new Error("All tensors passed to tf.addN() must have the same dtype")}),t.forEach(r=>{if(!Nr(r.shape,a.shape))throw new Error("All tensors passed to tf.addN() must have the same shape")});let n=t;return L.runKernel(ui,n)}var Dh=z({addN_:pR});function cR(e,t=null,a=!1){let n={x:R(e,"x","all","bool")},r={axis:t,keepDims:a};return L.runKernel(di,n,r)}var rb=z({all_:cR});function hR(e,t=null,a=!1){let n={x:R(e,"x","any","bool")},r={axis:t,keepDims:a};return L.runKernel(pi,n,r)}var sb=z({any_:hR});function mR(e,t=0){let a={x:R(e,"x","argMax")},n={axis:t};return L.runKernel(lu,a,n)}var ir=z({argMax_:mR});function fR(e,t=0){let a={x:R(e,"x","argMin")},n={axis:t};return L.runKernel(uu,a,n)}var ib=z({argMin_:fR});function gR(e){let t={x:R(e,"x","asin")};return L.runKernel(ci,t)}var ob=z({asin_:gR});function yR(e){let t={x:R(e,"x","asinh")};return L.runKernel(hi,t)}var lb=z({asinh_:yR});function xR(e){let t={x:R(e,"x","atan")};return L.runKernel(mi,t)}var ub=z({atan_:xR});function AR(e,t){let a=R(e,"a","atan2"),n=R(t,"b","atan2");[a,n]=Rt(a,n);let r={a,b:n};return L.runKernel(gi,r)}var db=z({atan2_:AR});function bR(e){let t={x:R(e,"x","atanh")};return L.runKernel(fi,t)}var pb=z({atanh_:bR});function vR(e,t,a,n,r="NHWC",s){let i=e[3],o=[...t,i],l=mb(r);return Lp(e,o,a,s,n,null,null,l)}function cb(e,t,a,n,r,s,i="channelsLast"){let[o,l]=jd(t),u;if(i==="channelsLast")u=[o,l,e[3],e[3]];else if(i==="channelsFirst")u=[o,l,e[1],e[1]];else throw new Error(`Unknown dataFormat ${i}`);return Lp(e,u,a,n,r,s,!1,i)}function wR(e,t,a,n,r,s,i="NDHWC"){let[o,l,u]=m1(t),p,c;if(i==="NDHWC")c="channelsLast",p=[o,l,u,e[4],e[4]];else if(i==="NCDHW")c="channelsFirst",p=[o,l,u,e[1],e[1]];else throw new Error(`Unknown dataFormat ${i}`);return hb(e,p,a,n,r,!1,c,s)}function Lp(e,t,a,n,r,s,i=!1,o="channelsLast"){let[l,u,p,c]=[-1,-1,-1,-1];if(o==="channelsLast")[l,u,p,c]=e;else if(o==="channelsFirst")[l,c,u,p]=e;else throw new Error(`Unknown dataFormat ${o}`);let[d,h,,m]=t,[f,g]=jd(a),[y,x]=jd(n),A=Ul(d,y),b=Ul(h,x),{padInfo:w,outHeight:I,outWidth:T}=SR(r,u,p,f,g,A,b,s,o),N=i?m*c:m,M;return o==="channelsFirst"?M=[l,N,I,T]:o==="channelsLast"&&(M=[l,I,T,N]),{batchSize:l,dataFormat:o,inHeight:u,inWidth:p,inChannels:c,outHeight:I,outWidth:T,outChannels:N,padInfo:w,strideHeight:f,strideWidth:g,filterHeight:d,filterWidth:h,effectiveFilterHeight:A,effectiveFilterWidth:b,dilationHeight:y,dilationWidth:x,inShape:e,outShape:M,filterShape:t}}function hb(e,t,a,n,r,s=!1,i="channelsLast",o){let[l,u,p,c,d]=[-1,-1,-1,-1,-1];if(i==="channelsLast")[l,u,p,c,d]=e;else if(i==="channelsFirst")[l,d,u,p,c]=e;else throw new Error(`Unknown dataFormat ${i}`);let[h,m,f,,g]=t,[y,x,A]=m1(a),[b,w,I]=m1(n),T=Ul(h,b),N=Ul(m,w),M=Ul(f,I),{padInfo:$,outDepth:E,outHeight:S,outWidth:_}=CR(r,u,p,c,y,x,A,T,N,M,o),O=s?g*d:g,W;return i==="channelsFirst"?W=[l,O,E,S,_]:i==="channelsLast"&&(W=[l,E,S,_,O]),{batchSize:l,dataFormat:i,inDepth:u,inHeight:p,inWidth:c,inChannels:d,outDepth:E,outHeight:S,outWidth:_,outChannels:O,padInfo:$,strideDepth:y,strideHeight:x,strideWidth:A,filterDepth:h,filterHeight:m,filterWidth:f,effectiveFilterDepth:T,effectiveFilterHeight:N,effectiveFilterWidth:M,dilationDepth:b,dilationHeight:w,dilationWidth:I,inShape:e,outShape:W,filterShape:t}}function kR(e,t,a,n,r){n==null&&(n=cg(e,t,a));let s=e[0],i=e[1],o=qd((s-t+2*n)/a+1,r),l=qd((i-t+2*n)/a+1,r);return[o,l]}function IR(e,t,a,n,r,s){r==null&&(r=cg(e,t[0],n[0]));let i=[0,0,0,a];for(let o=0;o<3;o++)e[o]+2*r>=t[o]&&(i[o]=qd((e[o]-t[o]+2*r)/n[o]+1,s));return i}function cg(e,t,a,n=1){let r=Ul(t,n);return Math.floor((e[0]*(a-1)-a+r)/2)}function jd(e){return typeof e=="number"?[e,e,e]:e.length===2?[e[0],e[1],1]:e}function m1(e){return typeof e=="number"?[e,e,e]:e}function Ul(e,t){return t<=1?e:e+(e-1)*(t-1)}function SR(e,t,a,n,r,s,i,o,l){let u,p,c;if(typeof e=="number"){u={top:e,bottom:e,left:e,right:e,type:e===0?"VALID":"NUMBER"};let d=kR([t,a],s,n,e,o);p=d[0],c=d[1]}else if(e==="same"){p=Math.ceil(t/n),c=Math.ceil(a/r);let d=Math.max(0,(p-1)*n+s-t),h=Math.max(0,(c-1)*r+i-a),m=Math.floor(d/2),f=d-m,g=Math.floor(h/2),y=h-g;u={top:m,bottom:f,left:g,right:y,type:"SAME"}}else if(e==="valid")u={top:0,bottom:0,left:0,right:0,type:"VALID"},p=Math.ceil((t-s+1)/n),c=Math.ceil((a-i+1)/r);else if(typeof e=="object"){let d=l==="channelsLast"?e[1][0]:e[2][0],h=l==="channelsLast"?e[1][1]:e[2][1],m=l==="channelsLast"?e[2][0]:e[3][0],f=l==="channelsLast"?e[2][1]:e[3][1];u={top:d,bottom:h,left:m,right:f,type:d===0&&h===0&&m===0&&f===0?"VALID":"EXPLICIT"},p=qd((t-s+d+h)/n+1,o),c=qd((a-i+m+f)/r+1,o)}else throw Error(`Unknown padding parameter: ${e}`);return{padInfo:u,outHeight:p,outWidth:c}}function CR(e,t,a,n,r,s,i,o,l,u,p){let c,d,h,m;if(e==="valid"&&(e=0),typeof e=="number"){c={top:e,bottom:e,left:e,right:e,front:e,back:e,type:e===0?"VALID":"NUMBER"};let f=IR([t,a,n,1],[o,l,u],1,[r,s,i],e,p);d=f[0],h=f[1],m=f[2]}else if(e==="same"){d=Math.ceil(t/r),h=Math.ceil(a/s),m=Math.ceil(n/i);let f=(d-1)*r+o-t,g=(h-1)*s+l-a,y=(m-1)*i+u-n,x=Math.floor(f/2),A=f-x,b=Math.floor(g/2),w=g-b,I=Math.floor(y/2),T=y-I;c={top:b,bottom:w,left:I,right:T,front:x,back:A,type:"SAME"}}else throw Error(`Unknown padding parameter: ${e}`);return{padInfo:c,outDepth:d,outHeight:h,outWidth:m}}function qd(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 Xd(e){let[t,a,n]=jd(e);return t===1&&a===1&&n===1}function Er(e,t){return Xd(e)||Xd(t)}function Js(e){return jd(e).every(t=>t>0)}function mb(e){if(e==="NHWC")return"channelsLast";if(e==="NCHW")return"channelsFirst";throw new Error(`Unknown dataFormat ${e}`)}function Nn(e,t,a){if(a!=null){if(typeof t=="string")throw Error(`Error in ${e}: pad must be an integer when using dimRoundingMode ${a} but got pad ${t}.`);if(typeof t=="number")F(jl(t),()=>`Error in ${e}: pad must be an integer when using dimRoundingMode ${a} but got pad ${t}.`);else if(typeof t=="object")t.forEach(n=>{n.forEach(r=>{F(jl(r),()=>`Error in ${e}: pad must be an integer when using dimRoundingMode ${a} but got pad ${r}.`)})});else throw Error(`Error in ${e}: Unknown padding parameter: ${t}`)}}function TR(e,t){let a={x:R(e,"x","reshape","string_or_numeric")},n={shape:t};return L.runKernel(Eu,a,n)}var Q=z({reshape_:TR});function NR(e,t,a,n,r){let s=R(e,"x","avgPool","float32"),i=1;F(Er(a,i),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${a} and dilations '${i}'`);let o=s,l=!1;s.rank===3&&(l=!0,o=Q(s,[1,s.shape[0],s.shape[1],s.shape[2]])),F(o.rank===4,()=>`Error in avgPool: x must be rank 4 but got rank ${o.rank}.`),Nn("avgPool",n,r);let u={x:o},p={filterSize:t,strides:a,pad:n,dimRoundingMode:r},c=L.runKernel(yi,u,p);return c=Ue(c,s.dtype),l?Q(c,[c.shape[1],c.shape[2],c.shape[3]]):c}var hg=z({avgPool_:NR});function RR(e,t,a,n,r,s="NDHWC"){let i=R(e,"x","avgPool3d","float32"),o=i,l=!1;i.rank===4&&(l=!0,o=Q(i,[1,i.shape[0],i.shape[1],i.shape[2],i.shape[3]])),F(o.rank===5,()=>`Error in avgPool3d: x must be rank 5 but got rank ${o.rank}.`),F(s==="NDHWC",()=>`Error in avgPool3d: Only NDHWC is currently supported, but got dataFormat of ${s}`),F(typeof a=="number"&&a>0||Array.isArray(a)&&a[0]>0&&a[1]>0&&a[2]>0,()=>`Error in avgPool3d: Stride must be > 0, but got '${a}'`),Nn("avgPool3d",n,r);let u={x:o},p={filterSize:t,strides:a,pad:n,dimRoundingMode:r,dataFormat:s},c=L.runKernel(du,u,p);return c=Ue(c,o.dtype),l?Q(c,[c.shape[1],c.shape[2],c.shape[3],c.shape[4]]):c}var fb=z({avgPool3d_:RR});function ER(e,t=0){F(e.length>=1,()=>"Pass at least one tensor to concat");let a=Hd(e,"tensors","concat","string_or_numeric");if(a[0].dtype==="complex64"&&a.forEach(s=>{if(s.dtype!=="complex64")throw new Error(`Cannot concatenate complex64 tensors with a tensor
          with dtype ${s.dtype}. `)}),a.length===1)return Ia(a[0]);let n=a,r={axis:t};return L.runKernel(mu,n,r)}var lt=z({concat_:ER});function MR(e,t,a=!1,n=!1){let r=R(e,"a","matMul"),s=R(t,"b","matMul");[r,s]=Rt(r,s);let i={a:r,b:s},o={transposeA:a,transposeB:n};return L.runKernel(xi,i,o)}var pt=z({matMul_:MR});function $R(e){let t={x:R(e,"x","sigmoid","float32")};return L.runKernel(Bo,t)}var za=z({sigmoid_:$R});function PR(e,t,a){let n=R(e,"x","slice","string_or_numeric");if(n.rank===0)throw new Error("Slicing scalar is not possible");let r={x:n},s={begin:t,size:a};return L.runKernel(_u,r,s)}var Fe=z({slice_:PR});function _R(e){let t={x:R(e,"x","tanh","float32")};return L.runKernel(Zo,t)}var hh=z({tanh_:_R});function FR(e,t,a,n,r,s){let i=R(e,"forgetBias","basicLSTMCell"),o=R(t,"lstmKernel","basicLSTMCell"),l=R(a,"lstmBias","basicLSTMCell"),u=R(n,"data","basicLSTMCell"),p=R(r,"c","basicLSTMCell"),c=R(s,"h","basicLSTMCell"),d=lt([u,c],1),h=pt(d,o),m=we(h,l),f=m.shape[0],g=m.shape[1]/4,y=[f,g],x=Fe(m,[0,0],y),A=Fe(m,[0,g],y),b=Fe(m,[0,g*2],y),w=Fe(m,[0,g*3],y),I=we(te(za(x),hh(A)),te(p,za(we(i,b)))),T=te(hh(I),za(w));return[I,T]}var gb=z({basicLSTMCell_:FR});function DR(e,t,a){let n=R(e,"x","batchToSpaceND"),r=t.reduce((o,l)=>o*l);F(n.rank>=1+t.length,()=>`input rank is ${n.rank} but should be > than blockShape.length ${t.length}`),F(a.length===t.length,()=>`crops.length is ${a.length} but should be equal to blockShape.length  ${t.length}`),F(n.shape[0]%r===0,()=>`input tensor batch is ${n.shape[0]} but is not divisible by the product of the elements of blockShape ${t.join(" * ")} === ${r}`);let s={x:n},i={blockShape:t,crops:a};return L.runKernel(pu,s,i)}var mg=z({batchToSpaceND_:DR});function OR(e){let t;return e.rank===0||e.rank===1?t=Q(e,[1,1,1,e.size]):e.rank===2?t=Q(e,[1,1,e.shape[0],e.shape[1]]):e.rank===3?t=Q(e,[1,e.shape[0],e.shape[1],e.shape[2]]):t=e,t}function zR(e,t,a,n,r,s){s==null&&(s=.001);let i=R(e,"x","batchNorm"),o=R(t,"mean","batchNorm"),l=R(a,"variance","batchNorm"),u;r!=null&&(u=R(r,"scale","batchNorm"));let p;n!=null&&(p=R(n,"offset","batchNorm")),F(o.rank===l.rank,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),F(p==null||o.rank===p.rank,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),F(u==null||o.rank===u.rank,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let c={x:OR(i),scale:u,offset:p,mean:o,variance:l},d={varianceEpsilon:s},h=L.runKernel(Ui,c,d);return Q(h,i.shape)}var Wp=z({batchNorm_:zR});function LR(e,t,a,n,r,s){let i=R(e,"x","batchNorm"),o=R(t,"mean","batchNorm"),l=R(a,"variance","batchNorm"),u;r!=null&&(u=R(r,"scale","batchNorm"));let p;return n!=null&&(p=R(n,"offset","batchNorm")),F(i.rank===2,()=>`Error in batchNorm2D: x must be rank 2 but got rank ${i.rank}.`),F(o.rank===2||o.rank===1,()=>`Error in batchNorm2D: mean must be rank 2 or rank 1 but got rank ${o.rank}.`),F(l.rank===2||l.rank===1,()=>`Error in batchNorm2D: variance must be rank 2 or rank 1 but got rank ${l.rank}.`),u!=null&&F(u.rank===2||u.rank===1,()=>`Error in batchNorm2D: scale must be rank 2 or rank 1 but got rank ${u.rank}.`),p!=null&&F(p.rank===2||p.rank===1,()=>`Error in batchNorm2D: offset must be rank 2 or rank 1 but got rank ${p.rank}.`),Wp(i,o,l,p,u,s)}var yb=z({batchNorm2d_:LR});function WR(e,t,a,n,r,s){let i=R(e,"x","batchNorm"),o=R(t,"mean","batchNorm"),l=R(a,"variance","batchNorm"),u;r!=null&&(u=R(r,"scale","batchNorm"));let p;return n!=null&&(p=R(n,"offset","batchNorm")),F(i.rank===3,()=>`Error in batchNorm3D: x must be rank 3 but got rank ${i.rank}.`),F(o.rank===3||o.rank===1,()=>`Error in batchNorm3D: mean must be rank 3 or rank 1 but got rank ${o.rank}.`),F(l.rank===3||l.rank===1,()=>`Error in batchNorm3D: variance must be rank 3 or rank 1 but got rank ${l.rank}.`),u!=null&&F(u.rank===3||u.rank===1,()=>`Error in batchNorm3D: scale must be rank 3 or rank 1 but got rank ${u.rank}.`),p!=null&&F(p.rank===3||p.rank===1,()=>`Error in batchNorm3D: offset must be rank 3 or rank 1 but got rank ${p.rank}.`),Wp(i,o,l,p,u,s)}var xb=z({batchNorm3d_:WR});function BR(e,t,a,n,r,s){let i=R(e,"x","batchNorm"),o=R(t,"mean","batchNorm"),l=R(a,"variance","batchNorm"),u;r!=null&&(u=R(r,"scale","batchNorm"));let p;return n!=null&&(p=R(n,"offset","batchNorm")),F(i.rank===4,()=>`Error in batchNorm4D: x must be rank 4 but got rank ${i.rank}.`),F(o.rank===4||o.rank===1,()=>`Error in batchNorm4D: mean must be rank 4 or rank 1 but got rank ${o.rank}.`),F(l.rank===4||l.rank===1,()=>`Error in batchNorm4D: variance must be rank 4 or rank 1 but got rank ${l.rank}.`),u!=null&&F(u.rank===4||u.rank===1,()=>`Error in batchNorm4D: scale must be rank 4 or rank 1 but got rank ${u.rank}.`),p!=null&&F(p.rank===4||p.rank===1,()=>`Error in batchNorm4D: offset must be rank 4 or rank 1 but got rank ${p.rank}.`),Wp(i,o,l,p,u,s)}var Ab=z({batchNorm4d_:BR});function VR(e,t,a){let n=R(e,"x","bincount"),r=R(t,"weights","bincount");F(n.dtype==="int32",()=>`Error in bincount: input dtype must be int32, but got ${n.dtype}`),F(a>=0,()=>`size must be non-negative, but got ${a}.`),F(r.size===n.size||r.size===0,()=>`Error in bincount: weights must have the same size as input or0-length, but got input shape: ${n.shape}, weights shape: ${r.shape}.`);let s={x:n,weights:r},i={size:a};return L.runKernel(Ai,s,i)}var fg=z({bincount_:VR});function UR(e,t){let a=R(e,"x","bitwiseAnd"),n=R(t,"y","bitwiseAnd");if(!Nr(a.shape,n.shape))throw new Error(`BitwiseAnd: Tensors must have the same shape. x: ${a.shape}, y: ${n.shape}`);if(a.dtype!=="int32"||n.dtype!=="int32")throw new Error(`BitwiseAnd: Only supports 'int32' values in tensor, found type of x: ${a.dtype} and type of y: ${n.dtype}`);let r={a,b:n};return L.runKernel(cu,r)}var bb=z({bitwiseAnd_:UR});function GR(e,t){let a=R(e,"s0","broadcastArgs","int32"),n=R(t,"s1","broadcastArgs","int32");if(a.rank!==1)throw new Error(`broadcastArgs(): first input must be a vector (rank=1). Has rank ${a.rank}`);if(n.rank!==1)throw new Error(`broadcastArgs(): second input must be a vector (rank=1). Has rank ${n.rank}`);let r={s0:a,s1:n};return L.runKernel(hu,r)}var vb=z({broadcastArgs_:GR});function HR(e,t){let a=R(e,"broadcastTo","x"),n=a.shape;if(an(t),t.length<a.rank)throw new Error(`broadcastTo(): shape.length=${t.length} < input.rank=${a.rank}.`);if(t.length>a.rank){let l=a.shape.slice();for(;l.length<t.length;)l.unshift(1);a=Q(a,l)}let r=a.shape,s=Array.from(t);for(let l=t.length-1;l>=0;l--)if(r[l]===t[l])s[l]=1;else if(a.shape[l]!==1)throw new Error(`broadcastTo(): [${n}] cannot be broadcast to [${t}].`);if(s.map((l,u)=>l>1?u:-1).filter(l=>l>=0).length===0)return Ia(a);let i={x:a},o={reps:s};return L.runKernel(ds,i,o)}var Gl=z({broadcastTo_:HR});function jR(e){let t={x:R(e,"x","ceil","float32")};return L.runKernel(vi,t)}var wb=z({ceil_:jR});function or(e,t,a){an(e),a=a||up(t);let n={shape:e,value:t,dtype:a};return L.runKernel(bu,{},n)}function qR(e,t,a){let n=R(e,"x","clipByValue");if(F(t<=a,()=>`Error in clip: min (${t}) must be less than or equal to max (${a}).`),t===a)return or(n.shape,t,n.dtype);let r={x:n},s={clipValueMin:t,clipValueMax:a};return L.runKernel(us,r,s)}var kb=z({clipByValue_:qR});function XR(e){return lt(e,0)}var Ib=z({concat1d_:XR});function KR(e,t){return lt(e,t)}var Uu=z({concat2d_:KR});function YR(e,t){return lt(e,t)}var Sb=z({concat3d_:YR});function ZR(e,t){return lt(e,t)}var Cb=z({concat4d_:ZR});function JR(e,t,a,n,r="NHWC",s=[1,1],i){let o=R(e,"x","conv2d","float32"),l=R(t,"filter","conv2d","float32"),u=o,p=!1;o.rank===3&&(p=!0,u=Q(o,[1,o.shape[0],o.shape[1],o.shape[2]])),F(u.rank===4,()=>`Error in conv2d: input must be rank 4, but got rank ${u.rank}.`),F(l.rank===4,()=>`Error in conv2d: filter must be rank 4, but got rank ${l.rank}.`),Nn("conv2d",n,i);let c=r==="NHWC"?u.shape[3]:u.shape[1];F(c===l.shape[2],()=>`Error in conv2d: depth of input (${c}) must match input depth for filter ${l.shape[2]}.`),F(Er(a,s),()=>`Error in conv2D: Either strides or dilations must be 1. Got strides ${a} and dilations '${s}'`),F(Js(s),()=>"Error in conv2D: Dilated rates should be larger than 0."),F(Js(a),()=>"Error in conv2D: Strides should be larger than 0.");let d={x:u,filter:l},h={strides:a,pad:n,dataFormat:r,dilations:s,dimRoundingMode:i},m=L.runKernel(wi,d,h);return p?Q(m,[m.shape[1],m.shape[2],m.shape[3]]):m}var Bp=z({conv2d_:JR});function QR(e,t,a,n,r="NWC",s=1,i){let o=R(e,"x","conv1d"),l=R(t,"filter","conv1d"),u=o,p=!1;o.rank===2&&(p=!0,u=Q(o,[1,o.shape[0],o.shape[1]])),F(u.rank===3,()=>`Error in conv1d: input must be rank 3, but got rank ${u.rank}.`),F(l.rank===3,()=>`Error in conv1d: filter must be rank 3, but got rank ${l.rank}.`),Nn("conv1d",n,i),F(u.shape[2]===l.shape[1],()=>`Error in conv1d: depth of input (${u.shape[2]}) must match input depth for filter ${l.shape[1]}.`),F(Er(a,s),()=>`Error in conv1D: Either stride or dilation must be 1. Got stride ${a} and dilation '${s}'`),F(Js(s),()=>"Error in conv1D: Dilated rates should be larger than 0."),F(Js(a),()=>"Error in conv1D: Stride should be larger than 0."),F(r==="NWC",()=>`Error in conv1d: got dataFormat of ${r} but only NWC is currently supported.`);let c=Q(l,[1,l.shape[0],l.shape[1],l.shape[2]]),d=Q(u,[u.shape[0],1,u.shape[1],u.shape[2]]),h=Bp(d,c,[1,a],n,"NHWC",[1,s],i);return p?Q(h,[h.shape[2],h.shape[3]]):Q(h,[h.shape[0],h.shape[2],h.shape[3]])}var Tb=z({conv1d_:QR});function eE(e,t,a,n,r,s="NHWC",i){F(e.length===t.rank,()=>`Length of inShape (${e.length}) and rank of dy (${t.rank}) must match`);let o=e,l=t,u=!1;t.rank===3&&(u=!0,l=Q(t,[1,t.shape[0],t.shape[1],t.shape[2]]),o=[1,e[0],e[1],e[2]]),F(o.length===4,()=>`Error in conv2dDerInput: inShape must be length 4, but got length ${o.length}.`),F(l.rank===4,()=>`Error in conv2dDerInput: dy must be rank 4, but got rank ${l.rank}`),F(a.rank===4,()=>`Error in conv2dDerInput: filter must be rank 4, but got rank ${a.rank}`);let p=s==="NHWC"?o[3]:o[1],c=s==="NHWC"?l.shape[3]:l.shape[1];F(p===a.shape[2],()=>`Error in conv2dDerInput: depth of input (${p}) must match input depth for filter ${a.shape[2]}.`),F(c===a.shape[3],()=>`Error in conv2dDerInput: depth of output (${c}) must match output depth for filter ${a.shape[3]}.`),Nn("conv2dDerInput",r,i);let d={dy:l,filter:a},h={strides:n,pad:r,dataFormat:s,dimRoundingMode:i,inputShape:o},m=L.runKernel(ki,d,h);return u?Q(m,[m.shape[1],m.shape[2],m.shape[3]]):m}var Nb=z({conv2DBackpropInput_:eE});function tE(e,t,a,n,r,s){let i=R(e,"x","conv2dTranspose"),o=R(t,"filter","conv2dTranspose");return Nb(a,i,o,n,r,"NHWC",s)}var Rb=z({conv2dTranspose_:tE});function aE(e,t,a,n,r="NDHWC",s=[1,1,1]){let i=R(e,"x","conv3d"),o=R(t,"filter","conv3d"),l=i,u=!1;i.rank===4&&(u=!0,l=Q(i,[1,i.shape[0],i.shape[1],i.shape[2],i.shape[3]])),F(l.rank===5,()=>`Error in conv3d: input must be rank 5, but got rank ${l.rank}.`),F(o.rank===5,()=>`Error in conv3d: filter must be rank 5, but got rank ${o.rank}.`),F(l.shape[4]===o.shape[3],()=>`Error in conv3d: depth of input (${l.shape[4]}) must match input depth for filter ${o.shape[3]}.`),F(Er(a,s),()=>`Error in conv3D: Either strides or dilations must be 1. Got strides ${a} and dilations '${s}'`),F(r==="NDHWC",()=>`Error in conv3d: got dataFormat of ${r} but only NDHWC is currently supported.`),F(Js(s),()=>"Error in conv3D: Dilated rates should be larger than 0."),F(Js(a),()=>"Error in conv3D: Strides should be larger than 0.");let p={x:l,filter:o},c={strides:a,pad:n,dataFormat:r,dilations:s},d=L.runKernel(Ii,p,c);return u?Q(d,[d.shape[1],d.shape[2],d.shape[3],d.shape[4]]):d}var Eb=z({conv3d_:aE});function nE(e,t,a,n,r){F(e.length===t.rank,()=>`Length of inShape (${e.length}) and rank of dy (${t.rank}) must match`);let s=e,i=t,o=!1;t.rank===4&&(o=!0,i=Q(t,[1,t.shape[0],t.shape[1],t.shape[2],t.shape[3]]),s=[1,e[0],e[1],e[2],e[3]]);let l=s[4],u=i.shape[4];F(s.length===5,()=>`Error in conv3dDerInput: inShape must be length 5, but got length ${s.length}.`),F(i.rank===5,()=>`Error in conv3dDerInput: dy must be rank 5, but got rank ${i.rank}`),F(a.rank===5,()=>`Error in conv3dDerInput: filter must be rank 5, but got rank ${a.rank}`),F(l===a.shape[3],()=>`Error in conv3dDerInput: depth of input (${l}) must match input depth for filter ${a.shape[3]}.`),F(u===a.shape[4],()=>`Error in conv3dDerInput: depth of output (${u}) must match output depth for filter ${a.shape[4]}.`);let p={dy:i,filter:a},c={pad:r,strides:n,inputShape:s},d=L.runKernel(Si,p,c);return o?Q(d,[d.shape[1],d.shape[2],d.shape[3],d.shape[4]]):d}var rE=z({conv3DBackpropInput_:nE});function sE(e,t,a,n,r){let s=R(e,"x","conv3dTranspose"),i=R(t,"filter","conv3dTranspose");return rE(a,s,i,n,r)}var Mb=z({conv3dTranspose_:sE});function iE(e){let t={x:R(e,"x","cos","float32")};return L.runKernel(Ci,t)}var $b=z({cos_:iE});function oE(e){let t={x:R(e,"x","cosh","float32")};return L.runKernel(Ti,t)}var Pb=z({cosh_:oE});function lE(e,t=0,a=!1,n=!1){let r={x:R(e,"x","cumprod")},s={axis:t,exclusive:a,reverse:n};return L.runKernel(Ni,r,s)}var _b=z({cumprod_:lE});function uE(e,t=0,a=!1,n=!1){let r={x:R(e,"x","cumsum")},s={axis:t,exclusive:a,reverse:n};return L.runKernel(Ri,r,s)}var Fb=z({cumsum_:uE});function dE(e,t,a,n=!1){let r=R(e,"x","denseBincount"),s=R(t,"weights","denseBincount");F(r.dtype==="int32",()=>`Error in denseBincount: input dtype must be int32, but got ${r.dtype}`),F(r.rank<=2,()=>`Error in denseBincount: input must be at most rank 2, but got rank ${r.rank}.`),F(a>=0,()=>`size must be non-negative, but got ${a}.`),F(s.size===r.size||s.size===0,()=>`Error in denseBincount: weights must have the same shape as x or 0-length, but got x shape: ${r.shape}, weights shape: ${s.shape}.`);let i={x:r,weights:s},o={size:a,binaryOutput:n};return L.runKernel(gu,i,o)}var Db=z({denseBincount_:dE});function pE(e,t,a="NHWC"){let n=R(e,"x","depthToSpace","float32"),r=a==="NHWC"?n.shape[1]:n.shape[2],s=a==="NHWC"?n.shape[2]:n.shape[3],i=a==="NHWC"?n.shape[3]:n.shape[1];F(t>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${t}`),F(r*t>=0,()=>`Negative dimension size caused by overflow when multiplying
    ${r} and ${t}  for depthToSpace with input shape
    ${n.shape}`),F(s*t>=0,()=>`Negative dimension size caused by overflow when multiplying
    ${s} and ${t} for depthToSpace with input shape
        ${n.shape}`),F(i%(t*t)===0,()=>`Dimension size must be evenly divisible by ${t*t} but is ${i} for depthToSpace with input shape ${n.shape}`);let o={x:n},l={blockSize:t,dataFormat:a};return L.runKernel(Mi,o,l)}var Ob=z({depthToSpace_:pE});function cE(e,t,a,n,r="NHWC",s=[1,1],i){let o=R(e,"x","depthwiseConv2d","float32"),l=R(t,"filter","depthwiseConv2d","float32"),u=o,p=!1;o.rank===3&&(p=!0,u=Q(o,[1,o.shape[0],o.shape[1],o.shape[2]])),F(u.rank===4,()=>`Error in depthwiseConv2d: input must be rank 4, but got rank ${u.rank}.`),F(l.rank===4,()=>`Error in depthwiseConv2d: filter must be rank 4, but got rank ${l.rank}.`);let c=r==="NHWC"?u.shape[3]:u.shape[1];F(c===l.shape[2],()=>`Error in depthwiseConv2d: number of input channels (${c}) must match the inChannels dimension in filter ${l.shape[2]}.`),Nn("depthwiseConv2d",n,i);let d={x:u,filter:l},h={strides:a,pad:n,dataFormat:r,dilations:s,dimRoundingMode:i},m=L.runKernel($i,d,h);return p?Q(m,[m.shape[1],m.shape[2],m.shape[3]]):m}var Oh=z({depthwiseConv2d_:cE});function hE(e){let t={x:R(e,"x","diag")};return L.runKernel(yu,t)}var zb=z({diag_:hE});function mE(e,t,a,n,r=[1,1],s="NHWC"){let i=R(e,"x","dilation2d"),o=R(t,"filter","dilation2d");F(i.rank===3||i.rank===4,()=>`Error in dilation2d: input must be rank 3 or 4, but got rank ${i.rank}.`),F(o.rank===3,()=>`Error in dilation2d: filter must be rank 3, but got rank ${o.rank}.`),F(s==="NHWC",()=>`Error in dilation2d: Only NHWC is currently supported, but got dataFormat of ${s}`);let l=i,u=!1;i.rank===3&&(l=Q(i,[1,i.shape[0],i.shape[1],i.shape[2]]),u=!0),F(l.shape[3]===o.shape[2],()=>`Error in dilation2d:  input and filter must have the same depth: ${l.shape[3]} vs ${o.shape[2]}`);let p={x:l,filter:o},c={strides:a,pad:n,dilations:r},d=L.runKernel(Pi,p,c);return u?Q(d,[d.shape[1],d.shape[2],d.shape[3]]):d}var Lb=z({dilation2d_:mE}),nl={};Ze(nl,{assertAndGetBroadcastShape:()=>Ut,getBroadcastDims:()=>Wb,getReductionAxes:()=>gg});function Wb(e,t){let a=e.length,n=[];for(let r=0;r<a;r++){let s=a-1-r,i=e[s]||1;(t[t.length-1-r]||1)>1&&i===1&&n.unshift(s)}return n}function gg(e,t){let a=[];for(let n=0;n<t.length;n++){let r=e[e.length-n-1],s=t.length-n-1,i=t[s];(r==null||r===1&&i>1)&&a.unshift(s)}return a}function Ut(e,t){let a=Math.max(e.length,t.length),n=new Array(a);for(let r=0;r<a;r++){let s=e[e.length-r-1];s==null&&(s=1);let i=t[t.length-r-1];if(i==null&&(i=1),s===1)n[a-r-1]=i;else if(i===1)n[a-r-1]=s;else if(s!==i){let o=`Operands could not be broadcast together with shapes ${e} and ${t}.`;throw Error(o)}else n[a-r-1]=s}return n}function fE(e,t){let a=R(e,"a","equal","string_or_numeric"),n=R(t,"b","equal","string_or_numeric");[a,n]=Rt(a,n),Ut(a.shape,n.shape);let r={a,b:n};return L.runKernel(Oi,r)}var yg=z({equal_:fE});function gE(e,t,a){let n=R(t,"a","where"),r=R(a,"b","where"),s=R(e,"condition","where","bool"),i=Ut(Ut(s.shape,n.shape),r.shape),o=Gl(s,i),l=Gl(n,i),u=Gl(r,i),p={condition:o,t:l,e:u};return L.runKernel(Pu,p)}var Sr=z({where_:gE});function yE(e){let t={x:R(e,"x","zerosLike")};return L.runKernel(Vu,t)}var Qa=z({zerosLike_:yE});function xE(e,t){let a=R(e,"a","div"),n=R(t,"b","div");[a,n]=Rt(a,n);let r=ve(a,n),s=Qa(r),i=yg(n,s);return Sr(i,s,r)}var Bb=z({divNoNan_:xE});function AE(e,t){let a=R(e,"t1","dot"),n=R(t,"t2","dot");F((a.rank===1||a.rank===2)&&(n.rank===1||n.rank===2),()=>`Error in dot: inputs must all be rank 1 or 2, but got ranks ${a.rank} and ${n.rank}.`);let r=a.rank===1?a.size:a.shape[1],s=n.rank===1?n.size:n.shape[0];if(F(r===s,()=>`Error in dot: inner dimensions of inputs must match, but got ${r} and ${s}.`),a.rank===1&&n.rank===1){let i=Q(a,[1,-1]),o=Q(n,[-1,1]),l=pt(i,o);return Q(l,[])}else if(a.rank===1&&n.rank===2){let i=Q(a,[1,-1]),o=Q(n,[n.shape[0],n.shape[1]]),l=pt(i,o);return Q(l,[l.size])}else if(a.rank===2&&n.rank===1){let i=Q(n,[-1,1]),o=pt(a,i);return Q(o,[o.size])}else{let i=Q(n,[n.shape[0],n.shape[1]]);return pt(a,i)}}var Vb=z({dot_:AE});function bE(e,...t){let a=t.map((r,s)=>R(r,`tensors${s}`,"einsum")),n={equation:e};return L.runKernel(xp,a,n)}var Vs=z({einsum_:bE});function vE(e){let t={x:R(e,"x","elu","float32")};return L.runKernel(Fi,t)}var xg=z({elu_:vE});function wE(e,t){let a=R(e,"x","ensureShape","string_or_numeric");if(!xA(a.shape,t))throw new Error(`EnsureShape: Shape of tensor ${a.shape} is not compatible with expected shape ${t}`);return e}var Ub=z({ensureShape_:wE});function kE(e){let t=R(e,"x","erf");F(t.dtype==="int32"||t.dtype==="float32",()=>"Input dtype must be `int32` or `float32`."),t.dtype==="int32"&&(t=Ue(t,"float32"));let a={x:t};return L.runKernel(Di,a)}var Gb=z({erf_:kE});function Ag(e,t){for(let a=0;a<e.length;++a)if(e[e.length-a-1]!==t-1-a)return!1;return!0}function Hb(e,t,a){let n=e.length+t.length,r=[],s=0,i=0;for(let o=0;o<n;o++)a.indexOf(o)===-1?r.push(e[s++]):r.push(t[i++]);return r}function IE(e,t){let a=[],n=e.length;for(let s=0;s<n;s++)t.indexOf(s)===-1&&a.push(e[s]);let r=t.map(s=>e[s]);return[a,r]}function Vp(e,t){let a=t.map(n=>1);return Hb(e,a,t)}function SE(e,t,a){F(Ag(t,a),()=>`${e} supports only inner-most axes for now. Got axes ${t} and rank-${a} input.`)}function CE(e,t){if(Ag(e,t))return null;let a=[];for(let n=0;n<t;++n)e.indexOf(n)===-1&&a.push(n);return e.forEach(n=>a.push(n)),a}function TE(e){return e.map((t,a)=>[a,t]).sort((t,a)=>t[1]-a[1]).map(t=>t[0])}function NE(e,t){let a=[];for(let n=t-e;n<t;++n)a.push(n);return a}function RE(e,t=null,a=!1){let n={x:R(e,"x","max")},r={reductionIndices:t,keepDims:a};return L.runKernel(oo,n,r)}var ga=z({max_:RE});function EE(e,t=null,a=!1){let n={x:R(e,"x","min")},r={axis:t,keepDims:a};return L.runKernel(co,n,r)}var ns=z({min_:EE});function ME(e,t){let a=R(e,"base","pow"),n=R(t,"exp","pow");[a,n]=Rt(a,n);let r={a,b:n};return L.runKernel(ko,r)}var Yl=z({pow_:ME});function Ge(e,t){if((Qt(e)&&t!=="string"||Array.isArray(e))&&t!=="complex64")throw new Error("Error creating a new Scalar: value must be a primitive (number|boolean|string)");if(t==="string"&&Qt(e)&&!(e instanceof Uint8Array))throw new Error("When making a scalar from encoded string, the value must be `Uint8Array`.");return cs(e,[],[],t)}function $E(e){let t={x:R(e,"x","sqrt","float32")};return L.runKernel(Uo,t)}var ar=z({sqrt_:$E});function PE(e){let t=R(e,"x","square"),a={};return L.runKernel("Square",{x:t},a)}var Tn=z({square_:PE});function _E(e,t=null,a=!1){let n=R(e,"x","sum");n.dtype==="bool"&&(n=Ue(n,"int32"));let r={x:n},s={axis:t,keepDims:a};return L.runKernel(Go,r,s)}var ot=z({sum_:_E});function FE(e,t="euclidean",a=null,n=!1){e=R(e,"x","norm");let r=jb(e,t,a),s=r.shape;if(n){let i=lp(a,e.shape);s=Vp(r.shape,i)}return Q(r,s)}function jb(e,t,a=null){if(e.rank===0)return Za(e);if(e.rank!==1&&a===null)return jb(Q(e,[-1]),t,a);if(e.rank===1||typeof a=="number"||Array.isArray(a)&&a.length===1){if(t===1)return ot(Za(e),a);if(t===1/0)return ga(Za(e),a);if(t===-1/0)return ns(Za(e),a);if(t==="euclidean"||t===2)return ar(ot(Yl(Za(e),Ge(2,"int32")),a));throw new Error(`Error in norm: invalid ord value: ${t}`)}if(Array.isArray(a)&&a.length===2){if(t===1)return ga(ot(Za(e),a[0]),a[1]-1);if(t===1/0)return ga(ot(Za(e),a[1]),a[0]);if(t===-1/0)return ns(ot(Za(e),a[1]),a[0]);if(t==="fro"||t==="euclidean")return ar(ot(Tn(e),a));throw new Error(`Error in norm: invalid ord value: ${t}`)}throw new Error(`Error in norm: invalid axis: ${a}`)}var Up=z({norm_:FE});function DE(e,t=null,a=!1){return Up(e,"euclidean",t,a)}var qb=z({euclideanNorm_:DE});function OE(e){let t={x:R(e,"x","exp")};return L.runKernel(zi,t)}var rs=z({exp_:OE});function zE(e,t=0){let a=R(e,"x","expandDims","string_or_numeric");F(t<=a.rank,()=>"Axis must be <= rank of the tensor");let n={input:a},r={dim:t};return L.runKernel(Au,n,r)}var Wt=z({expandDims_:zE});function LE(e){let t={x:R(e,"x","expm1")};return L.runKernel(Li,t)}var Xb=z({expm1_:LE});function WE(e,t){let a=R(e,"x","tile","string_or_numeric");F(a.rank===t.length,()=>`Error in transpose: rank of input ${a.rank} must match length of reps ${t}.`);let n={x:a},r={reps:t};return L.runKernel(ds,n,r)}var Kr=z({tile_:WE});function BE(e,t,a,n="float32"){t==null&&(t=e);let r=_e([e,t],n),s=e<=t?e:t;for(let o=0;o<s;++o)r.set(1,o,o);let i=Q(r.toTensor(),[e,t]);if(a==null)return i;if(a.length===1)return Kr(Wt(i,0),[a[0],1,1]);if(a.length===2)return Kr(Wt(Wt(i,0),0),[a[0],a[1],1,1]);if(a.length===3)return Kr(Wt(Wt(Wt(i,0),0),0),[a[0],a[1],a[2],1,1]);throw new Error(`eye() currently supports only 1D and 2D batchShapes, but received ${a.length}D.`)}var bg=z({eye_:BE});function VE(e){let t={x:R(e,"x","floor","float32")};return L.runKernel(Bi,t)}var vg=z({floor_:VE});function UE(e,t,a=0,n=0){let r=R(e,"x","gather"),s=R(t,"indices","gather","int32"),i={x:r,indices:s},o={axis:a,batchDims:n};return L.runKernel(vu,i,o)}var wg=z({gather_:UE});function GE(e,t){let a=R(e,"a","greater","string_or_numeric"),n=R(t,"b","greater","string_or_numeric");[a,n]=Rt(a,n),Ut(a.shape,n.shape);let r={a,b:n};return L.runKernel(Hi,r)}var Gp=z({greater_:GE});function HE(e,t){let a=R(e,"a","greaterEqual","string_or_numeric"),n=R(t,"b","greaterEqual","string_or_numeric");[a,n]=Rt(a,n),Ut(a.shape,n.shape);let r={a,b:n};return L.runKernel(ji,r)}var kg=z({greaterEqual_:HE});function jE(e){let t={input:R(e,"input","imag")};return L.runKernel(vp,t)}var Hp=z({imag_:jE});function qE(e){let t={x:R(e,"x","isFinite")};return L.runKernel(Xi,t)}var Kb=z({isFinite_:qE});function XE(e){let t={x:R(e,"x","isInf")};return L.runKernel(Ki,t)}var Yb=z({isInf_:XE});function KE(e){let t={x:R(e,"x","isNaN")};return L.runKernel(Yi,t)}var Zb=z({isNaN_:KE});function YE(e,t=.2){let a={x:R(e,"x","leakyRelu")},n={alpha:t};return L.runKernel(Zi,a,n)}var Ig=z({leakyRelu_:YE});function ZE(e,t){let a=R(e,"a","less","string_or_numeric"),n=R(t,"b","less","string_or_numeric");[a,n]=Rt(a,n),Ut(a.shape,n.shape);let r={a,b:n};return L.runKernel(Ji,r)}var mh=z({less_:ZE});function JE(e,t){let a=R(e,"a","lessEqual","string_or_numeric"),n=R(t,"b","lessEqual","string_or_numeric");[a,n]=Rt(a,n),Ut(a.shape,n.shape);let r={a,b:n};return L.runKernel(Qi,r)}var zh=z({lessEqual_:JE});function Jb(e,t,a){if(a<=0)throw new Error("The number of values should be positive.");let n={start:e,stop:t,num:a};return L.runKernel(eo,{},n)}function QE(e,t=5,a=1,n=1,r=.5){let s=R(e,"x","localResponseNormalization");F(s.rank===4||s.rank===3,()=>`Error in localResponseNormalization: x must be rank 3 or 4 but got
               rank ${s.rank}.`),F(jl(t),()=>`Error in localResponseNormalization: depthRadius must be an integer but got depthRadius ${t}.`);let i=s,o=!1;s.rank===3&&(o=!0,i=Q(s,[1,s.shape[0],s.shape[1],s.shape[2]]));let l={x:i},u={depthRadius:t,bias:a,alpha:n,beta:r},p=L.runKernel(io,l,u);return o?Q(p,[p.shape[1],p.shape[2],p.shape[3]]):p}var Qb=z({localResponseNormalization_:QE});function eM(e){let t={x:R(e,"x","log","float32")};return L.runKernel(to,t)}var Zl=z({log_:eM});function tM(e){let t={x:R(e,"x","log1p")};return L.runKernel(ao,t)}var Sg=z({log1p_:tM});function aM(e){return F(Yr(e),()=>"The f passed in grad(f) must be a function"),(t,a)=>{let n=R(t,"x","tf.grad","string_or_numeric"),r=a!=null?R(a,"dy","tf.grad"):null;return L.tidy(()=>{let{value:s,grads:i}=L.gradients(()=>e(n),[n],r);return r!=null&&Ta(s.shape,r.shape,"The shape of dy passed in grad(f)(x, dy) must match the shape returned by f(x)"),Lh(i),i[0]})}}function nM(e){return F(Yr(e),()=>"The f passed in grads(f) must be a function"),(t,a)=>{F(Array.isArray(t),()=>"The args passed in grads(f)(args) must be an array of `Tensor`s or `TensorLike`s");let n=Hd(t,"args","tf.grads","string_or_numeric"),r=a!=null?R(a,"dy","tf.grads"):null;return L.tidy(()=>{let{value:s,grads:i}=L.gradients(()=>e(...n),n,r);return r!=null&&Ta(s.shape,r.shape,"The shape of dy passed in grads(f)([x1,...], dy) must match the shape returned by f([x1,...])"),Lh(i),i})}}function rM(e){return F(Yr(e),()=>"The f passed in valueAndGrad(f) must be a function"),(t,a)=>{F(t instanceof yt,()=>"The x passed in valueAndGrad(f)(x) must be a tensor"),F(a==null||a instanceof yt,()=>"The dy passed in valueAndGrad(f)(x, dy) must be a tensor");let{grads:n,value:r}=L.gradients(()=>e(t),[t],a);return Lh(n),{grad:n[0],value:r}}}function sM(e){return F(Yr(e),()=>"The f passed in valueAndGrads(f) must be a function"),(t,a)=>{F(Array.isArray(t)&&t.every(r=>r instanceof yt),()=>"The args passed in valueAndGrads(f)(args) must be array of tensors"),F(a==null||a instanceof yt,()=>"The dy passed in valueAndGrads(f)(args, dy) must be a tensor");let n=L.gradients(()=>e(...t),t,a);return a!=null&&Ta(n.value.shape,a.shape,"The shape of dy passed in valueAndGrads(f)([x1,...], dy) must match the shape returned by f([x1,...])"),Lh(n.grads),n}}function e4(e,t){F(Yr(e),()=>"The f passed in variableGrads(f) must be a function"),F(t==null||Array.isArray(t)&&t.every(u=>u instanceof Gd),()=>"The varList passed in variableGrads(f, varList) must be an array of variables");let a=t!=null;if(!a){t=[];for(let u in L.registeredVariables)t.push(L.registeredVariables[u])}let n=a?t.filter(u=>!u.trainable):null,r=t.length;t=t.filter(u=>u.trainable),F(t.length>0,()=>`variableGrads() expects at least one of the input variables to be trainable, but none of the ${r} variables is trainable.`);let s=!0,{value:i,grads:o}=L.gradients(e,t,null,s);F(o.some(u=>u!=null),()=>"Cannot find a connection between any variable and the result of the loss function y=f(x). Please make sure the operations that use variables are inside the function f passed to minimize()."),F(i.rank===0,()=>`The f passed in variableGrads(f) must return a scalar, but it returned a rank-${i.rank} tensor`);let l={};return t.forEach((u,p)=>{o[p]!=null&&(l[u.name]=o[p])}),n!=null&&n.forEach(u=>l[u.name]=null),{value:i,grads:l}}function nr(e){return L.customGrad(e)}function Lh(e){if(e.filter(t=>t==null).length>0)throw new Error(`Cannot compute gradient of y=f(x) with respect to x. Make sure that
    the f you passed encloses all operations that lead from x to y.`)}function iM(e){let t={x:R(e,"x","neg")};return L.runKernel(Su,t)}var Wn=z({neg_:iM});function oM(e){let t={x:R(e,"x","softplus")};return L.runKernel(Vo,t)}var Cg=z({softplus_:oM});function lM(e){let t=R(e,"x","logSigmoid");return nr(a=>({value:Wn(Cg(Wn(a))),gradFunc:n=>te(n,za(Wn(a)))}))(t)}var t4=z({logSigmoid_:lM});function uM(e,t){let a=R(e,"a","sub"),n=R(t,"b","sub");[a,n]=Rt(a,n);let r={a,b:n};return L.runKernel(Ko,r)}var xe=z({sub_:uM});function dM(e,t=-1){let a=R(e,"logits","logSoftmax");if(t===-1&&(t=a.rank-1),t!==a.rank-1)throw Error(`Log Softmax along a non-last dimension is not yet supported. Logits was rank ${a.rank} and axis was ${t}`);return nr((n,r)=>{let s=ga(n,t,!0),i=xe(n,s),o=xe(Ue(i,"float32"),Zl(ot(rs(i),t,!0)));return r([o]),{value:o,gradFunc:(l,u)=>{let[p]=u,c=!0,d=rs(p);return xe(l,te(ot(l,t,c),d))}}})(a)}var a4=z({logSoftmax_:dM});function pM(e,t=null,a=!1){let n=R(e,"x","logSumExp"),r=lp(t,n.shape),s=ga(n,r,!0),i=xe(n,s),o=rs(i),l=ot(o,r),u=Zl(l),p=we(Q(s,u.shape),u);if(a){let c=Vp(p.shape,r);return Q(p,c)}return p}var Tg=z({logSumExp_:pM});function cM(e,t){let a=R(e,"a","logicalAnd","bool"),n=R(t,"b","logicalAnd","bool");Ut(a.shape,n.shape);let r={a,b:n};return L.runKernel(no,r)}var Kd=z({logicalAnd_:cM});function hM(e){let t={x:R(e,"x","logicalNot","bool")};return L.runKernel(ro,t)}var Ng=z({logicalNot_:hM});function mM(e,t){let a=R(e,"a","logicalOr","bool"),n=R(t,"b","logicalOr","bool");Ut(a.shape,n.shape);let r={a,b:n};return L.runKernel(so,r)}var Rg=z({logicalOr_:mM});function fM(e,t){let a=R(e,"a","logicalXor","bool"),n=R(t,"b","logicalXor","bool");return Ut(a.shape,n.shape),Kd(Rg(e,t),Ng(Kd(e,t)))}var n4=z({logicalXor_:fM}),Xc=2147483648;function gM(e,t,a="left"){let n=R(e,"sortedSequence","searchSorted"),r=R(t,"values","searchSorted"),s=n.shape[n.shape.length-1],i=r.shape[r.shape.length-1],o=Q(n,[-1,s]),l=Q(r,[-1,i]);if(o.rank<2)throw new Error("Sorted input argument must be at least 2-dimensional");if(o.shape[0]!==l.shape[0])throw new Error("Leading dimension of 'sortedSequence' and 'values' must match.");if(mt(l.shape)>=Xc)throw new Error(`values tensor size must less than ${Xc}`);if(o.shape[1]>=Xc)throw new Error(`trailing dim_size must less than ${Xc} for int32 output type, was ${o.shape[1]}`);let u={sortedSequence:o,values:l},p={side:a};return L.runKernel(Do,u,p)}var Wh=z({searchSorted_:gM});function r4(e,t){return Wh(e,t,"left")}function yM(e,t,a,n,r){let s=R(e,"x","maxPool"),i=1,o=s,l=!1;s.rank===3&&(l=!0,o=Q(s,[1,s.shape[0],s.shape[1],s.shape[2]])),F(o.rank===4,()=>`Error in maxPool: input must be rank 4 but got rank ${o.rank}.`),F(Er(a,i),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${a} and dilations '${i}'`),Nn("maxPool",n,r);let u={x:o},p={filterSize:t,strides:a,pad:n,dimRoundingMode:r},c=L.runKernel(uo,u,p);return l?Q(c,[c.shape[1],c.shape[2],c.shape[3]]):c}var Eg=z({maxPool_:yM});function xM(e,t=[1,1,1],a,n,r,s="NDHWC"){let i=R(e,"x","maxPool3d"),o=i,l=!1;i.rank===4&&(l=!0,o=Q(i,[1,i.shape[0],i.shape[1],i.shape[2],i.shape[3]])),F(o.rank===5,()=>`Error in maxPool3d: x must be rank 5 but got rank ${o.rank}.`),F(s==="NDHWC",()=>`Error in maxPool3d: Only NDHWC is currently supported, but got dataFormat of ${s}`),Nn("maxPool3d",n,r);let u={x:o},p={filterSize:t,strides:a,pad:n,dimRoundingMode:r,dataFormat:s},c=L.runKernel(ku,u,p);return l?Q(c,[c.shape[1],c.shape[2],c.shape[3],c.shape[4]]):c}var s4=z({maxPool3d_:xM});function AM(e,t,a,n,r=!1){let s={x:R(e,"x","maxPoolWithArgmax")},i={filterSize:t,strides:a,pad:n,includeBatchInIndex:r},o=L.runKernel(Iu,s,i);return{result:o[0],indexes:o[1]}}var i4=z({maxPoolWithArgmax_:AM});function bM(e,t){let a=R(e,"a","maximum"),n=R(t,"b","maximum");[a,n]=Rt(a,n),a.dtype==="bool"&&(a=Ue(a,"int32"),n=Ue(n,"int32")),Ut(a.shape,n.shape);let r={a,b:n};return L.runKernel(lo,r)}var Mg=z({maximum_:bM});function vM(e,t=null,a=!1){let n={x:R(e,"x","mean")},r={axis:t,keepDims:a};return L.runKernel(po,n,r)}var Yd=z({mean_:vM});function yn(e,t="float32"){if(an(e),t==="complex64"){let n=yn(e,"float32"),r=yn(e,"float32");return Tr(n,r)}let a=Eh(mt(e),t);return L.makeTensor(a,e,t)}function jr(e,t="float32"){if(an(e),t==="complex64"){let n=jr(e,"float32"),r=yn(e,"float32");return Tr(n,r)}let a=Q1(mt(e),t);return L.makeTensor(a,e,t)}function o4(e,t,{indexing:a="xy"}={}){if(a!=="xy"&&a!=="ij")throw new TypeError(`${a} is not a valid third argument to meshgrid`);if(e===void 0)return[];let n=R(e,"x","meshgrid",e instanceof yt?e.dtype:"float32");if(t===void 0)return[n];let r=R(t,"y","meshgrid",t instanceof yt?t.dtype:"float32"),s=mt(n.shape),i=mt(r.shape);return a==="xy"?(n=Q(n,[1,-1]),r=Q(r,[-1,1]),[pt(jr([i,1],n.dtype),n),pt(r,jr([1,s],r.dtype))]):(n=Q(n,[-1,1]),r=Q(r,[1,-1]),[pt(n,jr([1,i],n.dtype)),pt(jr([s,1],r.dtype),r)])}function wM(e,t){let a=R(e,"a","minimum"),n=R(t,"b","minimum");[a,n]=Rt(a,n),a.dtype==="bool"&&(a=Ue(a,"int32"),n=Ue(n,"int32")),Ut(a.shape,n.shape);let r={a,b:n};return L.runKernel(ho,r)}var Zd=z({minimum_:wM});function kM(e,t,a){F(a==="reflect"||a==="symmetric",()=>`Invalid mode. Mode must be either reflect or symmetric. Got ${a}.`);let n=R(e,"x","mirrorPad");if(n.rank===0)throw new Error("mirrorPad(scalar) is not defined. Pass non-scalar to mirrorPad");F(t.length===n.rank,()=>`Padding doesn't match input. Must be ${n.rank}. Got ${t.length}.`);let r=a==="reflect"?1:0;for(let o=0;o<n.rank;o++)F(t[o].length===2,()=>"Invalid number of paddings. Must be length of 2 each."),F(t[o][0]>=0&&t[o][0]<=n.shape[o]-r&&t[o][1]>=0&&t[o][1]<=n.shape[o]-r,()=>`Padding in dimension ${o} cannot be greater than or equal to ${n.shape[o]-r} or less than 0 for input of shape ${n.shape}`);let s={paddings:t,mode:a},i={x:n};return L.runKernel(mo,i,s)}var l4=z({mirrorPad_:kM});function IM(e,t){let a=R(e,"a","mod"),n=R(t,"b","mod");[a,n]=Rt(a,n);let r={a,b:n};return L.runKernel(fo,r)}var Gu=z({mod_:IM});function SM(e,t=null,a=!1){e=R(e,"x","moments");let n=lp(t,e.shape),r=Yd(e,n,a),s=r.shape;a||(s=Vp(r.shape,n));let i=Tn(xe(Ue(e,"float32"),Q(r,s))),o=Yd(i,n,a);return{mean:r,variance:o}}var u4=z({moments_:SM});function CM(e,t,a,n){let r=R(t,"data","multiRNNCell"),s=Hd(a,"c","multiRNNCell"),i=Hd(n,"h","multiRNNCell"),o=r,l=[];for(let c=0;c<e.length;c++){let d=e[c](o,s[c],i[c]);l.push(d[0]),l.push(d[1]),o=d[1]}let u=[],p=[];for(let c=0;c<l.length;c+=2)u.push(l[c]),p.push(l[c+1]);return[u,p]}var d4=z({multiRNNCell_:CM});function TM(e,t,a,n=!1){let r=R(e,"logits","multinomial"),s=r.size,i=r.rank;if(s<2)throw new Error(`Error in multinomial: you need at least 2 outcomes, but got ${s}.`);if(i>2)throw new Error(`Rank of probabilities must be 1 or 2, but is ${i}`);a=a||Math.random();let o={logits:i===1?Q(r,[1,-1]):r},l={numSamples:t,seed:a,normalized:n},u=L.runKernel(go,o,l);return i===1?Q(u,[u.size]):u}var p4=z({multinomial_:TM});function NM(e,t){let a=R(e,"a","notEqual","string_or_numeric"),n=R(t,"b","notEqual","string_or_numeric");[a,n]=Rt(a,n),Ut(a.shape,n.shape);let r={a,b:n};return L.runKernel(xo,r)}var $g=z({notEqual_:NM});function RM(e,t,a=1,n=0,r="int32"){if(t<2)throw new Error(`Error in oneHot: depth must be >=2, but it is ${t}`);let s={indices:R(e,"indices","oneHot","int32")},i={dtype:r,depth:t,onValue:a,offValue:n};return L.runKernel(vo,s,i)}var fh=z({oneHot_:RM});function EM(e){let t={x:R(e,"x","onesLike")};return L.runKernel(Tu,t)}var c4=z({onesLike_:EM});function MM(e,t){let a=R(e,"v1","outerProduct"),n=R(t,"v2","outerProduct");F(a.rank===1&&n.rank===1,()=>`Error in outerProduct: inputs must be rank 1, but got ranks ${a.rank} and ${n.rank}.`);let r=Q(a,[-1,1]),s=Q(n,[1,-1]);return pt(r,s)}var h4=z({outerProduct_:MM});function $M(e,t,a=0){let n=R(e,"x","pad");if(n.rank===0)throw new Error("pad(scalar) is not defined. Pass non-scalar to pad");let r={paddings:t,constantValue:a},s={x:n};return L.runKernel(wo,s,r)}var Rn=z({pad_:$M});function PM(e,t,a=0){return F(t.length===2,()=>"Invalid number of paddings. Must be length of 2."),Rn(e,[t],a)}var m4=z({pad1d_:PM});function _M(e,t,a=0){return F(t.length===2&&t[0].length===2&&t[1].length===2,()=>"Invalid number of paddings. Must be length of 2 each."),Rn(e,t,a)}var f4=z({pad2d_:_M});function FM(e,t,a=0){return F(t.length===3&&t[0].length===2&&t[1].length===2&&t[2].length===2,()=>"Invalid number of paddings. Must be length of 2 each."),Rn(e,t,a)}var g4=z({pad3d_:FM});function DM(e,t,a=0){return F(t.length===4&&t[0].length===2&&t[1].length===2&&t[2].length===2&&t[3].length===2,()=>"Invalid number of paddings. Must be length of 2 each."),Rn(e,t,a)}var y4=z({pad4d_:DM});function OM(e,t,a){let n=R(e,"x","spaceToBatchND");F(n.rank>=1+t.length,()=>`input rank ${n.rank} should be > than [blockShape] ${t.length}`),F(a.length===t.length,()=>`paddings.shape[0] ${a.length} must be equal to [blockShape] ${t.length}`),F(n.shape.reduce((i,o,l)=>l>0&&l<=t.length?i&&(o+a[l-1][0]+a[l-1][1])%t[l-1]===0:i,!0),()=>`input spatial dimensions ${n.shape.slice(1)} with paddings ${a.toString()} must be divisible by blockShapes ${t.toString()}`);let r={x:n},s={blockShape:t,paddings:a};return L.runKernel(Fu,r,s)}var Pg=z({spaceToBatchND_:OM});function zM(e,t,a,n,r,s,i){r==null&&(r=[1,1]),s==null&&(s=1),n===0&&(n="valid");let o=R(e,"x","maxPool"),l=o,u=!1;o.rank===3&&(u=!0,l=Q(o,[1,o.shape[0],o.shape[1],o.shape[2]])),F(Er(s,r),()=>`Error in pool: Either strides or dilations must be 1. Got strides ${s} and dilations '${r}'`);let p=cb(l.shape,t,s,r,n),c=[p.dilationHeight,p.dilationWidth],d;n==="same"?d=WM([p.filterHeight,p.filterWidth],c):d=[[0,0],[0,0]];let h=c[0]===1&&c[1]===1,[m,f]=LM([p.inHeight,p.inWidth],c,d),g=h?n:"valid",y=h?l:Pg(l,c,m),x=(a==="avg"?()=>hg(y,t,s,g,i):()=>Eg(y,t,s,g,i))(),A=h?x:mg(x,c,f);return u?Q(A,[A.shape[1],A.shape[2],A.shape[3]]):A}function LM(e,t,a){let n=a.map(p=>p[0]),r=a.map(p=>p[1]),s=e.concat(n,r),i=t.map((p,c)=>(p-s[c]%p)%p),o=r.map((p,c)=>p+i[c]),l=t.map((p,c)=>[n[c],o[c]]),u=t.map((p,c)=>[0,i[c]]);return[l,u]}function WM(e,t){let a=e.map((s,i)=>s+(s-1)*(t[i]-1)).map(s=>s-1),n=a.map(s=>Math.floor(s/2)),r=a.map((s,i)=>s-n[i]);return a.map((s,i)=>[n[i],r[i]])}var x4=z({pool_:zM});function BM(e,t){let a=R(e,"x","prelu"),n=R(t,"alpha","prelu"),r={x:a,alpha:n};return L.runKernel(Io,r)}var _g=z({prelu_:BM});function VM(e,t=null,a=!1){let n=R(e,"x","prod");n.dtype==="bool"&&(n=Ue(n,"int32"));let r={x:n},s={axis:t,keepDims:a};return L.runKernel(So,r,s)}var A4=z({prod_:VM});function UM(e,t,a,n){let r=e.map((p,c)=>R(p,`tensors${c}`,"raggedGather","int32")),s=R(t,"paramsDenseValues","raggedGather"),i=R(a,"indices","raggedGather","int32"),o={paramsNestedSplits:r,paramsDenseValues:s,indices:i},l={outputRaggedRank:n},u=L.runKernel($h,o,l);return{outputNestedSplits:u.slice(0,u.length-1),outputDenseValues:u[u.length-1]}}var b4=z({raggedGather_:UM});function GM(e,t,a){let n=R(e,"starts","raggedRange"),r=R(t,"limits","raggedRange",n.dtype),s=R(a,"deltas","raggedRange",n.dtype),i={starts:n,limits:r,deltas:s},o=L.runKernel(Ph,i);return{rtNestedSplits:o[0],rtDenseValues:o[1]}}var v4=z({raggedRange_:GM});function HM(e,t,a,n,r){let s=R(e,"shape","raggedTensorToTensor","int32"),i=R(t,"values","raggedTensorToTensor"),o=R(a,"defaultValue","raggedTensorToTensor",i.dtype),l=n.map((c,d)=>R(c,`tensors${d}`,"raggedTensorToTensor","int32")),u={shape:s,values:i,defaultValue:o,rowPartitionTensors:l},p={rowPartitionTypes:r};return L.runKernel(_h,u,p)}var w4=z({raggedTensorToTensor_:HM});function jM(e,t,a){an(e);let n=mt(e),r=null;if(a==null||a==="float32")r=new Float32Array(n);else if(a==="int32")r=new Int32Array(n);else if(a==="bool")r=new Uint8Array(n);else throw new Error(`Unknown data type ${a}`);for(let s=0;s<n;s++)r[s]=t();return L.makeTensor(r,e,a)}var k4=z({rand_:jM}),Fg=ru(mA()),I4={};Ze(I4,{TEST_EPSILON_FLOAT16:()=>S4,createVideoElement:()=>e$,encodeStrings:()=>C4,expectArrayBuffersEqual:()=>QM,expectArraysClose:()=>XM,expectArraysEqual:()=>YM,expectNumbersClose:()=>ZM,expectPromiseToFail:()=>KM,expectValuesInRange:()=>JM,play:()=>t$,testEpsilon:()=>Dg});var qM=.001,S4=.1;function XM(e,t,a){return a==null&&(a=Dg()),f1(e,t,(n,r)=>Og(n,r,a))}function Dg(){return L.backend.floatPrecision()===32?qM:S4}function f1(e,t,a){let n=!0;if((Qt(e)||Qt(t))&&(n=!1),Qt(e)&&Qt(t)&&(n=!0),n){let i=e.constructor.name,o=t.constructor.name;if(i!==o)throw new Error(`Arrays are of different type. Actual: ${i}. Expected: ${o}`)}if(Array.isArray(e)&&Array.isArray(t)){let i=tr(e),o=tr(t);if(!Nr(i,o))throw new Error(`Arrays have different shapes. Actual: [${i}]. Expected: [${o}]`)}let r=Qt(e)?e:es(e),s=Qt(t)?t:es(t);if(r.length!==s.length)throw new Error(`Arrays have different lengths actual: ${r.length} vs expected: ${s.length}.
Actual:   ${r}.
Expected: ${s}.`);for(let i=0;i<s.length;++i){let o=r[i],l=s[i];if(!a(o,l))throw new Error(`Arrays differ: actual[${i}] = ${o}, expected[${i}] = ${l}.
Actual:   ${r}.
Expected: ${s}.`)}typeof expect!="undefined"&&expect().nothing()}function KM(e,t){e().then(()=>t.fail(),()=>t()),typeof expect!="undefined"&&expect().nothing()}function YM(e,t){let a=typeof t=="string"||typeof t=="number"||typeof t=="boolean"?[t]:t;return Gr(e)||Gr(e[0])||Gr(t)||Gr(t[0])?f1(e,a,(n,r)=>n==r):f1(e,t,(n,r)=>Og(n,r,0))}function ZM(e,t,a){if(a==null&&(a=Dg()),!Og(e,t,a))throw new Error(`Numbers differ: actual === ${e}, expected === ${t}`);typeof expect!="undefined"&&expect().nothing()}function Og(e,t,a){return!isFinite(e)&&!isFinite(t)?!0:!(isNaN(e)||isNaN(t)||Math.abs(e-t)>a)}function JM(e,t,a){for(let n=0;n<e.length;n++)if(e[n]<t||e[n]>a)throw new Error(`Value out of range:${e[n]} low: ${t}, high: ${a}`)}function QM(e,t){let a=new Float32Array(e),n=new Float32Array(t);if(a.length!==n.length)throw new Error(`Expected ArrayBuffer to be of length ${n.length}, but it was ${a.length}`);for(let r=0;r<n.length;r++)if(a[r]!==n[r])throw new Error(`Expected ArrayBuffer value at ${r} to be ${n[r]} but got ${a[r]} instead`)}function C4(e){for(let t=0;t<e.length;t++){let a=e[t];Array.isArray(a)?C4(a):e[t]=Pp(a)}return e}function e$(e){let t=document.createElement("video");return"playsInline"in t&&(t.playsInline=!0),t.muted=!0,t.loop=!0,t.style.position="fixed",t.style.left="0px",t.style.top="0px",t.preload="auto",t.appendChild(e),new Promise(a=>{t.addEventListener("loadeddata",n=>a(t)),t.load()})}async function t$(e){await e.play(),"requestVideoFrameCallback"in e&&await new Promise(t=>{e.requestVideoFrameCallback(t)})}var zg=class{constructor(e,t,a,n,r){this.mean=e,this.stdDev=t,this.dtype=a,this.nextVal=NaN,this.truncated=n,this.truncated&&(this.upper=this.mean+this.stdDev*2,this.lower=this.mean-this.stdDev*2);let s=r||Math.random();this.random=Fg.alea(s.toString())}nextValue(){if(!isNaN(this.nextVal)){let n=this.nextVal;return this.nextVal=NaN,n}let e,t,a=!1;for(;!a;){let n,r,s;do n=2*this.random()-1,r=2*this.random()-1,s=n*n+r*r;while(s>=1||s===0);let i=Math.sqrt(-2*Math.log(s)/s);e=this.mean+this.stdDev*n*i,t=this.mean+this.stdDev*r*i,(!this.truncated||this.isValidTruncated(e))&&(a=!0)}return(!this.truncated||this.isValidTruncated(t))&&(this.nextVal=this.convertValue(t)),this.convertValue(e)}convertValue(e){return this.dtype==null||this.dtype==="float32"?e:Math.round(e)}isValidTruncated(e){return e<=this.upper&&e>=this.lower}},a$=class{constructor(e,t,a,n){this.alpha=e,this.beta=1/t,this.dtype=a;let r=n||Math.random();this.randu=Fg.alea(r.toString()),this.randn=new zg(0,1,a,!1,this.randu()),e<1?this.d=e+2/3:this.d=e-1/3,this.c=1/Math.sqrt(9*this.d)}nextValue(){let e,t,a,n,r,s;for(;;){do n=this.randn.nextValue(),s=1+this.c*n;while(s<=0);if(s*=s*s,e=n*n,t=1-.331*e*e,a=.5*e+this.d*(1-s+Math.log(s)),r=this.randu(),r<t||Math.log(r)<a)break}return s=1/this.beta*this.d*s,this.alpha<1&&(s*=Math.pow(this.randu(),1/this.alpha)),this.convertValue(s)}convertValue(e){return this.dtype==="float32"?e:Math.round(e)}},n$=class{constructor(e=0,t=1,a,n){if(this.canReturnFloat=()=>this.dtype==null||this.dtype==="float32",this.min=e,this.range=t-e,this.dtype=a,n==null&&(n=Math.random()),typeof n=="number"&&(n=n.toString()),!this.canReturnFloat()&&this.range<=1)throw new Error(`The difference between ${e} - ${t} <= 1 and dtype is not float`);this.random=Fg.alea(n)}convertValue(e){return this.canReturnFloat()?e:Math.round(e)}nextValue(){return this.convertValue(this.min+this.range*this.random())}};function r$(e,t,a=1,n="float32",r){if(an(e),a==null&&(a=1),n==null&&(n="float32"),n!=="float32"&&n!=="int32")throw new Error(`Unsupported data type ${n}`);let s=new a$(t,a,n,r),i=_e(e,n);for(let o=0;o<i.values.length;o++)i.values[o]=s.nextValue();return i.toTensor()}var T4=z({randomGamma_:r$});function s$(e,t=0,a=1,n,r){if(an(e),n!=null&&n==="bool")throw new Error(`Unsupported data type ${n}`);let s=new zg(t,a,n,!1,r),i=_e(e,n);for(let o=0;o<i.values.length;o++)i.values[o]=s.nextValue();return i.toTensor()}var Lg=z({randomNormal_:s$});function i$(e,t,a){if(t!=null&&t==="bool")throw new Error(`Unsupported data type ${t}`);return Lg(e,0,1,t,a)}var N4=z({randomStandardNormal_:i$});function o$(e,t=0,a=1,n="float32",r){an(e);let s=_e(e,n),i=new n$(t,a,null,r);for(let o=0;o<s.values.length;o++)s.values[o]=i.nextValue();return s.toTensor()}var Bh=z({randomUniform_:o$});function l$(e,t,a,n){return Bh(e,t,a,"int32",n)}var R4=z({randomUniformInt_:l$});function Jl(e,t,a=1,n="float32"){if(a===0)throw new Error("Cannot have a step of zero");let r={start:e,stop:t,step:a,dtype:n};return L.runKernel(Ru,{},r)}function u$(e){let t={input:R(e,"input","real")};return L.runKernel(Ip,t)}var Ql=z({real_:u$});function d$(e){let t={x:R(e,"x","reciprocal")};return L.runKernel(Co,t)}var E4=z({reciprocal_:d$});function p$(e){let t={x:R(e,"x","relu")};return L.runKernel(To,t)}var jp=z({relu_:p$});function c$(e){let t={x:R(e,"x","relu6")};return L.runKernel(Eo,t)}var Wg=z({relu6_:c$});function h$(e,t){let a={x:R(e,"x","reverse")},n={dims:t};return L.runKernel(Mo,a,n)}var ss=z({reverse_:h$});function m$(e){let t=R(e,"x","reverse");return F(t.rank===1,()=>`Error in reverse1D: x must be rank 1 but got rank ${t.rank}.`),ss(t,0)}var M4=z({reverse1d_:m$});function f$(e,t){let a=R(e,"x","reverse");return F(a.rank===2,()=>`Error in reverse2D: x must be rank 2 but got rank ${a.rank}.`),ss(a,t)}var $4=z({reverse2d_:f$});function g$(e,t){let a=R(e,"x","reverse");return F(a.rank===3,()=>`Error in reverse3D: x must be rank 3 but got rank ${a.rank}.`),ss(a,t)}var P4=z({reverse3d_:g$});function y$(e,t){let a=R(e,"x","reverse");return F(a.rank===4,()=>`Error in reverse4D: x must be rank 4 but got rank ${a.rank}.`),ss(a,t)}var _4=z({reverse4d_:y$});function x$(e){let t={x:R(e,"x","round")};return L.runKernel($o,t)}var Bg=z({round_:x$});function A$(e){let t={x:R(e,"x","rsqrt","float32")};return L.runKernel(Po,t)}var F4=z({rsqrt_:A$});function b$(e){let t={x:R(e,"x","selu")};return L.runKernel(Oo,t)}var D4=z({selu_:b$});function v$(e,t,a,n,r,s=[1,1],i="NHWC"){let o=R(e,"x","separableConv2d"),l=R(t,"depthwiseFilter","separableConv2d"),u=R(a,"pointwiseFilter","separableConv2d"),p=o,c=!1;if(o.rank===3&&(c=!0,p=Q(o,[1,o.shape[0],o.shape[1],o.shape[2]])),i==="NCHW")throw new Error("separableConv2d currently does not support dataFormat NCHW; only NHWC is supported");F(p.rank===4,()=>`Error in separableConv2d: input must be rank 4, but got rank ${p.rank}.`),F(l.rank===4,()=>`Error in separableConv2d: depthwise filter must be rank 4, but got rank ${l.rank}.`),F(u.rank===4,()=>`Error in separableConv2d: pointwise filter must be rank 4, but got rank ${l.rank}.`),F(u.shape[0]===1,()=>`Error in separableConv2d: the first dimension of pointwise filter  must be 1, but got ${u.shape[0]}.`),F(u.shape[1]===1,()=>`Error in separableConv2d: the second dimension of pointwise filter must be 1, but got ${u.shape[1]}.`);let d=l.shape[2],h=l.shape[3];F(u.shape[2]===d*h,()=>`Error in separableConv2d: the third dimension of pointwise filter must be ${d*h}, but got ${u.shape[2]}.`);let m=Oh(p,l,n,r,i,s),f=Bp(m,u,1,"valid",i);return c?Q(f,[f.shape[1],f.shape[2],f.shape[3]]):f}var O4=z({separableConv2d_:v$});async function w$(e,t){let a=R(e,"x","setdiff1d"),n=R(t,"y","setdiff1d");F(a.dtype===n.dtype,()=>`x and y should have the same dtype, but got x (${a.dtype}) and y (${n.dtype}).`),F(a.rank===1,()=>`x should be 1D tensor, but got x (${a.shape}).`),F(n.rank===1,()=>`y should be 1D tensor, but got y (${n.shape}).`);let r=await a.data(),s=await n.data(),i=new Set(s),o=0;for(let p=0;p<r.length;p++)i.has(r[p])||o++;let l=new Vt([o],a.dtype),u=new Vt([o],"int32");for(let p=0,c=0;p<r.length;p++)i.has(r[p])||(l.values[c]=r[p],u.values[c]=p,c++);return[l.toTensor(),u.toTensor()]}var z4=w$;function k$(e){let t={x:R(e,"x","sign")};return L.runKernel(Wo,t)}var L4=z({sign_:k$});function I$(e){let t={x:R(e,"x","sin","float32")};return L.runKernel(zo,t)}var W4=z({sin_:I$});function S$(e){let t={x:R(e,"x","sinh")};return L.runKernel(Lo,t)}var B4=z({sinh_:S$});function C$(e,t,a){let n=R(e,"x","slice1d");return F(n.rank===1,()=>`slice1d expects a rank-1 tensor, but got a rank-${n.rank} tensor`),Fe(n,[t],[a])}var V4=z({slice1d_:C$});function T$(e,t,a){let n=R(e,"x","slice2d");return F(n.rank===2,()=>`slice2d expects a rank-2 tensor, but got a rank-${n.rank} tensor`),Fe(n,t,a)}var U4=z({slice2d_:T$});function N$(e,t,a){let n=R(e,"x","slice3d");return F(n.rank===3,()=>`slice3d expects a rank-3 tensor, but got a rank-${n.rank} tensor`),Fe(n,t,a)}var qp=z({slice3d_:N$});function R$(e,t,a){let n=R(e,"x","slice4d");return F(n.rank===4,()=>`slice4d expects a rank-4 tensor, but got a rank-${n.rank} tensor`),Fe(n,t,a)}var Vh=z({slice4d_:R$});function E$(e,t=-1){let a=R(e,"logits","softmax","float32");if(t===-1&&(t=a.rank-1),t!==a.rank-1)throw Error(`Softmax along a non-last dimension is not yet supported. Logits was rank ${a.rank} and dim was ${t}`);let n={logits:a},r={dim:t};return L.runKernel(Ho,n,r)}var Uh=z({softmax_:E$});function M$(e){F(e.dtype==="complex64",()=>`The dtype for tf.spectral.fft() must be complex64 but got ${e.dtype}.`);let t={input:e};return L.runKernel(Ap,t)}var Gh=z({fft_:M$});function $$(e){F(e.dtype==="complex64",()=>`The dtype for tf.spectral.ifft() must be complex64 but got ${e.dtype}.`);let t={input:e};return L.runKernel(bp,t)}var Jd=z({ifft_:$$});function P$(e){let t=e.shape[e.shape.length-1],a=e.size/t,n;if(t<=2){let r=Q(e,[a,t]);n=Jd(r)}else{let r=[a,2*(t-1)],s=Q(Ql(e),[a,t]),i=Q(Hp(e),[a,t]),o=ss(Fe(s,[0,1],[a,t-2]),1),l=te(ss(Fe(i,[0,1],[a,t-2]),1),Ge(-1)),u=lt([s,o],1),p=lt([i,l],1),c=Q(Tr(u,p),[r[0],r[1]]);n=Jd(c)}if(n=Ql(n),e.rank===3&&e.shape[0]!==0){let r=n,s=e.shape[0];n=Q(n,[s,n.shape[0]/s,n.shape[1]]),r.dispose()}return n}var Vg=z({irfft_:P$});function _$(e,t,a=0){let n={x:R(e,"x","split")},r={numOrSizeSplits:t,axis:a};return L.runKernel(Du,n,r)}var Sa=z({split_:_$});function F$(e,t){F(e.dtype==="float32",()=>`The dtype for rfft() must be real value but got ${e.dtype}`);let a=e.shape[e.shape.length-1],n=e.size/a,r;if(t!=null&&t<a){let m=e.shape.map(g=>0),f=e.shape.map(g=>g);f[e.shape.length-1]=t,r=Fe(e,m,f),a=t}else if(t!=null&&t>a){let m=e.shape.map(f=>f);m[e.shape.length-1]=t-a,r=lt([e,yn(m)],e.shape.length-1),a=t}else r=e;let s=Qa(r),i=Q(Tr(r,s),[n,a]),o=Gh(i),l=Math.floor(a/2)+1,u=Ql(o),p=Hp(o),c=Sa(u,[l,a-l],u.shape.length-1),d=Sa(p,[l,a-l],p.shape.length-1),h=r.shape.slice();return h[r.shape.length-1]=l,Q(Tr(c[0],d[0]),h)}var Hh=z({rfft_:F$});function D$(e,t){let a=R(e,"a","squaredDifference"),n=R(t,"b","squaredDifference");[a,n]=Rt(a,n),Ut(a.shape,n.shape);let r={a,b:n},s={};return L.runKernel(qo,r,s)}var Ug=z({squaredDifference_:D$});function O$(e,t){let a=R(e,"x","squeeze","string_or_numeric");return Q(a,AA(a.shape,t).newShape)}var Oe=z({squeeze_:O$});function z$(e,t=0){let a=Hd(e,"tensors","stack","string_or_numeric");F(a.length>=1,()=>"Pass at least one tensor to tf.stack"),a.length>0&&F(t<=a[0].rank,()=>"Axis must be <= rank of the tensor");let n=a,r={axis:t};return L.runKernel(Nu,n,r)}var ha=z({stack_:z$});function L$(e,t=0){let a={x:R(e,"x","step")},n={alpha:t};return L.runKernel(ps,a,n)}var Gg=z({step_:L$});function W$(e,t,a,n,r=0,s=0,i=0,o=0,l=0){let u={x:R(e,"x","stridedSlice","string_or_numeric")},p={begin:t,end:a,strides:n,beginMask:r,endMask:s,ellipsisMask:i,newAxisMask:o,shrinkAxisMask:l};return L.runKernel(Xo,u,p)}var G4=z({stridedSlice_:W$});function B$(e){let t={x:R(e,"x","tan","float32")};return L.runKernel(Yo,t)}var H4=z({tan_:B$});function Bt(e,t){ii(e);let a=tr(e,t);if(a.length!==1)throw new Error("tensor1d() requires values to be a flat/TypedArray");return cs(e,null,a,t)}function Qn(e,t,a){if(ii(e),t!=null&&t.length!==2)throw new Error("tensor2d() requires shape to have two numbers");let n=tr(e,a);if(n.length!==2&&n.length!==1)throw new Error("tensor2d() requires values to be number[][] or flat/TypedArray");if(n.length===1&&t==null)throw new Error("tensor2d() requires shape to be provided when `values` are a flat/TypedArray");return cs(e,t,n,a)}function Hg(e,t,a){if(ii(e),t!=null&&t.length!==3)throw new Error("tensor3d() requires shape to have three numbers");let n=tr(e,a);if(n.length!==3&&n.length!==1)throw new Error("tensor3d() requires values to be number[][][] or flat/TypedArray");if(n.length===1&&t==null)throw new Error("tensor3d() requires shape to be provided when `values` are a flat array");return cs(e,t,n,a)}function j4(e,t,a){if(ii(e),t!=null&&t.length!==4)throw new Error("tensor4d() requires shape to have four numbers");let n=tr(e,a);if(n.length!==4&&n.length!==1)throw new Error("tensor4d() requires values to be number[][][][] or flat/TypedArray");if(n.length===1&&t==null)throw new Error("tensor4d() requires shape to be provided when `values` are a flat array");return cs(e,t,n,a)}function q4(e,t,a){if(ii(e),t!=null&&t.length!==5)throw new Error("tensor5d() requires shape to have five numbers");let n=tr(e,a);if(n.length!==5&&n.length!==1)throw new Error("tensor5d() requires values to be number[][][][][] or flat/TypedArray");if(n.length===1&&t==null)throw new Error("tensor5d() requires shape to be provided when `values` are a flat array");return cs(e,t,n,a)}function X4(e,t,a){if(ii(e),t!=null&&t.length!==6)throw new Error("tensor6d() requires shape to have six numbers");let n=tr(e,a);if(n.length!==6&&n.length!==1)throw new Error("tensor6d() requires values to be number[][][][][][] or flat/TypedArray");if(n.length===1&&t==null)throw new Error("tensor6d() requires shape to be provided when `values` are a flat array");return t=t||n,cs(e,t,n,a)}var jh={};Ze(jh,{calculateShapes:()=>K4,validateInput:()=>qh,validateUpdateShape:()=>jg});function jg(e,t,a){let n=t.rank>1?t.shape[t.rank-1]:1,r=t.rank>1?t.rank-1:1,s=`Must have updates.shape = indices.shape[:batchDim] + shape[sliceDim:], got updates.shape: ${a.shape}, indices.shape: ${t.shape}, shape: ${e}, sliceDim: ${n}, and batchDim: ${r}.`;if(a.rank<r)throw new Error(s+` update.rank < ${r}. `);if(e.length<n+(a.rank-r))throw new Error(s+` Output shape length < ${n+(a.rank-r)}`);if(a.rank!==r+e.length-n)throw new Error(s+` update.rank != ${r+e.length-n}`);for(let i=0;i<r;++i)if(a.shape[i]!==t.shape[i])throw new Error(s+` updates.shape[${i}] (${a.shape[i]}) != indices.shape[${i}] (${t.shape[i]}).`);for(let i=0;i<a.rank-r;++i)if(a.shape[i+r]!==e[i+n])throw new Error(s+` updates.shape[${i+r}] (${a.shape[i+r]}) != shape[${i+r}] (${e[i+r]})`)}function qh(e,t,a){if(t.rank<1)throw new Error(`tf.scatterND() expects the indices to be rank 1 or higher, but the rank was ${t.rank}.`);if(e.rank<1)throw new Error(`tf.scatterND() expects the updates to be rank 1 or higher, but the rank was ${e.rank}.`);if(t.dtype!=="int32")throw new Error(`The dtype of 'indices' should be int32, but got dtype: ${t.dtype}`);if(a.length<1)throw new Error(`Output rank must be greater or equal to 1, but got shape: ${a}`);if(a.length===0){if(t.size===0)throw new Error(`Indices specified for empty output. indices shape: ${t.shape}`);if(e.size===0)throw new Error(`Updates specified for empty output. updates shape: ${e.shape}`)}jg(a,t,e)}function K4(e,t,a){let n=t.shape.length,r=n>1?t.shape[n-1]:1,s=a.length,i=1;for(let c=r;c<s;++c)i*=a[c];let o=r<1?1:r,l=mt(t.shape)/o,u=[...iu(a.slice(0,r)),1],p=mt(a);return{sliceRank:r,numUpdates:l,sliceSize:i,strides:u,outputSize:p}}function V$(e,t,a){let n=R(e,"tensor","tensorScatterupdate"),r=R(t,"indices","tensorScatterupdate","int32"),s=R(a,"updates","tensorScatterupdate");if(qh(s,r,n.shape),n.dtype!==s.dtype)throw new Error(`tensor and updates must have the same dtype, instead they are ${n.dtype} and ${s.dtype}.`);let i={tensor:n,indices:r,updates:s},o={};return L.runKernel(Fo,i,o)}var Y4=z({tensorScatterUpdate_:V$});function U$(e,t=1,a=!0){let n=R(e,"x","topk");if(n.rank===0)throw new Error("topk() expects the input to be of rank 1 or higher");let r=n.shape[n.shape.length-1];if(t<0)throw new Error(`'k' passed to topk() must be >= 0 but got ${t}`);if(t>r)throw new Error(`'k' passed to topk() must be <= the last dimension (${r}) but got ${t}`);let s={x:n},i={k:t,sorted:a},[o,l]=L.runKernel(Jo,s,i);return{values:o,indices:l}}var Z4=z({topk_:U$});function G$(e,t=0,a=1,n,r){if(an(e),n!=null&&n==="bool")throw new Error("Unsupported data type $ { dtype }");let s=new zg(t,a,n,!0,r),i=_e(e,n);for(let o=0;o<i.values.length;o++)i.values[o]=s.nextValue();return i.toTensor()}var J4=z({truncatedNormal_:G$});function H$(e,t=0){let a=R(e,"x","unique","string_or_numeric");F(a.rank>0,()=>"The input tensor must be at least 1D");let n={x:a},r={axis:t},[s,i]=L.runKernel(Ep,n,r);return{values:s,indices:i}}var Q4=z({unique_:H$});function j$(e,t,a){let n=R(e,"x","unsortedSegmentSum"),r=R(t,"segmentIds","unsortedSegmentSum","int32");F(jl(a),()=>"numSegments must be of dtype int");let s={x:n,segmentIds:r},i={numSegments:a};return L.runKernel(Mp,s,i)}var e7=z({unsortedSegmentSum_:j$});function q$(e,t=0){let a=R(e,"x","unstack","string_or_numeric");F(t>=-a.shape.length&&t<a.shape.length,()=>`Axis = ${t} is not in [-${a.shape.length}, ${a.shape.length})`);let n={value:a},r={axis:t};return L.runKernel(Bu,n,r)}var Na=z({unstack_:q$});function t7(e,t){return Wh(e,t,"right")}function a7(e,t=!0,a,n){return L.makeVariable(e,t,a,n)}function n7(e,t){let a=[];for(let s=0;s<t.length;s++)t[s]&&a.push(s);let n=_e(e,"int32"),r=_e([a.length,e.length],"int32");for(let s=0;s<a.length;s++){let i=n.indexToLoc(a[s]),o=s*e.length;r.values.set(i,o)}return r.toTensor()}async function X$(e){let t=R(e,"condition","whereAsync","bool"),a=await t.data(),n=n7(t.shape,a);return e!==t&&t.dispose(),n}var qg=X$;async function K$(e,t,a){let n=R(e,"tensor","boolMask"),r=R(t,"mask","boolMask","bool"),s=a==null?0:a,i=r.rank,o=n.shape;F(i>0,()=>"mask cannot be scalar"),Ta(o.slice(s,s+i),r.shape,"mask's shape must match the first K dimensions of tensor's shape,");let l=1;for(let f=s;f<s+i;f++)l*=o[f];let u=o.slice(0,s).concat([l],o.slice(s+i)),p=Q(n,u),c=Q(r,[-1]),d=await qg(c),h=Oe(d,[1]),m=wg(p,h,s);return e!==n&&n.dispose(),t!==r&&r.dispose(),h.dispose(),p.dispose(),c.dispose(),d.dispose(),m}var r7=K$;function Y$(e,t,a){let n=R(e,"x","transpose");if(t==null&&(t=n.shape.map((i,o)=>o).reverse()),F(n.rank===t.length,()=>`Error in transpose: rank of input ${n.rank} must match length of perm ${t}.`),t.forEach(i=>{F(i>=0&&i<n.rank,()=>`All entries in 'perm' must be between 0 and ${n.rank-1} but got ${t}`)}),n.rank<=1)return n.clone();let r={x:n},s={perm:t};return n.dtype==="complex64"?De(()=>{let i=Ql(n),o=Hp(n);return i=L.runKernel(Ir,{x:i},s),o=L.runKernel(Ir,{x:o},s),a&&(o=Wn(o)),Tr(i,o)}):L.runKernel(Ir,r,s)}var Qs=z({transpose_:Y$});function Z$(e,t,a,n,r=!0){let s=R(e,"v","movingAverage"),i=R(t,"x","movingAverage"),o=R(a,"decay","movingAverage");zA(s,i),F(Nr(s.shape,i.shape),()=>"Shape mismatch in v and x");let l=Ge(1),u=xe(l,o),p=te(xe(i,s),u);if(r){F(n!=null,()=>"When using zeroDebias: true, step is required.");let c=R(n,"step","movingAverage");p=ve(p,xe(l,Yl(o,c)))}return we(s,p)}var s7=z({movingAverage_:Z$});function J$(e,t,a){an(a);let n=R(e,"indices","scatterND","int32"),r=R(t,"updates","scatterND");qh(r,n,a);let s={indices:n,updates:r},i={shape:a};return L.runKernel(_o,s,i)}var i7=z({scatterND_:J$});function Q$(e,t,a,n){if(e.dtype!=="int32")throw new Error(`tf.sparseToDense() expects the indices to be int32 type, but the dtype was ${e.dtype}.`);if(e.rank>2)throw new Error(`sparseIndices should be a scalar, vector, or matrix, but got shape ${e.shape}.`);let r=e.rank>0?e.shape[0]:1,s=e.rank>1?e.shape[1]:1;if(a.length!==s)throw new Error(`outputShape has incorrect number of elements:, ${a.length}, should be: ${s}.`);let i=t.size;if(!(t.rank===0||t.rank===1&&i===r))throw new Error(`sparseValues has incorrect shape ${t.shape}, should be [] or [${r}]`);if(t.dtype!==n.dtype)throw new Error("sparseValues.dtype must match defaultValues.dtype")}function eP(e,t,a,n=0){an(a);let r=R(e,"sparseIndices","sparseToDense","int32"),s=R(t,"sparseValues","sparseToDense","string_or_numeric"),i=R(n,"defaultValue","sparseToDense",s.dtype);Q$(r,s,a,i);let o={sparseIndices:r,sparseValues:s,defaultValue:i},l={outputShape:a};return L.runKernel(jo,o,l)}var o7=z({sparseToDense_:eP});function tP(e,t){let a=R(t,"indices","gatherND","int32"),n={params:R(e,"x","gatherND","string_or_numeric"),indices:a};return L.runKernel(Gi,n)}var l7=z({gatherND_:tP});function aP(e,t){if(t==null)return e.shape.slice();if(Nr(e.shape,t))return t;if(e.shape.length===t.length){let a=[];for(let n=0;n<e.shape.length;n++)t[n]==null&&e.shape[n]!=null?a.push(e.shape[n]):a.push(t[n]);return a}return t}function nP(e,t,a,n){let r=R(e,"x","dropout");if(F(r.dtype==="float32",()=>`x has to be a floating point tensor since it's going to be scaled, but got a ${r.dtype} tensor instead.`),F(t>=0&&t<1,()=>`rate must be a float in the range [0, 1), but got ${t}.`),t===0)return e instanceof yt?r.clone():r;let s=aP(r,a),i=1-t,o=ve(vg(we(Bh(s,0,1,"float32",n),i)),i);return te(r,o)}var u7=z({dropout_:nP});function Xg(e){return Math.floor(Math.pow(2,Math.ceil(Math.log(e)/Math.log(2))))}function Xh(e,t,a){let n=1-e%2,r=new Float32Array(e);for(let s=0;s<e;++s){let i=2*Math.PI*s/(e+n-1);r[s]=t-a*Math.cos(i)}return Bt(r,"float32")}async function rP(e,t,a=1){let n=R(e,"predictions","inTopK"),r=R(t,"targets","inTopK");F(n.rank>1,()=>`inTopK() expects the predictions to be of rank 2 or higher, but got ${n.rank}`),F(n.rank-1===r.rank,()=>`predictions rank should be 1 larger than targets rank, but got predictions rank ${n.rank} and targets rank ${r.rank}`),Ta(n.shape.slice(0,n.shape.length-1),r.shape,"predictions's shape should be align with the targets' shape, except the last dimension.");let s=n.shape[n.shape.length-1];F(a>0&&a<=s,()=>`'k' passed to inTopK() must be > 0 && <= the predictions last dimension (${s}), but got ${a}`);let i=await n.data(),o=await r.data(),[l,u]=[i.length/s,s],p=bA("bool",l);for(let c=0;c<l;c++){let d=c*u,h=i.subarray(d,d+u),m=[];for(let f=0;f<h.length;f++)m.push({value:h[f],index:f});m.sort((f,g)=>g.value-f.value),p[c]=0;for(let f=0;f<a;f++)if(m[f].index===o[c]){p[c]=1;break}}return e!==n&&n.dispose(),t!==r&&r.dispose(),Ve(p,r.shape,"bool")}var d7=rP,Kg={};Ze(Kg,{conv2d:()=>lP,depthwiseConv2d:()=>mP,matMul:()=>gP});function sP(e,t,a,n,r,s="NHWC",i){let o=e;e.rank===3&&(o=Q(e,[1,e.shape[0],e.shape[1],e.shape[2]]));let l=t;l.rank===3&&(l=Q(t,[1,t.shape[0],t.shape[1],t.shape[2]])),F(o.rank===4,()=>`Error in conv2dDerFilter: input must be rank 4, but got shape ${o.shape}.`),F(l.rank===4,()=>`Error in conv2dDerFilter: dy must be rank 4, but got shape ${l.shape}.`),F(a.length===4,()=>`Error in conv2dDerFilter: filterShape must be length 4, but got ${a}.`);let u=s==="NHWC"?o.shape[3]:o.shape[1],p=s==="NHWC"?l.shape[3]:l.shape[1];F(u===a[2],()=>`Error in conv2dDerFilter: depth of input ${u}) must match input depth in filter (${a[2]}.`),F(p===a[3],()=>`Error in conv2dDerFilter: depth of dy (${p}) must match output depth for filter (${a[3]}).`),Nn("conv2dDerFilter",r,i);let c={x:o,dy:l},d={strides:n,pad:r,dataFormat:s,dimRoundingMode:i,filterShape:a};return L.runKernel(mp,c,d)}var iP=z({conv2DBackpropFilter_:sP});function Kh(e,t,a){if(a==null||a==="linear")return e;if(a==="relu")return te(e,Gg(t));throw new Error(`Cannot compute gradient for fused activation ${a}.`)}function Yh(e,t){let a=t,n=gg(e.shape,t.shape);return n.length>0&&(a=ot(a,n)),Q(a,e.shape)}function Zh(e,t,a,n){if(t==="linear")return e;if(t==="relu")return jp(e);if(t==="elu")return xg(e);if(t==="relu6")return Wg(e);if(t==="prelu")return _g(e,a);if(t==="leakyrelu")return Ig(e,n);if(t==="sigmoid")return za(e);throw new Error(`Unknown fused activation ${t}.`)}var Jh=(e,t)=>!(e>0)||t==="linear";function oP({x:e,filter:t,strides:a,pad:n,dataFormat:r="NHWC",dilations:s=[1,1],dimRoundingMode:i,bias:o,activation:l="linear",preluActivationWeights:u,leakyreluAlpha:p}){if(l=l||"linear",Jh(L.state.gradientDepth,l)===!1){F(r==="NHWC",()=>`Error in fused conv2d: got dataFormat of ${r} but only NHWC is currently supported for the case of gradient depth is 0 and the activation is not linear.`);let I=Bp(e,t,a,n,r,s,i);return o!=null&&(I=we(I,o)),Zh(I,l,u,p)}let c=R(e,"x","conv2d","float32"),d=R(t,"filter","conv2d","float32"),h=c,m=!1;c.rank===3&&(m=!0,h=Q(c,[1,c.shape[0],c.shape[1],c.shape[2]])),F(h.rank===4,()=>`Error in fused conv2d: input must be rank 4, but got rank ${h.rank}.`),F(d.rank===4,()=>`Error in fused conv2d: filter must be rank 4, but got rank ${d.rank}.`),Nn("fused conv2d",n,i);let f=r==="NHWC"?h.shape[3]:h.shape[1];F(d.shape[2]===f,()=>`Error in conv2d: depth of input (${f}) must match input depth for filter ${d.shape[2]}.`),F(Er(a,s),()=>`Error in conv2D: Either strides or dilations must be 1. Got strides ${a} and dilations '${s}'`);let g=Lp(h.shape,d.shape,a,s,n,i),y;o!=null&&(y=R(o,"bias","fused conv2d"),[y]=Rt(y,c),r==="NHWC"?Ut(g.outShape,y.shape):(F(y.shape.length<=1,()=>`Error in fused conv2d: only supports scalar or 1-D Tensor bias for NCHW format but got the bias of rank-${y.shape.length}.`),F(y.shape.length===0||y.shape[0]===g.outChannels||y.shape[0]===1,()=>`Error in fused conv2d: bias shape (${y.shape}) is not compatible with the number of output channels (${g.outChannels})`)));let x;if(u!=null){let I=u.shape;if(F(I.length<=1||I.length===3,()=>`Error in fused conv2d: only supports scalar, 1-D Tensor or 3-D Tensor PReLU activation weights but got a tensor of rank-${I.length}.`),I.length===1)F(I[0]===1||I[0]===g.outChannels,()=>`Error in fused conv2d: PReLU activation weights (${I}) is not compatible with the number of output channels (${g.outChannels}).`);else if(I.length===3)try{Ut(I,g.outShape)}catch(T){let N=`Error in fused conv2d: PReLU activation weights (${I}) is not compatible with the output shape of the conv2d (${g.outShape}).`;throw Error(N)}x=R(u,"prelu weights","fused conv2d")}let A=(I,T)=>{F(r==="NHWC",()=>`Error in gradient of fused conv2D: got dataFormat of ${r} but only NHWC is currently supported.`);let[N,M,$,E]=T,S=Kh(I,$,l);F(Xd(s),()=>`Error in gradient of fused conv2D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '${s}'`);let _=Nb(M.shape,S,N,a,n),O=iP(M,S,N.shape,a,n),W=[_,O];if(E!=null){let P=Yh(E,S);W.push(P)}return W},b={x:h,filter:d,bias:y,preluActivationWeights:x},w={strides:a,pad:n,dataFormat:r,dilations:s,dimRoundingMode:i,activation:l,leakyreluAlpha:p};return o==null?nr((I,T,N)=>{let M=L.runKernel(Jr,b,w);return N([T,I,M]),m&&(M=Q(M,[M.shape[1],M.shape[2],M.shape[3]])),{value:M,gradFunc:A}})(h,d):nr((I,T,N,M)=>{let $=L.runKernel(Jr,b,w);return M([T,I,$,N]),m&&($=Q($,[$.shape[1],$.shape[2],$.shape[3]])),{value:$,gradFunc:A}})(h,d,y)}var lP=z({fusedConv2d_:oP});function uP(e,t,a,n,r,s=[1,1],i){let o=e;e.rank===3&&(o=Q(e,[1,e.shape[0],e.shape[1],e.shape[2]]));let l=t;l.rank===3&&(l=Q(t,[1,t.shape[0],t.shape[1],t.shape[2]]));let u={x:o,dy:l},p={strides:n,pad:r,dimRoundingMode:i,dilations:s,filterShape:a};return L.runKernel(fp,u,p)}var dP=z({depthwiseConv2dNativeBackpropFilter_:uP});function pP(e,t,a,n,r,s=[1,1],i){let o=t,l=!1;t.rank===3&&(l=!0,o=Q(t,[1,t.shape[0],t.shape[1],t.shape[2]]));let u={dy:o,filter:a},p={strides:n,pad:r,dimRoundingMode:i,dilations:s,inputShape:e},c=L.runKernel(gp,u,p);return l?Q(c,[c.shape[1],c.shape[2],c.shape[3]]):c}var cP=z({depthwiseConv2dNativeBackpropInput_:pP});function hP({x:e,filter:t,strides:a,pad:n,dataFormat:r="NHWC",dilations:s=[1,1],dimRoundingMode:i,bias:o,activation:l="linear",preluActivationWeights:u,leakyreluAlpha:p}){if(Jh(L.state.gradientDepth,l)===!1){let w=Oh(e,t,a,n,r,s,i);return o!=null&&(w=we(w,o)),Zh(w,l,u,p)}let c=R(e,"x","depthwiseConv2d","float32"),d=R(t,"filter","depthwiseConv2d","float32"),h=c,m=!1;c.rank===3&&(m=!0,h=Q(c,[1,c.shape[0],c.shape[1],c.shape[2]])),F(h.rank===4,()=>`Error in fused depthwiseConv2d: input must be rank 4, but got rank ${h.rank}.`),F(d.rank===4,()=>`Error in fused depthwiseConv2d: filter must be rank 4, but got rank ${d.rank}.`),F(h.shape[3]===d.shape[2],()=>`Error in fused depthwiseConv2d: number of input channels (${h.shape[3]}) must match the inChannels dimension in filter ${d.shape[2]}.`),s==null&&(s=[1,1]),F(Er(a,s),()=>`Error in fused depthwiseConv2d: Either strides or dilations must be 1. Got strides ${a} and dilations '${s}'`),Nn("fused depthwiseConv2d",n,i);let f=Lp(h.shape,d.shape,a,s,n,i,!0),g;o!=null&&(g=R(o,"bias","fused conv2d"),[g]=Rt(g,c),Ut(f.outShape,g.shape));let y;u!=null&&(y=R(u,"prelu weights","fused depthwiseConv2d"));let x=(w,I)=>{F(Xd(s),()=>`Error in gradient of fused depthwiseConv2d: dilation rates greater than 1 are not yet supported. Got dilations '${s}'`);let[T,N,M,$]=I,E=Kh(w,M,l),S=cP(N.shape,E,T,a,n,s,i),_=dP(N,E,T.shape,a,n,s,i);if($!=null){let O=Yh(g,E);return[S,_,O]}return[S,_]},A={x:h,filter:d,bias:g,preluActivationWeights:y},b={strides:a,pad:n,dataFormat:r,dilations:s,dimRoundingMode:i,activation:l,leakyreluAlpha:p};return o==null?nr((w,I,T)=>{let N=L.runKernel(Qr,A,b);return T([I,w,N]),m&&(N=Q(N,[N.shape[1],N.shape[2],N.shape[3]])),{value:N,gradFunc:x}})(h,d):nr((w,I,T,N)=>{let M=L.runKernel(Qr,A,b);return N([I,w,M,T]),m&&(M=Q(M,[M.shape[1],M.shape[2],M.shape[3]])),{value:M,gradFunc:x}})(h,d,g)}var mP=z({fusedDepthwiseConv2d_:hP});function fP({a:e,b:t,transposeA:a=!1,transposeB:n=!1,bias:r,activation:s="linear",preluActivationWeights:i,leakyreluAlpha:o=.2}){if(Jh(L.state.gradientDepth,s)===!1){let $=pt(e,t,a,n);return r!=null&&($=we($,r)),Zh($,s,i,o)}let l=R(e,"a","fused matMul"),u=R(t,"b","fused matMul");[l,u]=Rt(l,u);let p=a?l.shape[l.rank-2]:l.shape[l.rank-1],c=n?u.shape[u.rank-1]:u.shape[u.rank-2],d=a?l.shape[l.rank-1]:l.shape[l.rank-2],h=n?u.shape[u.rank-2]:u.shape[u.rank-1],m=l.shape.slice(0,-2),f=u.shape.slice(0,-2),g=mt(m),y=mt(f);F(p===c,()=>`Error in fused matMul: inner shapes (${p}) and (${c}) of Tensors with shapes ${l.shape} and ${u.shape} and transposeA=${a} and transposeB=${n} must match.`);let x=Ut(l.shape.slice(0,-2),u.shape.slice(0,-2)).concat([d,h]),A=a?Q(l,[g,p,d]):Q(l,[g,d,p]),b=n?Q(u,[y,h,c]):Q(u,[y,c,h]),w;r!=null&&(w=R(r,"bias","fused matMul"),[w]=Rt(w,l),Ut(x,w.shape));let I;i!=null&&(I=R(i,"prelu weights","fused matMul"));let T=($,E)=>{let[S,_,O,W]=E,P=Kh(Q($,O.shape),O,s),U,G;if(!a&&!n?(U=pt(P,_,!1,!0),G=pt(S,P,!0,!1)):!a&&n?(U=pt(P,_,!1,!1),G=pt(P,S,!0,!1)):a&&!n?(U=pt(_,P,!1,!0),G=pt(S,P,!1,!1)):(U=pt(_,P,!0,!0),G=pt(P,S,!0,!0)),r!=null){let q=Yh(W,P);return[U,G,q]}else return[U,G]},N={a:A,b,bias:w,preluActivationWeights:I},M={transposeA:a,transposeB:n,activation:s,leakyreluAlpha:o};return r==null?nr(($,E,S)=>{let _=L.runKernel(Zr,N,M);return S([$,E,_]),{value:Q(_,x),gradFunc:T}})(A,b):nr(($,E,S,_)=>{let O=L.runKernel(Zr,N,M);return _([$,E,O,S]),{value:Q(O,x),gradFunc:T}})(A,b,w)}var gP=z({fusedMatMul_:fP});function yP(e){return Xh(e,.54,.46)}var xP=z({hammingWindow_:yP});function AP(e){return Xh(e,.5,.5)}var p7=z({hannWindow_:AP});function bP(e,t,a,n=!1,r=0){let s=0,i=[];for(;s+t<=e.size;)i.push(Fe(e,s,t)),s+=a;if(n)for(;s<e.size;){let o=s+t-e.size,l=lt([Fe(e,s,t-o),or([o],r)]);i.push(l),s+=a}return i.length===0?Qn([],[0,t]):Q(lt(i),[i.length,t])}var c7=z({frame_:bP});function vP(e,t,a,n,r=p7){n==null&&(n=Xg(t));let s=c7(e,t,a),i=te(s,r(t));return Hh(i,n)}var wP=z({stft_:vP});function kP(e,t,a,n,r="bilinear",s=0){let i=R(e,"image","cropAndResize"),o=R(t,"boxes","cropAndResize","float32"),l=R(a,"boxInd","cropAndResize","int32"),u=o.shape[0];F(i.rank===4,()=>`Error in cropAndResize: image must be rank 4,but got rank ${i.rank}.`),F(o.rank===2&&o.shape[1]===4,()=>`Error in cropAndResize: boxes must be have size [${u},4] but had shape ${o.shape}.`),F(l.rank===1&&l.shape[0]===u,()=>`Error in cropAndResize: boxInd must be have size [${u}] but had shape ${o.shape}.`),F(n.length===2,()=>`Error in cropAndResize: cropSize must be of length 2, but got length ${n.length}.`),F(n[0]>=1&&n[1]>=1,()=>`cropSize must be atleast [1,1], but was ${n}`),F(r==="bilinear"||r==="nearest",()=>`method must be bilinear or nearest, but was ${r}`);let p={image:i,boxes:o,boxInd:l},c={method:r,extrapolationValue:s,cropSize:n};return L.runKernel(Ei,p,c)}var IP=z({cropAndResize_:kP});function SP(e){let t=R(e,"image","flipLeftRight","float32");F(t.rank===4,()=>`Error in flipLeftRight: image must be rank 4,but got rank ${t.rank}.`);let a={image:t};return L.runKernel(Wi,a,{})}var CP=z({flipLeftRight_:SP});function TP(e){let t=R(e,"image","grayscaleToRGB"),a=t.rank-1,n=t.shape[a];F(t.rank>=2,()=>`Error in grayscaleToRGB: images must be at least rank 2, but got rank ${t.rank}.`),F(n===1,()=>`Error in grayscaleToRGB: last dimension of a grayscale image should be size 1, but got size ${n}.`);let r=new Array(t.rank);return r.fill(1,0,a),r[a]=3,Kr(t,r)}var NP=z({grayscaleToRGB_:TP});function RP(e){let t=R(e,"image","RGBToGrayscale"),a=t.rank-1,n=t.shape[a];F(t.rank>=2,()=>`Error in RGBToGrayscale: images must be at least rank 2, but got rank ${t.rank}.`),F(n===3,()=>`Error in RGBToGrayscale: last dimension of an RGB image should be size 3, but got size ${n}.`);let r=t.dtype,s=Ue(t,"float32"),i=Bt([.2989,.587,.114]),o;switch(t.rank){case 2:o=Vs("ij,j->i",s,i);break;case 3:o=Vs("ijk,k->ij",s,i);break;case 4:o=Vs("ijkl,l->ijk",s,i);break;case 5:o=Vs("ijklm,m->ijkl",s,i);break;case 6:o=Vs("ijklmn,n->ijklm",s,i);break;default:throw new Error("Not a valid tensor rank.")}return o=Wt(o,-1),Ue(o,r)}var EP=z({rgbToGrayscale_:RP});function MP(e,t,a=0,n=.5){let r=R(e,"image","rotateWithOffset","float32");F(r.rank===4,()=>`Error in rotateWithOffset: image must be rank 4,but got rank ${r.rank}.`);let s={image:r},i={radians:t,fillValue:a,center:n};return L.runKernel(el,s,i)}var $P=z({rotateWithOffset_:MP});function Hu(e,t,a,n,r,s){n==null&&(n=.5),r==null&&(r=Number.NEGATIVE_INFINITY),s==null&&(s=0);let i=e.shape[0];return a=Math.min(a,i),F(0<=n&&n<=1,()=>`iouThreshold must be in [0, 1], but was '${n}'`),F(e.rank===2,()=>`boxes must be a 2D tensor, but was of rank '${e.rank}'`),F(e.shape[1]===4,()=>`boxes must have 4 columns, but 2nd dimension was ${e.shape[1]}`),F(t.rank===1,()=>"scores must be a 1D tensor"),F(t.shape[0]===i,()=>`scores has incompatible shape with boxes. Expected ${i}, but was ${t.shape[0]}`),F(0<=s&&s<=1,()=>`softNmsSigma must be in [0, 1], but was '${s}'`),{maxOutputSize:a,iouThreshold:n,scoreThreshold:r,softNmsSigma:s}}function PP(e,t,a,n=.5,r=Number.NEGATIVE_INFINITY){let s=R(e,"boxes","nonMaxSuppression","float32"),i=R(t,"scores","nonMaxSuppression","float32"),o=Hu(s,i,a,n,r);a=o.maxOutputSize,n=o.iouThreshold,r=o.scoreThreshold;let l={maxOutputSize:a,iouThreshold:n,scoreThreshold:r};return L.runKernel(Ao,{boxes:s,scores:i},l)}var _P=z({nonMaxSuppression_:PP});function FP(e,t,a){let n=DP(e,t,a),r=n<0?-(n+1):n;e.splice(r,0,t)}function DP(e,t,a){return zP(e,t,a||OP)}function OP(e,t){return e>t?1:e<t?-1:0}function zP(e,t,a){let n=0,r=e.length,s=0,i=!1;for(;n<r;){s=n+(r-n>>>1);let o=a(t,e[s]);o>0?n=s+1:(r=s,i=!o)}return i?n:-n-1}function h7(e,t,a,n,r){return Yg(e,t,a,n,r,0)}function m7(e,t,a,n,r,s){return Yg(e,t,a,n,r,0,!1,s,!0)}function f7(e,t,a,n,r,s){return Yg(e,t,a,n,r,s,!0)}function Yg(e,t,a,n,r,s,i=!1,o=!1,l=!1){let u=[];for(let g=0;g<t.length;g++)t[g]>r&&u.push({score:t[g],boxIndex:g,suppressBeginIndex:0});u.sort(t5);let p=s>0?-.5/s:0,c=[],d=[];for(;c.length<a&&u.length>0;){let g=u.pop(),{score:y,boxIndex:x,suppressBeginIndex:A}=g;if(y<r)break;let b=!1;for(let w=c.length-1;w>=A;--w){let I=LP(e,x,c[w]);if(I>=n){b=!0;break}if(g.score=g.score*WP(n,p,I),g.score<=r)break}g.suppressBeginIndex=c.length,b||(g.score===y?(c.push(x),d.push(g.score)):g.score>r&&FP(u,g,t5))}let h=c.length,m=a-h;o&&m>0&&(c.push(...new Array(m).fill(0)),d.push(...new Array(m).fill(0)));let f={selectedIndices:c};return i&&(f.selectedScores=d),l&&(f.validOutputs=h),f}function LP(e,t,a){let n=e.subarray(t*4,t*4+4),r=e.subarray(a*4,a*4+4),s=Math.min(n[0],n[2]),i=Math.min(n[1],n[3]),o=Math.max(n[0],n[2]),l=Math.max(n[1],n[3]),u=Math.min(r[0],r[2]),p=Math.min(r[1],r[3]),c=Math.max(r[0],r[2]),d=Math.max(r[1],r[3]),h=(o-s)*(l-i),m=(c-u)*(d-p);if(h<=0||m<=0)return 0;let f=Math.max(s,u),g=Math.max(i,p),y=Math.min(o,c),x=Math.min(l,d),A=Math.max(y-f,0)*Math.max(x-g,0);return A/(h+m-A)}function WP(e,t,a){let n=Math.exp(t*a*a);return a<=e?n:0}function t5(e,t){return e.score-t.score||e.score===t.score&&t.boxIndex-e.boxIndex}async function BP(e,t,a,n=.5,r=Number.NEGATIVE_INFINITY){let s=R(e,"boxes","nonMaxSuppressionAsync"),i=R(t,"scores","nonMaxSuppressionAsync"),o=Hu(s,i,a,n,r);a=o.maxOutputSize,n=o.iouThreshold,r=o.scoreThreshold;let l=await Promise.all([s.data(),i.data()]),u=l[0],p=l[1],{selectedIndices:c}=h7(u,p,a,n,r);return s!==e&&s.dispose(),i!==t&&i.dispose(),Bt(c,"int32")}var VP=BP;function UP(e,t,a,n=.5,r=Number.NEGATIVE_INFINITY,s=0){let i=R(e,"boxes","nonMaxSuppression"),o=R(t,"scores","nonMaxSuppression"),l=Hu(i,o,a,n,r,s);a=l.maxOutputSize,n=l.iouThreshold,r=l.scoreThreshold,s=l.softNmsSigma;let u={boxes:i,scores:o},p={maxOutputSize:a,iouThreshold:n,scoreThreshold:r,softNmsSigma:s},c=L.runKernel(bo,u,p);return{selectedIndices:c[0],selectedScores:c[1]}}var GP=z({nonMaxSuppressionWithScore_:UP});async function HP(e,t,a,n=.5,r=Number.NEGATIVE_INFINITY,s=0){let i=R(e,"boxes","nonMaxSuppressionAsync"),o=R(t,"scores","nonMaxSuppressionAsync"),l=Hu(i,o,a,n,r,s);a=l.maxOutputSize,n=l.iouThreshold,r=l.scoreThreshold,s=l.softNmsSigma;let u=await Promise.all([i.data(),o.data()]),p=u[0],c=u[1],{selectedIndices:d,selectedScores:h}=f7(p,c,a,n,r,s);return i!==e&&i.dispose(),o!==t&&o.dispose(),{selectedIndices:Bt(d,"int32"),selectedScores:Bt(h)}}var jP=HP;function qP(e,t,a,n=.5,r=Number.NEGATIVE_INFINITY,s=!1){let i=R(e,"boxes","nonMaxSuppression"),o=R(t,"scores","nonMaxSuppression"),l=Hu(i,o,a,n,r,null),u=l.maxOutputSize,p=l.iouThreshold,c=l.scoreThreshold,d={boxes:i,scores:o},h={maxOutputSize:u,iouThreshold:p,scoreThreshold:c,padToMaxOutputSize:s},m=L.runKernel(Cu,d,h);return{selectedIndices:m[0],validOutputs:m[1]}}var XP=z({nonMaxSuppressionPadded_:qP});async function KP(e,t,a,n=.5,r=Number.NEGATIVE_INFINITY,s=!1){let i=R(e,"boxes","nonMaxSuppressionAsync"),o=R(t,"scores","nonMaxSuppressionAsync"),l=Hu(i,o,a,n,r,null),u=l.maxOutputSize,p=l.iouThreshold,c=l.scoreThreshold,[d,h]=await Promise.all([i.data(),o.data()]),{selectedIndices:m,validOutputs:f}=m7(d,h,u,p,c,s);return i!==e&&i.dispose(),o!==t&&o.dispose(),{selectedIndices:Bt(m,"int32"),validOutputs:Ge(f,"int32")}}var YP=KP;function ZP(e,t,a=!1,n=!1){let r=R(e,"images","resizeBilinear");F(r.rank===3||r.rank===4,()=>`Error in resizeBilinear: x must be rank 3 or 4, but got rank ${r.rank}.`),F(t.length===2,()=>`Error in resizeBilinear: new shape must 2D, but got shape ${t}.`),F(n===!1||a===!1,()=>"Error in resizeBilinear: If halfPixelCenters is true, alignCorners must be false.");let s=r,i=!1;r.rank===3&&(i=!0,s=Q(r,[1,r.shape[0],r.shape[1],r.shape[2]]));let[]=t,o={images:s},l={alignCorners:a,halfPixelCenters:n,size:t},u=L.runKernel(Ro,o,l);return i?Q(u,[u.shape[1],u.shape[2],u.shape[3]]):u}var JP=z({resizeBilinear_:ZP});function QP(e,t,a=!1,n=!1){let r=R(e,"images","resizeNearestNeighbor");F(r.rank===3||r.rank===4,()=>`Error in resizeNearestNeighbor: x must be rank 3 or 4, but got rank ${r.rank}.`),F(t.length===2,()=>`Error in resizeNearestNeighbor: new shape must 2D, but got shape ${t}.`),F(r.dtype==="float32"||r.dtype==="int32",()=>"`images` must have `int32` or `float32` as dtype"),F(n===!1||a===!1,()=>"Error in resizeNearestNeighbor: If halfPixelCenters is true, alignCorners must be false.");let s=r,i=!1;r.rank===3&&(i=!0,s=Q(r,[1,r.shape[0],r.shape[1],r.shape[2]]));let[]=t,o={images:s},l={alignCorners:a,halfPixelCenters:n,size:t},u=L.runKernel(No,o,l);return i?Q(u,[u.shape[1],u.shape[2],u.shape[3]]):u}var e_=z({resizeNearestNeighbor_:QP});function t_(e,t="binary",a=!1,n=.5){let r=R(e,"image","threshold"),s=.2989,i=.587,o=.114,l=r.shape[0]*r.shape[1],u=te(Bt([n]),255),p,c,d,h;if(F(r.rank===3,()=>`Error in threshold: image must be rank 3,but got rank ${r.rank}.`),F(r.shape[2]===3||r.shape[2]===1,()=>`Error in threshold: image color channel must be equal to 3 or 1but got ${r.shape[2]}.`),F(r.dtype==="int32"||r.dtype==="float32",()=>`Error in dtype: image dtype must be int32 or float32,but got dtype ${r.dtype}.`),F(t==="otsu"||t==="binary",()=>`Method must be binary or otsu, but was ${t}`),r.shape[2]===3){[p,c,d]=Sa(r,[1,1,1],-1);let f=te(p,s),g=te(c,i),y=te(d,o);h=we(we(f,g),y)}else h=e;if(t==="otsu"){let f=fg(Ue(Bg(h),"int32"),Ve([]),256);u=a_(f,l)}let m=a?zh(h,u):Gp(h,u);return Ue(te(m,255),"int32")}function a_(e,t){let a=Bt([-1]),n=Bt([0]),r=Bt([0]),s,i,o,l,u,p;for(let c=0;c<e.size-1;c++){s=Fe(e,0,c+1),i=Fe(e,c+1),u=ve(ot(s),t),p=ve(ot(i),t);let d=ot(te(s,Jl(0,s.size)));o=ve(d,ot(s));let h=or(i.shape,s.size),m=we(Jl(0,i.size),h),f=te(i,m);l=ve(ot(f),ot(i));let g=xe(o,l),y=xe(o,l),x=te(u,p);r=te(te(x,g),y);let A=Gp(r,n);n=Sr(A,r,n),a=Sr(A,Bt([c]),a)}return a}var n_=z({threshold_:t_});function r_(e,t,a="nearest",n="constant",r=0,s){let i=R(e,"image","transform","float32"),o=R(t,"transforms","transform","float32");F(i.rank===4,()=>`Error in transform: image must be rank 4,but got rank ${i.rank}.`),F(o.rank===2&&(o.shape[0]===i.shape[0]||o.shape[0]===1)&&o.shape[1]===8,()=>"Error in transform: Input transform should be batch x 8 or 1 x 8"),F(s==null||s.length===2,()=>`Error in transform: outputShape must be [height, width] or null, but got ${s}.`);let l={image:i,transforms:o},u={interpolation:a,fillMode:n,fillValue:r,outputShape:s};return L.runKernel(Qo,l,u)}var s_=z({transform_:r_});function i_(e,t,a){let n=R(e,"a","bandPart");F(n.rank>=2,()=>`bandPart(): Rank must be at least 2, got ${n.rank}.`);let r=n.shape,[s,i]=n.shape.slice(-2),o,l;typeof t=="number"?(F(t%1===0,()=>`bandPart(): numLower must be an integer, got ${t}.`),F(t<=s,()=>`bandPart(): numLower (${t}) must not be greater than the number of rows (${s}).`),o=R(t<0?s:t,"numLower","bandPart")):(F(t.dtype==="int32",()=>"bandPart(): numLower's dtype must be an int32."),o=Sr(mh(t,0),s,Zd(t,s))),typeof a=="number"?(F(a%1===0,()=>`bandPart(): numUpper must be an integer, got ${a}.`),F(a<=i,()=>`bandPart(): numUpper (${a}) must not be greater than the number of columns (${i}).`),l=R(a<0?i:a,"numUpper","bandPart")):(F(a.dtype==="int32",()=>"bandPart(): numUpper's dtype must be an int32."),l=Sr(mh(a,0),i,Zd(a,i)));let u=Q(Jl(0,s,1,"int32"),[-1,1]),p=Jl(0,i,1,"int32"),c=xe(u,p),d=Kd(zh(c,o),kg(c,Wn(l))),h=yn([s,i],n.dtype);return Q(ha(Na(Q(n,[-1,s,i])).map(m=>Sr(d,m,h))),r)}var o_=z({bandPart_:i_});function l_(e){let t;if(Array.isArray(e)){t=!1,F(e!=null&&e.length>0,()=>"Gram-Schmidt process: input must not be null, undefined, or empty");let r=e[0].shape[0];for(let s=1;s<e.length;++s)F(e[s].shape[0]===r,()=>`Gram-Schmidt: Non-unique lengths found in the input vectors: (${e[s].shape[0]} vs. ${r})`)}else t=!0,e=Sa(e,e.shape[0],0).map(r=>Oe(r,[0]));F(e.length<=e[0].shape[0],()=>`Gram-Schmidt: Number of vectors (${e.length}) exceeds number of dimensions (${e[0].shape[0]}).`);let a=[],n=e;for(let r=0;r<e.length;++r)a.push(L.tidy(()=>{let s=n[r];if(r>0)for(let i=0;i<r;++i){let o=te(ot(te(a[i],s)),a[i]);s=xe(s,o)}return ve(s,Up(s,"euclidean"))}));return t?ha(a,0):a}var u_=z({gramSchmidt_:l_});function d_(e,t=!1){if(F(e.rank>=2,()=>`qr() requires input tensor to have a rank >= 2, but got rank ${e.rank}`),e.rank===2)return a5(e,t);{let a=e.shape.slice(0,e.shape.length-2).reduce((l,u)=>l*u),n=Na(Q(e,[a,e.shape[e.shape.length-2],e.shape[e.shape.length-1]]),0),r=[],s=[];n.forEach(l=>{let[u,p]=a5(l,t);r.push(u),s.push(p)});let i=Q(ha(r,0),e.shape),o=Q(ha(s,0),e.shape);return[i,o]}}function a5(e,t=!1){return L.tidy(()=>{F(e.shape.length===2,()=>`qr2d() requires a 2D Tensor, but got a ${e.shape.length}D Tensor.`);let a=e.shape[0],n=e.shape[1],r=bg(a),s=Ia(e),i=Qn([[1]],[1,1]),o=Ia(i),l=a>=n?n:a;for(let u=0;u<l;++u){let p=s,c=o,d=r;[o,s,r]=L.tidy(()=>{let h=Fe(s,[u,u],[a-u,1]),m=Up(h),f=Fe(s,[u,u],[1,1]),g=Sr(Gp(f,0),Qn([[-1]]),Qn([[1]])),y=xe(f,te(g,m)),x=ve(h,y);x.shape[0]===1?o=Ia(i):o=lt([i,Fe(x,[1,0],[x.shape[0]-1,x.shape[1]])],0);let A=Wn(ve(pt(g,y),m)),b=Fe(s,[u,0],[a-u,n]),w=te(A,o),I=Qs(o);if(u===0)s=xe(b,pt(w,pt(I,b)));else{let M=xe(b,pt(w,pt(I,b)));s=lt([Fe(s,[0,0],[u,n]),M],0)}let T=Qs(w),N=Fe(r,[0,u],[a,r.shape[1]-u]);if(u===0)r=xe(N,pt(pt(N,o),T));else{let M=xe(N,pt(pt(N,o),T));r=lt([Fe(r,[0,0],[a,u]),M],1)}return[o,s,r]}),J([p,c,d])}return!t&&a>n&&(r=Fe(r,[0,0],[a,n]),s=Fe(s,[0,0],[n,n])),[r,s]})}var p_=z({qr_:d_}),wa;(function(e){e[e.NONE=0]="NONE",e[e.MEAN=1]="MEAN",e[e.SUM=2]="SUM",e[e.SUM_BY_NONZERO_WEIGHTS=3]="SUM_BY_NONZERO_WEIGHTS"})(wa||(wa={}));function c_(e,t,a=wa.SUM_BY_NONZERO_WEIGHTS){let n=R(e,"losses","computeWeightedLoss"),r=null;t!=null&&(r=R(t,"weights","computeWeightedLoss"));let s=r==null?n:te(n,r);if(a===wa.NONE)return s;if(a===wa.SUM)return ot(s);if(a===wa.MEAN){if(r==null)return Yd(s);{let i=n.size/r.size,o=ve(ot(s),ot(r));return i>1?ve(o,Ge(i)):o}}if(a===wa.SUM_BY_NONZERO_WEIGHTS){if(r==null)return ve(ot(s),Ge(n.size));{let i=te(r,jr(n.shape)),o=Ue(ot($g(i,Ge(0))),"float32");return ve(ot(s),o)}}throw Error(`Unknown reduction: ${a}`)}var Mr=z({computeWeightedLoss_:c_});function h_(e,t,a,n=wa.SUM_BY_NONZERO_WEIGHTS){let r=R(e,"labels","absoluteDifference"),s=R(t,"predictions","absoluteDifference"),i=null;a!=null&&(i=R(a,"weights","absoluteDifference")),Ta(r.shape,s.shape,"Error in absoluteDifference: ");let o=Za(xe(r,s));return Mr(o,i,n)}var m_=z({absoluteDifference_:h_});function f_(e,t,a,n,r=wa.SUM_BY_NONZERO_WEIGHTS){let s=R(e,"labels","cosineDistance"),i=R(t,"predictions","cosineDistance"),o=null;n!=null&&(o=R(n,"weights","cosineDistance")),Ta(s.shape,i.shape,"Error in cosineDistance: ");let l=Ge(1),u=xe(l,ot(te(s,i),a,!0));return Mr(u,o,r)}var g_=z({cosineDistance_:f_});function y_(e,t,a,n=wa.SUM_BY_NONZERO_WEIGHTS){let r=R(e,"labels","hingeLoss"),s=R(t,"predictions","hingeLoss"),i=null;a!=null&&(i=R(a,"weights","hingeLoss")),Ta(r.shape,s.shape,"Error in hingeLoss: ");let o=Ge(1);r=xe(te(Ge(2),r),o);let l=jp(xe(o,te(r,s)));return Mr(l,i,n)}var x_=z({hingeLoss_:y_});function A_(e,t,a,n=1,r=wa.SUM_BY_NONZERO_WEIGHTS){let s=R(e,"labels","huberLoss"),i=R(t,"predictions","huberLoss"),o=null;a!=null&&(o=R(a,"weights","huberLoss")),Ta(s.shape,i.shape,"Error in huberLoss: ");let l=Ge(n),u=Za(xe(i,s)),p=Zd(u,l),c=xe(u,p),d=we(te(Ge(.5),Tn(p)),te(l,c));return Mr(d,o,r)}var b_=z({huberLoss_:A_});function v_(e,t,a,n=1e-7,r=wa.SUM_BY_NONZERO_WEIGHTS){let s=R(e,"labels","logLoss"),i=R(t,"predictions","logLoss"),o=null;a!=null&&(o=R(a,"weights","logLoss")),Ta(s.shape,i.shape,"Error in logLoss: ");let l=Ge(1),u=Ge(n),p=Wn(te(s,Zl(we(i,u)))),c=te(xe(l,s),Zl(we(xe(l,i),u))),d=xe(p,c);return Mr(d,o,r)}var w_=z({logLoss_:v_});function k_(e,t,a,n=wa.SUM_BY_NONZERO_WEIGHTS){let r=R(e,"labels","meanSquaredError"),s=R(t,"predictions","meanSquaredError"),i=null;a!=null&&(i=R(a,"weights","meanSquaredError")),Ta(r.shape,s.shape,"Error in meanSquaredError: ");let o=Ug(r,s);return Mr(o,i,n)}var I_=z({meanSquaredError_:k_});function S_(e,t){let a=R(e,"labels","sigmoidCrossEntropyWithLogits"),n=R(t,"logits","sigmoidCrossEntropyWithLogits");Ta(a.shape,n.shape,"Error in sigmoidCrossEntropyWithLogits: ");let r=jp(n),s=te(n,a),i=Sg(rs(Wn(Za(n))));return we(xe(r,s),i)}function C_(e,t,a,n=0,r=wa.SUM_BY_NONZERO_WEIGHTS){let s=R(e,"multiClassLabels","sigmoidCrossEntropy"),i=R(t,"logits","sigmoidCrossEntropy"),o=null;if(a!=null&&(o=R(a,"weights","sigmoidCrossEntropy")),Ta(s.shape,i.shape,"Error in sigmoidCrossEntropy: "),n>0){let u=Ge(n),p=Ge(1),c=Ge(.5);s=we(te(s,xe(p,u)),te(c,u))}let l=S_(s,i);return Mr(l,o,r)}var T_=z({sigmoidCrossEntropy_:C_});function N_(e,t,a=-1){if(a===-1&&(a=t.rank-1),a!==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 ${a}`);return nr((n,r,s)=>{let i=Tg(r,[a],!0),o=xe(Ue(r,"float32"),i);s([n,o]);let l=Wn(te(o,n));return{value:ot(l,[a]),gradFunc:(u,p)=>{let[c,d]=p,h=Vp(u.shape,[a]);return[te(Q(u,h),xe(Ue(c,"float32"),rs(d))),te(Q(u,h),xe(rs(d),Ue(c,"float32")))]}}})(e,t)}function R_(e,t,a,n=0,r=wa.SUM_BY_NONZERO_WEIGHTS){let s=R(e,"onehotLabels","softmaxCrossEntropy"),i=R(t,"logits","softmaxCrossEntropy"),o=null;if(a!=null&&(o=R(a,"weights","softmaxCrossEntropy")),Ta(s.shape,i.shape,"Error in softmaxCrossEntropy: "),n>0){let u=Ge(n),p=Ge(1),c=Ge(s.shape[1]);s=we(te(s,xe(p,u)),ve(u,c))}let l=N_(s,i);return Mr(l,o,r)}var E_=z({softmaxCrossEntropy_:R_});function M_(e,t,a,n){let r=R(e,"indices","sparseFillEmptyRows","int32"),s=R(t,"values","sparseFillEmptyRows"),i=R(a,"denseShape","sparseFillEmptyRows","int32"),o=R(n,"defaultValue","sparseFillEmptyRows",s.dtype);if(r.rank!==2)throw new Error(`Indices should be Tensor2D but received shape
        ${r.shape}`);if(s.rank!==1)throw new Error(`Values should be Tensor1D but received shape ${s.shape}`);if(i.rank!==1)throw new Error(`Dense shape should be Tensor1D but received shape ${i.shape}`);if(o.rank!==0)throw new Error(`Default value should be a scalar but received shape ${o.shape}`);let l={indices:r,values:s,denseShape:i,defaultValue:o},u=L.runKernel(Sp,l);return{outputIndices:u[0],outputValues:u[1],emptyRowIndicator:u[2],reverseIndexMap:u[3]}}var $_=z({sparseFillEmptyRows_:M_});function P_(e,t,a){let n=R(e,"inputIndices","sparseReshape","int32"),r=R(t,"inputShape","sparseReshape","int32"),s=R(a,"newShape","sparseReshape","int32");if(n.rank!==2)throw new Error(`Input indices should be Tensor2D but received shape
        ${n.shape}`);if(r.rank!==1)throw new Error(`Input shape should be Tensor1D but received shape ${r.shape}`);if(s.rank!==1)throw new Error(`New shape should be Tensor1D but received shape ${s.shape}`);let i={inputIndices:n,inputShape:r,newShape:s},o=L.runKernel(Ou,i);return{outputIndices:o[0],outputShape:o[1]}}var __=z({sparseReshape_:P_});function F_(e,t,a){let n=R(e,"data","sparseSegmentMean"),r=R(t,"indices","sparseSegmentMean","int32"),s=R(a,"segmentIds","sparseSegmentMean","int32");if(n.rank<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(r.rank!==1)throw new Error(`Indices should be Tensor1D but received shape
          ${r.shape}`);if(s.rank!==1)throw new Error(`Segment ids should be Tensor1D but received shape
          ${s.shape}`);let i={data:n,indices:r,segmentIds:s};return L.runKernel(zu,i)}var D_=z({sparseSegmentMean_:F_});function O_(e,t,a){let n=R(e,"data","sparseSegmentSum"),r=R(t,"indices","sparseSegmentSum","int32"),s=R(a,"segmentIds","sparseSegmentSum","int32");if(n.rank<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(r.rank!==1)throw new Error(`Indices should be Tensor1D but received shape
         ${r.shape}`);if(s.rank!==1)throw new Error(`Segment ids should be Tensor1D but received shape
         ${s.shape}`);let i={data:n,indices:r,segmentIds:s};return L.runKernel(Lu,i)}var z_=z({sparseSegmentSum_:O_});function L_(e,t,a,n,r,s,i,o){let l=R(e,"data","stringNGrams","string");if(l.dtype!=="string")throw new Error("Data must be of datatype string");if(l.shape.length!==1)throw new Error(`Data must be a vector, saw: ${l.shape}`);let u=R(t,"dataSplits","stringNGrams");if(u.dtype!=="int32")throw new Error("Data splits must be of datatype int32");let p={separator:a,nGramWidths:n,leftPad:r,rightPad:s,padWidth:i,preserveShortSequences:o},c={data:l,dataSplits:u},d=L.runKernel(Wu,c,p);return{nGrams:d[0],nGramsSplits:d[1]}}var W_=z({stringNGrams_:L_});function B_(e,t,a=!0){let n=R(e,"input","stringSplit","string"),r=R(t,"delimiter","stringSplit","string");if(n.rank!==1)throw new Error(`Input should be Tensor1D but received shape ${n.shape}`);if(r.rank!==0)throw new Error(`Delimiter should be a scalar but received shape ${r.shape}`);let s={skipEmpty:a},i={input:n,delimiter:r},o=L.runKernel(Np,i,s);return{indices:o[0],values:o[1],shape:o[2]}}var V_=z({stringSplit_:B_});function U_(e,t){let a=R(e,"input","stringToHashBucketFast","string"),n={numBuckets:t};if(t<=0)throw new Error("Number of buckets must be at least 1");let r={input:a};return L.runKernel(Rp,r,n)}var G_=z({stringToHashBucketFast_:U_});function H_(e,t,a,n=!0){let r=R(e,"input","staticRegexReplace","string"),s={pattern:t,rewrite:a,replaceGlobal:n};return L.runKernel(Tp,{x:r},s)}var j_=z({staticRegexReplace_:H_}),g7={fft:Gh,ifft:Jd,rfft:Hh,irfft:Vg},y7={hammingWindow:xP,hannWindow:p7,frame:c7,stft:wP},fe={flipLeftRight:CP,grayscaleToRGB:NP,resizeNearestNeighbor:e_,resizeBilinear:JP,rgbToGrayscale:EP,rotateWithOffset:$P,cropAndResize:IP,nonMaxSuppression:_P,nonMaxSuppressionAsync:VP,nonMaxSuppressionWithScore:GP,nonMaxSuppressionWithScoreAsync:jP,nonMaxSuppressionPadded:XP,nonMaxSuppressionPaddedAsync:YP,threshold:n_,transform:s_},x7={bandPart:o_,gramSchmidt:u_,qr:p_},A7={absoluteDifference:m_,computeWeightedLoss:Mr,cosineDistance:g_,hingeLoss:x_,huberLoss:b_,logLoss:w_,meanSquaredError:I_,sigmoidCrossEntropy:T_,softmaxCrossEntropy:E_},b7={sparseFillEmptyRows:$_,sparseReshape:__,sparseSegmentMean:D_,sparseSegmentSum:z_},v7={stringNGrams:W_,stringSplit:V_,stringToHashBucketFast:G_,staticRegexReplace:j_},w7={};Ze(w7,{Serializable:()=>k7,SerializationMap:()=>I7,getRegisteredName:()=>X_,registerClass:()=>S7});var q_=new Map,g1=new Map,k7=class{getClassName(){return this.constructor.className}static fromConfig(e,t){return new e(t)}},I7=class Wl{constructor(){this.classNameMap={}}static getMap(){return Wl.instance==null&&(Wl.instance=new Wl),Wl.instance}static register(t){Wl.getMap().classNameMap[t.className]=[t,t.fromConfig]}};function S7(e,t,a){F(e.className!=null,()=>"Class being registered does not have the static className property defined."),F(typeof e.className=="string",()=>"className is required to be a string, but got type "+typeof e.className),F(e.className.length>0,()=>"Class being registered has an empty-string as its className, which is disallowed."),typeof t=="undefined"&&(t="Custom"),typeof a=="undefined"&&(a=e.className);let n=a,r=t+">"+n;return I7.register(e),q_.set(r,e),g1.set(e,r),e}function X_(e){return g1.has(e)?g1.get(e):e.className}var hs=class extends k7{minimize(e,t=!1,a){let{value:n,grads:r}=this.computeGradients(e,a);if(a!=null){let s=a.map(i=>({name:i.name,tensor:r[i.name]}));this.applyGradients(s)}else this.applyGradients(r);return J(r),t?n:(n.dispose(),null)}get iterations(){return this.iterations_==null&&(this.iterations_=0),this.iterations_}incrementIterations(){this.iterations_=this.iterations+1}computeGradients(e,t){return e4(e,t)}dispose(){this.iterations_!=null&&J(this.iterations_)}async saveIterations(){return this.iterations_==null&&(this.iterations_=0),{name:"iter",tensor:Ge(this.iterations_,"int32")}}async getWeights(){throw new Error("getWeights() is not implemented for this optimizer yet.")}async setWeights(e){throw new Error(`setWeights() is not implemented for this optimizer class ${this.getClassName()}`)}async extractIterations(e){return this.iterations_=(await e[0].tensor.data())[0],e.slice(1)}};Object.defineProperty(hs,Symbol.hasInstance,{value:e=>e.minimize!=null&&e.computeGradients!=null&&e.applyGradients!=null});var Zg=class extends hs{static get className(){return"Adadelta"}constructor(e,t,a=null){super(),this.learningRate=e,this.rho=t,this.epsilon=a,this.accumulatedGrads=[],this.accumulatedUpdates=[],a==null&&(this.epsilon=L.backend.epsilon())}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,a)=>{let n=L.registeredVariables[t],r=!1;this.accumulatedGrads[a]==null&&(this.accumulatedGrads[a]={originalName:`${t}/accum_grad`,variable:De(()=>Qa(n).variable(r))}),this.accumulatedUpdates[a]==null&&(this.accumulatedUpdates[a]={originalName:`${t}/accum_var`,variable:De(()=>Qa(n).variable(r))});let s=Array.isArray(e)?e[a].tensor:e[t];if(s==null)return;let i=this.accumulatedGrads[a].variable,o=this.accumulatedUpdates[a].variable;De(()=>{let l=we(te(i,this.rho),te(Tn(s),1-this.rho)),u=te(ve(ar(we(o,this.epsilon)),ar(we(i,this.epsilon))),s),p=we(te(o,this.rho),te(Tn(u),1-this.rho));i.assign(l),o.assign(p);let c=we(te(u,-this.learningRate),n);n.assign(c)})}),this.incrementIterations()}dispose(){this.accumulatedUpdates!=null&&(J(this.accumulatedGrads.map(e=>e.variable)),J(this.accumulatedUpdates.map(e=>e.variable)))}async getWeights(){let e=[...this.accumulatedGrads,...this.accumulatedUpdates];return[await this.saveIterations()].concat(e.map(t=>({name:t.originalName,tensor:t.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=e.length/2,a=!1;this.accumulatedGrads=e.slice(0,t).map(n=>({originalName:n.name,variable:n.tensor.variable(a)})),this.accumulatedUpdates=e.slice(t,t*2).map(n=>({originalName:n.name,variable:n.tensor.variable(a)}))}getConfig(){return{learningRate:this.learningRate,rho:this.rho,epsilon:this.epsilon}}static fromConfig(e,t){return new e(t.learningRate,t.rho,t.epsilon)}},Jg=class extends hs{static get className(){return"Adagrad"}constructor(e,t=.1){super(),this.learningRate=e,this.initialAccumulatorValue=t,this.accumulatedGrads=[]}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,a)=>{let n=L.registeredVariables[t];this.accumulatedGrads[a]==null&&(this.accumulatedGrads[a]={originalName:`${t}/accumulator`,variable:De(()=>or(n.shape,this.initialAccumulatorValue).variable(!1))});let r=Array.isArray(e)?e[a].tensor:e[t];if(r==null)return;let s=this.accumulatedGrads[a].variable;De(()=>{let i=we(s,Tn(r));s.assign(i);let o=we(te(ve(r,ar(we(i,L.backend.epsilon()))),-this.learningRate),n);n.assign(o)})}),this.incrementIterations()}dispose(){this.accumulatedGrads!=null&&J(this.accumulatedGrads.map(e=>e.variable))}async getWeights(){return[await this.saveIterations()].concat(this.accumulatedGrads.map(e=>({name:e.originalName,tensor:e.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=!1;this.accumulatedGrads=e.map(a=>({originalName:a.name,variable:a.tensor.variable(t)}))}getConfig(){return{learningRate:this.learningRate,initialAccumulatorValue:this.initialAccumulatorValue}}static fromConfig(e,t){return new e(t.learningRate,t.initialAccumulatorValue)}},Qg=class extends hs{static get className(){return"Adam"}constructor(e,t,a,n=null){super(),this.learningRate=e,this.beta1=t,this.beta2=a,this.epsilon=n,this.accumulatedFirstMoment=[],this.accumulatedSecondMoment=[],De(()=>{this.accBeta1=Ge(t).variable(),this.accBeta2=Ge(a).variable()}),n==null&&(this.epsilon=L.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(a=>a.name):Object.keys(e);De(()=>{let a=xe(1,this.accBeta1),n=xe(1,this.accBeta2);t.forEach((r,s)=>{let i=L.registeredVariables[r],o=!1;this.accumulatedFirstMoment[s]==null&&(this.accumulatedFirstMoment[s]={originalName:`${r}/m`,variable:De(()=>Qa(i).variable(o))}),this.accumulatedSecondMoment[s]==null&&(this.accumulatedSecondMoment[s]={originalName:`${r}/v`,variable:De(()=>Qa(i).variable(o))});let l=Array.isArray(e)?e[s].tensor:e[r];if(l==null)return;let u=this.accumulatedFirstMoment[s].variable,p=this.accumulatedSecondMoment[s].variable,c=we(te(u,this.beta1),te(l,1-this.beta1)),d=we(te(p,this.beta2),te(Tn(l),1-this.beta2)),h=ve(c,a),m=ve(d,n);u.assign(c),p.assign(d);let f=we(te(ve(h,we(ar(m),this.epsilon)),-this.learningRate),i);i.assign(f)}),this.accBeta1.assign(te(this.accBeta1,this.beta1)),this.accBeta2.assign(te(this.accBeta2,this.beta2))}),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.accBeta2.dispose(),this.accumulatedFirstMoment!=null&&J(this.accumulatedFirstMoment.map(e=>e.variable)),this.accumulatedSecondMoment!=null&&J(this.accumulatedSecondMoment.map(e=>e.variable))}async getWeights(){let e=[...this.accumulatedFirstMoment,...this.accumulatedSecondMoment];return[await this.saveIterations()].concat(e.map(t=>({name:t.originalName,tensor:t.variable})))}async setWeights(e){e=await this.extractIterations(e),De(()=>{this.accBeta1.assign(Yl(this.beta1,this.iterations_+1)),this.accBeta2.assign(Yl(this.beta2,this.iterations_+1))});let t=e.length/2,a=!1;this.accumulatedFirstMoment=e.slice(0,t).map(n=>({originalName:n.name,variable:n.tensor.variable(a)})),this.accumulatedSecondMoment=e.slice(t,t*2).map(n=>({originalName:n.name,variable:n.tensor.variable(a)}))}getConfig(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon}}static fromConfig(e,t){return new e(t.learningRate,t.beta1,t.beta2,t.epsilon)}},e3=class extends hs{static get className(){return"Adamax"}constructor(e,t,a,n=null,r=0){super(),this.learningRate=e,this.beta1=t,this.beta2=a,this.epsilon=n,this.decay=r,this.accumulatedFirstMoment=[],this.accumulatedWeightedInfNorm=[],De(()=>{this.iteration=Ge(0).variable(),this.accBeta1=Ge(t).variable()}),n==null&&(this.epsilon=L.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(a=>a.name):Object.keys(e);De(()=>{let a=xe(1,this.accBeta1),n=ve(-this.learningRate,we(te(this.iteration,this.decay),1));t.forEach((r,s)=>{let i=L.registeredVariables[r],o=!1;this.accumulatedFirstMoment[s]==null&&(this.accumulatedFirstMoment[s]={originalName:`${r}/m`,variable:Qa(i).variable(o)}),this.accumulatedWeightedInfNorm[s]==null&&(this.accumulatedWeightedInfNorm[s]={originalName:`${r}/v`,variable:Qa(i).variable(o)});let l=Array.isArray(e)?e[s].tensor:e[r];if(l==null)return;let u=this.accumulatedFirstMoment[s].variable,p=this.accumulatedWeightedInfNorm[s].variable,c=we(te(u,this.beta1),te(l,1-this.beta1)),d=te(p,this.beta2),h=Za(l),m=Mg(d,h);u.assign(c),p.assign(m);let f=we(te(ve(n,a),ve(c,we(m,this.epsilon))),i);i.assign(f)}),this.iteration.assign(we(this.iteration,1)),this.accBeta1.assign(te(this.accBeta1,this.beta1))}),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.iteration.dispose(),this.accumulatedFirstMoment!=null&&J(this.accumulatedFirstMoment.map(e=>e.variable)),this.accumulatedWeightedInfNorm!=null&&J(this.accumulatedWeightedInfNorm.map(e=>e.variable))}async getWeights(){throw new Error("getWeights() is not implemented for Adamax yet.")}async setWeights(e){throw new Error("setWeights() is not implemented for Adamax yet.")}getConfig(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon,decay:this.decay}}static fromConfig(e,t){return new e(t.learningRate,t.beta1,t.beta2,t.epsilon,t.decay)}},Qh=class extends hs{static get className(){return"SGD"}constructor(e){super(),this.learningRate=e,this.setLearningRate(e)}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,a)=>{let n=Array.isArray(e)?e[a].tensor:e[t];if(n==null)return;let r=L.registeredVariables[t];De(()=>{let s=we(te(this.c,n),r);r.assign(s)})}),this.incrementIterations()}setLearningRate(e){this.learningRate=e,this.c!=null&&this.c.dispose(),this.c=Ln(Ge(-e))}dispose(){this.c.dispose()}async getWeights(){return[await this.saveIterations()]}async setWeights(e){if(e=await this.extractIterations(e),e.length!==0)throw new Error("SGD optimizer does not have settable weights.")}getConfig(){return{learningRate:this.learningRate}}static fromConfig(e,t){return new e(t.learningRate)}},t3=class extends Qh{static get className(){return"Momentum"}constructor(e,t,a=!1){super(e),this.learningRate=e,this.momentum=t,this.useNesterov=a,this.accumulations=[],this.m=Ge(this.momentum)}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,a)=>{let n=L.registeredVariables[t];this.accumulations[a]==null&&(this.accumulations[a]={originalName:`${t}/momentum`,variable:De(()=>Qa(n).variable(!1))});let r=this.accumulations[a].variable,s=Array.isArray(e)?e[a].tensor:e[t];s!=null&&De(()=>{let i,o=we(te(this.m,r),s);this.useNesterov?i=we(te(this.c,we(s,te(o,this.m))),n):i=we(te(this.c,o),n),r.assign(o),n.assign(i)})}),this.incrementIterations()}dispose(){this.m.dispose(),this.accumulations!=null&&J(this.accumulations.map(e=>e.variable))}setMomentum(e){this.momentum=e}async getWeights(){return[await this.saveIterations()].concat(this.accumulations.map(e=>({name:e.originalName,tensor:e.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=!1;this.accumulations=e.map(a=>({originalName:a.name,variable:a.tensor.variable(t)}))}getConfig(){return{learningRate:this.learningRate,momentum:this.momentum,useNesterov:this.useNesterov}}static fromConfig(e,t){return new e(t.learningRate,t.momentum,t.useNesterov)}},a3=class extends hs{static get className(){return"RMSProp"}constructor(e,t=.9,a=0,n=null,r=!1){if(super(),this.learningRate=e,this.decay=t,this.momentum=a,this.epsilon=n,this.accumulatedMeanSquares=[],this.accumulatedMoments=[],this.accumulatedMeanGrads=[],this.centered=r,n==null&&(this.epsilon=L.backend.epsilon()),e==null)throw new Error("learningRate for RMSPropOptimizer must be defined.")}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,a)=>{let n=L.registeredVariables[t],r=!1;this.accumulatedMeanSquares[a]==null&&(this.accumulatedMeanSquares[a]={originalName:`${t}/rms`,variable:De(()=>Qa(n).variable(r))}),this.accumulatedMoments[a]==null&&(this.accumulatedMoments[a]={originalName:`${t}/momentum`,variable:De(()=>Qa(n).variable(r))}),this.accumulatedMeanGrads[a]==null&&this.centered&&(this.accumulatedMeanGrads[a]={originalName:`${t}/mg`,variable:De(()=>Qa(n).variable(r))});let s=Array.isArray(e)?e[a].tensor:e[t];if(s==null)return;let i=this.accumulatedMeanSquares[a].variable,o=this.accumulatedMoments[a].variable;De(()=>{let l=we(te(i,this.decay),te(Tn(s),1-this.decay));if(this.centered){let u=this.accumulatedMeanGrads[a].variable,p=we(te(u,this.decay),te(s,1-this.decay)),c=ve(te(s,this.learningRate),ar(xe(l,we(Tn(p),this.epsilon)))),d=we(te(o,this.momentum),c);i.assign(l),u.assign(p),o.assign(d);let h=xe(n,d);n.assign(h)}else{let u=we(te(i,this.decay),te(Tn(s),1-this.decay)),p=we(te(o,this.momentum),ve(te(s,this.learningRate),ar(we(u,this.epsilon))));i.assign(u),o.assign(p);let c=xe(n,p);n.assign(c)}})}),this.incrementIterations()}dispose(){this.accumulatedMeanSquares!=null&&J(this.accumulatedMeanSquares.map(e=>e.variable)),this.accumulatedMeanGrads!=null&&this.centered&&J(this.accumulatedMeanGrads.map(e=>e.variable)),this.accumulatedMoments!=null&&J(this.accumulatedMoments.map(e=>e.variable))}async getWeights(){let e=[...this.accumulatedMeanSquares,...this.accumulatedMoments];return this.centered&&e.push(...this.accumulatedMeanGrads),[await this.saveIterations()].concat(e.map(t=>({name:t.originalName,tensor:t.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=this.centered?e.length/3:e.length/2,a=!1;this.accumulatedMeanSquares=e.slice(0,t).map(n=>({originalName:n.name,variable:n.tensor.variable(a)})),this.accumulatedMoments=e.slice(t,t*2).map(n=>({originalName:n.name,variable:n.tensor.variable(a)})),this.centered&&(this.accumulatedMeanGrads=e.slice(t*2,t*3).map(n=>({originalName:n.name,variable:n.tensor.variable(a)})))}getConfig(){return{learningRate:this.learningRate,decay:this.decay,momentum:this.momentum,epsilon:this.epsilon,centered:this.centered}}static fromConfig(e,t){return new e(t.learningRate,t.decay,t.momentum,t.epsilon,t.centered)}},K_=[Zg,Jg,Qg,e3,t3,a3,Qh];function Y_(){for(let e of K_)S7(e)}var Zn={};Ze(Zn,{CompositeArrayBuffer:()=>Rr,browserFiles:()=>nF,browserHTTPRequest:()=>uF,concatenateArrayBuffers:()=>NN,copyModel:()=>YN,decodeWeights:()=>GA,decodeWeightsStream:()=>jA,encodeWeights:()=>wN,fromMemory:()=>pF,fromMemorySync:()=>E7,getLoadHandlers:()=>DN,getModelArtifactsForJSON:()=>dg,getModelArtifactsForJSONSync:()=>XA,getModelArtifactsInfoForJSON:()=>Op,getSaveHandlers:()=>FN,getWeightSpecs:()=>d1,http:()=>r3,isHTTPScheme:()=>x1,listModels:()=>XN,loadWeights:()=>sF,moveModel:()=>ZN,registerLoadRouter:()=>_N,registerSaveRouter:()=>PN,removeModel:()=>KN,weightsLoaderFactory:()=>T7,withSaveHandler:()=>cF,withSaveHandlerSync:()=>hF});var Z_="model",J_=".json",Q_=".weights.bin";function n5(e){return new Promise(t=>setTimeout(t)).then(e)}var gh=class y1{constructor(t){if(!B().getBool("IS_BROWSER"))throw new Error("browserDownloads() cannot proceed because the current environment is not a browser.");t.startsWith(y1.URL_SCHEME)&&(t=t.slice(y1.URL_SCHEME.length)),(t==null||t.length===0)&&(t=Z_),this.modelJsonFileName=t+J_,this.weightDataFileName=t+Q_}async save(t){if(typeof document=="undefined")throw new Error("Browser downloads are not supported in this environment since `document` is not present");let a=Rr.join(t.weightData),n=window.URL.createObjectURL(new Blob([a],{type:"application/octet-stream"}));if(t.modelTopology instanceof ArrayBuffer)throw new Error("BrowserDownloads.save() does not support saving model topology in binary formats yet.");{let r=[{paths:["./"+this.weightDataFileName],weights:t.weightSpecs}],s=qA(t,r),i=window.URL.createObjectURL(new Blob([JSON.stringify(s)],{type:"application/json"})),o=this.modelJsonAnchor==null?document.createElement("a"):this.modelJsonAnchor;if(o.download=this.modelJsonFileName,o.href=i,await n5(()=>o.dispatchEvent(new MouseEvent("click"))),t.weightData!=null){let l=this.weightDataAnchor==null?document.createElement("a"):this.weightDataAnchor;l.download=this.weightDataFileName,l.href=n,await n5(()=>l.dispatchEvent(new MouseEvent("click")))}return{modelArtifactsInfo:Op(t)}}}};gh.URL_SCHEME="downloads://";var eF=class{constructor(e){if(e==null||e.length<1)throw new Error(`When calling browserFiles, at least 1 file is required, but received ${e}`);this.jsonFile=e[0],this.weightsFiles=e.slice(1)}async load(){return new Promise((e,t)=>{let a=new FileReader;a.onload=n=>{let r=JSON.parse(n.target.result),s=r.modelTopology;if(s==null){t(new Error(`modelTopology field is missing from file ${this.jsonFile.name}`));return}if(r.weightsManifest==null){t(new Error(`weightManifest field is missing from file ${this.jsonFile.name}`));return}if(this.weightsFiles.length===0){e({modelTopology:s});return}let i=dg(r,o=>this.loadWeights(o));e(i)},a.onerror=n=>t(`Failed to read model topology and weights manifest JSON from file '${this.jsonFile.name}'. BrowserFiles supports loading Keras-style tf.Model artifacts only.`),a.readAsText(this.jsonFile)})}loadWeights(e){let t=[],a=[];for(let s of e)t.push(...s.weights),a.push(...s.paths);let n=this.checkManifestAndWeightFiles(e),r=a.map(s=>this.loadWeightsFile(s,n[s]));return Promise.all(r).then(s=>[t,s])}loadWeightsFile(e,t){return new Promise((a,n)=>{let r=new FileReader;r.onload=s=>{let i=s.target.result;a(i)},r.onerror=s=>n(`Failed to weights data from file of path '${e}'.`),r.readAsArrayBuffer(t)})}checkManifestAndWeightFiles(e){let t=[],a=this.weightsFiles.map(r=>e5(r.name)),n={};for(let r of e)r.paths.forEach(s=>{let i=e5(s);if(t.indexOf(i)!==-1)throw new Error(`Duplicate file basename found in weights manifest: '${i}'`);if(t.push(i),a.indexOf(i)===-1)throw new Error(`Weight file with basename '${i}' is not provided.`);n[s]=this.weightsFiles[a.indexOf(i)]});if(t.length!==this.weightsFiles.length)throw new Error(`Mismatch in the number of files in weights manifest (${t.length}) and the number of weight files provided (${this.weightsFiles.length}).`);return n}},tF=e=>B().getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(gh.URL_SCHEME)?aF(e.slice(gh.URL_SCHEME.length)):null;gn.registerSaveRouter(tF);function aF(e="model"){return new gh(e)}function nF(e){return new eF(e)}function r5(e,t,a,n){i(e),a=a==null?0:a,n=n==null?1:n,o(a,n);let r=0,s=l=>(l.then(u=>{let p=a+ ++r/e.length*(n-a);return t(p),u}),l);function i(l){F(l!=null&&Array.isArray(l)&&l.length>0,()=>"promises must be a none empty array")}function o(l,u){F(l>=0&&l<=1,()=>`Progress fraction must be in range [0, 1], but got startFraction ${l}`),F(u>=0&&u<=1,()=>`Progress fraction must be in range [0, 1], but got endFraction ${u}`),F(u>=l,()=>`startFraction must be no more than endFraction, but got startFraction ${l} and endFraction ${u}`)}return Promise.all(e.map(s))}async function C7(e,t){t==null&&(t={});let a=t.fetchFunc==null?B().platform.fetch:t.fetchFunc,n=e.map(s=>a(s,t.requestInit,{isBinary:!0})),r=(t.onProgress==null?await Promise.all(n):await r5(n,t.onProgress,0,.5)).map(s=>s.arrayBuffer());return t.onProgress==null?await Promise.all(r):await r5(r,t.onProgress,.5,1)}function rF(e,t){var a;let n=t.fetchFunc==null?B().platform.fetch:t.fetchFunc,r=0,s;return(a=t.onProgress)===null||a===void 0||a.call(t,0),new ReadableStream({pull:async i=>{for(var o;r<e.length;){s||(s=(await n(e[r],t.requestInit,{isBinary:!0})).body.getReader());let{done:l,value:u}=await s.read();if(l){r++,s=void 0,(o=t.onProgress)===null||o===void 0||o.call(t,r/e.length);continue}i.enqueue(u);return}i.close()}})}async function sF(e,t="",a,n){return T7(r=>C7(r,{requestInit:n}))(e,t,a)}function T7(e){return async(t,a="",n)=>{let r=t.map(()=>!1),s={},i=n!=null?n.map(()=>!1):[],o=[];if(t.forEach((h,m)=>{let f=0;h.weights.forEach(g=>{let y="quantization"in g?g.quantization.dtype:g.dtype,x=Ks[y]*mt(g.shape),A=()=>{r[m]=!0,s[m]==null&&(s[m]=[]),s[m].push({manifestEntry:g,groupOffset:f,sizeBytes:x})};n!=null?n.forEach((b,w)=>{b===g.name&&(A(),i[w]=!0)}):A(),o.push(g.name),f+=x})}),!i.every(h=>h)){let h=n.filter((m,f)=>!i[f]);throw new Error(`Could not find weights in manifest with names: ${h.join(", ")}. 
Manifest JSON has weights with names: ${o.join(", ")}.`)}let l=r.reduce((h,m,f)=>(m&&h.push(f),h),[]),u=[];l.forEach(h=>{t[h].paths.forEach(m=>{let f=a+(a.endsWith("/")?"":"/")+m;u.push(f)})});let p=await e(u),c={},d=0;return l.forEach(h=>{let m=t[h].paths.length,f=new Rr(p.slice(d,d+m));s[h].forEach(g=>{let y=f.slice(g.groupOffset,g.groupOffset+g.sizeBytes),x=GA(y,[g.manifestEntry]);for(let A in x)c[A]=x[A]}),d+=m}),c}}var iF="application/octet-stream",oF="application/json",n3=class{constructor(e,t){if(this.DEFAULT_METHOD="POST",t==null&&(t={}),this.weightPathPrefix=t.weightPathPrefix,this.weightUrlConverter=t.weightUrlConverter,t.fetchFunc!=null?(F(typeof t.fetchFunc=="function",()=>"Must pass a function that matches the signature of `fetch` (see https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API)"),this.fetch=t.fetchFunc):this.fetch=B().platform.fetch,F(e!=null&&e.length>0,()=>"URL path for http must not be null, undefined or empty."),Array.isArray(e)&&F(e.length===2,()=>`URL paths for http must have a length of 2, (actual length is ${e.length}).`),this.path=e,t.requestInit!=null&&t.requestInit.body!=null)throw new Error("requestInit is expected to have no pre-existing body, but has one.");this.requestInit=t.requestInit||{},this.loadOptions=t}async save(e){if(e.modelTopology instanceof ArrayBuffer)throw new Error("BrowserHTTPRequest.save() does not support saving model topology in binary formats yet.");let t=Object.assign({method:this.DEFAULT_METHOD},this.requestInit);t.body=new FormData;let a=[{paths:["./model.weights.bin"],weights:e.weightSpecs}],n=qA(e,a);if(t.body.append("model.json",new Blob([JSON.stringify(n)],{type:oF}),"model.json"),e.weightData!=null){let s=Rr.join(e.weightData);t.body.append("model.weights.bin",new Blob([s],{type:iF}),"model.weights.bin")}let r=await this.fetch(this.path,t);if(r.ok)return{modelArtifactsInfo:Op(e),responses:[r]};throw new Error(`BrowserHTTPRequest.save() failed due to HTTP response status ${r.status}.`)}async loadModelJSON(){let e=await this.fetch(this.path,this.requestInit);if(!e.ok)throw new Error(`Request to ${this.path} failed with status code ${e.status}. Please verify this URL points to the model JSON of the model to load.`);let t;try{t=await e.json()}catch(r){let s=`Failed to parse model JSON of response from ${this.path}.`;throw this.path.endsWith(".pb")?s+=" Your path contains a .pb file extension. Support for .pb models have been removed in TensorFlow.js 1.0 in favor of .json models. You can re-convert your Python TensorFlow model using the TensorFlow.js 1.0 conversion scripts or you can convert your.pb models with the 'pb2json'NPM script in the tensorflow/tfjs-converter repository.":s+=" Please make sure the server is serving valid JSON for this request.",new Error(s)}let a=t.modelTopology,n=t.weightsManifest;if(a==null&&n==null)throw new Error(`The JSON from HTTP path ${this.path} contains neither model topology or manifest for weights.`);return t}async load(){if(this.loadOptions.streamWeights)return this.loadStream();let e=await this.loadModelJSON();return dg(e,t=>this.loadWeights(t))}async loadStream(){let e=await this.loadModelJSON(),t=await this.getWeightUrls(e.weightsManifest),a=d1(e.weightsManifest),n=()=>rF(t,this.loadOptions);return Object.assign(Object.assign({},e),{weightSpecs:a,getWeightStream:n})}async getWeightUrls(e){let t=Array.isArray(this.path)?this.path[1]:this.path,[a,n]=lF(t),r=this.weightPathPrefix||a,s=[],i=[];for(let o of e)for(let l of o.paths)this.weightUrlConverter!=null?i.push(this.weightUrlConverter(l)):s.push(r+l+n);return this.weightUrlConverter&&s.push(...await Promise.all(i)),s}async loadWeights(e){let t=await this.getWeightUrls(e),a=d1(e),n=await C7(t,this.loadOptions);return[a,n]}};n3.URL_SCHEME_REGEX=/^https?:\/\//;function lF(e){let t=e.lastIndexOf("/"),a=e.lastIndexOf("?"),n=e.substring(0,t),r=a>t?e.substring(a):"";return[n+"/",r]}function x1(e){return e.match(n3.URL_SCHEME_REGEX)!=null}var N7=(e,t)=>{if(typeof fetch=="undefined"&&(t==null||t.fetchFunc==null))return null;{let a=!0;if(Array.isArray(e)?a=e.every(n=>x1(n)):a=x1(e),a)return r3(e,t)}return null};gn.registerSaveRouter(N7);gn.registerLoadRouter(N7);function r3(e,t){return new n3(e,t)}function uF(e,t){return r3(e,t)}var K2=class{constructor(e){this.modelArtifacts=e}load(){return this.modelArtifacts}},R7=class{constructor(e){this.saveHandler=e}save(e){return this.saveHandler(e)}},dF=class{constructor(e){e.load&&(this.load=()=>Promise.resolve(e.load())),e.save&&(this.save=t=>Promise.resolve(e.save(t)))}};function pF(e,t,a,n){let r=arguments;return new dF(E7(...r))}function E7(e,t,a,n){return arguments.length===1?e.modelTopology!=null||e.weightSpecs!=null?new K2(e):(console.warn("Please call tf.io.fromMemory() with only one argument. The argument should be of type ModelArtifacts. The multi-argument signature of tf.io.fromMemory() has been deprecated and will be removed in a future release."),new K2({modelTopology:e})):(console.warn("Please call tf.io.fromMemory() with only one argument. The argument should be of type ModelArtifacts. The multi-argument signature of tf.io.fromMemory() has been deprecated and will be removed in a future release."),new K2({modelTopology:e,weightSpecs:t,weightData:a,trainingConfig:n}))}function cF(e){return new R7(e)}function hF(e){return new R7(e)}var M7={};Ze(M7,{confusionMatrix:()=>fF});function mF(e,t,a){let n=R(e,"labels","confusionMatrix"),r=R(t,"predictions","confusionMatrix");F(a==null||a>0&&Number.isInteger(a),()=>`If provided, numClasses must be a positive integer, but got ${a}`),F(n.rank===1,()=>`Expected the rank of labels to be 1, but got ${n.rank}`),F(r.rank===1,()=>`Expected the rank of predictions to be 1, but got ${r.rank}`),F(n.shape[0]===r.shape[0],()=>`Mismatch in the number of examples: ${n.shape[0]} vs. ${r.shape[0]}. Labels and predictions should have the same number of elements.`),F(a>0&&Number.isInteger(a),()=>`numClasses is required to be a positive integer, but got ${a}`);let s=fh(Ue(n,"int32"),a),i=fh(Ue(r,"int32"),a),o=Qs(s),l=pt(o,i);return Ue(l,"int32")}var fF=z({confusionMatrix_:mF}),Un={};Ze(Un,{draw:()=>kF,fromPixels:()=>IF,fromPixelsAsync:()=>bF,toPixels:()=>wF});var Os,s5=!1;function $7(e,t=3){if(t>4)throw new Error("Cannot construct Tensor with more than 4 channels from pixels.");if(e==null)throw new Error("pixels passed to tf.browser.fromPixels() can not be null");let a=!1,n=!1,r=!1,s=!1,i=!1,o=!1;if(e.data instanceof Uint8Array)a=!0;else if(typeof ImageData!="undefined"&&e instanceof ImageData)n=!0;else if(typeof HTMLVideoElement!="undefined"&&e instanceof HTMLVideoElement)r=!0;else if(typeof HTMLImageElement!="undefined"&&e instanceof HTMLImageElement)s=!0;else if(e.getContext!=null)i=!0;else if(typeof ImageBitmap!="undefined"&&e instanceof ImageBitmap)o=!0;else throw new Error(`pixels passed to tf.browser.fromPixels() must be either an HTMLVideoElement, HTMLImageElement, HTMLCanvasElement, ImageData in browser, or OffscreenCanvas, ImageData in webworker or {data: Uint32Array, width: number, height: number}, but was ${e.constructor.name}`);if(Vd(Wd,L.backendName)!=null){let d={pixels:e},h={numChannels:t};return L.runKernel(Wd,d,h)}let[l,u]=r?[e.videoWidth,e.videoHeight]:[e.width,e.height],p;if(i)p=e.getContext("2d").getImageData(0,0,l,u).data;else if(n||a)p=e.data;else if(s||r||o){if(Os==null)if(typeof document=="undefined")if(typeof OffscreenCanvas!="undefined"&&typeof OffscreenCanvasRenderingContext2D!="undefined")Os=new OffscreenCanvas(1,1).getContext("2d");else throw new Error("Cannot parse input in current context. Reason: OffscreenCanvas Context2D rendering is not supported.");else Os=document.createElement("canvas").getContext("2d",{willReadFrequently:!0});Os.canvas.width=l,Os.canvas.height=u,Os.drawImage(e,0,0,l,u),p=Os.getImageData(0,0,l,u).data}let c;if(t===4)c=new Int32Array(p);else{let d=l*u;c=new Int32Array(d*t);for(let h=0;h<d;h++)for(let m=0;m<t;++m)c[h*t+m]=p[h*4+m]}return Hg(c,[u,l,t],"int32")}function gF(e){return e!=null&&e.data instanceof Uint8Array}function yF(){return typeof window!="undefined"&&typeof ImageBitmap!="undefined"&&window.hasOwnProperty("createImageBitmap")}function xF(e){return e!=null&&e.width!==0&&e.height!==0}function AF(e){return yF()&&!(e instanceof ImageBitmap)&&xF(e)&&!gF(e)}async function bF(e,t=3){let a=null;if(B().getBool("WRAP_TO_IMAGEBITMAP")&&AF(e)){let n;try{n=await createImageBitmap(e,{premultiplyAlpha:"none"})}catch(r){n=null}n!=null&&n.width===e.width&&n.height===e.height?a=n:a=e}else a=e;return $7(a,t)}function P7(e){if(e.rank!==2&&e.rank!==3)throw new Error(`toPixels only supports rank 2 or 3 tensors, got rank ${e.rank}.`);let t=e.rank===2?1:e.shape[2];if(t>4||t===2)throw new Error(`toPixels only supports depth of size 1, 3 or 4 but got ${t}`);if(e.dtype!=="float32"&&e.dtype!=="int32")throw new Error(`Unsupported type for toPixels: ${e.dtype}. Please use float32 or int32 tensors.`)}function vF(e){let t=(e==null?void 0:e.alpha)||1;if(t>1||t<0)throw new Error(`Alpha value ${t} is suppoed to be in range [0 - 1].`)}async function wF(e,t){let a=R(e,"img","toPixels");if(!(e instanceof yt)){let u=a;a=Ue(u,"int32"),u.dispose()}P7(a);let[n,r]=a.shape.slice(0,2),s=a.rank===2?1:a.shape[2],i=await a.data(),o=a.dtype==="float32"?255:1,l=new Uint8ClampedArray(r*n*4);for(let u=0;u<n*r;++u){let p=[0,0,0,255];for(let d=0;d<s;d++){let h=i[u*s+d];if(a.dtype==="float32"){if(h<0||h>1)throw new Error(`Tensor values for a float32 Tensor must be in the range [0 - 1] but encountered ${h}.`)}else if(a.dtype==="int32"&&(h<0||h>255))throw new Error(`Tensor values for a int32 Tensor must be in the range [0 - 255] but encountered ${h}.`);s===1?(p[0]=h*o,p[1]=h*o,p[2]=h*o):p[d]=h*o}let c=u*4;l[c+0]=Math.round(p[0]),l[c+1]=Math.round(p[1]),l[c+2]=Math.round(p[2]),l[c+3]=Math.round(p[3])}if(t!=null){s5||Vd(yp,L.backendName)!=null&&(console.warn("tf.browser.toPixels is not efficient to draw tensor on canvas. Please try tf.browser.draw instead."),s5=!0),t.width=r,t.height=n;let u=t.getContext("2d"),p=new ImageData(l,r,n);u.putImageData(p,0,0)}return a!==e&&a.dispose(),l}function kF(e,t,a){let n=R(e,"img","draw");if(!(e instanceof yt)){let i=n;n=Ue(i,"int32"),i.dispose()}P7(n),vF(a==null?void 0:a.imageOptions);let r={image:n},s={canvas:t,options:a};L.runKernel(yp,r,s)}var IF=z({fromPixels_:$7}),s3={};Ze(s3,{prepareAndValidate:()=>_7});function _7(e,t){let a=e.shape.length,n=t.shape.length;if(a<1)throw new Error(`tf.gatherND() expects the input to be rank 1 or higher, but the rank was ${a}.`);if(n<1)throw new Error(`tf.gatherND() expects the indices to be rank 1 or higher, but the rank was ${n}.`);if(t.dtype!=="int32")throw new Error(`tf.gatherND() expects the indices to be int32 type, but the dtype was ${t.dtype}.`);if(t.shape[n-1]>a)throw new Error(`index innermost dimension length must be <= tensor rank; saw: ${t.shape[n-1]} vs. ${a}`);if(mt(e.shape)===0)throw new Error(`Requested more than 0 entries, but input is empty. Input shape: ${e.shape}.`);let r=t.shape,s=r[r.length-1],i=1;for(let c=0;c<r.length-1;++c)i*=r[c];let o=e.shape,l=r.slice();l.pop();let u=1;for(let c=s;c<a;++c)u*=o[c],l.push(o[c]);let p=[...iu(e.shape).map(c=>c/u),1].slice(0,s);return[l,i,u,p]}var Nt={};Ze(Nt,{assertParamsValid:()=>CF,computeFlatOffset:()=>MF,computeOutShape:()=>NF,getNormalizedAxes:()=>RF,isSliceContinous:()=>EF,maskToAxes:()=>TF,parseSliceParams:()=>$F,sliceInfo:()=>PF,startForAxis:()=>B7,startIndicesWithElidedDims:()=>z7,stopForAxis:()=>V7,stopIndicesWithElidedDims:()=>L7,stridesForAxis:()=>W7,stridesWithElidedDims:()=>F7});var A1=-2,SF=-1;function CF(e,t,a){let n=e.shape.length;F(n===t.length,()=>`Error in slice${n}D: Length of begin ${t} must match the rank of the array (${n}).`),F(n===a.length,()=>`Error in slice${n}D: Length of size ${a} must match the rank of the array (${n}).`);for(let r=0;r<n;++r)F(t[r]+a[r]<=e.shape[r],()=>`Error in slice${n}D: begin[${r}] + size[${r}] (${t[r]+a[r]}) would overflow input.shape[${r}] (${e.shape[r]})`)}function TF(e){let t=[],a=0;for(;e>0;)e&1&&t.push(a),e/=2,a++;return t}function NF(e,t,a){let n=[];for(let r=0;r<e.length;r++)n[r]=Math.ceil((t[r]-e[r])/a[r]);return n}function F7(e,t,a,n){let r=[...e];for(let s=r.length;s<n.length;s++)r.push(1);for(let s=0;s<a;s++)s===0?r[t]=1:(r.splice(t,0,1),r.pop());return r}function D7(e,t,a){return a<=e?a:a-(t-1)}function O7(e,t){let a=[];for(let n=0;n<e;n++)a.push(t+n);return a}function RF(e,t,a,n,r,s,i,o,l){let u=e.length,p=new Array(u),c=new Array(u),d=new Array(u);if(t.length&&a>0){let h=t[0],m=a+1;p=z7(i,h,m,n,e),c=L7(o,h,m,r,e),d=F7(s,h,m,e)}else for(let h=0;h<u;h++)p[h]=B7(i,n,s,e,h,l),c[h]=V7(o,r,s,e,h,l),d[h]=W7(s,h,l);return{begin:p,end:c,strides:d}}function z7(e,t,a,n,r){let s=[...r],i=O7(a,t);for(let o=0;o<s.length;o++)if(i.indexOf(o)>-1)s[o]=0;else{let l=D7(t,a,o),u=n[l];e&1<<l&&(u=0),s[o]=u}return s}function L7(e,t,a,n,r){let s=[...r],i=O7(a,t);for(let o=0;o<s.length;o++)if(i.indexOf(o)>-1)s[o]=Number.MAX_SAFE_INTEGER;else{let l=D7(t,a,o),u=n[l];e&1<<l&&(u=Number.MAX_SAFE_INTEGER),s[o]=u}for(let o=0;o<s.length;o++){let l=r[o];s[o]<0&&(s[o]+=l),s[o]=Ld(0,s[o],r[o])}return s}function W7(e,t,a){let n=e[t];return(a&1<<t||n==null)&&(n=1),n}function B7(e,t,a,n,r,s){let i=t[r],o=a[r]||1;(e&1<<r||s&1<<r||i==null)&&(o>0?i=Number.MIN_SAFE_INTEGER:i=Number.MAX_SAFE_INTEGER);let l=n[r];return i<0&&(i+=l),i=Ld(0,i,l-1),i}function V7(e,t,a,n,r,s){let i=t[r],o=a[r]||1;(e&1<<r||s&1<<r||i==null)&&(o>0?i=Number.MAX_SAFE_INTEGER:i=Number.MIN_SAFE_INTEGER);let l=n[r];return i<0&&(i+=l),o>0?i=Ld(0,i,l):i=Ld(-1,i,l-1),i}function EF(e,t,a){let n=a.length;for(let r=0;r<a.length;r++)if(a[r]>1){n=r;break}for(let r=n+1;r<a.length;r++)if(t[r]>0||a[r]!==e[r])return!1;return!0}function MF(e,t){let a=e.length>0?e[e.length-1]:1;for(let n=0;n<e.length-1;n++)a+=e[n]*t[n];return a}function $F(e,t,a){let n,r=e.shape.length;typeof t=="number"?n=[t,...new Array(r-1).fill(0)]:t.length<r?n=t.concat(new Array(r-t.length).fill(0)):n=t.slice(),n.forEach(i=>{F(i!==-1,()=>"slice() does not support negative begin indexing.")});let s;return a==null?s=new Array(r).fill(-1):typeof a=="number"?s=[a,...new Array(r-1).fill(-1)]:a.length<r?s=a.concat(new Array(r-a.length).fill(-1)):s=a,s=s.map((i,o)=>i>=0?i:(F(i===-1,()=>`Negative size values should be exactly -1 but got ${i} for the slice() size at index ${o}.`),e.shape[o]-n[o])),[n,s]}function PF(e,t,a,n,r,s,i,o,l){let u;if(n==null?(u=new Array(t.length),u.fill(1)):u=n,i!=null&&i&i-1)throw new Error("Multiple ellipses in slice is not allowed.");let p=!1,c={dims:u.length,numAddAxisAfterEllipsis:0,begin:t.slice(),end:a.slice(),strides:u.slice(),beginMask:r,endMask:s,ellipsisMask:i,newAxisMask:o,shrinkAxisMask:l};for(let x=0;x<c.dims;x++)p&&1<<x&o&&c.numAddAxisAfterEllipsis++,1<<x&i&&(p=!0);p||(c.ellipsisMask|=1<<c.dims,c.dims++);let d={dims:e.length,beginMask:0,endMask:0,beginValid:!1,endValid:!1};_F(c,d);let h=!0,m=!0,f=!0,g=[],y=[];for(let x=0;x<e.length;++x){if(d.strides[x]===0)throw Error(`strides[${x}] must be non-zero`);let A=!!(d.shrinkAxisMask&1<<x),b=e[x];if(b===-1){g.push(A?1:-1);continue}let w=[d.beginMask&1<<x,d.endMask&1<<x],I=[d.strides[x]>0?0:-1,d.strides[x]>0?b:b-1];if(A&&d.strides[x]<=0)throw Error("only stride 1 allowed on non-range indexing.");f=f&&d.strides[x]===1;let T=!!(d.beginMask&1<<x&&d.endMask&1<<x);if(d.beginValid&&d.endValid){if(A){let E=d.begin[x]<0?b+d.begin[x]:d.begin[x];if(d.begin[x]=E,d.end[x]=d.begin[x]+1,E<0||E>=b)throw Error(`slice index ${d.begin[x]} of dimension ${x} out of bounds.`)}else d.begin[x]=i5(d.begin[x],0,d.strides[x],b,w,I),d.end[x]=i5(d.end[x],1,d.strides[x],b,w,I);let $=d.strides[x]===1&&d.begin[x]===0&&d.end[x]===b;h=h&&$,m=m&&(x===0&&d.strides[x]===1||$)}else h=h&&d.strides[x]===1&&T,m=m&&(x===0&&d.strides[x]===1||T);let N,M=!1;if(d.beginValid&&d.endValid?(N=d.end[x]-d.begin[x],M=!0):A?(N=1,M=!0):T&&b>=0&&(d.strides[x]<0?N=-b:N=b,M=!0),M){let $;N===0||N<0!=d.strides[x]<0?$=0:$=Math.trunc(N/d.strides[x])+(N%d.strides[x]!==0?1:0),g.push($)}else g.push(-1)}for(let x=0;x<d.finalShapeGatherIndices.length;++x){let A=d.finalShapeGatherIndices[x];A>=0?y.push(g[A]):A===A1&&y.push(1)}return{finalShapeSparse:y.filter((x,A)=>d.finalShapeGatherIndices[A]!==A1),finalShape:y,isIdentity:h,sliceDim0:m,isSimpleSlice:f,begin:d.begin,end:d.end,strides:d.strides}}function _F(e,t){t.beginMask=0,t.endMask=0,t.shrinkAxisMask=0;let a=0;t.beginValid=e.begin!=null,t.endValid=e.end!=null,t.begin=new Array(t.dims),t.end=new Array(t.dims),t.strides=new Array(t.dims),t.finalShapeGatherIndices=[],t.finalShapeGatherIndicesSparse=[],t.inputShapeGatherIndicesSparse=new Array(t.dims);for(let n=0;n<e.dims;n++)if(1<<n&e.ellipsisMask){let r=Math.min(t.dims-(e.dims-n)+1+e.numAddAxisAfterEllipsis,t.dims);for(;a<r;a++)t.begin[a]=0,t.end[a]=0,t.strides[a]=1,t.beginMask|=1<<a,t.endMask|=1<<a,t.finalShapeGatherIndices.push(a),t.finalShapeGatherIndicesSparse.push(-1),t.inputShapeGatherIndicesSparse[a]=n}else if(1<<n&e.newAxisMask)t.finalShapeGatherIndices.push(A1),t.finalShapeGatherIndicesSparse.push(-1);else{if(a===t.begin.length)throw Error(`Index out of range using input dim ${a}; input has only ${t.dims} dims, ${t.begin.length}.`);e.begin!=null&&(t.begin[a]=e.begin[n]),e.end!=null&&(t.end[a]=e.end[n]),t.strides[a]=e.strides[n],e.beginMask&1<<n&&(t.beginMask|=1<<a),e.endMask&1<<n&&(t.endMask|=1<<a),e.shrinkAxisMask&1<<n?(t.finalShapeGatherIndices.push(SF),t.finalShapeGatherIndicesSparse.push(-1),t.shrinkAxisMask|=1<<a):(t.finalShapeGatherIndices.push(a),t.finalShapeGatherIndicesSparse.push(n)),t.inputShapeGatherIndicesSparse[a]=n,a++}}function i5(e,t,a,n,r,s){if(r[t])return a>0?s[t]:s[t+1&1];{let i=e<0?n+e:e;return i<s[0]?s[0]:i>s[1]?s[1]:i}}var i3="4.22.0",U7=class{static sgd(e){return new Qh(e)}static momentum(e,t,a=!1){return new t3(e,t,a)}static rmsprop(e,t=.9,a=0,n=null,r=!1){return new a3(e,t,a,n,r)}static adam(e=.001,t=.9,a=.999,n=null){return new Qg(e,t,a,n)}static adadelta(e=.001,t=.95,a=null){return new Zg(e,t,a)}static adamax(e=.002,t=.9,a=.999,n=null,r=0){return new e3(e,t,a,n,r)}static adagrad(e,t=.1){return new Jg(e,t)}},FF=U7,DF=typeof requestAnimationFrame!="undefined"?requestAnimationFrame:typeof setImmediate!="undefined"?setImmediate:e=>e();function G7(){return new Promise(e=>DF(()=>e()))}var C={};Ze(C,{ERF_A1:()=>QF,ERF_A2:()=>eD,ERF_A3:()=>tD,ERF_A4:()=>aD,ERF_A5:()=>nD,ERF_P:()=>JF,PARALLELIZE_THRESHOLD:()=>o3,RowPartitionType:()=>Yn,SELU_SCALE:()=>ZF,SELU_SCALEALPHA:()=>YF,applyActivation:()=>Zh,assertAndGetBroadcastShape:()=>Ut,assertAxesAreInnerMostDims:()=>SE,assertParamsConsistent:()=>OF,assignToTypedArray:()=>uD,axesAreInnerMostDims:()=>Ag,calculateShapes:()=>K4,checkEinsumDimSizes:()=>fD,checkPadOnDimRoundingMode:()=>Nn,combineLocations:()=>Hb,combineRaggedTensorToTensorShapes:()=>LF,complexWithEvenIndex:()=>iD,complexWithOddIndex:()=>oD,computeConv2DInfo:()=>Lp,computeConv3DInfo:()=>hb,computeDefaultPad:()=>cg,computeDilation2DInfo:()=>vR,computeOptimalWindowSize:()=>UF,computeOutAndReduceShapes:()=>IE,computeOutShape:()=>zF,computePool2DInfo:()=>cb,computePool3DInfo:()=>wR,convertConv2DDataFormat:()=>mb,decodeEinsumEquation:()=>hD,eitherStridesOrDilationsAreOne:()=>Er,expandShapeToKeepDim:()=>Vp,exponent:()=>pD,exponents:()=>dD,fromStringArrayToUint8:()=>DD,fromUint8ToStringArray:()=>FD,getAxesPermutation:()=>CE,getBroadcastDims:()=>Wb,getComplexWithIndex:()=>lD,getEinsumComputePath:()=>gD,getEinsumPermutation:()=>mD,getFusedBiasGradient:()=>Yh,getFusedDyActivation:()=>Kh,getImageCenter:()=>GF,getInnerMostAxes:()=>NE,getPermuted:()=>jF,getRaggedRank:()=>BF,getReductionAxes:()=>gg,getReshaped:()=>HF,getReshapedPermuted:()=>qF,getRowPartitionTypesHelper:()=>WF,getSliceBeginCoords:()=>XF,getSliceSize:()=>KF,getSparseFillEmptyRowsIndicesDenseShapeMismatch:()=>bD,getSparseFillEmptyRowsNegativeIndexErrorMessage:()=>vD,getSparseFillEmptyRowsOutOfRangeIndexErrorMessage:()=>wD,getSparseReshapeEmptyTensorZeroOutputDimErrorMessage:()=>SD,getSparseReshapeInputOutputMismatchErrorMessage:()=>TD,getSparseReshapeInputOutputMultipleErrorMessage:()=>CD,getSparseReshapeMultipleNegativeOneOutputDimErrorMessage:()=>kD,getSparseReshapeNegativeOutputDimErrorMessage:()=>ID,getSparseSegmentReductionIndicesOutOfRangeErrorMessage:()=>MD,getSparseSegmentReductionNegativeSegmentIdsErrorMessage:()=>ND,getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage:()=>RD,getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage:()=>ED,getUndoAxesPermutation:()=>TE,isIdentityPermutation:()=>yD,log:()=>PT,mergeRealAndImagArrays:()=>rD,prepareAndValidate:()=>_7,prepareSplitSize:()=>AD,segment_util:()=>H7,shouldFuse:()=>Jh,slice_util:()=>Nt,splitRealAndImagArrays:()=>sD,stridesOrDilationsArePositive:()=>Js,tupleValuesAreOne:()=>Xd,upcastType:()=>ca,validateDefaultValueShape:()=>VF,validateInput:()=>qh,validateUpdateShape:()=>jg,warn:()=>Ur});function OF(e,t){let a=e[0].length;e.forEach((r,s)=>{F(r.length===a,()=>`Error in concat${a}D: rank of tensors[${s}] must be the same as the rank of the rest (${a})`)}),F(t>=0&&t<a,()=>`Error in concat${a}D: axis must be between 0 and ${a-1}.`);let n=e[0];e.forEach((r,s)=>{for(let i=0;i<a;i++)F(i===t||r[i]===n[i],()=>`Error in concat${a}D: Shape of tensors[${s}] (${r}) does not match the shape of the rest (${n}) along the non-concatenated axis ${s}.`)})}function zF(e,t){let a=e[0].slice();for(let n=1;n<e.length;n++)a[t]+=e[n][t];return a}var Yn;(function(e){e[e.FIRST_DIM_SIZE=0]="FIRST_DIM_SIZE",e[e.VALUE_ROWIDS=1]="VALUE_ROWIDS",e[e.ROW_LENGTHS=2]="ROW_LENGTHS",e[e.ROW_SPLITS=3]="ROW_SPLITS",e[e.ROW_LIMITS=4]="ROW_LIMITS",e[e.ROW_STARTS=5]="ROW_STARTS"})(Yn||(Yn={}));function LF(e,t,a){let n=new Array;if(a==null&&t==null)return n;if(t==null)for(;n.length<e+a.length;)n.push(-1);else n=t.slice();if(a==null)return n;if(e+a.length!==n.length)throw new Error(`rt input.shape and shape=${t} are incompatible: rt input.rank = ${e+a.length}, but shape.rank = ${n.length}`);for(let r=1;r<a.length;++r){let s=a[r],i=n[n.length-a.length+r],o=n[i];if(s>=0)if(o>=0){if(o!==s)throw new Error(`rt input.shape and shape=${t} are incompatible: rt input.shape[${r+e}] = ${s} but shape[${r+e}] = ${o}`)}else n[i]=s}return n}function WF(e){let t={FIRST_DIM_SIZE:Yn.FIRST_DIM_SIZE,VALUE_ROWIDS:Yn.VALUE_ROWIDS,ROW_LENGTHS:Yn.ROW_LENGTHS,ROW_SPLITS:Yn.ROW_SPLITS,ROW_LIMITS:Yn.ROW_LIMITS,ROW_STARTS:Yn.ROW_STARTS},a=[];for(let n of e)if(n in t)a.push(t[n]);else break;return a}function BF(e){return e.length===0?0:e[0]===Yn.FIRST_DIM_SIZE?e.length-1:e.length}function VF(e,t){if(e==null||t==null)return;let a=e.length,n=t.length;if(a>=n)throw new Error(`defaultValue.shape=${e} and ragged tensor flatValues.shape=${t}, are incompatible: defaultValue.rank = ${a} must be less than ragged tensor input flatValues.rank = ${n})`);for(let r=0;r<Math.min(a,n-1);++r){let s=e[r],i=t[r+1];if(s>=0&&i>=0&&s!==1&&s!==i)throw new Error(`defaultValue.shape=${e}, and ragged tensor input flatValues.shape=${t} are incompatible: defaultValue.shape[${r-e.length}] = ${s} but ragged tensor input.flatValues.shape[${r-e.length}] = ${i}`)}}var o3=30;function UF(e){return e<=o3?e:ph(e,Math.floor(Math.sqrt(e)))}function GF(e,t,a){let n=a*(typeof e=="number"?e:e[0]),r=t*(typeof e=="number"?e:e[1]);return[n,r]}function HF(e,t,a,n=!0){let r=[];if(n)r=r.concat(t.slice(0)),r.push(e[0]/a),r=r.concat(e.slice(1));else{r=r.concat(e[0]);let s=t.length;for(let i=0;i<s;++i)r=r.concat([e[i+1]/t[i],t[i]]);r=r.concat(e.slice(s+1))}return r}function jF(e,t,a=!0){let n=[];if(a){n.push(t);for(let r=t+1;r<e;++r)r<=2*t?(n.push(r),n.push(r-(t+1))):n.push(r)}else{let r=[],s=[];for(let i=1;i<e;++i)i>=t*2+1||i%2===1?s.push(i):r.push(i);n.push(...r),n.push(0),n.push(...s)}return n}function qF(e,t,a,n=!0){let r=[];n?r.push(e[0]/a):r.push(e[0]*a);for(let s=1;s<e.length;++s)s<=t.length?n?r.push(t[s-1]*e[s]):r.push(e[s]/t[s-1]):r.push(e[s]);return r}function XF(e,t){let a=[0];for(let n=0;n<t;++n)a.push(e[n][0]);return a}function KF(e,t,a){let n=e.slice(0,1);for(let r=0;r<a;++r)n.push(e[r+1]-t[r][0]-t[r][1]);return n}var YF=1.7580993408473768,ZF=1.0507009873554805,JF=.3275911,QF=.254829592,eD=-.284496736,tD=1.421413741,aD=-1.453152027,nD=1.061405429;function rD(e,t){if(e.length!==t.length)throw new Error(`Cannot merge real and imag arrays of different lengths. real:${e.length}, imag: ${t.length}.`);let a=new Float32Array(e.length*2);for(let n=0;n<a.length;n+=2)a[n]=e[n/2],a[n+1]=t[n/2];return a}function sD(e){let t=new Float32Array(e.length/2),a=new Float32Array(e.length/2);for(let n=0;n<e.length;n+=2)t[n/2]=e[n],a[n/2]=e[n+1];return{real:t,imag:a}}function iD(e){let t=Math.ceil(e.length/4),a=new Float32Array(t),n=new Float32Array(t);for(let r=0;r<e.length;r+=4)a[Math.floor(r/4)]=e[r],n[Math.floor(r/4)]=e[r+1];return{real:a,imag:n}}function oD(e){let t=Math.floor(e.length/4),a=new Float32Array(t),n=new Float32Array(t);for(let r=2;r<e.length;r+=4)a[Math.floor(r/4)]=e[r],n[Math.floor(r/4)]=e[r+1];return{real:a,imag:n}}function lD(e,t){let a=e[t*2],n=e[t*2+1];return{real:a,imag:n}}function uD(e,t,a,n){e[n*2]=t,e[n*2+1]=a}function dD(e,t){let a=new Float32Array(e/2),n=new Float32Array(e/2);for(let r=0;r<Math.ceil(e/2);r++){let s=(t?2:-2)*Math.PI*(r/e);a[r]=Math.cos(s),n[r]=Math.sin(s)}return{real:a,imag:n}}function pD(e,t,a){let n=(a?2:-2)*Math.PI*(e/t),r=Math.cos(n),s=Math.sin(n);return{real:r,imag:s}}var Y2="->",cD=/->/g,o5=",",l5="...";function hD(e,t){e=e.replace(/\s/g,"");let a=(e.length-e.replace(cD,"").length)/Y2.length;if(a<1)throw new Error("Equations without an arrow are not supported.");if(a>1)throw new Error(`Equation must contain exactly one arrow ("${Y2}").`);let[n,r]=e.split(Y2);F(n.indexOf(l5)===-1,()=>`The ellipsis notation ("${l5}") is not supported yet.`);let s=n.split(o5),i=s.length;if(t!==i)throw new Error(`Expected ${i} input tensors, received ${t}`);if(i>2)throw new Error("Support for more than 2 input tensors is not implemented yet.");let o=[];for(let d=0;d<r.length;++d){let h=r[d];if(!s.some(m=>m.indexOf(h)!==-1))throw new Error(`Output subscripts contain the label ${h} not present in the input subscripts.`);o.indexOf(h)===-1&&o.push(h)}for(let d=0;d<n.length;++d){let h=n[d];o.indexOf(h)===-1&&h!==o5&&o.push(h)}let l=new Array(s.length);for(let d=0;d<i;++d){if(new Set(s[d].split("")).size!==s[d].length)throw new Error(`Found duplicate axes in input component ${s[d]}. Support for duplicate axes in input is not implemented yet.`);l[d]=[];for(let h=0;h<s[d].length;++h)l[d].push(o.indexOf(s[d][h]))}let u=o.length,p=r.length,c=[];for(let d=p;d<u;++d)c.push(d);return{allDims:o,summedDims:c,idDims:l}}function mD(e,t){let a=new Array(e);a.fill(-1);for(let r=0;r<t.length;++r)a[t[r]]=r;let n=[];for(let r=0;r<e;++r)a[r]===-1&&n.push(r);return a=a.filter(r=>r!==-1),{permutationIndices:a,expandDims:n}}function fD(e,t,a){let n=new Array(e);for(let r=0;r<a.length;++r){let s=a[r].shape;for(let i=0;i<t[r].length;++i)n[t[r][i]]===void 0?n[t[r][i]]=s[i]:F(n[t[r][i]]===s[i],()=>`Expected dimension ${n[t[r][i]]} at axis ${i} of input shaped ${JSON.stringify(s)}, but got dimension ${s[i]}`)}}function gD(e,t){let a=e,n=[],r=0;e.length===0&&a.push(-1),r=e.length+1;for(let i=0;i<r;++i)n.push([]);let s=[];for(let i=0;i<a.length;++i){let o=a[i],l=xD(t,o);for(let u of l)s.indexOf(u)===-1&&(n[i].push(u),s.push(u))}return{path:a,steps:n}}function yD(e){return e.every((t,a)=>t===a)}function xD(e,t){let a=[];for(let n=0;n<e.length;++n)(e[n].length===0||e[n].indexOf(t)!==-1||t===-1)&&a.push(n);return a}function AD(e,t,a=0){let n=[];if(typeof t=="number")F(e.shape[a]%t===0,()=>"Number of splits must evenly divide the axis."),n=new Array(t).fill(e.shape[a]/t);else{let r=t.reduce((i,o)=>(o===-1&&(i+=1),i),0);F(r<=1,()=>"There should be only one negative value in split array.");let s=t.indexOf(-1);if(s!==-1){let i=t.reduce((o,l)=>l>0?o+l:o);t[s]=e.shape[a]-i}F(e.shape[a]===t.reduce((i,o)=>i+o),()=>"The sum of sizes must match the size of the axis dimension."),n=t}return n}function bD(e){return`Received SparseTensor with denseShape[0] = 0 but
  indices.shape[0] = ${e}`}function vD(e,t){return`indices(${e}, 0) is invalid: ${t} < 0`}function wD(e,t,a){return`indices(${e}, 0) is invalid: ${t} >= ${a}`}function kD(e,t){return`only one output dimension may be -1, not both ${e} and ${t}`}function ID(e,t){return`size ${e} must be non-negative, not ${t}`}function SD(){return"reshape cannot infer the missing input size for an empty tensor unless all specified input sizes are non-zero"}function CD(e,t){let a=mt(e),n=mt(t);return`Input to reshape is a SparseTensor with ${a}
  dense values, but the requested shape requires a multiple of ${n}. inputShape=${e} outputShape= ${t}`}function TD(e,t){let a=mt(e),n=mt(t);return`Input to reshape is a tensor with ${a} dense values, but the requested shape has ${n}. inputShape=${e} outputShape=${t}`}function ND(){return"segment ids must be >= 0"}function RD(){return"segment ids are not increasing"}function ED(e,t){return`Segment id ${e} out of range [0, ${t}), possibly because segmentIds input is not sorted.`}function MD(e,t,a){return`Bad: indices[${e}] == ${t} out of range [0, ${a})`}var H7={};Ze(H7,{collectGatherOpShapeInfo:()=>_D,computeOutShape:()=>PD,segOpComputeOptimalWindowSize:()=>$D});function $D(e,t){let a=!1,n;for(e<=o3?(n=e,a=!0):n=ph(e,Math.floor(Math.sqrt(e)));!a;)n>t||n===e?a=!0:n=ph(e,n+1);return n}function PD(e,t,a){let n=[],r=e.length;for(let s=0;s<r;s++)s!==t?n.push(e[s]):n.push(a);return n}function _D(e,t,a,n){let r=t.shape.length,s=e.shape.length;if(n!==0&&(n<-r||n>r))throw new Error(`Expect batchDims in the range of [-${r}, ${r}], but got ${n}`);if(n<0&&(n+=r),n>s)throw new Error(`batchDims (${n}) must be less than rank(x) (
    ${s}).`);if(a<n)throw new Error(`batchDims (${n}) must be less than or equal to axis (${a}).`);for(let c=0;c<n;++c)if(e.shape[c]!==t.shape[c])throw new Error(`x.shape[${c}]: ${e.shape[c]} should be equal to indices.shape[${c}]: ${t.shape[c]}.`);let i=e.shape[a],o=[],l=1,u=1,p=1;for(let c=0;c<n;++c)o.push(e.shape[c]),l*=e.shape[c];for(let c=n;c<a;c++)o.push(e.shape[c]),u*=e.shape[c];for(let c=n;c<r;c++)o.push(t.shape[c]);for(let c=a+1;c<s;c++)o.push(e.shape[c]),p*=e.shape[c];return{batchSize:l,sliceSize:p,outerSize:u,dimSize:i,outputShape:o}}function FD(e){try{return e.map(t=>ch(t))}catch(t){throw new Error(`Failed to decode encoded string bytes into utf-8, error: ${t}`)}}function DD(e){return e.map(t=>Pp(t))}var En={};Ze(En,{nonMaxSuppressionV3Impl:()=>h7,nonMaxSuppressionV4Impl:()=>m7,nonMaxSuppressionV5Impl:()=>f7,whereImpl:()=>n7});Y_();var OD=B();OD.registerFlag("KEEP_INTERMEDIATE_TENSORS",()=>!1,e=>{e&&console.warn("Keep intermediate tensors is ON. This will print the values of all intermediate tensors during model inference. Not all models support this mode. For details, check e2e/benchmarks/ model_config.js. This significantly impacts performance.")});var Ka;(function(e){e[e.DT_INVALID=0]="DT_INVALID",e[e.DT_FLOAT=1]="DT_FLOAT",e[e.DT_DOUBLE=2]="DT_DOUBLE",e[e.DT_INT32=3]="DT_INT32",e[e.DT_UINT8=4]="DT_UINT8",e[e.DT_INT16=5]="DT_INT16",e[e.DT_INT8=6]="DT_INT8",e[e.DT_STRING=7]="DT_STRING",e[e.DT_COMPLEX64=8]="DT_COMPLEX64",e[e.DT_INT64=9]="DT_INT64",e[e.DT_BOOL=10]="DT_BOOL",e[e.DT_QINT8=11]="DT_QINT8",e[e.DT_QUINT8=12]="DT_QUINT8",e[e.DT_QINT32=13]="DT_QINT32",e[e.DT_BFLOAT16=14]="DT_BFLOAT16",e[e.DT_QINT16=15]="DT_QINT16",e[e.DT_QUINT16=16]="DT_QUINT16",e[e.DT_UINT16=17]="DT_UINT16",e[e.DT_COMPLEX128=18]="DT_COMPLEX128",e[e.DT_HALF=19]="DT_HALF",e[e.DT_RESOURCE=20]="DT_RESOURCE",e[e.DT_VARIANT=21]="DT_VARIANT",e[e.DT_UINT32=22]="DT_UINT32",e[e.DT_UINT64=23]="DT_UINT64",e[e.DT_FLOAT_REF=101]="DT_FLOAT_REF",e[e.DT_DOUBLE_REF=102]="DT_DOUBLE_REF",e[e.DT_INT32_REF=103]="DT_INT32_REF",e[e.DT_UINT8_REF=104]="DT_UINT8_REF",e[e.DT_INT16_REF=105]="DT_INT16_REF",e[e.DT_INT8_REF=106]="DT_INT8_REF",e[e.DT_STRING_REF=107]="DT_STRING_REF",e[e.DT_COMPLEX64_REF=108]="DT_COMPLEX64_REF",e[e.DT_INT64_REF=109]="DT_INT64_REF",e[e.DT_BOOL_REF=110]="DT_BOOL_REF",e[e.DT_QINT8_REF=111]="DT_QINT8_REF",e[e.DT_QUINT8_REF=112]="DT_QUINT8_REF",e[e.DT_QINT32_REF=113]="DT_QINT32_REF",e[e.DT_BFLOAT16_REF=114]="DT_BFLOAT16_REF",e[e.DT_QINT16_REF=115]="DT_QINT16_REF",e[e.DT_QUINT16_REF=116]="DT_QUINT16_REF",e[e.DT_UINT16_REF=117]="DT_UINT16_REF",e[e.DT_COMPLEX128_REF=118]="DT_COMPLEX128_REF",e[e.DT_HALF_REF=119]="DT_HALF_REF",e[e.DT_RESOURCE_REF=120]="DT_RESOURCE_REF",e[e.DT_VARIANT_REF=121]="DT_VARIANT_REF",e[e.DT_UINT32_REF=122]="DT_UINT32_REF",e[e.DT_UINT64_REF=123]="DT_UINT64_REF"})(Ka||(Ka={}));var u5;(function(e){let t;(function(a){a[a.LEGACY=0]="LEGACY",a[a.V1=1]="V1",a[a.V2=2]="V2"})(t=e.CheckpointFormatVersion||(e.CheckpointFormatVersion={}))})(u5||(u5={}));var l3={};function zD(e,t){let a={tfOpName:e,category:"custom",inputs:[],attrs:[],customExecutor:t};l3[e]=a}function j7(e){return l3[e]}function LD(e){delete l3[e]}function k(e,t,a,n,r){let s=t.inputParams[e];if(s&&s.inputIndexStart!==void 0){let o=s.inputIndexStart,l=s.inputIndexEnd===0?void 0:s.inputIndexEnd===void 0?o+1:s.inputIndexEnd,u=o<0?t.inputNames.length+o:o;if(s.type==="tensor")return da(t.inputNames[u],a,n,r);if(s.type==="tensors"){let d=t.inputs.slice(o,l);return t.inputNames.slice(o,l).filter((h,m)=>{var f;return((f=d[m])===null||f===void 0?void 0:f.op)!=="NoOp"}).map(h=>da(h,a,n,r))}let p=da(t.inputNames[u],a,n,r),c=p.dataSync();return s.type==="number"?c[0]:v.toNestedArray(p.shape,c)}let i=t.attrParams[e];return i&&i.value}function da(e,t,a,n){let[r,s]=Ya(e,a);if(n!=null){let o=n.getHashTableHandleByName(r);if(o!=null)return o}let i=a.currentContextIds.find(o=>!!t[yh(r,o)]);return i!==void 0?t[yh(r,i)][s]:void 0}function d5(e,t,a){return t[yh(e,a.currentContextId)]}function vr(e,t){let[a,n,r]=Ya(e,t);return[yh(a,t&&t.currentContextId),n,r]}function yh(e,t){return t?`${e}-${t}`:e}function Ya(e,t){if(e==="")return["",0,void 0];let a=t!=null&&t.parseNodeNameCache!=null;if(a){let s=t.parseNodeNameCache.get(e);if(s!=null)return s}let n=e.split(":"),r;if(n.length===1)r=[e,0,void 0];else{let s=n[0],i=n.length===3?n[1]:void 0,o=Number(n[n.length-1]);r=[s,o,i]}return a&&t.parseNodeNameCache.set(e,r),r}function ah(e,t,a){let n=k("pad",e,t,a);if(n==="explicit"){n=k("explicitPaddings",e,t,a);let r=[[0,0],[0,0],[0,0],[0,0]];for(let s=0;s<4;s++)r[s][0]=n[s*2],r[s][1]=n[s*2+1];return r}return n}function wr(e){return e.kept?e:Ia(e)}var q7={};Ze(q7,{json:()=>WD});var WD=[{tfOpName:"Add",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"AddV2",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"AddN",category:"arithmetic",inputs:[{start:0,end:0,name:"tensors",type:"tensors"}]},{tfOpName:"BiasAdd",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0}]},{tfOpName:"Sub",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"RealDiv",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Div",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"DivNoNan",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"FloorDiv",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Mul",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Maximum",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Minimum",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Pow",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"SquaredDifference",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Mod",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"FloorMod",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]}],X7={};Ze(X7,{json:()=>BD});var BD=[{tfOpName:"Abs",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Acos",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Asin",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Atan",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Atan2",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"y",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Ceil",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"ClipByValue",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"clipValueMin",type:"number"},{start:2,name:"clipValueMax",type:"number"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Complex",category:"basic_math",inputs:[{start:0,name:"real",type:"tensor"},{start:1,name:"imag",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"ComplexAbs",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Cos",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Cosh",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Elu",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Exp",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Floor",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Log",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Imag",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"Tout",name:"outputType",type:"dtype",notSupported:!0}]},{tfOpName:"Neg",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Real",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"Tout",name:"outputType",type:"dtype",notSupported:!0}]},{tfOpName:"Prelu",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"alpha",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Relu",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Relu6",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Selu",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Sigmoid",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Sin",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Sinh",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Sqrt",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Rsqrt",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Square",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Tan",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Tanh",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Sign",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Round",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Expm1",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Log1p",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Reciprocal",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Softplus",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Asinh",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Acosh",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Atanh",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Erf",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"LeakyRelu",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"alpha",name:"alpha",type:"number",defaultValue:.2},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"IsNan",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"IsFinite",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"IsInf",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]}],K7={};Ze(K7,{json:()=>VD});var VD=[{tfOpName:"EmptyTensorList",category:"control",inputs:[{start:0,name:"elementShape",type:"shape"},{start:1,name:"maxNumElements",type:"number"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"LoopCond",category:"control",inputs:[{start:0,name:"pred",type:"tensor"}]},{tfOpName:"Switch",category:"control",inputs:[{start:0,name:"data",type:"tensor"},{start:1,name:"pred",type:"tensor"}]},{tfOpName:"Merge",category:"control",inputs:[{start:0,end:0,name:"tensors",type:"tensors"}]},{tfOpName:"Enter",category:"control",inputs:[{start:0,name:"tensor",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"frame_name",name:"frameName",type:"string"},{tfName:"is_constant",name:"isConstant",type:"bool"}]},{tfOpName:"Exit",category:"control",inputs:[{start:0,name:"tensor",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"NextIteration",category:"control",inputs:[{start:0,name:"tensor",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"TensorArrayV3",category:"control",inputs:[{start:0,name:"size",type:"number"}],attrs:[{tfName:"dtype",name:"dtype",type:"dtype"},{tfName:"element_shape",name:"elementShape",type:"shape"},{tfName:"dynamic_size",name:"dynamicSize",type:"bool"},{tfName:"clear_after_read",name:"clearAfterRead",type:"bool"},{tfName:"identical_element_shapes",name:"identicalElementShapes",type:"bool"},{tfName:"tensor_array_name",name:"name",type:"string"}]},{tfOpName:"TensorArrayWriteV3",category:"control",inputs:[{start:0,name:"tensorArrayId",type:"tensor"},{start:1,name:"index",type:"number"},{start:2,name:"tensor",type:"tensor"},{start:3,name:"flowIn",type:"number"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"TensorArrayReadV3",category:"control",inputs:[{start:0,name:"tensorArrayId",type:"tensor"},{start:1,name:"index",type:"number"},{start:2,name:"flowIn",type:"number"}],attrs:[{tfName:"dtype",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"TensorArrayGatherV3",category:"control",inputs:[{start:0,name:"tensorArrayId",type:"tensor"},{start:1,name:"indices",type:"number[]"},{start:2,name:"flowIn",type:"number"}],attrs:[{tfName:"dtype",name:"dtype",type:"dtype"},{tfName:"element_shape",name:"elementShape",type:"shape"}]},{tfOpName:"TensorArrayScatterV3",category:"control",inputs:[{start:0,name:"tensorArrayId",type:"tensor"},{start:1,name:"indices",type:"number[]"},{start:2,name:"tensor",type:"tensor"},{start:3,name:"flowIn",type:"number"}],attrs:[{tfName:"T",name:"dtype",type:"dtype"}]},{tfOpName:"TensorArrayConcatV3",category:"control",inputs:[{start:0,name:"tensorArrayId",type:"tensor"},{start:1,name:"flowIn",type:"number"}],attrs:[{tfName:"dtype",name:"dtype",type:"dtype"},{tfName:"element_shape_except0",name:"elementShapeExcept0",type:"shape",notSupported:!0}]},{tfOpName:"TensorArraySplitV3",category:"control",inputs:[{start:0,name:"tensorArrayId",type:"tensor"},{start:1,name:"tensor",type:"tensor"},{start:2,name:"lengths",type:"number[]"},{start:3,name:"flowIn",type:"number"}],attrs:[{tfName:"T",name:"dtype",type:"dtype"}]},{tfOpName:"TensorArraySizeV3",category:"control",inputs:[{start:0,name:"tensorArrayId",type:"tensor"},{start:1,name:"flowIn",type:"number"}]},{tfOpName:"TensorArrayCloseV3",category:"control",inputs:[{start:0,name:"tensorArrayId",type:"tensor"}]},{tfOpName:"StatelessIf",category:"control",inputs:[{start:0,name:"cond",type:"tensor"},{start:1,end:0,name:"args",type:"tensors"}],attrs:[{tfName:"then_branch",name:"thenBranch",type:"func"},{tfName:"else_branch",name:"elseBranch",type:"func"}]},{tfOpName:"If",category:"control",inputs:[{start:0,name:"cond",type:"tensor"},{start:1,end:0,name:"args",type:"tensors"}],attrs:[{tfName:"then_branch",name:"thenBranch",type:"func"},{tfName:"else_branch",name:"elseBranch",type:"func"}]},{tfOpName:"StatelessWhile",category:"control",inputs:[{start:0,end:0,name:"args",type:"tensors"}],attrs:[{tfName:"cond",name:"cond",type:"func"},{tfName:"body",name:"body",type:"func"}]},{tfOpName:"While",category:"control",inputs:[{start:0,end:0,name:"args",type:"tensors"}],attrs:[{tfName:"cond",name:"cond",type:"func"},{tfName:"body",name:"body",type:"func"}]},{tfOpName:"TensorListScatter",category:"control",inputs:[{start:0,name:"tensor",type:"tensor"},{start:1,name:"indices",type:"number[]"},{start:2,name:"elementShape",type:"shape"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListScatterV2",category:"control",inputs:[{start:0,name:"tensor",type:"tensor"},{start:1,name:"indices",type:"number[]"},{start:2,name:"elementShape",type:"shape"},{start:3,name:"numElements",type:"number"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListGather",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"},{start:1,name:"indices",type:"number[]"},{start:2,name:"elementShape",type:"shape"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListGetItem",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"},{start:1,name:"index",type:"number"},{start:2,name:"elementShape",type:"shape"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListSetItem",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"},{start:1,name:"index",type:"number"},{start:2,name:"tensor",type:"tensor"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListReserve",category:"control",inputs:[{start:0,name:"elementShape",type:"shape"},{start:1,name:"numElements",type:"number"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListFromTensor",category:"control",inputs:[{start:0,name:"tensor",type:"tensor"},{start:1,name:"elementShape",type:"shape"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListStack",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"},{start:1,name:"elementShape",type:"shape"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"},{tfName:"num_elements",name:"numElements",type:"dtype"}]},{tfOpName:"TensorListSplit",category:"control",inputs:[{start:0,name:"tensor",type:"tensor"},{start:1,name:"elementShape",type:"shape"},{start:2,name:"lengths",type:"number[]"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListConcat",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"}],attrs:[{tfName:"element_shape",name:"elementShape",type:"shape"},{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListConcatV2",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"}],attrs:[{tfName:"element_shape",name:"elementShape",type:"shape"},{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListPopBack",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"},{start:1,name:"elementShape",type:"shape"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListPushBack",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"},{start:1,name:"tensor",type:"tensor"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListLength",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"}]},{tfOpName:"TensorListResize",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"},{start:1,name:"size",type:"number"}]}],Y7={};Ze(Y7,{json:()=>UD});var UD=[{tfOpName:"AvgPool",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0},{tfName:"ksize",name:"kernelSize",type:"number[]"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"MaxPool",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0},{tfName:"ksize",name:"kernelSize",type:"number[]"},{tfName:"explicit_paddings",name:"explicitPaddings",type:"number[]",defaultValue:[],notSupported:!0},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"MaxPoolWithArgmax",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"ksize",name:"kernelSize",type:"number[]"},{tfName:"include_batch_in_index",name:"includeBatchInIndex",type:"bool"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"AvgPool3D",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0},{tfName:"ksize",name:"kernelSize",type:"number[]"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"MaxPool3D",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0},{tfName:"ksize",name:"kernelSize",type:"number[]"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Conv1D",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"filter",type:"tensor"}],attrs:[{tfName:"stride",name:"stride",type:"number"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",defaultValue:"NWC"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"dilation",name:"dilation",type:"number",defaultValue:1}]},{tfOpName:"Conv2D",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"filter",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"useCudnnOnGpu",name:"useCudnnOnGpu",type:"bool"},{tfName:"data_format",name:"dataFormat",type:"string",defaultValue:"NHWC"},{tfName:"explicit_paddings",name:"explicitPaddings",type:"number[]",defaultValue:[]},{tfName:"dilations",name:"dilations",type:"number[]"}]},{tfOpName:"_FusedConv2D",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"filter",type:"tensor"},{start:2,end:0,name:"args",type:"tensors"}],attrs:[{tfName:"num_args",name:"numArgs",type:"number"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"explicit_paddings",name:"explicitPaddings",type:"number[]",defaultValue:[]},{tfName:"use_cudnn_on_gpu",name:"useCudnnOnGpu",type:"bool",defaultValue:!0},{tfName:"data_format",name:"dataFormat",type:"string",defaultValue:"NHWC"},{tfName:"dilations",name:"dilations",type:"number[]",defaultValue:[1,1,1,1]},{tfName:"fused_ops",name:"fusedOps",type:"string[]",defaultValue:[]},{tfName:"epsilon",name:"epsilon",type:"number",defaultValue:1e-4},{tfName:"leakyrelu_alpha",name:"leakyreluAlpha",type:"number",defaultValue:.2}]},{tfOpName:"Conv2DBackpropInput",category:"convolution",inputs:[{start:2,name:"x",type:"tensor"},{start:1,name:"filter",type:"tensor"},{start:0,name:"outputShape",type:"number[]"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0},{tfName:"explicit_paddings",name:"explicitPaddings",type:"number[]",defaultValue:[]},{tfName:"dilations",name:"dilations",type:"number[]",notSupported:!0}]},{tfOpName:"DepthwiseConv2d",category:"convolution",inputs:[{start:0,name:"input",type:"tensor"},{start:1,name:"filter",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",defaultValue:"NHWC"},{tfName:"explicit_paddings",name:"explicitPaddings",type:"number[]",defaultValue:[]},{tfName:"dilations",name:"dilations",type:"number[]"}]},{tfOpName:"DepthwiseConv2dNative",category:"convolution",inputs:[{start:0,name:"input",type:"tensor"},{start:1,name:"filter",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",defaultValue:"NHWC"},{tfName:"explicit_paddings",name:"explicitPaddings",type:"number[]",defaultValue:[]},{tfName:"dilations",name:"dilations",type:"number[]"}]},{tfOpName:"FusedDepthwiseConv2dNative",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"filter",type:"tensor"},{start:2,end:0,name:"args",type:"tensors"}],attrs:[{tfName:"num_args",name:"numArgs",type:"number"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",defaultValue:"NHWC"},{tfName:"dilations",name:"dilations",type:"number[]",defaultValue:[1,1,1,1]},{tfName:"fused_ops",name:"fusedOps",type:"string[]",defaultValue:[]},{tfName:"explicit_paddings",name:"explicitPaddings",type:"number[]",defaultValue:[]}]},{tfOpName:"Conv3D",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"filter",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",defaultValue:"NHWC"},{tfName:"dilations",name:"dilations",type:"number[]"}]},{tfOpName:"Dilation2D",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"filter",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"rates",name:"dilations",type:"number[]"},{tfName:"padding",name:"pad",type:"string"}]}],Z7={};Ze(Z7,{json:()=>GD});var GD=[{tfOpName:"Fill",category:"creation",inputs:[{start:0,name:"shape",type:"number[]"},{start:1,name:"value",type:"number"}],attrs:[{tfName:"T",name:"dtype",type:"dtype"}]},{tfOpName:"LinSpace",category:"creation",inputs:[{start:0,name:"start",type:"number"},{start:1,name:"stop",type:"number"},{start:2,name:"num",type:"number"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"OneHot",category:"creation",inputs:[{start:0,name:"indices",type:"tensor"},{start:1,name:"depth",type:"number"},{start:2,name:"onValue",type:"number",defaultValue:1},{start:3,name:"offValue",type:"number",defaultValue:0}],attrs:[{tfName:"axis",name:"axis",type:"number",notSupported:!0},{tfName:"T",name:"dtype",type:"dtype"}]},{tfOpName:"Ones",category:"creation",inputs:[{start:0,name:"shape",type:"number[]"}],attrs:[{tfName:"T",name:"dtype",type:"dtype"}]},{tfOpName:"OnesLike",category:"creation",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"dtype",name:"dtype",type:"dtype"}]},{tfOpName:"RandomStandardNormal",category:"creation",inputs:[{start:0,name:"shape",type:"number[]"}],attrs:[{tfName:"seed",name:"seed",type:"number",defaultValue:0},{tfName:"seed2",name:"seed2",type:"number",defaultValue:0,notSupported:!0},{tfName:"dtype",name:"dtype",type:"dtype"},{tfName:"T",name:"T",type:"number",notSupported:!0}]},{tfOpName:"RandomUniform",category:"creation",inputs:[{start:0,name:"shape",type:"number[]"}],attrs:[{tfName:"minval",name:"minval",type:"number",defaultValue:0},{tfName:"maxval",name:"maxval",type:"number",defaultValue:1},{tfName:"dtype",name:"dtype",type:"dtype"},{tfName:"seed",name:"seed",type:"number",defaultValue:0},{tfName:"seed2",name:"seed2",type:"number",defaultValue:0,notSupported:!0},{tfName:"T",name:"T",type:"number",notSupported:!0}]},{tfOpName:"RandomUniformInt",category:"creation",inputs:[{start:0,name:"shape",type:"number[]"}],attrs:[{tfName:"minval",name:"minval",type:"number"},{tfName:"maxval",name:"maxval",type:"number"},{tfName:"seed",name:"seed",type:"number",defaultValue:0},{tfName:"seed2",name:"seed2",type:"number",defaultValue:0,notSupported:!0}]},{tfOpName:"Range",category:"creation",inputs:[{start:0,name:"start",type:"number"},{start:1,name:"stop",type:"number"},{start:2,name:"step",type:"number",defaultValue:0}],attrs:[{tfName:"Tidx",name:"dtype",type:"dtype"}]},{tfOpName:"TruncatedNormal",category:"creation",inputs:[{start:0,name:"shape",type:"number[]"}],attrs:[{tfName:"means",name:"mean",type:"number",defaultValue:0},{tfName:"stddev",name:"stdDev",type:"number",defaultValue:1},{tfName:"seed",name:"seed",type:"number"},{tfName:"seed2",name:"seed2",type:"number",defaultValue:0,notSupported:!0},{tfName:"dtype",name:"dtype",type:"dtype"},{tfName:"T",name:"T",type:"number",notSupported:!0}]},{tfOpName:"Zeros",category:"creation",inputs:[{start:0,name:"shape",type:"number[]"}],attrs:[{tfName:"T",name:"dtype",type:"dtype"}]},{tfOpName:"ZerosLike",category:"creation",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype"}]},{tfOpName:"Multinomial",category:"creation",inputs:[{start:0,name:"logits",type:"tensor"},{start:1,name:"numSamples",type:"number"}],attrs:[{tfName:"seed",name:"seed",type:"number"},{tfName:"seed2",name:"seed2",type:"number"},{tfName:"T",name:"dtype",type:"dtype"},{tfName:"output_dtype",name:"output_dtype",type:"dtype"}]}],J7={};Ze(J7,{json:()=>HD});var HD=[{tfOpName:"NonMaxSuppressionV2",category:"dynamic",inputs:[{start:0,name:"boxes",type:"tensor"},{start:1,name:"scores",type:"tensor"},{start:2,name:"maxOutputSize",type:"number"},{start:3,name:"iouThreshold",type:"number"}]},{tfOpName:"NonMaxSuppressionV3",category:"dynamic",inputs:[{start:0,name:"boxes",type:"tensor"},{start:1,name:"scores",type:"tensor"},{start:2,name:"maxOutputSize",type:"number"},{start:3,name:"iouThreshold",type:"number"},{start:4,name:"scoreThreshold",type:"number"}]},{tfOpName:"NonMaxSuppressionV4",category:"dynamic",inputs:[{start:0,name:"boxes",type:"tensor"},{start:1,name:"scores",type:"tensor"},{start:2,name:"maxOutputSize",type:"number"},{start:3,name:"iouThreshold",type:"number"},{start:4,name:"scoreThreshold",type:"number"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"T_threshold",name:"threshold",type:"dtype",notSupported:!0},{tfName:"pad_to_max_output_size",name:"padToMaxOutputSize",type:"bool"}]},{tfOpName:"NonMaxSuppressionV5",category:"dynamic",inputs:[{start:0,name:"boxes",type:"tensor"},{start:1,name:"scores",type:"tensor"},{start:2,name:"maxOutputSize",type:"number"},{start:3,name:"iouThreshold",type:"number"},{start:4,name:"scoreThreshold",type:"number"},{start:5,name:"softNmsSigma",type:"number"}]},{tfOpName:"Where",category:"dynamic",inputs:[{start:0,name:"condition",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"ListDiff",category:"dynamic",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"y",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]}],Q7={};Ze(Q7,{json:()=>jD});var jD=[{tfOpName:"LowerBound",category:"evaluation",inputs:[{start:0,name:"sortedSequence",type:"tensor"},{start:1,name:"values",type:"tensor"}]},{tfOpName:"TopKV2",category:"evaluation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"k",type:"number"}],attrs:[{tfName:"sorted",name:"sorted",type:"bool"}]},{tfOpName:"UpperBound",category:"evaluation",inputs:[{start:0,name:"sortedSequence",type:"tensor"},{start:1,name:"values",type:"tensor"}]},{tfOpName:"Unique",category:"evaluation",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"UniqueV2",category:"evaluation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number"}]}],e6={};Ze(e6,{json:()=>qD});var qD=[{tfOpName:"PlaceholderWithDefault",category:"graph",inputs:[{start:0,name:"default",type:"tensor"}],attrs:[{tfName:"shape",name:"shape",type:"shape"},{tfName:"dtype",name:"dtype",type:"dtype"}]},{tfOpName:"Placeholder",category:"graph",attrs:[{tfName:"shape",name:"shape",type:"shape"},{tfName:"dtype",name:"dtype",type:"dtype"}]},{tfOpName:"Const",category:"graph"},{tfOpName:"Identity",category:"graph",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"IdentityN",category:"graph",inputs:[{start:0,end:0,name:"x",type:"tensors"}]},{tfOpName:"Snapshot",category:"graph",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"Rank",category:"graph",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"Size",category:"graph",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"Shape",category:"graph",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"ShapeN",category:"graph",inputs:[{start:0,end:0,name:"x",type:"tensors"}]},{tfOpName:"Print",category:"graph",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"data",type:"tensors"}],attrs:[{tfName:"message",name:"message",type:"string"},{tfName:"first_n",name:"firstN",type:"number",notSupported:!0},{tfName:"summarize",name:"summarize",type:"number",defaultValue:3}]},{tfOpName:"NoOp",category:"graph",inputs:[]},{tfOpName:"StopGradient",category:"graph",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"FakeQuantWithMinMaxVars",category:"graph",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"min",name:"min",type:"number"},{tfName:"max",name:"max",type:"number"}]}],t6={};Ze(t6,{json:()=>XD});var XD=[{tfOpName:"HashTable",category:"hash_table",inputs:[],attrs:[{tfName:"shared_name",name:"sharedName",type:"string"},{tfName:"use_node_name_sharing",name:"useNodeNameSharing",type:"bool"},{tfName:"key_dtype",name:"keyDType",type:"dtype"},{tfName:"value_dtype",name:"valueDType",type:"dtype"}]},{tfOpName:"HashTableV2",category:"hash_table",inputs:[],attrs:[{tfName:"shared_name",name:"sharedName",type:"string"},{tfName:"use_node_name_sharing",name:"useNodeNameSharing",type:"bool"},{tfName:"key_dtype",name:"keyDType",type:"dtype"},{tfName:"value_dtype",name:"valueDType",type:"dtype"}]},{tfOpName:"LookupTableImport",category:"hash_table",inputs:[{start:0,name:"tableHandle",type:"tensor"},{start:1,name:"keys",type:"tensor"},{start:2,name:"values",type:"tensor"}],attrs:[{tfName:"Tin",name:"tIn",type:"dtype",notSupported:!0},{tfName:"Tout",name:"tOut",type:"dtype",notSupported:!0}]},{tfOpName:"LookupTableImportV2",category:"hash_table",inputs:[{start:0,name:"tableHandle",type:"tensor"},{start:1,name:"keys",type:"tensor"},{start:2,name:"values",type:"tensor"}],attrs:[{tfName:"Tin",name:"tIn",type:"dtype",notSupported:!0},{tfName:"Tout",name:"tOut",type:"dtype",notSupported:!0}]},{tfOpName:"LookupTableFind",category:"hash_table",inputs:[{start:0,name:"tableHandle",type:"tensor"},{start:1,name:"keys",type:"tensor"},{start:2,name:"defaultValue",type:"tensor"}],attrs:[{tfName:"Tin",name:"tIn",type:"dtype",notSupported:!0},{tfName:"Tout",name:"tOut",type:"dtype",notSupported:!0}]},{tfOpName:"LookupTableFindV2",category:"hash_table",inputs:[{start:0,name:"tableHandle",type:"tensor"},{start:1,name:"keys",type:"tensor"},{start:2,name:"defaultValue",type:"tensor"}],attrs:[{tfName:"Tin",name:"tIn",type:"dtype",notSupported:!0},{tfName:"Tout",name:"tOut",type:"dtype",notSupported:!0}]},{tfOpName:"LookupTableSize",category:"hash_table",inputs:[{start:0,name:"tableHandle",type:"tensor"}]},{tfOpName:"LookupTableSizeV2",category:"hash_table",inputs:[{start:0,name:"tableHandle",type:"tensor"}]},{tfOpName:"InitializeTable",category:"hash_table",inputs:[{start:0,name:"tableHandle",type:"tensor"},{start:1,name:"keys",type:"tensor"},{start:2,name:"values",type:"tensor"}]},{tfOpName:"InitializeTableV2",category:"hash_table",inputs:[{start:0,name:"tableHandle",type:"tensor"},{start:1,name:"keys",type:"tensor"},{start:2,name:"values",type:"tensor"}]}],a6={};Ze(a6,{json:()=>KD});var KD=[{tfOpName:"ResizeBilinear",category:"image",inputs:[{start:0,name:"images",type:"tensor"},{start:1,name:"size",type:"number[]"}],attrs:[{tfName:"align_corners",name:"alignCorners",type:"bool"},{tfName:"half_pixel_centers",name:"halfPixelCenters",type:"bool"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"ResizeNearestNeighbor",category:"image",inputs:[{start:0,name:"images",type:"tensor"},{start:1,name:"size",type:"number[]"}],attrs:[{tfName:"align_corners",name:"alignCorners",type:"bool"},{tfName:"half_pixel_centers",name:"halfPixelCenters",type:"bool"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"CropAndResize",category:"image",inputs:[{start:0,name:"image",type:"tensor"},{start:1,name:"boxes",type:"tensor"},{start:2,name:"boxInd",type:"tensor"},{start:3,name:"cropSize",type:"number[]"}],attrs:[{tfName:"method",name:"method",type:"string"},{tfName:"extrapolation_value",name:"extrapolationValue",type:"number"}]},{tfOpName:"ImageProjectiveTransformV3",category:"image",inputs:[{start:0,name:"images",type:"tensor"},{start:1,name:"transforms",type:"tensor"},{start:2,name:"outputShape",type:"number[]"},{start:3,name:"fillValue",type:"number"}],attrs:[{tfName:"interpolation",name:"interpolation",type:"string"},{tfName:"fill_mode",name:"fillMode",type:"string"}]}],n6={};Ze(n6,{json:()=>YD});var YD=[{tfOpName:"Equal",category:"logical",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"NotEqual",category:"logical",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Greater",category:"logical",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"GreaterEqual",category:"logical",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Less",category:"logical",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"LessEqual",category:"logical",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"LogicalAnd",category:"logical",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"LogicalNot",category:"logical",inputs:[{start:0,name:"a",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"LogicalOr",category:"logical",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Select",category:"logical",inputs:[{start:0,name:"condition",type:"tensor"},{start:1,name:"a",type:"tensor"},{start:2,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"SelectV2",category:"logical",inputs:[{start:0,name:"condition",type:"tensor"},{start:1,name:"a",type:"tensor"},{start:2,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"BitwiseAnd",category:"logical",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"y",type:"tensor"}]}],r6={};Ze(r6,{json:()=>ZD});var ZD=[{tfOpName:"_FusedMatMul",category:"matrices",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"},{start:2,end:0,name:"args",type:"tensors"}],attrs:[{tfName:"num_args",name:"numArgs",type:"number"},{tfName:"fused_ops",name:"fusedOps",type:"string[]",defaultValue:[]},{tfName:"epsilon",name:"epsilon",type:"number",defaultValue:1e-4},{tfName:"transpose_a",name:"transposeA",type:"bool",defaultValue:!1},{tfName:"transpose_b",name:"transposeB",type:"bool",defaultValue:!1},{tfName:"leakyrelu_alpha",name:"leakyreluAlpha",type:"number",defaultValue:.2},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"MatMul",category:"matrices",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"transpose_a",name:"transposeA",type:"bool",defaultValue:!1},{tfName:"transpose_b",name:"transposeB",type:"bool",defaultValue:!1},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"BatchMatMul",category:"matrices",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"adj_x",name:"transposeA",type:"bool",defaultValue:!1},{tfName:"adj_y",name:"transposeB",type:"bool",defaultValue:!1},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"BatchMatMulV2",category:"matrices",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"adj_x",name:"transposeA",type:"bool",defaultValue:!1},{tfName:"adj_y",name:"transposeB",type:"bool",defaultValue:!1},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Transpose",category:"matrices",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"perm",type:"number[]"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Einsum",category:"matrices",inputs:[{start:0,end:0,name:"tensors",type:"tensors"}],attrs:[{tfName:"equation",name:"equation",type:"string"},{tfName:"N",name:"n",type:"number",defaultValue:2},{tfName:"T",name:"dtype",type:"dtype"}]},{tfOpName:"MatrixBandPart",category:"matrices",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"numLower",type:"tensor"},{start:1,name:"numUpper",type:"tensor"}]}],s6={};Ze(s6,{json:()=>JD});var JD=[{tfOpName:"EuclideanNorm",category:"normalization",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool",defaultValue:!1}]},{tfOpName:"FusedBatchNorm",category:"normalization",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"scale",type:"tensor"},{start:2,name:"offset",type:"tensor"},{start:3,name:"mean",type:"tensor"},{start:4,name:"variance",type:"tensor"}],attrs:[{tfName:"epsilon",name:"epsilon",type:"number",defaultValue:.001},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0}]},{tfOpName:"FusedBatchNormV2",category:"normalization",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"scale",type:"tensor"},{start:2,name:"offset",type:"tensor"},{start:3,name:"mean",type:"tensor"},{start:4,name:"variance",type:"tensor"}],attrs:[{tfName:"epsilon",name:"epsilon",type:"number",defaultValue:.001},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0}]},{tfOpName:"FusedBatchNormV3",category:"normalization",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"scale",type:"tensor"},{start:2,name:"offset",type:"tensor"},{start:3,name:"mean",type:"tensor"},{start:4,name:"variance",type:"tensor"}],attrs:[{tfName:"epsilon",name:"epsilon",type:"number",defaultValue:.001},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0}]},{tfOpName:"LRN",category:"normalization",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"depth_radius",name:"radius",type:"number",defaultValue:5},{tfName:"bias",name:"bias",type:"number",defaultValue:1},{tfName:"alpha",name:"alpha",type:"number",defaultValue:1},{tfName:"beta",name:"beta",type:"number",defaultValue:.5}]},{tfOpName:"Softmax",category:"normalization",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"LogSoftmax",category:"normalization",inputs:[{start:0,name:"x",type:"tensor"}]}],i6={};Ze(i6,{json:()=>QD});var QD=[{tfOpName:"Bincount",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"size",type:"number"},{start:2,name:"weights",type:"tensor"}]},{tfOpName:"DenseBincount",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"size",type:"number"},{start:2,name:"weights",type:"tensor"}],attrs:[{tfName:"binary_output",name:"binaryOutput",type:"bool"}]},{tfOpName:"Max",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool"}]},{tfOpName:"Mean",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool"}]},{tfOpName:"Min",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool"}]},{tfOpName:"Sum",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool"}]},{tfOpName:"All",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool"}]},{tfOpName:"Any",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool"}]},{tfOpName:"ArgMax",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number"}]},{tfOpName:"ArgMin",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number"}]},{tfOpName:"Prod",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Cumprod",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number"}],attrs:[{tfName:"exclusive",name:"exclusive",type:"bool"},{tfName:"reverse",name:"reverse",type:"bool"}]},{tfOpName:"Cumsum",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number"}],attrs:[{tfName:"exclusive",name:"exclusive",type:"bool"},{tfName:"reverse",name:"reverse",type:"bool"}]}],o6={};Ze(o6,{json:()=>eO});var eO=[{tfOpName:"ConcatV2",category:"slice_join",inputs:[{start:0,end:-1,name:"tensors",type:"tensors"},{start:-1,name:"axis",type:"number"}],attrs:[{tfName:"N",name:"n",type:"number",defaultValue:2}]},{tfOpName:"Concat",category:"slice_join",inputs:[{start:1,end:0,name:"tensors",type:"tensors"},{start:0,name:"axis",type:"number"}],attrs:[{tfName:"N",name:"n",type:"number",defaultValue:2}]},{tfOpName:"GatherV2",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"indices",type:"tensor"},{start:2,name:"axis",type:"number",defaultValue:0}],attrs:[{tfName:"batch_dims",name:"batchDims",type:"number",defaultValue:0}]},{tfOpName:"Gather",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"indices",type:"tensor"}],attrs:[{tfName:"validate_indices",name:"validateIndices",type:"bool",notSupported:!0}]},{tfOpName:"Reverse",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"dims",type:"bool[]"}]},{tfOpName:"ReverseV2",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}]},{tfOpName:"Slice",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"begin",type:"number[]"},{start:2,name:"size",type:"number[]"}]},{tfOpName:"StridedSlice",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"begin",type:"number[]"},{start:2,name:"end",type:"number[]"},{start:3,name:"strides",type:"number[]"}],attrs:[{tfName:"begin_mask",name:"beginMask",type:"number",defaultValue:0},{tfName:"end_mask",name:"endMask",type:"number",defaultValue:0},{tfName:"new_axis_mask",name:"newAxisMask",type:"number",defaultValue:0},{tfName:"ellipsis_mask",name:"ellipsisMask",type:"number",defaultValue:0},{tfName:"shrink_axis_mask",name:"shrinkAxisMask",type:"number",defaultValue:0}]},{tfOpName:"Pack",category:"slice_join",inputs:[{start:0,end:0,name:"tensors",type:"tensors"}],attrs:[{tfName:"axis",name:"axis",type:"number",defaultValue:0}]},{tfOpName:"Unpack",category:"slice_join",inputs:[{start:0,name:"tensor",type:"tensor"}],attrs:[{tfName:"axis",name:"axis",type:"number",defaultValue:0},{tfName:"num",name:"num",type:"number",defaultValue:0,notSupported:!0}]},{tfOpName:"Tile",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"reps",type:"number[]"}]},{tfOpName:"Split",category:"slice_join",inputs:[{start:0,name:"axis",type:"number",defaultValue:0},{start:1,name:"x",type:"tensor"}],attrs:[{tfName:"num_split",name:"numOrSizeSplits",type:"number",defaultValue:1}]},{tfOpName:"SplitV",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"numOrSizeSplits",type:"number[]"},{start:2,name:"axis",type:"number",defaultValue:0}]},{tfOpName:"ScatterNd",category:"slice_join",inputs:[{start:0,name:"indices",type:"tensor"},{start:1,name:"values",type:"tensor"},{start:2,name:"shape",type:"number[]"}]},{tfOpName:"GatherNd",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"indices",type:"tensor"}]},{tfOpName:"SparseToDense",category:"slice_join",inputs:[{start:0,name:"sparseIndices",type:"tensor"},{start:1,name:"outputShape",type:"number[]"},{start:2,name:"sparseValues",type:"tensor"},{start:3,name:"defaultValue",type:"tensor"}],attrs:[{tfName:"validate_indices",name:"validateIndices",type:"bool",defaultValue:!1,notSupported:!0}]},{tfOpName:"TensorScatterUpdate",category:"slice_join",inputs:[{start:0,name:"tensor",type:"tensor"},{start:1,name:"indices",type:"tensor"},{start:2,name:"values",type:"tensor"}]}],l6={};Ze(l6,{json:()=>tO});var tO=[{tfOpName:"SparseFillEmptyRows",category:"sparse",inputs:[{start:0,name:"indices",type:"tensor"},{start:1,name:"values",type:"tensor"},{start:2,name:"denseShape",type:"tensor"},{start:3,name:"defaultValue",type:"tensor"}]},{tfOpName:"SparseReshape",category:"sparse",inputs:[{start:0,name:"inputIndices",type:"tensor"},{start:1,name:"inputShape",type:"tensor"},{start:2,name:"newShape",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"SparseSegmentMean",category:"sparse",inputs:[{start:0,name:"data",type:"tensor"},{start:1,name:"indices",type:"tensor"},{start:2,name:"segmentIds",type:"tensor"}]},{tfOpName:"SparseSegmentSum",category:"sparse",inputs:[{start:0,name:"data",type:"tensor"},{start:1,name:"indices",type:"tensor"},{start:2,name:"segmentIds",type:"tensor"}]}],u6={};Ze(u6,{json:()=>aO});var aO=[{tfOpName:"FFT",category:"spectral",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"IFFT",category:"spectral",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"RFFT",category:"spectral",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"fft_length",type:"number",notSupported:!0}]},{tfOpName:"IRFFT",category:"spectral",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"fft_length",type:"number",notSupported:!0}]}],d6={};Ze(d6,{json:()=>nO});var nO=[{tfOpName:"StaticRegexReplace",category:"string",inputs:[{start:0,name:"input",type:"tensor"}],attrs:[{tfName:"pattern",name:"pattern",type:"string"},{tfName:"rewrite",name:"rewrite",type:"string"},{tfName:"replace_global",name:"replaceGlobal",type:"bool"}]},{tfOpName:"StringNGrams",category:"string",inputs:[{start:0,name:"data",type:"tensor"},{start:1,name:"dataSplits",type:"tensor"}],attrs:[{tfName:"separator",name:"separator",type:"string"},{tfName:"ngram_widths",name:"nGramWidths",type:"number[]"},{tfName:"left_pad",name:"leftPad",type:"string"},{tfName:"right_pad",name:"rightPad",type:"string"},{tfName:"pad_width",name:"padWidth",type:"number"},{tfName:"preserve_short_sequences",name:"preserveShortSequences",type:"bool"}],outputs:["ngrams","ngrams_splits"]},{tfOpName:"StringSplit",category:"string",inputs:[{start:0,name:"input",type:"tensor"},{start:1,name:"delimiter",type:"tensor"}],attrs:[{tfName:"skip_empty",name:"skipEmpty",type:"bool"}],outputs:["indices","values","shape"]},{tfOpName:"StringToHashBucketFast",category:"string",inputs:[{start:0,name:"input",type:"tensor"}],attrs:[{tfName:"num_buckets",name:"numBuckets",type:"number"}]}],p6={};Ze(p6,{json:()=>rO});var rO=[{tfOpName:"Cast",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"SrcT",name:"sdtype",type:"dtype",notSupported:!0},{tfName:"DstT",name:"dtype",type:"dtype"}]},{tfOpName:"ExpandDims",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number"}]},{tfOpName:"MirrorPad",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"padding",type:"number[]"}],attrs:[{tfName:"mode",name:"mode",type:"string"}]},{tfOpName:"Pad",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"padding",type:"number[]"}],attrs:[{tfName:"constant_value",name:"constantValue",type:"number",defaultValue:0}]},{tfOpName:"PadV2",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"padding",type:"number[]"},{start:2,name:"constantValue",type:"number",defaultValue:0}]},{tfOpName:"Reshape",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"shape",type:"number[]"}]},{tfOpName:"EnsureShape",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"shape",type:"number[]"}]},{tfOpName:"Squeeze",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"axis",tfDeprecatedName:"squeeze_dims",name:"axis",type:"number[]"}]},{tfOpName:"SpaceToBatchND",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"blockShape",type:"number[]"},{start:2,name:"paddings",type:"number[]"}]},{tfOpName:"BatchToSpaceND",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"blockShape",type:"number[]"},{start:2,name:"crops",type:"number[]"}]},{tfOpName:"DepthToSpace",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"block_size",name:"blockSize",type:"number"},{tfName:"data_format",name:"dataFormat",type:"string"}]},{tfOpName:"BroadcastTo",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"shape",type:"number[]"}],attrs:[]},{tfOpName:"BroadcastArgs",category:"transformation",inputs:[{start:0,name:"s0",type:"tensor"},{start:1,name:"s1",type:"tensor"}],attrs:[]}],p5=class{static get Instance(){return this._instance||(this._instance=new this)}constructor(){let e=[q7,X7,K7,Y7,Z7,J7,Q7,e6,t6,a6,n6,r6,s6,i6,o6,l6,u6,d6,p6],t=[].concat(...e.map(a=>a.json));this.opMappers=t.reduce((a,n)=>(a[n.tfOpName]=n,a),{})}transformGraph(e,t={}){let a=e.node,n=[],r=[],s=[],i=a.reduce((m,f)=>(m[f.name]=this.mapNode(f),f.op.startsWith("Placeholder")?n.push(m[f.name]):f.op==="Const"?r.push(m[f.name]):(f.input==null||f.input.length===0)&&s.push(m[f.name]),m),{}),o=[],l=[],u={},p={};t!=null&&(u=this.mapSignatureEntries(t.inputs),p=this.mapSignatureEntries(t.outputs));let c=Object.keys(i);c.forEach(m=>{let f=i[m];f.inputNames.forEach((g,y)=>{let[x,,A]=vr(g),b=i[x];if(b.outputs!=null){let w=b.outputs.indexOf(A);if(w!==-1){let I=`${x}:${w}`;f.inputNames[y]=I}}f.inputs.push(b),b.children.push(f)})}),Object.keys(p).length===0?c.forEach(m=>{let f=i[m];f.children.length===0&&l.push(f)}):Object.keys(p).forEach(m=>{let[f]=vr(m),g=i[f];g!=null&&(g.signatureKey=p[m],l.push(g))}),Object.keys(u).length>0?Object.keys(u).forEach(m=>{let[f]=vr(m),g=i[f];g&&(g.signatureKey=u[m],o.push(g))}):o=n;let d={};e.library!=null&&e.library.function!=null&&(d=e.library.function.reduce((m,f)=>(m[f.signature.name]=this.mapFunction(f),m),{}));let h={nodes:i,inputs:o,outputs:l,weights:r,placeholders:n,signature:t,functions:d};return s.length>0&&(h.initNodes=s),h}mapSignatureEntries(e){return Object.keys(e||{}).reduce((t,a)=>(t[e[a].name]=a,t),{})}mapNode(e){let t=j7(e.op)||this.opMappers[e.op]||{};e.attr==null&&(e.attr={});let a={name:e.name,op:e.op,category:t.category,inputNames:(e.input||[]).map(n=>n.startsWith("^")?n.slice(1):n),inputs:[],children:[],inputParams:{},attrParams:{},rawAttrs:e.attr,outputs:t.outputs};return t.inputs!=null&&(a.inputParams=t.inputs.reduce((n,r)=>(n[r.name]={type:r.type,inputIndexStart:r.start,inputIndexEnd:r.end},n),{})),t.attrs!=null&&(a.attrParams=t.attrs.reduce((n,r)=>{let s=r.type,i;switch(r.type){case"string":i=b1(e.attr,r.tfName,r.defaultValue),i===void 0&&r.tfDeprecatedName&&(i=b1(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"string[]":i=T1(e.attr,r.tfName,r.defaultValue),i===void 0&&r.tfDeprecatedName&&(i=T1(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"number":i=w1(e.attr,r.tfName,r.defaultValue||0),i===void 0&&r.tfDeprecatedName&&(i=w1(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"number[]":i=C1(e.attr,r.tfName,r.defaultValue),i===void 0&&r.tfDeprecatedName&&(i=C1(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"bool":i=v1(e.attr,r.tfName,r.defaultValue),i===void 0&&r.tfDeprecatedName&&(i=v1(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"bool[]":i=R1(e.attr,r.tfName,r.defaultValue),i===void 0&&r.tfDeprecatedName&&(i=R1(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"shape":i=S1(e.attr,r.tfName,r.defaultValue),i===void 0&&r.tfDeprecatedName&&(i=S1(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"shape[]":i=N1(e.attr,r.tfName,r.defaultValue),i===void 0&&r.tfDeprecatedName&&(i=N1(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"dtype":i=k1(e.attr,r.tfName,r.defaultValue),i===void 0&&r.tfDeprecatedName&&(i=k1(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"dtype[]":i=I1(e.attr,r.tfName,r.defaultValue),i===void 0&&r.tfDeprecatedName&&(i=I1(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"func":i=c5(e.attr,r.tfName,r.defaultValue),i===void 0&&r.tfDeprecatedName&&(i=c5(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"tensor":case"tensors":break;default:throw new Error(`Unsupported param type: ${r.type} for op: ${e.op}`)}return n[r.name]={value:i,type:s},n},{})),a}mapFunction(e){let t=e.nodeDef,a=[],n=[],r={};t!=null&&(r=t.reduce((u,p)=>(u[p.name]=this.mapNode(p),p.op==="Const"&&n.push(u[p.name]),u),{}));let s=[],i=[];e.signature.inputArg.forEach(u=>{let[p]=vr(u.name),c={name:p,op:"Placeholder",inputs:[],inputNames:[],category:"graph",inputParams:{},attrParams:{dtype:{value:u3(u.type),type:"dtype"}},children:[]};c.signatureKey=u.name,s.push(c),r[p]=c}),Object.keys(r).forEach(u=>{let p=r[u];p.inputNames.forEach((c,d)=>{let[h,,m]=vr(c),f=r[h];if(f.outputs!=null){let g=f.outputs.indexOf(m);if(g!==-1){let y=`${h}:${g}`;p.inputNames[d]=y}}p.inputs.push(f),f.children.push(p)})});let o=e.ret;e.signature.outputArg.forEach(u=>{let[p,c]=vr(o[u.name]),d=r[p];d!=null&&(d.defaultOutput=c,i.push(d))});let l=this.mapArgsToSignature(e);return{nodes:r,inputs:s,outputs:i,weights:n,placeholders:a,signature:l}}mapArgsToSignature(e){return{methodName:e.signature.name,inputs:e.signature.inputArg.reduce((t,a)=>(t[a.name]=this.mapArgToTensorInfo(a),t),{}),outputs:e.signature.outputArg.reduce((t,a)=>(t[a.name]=this.mapArgToTensorInfo(a,e.ret),t),{})}}mapArgToTensorInfo(e,t){let a=e.name;return t!=null&&(a=t[a]),{name:a,dtype:e.type}}};function sO(e){let t=B().global;if(typeof t.atob!="undefined")return t.atob(e);if(typeof Buffer!="undefined")return new Buffer(e,"base64").toString();throw new Error("Unable to decode base64 in this environment. Missing built-in atob() or Buffer()")}function c6(e,t){let a=Array.isArray(e)?String.fromCharCode.apply(null,e):sO(e);return t?a:a.toLowerCase()}function b1(e,t,a,n=!1){let r=e[t];return r!=null?c6(r.s,n):a}function v1(e,t,a){let n=e[t];return n?n.b:a}function w1(e,t,a){let n=e[t]||{},r=n.i!=null?n.i:n.f!=null?n.f:a;return typeof r=="number"?r:parseInt(r,10)}function u3(e){switch(typeof e=="string"&&(e=Ka[e]),e){case Ka.DT_FLOAT:case Ka.DT_HALF:return"float32";case Ka.DT_INT32:case Ka.DT_INT64:case Ka.DT_INT8:case Ka.DT_UINT8:return"int32";case Ka.DT_BOOL:return"bool";case Ka.DT_DOUBLE:return"float32";case Ka.DT_STRING:return"string";case Ka.DT_COMPLEX64:case Ka.DT_COMPLEX128:return"complex64";default:return null}}function c5(e,t,a){let n=e[t];return n&&n.func?n.func.name:a}function k1(e,t,a){let n=e[t];return n&&n.type?u3(n.type):a}function I1(e,t,a){let n=e[t];return n&&n.list&&n.list.type?n.list.type.map(r=>u3(r)):a}function h6(e){if(!e.unknownRank)return e.dim!=null?e.dim.map(t=>typeof t.size=="number"?t.size:parseInt(t.size,10)):[]}function S1(e,t,a){let n=e[t];return n&&n.shape?h6(n.shape):a}function C1(e,t,a){let n=e[t];return n?((n.list.f&&n.list.f.length?n.list.f:n.list.i)||[]).map(r=>typeof r=="number"?r:parseInt(r,10)):a}function T1(e,t,a,n=!1){let r=e[t];return r&&r.list&&r.list.s?r.list.s.map(s=>c6(s,n)):a}function N1(e,t,a){let n=e[t];return n&&n.list&&n.list.shape?n.list.shape.map(r=>h6(r)):a}function R1(e,t,a){let n=e[t];return n&&n.list&&n.list.b?n.list.b:a}var iO=class{constructor(e,t,a){this.node=e,this.tensorMap=t,this.context=a,this.inputs=[],this.attrs={},this.inputs=e.inputNames.map(n=>this.getInput(n)),e.rawAttrs!=null&&(this.attrs=Object.keys(e.rawAttrs).reduce((n,r)=>(n[r]=this.getAttr(r),n),{}))}getInput(e){return da(e,this.tensorMap,this.context)}getAttr(e,t){let a=this.node.rawAttrs[e];if(a.tensor!=null)return da(e,this.tensorMap,this.context);if(a.i!=null||a.f!=null)return w1(this.node.rawAttrs,e,t);if(a.s!=null)return b1(this.node.rawAttrs,e,t);if(a.b!=null)return v1(this.node.rawAttrs,e,t);if(a.shape!=null)return S1(this.node.rawAttrs,e,t);if(a.type!=null)return k1(this.node.rawAttrs,e,t);if(a.list!=null){if(a.list.i!=null||a.list.f!=null)return C1(this.node.rawAttrs,e,t);if(a.list.s!=null)return T1(this.node.rawAttrs,e,t);if(a.list.shape!=null)return N1(this.node.rawAttrs,e,t);if(a.list.b!=null)return R1(this.node.rawAttrs,e,t);if(a.list.type!=null)return I1(this.node.rawAttrs,e,t)}return t}},ta={};Ze(ta,{OP_SCOPE_SUFFIX:()=>sg,abs:()=>Za,acos:()=>ab,acosh:()=>nb,add:()=>we,addN:()=>Dh,all:()=>rb,any:()=>sb,argMax:()=>ir,argMin:()=>ib,asin:()=>ob,asinh:()=>lb,atan:()=>ub,atan2:()=>db,atanh:()=>pb,avgPool:()=>hg,avgPool3d:()=>fb,basicLSTMCell:()=>gb,batchNorm:()=>Wp,batchNorm2d:()=>yb,batchNorm3d:()=>xb,batchNorm4d:()=>Ab,batchToSpaceND:()=>mg,bincount:()=>fg,bitwiseAnd:()=>bb,booleanMaskAsync:()=>r7,broadcastArgs:()=>vb,broadcastTo:()=>Gl,buffer:()=>_e,cast:()=>Ue,ceil:()=>wb,clipByValue:()=>kb,clone:()=>Ia,complex:()=>Tr,concat:()=>lt,concat1d:()=>Ib,concat2d:()=>Uu,concat3d:()=>Sb,concat4d:()=>Cb,conv1d:()=>Tb,conv2d:()=>Bp,conv2dTranspose:()=>Rb,conv3d:()=>Eb,conv3dTranspose:()=>Mb,cos:()=>$b,cosh:()=>Pb,cosineWindow:()=>Xh,cumprod:()=>_b,cumsum:()=>Fb,denseBincount:()=>Db,depthToSpace:()=>Ob,depthwiseConv2d:()=>Oh,diag:()=>zb,dilation2d:()=>Lb,div:()=>ve,divNoNan:()=>Bb,dot:()=>Vb,dropout:()=>u7,einsum:()=>Vs,elu:()=>xg,enclosingPowerOfTwo:()=>Xg,ensureShape:()=>Ub,equal:()=>yg,erf:()=>Gb,euclideanNorm:()=>qb,exp:()=>rs,expandDims:()=>Wt,expm1:()=>Xb,eye:()=>bg,fft:()=>Gh,fill:()=>or,floor:()=>vg,floorDiv:()=>zp,fused:()=>Kg,gather:()=>wg,gatherND:()=>l7,greater:()=>Gp,greaterEqual:()=>kg,ifft:()=>Jd,imag:()=>Hp,image:()=>fe,inTopKAsync:()=>d7,irfft:()=>Vg,isFinite:()=>Kb,isInf:()=>Yb,isNaN:()=>Zb,leakyRelu:()=>Ig,less:()=>mh,lessEqual:()=>zh,linalg:()=>x7,linspace:()=>Jb,localResponseNormalization:()=>Qb,log:()=>Zl,log1p:()=>Sg,logSigmoid:()=>t4,logSoftmax:()=>a4,logSumExp:()=>Tg,logicalAnd:()=>Kd,logicalNot:()=>Ng,logicalOr:()=>Rg,logicalXor:()=>n4,losses:()=>A7,lowerBound:()=>r4,matMul:()=>pt,max:()=>ga,maxPool:()=>Eg,maxPool3d:()=>s4,maxPoolWithArgmax:()=>i4,maximum:()=>Mg,mean:()=>Yd,meshgrid:()=>o4,min:()=>ns,minimum:()=>Zd,mirrorPad:()=>l4,mod:()=>Gu,moments:()=>u4,movingAverage:()=>s7,mul:()=>te,multiRNNCell:()=>d4,multinomial:()=>p4,neg:()=>Wn,norm:()=>Up,notEqual:()=>$g,oneHot:()=>fh,ones:()=>jr,onesLike:()=>c4,op:()=>z,outerProduct:()=>h4,pad:()=>Rn,pad1d:()=>m4,pad2d:()=>f4,pad3d:()=>g4,pad4d:()=>y4,pool:()=>x4,pow:()=>Yl,prelu:()=>_g,print:()=>pg,prod:()=>A4,raggedGather:()=>b4,raggedRange:()=>v4,raggedTensorToTensor:()=>w4,rand:()=>k4,randomGamma:()=>T4,randomNormal:()=>Lg,randomStandardNormal:()=>N4,randomUniform:()=>Bh,randomUniformInt:()=>R4,range:()=>Jl,real:()=>Ql,reciprocal:()=>E4,relu:()=>jp,relu6:()=>Wg,reshape:()=>Q,reverse:()=>ss,reverse1d:()=>M4,reverse2d:()=>$4,reverse3d:()=>P4,reverse4d:()=>_4,rfft:()=>Hh,round:()=>Bg,rsqrt:()=>F4,scalar:()=>Ge,scatterND:()=>i7,searchSorted:()=>Wh,selu:()=>D4,separableConv2d:()=>O4,setdiff1dAsync:()=>z4,sigmoid:()=>za,sign:()=>L4,signal:()=>y7,sin:()=>W4,sinh:()=>B4,slice:()=>Fe,slice1d:()=>V4,slice2d:()=>U4,slice3d:()=>qp,slice4d:()=>Vh,softmax:()=>Uh,softplus:()=>Cg,spaceToBatchND:()=>Pg,sparse:()=>b7,sparseToDense:()=>o7,spectral:()=>g7,split:()=>Sa,sqrt:()=>ar,square:()=>Tn,squaredDifference:()=>Ug,squeeze:()=>Oe,stack:()=>ha,step:()=>Gg,stridedSlice:()=>G4,string:()=>v7,sub:()=>xe,sum:()=>ot,tan:()=>H4,tanh:()=>hh,tensor:()=>Ve,tensor1d:()=>Bt,tensor2d:()=>Qn,tensor3d:()=>Hg,tensor4d:()=>j4,tensor5d:()=>q4,tensor6d:()=>X4,tensorScatterUpdate:()=>Y4,tile:()=>Kr,topk:()=>Z4,transpose:()=>Qs,truncatedNormal:()=>J4,unique:()=>Q4,unsortedSegmentSum:()=>e7,unstack:()=>Na,upperBound:()=>t7,variable:()=>a7,where:()=>Sr,whereAsync:()=>qg,zeros:()=>yn,zerosLike:()=>Qa});var oO=(e,t,a,n=ta)=>{switch(e.op){case"BiasAdd":case"AddV2":case"Add":return[n.add(k("a",e,t,a),k("b",e,t,a))];case"AddN":return[n.addN(k("tensors",e,t,a))];case"FloorMod":case"Mod":return[n.mod(k("a",e,t,a),k("b",e,t,a))];case"Mul":return[n.mul(k("a",e,t,a),k("b",e,t,a))];case"RealDiv":case"Div":return[n.div(k("a",e,t,a),k("b",e,t,a))];case"DivNoNan":return[n.divNoNan(k("a",e,t,a),k("b",e,t,a))];case"FloorDiv":return[n.floorDiv(k("a",e,t,a),k("b",e,t,a))];case"Sub":return[n.sub(k("a",e,t,a),k("b",e,t,a))];case"Minimum":return[n.minimum(k("a",e,t,a),k("b",e,t,a))];case"Maximum":return[n.maximum(k("a",e,t,a),k("b",e,t,a))];case"Pow":return[n.pow(k("a",e,t,a),k("b",e,t,a))];case"SquaredDifference":return[n.squaredDifference(k("a",e,t,a),k("b",e,t,a))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},lO=(e,t,a,n=ta)=>{switch(e.op){case"Abs":case"ComplexAbs":return[n.abs(k("x",e,t,a))];case"Acos":return[n.acos(k("x",e,t,a))];case"Acosh":return[n.acosh(k("x",e,t,a))];case"Asin":return[n.asin(k("x",e,t,a))];case"Asinh":return[n.asinh(k("x",e,t,a))];case"Atan":return[n.atan(k("x",e,t,a))];case"Atan2":return[n.atan2(k("x",e,t,a),k("y",e,t,a))];case"Atanh":return[n.atanh(k("x",e,t,a))];case"Ceil":return[n.ceil(k("x",e,t,a))];case"Complex":return[n.complex(k("real",e,t,a),k("imag",e,t,a))];case"Cos":return[n.cos(k("x",e,t,a))];case"Cosh":return[n.cosh(k("x",e,t,a))];case"Elu":return[n.elu(k("x",e,t,a))];case"Erf":return[n.erf(k("x",e,t,a))];case"Exp":return[n.exp(k("x",e,t,a))];case"Expm1":return[n.expm1(k("x",e,t,a))];case"Floor":return[n.floor(k("x",e,t,a))];case"Log":return[n.log(k("x",e,t,a))];case"Log1p":return[n.log1p(k("x",e,t,a))];case"Imag":return[n.imag(k("x",e,t,a))];case"Neg":return[n.neg(k("x",e,t,a))];case"Reciprocal":return[n.reciprocal(k("x",e,t,a))];case"Real":return[n.real(k("x",e,t,a))];case"Relu":return[n.relu(k("x",e,t,a))];case"Round":return[n.round(k("x",e,t,a))];case"Selu":return[n.selu(k("x",e,t,a))];case"Sigmoid":return[n.sigmoid(k("x",e,t,a))];case"Sin":return[n.sin(k("x",e,t,a))];case"Sign":return[n.sign(k("x",e,t,a))];case"Sinh":return[n.sinh(k("x",e,t,a))];case"Softplus":return[n.softplus(k("x",e,t,a))];case"Sqrt":return[n.sqrt(k("x",e,t,a))];case"Square":return[n.square(k("x",e,t,a))];case"Tanh":return[n.tanh(k("x",e,t,a))];case"Tan":return[n.tan(k("x",e,t,a))];case"ClipByValue":return[n.clipByValue(k("x",e,t,a),k("clipValueMin",e,t,a),k("clipValueMax",e,t,a))];case"Relu6":return[n.relu6(k("x",e,t,a))];case"Rsqrt":return[n.rsqrt(da(e.inputNames[0],t,a))];case"LeakyRelu":return[n.leakyRelu(k("x",e,t,a),k("alpha",e,t,a))];case"Prelu":return[n.prelu(k("x",e,t,a),k("alpha",e,t,a))];case"IsNan":return[n.isNaN(da(e.inputNames[0],t,a))];case"IsInf":return[n.isInf(da(e.inputNames[0],t,a))];case"IsFinite":return[n.isFinite(da(e.inputNames[0],t,a))];default:throw TypeError(`Node type ${e.op} is not implemented`)}};function Cn(e,t,a=""){if(!(typeof e=="number"||typeof t=="number")){v.assert(e.length===t.length,()=>a+` Shapes ${e} and ${t} must match`);for(let n=0;n<e.length;n++){let r=e[n],s=t[n];v.assert(r<0||s<0||r===s,()=>a+` Shapes ${e} and ${t} must match`)}}}function h5(e){return!(typeof e=="number"||e.some(t=>t<0))}function Id(e,t,a){let n=E1(e,a),r=!h5(n);if(r&&t.length===0)throw new Error(`Tried to calculate elements of an empty list with non-fully-defined elementShape: ${n}`);if(r&&t.forEach(s=>{n=E1(s.shape,n)}),!h5(n))throw new Error(`Non-fully-defined elementShape: ${n}`);return n}function E1(e,t){if(typeof e=="number")return t;if(typeof t=="number")return e;if(e.length!==t.length)throw new Error(`Incompatible ranks during merge: ${e} vs. ${t}`);let a=[];for(let n=0;n<e.length;++n){let r=e[n],s=t[n];if(r>=0&&s>=0&&r!==s)throw new Error(`Incompatible shape during merge: ${e} vs. ${t}`);a[n]=r>=0?r:s}return a}var uO=class{constructor(e,t,a,n,r,s,i){this.name=e,this.dtype=t,this.maxSize=a,this.elementShape=n,this.identicalElementShapes=r,this.dynamicSize=s,this.clearAfterRead=i,this.tensors=[],this.closed_=!1,this.idTensor=Ge(0),Ln(this.idTensor)}get id(){return this.idTensor.id}get closed(){return this.closed_}clearAndClose(e){this.tensors.forEach(t=>{(e==null||!e.has(t.tensor.id))&&t.tensor.dispose()}),this.tensors=[],this.closed_=!0,this.idTensor.dispose()}size(){return this.tensors.length}read(e){if(this.closed_)throw new Error(`TensorArray ${this.name} has already been closed.`);if(e<0||e>=this.size())throw new Error(`Tried to read from index ${e}, but array size is: ${this.size()}`);let t=this.tensors[e];if(t.cleared)throw new Error(`TensorArray ${this.name}: Could not read index ${e} twice because it was cleared after a previous read (perhaps try setting clear_after_read = false?).`);return this.clearAfterRead&&(t.cleared=!0),t.read=!0,t.tensor}readMany(e){return e.map(t=>this.read(t))}write(e,t){if(this.closed_)throw new Error(`TensorArray ${this.name} has already been closed.`);if(e<0||!this.dynamicSize&&e>=this.maxSize)throw new Error(`Tried to write to index ${e}, but array is not resizeable and size is: ${this.maxSize}`);let a=this.tensors[e]||{};if(t.dtype!==this.dtype)throw new Error(`TensorArray ${this.name}: Could not write to TensorArray index ${e},
          because the value dtype is ${t.dtype}, but TensorArray dtype is ${this.dtype}.`);if(this.size()===0&&(this.elementShape==null||this.elementShape.length===0)&&(this.elementShape=t.shape),Cn(this.elementShape,t.shape,`TensorArray ${this.name}: Could not write to TensorArray index ${e}.`),a.read)throw new Error(`TensorArray ${this.name}: Could not write to TensorArray index ${e}, because it has already been read.`);if(a.written)throw new Error(`TensorArray ${this.name}: Could not write to TensorArray index ${e}, because it has already been written.`);a.tensor=t,Ln(t),a.written=!0,this.tensors[e]=a}writeMany(e,t){if(e.length!==t.length)throw new Error(`TensorArray ${this.name}: could not write multiple tensors,because the index size: ${e.length} is not the same as tensors size: ${t.length}.`);e.forEach((a,n)=>this.write(a,t[n]))}gather(e,t){if(t&&t!==this.dtype)throw new Error(`TensorArray dtype is ${this.dtype} but gather requested dtype ${t}`);if(e)e=e.slice(0,this.size());else{e=[];for(let n=0;n<this.size();n++)e.push(n)}if(e.length===0)return Ve([],[0].concat(this.elementShape));let a=this.readMany(e);return Cn(this.elementShape,a[0].shape,"TensorArray shape mismatch: "),ha(a,0)}concat(e){if(e&&e!==this.dtype)throw new Error(`TensorArray dtype is ${this.dtype} but concat requested dtype ${e}`);if(this.size()===0)return Ve([],[0].concat(this.elementShape));let t=[];for(let n=0;n<this.size();n++)t.push(n);let a=this.readMany(t);return Cn(this.elementShape,a[0].shape,`TensorArray shape mismatch: tensor array shape (${this.elementShape}) vs first tensor shape (${a[0].shape})`),lt(a,0)}scatter(e,t){if(t.dtype!==this.dtype)throw new Error(`TensorArray dtype is ${this.dtype} but tensor has dtype ${t.dtype}`);if(e.length!==t.shape[0])throw new Error(`Expected len(indices) == tensor.shape[0], but saw: ${e.length} vs. ${t.shape[0]}`);let a=Math.max(...e);if(!this.dynamicSize&&a>=this.maxSize)throw new Error(`Max index must be < array size (${a}  vs. ${this.maxSize})`);this.writeMany(e,Na(t,0))}split(e,t){if(t.dtype!==this.dtype)throw new Error(`TensorArray dtype is ${this.dtype} but tensor has dtype ${t.dtype}`);let a=0,n=e.map(o=>(a+=o,a));if(a!==t.shape[0])throw new Error(`Expected sum of lengths to be equal to
          tensor.shape[0], but sum of lengths is
        ${a}, and tensor's shape is: ${t.shape}`);if(!this.dynamicSize&&e.length!==this.maxSize)throw new Error(`TensorArray's size is not equal to the size of lengths (${this.maxSize} vs. ${e.length}), and the TensorArray is not marked as dynamically resizeable`);let r=a===0?0:t.size/a,s=[];De(()=>{t=Q(t,[1,a,r]);for(let o=0;o<e.length;++o){let l=[0,o===0?0:n[o-1],0],u=[1,e[o],r];s[o]=Q(Fe(t,l,u),this.elementShape)}return s});let i=[];for(let o=0;o<e.length;o++)i[o]=o;this.writeMany(i,s)}},e0=class M1{get id(){return this.idTensor.id}constructor(t,a,n,r=-1){this.tensors=t,this.elementShape=a,this.elementDtype=n,t!=null&&t.forEach(s=>{if(n!==s.dtype)throw new Error(`Invalid data types; op elements ${n}, but list elements ${s.dtype}`);Cn(a,s.shape,"TensorList shape mismatch: "),Ln(s)}),this.idTensor=Ge(0),this.maxNumElements=r,Ln(this.idTensor)}copy(){return new M1([...this.tensors],this.elementShape,this.elementDtype)}clearAndClose(t){this.tensors.forEach(a=>{(t==null||!t.has(a.id))&&a.dispose()}),this.tensors.length=0,this.idTensor.dispose()}size(){return this.tensors.length}stack(t,a,n=-1){if(a!==this.elementDtype)throw new Error(`Invalid data types; op elements ${a}, but list elements ${this.elementDtype}`);if(n!==-1&&this.tensors.length!==n)throw new Error(`Operation expected a list with ${n} elements but got a list with ${this.tensors.length} elements.`);Cn(t,this.elementShape,"TensorList shape mismatch: ");let r=Id(this.elementShape,this.tensors,t);return De(()=>{let s=this.tensors.map(i=>Q(i,r));return ha(s,0)})}popBack(t,a){if(a!==this.elementDtype)throw new Error(`Invalid data types; op elements ${a}, but list elements ${this.elementDtype}`);if(this.size()===0)throw new Error("Trying to pop from an empty list.");let n=Id(this.elementShape,this.tensors,t),r=this.tensors.pop();return r.kept=!1,Cn(r.shape,t,"TensorList shape mismatch: "),Q(r,n)}pushBack(t){if(t.dtype!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t.dtype}, but list elements ${this.elementDtype}`);if(Cn(t.shape,this.elementShape,"TensorList shape mismatch: "),this.maxNumElements===this.size())throw new Error("Trying to push element into a full list.");Ln(t),this.tensors.push(t)}resize(t){if(t<0)throw new Error(`TensorListResize expects size to be non-negative. Got: ${t}`);if(this.maxNumElements!==-1&&t>this.maxNumElements)throw new Error(`TensorListResize input size ${t} is greater maxNumElement ${this.maxNumElements}.`);let a=new M1([],this.elementShape,this.elementDtype,this.maxNumElements);a.tensors.length=t;for(let n=0;n<Math.min(this.tensors.length,t);++n)a.tensors[n]=this.tensors[n];return a}getItem(t,a,n){if(n!==this.elementDtype)throw new Error(`Invalid data types; op elements ${n}, but list elements ${this.elementDtype}`);if(t<0||t>this.tensors.length)throw new Error(`Trying to access element ${t} in a list with ${this.tensors.length} elements.`);if(this.tensors[t]==null)throw new Error(`element at index ${t} is null.`);Cn(this.tensors[t].shape,a,"TensorList shape mismatch: ");let r=Id(this.elementShape,this.tensors,a);return Q(this.tensors[t],r)}setItem(t,a){if(a.dtype!==this.elementDtype)throw new Error(`Invalid data types; op elements ${a.dtype}, but list elements ${this.elementDtype}`);if(t<0||this.maxNumElements!==-1&&t>=this.maxNumElements)throw new Error(`Trying to set element ${t} in a list with max ${this.maxNumElements} elements.`);Cn(this.elementShape,a.shape,"TensorList shape mismatch: "),Ln(a),this.tensors[t]!=null&&(this.tensors[t].kept=!1),this.tensors[t]=a}gather(t,a,n){if(a!==this.elementDtype)throw new Error(`Invalid data types; op elements ${a}, but list elements ${this.elementDtype}`);Cn(this.elementShape,n,"TensorList shape mismatch: "),t=t.slice(0,this.size());let r=Id(this.elementShape,this.tensors,n);return t.length===0?Ve([],[0].concat(r)):De(()=>{let s=t.map(i=>Q(this.tensors[i],r));return ha(s,0)})}concat(t,a){if(t&&t!==this.elementDtype)throw new Error(`TensorList dtype is ${this.elementDtype} but concat requested dtype ${t}`);Cn(this.elementShape,a,"TensorList shape mismatch: ");let n=Id(this.elementShape,this.tensors,a);return this.size()===0?Ve([],[0].concat(n)):De(()=>{let r=this.tensors.map(s=>Q(s,n));return lt(r,0)})}};function dO(e,t,a){let n=e.dtype;if(e.shape.length<1)throw new Error(`Tensor must be at least a vector, but saw shape: ${e.shape}`);if(e.dtype!==a)throw new Error(`Invalid data types; op elements ${e.dtype}, but list elements ${a}`);let r=e.shape.slice(1);Cn(r,t,"TensorList shape mismatch: ");let s=Na(e);return new e0(s,t,n)}function pO(e,t,a,n){return new e0([],e,t,n)}function cO(e,t,a,n){if(t.length!==e.shape[0])throw new Error(`Expected len(indices) == tensor.shape[0], but saw: ${t.length} vs. ${e.shape[0]}`);let r=Math.max(...t);if(n!=null&&n!==-1&&r>=n)throw new Error(`Max index must be < array size (${r}  vs. ${n})`);let s=new e0([],a,e.dtype,n),i=Na(e,0);return t.forEach((o,l)=>{s.setItem(o,i[l])}),s}function hO(e,t,a){let n=0,r=t.map(p=>(n+=p,n));if(n!==e.shape[0])throw new Error(`Expected sum of lengths to be equal to
          tensor.shape[0], but sum of lengths is
        ${n}, and tensor's shape is: ${e.shape}`);let s=e.shape.slice(1),i=E1(s,a),o=n===0?0:e.size/n,l=De(()=>{let p=[];e=Q(e,[1,n,o]);for(let c=0;c<t.length;++c){let d=[0,c===0?0:r[c-1],0],h=[1,t[c],o];p[c]=Q(Fe(e,d,h),i)}return e.dispose(),p}),u=new e0([],a,e.dtype,t.length);for(let p=0;p<l.length;p++)u.setItem(p,l[p]);return u}var mO=async(e,t,a)=>{switch(e.op){case"If":case"StatelessIf":{let n=k("thenBranch",e,t,a),r=k("elseBranch",e,t,a),s=k("cond",e,t,a),i=k("args",e,t,a);return(await s.data())[0]?a.functionMap[n].executeFunctionAsync(i,a.tensorArrayMap,a.tensorListMap):a.functionMap[r].executeFunctionAsync(i,a.tensorArrayMap,a.tensorListMap)}case"While":case"StatelessWhile":{let n=k("body",e,t,a),r=k("cond",e,t,a),s=k("args",e,t,a),i=await a.functionMap[r].executeFunctionAsync(s,a.tensorArrayMap,a.tensorListMap),o=s.map(p=>p.id),l=await i[0].data();i.forEach(p=>{!p.kept&&o.indexOf(p.id)===-1&&p.dispose()});let u=s;for(;l[0];){let p=u;u=await a.functionMap[n].executeFunctionAsync(u,a.tensorArrayMap,a.tensorListMap);let c=u.map(h=>h.id);p.forEach(h=>{!h.kept&&o.indexOf(h.id)===-1&&c.indexOf(h.id)===-1&&h.dispose()});let d=await a.functionMap[r].executeFunctionAsync(u,a.tensorArrayMap,a.tensorListMap);l=await d[0].data(),d.forEach(h=>{!h.kept&&o.indexOf(h.id)===-1&&c.indexOf(h.id)===-1&&h.dispose()})}return u}case"LoopCond":{let n=k("pred",e,t,a);return[wr(n)]}case"Switch":{let n=k("pred",e,t,a),r=k("data",e,t,a);return r.kept||(r=wr(r)),(await n.data())[0]?[void 0,r]:[r,void 0]}case"Merge":{let n=e.inputNames.find(r=>da(r,t,a)!==void 0);if(n){let r=da(n,t,a);return[wr(r)]}return}case"Enter":{let n=k("frameName",e,t,a),r=k("tensor",e,t,a);return a.enterFrame(n),[wr(r)]}case"Exit":{let n=k("tensor",e,t,a);return a.exitFrame(),[wr(n)]}case"NextIteration":{let n=k("tensor",e,t,a);return a.nextIteration(),[wr(n)]}case"TensorArrayV3":{let n=k("size",e,t,a),r=k("dtype",e,t,a),s=k("elementShape",e,t,a),i=k("dynamicSize",e,t,a),o=k("clearAfterRead",e,t,a),l=k("identicalElementShapes",e,t,a),u=k("name",e,t,a),p=new uO(u,r,n,s,l,i,o);return a.addTensorArray(p),[p.idTensor,Ge(1)]}case"TensorArrayWriteV3":{let n=k("tensorArrayId",e,t,a),r=k("index",e,t,a),s=k("tensor",e,t,a),i=a.getTensorArray(n.id);return i.write(r,s),[i.idTensor]}case"TensorArrayReadV3":{let n=k("tensorArrayId",e,t,a),r=k("index",e,t,a);return[a.getTensorArray(n.id).read(r)]}case"TensorArrayGatherV3":{let n=k("tensorArrayId",e,t,a),r=k("indices",e,t,a),s=k("dtype",e,t,a);return[a.getTensorArray(n.id).gather(r,s)]}case"TensorArrayScatterV3":{let n=k("tensorArrayId",e,t,a),r=k("indices",e,t,a),s=k("tensor",e,t,a),i=a.getTensorArray(n.id);return i.scatter(r,s),[i.idTensor]}case"TensorArrayConcatV3":{let n=k("tensorArrayId",e,t,a),r=a.getTensorArray(n.id),s=k("dtype",e,t,a);return[r.concat(s)]}case"TensorArraySplitV3":{let n=k("tensorArrayId",e,t,a),r=k("tensor",e,t,a),s=k("lengths",e,t,a),i=a.getTensorArray(n.id);return i.split(s,r),[i.idTensor]}case"TensorArraySizeV3":{let n=k("tensorArrayId",e,t,a),r=a.getTensorArray(n.id);return[Ge(r.size(),"int32")]}case"TensorArrayCloseV3":{let n=k("tensorArrayId",e,t,a),r=a.getTensorArray(n.id);return r.clearAndClose(),[r.idTensor]}case"TensorListSetItem":{let n=k("tensorListId",e,t,a),r=k("index",e,t,a),s=k("tensor",e,t,a),i=a.getTensorList(n.id);return i.setItem(r,s),[i.idTensor]}case"TensorListGetItem":{let n=k("tensorListId",e,t,a),r=k("index",e,t,a),s=k("elementShape",e,t,a),i=k("elementDType",e,t,a);return[a.getTensorList(n.id).getItem(r,s,i)]}case"TensorListScatterV2":case"TensorListScatter":{let n=k("indices",e,t,a),r=k("tensor",e,t,a),s=k("elementShape",e,t,a),i=k("numElements",e,t,a),o=cO(r,n,s,i);return a.addTensorList(o),[o.idTensor]}case"TensorListReserve":case"EmptyTensorList":{let n=k("elementShape",e,t,a),r=k("elementDType",e,t,a),s;e.op==="TensorListReserve"?s="numElements":s="maxNumElements";let i=k(s,e,t,a),o=e.op==="TensorListReserve"?-1:i,l=pO(n,r,i,o);return a.addTensorList(l),[l.idTensor]}case"TensorListGather":{let n=k("tensorListId",e,t,a),r=k("indices",e,t,a),s=k("elementShape",e,t,a),i=k("elementDType",e,t,a);return[a.getTensorList(n.id).gather(r,i,s)]}case"TensorListStack":{let n=k("tensorListId",e,t,a),r=k("elementShape",e,t,a),s=k("elementDType",e,t,a),i=k("numElements",e,t,a);return[a.getTensorList(n.id).stack(r,s,i)]}case"TensorListFromTensor":{let n=k("tensor",e,t,a),r=k("elementShape",e,t,a),s=k("elementDType",e,t,a),i=dO(n,r,s);return a.addTensorList(i),[i.idTensor]}case"TensorListConcat":case"TensorListConcatV2":{let n=k("tensorListId",e,t,a),r=a.getTensorList(n.id),s=k("dtype",e,t,a),i=k("elementShape",e,t,a);return[r.concat(s,i)]}case"TensorListPushBack":{let n=k("tensorListId",e,t,a),r=k("tensor",e,t,a),s=a.getTensorList(n.id);return s.pushBack(r),[s.idTensor]}case"TensorListPopBack":{let n=k("tensorListId",e,t,a),r=k("elementShape",e,t,a),s=k("elementDType",e,t,a);return[a.getTensorList(n.id).popBack(r,s)]}case"TensorListSplit":{let n=k("tensor",e,t,a),r=k("elementShape",e,t,a),s=k("lengths",e,t,a),i=hO(n,s,r);return a.addTensorList(i),[i.idTensor]}case"TensorListLength":{let n=k("tensorListId",e,t,a),r=a.getTensorList(n.id);return[Ge(r.size(),"int32")]}case"TensorListResize":{let n=k("tensorListId",e,t,a),r=k("size",e,t,a),s=a.getTensorList(n.id).resize(r);return a.addTensorList(s),[s.idTensor]}default:throw TypeError(`Node type ${e.op} is not implemented`)}};function m5(e,t,a){let[n,r]=k("fusedOps",e,t,a),s=n==="biasadd",i=!s,o=r==="prelu",l=n==="fusedbatchnorm",u=k("numArgs",e,t,a);if(s){if(o&&u!==2)throw new Error("FusedConv2d and DepthwiseConv2d with BiasAdd and Prelu must have two extra arguments: bias and alpha.");if(!o&&s&&u!==1)throw new Error("FusedConv2d and DepthwiseConv2d with BiasAdd must have one extra argument: bias.")}if(l)throw new Error("FusedConv2d and DepthwiseConv2d with FusedBatchNorm is not supported");let p=k("strides",e,t,a),c=ah(e,t,a),d=k("dataFormat",e,t,a).toUpperCase(),h=k("dilations",e,t,a),[m,f]=k("args",e,t,a);i&&(f=m,m=void 0);let g=k("leakyreluAlpha",e,t,a);return{stride:p,pad:c,dataFormat:d,dilations:h,biasArg:m,preluArg:f,activationFunc:r,leakyreluAlpha:g}}var fO=(e,t,a,n=ta)=>{switch(e.op){case"Conv1D":{let r=k("stride",e,t,a),s=k("pad",e,t,a),i=k("dataFormat",e,t,a).toUpperCase(),o=k("dilation",e,t,a);return[n.conv1d(k("x",e,t,a),k("filter",e,t,a),r,s,i,o)]}case"Conv2D":{let r=k("strides",e,t,a),s=ah(e,t,a),i=k("dataFormat",e,t,a).toUpperCase(),o=k("dilations",e,t,a);return[n.conv2d(k("x",e,t,a),k("filter",e,t,a),[r[1],r[2]],s,i,[o[1],o[2]])]}case"_FusedConv2D":{let{stride:r,pad:s,dataFormat:i,dilations:o,biasArg:l,preluArg:u,activationFunc:p,leakyreluAlpha:c}=m5(e,t,a);return[n.fused.conv2d({x:k("x",e,t,a),filter:k("filter",e,t,a),strides:[r[1],r[2]],pad:s,dataFormat:i,dilations:[o[1],o[2]],bias:l,activation:p,preluActivationWeights:u,leakyreluAlpha:c})]}case"FusedDepthwiseConv2dNative":{let{stride:r,pad:s,dataFormat:i,dilations:o,biasArg:l,preluArg:u,activationFunc:p,leakyreluAlpha:c}=m5(e,t,a);return[n.fused.depthwiseConv2d({x:k("x",e,t,a),filter:k("filter",e,t,a),strides:[r[1],r[2]],pad:s,dataFormat:i,dilations:[o[1],o[2]],bias:l,activation:p,preluActivationWeights:u,leakyreluAlpha:c})]}case"Conv2DBackpropInput":case"Conv2dTranspose":{let r=k("outputShape",e,t,a),s=k("strides",e,t,a),i=ah(e,t,a);return[n.conv2dTranspose(k("x",e,t,a),k("filter",e,t,a),r,[s[1],s[2]],i)]}case"DepthwiseConv2dNative":case"DepthwiseConv2d":{let r=k("strides",e,t,a),s=ah(e,t,a),i=k("dilations",e,t,a),o=k("dataFormat",e,t,a).toUpperCase();return[n.depthwiseConv2d(k("input",e,t,a),k("filter",e,t,a),[r[1],r[2]],s,o,[i[1],i[2]])]}case"Conv3D":{let r=k("strides",e,t,a),s=k("pad",e,t,a),i=k("dataFormat",e,t,a).toUpperCase(),o=k("dilations",e,t,a);return[n.conv3d(k("x",e,t,a),k("filter",e,t,a),[r[1],r[2],r[3]],s,i,[o[1],o[2],o[3]])]}case"AvgPool":{let r=k("strides",e,t,a),s=k("pad",e,t,a),i=k("kernelSize",e,t,a);return[n.avgPool(k("x",e,t,a),[i[1],i[2]],[r[1],r[2]],s)]}case"MaxPool":{let r=k("strides",e,t,a),s=k("pad",e,t,a),i=k("kernelSize",e,t,a);return[n.maxPool(k("x",e,t,a),[i[1],i[2]],[r[1],r[2]],s)]}case"MaxPoolWithArgmax":{let r=k("strides",e,t,a),s=k("pad",e,t,a),i=k("kernelSize",e,t,a),o=k("includeBatchInIndex",e,t,a),{result:l,indexes:u}=n.maxPoolWithArgmax(k("x",e,t,a),[i[1],i[2]],[r[1],r[2]],s,o);return[l,u]}case"AvgPool3D":{let r=k("strides",e,t,a),s=k("pad",e,t,a),i=k("kernelSize",e,t,a);return[n.avgPool3d(k("x",e,t,a),[i[1],i[2],i[3]],[r[1],r[2],r[3]],s)]}case"MaxPool3D":{let r=k("strides",e,t,a),s=k("pad",e,t,a),i=k("kernelSize",e,t,a);return[n.maxPool3d(k("x",e,t,a),[i[1],i[2],i[3]],[r[1],r[2],r[3]],s)]}case"Dilation2D":{let r=k("strides",e,t,a),s=k("pad",e,t,a),i=k("dilations",e,t,a),o=r[1],l=r[2],u=i[1],p=i[2];return[n.dilation2d(k("x",e,t,a),k("filter",e,t,a),[o,l],s,[u,p],"NHWC")]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},gO=(e,t,a,n=ta)=>{switch(e.op){case"Fill":{let r=k("shape",e,t,a),s=k("dtype",e,t,a),i=k("value",e,t,a);return[n.fill(r,i,s)]}case"LinSpace":{let r=k("start",e,t,a),s=k("stop",e,t,a),i=k("num",e,t,a);return[n.linspace(r,s,i)]}case"Multinomial":{let r=k("logits",e,t,a),s=k("numSamples",e,t,a),i=k("seed",e,t,a);return[n.multinomial(r,s,i)]}case"OneHot":{let r=k("indices",e,t,a),s=k("depth",e,t,a),i=k("onValue",e,t,a),o=k("offValue",e,t,a),l=k("dtype",e,t,a);return[n.oneHot(r,s,i,o,l)]}case"Ones":return[n.ones(k("shape",e,t,a),k("dtype",e,t,a))];case"OnesLike":return[n.onesLike(k("x",e,t,a))];case"RandomStandardNormal":return[n.randomStandardNormal(k("shape",e,t,a),k("dtype",e,t,a),k("seed",e,t,a))];case"RandomUniform":return[n.randomUniform(k("shape",e,t,a),k("minval",e,t,a),k("maxval",e,t,a),k("dtype",e,t,a))];case"RandomUniformInt":return[n.randomUniformInt(k("shape",e,t,a),k("minval",e,t,a),k("maxval",e,t,a),k("seed",e,t,a))];case"Range":{let r=k("start",e,t,a),s=k("stop",e,t,a),i=k("step",e,t,a);return[n.range(r,s,i,k("dtype",e,t,a))]}case"TruncatedNormal":{let r=k("shape",e,t,a),s=k("mean",e,t,a),i=k("stdDev",e,t,a),o=k("seed",e,t,a);return[n.truncatedNormal(r,s,i,k("dtype",e,t,a),o)]}case"Zeros":return[n.zeros(k("shape",e,t,a),k("dtype",e,t,a))];case"ZerosLike":return[n.zerosLike(k("x",e,t,a))];default:throw TypeError(`Node type ${e.op} is not implemented`)}};function Z2(e,t,a){let n=k("boxes",e,t,a),r=k("scores",e,t,a),s=k("maxOutputSize",e,t,a),i=k("iouThreshold",e,t,a),o=k("scoreThreshold",e,t,a),l=k("softNmsSigma",e,t,a);return{boxes:n,scores:r,maxOutputSize:s,iouThreshold:i,scoreThreshold:o,softNmsSigma:l}}var yO=async(e,t,a,n,r=ta)=>{switch(e.op){case"NonMaxSuppressionV5":{let{boxes:s,scores:i,maxOutputSize:o,iouThreshold:l,scoreThreshold:u,softNmsSigma:p}=Z2(e,t,a),c=await r.image.nonMaxSuppressionWithScoreAsync(s,i,o,l,u,p);return[c.selectedIndices,c.selectedScores]}case"NonMaxSuppressionV4":{let{boxes:s,scores:i,maxOutputSize:o,iouThreshold:l,scoreThreshold:u}=Z2(e,t,a),p=k("padToMaxOutputSize",e,t,a),c=await r.image.nonMaxSuppressionPaddedAsync(s,i,o,l,u,p);return[c.selectedIndices,c.validOutputs]}case"NonMaxSuppressionV3":case"NonMaxSuppressionV2":{let{boxes:s,scores:i,maxOutputSize:o,iouThreshold:l,scoreThreshold:u}=Z2(e,t,a);return[await r.image.nonMaxSuppressionAsync(s,i,o,l,u)]}case"Where":{let s=r.cast(k("condition",e,t,a),"bool"),i=[await r.whereAsync(s)];return s.dispose(),i}case"ListDiff":return r.setdiff1dAsync(k("x",e,t,a),k("y",e,t,a));default:throw TypeError(`Node type ${e.op} is not implemented`)}},xO=(e,t,a,n=ta)=>{switch(e.op){case"LowerBound":{let r=k("sortedSequence",e,t,a),s=k("values",e,t,a);return[n.lowerBound(r,s)]}case"TopKV2":{let r=k("x",e,t,a),s=k("k",e,t,a),i=k("sorted",e,t,a),o=n.topk(r,s,i);return[o.values,o.indices]}case"UpperBound":{let r=k("sortedSequence",e,t,a),s=k("values",e,t,a);return[n.upperBound(r,s)]}case"Unique":{let r=k("x",e,t,a),s=n.unique(r);return[s.values,s.indices]}case"UniqueV2":{let r=k("x",e,t,a),s=k("axis",e,t,a),i=n.unique(r,s);return[i.values,i.indices]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},AO=(e,t,a,n=ta)=>{switch(e.op){case"Const":return t[e.name];case"PlaceholderWithDefault":let r=k("default",e,t,a);return[da(e.name,t,a)||r];case"Placeholder":return[da(e.name,t,a)];case"Identity":case"StopGradient":case"FakeQuantWithMinMaxVars":{let p=k("x",e,t,a);return[wr(p)]}case"IdentityN":return k("x",e,t,a).map(p=>wr(p));case"Snapshot":let s=k("x",e,t,a);return[wr(s)];case"Shape":return[n.tensor1d(k("x",e,t,a).shape,"int32")];case"ShapeN":return k("x",e,t,a).map(p=>n.tensor1d(p.shape));case"Size":return[n.scalar(k("x",e,t,a).size,"int32")];case"Rank":return[n.scalar(k("x",e,t,a).rank,"int32")];case"NoOp":return[n.scalar(1)];case"Print":let i=k("x",e,t,a),o=k("data",e,t,a),l=k("message",e,t,a),u=k("summarize",e,t,a);console.warn("The graph has a tf.print() operation,usually used for debugging, which slows down performance."),console.log(l);for(let p=0;p<o.length;p++)console.log(Array.prototype.slice.call(o[p].dataSync()).slice(0,u));return[i];default:throw TypeError(`Node type ${e.op} is not implemented`)}},bO=class{get id(){return this.handle.id}constructor(e,t){this.keyDType=e,this.valueDType=t,this.handle=Ge(0),this.tensorMap=new Map,Ln(this.handle)}clearAndClose(){this.tensorMap.forEach(e=>e.dispose()),this.tensorMap.clear(),this.handle.dispose()}size(){return this.tensorMap.size}tensorSize(){return Ge(this.size(),"int32")}async import(e,t){this.checkKeyAndValueTensor(e,t);let a=await e.data();return this.tensorMap.forEach(n=>n.dispose()),this.tensorMap.clear(),De(()=>{let n=Na(t),r=a.length,s=n.length;v.assert(r===s,()=>`The number of elements doesn't match, keys has ${r} elements, the values has ${s} elements.`);for(let i=0;i<r;i++){let o=a[i],l=n[i];Ln(l),this.tensorMap.set(o,l)}return this.handle})}async find(e,t){this.checkKeyAndValueTensor(e,t);let a=await e.data();return De(()=>{let n=[];for(let r=0;r<a.length;r++){let s=a[r],i=this.findWithDefault(s,t);n.push(i)}return ha(n)})}findWithDefault(e,t){let a=this.tensorMap.get(e);return a!=null?a:t}checkKeyAndValueTensor(e,t){if(e.dtype!==this.keyDType)throw new Error(`Expect key dtype ${this.keyDType}, but got ${e.dtype}`);if(t.dtype!==this.valueDType)throw new Error(`Expect value dtype ${this.valueDType}, but got ${t.dtype}`)}},vO=async(e,t,a,n)=>{switch(e.op){case"HashTable":case"HashTableV2":{let r=n.getHashTableHandleByName(e.name);if(r!=null)return[r];{let s=k("keyDType",e,t,a),i=k("valueDType",e,t,a),o=new bO(s,i);return n.addHashTable(e.name,o),[o.handle]}}case"InitializeTable":case"InitializeTableV2":case"LookupTableImport":case"LookupTableImportV2":{let r=k("tableHandle",e,t,a,n),s=k("keys",e,t,a),i=k("values",e,t,a);return[await n.getHashTableById(r.id).import(s,i)]}case"LookupTableFind":case"LookupTableFindV2":{let r=k("tableHandle",e,t,a,n),s=k("keys",e,t,a),i=k("defaultValue",e,t,a);return[await n.getHashTableById(r.id).find(s,i)]}case"LookupTableSize":case"LookupTableSizeV2":{let r=k("tableHandle",e,t,a,n);return[n.getHashTableById(r.id).tensorSize()]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},wO=(e,t,a,n=ta)=>{switch(e.op){case"ResizeBilinear":{let r=k("images",e,t,a),s=k("size",e,t,a),i=k("alignCorners",e,t,a),o=k("halfPixelCenters",e,t,a);return[n.image.resizeBilinear(r,[s[0],s[1]],i,o)]}case"ResizeNearestNeighbor":{let r=k("images",e,t,a),s=k("size",e,t,a),i=k("alignCorners",e,t,a),o=k("halfPixelCenters",e,t,a);return[n.image.resizeNearestNeighbor(r,[s[0],s[1]],i,o)]}case"CropAndResize":{let r=k("image",e,t,a),s=k("boxes",e,t,a),i=k("boxInd",e,t,a),o=k("cropSize",e,t,a),l=k("method",e,t,a),u=k("extrapolationValue",e,t,a);return[n.image.cropAndResize(r,s,i,o,l,u)]}case"ImageProjectiveTransformV3":{let r=k("images",e,t,a),s=k("transforms",e,t,a),i=k("outputShape",e,t,a),o=k("fillValue",e,t,a),l=k("interpolation",e,t,a),u=k("fillMode",e,t,a);return[n.image.transform(r,s,l.toLowerCase(),u.toLowerCase(),o,i)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},kO=(e,t,a,n=ta)=>{switch(e.op){case"Equal":return[n.equal(k("a",e,t,a),k("b",e,t,a))];case"NotEqual":return[n.notEqual(k("a",e,t,a),k("b",e,t,a))];case"Greater":return[n.greater(k("a",e,t,a),k("b",e,t,a))];case"GreaterEqual":return[n.greaterEqual(k("a",e,t,a),k("b",e,t,a))];case"Less":return[n.less(k("a",e,t,a),k("b",e,t,a))];case"LessEqual":return[n.lessEqual(k("a",e,t,a),k("b",e,t,a))];case"LogicalAnd":return[n.logicalAnd(k("a",e,t,a),k("b",e,t,a))];case"LogicalNot":return[n.logicalNot(k("a",e,t,a))];case"LogicalOr":return[n.logicalOr(k("a",e,t,a),k("b",e,t,a))];case"Select":case"SelectV2":return[n.where(k("condition",e,t,a),k("a",e,t,a),k("b",e,t,a))];case"BitwiseAnd":return[n.bitwiseAnd(k("a",e,t,a),k("b",e,t,a))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},IO=(e,t,a,n=ta)=>{switch(e.op){case"BatchMatMul":case"BatchMatMulV2":case"MatMul":return[n.matMul(k("a",e,t,a),k("b",e,t,a),k("transposeA",e,t,a),k("transposeB",e,t,a))];case"Einsum":return[n.einsum(k("equation",e,t,a),...k("tensors",e,t,a))];case"Transpose":return[n.transpose(k("x",e,t,a),k("perm",e,t,a))];case"_FusedMatMul":let[r,s]=k("fusedOps",e,t,a),i=r==="biasadd",o=s==="prelu",l=k("numArgs",e,t,a),u=k("leakyreluAlpha",e,t,a);if(i){if(o&&l!==2)throw new Error("Fused MatMul with BiasAdd and Prelu must have two extra arguments: bias and alpha.");if(!o&&l!==1)throw new Error("Fused MatMul with BiasAdd must have one extra argument: bias.")}let[p,c]=k("args",e,t,a);return[n.fused.matMul({a:k("a",e,t,a),b:k("b",e,t,a),transposeA:k("transposeA",e,t,a),transposeB:k("transposeB",e,t,a),bias:p,activation:s,preluActivationWeights:c,leakyreluAlpha:u})];case"MatrixBandPart":return[n.linalg.bandPart(k("a",e,t,a),k("numLower",e,t,a),k("numUpper",e,t,a))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},SO=(e,t,a,n=ta)=>{switch(e.op){case"EuclideanNorm":return[n.euclideanNorm(k("x",e,t,a),k("axis",e,t,a),k("keepDims",e,t,a))];case"FusedBatchNorm":case"FusedBatchNormV2":return[n.batchNorm(k("x",e,t,a),k("mean",e,t,a),k("variance",e,t,a),k("offset",e,t,a),k("scale",e,t,a),k("epsilon",e,t,a))];case"FusedBatchNormV3":return[n.batchNorm(k("x",e,t,a),k("mean",e,t,a),k("variance",e,t,a),k("offset",e,t,a),k("scale",e,t,a),k("epsilon",e,t,a))];case"LRN":return[n.localResponseNormalization(k("x",e,t,a),k("radius",e,t,a),k("bias",e,t,a),k("alpha",e,t,a),k("beta",e,t,a))];case"Softmax":return[n.softmax(k("x",e,t,a))];case"LogSoftmax":return[n.logSoftmax(k("x",e,t,a))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},CO=(e,t,a,n=ta)=>{switch(e.op){case"RaggedGather":{let{outputNestedSplits:r,outputDenseValues:s}=n.raggedGather(k("paramsNestedSplits",e,t,a),k("paramsDenseValues",e,t,a),k("indices",e,t,a),k("outputRaggedRank",e,t,a));return r.concat(s)}case"RaggedRange":{let{rtNestedSplits:r,rtDenseValues:s}=n.raggedRange(k("starts",e,t,a),k("limits",e,t,a),k("splits",e,t,a));return[r,s]}case"RaggedTensorToTensor":return[n.raggedTensorToTensor(k("shape",e,t,a),k("values",e,t,a),k("defaultValue",e,t,a),k("rowPartitionTensors",e,t,a),k("rowPartitionTypes",e,t,a))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},TO=(e,t,a,n=ta)=>{switch(e.op){case"Max":{let o=k("axis",e,t,a),l=k("keepDims",e,t,a);return[n.max(k("x",e,t,a),o,l)]}case"Mean":{let o=k("axis",e,t,a),l=k("keepDims",e,t,a);return[n.mean(k("x",e,t,a),o,l)]}case"Min":{let o=k("axis",e,t,a),l=k("keepDims",e,t,a);return[n.min(k("x",e,t,a),o,l)]}case"Sum":{let o=k("axis",e,t,a),l=k("keepDims",e,t,a);return[n.sum(k("x",e,t,a),o,l)]}case"All":{let o=k("axis",e,t,a),l=k("keepDims",e,t,a);return[n.all(k("x",e,t,a),o,l)]}case"Any":{let o=k("axis",e,t,a),l=k("keepDims",e,t,a);return[n.any(k("x",e,t,a),o,l)]}case"ArgMax":{let o=k("axis",e,t,a);return[n.argMax(k("x",e,t,a),o)]}case"ArgMin":{let o=k("axis",e,t,a);return[n.argMin(k("x",e,t,a),o)]}case"Prod":{let o=k("axis",e,t,a),l=k("keepDims",e,t,a);return[n.prod(k("x",e,t,a),o,l)]}case"Cumprod":{let o=k("axis",e,t,a),l=k("exclusive",e,t,a),u=k("reverse",e,t,a);return[n.cumprod(k("x",e,t,a),o,l,u)]}case"Cumsum":{let o=k("axis",e,t,a),l=k("exclusive",e,t,a),u=k("reverse",e,t,a);return[n.cumsum(k("x",e,t,a),o,l,u)]}case"Bincount":let r=k("x",e,t,a),s=k("weights",e,t,a),i=k("size",e,t,a);return[n.bincount(r,s,i)];case"DenseBincount":{let o=k("x",e,t,a),l=k("weights",e,t,a),u=k("size",e,t,a),p=k("binaryOutput",e,t,a);return[n.denseBincount(o,l,u,p)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},NO=(e,t,a,n=ta)=>{switch(e.op){case"ConcatV2":case"Concat":{let r=k("n",e,t,a),s=k("axis",e,t,a),i=k("tensors",e,t,a);return i=i.slice(0,r),[n.concat(i,s)]}case"Gather":{let r=k("x",e,t,a),s=k("indices",e,t,a);return[n.gather(r,n.cast(s,"int32"),0)]}case"GatherV2":{let r=k("axis",e,t,a),s=k("batchDims",e,t,a),i=k("x",e,t,a),o=k("indices",e,t,a);return[n.gather(i,n.cast(o,"int32"),r,s)]}case"Reverse":{let r=k("dims",e,t,a),s=[];for(let o=0;o<r.length;o++)r[o]&&s.push(o);let i=k("x",e,t,a);return[n.reverse(i,s)]}case"ReverseV2":{let r=k("axis",e,t,a),s=k("x",e,t,a);return[n.reverse(s,r)]}case"Slice":{let r=k("begin",e,t,a),s=k("size",e,t,a);return[n.slice(k("x",e,t,a),r,s)]}case"StridedSlice":{let r=k("begin",e,t,a),s=k("end",e,t,a),i=k("strides",e,t,a),o=k("beginMask",e,t,a),l=k("endMask",e,t,a),u=k("ellipsisMask",e,t,a),p=k("newAxisMask",e,t,a),c=k("shrinkAxisMask",e,t,a),d=k("x",e,t,a);return[n.stridedSlice(d,r,s,i,o,l,u,p,c)]}case"Pack":return De(()=>{let r=k("axis",e,t,a),s=k("tensors",e,t,a),i=s[0].shape,o=n.squeeze(s[0]).shape,l=s.map(u=>{let p=v.arraysEqual(u.shape,i);if(!p&&!v.arraysEqual(n.squeeze(u).shape,o))throw new Error("the input tensors shape does not match");return p?u:n.reshape(u,i)});return[n.stack(l,r)]});case"Unpack":{let r=k("axis",e,t,a),s=k("tensor",e,t,a);return n.unstack(s,r)}case"Tile":{let r=k("reps",e,t,a);return[n.tile(k("x",e,t,a),r)]}case"Split":case"SplitV":{let r=k("axis",e,t,a),s=k("numOrSizeSplits",e,t,a),i=k("x",e,t,a);return n.split(i,s,r)}case"ScatterNd":{let r=k("indices",e,t,a),s=k("values",e,t,a),i=k("shape",e,t,a);return[n.scatterND(r,s,i)]}case"GatherNd":{let r=k("x",e,t,a),s=k("indices",e,t,a);return[n.gatherND(r,s)]}case"SparseToDense":{let r=k("sparseIndices",e,t,a),s=k("outputShape",e,t,a),i=k("sparseValues",e,t,a),o=k("defaultValue",e,t,a);return[n.sparseToDense(r,i,s,i.dtype===o.dtype?o:n.cast(o,i.dtype))]}case"TensorScatterUpdate":{let r=k("indices",e,t,a),s=k("values",e,t,a),i=k("tensor",e,t,a);return[n.tensorScatterUpdate(i,r,s)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},RO=(e,t,a,n=ta)=>{switch(e.op){case"SparseFillEmptyRows":{let{outputIndices:r,outputValues:s,emptyRowIndicator:i,reverseIndexMap:o}=n.sparse.sparseFillEmptyRows(k("indices",e,t,a),k("values",e,t,a),k("denseShape",e,t,a),k("defaultValue",e,t,a));return[r,s,i,o]}case"SparseReshape":{let{outputIndices:r,outputShape:s}=n.sparse.sparseReshape(k("inputIndices",e,t,a),k("inputShape",e,t,a),k("newShape",e,t,a));return[r,s]}case"SparseSegmentMean":return[n.sparse.sparseSegmentMean(k("data",e,t,a),k("indices",e,t,a),k("segmentIds",e,t,a))];case"SparseSegmentSum":return[n.sparse.sparseSegmentSum(k("data",e,t,a),k("indices",e,t,a),k("segmentIds",e,t,a))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},EO=(e,t,a,n=ta)=>{switch(e.op){case"FFT":return[n.fft(k("x",e,t,a))];case"IFFT":return[n.ifft(k("x",e,t,a))];case"RFFT":return[n.rfft(k("x",e,t,a))];case"IRFFT":return[n.irfft(k("x",e,t,a))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},MO=(e,t,a,n=ta)=>{switch(e.op){case"StaticRegexReplace":return[n.string.staticRegexReplace(k("input",e,t,a),k("pattern",e,t,a),k("rewrite",e,t,a),k("replaceGlobal",e,t,a))];case"StringNGrams":{let{nGrams:r,nGramsSplits:s}=n.string.stringNGrams(k("data",e,t,a),k("dataSplits",e,t,a),k("separator",e,t,a),k("nGramWidths",e,t,a),k("leftPad",e,t,a),k("rightPad",e,t,a),k("padWidth",e,t,a),k("preserveShortSequences",e,t,a));return[r,s]}case"StringSplit":{let{indices:r,values:s,shape:i}=n.string.stringSplit(k("input",e,t,a),k("delimiter",e,t,a),k("skipEmpty",e,t,a));return[r,s,i]}case"StringToHashBucketFast":return[n.string.stringToHashBucketFast(k("input",e,t,a),k("numBuckets",e,t,a))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},$O=(e,t,a,n=ta)=>{switch(e.op){case"Cast":return[n.cast(k("x",e,t,a),k("dtype",e,t,a))];case"ExpandDims":{let r=k("axis",e,t,a);return[n.expandDims(k("x",e,t,a),r)]}case"Squeeze":{let r=k("axis",e,t,a);return[n.squeeze(k("x",e,t,a),r)]}case"Reshape":return[n.reshape(k("x",e,t,a),k("shape",e,t,a))];case"EnsureShape":return[n.ensureShape(k("x",e,t,a),k("shape",e,t,a))];case"MirrorPad":return[n.mirrorPad(k("x",e,t,a),k("padding",e,t,a),k("mode",e,t,a))];case"PadV2":case"Pad":return[n.pad(k("x",e,t,a),k("padding",e,t,a),k("constantValue",e,t,a))];case"SpaceToBatchND":{let r=k("blockShape",e,t,a),s=k("paddings",e,t,a);return[n.spaceToBatchND(k("x",e,t,a),r,s)]}case"BatchToSpaceND":{let r=k("blockShape",e,t,a),s=k("crops",e,t,a);return[n.batchToSpaceND(k("x",e,t,a),r,s)]}case"DepthToSpace":{let r=k("blockSize",e,t,a),s=k("dataFormat",e,t,a).toUpperCase();return[n.depthToSpace(k("x",e,t,a),r,s)]}case"BroadcastTo":return[n.broadcastTo(k("x",e,t,a),k("shape",e,t,a))];case"BroadcastArgs":return[n.broadcastArgs(k("s0",e,t,a),k("s1",e,t,a))];default:throw TypeError(`Node type ${e.op} is not implemented`)}};function f5(e,t,a,n,r=De){let s=((i,o,l)=>{switch(i.category){case"arithmetic":return r(()=>oO(i,o,l));case"basic_math":return r(()=>lO(i,o,l));case"control":return mO(i,o,l);case"convolution":return r(()=>fO(i,o,l));case"creation":return r(()=>gO(i,o,l));case"dynamic":return yO(i,o,l);case"evaluation":return r(()=>xO(i,o,l));case"image":return r(()=>wO(i,o,l));case"graph":return r(()=>AO(i,o,l));case"logical":return r(()=>kO(i,o,l));case"matrices":return r(()=>IO(i,o,l));case"normalization":return r(()=>SO(i,o,l));case"ragged":return r(()=>CO(i,o,l));case"reduction":return r(()=>TO(i,o,l));case"slice_join":return r(()=>NO(i,o,l));case"sparse":return r(()=>RO(i,o,l));case"spectral":return r(()=>EO(i,o,l));case"string":return r(()=>MO(i,o,l));case"transformation":return r(()=>$O(i,o,l));case"hash_table":return vO(i,o,l,n);case"custom":let u=j7(i.op);if(u&&u.customExecutor)return u.customExecutor(new iO(i,o,l));throw TypeError(`Custom op ${i.op} is not registered.`);default:throw TypeError(`Unknown op '${i.op}'. File an issue at https://github.com/tensorflow/tfjs/issues so we can add it, or register a custom execution with tf.registerOp()`)}})(e,t,a);return v.isPromise(s)?s.then(i=>[].concat(i)):[].concat(s)}var g5=class{constructor(e={},t={},a={},n={},r){this.weightMap=e,this.tensorArrayMap=t,this.tensorListMap=a,this.functionMap=n,this.parseNodeNameCache=r,this.rootContext={id:0,frameName:"",iterationId:0},this.contexts=[this.rootContext],this.lastId=0,this.generateCurrentContextIds()}newFrame(e,t){return{id:e,frameName:t,iterationId:0}}set currentContext(e){this.contexts!==e&&(this.contexts=e,this.generateCurrentContextIds())}get currentContext(){return this.contexts}get currentContextId(){return this._currentContextIds[0]}get currentContextIds(){return this._currentContextIds}generateCurrentContextIds(){let e=[];for(let t=0;t<this.contexts.length-1;t++){let a=this.contexts.slice(0,this.contexts.length-t);e.push(this.contextIdforContexts(a))}e.push(""),this._currentContextIds=e}contextIdforContexts(e){return e?e.map(t=>t.id===0&&t.iterationId===0?"":`${t.frameName}-${t.iterationId}`).join("/"):""}enterFrame(e){this.contexts&&(this.lastId++,this.contexts=this.contexts.slice(),this.contexts.push(this.newFrame(this.lastId,e)),this._currentContextIds.unshift(this.contextIdforContexts(this.contexts)))}exitFrame(){if(this.contexts&&this.contexts.length>1)this.contexts=this.contexts.slice(),this.contexts.splice(-1),this.currentContextIds.shift();else throw new Error("Cannot exit frame, the context is empty")}nextIteration(){if(this.contexts&&this.contexts.length>0){this.contexts=this.contexts.slice(),this.lastId++;let e=Object.assign({},this.contexts[this.contexts.length-1]);e.iterationId+=1,e.id=this.lastId,this.contexts.splice(-1,1,e),this._currentContextIds.splice(0,1,this.contextIdforContexts(this.contexts))}else throw new Error("Cannot increase frame iteration, the context is empty")}getWeight(e){return this.weightMap[e]}addTensorArray(e){this.tensorArrayMap[e.id]=e}getTensorArray(e){return this.tensorArrayMap[e]}addTensorList(e){this.tensorListMap[e.id]=e}getTensorList(e){return this.tensorListMap[e]}dispose(e){for(let t in this.tensorArrayMap)this.tensorArrayMap[t].clearAndClose(e);for(let t in this.tensorListMap)this.tensorListMap[t].clearAndClose(e)}};function y5(e,t,a,n){let r=new Set,s=[],i=null,o=null,l=new Set,u=new Set(Object.keys(e).map(d=>Ya(d)[0]));n=n||[];let p=new Set(n.map(d=>Ya(d.name)[0])),c=[...t];for(;c.length>0;){let d=c.pop();if((Us(d)||WO(d)||BO(d))&&i==null&&(i=d,o=i.children.map(h=>h.name).filter(h=>r.has(h))),r.add(d.name),a[d.name]==null&&!u.has(d.name)&&!p.has(d.name)){if(d.inputs.length===0){s.push(d.name);continue}d.inputs.forEach(h=>{l.has(h.name)||(l.add(h.name),c.push(h))})}}return{inputs:e,outputs:t,usedNodes:r,missingInputs:s,dynamicNode:i,syncInputs:o}}function PO(e,t){let{usedNodes:a,inputs:n}=t,r=Object.keys(n).map(g=>Ya(g)[0]).map(g=>e.nodes[g]),s=e.initNodes||[],i=g=>a.has(typeof g=="string"?g:g.name);function o(g){return[...new Map(g.map(y=>[y.name,y])).values()]}let l=o([...r,...e.weights,...s]).filter(i),u=o([...l,...Object.values(e.nodes)]).filter(i),p=new Map(u.map(g=>[g.name,g])),c={};for(let g of u){c[g.name]=c[g.name]||0;for(let y of g.children)i(y)||(c[y.name]=Number.POSITIVE_INFINITY),c[y.name]=(c[y.name]||0)+1}let d=Object.entries(c).filter(([,g])=>g===0).map(([g])=>g),h=[...d];for(;d.length>0;){let g=d.pop(),y=p.get(g);for(let x of y.children.filter(i))--c[x.name]===0&&(h.push(x.name),d.push(x.name))}let m=h.map(g=>p.get(g)),f=_O(m,l);return FO(f,l),f}function _O(e,t){let a=new Map(e.map(s=>[s.name,s])),n=t.map(s=>s.name),r=new Set(n);for(;n.length>0;){let s=n.pop(),i=a.get(s);for(let o of i.children)!a.has(o.name)||r.has(o.name)||(r.add(o.name),n.push(o.name))}return e.filter(s=>r.has(s.name))}var Kc=class extends Error{constructor(e){super(`NodesExecutionOrderError: ${e}`)}};function FO(e,t){let a=new Map(e.map((o,l)=>[o.name,l])),n=new Set(t.map(o=>o.name)),r=o=>n.has(typeof o=="string"?o:o.name),s=new Set(e.map(o=>o.name)),i=o=>s.has(typeof o=="string"?o:o.name);for(let o of e){for(let l of o.children.filter(i)){if(!a.has(l.name))throw new Kc(`Child ${l.name} of node ${o.name} is unreachable.`);if(a.get(o.name)>a.get(l.name))throw new Kc(`Node ${o.name} is scheduled to run after its child ${l.name}.`)}if(!r(o))for(let l of o.inputs){if(!a.has(l.name))throw new Kc(`Input ${l.name} of node ${o.name} is unreachable.`);if(a.get(l.name)>a.get(o.name))throw new Kc(`Node ${o.name} is scheduled to run before its input ${l.name}.`)}}}function DO(e){let t=new Map(e.map((o,l)=>[o.name,l])),a=Number.MAX_SAFE_INTEGER,n=e.map((o,l)=>Us(o)?a:l),r=o=>{let l=n[t.get(o.name)];return l==null?-1:l},s=e.map((o,l)=>o.children.map(r).reduce((u,p)=>Math.max(u,p),n[l])),i=new Map;for(let o=0;o<e.length;++o){let l=s[o];if(l===a)continue;let u=e[o],p=e[l];i.has(p.name)||i.set(p.name,[]),i.get(p.name).push(u)}return i}var OO=new Set(["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"]),zO=new Set(["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"]),LO=new Set(["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2","LookupTableSize","LookupTableSizeV2"]);function Us(e){return OO.has(e.op)}function WO(e){return zO.has(e.op)}function BO(e){return LO.has(e.op)}var x5=class m6{get weightIds(){return this.parent?this.parent.weightIds:this._weightIds}get functionExecutorMap(){return this.parent?this.parent.functionExecutorMap:this._functionExecutorMap}get weightMap(){return this.parent?this.parent.weightMap:this._weightMap}set weightMap(t){let a=Object.keys(t).map(n=>t[n].map(r=>r.id));this._weightIds=[].concat(...a),this._weightMap=t}set resourceManager(t){this._resourceManager=t}get inputs(){return this._inputs.map(t=>({name:t.name,shape:t.attrParams.shape?t.attrParams.shape.value:void 0,dtype:t.attrParams.dtype?t.attrParams.dtype.value:void 0}))}get outputs(){return this._outputs.map(t=>({name:t.name,shape:t.attrParams.shape?t.attrParams.shape.value:void 0,dtype:t.attrParams.dtype?t.attrParams.dtype.value:void 0}))}get inputNodes(){return this._inputs.map(t=>t.signatureKey||t.name)}get outputNodes(){return this._outputs.map(t=>{let a=t.signatureKey||t.name;return t.defaultOutput?`${a}:${t.defaultOutput}`:a})}get functions(){return Object.keys(this._functions).reduce((t,a)=>(t[a]=this._functions[a].signature,t),{})}constructor(t,a){this.graph=t,this.parent=a,this.compiledMap=new Map,this.parseNodeNameCache=new Map,this._weightMap={},this.SEPARATOR=",",this._functions={},this._functionExecutorMap={},this.keepIntermediateTensors=!1,this._outputs=t.outputs,this._inputs=t.inputs,this._initNodes=t.initNodes,this._signature=t.signature,this._functions=t.functions,t.functions!=null&&Object.keys(t.functions).forEach(n=>{this._functionExecutorMap[n]=new m6(t.functions[n],this)})}getCompilationKey(t,a){let n=t.map(s=>s.name).sort(),r=a.map(s=>s.name).sort();return n.join(this.SEPARATOR)+"--"+r.join(this.SEPARATOR)}compile(t,a){let n=y5(t,a,this.weightMap,this._initNodes),{missingInputs:r,dynamicNode:s,syncInputs:i}=n;if(s!=null)throw new Error(`This execution contains the node '${s.name}', which has the dynamic op '${s.op}'. Please use model.executeAsync() instead. Alternatively, to avoid the dynamic ops, specify the inputs [${i}]`);if(r.length>0){let u=a.map(c=>c.name),p=Object.keys(t);throw new Error(`Cannot compute the outputs [${u}] from the provided inputs [${p}]. Missing the following inputs: [${r}]`)}let o=PO(this.graph,n),l=DO(o);return{orderedNodes:o,nodeLiveUntilMap:l}}cloneAndKeepTensor(t){if(t==null)return null;let a=t.clone();return Ln(a),a}cloneTensorList(t){return t?t.map(a=>this.cloneAndKeepTensor(a)):null}cloneTensorMap(t){return Object.fromEntries(Object.entries(t).map(([a,n])=>[a,this.cloneTensorList(n)]))}execute(t,a){this.disposeIntermediateTensors(),t=this.mapInputs(t);let n=Object.keys(t).sort();this.checkInputs(t),this.checkInputShapeAndType(t),a=this.mapOutputs(a),this.checkOutputs(a);let r=n.map(d=>this.graph.nodes[Ya(d)[0]]),s=a.map(d=>Ya(d)[0]),i=new Set(s),o=s.map(d=>this.graph.nodes[d]);o.length===0&&(o=this._outputs);let l=this.getCompilationKey(r,o),u=this.compiledMap.get(l);u==null&&(u=this.compile(t,o),this.compiledMap.set(l,u));try{this.keepIntermediateTensors=B().getBool("KEEP_INTERMEDIATE_TENSORS")}catch(d){this.keepIntermediateTensors=!1,console.warn(d.message)}let p={},c={};return De(()=>{let d=new g5(this.weightMap,p,c,this.functionExecutorMap,this.parseNodeNameCache),h=Object.assign({},this.weightMap);this.keepIntermediateTensors&&(this.clonedTensorsMap=this.cloneTensorMap(this.weightMap)),Object.keys(t).forEach(y=>{let[x,A]=Ya(y,d),b=[];b[A]=t[y],h[x]=b,this.keepIntermediateTensors&&(this.clonedTensorsMap[x]=this.cloneTensorList(b))});let m=this.getFrozenTensorIds(h),{orderedNodes:f,nodeLiveUntilMap:g}=u;for(let y of f){if(h[y.name])continue;let x=f5(y,h,d,this._resourceManager);if(v.isPromise(x))throw new Error(`The execution of the op '${y.op}' returned a promise. Please use model.executeAsync() instead.`);h[y.name]=x,this.keepIntermediateTensors&&(this.clonedTensorsMap[y.name]=this.cloneTensorList(x)),this.checkTensorForDisposalWithNodeLiveUntilInfo(y,h,d,m,i,g.get(y.name))}return this.parent==null&&d.dispose(m),a.map(y=>da(y,h,d))})}getFrozenTensorIds(t){let a=[].concat.apply([],Object.keys(t).map(n=>t[n]).map(n=>n.map(r=>r.id)));return new Set(a)}checkTensorForDisposal(t,a,n,r,s,i,o){if(!(Us(a)||i.has(t))){for(let l of n[t])l!=null&&(o[l.id]=(o[l.id]||0)+a.children.length);for(let l of a.inputs){if(Us(l))continue;let u=d5(l.name,n,r);if(u!=null)for(let p of u){if(!p||p.kept||s.has(p.id))continue;let c=o[p.id];c===1?(p.dispose(),delete o[p.id]):c!=null&&o[p.id]--}}}}checkTensorForDisposalWithNodeLiveUntilInfo(t,a,n,r,s,i){function o(l){return Us(l)||s.has(l.name)}if(!(Us(t)||i==null))for(let l of i){if(o(l))continue;let u=d5(l.name,a,n);for(let p of u)!p||p.kept||r.has(p.id)||p.dispose()}}async executeAsync(t,a){return this._executeAsync(t,a)}disposeIntermediateTensors(){this.clonedTensorsMap&&(Object.values(this.clonedTensorsMap).forEach(t=>{for(let a of t)a&&!a.isDisposed&&a.dispose()}),this.clonedTensorsMap=null)}getIntermediateTensors(){return this.clonedTensorsMap}async _executeAsync(t,a,n=!1,r={},s={}){this.disposeIntermediateTensors(),n||(t=this.mapInputs(t),this.checkInputs(t),this.checkInputShapeAndType(t),a=this.mapOutputs(a),this.checkOutputs(a));try{this.keepIntermediateTensors=B().getBool("KEEP_INTERMEDIATE_TENSORS")}catch(d){this.keepIntermediateTensors=!1,console.warn(d.message)}let i=new g5(this.weightMap,r,s,this.functionExecutorMap,this.parseNodeNameCache);this.keepIntermediateTensors&&(this.clonedTensorsMap=this.cloneTensorMap(this.weightMap));let o=await this.executeWithControlFlow(t,i,a,n),l=a.map(d=>da(d,o,i)),u=l.map(d=>d.id),p=Object.keys(t).map(d=>t[d].id),c=new Set([...u,...p,...this.weightIds]);return Object.values(o).forEach(d=>{d.forEach(h=>{h&&!h.isDisposed&&!c.has(h.id)&&h.dispose()})}),this.parent==null&&i.dispose(c),l}async executeFunctionAsync(t,a,n){let r=t.reduce((s,i,o)=>(s[this.inputs[o].name]=i,s),{});return this._executeAsync(r,this.outputNodes,!0,a,n)}async executeWithControlFlow(t,a,n,r){let s=Object.keys(t),i=s.map(b=>this.graph.nodes[Ya(b)[0]]),o=n.map(b=>Ya(b)[0]),l=new Set(o),u=o.map(b=>this.graph.nodes[b]);u.length===0&&(u=this._outputs);let{usedNodes:p,missingInputs:c,dynamicNode:d,syncInputs:h}=y5(t,u,this.weightMap,this._initNodes),m=[...i,...this.graph.weights,...this._initNodes||[]].map(b=>({node:b,contexts:a.currentContext})),f=Object.assign({},this.weightMap);Object.keys(t).forEach(b=>{let[w,I]=Ya(b),T=[];T[I]=t[b],f[w]=T});let g={},y=this.getFrozenTensorIds(f),x={};for(;m.length>0;){let b=this.processStack(i,m,a,f,x,y,l,g,p);await Promise.all(b)}d==null&&!r&&console.warn("This model execution did not contain any nodes with control flow or dynamic output shapes. You can use model.execute() instead.");let A=u.filter(b=>!Us(b)&&!da(b.name,f,a)).map(b=>b.name);if(A.length>0){let b="";throw d!=null&&(b=`Alternatively, to avoid the dynamic ops, use model.execute() and specify the inputs [${h}]`),new Error(`Cannot compute the outputs [${A}] from the provided inputs [${s}]. Consider providing the following inputs: [${c}]. ${b}`)}return f}processStack(t,a,n,r,s,i,o,l,u){let p=[];for(;a.length>0;){let c=a.pop();n.currentContext=c.contexts;let d="";if(c.node.op==="Enter"&&k("isConstant",c.node,r,n)&&([d]=vr(c.node.name,n)),r[c.node.name]==null){let h=f5(c.node,r,n,this._resourceManager);d||([d]=vr(c.node.name,n));let m=n.currentContext;v.isPromise(h)?p.push(h.then(f=>(r[d]=f,this.keepIntermediateTensors&&(this.clonedTensorsMap[d]=this.cloneTensorList(f)),n.currentContext=m,this.checkTensorForDisposal(d,c.node,r,n,i,o,l),this.processChildNodes(c.node,a,n,r,s,u),f))):(r[d]=h,this.keepIntermediateTensors&&(this.clonedTensorsMap[d]=this.cloneTensorList(h)),this.checkTensorForDisposal(d,c.node,r,n,i,o,l),this.processChildNodes(c.node,a,n,r,s,u))}else this.processChildNodes(c.node,a,n,r,s,u)}return p}processChildNodes(t,a,n,r,s,i){t.children.forEach(o=>{let[l]=vr(o.name,n);s[l]||!i.has(o.name)||(o.op==="Merge"?o.inputNames.some(u=>!!da(u,r,n))&&(s[l]=!0,a.push({contexts:n.currentContext,node:o})):o.inputNames.every(u=>!!da(u,r,n))&&(s[l]=!0,a.push({contexts:n.currentContext,node:o})))})}dispose(){Object.keys(this.weightMap).forEach(t=>this.weightMap[t].forEach(a=>a.dispose()))}checkInputShapeAndType(t){Object.keys(t).forEach(a=>{let n=t[a],[r]=Ya(a),s=this.graph.nodes[r];if(s.attrParams.shape&&s.attrParams.shape.value){let i=s.attrParams.shape.value,o=i.length===n.shape.length&&n.shape.every((l,u)=>i[u]===-1||i[u]===l);v.assert(o,()=>`The shape of dict['${s.name}'] provided in model.execute(dict) must be [${i}], but was [${n.shape}]`)}s.attrParams.dtype&&s.attrParams.dtype.value&&v.assert(n.dtype===s.attrParams.dtype.value,()=>`The dtype of dict['${s.name}'] provided in model.execute(dict) must be ${s.attrParams.dtype.value}, but was ${n.dtype}`)})}mapInputs(t){var a,n;let r={};for(let s in t){let i=(n=(a=this._signature)===null||a===void 0?void 0:a.inputs)===null||n===void 0?void 0:n[s];i!=null?r[i.name]=t[s]:r[s]=t[s]}return r}checkInputs(t){let a=Object.keys(t).filter(n=>{let[r]=Ya(n);return this.graph.nodes[r]==null});if(a.length>0)throw new Error(`The dict provided in model.execute(dict) has keys: [${a}] that are not part of graph`)}mapOutputs(t){return t.map(a=>{var n,r;let s=(r=(n=this._signature)===null||n===void 0?void 0:n.outputs)===null||r===void 0?void 0:r[a];return s!=null?s.name:a},{})}checkOutputs(t){t.forEach(a=>{let[n]=Ya(a);if(!this.graph.nodes[n])throw new Error(`The output '${a}' is not found in the graph`)})}},VO=class{constructor(e={},t={}){this.hashTableNameToHandle=e,this.hashTableMap=t}addHashTable(e,t){this.hashTableNameToHandle[e]=t.handle,this.hashTableMap[t.id]=t}getHashTableHandleByName(e){return this.hashTableNameToHandle[e]}getHashTableById(e){return this.hashTableMap[e]}dispose(){for(let e in this.hashTableMap)this.hashTableMap[e].clearAndClose(),delete this.hashTableMap[e];for(let e in this.hashTableNameToHandle)this.hashTableNameToHandle[e].dispose(),delete this.hashTableNameToHandle[e]}},UO="?tfjs-format=file",GO="model.json",Xp=class{get modelVersion(){return this.version}get inputNodes(){return this.executor.inputNodes}get outputNodes(){return this.executor.outputNodes}get inputs(){return this.executor.inputs}get outputs(){return this.executor.outputs}get weights(){return this.executor.weightMap}get metadata(){return this.artifacts.userDefinedMetadata}get modelSignature(){return this.signature}get modelStructuredOutputKeys(){return this.structuredOutputKeys}constructor(e,t={},a=Zn){this.modelUrl=e,this.loadOptions=t,this.version="n/a",this.io=a,t==null&&(this.loadOptions={}),this.resourceManager=new VO}findIOHandler(){let e=this.modelUrl;if(e.load!=null)this.handler=e;else if(this.loadOptions.requestInit!=null)this.handler=this.io.browserHTTPRequest(e,this.loadOptions);else{let t=this.io.getLoadHandlers(e,this.loadOptions);if(t.length===0)t.push(this.io.browserHTTPRequest(e,this.loadOptions));else if(t.length>1)throw new Error(`Found more than one (${t.length}) load handlers for URL '${[e]}'`);this.handler=t[0]}}load(){if(this.findIOHandler(),this.handler.load==null)throw new Error("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");let e=this.handler.load();return v.isPromise(e)?e.then(t=>t.getWeightStream==null?this.loadSync(t):this.loadStreaming(t)):this.loadSync(e)}loadSync(e){let t=this.io.decodeWeights(e.weightData,e.weightSpecs);return this.loadWithWeightMap(e,t)}async loadStreaming(e){if(e.getWeightStream==null)throw new Error("Model artifacts missing streamWeights function");let t=await jA(e.getWeightStream(),e.weightSpecs);return this.loadWithWeightMap(e,t)}loadWithWeightMap(e,t){this.artifacts=e;let a=this.artifacts.modelTopology,n=this.artifacts.signature;if(this.artifacts.userDefinedMetadata!=null){let r=this.artifacts.userDefinedMetadata;r.signature!=null&&(n=r.signature),r.structuredOutputKeys!=null&&(this.structuredOutputKeys=r.structuredOutputKeys)}if(this.signature=n,this.version=`${a.versions.producer}.${a.versions.minConsumer}`,this.executor=new x5(p5.Instance.transformGraph(a,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(t),this.executor.resourceManager=this.resourceManager,e.modelInitializer!=null&&e.modelInitializer.node!=null){let r=p5.Instance.transformGraph(e.modelInitializer);this.initializer=new x5(r),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializerSignature=e.initializerSignature}return!0}async save(e,t){if(typeof e=="string"){let a=this.io.getSaveHandlers(e);if(a.length===0)throw new Error(`Cannot find any save handlers for URL '${e}'`);if(a.length>1)throw new Error(`Found more than one (${a.length}) save handlers for URL '${e}'`);e=a[0]}if(e.save==null)throw new Error("GraphModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");return e.save(this.artifacts)}addStructuredOutputNames(e){if(this.structuredOutputKeys){let t=e instanceof yt?[e]:e,a={};return t.forEach((n,r)=>a[this.structuredOutputKeys[r]]=n),a}return e}predict(e,t){let a=this.execute(e,this.outputNodes);return this.addStructuredOutputNames(a)}async predictAsync(e,t){let a=await this.executeAsync(e,this.outputNodes);return this.addStructuredOutputNames(a)}normalizeInputs(e){var t;if(!(e instanceof yt)&&!Array.isArray(e)){let r=(t=this.signature)===null||t===void 0?void 0:t.inputs;if(r!=null)for(let s in r){let i=r[s];i.resourceId!=null&&(e[s]=this.resourceIdToCapturedInput[i.resourceId])}return e}e=Array.isArray(e)?e:[e];let a=Object.keys(this.resourceIdToCapturedInput).length;if(e.length+a!==this.inputNodes.length)throw new Error(`Input tensor count mismatch, the graph model has ${this.inputNodes.length-a} non-resource placeholders, while there are ${e.length} input tensors provided.`);let n=0;return this.inputNodes.reduce((r,s)=>{var i,o,l;let u=(l=(o=(i=this.signature)===null||i===void 0?void 0:i.inputs)===null||o===void 0?void 0:o[s])===null||l===void 0?void 0:l.resourceId;return u!=null?r[s]=this.resourceIdToCapturedInput[u]:r[s]=e[n++],r},{})}normalizeOutputs(e){return e=e||this.outputNodes,Array.isArray(e)?e:[e]}executeInitializerGraph(){return this.initializer==null?[]:this.initializerSignature==null?this.initializer.execute({},[]):this.initializer.execute({},Object.keys(this.initializerSignature.outputs))}async executeInitializerGraphAsync(){return this.initializer==null?[]:this.initializerSignature==null?this.initializer.executeAsync({},[]):this.initializer.executeAsync({},Object.keys(this.initializerSignature.outputs))}setResourceIdToCapturedInput(e){if(this.resourceIdToCapturedInput={},this.initializerSignature){let t=this.initializerSignature.outputs,a=Object.keys(t);for(let n=0;n<a.length;n++){let r=a[n],s=t[r];this.resourceIdToCapturedInput[s.resourceId]=e[n]}}}execute(e,t){this.resourceIdToCapturedInput==null&&this.setResourceIdToCapturedInput(this.executeInitializerGraph()),e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let a=this.executor.execute(e,t);return a.length>1?a:a[0]}async executeAsync(e,t){this.resourceIdToCapturedInput==null&&this.setResourceIdToCapturedInput(await this.executeInitializerGraphAsync()),e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let a=await this.executor.executeAsync(e,t);return a.length>1?a:a[0]}getIntermediateTensors(){return this.executor.getIntermediateTensors()}disposeIntermediateTensors(){this.executor.disposeIntermediateTensors()}convertTensorMapToTensorsMap(e){return Object.keys(e).reduce((t,a)=>(t[a]=[e[a]],t),{})}dispose(){this.executor.dispose(),this.initializer&&(this.initializer.dispose(),this.resourceIdToCapturedInput&&J(this.resourceIdToCapturedInput)),this.resourceManager.dispose()}};async function d3(e,t={},a=Zn){if(e==null)throw new Error("modelUrl in loadGraphModel() cannot be null. Please provide a url or an IOHandler that loads the model");t==null&&(t={}),t.fromTFHub&&typeof e=="string"&&(e=jO(e));let n=new Xp(e,t,a);return await n.load(),n}function HO(e){if(e==null)throw new Error("modelUrl in loadGraphModelSync() cannot be null. Please provide model artifacts or an IOHandler that loads the model");let t;if(e instanceof Array){let[n,r]=e;if(!n)throw new Error("modelJSON must be the first element of the array");if(!r||!(r instanceof ArrayBuffer))throw new Error("An ArrayBuffer of weights must be the second element of the array");if(!("modelTopology"in n))throw new Error("Model JSON is missing 'modelTopology'");if(!("weightsManifest"in n))throw new Error("Model JSON is missing 'weightsManifest'");let s=Zn.getWeightSpecs(n.weightsManifest),i=Zn.getModelArtifactsForJSONSync(n,s,r);t=Zn.fromMemorySync(i)}else if("load"in e)t=e;else if("modelTopology"in e&&"weightSpecs"in e&&"weightData"in e)t=Zn.fromMemorySync(e);else throw new Error("Unknown model format");let a=new Xp(t);return a.load(),a}function jO(e){return e.endsWith("/")||(e=e+"/"),`${e}${GO}${UO}`}var qO="4.22.0";function Ie(e,t){Array.isArray(e)||(e=[e]),e.forEach(a=>{a!=null&&v.assert(a.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the CPU backend.`)})}var XO=En.whereImpl,p3=class f6 extends su{nextDataId(){return f6.nextDataId++}constructor(){super(),this.blockSize=48,this.firstUse=!0,this.data=new op(this,It())}write(t,a,n){this.firstUse&&(this.firstUse=!1,B().get("IS_NODE")&&C.warn(`
============================
Hi, looks like you are running TensorFlow.js in Node.js. To speed things up dramatically, install our node backend, visit https://github.com/tensorflow/tfjs-node for more details. 
============================`));let r={id:this.nextDataId()};return this.data.set(r,{values:t,dtype:n,refCount:1}),r}makeTensorInfo(t,a,n){let r;if(a==="string"&&n!=null&&n.length>0&&v.isString(n[0])){let s=n.map(i=>v.encodeString(i));r=this.write(s,t,a)}else r=this.write(n,t,a);return{dataId:r,shape:t,dtype:a}}refCount(t){return this.data.has(t)?this.data.get(t).refCount:0}incRef(t){let a=this.data.get(t);a.refCount++}decRef(t){if(this.data.has(t)){let a=this.data.get(t);a.refCount--}}move(t,a,n,r,s){this.data.set(t,{values:a,dtype:r,refCount:s})}numDataIds(){return this.data.numDataIds()}async read(t){return this.readSync(t)}readSync(t){let{dtype:a,complexTensorInfos:n}=this.data.get(t);if(a==="complex64"){let r=this.readSync(n.real.dataId),s=this.readSync(n.imag.dataId);return C.mergeRealAndImagArrays(r,s)}return v.convertBackendValuesAndArrayBuffer(this.data.get(t).values,a)}bufferSync(t){let a=this.readSync(t.dataId);if(t.dtype==="string")try{let n=a.map(r=>v.decodeString(r));return _e(t.shape,t.dtype,n)}catch(n){throw new Error("Failed to decode encoded string bytes into utf-8")}return _e(t.shape,t.dtype,a)}makeOutput(t,a,n){return It().makeTensorFromTensorInfo(this.makeTensorInfo(a,n,t),this)}disposeData(t,a=!1){if(this.data.has(t)){if(this.data.get(t).refCount--,!a&&this.data.get(t).refCount>0)return!1;let{complexTensorInfos:n}=this.data.get(t);n!=null&&(this.disposeData(n.real.dataId,!0),this.disposeData(n.imag.dataId,!0)),this.data.delete(t)}return!0}disposeIntermediateTensorInfo(t){this.disposeData(t.dataId)}async time(t){let a=v.now();return t(),{kernelMs:v.now()-a}}memory(){return{unreliable:!0,reasons:["The reported memory is an upper bound. Due to automatic garbage collection, the true allocated memory may be less."]}}where(t){Ie([t],"where");let a=this.readSync(t.dataId);return XO(t.shape,a)}dispose(){}floatPrecision(){return 32}epsilon(){return super.epsilon()}};p3.nextDataId=0;var t0={};Ze(t0,{addImpl:()=>x6,bincountImpl:()=>h3,bincountReduceImpl:()=>A6,bitwiseAndImpl:()=>b6,castImpl:()=>y6,ceilImpl:()=>v6,concatImpl:()=>m3,equalImpl:()=>w6,expImpl:()=>I6,expm1Impl:()=>C6,floorDivImpl:()=>N6,floorImpl:()=>T6,gatherNdImpl:()=>R6,gatherV2Impl:()=>E6,greaterEqualImpl:()=>$6,greaterImpl:()=>M6,lessEqualImpl:()=>_6,lessImpl:()=>P6,linSpaceImpl:()=>F6,logImpl:()=>D6,maxImpl:()=>O6,maximumImpl:()=>z6,minimumImpl:()=>L6,multiplyImpl:()=>f3,negImpl:()=>W6,notEqualImpl:()=>B6,prodImpl:()=>V6,raggedGatherImpl:()=>U6,raggedRangeImpl:()=>G6,raggedTensorToTensorImpl:()=>H6,rangeImpl:()=>y3,rsqrtImpl:()=>j6,scatterImpl:()=>qs,sigmoidImpl:()=>qz,simpleAbsImpl:()=>g6,sliceImpl:()=>Ah,sparseFillEmptyRowsImpl:()=>X6,sparseReshapeImpl:()=>K6,sparseSegmentReductionImpl:()=>x3,sqrtImpl:()=>Yz,squaredDifferenceImpl:()=>Y6,staticRegexReplaceImpl:()=>Z6,stridedSliceImpl:()=>J6,stringNGramsImpl:()=>A3,stringSplitImpl:()=>b3,stringToHashBucketFastImpl:()=>v3,subImpl:()=>Q6,tileImpl:()=>ev,topKImpl:()=>av,transposeImpl:()=>g3,uniqueImpl:()=>k3});function g6(e){let t=new Float32Array(e.length);for(let a=0;a<e.length;++a)t[a]=Math.abs(e[a]);return t}var KO=e=>{let{x:t}=e.inputs,a=e.backend;Ie(t,"abs");let n=new Float32Array(v.sizeFromShape(t.shape)),r=a.data.get(t.dataId).values;return n=g6(r),a.makeOutput(n,t.shape,t.dtype)},YO={kernelName:ou,backendName:"cpu",kernelFunc:KO};function _t(e){return(t,a,n,r,s)=>{let i=C.assertAndGetBroadcastShape(t,a),o=i.length,l=v.computeStrides(i),u=v.sizeFromShape(i),p=v.getTypedArrayFromDType(s,u),c=t.length,d=a.length,h=v.computeStrides(t),m=v.computeStrides(a),f=C.getBroadcastDims(t,i),g=C.getBroadcastDims(a,i);if(f.length+g.length===0)for(let y=0;y<p.length;++y)p[y]=e(n[y%n.length],r[y%r.length]);else for(let y=0;y<p.length;++y){let x=v.indexToLoc(y,o,l),A=x.slice(-c);f.forEach(T=>A[T]=0);let b=v.locToIndex(A,c,h),w=x.slice(-d);g.forEach(T=>w[T]=0);let I=v.locToIndex(w,d,m);p[y]=e(n[b],r[I])}return[p,i]}}function Ja(e){let{inputs:t,backend:a}=e,{real:n,imag:r}=t,s=a.data.get(n.dataId).values,i=a.data.get(r.dataId).values,o=a.makeTensorInfo(n.shape,"complex64"),l=a.data.get(o.dataId);return l.complexTensorInfos={real:a.makeTensorInfo(n.shape,"float32",s),imag:a.makeTensorInfo(r.shape,"float32",i)},o}var ZO={kernelName:cp,backendName:"cpu",kernelFunc:Ja};function xh(e,t,a="float32"){if(a==="complex64"){let r=xh(e,t,"float32"),s=xh(e,t,"float32");return Ja({inputs:{real:r,imag:s},backend:e})}let n=v.makeZerosTypedArray(v.sizeFromShape(t),a);return e.makeTensorInfo(t,a,n)}function rr(e){let{inputs:t,backend:a}=e,{x:n}=t;return a.incRef(n.dataId),{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}var JO={kernelName:qi,backendName:"cpu",kernelFunc:rr};function ei(e){let{inputs:t,backend:a}=e,{input:n}=t,r=a.data.get(n.dataId).complexTensorInfos.real,s=a.data.get(r.dataId).values;return a.makeTensorInfo(r.shape,r.dtype,s)}var QO={kernelName:Ip,backendName:"cpu",kernelFunc:ei};function y6(e,t,a,n){if(n==="int32"){let r=Int32Array.from(e);return[t,"int32",r]}if(n==="bool"){let r=v.toTypedArray([0],a),[s,i]=_t((o,l)=>o!==l?1:0)(t,[],e,r,"bool");return[i,"bool",s]}throw new Error(`Error in Cast: failed to cast ${a} to ${n}`)}function is(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{dtype:s}=n;if(s==="complex64"){if(r.dtype==="complex64")return rr({inputs:{x:r},backend:a});let p=xh(a,r.shape,r.dtype),c=is({inputs:{x:r},backend:a,attrs:{dtype:"float32"}}),d=Ja({inputs:{real:c,imag:p},backend:a});return a.disposeIntermediateTensorInfo(p),a.disposeIntermediateTensorInfo(c),d}if(r.dtype==="complex64"){let p=ei({inputs:{input:r},backend:a}),c=is({inputs:{x:p},backend:a,attrs:{dtype:s}});return a.disposeIntermediateTensorInfo(p),c}if(!v.hasEncodingLoss(r.dtype,s)){let p=rr({inputs:{x:r},backend:a});return{dataId:p.dataId,shape:p.shape,dtype:s}}let i=a.data.get(r.dataId).values,[o,l,u]=y6(i,r.shape,r.dtype,s);return a.makeTensorInfo(o,l,u)}var ez={kernelName:bi,backendName:"cpu",kernelFunc:is};function Kt(e,t,a,n){return a==null?({inputs:r,backend:s})=>{let{a:i,b:o}=r,l=s;Ie([i,o],e);let u=l.data.get(i.dataId).values,p=l.data.get(o.dataId).values,c=i.dtype==="string"?C.fromUint8ToStringArray(u):u,d=i.dtype==="string"?C.fromUint8ToStringArray(p):p,h=n||i.dtype,[m,f]=t(i.shape,o.shape,c,d,h);return l.makeTensorInfo(f,h,m)}:({inputs:r,backend:s})=>{let{a:i,b:o}=r,l=s;if(i.dtype==="complex64"||o.dtype==="complex64"){let u=is({inputs:{x:i},backend:l,attrs:{dtype:"complex64"}}),p=l.data.get(u.dataId),c=p.complexTensorInfos.real,d=p.complexTensorInfos.imag,h=l.data.get(c.dataId).values,m=l.data.get(d.dataId).values,f=is({inputs:{x:o},backend:l,attrs:{dtype:"complex64"}}),g=l.data.get(f.dataId),y=g.complexTensorInfos.real,x=g.complexTensorInfos.imag,A=l.data.get(y.dataId).values,b=l.data.get(x.dataId).values,[w,I,T]=a(i.shape,o.shape,h,m,A,b),N=l.makeTensorInfo(T,"float32",w),M=l.makeTensorInfo(T,"float32",I),$=Ja({inputs:{real:N,imag:M},backend:l});return l.disposeIntermediateTensorInfo(u),l.disposeIntermediateTensorInfo(f),l.disposeIntermediateTensorInfo(N),l.disposeIntermediateTensorInfo(M),$}else{let u=l.data.get(i.dataId).values,p=l.data.get(o.dataId).values,c=n||i.dtype,[d,h]=t(i.shape,o.shape,u,p,c);return l.makeTensorInfo(h,c,d)}}}function c3(e){return(t,a,n,r,s,i)=>{let o=C.assertAndGetBroadcastShape(t,a),l=v.sizeFromShape(o),u=o.length,p=v.computeStrides(o),c=v.getTypedArrayFromDType("float32",l),d=v.getTypedArrayFromDType("float32",l),h=C.getBroadcastDims(t,o),m=C.getBroadcastDims(a,o),f=C.mergeRealAndImagArrays(n,r),g=C.mergeRealAndImagArrays(s,i),y=t.length,x=v.computeStrides(t),A=a.length,b=v.computeStrides(a);if(h.length+m.length===0)for(let w=0;w<c.length;w++){let I=w%f.length,T=w%g.length,N=e(f[I*2],f[I*2+1],g[T*2],g[T*2+1]);c[w]=N.real,d[w]=N.imag}else for(let w=0;w<c.length;w++){let I=v.indexToLoc(w,u,p),T=I.slice(-y);h.forEach(S=>T[S]=0);let N=v.locToIndex(T,y,x),M=I.slice(-A);m.forEach(S=>M[S]=0);let $=v.locToIndex(M,A,b),E=e(f[N*2],f[N*2+1],g[$*2],g[$*2+1]);c[w]=E.real,d[w]=E.imag}return[c,d,o]}}var x6=_t((e,t)=>e+t),tz=c3((e,t,a,n)=>({real:e+a,imag:t+n})),eu=Kt(ls,x6,tz),az={kernelName:ls,backendName:"cpu",kernelFunc:eu};function h3(e,t,a,n,r){let s=v.sizeFromShape(n),i=v.makeZerosTypedArray(r,a);for(let o=0;o<e.length;o++){let l=e[o];if(l<0)throw new Error("Input x must be non-negative!");l>=r||(s>0?i[l]+=t[o]:i[l]+=1)}return i}function A6(e,t,a,n=!1){let r=e.shape[0],s=e.shape[1],i=_e([r,a],t.dtype);for(let o=0;o<r;o++)for(let l=0;l<s;l++){let u=e.get(o,l);if(u<0)throw new Error("Input x must be non-negative!");u>=a||(n?i.set(1,o,u):t.size>0?i.set(i.get(o,u)+t.get(o,l),o,u):i.set(i.get(o,u)+1,o,u))}return i}var b6=_t((e,t)=>e&t),nz=Kt(cu,b6),rz={kernelName:cu,backendName:"cpu",kernelFunc:nz};function lr(e){return(t,a,n)=>{let r=v.getArrayFromDType(a,t.length);for(let s=0;s<t.length;++s)r[s]=e(t[s],n);return r}}function ct(e,t,a){let n=lr(t);return ms(e,n,a)}function ms(e,t,a){return({inputs:n,attrs:r,backend:s})=>{let{x:i}=n;Ie(i,e);let o=s,l=o.data.get(i.dataId).values,u;if(i.dtype==="string"){if(!Array.isArray(l))throw new Error("String tensor's value was not an instance of Array");u=C.fromUint8ToStringArray(l)}else u=l;let p=a||i.dtype,c=t(u,p,r);return o.makeTensorInfo(i.shape,p,c)}}var v6=lr(e=>Math.ceil(e)),sz=ms(vi,v6),iz={kernelName:vi,backendName:"cpu",kernelFunc:sz};function m3(e,t,a,n){let r=v.getArrayFromDType(a,v.sizeFromShape(t));if(n&&a!=="string"){let s=0;e.forEach(i=>{let o=v.sizeFromShape(i.shape);r.set(i.vals,s),s+=o})}else{let s=0;e.forEach(i=>{let o=a==="string"?C.fromUint8ToStringArray(i.vals):i.vals,l=0;for(let u=0;u<i.shape[0];++u){let p=u*t[1]+s;for(let c=0;c<i.shape[1];++c)r[p+c]=o[l++]}s+=i.shape[1]})}return r}var w6=_t((e,t)=>e===t?1:0),k6=Kt(Oi,w6,null,"bool"),oz={kernelName:Oi,backendName:"cpu",kernelFunc:k6},I6=lr(e=>Math.exp(e)),S6=ms(zi,I6,"float32"),lz={kernelName:zi,backendName:"cpu",kernelFunc:S6},C6=lr(e=>Math.expm1(e)),uz=ms(Li,C6),dz={kernelName:Li,backendName:"cpu",kernelFunc:uz},T6=lr(e=>Math.floor(e)),pz=ms(Bi,T6),cz={kernelName:Bi,backendName:"cpu",kernelFunc:pz},N6=_t((e,t)=>Math.floor(e/t)),hz=Kt(Vi,N6,null,"int32"),mz={kernelName:Vi,backendName:"cpu",kernelFunc:hz};function R6(e,t,a,n,r,s,i,o,l){let u=_e([n,s],a);for(let p=0;p<n;p++){let c=[],d=0;for(let h=0;h<r;h++){let m=e[p*r+h];d+=m*i[h],c.push(m)}if(d<0||d>=l/s)throw new Error(`Invalid indices: ${c} does not index into ${o}`);for(let h=0;h<s;h++)u.values[p*s+h]=t.get(...t.indexToLoc(d*s+h))}return u}function E6(e,t,a){let n=_e(a,e.dtype);for(let r=0;r<n.size;++r){let s=n.indexToLoc(r).slice(),i=s[0],o=s[2],l=t.locToIndex([i,o]);s[2]=t.values[l];let u=e.locToIndex(s);0<=u&&u<e.values.length&&(n.values[r]=e.values[u])}return n}var M6=_t((e,t)=>e>t?1:0),fz=Kt(Hi,M6,null,"bool"),gz={kernelName:Hi,backendName:"cpu",kernelFunc:fz},$6=_t((e,t)=>e>=t?1:0),yz=Kt(ji,$6,null,"bool"),xz={kernelName:ji,backendName:"cpu",kernelFunc:yz},P6=_t((e,t)=>e<t?1:0),Az=Kt(Ji,P6,null,"bool"),bz={kernelName:Ji,backendName:"cpu",kernelFunc:Az},_6=_t((e,t)=>e<=t?1:0),vz=Kt(Qi,_6,null,"bool"),wz={kernelName:Qi,backendName:"cpu",kernelFunc:vz};function F6(e,t,a){let n=(t-e)/(a-1),r=v.makeZerosTypedArray(a,"float32");r[0]=e;for(let s=1;s<r.length;s++)r[s]=r[s-1]+n;return r}var D6=lr(e=>Math.log(e)),kz=ms(to,D6),Iz={kernelName:to,backendName:"cpu",kernelFunc:kz};function O6(e,t,a,n){let r=v.getTypedArrayFromDType(n,v.sizeFromShape(a));for(let s=0;s<r.length;++s){let i=s*t,o=e[i];for(let l=0;l<t;++l){let u=e[i+l];(Number.isNaN(u)||u>o)&&(o=u)}r[s]=o}return r}var z6=_t((e,t)=>Math.max(e,t)),Sz=Kt(lo,z6),Cz={kernelName:lo,backendName:"cpu",kernelFunc:Sz},L6=_t((e,t)=>Math.min(e,t)),Tz=Kt(ho,L6),Nz={kernelName:ho,backendName:"cpu",kernelFunc:Tz},f3=_t((e,t)=>e*t),Rz=c3((e,t,a,n)=>({real:e*a-t*n,imag:e*n+t*a})),a0=Kt(yo,f3,Rz),Ez={kernelName:yo,backendName:"cpu",kernelFunc:a0};function W6(e,t,a){let n=v.createScalarValue(-1,a);return f3([],t,n,e,a)}function Mz(e){let{inputs:t,backend:a}=e,{x:n}=t;Ie(n,"neg");let r=a.data.get(n.dataId).values,[s,i]=W6(r,n.shape,n.dtype);return a.makeTensorInfo(i,n.dtype,s)}var $z={kernelName:Su,backendName:"cpu",kernelFunc:Mz},B6=_t((e,t)=>e!==t?1:0),Pz=Kt(xo,B6,null,"bool"),_z={kernelName:xo,backendName:"cpu",kernelFunc:Pz};function g3(e,t,a,n,r){let s=t.length,i=v.sizeFromShape(t),o=v.computeStrides(t),l=v.computeStrides(r),u=v.getTypedArrayFromDType(a,v.sizeFromShape(r));for(let p=0;p<i;++p){let c=v.indexToLoc(p,s,o),d=new Array(c.length);for(let m=0;m<d.length;m++)d[m]=c[n[m]];let h=v.locToIndex(d,s,l);u[h]=e[p]}return u}function Va(e){let{inputs:t,attrs:a,backend:n}=e,{x:r}=t,{perm:s}=a;Ie(r,"transpose");let i=r.shape.length,o=new Array(i);for(let p=0;p<o.length;p++)o[p]=r.shape[s[p]];let l=n.data.get(r.dataId).values,u=g3(l,r.shape,r.dtype,s,o);return{dataId:n.write(u,o,r.dtype),shape:o,dtype:r.dtype}}var Fz={kernelName:Ir,backendName:"cpu",kernelFunc:Va};function V6(e,t,a,n){let[r,s]=C.computeOutAndReduceShapes(e,n),i=ca(t,"int32"),o=v.makeZerosTypedArray(v.sizeFromShape(r),i),l=v.sizeFromShape(s);for(let u=0;u<o.length;++u){let p=u*l,c=1;for(let d=0;d<l;++d)c*=a[p+d];o[u]=c}return{outVals:o,outShape:r,outDtype:i}}function Dz(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;Ie(r,"prod");let o=r.shape.length,l=v.parseAxisParam(s,r.shape),u=C.getAxesPermutation(l,o),p=l,c=r,d=[];u!=null&&(c=Va({inputs:{x:r},backend:a,attrs:{perm:u}}),d.push(c),p=C.getInnerMostAxes(p.length,o));let h=a.data.get(c.dataId).values,{outVals:m,outShape:f,outDtype:g}=V6(c.shape,c.dtype,h,p),y=f;return i&&(y=C.expandShapeToKeepDim(f,l)),d.forEach(x=>a.disposeIntermediateTensorInfo(x)),a.makeTensorInfo(y,g,m)}var Oz={kernelName:So,backendName:"cpu",kernelFunc:Dz};function zz(e,t,a){e.forEach((n,r)=>{if(n<0||n>=a){let s=v.indexToLoc(r,t.length,v.computeStrides(t)).join(",");throw new Error(`indices[${s}] = ${n} is not in [0, ${a})`)}})}function Lz(e,t){for(let a=0;a<e.length;++a){let n=e[a],r=a===e.length-1?t:e[a+1].length;if(n.length===0)throw new Error("Ragged splits may not be empty");if(n[0]<0)throw new Error("Ragged splits must be non-negative");if(n[n.length-1]>r)throw new Error("Ragged splits must not point past values");for(let s=1;s<n.length;++s)if(n[s-1]>n[s])throw new Error("Ragged splits must be sorted in ascending order")}}function Wz(e,t,a,n){let r=[],s=0,i=t.length-1+a.length,o=new Array(i).fill(null).map(()=>[0]);Lz(a,n);let l=1;for(let u=0;u<t.length-1;++u){l*=t[u];let p=t[u+1];for(let c=1;c<l+1;++c)o[u].push(c*p)}for(let u=0;u<e.length;++u){let p=e[u],c=e[u]+1;for(let d=0;d<a.length;++d){let h=a[d],m=d+t.length-1;if(m>=0){let f=o[m],g=f[f.length-1]-h[p];for(let y=p;y<c;++y)o[m].push(h[y+1]+g)}p=h[p],c=h[c]}c!==p&&(r.push([p,c]),s+=c-p)}return{outSplits:o,valueSlices:r,numValues:s}}function Bz(e){let t=[];for(let a=0;a<e.length;++a){let n=e[a].length,r=v.getArrayFromDType("int32",n);t.push(r),e[a].forEach((s,i)=>r[i]=s)}return t}function A5(e,t){let a=e.slice(0,t);for(;a.length<t;)a.push(1);for(let n=t;n<e.length;n++)a[t-1]*=e[n];return a}function Vz(e,t,a,n,r,s){let i=A5(t,2)[1],o=A5(s,2)[1],l=0;for(let u of a)for(let p=u[0];p<u[1];++p){for(let c=0;c<n;++c)r[l*o+c]=e[p*i+c];++l}}function Uz(e,t,a,n,r){let s=t.slice();s[0]=r;let i=v.getArrayFromDType(a,v.sizeFromShape(s)),o=e.length,l=o===0?0:o/t[0];return Vz(e,t,n,l,i,s),[i,s]}function U6(e,t,a,n,r,s,i,o){if(e.length===0)throw new Error("paramsNestedSplits must be non empty");if(t[0].length===0)throw new Error("Split tensors must not be scalars");let l=t[0][0]-1;if(zz(s,i,l),n.length===0)throw new Error("params.rank must be nonzero");let u=n[0],{outSplits:p,valueSlices:c,numValues:d}=Wz(s,i,e,u),h=Bz(p),m=Uz(a,n,r,c,d);return[h,m[0],m[1]]}var b5=2147483647;function G6(e,t,a,n,r,s,i){if(t.length>1)throw new Error("starts must be a scalar or vector");if(r.length>1)throw new Error("limits must be a scalar or vector");if(i.length>1)throw new Error("deltas must be a scalar or vector");let o=t.length===0,l=r.length===0,u=i.length===0,p=[];o||p.push(t[0]),l||p.push(r[0]),u||p.push(i[0]);for(let g=1;g<p.length;++g)if(p[g]!==p[g-1])throw new Error("starts, limits, and deltas must have the same shape");let c=p.length===0?1:p[0],d=v.getArrayFromDType("int32",c+1);d[0]=0;for(let g=0;g<c;++g){let y=o?e[0]:e[g],x=l?n[0]:n[g],A=u?s[0]:s[g];if(A===0)throw new Error("Requires delta != 0");let b;if(A>0&&x<y||A<0&&x>y)b=0;else if(b=Math.ceil(Math.abs((x-y)/A)),b>b5)throw new Error(`Requires ((limit - start) / delta) <= ${b5}`);d[g+1]=d[g]+b}let h=d[c],m=v.getArrayFromDType(a,h),f=0;for(let g=0;g<c;++g){let y=d[g+1]-d[g],x=o?e[0]:e[g],A=u?s[0]:s[g];for(let b=0;b<y;++b)m[f++]=x,x+=A}return[d,m]}var Sn=C.RowPartitionType,Gz=class $1{constructor(t,a,n,r,s,i,o,l,u,p){this.shape=t,this.shapeShape=a,this.values=n,this.valuesShape=r,this.valuesDType=s,this.defaultValue=i,this.defaultValueShape=o,this.rowPartitionValues=l,this.rowPartitionValuesShapes=u,this.rowPartitionTypes=C.getRowPartitionTypesHelper(p),this.raggedRank=C.getRaggedRank(this.rowPartitionTypes)}getRowPartitionTypeByDimension(t){return this.rowPartitionTypes[0]===Sn.FIRST_DIM_SIZE?this.rowPartitionTypes[t+1]:this.rowPartitionTypes[t]}getRowPartitionTensor(t){return this.rowPartitionTypes[0]===Sn.FIRST_DIM_SIZE?this.rowPartitionValues[t+1]:this.rowPartitionValues[t]}getMaxWidth(t){let a=this.getRowPartitionTensor(t-1);switch(this.getRowPartitionTypeByDimension(t-1)){case Sn.VALUE_ROWIDS:return $1.getMaxWidthValueRowID(a);case Sn.ROW_SPLITS:return $1.getMaxWidthRowSplit(a);default:throw new Error(`Cannot handle partition type ${Sn[this.getRowPartitionTypeByDimension(t-1)]}`)}}static getMaxWidthRowSplit(t){let a=t.length;if(a===0||a===1)return 0;let n=0;for(let r=0;r<a-1;++r){let s=t[r+1]-t[r];s>n&&(n=s)}return n}static getMaxWidthValueRowID(t){let a=t.length;if(a===0)return 0;let n=0,r=t[0],s=0;for(let i=1;i<a;++i){let o=t[i];o!==r&&(r=o,s=Math.max(i-n,s),n=i)}return Math.max(a-n,s)}tensorShapeFromTensor(t,a,n=!0){if(a.length===0){if(t[0]===-1)return[];throw new Error("The only valid scalar shape tensor is the fully unknown shape specified as -1.")}return w5(t,n)}calculateOutputSize(t){let a=this.valuesShape,n=this.defaultValueShape;C.validateDefaultValueShape(n,a);let r=this.tensorShapeFromTensor(this.shape,this.shapeShape),s=C.combineRaggedTensorToTensorShapes(this.raggedRank,r,a);s[0]<0&&(s[0]=t);for(let i=1;i<=this.raggedRank;++i)s[i]<0&&(s[i]=this.getMaxWidth(i));return s}calculateFirstParentOutputIndex(t,a,n){let r=Math.min(t,n),s=[],i=0;for(let o=0;o<r;++o,i+=a)s.push(i);for(let o=r;o<t;++o)s.push(-1);return v.assert(s.length===t,()=>"Final length of result must be equal to firstDimension."),s}calculateOutputIndexRowSplit(t,a,n,r){let s=t.length,i=[];for(let o=0;o<s-1;++o){let l=t[o+1]-t[o],u=Math.min(r,l),p=a[o];p===-1&&(u=0);for(let c=0;c<u;++c)i.push(p),p+=n;for(let c=0;c<l-u;++c)i.push(-1)}if(s>0&&i.length!==t[s-1])throw new Error("Invalid row split size.");return i}calculateOutputIndexValueRowID(t,a,n,r){let s=t.length,i=[];if(s===0)return[];let o=0,l=t[0];if(l>=a.length)throw new Error(`Got currentValueRowId=${l}, which is not less than ${a.length}`);let u=a[l];i.push(u);for(let p=1;p<s;++p){let c=t[p];if(c===l)u>=0&&(++o,o<r?u+=n:u=-1);else{if(o=0,l=c,c>=a.length)throw new Error(`Got nextValueRowId=${c} which is not less than ${a.length}`);u=a[c]}i.push(u)}if(i.length!==t.length)throw new Error("Invalid row ids.");return i}calculateOutputIndex(t,a,n,r){let s=this.getRowPartitionTensor(t),i=this.getRowPartitionTypeByDimension(t);switch(i){case Sn.VALUE_ROWIDS:return this.calculateOutputIndexValueRowID(s,a,n,r);case Sn.ROW_SPLITS:if(s.length-1>a.length)throw new Error(`Row partition size is greater than output size: ${s.length-1} > ${a.length}`);return this.calculateOutputIndexRowSplit(s,a,n,r);default:throw new Error(`Unsupported partition type: ${Sn[i]}`)}}getFirstDimensionSize(){let t=this.rowPartitionValues[0];if(this.rowPartitionTypes.length===0)throw new Error("No row_partition_types given.");let a=this.rowPartitionTypes[0];switch(a){case Sn.FIRST_DIM_SIZE:return t[0];case Sn.VALUE_ROWIDS:throw new Error("Cannot handle VALUE_ROWIDS in first dimension.");case Sn.ROW_SPLITS:return this.rowPartitionValuesShapes[0][0]-1;default:throw new Error(`Cannot handle type ${Sn[a]}`)}}compute(){if(this.rowPartitionValues[0].length<=0)throw new Error("Invalid first partition input. Tensor requires at least one element.");let t=this.getFirstDimensionSize(),a=this.calculateOutputSize(t),n=new Array(this.raggedRank+1);n[n.length-1]=1;for(let i=n.length-2;i>=0;--i)n[i]=n[i+1]*a[i+1];let r=w5(a,!1),s=v.getArrayFromDType(this.valuesDType,v.sizeFromShape(r));if(n[0]*a[0]>0){let i=this.calculateFirstParentOutputIndex(t,n[0],a[0]);for(let o=1;o<=this.raggedRank;++o)i=this.calculateOutputIndex(o-1,i,n[o],a[o]);this.setOutput(this.raggedRank,i,s,r)}return[r,s]}setOutput(t,a,n,r){if(n.length===0)return;let s=this.values,i=n,o=r.slice();o=o.slice(t+1);let l=v.sizeFromShape(o),u=a.length,p=this.defaultValue;if(p.length!==l&&p.length!==1){let m=this.defaultValueShape;De(()=>{let f=Q(p,m);p=Gl(f,o).dataSync()})}let c=0,d=0,h=0;for(let m=0;m<=u;++m){let f=m<u?a[m]:-1;if(f===h){++h;continue}if(d<h){let g=s.subarray(c*l),y=i.subarray(d*l),x=(h-d)*l;v5(y,g,x)}if(m>=u){let g=n.length;f=Math.floor(g/l)}if(f>h)if(this.defaultValue.length===1)i.subarray(h*l,f*l).fill(this.defaultValue[0]),h=f;else for(;f>h;){let g=i.slice(h*l);v5(g,p,l),++h}f<0?(c=m+1,d=h):(c=m,d=h,h=d+1)}}};function v5(e,t,a){for(let n=0;n<a;n++)e[n]=t[n]}function w5(e,t){let a=[];for(let n of e){if(n<0){if(!t)throw new Error(`Dimension ${n} must be >= 0`);if(n<-1)throw new Error(`Dimension ${n} must be >= -1`);n=-1}a.push(n)}return a}function H6(e,t,a,n,r,s,i,o,l,u){return new Gz(e,t,a,n,r,s,i,o,l,u).compute()}function y3(e,t,a,n){let r=e===t,s=e<t&&a<0,i=t<e&&a>1;if(r||s||i)return v.makeZerosTypedArray(0,n);let o=Math.abs(Math.ceil((t-e)/a)),l=v.makeZerosTypedArray(o,n);t<e&&a===1&&(a=-1),l[0]=e;for(let u=1;u<l.length;u++)l[u]=l[u-1]+a;return l}var j6=lr(e=>1/Math.sqrt(e)),Hz=ms(Po,j6),jz={kernelName:Po,backendName:"cpu",kernelFunc:Hz};function qs(e,t,a,n,r,s,i,o,l,u){let p=[n/r,r],c=e.values,d=t.values;if(n===0)return _e(a,t.dtype);let h=l instanceof Vt?l:_e(p,t.dtype);typeof l=="string"||typeof l=="number"?h.values.fill(l):typeof l=="boolean"&&h.values.fill(+l);for(let m=0;m<s;m++){let f=[],g=0;for(let y=0;y<i;y++){let x=c[m*i+y];f.push(x),g+=x*o[y]}if(g<0||g>=n/r)throw new Error(`Invalid indices: ${f} does not index into ${a}`);for(let y=0;y<r;y++)u?h.values[g*r+y]+=d[m*r+y]:h.values[g*r+y]=t.rank===0?d[0]:d[m*r+y]}return h}var qz=lr(e=>1/(1+Math.exp(-e))),q6=ct(Bo,e=>1/(1+Math.exp(-e))),Xz={kernelName:Bo,backendName:"cpu",kernelFunc:q6};function Ah(e,t,a,n,r){let s=Nt.isSliceContinous(n,t,a),i=v.sizeFromShape(a),o=v.computeStrides(n);if(s){let c=Nt.computeFlatOffset(t,o);return r==="string"?e.slice(c,c+i):e.subarray(c,c+i)}let l=r==="string"?C.fromUint8ToStringArray(e):e,u=_e(n,r,l),p=_e(a,r);for(let c=0;c<p.size;++c){let d=p.indexToLoc(c),h=d.map((m,f)=>m+t[f]);p.set(u.get(...h),...d)}return r==="string"?C.fromStringArrayToUint8(p.values):p.values}function ti(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{begin:s,size:i}=n;Ie(r,"slice");let[o,l]=Nt.parseSliceParams(r,s,i);Nt.assertParamsValid(r,o,l);let u=a.data.get(r.dataId).values,p=Ah(u,o,l,r.shape,r.dtype);return a.makeTensorInfo(l,r.dtype,p)}var Kz={kernelName:_u,backendName:"cpu",kernelFunc:ti};function X6(e,t,a,n,r,s,i){let o=t[0],l=s[0],u=new Array(l),p=new Array(o),c=t[1];if(l===0){if(o!==0)throw new Error(C.getSparseFillEmptyRowsIndicesDenseShapeMismatch(o));let g=v.getArrayFromDType(a,0),y=v.getArrayFromDType(r,0);return[g,[0,c],y,u,p]}let d=!0,h=0,m=new Array(l).fill(0);for(let g=0;g<o;++g){let y=e[g*c];if(y<0)throw new Error(C.getSparseFillEmptyRowsNegativeIndexErrorMessage(g,y));if(y>=l)throw new Error(C.getSparseFillEmptyRowsOutOfRangeIndexErrorMessage(g,y,l));++m[y],d=d&&y>=h,h=y}let f=!0;for(let g=0;g<l;++g){let y=m[g]===0;u[g]=y,f=f&&!y,m[g]=Math.max(m[g],1),g>0&&(m[g]+=m[g-1])}if(f&&d){let g=e,y=n;for(let x=0;x<o;++x)p[x]=x;return[g,[o,c],y,u,p]}else{let g=m[l-1],y=v.getArrayFromDType(a,g*c),x=v.getArrayFromDType(r,g),A=new Array(l).fill(0);for(let b=0;b<o;++b){let w=e[b*c],I=A[w],T=(w===0?0:m[w-1])+I;A[w]++;for(let N=0;N<c;++N)y[T*c+N]=e[b*c+N];x[T]=n[b],p[b]=T}for(let b=0;b<l;++b)if(A[b]===0){let w=b===0?0:m[b-1];y[w*c+0]=b;for(let I=1;I<c;++I)y[w*c+I]=0;x[w]=i}return[y,[g,c],x,u,p]}}function K6(e,t,a,n,r){let s=v.sizeFromShape(n),i=t[0],o=r.length,l=[],u=1,p=-1;for(let f=0;f<o;++f){let g=r[f];if(g===-1){if(p!==-1)throw new Error(C.getSparseReshapeMultipleNegativeOneOutputDimErrorMessage(p,f));p=f,l.push(1)}else{if(g<0)throw new Error(C.getSparseReshapeNegativeOutputDimErrorMessage(f,g));u*=g,l.push(g)}}if(p!==-1){if(u<=0)throw new Error(C.getSparseReshapeEmptyTensorZeroOutputDimErrorMessage());let f=Math.trunc(s/u);if(u*f!==s)throw new Error(C.getSparseReshapeInputOutputMultipleErrorMessage(n,l));l[p]=f}if(v.sizeFromShape(l)!==s)throw new Error(C.getSparseReshapeInputOutputMismatchErrorMessage(n,l));let c=n.length,d=[];if(c>0){d[c-1]=1;for(let f=c-2;f>=0;--f)d[f]=d[f+1]*n[f+1]}let h=[];if(o>0){h[o-1]=1;for(let f=o-2;f>=0;--f)h[f]=h[f+1]*l[f+1]}let m=v.getArrayFromDType(a,i*o);for(let f=0;f<i;++f){let g=0;for(let y=0;y<c;++y)g+=e[f*c+y]*d[y];for(let y=0;y<o;++y)m[f*o+y]=Math.trunc(g/h[y]),g%=h[y]}return[m,[i,o],l]}function x3(e,t,a,n,r,s=!1,i=0){let o=n.length,l=[t[0],e.length/t[0]],u=l[1],p=o>0?r[o-1]+1:0;if(p<0)throw new Error(C.getSparseSegmentReductionNegativeSegmentIdsErrorMessage());let c=t.slice();c[0]=p;let d=c.reduce((x,A)=>x*A,1),h=v.getArrayFromDType(a,d);if(o===0)return p>0&&h.fill(i),[h,c];if(p<=0)throw new Error(C.getSparseSegmentReductionNegativeSegmentIdsErrorMessage());let m=0,f=1,g=0,y=r[m];for(;;){let x=0;if(f<o){if(x=r[f],y===x){++f;continue}if(y>=x)throw new Error(C.getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage())}if(y<0||y>=p)throw new Error(C.getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage(y,p));y>g&&h.fill(i,g*u,y*u);for(let A=m;A<f;++A){let b=n[A];if(b<0||b>=l[0])throw new Error(C.getSparseSegmentReductionIndicesOutOfRangeErrorMessage(A,n[A],l[0]));for(let w=0;w<u;w++)h[y*u+w]+=e[b*u+w]}if(s)for(let A=0;A<u;A++)h[y*u+A]/=f-m;if(m=f,++f,g=y+1,y=x,f>o)break}return g<p&&h.fill(i,g*u,p*u),[h,c]}var Yz=lr(e=>Math.sqrt(e)),Zz=ct(Uo,e=>Math.sqrt(e)),Jz={kernelName:Uo,backendName:"cpu",kernelFunc:Zz},Y6=_t((e,t)=>{let a=e-t;return a*a}),Qz=Kt(qo,Y6),eL={kernelName:qo,backendName:"cpu",kernelFunc:Qz},Z6=lr((e,t)=>{let{pattern:a,replaceGlobal:n,rewrite:r}=t;return e.replace(new RegExp(a,n?"g":""),r)}),tL=ms(Tp,Z6),aL={kernelName:Tp,backendName:"cpu",kernelFunc:tL};function J6(e,t,a,n){let r=_e(e,t.dtype);for(let s=0;s<r.size;s++){let i=r.indexToLoc(s),o=new Array(i.length);for(let l=0;l<o.length;l++)o[l]=i[l]*a[l]+n[l];r.set(t.get(...o),...i)}return r}var nL=class{constructor(e,t,a,n,r,s){this.separator=v.encodeString(e),this.nGramWidths=t,this.leftPad=v.encodeString(a),this.rightPad=v.encodeString(n),this.padWidth=r,this.preserveShort=s}getPadWidth(e){return Math.min(this.padWidth<0?e-1:this.padWidth,e-1)}getNumNGrams(e,t){let a=this.getPadWidth(t);return Math.max(0,e+2*a-t+1)}createNGrams(e,t,a,n,r,s){for(let i=0;i<r;++i){let o=this.getPadWidth(s),l=Math.max(0,o-i),u=Math.max(0,o-(r-(i+1))),p=s-(l+u),c=t+(l>0?0:i-o),d=0;d+=l*this.leftPad.length;for(let y=0;y<p;++y)d+=e[c+y].length;d+=u*this.rightPad.length;let h=l+u+p-1;d+=h*this.separator.length,a[n+i]=new Uint8Array(d);let m=a[n+i],f=0,g=y=>y.forEach(x=>m[f++]=x);for(let y=0;y<l;++y)g(this.leftPad),g(this.separator);for(let y=0;y<p-1;++y)g(e[c+y]),g(this.separator);if(p>0){g(e[c+p-1]);for(let y=0;y<u;++y)g(this.separator),g(this.rightPad)}else{for(let y=0;y<u-1;++y)g(this.rightPad),g(this.separator);g(this.rightPad)}}}compute(e,t){let a=e.length,n=t.length;if(n>0){let o=t[0];if(o!==0)throw new Error(`First split value must be 0, got ${o}`);for(let l=1;l<n;++l){let u=t[l]>=o;if(u=u&&t[l]<=a,!u)throw new Error(`Invalid split value ${t[l]}, must be in [${o}, ${a}]`);o=t[l]}if(o!==a)throw new Error(`Last split value must be data size. Expected ${a}, got ${o}`)}let r=n-1,s=v.getArrayFromDType("int32",n);if(a===0||n===0){let o=new Array(a);for(let l=0;l<=r;++l)s[l]=0;return[o,s]}s[0]=0;for(let o=1;o<=r;++o){let l=t[o]-t[o-1],u=0;this.nGramWidths.forEach(p=>{u+=this.getNumNGrams(l,p)}),this.preserveShort&&l>0&&u===0&&(u=1),s[o]=s[o-1]+u}let i=new Array(s[r]);for(let o=0;o<r;++o){let l=t[o],u=s[o];if(this.nGramWidths.forEach(p=>{let c=t[o+1]-t[o],d=this.getNumNGrams(c,p);this.createNGrams(e,l,i,u,d,p),u+=d}),this.preserveShort&&u===s[o]){let p=t[o+1]-t[o];if(p===0)continue;let c=p+2*this.padWidth;this.createNGrams(e,l,i,u,1,c)}}return[i,s]}};function A3(e,t,a,n,r,s,i,o){return new nL(a,n,r,s,i,o).compute(e,t)}function rL(e,t,a,n){if(!e.length)return;if(t.length===0){for(let s=0;s<e.length;++s)n.push(e.subarray(s,s+1));return}if(t.length===1){let s=t[0],i=e.indexOf(s);for(;i!==-1;){let o=e.subarray(0,i);(!a||o.length!==0)&&n.push(o),e=e.subarray(i+1),i=e.indexOf(s)}(!a||e.length!==0)&&n.push(e);return}let r=0;for(let s=0;s<e.length+1;s++)if(s===e.length||t.indexOf(e[s])!==-1){let i=e.subarray(r,s);(!a||i.length!==0)&&n.push(i),r=s+1}}function b3(e,t,a){let n=e.length,r=[],s=0,i=0,o=new Array(n);for(let d=0;d<n;++d){let h=r.length;rL(e[d],t,a,r);let m=r.length-h;o[d]=m,s+=m,i=Math.max(i,m)}let l=v.getArrayFromDType("int32",s*2),u=new Array(s),p=[n,i],c=0;for(let d=0;d<n;++d)for(let h=0;h<o[d];++h)l[c*2]=d,l[c*2+1]=h,u[c]=r[c],++c;return[l,u,p]}function v3(e,t){let a=v.getArrayFromDType("int32",e.length);for(let n=0;n<e.length;++n)a[n]=v.fingerPrint64(e[n]).modulo(t).getLowBitsUnsigned();return a}var Q6=_t((e,t)=>e-t),sL=c3((e,t,a,n)=>({real:e-a,imag:t-n})),w3=Kt(Ko,Q6,sL),iL={kernelName:Ko,backendName:"cpu",kernelFunc:w3};function ev(e,t){let a=new Array(e.rank);for(let r=0;r<a.length;r++)a[r]=e.shape[r]*t[r];let n=_e(a,e.dtype);for(let r=0;r<n.values.length;++r){let s=n.indexToLoc(r),i=new Array(e.rank);for(let l=0;l<i.length;l++)i[l]=s[l]%e.shape[l];let o=e.locToIndex(i);n.values[r]=e.values[o]}return n}var Td=(e,t)=>{let a=t.value-e.value;return a===0?e.index-t.index:a};function tv(e,t,a=0,n=e.length-1){for(;n>a;){if(n-a>600){let o=n-a+1,l=t-a+1,u=Math.log(o),p=.5*Math.exp(2*u/3),c=.5*Math.sqrt(u*p*(o-p)/o)*Math.sign(l-o/2),d=Math.max(a,Math.floor(t-l*p/o+c)),h=Math.min(n,Math.floor(t+(o-l)*p/o+c));tv(e,t,d,h)}let r=e[t],s=a,i=n;for(v.swap(e,a,t),Td(e[n],r)>0&&v.swap(e,a,n);s<i;){for(v.swap(e,s,i),s++,i--;Td(e[s],r)<0;)s=s+1;for(;Td(e[i],r)>0;)i=i-1}Td(e[a],r)===0?v.swap(e,a,i):(i=i+1,v.swap(e,i,n)),i<=t&&(a=i+1),t<=i&&(n=i-1)}}function av(e,t,a,n,r){let s=t[t.length-1],[i,o]=[e.length/s,s],l=v.getTypedArrayFromDType(a,i*n),u=v.getTypedArrayFromDType("int32",i*n);for(let c=0;c<i;c++){let d=c*o,h=e.subarray(d,d+o),m=new Array(h.length);h.forEach((x,A)=>m[A]={value:x,index:A}),n<m.length&&(tv(m,n),m=m.slice(0,n)),r&&m.sort(Td);let f=c*n,g=l.subarray(f,f+n),y=u.subarray(f,f+n);for(let x=0;x<n;x++)g[x]=m[x].value,y[x]=m[x].index}let p=t.slice();return p[p.length-1]=n,[_e(p,a,l),_e(p,"int32",u)]}function k3(e,t,a,n){let r=v.parseAxisParam(t,a)[0],s=[1,a[0],1];for(let m=0;m<r;m++)s[0]*=a[m];s[1]=a[r];for(let m=r+1;m<a.length;m++)s[2]*=a[m];let i=new Map,o=new Int32Array(a[r]),l=new Vt(s,n,e),u=[],p=s[0]===1&&s[2]===1;for(let m=0;m<a[r];m++){let f;if(p)f=e[m].toString();else{let y=[];for(let x=0;x<s[0];x++)for(let A=0;A<s[2];A++)y.push(l.get(x,m,A));f=y.join(",")}let g=i.get(f);if(g!=null)o[m]=g;else{let y=i.size;i.set(f,y),o[m]=y,u.push(m)}}let c=s.slice();c[1]=i.size;let d=new Vt(c,n);u.forEach((m,f)=>{for(let g=0;g<s[0];g++)for(let y=0;y<s[2];y++)d.set(l.get(g,m,y),g,f,y)});let h=a.slice();return h[r]=c[1],{outputValues:d.values,outputShape:h,indices:o}}var oL="4.22.0";al("cpu",()=>new p3,1);var nv=ct(Fi,e=>e>=0?e:Math.exp(e)-1),lL={kernelName:Fi,backendName:"cpu",kernelFunc:nv};function rv(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{alpha:s}=n;Ie([r],"leakyRelu");let i=v.sizeFromShape(r.shape),o=a.data.get(r.dataId).values,l=v.getTypedArrayFromDType("float32",i);for(let u=0;u<o.length;u++)l[u]=o[u]<0?s*o[u]:o[u];return a.makeTensorInfo(r.shape,"float32",l)}var uL={kernelName:Zi,backendName:"cpu",kernelFunc:rv},dL=_t((e,t)=>e<0?t*e:e);function sv(e){let{inputs:t,backend:a}=e,{x:n,alpha:r}=t;Ie([n,r],"prelu");let s=a.data.get(n.dataId).values,i=a.data.get(r.dataId).values,[o,l]=dL(n.shape,r.shape,s,i,"float32");return a.makeTensorInfo(l,"float32",o)}var pL={kernelName:Io,backendName:"cpu",kernelFunc:sv},iv=ct(To,e=>Math.max(0,e)),cL={kernelName:To,backendName:"cpu",kernelFunc:iv},ov=ct(Eo,e=>Math.min(Math.max(0,e),6)),hL={kernelName:Eo,backendName:"cpu",kernelFunc:ov};function bh(e,t,a,n,r){if(a==="linear")return rr({inputs:{x:t},backend:e});if(a==="relu")return iv({inputs:{x:t},backend:e});if(a==="elu")return nv({inputs:{x:t},backend:e});if(a==="relu6")return ov({inputs:{x:t},backend:e});if(a==="prelu")return sv({inputs:{x:t,alpha:n},backend:e});if(a==="leakyrelu")return rv({inputs:{x:t},backend:e,attrs:{alpha:r}});if(a==="sigmoid")return q6({inputs:{x:t},backend:e});throw new Error(`Activation ${a} has not been implemented for the CPU backend.`)}function bt(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{shape:s}=n,i=v.sizeFromShape(r.shape),o=v.inferFromImplicitShape(s,i),l=v.sizeFromShape(o);v.assert(i===l,()=>`The new shape (${o}) has ${l} elements and the old shape (${r.shape}) has ${i} elements. The new shape and old shape must have the same number of elements.`),a.incRef(r.dataId);let u=a.data.get(r.dataId);if(u.complexTensorInfos!=null){let p=u.complexTensorInfos.real,c=u.complexTensorInfos.imag;p.shape=o,c.shape=o}return{dataId:r.dataId,shape:o,dtype:r.dtype}}var mL={kernelName:Eu,backendName:"cpu",kernelFunc:bt};function lv(e){let{inputs:t,backend:a,attrs:n}=e,{a:r,b:s}=t,{transposeA:i,transposeB:o}=n;Ie([r,s],"matMul");let l=r.shape.length,u=s.shape.length,p=i?r.shape[l-2]:r.shape[l-1],c=o?s.shape[u-1]:s.shape[u-2],d=i?r.shape[l-1]:r.shape[l-2],h=o?s.shape[u-2]:s.shape[u-1],m=r.shape.slice(0,-2),f=s.shape.slice(0,-2),g=v.sizeFromShape(m),y=v.sizeFromShape(f),x=nl.assertAndGetBroadcastShape(r.shape.slice(0,-2),s.shape.slice(0,-2)).concat([d,h]);v.assert(p===c,()=>`Error in matMul: inner shapes (${p}) and (${c}) of Tensors with shapes ${r.shape} and ${s.shape} and transposeA=${i} and transposeB=${o} must match.`);let A=i?[g,p,d]:[g,d,p],b=o?[y,h,c]:[y,c,h],w=bt({inputs:{x:r},backend:a,attrs:{shape:A}}),I=bt({inputs:{x:s},backend:a,attrs:{shape:b}}),T=i?w.shape[1]:w.shape[2],N=i?w.shape[2]:w.shape[1],M=o?I.shape[1]:I.shape[2],$=Math.max(g,y),E=a.data.get(w.dataId).values,S=a.data.get(I.dataId).values,_=v.computeStrides(w.shape),O=v.computeStrides(I.shape),[W,P,U]=i?[_[0],1,_[1]]:[_[0],_[1],1],[G,q,H]=o?[1,O[1],O[0]]:[O[1],1,O[0]],V=N*M,Z=_e([$,N,M],w.dtype),X=Z.values,re=a.blockSize;for(let ee=0;ee<$;ee++){let ge=ee%g,ie=ee%y;for(let be=0;be<N;be+=re){let Ce=Math.min(be+re,N);for(let Re=0;Re<M;Re+=re){let Le=Math.min(Re+re,M);for(let qe=0;qe<T;qe+=re){let gt=Math.min(qe+re,T);for(let dt=be;dt<Ce;dt++)for(let st=Re;st<Le;st++){let it=0;for(let He=qe;He<gt;He++){let xt=E[ge*W+dt*P+He*U],Ha=S[He*G+st*q+ie*H];it+=xt*Ha}X[ee*V+(dt*M+st)]+=it}}}}}return a.disposeIntermediateTensorInfo(w),a.disposeIntermediateTensorInfo(I),a.makeTensorInfo(x,Z.dtype,Z.values)}var fL={kernelName:xi,backendName:"cpu",kernelFunc:lv};function gL(e){let{inputs:t,backend:a,attrs:n}=e,{a:r,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:u,activation:p,leakyreluAlpha:c}=n,d,h,m,f=[];d=lv({inputs:{a:r,b:s},attrs:{transposeA:l,transposeB:u},backend:a}),i&&(h=eu({inputs:{a:d,b:i},backend:a}),f.push(d),d=h),p&&(m=bh(a,d,p,o,c),f.push(d),d=m);for(let g of f)a.disposeIntermediateTensorInfo(g);return d}var yL={kernelName:Zr,backendName:"cpu",kernelFunc:gL},xL=ct(oi,e=>Math.acos(e)),AL={kernelName:oi,backendName:"cpu",kernelFunc:xL},bL=ct(li,e=>Math.acosh(e)),vL={kernelName:li,backendName:"cpu",kernelFunc:bL};function wL(e){let{inputs:t,backend:a}=e,n=t;Ie(t,"addN");let r=n.map(o=>a.data.get(o.dataId).values),s=_e(n[0].shape,n[0].dtype),i=s.values;for(let o=0;o<n.length;o++){let l=r[o];for(let u=0;u<i.length;u++)i[u]+=l[u]}return a.makeTensorInfo(s.shape,s.dtype,s.values)}var kL={kernelName:ui,backendName:"cpu",kernelFunc:wL};function IL(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;Ie(r,"all");let o=v.parseAxisParam(s,r.shape),l=o,u=C.getAxesPermutation(l,r.shape.length),p=r;u!=null&&(p=Va({inputs:{x:r},backend:a,attrs:{perm:u}}),l=C.getInnerMostAxes(l.length,r.shape.length)),C.assertAxesAreInnerMostDims("all",l,p.shape.length);let[c,d]=C.computeOutAndReduceShapes(p.shape,l),h=v.sizeFromShape(d),m=v.makeZerosTypedArray(v.sizeFromShape(c),p.dtype),f=a.data.get(p.dataId).values;for(let y=0;y<m.length;++y){let x=y*h,A=f[x];for(let b=0;b<h;++b){let w=f[x+b];A=A&&w}m[y]=A}u!=null&&a.disposeIntermediateTensorInfo(p);let g=a.makeTensorInfo(c,p.dtype,m);if(i){let y=C.expandShapeToKeepDim(c,o),x=bt({inputs:{x:g},backend:a,attrs:{shape:y}});return a.disposeIntermediateTensorInfo(g),x}return g}var SL={kernelName:di,backendName:"cpu",kernelFunc:IL};function CL(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;Ie(r,"any");let o=v.parseAxisParam(s,r.shape),l=o,u=C.getAxesPermutation(l,r.shape.length),p=r;u!=null&&(p=Va({inputs:{x:r},backend:a,attrs:{perm:u}}),l=C.getInnerMostAxes(l.length,r.shape.length)),C.assertAxesAreInnerMostDims("any",l,p.shape.length);let[c,d]=C.computeOutAndReduceShapes(p.shape,l),h=v.sizeFromShape(d),m=v.makeZerosTypedArray(v.sizeFromShape(c),p.dtype),f=a.data.get(p.dataId).values;for(let y=0;y<m.length;++y){let x=y*h,A=f[x];for(let b=0;b<h;++b){let w=f[x+b];A=A||w}m[y]=A}u!=null&&a.disposeIntermediateTensorInfo(p);let g=a.makeTensorInfo(c,p.dtype,m);if(i){let y=C.expandShapeToKeepDim(c,o),x=bt({inputs:{x:g},backend:a,attrs:{shape:y}});return a.disposeIntermediateTensorInfo(g),x}return g}var TL={kernelName:pi,backendName:"cpu",kernelFunc:CL};function NL(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s}=n;Ie(r,"argMax");let i=v.parseAxisParam(s,r.shape),o=C.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=Va({inputs:{x:r},backend:a,attrs:{perm:o}}),u.push(l),i=C.getInnerMostAxes(i.length,l.shape.length)),i=[i[0]],C.assertAxesAreInnerMostDims("argMax",i,l.shape.length);let[p,c]=C.computeOutAndReduceShapes(l.shape,i),d=v.sizeFromShape(p),h=v.makeZerosTypedArray(d,"int32"),m=v.sizeFromShape(c),f=a.data.get(l.dataId).values;for(let g=0;g<h.length;++g){let y=g*m,x=f[y],A=0;for(let b=0;b<m;++b){let w=f[y+b];w>x&&(x=w,A=b)}h[g]=A}return u.forEach(g=>a.disposeIntermediateTensorInfo(g)),a.makeTensorInfo(p,"int32",h)}var RL={kernelName:lu,backendName:"cpu",kernelFunc:NL};function EL(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s}=n;Ie(r,"argMin");let i=v.parseAxisParam(s,r.shape),o=C.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=Va({inputs:{x:r},backend:a,attrs:{perm:o}}),u.push(l),i=C.getInnerMostAxes(i.length,l.shape.length)),i=[i[0]],C.assertAxesAreInnerMostDims("argMin",i,l.shape.length);let[p,c]=C.computeOutAndReduceShapes(l.shape,i),d=v.sizeFromShape(p),h=v.makeZerosTypedArray(d,"int32"),m=v.sizeFromShape(c),f=a.data.get(l.dataId).values;for(let g=0;g<h.length;++g){let y=g*m,x=f[y],A=0;for(let b=0;b<m;++b){let w=f[y+b];w<x&&(x=w,A=b)}h[g]=A}return u.forEach(g=>a.disposeIntermediateTensorInfo(g)),a.makeTensorInfo(p,"int32",h)}var ML={kernelName:uu,backendName:"cpu",kernelFunc:EL},$L=ct(ci,e=>Math.asin(e)),PL={kernelName:ci,backendName:"cpu",kernelFunc:$L},_L=ct(hi,e=>Math.asinh(e)),FL={kernelName:hi,backendName:"cpu",kernelFunc:_L},DL=ct(mi,e=>Math.atan(e)),OL={kernelName:mi,backendName:"cpu",kernelFunc:DL},zL=_t((e,t)=>Math.atan2(e,t)),LL=Kt(gi,zL),WL={kernelName:gi,backendName:"cpu",kernelFunc:LL},BL=ct(fi,e=>Math.atanh(e)),VL={kernelName:fi,backendName:"cpu",kernelFunc:BL};function I3(e,t,a,n,r,s){let i=r.strideHeight,o=r.strideWidth,l=r.dilationHeight,u=r.dilationWidth,p=r.effectiveFilterHeight,c=r.effectiveFilterWidth,d=r.padInfo.top,h=r.padInfo.left,m=s==="max"?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,f=_e(r.outShape,a),g=f.values,y=r.outShape[1]*r.outShape[2]*r.outShape[3],x=r.outShape[2]*r.outShape[3],A=r.outShape[3];for(let b=0;b<r.batchSize;++b){let w=b*y,I=b*n[0];for(let T=0;T<r.inChannels;++T)for(let N=0;N<r.outHeight;++N){let M=N*i-d,$=Math.max(0,M),E=Math.min(r.inHeight,p+M),S=w+N*x;for(let _=0;_<r.outWidth;++_){let O=_*o-h,W=Math.max(0,O),P=Math.min(r.inWidth,c+O),U=m,G=0,q=0;for(let V=$;V<E;V+=l){let Z=I+V*n[1];for(let X=W;X<P;X+=u){let re=Z+X*n[2],ee=e[re+T];s==="max"&&ee>U?U=ee:s==="avg"&&(G+=ee,q++)}if(isNaN(U))break}let H=S+_*A+T;g[H]=s==="avg"?G/q:U}}}return f}function uv(e,t,a,n,r=!1,s=!1){let i=_e(n.outShape,"int32"),o=n.strideHeight,l=n.strideWidth,u=n.dilationHeight,p=n.dilationWidth,c=n.effectiveFilterHeight,d=n.effectiveFilterWidth,h=n.padInfo.top,m=n.padInfo.left,f=_e(t,a,e);for(let g=0;g<n.batchSize;++g)for(let y=0;y<n.inChannels;++y)for(let x=0;x<n.outHeight;++x){let A=x*o-h,b=A;for(;b<0;)b+=u;let w=Math.min(n.inHeight,c+A);for(let I=0;I<n.outWidth;++I){let T=I*l-m,N=T;for(;N<0;)N+=p;let M=Math.min(n.inWidth,d+T),$=Number.NEGATIVE_INFINITY,E=-1;for(let S=b;S<w;S+=u){let _=S-A;for(let O=N;O<M;O+=p){let W=O-T,P=f.get(g,S,O,y);P>$&&($=P,r?E=s?((g*n.inHeight+S)*n.inWidth+O)*n.inChannels+y:(S*n.inWidth+O)*n.inChannels+y:E=_*d+W)}}i.set(E,g,x,I,y)}}return i}function dv(e,t,a,n,r,s){let i=r.strideDepth,o=r.strideHeight,l=r.strideWidth,u=r.dilationDepth,p=r.dilationHeight,c=r.dilationWidth,d=r.effectiveFilterDepth,h=r.effectiveFilterHeight,m=r.effectiveFilterWidth,f=r.padInfo.front,g=r.padInfo.top,y=r.padInfo.left,x=s==="max"?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,A=_e(r.outShape,a),b=A.values,w=r.outShape[1]*r.outShape[2]*r.outShape[3]*r.outShape[4],I=r.outShape[2]*r.outShape[3]*r.outShape[4],T=r.outShape[3]*r.outShape[4],N=r.outShape[4];for(let M=0;M<r.batchSize;++M){let $=M*w,E=M*n[0];for(let S=0;S<r.inChannels;++S)for(let _=0;_<r.outDepth;++_){let O=_*i-f,W=O;for(;W<0;)W+=u;let P=Math.min(r.inDepth,d+O),U=$+_*I;for(let G=0;G<r.outHeight;++G){let q=G*o-g,H=q;for(;H<0;)H+=p;let V=Math.min(r.inHeight,h+q),Z=U+G*T;for(let X=0;X<r.outWidth;++X){let re=X*l-y,ee=re;for(;ee<0;)ee+=c;let ge=Math.min(r.inWidth,m+re),ie=Z+X*N,be=x,Ce=0,Re=0;for(let qe=W;qe<P;qe+=u){let gt=E+qe*n[1];for(let dt=H;dt<V;dt+=p){let st=gt+dt*n[2];for(let it=ee;it<ge;it+=c){let He=st+it*n[3],xt=e[He+S];if(s==="max"&&xt>be?be=xt:s==="avg"&&(Ce+=xt,Re++),isNaN(be))break}if(isNaN(be))break}if(isNaN(be))break}let Le=ie+S;b[Le]=s==="avg"?Ce/Math.max(Re,1):be}}}}return A}function UL(e,t){let a=_e(t.outShape,"int32"),n=t.strideDepth,r=t.strideHeight,s=t.strideWidth,i=t.dilationDepth,o=t.dilationHeight,l=t.dilationWidth,u=t.effectiveFilterDepth,p=t.effectiveFilterHeight,c=t.effectiveFilterWidth,d=t.padInfo.front,h=t.padInfo.top,m=t.padInfo.left;for(let f=0;f<t.batchSize;++f)for(let g=0;g<t.inChannels;++g)for(let y=0;y<t.outDepth;++y){let x=y*n-d,A=x;for(;A<0;)A+=i;let b=Math.min(t.inDepth,u+x);for(let w=0;w<t.outHeight;++w){let I=w*r-h,T=I;for(;T<0;)T+=o;let N=Math.min(t.inHeight,p+I);for(let M=0;M<t.outWidth;++M){let $=M*s-m,E=$;for(;E<0;)E+=l;let S=Math.min(t.inWidth,c+$),_=Number.NEGATIVE_INFINITY,O=-1;for(let W=A;W<b;W+=i){let P=W-x;for(let U=T;U<N;U+=o){let G=U-I;for(let q=E;q<S;q+=l){let H=q-$,V=e.get(f,W,U,q,g);V>=_&&(_=V,O=P*p*c+G*p+H)}}}a.set(O,f,y,w,M,g)}}}return a}function GL(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t;Ie(r,"avgPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=n,u=1;v.assert(C.eitherStridesOrDilationsAreOne(i,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let p=C.computePool2DInfo(r.shape,s,i,u,o,l),c;if(p.filterWidth===1&&p.filterHeight===1&&v.arraysEqual(p.inShape,p.outShape))c=rr({inputs:{x:r},backend:a});else{let d=a.data.get(r.dataId).values,h=v.computeStrides(r.shape),m=I3(d,r.shape,r.dtype,h,p,"avg");c=a.makeTensorInfo(p.outShape,r.dtype,m.values)}return c}var HL={kernelName:yi,backendName:"cpu",kernelFunc:GL};function jL(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:u}=n;Ie(r,"avgPool3d");let p=C.computePool3DInfo(r.shape,s,i,1,o,l,u),c=a.data.get(r.dataId).values,d=dv(c,r.shape,r.dtype,v.computeStrides(r.shape),p,"avg");return a.makeTensorInfo(d.shape,"float32",d.values)}var qL={kernelName:du,backendName:"cpu",kernelFunc:jL};function XL(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=n;Ie([r,s],"avgPool3DGrad");let p=C.computePool3DInfo(s.shape,i,o,1,l,u),c=p.strideDepth,d=p.strideHeight,h=p.strideWidth,m=p.filterDepth,f=p.filterHeight,g=p.filterWidth,y=p.dilationDepth,x=p.dilationHeight,A=p.dilationWidth,b=p.effectiveFilterDepth,w=p.effectiveFilterHeight,I=p.effectiveFilterWidth,T=b-1-p.padInfo.front,N=I-1-p.padInfo.left,M=w-1-p.padInfo.top,$=_e(s.shape,"float32"),E=1/(m*f*g),S=a.bufferSync(r);for(let _=0;_<p.batchSize;++_)for(let O=0;O<p.inChannels;++O)for(let W=0;W<p.inDepth;++W)for(let P=0;P<p.inHeight;++P)for(let U=0;U<p.inWidth;++U){let G=W-T,q=P-M,H=U-N,V=0;for(let Z=0;Z<b;Z+=y){let X=(G+Z)/c;if(!(X<0||X>=p.outDepth||Math.floor(X)!==X))for(let re=0;re<w;re+=x){let ee=(q+re)/d;if(!(ee<0||ee>=p.outHeight||Math.floor(ee)!==ee))for(let ge=0;ge<I;ge+=A){let ie=(H+ge)/h;if(ie<0||ie>=p.outWidth||Math.floor(ie)!==ie)continue;let be=S.get(_,X,ee,ie,O);V+=be}}}$.set(V*E,_,W,P,U,O)}return a.makeTensorInfo($.shape,$.dtype,$.values)}var KL={kernelName:pp,backendName:"cpu",kernelFunc:XL};function YL(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,i=s;Ie([r,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:u}=n,p=C.computePool2DInfo(i.shape,o,l,1,u),c=p.strideHeight,d=p.strideWidth,h=p.filterHeight,m=p.filterWidth,f=p.dilationHeight,g=p.dilationWidth,y=p.effectiveFilterHeight,x=p.effectiveFilterWidth,A=x-1-p.padInfo.left,b=y-1-p.padInfo.top,w=_e(i.shape,"float32"),I=1/(h*m),T=a.data.get(r.dataId).values,N=_e(r.shape,"float32",T);for(let M=0;M<p.batchSize;++M)for(let $=0;$<p.inChannels;++$)for(let E=0;E<p.inHeight;++E)for(let S=0;S<p.inWidth;++S){let _=E-b,O=S-A,W=0;for(let P=0;P<y;P+=f){let U=(_+P)/c;if(!(U<0||U>=p.outHeight||Math.floor(U)!==U))for(let G=0;G<x;G+=g){let q=(O+G)/d;if(q<0||q>=p.outWidth||Math.floor(q)!==q)continue;let H=N.get(M,U,q,$);W+=H}}w.set(W*I,M,E,S,$)}return a.makeTensorInfo(w.shape,w.dtype,w.values)}var ZL={kernelName:dp,backendName:"cpu",kernelFunc:YL};function JL(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,scale:s,offset:i,mean:o,variance:l}=t;v.assert(o.shape.length===l.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),v.assert(i==null||o.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),v.assert(s==null||o.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks."),Ie([r,o,l,s,i],"batchNorm");let{varianceEpsilon:u}=n;u==null&&(u=.001);let p=a.data.get(r.dataId).values,c=a.data.get(o.dataId).values,d=a.data.get(l.dataId).values,h=s?a.data.get(s.dataId).values:new Float32Array([1]),m=i?a.data.get(i.dataId).values:new Float32Array([0]),f=new Float32Array(p.length),g=m.length,y=h.length,x=d.length,A=c.length,b=0,w=0,I=0,T=0;for(let N=0;N<p.length;++N)f[N]=m[b++]+(p[N]-c[w++])*h[I++]/Math.sqrt(d[T++]+u),b>=g&&(b=0),w>=A&&(w=0),I>=y&&(I=0),T>=x&&(T=0);return a.makeTensorInfo(r.shape,r.dtype,f)}var QL={kernelName:Ui,backendName:"cpu",kernelFunc:JL};function eW(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockShape:s,crops:i}=n;Ie([r],"batchToSpaceND");let o=s.reduce((y,x)=>y*x),l=C.getReshaped(r.shape,s,o),u=C.getPermuted(l.length,s.length),p=C.getReshapedPermuted(r.shape,s,o),c=C.getSliceBeginCoords(i,s.length),d=C.getSliceSize(p,i,s.length),h=bt({inputs:{x:r},backend:a,attrs:{shape:l}}),m=Va({inputs:{x:h},backend:a,attrs:{perm:u}}),f=bt({inputs:{x:m},backend:a,attrs:{shape:p}}),g=ti({inputs:{x:f},backend:a,attrs:{begin:c,size:d}});return a.disposeIntermediateTensorInfo(h),a.disposeIntermediateTensorInfo(m),a.disposeIntermediateTensorInfo(f),g}var tW={kernelName:pu,backendName:"cpu",kernelFunc:eW};function aW(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,weights:s}=t,{size:i}=n,o=a.data.get(r.dataId).values,l=a.data.get(s.dataId).values,u=h3(o,l,s.dtype,s.shape,i);return a.makeTensorInfo([i],s.dtype,u)}var nW={kernelName:Ai,backendName:"cpu",kernelFunc:aW};function rW(e){let{inputs:t,backend:a}=e,{s0:n,s1:r}=t,s=a.data.get(n.dataId).values,i=a.data.get(r.dataId).values,o=C.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return a.makeTensorInfo([o.length],"int32",Int32Array.from(o))}var sW={kernelName:hu,backendName:"cpu",kernelFunc:rW},iW=ct(us,(e,t)=>{let a=t;return e>a.clipValueMax?a.clipValueMax:e<a.clipValueMin?a.clipValueMin:e}),oW={kernelName:us,backendName:"cpu",kernelFunc:iW},lW=e=>{let{x:t}=e.inputs,a=e.backend,n=new Float32Array(v.sizeFromShape(t.shape)),r=a.data.get(t.dataId),s=r.complexTensorInfos.real,i=r.complexTensorInfos.imag,o=a.data.get(s.dataId).values,l=a.data.get(i.dataId).values;for(let u=0;u<o.length;u++){let p=o[u],c=l[u];n[u]=Math.hypot(p,c)}return a.makeOutput(n,t.shape,"float32")},uW={kernelName:hp,backendName:"cpu",kernelFunc:lW};function tu(e){let{inputs:t,backend:a}=e,{input:n}=t,r=a.data.get(n.dataId).complexTensorInfos.imag,s=a.data.get(r.dataId).values;return a.makeTensorInfo(r.shape,r.dtype,s)}var dW={kernelName:vp,backendName:"cpu",kernelFunc:tu};function au(e){let{inputs:t,backend:a,attrs:n}=e,{axis:r}=n,s=v.parseAxisParam(r,t[0].shape)[0],i=t.map(f=>f.shape);C.assertParamsConsistent(i,s);let o=C.computeOutShape(t.map(f=>f.shape),s);if(v.sizeFromShape(o)===0)return a.makeTensorInfo(o,t[0].dtype,[]);let l=t.filter(f=>v.sizeFromShape(f.shape)>0);if(l.length===1)return rr({inputs:{x:l[0]},backend:a});if(l[0].dtype==="complex64"){let f=l.map(b=>ei({inputs:{input:b},backend:a})),g=l.map(b=>tu({inputs:{input:b},backend:a})),y=au({inputs:f,backend:a,attrs:{axis:s}}),x=au({inputs:g,backend:a,attrs:{axis:s}}),A=Ja({inputs:{real:y,imag:x},backend:a});return f.forEach(b=>a.disposeIntermediateTensorInfo(b)),g.forEach(b=>a.disposeIntermediateTensorInfo(b)),a.disposeIntermediateTensorInfo(y),a.disposeIntermediateTensorInfo(x),A}let u=l.map(f=>{let g=[-1,v.sizeFromShape(f.shape.slice(s))];return bt({inputs:{x:f},backend:a,attrs:{shape:g}})}),p=u.map(f=>({vals:a.data.get(f.dataId).values,shape:f.shape}));o=C.computeOutShape(u.map(f=>f.shape),1);let c=u[0].shape[0]===1,d=m3(p,o,t[0].dtype,c),h=C.computeOutShape(l.map(f=>f.shape),s),m=a.makeTensorInfo(h,t[0].dtype,d);return u.forEach(f=>a.disposeIntermediateTensorInfo(f)),m}var pW={kernelName:mu,backendName:"cpu",kernelFunc:au};function pv(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:u,dimRoundingMode:p}=n;Ie([r,s],"conv2d");let c=C.convertConv2DDataFormat(l),d=C.computeConv2DInfo(r.shape,s.shape,i,u,o,p,!1,c),h=d.filterHeight,m=d.filterWidth,f=d.dilationHeight,g=d.dilationWidth,y=d.padInfo.left,x=d.padInfo.top,A=d.dataFormat==="channelsLast",b=new Vt(d.outShape,r.dtype),w=v.computeStrides(r.shape),I=v.computeStrides(s.shape),T=w[0],N=A?w[1]:w[2],M=A?w[2]:1,$=A?1:w[1],E=b.strides[0],S=A?b.strides[1]:b.strides[2],_=A?b.strides[2]:1,O=A?1:b.strides[1],W=a.data.get(r.dataId).values,P=a.data.get(s.dataId).values,U=b.values;for(let G=0;G<d.batchSize;++G){let q=G*T,H=G*E;for(let V=0;V<d.outHeight;++V){let Z=H+V*S,X=V*d.strideHeight-x;for(let re=0;re<h;++re){let ee=X+re*f;if(ee<0||ee>=d.inHeight)continue;let ge=re*I[0],ie=q+ee*N;for(let be=0;be<d.outWidth;++be){let Ce=Z+be*_,Re=be*d.strideWidth-y;for(let Le=0;Le<m;++Le){let qe=Re+Le*g;if(qe<0||qe>=d.inWidth)continue;let gt=ge+Le*I[1],dt=ie+qe*M,st=gt;for(let it=0;it<d.inChannels;++it){let He=W[dt+it*$];for(let xt=0;xt<d.outChannels;++xt)U[Ce+xt*O]+=He*P[st+xt];st+=d.outChannels}}}}}}return a.makeTensorInfo(b.shape,b.dtype,U)}var cW={kernelName:wi,backendName:"cpu",kernelFunc:pv};function hW(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:u,filterShape:p}=n;Ie([r,s],"conv2dBackpropFilter");let c=C.convertConv2DDataFormat(l),d=C.computeConv2DInfo(r.shape,p,i,1,o,u,!1,c),{strideHeight:h,strideWidth:m,filterHeight:f,filterWidth:g}=d,y=d.dataFormat==="channelsLast",x=new Vt(d.filterShape,"float32"),A=d.padInfo.left,b=d.padInfo.top,w=a.data.get(r.dataId).values,I=a.data.get(s.dataId).values,T=new Vt(r.shape,r.dtype,w),N=new Vt(s.shape,s.dtype,I);for(let M=0;M<f;++M){let $=Math.max(0,Math.ceil((b-M)/h)),E=Math.min(d.outHeight,(d.inHeight+b-M)/h);for(let S=0;S<g;++S){let _=Math.max(0,Math.ceil((A-S)/m)),O=Math.min(d.outWidth,(d.inWidth+A-S)/m);for(let W=0;W<d.inChannels;++W)for(let P=0;P<d.outChannels;++P){let U=0;for(let G=0;G<d.batchSize;++G)for(let q=$;q<E;++q){let H=M+q*h-b;for(let V=_;V<O;++V){let Z=S+V*m-A;y?U+=T.get(G,H,Z,W)*N.get(G,q,V,P):U+=T.get(G,W,H,Z)*N.get(G,P,q,V)}}x.set(U,M,S,W,P)}}}return a.makeTensorInfo(x.shape,x.dtype,x.values)}var mW={kernelName:mp,backendName:"cpu",kernelFunc:hW};function fW(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:u,dimRoundingMode:p}=n;Ie([r,s],"conv2dBackpropInput");let c=v.computeStrides(s.shape),d=v.computeStrides(r.shape),h=C.convertConv2DDataFormat(u),m=C.computeConv2DInfo(i,s.shape,o,1,l,p,!1,h),f=new Vt(m.inShape,"float32"),g=f.values,y=a.data.get(r.dataId).values,x=a.data.get(s.dataId).values,[A,b,w]=c,{batchSize:I,filterHeight:T,filterWidth:N,inChannels:M,inHeight:$,inWidth:E,outChannels:S,outHeight:_,outWidth:O,strideHeight:W,strideWidth:P}=m;h=m.dataFormat;let U=T-1-m.padInfo.top,G=N-1-m.padInfo.left,q=h==="channelsLast",H=f.strides[0],V=q?f.strides[1]:f.strides[2],Z=q?f.strides[2]:1,X=q?1:f.strides[1],re=d[0],ee=q?d[1]:d[2],ge=q?d[2]:1,ie=q?1:d[1];for(let be=0;be<I;++be)for(let Ce=0;Ce<M;++Ce)for(let Re=0;Re<$;++Re){let Le=Re-U,qe=Math.max(0,Math.ceil(Le/W)),gt=Math.min(_,(T+Le)/W);for(let dt=0;dt<E;++dt){let st=dt-G,it=Math.max(0,Math.ceil(st/P)),He=Math.min(O,(N+st)/P),xt=0;for(let zt=qe;zt<gt;++zt){let un=zt*W-Le;for(let ua=it;ua<He;++ua){let _a=ua*P-st,dn=re*be+ee*zt+ge*ua,Fa=A*(T-1-un)+b*(N-1-_a)+w*Ce;for(let ht=0;ht<S;++ht){let Da=y[dn+ie*ht],ja=x[Fa+ht];xt+=Da*ja}}}let Ha=H*be+V*Re+Z*dt+X*Ce;g[Ha]=xt}}return a.makeTensorInfo(f.shape,f.dtype,f.values)}var gW={kernelName:ki,backendName:"cpu",kernelFunc:fW};function yW(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=n;Ie([r,s],"conv3d");let u=C.computeConv3DInfo(r.shape,s.shape,i,l,o),{filterDepth:p,filterHeight:c,filterWidth:d,dilationDepth:h,dilationHeight:m,dilationWidth:f,padInfo:g}=u,y=g.front,x=g.left,A=g.top,b=new Vt(u.outShape,r.dtype),w=a.data.get(r.dataId).values,I=a.data.get(s.dataId).values,T=b.values,N=v.computeStrides(r.shape),M=v.computeStrides(s.shape);for(let $=0;$<u.batchSize;++$){let E=$*N[0],S=$*b.strides[0];for(let _=0;_<u.outDepth;++_){let O=S+_*b.strides[1],W=_*u.strideDepth-y;for(let P=0;P<p;++P){let U=W+P*h;if(U<0||U>=u.inDepth)continue;let G=P*M[0],q=E+U*N[1];for(let H=0;H<u.outHeight;++H){let V=O+H*b.strides[2],Z=H*u.strideHeight-A;for(let X=0;X<c;++X){let re=Z+X*m;if(re<0||re>=u.inHeight)continue;let ee=G+X*M[1],ge=q+re*N[2];for(let ie=0;ie<u.outWidth;++ie){let be=V+ie*u.outChannels,Ce=ie*u.strideWidth-x;for(let Re=0;Re<d;++Re){let Le=Ce+Re*f;if(Le<0||Le>=u.inWidth)continue;let qe=ee+Re*M[2],gt=ge+Le*u.inChannels,dt=qe;for(let st=0;st<u.inChannels;++st){let it=w[gt+st];for(let He=0;He<u.outChannels;++He)T[be+He]+=it*I[dt+He];dt+=u.outChannels}}}}}}}}return a.makeTensorInfo(b.shape,b.dtype,b.values)}var xW={kernelName:Ii,backendName:"cpu",kernelFunc:yW};function AW(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,dy:s}=t,{strides:i,pad:o,filterShape:l}=n;Ie([r,s],"conv3dBackpropFilterV2");let u=v.computeStrides(r.shape),p=v.computeStrides(s.shape),c=C.computeConv3DInfo(r.shape,l,i,1,o),d=c.strideDepth,h=c.strideHeight,m=c.strideWidth,f=c.filterDepth,g=c.filterHeight,y=c.filterWidth,x=new Vt(c.filterShape,"float32"),A=x.values,[b,w,I,T]=x.strides,N=a.data.get(s.dataId).values,[M,$,E,S]=p,_=a.data.get(r.dataId).values,[O,W,P,U]=u,G=c.padInfo.front,q=c.padInfo.left,H=c.padInfo.top;for(let V=0;V<f;++V){let Z=Math.max(0,Math.ceil((G-V)/d)),X=Math.min(c.outDepth,(c.inDepth+G-V)/d),re=V*b;for(let ee=0;ee<g;++ee){let ge=Math.max(0,Math.ceil((H-ee)/h)),ie=Math.min(c.outHeight,(c.inHeight+H-ee)/h),be=ee*w+re;for(let Ce=0;Ce<y;++Ce){let Re=Math.max(0,Math.ceil((q-Ce)/m)),Le=Math.min(c.outWidth,(c.inWidth+q-Ce)/m),qe=Ce*I+be;for(let gt=0;gt<c.inChannels;++gt){let dt=gt*T+qe;for(let st=0;st<c.outChannels;++st){let it=0;for(let He=0;He<c.batchSize;++He){let xt=He*O,Ha=He*M;for(let zt=Z;zt<X;++zt){let un=(V+zt*d-G)*W+xt,ua=zt*$+Ha;for(let _a=ge;_a<ie;++_a){let dn=(ee+_a*h-H)*P+un,Fa=_a*E+ua;for(let ht=Re;ht<Le;++ht){let Da=(Ce+ht*m-q)*U+dn,ja=ht*S+Fa;it+=_[Da+gt]*N[ja+st]}}}}A[dt+st]=it}}}}}return a.makeTensorInfo(x.shape,x.dtype,x.values)}var bW={kernelName:fu,backendName:"cpu",kernelFunc:AW};function vW(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,filter:s}=t,{pad:i,strides:o,inputShape:l}=n;Ie([r],"conv3dBackpropInputV2");let u=v.computeStrides(r.shape),p=v.computeStrides(s.shape),c=C.computeConv3DInfo(l,s.shape,o,1,i),d=new Vt(c.inShape,"float32"),h=d.values,[m,f,g,y]=d.strides,x=a.data.get(r.dataId).values,[A,b,w,I]=u,T=a.data.get(s.dataId).values,[N,M,$,E]=p,{batchSize:S,filterDepth:_,filterHeight:O,filterWidth:W,inChannels:P,inDepth:U,inHeight:G,inWidth:q,outChannels:H,outDepth:V,outHeight:Z,outWidth:X,strideDepth:re,strideHeight:ee,strideWidth:ge}=c,ie=_-1-c.padInfo.front,be=O-1-c.padInfo.top,Ce=W-1-c.padInfo.left;for(let Re=0;Re<S;++Re)for(let Le=0;Le<P;++Le)for(let qe=0;qe<U;++qe){let gt=qe-ie,dt=Math.max(0,Math.ceil(gt/re)),st=Math.min(V,(_+gt)/re);for(let it=0;it<G;++it){let He=it-be,xt=Math.max(0,Math.ceil(He/ee)),Ha=Math.min(Z,(O+He)/ee);for(let zt=0;zt<q;++zt){let un=zt-Ce,ua=Math.max(0,Math.ceil(un/ge)),_a=Math.min(X,(W+un)/ge),dn=0;for(let Fa=dt;Fa<st;++Fa){let ht=Fa*re-gt;for(let Da=xt;Da<Ha;++Da){let ja=Da*ee-He;for(let fr=ua;fr<_a;++fr){let Tl=fr*ge-un,Xn=A*Re+b*Fa+w*Da+I*fr,fd=N*(_-1-ht)+M*(O-1-ja)+$*(W-1-Tl)+E*Le;for(let In=0;In<H;++In){let Or=x[Xn+In],Zt=T[fd+In];dn+=Or*Zt}}}}h[m*Re+f*qe+g*it+y*zt+Le]=dn}}}return a.makeTensorInfo(d.shape,d.dtype,d.values)}var wW={kernelName:Si,backendName:"cpu",kernelFunc:vW},kW=ct(Ci,e=>Math.cos(e)),IW={kernelName:Ci,backendName:"cpu",kernelFunc:kW},SW=ct(Ti,e=>Math.cosh(e)),CW={kernelName:Ti,backendName:"cpu",kernelFunc:SW};function TW(e){let{inputs:t,backend:a,attrs:n}=e,{image:r,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:u}=n,[p,c,d,h]=r.shape,m=s.shape[0],[f,g]=o,y=_e([m,f,g,h],"float32"),x=a.data.get(s.dataId).values,A=a.data.get(i.dataId).values,b=a.data.get(r.dataId).values,w=v.computeStrides(r.shape),I=v.computeStrides(y.shape);for(let T=0;T<m;T++){let N=T*4,M=x[N],$=x[N+1],E=x[N+2],S=x[N+3],_=A[T];if(_>=p)continue;let O=f>1?(E-M)*(c-1)/(f-1):0,W=g>1?(S-$)*(d-1)/(g-1):0;for(let P=0;P<f;P++){let U=f>1?M*(c-1)+P*O:.5*(M+E)*(c-1);if(U<0||U>c-1){for(let G=0;G<g;G++)for(let q=0;q<h;q++){let H=q+G*I[2]+P*I[1]+T*I[0];y.values[H]=u}continue}if(l==="bilinear"){let G=Math.floor(U),q=Math.ceil(U),H=U-G;for(let V=0;V<g;V++){let Z=g>1?$*(d-1)+V*W:.5*($+S)*(d-1);if(Z<0||Z>d-1){for(let ge=0;ge<h;ge++){let ie=ge+V*I[2]+P*I[1]+T*I[0];y.values[ie]=u}continue}let X=Math.floor(Z),re=Math.ceil(Z),ee=Z-X;for(let ge=0;ge<h;ge++){let ie=ge+X*w[2]+G*w[1]+_*w[0],be=b[ie];ie=ge+re*w[2]+G*w[1]+_*w[0];let Ce=b[ie];ie=ge+X*w[2]+q*w[1]+_*w[0];let Re=b[ie];ie=ge+re*w[2]+q*w[1]+_*w[0];let Le=b[ie],qe=be+(Ce-be)*ee,gt=Re+(Le-Re)*ee;ie=ge+V*I[2]+P*I[1]+T*I[0],y.values[ie]=qe+(gt-qe)*H}}}else for(let G=0;G<g;++G){let q=g>1?$*(d-1)+G*W:.5*($+S)*(d-1);if(q<0||q>d-1){for(let Z=0;Z<h;Z++){let X=Z+G*I[2]+P*I[1]+T*I[0];y.values[X]=u}continue}let H=Math.round(q),V=Math.round(U);for(let Z=0;Z<h;Z++){let X=Z+H*w[2]+V*w[1]+_*w[0],re=Z+G*I[2]+P*I[1]+T*I[0];y.values[re]=b[X]}}}}return a.makeTensorInfo(y.shape,y.dtype,y.values)}var NW={kernelName:Ei,backendName:"cpu",kernelFunc:TW};function RW(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=n;Ie(r,"cumprod");let l=C.getAxesPermutation([s],r.shape.length),u=r;l!=null&&(u=Va({inputs:{x:r},backend:a,attrs:{perm:l}}));let p=C.getInnerMostAxes(1,r.shape.length)[0];if(p!==u.shape.length-1)throw new Error(`backend.cumprod in CPU expects an inner-most axis=${u.shape.length-1} but got axis=${p}`);let c=ca(u.dtype,"int32"),d=v.makeOnesTypedArray(v.sizeFromShape(u.shape),c),h=a.data.get(u.dataId).values,m=u.shape[u.shape.length-1],f=o?(y,x)=>y+m-x-1:(y,x)=>y+x;for(let y=0;y<h.length;y+=m)for(let x=0;x<m;x++){let A=f(y,x);if(x===0)d[A]=i?1:h[A];else{let b=f(y,x-1);d[A]=i?h[b]*d[b]:h[A]*d[b]}}let g=a.makeTensorInfo(u.shape,c,d);if(l!=null){let y=C.getUndoAxesPermutation(l),x=Va({inputs:{x:g},backend:a,attrs:{perm:y}});return a.disposeIntermediateTensorInfo(g),a.disposeIntermediateTensorInfo(u),x}return g}var EW={kernelName:Ni,backendName:"cpu",kernelFunc:RW};function MW(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=n;Ie(r,"cumsum");let l=C.getAxesPermutation([s],r.shape.length),u=r;l!=null&&(u=Va({inputs:{x:r},backend:a,attrs:{perm:l}}));let p=C.getInnerMostAxes(1,r.shape.length)[0];if(p!==u.shape.length-1)throw new Error(`backend.cumsum in CPU expects an inner-most axis=${u.shape.length-1} but got axis=${p}`);let c=ca(u.dtype,"int32"),d=v.makeZerosTypedArray(v.sizeFromShape(u.shape),c),h=a.data.get(u.dataId).values,m=u.shape[u.shape.length-1],f=o?(y,x)=>y+m-x-1:(y,x)=>y+x;for(let y=0;y<h.length;y+=m)for(let x=0;x<m;x++){let A=f(y,x);if(x===0)d[A]=i?0:h[A];else{let b=f(y,x-1);d[A]=i?h[b]+d[b]:h[A]+d[b]}}let g=a.makeTensorInfo(u.shape,c,d);if(l!=null){let y=C.getUndoAxesPermutation(l),x=Va({inputs:{x:g},backend:a,attrs:{perm:y}});return a.disposeIntermediateTensorInfo(g),a.disposeIntermediateTensorInfo(u),x}return g}var $W={kernelName:Ri,backendName:"cpu",kernelFunc:MW};function PW(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,weights:s}=t,{size:i,binaryOutput:o}=n;if(r.shape.length===1){let l=a.data.get(r.dataId).values,u=a.data.get(s.dataId).values,p=h3(l,u,s.dtype,s.shape,i);return a.makeTensorInfo([i],s.dtype,p)}else if(r.shape.length===2){let l=a.bufferSync(r),u=a.bufferSync(s),p=A6(l,u,i,o);return a.makeTensorInfo(p.shape,s.dtype,p.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${r.shape.length}.`)}var _W={kernelName:gu,backendName:"cpu",kernelFunc:PW};function FW(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockSize:s,dataFormat:i}=n;v.assert(i==="NHWC",()=>`Only NHWC dataFormat supported on CPU for depthToSpace. Got ${i}`);let o=r.shape[0],l=r.shape[1],u=r.shape[2],p=r.shape[3],c=l*s,d=u*s,h=p/(s*s),m=a.data.get(r.dataId).values,f=new Float32Array(o*c*d*h),g=0;for(let y=0;y<o;++y)for(let x=0;x<c;++x){let A=Math.floor(x/s),b=x%s;for(let w=0;w<d;++w){let I=Math.floor(w/s),T=w%s,N=(b*s+T)*h;for(let M=0;M<h;++M){let $=M+N+p*(I+u*(A+l*y));f[g++]=m[$]}}}return a.makeTensorInfo([o,c,d,h],r.dtype,f)}var DW={kernelName:Mi,backendName:"cpu",kernelFunc:FW};function cv(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l,dimRoundingMode:u}=n;Ie([r,s],"depthwiseConv2DNative");let p=v.computeStrides(r.shape),c=v.computeStrides(s.shape),d=l;d==null&&(d=[1,1]),v.assert(C.eitherStridesOrDilationsAreOne(i,d),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${d}'`);let h=C.computeConv2DInfo(r.shape,s.shape,i,d,o,u,!0),{filterHeight:m,filterWidth:f,dilationHeight:g,dilationWidth:y,padInfo:x}=h,A=x.left,b=x.top,w=h.outChannels/h.inChannels,I=new Vt(h.outShape,r.dtype),T=a.data.get(r.dataId).values,N=a.data.get(s.dataId).values,M=I.values;for(let $=0;$<h.batchSize;++$){let E=$*p[0],S=$*I.strides[0];for(let _=0;_<h.outHeight;++_){let O=S+_*I.strides[1],W=_*h.strideHeight-b;for(let P=0;P<m;++P){let U=W+P*g;if(U<0||U>=h.inHeight)continue;let G=P*c[0],q=E+U*p[1];for(let H=0;H<h.outWidth;++H){let V=O+H*I.strides[2],Z=H*h.strideWidth-A;for(let X=0;X<f;++X){let re=Z+X*y;if(re<0||re>=h.inWidth)continue;let ee=G+X*c[1],ge=q+re*h.inChannels,ie=V,be=ee;for(let Ce=0;Ce<h.inChannels;++Ce){let Re=T[ge+Ce];for(let Le=0;Le<w;++Le)M[ie+Le]+=Re*N[be+Le];ie+=w,be+=w}}}}}}return a.makeTensorInfo(I.shape,I.dtype,I.values)}var OW={kernelName:$i,backendName:"cpu",kernelFunc:cv};function zW(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,filterShape:p}=n;Ie([r,s],"depthwiseConv2dNativeBackpropFilter");let c=C.computeConv2DInfo(r.shape,p,i,o,l,u,!0),{strideHeight:d,strideWidth:h,filterHeight:m,filterWidth:f}=c,g=new Vt(c.filterShape,"float32"),y=c.padInfo.left,x=c.padInfo.top,A=c.outChannels/c.inChannels,b=a.data.get(r.dataId).values,w=new Vt(r.shape,r.dtype,b),I=a.data.get(s.dataId).values,T=new Vt(s.shape,s.dtype,I);for(let N=0;N<m;++N){let M=Math.max(0,Math.ceil((x-N)/d)),$=Math.min(c.outHeight,(c.inHeight+x-N)/d);for(let E=0;E<f;++E){let S=Math.max(0,Math.ceil((y-E)/h)),_=Math.min(c.outWidth,(c.inWidth+y-E)/h);for(let O=0;O<c.outChannels;++O){let W=Math.trunc(O/A),P=O%A,U=0;for(let G=0;G<c.batchSize;++G)for(let q=M;q<$;++q){let H=N+q*d-x;for(let V=S;V<_;++V){let Z=E+V*h-y;U+=w.get(G,H,Z,W)*T.get(G,q,V,O)}}g.set(U,N,E,W,P)}}}return a.makeTensorInfo(g.shape,g.dtype,g.values)}var LW={kernelName:fp,backendName:"cpu",kernelFunc:zW};function WW(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,inputShape:p}=n;Ie([r,s],"depthwiseConv2DNativeBackpropInput");let c=v.computeStrides(r.shape),d=v.computeStrides(s.shape),h=C.computeConv2DInfo(p,s.shape,i,o,l,u,!0),m=new Vt(h.inShape,"float32"),f=m.values,[g,y,x]=m.strides,A=a.data.get(r.dataId).values,[b,w,I]=c,T=a.data.get(s.dataId).values,[N,M,$]=d,{batchSize:E,filterHeight:S,filterWidth:_,inChannels:O,inHeight:W,inWidth:P,outChannels:U,outHeight:G,outWidth:q,strideHeight:H,strideWidth:V}=h,Z=S-1-h.padInfo.top,X=_-1-h.padInfo.left,re=U/O;for(let ee=0;ee<E;++ee)for(let ge=0;ge<O;++ge)for(let ie=0;ie<W;++ie){let be=ie-Z,Ce=Math.max(0,Math.ceil(be/H)),Re=Math.min(G,(S+be)/H);for(let Le=0;Le<P;++Le){let qe=Le-X,gt=Math.max(0,Math.ceil(qe/V)),dt=Math.min(q,(_+qe)/V),st=0;for(let it=Ce;it<Re;++it){let He=it*H-be;for(let xt=gt;xt<dt;++xt){let Ha=xt*V-qe,zt=b*ee+w*it+I*xt,un=N*(S-1-He)+M*(_-1-Ha)+$*ge;for(let ua=0;ua<re;++ua){let _a=ge*re+ua,dn=A[zt+_a],Fa=T[un+ua];st+=dn*Fa}}}f[g*ee+y*ie+x*Le+ge]=st}}return a.makeTensorInfo(m.shape,m.dtype,m.values)}var BW={kernelName:gp,backendName:"cpu",kernelFunc:WW};function VW(e){let{inputs:t,backend:a}=e,{x:n}=t,r=v.sizeFromShape(n.shape),s=a.data.get(n.dataId).values,i=_e([r,r],n.dtype),o=i.values;for(let u=0;u<s.length;u++)o[u*r+u]=s[u];let l=[...n.shape,...n.shape];return a.makeTensorInfo(l,i.dtype,i.values)}var UW={kernelName:yu,backendName:"cpu",kernelFunc:VW},GW={kernelName:Pi,backendName:"cpu",kernelFunc:({inputs:e,backend:t,attrs:a})=>{let{x:n,filter:r}=e,{strides:s,pad:i,dilations:o}=a,l=t,u=l.data.get(n.dataId).values,p=n.shape.length,c=l.data.get(r.dataId).values,d=r.shape.length,{batchSize:h,inHeight:m,inWidth:f,inChannels:g,outHeight:y,outWidth:x,padInfo:A,strideHeight:b,strideWidth:w,filterHeight:I,filterWidth:T,dilationHeight:N,dilationWidth:M,outShape:$}=C.computeDilation2DInfo(n.shape,r.shape,s,i,"NHWC",o),E=v.sizeFromShape($),S=$.length,_=v.getArrayFromDType(n.dtype,E);for(let O=0;O<h;++O)for(let W=0;W<y;++W){let P=W*b-A.top;for(let U=0;U<x;++U){let G=U*w-A.left;for(let q=0;q<g;++q){let H=Number.MIN_SAFE_INTEGER;for(let Z=0;Z<I;++Z){let X=P+Z*N;if(X>=0&&X<m)for(let re=0;re<T;++re){let ee=G+re*M;if(ee>=0&&ee<f){let ge=v.locToIndex([O,X,ee,q],p,v.computeStrides(n.shape)),ie=v.locToIndex([Z,re,q],d,v.computeStrides(r.shape)),be=u[ge]+c[ie];be>H&&(H=be)}}}let V=v.locToIndex([O,W,U,q],S,v.computeStrides($));_[V]=H}}}return{dataId:l.write(v.toTypedArray(_,n.dtype),$,n.dtype),shape:$,dtype:n.dtype}}},HW={kernelName:Xl,backendName:"cpu",kernelFunc:({inputs:e,backend:t,attrs:a})=>{let{x:n,filter:r,dy:s}=e,{strides:i,pad:o,dilations:l}=a,u=t,p=v.toNestedArray(n.shape,u.data.get(n.dataId).values),c=v.toNestedArray(r.shape,u.data.get(r.dataId).values),{batchSize:d,inHeight:h,inWidth:m,inChannels:f,outHeight:g,outWidth:y,padInfo:x,strideHeight:A,strideWidth:b,filterHeight:w,filterWidth:I,dilationHeight:T,dilationWidth:N,outShape:M}=C.computeDilation2DInfo(n.shape,r.shape,i,o,"NHWC",l);v.assert(s.rank===M.length,()=>`Error in ${Xl}, dy must have the same rank as output ${M.length}, but got ${s.rank}`);let $=v.toNestedArray(M,u.data.get(s.dataId).values),E=v.makeZerosNestedTypedArray(r.shape,r.dtype);for(let S=0;S<d;++S)for(let _=0;_<g;++_){let O=_*A-x.top;for(let W=0;W<y;++W){let P=W*b-x.left;for(let U=0;U<f;++U){let G=Number.MIN_SAFE_INTEGER,q=0,H=0;for(let V=0;V<w;++V){let Z=O+V*T;if(Z>=0&&Z<h)for(let X=0;X<I;++X){let re=P+X*N;if(re>=0&&re<m){let ee=p[S][Z][re][U]+c[V][X][U];ee>G&&(G=ee,q=V,H=X)}}}E[q][H][U]+=$[S][_][W][U]}}}return{dataId:u.write(v.toTypedArray(E,n.dtype),r.shape,r.dtype),shape:r.shape,dtype:r.dtype}}},jW={kernelName:ql,backendName:"cpu",kernelFunc:({inputs:e,backend:t,attrs:a})=>{let{x:n,filter:r,dy:s}=e,{strides:i,pad:o,dilations:l}=a,u=t,p=v.toNestedArray(n.shape,u.data.get(n.dataId).values),c=v.toNestedArray(r.shape,u.data.get(r.dataId).values),{batchSize:d,inHeight:h,inWidth:m,inChannels:f,outHeight:g,outWidth:y,padInfo:x,strideHeight:A,strideWidth:b,filterHeight:w,filterWidth:I,dilationHeight:T,dilationWidth:N,outShape:M}=C.computeDilation2DInfo(n.shape,r.shape,i,o,"NHWC",l);v.assert(s.rank===M.length,()=>`Error in ${ql}, dy must have the same rank as output ${M.length}, but got ${s.rank}`);let $=v.toNestedArray(M,u.data.get(s.dataId).values),E=v.makeZerosNestedTypedArray(n.shape,n.dtype);for(let S=0;S<d;++S)for(let _=0;_<g;++_){let O=_*A-x.top;for(let W=0;W<y;++W){let P=W*b-x.left;for(let U=0;U<f;++U){let G=Number.MIN_SAFE_INTEGER,q=O<0?0:O,H=P<0?0:P;for(let V=0;V<w;++V){let Z=O+V*T;if(Z>=0&&Z<h)for(let X=0;X<I;++X){let re=P+X*N;if(re>=0&&re<m){let ee=p[S][Z][re][U]+c[V][X][U];ee>G&&(G=ee,q=Z,H=re)}}}E[S][q][H][U]+=$[S][_][W][U]}}}return{dataId:u.write(v.toTypedArray(E,n.dtype),n.shape,n.dtype),shape:n.shape,dtype:n.dtype}}};function qW(e){let{inputs:t,backend:a,attrs:n}=e,{image:r}=t,{canvas:s,options:i}=n,{contextOptions:o,imageOptions:l}=i||{},u=(l==null?void 0:l.alpha)||1,p=(o==null?void 0:o.contextType)||"2d";if(p!=="2d")throw new Error(`Context type ${o.contextType} is not supported by the CPU backend.`);let c=s.getContext(p,(o==null?void 0:o.contextAttributes)||{});if(c==null)throw new Error(`Could not get the context with ${p} type.`);let[d,h]=r.shape.slice(0,2),m=r.shape.length===2?1:r.shape[2],f=a.data.get(r.dataId).values,g=r.dtype==="float32"?255:1,y=new Uint8ClampedArray(h*d*4);for(let A=0;A<d*h;++A){let b=[0,0,0,255*u];for(let I=0;I<m;I++){let T=f[A*m+I];if(r.dtype==="float32"){if(T<0||T>1)throw new Error(`Tensor values for a float32 Tensor must be in the range [0 - 1] but encountered ${T}.`)}else if(r.dtype==="int32"&&(T<0||T>255))throw new Error(`Tensor values for a int32 Tensor must be in the range [0 - 255] but encountered ${T}.`);m===1?(b[0]=T*g,b[1]=T*g,b[2]=T*g):b[I]=T*g}let w=A*4;y[w+0]=Math.round(b[0]),y[w+1]=Math.round(b[1]),y[w+2]=Math.round(b[2]),y[w+3]=Math.round(b[3])}s.width=h,s.height=d;let x=new ImageData(y,h,d);return c.putImageData(x,0,0),r}var XW={kernelName:yp,backendName:"cpu",kernelFunc:qW};function Kp(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;Ie(r,"sum");let o;r.dtype==="bool"?o=is({inputs:{x:r},backend:a,attrs:{dtype:"int32"}}):o=rr({inputs:{x:r},backend:a});let l=o.shape.length,u=v.parseAxisParam(s,o.shape),p=C.getAxesPermutation(u,l),c=u,d=o;p!=null&&(d=Va({inputs:{x:o},backend:a,attrs:{perm:p}}),c=C.getInnerMostAxes(c.length,l)),C.assertAxesAreInnerMostDims("sum",c,d.shape.length);let[h,m]=C.computeOutAndReduceShapes(d.shape,c),f=C.upcastType(d.dtype,"int32"),g=xh(a,h,f),y=v.sizeFromShape(m),x=a.data.get(g.dataId).values,A=a.data.get(d.dataId).values;for(let b=0;b<x.length;++b){let w=b*y,I=0;for(let T=0;T<y;++T)I+=A[w+T];x[b]=I}if(i){let b=C.expandShapeToKeepDim(g.shape,u),w=g;g=bt({inputs:{x:g},backend:a,attrs:{shape:b}}),a.disposeIntermediateTensorInfo(w)}return a.disposeIntermediateTensorInfo(o),p!=null&&a.disposeIntermediateTensorInfo(d),g}var KW={kernelName:Go,backendName:"cpu",kernelFunc:Kp};function YW(e){let{inputs:t,backend:a,attrs:n}=e,{equation:r}=n,s=t,{allDims:i,summedDims:o,idDims:l}=C.decodeEinsumEquation(r,s.length);C.checkEinsumDimSizes(i.length,l,s);let{path:u,steps:p}=C.getEinsumComputePath(o,l),c=p.length,d=null,h=i.length,m=[];for(let f=0;f<c;++f){for(let g of p[f]){let{permutationIndices:y,expandDims:x}=C.getEinsumPermutation(h,l[g]),A;C.isIdentityPermutation(y)?A=s[g]:(A=Va({inputs:{x:s[g]},backend:a,attrs:{perm:y}}),m.push(A));let b=A.shape.slice();for(let w=0;w<x.length;++w)b.splice(x[w],0,1);v.arraysEqual(A.shape,b)||(A=bt({inputs:{x:A},backend:a,attrs:{shape:b}}),m.push(A)),d===null?d=A:(d=a0({inputs:{a:A,b:d},backend:a}),m.push(d))}f<c-1&&(u[f]>=0&&(d=Kp({inputs:{x:d},backend:a,attrs:{axis:u[f]-(i.length-h),keepDims:!1}}),m.push(d)),h--)}for(let f of m)f!==d&&a.disposeIntermediateTensorInfo(f);return d}var ZW={kernelName:xp,backendName:"cpu",kernelFunc:YW};function JW(e){let{inputs:t,backend:a}=e,{dy:n,y:r}=t;Ie([n,r],"eluGrad");let s=new Float32Array(v.sizeFromShape(r.shape)),i=a.data.get(r.dataId).values,o=a.data.get(n.dataId).values;for(let l=0;l<i.length;++l){let u=i[l];u>=0?s[l]=o[l]:s[l]=o[l]*(u+1)}return a.makeTensorInfo(r.shape,"float32",s)}var QW={kernelName:xu,backendName:"cpu",kernelFunc:JW},eB=C.ERF_P,tB=C.ERF_A1,aB=C.ERF_A2,nB=C.ERF_A3,rB=C.ERF_A4,sB=C.ERF_A5,iB=ct(Di,e=>{let t=Math.sign(e),a=Math.abs(e),n=1/(1+eB*a);return t*(1-((((sB*n+rB)*n+nB)*n+aB)*n+tB)*n*Math.exp(-a*a))}),oB={kernelName:Di,backendName:"cpu",kernelFunc:iB};function vh(e){let{inputs:t,backend:a,attrs:n}=e,{input:r}=t,{dim:s}=n,i=r.shape.length,o=r.shape.slice(),l=s;return s<0&&(v.assert(-(i+1)<=s,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+s+1),o.splice(l,0,1),bt({inputs:{x:r},backend:a,attrs:{shape:o}})}var lB={kernelName:Au,backendName:"cpu",kernelFunc:vh},uB=_t((e,t)=>e/t),S3=Kt(_i,uB),P1={kernelName:_i,backendName:"cpu",kernelFunc:S3};function hv(e,t,a){let n=e.shape,r=n[0],s=n[1],i=a.data.get(e.dataId),o=i.complexTensorInfos.real,l=i.complexTensorInfos.imag,u=[r,s],p=v.sizeFromShape(u),c=v.getTypedArrayFromDType("float32",p),d=v.getTypedArrayFromDType("float32",p);for(let g=0;g<r;g++){let y=ti({inputs:{x:o},backend:a,attrs:{begin:[g,0],size:[1,s]}}),x=ti({inputs:{x:l},backend:a,attrs:{begin:[g,0],size:[1,s]}}),A=Ja({inputs:{real:y,imag:x},backend:a}),{real:b,imag:w}=dB(A,t,a),I=C.mergeRealAndImagArrays(b,w);for(let T=0;T<s;T++){let N=C.getComplexWithIndex(I,T);c[g*s+T]=N.real,d[g*s+T]=N.imag}a.disposeIntermediateTensorInfo(y),a.disposeIntermediateTensorInfo(x),a.disposeIntermediateTensorInfo(A)}let h=a.makeTensorInfo(u,"float32",c),m=a.makeTensorInfo(u,"float32",d),f=Ja({inputs:{real:h,imag:m},backend:a});return a.disposeIntermediateTensorInfo(h),a.disposeIntermediateTensorInfo(m),f}function dB(e,t,a){let n=v.sizeFromShape(e.shape),r=a.data.get(e.dataId),s=a.data.get(r.complexTensorInfos.real.dataId).values,i=a.data.get(r.complexTensorInfos.imag.dataId).values;if(pB(n)){let o=_1(s,i,n,t,a),l=[e.shape[0],e.shape[1]];if(t){let u=a.makeTensorInfo(l,"float32",o.real),p=a.makeTensorInfo(l,"float32",o.imag),c=a.makeTensorInfo([],"float32",v.createScalarValue(n,"float32")),d=rr({inputs:{x:c},backend:a}),h=P1.kernelFunc({inputs:{a:u,b:c},backend:a}),m=P1.kernelFunc({inputs:{a:p,b:d},backend:a}),f=a.data.get(h.dataId).values,g=a.data.get(m.dataId).values;return a.disposeIntermediateTensorInfo(u),a.disposeIntermediateTensorInfo(p),a.disposeIntermediateTensorInfo(c),a.disposeIntermediateTensorInfo(d),a.disposeIntermediateTensorInfo(h),a.disposeIntermediateTensorInfo(m),{real:f,imag:g}}return o}else{let o=C.mergeRealAndImagArrays(s,i),l=cB(o,n,t);return C.splitRealAndImagArrays(l)}}function pB(e){return(e&e-1)===0}function _1(e,t,a,n,r){if(a===1)return{real:e,imag:t};let s=C.mergeRealAndImagArrays(e,t),i=a/2,o=C.complexWithEvenIndex(s),l=o.real,u=o.imag,p=[l.length],c=r.makeTensorInfo(p,"float32",l),d=r.makeTensorInfo(p,"float32",u),h=Ja({inputs:{real:c,imag:d},backend:r}),m=C.complexWithOddIndex(s),f=m.real,g=m.imag,y=[f.length],x=r.makeTensorInfo(y,"float32",f),A=r.makeTensorInfo(y,"float32",g),b=Ja({inputs:{real:x,imag:A},backend:r}),w=_1(l,u,i,n,r),I=w.real,T=w.imag,N=[I.length],M=r.makeTensorInfo(N,"float32",I),$=r.makeTensorInfo(N,"float32",T),E=Ja({inputs:{real:M,imag:$},backend:r}),S=_1(f,g,i,n,r),_=S.real,O=S.imag,W=[_.length],P=r.makeTensorInfo(W,"float32",_),U=r.makeTensorInfo(W,"float32",O),G=Ja({inputs:{real:P,imag:U},backend:r}),q=C.exponents(a,n),H=[q.real.length],V=r.makeTensorInfo(H,"float32",q.real),Z=r.makeTensorInfo(H,"float32",q.imag),X=Ja({inputs:{real:V,imag:Z},backend:r}),re=a0({inputs:{a:X,b:G},backend:r}),ee=eu({inputs:{a:E,b:re},backend:r}),ge=w3({inputs:{a:E,b:re},backend:r}),ie=ei({inputs:{input:ee},backend:r}),be=ei({inputs:{input:ge},backend:r}),Ce=tu({inputs:{input:ee},backend:r}),Re=tu({inputs:{input:ge},backend:r}),Le=au({inputs:[ie,be],backend:r,attrs:{axis:0}}),qe=au({inputs:[Ce,Re],backend:r,attrs:{axis:0}}),gt=r.data.get(Le.dataId).values,dt=r.data.get(qe.dataId).values;return r.disposeIntermediateTensorInfo(c),r.disposeIntermediateTensorInfo(d),r.disposeIntermediateTensorInfo(h),r.disposeIntermediateTensorInfo(x),r.disposeIntermediateTensorInfo(A),r.disposeIntermediateTensorInfo(b),r.disposeIntermediateTensorInfo(M),r.disposeIntermediateTensorInfo($),r.disposeIntermediateTensorInfo(E),r.disposeIntermediateTensorInfo(P),r.disposeIntermediateTensorInfo(U),r.disposeIntermediateTensorInfo(G),r.disposeIntermediateTensorInfo(V),r.disposeIntermediateTensorInfo(Z),r.disposeIntermediateTensorInfo(X),r.disposeIntermediateTensorInfo(re),r.disposeIntermediateTensorInfo(ee),r.disposeIntermediateTensorInfo(ge),r.disposeIntermediateTensorInfo(ie),r.disposeIntermediateTensorInfo(Ce),r.disposeIntermediateTensorInfo(be),r.disposeIntermediateTensorInfo(Re),r.disposeIntermediateTensorInfo(Le),r.disposeIntermediateTensorInfo(qe),{real:gt,imag:dt}}function cB(e,t,a){let n=new Float32Array(t*2);for(let r=0;r<t;r++){let s=0,i=0;for(let o=0;o<t;o++){let l=C.exponent(r*o,t,a),u=C.getComplexWithIndex(e,o);s+=u.real*l.real-u.imag*l.imag,i+=u.real*l.imag+u.imag*l.real}a&&(s/=t,i/=t),C.assignToTypedArray(n,s,i,r)}return n}function hB(e){let{inputs:t,backend:a}=e,{input:n}=t,r=v.sizeFromShape(n.shape),s=n.shape[n.shape.length-1],i=r/s,o=bt({inputs:{x:n},backend:a,attrs:{shape:[i,s]}}),l=hv(o,!1,a),u=bt({inputs:{x:l},backend:a,attrs:{shape:n.shape}});return a.disposeIntermediateTensorInfo(o),a.disposeIntermediateTensorInfo(l),u}var mB={kernelName:Ap,backendName:"cpu",kernelFunc:hB};function C3(e){let{backend:t,attrs:a}=e,{shape:n,value:r,dtype:s}=a,i=s||v.inferDtype(r),o=v.getArrayFromDType(i,v.sizeFromShape(n));return gB(o,r,i),t.makeTensorInfo(n,i,o)}var fB={kernelName:bu,backendName:"cpu",kernelFunc:C3};function gB(e,t,a){e.fill(t)}var yB={kernelName:Wi,backendName:"cpu",kernelFunc:({inputs:e,attrs:t,backend:a})=>{let{image:n}=e,r=a,s=v.getTypedArrayFromDType(n.dtype,v.sizeFromShape(n.shape)),[i,o,l,u]=n.shape,p=r.data.get(n.dataId).values;for(let c=0;c<i;c++){let d=c*l*o*u;for(let h=0;h<o;h++){let m=h*(l*u);for(let f=0;f<l;f++){let g=f*u;for(let y=0;y<u;y++){let x=Math.round(l-f-1),A=d+m+g+y,b=p[A];if(x>=0&&x<l){let w=x*u,I=d+m+w+y;b=p[I]}s[A]=b}}}}return{dataId:r.write(s,n.shape,n.dtype),shape:n.shape,dtype:n.dtype}}};function xB(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dataFormat:p,dilations:c,dimRoundingMode:d,activation:h,leakyreluAlpha:m}=n,f=pv({inputs:{x:r,filter:s},backend:a,attrs:{strides:l,pad:u,dataFormat:p,dilations:c,dimRoundingMode:d}});if(i){let g=f;if(p==="NCHW"&&i.shape.length===1&&i.shape[0]!==1){let y=bt({inputs:{x:i},backend:a,attrs:{shape:[i.shape[0],1,1]}});f=eu({inputs:{a:f,b:y},backend:a}),a.disposeIntermediateTensorInfo(y)}else f=eu({inputs:{a:f,b:i},backend:a});a.disposeIntermediateTensorInfo(g)}if(h){let g=f;if(p==="NCHW"&&h==="prelu"&&o.shape.length===1&&o.shape[0]!==1){let y=bt({inputs:{x:o},backend:a,attrs:{shape:[o.shape[0],1,1]}});f=bh(a,f,h,y,m),a.disposeIntermediateTensorInfo(y)}else f=bh(a,f,h,o,m);a.disposeIntermediateTensorInfo(g)}return f}var AB={kernelName:Jr,backendName:"cpu",kernelFunc:xB};function bB(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dataFormat:p,dilations:c,dimRoundingMode:d,activation:h,leakyreluAlpha:m}=n,f=cv({inputs:{x:r,filter:s},backend:a,attrs:{strides:l,pad:u,dataFormat:p,dilations:c,dimRoundingMode:d}});if(i){let g=f;f=eu({inputs:{a:f,b:i},backend:a}),a.disposeIntermediateTensorInfo(g)}if(h){let g=f;f=bh(a,f,h,o,m),a.disposeIntermediateTensorInfo(g)}return f}var vB={kernelName:Qr,backendName:"cpu",kernelFunc:bB};function wB(e){let{inputs:t,backend:a}=e,{params:n,indices:r}=t,s=v.sizeFromShape(n.shape),i=r.shape,o=i[i.length-1],[l,u,p,c]=C.prepareAndValidate(n,r);if(u===0)return a.makeTensorInfo(l,n.dtype,[]);let d=a.data.get(r.dataId).values,h=a.bufferSync(n),m=R6(d,h,n.dtype,u,o,p,c,n.shape,s);return a.makeTensorInfo(l,n.dtype,m.values)}var kB={kernelName:Gi,backendName:"cpu",kernelFunc:wB};function IB(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,indices:s}=t,{axis:i,batchDims:o}=n;Ie([r,s],"gatherV2");let l=v.parseAxisParam(i,r.shape)[0],u=a.data.get(s.dataId).values,p=r.shape[l];for(let b=0;b<u.length;++b){let w=u[b];v.assert(w<=p-1&&w>=0,()=>`GatherV2: the index value ${w} is not in [0, ${p-1}]`)}let c=o;o==null&&(c=0);let d=v.sizeFromShape(s.shape),h=C.segment_util.collectGatherOpShapeInfo(r,s,l,c),m=bt({inputs:{x:r},backend:a,attrs:{shape:[h.batchSize,h.outerSize,h.dimSize,h.sliceSize]}}),f=bt({inputs:{x:s},backend:a,attrs:{shape:[h.batchSize,d/h.batchSize]}}),g=[h.batchSize,h.outerSize,d/h.batchSize,h.sliceSize],y=a.bufferSync(f),x=a.bufferSync(m),A=E6(x,y,g);return a.disposeIntermediateTensorInfo(m),a.disposeIntermediateTensorInfo(f),a.makeTensorInfo(h.outputShape,A.dtype,A.values)}var SB={kernelName:vu,backendName:"cpu",kernelFunc:IB};function CB(e){let{inputs:t,backend:a}=e,{input:n}=t,r=v.sizeFromShape(n.shape),s=n.shape[n.shape.length-1],i=r/s,o=bt({inputs:{x:n},backend:a,attrs:{shape:[i,s]}}),l=hv(o,!0,a),u=bt({inputs:{x:l},backend:a,attrs:{shape:n.shape}});return a.disposeIntermediateTensorInfo(o),a.disposeIntermediateTensorInfo(l),u}var TB={kernelName:bp,backendName:"cpu",kernelFunc:CB},NB=ct(Xi,e=>Number.isFinite(e)?1:0,"bool"),RB={kernelName:Xi,backendName:"cpu",kernelFunc:NB},EB=ct(Ki,e=>Math.abs(e)===1/0?1:0,"bool"),MB={kernelName:Ki,backendName:"cpu",kernelFunc:EB},$B=ct(Yi,e=>Number.isNaN(e)?1:0,"bool"),PB={kernelName:Yi,backendName:"cpu",kernelFunc:$B};function _B(e){let{backend:t,attrs:a}=e,{start:n,stop:r,num:s}=a,i=F6(n,r,s);return t.makeTensorInfo([i.length],"float32",i)}var FB={kernelName:eo,backendName:"cpu",kernelFunc:_B},DB=ct(ao,e=>Math.log1p(e)),OB={kernelName:ao,backendName:"cpu",kernelFunc:DB},zB=_t((e,t)=>e&&t),LB=Kt(no,zB,null,"bool"),WB={kernelName:no,backendName:"cpu",kernelFunc:LB},BB=ct(ro,e=>e?0:1,"bool"),VB={kernelName:ro,backendName:"cpu",kernelFunc:BB},UB=_t((e,t)=>e||t),GB=Kt(so,UB,null,"bool"),HB={kernelName:so,backendName:"cpu",kernelFunc:GB};function jB(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=n;Ie(r,"LRN");let u=r.shape[3],p=u-1,c=a.data.get(r.dataId).values,d=v.sizeFromShape(r.shape),h=new Float32Array(d);function m(f){let g=f%u,y=f-g+Math.max(0,g-s),x=f-g+Math.min(g+s,p),A=0;for(;y<=x;y++){let b=c[y];A+=b*b}return A}for(let f=0;f<d;f++){let g=m(f),y=c[f]*Math.pow(i+o*g,-l);h[f]=y}return a.makeTensorInfo(r.shape,r.dtype,h)}var qB={kernelName:io,backendName:"cpu",kernelFunc:jB};function XB(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:u,beta:p}=n;Ie(i,"LRNGrad");let c=v.sizeFromShape(i.shape),d=i.shape[3],h=a.data.get(i.dataId).values,m=a.data.get(r.dataId).values,f=a.data.get(s.dataId).values,g=new Float32Array(c),y=c;for(let x=0;x<y;x++){let A=x%d,b=x-A+Math.max(0,A-o),w=x-A+Math.min(d,A+o+1),I=0;for(let T=b;T<w;T++)I+=Math.pow(m[T],2);I=u*I+l;for(let T=b;T<w;T++){let N=-2*u*p*m[T]*f[x]/I;x===T&&(N+=Math.pow(I,-p)),N*=h[x],g[T]+=N}}return a.makeTensorInfo(i.shape,r.dtype,g)}var KB={kernelName:wu,backendName:"cpu",kernelFunc:XB};function mv(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{reductionIndices:s,keepDims:i}=n,o=a,l=r.shape,u=l.length,p=v.parseAxisParam(s,l),c=p,d=C.getAxesPermutation(c,u),h=o.data.get(r.dataId).values;if(d!=null){let b=new Array(u);for(let w=0;w<b.length;w++)b[w]=l[d[w]];h=g3(h,l,r.dtype,d,b),c=C.getInnerMostAxes(c.length,u),l=b}Ie(r,"max"),C.assertAxesAreInnerMostDims("max",c,u);let[m,f]=C.computeOutAndReduceShapes(l,c),g=v.sizeFromShape(f),y=O6(h,g,m,r.dtype),x=o.write(y,m,r.dtype),A=m;return i&&(A=C.expandShapeToKeepDim(m,p)),{dataId:x,shape:A,dtype:r.dtype}}var YB={kernelName:oo,backendName:"cpu",kernelFunc:mv};function ZB(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t;Ie(r,"maxPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=n,u=1;v.assert(C.eitherStridesOrDilationsAreOne(i,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let p=C.computePool2DInfo(r.shape,s,i,u,o,l),c;if(p.filterWidth===1&&p.filterHeight===1&&v.arraysEqual(p.inShape,p.outShape))c=rr({inputs:{x:r},backend:a});else{let d=a.data.get(r.dataId).values,h=v.computeStrides(r.shape),m=I3(d,r.shape,r.dtype,h,p,"max");c=a.makeTensorInfo(p.outShape,r.dtype,m.values)}return c}var JB={kernelName:uo,backendName:"cpu",kernelFunc:ZB};function QB(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:u}=n;Ie(r,"maxPool3d");let p=C.computePool3DInfo(r.shape,s,i,1,o,l,u),c=a.data.get(r.dataId).values,d=dv(c,r.shape,r.dtype,v.computeStrides(r.shape),p,"max");return a.makeTensorInfo(d.shape,"float32",d.values)}var eV={kernelName:ku,backendName:"cpu",kernelFunc:QB};function tV(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=n;Ie([r,s],"maxPool3DGrad");let p=C.computePool3DInfo(s.shape,i,o,1,l,u),c=a.bufferSync(s),d=UL(c,p),h=p.strideDepth,m=p.strideHeight,f=p.strideWidth,g=p.dilationDepth,y=p.dilationHeight,x=p.dilationWidth,A=p.effectiveFilterDepth,b=p.effectiveFilterHeight,w=p.effectiveFilterWidth,I=A-1-p.padInfo.front,T=w-1-p.padInfo.left,N=b-1-p.padInfo.top,M=_e(s.shape,"float32"),$=a.bufferSync(r);for(let E=0;E<p.batchSize;++E)for(let S=0;S<p.inChannels;++S)for(let _=0;_<p.inDepth;++_)for(let O=0;O<p.inHeight;++O)for(let W=0;W<p.inWidth;++W){let P=_-I,U=O-N,G=W-T,q=0;for(let H=0;H<A;H+=g){let V=(P+H)/h;if(!(V<0||V>=p.outDepth||Math.floor(V)!==V))for(let Z=0;Z<b;Z+=y){let X=(U+Z)/m;if(!(X<0||X>=p.outHeight||Math.floor(X)!==X))for(let re=0;re<w;re+=x){let ee=(G+re)/f;if(ee<0||ee>=p.outWidth||Math.floor(ee)!==ee)continue;let ge=A*b*w-1-d.get(E,V,X,ee,S),ie=H*b*w+Z*w+re,be=ge===ie?1:0;if(be===0)continue;let Ce=$.get(E,V,X,ee,S);q+=Ce*be}}}M.set(q,E,_,O,W,S)}return a.makeTensorInfo(M.shape,M.dtype,M.values)}var aV={kernelName:kp,backendName:"cpu",kernelFunc:tV};function nV(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s,output:i}=t,o=s;Ie([s,i],"maxPoolGrad");let{filterSize:l,strides:u,pad:p,dimRoundingMode:c}=n,d=C.computePool2DInfo(o.shape,l,u,1,p,c),h=a.data.get(o.dataId).values,m=_e(d.outShape,o.dtype,uv(h,o.shape,o.dtype,d).values),f=d.strideHeight,g=d.strideWidth,y=d.dilationHeight,x=d.dilationWidth,A=d.effectiveFilterHeight,b=d.effectiveFilterWidth,w=b-1-d.padInfo.left,I=A-1-d.padInfo.top,T=_e(o.shape,"float32"),N=a.data.get(r.dataId).values,M=_e(r.shape,"float32",N);for(let $=0;$<d.batchSize;++$)for(let E=0;E<d.inChannels;++E)for(let S=0;S<d.inHeight;++S)for(let _=0;_<d.inWidth;++_){let O=S-I,W=_-w,P=0;for(let U=0;U<A;U+=y){let G=(O+U)/f;if(!(G<0||G>=d.outHeight||Math.floor(G)!==G))for(let q=0;q<b;q+=x){let H=(W+q)/g;if(H<0||H>=d.outWidth||Math.floor(H)!==H)continue;let V=A*b-1-m.get($,G,H,E),Z=U*b+q,X=V===Z?1:0;if(X===0)continue;let re=M.get($,G,H,E);P+=re*X}}T.set(P,$,S,_,E)}return a.makeTensorInfo(T.shape,T.dtype,T.values)}var rV={kernelName:wp,backendName:"cpu",kernelFunc:nV};function sV(e,t,a,n,r){let s=v.computeStrides(t),i=I3(e,t,a,s,r,"max"),o=uv(e,t,a,r,!0,n);return[i.values,o.values]}var iV={kernelName:Iu,backendName:"cpu",kernelFunc:({inputs:e,attrs:t,backend:a})=>{let{x:n}=e,{filterSize:r,strides:s,pad:i,includeBatchInIndex:o}=t,l=a;Ie(n,"MaxPoolWithArgmax");let u=l.data.get(n.dataId).values,p=C.computePool2DInfo(n.shape,r,s,[1,1],i),[c,d]=sV(u,n.shape,n.dtype,o,p),h=l.write(c,p.outShape,n.dtype),m=l.write(d,p.outShape,n.dtype);return[{dataId:h,shape:p.outShape,dtype:n.dtype},{dataId:m,shape:p.outShape,dtype:"int32"}]}};function oV(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n,o=v.parseAxisParam(s,r.shape),l=C.computeOutAndReduceShapes(r.shape,o)[1],u=v.sizeFromShape(l),p=[],c=a.makeTensorInfo([],"float32",new Float32Array([u]));p.push(c);let d=is({inputs:{x:r},backend:a,attrs:{dtype:"float32"}});p.push(d);let h=S3({inputs:{a:d,b:c},backend:a});p.push(h);let m=Kp({inputs:{x:h},backend:a,attrs:{axis:s,keepDims:i}});return p.forEach(f=>a.disposeIntermediateTensorInfo(f)),m}var lV={kernelName:po,backendName:"cpu",kernelFunc:oV};function uV(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;Ie(r,"min");let o=v.parseAxisParam(s,r.shape),l=o,u=C.getAxesPermutation(l,r.shape.length),p=r;u!=null&&(p=Va({inputs:{x:r},backend:a,attrs:{perm:u}}),l=C.getInnerMostAxes(l.length,r.shape.length)),C.assertAxesAreInnerMostDims("min",l,p.shape.length);let[c,d]=C.computeOutAndReduceShapes(p.shape,l),h=v.sizeFromShape(d),m=v.makeZerosTypedArray(v.sizeFromShape(c),p.dtype),f=a.data.get(p.dataId).values;for(let y=0;y<m.length;++y){let x=y*h,A=f[x];for(let b=0;b<h;++b){let w=f[x+b];(Number.isNaN(w)||w<A)&&(A=w)}m[y]=A}u!=null&&a.disposeIntermediateTensorInfo(p);let g=a.makeTensorInfo(c,p.dtype,m);if(i){let y=C.expandShapeToKeepDim(c,o),x=bt({inputs:{x:g},backend:a,attrs:{shape:y}});return a.disposeIntermediateTensorInfo(g),x}return g}var dV={kernelName:co,backendName:"cpu",kernelFunc:uV};function pV(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{paddings:s,mode:i}=n;Ie(r,"mirrorPad");let o=s.map((x,A)=>x[0]+r.shape[A]+x[1]),l=s.map(x=>x[0]),u=s.map((x,A)=>x[0]+r.shape[A]),p=i==="reflect"?0:1,c=a.data.get(r.dataId).values,d=r.shape.length,h=v.computeStrides(r.shape),m=v.sizeFromShape(o),f=o.length,g=v.computeStrides(o),y=v.getTypedArrayFromDType(r.dtype,m);for(let x=0;x<m;x++){let A=v.indexToLoc(x,f,g);for(let w=0;w<f;w++)A[w]<l[w]?A[w]=l[w]*2-A[w]-p:A[w]>=u[w]&&(A[w]=(u[w]-1)*2-A[w]+p);A=A.map((w,I)=>w-l[I]);let b=v.locToIndex(A,d,h);y[x]=c[b]}return{dataId:a.write(y,o,r.dtype),shape:o,dtype:r.dtype}}var cV={kernelName:mo,backendName:"cpu",kernelFunc:pV},hV=_t((e,t)=>{let a=e%t;return e<0&&t<0||e>=0&&t>=0?a:(a+t)%t}),mV=Kt(fo,hV),fV={kernelName:fo,backendName:"cpu",kernelFunc:mV},gV=ru(mA());function fv(e){let{inputs:t,backend:a,attrs:n}=e,{logits:r}=t,{dim:s}=n,i=r.shape.length,o=s;if(o===-1&&(o=i-1),o!==i-1)throw Error(`Softmax along a non-last dimension is not yet supported. Logits was rank ${i} and dim was ${o}`);let l=v.parseAxisParam([o],r.shape),u=mv({inputs:{x:r},backend:a,attrs:{reductionIndices:l,keepDims:!1}}),p=C.expandShapeToKeepDim(u.shape,l),c=bt({inputs:{x:u},backend:a,attrs:{shape:p}}),d=w3({inputs:{a:r,b:c},backend:a}),h=S6({inputs:{x:d},backend:a}),m=Kp({inputs:{x:h},backend:a,attrs:{axis:l,keepDims:!1}}),f=bt({inputs:{x:m},backend:a,attrs:{shape:p}}),g=S3({inputs:{a:h,b:f},backend:a});return a.disposeIntermediateTensorInfo(u),a.disposeIntermediateTensorInfo(c),a.disposeIntermediateTensorInfo(d),a.disposeIntermediateTensorInfo(h),a.disposeIntermediateTensorInfo(m),a.disposeIntermediateTensorInfo(f),g}var yV={kernelName:Ho,backendName:"cpu",kernelFunc:fv};function xV(e){let{inputs:t,backend:a,attrs:n}=e,{logits:r}=t,{numSamples:s,seed:i,normalized:o}=n;Ie(r,"multinomial");let l=o?r:fv({inputs:{logits:r},backend:a,attrs:{dim:-1}}),u=l.shape[0],p=l.shape[1],c=a.data.get(l.dataId).values,d=[u,s],h=v.makeZerosTypedArray(v.sizeFromShape(d),"int32");for(let m=0;m<u;++m){let f=m*p,g=new Float32Array(p-1);g[0]=c[f];for(let A=1;A<g.length;++A)g[A]=g[A-1]+c[f+A];let y=gV.alea(i.toString()),x=m*s;for(let A=0;A<s;++A){let b=y();h[x+A]=g.length;for(let w=0;w<g.length;w++)if(b<g[w]){h[x+A]=w;break}}}return o||a.disposeIntermediateTensorInfo(l),a.makeTensorInfo(d,"int32",h)}var AV={kernelName:go,backendName:"cpu",kernelFunc:xV},bV=En.nonMaxSuppressionV3Impl;function vV(e){let{inputs:t,backend:a,attrs:n}=e,{boxes:r,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l}=n;Ie(r,"NonMaxSuppression");let u=a.data.get(r.dataId).values,p=a.data.get(s.dataId).values,{selectedIndices:c}=bV(u,p,i,o,l);return a.makeTensorInfo([c.length],"int32",new Int32Array(c))}var wV={kernelName:Ao,backendName:"cpu",kernelFunc:vV},kV=En.nonMaxSuppressionV4Impl;function IV(e){let{inputs:t,backend:a,attrs:n}=e,{boxes:r,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,padToMaxOutputSize:u}=n;Ie(r,"NonMaxSuppressionPadded");let p=a.data.get(r.dataId).values,c=a.data.get(s.dataId).values,{selectedIndices:d,validOutputs:h}=kV(p,c,i,o,l,u);return[a.makeTensorInfo([d.length],"int32",new Int32Array(d)),a.makeTensorInfo([],"int32",new Int32Array([h]))]}var SV={kernelName:Cu,backendName:"cpu",kernelFunc:IV},CV=En.nonMaxSuppressionV5Impl;function TV(e){let{inputs:t,backend:a,attrs:n}=e,{boxes:r,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,softNmsSigma:u}=n;Ie(r,"NonMaxSuppressionWithScore");let p=a.data.get(r.dataId).values,c=a.data.get(s.dataId).values,d=i,h=o,m=l,f=u,{selectedIndices:g,selectedScores:y}=CV(p,c,d,h,m,f);return[a.makeTensorInfo([g.length],"int32",new Int32Array(g)),a.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var NV={kernelName:bo,backendName:"cpu",kernelFunc:TV};function RV(e){let{inputs:t,backend:a,attrs:n}=e,{indices:r}=t,{dtype:s,depth:i,onValue:o,offValue:l}=n;Ie(r,"oneHot");let u=v.sizeFromShape(r.shape),p=new Float32Array(u*i);p.fill(l);let c=a.data.get(r.dataId).values;for(let d=0;d<u;++d)c[d]>=0&&c[d]<i&&(p[d*i+c[d]]=o);return a.makeTensorInfo([...r.shape,i],s,p)}var EV={kernelName:vo,backendName:"cpu",kernelFunc:RV};function wh(e){let{inputs:t,backend:a}=e,{x:n}=t;if(n.dtype==="string")throw new Error("zerosLike is not supported for string tensors");if(n.dtype==="complex64"){let r=ei({inputs:{input:n},backend:a}),s=wh({inputs:{x:r},backend:a}),i=tu({inputs:{input:n},backend:a}),o=wh({inputs:{x:i},backend:a}),l=Ja({inputs:{real:s,imag:o},backend:a});return a.disposeIntermediateTensorInfo(r),a.disposeIntermediateTensorInfo(s),a.disposeIntermediateTensorInfo(i),a.disposeIntermediateTensorInfo(o),l}else return C3({backend:a,attrs:{shape:n.shape,value:0,dtype:n.dtype}})}var MV={kernelName:Vu,backendName:"cpu",kernelFunc:wh};function gv(e){let{inputs:t,backend:a}=e,{x:n}=t;if(n.dtype==="string")throw new Error("onesLike is not supported for string tensors");if(n.dtype==="complex64"){let r=ei({inputs:{input:n},backend:a}),s=gv({inputs:{x:r},backend:a}),i=tu({inputs:{input:n},backend:a}),o=wh({inputs:{x:i},backend:a}),l=Ja({inputs:{real:s,imag:o},backend:a});return a.disposeIntermediateTensorInfo(r),a.disposeIntermediateTensorInfo(s),a.disposeIntermediateTensorInfo(i),a.disposeIntermediateTensorInfo(o),l}else return C3({backend:a,attrs:{shape:n.shape,value:1,dtype:n.dtype}})}var $V={kernelName:Tu,backendName:"cpu",kernelFunc:gv};function yv(e){let{inputs:t,backend:a,attrs:n}=e,{axis:r}=n;if(t.length===1)return vh({inputs:{input:t[0]},backend:a,attrs:{dim:r}});let s=t[0].shape,i=t[0].dtype;t.forEach(p=>{v.assertShapesMatch(s,p.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===p.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(p=>{let c=vh({inputs:{input:p},backend:a,attrs:{dim:r}});return o.push(c),c}),u=au({inputs:l,backend:a,attrs:{axis:r}});return o.forEach(p=>a.disposeIntermediateTensorInfo(p)),u}var PV={kernelName:Nu,backendName:"cpu",kernelFunc:yv};function _V(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{paddings:s,constantValue:i}=n;Ie(r,"pad");let o=s.map((y,x)=>y[0]+r.shape[x]+y[1]),l=s.map(y=>y[0]),u=a.data.get(r.dataId).values,p=v.sizeFromShape(r.shape),c=r.shape.length,d=v.computeStrides(r.shape),h=v.sizeFromShape(o),m=o.length,f=v.computeStrides(o),g=v.getTypedArrayFromDType(r.dtype,h);i!==0&&g.fill(i);for(let y=0;y<p;y++){let x=v.indexToLoc(y,c,d).map((b,w)=>b+l[w]),A=v.locToIndex(x,m,f);g[A]=u[y]}return{dataId:a.write(g,o,r.dtype),shape:o,dtype:r.dtype}}var xv={kernelName:wo,backendName:"cpu",kernelFunc:_V},FV=_t((e,t)=>Math.pow(e,t)),DV=Kt(ko,FV),OV={kernelName:ko,backendName:"cpu",kernelFunc:DV};function zV(e){let{inputs:t,backend:a,attrs:n}=e,{paramsNestedSplits:r,paramsDenseValues:s,indices:i}=t,{outputRaggedRank:o}=n,l=r.map(y=>a.data.get(y.dataId).values),u=r.map(y=>y.shape),p=a.data.get(s.dataId).values,c=a.data.get(i.dataId).values,[d,h,m]=U6(l,u,p,s.shape,s.dtype,c,i.shape,o),f=d.map(y=>a.makeTensorInfo([y.length],"int32",y)),g=a.makeTensorInfo(m,s.dtype,h);return f.concat([g])}var LV={kernelName:$h,backendName:"cpu",kernelFunc:zV};function WV(e){let{inputs:t,backend:a}=e,{starts:n,limits:r,deltas:s}=t,i=a.data.get(n.dataId).values,o=a.data.get(r.dataId).values,l=a.data.get(s.dataId).values,[u,p]=G6(i,n.shape,n.dtype,o,r.shape,l,s.shape),c=a.makeTensorInfo([u.length],"int32",u),d=a.makeTensorInfo([p.length],n.dtype,p);return[c,d]}var BV={kernelName:Ph,backendName:"cpu",kernelFunc:WV};function VV(e){let{inputs:t,backend:a,attrs:n}=e,{shape:r,values:s,defaultValue:i,rowPartitionTensors:o}=t,{rowPartitionTypes:l}=n,u=a.data.get(r.dataId).values,p=a.data.get(s.dataId).values,c=a.data.get(i.dataId).values,d=o.map(g=>a.data.get(g.dataId).values),h=o.map(g=>g.shape),[m,f]=H6(u,r.shape,p,s.shape,s.dtype,c,i.shape,d,h,l);return a.makeTensorInfo(m,s.dtype,f)}var UV={kernelName:_h,backendName:"cpu",kernelFunc:VV};function GV(e){let{backend:t,attrs:a}=e,{start:n,stop:r,dtype:s,step:i}=a,o=y3(n,r,i,s);return t.makeTensorInfo([o.length],s,o)}var HV={kernelName:Ru,backendName:"cpu",kernelFunc:GV},jV=ct(Co,e=>1/e),qV={kernelName:Co,backendName:"cpu",kernelFunc:jV};function XV(e){let{inputs:t,backend:a,attrs:n}=e,{images:r}=t,{alignCorners:s,halfPixelCenters:i,size:o}=n;Ie(r,"resizeBilinear");let l=v.computeStrides(r.shape),[u,p]=o,[c,d,h,m]=r.shape,f=a.data.get(r.dataId).values,g=new Float32Array(v.sizeFromShape([c,u,p,m])),y=[s&&u>1?d-1:d,s&&p>1?h-1:h],x=[s&&u>1?u-1:u,s&&p>1?p-1:p],A=0,b=y[0]/x[0],w=y[1]/x[1];for(let I=0;I<c;I++)for(let T=0;T<u;T++){let N;i?N=b*(T+.5)-.5:N=b*T;let M=Math.max(0,Math.floor(N)),$=N-M,E=Math.min(d-1,Math.ceil(N)),S=I*l[0]+M*l[1],_=I*l[0]+E*l[1];for(let O=0;O<p;O++){let W;i?W=w*(O+.5)-.5:W=w*O;let P=Math.max(0,Math.floor(W)),U=W-P,G=Math.min(h-1,Math.ceil(W)),q=S+P*l[2],H=_+P*l[2],V=S+G*l[2],Z=_+G*l[2];for(let X=0;X<m;X++){let re=f[q+X],ee=f[H+X],ge=f[V+X],ie=f[Z+X],be=re+(ge-re)*U,Ce=ee+(ie-ee)*U,Re=be+(Ce-be)*$;g[A++]=Re}}}return a.makeTensorInfo([c,u,p,m],"float32",g)}var KV={kernelName:Ro,backendName:"cpu",kernelFunc:XV};function YV(e){let{inputs:t,backend:a,attrs:n}=e,{images:r,dy:s}=t,{alignCorners:i}=n;Ie([s,r],"resizeBilinearGrad");let o=v.computeStrides(r.shape),[l,u,p,c]=r.shape,[,d,h]=s.shape,m=new Float32Array(l*u*p*c),f=[i&&d>1?u-1:u,i&&h>1?p-1:p],g=[i&&d>1?d-1:d,i&&h>1?h-1:h],y=f[0]/g[0],x=f[1]/g[1],A=a.data.get(s.dataId).values,b=0;for(let w=0;w<l;w++){let I=w*o[0];for(let T=0;T<d;T++){let N=T*y,M=Math.floor(N),$=Math.min(Math.ceil(N),u-1),E=I+M*o[1],S=I+$*o[1],_=N-M,O=1-_;for(let W=0;W<h;W++){let P=W*x,U=Math.floor(P),G=Math.min(Math.ceil(P),p-1),q=P-U,H=1-q,V=E+U*o[2],Z=E+G*o[2],X=S+U*o[2],re=S+G*o[2],ee=O*H,ge=O*q,ie=_*H,be=_*q;for(let Ce=0;Ce<c;Ce++){let Re=A[b++];m[V+Ce]+=Re*ee,m[Z+Ce]+=Re*ge,m[X+Ce]+=Re*ie,m[re+Ce]+=Re*be}}}}return a.makeTensorInfo([l,p,u,c],"float32",m)}var ZV={kernelName:$u,backendName:"cpu",kernelFunc:YV};function JV(e){let{inputs:t,backend:a,attrs:n}=e,{images:r}=t,{alignCorners:s,halfPixelCenters:i,size:o}=n;Ie(r,"resizeNearestNeighbor");let l=v.computeStrides(r.shape),[u,p]=o,[c,d,h,m]=r.shape,f=a.data.get(r.dataId).values,g=new Float32Array(c*u*p*m),y=[s&&u>1?d-1:d,s&&p>1?h-1:h],x=[s&&u>1?u-1:u,s&&p>1?p-1:p],A=y[0]/x[0],b=y[1]/x[1],w=0;for(let I=0;I<c;I++){let T=I*l[0];for(let N=0;N<u;N++){let M=i?A*(N+.5):A*N,$=Math.min(d-1,s?Math.round(M):Math.floor(M));i&&($=Math.max(0,$));let E=T+$*l[1];for(let S=0;S<p;S++){let _=i?b*(S+.5):b*S,O=Math.min(h-1,s?Math.round(_):Math.floor(_));i&&(O=Math.max(0,O));let W=E+O*l[2];for(let P=0;P<m;P++){let U=f[W+P];g[w++]=U}}}}return a.makeTensorInfo([c,u,p,m],r.dtype,g)}var QV={kernelName:No,backendName:"cpu",kernelFunc:JV};function eU(e){let{inputs:t,backend:a,attrs:n}=e,{images:r,dy:s}=t,{alignCorners:i}=n;Ie([s,r],"resizeNearestNeighborGrad");let o=v.computeStrides(r.shape),l=v.computeStrides(s.shape),[u,p,c,d]=r.shape,[,h,m]=s.shape,f=new Float32Array(u*p*c*d),g=a.data.get(s.dataId).values,y=[i&&h>1?p-1:p,i&&m>1?c-1:c],x=[i&&h>1?h-1:h,i&&m>1?m-1:m],A=y[0]/x[0],b=y[1]/x[1],w=1/A,I=1/b,T=Math.ceil(w)*2+2,N=Math.ceil(I)*2+2;for(let M=0;M<u;M++){let $=M*o[0];for(let E=0;E<p;E++){let S=$+E*o[1],_=Math.floor(E*w),O=Math.floor(_-T/2);for(let W=0;W<c;W++){let P=S+W*o[2],U=Math.floor(W*I),G=Math.floor(U-N/2);for(let q=0;q<d;q++){let H=0;for(let V=0;V<T;V++){let Z=V+O;if(Z<0||Z>=h)continue;let X=$+Z*l[1],re=Z*A,ee=Math.min(p-1,i?Math.round(re):Math.floor(re));if(E===ee)for(let ge=0;ge<N;ge++){let ie=ge+G;if(ie<0||ie>=m)continue;let be=X+ie*l[2],Ce=ie*b,Re=Math.min(c-1,i?Math.round(Ce):Math.floor(Ce));W===Re&&(H+=g[be+q])}}f[P+q]=H}}}}return a.makeTensorInfo(r.shape,r.dtype,f)}var tU={kernelName:Mu,backendName:"cpu",kernelFunc:eU};function aU(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{dims:s}=n;Ie(r,"reverse");let i=r.shape.length,o=v.parseAxisParam(s,r.shape);if(i===0)return rr({inputs:{x:r},backend:a});let l=new Vt(r.shape,r.dtype),u=a.bufferSync(r);for(let p=0;p<l.size;p++){let c=l.indexToLoc(p),d=c.slice();o.forEach(h=>d[h]=r.shape[h]-1-d[h]),l.set(u.get(...d),...c)}return a.makeTensorInfo(l.shape,l.dtype,l.values)}var nU={kernelName:Mo,backendName:"cpu",kernelFunc:aU},rU={kernelName:el,backendName:"cpu",kernelFunc:({inputs:e,attrs:t,backend:a})=>{let{image:n}=e,{radians:r,fillValue:s,center:i}=t,o=a,l=v.getTypedArrayFromDType(n.dtype,v.sizeFromShape(n.shape)),[u,p,c,d]=n.shape,[h,m]=C.getImageCenter(i,p,c),f=255,g=Math.sin(r),y=Math.cos(r),x=o.data.get(n.dataId).values;for(let A=0;A<u;A++){let b=A*c*p*d;for(let w=0;w<p;w++){let I=w*(c*d);for(let T=0;T<c;T++){let N=T*d;for(let M=0;M<d;M++){let $=[u,w,T,M],E=$[2],S=$[1],_=(E-h)*y-(S-m)*g,O=(E-h)*g+(S-m)*y;_=Math.round(_+h),O=Math.round(O+m);let W=s;if(typeof s!="number"&&(M===3?W=f:W=s[M]),_>=0&&_<c&&O>=0&&O<p){let U=O*(c*d),G=_*d,q=b+U+G+M;W=x[q]}let P=b+I+N+M;l[P]=W}}}}return{dataId:o.write(l,n.shape,n.dtype),shape:n.shape,dtype:n.dtype}}},sU=ct($o,e=>{let t=Math.floor(e);return e-t<.5?Math.floor(e):e-t>.5?Math.ceil(e):t%2===0?t:t+1}),iU={kernelName:$o,backendName:"cpu",kernelFunc:sU};function oU(e){let{inputs:t,backend:a,attrs:n}=e,{indices:r,updates:s}=t,{shape:i}=n,{sliceRank:o,numUpdates:l,sliceSize:u,strides:p,outputSize:c}=C.calculateShapes(s,r,i),d=!0,h=a.bufferSync(r),m=a.bufferSync(s),f=qs(h,m,i,c,u,l,o,p,0,d);return a.makeTensorInfo(i,f.dtype,f.values)}var lU={kernelName:_o,backendName:"cpu",kernelFunc:oU};function uU(e,t){let a=0,n=e.length,r=0;for(;a<n;)r=Math.floor((a+n)/2),e[r]<t?a=r+1:n=r;return n}function dU(e,t){let a=0,n=e.length,r=0;for(;a<n;)r=Math.floor((a+n)/2),e[r]<=t?a=r+1:n=r;return n}function pU(e,t,a,n,r,s){let i=v.getArrayFromDType("int32",a*r);for(let o=0;o<a;++o){let l=e.slice(o*n,(o+1)*n),u=o*r;for(let p=0;p<r;++p)i[u+p]=s==="left"?uU(l,t[p+u]):dU(l,t[p+u])}return i}function cU(e){let{inputs:t,backend:a,attrs:n}=e,{sortedSequence:r,values:s}=t,{side:i}=n,o=a.data.get(r.dataId).values,l=a.data.get(s.dataId).values,u=pU(o,l,r.shape[0],r.shape[1],s.shape[1],i);return a.makeTensorInfo(s.shape,"int32",u)}var hU={kernelName:Do,backendName:"cpu",kernelFunc:cU};function mU(e){let{inputs:t,backend:a}=e,{condition:n,t:r,e:s}=t;Ie([n,r,s],"select");let i=n.shape.length,o=a.data.get(n.dataId).values,l=a.data.get(r.dataId).values,u=a.data.get(s.dataId).values,p=ca(r.dtype,s.dtype),c=v.makeZerosTypedArray(v.sizeFromShape(r.shape),p),d=0,h=i===0||i>1||r.shape.length===1?1:v.sizeFromShape(r.shape.slice(1));for(let m=0;m<o.length;m++)for(let f=0;f<h;f++)o[m]===1?c[d++]=l[m]:c[d++]=u[m];return a.makeTensorInfo(r.shape,p,c)}var fU={kernelName:Pu,backendName:"cpu",kernelFunc:mU},gU=C.SELU_SCALEALPHA,yU=C.SELU_SCALE,xU=ct(Oo,e=>e>=0?yU*e:gU*(Math.exp(e)-1)),AU={kernelName:Oo,backendName:"cpu",kernelFunc:xU},bU=ct(Wo,e=>e<0?-1:e>0?1:0),vU={kernelName:Wo,backendName:"cpu",kernelFunc:bU},wU=ct(zo,e=>Math.sin(e)),kU={kernelName:zo,backendName:"cpu",kernelFunc:wU},IU=ct(Lo,e=>Math.sinh(e)),SU={kernelName:Lo,backendName:"cpu",kernelFunc:IU},CU=11920928955078125e-23,k5=Math.log(CU)+2,TU=ct(Vo,e=>{let t=e>-k5,a=e<k5,n=Math.exp(e),r;return a?r=n:t?r=e:r=Math.log(1+n),r}),NU={kernelName:Vo,backendName:"cpu",kernelFunc:TU};function RU(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockShape:s,paddings:i}=n;Ie([r],"spaceToBatchND");let o=v.sizeFromShape(s),l=[[0,0]];l.push(...i);for(let g=1+s.length;g<r.shape.length;++g)l.push([0,0]);let u=xv.kernelFunc({inputs:{x:r},backend:a,attrs:{paddings:l,constantValue:0}}),p=C.getReshaped(u.shape,s,o,!1),c=C.getPermuted(p.length,s.length,!1),d=C.getReshapedPermuted(u.shape,s,o,!1),h=bt({inputs:{x:u},backend:a,attrs:{shape:p}}),m=Va({inputs:{x:h},backend:a,attrs:{perm:c}}),f=bt({inputs:{x:m},backend:a,attrs:{shape:d}});return a.disposeIntermediateTensorInfo(u),a.disposeIntermediateTensorInfo(h),a.disposeIntermediateTensorInfo(m),f}var EU={kernelName:Fu,backendName:"cpu",kernelFunc:RU};function MU(e){let{inputs:t,backend:a}=e,{indices:n,values:r,denseShape:s,defaultValue:i}=t;if(s.shape.length!==1)throw new Error(`Dense shape must be a vector, saw:
        ${s.shape}`);if(n.shape.length!==2)throw new Error(`Indices must be a matrix, saw:
        ${n.shape}`);if(r.shape.length!==1)throw new Error(`Values must be a vector, saw:
        ${r.shape}`);if(i.shape.length!==0)throw new Error(`Default value must be a scalar, saw:
        ${i.shape}`);let o=a.data.get(n.dataId).values,l=a.data.get(r.dataId).values,u=a.data.get(s.dataId).values,p=a.data.get(i.dataId).values[0],[c,d,h,m,f]=X6(o,n.shape,n.dtype,l,r.dtype,u,p);return[a.makeTensorInfo(d,n.dtype,c),a.makeTensorInfo([d[0]],r.dtype,h),a.makeTensorInfo([m.length],"bool",new Uint8Array(m.map(g=>Number(g)))),a.makeTensorInfo([f.length],n.dtype,new Int32Array(f))]}var $U={kernelName:Sp,backendName:"cpu",kernelFunc:MU};function PU(e){let{inputs:t,backend:a}=e,{inputIndices:n,inputShape:r,newShape:s}=t;if(n.shape.length!==2)throw new Error(`Input indices should be a matrix but received shape
        ${n.shape}`);if(r.shape.length!==1)throw new Error(`Input shape should be a vector but received shape
        ${r.shape}`);if(s.shape.length!==1)throw new Error(`Target shape should be a vector but received shape ${s.shape}`);let i=Array.from(a.data.get(r.dataId).values),o=a.data.get(n.dataId).values,l=Array.from(a.data.get(s.dataId).values),[u,p,c]=K6(o,n.shape,n.dtype,i,l);return[a.makeTensorInfo(p,n.dtype,u),a.makeTensorInfo([c.length],s.dtype,new Int32Array(c))]}var _U={kernelName:Ou,backendName:"cpu",kernelFunc:PU};function FU(e){let{inputs:t,backend:a}=e,{data:n,indices:r,segmentIds:s}=t;if(n.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(r.shape.length!==1)throw new Error(`Indices should be a vector but received shape
          ${r.shape}`);if(s.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
          ${s.shape}`);if(r.shape[0]!==s.shape[0])throw new Error("segmentIds and indices should have same size.");let i=a.data.get(n.dataId).values,o=a.data.get(r.dataId).values,l=a.data.get(s.dataId).values,[u,p]=x3(i,n.shape,n.dtype,o,l,!0);return a.makeTensorInfo(p,n.dtype,u)}var DU={kernelName:zu,backendName:"cpu",kernelFunc:FU};function OU(e){let{inputs:t,backend:a}=e,{data:n,indices:r,segmentIds:s}=t;if(n.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(r.shape.length!==1)throw new Error(`Indices should be a vector but received shape
         ${r.shape}`);if(s.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
         ${s.shape}`);if(r.shape[0]!==s.shape[0])throw new Error("segmentIds and indices should have same size.");let i=a.data.get(n.dataId).values,o=a.data.get(r.dataId).values,l=a.data.get(s.dataId).values,[u,p]=x3(i,n.shape,n.dtype,o,l);return a.makeTensorInfo(p,n.dtype,u)}var zU={kernelName:Lu,backendName:"cpu",kernelFunc:OU};function LU(e){let{inputs:t,backend:a,attrs:n}=e,{sparseIndices:r,sparseValues:s,defaultValue:i}=t,{outputShape:o}=n,{sliceRank:l,numUpdates:u,sliceSize:p,strides:c,outputSize:d}=C.calculateShapes(s,r,o),h=!1,m=a.bufferSync(r),f;switch(s.dtype){case"bool":{let g=a.bufferSync(s),y=!!a.data.get(i.dataId).values[0];f=qs(m,g,o,d,p,u,l,c,y,h);break}case"float32":{let g=a.bufferSync(s),y=a.data.get(i.dataId).values[0];f=qs(m,g,o,d,p,u,l,c,y,h);break}case"int32":{let g=a.bufferSync(s),y=a.data.get(i.dataId).values[0];f=qs(m,g,o,d,p,u,l,c,y,h);break}case"string":{let g=a.bufferSync(s),y=v.decodeString(a.data.get(i.dataId).values[0]);f=qs(m,g,o,d,p,u,l,c,y,h);break}default:throw new Error(`Unsupported type ${s.dtype}`)}return a.makeTensorInfo(o,f.dtype,f.values)}var WU={kernelName:jo,backendName:"cpu",kernelFunc:LU};function BU(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{numOrSizeSplits:s,axis:i}=n,o=v.parseAxisParam(i,r.shape)[0],l=C.prepareSplitSize(r,s,o),u=new Array(r.shape.length).fill(0),p=r.shape.slice();return l.map(c=>{let d=[...p];d[o]=c;let h=ti({inputs:{x:r},backend:a,attrs:{begin:u,size:d}});return u[o]+=c,h})}var VU={kernelName:Du,backendName:"cpu",kernelFunc:BU},UU={kernelName:Cp,backendName:"cpu",kernelFunc:({inputs:e,backend:t})=>{let{x:a}=e,n=t;Ie(a,"square");let r=n.data.get(a.dataId).values,s=new Float32Array(r.length);for(let i=0;i<r.length;++i){let o=r[i];s[i]=o*o}return{dataId:n.write(s,a.shape,a.dtype),shape:a.shape,dtype:a.dtype}}},GU=ct(ps,(e,t)=>{let a=t;return isNaN(e)?NaN:e>0?1:a.alpha}),HU={kernelName:ps,backendName:"cpu",kernelFunc:GU};function jU(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{begin:s,end:i,strides:o,beginMask:l,endMask:u,ellipsisMask:p,newAxisMask:c,shrinkAxisMask:d}=n;Ie(r,"stridedSlice");let{finalShapeSparse:h,finalShape:m,isIdentity:f,sliceDim0:g,isSimpleSlice:y,begin:x,end:A,strides:b}=Nt.sliceInfo(r.shape,s,i,o,l,u,p,c,d),w;if(f)w=bt({inputs:{x:r},backend:a,attrs:{shape:m}});else if(g||y){v.assert(r.shape.length>=1,()=>`Input must have rank at least 1, got: ${r.shape.length}`);let I=Nt.computeOutShape(x,A,b),T=ti({inputs:{x:r},backend:a,attrs:{begin:x,size:I}});w=bt({inputs:{x:T},backend:a,attrs:{shape:m}}),a.disposeIntermediateTensorInfo(T)}else{let I=a.bufferSync(r),T=J6(h,I,b,x);w=a.makeTensorInfo(m,T.dtype,T.values)}return w}var qU={kernelName:Xo,backendName:"cpu",kernelFunc:jU};function XU(e){let{inputs:t,backend:a,attrs:n}=e,{separator:r,nGramWidths:s,leftPad:i,rightPad:o,padWidth:l,preserveShortSequences:u}=n,{data:p,dataSplits:c}=t,d=a.data.get(p.dataId).values,h=a.data.get(c.dataId).values,[m,f]=A3(d,h,r,s,i,o,l,u);return[a.makeTensorInfo([m.length],"string",m),a.makeTensorInfo(c.shape,"int32",f)]}var KU={kernelName:Wu,backendName:"cpu",kernelFunc:XU};function YU(e){let{inputs:t,backend:a,attrs:n}=e,{skipEmpty:r}=n,{input:s,delimiter:i}=t;if(s.dtype!=="string")throw new Error("Input must be of datatype string");if(s.shape.length!==1)throw new Error(`Input must be a vector, got shape: ${s.shape}`);if(i.shape.length!==0)throw new Error(`Delimiter must be a scalar, got shape: ${i.shape}`);let o=a.data.get(s.dataId).values,l=a.data.get(i.dataId).values[0],[u,p,c]=b3(o,l,r),d=p.length;return[a.makeTensorInfo([d,2],"int32",u),a.makeTensorInfo([d],"string",p),a.makeTensorInfo([2],"int32",new Int32Array(c))]}var ZU={kernelName:Np,backendName:"cpu",kernelFunc:YU};function JU(e){let{inputs:t,backend:a,attrs:n}=e,{numBuckets:r}=n,{input:s}=t;if(s.dtype!=="string")throw new Error("Input must be of datatype string");if(r<=0)throw new Error("Number of buckets must be at least 1");let i=a.data.get(s.dataId).values,o=v3(i,r);return a.makeTensorInfo(s.shape,"int32",o)}var QU={kernelName:Rp,backendName:"cpu",kernelFunc:JU},eG=ct(Yo,e=>Math.tan(e)),tG={kernelName:Yo,backendName:"cpu",kernelFunc:eG},aG=ct(Zo,e=>Math.tanh(e)),nG={kernelName:Zo,backendName:"cpu",kernelFunc:aG};function rG(e){let{inputs:t,backend:a}=e,{tensor:n,indices:r,updates:s}=t,{sliceRank:i,numUpdates:o,sliceSize:l,strides:u,outputSize:p}=C.calculateShapes(s,r,n.shape),c=!1,d=a.bufferSync(r),h=a.bufferSync(s),m=a.bufferSync(n),f=qs(d,h,n.shape,p,l,o,i,u,m,c);return a.makeTensorInfo(n.shape,f.dtype,f.values)}var sG={kernelName:Fo,backendName:"cpu",kernelFunc:rG};function iG(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{reps:s}=n;Ie(r,"tile");let i=ev(a.bufferSync(r),s);return a.makeTensorInfo(i.shape,i.dtype,i.values)}var oG={kernelName:ds,backendName:"cpu",kernelFunc:iG};function lG(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{k:s,sorted:i}=n;Ie(r,"topk");let o=a.data.get(r.dataId).values,[l,u]=av(o,r.shape,r.dtype,s,i);return[a.makeTensorInfo(l.shape,l.dtype,l.values),a.makeTensorInfo(u.shape,u.dtype,u.values)]}var uG={kernelName:Jo,backendName:"cpu",kernelFunc:lG};function dG(e){let{inputs:t,attrs:a,backend:n}=e,{image:r,transforms:s}=t,{interpolation:i,fillMode:o,fillValue:l,outputShape:u}=a,[p,c,d,h]=r.shape,[m,f]=u!=null?u:[c,d],g=[p,m,f,h],y=v.computeStrides(r.shape),x=y[0],A=y[1],b=y[2],w=v.computeStrides(g),I=w[0],T=w[1],N=w[2],M=v.getTypedArrayFromDType(r.dtype,v.sizeFromShape(g));M.fill(l);let $=n.data.get(r.dataId).values,E=n.data.get(s.dataId).values;for(let S=0;S<p;++S){let _=s.shape[0]===1?E:E.subarray(S*8,S*8+8);for(let O=0;O<m;++O)for(let W=0;W<f;++W)for(let P=0;P<h;++P){let U,G=_[6]*W+_[7]*O+1;if(G===0)continue;let q=(_[0]*W+_[1]*O+_[2])/G,H=(_[3]*W+_[4]*O+_[5])/G,V=I5(q,d,o),Z=I5(H,c,o);switch(i){case"nearest":U=gG($,c,d,x,A,b,S,Z,V,P,l);break;case"bilinear":U=yG($,c,d,x,A,b,S,Z,V,P,l);break;default:throw new Error(`Error in Transform: Expect 'nearest' or 'bilinear', but got ${i}`)}let X=S*I+O*T+W*N+P;M[X]=U}return n.makeTensorInfo(g,r.dtype,M)}return{dataId:n.write(M,g,r.dtype),shape:r.shape,dtype:r.dtype}}var pG={kernelName:Qo,backendName:"cpu",kernelFunc:dG};function I5(e,t,a){switch(a){case"reflect":return cG(e,t);case"wrap":return hG(e,t);case"nearest":return fG(e,t);case"constant":default:return mG(e,t)}}function cG(e,t){let a=e;if(a<0)if(t<=1)a=0;else{let n=2*t;a<n&&(a=n*Math.trunc(-a/n)+a),a=a<-t?a+n:-a-1}else if(a>t-1)if(t<=1)a=0;else{let n=2*t;a-=n*Math.trunc(a/n),a>=t&&(a=n-a-1)}return v.clamp(0,a,t-1)}function hG(e,t){let a=e;if(a<0)if(t<=1)a=0;else{let n=t-1;a+=t*(Math.trunc(-a/n)+1)}else if(a>t-1)if(t<=1)a=0;else{let n=t-1;a-=t*Math.trunc(a/n)}return v.clamp(0,a,t-1)}function mG(e,t){return e}function fG(e,t){return v.clamp(0,e,t-1)}function Nd(e,t,a,n,r,s,i,o,l,u,p){let c=i*n+o*r+l*s+u;return 0<=o&&o<t&&0<=l&&l<a?e[c]:p}function gG(e,t,a,n,r,s,i,o,l,u,p){let c=Math.round(o),d=Math.round(l);return Nd(e,t,a,n,r,s,i,c,d,u,p)}function yG(e,t,a,n,r,s,i,o,l,u,p){let c=Math.floor(o),d=Math.floor(l),h=c+1,m=d+1,f=(m-l)*Nd(e,t,a,n,r,s,i,c,d,u,p)+(l-d)*Nd(e,t,a,n,r,s,i,c,m,u,p),g=(m-l)*Nd(e,t,a,n,r,s,i,h,d,u,p)+(l-d)*Nd(e,t,a,n,r,s,i,h,m,u,p);return(h-o)*f+(o-c)*g}function xG(e){let{inputs:t,attrs:a,backend:n}=e,{axis:r}=a,{x:s}=t;Ie(s,"unique");let i=n.data.get(s.dataId).values,{outputValues:o,outputShape:l,indices:u}=k3(i,r,s.shape,s.dtype);return[n.makeTensorInfo(l,s.dtype,o),n.makeTensorInfo([u.length],"int32",u)]}var AG={kernelName:Ep,backendName:"cpu",kernelFunc:xG};function bG(e){let{inputs:t,backend:a,attrs:n}=e,{value:r}=t,{axis:s}=n;s<0&&(s+=r.shape.length);let i=r.shape.length,o=r.shape[s],l=new Array(i-1),u=0;for(let h=0;h<i;h++)h!==s&&(l[u++]=r.shape[h]);let p=new Array(i).fill(0),c=r.shape.slice();c[s]=1;let d=new Array(o);for(let h=0;h<d.length;h++){p[s]=h;let m=ti({inputs:{x:r},backend:a,attrs:{begin:p,size:c}});d[h]=bt({inputs:{x:m},backend:a,attrs:{shape:l}}),a.disposeIntermediateTensorInfo(m)}return d}var vG={kernelName:Bu,backendName:"cpu",kernelFunc:bG};function wG(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,segmentIds:s}=t,{numSegments:i}=n;Ie(r,"unsortedSegmentSum");let o=r.shape.length,l=s.shape.length,u=[],p=[],c=o-l,d=s;for(let m=0;m<c;++m){let f=vh({inputs:{input:d},backend:a,attrs:{dim:m+1}});d=f,p.push(f)}for(let m=0;m<i;++m){let f=v.createScalarValue(m,"int32"),g=a.makeTensorInfo([],"int32",f),y=k6({inputs:{a:g,b:d},backend:a}),x=is({inputs:{x:y},backend:a,attrs:{dtype:"float32"}}),A=a0({inputs:{a:x,b:r},backend:a}),b=Kp({inputs:{x:A},backend:a,attrs:{axis:0,keepDims:!1}});u.push(b),p.push(g),p.push(y),p.push(x),p.push(A),p.push(b)}let h=yv({inputs:u,backend:a,attrs:{axis:0}});return p.forEach(m=>a.disposeIntermediateTensorInfo(m)),h}var kG={kernelName:Mp,backendName:"cpu",kernelFunc:wG},IG=[yL,YO,AL,vL,az,kL,SL,TL,RL,ML,PL,FL,OL,WL,VL,HL,qL,KL,ZL,fL,QL,tW,nW,rz,sW,ez,iz,oW,ZO,uW,pW,cW,mW,gW,xW,bW,wW,IW,CW,NW,EW,$W,_W,DW,OW,LW,BW,UW,GW,HW,jW,XW,ZW,lL,QW,oz,oB,lz,lB,dz,mB,fB,yB,cz,mz,AB,vB,kB,SB,gz,xz,JO,TB,dW,RB,MB,PB,uL,bz,wz,FB,Iz,OB,WB,VB,HB,qB,KB,YB,Cz,JB,eV,aV,rV,iV,lV,dV,Nz,cV,fV,AV,Ez,$z,wV,SV,NV,_z,EV,$V,PV,xv,OV,pL,Oz,LV,BV,UV,HV,QO,P1,qV,cL,hL,mL,KV,ZV,QV,tU,nU,rU,iU,jz,lU,hU,fU,AU,Xz,vU,kU,SU,Kz,yV,NU,EU,$U,_U,DU,zU,WU,VU,Jz,UU,eL,aL,HU,qU,KU,ZU,QU,iL,KW,tG,nG,sG,oG,uG,pG,Fz,AG,vG,kG,MV];for(let e of IG)xn(e);var Av={};Ze(Av,{assertNotComplex:()=>qu,bindCanvasToFramebuffer:()=>FG,bindColorTextureToFramebuffer:()=>rh,bindTextureToProgramUniformSampler:()=>_v,bindTextureUnit:()=>Mv,bindVertexBufferToProgramAttribute:()=>F1,callAndCheck:()=>ce,canBeRepresented:()=>bv,createFragmentShader:()=>kv,createFramebuffer:()=>Ev,createProgram:()=>Iv,createStaticIndexBuffer:()=>Tv,createStaticVertexBuffer:()=>Cv,createTexture:()=>Nv,createVertexShader:()=>wv,getBatchDim:()=>ai,getExtensionOrThrow:()=>Rd,getFramebufferErrorMessage:()=>Fv,getMaxTexturesInShader:()=>Lv,getNumChannels:()=>PG,getProgramUniformLocation:()=>Pv,getProgramUniformLocationOrThrow:()=>$v,getRowsCols:()=>ni,getShapeAs3D:()=>Md,getTextureShapeFromLogicalShape:()=>Ov,getWebGLDisjointQueryTimerVersion:()=>Wv,getWebGLErrorMessage:()=>vv,getWebGLMaxTextureSize:()=>zv,hasExtension:()=>fn,isCapableOfRenderingToFloatTexture:()=>Bv,isDownloadFloatTextureEnabled:()=>Vv,isReshapeFree:()=>ep,isWebGLFenceEnabled:()=>Uv,isWebGLVersionEnabled:()=>O1,linkProgram:()=>Sv,logShaderSourceAndInfoLog:()=>N3,resetMaxTextureSize:()=>DG,resetMaxTexturesInShader:()=>OG,unbindColorTextureFromFramebuffer:()=>D1,unbindTextureUnit:()=>_G,validateFramebuffer:()=>Ed,validateProgram:()=>nh,validateTextureSize:()=>Rv});var Gs={},Yc={alpha:!1,antialias:!1,premultipliedAlpha:!1,preserveDrawingBuffer:!1,depth:!1,stencil:!1,failIfMajorPerformanceCaveat:!0};function n0(e,t){Gs[e]=t}function Bn(e,t){if(!(e in Gs)||t!=null){let n=CG(e,t);if(n!==null)Gs[e]=n;else return console.log("Could not get context for WebGL version",e),null}let a=Gs[e];return a==null||a.isContextLost()?(delete Gs[e],Bn(e)):(a.disable(a.DEPTH_TEST),a.disable(a.STENCIL_TEST),a.disable(a.BLEND),a.disable(a.DITHER),a.disable(a.POLYGON_OFFSET_FILL),a.disable(a.SAMPLE_COVERAGE),a.enable(a.SCISSOR_TEST),a.enable(a.CULL_FACE),a.cullFace(a.BACK),Gs[e])}function SG(e){if(!B().getBool("IS_SAFARI")&&typeof OffscreenCanvas!="undefined"&&e===2)return new OffscreenCanvas(300,150);if(typeof document!="undefined")return document.createElement("canvas");throw new Error("Cannot create a canvas in this context")}function CG(e,t){if(e!==1&&e!==2)throw new Error("Cannot get WebGL rendering context, WebGL is disabled.");let a=t==null?SG(e):t;return a.addEventListener("webglcontextlost",n=>{n.preventDefault(),delete Gs[e]},!1),B().getBool("SOFTWARE_WEBGL_ENABLED")&&(Yc.failIfMajorPerformanceCaveat=!1),e===1?a.getContext("webgl",Yc)||a.getContext("experimental-webgl",Yc):a.getContext("webgl2",Yc)}var Qd;(function(e){e[e.DENSE=0]="DENSE",e[e.SHARED_BATCH=1]="SHARED_BATCH"})(Qd||(Qd={}));var mn;(function(e){e[e.RENDER=0]="RENDER",e[e.UPLOAD=1]="UPLOAD",e[e.PIXELS=2]="PIXELS",e[e.DOWNLOAD=3]="DOWNLOAD"})(mn||(mn={}));var pa;(function(e){e[e.UNPACKED_FLOAT16=0]="UNPACKED_FLOAT16",e[e.UNPACKED_FLOAT32=1]="UNPACKED_FLOAT32",e[e.PACKED_4X1_UNSIGNED_BYTE=2]="PACKED_4X1_UNSIGNED_BYTE",e[e.PACKED_2X2_FLOAT32=3]="PACKED_2X2_FLOAT32",e[e.PACKED_2X2_FLOAT16=4]="PACKED_2X2_FLOAT16"})(pa||(pa={}));function Yp(e,t){return[t,e]}function TG(e,t){return e*t}function Zc(e){let t=v.sizeFromShape(e),a=Math.ceil(t/4);return v.sizeToSquarishShape(a)}function ju(e,t){return[Math.max(1,Math.ceil(t/2)),Math.max(1,Math.ceil(e/2))]}function NG(e,t){let[a,n]=ju(e,t);return a*n*4}function T3(e,t){let a=e,n,r,s,i,o,l,u,p,c,d;return B().getNumber("WEBGL_VERSION")===2?(n=a.R32F,r=a.R16F,s=a.RGBA16F,i=a.RGBA32F,o=a.RED,u=4,p=1,c=a.HALF_FLOAT,d=a.FLOAT,l=a.RGBA8):(n=e.RGBA,r=e.RGBA,s=e.RGBA,i=a.RGBA,o=e.RGBA,u=4,p=4,c=t!=null?t.HALF_FLOAT_OES:null,d=e.FLOAT,l=e.RGBA),{internalFormatFloat:n,internalFormatHalfFloat:r,internalFormatPackedHalfFloat:s,internalFormatPackedFloat:i,textureFormatFloat:o,downloadTextureFormat:l,downloadUnpackNumChannels:u,defaultNumChannels:p,textureTypeHalfFloat:c,textureTypeFloat:d}}function ce(e,t){let a=t();return B().getBool("DEBUG")&&RG(e),a}function RG(e){let t=e.getError();if(t!==e.NO_ERROR)throw new Error("WebGL Error: "+vv(e,t))}var EG=596e-10,MG=65504;function bv(e){return!!(B().getBool("WEBGL_RENDER_FLOAT32_ENABLED")||e===0||EG<Math.abs(e)&&Math.abs(e)<MG)}function vv(e,t){switch(t){case e.NO_ERROR:return"NO_ERROR";case e.INVALID_ENUM:return"INVALID_ENUM";case e.INVALID_VALUE:return"INVALID_VALUE";case e.INVALID_OPERATION:return"INVALID_OPERATION";case e.INVALID_FRAMEBUFFER_OPERATION:return"INVALID_FRAMEBUFFER_OPERATION";case e.OUT_OF_MEMORY:return"OUT_OF_MEMORY";case e.CONTEXT_LOST_WEBGL:return"CONTEXT_LOST_WEBGL";default:return`Unknown error code ${t}`}}function Rd(e,t){return $r(e,()=>e.getExtension(t),'Extension "'+t+'" not supported on this browser.')}function wv(e,t){let a=$r(e,()=>e.createShader(e.VERTEX_SHADER),"Unable to create vertex WebGLShader.");if(ce(e,()=>e.shaderSource(a,t)),ce(e,()=>e.compileShader(a)),e.getShaderParameter(a,e.COMPILE_STATUS)===!1)throw console.log(e.getShaderInfoLog(a)),new Error("Failed to compile vertex shader.");return a}function kv(e,t){let a=$r(e,()=>e.createShader(e.FRAGMENT_SHADER),"Unable to create fragment WebGLShader.");if(ce(e,()=>e.shaderSource(a,t)),ce(e,()=>e.compileShader(a)),B().get("ENGINE_COMPILE_ONLY"))return a;if(e.getShaderParameter(a,e.COMPILE_STATUS)===!1)throw N3(t,e.getShaderInfoLog(a)),new Error("Failed to compile fragment shader.");return a}var $G=/ERROR: [0-9]+:([0-9]+):/g;function N3(e,t){let a=$G.exec(t);if(a==null){console.log(`Couldn't parse line number in error: ${t}`),console.log(e);return}let n=+a[1],r=e.split(`
`),s=r.length.toString().length+2,i=r.map((c,d)=>v.rightPad((d+1).toString(),s)+c),o=0;for(let c=0;c<i.length;c++)o=Math.max(i[c].length,o);let l=i.slice(0,n-1),u=i.slice(n-1,n),p=i.slice(n);console.log(l.join(`
`)),console.log(t.split(`
`)[0]),console.log(`%c ${v.rightPad(u[0],o)}`,"border:1px solid red; background-color:#e3d2d2; color:#a61717"),console.log(p.join(`
`))}function Iv(e){return $r(e,()=>e.createProgram(),"Unable to create WebGLProgram.")}function Sv(e,t){if(ce(e,()=>e.linkProgram(t)),!B().get("ENGINE_COMPILE_ONLY")&&e.getProgramParameter(t,e.LINK_STATUS)===!1)throw console.log(e.getProgramInfoLog(t)),new Error("Failed to link vertex and fragment shaders.")}function nh(e,t){if(ce(e,()=>e.validateProgram(t)),e.getProgramParameter(t,e.VALIDATE_STATUS)===!1)throw console.log(e.getProgramInfoLog(t)),new Error("Shader program validation failed.")}function Cv(e,t){let a=$r(e,()=>e.createBuffer(),"Unable to create WebGLBuffer");return ce(e,()=>e.bindBuffer(e.ARRAY_BUFFER,a)),ce(e,()=>e.bufferData(e.ARRAY_BUFFER,t,e.STATIC_DRAW)),a}function Tv(e,t){let a=$r(e,()=>e.createBuffer(),"Unable to create WebGLBuffer");return ce(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,a)),ce(e,()=>e.bufferData(e.ELEMENT_ARRAY_BUFFER,t,e.STATIC_DRAW)),a}function PG(){return B().getNumber("WEBGL_VERSION")===2?1:4}function Nv(e){return $r(e,()=>e.createTexture(),"Unable to create WebGLTexture.")}function Rv(e,t){let a=B().getNumber("WEBGL_MAX_TEXTURE_SIZE");if(e<=0||t<=0){let n=`[${e}x${t}]`;throw new Error("Requested texture size "+n+" is invalid.")}if(e>a||t>a){let n=`[${e}x${t}]`,r=`[${a}x${a}]`;throw new Error("Requested texture size "+n+" greater than WebGL maximum on this browser / GPU "+r+".")}}function Ev(e){return $r(e,()=>e.createFramebuffer(),"Unable to create WebGLFramebuffer.")}function F1(e,t,a,n,r,s,i){let o=e.getAttribLocation(t,a);return o===-1?!1:(ce(e,()=>e.bindBuffer(e.ARRAY_BUFFER,n)),ce(e,()=>e.vertexAttribPointer(o,r,e.FLOAT,!1,s,i)),ce(e,()=>e.enableVertexAttribArray(o)),!0)}function Mv(e,t,a){Dv(e,a),ce(e,()=>e.activeTexture(e.TEXTURE0+a)),ce(e,()=>e.bindTexture(e.TEXTURE_2D,t))}function _G(e,t){Dv(e,t),ce(e,()=>e.activeTexture(e.TEXTURE0+t)),ce(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function $v(e,t,a){return $r(e,()=>e.getUniformLocation(t,a),'uniform "'+a+'" not present in program.')}function Pv(e,t,a){return e.getUniformLocation(t,a)}function _v(e,t,a,n){ce(e,()=>Mv(e,t,n)),ce(e,()=>e.uniform1i(a,n))}function FG(e){ce(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),ce(e,()=>e.viewport(0,0,e.canvas.width,e.canvas.height)),ce(e,()=>e.scissor(0,0,e.canvas.width,e.canvas.height))}function rh(e,t,a){ce(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,a)),ce(e,()=>e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,t,0))}function D1(e,t){ce(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,t)),ce(e,()=>e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,null,0))}function Ed(e){let t=e.checkFramebufferStatus(e.FRAMEBUFFER);if(t!==e.FRAMEBUFFER_COMPLETE)throw new Error("Error binding framebuffer: "+Fv(e,t))}function Fv(e,t){switch(t){case e.FRAMEBUFFER_INCOMPLETE_ATTACHMENT:return"FRAMEBUFFER_INCOMPLETE_ATTACHMENT";case e.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT:return"FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT";case e.FRAMEBUFFER_INCOMPLETE_DIMENSIONS:return"FRAMEBUFFER_INCOMPLETE_DIMENSIONS";case e.FRAMEBUFFER_UNSUPPORTED:return"FRAMEBUFFER_UNSUPPORTED";default:return`unknown error ${t}`}}function $r(e,t,a){let n=ce(e,()=>t());if(n==null)throw new Error(a);return n}function Dv(e,t){let a=e.MAX_COMBINED_TEXTURE_IMAGE_UNITS-1,n=t+e.TEXTURE0;if(n<e.TEXTURE0||n>a){let r=`[gl.TEXTURE0, gl.TEXTURE${a}]`;throw new Error(`textureUnit must be in ${r}.`)}}function ai(e,t=2){return v.sizeFromShape(e.slice(0,e.length-t))}function ni(e){if(e.length===0)throw Error("Cannot get rows and columns of an empty shape array.");return[e.length>1?e[e.length-2]:1,e[e.length-1]]}function Md(e){let t=[1,1,1];return e.length===0||e.length===1&&e[0]===1||(t=[ai(e),...ni(e)]),t}function Ov(e,t=!1){let a=B().getNumber("WEBGL_MAX_TEXTURE_SIZE"),n=B().getNumber("WEBGL_MAX_SIZE_FOR_NARROW_TEXTURE");n===1/0&&B().getBool("WEBGL_AUTO_SQUARIFY_NARROW_TEXTURE_SHAPE")&&(n=a/2),t&&(a=a*2,n=n*2,e=e.map((o,l)=>l>=e.length-2?v.nearestLargerEven(e[l]):e[l]),e.length===1&&(e=[2,e[0]])),e.length!==2&&(e=v.squeezeShape(e).newShape);let r=v.sizeFromShape(e),s=null;e.length<=1&&r<=a?s=[1,r]:e.length===2&&e[0]<=a&&e[1]<=a?s=e:e.length===3&&e[0]*e[1]<=a&&e[2]<=a?s=[e[0]*e[1],e[2]]:e.length===3&&e[0]<=a&&e[1]*e[2]<=a?s=[e[0],e[1]*e[2]]:e.length===4&&e[0]*e[1]*e[2]<=a&&e[3]<=a?s=[e[0]*e[1]*e[2],e[3]]:e.length===4&&e[0]<=a&&e[1]*e[2]*e[3]<=a&&(s=[e[0],e[1]*e[2]*e[3]]);let i=s!=null&&Math.max(...s)>n&&Math.min(...s)<=(t?2:1)&&Math.min(...s)>0;if(s==null||i)if(t){let o=ai(e),l=2,u=2;e.length&&([l,u]=ni(e)),r=o*(l/2)*(u/2),s=v.sizeToSquarishShape(r).map(p=>p*2)}else s=v.sizeToSquarishShape(r);return s}function Jc(e){return e%2===0}function ep(e,t){if(e=e.slice(-2),t=t.slice(-2),v.arraysEqual(e,t)||!e.length||!t.length||e[0]===0||e[1]===0||t[0]===0||t[1]===0)return!0;if(e.length!==t.length){let a=e[e.length-1],n=t[t.length-1];if(a===n||Jc(a)&&Jc(n)&&(e[0]===1||t[0]===1))return!0}return e[1]===t[1]&&Jc(e[0])&&Jc(t[0])}var sh,ih;function zv(e){if(sh==null){let t=Bn(e);sh=t.getParameter(t.MAX_TEXTURE_SIZE)}return sh}function DG(){sh=null}function OG(){ih=null}function Lv(e){if(ih==null){let t=Bn(e);ih=t.getParameter(t.MAX_TEXTURE_IMAGE_UNITS)}return Math.min(16,ih)}function Wv(e){if(e===0)return 0;let t,a=Bn(e);return fn(a,"EXT_disjoint_timer_query_webgl2")&&e===2?t=2:fn(a,"EXT_disjoint_timer_query")?t=1:t=0,t}function fn(e,t){return e.getExtension(t)!=null}function O1(e){try{if(Bn(e)!=null)return!0}catch(t){return console.log("Error when getting WebGL context: ",t),!1}return!1}function Bv(e){if(e===0)return!1;let t=Bn(e);if(e===1){if(!fn(t,"OES_texture_float"))return!1}else if(!fn(t,"EXT_color_buffer_float"))return!1;return z1(t)}function Vv(e){if(e===0)return!1;let t=Bn(e);if(e===1){if(!fn(t,"OES_texture_float")||!fn(t,"WEBGL_color_buffer_float"))return!1}else{if(fn(t,"EXT_color_buffer_float"))return z1(t);let a="EXT_color_buffer_half_float";if(fn(t,a)){let n=t.getExtension(a);return zG(t,n)}return!1}return z1(t)}function z1(e){let t=T3(e),a=e.createTexture();e.bindTexture(e.TEXTURE_2D,a),e.texImage2D(e.TEXTURE_2D,0,t.internalFormatFloat,1,1,0,t.textureFormatFloat,t.textureTypeFloat,null);let n=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,n),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,a,0);let r=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(a),e.deleteFramebuffer(n),r}function zG(e,t){let a=T3(e,t),n=e.createTexture();e.bindTexture(e.TEXTURE_2D,n),e.texImage2D(e.TEXTURE_2D,0,a.internalFormatHalfFloat,1,1,0,a.textureFormatFloat,a.textureTypeHalfFloat,null);let r=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,r),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,n,0);let s=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(n),e.deleteFramebuffer(r),s}function Uv(e){return e!==2?!1:Bn(e).fenceSync!=null}function qu(e,t){Array.isArray(e)||(e=[e]),e.forEach(a=>{a!=null&&v.assert(a.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the WebGL backend.`)})}var Se=B();Se.registerFlag("HAS_WEBGL",()=>Se.getNumber("WEBGL_VERSION")>0);Se.registerFlag("WEBGL_VERSION",()=>O1(2)?2:O1(1)?1:0);Se.registerFlag("WEBGL_CHECK_NUMERICAL_PROBLEMS",()=>!1);Se.registerFlag("WEBGL_BUFFER_SUPPORTED",()=>Se.get("WEBGL_VERSION")===2);Se.registerFlag("WEBGL_CPU_FORWARD",()=>!0);Se.registerFlag("WEBGL_FORCE_F16_TEXTURES",()=>!1);Se.registerFlag("WEBGL_PACK",()=>Se.getBool("HAS_WEBGL"));Se.registerFlag("WEBGL_PACK_NORMALIZATION",()=>Se.getBool("WEBGL_PACK"));Se.registerFlag("WEBGL_PACK_CLIP",()=>Se.getBool("WEBGL_PACK"));Se.registerFlag("WEBGL_PACK_DEPTHWISECONV",()=>Se.getBool("WEBGL_PACK"));Se.registerFlag("WEBGL_PACK_BINARY_OPERATIONS",()=>Se.getBool("WEBGL_PACK"));Se.registerFlag("WEBGL_PACK_UNARY_OPERATIONS",()=>Se.getBool("WEBGL_PACK"));Se.registerFlag("WEBGL_PACK_ARRAY_OPERATIONS",()=>Se.getBool("WEBGL_PACK"));Se.registerFlag("WEBGL_PACK_IMAGE_OPERATIONS",()=>Se.getBool("WEBGL_PACK"));Se.registerFlag("WEBGL_PACK_REDUCE",()=>Se.getBool("WEBGL_PACK"));Se.registerFlag("WEBGL_LAZILY_UNPACK",()=>Se.getBool("WEBGL_PACK"));Se.registerFlag("WEBGL_CONV_IM2COL",()=>Se.getBool("WEBGL_PACK"));Se.registerFlag("WEBGL_PACK_CONV2DTRANSPOSE",()=>Se.getBool("WEBGL_PACK"));Se.registerFlag("WEBGL_MAX_TEXTURE_SIZE",()=>zv(Se.getNumber("WEBGL_VERSION")));Se.registerFlag("WEBGL_MAX_TEXTURES_IN_SHADER",()=>Lv(Se.getNumber("WEBGL_VERSION")));Se.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION",()=>{let e=Se.getNumber("WEBGL_VERSION");return e===0?0:Wv(e)});Se.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE",()=>Se.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0&&!Fp.isMobile());Se.registerFlag("WEBGL_RENDER_FLOAT32_CAPABLE",()=>Bv(Se.getNumber("WEBGL_VERSION")));Se.registerFlag("WEBGL_RENDER_FLOAT32_ENABLED",()=>Se.getBool("WEBGL_FORCE_F16_TEXTURES")?!1:Se.getBool("WEBGL_RENDER_FLOAT32_CAPABLE"));Se.registerFlag("WEBGL_DOWNLOAD_FLOAT_ENABLED",()=>Vv(Se.getNumber("WEBGL_VERSION")));Se.registerFlag("WEBGL_FENCE_API_ENABLED",()=>Uv(Se.getNumber("WEBGL_VERSION")));Se.registerFlag("WEBGL_SIZE_UPLOAD_UNIFORM",()=>Se.getBool("WEBGL_RENDER_FLOAT32_ENABLED")?4:0);Se.registerFlag("WEBGL_DELETE_TEXTURE_THRESHOLD",()=>-1,e=>{if(typeof e!="number")throw new Error(`WEBGL_DELETE_TEXTURE_THRESHOLD must be a number but got ${e}.`);if(e<0&&e!==-1)throw new Error(`WEBGL_DELETE_TEXTURE_THRESHOLD must be -1 (indicating never delete) or at least 0, but got ${e}.`)});Se.registerFlag("WEBGL_FLUSH_THRESHOLD",()=>Fp.isMobile()?1:-1,e=>{if(typeof e!="number")throw new Error(`WEBGL_FLUSH_THRESHOLD must be a number but got ${e}.`);if(e<0&&e!==-1)throw new Error(`WEBGL_FLUSH_THRESHOLD must be -1 (indicating never manual flush) or at least 0, but got ${e}.`)});Se.registerFlag("CPU_HANDOFF_SIZE_THRESHOLD",()=>128);Se.registerFlag("WEBGL_USE_SHAPES_UNIFORMS",()=>!1);Se.registerFlag("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD",()=>1e5);Se.registerFlag("TOPK_K_CPU_HANDOFF_THRESHOLD",()=>128);Se.registerFlag("WEBGL_EXP_CONV",()=>!1);Se.registerFlag("SOFTWARE_WEBGL_ENABLED",()=>Se.getBool("IS_TEST"));Se.registerFlag("WEBGL_MAX_SIZE_FOR_NARROW_TEXTURE",()=>1/0);Se.registerFlag("WEBGL_AUTO_SQUARIFY_NARROW_TEXTURE_SHAPE",()=>!1);Se.registerFlag("WEBGL2_ISNAN_CUSTOM",()=>!1);Se.registerFlag("ENGINE_COMPILE_ONLY",()=>!1);function Ra(){let e,t,a,n,r,s,i,o,l,u;return B().getNumber("WEBGL_VERSION")===2?(e="#version 300 es",t="in",a="out",n="in",r="texture",s="outputColor",i="out vec4 outputColor;",o=B().getBool("WEBGL2_ISNAN_CUSTOM")?`
      bool isnan_custom(float val) {
        uint floatToUint = floatBitsToUint(val);
        return (floatToUint & 0x7fffffffu) > 0x7f800000u;
      }

      bvec4 isnan_custom(vec4 val) {
        return bvec4(isnan_custom(val.x),
          isnan_custom(val.y), isnan_custom(val.z), isnan_custom(val.w));
      }

      #define isnan(value) isnan_custom(value)
    `:"",l="",u=`
      #define round(value) newRound(value)
      int newRound(float value) {
        return int(floor(value + 0.5));
      }

      ivec4 newRound(vec4 value) {
        return ivec4(floor(value + vec4(0.5)));
      }
    `):(e="",t="attribute",a="varying",n="varying",r="texture2D",s="gl_FragColor",i="",o=`
      #define isnan(value) isnan_custom(value)
      bool isnan_custom(float val) {
        return (val > 0. || val < 1. || val == 0.) ? false : true;
      }
      bvec4 isnan_custom(vec4 val) {
        return bvec4(isnan(val.x), isnan(val.y), isnan(val.z), isnan(val.w));
      }
    `,l=`
      uniform float INFINITY;

      bool isinf(float val) {
        return abs(val) == INFINITY;
      }
      bvec4 isinf(vec4 val) {
        return equal(abs(val), vec4(INFINITY));
      }
    `,u=`
      int round(float value) {
        return int(floor(value + 0.5));
      }

      ivec4 round(vec4 value) {
        return ivec4(floor(value + vec4(0.5)));
      }
    `),{version:e,attribute:t,varyingVs:a,varyingFs:n,texture2D:r,output:s,defineOutput:i,defineSpecialNaN:o,defineSpecialInf:l,defineRound:u}}function rl(e,t,a="index"){let n=v.computeStrides(t);return n.map((r,s)=>{let i=`int ${e[s]} = ${a} / ${r}`,o=s===n.length-1?`int ${e[s+1]} = ${a} - ${e[s]} * ${r}`:`index -= ${e[s]} * ${r}`;return`${i}; ${o};`}).join("")}function r0(e,t,a="index"){let n=v.computeStrides(t);return n.map((r,s)=>{let i=`int ${e[s]} = ${a} / outShapeStrides[${s}]`,o=s===n.length-1?`int ${e[s+1]} = ${a} - ${e[s]} * outShapeStrides[${s}]`:`index -= ${e[s]} * outShapeStrides[${s}]`;return`${i}; ${o};`}).join("")}function LG(e,t){let a=e.length,n=e.map(s=>`${t}[${s}]`),r=new Array(a-1);r[a-2]=n[a-1];for(let s=a-3;s>=0;--s)r[s]=`(${r[s+1]} * ${n[s+1]})`;return r}function WG(e,t,a="index"){let n=e.map((s,i)=>i),r=LG(n,t);return r.map((s,i)=>{let o=`int ${e[i]} = ${a} / ${r[i]}`,l=i===r.length-1?`int ${e[i+1]} = ${a} - ${e[i]} * ${r[i]}`:`index -= ${e[i]} * ${r[i]}`;return`${o}; ${l};`}).join("")}function R3(e){let t=v.computeStrides(e).map(a=>a.toString());return`
  int getFlatIndex(ivec3 coords) {
    return coords.x * ${t[0]} + coords.y * ${t[1]} + coords.z;
  }
`}function E3(){return`
  int getFlatIndex(ivec3 coords) {
    return coords.x * outShapeStrides[0] + coords.y * outShapeStrides[1] + coords.z;
  }
`}var Gv=`
  const float FLOAT_MAX = 1.70141184e38;
  const float FLOAT_MIN = 1.17549435e-38;

  lowp vec4 encode_float(highp float v) {
    if (isnan(v)) {
      return vec4(255, 255, 255, 255);
    }

    highp float av = abs(v);

    if(av < FLOAT_MIN) {
      return vec4(0.0, 0.0, 0.0, 0.0);
    } else if(v > FLOAT_MAX) {
      return vec4(0.0, 0.0, 128.0, 127.0) / 255.0;
    } else if(v < -FLOAT_MAX) {
      return vec4(0.0, 0.0,  128.0, 255.0) / 255.0;
    }

    highp vec4 c = vec4(0,0,0,0);

    highp float e = floor(log2(av));
    highp float m = exp2(fract(log2(av))) - 1.0;

    c[2] = floor(128.0 * m);
    m -= c[2] / 128.0;
    c[1] = floor(32768.0 * m);
    m -= c[1] / 32768.0;
    c[0] = floor(8388608.0 * m);

    highp float ebias = e + 127.0;
    c[3] = floor(ebias / 2.0);
    ebias -= c[3] * 2.0;
    c[2] += floor(ebias) * 128.0;

    c[3] += 128.0 * step(0.0, -v);

    return c / 255.0;
  }
`,{getBroadcastDims:Hv}=C;function BG(e,t,a){let n=[];if(e.forEach(d=>{let h=v.sizeFromShape(d.shapeInfo.logicalShape);if(d.shapeInfo.isUniform?n.push(`uniform float ${d.name}${h>1?`[${h}]`:""};`):(n.push(`uniform sampler2D ${d.name};`),n.push(`uniform int offset${d.name};`)),a.enableShapeUniforms){let{uniformShape:m}=M3(a.packedInputs,d.shapeInfo.logicalShape,d.shapeInfo.texShape);switch(m.length){case 1:n.push(`uniform int ${d.name}Shape;`);break;case 2:n.push(`uniform ivec2 ${d.name}Shape;`);break;case 3:n.push(`uniform ivec3 ${d.name}Shape;`);break;case 4:n.push(`uniform ivec4 ${d.name}Shape;`);break;default:break}n.push(`uniform ivec2 ${d.name}TexShape;`)}}),a.enableShapeUniforms){switch(t.logicalShape.length){case 1:n.push("uniform int outShape;");break;case 2:n.push("uniform ivec2 outShape;"),n.push("uniform int outShapeStrides;");break;case 3:n.push("uniform ivec3 outShape;"),n.push("uniform ivec2 outShapeStrides;");break;case 4:n.push("uniform ivec4 outShape;"),n.push("uniform ivec3 outShapeStrides;");break;default:break}n.push("uniform ivec2 outTexShape;")}a.customUniforms&&a.customUniforms.forEach(d=>{n.push(`uniform ${d.type} ${d.name}${d.arrayIndex?`[${d.arrayIndex}]`:""};`)});let r=n.join(`
`),s=e.map(d=>VG(d,t,a.packedInputs,a.enableShapeUniforms)).join(`
`),i=t.texShape,o=Ra(),l=HG(o),u,p,c=XG(o);return t.isPacked?(u=UG(t.logicalShape,i,a.enableShapeUniforms),p=qG(o)):(u=GG(t.logicalShape,i,a.enableShapeUniforms),p=jG(o)),a.packedInputs&&(c+=JG),[c,l,p,r,u,s,a.userCode].join(`
`)}function Xu(e,t=!1){let a=e.shapeInfo.logicalShape;switch(a.length){case 0:return dH(e,t);case 1:return cH(e,t);case 2:return mH(e,t);case 3:return gH(e,t);case 4:return xH(e,t);case 5:return AH(e);case 6:return bH(e);default:throw new Error(`${a.length}-D input sampling is not yet supported`)}}function jv(e,t){switch(e.shapeInfo.logicalShape.length){case 0:return uH(e);case 1:return pH(e,t);case 2:return hH(e,t);case 3:return fH(e,t);default:return yH(e,t)}}function VG(e,t,a=!1,n){let r="";a?r+=jv(e,n):r+=Xu(e,n);let s=e.shapeInfo.logicalShape,i=t.logicalShape;return s.length<=i.length&&(a?r+=vH(e,t):r+=wH(e,t)),r}function UG(e,t,a){switch(e.length){case 0:return qv();case 1:return QG(e,t,a);case 2:return oH(e,t,a);case 3:return tH(e,t,a);default:return nH(e,t,a)}}function GG(e,t,a){switch(e.length){case 0:return qv();case 1:return eH(e,t,a);case 2:return lH(e,t,a);case 3:return aH(e,t,a);case 4:return rH(e,t,a);case 5:return sH(e,t);case 6:return iH(e,t);default:throw new Error(`${e.length}-D output sampling is not yet supported`)}}function HG(e){return`
    float sampleTexture(sampler2D textureSampler, vec2 uv) {
      return ${e.texture2D}(textureSampler, uv).r;
    }
  `}function jG(e){return`
    void setOutput(float val) {
      ${e.output} = vec4(val, 0, 0, 0);
    }
  `}function qG(e){return`
    void setOutput(vec4 val) {
      ${e.output} = val;
    }
  `}function XG(e){return`${e.version}
    precision highp float;
    precision highp int;
    precision highp sampler2D;
    ${e.varyingFs} vec2 resultUV;
    ${e.defineOutput}
    const vec2 halfCR = vec2(0.5, 0.5);

    struct ivec5
    {
      int x;
      int y;
      int z;
      int w;
      int u;
    };

    struct ivec6
    {
      int x;
      int y;
      int z;
      int w;
      int u;
      int v;
    };

    uniform float NAN;
    ${e.defineSpecialNaN}
    ${e.defineSpecialInf}
    ${e.defineRound}

    int imod(int x, int y) {
      return x - y * (x / y);
    }

    int idiv(int a, int b, float sign) {
      int res = a / b;
      int mod = imod(a, b);
      if (sign < 0. && mod != 0) {
        res -= 1;
      }
      return res;
    }

    //Based on the work of Dave Hoskins
    //https://www.shadertoy.com/view/4djSRW
    #define HASHSCALE1 443.8975
    float random(float seed){
      vec2 p = resultUV * seed;
      vec3 p3  = fract(vec3(p.xyx) * HASHSCALE1);
      p3 += dot(p3, p3.yzx + 19.19);
      return fract((p3.x + p3.y) * p3.z);
    }

    ${KG}
    ${YG}
    ${ZG}
  `}var KG=`
vec2 uvFromFlat(int texNumR, int texNumC, int index) {
  int texR = index / texNumC;
  int texC = index - texR * texNumC;
  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
}
vec2 packedUVfrom1D(int texNumR, int texNumC, int index) {
  int texelIndex = index / 2;
  int texR = texelIndex / texNumC;
  int texC = texelIndex - texR * texNumC;
  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
}
`,YG=`
vec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,
  int texNumC, int row, int col) {
  int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);
  int texR = texelIndex / texNumC;
  int texC = texelIndex - texR * texNumC;
  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
}
`,ZG=`
vec2 packedUVfrom3D(int texNumR, int texNumC,
    int texelsInBatch, int texelsInLogicalRow, int b,
    int row, int col) {
  int index = b * texelsInBatch + (row / 2) * texelsInLogicalRow + (col / 2);
  int texR = index / texNumC;
  int texC = index - texR * texNumC;
  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
}
`,JG=`
  float getChannel(vec4 frag, vec2 innerDims) {
    vec2 modCoord = mod(innerDims, 2.);
    return modCoord.x == 0. ?
      (modCoord.y == 0. ? frag.r : frag.g) :
      (modCoord.y == 0. ? frag.b : frag.a);
  }
  float getChannel(vec4 frag, int dim) {
    float modCoord = mod(float(dim), 2.);
    return modCoord == 0. ? frag.r : frag.g;
  }
`;function qv(){return`
    int getOutputCoords() {
      return 0;
    }
  `}function QG(e,t,a){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];return n[0]===1?a?`
      int getOutputCoords() {
        return 2 * int(resultUV.x * ceil(float(outTexShape[1]) / 2.0));
      }
    `:`
      int getOutputCoords() {
        return 2 * int(resultUV.x * ${n[1]}.0);
      }
    `:n[1]===1?a?`
      int getOutputCoords() {
        return 2 * int(resultUV.y * ceil(float(outTexShape[0]) / 2.0));
      }
    `:`
      int getOutputCoords() {
        return 2 * int(resultUV.y * ${n[0]}.0);
      }
    `:a?`
    int getOutputCoords() {
      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(packedTexShape[0], packedTexShape[1]));
      return 2 * (resTexRC.x * packedTexShape[1] + resTexRC.y);
    }
  `:`
    int getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${n[0]}, ${n[1]}));
      return 2 * (resTexRC.x * ${n[1]} + resTexRC.y);
    }
  `}function eH(e,t,a){return t[0]===1?a?`
      int getOutputCoords() {
        return int(resultUV.x * float(outTexShape[1]));
      }
    `:`
      int getOutputCoords() {
        return int(resultUV.x * ${t[1]}.0);
      }
    `:t[1]===1?a?`
      int getOutputCoords() {
        return int(resultUV.y * float(outTexShape[0]));
      }
    `:`
      int getOutputCoords() {
        return int(resultUV.y * ${t[0]}.0);
      }
    `:a?`
    int getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(outTexShape[0], outTexShape[1]));
      return resTexRC.x * outTexShape[1] + resTexRC.y;
    }
  `:`
    int getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${t[0]}, ${t[1]}));
      return resTexRC.x * ${t[1]} + resTexRC.y;
    }
  `}function tH(e,t,a){if(a)return`
    ivec3 getOutputCoords() {
      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
      int texelsInLogicalRow = int(ceil(float(outShape[2]) / 2.0));
      int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[1]) / 2.0));
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(packedTexShape[0], packedTexShape[1]));
      int index = resTexRC.x * packedTexShape[1] + resTexRC.y;

      int b = index / texelsInBatch;
      index -= b * texelsInBatch;

      int r = 2 * (index / texelsInLogicalRow);
      int c = imod(index, texelsInLogicalRow) * 2;

      return ivec3(b, r, c);
    }
  `;let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[2]/2),s=r*Math.ceil(e[1]/2);return`
    ivec3 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${n[0]}, ${n[1]}));
      int index = resTexRC.x * ${n[1]} + resTexRC.y;

      int b = index / ${s};
      index -= b * ${s};

      int r = 2 * (index / ${r});
      int c = imod(index, ${r}) * 2;

      return ivec3(b, r, c);
    }
  `}function aH(e,t,a){if(a)return`
  ivec3 getOutputCoords() {
    ivec2 resTexRC = ivec2(resultUV.yx *
                           vec2(outTexShape[0], outTexShape[1]));
    int index = resTexRC.x * outTexShape[1] + resTexRC.y;
    ${r0(["r","c","d"],e)}
    return ivec3(r, c, d);
  }
`;let n=rl(["r","c","d"],e);return`
    ivec3 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${t[0]}, ${t[1]}));
      int index = resTexRC.x * ${t[1]} + resTexRC.y;
      ${n}
      return ivec3(r, c, d);
    }
  `}function nH(e,t,a){if(a)return`
    ivec4 getOutputCoords() {
      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(packedTexShape[0], packedTexShape[1]));
      int index = resTexRC.x * packedTexShape[1] + resTexRC.y;

      int texelsInLogicalRow = int(ceil(float(outShape[3]) / 2.0));
      int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[2]) / 2.0));
      int texelsInBatchN = texelsInBatch * outShape[1];

      int b2 = index / texelsInBatchN;
      index -= b2 * texelsInBatchN;

      int b = index / texelsInBatch;
      index -= b * texelsInBatch;

      int r = 2 * (index / texelsInLogicalRow);
      int c = imod(index, texelsInLogicalRow) * 2;

      return ivec4(b2, b, r, c);
    }
  `;let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[e.length-1]/2),s=r*Math.ceil(e[e.length-2]/2),i=s,o="",l="b, r, c";for(let u=2;u<e.length-1;u++)i*=e[e.length-u-1],o=`
      int b${u} = index / ${i};
      index -= b${u} * ${i};
    `+o,l=`b${u}, `+l;return`
    ivec${e.length} getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${n[0]}, ${n[1]}));
      int index = resTexRC.x * ${n[1]} + resTexRC.y;

      ${o}

      int b = index / ${s};
      index -= b * ${s};

      int r = 2 * (index / ${r});
      int c = imod(index, ${r}) * 2;

      return ivec${e.length}(${l});
    }
  `}function rH(e,t,a){if(a)return`
    ivec4 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
        vec2(outTexShape[0], outTexShape[1]));
      int index = resTexRC.x * outTexShape[1] + resTexRC.y;
      ${r0(["r","c","d","d2"],e)}
      return ivec4(r, c, d, d2);
    }
  `;let n=rl(["r","c","d","d2"],e);return`
    ivec4 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
        vec2(${t[0]}, ${t[1]}));
      int index = resTexRC.x * ${t[1]} + resTexRC.y;
      ${n}
      return ivec4(r, c, d, d2);
    }
  `}function sH(e,t){let a=rl(["r","c","d","d2","d3"],e);return`
    ivec5 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx * vec2(${t[0]},
                             ${t[1]}));

      int index = resTexRC.x * ${t[1]} + resTexRC.y;

      ${a}

      ivec5 outShape = ivec5(r, c, d, d2, d3);
      return outShape;
    }
  `}function iH(e,t){let a=rl(["r","c","d","d2","d3","d4"],e);return`
    ivec6 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
        vec2(${t[0]}, ${t[1]}));
      int index = resTexRC.x * ${t[1]} + resTexRC.y;

      ${a}

      ivec6 result = ivec6(r, c, d, d2, d3, d4);
      return result;
    }
  `}function oH(e,t,a){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(v.arraysEqual(e,t))return a?`
      ivec2 getOutputCoords() {
        ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
        return 2 * ivec2(resultUV.yx * vec2(packedTexShape[0], packedTexShape[1]));
      }
    `:`
      ivec2 getOutputCoords() {
        return 2 * ivec2(resultUV.yx * vec2(${n[0]}, ${n[1]}));
      }
    `;let r=Math.ceil(e[1]/2);return a?`
    ivec2 getOutputCoords() {
      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
      int texelsInLogicalRow = int(ceil(float(outShape[1]) / 2.0));
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(packedTexShape[0], packedTexShape[1]));

      int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
      int r = 2 * (index / texelsInLogicalRow);
      int c = imod(index, texelsInLogicalRow) * 2;

      return ivec2(r, c);
    }
  `:`
    ivec2 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${n[0]}, ${n[1]}));

      int index = resTexRC.x * ${n[1]} + resTexRC.y;
      int r = 2 * (index / ${r});
      int c = imod(index, ${r}) * 2;

      return ivec2(r, c);
    }
  `}function lH(e,t,a){return v.arraysEqual(e,t)?a?`
      ivec2 getOutputCoords() {
        return ivec2(resultUV.yx * vec2(outTexShape[0], outTexShape[1]));
      }
    `:`
      ivec2 getOutputCoords() {
        return ivec2(resultUV.yx * vec2(${t[0]}, ${t[1]}));
      }
    `:e[1]===1?a?`
      ivec2 getOutputCoords() {
        ivec2 resTexRC = ivec2(resultUV.yx *
                               vec2(outTexShape[0], outTexShape[1]));
        int index = resTexRC.x * outTexShape[1] + resTexRC.y;
        return ivec2(index, 0);
      }
    `:`
      ivec2 getOutputCoords() {
        ivec2 resTexRC = ivec2(resultUV.yx *
                               vec2(${t[0]}, ${t[1]}));
        int index = resTexRC.x * ${t[1]} + resTexRC.y;
        return ivec2(index, 0);
      }
    `:e[0]===1?a?`
      ivec2 getOutputCoords() {
        ivec2 resTexRC = ivec2(resultUV.yx *
                               vec2(outTexShape[0], outTexShape[1]));
        int index = resTexRC.x * outTexShape[1] + resTexRC.y;
        return ivec2(0, index);
      }
    `:`
      ivec2 getOutputCoords() {
        ivec2 resTexRC = ivec2(resultUV.yx *
                               vec2(${t[0]}, ${t[1]}));
        int index = resTexRC.x * ${t[1]} + resTexRC.y;
        return ivec2(0, index);
      }
    `:a?`
    ivec2 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(outTexShape[0], outTexShape[1]));
      int index = resTexRC.x * outTexShape[1] + resTexRC.y;
      int r = index / outShape[1];
      int c = index - r * outShape[1];
      return ivec2(r, c);
    }
  `:`
    ivec2 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${t[0]}, ${t[1]}));
      int index = resTexRC.x * ${t[1]} + resTexRC.y;
      int r = index / ${e[1]};
      int c = index - r * ${e[1]};
      return ivec2(r, c);
    }
  `}function sl(e){return`offset${e}`}function uH(e){let t=e.name,a="get"+t.charAt(0).toUpperCase()+t.slice(1),n=Ra();return`
    vec4 ${a}() {
      return ${n.texture2D}(${t}, halfCR);
    }
  `}function dH(e,t){let a=e.name,n="get"+a.charAt(0).toUpperCase()+a.slice(1);if(e.shapeInfo.isUniform)return`float ${n}() {return ${a};}`;let[r,s]=e.shapeInfo.texShape;if(r===1&&s===1)return`
      float ${n}() {
        return sampleTexture(${a}, halfCR);
      }
    `;let i=sl(a);if(t)return`
    float ${n}() {
      vec2 uv = uvFromFlat(${a}TexShape[0], ${a}TexShape[1], ${i});
      return sampleTexture(${a}, uv);
    }
  `;let[o,l]=e.shapeInfo.texShape;return`
    float ${n}() {
      vec2 uv = uvFromFlat(${o}, ${l}, ${i});
      return sampleTexture(${a}, uv);
    }
  `}function pH(e,t){let a=e.name,n="get"+a.charAt(0).toUpperCase()+a.slice(1),r=e.shapeInfo.texShape,s=Ra();if(t)return`
    vec4 ${n}(int index) {
      ivec2 packedTexShape = ivec2(ceil(float(${a}TexShape[0]) / 2.0), ceil(float(${a}TexShape[1]) / 2.0));
      vec2 uv = packedUVfrom1D(
        packedTexShape[0], packedTexShape[1], index);
      return ${s.texture2D}(${a}, uv);
    }
  `;let i=[Math.ceil(r[0]/2),Math.ceil(r[1]/2)];return`
    vec4 ${n}(int index) {
      vec2 uv = packedUVfrom1D(
        ${i[0]}, ${i[1]}, index);
      return ${s.texture2D}(${a}, uv);
    }
  `}function cH(e,t){let a=e.name,n="get"+a.charAt(0).toUpperCase()+a.slice(1);if(e.shapeInfo.isUniform)return`
      float ${n}(int index) {
        ${Ku(e)}
      }
    `;let r=e.shapeInfo.texShape,s=r[0],i=r[1];if(i===1&&s===1)return`
      float ${n}(int index) {
        return sampleTexture(${a}, halfCR);
      }
    `;let o=sl(a);return i===1?t?`
      float ${n}(int index) {
        vec2 uv = vec2(0.5, (float(index + ${o}) + 0.5) / float(${a}TexShape[0]));
        return sampleTexture(${a}, uv);
      }
    `:`
      float ${n}(int index) {
        vec2 uv = vec2(0.5, (float(index + ${o}) + 0.5) / ${s}.0);
        return sampleTexture(${a}, uv);
      }
    `:s===1?t?`
      float ${n}(int index) {
        vec2 uv = vec2((float(index + ${o}) + 0.5) / float(${a}TexShape[1]), 0.5);
        return sampleTexture(${a}, uv);
      }
    `:`
      float ${n}(int index) {
        vec2 uv = vec2((float(index + ${o}) + 0.5) / ${i}.0, 0.5);
        return sampleTexture(${a}, uv);
      }
    `:t?`
    float ${n}(int index) {
      vec2 uv = uvFromFlat(${a}TexShape[0], ${a}TexShape[1], index + ${o});
      return sampleTexture(${a}, uv);
    }
  `:`
    float ${n}(int index) {
      vec2 uv = uvFromFlat(${s}, ${i}, index + ${o});
      return sampleTexture(${a}, uv);
    }
  `}function hH(e,t){let a=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),s=e.shapeInfo.texShape,i=s[0],o=s[1],l=Ra();if(s!=null&&v.arraysEqual(a,s))return t?`
      vec4 ${r}(int row, int col) {
        vec2 uv = (vec2(col, row) + halfCR) / vec2(${n}TexShape[1], ${n}TexShape[0]);

        return ${l.texture2D}(${n}, uv);
      }
    `:`
      vec4 ${r}(int row, int col) {
        vec2 uv = (vec2(col, row) + halfCR) / vec2(${o}.0, ${i}.0);

        return ${l.texture2D}(${n}, uv);
      }
    `;if(t)return`
    vec4 ${r}(int row, int col) {
      ivec2 packedTexShape = ivec2(ceil(float(${n}TexShape[0]) / 2.0), ceil(float(${n}TexShape[1]) / 2.0));
      int valuesPerRow = int(ceil(float(${n}Shape[1]) / 2.0));
      vec2 uv = packedUVfrom2D(valuesPerRow, packedTexShape[0], packedTexShape[1], row, col);
      return ${l.texture2D}(${n}, uv);
    }
  `;let u=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)],p=Math.ceil(a[1]/2);return`
    vec4 ${r}(int row, int col) {
      vec2 uv = packedUVfrom2D(${p}, ${u[0]}, ${u[1]}, row, col);
      return ${l.texture2D}(${n}, uv);
    }
  `}function mH(e,t){let a=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),s=e.shapeInfo.texShape;if(s!=null&&v.arraysEqual(a,s)){if(t)return`
      float ${r}(int row, int col) {
        vec2 uv = (vec2(col, row) + halfCR) / vec2(${n}TexShape[1], ${n}TexShape[0]);
        return sampleTexture(${n}, uv);
      }
    `;let d=s[0],h=s[1];return`
    float ${r}(int row, int col) {
      vec2 uv = (vec2(col, row) + halfCR) / vec2(${h}.0, ${d}.0);
      return sampleTexture(${n}, uv);
    }
  `}let{newShape:i,keptDims:o}=v.squeezeShape(a),l=i;if(l.length<a.length){let d=Yu(e,l),h=["row","col"];return`
      ${Xu(d,t)}
      float ${r}(int row, int col) {
        return ${r}(${Zu(h,o)});
      }
    `}if(e.shapeInfo.isUniform)return`
      float ${r}(int row, int col) {
        int index = round(dot(vec2(row, col), vec2(${a[1]}, 1)));
        ${Ku(e)}
      }
    `;let u=s[0],p=s[1],c=sl(n);return p===1?t?`
      float ${r}(int row, int col) {
        float index = dot(vec3(row, col, ${c}), vec3(${n}Shape[1], 1, 1));
        vec2 uv = vec2(0.5, (index + 0.5) / float(${n}TexShape[0]));
        return sampleTexture(${n}, uv);
      }
    `:`
    float ${r}(int row, int col) {
      float index = dot(vec3(row, col, ${c}), vec3(${a[1]}, 1, 1));
      vec2 uv = vec2(0.5, (index + 0.5) / ${u}.0);
      return sampleTexture(${n}, uv);
    }
  `:u===1?t?`
      float ${r}(int row, int col) {
        float index = dot(vec3(row, col, ${c}), vec3(${n}Shape[1], 1, 1));
        vec2 uv = vec2((index + 0.5) / float(${n}TexShape[1]), 0.5);
        return sampleTexture(${n}, uv);
      }
    `:`
    float ${r}(int row, int col) {
      float index = dot(vec3(row, col, ${c}), vec3(${a[1]}, 1, 1));
      vec2 uv = vec2((index + 0.5) / ${p}.0, 0.5);
      return sampleTexture(${n}, uv);
    }
  `:t?`
      float ${r}(int row, int col) {
        // Explicitly use integer operations as dot() only works on floats.
        int index = row * ${n}Shape[1] + col + ${c};
        vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], index);
        return sampleTexture(${n}, uv);
      }
    `:`
  float ${r}(int row, int col) {
    // Explicitly use integer operations as dot() only works on floats.
    int index = row * ${a[1]} + col + ${c};
    vec2 uv = uvFromFlat(${u}, ${p}, index);
    return sampleTexture(${n}, uv);
  }
`}function fH(e,t){let a=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),s=e.shapeInfo.texShape,i=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)];if(a[0]===1){let d=a.slice(1),h=[1,2],m=Yu(e,d),f=["b","row","col"];return`
        ${jv(m,t)}
        vec4 ${r}(int b, int row, int col) {
          return ${r}(${Zu(f,h)});
        }
      `}let o=Ra();if(t)return`
    vec4 ${r}(int b, int row, int col) {
      ivec2 packedTexShape = ivec2(ceil(float(${n}TexShape[0]) / 2.0), ceil(float(${n}TexShape[1]) / 2.0));
      int valuesPerRow = int(ceil(float(${n}Shape[2]) / 2.0));
      int texelsInBatch = valuesPerRow * int(ceil(float(${n}Shape[1]) / 2.0));
      vec2 uv = packedUVfrom3D(
        packedTexShape[0], packedTexShape[1], texelsInBatch, valuesPerRow, b, row, col);
      return ${o.texture2D}(${n}, uv);
    }
  `;let l=i[0],u=i[1],p=Math.ceil(a[2]/2),c=p*Math.ceil(a[1]/2);return`
    vec4 ${r}(int b, int row, int col) {
      vec2 uv = packedUVfrom3D(
        ${l}, ${u}, ${c}, ${p}, b, row, col);
      return ${o.texture2D}(${n}, uv);
    }
  `}function gH(e,t){let a=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),s=a[1]*a[2],i=a[2],{newShape:o,keptDims:l}=v.squeezeShape(a),u=o;if(u.length<a.length){let f=Yu(e,u),g=["row","col","depth"];return`
        ${Xu(f,t)}
        float ${r}(int row, int col, int depth) {
          return ${r}(${Zu(g,l)});
        }
      `}if(e.shapeInfo.isUniform)return`
      float ${r}(int row, int col, int depth) {
        int index = round(dot(vec3(row, col, depth),
                          vec3(${s}, ${i}, 1)));
        ${Ku(e)}
      }
    `;let p=e.shapeInfo.texShape,c=p[0],d=p[1],h=e.shapeInfo.flatOffset;if(d===s&&h==null)return t?`
      float ${r}(int row, int col, int depth) {
        int stride1 = ${n}Shape[2];
        float texR = float(row);
        float texC = dot(vec2(col, depth), vec2(stride1, 1));
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(${n}TexShape[1], ${n}TexShape[0]);
        return sampleTexture(${n}, uv);
      }
    `:`
        float ${r}(int row, int col, int depth) {
          float texR = float(row);
          float texC = dot(vec2(col, depth), vec2(${i}, 1));
          vec2 uv = (vec2(texC, texR) + halfCR) /
                     vec2(${d}.0, ${c}.0);
          return sampleTexture(${n}, uv);
        }
      `;if(d===i&&h==null)return t?`
      float ${r}(int row, int col, int depth) {
        float texR = dot(vec2(row, col), vec2(${n}Shape[1], 1));
        float texC = float(depth);
        vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${n}TexShape[1], ${n}TexShape[0]);
        return sampleTexture(${n}, uv);
      }
    `:`
    float ${r}(int row, int col, int depth) {
      float texR = dot(vec2(row, col), vec2(${a[1]}, 1));
      float texC = float(depth);
      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${d}.0, ${c}.0);
      return sampleTexture(${n}, uv);
    }
  `;let m=sl(n);return t?`
    float ${r}(int row, int col, int depth) {
      // Explicitly use integer operations as dot() only works on floats.
      int stride0 = ${n}Shape[1] * ${n}Shape[2];
      int stride1 = ${n}Shape[2];
      int index = row * stride0 + col * stride1 + depth + ${m};
      vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], index);
      return sampleTexture(${n}, uv);
    }
    `:`
      float ${r}(int row, int col, int depth) {
        // Explicitly use integer operations as dot() only works on floats.
        int index = row * ${s} + col * ${i} + depth + ${m};
        vec2 uv = uvFromFlat(${c}, ${d}, index);
        return sampleTexture(${n}, uv);
      }
  `}function yH(e,t){let a=e.name,n="get"+a.charAt(0).toUpperCase()+a.slice(1),r=Ra();if(t)return`
    vec4 ${n}(int b2, int b, int row, int col) {
      int valuesPerRow = int(ceil(float(${a}Shape[3]) / 2.0));
      int texelsInBatch = valuesPerRow * int(ceil(float(${a}Shape[2]) / 2.0));
      int index = b * texelsInBatch + (row / 2) * valuesPerRow + (col / 2);
      texelsInBatch *= ${a}Shape[1];
      index = b2 * texelsInBatch + index;
      ivec2 packedTexShape = ivec2(ceil(float(${a}TexShape[0]) / 2.0), ceil(float(${a}TexShape[1]) / 2.0));
      int texR = index / packedTexShape[1];
      int texC = index - texR * packedTexShape[1];
      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(packedTexShape[1], packedTexShape[0]); return ${r.texture2D}(${a}, uv);
    }
  `;let s=e.shapeInfo.logicalShape,i=s.length,o=e.shapeInfo.texShape,l=[Math.ceil(o[0]/2),Math.ceil(o[1]/2)],u=l[0],p=l[1],c=Math.ceil(s[i-1]/2),d=c*Math.ceil(s[i-2]/2),h="int b, int row, int col",m=`b * ${d} + (row / 2) * ${c} + (col / 2)`;for(let f=2;f<i-1;f++)h=`int b${f}, `+h,d*=s[i-f-1],m=`b${f} * ${d} + `+m;return`
    vec4 ${n}(${h}) {
      int index = ${m};
      int texR = index / ${p};
      int texC = index - texR * ${p};
      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${p}, ${u});
      return ${r.texture2D}(${a}, uv);
    }
  `}function xH(e,t){let a=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),s=a[3],i=a[2]*s,o=a[1]*i,{newShape:l,keptDims:u}=v.squeezeShape(a);if(l.length<a.length){let x=Yu(e,l),A=["row","col","depth","depth2"];return`
      ${Xu(x,t)}
      float ${r}(int row, int col, int depth, int depth2) {
        return ${r}(${Zu(A,u)});
      }
    `}if(e.shapeInfo.isUniform)return`
      float ${r}(int row, int col, int depth, int depth2) {
        int index = round(dot(vec4(row, col, depth, depth2),
                          vec4(${o}, ${i}, ${s}, 1)));
        ${Ku(e)}
      }
    `;let p=e.shapeInfo.flatOffset,c=e.shapeInfo.texShape,d=c[0],h=c[1],m=`int stride2 = ${n}Shape[3];`,f=`int stride1 = ${n}Shape[2] * stride2;`,g=`int stride0 = ${n}Shape[1] * stride1;`;if(h===o&&p==null)return t?`
      float ${r}(int row, int col, int depth, int depth2) {
        ${m}
        ${f}
        float texR = float(row);
        float texC =
            dot(vec3(col, depth, depth2),
                vec3(stride1, stride2, 1));
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(${n}TexShape[1], ${n}TexShape[0]);
        return sampleTexture(${n}, uv);
      }
    `:`
      float ${r}(int row, int col, int depth, int depth2) {
        float texR = float(row);
        float texC =
            dot(vec3(col, depth, depth2),
                vec3(${i}, ${s}, 1));
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(${h}.0, ${d}.0);
        return sampleTexture(${n}, uv);
      }
    `;if(h===s&&p==null)return t?`
      float ${r}(int row, int col, int depth, int depth2) {
        float texR = dot(vec3(row, col, depth),
                         vec3(${n}Shape[1] * ${n}Shape[2], ${n}Shape[2], 1));
        float texC = float(depth2);
        vec2 uv = (vec2(texC, texR) + halfCR) /
                  vec2(${n}TexShape[1], ${n}TexShape[0]);
        return sampleTexture(${n}, uv);
      }
    `:`
      float ${r}(int row, int col, int depth, int depth2) {
        float texR = dot(vec3(row, col, depth),
                         vec3(${a[1]*a[2]}, ${a[2]}, 1));
        float texC = float(depth2);
        vec2 uv = (vec2(texC, texR) + halfCR) /
                  vec2(${h}.0, ${d}.0);
        return sampleTexture(${n}, uv);
      }
    `;let y=sl(n);return t?`
    float ${r}(int row, int col, int depth, int depth2) {
      // Explicitly use integer operations as dot() only works on floats.
      ${m}
      ${f}
      ${g}
      int index = row * stride0 + col * stride1 +
          depth * stride2 + depth2;
      vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], index + ${y});
      return sampleTexture(${n}, uv);
    }
  `:`
    float ${r}(int row, int col, int depth, int depth2) {
      // Explicitly use integer operations as dot() only works on floats.
      int index = row * ${o} + col * ${i} +
          depth * ${s} + depth2;
      vec2 uv = uvFromFlat(${d}, ${h}, index + ${y});
      return sampleTexture(${n}, uv);
    }
  `}function AH(e){let t=e.shapeInfo.logicalShape,a=e.name,n="get"+a.charAt(0).toUpperCase()+a.slice(1),r=t[4],s=t[3]*r,i=t[2]*s,o=t[1]*i,{newShape:l,keptDims:u}=v.squeezeShape(t);if(l.length<t.length){let f=Yu(e,l),g=["row","col","depth","depth2","depth3"];return`
      ${Xu(f)}
      float ${n}(int row, int col, int depth, int depth2, int depth3) {
        return ${n}(${Zu(g,u)});
      }
    `}if(e.shapeInfo.isUniform)return`
      float ${n}(int row, int col, int depth, int depth2, int depth3) {
        float index = dot(
          vec4(row, col, depth, depth2),
          vec4(${o}, ${i}, ${s}, ${r})) +
          depth3;
        ${Ku(e)}
      }
    `;let p=e.shapeInfo.flatOffset,c=e.shapeInfo.texShape,d=c[0],h=c[1];if(h===o&&p==null)return`
      float ${n}(int row, int col, int depth, int depth2, int depth3) {
        int texR = row;
        float texC = dot(vec4(col, depth, depth2, depth3),
                         vec4(${i}, ${s}, ${r}, 1));
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(${h}.0, ${d}.0);
        return sampleTexture(${a}, uv);
      }
    `;if(h===r&&p==null)return`
      float ${n}(int row, int col, int depth, int depth2, int depth3) {
        float texR = dot(
          vec4(row, col, depth, depth2),
          vec4(${t[1]*t[2]*t[3]},
               ${t[2]*t[3]}, ${t[3]}, 1));
        int texC = depth3;
        vec2 uv = (vec2(texC, texR) + halfCR) /
                  vec2(${h}.0, ${d}.0);
        return sampleTexture(${a}, uv);
      }
    `;let m=sl(a);return`
    float ${n}(int row, int col, int depth, int depth2, int depth3) {
      // Explicitly use integer operations as dot() only works on floats.
      int index = row * ${o} + col * ${i} + depth * ${s} +
          depth2 * ${r} + depth3 + ${m};
      vec2 uv = uvFromFlat(${d}, ${h}, index);
      return sampleTexture(${a}, uv);
    }
  `}function bH(e){let t=e.shapeInfo.logicalShape,a=e.name,n="get"+a.charAt(0).toUpperCase()+a.slice(1),{newShape:r,keptDims:s}=v.squeezeShape(t);if(r.length<t.length){let g=Yu(e,r),y=["row","col","depth","depth2","depth3","depth4"];return`
      ${Xu(g)}
      float ${n}(int row, int col, int depth,
                    int depth2, int depth3, int depth4) {
        return ${n}(${Zu(y,s)});
      }
    `}let i=t[5],o=t[4]*i,l=t[3]*o,u=t[2]*l,p=t[1]*u;if(e.shapeInfo.isUniform)return`
      float ${n}(int row, int col, int depth,
                  int depth2, int depth3, int depth4) {
        int index = round(dot(
          vec4(row, col, depth, depth2),
          vec4(${p}, ${u}, ${l}, ${o})) +
          dot(
            vec2(depth3, depth4),
            vec2(${i}, 1)));
        ${Ku(e)}
      }
    `;let c=e.shapeInfo.flatOffset,d=e.shapeInfo.texShape,h=d[0],m=d[1];if(m===p&&c==null)return`
      float ${n}(int row, int col, int depth,
                    int depth2, int depth3, int depth4) {
        int texR = row;
        float texC = dot(vec4(col, depth, depth2, depth3),
          vec4(${u}, ${l}, ${o}, ${i})) +
               float(depth4);
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(${m}.0, ${h}.0);
        return sampleTexture(${a}, uv);
      }
    `;if(m===i&&c==null)return`
      float ${n}(int row, int col, int depth,
                    int depth2, int depth3, int depth4) {
        float texR = dot(vec4(row, col, depth, depth2),
          vec4(${t[1]*t[2]*t[3]*t[4]},
               ${t[2]*t[3]*t[4]},
               ${t[3]*t[4]},
               ${t[4]})) + float(depth3);
        int texC = depth4;
        vec2 uv = (vec2(texC, texR) + halfCR) /
                  vec2(${m}.0, ${h}.0);
        return sampleTexture(${a}, uv);
      }
    `;let f=sl(a);return`
    float ${n}(int row, int col, int depth,
                  int depth2, int depth3, int depth4) {
      // Explicitly use integer operations as dot() only works on floats.
      int index = row * ${p} + col * ${u} + depth * ${l} +
          depth2 * ${o} + depth3 * ${i} + depth4 + ${f};
      vec2 uv = uvFromFlat(${h}, ${m}, index);
      return sampleTexture(${a}, uv);
    }
  `}function Ku(e){let t=e.name,a=v.sizeFromShape(e.shapeInfo.logicalShape);return a<2?`return ${t};`:`
    for (int i = 0; i < ${a}; i++) {
      if (i == index) {
        return ${t}[i];
      }
    }
  `}function vH(e,t){let a=e.name,n=a.charAt(0).toUpperCase()+a.slice(1),r="get"+n+"AtOutCoords",s=e.shapeInfo.logicalShape.length,i=t.logicalShape.length,o=Hv(e.shapeInfo.logicalShape,t.logicalShape),l=ft(i),u=i-s,p,c=["x","y","z","w","u","v"];s===0?p="":i<2&&o.length>=1?p="coords = 0;":p=o.map(g=>`coords.${c[g+u]} = 0;`).join(`
`);let d="";i<2&&s>0?d="coords":d=e.shapeInfo.logicalShape.map((g,y)=>`coords.${c[y+u]}`).join(", ");let h="return outputValue;",m=v.sizeFromShape(e.shapeInfo.logicalShape)===1,f=v.sizeFromShape(t.logicalShape)===1;if(s===1&&!m&&!f)h=`
      return vec4(outputValue.xy, outputValue.xy);
    `;else if(m&&!f)i===1?h=`
        return vec4(outputValue.x, outputValue.x, 0., 0.);
      `:h=`
        return vec4(outputValue.x);
      `;else if(o.length){let g=s-2,y=s-1;o.indexOf(g)>-1&&o.indexOf(y)>-1?h="return vec4(outputValue.x);":o.indexOf(g)>-1?h="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":o.indexOf(y)>-1&&(h="return vec4(outputValue.xx, outputValue.zz);")}return`
    vec4 ${r}() {
      ${l} coords = getOutputCoords();
      ${p}
      vec4 outputValue = get${n}(${d});
      ${h}
    }
  `}function wH(e,t){let a=e.name,n=a.charAt(0).toUpperCase()+a.slice(1),r="get"+n+"AtOutCoords",s=t.texShape,i=e.shapeInfo.texShape,o=e.shapeInfo.logicalShape.length,l=t.logicalShape.length;if(!e.shapeInfo.isUniform&&o===l&&e.shapeInfo.flatOffset==null&&v.arraysEqual(i,s))return`
      float ${r}() {
        return sampleTexture(${a}, resultUV);
      }
    `;let u=ft(l),p=Hv(e.shapeInfo.logicalShape,t.logicalShape),c=l-o,d,h=["x","y","z","w","u","v"];o===0?d="":l<2&&p.length>=1?d="coords = 0;":d=p.map(f=>`coords.${h[f+c]} = 0;`).join(`
`);let m="";return l<2&&o>0?m="coords":m=e.shapeInfo.logicalShape.map((f,g)=>`coords.${h[g+c]}`).join(", "),`
    float ${r}() {
      ${u} coords = getOutputCoords();
      ${d}
      return get${n}(${m});
    }
  `}function ft(e){if(e<=1)return"int";if(e===2)return"ivec2";if(e===3)return"ivec3";if(e===4)return"ivec4";if(e===5)return"ivec5";if(e===6)return"ivec6";throw Error(`GPU for rank ${e} is not yet supported`)}function M3(e,t,a){let{newShape:n,keptDims:r}=v.squeezeShape(t),s=t.length,i=e&&s===3&&t[0]===1,o=i?t.slice(1):n,l=!e&&s>1&&!v.arraysEqual(t,a)&&n.length<s||i;return{useSqueezeShape:l,uniformShape:l?o:t,keptDims:r}}function Yu(e,t){let a=JSON.parse(JSON.stringify(e));return a.shapeInfo.logicalShape=t,a}function Zu(e,t){return t.map(a=>e[a]).join(", ")}function kH(e,t,a,n){let r=a.map((p,c)=>{let d={logicalShape:p.shape,texShape:p.isUniform?null:p.texData.texShape,isUniform:p.isUniform,isPacked:p.isUniform?!1:p.texData.isPacked,flatOffset:null};return p.texData!=null&&p.texData.slice!=null&&p.texData.slice.flatOffset>0&&(d.flatOffset=p.texData.slice.flatOffset),{name:t.variableNames[c],shapeInfo:d}}),s=r.map(p=>p.shapeInfo),i={logicalShape:n.shape,texShape:n.texData.texShape,isUniform:!1,isPacked:n.texData.isPacked,flatOffset:null},o=BG(r,i,t),l=kv(e.gl,o),u=e.createProgram(l);return B().get("ENGINE_COMPILE_ONLY")?{program:t,fragmentShader:l,source:o,webGLProgram:u,inShapeInfos:s,outShapeInfo:i,variablesLocations:null,customUniformLocations:null,infLoc:null,nanLoc:null,outShapeLocation:null,outShapeStridesLocation:null,outTexShapeLocation:null}:(e.buildVao(u),Object.assign({program:t,fragmentShader:l,source:o,webGLProgram:u,inShapeInfos:s,outShapeInfo:i},Xv(e,t,u)))}function Xv(e,t,a){let n=[],r=[],s,i,o,l=null,u=null;u=e.getUniformLocation(a,"NAN",!1),B().getNumber("WEBGL_VERSION")===1&&(l=e.getUniformLocation(a,"INFINITY",!1));let p=!1;for(let c of t.variableNames){let d={name:c,uniform:e.getUniformLocation(a,c,p),offset:e.getUniformLocation(a,`offset${c}`,p)};t.enableShapeUniforms&&(d.shape=e.getUniformLocation(a,`${c}Shape`,p),d.texShape=e.getUniformLocation(a,`${c}TexShape`,p)),n.push(d)}if(t.enableShapeUniforms&&(s=e.getUniformLocation(a,"outShape",p),o=e.getUniformLocation(a,"outShapeStrides",p),i=e.getUniformLocation(a,"outTexShape",p)),t.customUniforms)for(let c of t.customUniforms)r.push(e.getUniformLocation(a,c.name,p));return{variablesLocations:n,customUniformLocations:r,infLoc:l,nanLoc:u,outShapeLocation:s,outShapeStridesLocation:o,outTexShapeLocation:i}}function S5(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((a,n)=>{let r=a.logicalShape,s=t[n],i=s.shape;if(!v.arraysEqual(r,i))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${r} and ${i} must match`);if(a.isUniform&&s.isUniform)return;let o=a.texShape,l=s.isUniform?null:s.texData.texShape;if(!v.arraysEqual(o,l))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${o} and ${l} must match`)})}function IH(e,t,a,n,r){t.program.enableShapeUniforms||(S5(t.inShapeInfos,a),S5([t.outShapeInfo],[n]));let s=n.texData.texture,i=n.texData.texShape;n.texData.isPacked?e.setOutputPackedMatrixTexture(s.texture,i[0],i[1]):e.setOutputMatrixTexture(s.texture,i[0],i[1]),e.setProgram(t.webGLProgram),e.bindVertexArray(t.webGLProgram.vao),B().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&e.gl.uniform1f(t.infLoc,1/0),t.nanLoc!==null&&e.gl.uniform1f(t.nanLoc,NaN);for(let l=0;l<a.length;++l){let u=a[l],{uniform:p,offset:c,shape:d,texShape:h}=t.variablesLocations[l];if(d){let{uniformShape:m}=M3(t.program.packedInputs,u.shape,u.texData.texShape);switch(m.length){case 1:e.gl.uniform1iv(d,new Int32Array(m));break;case 2:e.gl.uniform2iv(d,new Int32Array(m));break;case 3:e.gl.uniform3iv(d,new Int32Array(m));break;case 4:e.gl.uniform4iv(d,new Int32Array(m));break;default:break}}if(h&&e.gl.uniform2i(h,u.texData.texShape[0],u.texData.texShape[1]),p!=null){if(u.isUniform){if(v.sizeFromShape(u.shape)<2)e.gl.uniform1f(p,u.uniformValues[0]);else{let m=u.uniformValues;m instanceof Float32Array||(m=new Float32Array(m)),e.gl.uniform1fv(p,m)}continue}u.texData.slice!=null&&c!=null&&e.gl.uniform1i(c,u.texData.slice.flatOffset),e.setInputMatrixTexture(u.texData.texture.texture,p,l)}}let o=t.outShapeLocation;if(o)switch(n.shape.length){case 1:e.gl.uniform1iv(o,new Int32Array(n.shape));break;case 2:e.gl.uniform2iv(o,new Int32Array(n.shape));break;case 3:e.gl.uniform3iv(o,new Int32Array(n.shape));break;case 4:e.gl.uniform4iv(o,new Int32Array(n.shape));break;default:break}if(t.outShapeStridesLocation){let l=v.computeStrides(n.shape);switch(n.shape.length){case 2:e.gl.uniform1iv(t.outShapeStridesLocation,new Int32Array(l));break;case 3:e.gl.uniform2iv(t.outShapeStridesLocation,new Int32Array(l));break;case 4:e.gl.uniform3iv(t.outShapeStridesLocation,new Int32Array(l));break;default:break}}if(t.outTexShapeLocation&&e.gl.uniform2i(t.outTexShapeLocation,n.texData.texShape[0],n.texData.texShape[1]),t.program.customUniforms&&r)for(let l=0;l<t.program.customUniforms.length;++l){let u=t.program.customUniforms[l],p=t.customUniformLocations[l],c=r[l];if(u.type==="float")e.gl.uniform1fv(p,c);else if(u.type==="vec2")e.gl.uniform2fv(p,c);else if(u.type==="vec3")e.gl.uniform3fv(p,c);else if(u.type==="vec4")e.gl.uniform4fv(p,c);else if(u.type==="int")e.gl.uniform1iv(p,c);else if(u.type==="ivec2")e.gl.uniform2iv(p,c);else if(u.type==="ivec3")e.gl.uniform3iv(p,c);else if(u.type==="ivec4")e.gl.uniform4iv(p,c);else throw Error(`uniform type ${u.type} is not supported yet.`)}e.executeProgram()}function SH(e,t,a){let n="";t.concat(a).forEach(i=>{let o=i.texData!=null&&i.texData.slice!=null&&i.texData.slice.flatOffset>0;if(e.enableShapeUniforms&&!i.isUniform){let l=i.texData.texShape,{useSqueezeShape:u,uniformShape:p,keptDims:c}=M3(e.packedInputs,i.shape,l),d="",h="",m="";if(p.length===1&&e.packedInputs){let w=[Math.ceil(l[0]/2),Math.ceil(l[1]/2)];d=`${w[0]>1}_${w[1]>1}`}else if(p.length===2&&!e.packedInputs)h=`${p[0]>1}_${p[1]>1}`;else if(p.length>2&&!e.packedInputs){let w=v.computeStrides(p);m=`${w[0]===l[1]}_${w[w.length-1]===l[1]}`}let f=i.shape.length,g=p.length===2&&v.arraysEqual(i.shape,l),y=v.sizeFromShape(i.shape)===1,x=C.getBroadcastDims(i.shape,a.shape),A=!e.packedInputs&&f===a.shape.length&&v.arraysEqual(l,a.texData.texShape),b=e.packedInputs||p.length>2?"":`${l[0]>1}_${l[1]>1}`;n+=`${f}_${A}_${u?c:""}_${p.length}_${y}_${x}_${g}_${d}_${h}_${m}_${b}_${o}`}else{let l=i.isUniform?"uniform":i.texData.texShape;n+=`${i.shape}_${l}_${o}`}});let r=e.userCode,s=e.constructor.name;return s+="_"+n+"_"+r+`${B().getNumber("WEBGL_VERSION")}`,s}function ya(e){return B().getBool("WEBGL_USE_SHAPES_UNIFORMS")&&e<=4}var CH=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=Qd.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let t=Ra();this.outputShape=e,this.enableShapeUniforms=ya(this.outputShape.length),this.userCode=`
      ivec3 outCoordsFromFlatIndex(int index) {
        ${this.enableShapeUniforms?r0(["r","c","d"],e):rl(["r","c","d"],e)}
        return ivec3(r, c, d);
      }

      void main() {
        ivec2 resTexRC = ivec2(resultUV.yx * vec2(texShape[0], texShape[1]));
        int index = 4 * (resTexRC.x * texShape[1] + resTexRC.y);

        vec4 result = vec4(0.);

        for (int i=0; i<4; i++) {
          int flatIndex = index + i;
          ivec3 rc = outCoordsFromFlatIndex(flatIndex);
          result[i] = getA(rc.x, rc.y, rc.z);
        }

        ${t.output} = result;
      }
    `}},TH=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=Qd.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let t=Ra();this.outputShape=e,this.enableShapeUniforms=ya(this.outputShape.length),this.userCode=`
      ivec3 outCoordsFromFlatIndex(int index) {
        ${this.enableShapeUniforms?r0(["r","c","d"],e):rl(["r","c","d"],e)}
        return ivec3(r, c, d);
      }

      void main() {
        ivec2 resTexRC = ivec2(resultUV.yx * vec2(texShape[0], texShape[1]));
        int index = 4 * (resTexRC.x * texShape[1] + resTexRC.y);

        vec4 result = vec4(0.);

        for (int i=0; i<4; i++) {
          int flatIndex = index + i;
          ivec3 rc = outCoordsFromFlatIndex(flatIndex);
          result[i] = getChannel(getA(rc.x, rc.y, rc.z), vec2(rc.y, rc.z));
        }

        ${t.output} = result;
      }
    `}},NH=class{constructor(e){this.variableNames=["A"],this.outTexUsage=mn.DOWNLOAD;let t=Ra();this.outputShape=e,this.userCode=`
      ${Gv}

      void main() {
        float x = getAAtOutCoords();
        ${t.output} = encode_float(x);
      }
    `}},RH=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=mn.DOWNLOAD;let t=Ra();this.outputShape=e,this.userCode=`
      ${Gv}

      void main() {
        ivec3 coords = getOutputCoords();
        float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));
        ${t.output} = encode_float(x);
      }
    `}},EH={R:0,G:1,B:2,A:3},C5=class{constructor(e,t=!1,a="RGBA"){this.variableNames=["A"],this.customUniforms=[{name:"texShape",type:"ivec2"}];let n=Ra();this.outputShape=e,this.enableShapeUniforms=ya(this.outputShape.length);let r="result";t&&(r="floor(result * 255. + 0.5)");let s="";for(let i=0;i<a.length;i++){let o=a[i];s+=`
          if(offset == ${i}) {
            result = values[${EH[o]}];
          }`}this.userCode=`
      ${this.enableShapeUniforms?E3():R3(e)}

      void main() {
        ivec3 coords = getOutputCoords();
        int flatIndex = getFlatIndex(coords);
        float result = 0.;
        int offset = imod(flatIndex, ${a.length});

        flatIndex = idiv(flatIndex, ${a.length}, 1.);

        int r = flatIndex / texShape[1];
        if (r < texShape[0]) {
          int c = imod(flatIndex, texShape[1]);
          vec2 uv = (vec2(c, r) + halfCR) / vec2(texShape[1], texShape[0]);
          vec4 values = ${n.texture2D}(A, uv);
          ${s}
        }
        ${n.output} = vec4(${r}, 0., 0., 0.);
      }
    `}},MH=class{constructor(e,t=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.customUniforms=[{name:"texShape",type:"ivec2"}];let a=Ra();this.outputShape=e,this.enableShapeUniforms=ya(this.outputShape.length);let n="",r="result";t&&(r="floor(result * 255. + 0.5)");for(let s=0;s<=1;s++)for(let i=0;i<=1;i++){let o=s*2+i;n+=`
          localCoords = coords;
          if(localCoords[2] + ${i} < ${this.enableShapeUniforms?"outShape[2]":`${e[2]}`}) {
          localCoords[2] += ${i};
          if (localCoords[1] + ${s} < ${this.enableShapeUniforms?"outShape[1]":`${e[1]}`}) {
            localCoords[1] += ${s};

            flatIndex = getFlatIndex(localCoords);
            offset = imod(flatIndex, 4);

            flatIndex = idiv(flatIndex, 4, 1.);

            int r = flatIndex / texShape[1];
            int c = imod(flatIndex, texShape[1]);
            vec2 uv = (vec2(c, r) + halfCR) / vec2(texShape[1], texShape[0]);
            values = ${a.texture2D}(A, uv);

            if (offset == 0) {
              result[${o}] = values[0];
            } else if (offset == 1) {
              result[${o}] = values[1];
            } else if (offset == 2) {
              result[${o}] = values[2];
            } else {
              result[${o}] = values[3];
            }
          }
        }
        `}this.userCode=`
        ${this.enableShapeUniforms?E3():R3(e)}

        void main() {
          ivec3 coords = getOutputCoords();

          vec4 result = vec4(0.);
          int flatIndex, r, c, offset;
          ivec3 localCoords;
          vec2 uv;
          vec4 values;

          ${n}

          ${a.output} = ${r};
        }
    `}},Kv={};Ze(Kv,{bindVertexProgramAttributeStreams:()=>r8,createBufferFromOutputTexture:()=>o8,createFloat16MatrixTexture:()=>e8,createFloat16PackedMatrixTexture:()=>n8,createFloat32MatrixTexture:()=>Qv,createIndexBuffer:()=>Jv,createPackedMatrixTexture:()=>a8,createUnsignedBytesMatrixTexture:()=>t8,createVertexBuffer:()=>Zv,createVertexShader:()=>Yv,downloadByteEncodedFloatMatrixFromOutputTexture:()=>u8,downloadFloat32MatrixFromBuffer:()=>l8,downloadMatrixFromPackedOutputTexture:()=>p8,downloadPackedMatrixFromBuffer:()=>d8,getInternalFormatForFloat16MatrixTexture:()=>P3,getInternalFormatForFloat16PackedMatrixTexture:()=>D3,getInternalFormatForFloat32MatrixTexture:()=>$3,getInternalFormatForPackedMatrixTexture:()=>F3,getInternalFormatForUnsignedBytesMatrixTexture:()=>_3,uploadDenseMatrixToTexture:()=>s8,uploadPixelDataToTexture:()=>i8});function Yv(e){let t=Ra(),a=`${t.version}
    precision highp float;
    ${t.attribute} vec3 clipSpacePos;
    ${t.attribute} vec2 uv;
    ${t.varyingVs} vec2 resultUV;

    void main() {
      gl_Position = vec4(clipSpacePos, 1);
      resultUV = uv;
    }`;return wv(e,a)}function Zv(e){let t=new Float32Array([-1,1,0,0,1,-1,-1,0,0,0,1,1,0,1,1,1,-1,0,1,0]);return Cv(e,t)}function Jv(e){let t=new Uint16Array([0,1,2,2,1,3]);return Tv(e,t)}function Zp(e,t,a,n,r,s){Rv(t,a);let i=Nv(e),o=e.TEXTURE_2D;return ce(e,()=>e.bindTexture(o,i)),ce(e,()=>e.texParameteri(o,e.TEXTURE_WRAP_S,e.CLAMP_TO_EDGE)),ce(e,()=>e.texParameteri(o,e.TEXTURE_WRAP_T,e.CLAMP_TO_EDGE)),ce(e,()=>e.texParameteri(o,e.TEXTURE_MIN_FILTER,e.NEAREST)),ce(e,()=>e.texParameteri(o,e.TEXTURE_MAG_FILTER,e.NEAREST)),B().getNumber("WEBGL_VERSION")===1?ce(e,()=>e.texImage2D(o,0,n,t,a,0,r,s,null)):ce(e,()=>e.texStorage2D(o,1,n,t,a)),ce(e,()=>e.bindTexture(e.TEXTURE_2D,null)),{texture:i,texShape:[a,t]}}function $3(e){return e.internalFormatFloat}function Qv(e,t,a,n){let[r,s]=Yp(t,a);return Zp(e,r,s,$3(n),n.textureFormatFloat,e.FLOAT)}function P3(e){return e.internalFormatHalfFloat}function e8(e,t,a,n){let[r,s]=Yp(t,a);return Zp(e,r,s,P3(n),n.textureFormatFloat,n.textureTypeHalfFloat)}function _3(e){return e.downloadTextureFormat}function t8(e,t,a,n){let[r,s]=Yp(t,a);return Zp(e,r,s,_3(n),e.RGBA,e.UNSIGNED_BYTE)}function F3(e){return e.internalFormatPackedFloat}function a8(e,t,a,n){let[r,s]=ju(t,a);return Zp(e,r,s,F3(n),e.RGBA,e.FLOAT)}function D3(e){return e.internalFormatPackedHalfFloat}function n8(e,t,a,n){let[r,s]=ju(t,a);return Zp(e,r,s,D3(n),e.RGBA,n.textureTypeHalfFloat)}function r8(e,t,a){return ce(e,()=>e.bindBuffer(e.ARRAY_BUFFER,a)),F1(e,t,"clipSpacePos",a,3,20,0)&&F1(e,t,"uv",a,2,20,12)}function s8(e,t,a,n,r,s){ce(e,()=>e.bindTexture(e.TEXTURE_2D,t));let i,o,l;r instanceof Uint8Array?(i=new Uint8Array(a*n*4),o=e.UNSIGNED_BYTE,l=e.RGBA):(i=new Float32Array(a*n*4),o=e.FLOAT,l=s.internalFormatPackedFloat),i.set(r),B().getNumber("WEBGL_VERSION")===2?ce(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,a,n,e.RGBA,o,i)):ce(e,()=>e.texImage2D(e.TEXTURE_2D,0,l,a,n,0,e.RGBA,o,i)),ce(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function i8(e,t,a){ce(e,()=>e.bindTexture(e.TEXTURE_2D,t)),a.data instanceof Uint8Array?B().getNumber("WEBGL_VERSION")===2?ce(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,a.width,a.height,e.RGBA,e.UNSIGNED_BYTE,a.data)):ce(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,a.width,a.height,0,e.RGBA,e.UNSIGNED_BYTE,a.data)):B().getNumber("WEBGL_VERSION")===2?ce(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,e.RGBA,e.UNSIGNED_BYTE,a)):ce(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,e.RGBA,e.UNSIGNED_BYTE,a)),ce(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function o8(e,t,a,n){let r=e.createBuffer();ce(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,r));let s=4*4*t*a;return ce(e,()=>e.bufferData(e.PIXEL_PACK_BUFFER,s,e.STREAM_READ)),ce(e,()=>e.readPixels(0,0,a,t,e.RGBA,e.FLOAT,0)),ce(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,null)),r}function l8(e,t,a){let n=e,r=new Float32Array(a);return n.bindBuffer(n.PIXEL_PACK_BUFFER,t),n.getBufferSubData(n.PIXEL_PACK_BUFFER,0,r),n.bindBuffer(n.PIXEL_PACK_BUFFER,null),r}function u8(e,t,a,n){let[r,s]=Yp(t,a),i=4,o=new Uint8Array(TG(t*a,i));return ce(e,()=>e.readPixels(0,0,r,s,n.downloadTextureFormat,e.UNSIGNED_BYTE,o)),new Float32Array(o.buffer)}function d8(e,t,a,n,r,s,i,o){let l=e,u=new Float32Array(NG(s,i));return l.bindBuffer(l.PIXEL_PACK_BUFFER,t),l.getBufferSubData(l.PIXEL_PACK_BUFFER,0,u),l.bindBuffer(l.PIXEL_PACK_BUFFER,null),u}function p8(e,t,a){let n=new Float32Array(t*a*4);return ce(e,()=>e.readPixels(0,0,a,t,e.RGBA,e.FLOAT,n)),n}var Hl=class{constructor(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.itemsToPoll=[];let t=B().getNumber("WEBGL_VERSION");if(e!=null?(this.gl=e,n0(t,e)):this.gl=Bn(t),e=this.gl,B().getNumber("WEBGL_VERSION")===2){let r=e;this.createVertexArray=()=>ce(r,()=>r.createVertexArray()),this.bindVertexArray=s=>ce(r,()=>r.bindVertexArray(s)),this.deleteVertexArray=s=>ce(r,()=>r.deleteVertexArray(s)),this.getVertexArray=()=>ce(r,()=>r.getParameter(r.VERTEX_ARRAY_BINDING))}else if(e!=null){let r=e.getExtension("OES_vertex_array_object");if(r==null)throw new Error("All WebGL1 implementations are expected to offer OES_vertex_array_object.");this.createVertexArray=()=>ce(e,()=>r.createVertexArrayOES()),this.bindVertexArray=s=>ce(e,()=>r.bindVertexArrayOES(s)),this.deleteVertexArray=s=>ce(e,()=>r.deleteVertexArrayOES(s)),this.getVertexArray=()=>ce(e,()=>e.getParameter(r.VERTEX_ARRAY_BINDING_OES))}let a="WEBGL_color_buffer_float",n="EXT_color_buffer_half_float";if(this.parallelCompilationExtension=this.gl.getExtension("KHR_parallel_shader_compile"),B().getNumber("WEBGL_VERSION")===1){let r="OES_texture_float",s="OES_texture_half_float";if(this.textureFloatExtension=Rd(this.gl,r),fn(this.gl,s))this.textureHalfFloatExtension=Rd(this.gl,s);else if(B().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support half float textures, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.");if(this.colorBufferFloatExtension=this.gl.getExtension(a),fn(this.gl,n))this.colorBufferHalfFloatExtension=Rd(this.gl,n);else if(B().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support color renderable half floats, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.")}else if(a="EXT_color_buffer_float",fn(this.gl,a))this.colorBufferFloatExtension=this.gl.getExtension(a);else if(fn(this.gl,n))this.colorBufferHalfFloatExtension=this.gl.getExtension(n);else throw new Error("GL context does not support color renderable floats");this.vertexBuffer=Zv(this.gl),this.indexBuffer=Jv(this.gl),this.framebuffer=Ev(this.gl),this.textureConfig=T3(this.gl,this.textureHalfFloatExtension)}get debug(){return B().getBool("DEBUG")}dispose(){if(this.disposed)return;this.program!=null&&console.warn("Disposing a GPGPUContext that still has a bound WebGLProgram. This is probably a resource leak, delete the program with GPGPUContext.deleteProgram before disposing."),this.outputTexture!=null&&console.warn("Disposing a GPGPUContext that still has a bound output matrix texture.  This is probably a resource leak, delete the output matrix texture with GPGPUContext.deleteMatrixTexture before disposing.");let e=this.gl;ce(e,()=>e.finish()),ce(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),ce(e,()=>e.deleteFramebuffer(this.framebuffer)),ce(e,()=>e.bindBuffer(e.ARRAY_BUFFER,null)),ce(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null)),ce(e,()=>e.deleteBuffer(this.indexBuffer)),this.disposed=!0}createFloat32MatrixTexture(e,t){return this.throwIfDisposed(),Qv(this.gl,e,t,this.textureConfig)}createFloat16MatrixTexture(e,t){return this.throwIfDisposed(),e8(this.gl,e,t,this.textureConfig)}createUnsignedBytesMatrixTexture(e,t){return this.throwIfDisposed(),t8(this.gl,e,t,this.textureConfig)}uploadPixelDataToTexture(e,t){this.throwIfDisposed(),i8(this.gl,e,t)}uploadDenseMatrixToTexture(e,t,a,n){this.throwIfDisposed(),s8(this.gl,e,t,a,n,this.textureConfig)}createFloat16PackedMatrixTexture(e,t){return this.throwIfDisposed(),n8(this.gl,e,t,this.textureConfig)}createPackedMatrixTexture(e,t){return this.throwIfDisposed(),a8(this.gl,e,t,this.textureConfig)}deleteMatrixTexture(e){this.throwIfDisposed(),this.outputTexture===e&&(D1(this.gl,this.framebuffer),this.outputTexture=null),ce(this.gl,()=>this.gl.deleteTexture(e))}downloadByteEncodedFloatMatrixFromOutputTexture(e,t,a){return this.downloadMatrixDriver(e,()=>u8(this.gl,t,a,this.textureConfig))}downloadPackedMatrixFromBuffer(e,t,a,n,r,s){return d8(this.gl,e,t,a,n,r,s,this.textureConfig)}downloadFloat32MatrixFromBuffer(e,t){return l8(this.gl,e,t)}createBufferFromTexture(e,t,a){this.bindTextureToFrameBuffer(e);let n=o8(this.gl,t,a,this.textureConfig);return this.unbindTextureToFrameBuffer(),n}createAndWaitForFence(){let e=this.createFence(this.gl);return this.pollFence(e)}createFence(e){let t,a;if(B().getBool("WEBGL_FENCE_API_ENABLED")){let n=e,r=n.fenceSync(n.SYNC_GPU_COMMANDS_COMPLETE,0);e.flush(),a=()=>{let s=n.clientWaitSync(r,0,0);return s===n.ALREADY_SIGNALED||s===n.CONDITION_SATISFIED},t=r}else B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(t=this.beginQuery(),this.endQuery(),a=()=>this.isQueryAvailable(t,B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))):a=()=>!0;return{query:t,isFencePassed:a}}downloadMatrixFromPackedTexture(e,t,a){return this.downloadMatrixDriver(e,()=>p8(this.gl,t,a))}createProgram(e){this.throwIfDisposed();let t=this.gl;this.vertexShader==null&&(this.vertexShader=Yv(t));let a=Iv(t);ce(t,()=>t.attachShader(a,this.vertexShader)),ce(t,()=>t.attachShader(a,e)),Sv(t,a);let n=Object.assign(a,{vao:this.createVertexArray()});return this.debug&&nh(t,n),n}buildVao(e){this.setProgram(e),this.bindVertexArray(e.vao);let t=this.gl;ce(t,()=>t.bindBuffer(t.ELEMENT_ARRAY_BUFFER,this.indexBuffer)),r8(t,e,this.vertexBuffer)}deleteProgram(e){this.throwIfDisposed(),e===this.program&&(this.program=null),e!=null&&(ce(this.gl,()=>this.gl.deleteProgram(e)),this.deleteVertexArray(e.vao))}setProgram(e){this.throwIfDisposed(),this.program=e,this.program!=null&&this.debug&&nh(this.gl,this.program),ce(this.gl,()=>this.gl.useProgram(e))}getUniformLocation(e,t,a=!0){return this.throwIfDisposed(),a?$v(this.gl,e,t):Pv(this.gl,e,t)}getAttributeLocation(e,t){return this.throwIfDisposed(),ce(this.gl,()=>this.gl.getAttribLocation(e,t))}getUniformLocationNoThrow(e,t){return this.throwIfDisposed(),this.gl.getUniformLocation(e,t)}setInputMatrixTexture(e,t,a){this.throwIfDisposed(),this.throwIfNoProgram(),_v(this.gl,e,t,a)}setOutputMatrixTexture(e,t,a){this.setOutputMatrixTextureDriver(e,a,t)}setOutputPackedMatrixTexture(e,t,a){this.throwIfDisposed();let[n,r]=ju(t,a);this.setOutputMatrixTextureDriver(e,n,r)}setOutputMatrixWriteRegion(e,t,a,n){this.setOutputMatrixWriteRegionDriver(a,e,n,t)}setOutputPackedMatrixWriteRegion(e,t,a,n){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")}debugValidate(){this.program!=null&&nh(this.gl,this.program),Ed(this.gl)}executeProgram(){this.throwIfDisposed(),this.throwIfNoProgram();let e=this.gl;if(this.debug){let t=this.getVertexArray();console.assert(t===this.program.vao,"VAO changed between setProgram and executeProgram!"),this.debugValidate()}ce(e,()=>e.drawElements(e.TRIANGLES,6,e.UNSIGNED_SHORT,0))}blockUntilAllProgramsCompleted(){this.throwIfDisposed(),ce(this.gl,()=>this.gl.finish())}getQueryTimerExtension(){return this.disjointQueryTimerExtension==null&&(this.disjointQueryTimerExtension=Rd(this.gl,B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2?"EXT_disjoint_timer_query_webgl2":"EXT_disjoint_timer_query")),this.disjointQueryTimerExtension}getQueryTimerExtensionWebGL2(){return this.getQueryTimerExtension()}getQueryTimerExtensionWebGL1(){return this.getQueryTimerExtension()}beginQuery(){if(B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let a=this.gl,n=this.getQueryTimerExtensionWebGL2(),r=a.createQuery();return a.beginQuery(n.TIME_ELAPSED_EXT,r),r}let e=this.getQueryTimerExtensionWebGL1(),t=e.createQueryEXT();return e.beginQueryEXT(e.TIME_ELAPSED_EXT,t),t}endQuery(){if(B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let t=this.gl,a=this.getQueryTimerExtensionWebGL2();t.endQuery(a.TIME_ELAPSED_EXT);return}let e=this.getQueryTimerExtensionWebGL1();e.endQueryEXT(e.TIME_ELAPSED_EXT)}async waitForQueryAndGetTime(e){return await v.repeatedTry(()=>this.disposed||this.isQueryAvailable(e,B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))),this.getQueryTime(e,B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))}getQueryTime(e,t){if(t===0)return null;if(t===2){let a=this.gl;return a.getQueryParameter(e,a.QUERY_RESULT)/1e6}else{let a=this.getQueryTimerExtensionWebGL1();return a.getQueryObjectEXT(e,a.QUERY_RESULT_EXT)/1e6}}isQueryAvailable(e,t){if(t===0)return!0;if(t===2){let a=this.gl,n=this.getQueryTimerExtensionWebGL2(),r=a.getQueryParameter(e,a.QUERY_RESULT_AVAILABLE);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(n.GPU_DISJOINT_EXT)),r&&!this.disjoint}else{let a=this.getQueryTimerExtensionWebGL1(),n=a.getQueryObjectEXT(e,a.QUERY_RESULT_AVAILABLE_EXT);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(a.GPU_DISJOINT_EXT)),n&&!this.disjoint}}pollFence(e){return new Promise(t=>{this.addItemToPoll(()=>e.isFencePassed(),()=>t())})}pollItems(){let e=$H(this.itemsToPoll.map(t=>t.isDoneFn));for(let t=0;t<=e;++t){let{resolveFn:a}=this.itemsToPoll[t];a()}this.itemsToPoll=this.itemsToPoll.slice(e+1)}addItemToPoll(e,t){if(this.itemsToPoll.push({isDoneFn:e,resolveFn:t}),this.itemsToPoll.length>1)return;let a;"setTimeoutCustom"in B().platform&&(a=B().platform.setTimeoutCustom.bind(B().platform)),v.repeatedTry(()=>(this.pollItems(),this.itemsToPoll.length===0),()=>0,null,a)}bindTextureToFrameBuffer(e){this.throwIfDisposed(),rh(this.gl,e,this.framebuffer),this.debug&&Ed(this.gl)}unbindTextureToFrameBuffer(){this.outputTexture!=null?(rh(this.gl,this.outputTexture,this.framebuffer),this.debug&&Ed(this.gl)):D1(this.gl,this.framebuffer)}downloadMatrixDriver(e,t){this.bindTextureToFrameBuffer(e);let a=t();return this.unbindTextureToFrameBuffer(),a}setOutputMatrixTextureDriver(e,t,a){this.throwIfDisposed();let n=this.gl;rh(n,e,this.framebuffer),this.debug&&Ed(n),this.outputTexture=e,ce(n,()=>n.viewport(0,0,t,a)),ce(n,()=>n.scissor(0,0,t,a))}setOutputMatrixWriteRegionDriver(e,t,a,n){this.throwIfDisposed(),ce(this.gl,()=>this.gl.scissor(e,t,a,n))}throwIfDisposed(){if(this.disposed)throw new Error("Attempted to use disposed GPGPUContext.")}throwIfNoProgram(){if(this.program==null)throw new Error("No GPU program is currently set.")}};function $H(e){let t=0;for(;t<e.length&&e[t]();++t);return t-1}var{addImpl:PH,bincountImpl:c8,bincountReduceImpl:_H,bitwiseAndImpl:FH,castImpl:DH,ceilImpl:OH,concatImpl:zH,equalImpl:LH,expImpl:WH,expm1Impl:BH,floorImpl:VH,gatherNdImpl:UH,gatherV2Impl:GH,greaterImpl:HH,greaterEqualImpl:jH,lessImpl:qH,lessEqualImpl:XH,linSpaceImpl:KH,logImpl:YH,maxImpl:ZH,maximumImpl:JH,minimumImpl:QH,multiplyImpl:ej,negImpl:tj,notEqualImpl:aj,prodImpl:nj,raggedGatherImpl:rj,raggedRangeImpl:sj,raggedTensorToTensorImpl:ij,rangeImpl:oj,rsqrtImpl:lj,scatterImpl:uj,sigmoidImpl:dj,simpleAbsImpl:h8,sliceImpl:pj,sparseFillEmptyRowsImpl:cj,sparseReshapeImpl:hj,sparseSegmentReductionImpl:m8,sqrtImpl:mj,staticRegexReplaceImpl:fj,stridedSliceImpl:gj,stringNGramsImpl:yj,stringSplitImpl:xj,stringToHashBucketFastImpl:Aj,subImpl:bj,tileImpl:vj,topKImpl:wj,transposeImpl:O3,uniqueImpl:kj}=t0;function f8(e,t){return["x","y","z","w","u","v"].slice(0,t).map(a=>`${e}.${a}`)}function ka(e,t){return t===1?[e]:f8(e,t)}function Ij(e,t){if(e===1)return"rc";let a="";for(let n=0;n<e;n++)a+=t[n],n<e-1&&(a+=",");return a}var Sj=class{constructor(e){if(this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.enableShapeUniforms=ya(this.outputShape.length),this.rank===0)this.userCode=`
        void main() {
          setOutput(vec4(getA(), 0., 0., 0.));
        }
      `;else{let t=ka("rc",this.rank),a=ft(this.rank),n=this.getOutOfBoundsCondition(t),r=this.getSetup(t),s=this.getOutput(t);this.userCode=`
        void main() {
          ${a} rc = getOutputCoords();

          if(${n}) {
            setOutput(vec4(0));
          } else {
            ${r}

            setOutput(vec4(${s}));
          }
        }
      `}}getSourceCoordsArr(e){let t=[];for(let a=0;a<=1;a++)for(let n=0;n<=1;n++){let r=`${a===0?"r":"rp1"}, ${n===0?"c":"cp1"}`;for(let s=2;s<this.rank;s++)r=`${e[e.length-1-s]},`+r;t.push(r)}return t}getOutOfBoundsCondition(e){if(this.rank===1)return`rc > ${this.enableShapeUniforms?"outShape":this.outputShape[0]}`;let t="";for(let a=this.rank-2;a<this.rank;a++)t+=`${e[a]} >= ${this.enableShapeUniforms?`outShape[${a}]`:this.outputShape[a]}`,a<this.rank-1&&(t+="||");return t}getSetup(e){if(this.rank===1)return"";let t=e.slice(-2),a=this.enableShapeUniforms?`outShape[${this.rank} - 1]`:this.outputShape[this.rank-1],n=this.enableShapeUniforms?`outShape[${this.rank} - 2]`:this.outputShape[this.rank-2];return`
      int r = ${t[0]};
      int c = ${t[1]};
      int rp1 = r + 1;
      int cp1 = c + 1;

      bool cEdge = cp1 >= ${a};
      bool rEdge = rp1 >= ${n};
    `}getOutput(e){let t=this.getSourceCoordsArr(e);return this.rank===1?`getA(rc), (rc + 1 >= ${this.enableShapeUniforms?"outShape":this.outputShape[0]} ? 0. : getA(rc + 1)), 0, 0`:`getA(${t[0]}),
            cEdge ? 0. : getA(${t[1]}),
            rEdge ? 0. : getA(${t[2]}),
            rEdge || cEdge ? 0. : getA(${t[3]})`}},g8=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"inputShape",type:"ivec3"}],this.outputShape=e,this.enableShapeUniforms=ya(this.outputShape.length);let a="";for(let n=0;n<4;n++){let r="thisRC = rc;";n%2===1&&(r+="thisRC.z += 1;"),n>1&&(r+="thisRC.y += 1;"),a+=`
        ${r}
        ${n>0?"if(thisRC.y < rows && thisRC.z < cols){":""}
          int flatIndex = getFlatIndex(thisRC);

          ivec3 inputRC = inputCoordsFromReshapedOutCoords(flatIndex);
          vec2 inputRCInnerDims = vec2(float(inputRC.y),float(inputRC.z));

          result[${n}] =
            getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);
        ${n>0?"}":""}
      `}this.userCode=`
      ${Cj(t,this.enableShapeUniforms)}
      ${this.enableShapeUniforms?E3():R3(e)}

      void main() {
        ivec3 rc = getOutputCoords();

        vec4 result = vec4(0.);

        ivec3 thisRC;
        int rows = ${this.enableShapeUniforms?"outShape[1]":e[1]};
        int cols = ${this.enableShapeUniforms?"outShape[2]":e[2]};

        ${a}

        setOutput(result);
      }
    `}};function Cj(e,t){return`
    ivec3 inputCoordsFromReshapedOutCoords(int index) {
      ${t?WG(["r","c","d"],"inputShape"):rl(["r","c","d"],e)}
      return ivec3(r, c, d);
    }
  `}var Tj=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.usedTextures={},this.logEnabled=!1}acquireTexture(e,t,a){let n=N5(t,a),r=R5(e,n,a);r in this.freeTextures||(this.freeTextures[r]=[]),r in this.usedTextures||(this.usedTextures[r]=[]);let s=T5(e,n,this.gpgpu.gl,this.gpgpu.textureConfig,a);if(this.freeTextures[r].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=s,this.log();let o=this.freeTextures[r].pop();return this.usedTextures[r].push(o),o}let i;return n===pa.PACKED_2X2_FLOAT32?i=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):n===pa.PACKED_2X2_FLOAT16?i=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):n===pa.UNPACKED_FLOAT32?i=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):n===pa.UNPACKED_FLOAT16?i=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):n===pa.PACKED_4X1_UNSIGNED_BYTE&&(i=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[r].push(i),this.numUsedTextures++,this._numBytesAllocated+=s,this.log(),i}releaseTexture(e,t,a,n){if(this.freeTextures==null)return;let r=N5(a,n),s=R5(t,r,n);s in this.freeTextures||(this.freeTextures[s]=[]);let i=T5(t,r,this.gpgpu.gl,this.gpgpu.textureConfig,n),o=B().getNumber("WEBGL_DELETE_TEXTURE_THRESHOLD");o!==-1&&this._numBytesAllocated>o?(this.gpgpu.deleteMatrixTexture(e.texture),this._numBytesAllocated-=i):(this.freeTextures[s].push(e),this.numFreeTextures++,this._numBytesFree+=i),this.numUsedTextures--;let l=this.usedTextures[s],u=l&&l.indexOf(e);if(u==null||u<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l[u]=l[l.length-1],l.pop(),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${this.numFreeTextures} / ${this.numUsedTextures}`,`(${e})`);let t=this._numBytesFree/this._numBytesAllocated;console.log(`Bytes allocated: ${this._numBytesAllocated}`),console.log(`Bytes unused: ${this._numBytesFree} (${Math.round(100*t)}%)`)}get numBytesAllocated(){return this._numBytesAllocated}get numBytesFree(){return this._numBytesFree}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){if(this.freeTextures!=null){for(let e in this.freeTextures)this.freeTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t.texture)});for(let e in this.usedTextures)this.usedTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t.texture)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function Nj(e,t){let a=e;if(t===a.R32F)return 4;if(t===a.R16F)return 2;if(t===a.RGBA32F||t===e.RGBA)return 16;if(t===a.RGBA16F)return 8;if(t===a.RGBA8)return 4;throw new Error(`Unknown internal format ${t}`)}function T5(e,t,a,n,r){let s=Rj(t,n),i;if(r){let[l,u]=ju(e[0],e[1]);i=l*u}else{let[l,u]=Yp(e[0],e[1]);i=l*u}let o=Nj(a,s);return i*o}function Rj(e,t){switch(e){case pa.PACKED_2X2_FLOAT32:return F3(t);case pa.PACKED_2X2_FLOAT16:return D3(t);case pa.UNPACKED_FLOAT32:return $3(t);case pa.UNPACKED_FLOAT16:return P3(t);case pa.PACKED_4X1_UNSIGNED_BYTE:return _3(t);default:throw new Error(`Unknown physical texture type ${e}`)}}function Ej(e){return B().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?e?pa.PACKED_2X2_FLOAT32:pa.UNPACKED_FLOAT32:e?pa.PACKED_2X2_FLOAT16:pa.UNPACKED_FLOAT16}function N5(e,t){if(e===mn.UPLOAD)return pa.PACKED_2X2_FLOAT32;if(e===mn.RENDER||e==null)return Ej(t);if(e===mn.DOWNLOAD||e===mn.PIXELS)return pa.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${e}`)}function R5(e,t,a){return`${e[0]}_${e[1]}_${t}_${a}`}var Jn=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.enableShapeUniforms=ya(this.outputShape.length),this.userCode=`
      float unaryOperation(float x) {
        ${t}
      }

      void main() {
        float x = getAAtOutCoords();
        float y = unaryOperation(x);

        setOutput(y);
      }
    `}},Mn="if (isnan(x)) return x;",Mj="return x;",E5="return abs(x);",$j="return (x >= 0.0) ? x : (exp(x) - 1.0);",Pj=Mn+`
  return (x < 0.0) ? 0.0 : x;
`,_j=Mn+`
  return (x < 0.0) ? 0.0 : min(6.0, x);
`,Vr="return x;",Fj="return 1.0 / (1.0 + exp(-1.0 * x));",Dj="return x;",Oj=`
  vec4 result;

  result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);
  result.g = (x.g >= 0.0) ? x.g : (exp(x.g) - 1.0);
  result.b = (x.b >= 0.0) ? x.b : (exp(x.b) - 1.0);
  result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);

  return result;
`,zj=`
  vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));
  bvec4 isNaN = isnan(x);

  result.r = isNaN.r ? x.r : result.r;
  result.g = isNaN.g ? x.g : result.g;
  result.b = isNaN.b ? x.b : result.b;
  result.a = isNaN.a ? x.a : result.a;

  return result;
`,Lj=`
  vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));
  bvec4 isNaN = isnan(x);

  result.r = isNaN.r ? x.r : result.r;
  result.g = isNaN.g ? x.g : result.g;
  result.b = isNaN.b ? x.b : result.b;
  result.a = isNaN.a ? x.a : result.a;

  return result;
`,Wj="return 1.0 / (1.0 + exp(-1.0 * x));",qr=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.enableShapeUniforms=ya(this.outputShape.length),this.userCode=`
      vec4 unaryOperation(vec4 x) {
        ${t}
      }

      void main() {
        vec4 x = getAAtOutCoords();
        vec4 y = unaryOperation(x);

        setOutput(y);
      }
    `}},Bj=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=e,this.enableShapeUniforms=ya(this.outputShape.length);let t=e.length,a=ka("rc",t),n=ft(t),r=Ij(t,a),s=a.slice(-2),i=t<=1?"rc":`vec2(${s.join(",")})`;this.userCode=`
      void main() {
        ${n} rc = getOutputCoords();
        vec4 packedInput = getA(${r});

        setOutput(getChannel(packedInput, ${i}));
      }
    `}},Vj=En.whereImpl,Uj=1e-7,Gj=1e-4,J2={};function Hj(e){return e in J2||(J2[e]={}),J2[e]}var jj=B().getNumber("CPU_HANDOFF_SIZE_THRESHOLD"),qj=600;function Xj(){return B().global.screen==null?1024:B().global.screen.height*B().global.screen.width*window.devicePixelRatio*qj/1024/1024}var Jp=class y8 extends su{nextDataId(){return y8.nextDataId++}constructor(t){if(super(),this.pendingRead=new WeakMap,this.pendingDisposal=new WeakSet,this.dataRefCount=new WeakMap,this.numBytesInGPU=0,this.uploadWaitMs=0,this.downloadWaitMs=0,this.lastGlFlushTime=0,this.warnedAboutMemory=!1,this.pendingDeletes=0,this.disposed=!1,!B().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");let a;if(t!=null){if(t instanceof Hl)a=t;else{let n=Bn(B().getNumber("WEBGL_VERSION"),t);a=new Hl(n)}this.binaryCache={},this.gpgpuCreatedLocally=!1}else{let n=Bn(B().getNumber("WEBGL_VERSION"));a=new Hl(n),this.binaryCache=Hj(B().getNumber("WEBGL_VERSION")),this.gpgpuCreatedLocally=!0}this.gpgpu=a,this.canvas=this.gpgpu.gl.canvas,this.textureManager=new Tj(this.gpgpu),this.numMBBeforeWarning=Xj(),this.texData=new op(this,It())}numDataIds(){return this.texData.numDataIds()-this.pendingDeletes}writeTexture(t,a,n,r,s,i){let o=this.makeTensorInfo(a,n),l=this.texData.get(o.dataId);l.isPacked=!1,l.texture={texture:t,texShape:[r,s]},l.texShape=[r,s];let u=Md(a),p=new C5(u,!1,i),c=this.runWebGLProgram(p,[o],n,[[r,s]]);return c.shape=a,l.texture=null,this.disposeIntermediateTensorInfo(o),c.dataId}write(t,a,n){if((B().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||B().getBool("DEBUG"))&&this.checkNumericalProblems(t),n==="complex64"&&t!=null)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let r={id:this.nextDataId()};return this.texData.set(r,{shape:a,dtype:n,values:t,usage:mn.UPLOAD,refCount:1}),r}refCount(t){return this.texData.has(t)?this.texData.get(t).refCount:0}incRef(t){let a=this.texData.get(t);a.refCount++}decRef(t){if(this.texData.has(t)){let a=this.texData.get(t);a.refCount--}}move(t,a,n,r,s){if(B().getBool("DEBUG")&&this.checkNumericalProblems(a),r==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(t,{shape:n,dtype:r,values:a,usage:mn.UPLOAD,refCount:s})}disposeIntermediateTensorInfo(t){this.disposeData(t.dataId)}readSync(t){let a=this.texData.get(t),{values:n,dtype:r,complexTensorInfos:s,slice:i,shape:o,isPacked:l}=a;if(i!=null){let d;l?d=new qr(o,Vr):d=new Jn(o,Vr);let h=this.runWebGLProgram(d,[{dataId:t,shape:o,dtype:r}],r),m=this.readSync(h.dataId);return this.disposeIntermediateTensorInfo(h),m}if(n!=null)return this.convertAndCacheOnCPU(t);if(r==="string")return n;let u=this.activeTimers!=null,p;u&&(p=v.now());let c;if(r==="complex64"){let d=this.readSync(s.real.dataId),h=this.readSync(s.imag.dataId);c=C.mergeRealAndImagArrays(d,h)}else c=this.getValuesFromTexture(t);return u&&(this.downloadWaitMs+=v.now()-p),this.convertAndCacheOnCPU(t,c)}async read(t){if(this.pendingRead.has(t)){let m=this.pendingRead.get(t);return new Promise(f=>m.push(f))}let a=this.texData.get(t),{values:n,shape:r,slice:s,dtype:i,complexTensorInfos:o,isPacked:l}=a;if(s!=null){let m;l?m=new qr(r,Vr):m=new Jn(r,Vr);let f=this.runWebGLProgram(m,[{dataId:t,shape:r,dtype:i}],i),g=this.read(f.dataId);return this.disposeIntermediateTensorInfo(f),g}if(n!=null)return this.convertAndCacheOnCPU(t);if(B().getBool("DEBUG")&&!B().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&B().getNumber("WEBGL_VERSION")===2)throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");let u=null,p;if(i!=="complex64"&&B().get("WEBGL_BUFFER_SUPPORTED")){p=this.decode(t);let m=this.texData.get(p.dataId);u=this.gpgpu.createBufferFromTexture(m.texture.texture,...Zc(r))}this.pendingRead.set(t,[]),i!=="complex64"&&await this.gpgpu.createAndWaitForFence();let c;if(i==="complex64"){let m=await Promise.all([this.read(o.real.dataId),this.read(o.imag.dataId)]),f=m[0],g=m[1];c=C.mergeRealAndImagArrays(f,g)}else if(u==null)c=this.getValuesFromTexture(t);else{let m=v.sizeFromShape(r);c=this.gpgpu.downloadFloat32MatrixFromBuffer(u,m)}if(p!=null&&this.disposeIntermediateTensorInfo(p),u!=null){let m=this.gpgpu.gl;ce(m,()=>m.deleteBuffer(u))}let d=this.convertAndCacheOnCPU(t,c),h=this.pendingRead.get(t);return this.pendingRead.delete(t),h.forEach(m=>m(d)),this.pendingDisposal.has(t)&&(this.pendingDisposal.delete(t),this.disposeData(t)&&It().removeDataId(t,this),this.pendingDeletes--),d}readToGPU(t,a={}){let n=this.texData.get(t),{values:r,shape:s,slice:i,dtype:o,isPacked:l,texture:u}=n;if(o==="complex64")throw new Error("Does not support reading texture for complex64 dtype.");if(i!=null){let h;l?h=new qr(s,Vr):h=new Jn(s,Vr);let m=this.runWebGLProgram(h,[{dataId:t,shape:s,dtype:o}],o),f=this.readToGPU(m,a);return this.disposeIntermediateTensorInfo(m),f}if(u==null)throw r!=null?new Error("Data is not on GPU but on CPU."):new Error("There is no data on GPU or CPU.");let p=this.decode(t,a.customTexShape),c=It().makeTensorFromTensorInfo(p),d=this.texData.get(p.dataId);return Object.assign({tensorRef:c},d.texture)}bufferSync(t){let a=this.readSync(t.dataId);if(t.dtype==="string")try{let n=a.map(r=>v.decodeString(r));return _e(t.shape,t.dtype,n)}catch(n){throw new Error("Failed to decode encoded string bytes into utf-8")}return _e(t.shape,t.dtype,a)}checkNumericalProblems(t){if(t!=null)for(let a=0;a<t.length;a++){let n=t[a];if(!bv(n))throw B().getBool("WEBGL_RENDER_FLOAT32_CAPABLE")?Error(`The value ${n} cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`):Error(`The value ${n} cannot be represented on this device.`)}}getValuesFromTexture(t){let{shape:a,dtype:n,isPacked:r}=this.texData.get(t),s=v.sizeFromShape(a);if(B().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let d=this.decode(t),h=this.texData.get(d.dataId),m=this.gpgpu.downloadMatrixFromPackedTexture(h.texture.texture,...Zc(a)).subarray(0,s);return this.disposeIntermediateTensorInfo(d),m}let i=B().getBool("WEBGL_PACK")&&r===!0,o=i?Md(a):a,l=i?new RH(o):new NH(o),u=this.runWebGLProgram(l,[{shape:o,dtype:n,dataId:t}],"float32"),p=this.texData.get(u.dataId),c=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(p.texture.texture,p.texShape[0],p.texShape[1]).subarray(0,s);return this.disposeIntermediateTensorInfo(u),c}timerAvailable(){return B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}time(t){let a=this.activeTimers,n=[],r=!1;this.programTimersStack==null?(this.programTimersStack=n,r=!0):this.activeTimers.push(n),this.activeTimers=n,t();let s=v.flatten(this.activeTimers.map(l=>l.query)).filter(l=>l!=null),i=v.flatten(this.activeTimers.map(l=>l.name)).filter(l=>l!=null);this.activeTimers=a,r&&(this.programTimersStack=null);let o={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};return(async()=>{if(B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let l=await Promise.all(s);o.kernelMs=v.sum(l),o.getExtraProfileInfo=()=>l.map((u,p)=>({name:i[p],ms:u})).map(u=>`${u.name}: ${u.ms}`).join(", ")}else o.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,o})()}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:v.now(),endMs:null}}endTimer(t){return B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),t):(t.endMs=v.now(),t)}async getQueryTime(t){if(B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)return this.gpgpu.waitForQueryAndGetTime(t);let a=t;return a.endMs-a.startMs}disposeData(t,a=!1){if(this.pendingDisposal.has(t))return!1;if(!this.texData.has(t))return!0;if(a?this.texData.get(t).refCount=0:this.texData.get(t).refCount--,!a&&this.texData.get(t).refCount>0)return!1;if(this.pendingRead.has(t))return this.pendingDisposal.add(t),this.pendingDeletes++,!1;this.releaseGPUData(t);let{complexTensorInfos:n}=this.texData.get(t);return n!=null&&(this.disposeData(n.real.dataId,a),this.disposeData(n.imag.dataId,a)),this.texData.delete(t),!0}releaseGPUData(t){let{texture:a,dtype:n,texShape:r,usage:s,isPacked:i,slice:o}=this.texData.get(t),l=o&&o.origDataId||t,u=this.dataRefCount.get(l);u>1?this.dataRefCount.set(l,u-1):(this.dataRefCount.delete(l),a!=null&&(this.numBytesInGPU-=this.computeBytes(r,n),this.textureManager.releaseTexture(a,r,s,i)));let p=this.texData.get(t);p.texture=null,p.texShape=null,p.isPacked=!1,p.slice=null}getTexture(t){return this.uploadToGPU(t),this.texData.get(t).texture.texture}getDataInfo(t){return this.texData.get(t)}shouldExecuteOnCPU(t,a=jj){return B().getBool("WEBGL_CPU_FORWARD")&&t.every(n=>this.texData.get(n.dataId).texture==null&&v.sizeFromShape(n.shape)<a)}getGPGPUContext(){return this.gpgpu}where(t){C.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let a=t.dataSync();return Vj(t.shape,a)}packedUnaryOp(t,a,n){let r=new qr(t.shape,a),s=this.compileAndRun(r,[t],n);return It().makeTensorFromTensorInfo(s)}abs(t){if(this.shouldExecuteOnCPU([t])&&t.dtype!=="complex64"){let r=h8(this.texData.get(t.dataId).values);return this.makeOutput(t.shape,t.dtype,r)}if(B().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,E5,t.dtype);let a=new Jn(t.shape,E5),n=this.compileAndRun(a,[t]);return It().makeTensorFromTensorInfo(n)}makeTensorInfo(t,a,n){let r;if(a==="string"&&n!=null&&n.length>0&&v.isString(n[0])){let s=n.map(i=>v.encodeString(i));r=this.write(s,t,a)}else r=this.write(n,t,a);return this.texData.get(r).usage=null,{dataId:r,shape:t,dtype:a}}makeOutput(t,a,n){return It().makeTensorFromTensorInfo(this.makeTensorInfo(t,a,n),this)}unpackTensor(t){let a=new Bj(t.shape);return this.runWebGLProgram(a,[t],t.dtype)}packTensor(t){let a=new Sj(t.shape);return this.runWebGLProgram(a,[t],t.dtype,null,!0)}packedReshape(t,a){let n=[ai(t.shape),...ni(t.shape)],r={dtype:t.dtype,shape:n,dataId:t.dataId},s=[ai(a),...ni(a)],i=new g8(s,n),o=!0,l=[n],u=this.runWebGLProgram(i,[r],t.dtype,l,o);return{dataId:u.dataId,shape:a,dtype:u.dtype}}decode(t,a){let n=this.texData.get(t),{isPacked:r,shape:s,dtype:i}=n;if(a!=null){let d=v.sizeFromShape(s),h=a[0]*a[1]*4;v.assert(d<=h,()=>"customTexShape is too small. Row * Column * 4 should be equal or larger than the size of the tensor data.")}let o=Md(s),l;r?l=new TH(o):l=new CH(o);let u=!0,p=[a!=null?a:Zc(o)],c=this.runWebGLProgram(l,[{shape:o,dtype:i,dataId:t}],i,p,u,a);return{dtype:i,shape:s,dataId:c.dataId}}runWebGLProgram(t,a,n,r,s=!1,i){let o=this.makeTensorInfo(t.outputShape,n),l=this.texData.get(o.dataId);if(t.packedOutput&&(l.isPacked=!0),t.outPackingScheme===Qd.DENSE){let y=i!=null?i:Zc(t.outputShape);l.texShape=y.map(x=>x*2)}if(t.outTexUsage!=null&&(l.usage=t.outTexUsage),v.sizeFromShape(o.shape)===0)return l.values=v.getTypedArrayFromDType(o.dtype,0),o;let u=[],p=a.map(y=>{if(y.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let x=this.texData.get(y.dataId);if(x.texture==null){if(!t.packedInputs&&v.sizeFromShape(y.shape)<=B().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:y.shape,texData:null,isUniform:!0,uniformValues:x.values};t.packedInputs&&(x.isPacked=!0,x.shape=y.shape)}if(this.uploadToGPU(y.dataId),!!x.isPacked!=!!t.packedInputs)y=x.isPacked?this.unpackTensor(y):this.packTensor(y),u.push(y),x=this.texData.get(y.dataId);else if(x.isPacked&&!ep(x.shape,y.shape)){let A=y,b=y.shape;y.shape=x.shape,y=this.packedReshape(y,b),u.push(y),x=this.texData.get(y.dataId),A.shape=b}return{shape:y.shape,texData:x,isUniform:!1}});this.uploadToGPU(o.dataId);let c={shape:o.shape,texData:l,isUniform:!1},d=SH(t,p,c),h=this.getAndSaveBinary(d,()=>kH(this.gpgpu,t,p,c)),m=this.activeTimers!=null,f;m&&(f=this.startTimer()),B().get("ENGINE_COMPILE_ONLY")||IH(this.gpgpu,h,p,c,r),u.forEach(y=>this.disposeIntermediateTensorInfo(y)),m&&(f=this.endTimer(f),this.activeTimers.push({name:t.constructor.name,query:this.getQueryTime(f)}));let g=B().getNumber("WEBGL_FLUSH_THRESHOLD");if(g>0){let y=v.now();y-this.lastGlFlushTime>g&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=y)}if(!B().getBool("WEBGL_LAZILY_UNPACK")&&l.isPacked&&s===!1){let y=this.unpackTensor(o);return this.disposeIntermediateTensorInfo(o),y}return o}compileAndRun(t,a,n,r,s=!1){return n=n||a[0].dtype,this.runWebGLProgram(t,a,n,r,s)}getAndSaveBinary(t,a){return t in this.binaryCache||(this.binaryCache[t]=a()),this.binaryCache[t]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(B().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(t=>{this.gpgpu.deleteProgram(this.binaryCache[t].webGLProgram),delete this.binaryCache[t]}),this.textureManager.dispose(),this.canvas!=null&&typeof HTMLCanvasElement!="undefined"&&this.canvas instanceof HTMLCanvasElement?this.canvas.remove():this.canvas=null,this.gpgpuCreatedLocally&&(this.gpgpu.program=null,this.gpgpu.dispose()),this.disposed=!0)}floatPrecision(){return this.floatPrecisionValue==null&&(this.floatPrecisionValue=De(()=>{if(!B().get("WEBGL_RENDER_FLOAT32_ENABLED")){let t=B().getBool("DEBUG");B().set("DEBUG",!1);let a=this.abs(Ge(1e-8)).dataSync()[0];if(B().set("DEBUG",t),a>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?Uj:Gj}uploadToGPU(t){let a=this.texData.get(t),{shape:n,dtype:r,values:s,texture:i,usage:o,isPacked:l}=a;if(i!=null)return;let u=this.activeTimers!=null,p;u&&(p=v.now());let c=a.texShape;if(c==null&&(c=Ov(n,l),a.texShape=c),s!=null){let d=Md(n),h,m=c[1],f=c[0],g=s instanceof Uint8Array||s instanceof Uint8ClampedArray;(l||!g)&&([m,f]=ju(c[0],c[1])),l?h=new MH(d,g):h=new C5(d,g);let y=g?[f,m]:c,x=this.makeTensorInfo(y,r),A=this.texData.get(x.dataId);g?A.usage=mn.PIXELS:A.usage=mn.UPLOAD,A.texShape=y,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(x.dataId),m,f,s);let b=[[f,m]],w=this.runWebGLProgram(h,[x],r,b,!0),I=this.texData.get(w.dataId);a.texShape=I.texShape,a.isPacked=I.isPacked,a.usage=I.usage,B().get("ENGINE_COMPILE_ONLY")?this.disposeData(w.dataId):(a.texture=I.texture,a.values=null,this.texData.delete(w.dataId)),this.disposeIntermediateTensorInfo(x),u&&(this.uploadWaitMs+=v.now()-p)}else{let d=this.acquireTexture(c,o,r,l);a.texture=d}}convertAndCacheOnCPU(t,a){let n=this.texData.get(t),{dtype:r}=n;return a!=null&&(n.values=Kj(a,r)),n.values}acquireTexture(t,a,n,r){if(this.numBytesInGPU+=this.computeBytes(t,n),!this.warnedAboutMemory&&this.numBytesInGPU>this.numMBBeforeWarning*1024*1024){let s=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(`High memory usage in GPU: ${s} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(t,a,r)}computeBytes(t,a){return t[0]*t[1]*v.bytesPerElement(a)}checkCompileCompletion(){for(let[,t]of Object.entries(this.binaryCache))this.checkCompletion_(t)}async checkCompileCompletionAsync(){let t=[];if(this.gpgpu.parallelCompilationExtension){for(let[,a]of Object.entries(this.binaryCache))t.push(this.checkCompletionAsync_(a));return Promise.all(t)}else{for(let[,a]of Object.entries(this.binaryCache)){let n=new Promise(r=>{try{this.checkCompletion_(a),r(!0)}catch(s){throw s}});t.push(n)}return Promise.all(t)}}async checkCompletionAsync_(t){return this.gpgpu.gl.getProgramParameter(t.webGLProgram,this.gpgpu.parallelCompilationExtension.COMPLETION_STATUS_KHR)?this.checkCompletion_(t):(await G7(),this.checkCompletionAsync_(t))}checkCompletion_(t){if(this.gpgpu.gl.getProgramParameter(t.webGLProgram,this.gpgpu.gl.LINK_STATUS)===!1)throw console.log(this.gpgpu.gl.getProgramInfoLog(t.webGLProgram)),this.gpgpu.gl.getShaderParameter(t.fragmentShader,this.gpgpu.gl.COMPILE_STATUS)===!1?(N3(t.source,this.gpgpu.gl.getShaderInfoLog(t.fragmentShader)),new Error("Failed to compile fragment shader.")):new Error("Failed to link vertex and fragment shaders.");return!0}getUniformLocations(){for(let t of Object.values(this.binaryCache)){this.gpgpu.buildVao(t.webGLProgram);let{variablesLocations:a,customUniformLocations:n,infLoc:r,nanLoc:s,outShapeLocation:i,outShapeStridesLocation:o,outTexShapeLocation:l}=Xv(this.gpgpu,t.program,t.webGLProgram);t.variablesLocations=a,t.customUniformLocations=n,t.infLoc=r,t.nanLoc=s,t.outShapeLocation=i,t.outShapeStridesLocation=o,t.outTexShapeLocation=l}}createTensorFromGPUData(t,a,n){t.channels=t.channels||"RGBA";let{texture:r,height:s,width:i,channels:o}=t,l=It().backend;if(!l.gpgpu.gl.isTexture(r))throw new Error("The texture is invalid. Also, please make sure the texture and the TFJS WebGL backend are using the same canvas. If you want to use your own custom canvas, you have to create and use the custom TFJS WebGL backend created from the canvas through 'new tf.MathBackendWebGL(customCanvas)'.");let u=l.writeTexture(r,a,n,s,i,o);return It().makeTensorFromDataId(u,a,n,l)}};Jp.nextDataId=0;function Kj(e,t){if(t==="float32"||t==="complex64")return e;if(t==="int32"||t==="bool"){let a=t==="int32"?new Int32Array(e.length):new Uint8Array(e.length);for(let n=0;n<a.length;++n)a[n]=Math.round(e[n]);return a}else throw new Error(`Unknown dtype ${t}`)}var Yj="4.22.0";function x8(){B().set("WEBGL_FORCE_F16_TEXTURES",!0)}Fp.isBrowser()&&al("webgl",()=>new Jp,2);var Zj={forceHalfFloat:x8},z3=`
  if (isnan(a)) return a;
  if (isnan(b)) return b;
`,ri=class{constructor(e,t,a){this.variableNames=["A","B"],this.outputShape=C.assertAndGetBroadcastShape(t,a),this.enableShapeUniforms=ya(this.outputShape.length),this.userCode=`
      float binaryOperation(float a, float b) {
        ${e}
      }

      void main() {
        float a = getAAtOutCoords();
        float b = getBAtOutCoords();
        setOutput(binaryOperation(a, b));
      }
    `}},il=`
  result.r = isNaN.r ? NAN : result.r;
  result.g = isNaN.g ? NAN : result.g;
  result.b = isNaN.b ? NAN : result.b;
  result.a = isNaN.a ? NAN : result.a;
`,Ju=class{constructor(e,t,a,n=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=C.assertAndGetBroadcastShape(t,a);let r=this.outputShape.length;this.enableShapeUniforms=ya(r);let s="";if(n)if(r===0||v.sizeFromShape(this.outputShape)===1)s=`
          result.y = 0.;
          result.z = 0.;
          result.w = 0.;
        `;else if(s=`
          ${ft(r)} coords = getOutputCoords();
        `,r===1)this.enableShapeUniforms?s+=`
            result.y = (coords + 1) >= outShape ? 0. : result.y;
            result.z = 0.;
            result.w = 0.;
          `:s+=`
            result.y = (coords + 1) >= ${this.outputShape[0]} ? 0. : result.y;
            result.z = 0.;
            result.w = 0.;
          `;else{let i=ka("coords",r);this.enableShapeUniforms?s+=`
            bool nextRowOutOfBounds =
              (${i[r-2]} + 1) >= outShape[${r} - 2];
            bool nextColOutOfBounds =
              (${i[r-1]} + 1) >= outShape[${r} - 1];
            result.y = nextColOutOfBounds ? 0. : result.y;
            result.z = nextRowOutOfBounds ? 0. : result.z;
            result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;
          `:s+=`
            bool nextRowOutOfBounds =
              (${i[r-2]} + 1) >= ${this.outputShape[r-2]};
            bool nextColOutOfBounds =
              (${i[r-1]} + 1) >= ${this.outputShape[r-1]};
            result.y = nextColOutOfBounds ? 0. : result.y;
            result.z = nextRowOutOfBounds ? 0. : result.z;
            result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;
          `}this.userCode=`
      vec4 binaryOperation(vec4 a, vec4 b) {
        ${e}
      }

      void main() {
        vec4 a = getAAtOutCoords();
        vec4 b = getBAtOutCoords();

        vec4 result = binaryOperation(a, b);
        ${s}

        setOutput(result);
      }
    `}};function en(e){let{inputs:t,backend:a}=e,{x:n}=t;return a.incRef(n.dataId),{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}var Jj={kernelName:qi,backendName:"webgl",kernelFunc:en};function fs(e){let{inputs:t,backend:a}=e,{real:n,imag:r}=t,s=a.makeTensorInfo(n.shape,"complex64"),i=a.texData.get(s.dataId),o=en({inputs:{x:n},backend:a}),l=en({inputs:{x:r},backend:a});return i.complexTensorInfos={real:o,imag:l},s}var Qj={kernelName:cp,backendName:"webgl",kernelFunc:fs},A8="return (a < 0.) ? b * a : a;",b8=`
  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function eq(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{alpha:s}=n,i=a.makeTensorInfo([],"float32",v.createScalarValue(s,"float32")),o=B().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Ju(b8,r.shape,i.shape):new ri(A8,r.shape,i.shape),l=a.runWebGLProgram(o,[r,i],"float32");return a.disposeIntermediateTensorInfo(i),l}var tq={kernelName:Zi,backendName:"webgl",kernelFunc:eq},v8="return (a < 0.) ? b * a : a;",w8=`
  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function aq(e){let{inputs:t,backend:a}=e,{x:n,alpha:r}=t,s=B().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Ju(w8,n.shape,r.shape):new ri(v8,n.shape,r.shape);return a.runWebGLProgram(s,[n,r],"float32")}var nq={kernelName:Io,backendName:"webgl",kernelFunc:aq},Qu="if (isnan(x)) return x;";function tt({opSnippet:e,packedOpSnippet:t,cpuKernelImpl:a,dtype:n}){return({inputs:r,backend:s})=>{let{x:i}=r,o=s,l=n||i.dtype;if(o.shouldExecuteOnCPU([i])&&a!=null){let c=o.texData.get(i.dataId),d=a(c.values,l);return o.makeTensorInfo(i.shape,l,d)}let u=B().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,p;return u?p=new qr(i.shape,t):p=new Jn(i.shape,e),o.runWebGLProgram(p,[i],l)}}function ma({opSnippet:e,packedOpSnippet:t,checkOutOfBounds:a=!1,supportsComplex:n=!1,cpuKernelImpl:r,dtype:s}){return({inputs:i,backend:o})=>{let{a:l,b:u}=i,p=o;if(n&&l.dtype==="complex64"){let m=p.texData.get(l.dataId),f=p.texData.get(u.dataId),[g,y]=[[m.complexTensorInfos.real,f.complexTensorInfos.real],[m.complexTensorInfos.imag,f.complexTensorInfos.imag]].map(A=>{let[b,w]=A,I={dataId:b.dataId,dtype:b.dtype,shape:l.shape},T={dataId:w.dataId,dtype:w.dtype,shape:u.shape},N=new ri(e,l.shape,u.shape);return p.runWebGLProgram(N,[I,T],ca(b.dtype,w.dtype))}),x=fs({inputs:{real:g,imag:y},backend:p});return p.disposeIntermediateTensorInfo(g),p.disposeIntermediateTensorInfo(y),x}let c=s||ca(l.dtype,u.dtype);if((l.dtype==="string"||u.dtype==="string"||p.shouldExecuteOnCPU([l,u]))&&r!=null){let m=p.texData.get(l.dataId).values,f=p.texData.get(u.dataId).values,g=l.dtype==="string"?C.fromUint8ToStringArray(m):m,y=l.dtype==="string"?C.fromUint8ToStringArray(f):f,[x,A]=r(l.shape,u.shape,g,y,c),b=p.makeTensorInfo(A,c),w=p.texData.get(b.dataId);return w.values=x,b}let d=B().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,h;return d?h=new Ju(t,l.shape,u.shape,a):h=new ri(e,l.shape,u.shape),p.runWebGLProgram(h,[l,u],c)}}function tp(e,t=!1){if(e==="linear")return t?Dj:Mj;if(e==="relu")return t?zj:Pj;if(e==="elu")return t?Oj:$j;if(e==="relu6")return t?Lj:_j;if(e==="prelu")return t?w8:v8;if(e==="leakyrelu")return t?b8:A8;if(e==="sigmoid")return t?Wj:Fj;throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}var k8=class{constructor(e,t,a,n=!1,r=!1,s=!1,i=null,o=!1,l=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=a,this.enableShapeUniforms=ya(this.outputShape.length);let u=n?e[1]:e[2],p=Math.ceil(u/2),c=n?"i * 2, rc.y":"rc.y, i * 2",d=r?"rc.z, i * 2":"i * 2, rc.z",h=n?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],m=r?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],f="",g="";i&&(o?f=`vec4 activation(vec4 a) {
          vec4 b = getPreluActivationWeightsAtOutCoords();
          ${i}
        }`:l?f=`vec4 activation(vec4 a) {
          vec4 b = getLeakyreluAlphaAtOutCoords();
          ${i}
        }`:f=`vec4 activation(vec4 x) {
          ${i}
        }`,g="result = activation(result);");let y=s?"result += getBiasAtOutCoords();":"";s&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),l&&this.variableNames.push("leakyreluAlpha");let x="rc.x",A="rc.x";e[0]<t[0]?x=`imod(rc.x, ${e[0]})`:t[0]<e[0]&&(A=`imod(rc.x, ${t[0]})`),this.userCode=`
      ${f}
      // Don't use uniform for sharedDimensionPacked for performance.
      const float sharedDimension = ${p}.0;

      vec4 dot2x2ARowBCol(ivec3 rc) {
        vec4 result = vec4(0);
        int batchA = ${x};
        int batchB = ${A};
        for (int i = 0; i < ${p}; i++) {
          vec4 a = getMatrixA(batchA, ${c});
          vec4 b = getMatrixB(batchB, ${d});

          // These swizzled products need to be separately added.
          // See: https://github.com/tensorflow/tfjs/issues/1735
          result += (${h[0]} * ${m[0]});
          result += (${h[1]} * ${m[1]});
        }
        return result;
      }

      void main() {
        ivec3 rc = getOutputCoords();
        vec4 result = dot2x2ARowBCol(rc);

        ${y}

        ${g}

        setOutput(result);
      }
    `}},M5={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},$5=class{constructor(e,t,a){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=C.assertAndGetBroadcastShape(t,a),this.userCode=`
      float binaryOpComplex(
          float areal, float aimag, float breal, float bimag) {
        ${e}
      }

      void main() {
        float areal = getARealAtOutCoords();
        float aimag = getAImagAtOutCoords();
        float breal = getBRealAtOutCoords();
        float bimag = getBImagAtOutCoords();
        setOutput(binaryOpComplex(areal, aimag, breal, bimag));
      }
    `}},P5="return a * b;";function L3(e){let{inputs:t,backend:a}=e,{a:n,b:r}=t,s=C.upcastType(n.dtype,r.dtype);if(n.dtype==="complex64"){let o=a.texData.get(n.dataId),l=a.texData.get(r.dataId),u=new $5(M5.REAL,n.shape,r.shape),p=new $5(M5.IMAG,n.shape,r.shape),c=[{dataId:o.complexTensorInfos.real.dataId,dtype:o.complexTensorInfos.real.dtype,shape:n.shape},{dataId:o.complexTensorInfos.imag.dataId,dtype:o.complexTensorInfos.imag.dtype,shape:n.shape},{dataId:l.complexTensorInfos.real.dataId,dtype:l.complexTensorInfos.real.dtype,shape:r.shape},{dataId:l.complexTensorInfos.imag.dataId,dtype:l.complexTensorInfos.imag.dtype,shape:r.shape}],d=a.runWebGLProgram(u,c,"float32"),h=a.runWebGLProgram(p,c,"float32"),m=fs({inputs:{real:d,imag:h},backend:a});return a.disposeIntermediateTensorInfo(d),a.disposeIntermediateTensorInfo(h),m}if(a.shouldExecuteOnCPU([n,r])){let o=a.texData.get(n.dataId),l=a.texData.get(r.dataId),[u,p]=ej(n.shape,r.shape,o.values,l.values,s),c=a.makeTensorInfo(p,s),d=a.texData.get(c.dataId);return d.values=u,c}let i;return B().getBool("WEBGL_PACK_BINARY_OPERATIONS")?i=new Ju(P5,n.shape,r.shape):i=new ri(P5,n.shape,r.shape),a.runWebGLProgram(i,[n,r],s)}var rq={kernelName:yo,backendName:"webgl",kernelFunc:L3};function sq(e,t,a){let n=[ai(e.shape),...ni(e.shape)],r={dtype:e.dtype,shape:n,dataId:e.dataId},s=[ai(t),...ni(t)],i=new g8(s,n),o=!0,l=[n],u=a.runWebGLProgram(i,[r],e.dtype,l,o);return{dataId:u.dataId,shape:t,dtype:u.dtype}}function pe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{shape:s}=n,i=a,o=v.sizeFromShape(r.shape),l=v.inferFromImplicitShape(s,o),u=v.sizeFromShape(l);v.assert(o===u,()=>`The new shape (${l}) has ${u} elements and the old shape (${r.shape}) has ${o} elements. The new shape and old shape must have the same number of elements.`);let p=i.texData.get(r.dataId);return p.isPacked&&!ep(r.shape,l)&&!(p.texture!==null&&ep(p.shape,l))?sq(r,l,i):(i.incRef(r.dataId),{dataId:r.dataId,shape:l,dtype:r.dtype})}var iq={kernelName:Eu,backendName:"webgl",kernelFunc:pe},_5=class{constructor(e,t){this.variableNames=["x"];let{windowSize:a,batchSize:n,inSize:r,outSize:s}=e;this.outputShape=[n,s];let i=Math.floor(a/4)*4,o=a%4,l="sumValue += dot(values, ones);";if(t!=null){let p=1/t;l=`sumValue += dot(values * ${v.isInt(p)?p.toPrecision(2):p}, ones);`}let u="";r%a>0&&(u=`
        if (inIdx < 0 || inIdx >= ${r}) {
          return 0.0;
        }
      `),this.userCode=`
      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);

      float getValue(int batch, int inIdx) {
        ${u}
        return getX(batch, inIdx);
      }

      void main() {
        ivec2 coords = getOutputCoords();
        int batch = coords[0];
        int outIdx = coords[1];
        int inOffset = outIdx * ${a};

        float sumValue = 0.0;

        for (int i = 0; i < ${i}; i += 4) {
          int inIdx = inOffset + i;
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2),
            getValue(batch, inIdx + 3)
          );

          ${l}
        }

        int inIdx = inOffset + ${i};
        if (${o===1}) {
          vec4 values = vec4(getValue(batch, inIdx), 0.0, 0.0, 0.0);

          ${l}
        } else if (${o===2}) {
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1), 0.0, 0.0);

          ${l}
        } else if (${o===3}) {
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2), 0.0);

          ${l}
        }
        setOutput(sumValue);
      }
    `}},oq=class{constructor(e,t){this.variableNames=["x"];let{windowSize:a,batchSize:n,inSize:r,outSize:s}=e;this.outputShape=[n,s];let i="0.0",o="";t==="prod"?i="1.0":t==="min"?(i="1.0 / 1e-20",o="min"):t==="max"&&(i="-1.0 / 1e-20",o="max");let l=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="sum"?l="sumValue":t==="prod"?l="prodValue":t==="all"?l="allValue":t==="any"&&(l="anyValue");let u=Math.floor(a/4)*4,p=a%4,c=`
      if (${t==="sum"}) {
        sumValue += dot(values, ones);
      } else if (${t==="prod"}) {
        vec2 tmp = vec2(values[0], values[1]) * vec2(values[2], values[3]);
        prodValue *= tmp[0] * tmp[1];
      } else {
        minMaxValue = ${o}(values, minMaxValue);
        if (${t==="min"} || ${t==="max"}) {
          minMaxValue = ${o}(values, minMaxValue);
          bvec4 isNaN = isnan(values);
          if (isNaN.r || isNaN.g || isNaN.b || isNaN.a) {
            minMaxValue = vec4(NAN);
          }
        }
      }
    `,d="vec4";t==="all"?(i="1.0",c=`
        bool reducedAllValue = all(values);
        float floatedReducedAllValue = float(reducedAllValue);
        allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0);
      `,d="bvec4"):t==="any"&&(i="0.0",c=`
        bool reducedAnyValue = any(values);
        float floatedReducedAnyValue = float(reducedAnyValue);
        anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);
      `,d="bvec4");let h="";r%a>0&&(h=`
        if (inIdx < 0 || inIdx >= ${r}) {
          return initializationValue;
        }
      `),this.userCode=`
      const float initializationValue = ${i};
      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);

      float getValue(int batch, int inIdx) {
        ${h}
        return getX(batch, inIdx);
      }

      void main() {
        ivec2 coords = getOutputCoords();
        int batch = coords[0];
        int outIdx = coords[1];
        int inOffset = outIdx * ${a};

        vec4 minMaxValue = vec4(${i});
        float prodValue = 1.0;
        float sumValue = 0.0;
        float allValue = 1.0;
        float anyValue = 0.0;

        for (int i = 0; i < ${u}; i += 4) {
          int inIdx = inOffset + i;
          ${d} values = ${d}(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2),
            getValue(batch, inIdx + 3)
          );

          ${c}
        }

        int inIdx = inOffset + ${u};
        if (${p===1}) {
          ${d} values = ${d}(
            getValue(batch, inIdx),
            initializationValue,
            initializationValue,
            initializationValue
          );

          ${c}
        } else if (${p===2}) {
          ${d} values = ${d}(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            initializationValue,
            initializationValue
          );

          ${c}
        } else if (${p===3}) {
          ${d} values = ${d}(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2),
            initializationValue
          );

          ${c}
        }
        setOutput(${l});
      }
    `}};function lq(e){let t=[];for(;t.length===0||t[t.length-1].outSize!==1;){let a=t.length?t[t.length-1].outSize:e[1],n=C.computeOptimalWindowSize(a);t.push({inSize:a,windowSize:n,outSize:Math.ceil(a/n)})}return t}function ol(e,t,a,n){let r=lq(e.shape),s=e;for(let i=0;i<r.length;i++){let{inSize:o,windowSize:l,outSize:u}=r[i],p,c;a==="mean"?p=i===0?new _5({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u},o):new _5({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u}):p=new oq({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u},a),c=s,s=n.runWebGLProgram(p,[s],t),c.dataId!==e.dataId&&n.disposeIntermediateTensorInfo(c)}return s}var uq=class{constructor(e,t){this.variableNames=["A"];let a=new Array(e.length);for(let s=0;s<a.length;s++)a[s]=e[t[s]];this.outputShape=a,this.rank=a.length;let n=ft(this.rank),r=dq(t);this.userCode=`
    void main() {
      ${n} resRC = getOutputCoords();
      setOutput(getA(${r}));
    }
    `}};function dq(e){let t=e.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let a=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],n=new Array(t);for(let r=0;r<e.length;r++)n[e[r]]=a[r];return n.join()}var pq=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;let a=new Array(e.length);for(let u=0;u<a.length;u++)a[u]=e[t[u]];if(this.outputShape=a,this.rank=a.length,this.rank>6)throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);let n=ft(this.rank),r=f8("rc",this.rank),s=new Array(this.rank);for(let u=0;u<t.length;u++)s[t[u]]=r[u];let i=`vec2(${s.slice(-2).join()})`,o=`++${r[this.rank-1]} < ${a[this.rank-1]}`,l=`getChannel(getA(${s.join()}), ${i})`;this.userCode=`
    void main() {
      ${n} rc = getOutputCoords();
      vec4 result = vec4(0.);
      result[0] = ${l};
      if(${o}) {
        result[1] = ${l};
      }
      --${r[this.rank-1]};
      if(++${r[this.rank-2]} < ${a[this.rank-2]}) {
        result[2] = ${l};
        if(${o}) {
          result[3] = ${l};
        }
      }
      setOutput(result);
    }
    `}};function s0(e,t,a){let n=B().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new pq(e.shape,t):new uq(e.shape,t);return a.runWebGLProgram(n,[e],e.dtype)}function cq(e,t,a,n){let r=t,s=e.shape.length,i=v.parseAxisParam(r,e.shape),o=i,l=C.getAxesPermutation(o,s),u=l!=null,p=e;u&&(p=s0(e,l,n),o=C.getInnerMostAxes(o.length,s)),C.assertAxesAreInnerMostDims("sum",o,s);let[c,d]=C.computeOutAndReduceShapes(p.shape,o),h=c;a&&(h=C.expandShapeToKeepDim(c,i));let m=v.sizeFromShape(d),f=v.sizeFromShape(e.shape)/m,g=pe({inputs:{x:p},attrs:{shape:[f,m]},backend:n}),y=_p(e.dtype),x=ol(g,y,"sum",n),A=pe({inputs:{x},attrs:{shape:h},backend:n});return n.disposeIntermediateTensorInfo(g),n.disposeIntermediateTensorInfo(x),u&&n.disposeIntermediateTensorInfo(p),A}function i0(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;return cq(r,s,i,a)}var hq={kernelName:Go,backendName:"webgl",kernelFunc:i0};function Ca(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{perm:s}=n,i=a,o=r.shape.length,l=new Array(o);for(let p=0;p<l.length;p++)l[p]=r.shape[s[p]];let u;if(i.shouldExecuteOnCPU([r])){let p=i.texData.get(r.dataId).values,c=O3(p,r.shape,r.dtype,s,l);u=i.makeTensorInfo(l,r.dtype);let d=i.texData.get(u.dataId);d.values=c}else u=s0(r,s,i);return u}var mq={kernelName:Ir,backendName:"webgl",kernelFunc:Ca},I8=1e3;function kh({a:e,b:t,transposeA:a,transposeB:n,backend:r,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:o=0,activation:l=null}){let u=e.shape.length,p=t.shape.length,c=a?e.shape[u-2]:e.shape[u-1],d=n?t.shape[p-1]:t.shape[p-2],h=a?e.shape[u-1]:e.shape[u-2],m=n?t.shape[p-2]:t.shape[p-1],f=e.shape.slice(0,-2),g=t.shape.slice(0,-2),y=v.sizeFromShape(f),x=v.sizeFromShape(g),A=nl.assertAndGetBroadcastShape(e.shape.slice(0,-2),t.shape.slice(0,-2)).concat([h,m]);v.assert(c===d,()=>`Error in matMul: inner shapes (${c}) and (${d}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${a} and transposeB=${n} must match.`);let b=a?[y,c,h]:[y,h,c],w=n?[x,m,d]:[x,d,m],I=pe({inputs:{x:e},backend:r,attrs:{shape:b}}),T=pe({inputs:{x:t},backend:r,attrs:{shape:w}}),N=[I,T],M=Math.max(y,x),$=a?I.shape[1]:I.shape[2],E=s!=null,S=i!=null,_=l==="leakyrelu",O=l!=null?tp(l,!0):null,W=E||S||_||O!=null,P;if((h===1||m===1)&&$>I8&&W===!1){let G=I,q=T;a&&(G=Ca({inputs:{x:I},backend:r,attrs:{perm:[0,2,1]}}),N.push(G)),n&&(q=Ca({inputs:{x:T},backend:r,attrs:{perm:[0,2,1]}}),N.push(q));let H=m!==1,V=m===1,Z=G;H&&(Z=pe({inputs:{x:G},backend:r,attrs:{shape:[M,$,1]}}),N.push(Z));let X=m===1?2:1,re=q;V&&(re=pe({inputs:{x:q},backend:r,attrs:{shape:[M,1,$]}}),N.push(re));let ee=L3({inputs:{a:Z,b:re},backend:r});P=i0({inputs:{x:ee},backend:r,attrs:{axis:X,keepDims:!0}}),N.push(ee)}else{let G=ca(e.dtype,t.dtype),q=new k8(b,w,[M,h,m],a,n,E,O,S,_),H=[I,T];if(s!=null&&H.push(s),S&&H.push(i),_){let V=r.makeTensorInfo([],"float32",v.createScalarValue(o,"float32"));H.push(V),N.push(V)}P=r.runWebGLProgram(q,H,G)}let U=pe({inputs:{x:P},backend:r,attrs:{shape:A}});N.push(P);for(let G of N)r.disposeIntermediateTensorInfo(G);return U}function fq(e){let{inputs:t,backend:a,attrs:n}=e,{a:r,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:u,activation:p,leakyreluAlpha:c}=n;return kh({a:r,b:s,transposeA:l,transposeB:u,backend:a,bias:i,preluActivationWeights:o,leakyreluAlpha:c,activation:p})}var gq={kernelName:Zr,backendName:"webgl",kernelFunc:fq},F5="return abs(x);";function yq(e){let{inputs:t,backend:a}=e,{x:n}=t;if(a.shouldExecuteOnCPU([n])&&n.dtype!=="complex64"){let s=a.texData.get(n.dataId),i=h8(s.values);return a.makeTensorInfo(n.shape,n.dtype,i)}let r;return B().getBool("WEBGL_PACK_UNARY_OPERATIONS")?r=new qr(n.shape,F5):r=new Jn(n.shape,F5),a.runWebGLProgram(r,[n],n.dtype)}var xq={kernelName:ou,backendName:"webgl",kernelFunc:yq},Aq=Mn+`
  if (abs(x) > 1.) {
    return NAN;
  }
  return acos(x);
`,bq=tt({opSnippet:Aq}),vq={kernelName:oi,backendName:"webgl",kernelFunc:bq},wq=Mn+`
  if (x < 1.0) return NAN;
return log(x + sqrt(x * x - 1.0));`,kq=tt({opSnippet:wq}),Iq={kernelName:li,backendName:"webgl",kernelFunc:kq},D5="return a + b;",Sq=ma({opSnippet:D5,packedOpSnippet:D5,supportsComplex:!0,cpuKernelImpl:PH}),Cq={kernelName:ls,backendName:"webgl",kernelFunc:Sq},Tq=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((r,s)=>`T${s}`);let a=[];this.variableNames.forEach(r=>{a.push(`float v${r} = get${r}AtOutCoords();`)});let n=this.variableNames.map(r=>`v${r}`).join(" + ");this.userCode=`
      void main() {
        ${a.join(`
        `)}

        float result = ${n};
        setOutput(result);
      }
    `}},Nq=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((r,s)=>`T${s}`);let a=[];this.variableNames.forEach(r=>{a.push(`vec4 v${r} = get${r}AtOutCoords();`)});let n=this.variableNames.map(r=>`v${r}`).join(" + ");this.userCode=`
      void main() {
        ${a.join(`
        `)}

        vec4 result = ${n};
        setOutput(result);
      }
    `}};function oh(e){let{inputs:t,backend:a}=e,n=t;if(n.length===1)return en({inputs:{x:n[0]},backend:a});if(n.length>B().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){let o=Math.floor(n.length/2),l=oh({inputs:n.slice(0,o),backend:a}),u=oh({inputs:n.slice(o),backend:a});return oh({inputs:[l,u],backend:a})}let r=n.map(o=>o.dtype).reduce((o,l)=>ca(o,l)),s=n.map(o=>o.shape),i=B().getBool("WEBGL_PACK")?new Nq(n[0].shape,s):new Tq(n[0].shape,s);return a.runWebGLProgram(i,n,r)}var Rq={kernelName:ui,backendName:"webgl",kernelFunc:oh};function Eq(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n,o=r.shape.length,l=v.parseAxisParam(s,r.shape),u=l,p=C.getAxesPermutation(u,o),c=r;p!=null&&(c=Ca({inputs:{x:r},backend:a,attrs:{perm:p}}),u=C.getInnerMostAxes(u.length,o)),C.assertAxesAreInnerMostDims("all",u,o);let[d,h]=C.computeOutAndReduceShapes(c.shape,u),m=v.sizeFromShape(h),f=pe({inputs:{x:c},backend:a,attrs:{shape:[-1,m]}}),g=ol(f,f.dtype,"all",a),y;if(i){let x=C.expandShapeToKeepDim(d,l);y=pe({inputs:{x:g},backend:a,attrs:{shape:x}})}else y=pe({inputs:{x:g},backend:a,attrs:{shape:d}});return a.disposeIntermediateTensorInfo(f),a.disposeIntermediateTensorInfo(g),p!=null&&a.disposeIntermediateTensorInfo(c),y}var Mq={kernelName:di,backendName:"webgl",kernelFunc:Eq};function $q(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n,o=r.shape.length,l=v.parseAxisParam(s,r.shape),u=l,p=C.getAxesPermutation(u,o),c=r;p!=null&&(c=Ca({inputs:{x:r},backend:a,attrs:{perm:p}}),u=C.getInnerMostAxes(u.length,o)),C.assertAxesAreInnerMostDims("any",u,o);let[d,h]=C.computeOutAndReduceShapes(c.shape,u),m=v.sizeFromShape(h),f=pe({inputs:{x:c},backend:a,attrs:{shape:[-1,m]}}),g=ol(f,f.dtype,"any",a),y;if(i){let x=C.expandShapeToKeepDim(d,l);y=pe({inputs:{x:g},backend:a,attrs:{shape:x}})}else y=pe({inputs:{x:g},backend:a,attrs:{shape:d}});return a.disposeIntermediateTensorInfo(f),a.disposeIntermediateTensorInfo(g),p!=null&&a.disposeIntermediateTensorInfo(c),y}var Pq={kernelName:pi,backendName:"webgl",kernelFunc:$q},_q=class{constructor(e,t,a){this.variableNames=["A"];let{windowSize:n,batchSize:r,outSize:s}=e;a||this.variableNames.push("bestIndicesA"),this.outputShape=[r,s];let i=t==="max"?">":"<",o=a?"inOffset + i;":"round(getBestIndicesA(batch, inOffset + i));";this.userCode=`
      void main() {
        ivec2 coords = getOutputCoords();
        int batch = coords[0];
        int outIdx = coords[1];
        int inOffset = outIdx * ${n};

        int bestIndex = inOffset;
        float bestValue = getA(batch, bestIndex);

        for (int i = 0; i < ${n}; i++) {
          int inIdx = ${o};
          float candidate = getA(batch, inIdx);
          if (candidate ${i} bestValue) {
            bestValue = candidate;
            bestIndex = inIdx;
          }
        }
        setOutput(float(bestIndex));
      }
    `}},Fq=class{constructor(e,t,a,n){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,v.assert(e.length>2,()=>`Packed arg${a.charAt(0).toUpperCase()+a.slice(1)} supports only inputs with rank above 2.`);let r=e[e.length-1],s=Math.ceil(r/t);this.outputShape=e.slice(0,-1),s>1&&this.outputShape.push(s),n||this.variableNames.push("bestIndicesA");let i=this.outputShape,o=i.length,l=ft(o),u=ka("coords",o),p,c;if(s===1){c=o+1;let T=ft(c);p=`
        ${T} sourceLocR = ${T}(${u.join()}, 0);
        ++${u[o-1]};
        ${T} sourceLocG = ${T}(${u.join()}, 0);
        ++${u[o-2]};
        ${T} sourceLocA = ${T}(${u.join()}, 0);
        --${u[o-1]};
        ${T} sourceLocB = ${T}(${u.join()}, 0);
        --${u[o-2]};`}else c=o,p=`
        ${l} sourceLocR = coords;
        ++${u[o-1]};
        ${l} sourceLocG = coords;
        ++${u[o-2]};
        ${l} sourceLocA = coords;
        --${u[o-1]};
        ${l} sourceLocB = coords;
        --${u[o-2]};`;let d=["x","y","z","w","u","v"].slice(0,c),h="."+d[c-1],m=d.map(T=>"int "+T),f=ka("sourceLocR",c-1).concat("inIdx.r"),g=ka("sourceLocG",c-1).concat("inIdx.g"),y=ka("sourceLocB",c-1).concat("inIdx.b"),x=ka("sourceLocA",c-1).concat("inIdx.a"),A=a==="max"?"greaterThan":"lessThan",b=n?"":`
          inIdx = round(vec4(getBestIndicesAChannel(${f.join()}),
                             getBestIndicesAChannel(${g.join()}),
                             getBestIndicesAChannel(${y.join()}),
                             getBestIndicesAChannel(${x.join()})));`,w=`vec4(
            getAChannel(${f.join()}),
            hasNextCol ? getAChannel(${g.join()}) : 0.,
            hasNextRow ? getAChannel(${y.join()}) : 0.,
            hasNextRow && hasNextCol ? getAChannel(${x.join()}) : 0.)`,I=n?"":`
      float getBestIndicesAChannel(${m.join()}) {
        return getChannel(getBestIndicesA(${d.join()}),
                                          vec2(${d.slice(-2).join()}));
      }`;this.userCode=`
      float getAChannel(${m.join()}) {
        return getChannel(getA(${d.join()}),
                               vec2(${d.slice(-2).join()}));
      }
      ${I}
      void main() {
        ${l} coords = getOutputCoords();
        bool hasNextCol = ${u[o-1]} < ${i[o-1]-1};
        bool hasNextRow = ${u[o-2]} < ${i[o-2]-1};
        ${p}
        ivec4 srcIdx = ivec4(sourceLocR${h}, sourceLocG${h},
          sourceLocB${h}, sourceLocA${h}) * ${t};
        ivec4 inIdx = srcIdx;
        vec4 bestIndex = vec4(inIdx);
        vec4 bestValue = ${w};

        for (int i = 0; i < ${t}; i++) {
          inIdx = srcIdx;
          ${b}
          vec4 candidate = ${w};
          bvec4 nan = isnan(candidate);
          bvec4 replace = bvec4(
            vec4(${A}(candidate, bestValue)) * (vec4(1.0) - vec4(nan)));

          bestValue = vec4(replace.x  ? candidate.x : bestValue.x,
                           replace.y  ? candidate.y : bestValue.y,
                           replace.z  ? candidate.z : bestValue.z,
                           replace.w  ? candidate.w : bestValue.w);
          bestIndex = mix(bestIndex, vec4(inIdx), vec4(replace));
          srcIdx++;
        }
        setOutput(bestIndex);
      }
    `}};function S8(e,t,a,n=null){let r=t.shape[0],s=t.shape[1];n!=null&&(r=n.shape[0],s=n.shape[1]);let i=C.computeOptimalWindowSize(s),o={windowSize:i,inSize:s,batchSize:r,outSize:Math.ceil(s/i)},l=new _q(o,a,n==null),u=[t];n!=null&&u.push(n);let p=e.runWebGLProgram(l,u,"int32");if(p.shape[1]===1)return p;let c=S8(e,t,a,p);return e.disposeIntermediateTensorInfo(p),c}function C8(e,t,a,n=null){let r=n!=null?n.shape:t.shape,s=r[r.length-1],i=C.computeOptimalWindowSize(s),o=new Fq(r,i,a,n==null),l=n==null?[t]:[t,n],u=e.runWebGLProgram(o,l,"int32");if(u.shape.length===t.shape.length){let p=C8(e,t,a,u);return e.disposeIntermediateTensorInfo(u),p}return u}function T8(e,t,a,n){let r=[a];if(C.assertAxesAreInnerMostDims("arg"+n.charAt(0).toUpperCase()+n.slice(1),r,t.shape.length),!B().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let s=[],i=e.texData.get(t.dataId),o=i!==null&&i.isPacked,l=t;o&&(l=e.unpackTensor(t),s.push(l));let[u,p]=C.computeOutAndReduceShapes(l.shape,r),c=v.sizeFromShape(p),d=pe({inputs:{x:l},backend:e,attrs:{shape:[-1,c]}});s.push(d);let h=S8(e,d,n);s.push(h);let m=pe({inputs:{x:h},backend:e,attrs:{shape:u}});return s.forEach(f=>e.disposeIntermediateTensorInfo(f)),m}return C8(e,t,n)}function Dq(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s}=n,i=v.parseAxisParam(s,r.shape),o=C.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=Ca({inputs:{x:r},backend:a,attrs:{perm:o}}),u.push(l),i=C.getInnerMostAxes(i.length,l.shape.length)),C.assertAxesAreInnerMostDims("argMax",[i[0]],l.shape.length);let p=T8(a,l,i[0],"max");return u.forEach(c=>a.disposeIntermediateTensorInfo(c)),p}var Oq={kernelName:lu,backendName:"webgl",kernelFunc:Dq};function zq(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s}=n,i=v.parseAxisParam(s,r.shape),o=C.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=Ca({inputs:{x:r},backend:a,attrs:{perm:o}}),u.push(l),i=C.getInnerMostAxes(i.length,l.shape.length)),C.assertAxesAreInnerMostDims("argMin",[i[0]],l.shape.length);let p=T8(a,l,i[0],"min");return u.forEach(c=>a.disposeIntermediateTensorInfo(c)),p}var Lq={kernelName:uu,backendName:"webgl",kernelFunc:zq},Wq=Mn+`
  if (abs(x) > 1.) {
    return NAN;
  }
  return asin(x);
`,Bq=tt({opSnippet:Wq}),Vq={kernelName:ci,backendName:"webgl",kernelFunc:Bq},Uq=Mn+"return log(x + sqrt(x * x + 1.0));",Gq=tt({opSnippet:Uq}),Hq={kernelName:hi,backendName:"webgl",kernelFunc:Gq},jq=Mn+`
  return atan(x);
`,qq=tt({opSnippet:jq}),Xq={kernelName:mi,backendName:"webgl",kernelFunc:qq},Kq=z3+`
  return atan(a, b);
`,Yq=`
  vec4 result = atan(a, b);
  bvec4 isNaNA = isnan(a);
  bvec4 isNaNB = isnan(b);
  bvec4 isNaN = bvec4(isNaNA.x || isNaNB.x, isNaNA.y || isNaNB.y, isNaNA.z || isNaNB.z, isNaNA.w || isNaNB.w);
  `+il+`
  return result;
`,Zq=ma({opSnippet:Kq,packedOpSnippet:Yq}),Jq={kernelName:gi,backendName:"webgl",kernelFunc:Zq},Qq=Mn+`
  if ((x < -1.0) || (x > 1.0)) return NAN;
return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,eX=tt({opSnippet:Qq}),tX={kernelName:fi,backendName:"webgl",kernelFunc:eX},ap=class{constructor(e,t,a,n=!1,r=!1){if(this.variableNames=["x"],t==="avg"&&a)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideHeight,o=e.strideWidth,l=e.dilationHeight,u=e.dilationWidth,p=e.effectiveFilterHeight,c=e.effectiveFilterWidth,d=e.padInfo.top,h=e.padInfo.left;this.outputShape=e.outShape;let m=t==="avg",f=`((batch  * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,g=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,y="0.0";if(m||(y="-1.0 / 1e-20"),a){let T=">=";this.userCode=`
        const ivec2 strides = ivec2(${i}, ${o});
        const ivec2 pads = ivec2(${d}, ${h});

        void main() {
          ivec4 coords = getOutputCoords();
          int batch = coords[0];
          int d = coords[3];

          ivec2 xRCCorner = coords.yz * strides - pads;
          int xRCorner = xRCCorner.x;
          int xCCorner = xRCCorner.y;

          // max/min x(?, ?, d) to get y(yR, yC, d).
          // ? = to be determined
          float minMaxValue = 0.0;
          float minMaxValueFound = 0.0;
          int minMaxPosition = 0;
          float avgValue = 0.0;

          for (int wR = 0; wR < ${p};
              wR += ${l}) {
            int xR = xRCorner + wR;

            if (xR < 0 || xR >= ${e.inHeight}) {
              continue;
            }

            for (int wC = 0; wC < ${c};
                wC += ${u}) {
              int xC = xCCorner + wC;

              if (xC < 0 || xC >= ${e.inWidth}) {
                continue;
              }

              float value = getX(batch, xR, xC, d);

              // If a min / max value has already been found, use it. If not,
              // use the current value.
              float currMinMaxValue = mix(
                  value, minMaxValue, minMaxValueFound);
              if (value ${T} currMinMaxValue) {
                minMaxValue = value;
                minMaxValueFound = 1.0;
                minMaxPosition = ${n?r?f:g:`wR * ${c} + wC`};
              }
            }
          }
          setOutput(float(minMaxPosition));
        }
      `;return}let x="max",A=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(A="avgValue / max(count, 1.0)");let b=Math.floor(s/4)*4,w=s%4,I=`
      if (${m}) {
        avgValue += dot(values, ones);
      } else {
        minMaxValue = ${x}(values, minMaxValue);
      }
    `;this.userCode=`
      const ivec2 strides = ivec2(${i}, ${o});
      const ivec2 pads = ivec2(${d}, ${h});
      const float initializationValue = ${y};
      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);

      float count = 0.0;

      float getValue(int batch, int xR, int xC, int d) {
        if (xC < 0 || xC >= ${e.inWidth}) {
          return initializationValue;
        }
        count += 1.0;
        return getX(batch, xR, xC, d);
      }

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords[0];
        int d = coords[3];

        ivec2 xRCCorner = coords.yz * strides - pads;
        int xRCorner = xRCCorner.x;
        int xCCorner = xRCCorner.y;

        // max/min x(?, ?, d) to get y(yR, yC, d).
        // ? = to be determined
        vec4 minMaxValue = vec4(${y});
        float avgValue = 0.0;
        count = 0.0;

        for (int wR = 0; wR < ${p};
            wR += ${l}) {
          int xR = xRCorner + wR;

          if (xR < 0 || xR >= ${e.inHeight}) {
            continue;
          }

          for (int wC = 0; wC < ${b}; wC += 4) {
            int xC = xCCorner + wC * ${u};

            vec4 values = vec4(
              getValue(batch, xR, xC, d),
              getValue(batch, xR, xC + ${u}, d),
              getValue(batch, xR, xC + 2 * ${u}, d),
              getValue(batch, xR, xC + 3 * ${u}, d)
            );

            ${I}
          }

          int xC = xCCorner + ${b};
          if (${w===1}) {
            vec4 values = vec4(
              getValue(batch, xR, xC, d),
              initializationValue,
              initializationValue,
              initializationValue
            );

            ${I}
          } else if (${w===2}) {
            vec4 values = vec4(
              getValue(batch, xR, xC, d),
              getValue(batch, xR, xC + ${u}, d),
              initializationValue,
              initializationValue
            );

            ${I}
          } else if (${w===3}) {
            vec4 values = vec4(
              getValue(batch, xR, xC, d),
              getValue(batch, xR, xC + ${u}, d),
              getValue(batch, xR, xC + 2 * ${u}, d),
              initializationValue
            );

            ${I}
          }
        }
        setOutput(${A});
      }
    `}},W3=class{constructor(e,t,a,n=!1,r=!1){if(this.variableNames=["x"],t==="avg"&&a)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideDepth,o=e.strideHeight,l=e.strideWidth,u=e.dilationDepth,p=e.dilationHeight,c=e.dilationWidth,d=e.effectiveFilterDepth,h=e.effectiveFilterHeight,m=e.effectiveFilterWidth,f=e.padInfo.front,g=e.padInfo.top,y=e.padInfo.left;this.outputShape=e.outShape;let x=t==="avg",A="0.0";if(x||(A="-1.0 / 1e-20"),a){let M=">=";this.userCode=`
        const ivec3 strides =
            ivec3(${i}, ${o}, ${l});
        const ivec3 pads = ivec3(${f}, ${g}, ${y});

        void main() {
          ivec5 coords = getOutputCoords();
          int batch = coords.x;
          int ch = coords.u;

          ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
          int xDCorner = xCorner.x;
          int xRCorner = xCorner.y;
          int xCCorner = xCorner.z;

          // max/min x(?, ?, ?, ch) to get y(yD, yR, yC, ch).
          // ? = to be determined
          float minMaxValue = 0.0;
          float minMaxValueFound = 0.0;
          int minMaxPosition = 0;

          for (int wD = 0; wD < ${d};
              wD += ${u}) {
            int xD = xDCorner + wD;

            if (xD < 0 || xD >= ${e.inDepth}) {
              continue;
            }

            for (int wR = 0; wR < ${h};
                wR += ${p}) {
              int xR = xRCorner + wR;

              if (xR < 0 || xR >= ${e.inHeight}) {
                continue;
              }

              for (int wC = 0; wC < ${m};
                  wC += ${c}) {
                int xC = xCCorner + wC;

                if (xC < 0 || xC >= ${e.inWidth}) {
                  continue;
                }

                float value = getX(batch, xD, xR, xC, ch);

                // If a min / max value has already been found, use it. If not,
                // use the current value.
                float currMinMaxValue = mix(
                    value, minMaxValue, minMaxValueFound);
                if (value ${M} currMinMaxValue) {
                  minMaxValue = value;
                  minMaxValueFound = 1.0;
                  minMaxPosition = ${n?r?`(((batch * ${e.inDepth} + xD) * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`((xD * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`wD * ${h} * ${m} +
                      wR * ${m} + wC`};
                }
              }
            }
          }
          setOutput(float(minMaxPosition));
        }
      `;return}let b="max",w=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(w="avgValue / max(count, 1.0)");let I=Math.floor(s/4)*4,T=s%4,N=`
      if (${x}) {
        avgValue += dot(values, ones);
      } else {
        minMaxValue = ${b}(values, minMaxValue);
      }
    `;this.userCode=`
      const ivec3 strides =
        ivec3(${i}, ${o}, ${l});
      const ivec3 pads = ivec3(${f}, ${g}, ${y});
      const float initializationValue = ${A};
      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);

      float count = 0.0;

      float getValue(int batch, int xD, int xR, int xC, int ch) {
        if (xC < 0 || xC >= ${e.inWidth}) {
          return initializationValue;
        }
        count += 1.0;
        return getX(batch, xD, xR, xC, ch);
      }

      void main() {
        ivec5 coords = getOutputCoords();
        int batch = coords.x;
        int ch = coords.u;

        ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
        int xDCorner = xCorner.x;
        int xRCorner = xCorner.y;
        int xCCorner = xCorner.z;

        // max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).
        // ? = to be determined
        vec4 minMaxValue = vec4(${A});
        float avgValue = 0.0;
        count = 0.0;

        for (int wD = 0; wD < ${d};
            wD += ${u}) {
          int xD = xDCorner + wD;

          if (xD < 0 || xD >= ${e.inDepth}) {
            continue;
          }

          for (int wR = 0; wR < ${h};
            wR += ${p}) {
            int xR = xRCorner + wR;

            if (xR < 0 || xR >= ${e.inHeight}) {
              continue;
            }

            for (int wC = 0; wC < ${I}; wC += 4) {
              int xC = xCCorner + wC * ${c};

              vec4 values = vec4(
                getValue(batch, xD, xR, xC, ch),
                getValue(batch, xD, xR, xC + ${c}, ch),
                getValue(batch, xD, xR, xC + 2 * ${c}, ch),
                getValue(batch, xD, xR, xC + 3 * ${c}, ch)
              );

              ${N}
            }

            int xC = xCCorner + ${I};
            if (${T===1}) {
              vec4 values = vec4(
                getValue(batch, xD, xR, xC, ch),
                initializationValue,
                initializationValue,
                initializationValue
              );

              ${N}
            } else if (${T===2}) {
              vec4 values = vec4(
                getValue(batch, xD, xR, xC, ch),
                getValue(batch, xD, xR, xC + ${c}, ch),
                initializationValue,
                initializationValue
              );

              ${N}
            } else if (${T===3}) {
              vec4 values = vec4(
                getValue(batch, xD, xR, xC, ch),
                getValue(batch, xD, xR, xC + ${c}, ch),
                getValue(batch, xD, xR, xC + 2 * ${c}, ch),
                initializationValue
              );

              ${N}
            }
          }
        }
        setOutput(${w});
      }
    `}};function aX(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t;qu(r,"avgPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=n,u=1;v.assert(C.eitherStridesOrDilationsAreOne(i,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let p=C.computePool2DInfo(r.shape,s,i,u,o,l);if(p.filterWidth===1&&p.filterHeight===1&&v.arraysEqual(p.inShape,p.outShape))return en({inputs:{x:r},backend:a});let c=new ap(p,"avg",!1);return a.runWebGLProgram(c,[r],"float32")}var nX={kernelName:yi,backendName:"webgl",kernelFunc:aX};function rX(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:u}=n,p=[1,1,1],c=C.computePool3DInfo(r.shape,s,i,p,o,l,u),d=new W3(c,"avg",!1);return a.runWebGLProgram(d,[r],"float32")}var sX={kernelName:du,backendName:"webgl",kernelFunc:rX},iX=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterHeight,a=e.filterWidth,n=e.strideHeight,r=e.strideWidth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterHeight,l=e.effectiveFilterWidth,u=o-1-e.padInfo.top,p=l-1-e.padInfo.left,c=1/(t*a);this.userCode=`
      const ivec2 pads = ivec2(${u}, ${p});
      const float avgMultiplier = float(${c});

      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];

        ivec2 dyRCCorner = coords.yz - pads;
        int dyRCorner = dyRCCorner.x;
        int dyCCorner = dyRCCorner.y;

        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;
        for (int wR = 0; wR < ${o};
            wR += ${s}) {
          float dyR = float(dyRCorner + wR) / ${n}.0;

          if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
            continue;
          }
          int idyR = int(dyR);

          for (int wC = 0; wC < ${l};
            wC+= ${i}) {
            float dyC = float(dyCCorner + wC) / ${r}.0;

            if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
                fract(dyC) > 0.0) {
              continue;
            }
            int idyC = int(dyC);

            float dyValue = getDy(b, idyR, idyC, d);

            dotProd += dyValue * avgMultiplier;
          }
        }
        setOutput(dotProd);
      }
    `}},oX=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,a=e.filterHeight,n=e.filterWidth,r=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,p=e.effectiveFilterDepth,c=e.effectiveFilterHeight,d=e.effectiveFilterWidth,h=p-1-e.padInfo.front,m=c-1-e.padInfo.top,f=d-1-e.padInfo.left,g=1/(t*a*n);this.userCode=`
      const ivec3 pads = ivec3(${h}, ${m}, ${f});
      const float avgMultiplier = float(${g});

      void main() {
        ivec5 coords = getOutputCoords();
        int batch = coords.x;
        int ch = coords.u;

        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
        int dyDCorner = dyCorner.x;
        int dyRCorner = dyCorner.y;
        int dyCCorner = dyCorner.z;

        // Convolve dy(?, ?, ?, d) with pos mask(:, :, :, ch) to get
        // dx(xD, xR, xC, ch).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;

        for (int wD = 0; wD < ${p};
            wD += ${o}) {
          float dyD = float(dyDCorner + wD) / ${r}.0;

          if (dyD < 0.0 || dyD >= ${e.outDepth}.0 || fract(dyD) > 0.0) {
            continue;
          }
          int idyD = int(dyD);

          for (int wR = 0; wR < ${c};
              wR += ${l}) {
            float dyR = float(dyRCorner + wR) / ${s}.0;

            if (dyR < 0.0 || dyR >= ${e.outHeight}.0 ||
                fract(dyR) > 0.0) {
              continue;
            }
            int idyR = int(dyR);

            for (int wC = 0; wC < ${d};
                wC += ${u}) {
              float dyC = float(dyCCorner + wC) / ${i}.0;

              if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
                  fract(dyC) > 0.0) {
                continue;
              }
              int idyC = int(dyC);

              float dyValue = getDy(batch, idyD, idyR, idyC, ch);

              dotProd += dyValue * avgMultiplier;
            }
          }
        }
        setOutput(dotProd);
      }
    `}};function lX(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,i=s,{filterSize:o,strides:l,pad:u,dimRoundingMode:p}=n,c=[1,1,1],d=C.computePool3DInfo(i.shape,o,l,c,u,p),h=new oX(d);return a.runWebGLProgram(h,[r],i.dtype)}var uX={kernelName:pp,backendName:"webgl",kernelFunc:lX};function dX(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,i=s;qu([r,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:u}=n,p=C.computePool2DInfo(i.shape,o,l,1,u),c=new iX(p);return a.runWebGLProgram(c,[r],i.dtype)}var pX={kernelName:dp,backendName:"webgl",kernelFunc:dX};function cX(e){let{inputs:t,backend:a,attrs:n}=e,{a:r,b:s}=t,{transposeA:i,transposeB:o}=n;return kh({a:r,b:s,transposeA:i,transposeB:o,backend:a})}var hX={kernelName:xi,backendName:"webgl",kernelFunc:cX},mX=class{constructor(e,t,a,n,r,s){this.outputShape=[],this.variableNames=["x","mean","variance"],C.assertAndGetBroadcastShape(e,t),C.assertAndGetBroadcastShape(e,a);let i="0.0";n!=null&&(C.assertAndGetBroadcastShape(e,n),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="1.0";r!=null&&(C.assertAndGetBroadcastShape(e,r),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
      void main() {
        float x = getXAtOutCoords();
        float mean = getMeanAtOutCoords();
        float variance = getVarianceAtOutCoords();
        float offset = ${i};
        float scale = ${o};
        float inv = scale * inversesqrt(variance + float(${s}));
        setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));
      }
    `}},fX=class{constructor(e,t,a,n,r,s){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],C.assertAndGetBroadcastShape(e,t),C.assertAndGetBroadcastShape(e,a);let i="vec4(0.0)";n!=null&&(C.assertAndGetBroadcastShape(e,n),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="vec4(1.0)";r!=null&&(C.assertAndGetBroadcastShape(e,r),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
      void main() {
        vec4 offset = ${i};
        vec4 scale = ${o};

        vec4 x = getXAtOutCoords();
        vec4 mean = getMeanAtOutCoords();
        vec4 variance = getVarianceAtOutCoords();

        vec4 inv = scale * inversesqrt(variance + vec4(${s}));

        setOutput((x - mean) * inv + offset);
      }
    `}},gX=({inputs:e,backend:t,attrs:a})=>{let{x:n,mean:r,variance:s,offset:i,scale:o}=e;v.assert(r.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),v.assert(i==null||r.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),v.assert(o==null||r.shape.length===o.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:l}=a;l==null&&(l=.001);let u=[n,r,s],p=null;i!=null&&(p=i.shape,u.push(i));let c=null;o!=null&&(c=o.shape,u.push(o));let d=B().getBool("WEBGL_PACK_NORMALIZATION")?new fX(n.shape,r.shape,s.shape,p,c,l):new mX(n.shape,r.shape,s.shape,p,c,l);return t.runWebGLProgram(d,u,u[0].dtype)},yX={kernelName:Ui,backendName:"webgl",kernelFunc:gX},xX=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=ft(this.rank);this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let a=AX(this.rank),n,r=e.map((s,i)=>`sourceLoc.${L1[i]} = start[${i}] + coords.${L1[i]};`);n=`
        ${t} sourceLoc;
        ${t} coords = getOutputCoords();
        ${r.join(`
`)}
      `,this.userCode=`
      void main() {
        ${n}
        setOutput(getSource(${a}));
      }
    `}},L1=["x","y","z","w","u","v"];function AX(e){if(e===1)return"sourceLoc";if(e<=6)return L1.slice(0,e).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}var bX=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let t=ft(this.rank),a=ka("coords",this.rank),n=ka("sourceLoc",this.rank),r=this.rank===1?"sourceLoc":`vec2(${n.slice(-2).join()})`,s=`getChannel(getSource(${n.join()}), ${r})`,i=`
      result.x = ${s};
      if (++${a[this.rank-1]} < ${e[this.rank-1]}) {
        ++${n[this.rank-1]};
        result.y = ${s};
        --${n[this.rank-1]};
      }
    `,o=this.rank===1?"":`
      --${a[this.rank-1]};
      if (++${a[this.rank-2]} < ${e[this.rank-2]}) {
        ++${n[this.rank-2]};
        result.z = ${s};
        if (++${a[this.rank-1]} < ${e[this.rank-1]}) {
          ++${n[this.rank-1]};
          result.w = ${s};
        }
      }
    `,l=this.rank<=4?`sourceLoc = coords +
            ${t}(${e.map((u,p)=>`start[${p}]`).join()});`:e.map((u,p)=>`${n[p]} = ${a[p]} + start[${p}];`).join(`
`);this.userCode=`
      void main() {
        ${t} coords = getOutputCoords();
        ${t} sourceLoc;
        ${l}
        vec4 result = vec4(0.);
        ${i}
        ${o}
        setOutput(result);
      }
    `}};function vX(e,t,a,n){let r=n.texData.get(e.dataId),s=n.makeTensorInfo(a,e.dtype),i=n.texData.get(s.dataId);Object.assign(i,r),i.refCount=1,i.shape=a,i.dtype=e.dtype;let o=Nt.computeFlatOffset(t,v.computeStrides(e.shape));r.slice&&(o+=r.slice.flatOffset),i.slice={flatOffset:o,origDataId:r.slice&&r.slice.origDataId||e.dataId};let l=n.dataRefCount.get(i.slice.origDataId)||1;return n.dataRefCount.set(i.slice.origDataId,l+1),s}function ed(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{begin:s,size:i}=n,[o,l]=Nt.parseSliceParams(r,s,i);if(Nt.assertParamsValid(r,o,l),v.sizeFromShape(l)===0)return a.makeTensorInfo(l,r.dtype,[]);if(a.shouldExecuteOnCPU([r])||r.dtype==="string"){let c=a.texData.get(r.dataId),d=pj(c.values,o,l,r.shape,r.dtype);return a.makeTensorInfo(l,r.dtype,d)}let{isPacked:u}=a.texData.get(r.dataId),p=Nt.isSliceContinous(r.shape,o,l);if(u||!p){let c=B().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new bX(l):new xX(l),d=[o];return a.runWebGLProgram(c,[r],r.dtype,d)}return a.uploadToGPU(r.dataId),vX(r,o,l,a)}var wX={kernelName:_u,backendName:"webgl",kernelFunc:ed},kX=e=>{let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockShape:s,crops:i}=n;v.assert(r.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((x,A)=>x*A),l=C.getReshaped(r.shape,s,o),u=C.getPermuted(l.length,s.length),p=C.getReshapedPermuted(r.shape,s,o),c=C.getSliceBeginCoords(i,s.length),d=C.getSliceSize(p,i,s.length),h=[],m=pe({inputs:{x:r},backend:a,attrs:{shape:l}}),f=Ca({inputs:{x:m},backend:a,attrs:{perm:u}}),g=pe({inputs:{x:f},backend:a,attrs:{shape:p}}),y=ed({inputs:{x:g},backend:a,attrs:{begin:c,size:d}});return h.push(m),h.push(f),h.push(g),h.forEach(x=>a.disposeIntermediateTensorInfo(x)),y},IX={kernelName:pu,backendName:"webgl",kernelFunc:kX};function SX(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,weights:s}=t,{size:i}=n,o=a.readSync(r.dataId),l=a.readSync(s.dataId),u=c8(o,l,s.dtype,s.shape,i);return a.makeTensorInfo([i],s.dtype,u)}var CX={kernelName:Ai,backendName:"webgl",kernelFunc:SX},TX=`
  int r = int(a.r) & int(b.r);
  int g = int(a.g) & int(b.g);
  int rb = int(a.b) & int(b.b);
  int ra = int(a.a) & int(b.a);
  return vec4(r, g, rb, ra);
`,NX=`
  return float(int(a.r) & int(b.r));
`;function RX(e){let{inputs:t,backend:a}=e,{a:n,b:r}=t,s=B().getBool("WEBGL_PACK_BINARY_OPERATIONS"),i=B().getNumber("WEBGL_VERSION");if(a.shouldExecuteOnCPU([n,r])||i===1){let l=a.texData.get(n.dataId).values,u=a.texData.get(r.dataId).values,[p,c]=FH(n.shape,r.shape,l,u,n.dtype),d=a.makeTensorInfo(c,n.dtype),h=a.texData.get(d.dataId);return h.values=p,d}let o;return s?o=new Ju(TX,n.shape,r.shape,!1):o=new ri(NX,n.shape,r.shape),a.runWebGLProgram(o,[n,r],n.dtype)}var EX={kernelName:cu,backendName:"webgl",kernelFunc:RX};function MX(e){let{inputs:t,backend:a}=e,{s0:n,s1:r}=t,s=a.readSync(n.dataId),i=a.readSync(r.dataId),o=C.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return a.makeTensorInfo([o.length],"int32",Int32Array.from(o))}var $X={kernelName:hu,backendName:"webgl",kernelFunc:MX},PX="return float(a != b);",N8=ma({opSnippet:PX,cpuKernelImpl:aj,dtype:"bool"}),_X={kernelName:xo,backendName:"webgl",kernelFunc:N8};function Qp(e){let{inputs:t,backend:a}=e,{input:n}=t,r=a.texData.get(n.dataId);return en({inputs:{x:r.complexTensorInfos.real},backend:a})}var FX={kernelName:Ip,backendName:"webgl",kernelFunc:Qp},DX="return float(int(x));";function OX(e,t){let a=new Jn(e.shape,DX),n=t.runWebGLProgram(a,[e],"int32");return{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}function W1(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{dtype:s}=n;if(s==="complex64"){if(r.dtype==="complex64")return en({inputs:{x:r},backend:a});let i=yn(r.shape),o=W1({inputs:{x:r},backend:a,attrs:{dtype:"float32"}}),l=fs({inputs:{real:o,imag:i},backend:a});return i.dispose(),a.disposeIntermediateTensorInfo(o),l}if(r.dtype==="complex64"){let i=Qp({inputs:{input:r},backend:a}),o=W1({inputs:{x:i},backend:a,attrs:{dtype:s}});return a.disposeIntermediateTensorInfo(i),o}if(!v.hasEncodingLoss(r.dtype,s)){let i=en({inputs:{x:r},backend:a});return{dataId:i.dataId,shape:i.shape,dtype:s}}if(a.shouldExecuteOnCPU([r])){let i=a.texData.get(r.dataId).values,[o,l,u]=DH(i,r.shape,r.dtype,s);return a.makeTensorInfo(o,l,u)}if(s==="int32")return OX(r,a);if(s==="bool"){let i=a.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),o=N8({inputs:{a:r,b:i},backend:a});return a.disposeIntermediateTensorInfo(i),o}throw new Error(`Error in Cast: failed to cast ${r.dtype} to ${s}`)}var zX={kernelName:bi,backendName:"webgl",kernelFunc:W1},O5="return ceil(x);",LX=tt({opSnippet:O5,packedOpSnippet:O5,cpuKernelImpl:OH}),WX={kernelName:vi,backendName:"webgl",kernelFunc:LX},BX=class{constructor(e){this.variableNames=["A"],this.customUniforms=[{name:"minVal",type:"float"},{name:"maxVal",type:"float"}],this.outputShape=e,this.userCode=`

      void main() {
        float value = getAAtOutCoords();
        if (isnan(value)) {
          setOutput(value);
          return;
        }

        setOutput(clamp(value, minVal, maxVal));
      }
    `}},VX=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"minVal",type:"float"},{name:"maxVal",type:"float"}],this.outputShape=e,this.userCode=`
      void main() {
        vec4 value = getAAtOutCoords();

        if (any(isnan(value))) {
          setOutput(value);
          return;
        }

        setOutput(clamp(value, vec4(minVal), vec4(maxVal)));
      }
    `}};function UX(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{clipValueMin:s,clipValueMax:i}=n,o;B().getBool("WEBGL_PACK_CLIP")?o=new VX(r.shape):o=new BX(r.shape);let l=[[s],[i]];return a.runWebGLProgram(o,[r],r.dtype,l)}var GX={kernelName:us,backendName:"webgl",kernelFunc:UX},HX=class{constructor(e){this.variableNames=["real","imag"],this.outputShape=e,this.userCode=`
      void main() {
        float re = abs(getRealAtOutCoords());
        float im = abs(getImagAtOutCoords());
        float mx = max(re, im);

        // sadly the length function in glsl is not underflow-safe
        // (at least not on Intel GPUs). So the safe solution is
        // to ensure underflow-safety in all cases.
        setOutput(
          mx == 0.0 ? 0.0 : mx * length(vec2(1, min(re, im)/mx))
        );
      }
    `}};function z5(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function jX(e){let{inputs:t,backend:a}=e,{x:n}=t,r=a.texData.get(n.dataId),s=new HX(n.shape),i=[z5(n,r.complexTensorInfos.real),z5(n,r.complexTensorInfos.imag)];return a.runWebGLProgram(s,i,i[0].dtype)}var qX={kernelName:hp,backendName:"webgl",kernelFunc:jX},XX=class{constructor(e){this.outputShape=[],this.outputShape=C.computeOutShape(e,1),this.variableNames=e.map((s,i)=>`T${i}`);let t=new Array(e.length-1);t[0]=e[0][1];for(let s=1;s<t.length;s++)t[s]=t[s-1]+e[s][1];let a=[`if (yC < ${t[0]}) setOutput(getT0(yR, yC));`];for(let s=1;s<t.length;s++){let i=t[s-1];a.push(`else if (yC < ${t[s]}) setOutput(getT${s}(yR, yC-${i}));`)}let n=t.length,r=t[t.length-1];a.push(`else setOutput(getT${n}(yR, yC-${r}));`),this.userCode=`
      void main() {
        ivec2 coords = getOutputCoords();
        int yR = coords.x;
        int yC = coords.y;

        ${a.join(`
        `)}
      }
    `}},KX=class{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=C.computeOutShape(e,t);let a=this.outputShape,n=a.length,r=ft(n),s=ka("coords",n),i=["x","y","z","w","u","v"].slice(0,n);this.variableNames=e.map((m,f)=>`T${f}`);let o=new Array(e.length-1);o[0]=e[0][t];for(let m=1;m<o.length;m++)o[m]=o[m-1]+e[m][t];let l=i[t],u=i.slice(-2),p=i.join(),c=`if (${l} < ${o[0]}) {
        return getChannel(
            getT0(${p}), vec2(${u.join()}));
        }`;for(let m=1;m<o.length;m++){let f=o[m-1];c+=`
        if (${l} < ${o[m]}  && ${l} >= ${o[m-1]}) {
          return getChannel(
            getT${m}(${Qc(i,l,f)}),
            vec2(${Qc(u,l,f)}));
        }`}let d=o.length,h=o[o.length-1];c+=`
        return getChannel(
          getT${d}(${Qc(i,l,h)}),
          vec2(${Qc(u,l,h)}));`,this.userCode=`
      float getValue(${i.map(m=>"int "+m)}) {
        ${c}
      }

      void main() {
        ${r} coords = getOutputCoords();
        vec4 result = vec4(getValue(${s}), 0., 0., 0.);

        ${s[n-1]} = ${s[n-1]} + 1;
        if (${s[n-1]} < ${a[n-1]}) {
          result.g = getValue(${s});
        }

        ${s[n-2]} = ${s[n-2]} + 1;
        if (${s[n-2]} < ${a[n-2]}) {
          result.a = getValue(${s});
        }

        ${s[n-1]} = ${s[n-1]} - 1;
        if (${s[n-2]} < ${a[n-2]} &&
            ${s[n-1]} < ${a[n-1]}) {
          result.b = getValue(${s});
        }
        setOutput(result);
      }
    `}};function Qc(e,t,a){let n=e.indexOf(t);return e.map((r,s)=>s===n?`${r} - ${a}`:r).join()}function o0(e){let{inputs:t,backend:a}=e,{input:n}=t,r=a.texData.get(n.dataId);return en({inputs:{x:r.complexTensorInfos.imag},backend:a})}var YX={kernelName:vp,backendName:"webgl",kernelFunc:o0};function $d(e,t,a){let n=e[0].dtype;if(n==="complex64"){let h=e.map(x=>Qp({inputs:{input:x},backend:a})),m=e.map(x=>o0({inputs:{input:x},backend:a})),f=$d(h,t,a),g=$d(m,t,a),y=fs({inputs:{real:f,imag:g},backend:a});return h.forEach(x=>a.disposeIntermediateTensorInfo(x)),m.forEach(x=>a.disposeIntermediateTensorInfo(x)),a.disposeIntermediateTensorInfo(f),a.disposeIntermediateTensorInfo(g),y}let r=a.shouldExecuteOnCPU(e);if(n==="string"&&(r=!0),r){let h=e.map(b=>{let w=[-1,v.sizeFromShape(b.shape.slice(t))];return pe({inputs:{x:b},backend:a,attrs:{shape:w}})}),m=h.map(b=>({vals:a.readSync(b.dataId),shape:b.shape})),f=C.computeOutShape(h.map(b=>b.shape),1),g=h[0].shape[0]===1,y=zH(m,f,n,g),x=C.computeOutShape(e.map(b=>b.shape),t),A=a.makeTensorInfo(x,n,y);return h.forEach(b=>a.disposeIntermediateTensorInfo(b)),A}let s=e.filter(h=>v.sizeFromShape(h.shape)>0),i=B().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&s[0].shape.length>1;if(s.length===1){let h=i?new Jn(e[0].shape,Vr):new qr(e[0].shape,Vr);return a.runWebGLProgram(h,e,n)}let o=B().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER");if(s.length>o){let h=[];for(let f=0;f<s.length;f+=o){let g=s.slice(f,f+o);h.push($d(g,t,a))}let m=$d(h,t,a);for(let f of h)a.disposeIntermediateTensorInfo(f);return m}if(i){let h=new KX(s.map(m=>m.shape),t);return a.runWebGLProgram(h,s,n)}let{tensors2D:l,outShape:u}=ZX(s,t,a),p=new XX(l.map(h=>h.shape)),c=a.runWebGLProgram(p,l,n);l.forEach(h=>a.disposeIntermediateTensorInfo(h));let d=pe({inputs:{x:c},attrs:{shape:u},backend:a});return a.disposeIntermediateTensorInfo(c),d}function ZX(e,t,a){let n=C.computeOutShape(e.map(r=>r.shape),t);return{tensors2D:e.map(r=>pe({inputs:{x:r},attrs:{shape:[-1,v.sizeFromShape(r.shape.slice(t))]},backend:a})),outShape:n}}function R8(e){let{inputs:t,backend:a,attrs:n}=e,{axis:r}=n,s=v.parseAxisParam(r,t[0].shape)[0],i=t.map(u=>u.shape);C.assertParamsConsistent(i,s);let o=C.computeOutShape(t.map(u=>u.shape),s);if(v.sizeFromShape(o)===0)return a.makeTensorInfo(o,t[0].dtype,[]);let l=t.filter(u=>v.sizeFromShape(u.shape)>0);return l.length===1?en({inputs:{x:l[0]},backend:a}):$d(l,s,a)}var JX={kernelName:mu,backendName:"webgl",kernelFunc:R8},E8=class{constructor(e,t=!1,a=null,n=!1,r=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.padInfo.top,i=e.padInfo.left,o=e.strideHeight,l=e.strideWidth,u=e.dilationHeight,p=e.dilationWidth,c=e.filterHeight,d=e.filterWidth,h=Math.floor(e.inChannels/4)*4,m=e.inChannels%4,f=e.dataFormat==="channelsLast",g=f?1:2,y=f?2:3,x=f?3:1,A="",b="";a&&(n?A=`float activation(float a) {
          float b = getPreluActivationWeightsAtOutCoords();
          ${a}
        }`:r?A=`float activation(float a) {
          float b = getLeakyreluAlphaAtOutCoords();
          ${a}
        }`:A=`
          float activation(float x) {
            ${a}
          }
        `,b="result = activation(result);");let w=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),r&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
      ${A}

      const ivec2 strides = ivec2(${o}, ${l});
      const ivec2 pads = ivec2(${s}, ${i});

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords[0];
        int d2 = coords[${x}];

        ivec2 xRCCorner =
            ivec2(coords[${g}], coords[${y}]) * strides - pads;
        int xRCorner = xRCCorner.x;
        int xCCorner = xRCCorner.y;

        // Convolve x(?, ?, d1) with w(:, :, d1, d2) to get y(yR, yC, d2).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;
        for (int wR = 0; wR < ${c}; wR++) {
          int xR = xRCorner + wR * ${u};

          if (xR < 0 || xR >= ${e.inHeight}) {
            continue;
          }

          for (int wC = 0; wC < ${d}; wC++) {
            int xC = xCCorner + wC * ${p};

            if (xC < 0 || xC >= ${e.inWidth}) {
              continue;
            }

            for (int d1 = 0; d1 < ${h}; d1 += 4) {
              vec4 wValues = vec4(
                getW(wR, wC, d1, d2),
                getW(wR, wC, d1 + 1, d2),
                getW(wR, wC, d1 + 2, d2),
                getW(wR, wC, d1 + 3, d2)
              );

              if (${f}) {
                vec4 xValues = vec4(
                  getX(batch, xR, xC, d1),
                  getX(batch, xR, xC, d1 + 1),
                  getX(batch, xR, xC, d1 + 2),
                  getX(batch, xR, xC, d1 + 3)
                );
                dotProd += dot(xValues, wValues);
              } else {
                vec4 xValues = vec4(
                  getX(batch, d1, xR, xC),
                  getX(batch, d1 + 1, xR, xC),
                  getX(batch, d1 + 2, xR, xC),
                  getX(batch, d1 + 3, xR, xC)
                );
                dotProd += dot(xValues, wValues);
              }
            }

            if (${m===1}) {

              if (${f}) {
                dotProd +=
                    getX(batch, xR, xC, ${h}) *
                    getW(wR, wC, ${h}, d2);
              } else {
                dotProd +=
                    getX(batch, ${h}, xR, xC) *
                    getW(wR, wC, ${h}, d2);
              }

            } else if (${m===2}) {
              vec2 wValues = vec2(
                getW(wR, wC, ${h}, d2),
                getW(wR, wC, ${h} + 1, d2)
              );

              if (${f}) {
                vec2 xValues = vec2(
                  getX(batch, xR, xC, ${h}),
                  getX(batch, xR, xC, ${h} + 1)
                );
                dotProd += dot(xValues, wValues);
              } else {
                vec2 xValues = vec2(
                  getX(batch, ${h}, xR, xC),
                  getX(batch, ${h} + 1, xR, xC)
                );
                dotProd += dot(xValues, wValues);
              }

            } else if (${m===3}) {
              vec3 wValues = vec3(
                getW(wR, wC, ${h}, d2),
                getW(wR, wC, ${h} + 1, d2),
                getW(wR, wC, ${h} + 2, d2)
              );

              if (${f}) {
                vec3 xValues = vec3(
                  getX(batch, xR, xC, ${h}),
                  getX(batch, xR, xC, ${h} + 1),
                  getX(batch, xR, xC, ${h} + 2)
                );
                dotProd += dot(xValues, wValues);
              } else {
                vec3 xValues = vec3(
                  getX(batch, ${h}, xR, xC),
                  getX(batch, ${h} + 1, xR, xC),
                  getX(batch, ${h} + 2, xR, xC)
                );
                dotProd += dot(xValues, wValues);
              }

            }
          }
        }

        float result = dotProd;
        ${w}
        ${b}
        setOutput(result);
      }
    `}},QX=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,a=e.padInfo.top,n=e.padInfo.left,r=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,p=e.filterDepth,c=e.filterHeight,d=e.filterWidth,h=Math.floor(e.inChannels/4)*4,m=e.inChannels%4;this.userCode=`
      const ivec3 strides = ivec3(${r}, ${s}, ${i});
      const ivec3 pads = ivec3(${t}, ${a}, ${n});

      void main() {
        ivec5 coords = getOutputCoords();
        int batch = coords.x;
        int d2 = coords.u;

        ivec3 xFRCCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
        int xFCorner = xFRCCorner.x;
        int xRCorner = xFRCCorner.y;
        int xCCorner = xFRCCorner.z;

        // Convolve x(?, ?, ?, d1) with w(:, :, :, d1, d2) to get
        // y(yF, yR, yC, d2). ? = to be determined. : = across all
        // values in that axis.
        float dotProd = 0.0;
        for (int wF = 0; wF < ${p}; wF++) {
          int xF = xFCorner + wF * ${o};

          if (xF < 0 || xF >= ${e.inDepth}) {
            continue;
          }

          for (int wR = 0; wR < ${c}; wR++) {
            int xR = xRCorner + wR * ${l};

            if (xR < 0 || xR >= ${e.inHeight}) {
              continue;
            }

            for (int wC = 0; wC < ${d}; wC++) {
              int xC = xCCorner + wC * ${u};

              if (xC < 0 || xC >= ${e.inWidth}) {
                continue;
              }

              for (int d1 = 0; d1 < ${h}; d1 += 4) {
                vec4 xValues = vec4(
                  getX(batch, xF, xR, xC, d1),
                  getX(batch, xF, xR, xC, d1 + 1),
                  getX(batch, xF, xR, xC, d1 + 2),
                  getX(batch, xF, xR, xC, d1 + 3)
                );
                vec4 wValues = vec4(
                  getW(wF, wR, wC, d1, d2),
                  getW(wF, wR, wC, d1 + 1, d2),
                  getW(wF, wR, wC, d1 + 2, d2),
                  getW(wF, wR, wC, d1 + 3, d2)
                );

                dotProd += dot(xValues, wValues);
              }

              if (${m===1}) {
                dotProd +=
                  getX(batch, xF, xR, xC, ${h}) *
                  getW(wF, wR, wC, ${h}, d2);
              } else if (${m===2}) {
                vec2 xValues = vec2(
                  getX(batch, xF, xR, xC, ${h}),
                  getX(batch, xF, xR, xC, ${h} + 1)
                );
                vec2 wValues = vec2(
                  getW(wF, wR, wC, ${h}, d2),
                  getW(wF, wR, wC, ${h} + 1, d2)
                );
                dotProd += dot(xValues, wValues);
              } else if (${m===3}) {
                vec3 xValues = vec3(
                  getX(batch, xF, xR, xC, ${h}),
                  getX(batch, xF, xR, xC, ${h} + 1),
                  getX(batch, xF, xR, xC, ${h} + 2)
                );
                vec3 wValues = vec3(
                  getW(wF, wR, wC, ${h}, d2),
                  getW(wF, wR, wC, ${h} + 1, d2),
                  getW(wF, wR, wC, ${h} + 2, d2)
                );
                dotProd += dot(xValues, wValues);
              }
            }
          }
        }
        setOutput(dotProd);
      }
    `}},M8=class{constructor(e,t=!1,a=null,n=!1,r=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=ya(this.outputShape.length);let s=e.padInfo.left,i=e.strideWidth,o=e.dilationWidth,l=e.filterHeight,u=e.filterWidth,p=u,c=`
       int xR; int xC; int xCOffset;
       vec4 wTexel; vec4 previous; vec4 final;`;for(let f=0;f<u;f++)c+=`
           vec4 xTexelC${f*2};
           int xTexelC${f*2}Ready;
           vec4 xTexelC${f*2+1};
           int xTexelC${f*2+1}Ready;
           vec4 xC${f};`;c+=`
     for (int r = 0; r < ${l}; r++) {
      for (int d1 = 0; d1 < ${e.inChannels}; d1 += 2) {
       `;for(let f=0;f<u;f++)c+=`
           xTexelC${f*2} = vec4(0.0);
           xTexelC${f*2}Ready = 0;
           xTexelC${f*2+1} = vec4(0.0);
           xTexelC${f*2+1}Ready = 0;
           xC${f} = vec4(0.0);`;c+=`
         xR = xRCorner + r * dilations[0];
         if (xR >=0 && xR < inDims[0]) {
       `;for(let f=0;f<(p+1)/2;f++){let g=f*2;if(c+=`
           xC = xCCorner + ${g*o};
           `,i===1){if(g<u&&(s%2===1?(c+=`
                 xCOffset = xC + 1;
                 if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g}Ready == 0) {
                   xTexelC${g} = getX(batch, xR, xCOffset, d1);

                   // Need to manually clear unused channels in case
                   // we're reading from recycled texture.
                   if (xCOffset + 1 >= inDims[1]) {
                     xTexelC${g}.zw = vec2(0.0);
                   }
                   xTexelC${g}Ready = 1;
                 }
               `,o===1&&g>0?c+=`
                 xC${g} = vec4(xTexelC${g-2}.zw, xTexelC${g}.xy);
                 `:c+=`
                   xCOffset = xC + 1 - 2;

                   if (xCOffset >= 0 && xCOffset < inDims[1]) {
                     previous = getX(batch, xR, xCOffset, d1);

                     // Need to manually clear unused channels in case
                     // we're reading from recycled texture.
                     if (xCOffset + 1 >= inDims[1]) {
                       previous.zw = vec2(0.0);
                     }

                     xC${g} = vec4(previous.zw, xTexelC${g}.xy);
                   } else {
                     xC${g} = vec4(0.0, 0.0, xTexelC${g}.xy);
                   }
                   `):c+=`
                 if (xC >= 0 && xC < inDims[1] && xTexelC${g}Ready == 0) {
                   xTexelC${g} = getX(batch, xR, xC, d1);
                   if (xC + 1 >= inDims[1]) {
                     xTexelC${g}.zw = vec2(0.0);
                   }
                   xTexelC${g}Ready = 1;
                 }

                 xC${g} = xTexelC${g};
                 `,g+1<u)){let y=s%2===0?v.nearestLargerEven(o):o;o%2===0&&s%2===1||o%2!==0&&s%2!==1?(c+=`
                   xCOffset = xC + imod(pads[1], 2) + ${y};

                   if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g+1}Ready == 0) {
                     xTexelC${g+1} = getX(batch, xR, xCOffset, d1);

                     // Need to manually clear unused channels in case
                     // we're reading from recycled texture.
                     if (xCOffset + 1 >= inDims[1]) {
                       xTexelC${g+1}.zw = vec2(0.0);
                     }
                     xTexelC${g+1}Ready = 1;
                   }
                   `,o>1?c+=`
                     xCOffset -= 2;
                     if (xCOffset >= 0 && xCOffset < inDims[1]) {
                      previous = getX(batch, xR, xCOffset, d1);
                      xC${g+1} = vec4(previous.zw, xTexelC${g+1}.xy);
                     } else {
                      xC${g+1} = vec4(0.0, 0.0, xTexelC${g+1}.xy);
                     }
                     `:c+=`
                     xC${g+1} = vec4(xTexelC${g}.zw, xTexelC${g+1}.xy);
                     `):y===1?c+=`
                     xC${g+1} = xTexelC${g};
                     `:c+=`
                     xCOffset = xC + ${y};

                     if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g+1}Ready == 0) {
                       xTexelC${g+1} = getX(batch, xR, xCOffset, d1);
                       if (xCOffset + 1 >= inDims[1]) {
                         xTexelC${g+1}.zw = vec2(0.0);
                       }
                       xTexelC${g+1}Ready = 1;
                     }

                     xC${g+1} = xTexelC${g+1};
                     `}}else g<u&&(s%2===1?(c+=`
                 xCOffset = xC + 1 - strides[1];
                 if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g}Ready == 0) {
                   xTexelC${g} = getX(batch, xR, xCOffset, d1);
                   // Need to manually clear unused channels in case
                   // we're reading from recycled texture.
                   if (xCOffset + 1 >= inDims[1]) {
                     xTexelC${g}.zw = vec2(0.0);
                   }
                   xTexelC${g}Ready = 1;
                 }

                 if(xC + 1 >= 0 && xC + 1 < inDims[1] && xTexelC${g+1}Ready == 0) {
                   xTexelC${g+1} = getX(batch, xR, xC + 1, d1);
                   // Need to manually clear unused channels in case
                   // we're reading from recycled texture.
                   if (xC + 2 >= inDims[1]) {
                     xTexelC${g+1}.zw = vec2(0.0);
                   }
                   xTexelC${g+1}Ready = 1;
                 }

                 xC${g} = vec4(xTexelC${g}.zw, xTexelC${g+1}.zw);
               `,g+1<u&&(c+=`
                   final = vec4(0.0);
                   xCOffset = xC + 1 + strides[1];
                   if(xCOffset >= 0 && xCOffset < inDims[1]) {
                     final = getX(batch, xR, xCOffset, d1);
                   }
                   xC${g+1} = vec4(xTexelC${g+1}.xy, final.xy);
                 `)):(c+=`
                 if(xC >= 0 && xC < inDims[1] && xTexelC${g}Ready == 0) {
                   xTexelC${g} = getX(batch, xR, xC, d1);
                   if (xC + 1 >= inDims[1]) {
                     xTexelC${g}.zw = vec2(0.0);
                   }
                   xTexelC${g}Ready = 1;
                 }

                 xCOffset = xC + strides[1];
                 if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g+1}Ready == 0) {
                   xTexelC${g+1} = getX(batch, xR, xCOffset, d1);
                   if (xCOffset + 1 >= inDims[1]) {
                     xTexelC${g+1}.zw = vec2(0.);
                   }
                   xTexelC${g+1}Ready = 1;
                 }

                 xC${g} = vec4(
                   xTexelC${g}.xy, xTexelC${g+1}.xy);
               `,g+1<u&&(c+=`
                   xC${g+1} = vec4(xTexelC${g}.zw, xTexelC${g+1}.zw);
                 `)));g<u&&(c+=`
             wTexel = getW(r, ${g}, d1, d2);
             dotProd += xC${g}.xxzz * vec4(wTexel.xy, wTexel.xy);
             if(d1 + 1 < ${e.inChannels}) {
               dotProd += xC${g}.yyww * vec4(wTexel.zw, wTexel.zw);
             }
           `,g+1<u&&(c+=`
               wTexel = getW(r, ${g+1}, d1, d2);
               dotProd += xC${g+1}.xxzz * vec4(wTexel.xy, wTexel.xy);
               if(d1 + 1 < ${e.inChannels}) {
                 dotProd += xC${g+1}.yyww * vec4(wTexel.zw, wTexel.zw);
               }
             `))}c+=`
     }
   `,c+=`
     }
   `,c+=`
     }
   `;let d="",h="";a&&(n?d=`vec4 activation(vec4 a) {
           vec4 b = getPreluActivationWeightsAtOutCoords();
           ${a}
         }`:r?d=`vec4 activation(vec4 a) {
           vec4 b = getLeakyreluAlphaAtOutCoords();
           ${a}
         }`:d=`vec4 activation(vec4 x) {
           ${a}
         }`,h="result = activation(result);");let m=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),r&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
       ${d}

       void main() {
         ivec4 coords = getOutputCoords();
         int batch = coords.x;
         ivec2 xRCCorner = coords.yz * strides - pads;
         int d2 = coords.w;
         int xRCorner = xRCCorner.x;
         int xCCorner = xRCCorner.y;

         //intialize dotProd with a small epsilon seems to reduce GPU accuracy loss.
         vec4 dotProd = vec4(0.000000000000001);

         ${c}

         vec4 result = dotProd - vec4(0.000000000000001);
         ${m}
         ${h}
         setOutput(result);
       }
     `}},eK=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"inputShape",type:"ivec4"},{name:"pad",type:"ivec2"},{name:"stride",type:"ivec2"},{name:"dilation",type:"ivec2"},{name:"inChannels",type:"int"},{name:"itemsPerBlockRow",type:"int"},{name:"outWidth",type:"int"}],this.outputShape=e,this.enableShapeUniforms=ya(this.outputShape.length);let{dataFormat:a}=t,n=Ra(),r=a==="channelsLast",s=r?1:2,i=r?2:3,o=this.enableShapeUniforms?"if(blockIndex < outShape[2] && pos < outShape[1]) {":`if(blockIndex < ${e[2]} && pos < ${e[1]}) {`,l="";for(let u=0;u<=1;u++)for(let p=0;p<=1;p++)l+=`
          blockIndex = rc.z + ${p};
          pos = rc.y + ${u};

          ${o}
            offsetY = int(blockIndex / outWidth) * stride[0] - pad[0];
            d0 = offsetY + dilation[0] * (pos / itemsPerBlockRow);

            if(d0 < inputShape[${s}] && d0 >= 0) {
              // Use custom imod instead mod. On Intel GPU, mod may generate
              // unexpected value.
              // https://github.com/tensorflow/tfjs/issues/5447
              offsetX = imod(blockIndex, outWidth) * stride[1] - pad[1];
              d1 = offsetX + dilation[1] * (imod(pos, itemsPerBlockRow) /
                  inChannels);

              if(d1 < inputShape[${i}] && d1 >= 0) {

                ch = imod(pos, inChannels);

                if (${r}) {
                  innerDims = vec2(d1, ch);
                  result[${u*2+p}] = getChannel(
                    getA(rc.x, d0, int(innerDims.x),
                    int(innerDims.y)), innerDims);
                } else {
                  innerDims = vec2(d0, d1);
                  result[${u*2+p}] = getChannel(
                    getA(rc.x, ch, int(innerDims.x),
                    int(innerDims.y)), innerDims);
                }
              }
            }
          }
        `;this.userCode=`
      void main() {
        ivec3 rc = getOutputCoords();

        vec4 result = vec4(0);

        int blockIndex, pos, offsetY, d0, offsetX, d1, ch;
        vec2 innerDims;

        ${l}

        ${n.output} = result;
      }
    `}};function Ih(e,t){let a=e.length;return a>=3?t?[...e.slice(0,-3),e[a-3]*e[a-2],e[a-1]]:[...e.slice(0,-3),e[a-3],e[a-2]*e[a-1]]:!t&&a===1&&e[0]>1?[e[0],1]:null}function $8({x:e,filter:t,convInfo:a,backend:n,bias:r=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let l=e.shape,u=n.texData.get(e.dataId),p=a.inChannels,c=l[0]*l[1]*l[2],d=a.outChannels,h=a.dataFormat==="channelsLast",m=!1,f=!1,g,y=[];if(s!=null){let x=Ih(s.shape,h);x!=null&&(s=pe({inputs:{x:s},backend:n,attrs:{shape:x}}),y.push(s))}if(r!=null){let x=Ih(r.shape,h);x!=null&&(r=pe({inputs:{x:r},backend:n,attrs:{shape:x}}),y.push(r))}if(!((c===1||d===1)&&p>I8)&&u.isPacked&&h&&u.texture!=null&&l[2]%2!==0&&v.arraysEqual(u.shape.slice(-3),l.slice(-3))){let x=l[0]*l[1]*(l[2]+1),A={dataId:e.dataId,shape:[1,x,a.inChannels],dtype:e.dtype},b=u.shape;u.shape=u.shape.slice(),u.shape[u.shape.length-2]++,v.assert(ep(u.shape,A.shape),()=>`packed reshape ${u.shape} to ${A.shape} isn't free`);let w=pe({inputs:{x:t},backend:n,attrs:{shape:[1,a.inChannels,a.outChannels]}});y.push(w);let I=kh({a:A,b:w,backend:n,transposeA:m,transposeB:f,bias:r,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),T=n.texData.get(I.dataId);v.assert(T.isPacked,()=>"batchMatMul result is expected to be packed"),u.shape=b,T.shape=a.outShape,g=en({inputs:{x:I},backend:n}),g.shape=a.outShape,y.push(I)}else{let x=a.outHeight*a.outWidth,A=pe({inputs:{x:e},backend:n,attrs:{shape:h?[a.batchSize,x,a.inChannels]:[a.batchSize,a.inChannels,x]}}),b=pe({inputs:{x:t},backend:n,attrs:{shape:[1,a.inChannels,a.outChannels]}}),w=kh({a:h?A:b,b:h?b:A,transposeA:!h,transposeB:f,backend:n,bias:r,activation:o,preluActivationWeights:s,leakyreluAlpha:i});g=pe({inputs:{x:w},backend:n,attrs:{shape:a.outShape}}),y.push(A),y.push(b),y.push(w)}for(let x of y)n.disposeIntermediateTensorInfo(x);return g}function P8({x:e,filter:t,convInfo:a,backend:n,bias:r=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let{filterWidth:l,filterHeight:u,inChannels:p,outWidth:c,outHeight:d,dataFormat:h}=a,m=h==="channelsLast",f=l*u*p,g=d*c,y=[a.batchSize,f,g],x=!0,A=!1,b=[];if(s!=null){let G=Ih(s.shape,m);G!=null&&(s=pe({inputs:{x:s},backend:n,attrs:{shape:G}}),b.push(s))}if(r!=null){let G=Ih(r.shape,m);G!=null&&(r=pe({inputs:{x:r},backend:n,attrs:{shape:G}}),b.push(r))}let w=pe({inputs:{x:t},backend:n,attrs:{shape:[1,f,v.sizeFromShape(t.shape)/f]}});b.push(w);let I=new eK(y,a),T=[e.shape,[a.padInfo.top,a.padInfo.left],[a.strideHeight,a.strideWidth],[a.dilationHeight,a.dilationWidth],[a.inChannels],[a.filterWidth*a.inChannels],[a.outWidth]],N=n.runWebGLProgram(I,[e],"float32",T),M=pe({inputs:{x:N},backend:n,attrs:{shape:y}});b.push(N),b.push(M);let $=r!=null,E=s!=null,S=o==="leakyrelu",_=o?tp(o,!0):null,O=new k8(m?M.shape:w.shape,m?w.shape:M.shape,m?[a.batchSize,g,a.outChannels]:[a.batchSize,a.outChannels,g],x,A,$,_,E,S),W=m?[M,w]:[w,M];if(r&&W.push(r),E&&W.push(s),S){let G=n.makeTensorInfo([],"float32",v.createScalarValue(i,"float32"));W.push(G),b.push(G)}let P=n.runWebGLProgram(O,W,"float32"),U=pe({inputs:{x:P},backend:n,attrs:{shape:a.outShape}});b.push(P);for(let G of b)n.disposeIntermediateTensorInfo(G);return U}function tK(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:u,dimRoundingMode:p}=n,c=C.convertConv2DDataFormat(l),d=C.computeConv2DInfo(r.shape,s.shape,i,u,o,p,!1,c),h;if(d.filterHeight===1&&d.filterWidth===1&&d.dilationHeight===1&&d.dilationWidth===1&&d.strideHeight===1&&d.strideWidth===1&&(d.padInfo.type==="SAME"||d.padInfo.type==="VALID"))h=$8({x:r,filter:s,convInfo:d,backend:a});else if(d.strideWidth<=2&&c==="channelsLast"&&B().getBool("WEBGL_EXP_CONV")){let f=new M8(d),g=[[d.padInfo.top,d.padInfo.left],[d.strideHeight,d.strideWidth],[d.dilationHeight,d.dilationWidth],[d.inHeight,d.inWidth]];h=a.runWebGLProgram(f,[r,s],"float32",g)}else if(B().getBool("WEBGL_CONV_IM2COL"))h=P8({x:r,filter:s,convInfo:d,backend:a});else{let f=new E8(d);h=a.runWebGLProgram(f,[r,s],"float32")}let m=pe({inputs:{x:h},backend:a,attrs:{shape:d.outShape}});return a.disposeIntermediateTensorInfo(h),m}var aK={kernelName:wi,backendName:"webgl",kernelFunc:tK},nK=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,a=e.strideWidth,n=e.padInfo.top,r=e.padInfo.left,s=e.dataFormat==="channelsLast";this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int wR = coords.x;
        int wC = coords.y;
        int d1 = coords.z;
        int d2 = coords.w;

        // Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;

        for (int b = 0; b < ${e.batchSize}; b++) {
          for (int yR = 0; yR < ${e.outHeight}; yR++) {
            int xR = wR + yR * ${t} - ${n};

            if (xR < 0 || xR >= ${e.inHeight}) {
              continue;
            }

            for (int yC = 0; yC < ${e.outWidth}; yC++) {
              int xC = wC + yC * ${a} - ${r};

              if (xC < 0 || xC >= ${e.inWidth}) {
                continue;
              }

              ${s?`float dyValue = getDy(b, yR, yC, d2);
              float xValue = getX(b, xR, xC, d1);
              dotProd += (xValue * dyValue);`:`float dyValue = getDy(b, d2, yR, yC);
              float xValue = getX(b, d1, xR, xC);
              dotProd += (xValue * dyValue);`}
            }
          }
        }
        setOutput(dotProd);
      }
    `}},rK=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,a=e.filterWidth,n=e.strideHeight,r=e.strideWidth,s=e.dataFormat==="channelsLast",i=t-1-e.padInfo.top,o=a-1-e.padInfo.left,l=s?1:2,u=s?2:3,p=s?3:1;this.userCode=`
      const ivec2 pads = ivec2(${i}, ${o});

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords[0];
        int d1 = coords[${p}];

        ivec2 dyCorner = ivec2(coords[${l}], coords[${u}]) - pads;
        int dyRCorner = dyCorner.x;
        int dyCCorner = dyCorner.y;

        // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;
        for (int wR = 0; wR < ${t}; wR++) {
          float dyR = float(dyRCorner + wR) / ${n}.0;

          if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
            continue;
          }
          int idyR = int(dyR);

          int wRPerm = ${t} - 1 - wR;

          for (int wC = 0; wC < ${a}; wC++) {
            float dyC = float(dyCCorner + wC) / ${r}.0;

            if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
                fract(dyC) > 0.0) {
              continue;
            }
            int idyC = int(dyC);

            int wCPerm = ${a} - 1 - wC;

            for (int d2 = 0; d2 < ${e.outChannels}; d2++) {

              if (${s}) {
                float xValue = getDy(batch, idyR, idyC, d2);
                float wValue = getW(wRPerm, wCPerm, d1, d2);
                dotProd += xValue * wValue;
              } else {
                float xValue = getDy(batch, d2, idyR, idyC);
                float wValue = getW(wRPerm, wCPerm, d1, d2);
                dotProd += xValue * wValue;
              }

            }
          }
        }
        setOutput(dotProd);
      }
    `}},sK=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideDepth,a=e.strideHeight,n=e.strideWidth,r=e.padInfo.front,s=e.padInfo.top,i=e.padInfo.left;this.userCode=`
      void main() {
        ivec5 coords = getOutputCoords();
        int wF = coords.x;
        int wR = coords.y;
        int wC = coords.z;
        int d1 = coords.w;
        int d2 = coords.u;

        float dotProd = 0.0;

        for (int b = 0; b < ${e.batchSize}; b++) {
          for (int yF = 0; yF < ${e.outDepth}; yF++) {
            int xF = wF + yF * ${t} - ${r};

            if (xF < 0 || xF >= ${e.inDepth}) {
              continue;
            }

            for (int yR = 0; yR < ${e.outHeight}; yR++) {
              int xR = wR + yR * ${a} - ${s};

              if (xR < 0 || xR >= ${e.inHeight}) {
                continue;
              }

              for (int yC = 0; yC < ${e.outWidth}; yC++) {
                int xC = wC + yC * ${n} - ${i};

                if (xC < 0 || xC >= ${e.inWidth}) {
                  continue;
                }

                float dyValue = getDy(b, yF, yR, yC, d2);
                float xValue = getX(b, xF, xR, xC, d1);
                dotProd += (xValue * dyValue);
              }
            }
          }
        }
        setOutput(dotProd);
      }
    `}},iK=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,a=e.filterHeight,n=e.filterWidth,r=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=t-1-e.padInfo.front,l=a-1-e.padInfo.top,u=n-1-e.padInfo.left;this.userCode=`
      const ivec3 pads = ivec3(${o}, ${l}, ${u});

      void main() {
        ivec5 coords = getOutputCoords();
        int batch = coords.x;
        int d1 = coords.u;


        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
        int dyFCorner = dyCorner.x;
        int dyRCorner = dyCorner.y;
        int dyCCorner = dyCorner.z;

        float dotProd = 0.0;
        for (int wF = 0; wF < ${t}; wF++) {
          float dyF = float(dyFCorner + wF) / ${r}.0;

          if (dyF < 0.0 || dyF >= ${e.outDepth}.0 || fract(dyF) > 0.0) {
            continue;
          }
          int idyF = int(dyF);

          int wFPerm = ${t} - 1 - wF;

          for (int wR = 0; wR < ${a}; wR++) {
            float dyR = float(dyRCorner + wR) / ${s}.0;

            if (dyR < 0.0 || dyR >= ${e.outHeight}.0 ||
              fract(dyR) > 0.0) {
              continue;
            }
            int idyR = int(dyR);

            int wRPerm = ${a} - 1 - wR;

            for (int wC = 0; wC < ${n}; wC++) {
              float dyC = float(dyCCorner + wC) / ${i}.0;

              if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
                  fract(dyC) > 0.0) {
                continue;
              }
              int idyC = int(dyC);

              int wCPerm = ${n} - 1 - wC;

              for (int d2 = 0; d2 < ${e.outChannels}; d2++) {
                float xValue = getDy(batch, idyF, idyR, idyC, d2);
                float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);
                dotProd += xValue * wValue;
              }
            }
          }
        }
        setOutput(dotProd);
      }
    `}};function oK(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:u,filterShape:p}=n,c=C.convertConv2DDataFormat(l),d=C.computeConv2DInfo(r.shape,p,i,1,o,u,!1,c),h=new nK(d);return a.runWebGLProgram(h,[r,s],"float32")}var lK={kernelName:mp,backendName:"webgl",kernelFunc:oK},uK=class{constructor(e){this.variableNames=["dy","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"strides",type:"vec2"}],this.outputShape=e.inShape,this.enableShapeUniforms=ya(this.outputShape.length);let t=e.filterHeight,a=e.filterWidth,n=t-1-e.padInfo.top,r=a-1-e.padInfo.left;this.userCode=`
      const ivec2 pads = ivec2(${n}, ${r});

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords[0];
        int d1 = coords[3];

        ivec2 dyCorner = ivec2(coords[1], coords[2]) - pads;
        int dyRCorner = dyCorner.x;
        int dyCCorner = dyCorner.y;

        vec4 result = vec4(0.);
        for (int wR = 0; wR < ${t}; wR++) {
          float dyR = float(dyRCorner + wR) / strides[0];
          if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
            continue;
          }
          int idyR = int(dyR);
          int wRPerm = ${t} - 1 - wR;

          for (int wC = 0; wC < ${a}; wC++) {
            int wCPerm = ${a} - 1 - wC;

            float dyC = float(dyCCorner + wC) / strides[1];
            bool idyCVal = (dyC >= 0.0) && (dyC < ${e.outWidth}.0)
              && (fract(dyC) == 0.0);
            int idyC = int(dyC);

            float dyC2 = float(dyCCorner + wC + 1) / strides[1];
            bool idyCVal2 = (dyC2 >= 0.0) && (dyC2 < ${e.outWidth}.0)
              && (fract(dyC2) == 0.0);
            int idyC2 = int(dyC2);

            if (idyCVal && idyCVal2) {
              for (int d2 = 0; d2 < ${e.outChannels}; d2 += 2) {
                vec4 wValue = getW(wRPerm, wCPerm, d1, d2);
                vec4 dySample = getDy(batch, idyR, idyC, d2);
                vec4 dySample2 = (idyC / 2 == idyC2 / 2) ?
                  dySample : getDy(batch, idyR, idyC2, d2);

                vec2 dyValue = mod(float(idyC), 2.) == 0. ?
                  dySample.xy : dySample.zw;
                result.xy += vec2(dot(dyValue, wValue.xy),
                  dot(dyValue, wValue.zw));

                dyValue = mod(float(idyC2), 2.) == 0. ?
                  dySample2.xy : dySample2.zw;
                result.zw += vec2(dot(dyValue, wValue.xy),
                  dot(dyValue, wValue.zw));
              }
            } else if (idyCVal) {
              for (int d2 = 0; d2 < ${e.outChannels}; d2 += 2) {
                vec4 wValue = getW(wRPerm, wCPerm, d1, d2);
                vec4 dySample = getDy(batch, idyR, idyC, d2);
                vec2 dyValue = mod(float(idyC), 2.) == 0. ?
                  dySample.xy : dySample.zw;
                result.xy += vec2(dot(dyValue, wValue.xy),
                  dot(dyValue, wValue.zw));
              }
            } else if (idyCVal2) {
              for (int d2 = 0; d2 < ${e.outChannels}; d2 += 2) {
                vec4 wValue = getW(wRPerm, wCPerm, d1, d2);
                vec4 dySample = getDy(batch, idyR, idyC2, d2);
                vec2 dyValue = mod(float(idyC2), 2.) == 0. ?
                  dySample.xy : dySample.zw;
                result.zw += vec2(dot(dyValue, wValue.xy),
                  dot(dyValue, wValue.zw));
              }
            }
          }
        }
        setOutput(result);
      }
    `}};function dK(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:u,dimRoundingMode:p}=n,c=C.convertConv2DDataFormat(u),d=C.computeConv2DInfo(i,s.shape,o,1,l,p,!1,c);if(B().getBool("WEBGL_PACK_CONV2DTRANSPOSE")&&c==="channelsLast"){let h=[[d.strideHeight,d.strideWidth]],m=new uK(d);return a.runWebGLProgram(m,[r,s],"float32",h)}else{let h=new rK(d);return a.runWebGLProgram(h,[r,s],"float32")}}var pK={kernelName:ki,backendName:"webgl",kernelFunc:dK};function cK(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=n,u=C.computeConv3DInfo(r.shape,s.shape,i,l,o),p=new QX(u);return a.runWebGLProgram(p,[r,s],"float32")}var hK={kernelName:Ii,backendName:"webgl",kernelFunc:cK};function mK(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,dy:s}=t,{strides:i,pad:o,filterShape:l}=n,u=C.computeConv3DInfo(r.shape,l,i,1,o),p=new sK(u);return a.runWebGLProgram(p,[r,s],"float32")}var fK={kernelName:fu,backendName:"webgl",kernelFunc:mK};function gK(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,filter:s}=t,{pad:i,strides:o,inputShape:l}=n,u=C.computeConv3DInfo(l,s.shape,o,1,i),p=new iK(u);return a.runWebGLProgram(p,[r,s],"float32")}var yK={kernelName:Si,backendName:"webgl",kernelFunc:gK},xK=Qu+`
  return cos(x);
`,AK=`
  vec4 result = cos(x);
  bvec4 isNaN = isnan(x);
  ${il}
  return result;
`,bK=tt({opSnippet:xK,packedOpSnippet:AK}),vK={kernelName:Ci,backendName:"webgl",kernelFunc:bK},wK=`
  float e2x = exp(-x);
  return (e2x + 1.0 / e2x) / 2.0;
`,kK=tt({opSnippet:wK}),IK={kernelName:Ti,backendName:"webgl",kernelFunc:kK},SK=class{constructor(e,t,a,n,r){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[s,i,o,l]=e,[u]=t,[p,c]=a;this.outputShape=[u,p,c,l];let d=n==="bilinear"?1:0,[h,m]=[`${i-1}.0`,`${o-1}.0`],[f,g,y]=p>1?[`${(i-1)/(p-1)}`,"(y2-y1) * height_ratio",`y1*${h} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${h}`],[x,A,b]=c>1?[`${(o-1)/(c-1)}`,"(x2-x1) * width_ratio",`x1*${m} + float(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${m}`];this.userCode=`
      const float height_ratio = float(${f});
      const float width_ratio = float(${x});
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int y = coords[1];
        int x = coords[2];
        int d = coords[3];

        // get box vals
        float y1 = getBoxes(b,0);
        float x1 = getBoxes(b,1);
        float y2 = getBoxes(b,2);
        float x2 = getBoxes(b,3);

        // get image in batch index
        int bInd = round(getBoxInd(b));
        if(bInd < 0 || bInd >= ${s}) {
          return;
        }

        float height_scale = ${g};
        float width_scale = ${A};

        float in_y = ${y};
        if( in_y < 0.0 || in_y > ${h} ) {
          setOutput(float(${r}));
          return;
        }
        float in_x = ${b};
        if( in_x < 0.0 || in_x > ${m} ) {
          setOutput(float(${r}));
          return;
        }

        vec2 sourceFracIndexCR = vec2(in_x,in_y);
        if(${d} == 1) {
          // Compute the four integer indices.
          ivec2 sourceFloorCR = ivec2(sourceFracIndexCR);
          ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR));

          float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d);
          float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d);
          float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);
          float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);

          vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);

          float top = topLeft + (topRight - topLeft) * fracCR.x;
          float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;
          float newValue = top + (bottom - top) * fracCR.y;
          setOutput(newValue);
        } else {
          // Compute the coordinators of nearest neighbor point.
          ivec2 sourceNearestCR = ivec2(floor(
            sourceFracIndexCR + vec2(0.5,0.5)));
          float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);
          setOutput(newValue);
        }
      }
    `}},CK=e=>{let{inputs:t,backend:a,attrs:n}=e,{image:r,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:u}=n,p=new SK(r.shape,s.shape,o,l,u);return a.runWebGLProgram(p,[r,s,i],"float32")},TK={kernelName:Ei,backendName:"webgl",kernelFunc:CK},np;(function(e){e.Prod="*",e.Sum="+"})(np||(np={}));var L5=class{constructor(e,t,a,n){this.op=e,this.outputShape=t,this.variableNames=["x"],this.customUniforms=[{name:"index",type:"float"}];let r=this.outputShape.length,s=this.op===np.Prod?"1.0":"0.0",i=a?s:`getX(${W5(r,"coords",this.op)})`,o=this.outputShape[this.outputShape.length-1],l="",u="";a?(l=n?`end != ${o-1}`:"end != 0",u=n?"end + 1":"end - 1"):(l=n?`end + pow2 < ${o}`:"end >= pow2",u=n?"end + pow2":"end - pow2"),this.userCode=`
      void main() {
        ${ft(r)} coords = getOutputCoords();
        int end = ${B5(r,"coords",this.op)};
        float val = ${i};
        int pow2 = int(pow(2.0, index));
        if (${l}) {
          int idx = ${u};
          ${B5(r,"coords",this.op)} = idx;
          val ${this.op}= getX(${W5(r,"coords",this.op)});
        }
        setOutput(val);
      }
    `}};function W5(e,t,a){if(e===1)return`${t}`;if(e===2)return`${t}.x, ${t}.y`;if(e===3)return`${t}.x, ${t}.y, ${t}.z`;if(e===4)return`${t}.x, ${t}.y, ${t}.z, ${t}.w`;throw new Error(`Cumulative ${a} for rank ${e} is not yet supported`)}function B5(e,t,a){if(e===1)return`${t}`;if(e===2)return`${t}.y`;if(e===3)return`${t}.z`;if(e===4)return`${t}.w`;throw new Error(`Cumulative ${a} for rank ${e} is not yet supported`)}function _8(e,t,a,n,r,s){let i=t.shape.length,o=C.getAxesPermutation([n],i),l=t;o!=null&&(l=Ca({inputs:{x:t},backend:a,attrs:{perm:o}}));let u=C.getInnerMostAxes(1,i)[0];if(u!==i-1)throw new Error(`WebGL cumprod shader expects an inner-most axis=${t.shape.length-1} but got axis=${n}`);let p=l.shape[u],c=en({inputs:{x:l},backend:a});for(let d=0;d<=Math.ceil(Math.log2(p))-1;d++){let h=new L5(e,l.shape,!1,s),m=[[d]],f=c;c=a.runWebGLProgram(h,[c],c.dtype,m),a.disposeIntermediateTensorInfo(f)}if(r){let d=new L5(e,l.shape,r,s),h=c;c=a.runWebGLProgram(d,[c],c.dtype),a.disposeIntermediateTensorInfo(h)}if(o!=null){let d=C.getUndoAxesPermutation(o),h=Ca({inputs:{x:c},backend:a,attrs:{perm:d}});return a.disposeIntermediateTensorInfo(c),a.disposeIntermediateTensorInfo(l),h}return c}function NK(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=n;return _8(np.Prod,r,a,s,i,o)}var RK={kernelName:Ni,backendName:"webgl",kernelFunc:NK};function EK(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=n;return _8(np.Sum,r,a,s,i,o)}var MK={kernelName:Ri,backendName:"webgl",kernelFunc:EK};function $K(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,weights:s}=t,{size:i,binaryOutput:o}=n;if(r.shape.length===1){let l=a.readSync(r.dataId),u=a.readSync(s.dataId),p=c8(l,u,s.dtype,s.shape,i);return a.makeTensorInfo([i],s.dtype,p)}else if(r.shape.length===2){let l=a.bufferSync(r),u=a.bufferSync(s),p=_H(l,u,i,o);return a.makeTensorInfo(p.shape,s.dtype,p.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${r.shape.length}.`)}var PK={kernelName:gu,backendName:"webgl",kernelFunc:$K},_K=class{constructor(e,t,a){this.variableNames=["x"],this.outputShape=[],this.outputShape=e,this.blockSize=t,this.dataFormat=a,this.userCode=`
    void main() {
      ivec4 coords = getOutputCoords();
      int b = coords[0];
      int h = ${this.getHeightCoordString()};
      int w = ${this.getWidthCoordString()};
      int d = ${this.getDepthCoordString()};

      int in_h = h / ${t};
      int offset_h = imod(h, ${t});
      int in_w = w / ${t};
      int offset_w = imod(w, ${t});
      int offset_d = (offset_h * ${t} + offset_w) *
        ${this.getOutputDepthSize()};
      int in_d = d + offset_d;

      float result = ${this.getInputSamplingString()};
      setOutput(result);
    }
  `}getHeightCoordString(){return this.dataFormat==="NHWC"?"coords[1]":"coords[2]"}getWidthCoordString(){return this.dataFormat==="NHWC"?"coords[2]":"coords[3]"}getDepthCoordString(){return this.dataFormat==="NHWC"?"coords[3]":"coords[1]"}getOutputDepthSize(){return this.dataFormat==="NHWC"?this.outputShape[3]:this.outputShape[1]}getInputSamplingString(){return this.dataFormat==="NHWC"?"getX(b, in_h, in_w, in_d)":"getX(b, in_d, in_h, in_w)"}};function FK(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockSize:s,dataFormat:i}=n,o=r.shape[0],l=i==="NHWC"?r.shape[1]:r.shape[2],u=i==="NHWC"?r.shape[2]:r.shape[3],p=i==="NHWC"?r.shape[3]:r.shape[1],c=l*s,d=u*s,h=p/(s*s),m=i==="NHWC"?[o,c,d,h]:[o,h,c,d],f=new _K(m,s,i);return a.runWebGLProgram(f,[r],r.dtype)}var DK={kernelName:Mi,backendName:"webgl",kernelFunc:FK},F8=class{constructor(e,t=!1,a=null,n=!1,r=!1){this.variableNames=["x","W"],this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=ya(this.outputShape.length);let s=e.filterHeight,i=e.filterWidth,o=e.outChannels/e.inChannels,l="",u="";a&&(n?l=`float activation(float a) {
          float b = getPreluActivationWeightsAtOutCoords();
          ${a}
        }`:r?l=`float activation(float a) {
          float b = getLeakyreluAlphaAtOutCoords();
          ${a}
        }`:l=`
          float activation(float x) {
            ${a}
          }
        `,u="result = activation(result);");let p=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),r&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
      ${l}

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords.x;
        ivec2 xRCCorner = coords.yz * strides - pads;
        int d2 = coords.w;
        int d1 = d2 / ${o};
        int q = d2 - d1 * ${o};

        int xRCorner = xRCCorner.x;
        int xCCorner = xRCCorner.y;

        // Convolve x(?, ?, d1) with w(:, :, d1, q) to get y(yR, yC, d2).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;
        // TO DO(dsmilkov): Flatten the two for loops and vec4 the operations.
        for (int wR = 0; wR < ${s}; wR++) {
          int xR = xRCorner + wR * dilations[0];

          if (xR < 0 || xR >= inDims[0]) {
            continue;
          }

          for (int wC = 0; wC < ${i}; wC++) {
            int xC = xCCorner + wC * dilations[1];

            if (xC < 0 || xC >= inDims[1]) {
              continue;
            }

            float xVal = getX(batch, xR, xC, d1);
            float wVal = getW(wR, wC, d1, q);
            dotProd += xVal * wVal;
          }
        }

        float result = dotProd;
        ${p}
        ${u}
        setOutput(result);
      }
    `}},D8=class{constructor(e,t=!1,a=null,n=!1,r=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=ya(this.outputShape.length);let s=e.outChannels/e.inChannels,i=e.padInfo.left,o=e.strideWidth,l=e.dilationWidth,u=e.filterHeight,p=e.filterWidth,c=p,d=`
      int xR; int xC; int xCOffset;
      vec4 wTexel; vec4 previous; vec4 final;`;for(let g=0;g<p;g++)d+=`
          vec4 xTexelC${g*2};
          int xTexelC${g*2}Ready;
          vec4 xTexelC${g*2+1};
          int xTexelC${g*2+1}Ready;
          vec4 xC${g};`;d+=`
    for (int r = 0; r < ${u}; r++) {
      `;for(let g=0;g<p;g++)d+=`
          xTexelC${g*2} = vec4(0.0);
          xTexelC${g*2}Ready = 0;
          xTexelC${g*2+1} = vec4(0.0);
          xTexelC${g*2+1}Ready = 0;
          xC${g} = vec4(0.0);`;d+=`
        xR = xRCorner + r * dilations[0];
        if (xR >=0 && xR < inDims[0]) {
      `;for(let g=0;g<(c+1)/2;g++){let y=g*2;if(d+=`
          xC = xCCorner + ${y*l};
          `,o===1){if(y<p&&(i%2===1?(d+=`
                xCOffset = xC + 1;
                if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${y}Ready == 0) {
                  xTexelC${y} = getX(batch, xR, xCOffset, d1);

                  // Need to manually clear unused channels in case
                  // we're reading from recycled texture.
                  if (xCOffset + 1 >= inDims[1]) {
                    xTexelC${y}.zw = vec2(0.0);
                  }
                  xTexelC${y}Ready = 1;
                }
              `,l===1&&y>0?d+=`
                xC${y} = vec4(xTexelC${y-2}.zw, xTexelC${y}.xy);
                `:d+=`
                  xCOffset = xC + 1 - 2;

                  if (xCOffset >= 0 && xCOffset < inDims[1]) {
                    previous = getX(batch, xR, xCOffset, d1);

                    // Need to manually clear unused channels in case
                    // we're reading from recycled texture.
                    if (xCOffset + 1 >= inDims[1]) {
                      previous.zw = vec2(0.0);
                    }

                    xC${y} = vec4(previous.zw, xTexelC${y}.xy);
                  } else {
                    xC${y} = vec4(0.0, 0.0, xTexelC${y}.xy);
                  }
                  `):d+=`
                if (xC >= 0 && xC < inDims[1] && xTexelC${y}Ready == 0) {
                  xTexelC${y} = getX(batch, xR, xC, d1);
                  if (xC + 1 >= inDims[1]) {
                    xTexelC${y}.zw = vec2(0.0);
                  }
                  xTexelC${y}Ready = 1;
                }

                xC${y} = xTexelC${y};
                `,y+1<p)){let x=i%2===0?v.nearestLargerEven(l):l;l%2===0&&i%2===1||l%2!==0&&i%2!==1?(d+=`
                  xCOffset = xC + imod(pads[1], 2) + ${x};

                  if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${y+1}Ready == 0) {
                    xTexelC${y+1} = getX(batch, xR, xCOffset, d1);

                    // Need to manually clear unused channels in case
                    // we're reading from recycled texture.
                    if (xCOffset + 1 >= inDims[1]) {
                      xTexelC${y+1}.zw = vec2(0.0);
                    }
                    xTexelC${y+1}Ready = 1;
                  }
                  `,l>1?d+=`
                    xCOffset -= 2;
                    if (xCOffset >= 0 && xCOffset < inDims[1]) {
                     previous = getX(batch, xR, xCOffset, d1);
                     xC${y+1} = vec4(previous.zw, xTexelC${y+1}.xy);
                    } else {
                     xC${y+1} = vec4(0.0, 0.0, xTexelC${y+1}.xy);
                    }
                    `:d+=`
                    xC${y+1} = vec4(xTexelC${y}.zw, xTexelC${y+1}.xy);
                    `):x===1?d+=`
                    xC${y+1} = xTexelC${y};
                    `:d+=`
                    xCOffset = xC + ${x};

                    if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${y+1}Ready == 0) {
                      xTexelC${y+1} = getX(batch, xR, xCOffset, d1);
                      if (xCOffset + 1 >= inDims[1]) {
                        xTexelC${y+1}.zw = vec2(0.0);
                      }
                      xTexelC${y+1}Ready = 1;
                    }

                    xC${y+1} = xTexelC${y+1};
                    `}}else y<p&&(i%2===1?(d+=`
                xCOffset = xC + 1 - strides[1];
                if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${y}Ready == 0) {
                  xTexelC${y} = getX(batch, xR, xCOffset, d1);
                  // Need to manually clear unused channels in case
                  // we're reading from recycled texture.
                  if (xCOffset + 1 >= inDims[1]) {
                    xTexelC${y}.zw = vec2(0.0);
                  }
                  xTexelC${y}Ready = 1;
                }

                if(xC + 1 >= 0 && xC + 1 < inDims[1] && xTexelC${y+1}Ready == 0) {
                  xTexelC${y+1} = getX(batch, xR, xC + 1, d1);
                  // Need to manually clear unused channels in case
                  // we're reading from recycled texture.
                  if (xC + 2 >= inDims[1]) {
                    xTexelC${y+1}.zw = vec2(0.0);
                  }
                  xTexelC${y+1}Ready = 1;
                }

                xC${y} = vec4(xTexelC${y}.zw, xTexelC${y+1}.zw);
              `,y+1<p&&(d+=`
                  final = vec4(0.0);
                  xCOffset = xC + 1 + strides[1];
                  if(xCOffset >= 0 && xCOffset < inDims[1]) {
                    final = getX(batch, xR, xCOffset, d1);
                  }
                  xC${y+1} = vec4(xTexelC${y+1}.xy, final.xy);
                `)):(d+=`
                if(xC >= 0 && xC < inDims[1] && xTexelC${y}Ready == 0) {
                  xTexelC${y} = getX(batch, xR, xC, d1);
                  if (xC + 1 >= inDims[1]) {
                    xTexelC${y}.zw = vec2(0.0);
                  }
                  xTexelC${y}Ready = 1;
                }

                xCOffset = xC + strides[1];
                if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${y+1}Ready == 0) {
                  xTexelC${y+1} = getX(batch, xR, xCOffset, d1);
                  if (xCOffset + 1 >= inDims[1]) {
                    xTexelC${y+1}.zw = vec2(0.);
                  }
                  xTexelC${y+1}Ready = 1;
                }

                xC${y} = vec4(
                  xTexelC${y}.xy, xTexelC${y+1}.xy);
              `,y+1<p&&(d+=`
                  xC${y+1} = vec4(xTexelC${y}.zw, xTexelC${y+1}.zw);
                `)));y<p&&(d+=`
            wTexel = getW(r, ${y}, d1, q);
            dotProd += xC${y} * vec4(wTexel.xz, wTexel.xz);
          `,y+1<p&&(d+=`
              wTexel = getW(r, ${y+1}, d1, q);
              dotProd += xC${y+1} * vec4(wTexel.xz, wTexel.xz);
            `))}d+=`
    }
  `,d+=`
      }
    `;let h="",m="";a&&(n?h=`vec4 activation(vec4 a) {
          vec4 b = getPreluActivationWeightsAtOutCoords();
          ${a}
        }`:r?h=`vec4 activation(vec4 a) {
          vec4 b = getLeakyreluAlphaAtOutCoords();
          ${a}
        }`:h=`vec4 activation(vec4 x) {
          ${a}
        }`,m="result = activation(result);");let f=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),r&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
      ${h}

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords.x;
        ivec2 xRCCorner = coords.yz * strides - pads;
        int d2 = coords.w;
        int d1 = d2 / ${s};
        int q = d2 - d1 * ${s};
        int xRCorner = xRCCorner.x;
        int xCCorner = xRCCorner.y;

        //intialize dotProd with a small epsilon seems to reduce GPU accuracy loss.
        vec4 dotProd = vec4(0.000000000000001);

        ${d}

        vec4 result = dotProd - vec4(0.000000000000001);
        ${f}
        ${m}
        setOutput(result);
      }
    `}};function OK(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l,dimRoundingMode:u}=n,p=l;p==null&&(p=[1,1]),v.assert(C.eitherStridesOrDilationsAreOne(i,p),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${p}'`);let c=C.computeConv2DInfo(r.shape,s.shape,i,p,o,u,!0),d;B().getBool("WEBGL_PACK_DEPTHWISECONV")&&c.strideWidth<=2&&c.outChannels/c.inChannels===1?d=new D8(c):d=new F8(c);let h=[[c.padInfo.top,c.padInfo.left],[c.strideHeight,c.strideWidth],[c.dilationHeight,c.dilationWidth],[c.inHeight,c.inWidth]];return a.runWebGLProgram(d,[r,s],"float32",h)}var zK={kernelName:$i,backendName:"webgl",kernelFunc:OK},LK=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,a=e.strideWidth,n=e.padInfo.top,r=e.padInfo.left,s=e.outChannels/e.inChannels;this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int wR = coords.x;
        int wC = coords.y;
        int d1 = coords.z;
        int dm = coords.w;
        int d2 = d1 * ${s} + dm;

        float dotProd = 0.0;

        // TO DO: Vec4 over the batch size
        for (int b = 0; b < ${e.batchSize}; b++) {
          for (int yR = 0; yR < ${e.outHeight}; yR++) {
            int xR = wR + yR * ${t} - ${n};

            if (xR < 0 || xR >= ${e.inHeight}) {
              continue;
            }

            for (int yC = 0; yC < ${e.outWidth}; yC++) {
              int xC = wC + yC * ${a} - ${r};

              if (xC < 0 || xC >= ${e.inWidth}) {
                continue;
              }

              float dyValue = getDy(b, yR, yC, d2);
              float xValue = getX(b, xR, xC, d1);
              dotProd += (xValue * dyValue);
            }
          }
        }
        setOutput(dotProd);
      }
    `}},WK=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,a=e.filterWidth,n=e.strideHeight,r=e.strideWidth,s=t-1-e.padInfo.top,i=a-1-e.padInfo.left,o=e.outChannels/e.inChannels;this.userCode=`
      const ivec2 pads = ivec2(${s}, ${i});

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords[0];
        int d1 = coords[3];
        ivec2 dyCorner = coords.yz - pads;
        int dyRCorner = dyCorner.x;
        int dyCCorner = dyCorner.y;

        float dotProd = 0.0;

        for (int wR = 0; wR < ${t}; wR++) {
          float dyR = float(dyRCorner + wR) / ${n}.0;

          if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
            continue;
          }
          int idyR = int(dyR);

          int wRPerm = ${t} - 1 - wR;

          for (int wC = 0; wC < ${a}; wC++) {
            float dyC = float(dyCCorner + wC) / ${r}.0;

            if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
                fract(dyC) > 0.0) {
              continue;
            }
            int idyC = int(dyC);

            int wCPerm = ${a} - 1 - wC;

            // TO DO: Vec4 over the channelMul
            for (int dm = 0; dm < ${o}; dm++) {
              int d2 = d1 * ${o} + dm;
              float xValue = getDy(batch, idyR, idyC, d2);
              float wValue = getW(wRPerm, wCPerm, d1, dm);
              dotProd += xValue * wValue;
            }
          }
        }
        setOutput(dotProd);
      }
    `}};function BK(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,filterShape:p}=n,c=C.computeConv2DInfo(r.shape,p,i,o,l,u,!0),d=new LK(c);return a.runWebGLProgram(d,[r,s],"float32")}var VK={kernelName:fp,backendName:"webgl",kernelFunc:BK};function UK(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,inputShape:p}=n,c=C.computeConv2DInfo(p,s.shape,i,o,l,u,!0),d=new WK(c);return a.runWebGLProgram(d,[r,s],"float32")}var GK={kernelName:gp,backendName:"webgl",kernelFunc:UK},HK=class{constructor(e){this.variableNames=["X"],this.outputShape=[e,e],this.userCode=`
      void main() {
          ivec2 coords = getOutputCoords();
          float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;
          setOutput(val);
      }
    `}};function jK(e){let{inputs:t,backend:a}=e,{x:n}=t,r=[...n.shape,...n.shape],s=v.sizeFromShape(n.shape),i=pe({inputs:{x:n},backend:a,attrs:{shape:[s]}}),o=new HK(s),l=a.runWebGLProgram(o,[i],i.dtype),u=pe({inputs:{x:l},backend:a,attrs:{shape:r}});return a.disposeIntermediateTensorInfo(i),a.disposeIntermediateTensorInfo(l),u}var qK={kernelName:yu,backendName:"webgl",kernelFunc:jK},XK=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:a,padInfo:n,strideHeight:r,strideWidth:s,filterHeight:i,filterWidth:o,dilationHeight:l,dilationWidth:u}=e,{top:p,left:c}=n;this.userCode=`
      const ivec2 strides = ivec2(${r}, ${s});
      const ivec2 pads = ivec2(${p}, ${c});
      const float neg_infinity = -3.4e38;

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords.x;
        int d1 = coords.w;
        ivec2 outTopLeftCorner =
            coords.yz * strides - pads;
        int hBeg = outTopLeftCorner.x;
        int wBeg = outTopLeftCorner.y;

        float curVal = neg_infinity;
        for (int h = 0; h < ${i}; h++) {
          int hIn = hBeg + h * ${l};

          if (hIn >= 0 && hIn < ${t}) {
            for (int w = 0; w < ${o}; w++) {
              int wIn = wBeg + w * ${u};

              if (wIn >= 0 && wIn < ${a}) {
                float xVal = getX(batch, hIn, wIn, d1);
                float wVal = getW(h, w, d1);

                float val = xVal + wVal;
                if (val > curVal) {
                  curVal = val;
                }
              }
            }
          }
        }

        float result = curVal;
        setOutput(result);
      }
    `}};function KK(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=n,u=C.computeDilation2DInfo(r.shape,s.shape,i,o,"NHWC",l),p,c=new XK(u);p=a.runWebGLProgram(c,[r,s],"float32");let d=pe({inputs:{x:p},backend:a,attrs:{shape:u.outShape}});return a.disposeIntermediateTensorInfo(p),d}var YK={kernelName:Pi,backendName:"webgl",kernelFunc:KK};function ZK(e){let{inputs:t,backend:a,attrs:n}=e,{equation:r}=n,s=t,{allDims:i,summedDims:o,idDims:l}=C.decodeEinsumEquation(r,s.length);C.checkEinsumDimSizes(i.length,l,s);let{path:u,steps:p}=C.getEinsumComputePath(o,l),c=p.length,d=null,h=i.length,m=[];for(let f=0;f<c;++f){for(let g of p[f]){let{permutationIndices:y,expandDims:x}=C.getEinsumPermutation(h,l[g]),A;C.isIdentityPermutation(y)?A=s[g]:(A=Ca({inputs:{x:s[g]},backend:a,attrs:{perm:y}}),m.push(A));let b=A.shape.slice();for(let w=0;w<x.length;++w)b.splice(x[w],0,1);v.arraysEqual(A.shape,b)||(A=pe({inputs:{x:A},backend:a,attrs:{shape:b}}),m.push(A)),d===null?d=A:(d=L3({inputs:{a:A,b:d},backend:a}),m.push(d))}f<c-1&&(u[f]>=0&&(d=i0({inputs:{x:d},backend:a,attrs:{axis:u[f]-(i.length-h),keepDims:!1}}),m.push(d)),h--)}for(let f of m)f!==d&&a.disposeIntermediateTensorInfo(f);return d}var JK={kernelName:xp,backendName:"webgl",kernelFunc:ZK},QK="return (x >= 0.0) ? x : (exp(x) - 1.0);",eY=`
  vec4 result;

  result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);
  result.g = (x.g >= 0.0) ? x.g : (exp(x.g) - 1.0);
  result.b = (x.b >= 0.0) ? x.b : (exp(x.b) - 1.0);
  result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);

  return result;
`,tY=tt({opSnippet:QK,packedOpSnippet:eY}),aY={kernelName:Fi,backendName:"webgl",kernelFunc:tY},nY="return (b >= 0.0) ? a : a * (b + 1.0);",rY=`
  vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
  return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
`,sY=e=>{let{inputs:t,backend:a}=e,{dy:n,y:r}=t,s=B().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Ju(rY,n.shape,r.shape):new ri(nY,n.shape,r.shape);return a.runWebGLProgram(s,[n,r],n.dtype)},iY={kernelName:xu,backendName:"webgl",kernelFunc:sY},oY=`
  return vec4(equal(a, b));
`,lY="return float(a == b);",uY=ma({opSnippet:lY,packedOpSnippet:oY,dtype:"bool",cpuKernelImpl:LH}),dY={kernelName:Oi,backendName:"webgl",kernelFunc:uY},pY=`
  // Error function is calculated approximately with elementary function.
  // See "Handbook of Mathematical Functions with Formulas,
  // Graphs, and Mathematical Tables", Abramowitz and Stegun.
  float p = ${C.ERF_P};
  float a1 = ${C.ERF_A1};
  float a2 = ${C.ERF_A2};
  float a3 = ${C.ERF_A3};
  float a4 = ${C.ERF_A4};
  float a5 = ${C.ERF_A5};

  float sign = sign(x);
  x = abs(x);
  float t = 1.0 / (1.0 + p * x);
  return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));
`,cY=tt({opSnippet:pY}),hY={kernelName:Di,backendName:"webgl",kernelFunc:cY},mY=Qu+`
  return exp(x);
`,fY=`
  vec4 result = exp(x);
  bvec4 isNaN = isnan(x);
  result.r = isNaN.r ? x.r : result.r;
  result.g = isNaN.g ? x.g : result.g;
  result.b = isNaN.b ? x.b : result.b;
  result.a = isNaN.a ? x.a : result.a;

  return result;
`,O8=tt({opSnippet:mY,packedOpSnippet:fY,cpuKernelImpl:WH,dtype:"float32"}),gY={kernelName:zi,backendName:"webgl",kernelFunc:O8};function B1(e){let{inputs:t,attrs:a,backend:n}=e,{dim:r}=a,{input:s}=t,i=s.shape.length,o=s.shape.slice(),l=r;return r<0&&(v.assert(-(i+1)<=r,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+r+1),o.splice(l,0,1),pe({inputs:{x:s},backend:n,attrs:{shape:o}})}var yY={kernelName:Au,backendName:"webgl",kernelFunc:B1},V5="return exp(x) - 1.0;",xY=tt({opSnippet:V5,packedOpSnippet:V5,cpuKernelImpl:BH}),AY={kernelName:Li,backendName:"webgl",kernelFunc:xY},U5=class{constructor(e,t,a){this.variableNames=["real","imag"];let n=t[1];this.outputShape=t;let r=a?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,s=a?`${n}.0`:"1.0",i;if(e==="real")i="return real * expR - imag * expI;";else if(e==="imag")i="return real * expI + imag * expR;";else throw new Error(`FFT component must be either "real" or "imag", got ${e}.`);this.userCode=`
      const float exponentMultiplier = ${r};

      float unaryOpComplex(float real, float expR, float imag, float expI) {
        ${i}
      }

      float mulMatDFT(int batch, int index) {
        float indexRatio = float(index) / float(${n});
        float exponentMultiplierTimesIndexRatio =
            exponentMultiplier * indexRatio;

        float result = 0.0;

        for (int i = 0; i < ${n}; i++) {
          // x = (-2|2 * PI / N) * index * i;
          float x = exponentMultiplierTimesIndexRatio * float(i);
          float expR = cos(x);
          float expI = sin(x);
          float real = getReal(batch, i);
          float imag = getImag(batch, i);

          result +=
              unaryOpComplex(real, expR, imag, expI) / ${s};
        }

        return result;
      }

      void main() {
        ivec2 coords = getOutputCoords();
        setOutput(mulMatDFT(coords[0], coords[1]));
      }
    `}};function z8(e,t,a){let n=a.texData.get(e.dataId),r=v.sizeFromShape(e.shape),s=e.shape[e.shape.length-1],i=r/s,o=pe({inputs:{x:e},backend:a,attrs:{shape:[i,s]}}),l=o.shape,u=new U5("real",l,t),p=new U5("imag",l,t),c=[{dataId:n.complexTensorInfos.real.dataId,dtype:n.complexTensorInfos.real.dtype,shape:l},{dataId:n.complexTensorInfos.imag.dataId,dtype:n.complexTensorInfos.imag.dtype,shape:l}],d=a.runWebGLProgram(u,c,"float32"),h=a.runWebGLProgram(p,c,"float32"),m=fs({inputs:{real:d,imag:h},backend:a});a.disposeIntermediateTensorInfo(d),a.disposeIntermediateTensorInfo(h);let f=pe({inputs:{x:m},backend:a,attrs:{shape:e.shape}});return a.disposeIntermediateTensorInfo(o),a.disposeIntermediateTensorInfo(m),f}function bY(e){let{inputs:t,backend:a}=e,{input:n}=t;return z8(n,!1,a)}var vY={kernelName:Ap,backendName:"webgl",kernelFunc:bY},wY=class{constructor(e,t){this.outputShape=[],this.customUniforms=[{name:"value",type:"float"}],this.variableNames=["x"],this.outputShape=e,this.userCode=`
      void main() {
        // Input can be obtained from uniform value.
        setOutput(value);
      }
    `}};function ec(e){let{backend:t,attrs:a}=e,{shape:n,value:r}=a,{dtype:s}=a;if(s=s||v.inferDtype(r),s==="string"){let i=v.getArrayFromDType(s,v.sizeFromShape(n));return i.fill(r),t.makeTensorInfo(n,s,i)}else{let i=new wY(n,r),o=[[r]];return t.runWebGLProgram(i,[],s,o)}}var kY={kernelName:bu,backendName:"webgl",kernelFunc:ec},IY=class{constructor(e){this.variableNames=["Image"],this.outputShape=[];let t=e[2];this.outputShape=e,this.userCode=`
        void main() {
          ivec4 coords = getOutputCoords();
          int x = coords[2];

          int coordX = ${t} - x - 1;
          float outputValue;
          if(coordX >= 0 && coordX < ${t}) {
            outputValue = getImage(coords[0], coords[1], coordX, coords[3]);
          } else {
            outputValue = getImage(coords[0], coords[1], coords[2], coords[3]);
          }
          setOutput(outputValue);
        }
    `}},SY={kernelName:Wi,backendName:"webgl",kernelFunc:({inputs:e,backend:t})=>{let{image:a}=e,n=t,r=new IY(a.shape);return n.runWebGLProgram(r,[a],a.dtype)}},G5="return floor(x);",CY=tt({opSnippet:G5,packedOpSnippet:G5,cpuKernelImpl:VH}),TY={kernelName:Bi,backendName:"webgl",kernelFunc:CY},NY=`
  float s = sign(a) * sign(b);
  int ia = round(a);
  int ib = round(b);
  if (ib != 0) {
    // Windows (D3D) wants guaranteed non-zero int division at compile-time.
    return float(idiv(ia, ib, s));
  } else {
    return NAN;
  }
`,RY=`
  ivec4 ia = round(a);
  ivec4 ib = round(b);
  bvec4 cond = notEqual(ib, ivec4(0));
  ivec4 result = ivec4(0);
  vec4 s = sign(a) * sign(b);

  // Windows (D3D) wants guaranteed non-zero int division at compile-time.
  if (cond[0]) {
    result[0] = idiv(ia[0], ib[0], s[0]);
  }
  if (cond[1]) {
    result[1] = idiv(ia[1], ib[1], s[1]);
  }
  if (cond[2]) {
    result[2] = idiv(ia[2], ib[2], s[2]);
  }
  if (cond[3]) {
    result[3] = idiv(ia[3], ib[3], s[3]);
  }
  return vec4(result);
`,EY=ma({opSnippet:NY,packedOpSnippet:RY,dtype:"int32"}),MY={kernelName:Vi,backendName:"webgl",kernelFunc:EY},$Y=class{constructor(e){this.variableNames=["A"];let t=Ra(),[a,n]=e;this.outputShape=e,this.userCode=`
      void main() {
        ivec3 coords = getOutputCoords();
        int texR = coords[0];
        int texC = coords[1];
        int depth = coords[2];
        vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${n}.0, ${a}.0);

        vec4 values = ${t.texture2D}(A, uv);
        float value;
        if (depth == 0) {
          value = values.r;
        } else if (depth == 1) {
          value = values.g;
        } else if (depth == 2) {
          value = values.b;
        } else if (depth == 3) {
          value = values.a;
        }

        setOutput(floor(value * 255.0 + 0.5));
      }
    `}},PY=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let t=Ra(),[a,n]=e;this.outputShape=e,this.userCode=`
      void main() {
        ivec3 coords = getOutputCoords();
        int texR = coords[0];
        int texC = coords[1];
        int depth = coords[2];

        vec4 result = vec4(0.);

        for(int row=0; row<=1; row++) {
          for(int col=0; col<=1; col++) {
            texC = coords[1] + row;
            depth = coords[2] + col;

            vec2 uv = (vec2(texC, texR) + halfCR) /
                       vec2(${n}.0, ${a}.0);
            vec4 values = ${t.texture2D}(A, uv);
            float value;
            if (depth == 0) {
              value = values.r;
            } else if (depth == 1) {
              value = values.g;
            } else if (depth == 2) {
              value = values.b;
            } else if (depth == 3) {
              value = values.a;
            }

            result[row * 2 + col] = floor(value * 255.0 + 0.5);
          }
        }

        ${t.output} = result;
      }
    `}},_Y={kernelName:Wd,backendName:"webgl",kernelFunc:FY},Fl,Q2=B().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");function FY(e){let{inputs:t,backend:a,attrs:n}=e,{pixels:r}=t,{numChannels:s}=n,i=typeof HTMLVideoElement!="undefined"&&r instanceof HTMLVideoElement,o=typeof HTMLImageElement!="undefined"&&r instanceof HTMLImageElement,[l,u]=i?[r.videoWidth,r.videoHeight]:[r.width,r.height],p=[u,l],c=[u,l,s];if(o||i){let f=B().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");(Fl==null||f!==Q2)&&(Q2=f,Fl=document.createElement("canvas").getContext("2d",{willReadFrequently:Q2})),Fl.canvas.width=l,Fl.canvas.height=u,Fl.drawImage(r,0,0,l,u),r=Fl.canvas}let d=a.makeTensorInfo(p,"int32");a.texData.get(d.dataId).usage=mn.PIXELS,a.gpgpu.uploadPixelDataToTexture(a.getTexture(d.dataId),r);let h=B().getBool("WEBGL_PACK")?new PY(c):new $Y(c),m=a.runWebGLProgram(h,[d],"int32");return a.disposeData(d.dataId),m}function DY(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dataFormat:p,dilations:c,dimRoundingMode:d,activation:h,leakyreluAlpha:m}=n,f=C.convertConv2DDataFormat(p),g=C.computeConv2DInfo(r.shape,s.shape,l,c,u,d,!1,f),y,x=[],A=i!=null,b=o!=null,w=h==="leakyrelu",I=()=>{let N=[r,s],M=($,E)=>{if(E==="NCHW"&&$.shape.length===1&&$.shape[0]!==1){let S=pe({inputs:{x:$},backend:a,attrs:{shape:[$.shape[0],1,1]}});return x.push(S),S}return $};if(A&&N.push(M(i,p)),b&&N.push(M(o,p)),w){let $=a.makeTensorInfo([],"float32",v.createScalarValue(m,"float32"));N.push($),x.push($)}return N};if(g.filterHeight===1&&g.filterWidth===1&&g.dilationHeight===1&&g.dilationWidth===1&&g.strideHeight===1&&g.strideWidth===1&&(g.padInfo.type==="SAME"||g.padInfo.type==="VALID"))y=$8({x:r,filter:s,convInfo:g,backend:a,bias:i,activation:h,preluActivationWeights:o,leakyreluAlpha:m});else if(g.strideWidth<=2&&f==="channelsLast"&&B().getBool("WEBGL_EXP_CONV")){let N=h?tp(h,!0):null,M=new M8(g,A,N,b,w),$=[[g.padInfo.top,g.padInfo.left],[g.strideHeight,g.strideWidth],[g.dilationHeight,g.dilationWidth],[g.inHeight,g.inWidth]],E=I();y=a.runWebGLProgram(M,E,"float32",$)}else if(B().getBool("WEBGL_CONV_IM2COL"))y=P8({x:r,filter:s,convInfo:g,backend:a,bias:i,activation:h,preluActivationWeights:o,leakyreluAlpha:m});else{let N=h?tp(h,!1):null,M=new E8(g,A,N,b,w),$=I();y=a.runWebGLProgram(M,$,"float32")}let T=pe({inputs:{x:y},backend:a,attrs:{shape:g.outShape}});return x.push(y),x.forEach(N=>a.disposeIntermediateTensorInfo(N)),T}var OY={kernelName:Jr,backendName:"webgl",kernelFunc:DY};function zY(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:p,dimRoundingMode:c,activation:d,leakyreluAlpha:h}=n,m=[],f=p;f==null&&(f=[1,1]),v.assert(C.eitherStridesOrDilationsAreOne(l,f),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${f}'`);let g=C.computeConv2DInfo(r.shape,s.shape,l,f,u,c,!0),y=B().getBool("WEBGL_PACK_DEPTHWISECONV")&&g.strideWidth<=2&&g.outChannels/g.inChannels===1,x=d?tp(d,y):null,A=[r,s],b=i!=null,w=o!=null,I=d==="leakyrelu";if(b&&A.push(i),w&&A.push(o),I){let $=a.makeTensorInfo([],"float32",v.createScalarValue(h,"float32"));A.push($),m.push($)}let T;y?T=new D8(g,b,x,w,I):T=new F8(g,b,x,w,I);let N=[[g.padInfo.top,g.padInfo.left],[g.strideHeight,g.strideWidth],[g.dilationHeight,g.dilationWidth],[g.inHeight,g.inWidth]],M=a.runWebGLProgram(T,A,"float32",N);return m.forEach($=>a.disposeIntermediateTensorInfo($)),M}var LY={kernelName:Qr,backendName:"webgl",kernelFunc:zY},WY=class{constructor(e,t,a,n){this.sliceDim=e,this.strides=t,this.paramsShape=n,this.variableNames=["x","indices"],this.outputShape=a;let r=ft(a.length),s=`
    int index;`;for(let i=0;i<this.sliceDim;i++)s+=`
          index = round(getIndices(coords[0], ${i}));
          out_of_bounds = out_of_bounds || index < 0;
          out_of_bounds = out_of_bounds || index >= ${this.paramsShape[i]};
          flattenIndex += index * ${this.strides[i]};`;this.userCode=`
         void main() {
          ${r} coords = getOutputCoords();
          int flattenIndex = 0;
          bool out_of_bounds = false;

          ${s}

          setOutput(out_of_bounds ? 0.0 : getX(flattenIndex, coords[1]));
        }
      `}};function BY(e){let{inputs:t,backend:a}=e,{params:n,indices:r}=t,s=r.shape,i=s[s.length-1],o=v.sizeFromShape(n.shape),[l,u,p,c]=C.prepareAndValidate(n,r),d=pe({inputs:{x:r},backend:a,attrs:{shape:[u,i]}}),h=pe({inputs:{x:n},backend:a,attrs:{shape:[v.sizeFromShape(n.shape)/p,p]}});if(a.shouldExecuteOnCPU([n,r])||n.dtype==="string"){let y=a.readSync(r.dataId),x=a.bufferSync(n),A=UH(y,x,n.dtype,u,i,p,c,n.shape,o);return a.makeTensorInfo(l,n.dtype,A.values)}let m=new WY(i,c,[u,p],n.shape),f=a.runWebGLProgram(m,[h,d],h.dtype),g=pe({inputs:{x:f},backend:a,attrs:{shape:l}});return a.disposeIntermediateTensorInfo(d),a.disposeIntermediateTensorInfo(h),a.disposeIntermediateTensorInfo(f),g}var VY={kernelName:Gi,backendName:"webgl",kernelFunc:BY},UY=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let a=ft(this.rank),n=GY(e,2);this.userCode=`
      void main() {
        ${a} resRC = getOutputCoords();
        int index = int(getIndices(resRC.x, resRC.z));
        float inBounds = (index >= 0) && (index < ${e[2]}) ? 1.0 : 0.0;
        setOutput(inBounds * getA(${n}));
      }
    `}};function GY(e,t){let a=["resRC.x","resRC.y","resRC.z","resRC.w"],n=[];for(let r=0;r<e.length;r++)r===2?n.push("index"):n.push(`${a[r]}`);return n.join()}function L8(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,indices:s}=t,{axis:i,batchDims:o}=n,l=v.parseAxisParam(i,r.shape)[0];if(B().get("DEBUG")){let x=a.readSync(s.dataId),A=r.shape[l];for(let b=0;b<x.length;++b){let w=x[b];v.assert(w<=A-1&&w>=0,()=>`GatherV2: the index value ${w} is not in [0, ${A-1}]`)}}let u=C.segment_util.collectGatherOpShapeInfo(r,s,l,o),p=v.sizeFromShape(s.shape),c=[],d=pe({inputs:{x:r},backend:a,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),h=pe({inputs:{x:s},backend:a,attrs:{shape:[u.batchSize,p/u.batchSize]}});c.push(d),c.push(h);let m=[u.batchSize,u.outerSize,p/u.batchSize,u.sliceSize];if(a.shouldExecuteOnCPU([r,s])||r.dtype==="string"){let x=a.bufferSync(h),A=a.bufferSync(d),b=GH(A,x,m);return c.forEach(w=>a.disposeIntermediateTensorInfo(w)),a.makeTensorInfo(u.outputShape,b.dtype,b.values)}let f=new UY(d.shape,m),g=a.runWebGLProgram(f,[d,h],d.dtype);c.push(g);let y=pe({inputs:{x:g},backend:a,attrs:{shape:u.outputShape}});return c.forEach(x=>a.disposeIntermediateTensorInfo(x)),y}var HY={kernelName:vu,backendName:"webgl",kernelFunc:L8},jY="return float(a > b);",qY=`
  return vec4(greaterThan(a, b));
`,XY=ma({opSnippet:jY,packedOpSnippet:qY,cpuKernelImpl:HH,dtype:"bool"}),KY={kernelName:Hi,backendName:"webgl",kernelFunc:XY},YY="return float(a >= b);",ZY=`
  return vec4(greaterThanEqual(a, b));
`,JY=ma({opSnippet:YY,packedOpSnippet:ZY,dtype:"bool",cpuKernelImpl:jH}),QY={kernelName:ji,backendName:"webgl",kernelFunc:JY};function eZ(e){let{inputs:t,backend:a}=e,{input:n}=t;return z8(n,!0,a)}var tZ={kernelName:bp,backendName:"webgl",kernelFunc:eZ},aZ="return float(!isnan(x) && !isinf(x));",nZ=tt({opSnippet:aZ,dtype:"bool"}),rZ={kernelName:Xi,backendName:"webgl",kernelFunc:nZ},sZ="return float(isinf(x));",iZ=tt({opSnippet:sZ,dtype:"bool"}),oZ={kernelName:Ki,backendName:"webgl",kernelFunc:iZ},lZ="return float(isnan(x));",uZ=tt({opSnippet:lZ,dtype:"bool"}),dZ={kernelName:Yi,backendName:"webgl",kernelFunc:uZ},pZ="return float(a < b);",cZ=`
  return vec4(lessThan(a, b));
`,hZ=ma({opSnippet:pZ,packedOpSnippet:cZ,cpuKernelImpl:qH,dtype:"bool"}),mZ={kernelName:Ji,backendName:"webgl",kernelFunc:hZ},fZ="return float(a <= b);",gZ=`
  return vec4(lessThanEqual(a, b));
`,yZ=ma({opSnippet:fZ,packedOpSnippet:gZ,cpuKernelImpl:XH,dtype:"bool"}),xZ={kernelName:Qi,backendName:"webgl",kernelFunc:yZ};function AZ(e){let{backend:t,attrs:a}=e,{start:n,stop:r,num:s}=a,i=KH(n,r,s);return t.makeTensorInfo([i.length],"float32",i)}var bZ={kernelName:eo,backendName:"webgl",kernelFunc:AZ},vZ=Qu+`
  return x < 0.0 ? 0./0. : log(x);
`,wZ=`
  vec4 result = log(x);
  bvec4 isNaN = isnan(x);
  result.r = isNaN.r ? x.r : (x.r < 0.0 ? 0./0. : result.r);
  result.g = isNaN.g ? x.g : (x.g < 0.0 ? 0./0. : result.g);
  result.b = isNaN.b ? x.b : (x.b < 0.0 ? 0./0. : result.b);
  result.a = isNaN.a ? x.a : (x.a < 0.0 ? 0./0. : result.a);
  return result;
`,kZ=tt({opSnippet:vZ,packedOpSnippet:wZ,cpuKernelImpl:YH}),IZ={kernelName:to,backendName:"webgl",kernelFunc:kZ},SZ=Qu+`
  return log(1.0 + x);
`,CZ=tt({opSnippet:SZ}),TZ={kernelName:ao,backendName:"webgl",kernelFunc:CZ},NZ="return float(a >= 1.0 && b >= 1.0);",RZ=`
  return vec4(
    vec4(greaterThanEqual(a, vec4(1.0))) *
    vec4(greaterThanEqual(b, vec4(1.0))));
`,EZ=ma({opSnippet:NZ,packedOpSnippet:RZ,dtype:"bool"}),MZ={kernelName:no,backendName:"webgl",kernelFunc:EZ},$Z="return float(!(x >= 1.0));",PZ=tt({opSnippet:$Z}),_Z={kernelName:ro,backendName:"webgl",kernelFunc:PZ},FZ="return float(a >= 1.0 || b >= 1.0);",DZ=`
  return min(
    vec4(greaterThanEqual(a, vec4(1.0))) +
    vec4(greaterThanEqual(b, vec4(1.0))),
    vec4(1.0));
`,OZ=ma({opSnippet:FZ,packedOpSnippet:DZ,dtype:"bool"}),zZ={kernelName:so,backendName:"webgl",kernelFunc:OZ},LZ=class{constructor(e,t,a,n,r){this.variableNames=["x"],this.outputShape=[];let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${a}) + float(${n}) * sum`;r===.5?o=`inversesqrt(${l})`:r===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${r}));`,this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int r = coords[1];
        int c = coords[2];
        int d = coords[3];
        float x = getX(b, r, c, d);
        float sum = 0.0;
        for (int j = -${s}; j <= ${s}; j++) {
          int idx = d + j;
          if (idx >= 0 && idx <=  ${i}) {
            float z = getX(b, r, c, idx);
            sum += z * z;
          }
        }
        float val = x * ${o};
        setOutput(val);
      }
    `}},WZ=class{constructor(e,t,a,n,r){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${a}) + float(${n}) * sum`;r===.5?o=`inversesqrt(${l})`:r===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${r}));`,this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords.x;
        int r = coords.y;
        int c = coords.z;
        int d = coords.w;

        bool hasNextCol = d < ${this.outputShape[3]};
        bool hasNextRow = c < ${this.outputShape[2]};

        vec4 sum = vec4(0.);
        vec4 xFragAtOutputCoords = getX(b, r, c, d);

        vec4 xAtOutputCoords = vec4(
          getChannel(xFragAtOutputCoords, vec2(c, d)),
          hasNextCol ?
            getChannel(xFragAtOutputCoords, vec2(c, d + 1)) : 0.0,
          hasNextRow ?
            getChannel(xFragAtOutputCoords , vec2(c + 1, d)) : 0.0,
          (hasNextRow && hasNextCol) ?
            getChannel(xFragAtOutputCoords, vec2(c + 1, d + 1)) : 0.0
        );

        int firstChannel = d - ${s};
        vec2 cache = vec2(0.);
        if(firstChannel >= 0){
          vec4 firstChannelFrag = getX(b, r, c, firstChannel);
          cache.x = getChannel(firstChannelFrag, vec2(c, firstChannel));
            if(hasNextRow){
              cache.y = getChannel(firstChannelFrag, vec2(c + 1, firstChannel));
            }
        }

        ivec2 depth = ivec2(d, d + 1);
        for (int j = - ${s}; j <= ${s}; j++) {
          ivec2 idx = depth + j;
          bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));
          bvec2 belowUpperBound = lessThanEqual(idx, ivec2(${i}));

          bool depthInRange = aboveLowerBound.x && belowUpperBound.x;
          bool depthPlusOneInRange = aboveLowerBound.y && belowUpperBound.y;

          if(depthInRange || depthPlusOneInRange){
            vec4 z = vec4(0.);
            vec4 xFragAtCurrentDepth;
            z.xz = cache.xy;
            if(depthPlusOneInRange && hasNextCol){
              xFragAtCurrentDepth = idx.y != d ?
                getX(b, r, c, idx.y) : xFragAtOutputCoords;
              z.y = getChannel(xFragAtCurrentDepth, vec2(c, idx.y));
              if(hasNextRow){
                z.w = getChannel(xFragAtCurrentDepth, vec2(c + 1, idx.y));
              }
            }
            cache.xy = z.yw;
            sum += z * z;
          }
        }
        vec4 result = xAtOutputCoords * ${o};
        setOutput(result);
      }
    `}},BZ=e=>{let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=n,u=B().getBool("WEBGL_PACK_NORMALIZATION")?new WZ(r.shape,s,i,o,l):new LZ(r.shape,s,i,o,l);return a.runWebGLProgram(u,[r],r.dtype)},VZ={kernelName:io,backendName:"webgl",kernelFunc:BZ},UZ=class{constructor(e,t,a,n,r){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=a,this.alpha=n,this.beta=r,this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int r = coords[1];
        int c = coords[2];

        float result = 0.0;
        for (int d = 0; d < ${this.depth}; ++d) {
          int depthBegin = int(max(0.0, float(d - ${t})));
          int depthEnd = int(min(float(${this.depth}),
              float(d + ${t} + 1)));

          const int MIN_DEPTH_BEGIN = 0;
          const int MAX_DEPTH_END = ${this.depth};

          float norm = 0.0;
          for (int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k) {
            if (k < depthBegin){
              continue;
            }
            else if (k >= depthBegin && k < depthEnd) {
              norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k);
            }
            else {
              break;
            }
          }

          norm = float(${n}) * norm + float(${a});

          for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){
            if (k < depthBegin){
              continue;
            }
            else if (k >= depthBegin && k < depthEnd){
              float dyi = -2.0 * float(${n})
                * float(${r})
                * getInputImage(b, r, c, k) * getOutputImage(b, r, c, d)
                / norm;
              if (k == d) {
                dyi += pow(norm, -1.0 * ${r});
              }
              if (k == coords[3]) {
                dyi *= getDy(b, r, c, d);
                result += dyi;
              }
            }
            else {
              break;
            }
          }
      }
      setOutput(result);
      }
    `}},GZ=e=>{let{inputs:t,backend:a,attrs:n}=e,{x:r,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:u,beta:p}=n,c=new UZ(r.shape,o,l,u,p);return a.runWebGLProgram(c,[r,s,i],r.dtype)},HZ={kernelName:wu,backendName:"webgl",kernelFunc:GZ};function jZ(e,t,a,n){let r=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/r,i=pe({inputs:{x:e},attrs:{shape:[s,r]},backend:n}),o=ol(i,e.dtype,"max",n),l=pe({inputs:{x:o},attrs:{shape:a},backend:n});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}function W8(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{reductionIndices:s,keepDims:i}=n,o=r.shape.length,l=v.parseAxisParam(s,r.shape),u=l,p=C.getAxesPermutation(u,o),c=p!=null,d=a.shouldExecuteOnCPU([r]),h=r;if(c){if(d){let x=a.texData.get(h.dataId).values,A=new Array(o);for(let I=0;I<A.length;I++)A[I]=r.shape[p[I]];let b=O3(x,r.shape,r.dtype,p,A);h=a.makeTensorInfo(A,r.dtype);let w=a.texData.get(h.dataId);w.values=b}else h=s0(r,p,a);u=C.getInnerMostAxes(u.length,o)}C.assertAxesAreInnerMostDims("max",u,o);let[m,f]=C.computeOutAndReduceShapes(h.shape,u),g=m;i&&(g=C.expandShapeToKeepDim(m,l));let y;if(d){let x=a.texData.get(h.dataId).values,A=ZH(x,v.sizeFromShape(f),g,r.dtype);y=a.makeTensorInfo(g,r.dtype);let b=a.texData.get(y.dataId);b.values=A}else y=jZ(h,f,g,a);return c&&a.disposeIntermediateTensorInfo(h),y}var qZ={kernelName:oo,backendName:"webgl",kernelFunc:W8},XZ=z3+`
  return max(a, b);
`,KZ=`
  vec4 result = vec4(max(a, b));
  bvec4 isNaNA = isnan(a);
  bvec4 isNaNB = isnan(b);
  bvec4 isNaN = bvec4(isNaNA.x || isNaNB.x, isNaNA.y || isNaNB.y, isNaNA.z || isNaNB.z, isNaNA.w || isNaNB.w);
  `+il+`
  return result;
`,YZ=ma({opSnippet:XZ,packedOpSnippet:KZ,cpuKernelImpl:JH}),ZZ={kernelName:lo,backendName:"webgl",kernelFunc:YZ};function JZ(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t;qu(r,"maxPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=n,u=1;v.assert(C.eitherStridesOrDilationsAreOne(i,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let p=C.computePool2DInfo(r.shape,s,i,u,o,l);if(p.filterWidth===1&&p.filterHeight===1&&v.arraysEqual(p.inShape,p.outShape))return en({inputs:{x:r},backend:a});let c=new ap(p,"max",!1);return a.runWebGLProgram(c,[r],r.dtype)}var QZ={kernelName:uo,backendName:"webgl",kernelFunc:JZ};function eJ(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dataFormat:l,dimRoundingMode:u}=n,p=[1,1,1],c=C.computePool3DInfo(r.shape,s,i,p,o,u,l),d=new W3(c,"max",!1);return a.runWebGLProgram(d,[r],r.dtype)}var tJ={kernelName:ku,backendName:"webgl",kernelFunc:eJ},aJ=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideHeight,a=e.strideWidth,n=e.dilationHeight,r=e.effectiveFilterHeight,s=e.effectiveFilterWidth,i=r-1-e.padInfo.top,o=s-1-e.padInfo.left,l=r*s-1;this.userCode=`
      const ivec2 pads = ivec2(${i}, ${o});

      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];

        ivec2 dyRCCorner = coords.yz - pads;
        int dyRCorner = dyRCCorner.x;
        int dyCCorner = dyRCCorner.y;

        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;
        for (int wR = 0; wR < ${r};
          wR += ${n}) {
          float dyR = float(dyRCorner + wR) / ${t}.0;

          if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
            continue;
          }
          int idyR = int(dyR);

          for (int wC = 0; wC < ${s}; wC++) {
            float dyC = float(dyCCorner + wC) / ${a}.0;

            if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
                fract(dyC) > 0.0) {
              continue;
            }
            int idyC = int(dyC);

            float dyValue = getDy(b, idyR, idyC, d);
            int maxPosValue = ${l} - int(getMaxPos(b, idyR, idyC, d));

            // Get the current value, check it against the value from the
            // position matrix.
            int curPosValue = wR * ${s} + wC;
            float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);

            dotProd += dyValue * mask;
          }
        }
        setOutput(dotProd);
      }
    `}},nJ=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,a=e.strideHeight,n=e.strideWidth,r=e.dilationDepth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterDepth,l=e.effectiveFilterHeight,u=e.effectiveFilterWidth,p=o-1-e.padInfo.front,c=l-1-e.padInfo.top,d=u-1-e.padInfo.left,h=o*l*u-1;this.userCode=`
      const ivec3 pads = ivec3(${p}, ${c}, ${d});

      void main() {
        ivec5 coords = getOutputCoords();
        int batch = coords.x;
        int ch = coords.u;

        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
        int dyDCorner = dyCorner.x;
        int dyRCorner = dyCorner.y;
        int dyCCorner = dyCorner.z;

        // Convolve dy(?, ?, ?, ch) with pos mask(:, :, :, d) to get
        // dx(xD, xR, xC, ch).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;

        for (int wD = 0; wD < ${o};
           wD += ${r}) {
          float dyD = float(dyDCorner + wD) / ${t}.0;

          if (dyD < 0.0 || dyD >= ${e.outDepth}.0 || fract(dyD) > 0.0) {
            continue;
          }
          int idyD = int(dyD);

          for (int wR = 0; wR < ${l};
              wR += ${s}) {
            float dyR = float(dyRCorner + wR) / ${a}.0;

            if (dyR < 0.0 || dyR >= ${e.outHeight}.0 ||
                fract(dyR) > 0.0) {
              continue;
            }
            int idyR = int(dyR);

            for (int wC = 0; wC < ${u};
                wC += ${i}) {
              float dyC = float(dyCCorner + wC) / ${n}.0;

              if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
                  fract(dyC) > 0.0) {
                continue;
              }
              int idyC = int(dyC);

              float dyValue = getDy(batch, idyD, idyR, idyC, ch);
              int maxPosValue = ${h} -
                  int(getMaxPos(batch, idyD, idyR, idyC, ch));

              // Get the current value, check it against the value from the
              // position matrix.
              int curPosValue =
                  wD * ${l} * ${u} +
                  wR * ${u} + wC;
              float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);

              dotProd += dyValue * mask;
            }
          }
        }
        setOutput(dotProd);
      }
    `}};function rJ(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,i=s,{filterSize:o,strides:l,pad:u,dimRoundingMode:p}=n,c=[1,1,1],d=C.computePool3DInfo(i.shape,o,l,c,u,p),h=new W3(d,"max",!0),m=a.runWebGLProgram(h,[i],i.dtype),f=new nJ(d),g=a.runWebGLProgram(f,[r,m],i.dtype);return a.disposeIntermediateTensorInfo(m),g}var sJ={kernelName:kp,backendName:"webgl",kernelFunc:rJ};function iJ(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s,output:i}=t,o=s;qu([s,i],"maxPoolGrad");let{filterSize:l,strides:u,pad:p,dimRoundingMode:c}=n,d=C.computePool2DInfo(o.shape,l,u,1,p,c),h=!0,m=new ap(d,"max",h),f=a.runWebGLProgram(m,[o],o.dtype),g=new aJ(d),y=a.runWebGLProgram(g,[r,f],o.dtype);return a.disposeIntermediateTensorInfo(f),y}var oJ={kernelName:wp,backendName:"webgl",kernelFunc:iJ};function lJ(e,t,a,n){let r=new ap(a,"max",!1),s=n.runWebGLProgram(r,[e],"float32");r=new ap(a,"max",!0,!0,t);let i=n.runWebGLProgram(r,[e],"float32");return[s,i]}var uJ={kernelName:Iu,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:a})=>{let{x:n}=e,{filterSize:r,strides:s,pad:i,includeBatchInIndex:o}=t,l=a;v.assert(n.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${n.shape.length}.`);let u=[1,1];v.assert(C.eitherStridesOrDilationsAreOne(s,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${u}'`);let p=C.computePool2DInfo(n.shape,r,s,u,i),[c,d]=lJ(n,o,p,l);return[c,d]}};function dJ(e,t,a,n){let r=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/r,i=pe({inputs:{x:e},attrs:{shape:[s,r]},backend:n}),o=ol(i,"float32","mean",n),l=pe({inputs:{x:o},attrs:{shape:a},backend:n});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}var pJ={kernelName:po,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:a})=>{let{x:n}=e,{keepDims:r,axis:s}=t,i=a,o=n.shape.length,l=v.parseAxisParam(s,n.shape),u=l,p=C.getAxesPermutation(u,o),c=p!=null,d=i.shouldExecuteOnCPU([n]),h=[],m=n;if(c){if(d){let A=i.texData.get(m.dataId).values,b=new Array(o);for(let T=0;T<b.length;T++)b[T]=n.shape[p[T]];let w=O3(A,n.shape,n.dtype,p,b);m=i.makeTensorInfo(b,n.dtype);let I=i.texData.get(m.dataId);I.values=w}else m=s0(n,p,i);h.push(m),u=C.getInnerMostAxes(u.length,o)}C.assertAxesAreInnerMostDims("sum",u,o);let[f,g]=C.computeOutAndReduceShapes(m.shape,u),y=f;r&&(y=C.expandShapeToKeepDim(f,l));let x=dJ(m,g,y,i);for(let A of h)i.disposeIntermediateTensorInfo(A);return x}};function cJ(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n,o=r.shape.length,l=v.parseAxisParam(s,r.shape),u=l,p=C.getAxesPermutation(u,o),c=r;p!=null&&(c=Ca({inputs:{x:r},backend:a,attrs:{perm:p}}),u=C.getInnerMostAxes(u.length,r.shape.length)),C.assertAxesAreInnerMostDims("min",u,o);let[d,h]=C.computeOutAndReduceShapes(c.shape,u),m=v.sizeFromShape(h),f=pe({inputs:{x:c},backend:a,attrs:{shape:[-1,m]}}),g=ol(f,f.dtype,"min",a),y;if(i){let x=C.expandShapeToKeepDim(d,l);y=pe({inputs:{x:g},backend:a,attrs:{shape:x}})}else y=pe({inputs:{x:g},backend:a,attrs:{shape:d}});return a.disposeIntermediateTensorInfo(f),a.disposeIntermediateTensorInfo(g),p!=null&&a.disposeIntermediateTensorInfo(c),y}var hJ={kernelName:co,backendName:"webgl",kernelFunc:cJ},mJ=z3+`
  return min(a, b);
`,fJ=`
  vec4 result = vec4(min(a, b));
  bvec4 isNaNA = isnan(a);
  bvec4 isNaNB = isnan(b);
  bvec4 isNaN = bvec4(isNaNA.x || isNaNB.x, isNaNA.y || isNaNB.y, isNaNA.z || isNaNB.z, isNaNA.w || isNaNB.w);
  `+il+`
  return result;
`,gJ=ma({opSnippet:mJ,packedOpSnippet:fJ,cpuKernelImpl:QH}),yJ={kernelName:ho,backendName:"webgl",kernelFunc:gJ},xJ=class{constructor(e,t,a){this.variableNames=["x"],this.outputShape=t.map((u,p)=>u[0]+e[p]+u[1]);let n=e.length,r=ft(n),s=t.map(u=>u[0]).join(","),i=t.map((u,p)=>u[0]+e[p]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,n),l=a==="reflect"?0:1;if(n===1){this.userCode=`
        int start = ${s};
        int end = ${i};

        void main() {
          int outC = getOutputCoords();
          if (outC < start) {
            outC = start * 2 - outC - ${l};
          } else if(outC >= end) {
            outC = (end - 1) * 2 - outC + ${l};
          }
          setOutput(getX(outC - start));
        }
      `;return}this.userCode=`
      ${r} start = ${r}(${s});
      ${r} end = ${r}(${i});

      void main() {
        ${r} outC = getOutputCoords();
        for (int i = 0; i < ${n}; i++) {
          if (outC[i] < start[i]) {
            outC[i] = start[i] * 2 - outC[i] - ${l};
          } else if(outC[i] >= end[i]) {
            outC[i] = (end[i] - 1) * 2 - outC[i] + ${l};
          }
        }
        ${r} coords = outC - start;
        setOutput(getX(${o}));
      }
    `}},AJ=class{constructor(e,t,a){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((h,m)=>h[0]+e[m]+h[1]);let n=e.length,r=ft(n),s=t.map(h=>h[0]).join(","),i=t.map((h,m)=>h[0]+e[m]).join(","),o=ka("rc",n),l=ka("source",n),u=`${o[n-1]} < ${this.outputShape[n-1]}`,p=n===1?"source":`vec2(${l.slice(-2).join()})`,c=a==="reflect"?0:1,d="";if(n===1){let h=`
        ${r} source = rc;
        if (source < start) {
          source = start * 2 - source - ${c};
        } else if (source >= end) {
          source = (end - 1) * 2 - source + ${c};
        }
        source -= start;
      `;d=`
        ${r} rc = outputLoc;
        ${h}
        result[0] = getChannel(getX(${l.join()}), ${p});
        ${o[n-1]} += 1;
        if(${u}) {
          ${h}
          result[1] = getChannel(getX(${l.join()}), ${p});
        }
      `}else{let h=`
        ${r} source = rc;
        ${r} lt = ${r}(lessThan(source, start));
        ${r} gte = ${r}(greaterThanEqual(source, end));
        ${r} orig = 1 - (lt + gte);
        source = orig * source +
                lt * (start * 2 - source - ${c}) +
                gte * ((end - 1) * 2 - source + ${c});
        source -= start;
      `;d=`
        ${r} rc = outputLoc;
        ${h}
        result[0] = getChannel(getX(${l.join()}), ${p});
        ${o[n-1]} += 1;
        if(${u}) {
          ${h}
          result[1] = getChannel(getX(${l.join()}), ${p});
        }
        rc = outputLoc;
        ${o[n-2]} += 1;
        if(${o[n-2]} < ${this.outputShape[n-2]}) {
          ${h}
          result[2] = getChannel(getX(${l.join()}), ${p});
          ${o[n-1]} += 1;
          if(${u}) {
            ${h}
            result[3] = getChannel(getX(${l.join()}), ${p});
          }
        }
      `}this.userCode=`
      const ${r} start = ${r}(${s});
      const ${r} end = ${r}(${i});

      void main() {
        ${r} outputLoc = getOutputCoords();
        vec4 result = vec4(0.);
        ${d}
        setOutput(result);
      }
    `}},bJ=({inputs:e,backend:t,attrs:a})=>{let{x:n}=e,{paddings:r,mode:s}=a,i=B().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new AJ(n.shape,r,s):new xJ(n.shape,r,s);return t.runWebGLProgram(i,[n],n.dtype)},vJ={kernelName:mo,backendName:"webgl",kernelFunc:bJ},wJ=`if (b == 0.0) return NAN;
  return mod(a, b);`,kJ=`
  vec4 result = mod(a, b);
  bvec4 isNaN = equal(b, vec4(0.0));
  `+il+`
  return result;
`,IJ=ma({opSnippet:wJ,packedOpSnippet:kJ}),SJ={kernelName:fo,backendName:"webgl",kernelFunc:IJ},CJ=class{constructor(e,t,a){this.variableNames=["probs"],this.customUniforms=[{name:"seed",type:"float"}],this.outputShape=[e,a],this.userCode=`
      void main() {
        ivec2 coords = getOutputCoords();
        int batch = coords[0];

        float r = random(seed);
        float cdf = 0.0;

        for (int i = 0; i < ${t-1}; i++) {
          cdf += getProbs(batch, i);

          if (r < cdf) {
            setOutput(float(i));
            return;
          }
        }

        // If no other event happened, last event happened.
        setOutput(float(${t-1}));
      }
    `}},TJ=`
if (a == b) {
  return 1.0;
};
return a / b;`,NJ=`
  // vec4 one = vec4(equal(a, b));
  // return one + (vec4(1.0) - one) * a / b;
  vec4 result = a / b;
  if(a.x == b.x) {
    result.x = 1.;
  }
  if(a.y == b.y) {
    result.y = 1.;
  }
  if(a.z == b.z) {
    result.z = 1.;
  }
  if(a.w == b.w) {
    result.w = 1.;
  }

  return result;
`,B8=ma({opSnippet:TJ,packedOpSnippet:NJ,checkOutOfBounds:!0}),RJ={kernelName:_i,backendName:"webgl",kernelFunc:B8},H5="return a - b;",V8=ma({opSnippet:H5,packedOpSnippet:H5,supportsComplex:!0,cpuKernelImpl:bj}),EJ={kernelName:Ko,backendName:"webgl",kernelFunc:V8};function U8(e){let{inputs:t,backend:a,attrs:n}=e,{logits:r}=t,{dim:s}=n,i=v.parseAxisParam([s],r.shape),o=W8({inputs:{x:r},backend:a,attrs:{reductionIndices:i,keepDims:!1}}),l=C.expandShapeToKeepDim(o.shape,i),u=pe({inputs:{x:o},backend:a,attrs:{shape:l}}),p=V8({inputs:{a:r,b:u},backend:a}),c=O8({inputs:{x:p},backend:a}),d=i0({inputs:{x:c},backend:a,attrs:{axis:i,keepDims:!1}}),h=pe({inputs:{x:d},backend:a,attrs:{shape:l}}),m=B8({inputs:{a:c,b:h},backend:a});return a.disposeIntermediateTensorInfo(o),a.disposeIntermediateTensorInfo(u),a.disposeIntermediateTensorInfo(p),a.disposeIntermediateTensorInfo(c),a.disposeIntermediateTensorInfo(d),a.disposeIntermediateTensorInfo(h),m}var MJ={kernelName:Ho,backendName:"webgl",kernelFunc:U8};function $J(e){let{inputs:t,backend:a,attrs:n}=e,{logits:r}=t,{numSamples:s,seed:i,normalized:o}=n,l=o?r:U8({inputs:{logits:r},backend:a,attrs:{dim:r.shape.length-1}}),u=l.shape[0],p=l.shape[1],c=new CJ(u,p,s),d=[[i]],h=a.runWebGLProgram(c,[l],"int32",d);return o||a.disposeIntermediateTensorInfo(l),h}var PJ={kernelName:go,backendName:"webgl",kernelFunc:$J},_J=Mn+`
  return -x;
`,FJ=`
  vec4 result = -x;
  bvec4 isNaN = isnan(x);

  result.r = isNaN.r ? x.r : result.r;
  result.g = isNaN.g ? x.g : result.g;
  result.b = isNaN.b ? x.b : result.b;
  result.a = isNaN.a ? x.a : result.a;

  return result;
`;function DJ(e){let{inputs:t,backend:a}=e,{x:n}=t;if(a.shouldExecuteOnCPU([n])){let s=a.texData.get(n.dataId),[i,o]=tj(s.values,n.shape,n.dtype);return a.makeTensorInfo(o,n.dtype,i)}let r;return B().getBool("WEBGL_PACK_UNARY_OPERATIONS")?r=new qr(n.shape,FJ):r=new Jn(n.shape,_J),a.runWebGLProgram(r,[n],n.dtype)}var OJ={kernelName:Su,backendName:"webgl",kernelFunc:DJ},zJ=En.nonMaxSuppressionV3Impl;function LJ(e){C.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:a,attrs:n}=e,{boxes:r,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l}=n,u=a.readSync(r.dataId),p=a.readSync(s.dataId),{selectedIndices:c}=zJ(u,p,i,o,l);return a.makeTensorInfo([c.length],"int32",new Int32Array(c))}var WJ={kernelName:Ao,backendName:"webgl",kernelFunc:LJ},BJ=En.nonMaxSuppressionV4Impl;function VJ(e){C.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:a,attrs:n}=e,{boxes:r,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,padToMaxOutputSize:u}=n,p=a.readSync(r.dataId),c=a.readSync(s.dataId),{selectedIndices:d,validOutputs:h}=BJ(p,c,i,o,l,u);return[a.makeTensorInfo([d.length],"int32",new Int32Array(d)),a.makeTensorInfo([],"int32",new Int32Array([h]))]}var UJ={kernelName:Cu,backendName:"webgl",kernelFunc:VJ},GJ=En.nonMaxSuppressionV5Impl;function HJ(e){C.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:a,attrs:n}=e,{boxes:r,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,softNmsSigma:u}=n,p=a.readSync(r.dataId),c=a.readSync(s.dataId),d=i,h=o,m=l,f=u,{selectedIndices:g,selectedScores:y}=GJ(p,c,d,h,m,f);return[a.makeTensorInfo([g.length],"int32",new Int32Array(g)),a.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var jJ={kernelName:bo,backendName:"webgl",kernelFunc:HJ},qJ=class{constructor(e,t,a,n){this.variableNames=["indices"],this.outputShape=[e,t],this.userCode=`
      void main() {
        ivec2 coords = getOutputCoords();
        int index = round(getIndices(coords.x));
        setOutput(mix(float(${n}), float(${a}),
                      float(index == coords.y)));
      }
    `}},XJ=e=>{let{inputs:t,backend:a,attrs:n}=e,{indices:r}=t,{dtype:s,depth:i,onValue:o,offValue:l}=n,u=v.sizeFromShape(r.shape),p=new qJ(u,i,o,l),c=pe({inputs:{x:r},backend:a,attrs:{shape:[u]}}),d=a.runWebGLProgram(p,[c],s);a.disposeIntermediateTensorInfo(c);let h=[...r.shape,i],m=pe({inputs:{x:d},backend:a,attrs:{shape:h}});return a.disposeIntermediateTensorInfo(d),m},KJ={kernelName:vo,backendName:"webgl",kernelFunc:XJ};function Sh(e){let{inputs:t,backend:a}=e,{x:n}=t;if(n.dtype==="complex64"){let r=Qp({inputs:{input:n},backend:a}),s=Sh({inputs:{x:r},backend:a}),i=o0({inputs:{input:n},backend:a}),o=Sh({inputs:{x:i},backend:a}),l=fs({inputs:{real:s,imag:o},backend:a});return a.disposeIntermediateTensorInfo(r),a.disposeIntermediateTensorInfo(s),a.disposeIntermediateTensorInfo(i),a.disposeIntermediateTensorInfo(o),l}else return ec({attrs:{shape:n.shape,dtype:n.dtype,value:n.dtype==="string"?"":0},backend:a})}var YJ={kernelName:Vu,backendName:"webgl",kernelFunc:Sh};function G8(e){let{inputs:t,backend:a}=e,{x:n}=t;if(n.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(n.dtype==="complex64"){let r=Qp({inputs:{input:n},backend:a}),s=G8({inputs:{x:r},backend:a}),i=o0({inputs:{input:n},backend:a}),o=Sh({inputs:{x:i},backend:a}),l=fs({inputs:{real:s,imag:o},backend:a});return a.disposeIntermediateTensorInfo(r),a.disposeIntermediateTensorInfo(s),a.disposeIntermediateTensorInfo(i),a.disposeIntermediateTensorInfo(o),l}else return ec({attrs:{shape:n.shape,dtype:n.dtype,value:1},backend:a})}var ZJ={kernelName:Tu,backendName:"webgl",kernelFunc:G8};function JJ(e){let{inputs:t,backend:a,attrs:n}=e,{axis:r}=n;if(t.length===1)return B1({inputs:{input:t[0]},backend:a,attrs:{dim:r}});let s=t[0].shape,i=t[0].dtype;t.forEach(p=>{v.assertShapesMatch(s,p.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===p.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(p=>{let c=B1({inputs:{input:p},backend:a,attrs:{dim:r}});return o.push(c),c}),u=R8({inputs:l,backend:a,attrs:{axis:r}});return o.forEach(p=>a.disposeIntermediateTensorInfo(p)),u}var QJ={kernelName:Nu,backendName:"webgl",kernelFunc:JJ},eQ=class{constructor(e,t,a){this.variableNames=["x"],this.customUniforms=[{name:"value",type:"float"}],this.outputShape=t.map((l,u)=>l[0]+e[u]+l[1]);let n=e.length,r=ft(n),s=t.map(l=>l[0]).join(","),i=t.map((l,u)=>l[0]+e[u]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,n);if(n===1){this.userCode=`
        int start = ${s};
        int end = ${i};

        void main() {
          int outC = getOutputCoords();
          if (outC < start || outC >= end) {
            setOutput(value);
          } else {
            setOutput(getX(outC - start));
          }
        }
      `;return}this.userCode=`
      ${r} start = ${r}(${s});
      ${r} end = ${r}(${i});

      void main() {
        ${r} outC = getOutputCoords();
        if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {
          setOutput(value);
        } else {
          ${r} coords = outC - start;
          setOutput(getX(${o}));
        }
      }
    `}},tQ=class{constructor(e,t,a){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"value",type:"float"}],this.outputShape=t.map((m,f)=>m[0]+e[f]+m[1]);let n=e.length,r=ft(n),s=t.map(m=>m[0]).join(","),i=t.map((m,f)=>m[0]+e[f]).join(","),o=ka("rc",n),l=ka("source",n),u=`${o[n-1]} < ${this.outputShape[n-1]}`,p=n===1?"source":`vec2(${l.slice(-2).join()})`,c=[`${r} rc = outputLoc;`,`${o[n-1]} += 1;
       if(${u}) {
      `,n===1?"":`}
       rc = outputLoc;
       ${o[n-2]} += 1;
       if(${o[n-2]} < ${this.outputShape[n-2]}) {`,n===1?"":`  ${o[n-1]} += 1;
         if(${u}) {`],d=n===1?"rc < start || rc >= end":"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))",h="";for(let m=0,f=n===1?2:4;m<f;m++)h+=`
        ${c[m]}
        if (${d}) {
          result[${m}] = float(value);
        } else {
          ${r} source = rc - start;
          result[${m}] = getChannel(getX(${l.join()}), ${p});
        }
      `;h+=n===1?"} ":"}}",this.userCode=`
      const ${r} start = ${r}(${s});
      const ${r} end = ${r}(${i});

      void main() {
        ${r} outputLoc = getOutputCoords();
        vec4 result = vec4(0.);
        ${h}
        setOutput(result);
      }
    `}},H8=e=>{let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{paddings:s,constantValue:i}=n;if(v.sizeFromShape(r.shape)===0){let u=s.map((p,c)=>p[0]+r.shape[c]+p[1]);return ec({backend:a,attrs:{shape:u,value:i,dtype:r.dtype}})}let o=B().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new tQ(r.shape,s,i):new eQ(r.shape,s,i),l=[[i]];return a.runWebGLProgram(o,[r],r.dtype,l)},aQ={kernelName:wo,backendName:"webgl",kernelFunc:H8},nQ=`
  if(a < 0.0 && floor(b) < b){
    return NAN;
  }
  if (b == 0.0) {
    return 1.0;
  }
  return (round(mod(b, 2.0)) != 1) ?
      pow(abs(a), b) : sign(a) * pow(abs(a), b);
`,rQ=`
  // isModRound1 has 1 for components with round(mod(b, 2.0)) == 1, 0 otherwise.
  vec4 isModRound1 = vec4(equal(round(mod(b, 2.0)), ivec4(1)));
  vec4 multiplier = sign(a) * isModRound1 + (vec4(1.0) - isModRound1);
  vec4 result = multiplier * pow(abs(a), b);

  // Ensure that a^0 = 1, including 0^0 = 1 as this correspond to TF and JS
  bvec4 isExpZero = equal(b, vec4(0.0));
  result.r = isExpZero.r ? 1.0 : result.r;
  result.g = isExpZero.g ? 1.0 : result.g;
  result.b = isExpZero.b ? 1.0 : result.b;
  result.a = isExpZero.a ? 1.0 : result.a;

  bvec4 isNaN1 = lessThan(a, vec4(0.0));
  bvec4 isNaN2 = lessThan(floor(b), b);
  bvec4 isNaN = bvec4(isNaN1.x && isNaN2.x, isNaN1.y && isNaN2.y, isNaN1.z && isNaN2.z, isNaN1.w && isNaN2.w);
  `+il+`
  return result;
`,sQ=ma({opSnippet:nQ,packedOpSnippet:rQ}),iQ={kernelName:ko,backendName:"webgl",kernelFunc:sQ};function oQ(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n,o=r.shape.length,l=[],u=v.parseAxisParam(s,r.shape),p=u,c=C.getAxesPermutation(p,o),d=r;c!=null&&(d=Ca({inputs:{x:r},backend:a,attrs:{perm:c}}),p=C.getInnerMostAxes(p.length,o),l.push(d)),C.assertAxesAreInnerMostDims("prod",p,o);let h;if(a.shouldExecuteOnCPU([d])){let m=a.texData.get(d.dataId).values,{outVals:f,outShape:g,outDtype:y}=nj(d.shape,d.dtype,m,p);h=a.makeTensorInfo(g,y,f)}else{let[m,f]=C.computeOutAndReduceShapes(d.shape,p),g=v.sizeFromShape(f),y=pe({inputs:{x:d},backend:a,attrs:{shape:[-1,g]}}),x=_p(r.dtype),A=ol(y,x,"prod",a);h=pe({inputs:{x:A},backend:a,attrs:{shape:m}}),l.push(y),l.push(A)}if(i){l.push(h);let m=C.expandShapeToKeepDim(h.shape,u);h=pe({inputs:{x:h},backend:a,attrs:{shape:m}})}return l.forEach(m=>a.disposeIntermediateTensorInfo(m)),h}var lQ={kernelName:So,backendName:"webgl",kernelFunc:oQ};function uQ(e){let{inputs:t,backend:a,attrs:n}=e,{paramsNestedSplits:r,paramsDenseValues:s,indices:i}=t,{outputRaggedRank:o}=n,l=r.map(y=>a.readSync(y.dataId)),u=r.map(y=>y.shape),p=a.readSync(s.dataId),c=a.readSync(i.dataId),[d,h,m]=rj(l,u,p,s.shape,s.dtype,c,i.shape,o),f=d.map(y=>a.makeTensorInfo([y.length],"int32",y)),g=a.makeTensorInfo(m,s.dtype,h);return f.concat([g])}var dQ={kernelName:$h,backendName:"webgl",kernelFunc:uQ};function pQ(e){let{inputs:t,backend:a}=e,{starts:n,limits:r,deltas:s}=t,i=a.readSync(n.dataId),o=a.readSync(r.dataId),l=a.readSync(s.dataId),[u,p]=sj(i,n.shape,n.dtype,o,r.shape,l,s.shape),c=a.makeTensorInfo([u.length],"int32",u),d=a.makeTensorInfo([p.length],n.dtype,p);return[c,d]}var cQ={kernelName:Ph,backendName:"webgl",kernelFunc:pQ};function hQ(e){let{inputs:t,backend:a,attrs:n}=e,{shape:r,values:s,defaultValue:i,rowPartitionTensors:o}=t,{rowPartitionTypes:l}=n,u=a.readSync(r.dataId),p=a.readSync(s.dataId),c=a.readSync(i.dataId),d=o.map(g=>a.readSync(g.dataId)),h=o.map(g=>g.shape),[m,f]=ij(u,r.shape,p,s.shape,s.dtype,c,i.shape,d,h,l);return a.makeTensorInfo(m,s.dtype,f)}var mQ={kernelName:_h,backendName:"webgl",kernelFunc:hQ},j8=e=>{let{backend:t,attrs:a}=e,{start:n,stop:r,step:s,dtype:i}=a,o=oj(n,r,s,i);return t.makeTensorInfo([o.length],i,o)},fQ={kernelName:Ru,backendName:"webgl",kernelFunc:j8},gQ="return 1.0 / x;",yQ=tt({opSnippet:gQ}),xQ={kernelName:Co,backendName:"webgl",kernelFunc:yQ},AQ=Mn+`
  return (x < 0.0) ? 0.0 : x;
`,bQ=`
  vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));
  bvec4 isNaN = isnan(x);

  result.r = isNaN.r ? x.r : result.r;
  result.g = isNaN.g ? x.g : result.g;
  result.b = isNaN.b ? x.b : result.b;
  result.a = isNaN.a ? x.a : result.a;

  return result;
`,vQ=tt({opSnippet:AQ,packedOpSnippet:bQ}),wQ={kernelName:To,backendName:"webgl",kernelFunc:vQ},kQ=Mn+`
  return (x < 0.0) ? 0.0 : min(6.0, x);
`,IQ=`
  vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));
  bvec4 isNaN = isnan(x);

  result.r = isNaN.r ? x.r : result.r;
  result.g = isNaN.g ? x.g : result.g;
  result.b = isNaN.b ? x.b : result.b;
  result.a = isNaN.a ? x.a : result.a;

  return result;
`,SQ=tt({opSnippet:kQ,packedOpSnippet:IQ}),CQ={kernelName:Eo,backendName:"webgl",kernelFunc:SQ},TQ=class{constructor(e,t,a,n,r){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,a,l];let u=[n&&t>1?i-1:i,n&&a>1?o-1:o],p=[n&&t>1?t-1:t,n&&a>1?a-1:a],c;r?c="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":c="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
      const vec2 effectiveInputOverOutputRatioRC = vec2(
          ${u[0]/p[0]},
          ${u[1]/p[1]});
      const vec2 inputShapeRC = vec2(${i}.0, ${o}.0);

      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];
        ivec2 yRC = coords.yz;

        // Fractional source index.
        vec2 sourceFracIndexRC = ${c};

        // Compute the four integer indices.
        ivec2 sourceFloorRC = ivec2(max(sourceFracIndexRC, vec2(0.0)));
        ivec2 sourceCeilRC = ivec2(
          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));

        float topLeft = getA(b, sourceFloorRC.x, sourceFloorRC.y, d);
        float bottomLeft = getA(b, sourceCeilRC.x, sourceFloorRC.y, d);
        float topRight = getA(b, sourceFloorRC.x, sourceCeilRC.y, d);
        float bottomRight = getA(b, sourceCeilRC.x, sourceCeilRC.y, d);

        vec2 fracRC = sourceFracIndexRC - vec2(sourceFloorRC);

        float top = topLeft + (topRight - topLeft) * fracRC.y;
        float bottom = bottomLeft + (bottomRight - bottomLeft) * fracRC.y;
        float newValue = top + (bottom - top) * fracRC.x;

        setOutput(newValue);
      }
    `}},NQ=class{constructor(e,t,a,n,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,a,l];let u=[n&&t>1?i-1:i,n&&a>1?o-1:o],p=[n&&t>1?t-1:t,n&&a>1?a-1:a],c;r?c="(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":c="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
      const vec3 effectiveInputOverOutputRatioRC = vec3(
          ${u[0]/p[0]},
          ${u[1]/p[1]},
          ${u[1]/p[1]});
      const vec3 inputShapeRC = vec3(${i}.0, ${o}.0,
                                     ${o}.0);

      float getAValue(int b, int r, int c, int d) {
        return getChannel(getA(b, r, c, d), vec2(c, d));
      }

      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];
        // Calculate values for next column in yRC.z.
        ivec3 yRC = coords.yzz + ivec3(0, 0, 1);

        // Fractional source index.
        vec3 sourceFracIndexRC = ${c};

        // Compute the four integer indices.
        ivec3 sourceFloorRC = ivec3(max(sourceFracIndexRC, vec3(0.0)));
        ivec3 sourceCeilRC = ivec3(
          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));

        // Should we calculate next column and row elements in 2x2 packed cell.
        bool hasNextCol = d < ${l-1};
        bool hasNextRow = coords.z < ${a-1};

        // In parallel, construct four corners for all four components in
        // packed 2x2 cell.
        vec4 topLeft = vec4(
          getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d),
          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d + 1)
                     : 0.0,
          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d)
                     : 0.0,
          (hasNextRow && hasNextCol) ?
            getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d + 1) : 0.0);

        vec4 bottomLeft = vec4(
          getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d),
          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d + 1)
                     : 0.0,
          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d)
                     : 0.0,
          (hasNextRow && hasNextCol) ?
            getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d + 1) : 0.0);

        vec4 topRight = vec4(
          getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d),
          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d + 1)
                     : 0.0,
          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d)
                     : 0.0,
          (hasNextRow && hasNextCol) ?
            getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d + 1) : 0.0);

        vec4 bottomRight = vec4(
          getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d),
          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d + 1)
                     : 0.0,
          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d)
                     : 0.0,
          (hasNextRow && hasNextCol) ?
            getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d + 1) : 0.0);

        vec3 fracRC = sourceFracIndexRC - vec3(sourceFloorRC);

        vec4 top = mix(topLeft, topRight, fracRC.yyzz);
        vec4 bottom = mix(bottomLeft, bottomRight, fracRC.yyzz);
        vec4 newValue = mix(top, bottom, fracRC.x);

        setOutput(newValue);
      }
    `}};function RQ(e){let{inputs:t,backend:a,attrs:n}=e,{images:r}=t,{alignCorners:s,halfPixelCenters:i,size:o}=n,[l,u]=o,p=B().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new NQ(r.shape,l,u,s,i):new TQ(r.shape,l,u,s,i);return a.runWebGLProgram(p,[r],"float32")}var EQ={kernelName:Ro,backendName:"webgl",kernelFunc:RQ},MQ=class{constructor(e,t,a){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,n,r]=t,[,s,i]=e,o=[a&&s>1?n-1:n,a&&i>1?r-1:r],l=[a&&s>1?s-1:s,a&&i>1?i-1:i],u=o[0]/l[0],p=o[1]/l[1],c=1/u,d=1/p,h=Math.ceil(c)*2+2,m=Math.ceil(d)*2+2;this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];
        int r = coords[1];
        int c = coords[2];

        float accumulator = 0.0;

        const float heightScale = float(${u});
        const float widthScale = float(${p});

        const float invHeightScale = float(${c});
        const float invWidthScale = float(${d});

        const int winHeight = int(${h});
        const int winWidth = int(${m});

        // Compute bounds for where in dy we will look
        float startRLerp = floor(float(r) * invHeightScale);
        int startDyR = int(startRLerp - float(winHeight / 2));

        float startCLerp = floor(float(c) * invWidthScale);
        int startDyC = int(startCLerp - float(winWidth / 2));

        // Loop over dy
        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {
          int dyR = dyROffset + startDyR;

          // Guard against the window exceeding the bounds of dy
          if (dyR < 0 || dyR >= ${s}) {
            continue;
          }

          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {
            int dyC = dyCOffset + startDyC;

            // Guard against the window exceeding the bounds of dy
            if (dyC < 0 || dyC >= ${i}) {
              continue;
            }

            float dxR = float(dyR) * heightScale;
            int topDxRIndex = int(floor(dxR));
            int bottomDxRIndex = int(min(ceil(dxR), ${n-1}.0));
            float dxRLerp = dxR - float(topDxRIndex);
            float inverseDxRLerp = 1.0 - dxRLerp;

            float dxC = float(dyC) * widthScale;
            int leftDxCIndex = int(floor(dxC));
            int rightDxCIndex = int(min(ceil(dxC), ${r-1}.0));
            float dxCLerp = dxC - float(leftDxCIndex);
            float inverseDxCLerp = 1.0 - dxCLerp;

            if (r == topDxRIndex && c == leftDxCIndex) {
              // topLeft
              accumulator +=
                getDy(b, dyR, dyC, d) * inverseDxRLerp * inverseDxCLerp;
            }

            if (r == topDxRIndex && c == rightDxCIndex) {
              // topRight
              accumulator += getDy(b, dyR, dyC, d) * inverseDxRLerp * dxCLerp;
            }

            if (r == bottomDxRIndex && c == leftDxCIndex) {
              // bottomLeft
              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * inverseDxCLerp;
            }

            if (r == bottomDxRIndex && c == rightDxCIndex) {
              // bottomRight
              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * dxCLerp;
            }
          }
        }
        // End loop over dy

        setOutput(accumulator);
      }
    `}};function $Q(e){let{inputs:t,backend:a,attrs:n}=e,{images:r,dy:s}=t,{alignCorners:i}=n,o=new MQ(s.shape,r.shape,i);return a.runWebGLProgram(o,[s],s.dtype)}var PQ={kernelName:$u,backendName:"webgl",kernelFunc:$Q},_Q=class{constructor(e,t,a,n,r){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,a,l];let u=[n&&t>1?i-1:i,n&&a>1?o-1:o],p=[n&&t>1?t-1:t,n&&a>1?a-1:a],c=n?"0.5":"0.0",d;r?d="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":d="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
      const vec2 effectiveInputOverOutputRatioRC = vec2(
          ${u[0]/p[0]},
          ${u[1]/p[1]});
      const vec2 inputShapeRC = vec2(${i}.0, ${o}.0);

      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];
        ivec2 yRC = coords.yz;

        // Fractional source index.
        vec2 sourceFracIndexRC = ${d};

        // Compute the coordinators of nearest neighbor point.
        ivec2 sourceNearestRC = ivec2(
          min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${c})));
        float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d);

        setOutput(newValue);
      }
    `}},FQ=class{constructor(e,t,a,n,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,a,l];let u=[n&&t>1?i-1:i,n&&a>1?o-1:o],p=[n&&t>1?t-1:t,n&&a>1?a-1:a],c=n?"0.5":"0.0",d;r?d="max((vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC, vec3(0.0))":d="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
      const vec3 effectiveInputOverOutputRatioRC = vec3(
          ${u[0]/p[0]},
          ${u[1]/p[1]},
          ${u[1]/p[1]});
      const vec3 inputShapeRC = vec3(${i}.0, ${o}.0,
                                     ${o}.0);

      float getAValue(int b, int r, int c, int d) {
        return getChannel(getA(b, r, c, d), vec2(c, d));
      }

      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];
        // Calculate values for next column in yRC.z.
        ivec3 yRC = coords.yzz + ivec3(0, 0, 1);

        // Fractional source index.
        vec3 sourceFracIndexRC = ${d};

        // Compute the coordinators of nearest neighbor point.
        ivec3 sourceNearestRC = ivec3(
          min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${c})));

        // Should we calculate next column and row elements in 2x2 packed cell.
        bool hasNextCol = d < ${l-1};
        bool hasNextRow = coords.z < ${a-1};

        vec4 newValue = vec4(
          getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d),
          hasNextCol ? getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d + 1)
                     : 0.0,
          hasNextRow ? getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d)
                     : 0.0,
          (hasNextRow && hasNextCol) ?
            getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d + 1) : 0.0);

        setOutput(newValue);
      }
    `}};function DQ(e){let{inputs:t,backend:a,attrs:n}=e,{images:r}=t,{alignCorners:s,halfPixelCenters:i,size:o}=n,[l,u]=o,p=B().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new FQ(r.shape,l,u,s,i):new _Q(r.shape,l,u,s,i);return a.runWebGLProgram(p,[r],r.dtype)}var OQ={kernelName:No,backendName:"webgl",kernelFunc:DQ},zQ=class{constructor(e,t,a){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,n,r]=t,[,s,i]=e,o=[a&&s>1?n-1:n,a&&i>1?r-1:r],l=[a&&s>1?s-1:s,a&&i>1?i-1:i],u=o[0]/l[0],p=o[1]/l[1],c=1/u,d=1/p,h=Math.ceil(c)*2+2,m=Math.ceil(d)*2+2;this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];
        int r = coords[1];
        int c = coords[2];

        float accumulator = 0.0;

        const float heightScale = float(${u});
        const float widthScale = float(${p});

        const float invHeightScale = float(${c});
        const float invWidthScale = float(${d});

        const int winHeight = int(${h});
        const int winWidth = int(${m});

        // Compute bounds for where in dy we will look
        float startRLerp = floor(float(r) * invHeightScale);
        int startDyR = int(floor(startRLerp - float(winHeight / 2)));

        float startCLerp = floor(float(c) * invWidthScale);
        int startDyC = int(floor(startCLerp - float(winWidth / 2)));

        // Loop over dy
        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {
          int dyR = dyROffset + startDyR;

          // Guard against the window exceeding the bounds of dy
          if (dyR < 0 || dyR >= ${s}) {
            continue;
          }

          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {
            int dyC = dyCOffset + startDyC;

            // Guard against the window exceeding the bounds of dy
            if (dyC < 0 || dyC >= ${i}) {
              continue;
            }

            float sourceFracRow =
              float(${o[0]}) *
                (float(dyR) / float(${l[0]}));

            float sourceFracCol =
                float(${o[1]}) *
                  (float(dyC) / float(${l[1]}));

            int sourceNearestRow = int(min(
                float(int(${n}) - 1),
                ${a} ? float(round(sourceFracRow)) :
                                  float(floor(sourceFracRow))));

            int sourceNearestCol = int(min(
                float(int(${r}) - 1),
                ${a} ? float(round(sourceFracCol)) :
                                  float(floor(sourceFracCol))));

            if (r == sourceNearestRow && c == sourceNearestCol) {
              accumulator += getDy(b, dyR, dyC, d);
            }
          }
        }
        // End loop over dy

        setOutput(accumulator);
      }
    `}};function LQ(e){let{inputs:t,backend:a,attrs:n}=e,{images:r,dy:s}=t,{alignCorners:i}=n,o=new zQ(s.shape,r.shape,i);return a.runWebGLProgram(o,[s],s.dtype)}var WQ={kernelName:Mu,backendName:"webgl",kernelFunc:LQ},BQ=class{constructor(e,t){this.variableNames=["x"];let a=e.length;if(a>4)throw new Error(`WebGL backend: Reverse of rank-${a} tensor is not yet supported`);if(this.outputShape=e,a===1){this.userCode=`
        void main() {
          int coord = getOutputCoords();
          setOutput(getX(${e[0]} - coord - 1));
        }
      `;return}let n=i=>t.indexOf(i)!==-1&&e[i]!==1?`${e[i]} - coords[${i}] - 1`:`coords[${i}]`,r=e.map((i,o)=>n(o)).join(","),s=ft(a);this.userCode=`
      void main() {
        ${s} coords = getOutputCoords();
        setOutput(getX(${r}));
      }
    `}},VQ=class{constructor(e,t){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;let a=e.length;if(a>4)throw new Error(`WebGL backend: Reverse of rank-${a} tensor is not yet supported`);this.outputShape=e;let n=ka("rc",a),r=`${n[a-1]} + 1 < ${this.outputShape[a-1]}`,s=`${n[a-2]} + 1 < ${this.outputShape[a-2]}`,i=ft(a);a===1?this.userCode=`
        void main(){
          int rc = getOutputCoords();
          vec4 result = vec4(0.);
          result.r = getChannel(getX(${e[0]} - rc - 1),
            ${e[0]} - rc - 1);
          if(${r}){
              result.g = getChannel(getX(${e[0]} - (rc  + 1) - 1),
                ${e[0]} - (rc  + 1) - 1);
          }
          setOutput(result);
        }
      `:this.userCode=`
        void main() {
          ${i} rc = getOutputCoords();
          vec4 result = vec4(0.);
          result.r = ${o(n.slice())};
          if(${r}){
            result.g = ${l(n.slice())};
          }
          if(${s}) {
            result.b = ${u(n.slice())};
            if(${r}) {
              result.a = ${p(n.slice())};
            }
          }
          setOutput(result);
        }
    `;function o(h){return c(h)}function l(h){return h[a-1]="("+h[a-1]+" + 1)",c(h)}function u(h){return h[a-2]="("+h[a-2]+" + 1)",c(h)}function p(h){return h[a-1]="("+h[a-1]+" + 1)",h[a-2]="("+h[a-2]+" + 1)",c(h)}function c(h){let m=e.map((y,x)=>d(x,h)),f=m.join(","),g=m.slice(-2).join(",");return`getChannel(getX(${f}), vec2(${g}))`}function d(h,m){return t.indexOf(h)!==-1&&e[h]!==1?`${e[h]} - ${m[h]} - 1`:`${m[h]}`}}};function UQ(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{dims:s}=n,i=r.shape.length,o=v.parseAxisParam(s,r.shape);if(i===0)return en({inputs:{x:r},backend:a});let l=B().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new VQ(r.shape,o):new BQ(r.shape,o);return a.runWebGLProgram(l,[r],r.dtype)}var GQ={kernelName:Mo,backendName:"webgl",kernelFunc:UQ},HQ=class{constructor(e,t){this.variableNames=["Image"],this.outputShape=[],this.customUniforms=[{name:"params",type:"vec4"}];let a=e[1],n=e[2];this.outputShape=e;let r="";typeof t=="number"?r=`float outputValue = ${t.toFixed(2)};`:r=`
        vec3 fill = vec3(${t.join(",")});
        float outputValue = fill[coords[3]];`,this.userCode=`
        void main() {
          ivec4 coords = getOutputCoords();
          int x = coords[2];
          int y = coords[1];
          float coordXFloat = (float(x) - params[0]) * params[3] -
            (float(y) - params[1]) * params[2];
          float coordYFloat = (float(x) - params[0]) * params[2] +
            (float(y) - params[1]) * params[3];
          int coordX = int(round(coordXFloat + params[0]));
          int coordY = int(round(coordYFloat + params[1]));
          ${r}
          if(coordX >= 0 && coordX < ${n} && coordY >= 0 && coordY < ${a}) {
            outputValue = getImage(coords[0], coordY, coordX, coords[3]);
          }
          setOutput(outputValue);
        }
    `}},jQ={kernelName:el,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:a})=>{let{image:n}=e,{radians:r,fillValue:s,center:i}=t,o=a,l=new HQ(n.shape,s),[u,p]=C.getImageCenter(i,n.shape[1],n.shape[2]),c=[[u,p,Math.sin(r),Math.cos(r)]];return o.runWebGLProgram(l,[n],n.dtype,c)}},qQ=`
  // OpenGL ES does not support round function.
  // The algorithm is based on banker's rounding.
  float base = floor(x);
  if ((x - base) < 0.5) {
    return floor(x);
  } else if ((x - base) > 0.5) {
    return ceil(x);
  } else {
    if (mod(base, 2.0) == 0.0) {
      return base;
    } else {
      return base + 1.0;
    }
  }
`,XQ=tt({opSnippet:qQ}),KQ={kernelName:$o,backendName:"webgl",kernelFunc:XQ},YQ="return inversesqrt(x);",ZQ=tt({opSnippet:YQ,cpuKernelImpl:lj}),JQ={kernelName:Po,backendName:"webgl",kernelFunc:ZQ},B3=class{constructor(e,t,a,n,r,s,i=!0,o=!1){this.variableNames=["updates","indices","defaultValue"],this.outputShape=s;let l=ft(r.length),u=ft(s.length),p="";a===1?p="i":a===2&&(p="i, j");let c=`getIndices(${p})`,d="";n===1?d="i":n===2&&(d="i, coords[1]");let h=`getUpdates(${d})`,m="";o&&(m="coords[0], coords[1]");let f=`getDefaultValue(${m})`,g=t>1?"strides[j]":"strides";this.userCode=`
        ${l} strides = ${l}(${r});

        void main() {
          ${u} coords = getOutputCoords();
          float sum = 0.0;
          bool found = false;
          for (int i = 0; i < ${e}; i++) {
            int flattenedIndex = 0;
            for (int j = 0; j < ${t}; j++) {
              int index = round(${c});
              flattenedIndex += index * ${g};
            }
            if (flattenedIndex == coords[0]) {
              sum += ${h};
              found = true;
            }
          }
          setOutput(mix(${f}, sum, float(found)));
        }
      `}},QQ=class{constructor(e,t,a,n,r,s,i=!0,o=!1){this.variableNames=["updates","indices","defaultValue"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=s;let l=ft(r.length),u=ft(s.length),p="";a===1?p="i":a===2&&(p="i, j");let c=`getIndices(${p})`,d="";n===1?d="i":n===2&&(d="i, coords[1]");let h=`getUpdates(${d})`,m="";o&&(m="coords[0], coords[1]");let f=`getDefaultValue(${m})`,g=t>1?"strides[j]":"strides",y=t>1?"strides[j + 1]":"strides";this.userCode=`
        ${l} strides = ${l}(${r});

        void main() {
          ${u} coords = getOutputCoords();
          vec4 sum = vec4(0.);
          vec4 found = vec4(0.);
          for (int i = 0; i < ${e}; i+=2) {
            ivec2 flattenedIndex = ivec2(0);
            for (int j = 0; j < ${t}; j+=2) {
              ivec4 index = round(${c});
              flattenedIndex += index.xz * ${g};
              if (j + 1 < ${t}) {
                flattenedIndex += index.yw * ${y};
              }
            }
            if (flattenedIndex[0] == coords[0] || flattenedIndex[1] == coords[0] ||
                flattenedIndex[0] == coords[0] + 1 || flattenedIndex[1] == coords[0] + 1) {
              vec4 updVals = ${h};
              if (flattenedIndex[0] == coords[0]) {
                sum.xy += updVals.xy;
                found.xy = vec2(1.);
              } else if (flattenedIndex[0] == coords[0] + 1) {
                sum.zw += updVals.xy;
                found.zw = vec2(1.);
              }
              if (flattenedIndex[1] == coords[0]) {
                sum.xy += updVals.zw;
                found.xy = vec2(1.);
              } else if (flattenedIndex[1] == coords[0] + 1) {
                sum.zw += updVals.zw;
                found.zw = vec2(1.);
              }
            }
          }
          setOutput(mix(${f}, sum, found));
        }
      `}};function eee(e){let{inputs:t,backend:a,attrs:n}=e,{indices:r,updates:s}=t,{shape:i}=n,{sliceRank:o,numUpdates:l,sliceSize:u,strides:p,outputSize:c}=C.calculateShapes(s,r,i),d=[c/u,u];if(c===0)return a.makeTensorInfo(i,r.dtype);let h=pe({inputs:{x:r},backend:a,attrs:{shape:[l,o]}}),m=pe({inputs:{x:s},backend:a,attrs:{shape:[l,u]}}),f=a.makeTensorInfo([],"float32",new Float32Array([0])),g;B().getBool("WEBGL_PACK")?g=new QQ(l,o,h.shape.length,m.shape.length,p,d):g=new B3(l,o,h.shape.length,m.shape.length,p,d);let y=a.runWebGLProgram(g,[m,h,f],m.dtype),x=pe({inputs:{x:y},backend:a,attrs:{shape:i}});return a.disposeIntermediateTensorInfo(h),a.disposeIntermediateTensorInfo(m),a.disposeIntermediateTensorInfo(y),a.disposeIntermediateTensorInfo(f),x}var tee={kernelName:_o,backendName:"webgl",kernelFunc:eee},aee=class{constructor(e,t,a,n){this.variableNames=["sortedSequence","values"],this.customUniforms=[{name:"numInputs",type:"int"}],this.outputShape=[e,a];let r="while (left < right) {",s=`for (int i = 0; i < ${Math.ceil(Math.log2(t+1))}; ++i) { if (left >= right) break;`,i=B().getNumber("WEBGL_VERSION")===2?r:s,o=n==="left"?"<":"<=";this.userCode=`
       int findBound(int batch, float value) {
         int left = 0;
         int right = numInputs;
         int mid;
         ${i}
           mid = (left + right) / 2;
           if (getSortedSequence(batch, mid) ${o} value) {
             left = mid + 1;
           } else {
             right = mid;
           }
         }
         return right;
       }

       void main() {
         ivec2 coords = getOutputCoords();
         int batch = coords[0];
         int valueIndex = coords[1];

         float value = getValues(batch, valueIndex);

         setOutput(float(findBound(batch, value)));
       }
     `}};function nee(e){let{inputs:t,backend:a,attrs:n}=e,{sortedSequence:r,values:s}=t,{side:i}=n,o=new aee(r.shape[0],r.shape[1],s.shape[1],i),l=[[r.shape[1]]];return a.runWebGLProgram(o,[r,s],"int32",l)}var ree={kernelName:Do,backendName:"webgl",kernelFunc:nee},see=class{constructor(e,t,a){this.variableNames=["c","a","b"],this.outputShape=t;let n,r;if(a>4)throw Error(`Where for rank ${a} is not yet supported`);if(a===1)r="resRC",n="resRC";else{let i=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[],l=[];for(let u=0;u<t.length;u++)l.push(`${i[u]}`),u<e&&o.push(`${i[u]}`);n=o.join(),r=l.join()}let s=ft(a);this.userCode=`
      void main() {
        ${s} resRC = getOutputCoords();
        float cVal = getC(${n});
        if (cVal >= 1.0) {
          setOutput(getA(${r}));
        } else {
          setOutput(getB(${r}));
        }
      }
    `}};function iee(e){let{inputs:t,backend:a}=e,{condition:n,t:r,e:s}=t,i=new see(n.shape.length,r.shape,r.shape.length);return a.runWebGLProgram(i,[n,r,s],ca(r.dtype,s.dtype))}var oee={kernelName:Pu,backendName:"webgl",kernelFunc:iee},lee=`
  // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
  // see: https://arxiv.org/abs/1706.02515
  float scaleAlpha = ${C.SELU_SCALEALPHA};
  float scale = ${C.SELU_SCALE};
  return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
`,uee=tt({opSnippet:lee}),dee={kernelName:Oo,backendName:"webgl",kernelFunc:uee},pee=Qu+`
  return 1.0 / (1.0 + exp(-1.0 * x));
`,cee=`
  vec4 result = 1.0 / (1.0 + exp(-1.0 * x));
  bvec4 isNaN = isnan(x);

  result.r = isNaN.r ? x.r : result.r;
  result.g = isNaN.g ? x.g : result.g;
  result.b = isNaN.b ? x.b : result.b;
  result.a = isNaN.a ? x.a : result.a;

  return result;
`,hee=tt({opSnippet:pee,packedOpSnippet:cee,cpuKernelImpl:dj}),mee={kernelName:Bo,backendName:"webgl",kernelFunc:hee},fee=`
  if (isnan(x)) { return 0.0; }
  return sign(x);
`,gee=tt({opSnippet:fee}),yee={kernelName:Wo,backendName:"webgl",kernelFunc:gee},xee=Qu+`
  return sin(x);
`,Aee=`
  vec4 result = sin(x);
  bvec4 isNaN = isnan(x);
  ${il}
  return result;
`,bee=tt({opSnippet:xee,packedOpSnippet:Aee}),vee={kernelName:zo,backendName:"webgl",kernelFunc:bee},wee=`
  float e2x = exp(x);
  return (e2x - 1.0 / e2x) / 2.0;
`,kee=tt({opSnippet:wee}),Iee={kernelName:Lo,backendName:"webgl",kernelFunc:kee},See=`
  float epsilon = 1.1920928955078125e-7;
  float threshold = log(epsilon) + 2.0;

  bool too_large = x > -threshold;
  bool too_small = x < threshold;

  float result;
  float exp_x = exp(x);

  if (too_large){
    result = x;
  }
  else if (too_small){
    result = exp_x;
  }
  else{
    result = log(exp_x + 1.0);
  }
  return result;
`,Cee=tt({opSnippet:See}),Tee={kernelName:Vo,backendName:"webgl",kernelFunc:Cee},Nee=e=>{let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockShape:s,paddings:i}=n;v.assert(r.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((y,x)=>y*x),l=[[0,0]];l.push(...i);for(let y=1+s.length;y<r.shape.length;++y)l.push([0,0]);let u=[],p=H8({inputs:{x:r},backend:a,attrs:{paddings:l,constantValue:0}}),c=C.getReshaped(p.shape,s,o,!1),d=C.getPermuted(c.length,s.length,!1),h=C.getReshapedPermuted(p.shape,s,o,!1),m=pe({inputs:{x:p},backend:a,attrs:{shape:c}}),f=Ca({inputs:{x:m},backend:a,attrs:{perm:d}}),g=pe({inputs:{x:f},backend:a,attrs:{shape:h}});return u.push(p),u.push(m),u.push(f),u.forEach(y=>a.disposeIntermediateTensorInfo(y)),g},Ree={kernelName:Fu,backendName:"webgl",kernelFunc:Nee};function Eee(e){let{inputs:t,backend:a}=e,{indices:n,values:r,denseShape:s,defaultValue:i}=t;if(s.shape.length!==1)throw new Error(`Dense shape must be a vector, saw:
         ${s.shape}`);if(n.shape.length!==2)throw new Error(`Indices must be a matrix, saw:
         ${n.shape}`);if(r.shape.length!==1)throw new Error(`Values must be a vector, saw:
         ${r.shape}`);if(i.shape.length!==0)throw new Error(`Default value must be a scalar, saw:
        ${i.shape}`);let o=a.readSync(n.dataId),l=a.readSync(r.dataId),u=a.readSync(s.dataId),p=a.readSync(i.dataId)[0],[c,d,h,m,f]=cj(o,n.shape,n.dtype,l,r.dtype,u,p);return[a.makeTensorInfo(d,n.dtype,c),a.makeTensorInfo([d[0]],r.dtype,h),a.makeTensorInfo([m.length],"bool",new Uint8Array(m.map(g=>Number(g)))),a.makeTensorInfo([f.length],n.dtype,new Int32Array(f))]}var Mee={kernelName:Sp,backendName:"webgl",kernelFunc:Eee};function $ee(e){let{inputs:t,backend:a}=e,{inputIndices:n,inputShape:r,newShape:s}=t;if(n.shape.length!==2)throw new Error(`Input indices should be a matrix but received shape ${n.shape}`);if(r.shape.length!==1)throw new Error(`Input shape should be a vector but received shape ${r.shape}`);if(s.shape.length!==1)throw new Error(`Target shape should be a vector but received shape ${s.shape}`);let i=Array.from(a.readSync(r.dataId)),o=a.readSync(n.dataId),l=Array.from(a.readSync(s.dataId)),[u,p,c]=hj(o,n.shape,n.dtype,i,l);return[a.makeTensorInfo(p,n.dtype,u),a.makeTensorInfo([c.length],s.dtype,new Int32Array(c))]}var Pee={kernelName:Ou,backendName:"webgl",kernelFunc:$ee};function _ee(e){let{inputs:t,backend:a}=e,{data:n,indices:r,segmentIds:s}=t;if(n.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(r.shape.length!==1)throw new Error(`Indices should be a vector but received shape
              ${r.shape}`);if(s.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
              ${s.shape}`);let i=a.readSync(n.dataId),o=a.readSync(r.dataId),l=a.readSync(s.dataId),[u,p]=m8(i,n.shape,n.dtype,o,l,!0);return a.makeTensorInfo(p,n.dtype,u)}var Fee={kernelName:zu,backendName:"webgl",kernelFunc:_ee};function Dee(e){let{inputs:t,backend:a}=e,{data:n,indices:r,segmentIds:s}=t;if(n.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(r.shape.length!==1)throw new Error(`Indices should be a vector but received shape
             ${r.shape}`);if(s.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
             ${s.shape}`);let i=a.readSync(n.dataId),o=a.readSync(r.dataId),l=a.readSync(s.dataId),[u,p]=m8(i,n.shape,n.dtype,o,l);return a.makeTensorInfo(p,n.dtype,u)}var Oee={kernelName:Lu,backendName:"webgl",kernelFunc:Dee};function zee(e){let{inputs:t,backend:a,attrs:n}=e,{sparseIndices:r,sparseValues:s,defaultValue:i}=t,{outputShape:o}=n,{sliceRank:l,numUpdates:u,sliceSize:p,strides:c,outputSize:d}=C.calculateShapes(s,r,o),h=!1;if(s.dtype==="string"){let y=a.bufferSync(r),x=a.bufferSync(s),A=v.decodeString(a.readSync(i.dataId)[0]),b=uj(y,x,o,d,p,u,l,c,A,h);return a.makeTensorInfo(o,b.dtype,b.values)}let m=new B3(u,l,r.shape.length,s.shape.length,c,[d,1],h),f=a.runWebGLProgram(m,[s,r,i],s.dtype),g=pe({inputs:{x:f},backend:a,attrs:{shape:o}});return a.disposeIntermediateTensorInfo(f),g}var Lee={kernelName:jo,backendName:"webgl",kernelFunc:zee};function Wee(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{numOrSizeSplits:s,axis:i}=n,o=v.parseAxisParam(i,r.shape)[0],l=C.prepareSplitSize(r,s,o),u=r.shape.length,p=new Array(u).fill(0),c=r.shape.slice();return l.map(d=>{let h=[...c];h[o]=d;let m=ed({inputs:{x:r},backend:a,attrs:{begin:p,size:h}});return p[o]+=d,m})}var Bee={kernelName:Du,backendName:"webgl",kernelFunc:Wee},j5="return sqrt(x);",Vee=tt({opSnippet:j5,packedOpSnippet:j5,cpuKernelImpl:mj}),Uee={kernelName:Uo,backendName:"webgl",kernelFunc:Vee},Gee="return x * x;",Hee=tt({opSnippet:Gee}),jee={kernelName:Cp,backendName:"webgl",kernelFunc:Hee},q5="return (a - b) * (a - b);",qee=ma({opSnippet:q5,packedOpSnippet:q5}),Xee={kernelName:qo,backendName:"webgl",kernelFunc:qee};function Kee(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t;if(r.dtype!=="string")throw new Error("Input must be of datatype string");let s=a.readSync(r.dataId),i=C.fromUint8ToStringArray(s),o=fj(i,"string",n);return a.makeTensorInfo(r.shape,"string",o)}var Yee={kernelName:Tp,backendName:"webgl",kernelFunc:Kee};function Zee({inputs:e,attrs:t,backend:a}){let{x:n}=e,r=Mn+`
    return x > 0.0 ? 1.0 : float(${t.alpha});
  `,s=new Jn(n.shape,r);return a.runWebGLProgram(s,[n],n.dtype)}var Jee={kernelName:ps,backendName:"webgl",kernelFunc:Zee},Qee=class{constructor(e,t,a){this.variableNames=["x"],this.outputShape=a;let n=a.length,r=ft(a.length),s=ft(a.length),i="";if(n===1)i="coords * strides + begin";else{let o=0;i=a.map((l,u)=>(o++,a.length===1?`coords * strides[${u}] + begin[${u}]`:`coords[${o-1}] * strides[${u}] + begin[${u}]`)).join(",")}this.userCode=`
      ${r} begin = ${r}(${e});
      ${r} strides = ${r}(${t});

      void main() {
        ${s} coords = getOutputCoords();
        setOutput(getX(${i}));
      }
    `}};function ete(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{begin:s,end:i,strides:o,beginMask:l,endMask:u,ellipsisMask:p,newAxisMask:c,shrinkAxisMask:d}=n,{finalShapeSparse:h,finalShape:m,isIdentity:f,sliceDim0:g,isSimpleSlice:y,begin:x,end:A,strides:b}=Nt.sliceInfo(r.shape,s,i,o,l,u,p,c,d),w;if(f)w=pe({inputs:{x:r},backend:a,attrs:{shape:m}});else if(g||y){v.assert(r.shape.length>=1,()=>`Input must have rank at least 1, got: ${r.shape.length}`);let T=Nt.computeOutShape(x,A,b),N=ed({inputs:{x:r},backend:a,attrs:{begin:x,size:T}});w=pe({inputs:{x:N},backend:a,attrs:{shape:m}}),a.disposeIntermediateTensorInfo(N)}else if(a.shouldExecuteOnCPU([r])){let T=a.readSync(r.dataId),N=_e(r.shape,r.dtype,T),M=gj(h,N,b,x);w=a.makeTensorInfo(m,r.dtype,M.values)}else{let T=new Qee(x,b,h);w=a.runWebGLProgram(T,[r],r.dtype)}let I=pe({inputs:{x:w},backend:a,attrs:{shape:m}});return a.disposeIntermediateTensorInfo(w),I}var tte={kernelName:Xo,backendName:"webgl",kernelFunc:ete};function ate(e){let{inputs:t,backend:a,attrs:n}=e,{separator:r,nGramWidths:s,leftPad:i,rightPad:o,padWidth:l,preserveShortSequences:u}=n,{data:p,dataSplits:c}=t,d=a.readSync(p.dataId),h=a.readSync(c.dataId),[m,f]=yj(d,h,r,s,i,o,l,u);return[a.makeTensorInfo([m.length],"string",m),a.makeTensorInfo(c.shape,"int32",f)]}var nte={kernelName:Wu,backendName:"webgl",kernelFunc:ate};function rte(e){let{inputs:t,backend:a,attrs:n}=e,{skipEmpty:r}=n,{input:s,delimiter:i}=t;if(s.dtype!=="string")throw new Error("Input must be of datatype string");if(s.shape.length!==1)throw new Error(`Input must be a vector, got shape: ${s.shape}`);if(i.shape.length!==0)throw new Error(`Delimiter must be a scalar, got shape: ${i.shape}`);let o=a.readSync(s.dataId),l=a.readSync(i.dataId)[0],[u,p,c]=xj(o,l,r),d=p.length;return[a.makeTensorInfo([d,2],"int32",u),a.makeTensorInfo([d],"string",p),a.makeTensorInfo([2],"int32",new Int32Array(c))]}var ste={kernelName:Np,backendName:"webgl",kernelFunc:rte};function ite(e){let{inputs:t,backend:a,attrs:n}=e,{numBuckets:r}=n,{input:s}=t;if(s.dtype!=="string")throw new Error("Input must be of datatype string");if(r<=0)throw new Error("Number of buckets must be at least 1");let i=a.readSync(s.dataId),o=Aj(i,r);return a.makeTensorInfo(s.shape,"int32",o)}var ote={kernelName:Rp,backendName:"webgl",kernelFunc:ite},lte="return tan(x);",ute=tt({opSnippet:lte}),dte={kernelName:Yo,backendName:"webgl",kernelFunc:ute},pte=`
  float e2x = exp(-2.0 * abs(x));
  return sign(x) * (1.0 - e2x) / (1.0 + e2x);
`,cte=tt({opSnippet:pte}),hte={kernelName:Zo,backendName:"webgl",kernelFunc:cte};function mte(e){let{inputs:t,backend:a,attrs:n}=e,{tensor:r,indices:s,updates:i}=t,{}=n,{sliceRank:o,numUpdates:l,sliceSize:u,strides:p,outputSize:c}=C.calculateShapes(i,s,r.shape),d=[c/u,u];if(c===0)return a.makeTensorInfo(r.shape,s.dtype);let h=pe({inputs:{x:s},backend:a,attrs:{shape:[l,o]}}),m=pe({inputs:{x:i},backend:a,attrs:{shape:[l,u]}}),f=pe({inputs:{x:r},backend:a,attrs:{shape:d}}),g=new B3(l,o,h.shape.length,m.shape.length,p,d,!1,!0),y=a.runWebGLProgram(g,[m,h,f],f.dtype),x=pe({inputs:{x:y},backend:a,attrs:{shape:r.shape}});return a.disposeIntermediateTensorInfo(h),a.disposeIntermediateTensorInfo(m),a.disposeIntermediateTensorInfo(f),a.disposeIntermediateTensorInfo(y),x}var fte={kernelName:Fo,backendName:"webgl",kernelFunc:mte},gte=class{constructor(e,t){this.variableNames=["A"];let a=new Array(e.length);for(let s=0;s<a.length;s++)a[s]=e[s]*t[s];this.outputShape=a,this.rank=a.length;let n=ft(this.rank),r=yte(e);this.userCode=`
      void main() {
        ${n} resRC = getOutputCoords();
        setOutput(getA(${r}));
      }
    `}};function yte(e){let t=e.length;if(t>5)throw Error(`Tile for rank ${t} is not yet supported`);if(t===1)return`imod(resRC, ${e[0]})`;let a=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],n=[];for(let r=0;r<e.length;r++)n.push(`imod(${a[r]}, ${e[r]})`);return n.join()}function q8(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{reps:s}=n;if(r.dtype==="string"||r.shape.length>5){let o=a.readSync(r.dataId),l=r.dtype==="string"?o.map(c=>v.decodeString(c)):o,u=_e(r.shape,r.dtype,l),p=vj(u,s);return a.makeTensorInfo(p.shape,p.dtype,p.values)}let i=new gte(r.shape,s);return a.runWebGLProgram(i,[r],r.dtype)}var xte={kernelName:ds,backendName:"webgl",kernelFunc:q8},Ate=class{constructor(e){this.variableNames=["x","indices"],this.customUniforms=[{name:"n",type:"int"},{name:"firstPass",type:"int"},{name:"negativeInf",type:"float"},{name:"dir",type:"int"},{name:"inc",type:"int"}],this.outputShape=e,this.userCode=`
       void main() {
         ivec2 coords = getOutputCoords();
         int batch = coords[0];
         int elemIdx = coords[1];

         // We compare elements pair-wise within a group of size 2 * inc.
         // The comparing rule for each group alternates between ascending
         // and descending. Within each group, we compare each pair at
         // positions i and i+inc. To decide whether an element at position i
         // is x0 or x1, we mod it by 2 * inc, if the result is smaller than
         // inc, it is in the first half of the group, we denote it as x0,
         // otherwise we denote it as x1.
         // For example, as shown in the Bitonic top K paper referenced above,
         // Figure5(a) shows that element[1] is in the
         // second half of the group when group size is 2, but it is in the
         // first half of the group when group size is 4.

         bool isFirstInPair = imod(elemIdx, 2 * inc) < inc;
         int i = isFirstInPair ? elemIdx : elemIdx - inc;

         int i0 = firstPass == 1 ? i : int(getIndices(batch, i));
         int i1 = firstPass == 1 ? i + inc : int(getIndices(batch, i + inc));
         float x0 = i0 < n ? getX(batch, i0) : negativeInf;
         float x1 = i1 < n ? getX(batch, i1) : negativeInf;

         // Denotes which direction indices are in (ascending or descending).
         bool reverse = imod(elemIdx, 2 * dir) >= dir;
         bool isGreater = x0 > x1 || (x0 == x1 && i1 > i0);
         if (reverse == isGreater) { // Elements in opposite order of direction
           int iTemp = i0;
           i0 = i1;
           i1 = iTemp;
         }
         if (isFirstInPair) {
            setOutput(float(i0));
         } else {
            setOutput(float(i1));
         }
       }
     `}},bte=class{constructor(e){this.variableNames=["x","indices"],this.customUniforms=[{name:"n",type:"int"},{name:"firstPass",type:"int"},{name:"k",type:"int"}],this.outputShape=e,this.userCode=`
    void main() {
         // Takes max of indices (0, k), (1, k + 1), (2, k + 2) ...
         ivec2 coords = getOutputCoords();
         int batch = coords[0];
         int elemIdx = coords[1];

         // The output size is half of the previous size.
         // If the previous sequence is | | | | _ _ _ _  | | | |  _ _ _ _ (k=4),
         // we only need to output the indices at positions |, the indices at
         // positions _ can be thrown away, see Figure5(b) After Phase 2
         // (Merge phase) in the Bitonic Top K paper referenced above.
         // For example, the paper shows we only need to output the orange bars.
         // The output sequence should look like this | | | | | | | |.
         // Because the sequence is halved, to map the output index back
         // to the previous sequence to find the corresponding value,
         // we need to double the index. When we double the index,
         // we basically interpolate a position, so 2i looks like
         // | _ | _ | _ | _ | _ | _ | _. We move the | to the first k position
         // of each 2k positions by - elemIdx % k. E.g. for output at
         // index 4,5,6,7, we want to get the corresponding element at
         // original index 8,9,10,11, for output at index 8,9,10,11,
         // we want to get the corresponding element at original index
         // 16,17,18,19, so on and so forth.

         int i = elemIdx < k ? elemIdx : (elemIdx * 2 - imod(elemIdx, k));
         int i0 = firstPass == 1 ? i : int(getIndices(batch, i));
         int i1 = firstPass == 1 ? i + k : int(getIndices(batch, i + k));

         float x0 = getX(batch, i0);
         float x1 = i1 < n ? getX(batch, i1) : x0;

         setOutput(x0 >= x1 ? float(i0) : float(i1));
       }
     `}};function zs(e,t){t!==null&&e.disposeIntermediateTensorInfo(t)}function X5(e){let t=1;for(;t<e;)t*=2;return t}function vte(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{k:s,sorted:i}=n,o=B().getNumber("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD"),l=B().getNumber("TOPK_K_CPU_HANDOFF_THRESHOLD"),u=r.shape,p=u[u.length-1];if(a.shouldExecuteOnCPU([r])||p<o||s>l){let M=a.readSync(r.dataId),[$,E]=wj(M,u,r.dtype,s,i);return[a.makeTensorInfo($.shape,$.dtype,$.values),a.makeTensorInfo(E.shape,E.dtype,E.values)]}if(s===0)return u[u.length-1]=0,[a.makeTensorInfo(u,r.dtype,[]),a.makeTensorInfo(u,"int32",[])];if(p===1)return[r,ec({attrs:{shape:u,dtype:"int32",value:0},backend:a})];let c=a.texData.get(r.dataId),d=c!==null&&c.isPacked,h=d?a.unpackTensor(r):r,m=v.sizeFromShape(u)/p,f=pe({inputs:{x:h},attrs:{shape:[m,p]},backend:a});d&&zs(a,h);let g=X5(s),y=X5(p),x=null,A=()=>x===null?[f,f]:[f,x],b=(M,$,E)=>{let S=A(),_=new Ate(E),O=[[p],[x===null?1:0],[Number.NEGATIVE_INFINITY],[M],[$]],W=x;x=a.runWebGLProgram(_,S,"int32",O),zs(a,W)};for(let M=1;M<g;M*=2){let $=M*2;for(let E=M;E>=1;E/=2)b($,E,[m,y])}for(let M=y;M>g;M/=2){let $=A(),E=new bte([m,M/2]),S=[[p],[x===null?1:0],[g]],_=x;x=a.runWebGLProgram(E,$,"int32",S),zs(a,_);let O=g/2,W=O*2;for(let P=O;P>=1;P/=2)b(W,P,x.shape)}let w=x;x=ed({inputs:{x},backend:a,attrs:{begin:0,size:[m,s]}}),zs(a,w);let I=L8({inputs:{x:f,indices:x},backend:a,attrs:{axis:1,batchDims:1}});zs(a,f);let T=u.slice(0,-1);T.push(s),w=x,x=pe({inputs:{x},attrs:{shape:T},backend:a}),zs(a,w);let N=I;return I=pe({inputs:{x:I},attrs:{shape:T},backend:a}),zs(a,N),[I,x]}var wte={kernelName:Jo,backendName:"webgl",kernelFunc:vte},kte=class{constructor(e,t,a,n,r,s){this.variableNames=["Image","Transforms"],this.outputShape=s;let i=a==="nearest"?1:2,o;switch(n){case"constant":o=1;break;case"reflect":o=2;break;case"wrap":o=3;break;case"nearest":o=4;break;default:o=1;break}this.userCode=`
            float mapCoord(float outCoord, float len) {
              float inCoord = outCoord;
              if(${o} == 2) {
                if (inCoord < 0.0) {
                  if (len <= 1.0) {
                    inCoord = 0.0;
                  } else {
                    float sz2 = 2.0 * len;
                    if (inCoord < sz2) {
                      inCoord = sz2 * float(int(float(-inCoord / sz2))) +
                      inCoord;
                    }
                    inCoord = inCoord < -len ? inCoord + sz2 : -inCoord - 1.0;
                  }
                } else if (inCoord > len - 1.0) {
                  if (len <= 1.0) {
                    inCoord = 0.0;
                  } else {
                    float sz2 = 2.0 * len;
                    inCoord -= sz2 * float(int(float(inCoord / sz2)));
                    if (inCoord >= len) {
                      inCoord = sz2 - inCoord - 1.0;
                    }
                  }
                }
                return clamp(inCoord, 0.0, len - 1.0);
              } else if (${o} == 3) {
                if (inCoord < 0.0) {
                  if (len <= 1.0) {
                    inCoord = 0.0;
                  } else {
                    float sz = len - 1.0;
                    inCoord += len * (float(int(float(-inCoord / sz))) + 1.0);
                  }
                } else if (inCoord > len - 1.0) {
                  if (len <= 1.0) {
                    inCoord = 0.0;
                  } else {
                    float sz = len - 1.0;
                    inCoord -= len * float(int(float(inCoord / sz)));
                  }
                }
                return clamp(inCoord, 0.0, len - 1.0);
              } else if (${o} == 4) {
                return clamp(outCoord, 0.0, len - 1.0);
              } else {
                return outCoord;
              }
            }

            float readWithFillValue(int batch, int coordY, int coordX,
              int channel) {
              float outputValue;
              if (0 <= coordY && coordY < ${e} && 0 <= coordX && coordX < ${t}) {
                  outputValue = getImage(batch, coordY, coordX, channel);
              } else {
                outputValue = float(${r});
              }
              return outputValue;
            }

            void main() {
              ivec4 coords = getOutputCoords();
              float outputValue;
              int batch = coords[0];
              int x = coords[2];
              int y = coords[1];
              int channel = coords[3];
              float xf = float(x);
              float yf = float(y);
              float a1 = getTransforms(batch, 0);
              float a2 = getTransforms(batch, 1);
              float a3 = getTransforms(batch, 2);
              float b1 = getTransforms(batch, 3);
              float b2 = getTransforms(batch, 4);
              float b3 = getTransforms(batch, 5);
              float c1 = getTransforms(batch, 6);
              float c2 = getTransforms(batch, 7);
              float projection = c1 * xf + c2 * yf + 1.0;
              if (projection == 0.0) {
                outputValue = float(${r});
              } else {
                float inX = (a1 * xf + a2 * yf + a3) / projection;
                float inY = (b1 * xf + b2 * yf + b3) / projection;
                float mapX = mapCoord(inX, float(${t}));
                float mapY = mapCoord(inY, float(${e}));

                if (${i} == 1) {
                  int coordY = int(round(mapY));
                  int coordX = int(round(mapX));
                  outputValue = readWithFillValue(batch, coordY, coordX,
                    channel);
                } else {
                  float yFloor = floor(mapY);
                  float xFloor = floor(mapX);
                  float yCeil = yFloor + 1.0;
                  float xCeil = xFloor + 1.0;
                  float valueYFloor = (xCeil - mapX) *
                  readWithFillValue(batch, int(yFloor), int(xFloor), channel) +
                  (mapX - xFloor) *
                  readWithFillValue(batch, int(yFloor), int(xCeil), channel);
                  float valueYCeil = (xCeil - mapX) *
                  readWithFillValue(batch, int(yCeil), int(xFloor), channel) +
                  (mapX - xFloor) *
                  readWithFillValue(batch, int(yCeil), int(xCeil), channel);
                  outputValue = (yCeil - mapY) * valueYFloor +
                  (mapY - yFloor) * valueYCeil;
                }
              }
              setOutput(outputValue);
            }
        `}};function Ite(e){let{inputs:t,backend:a,attrs:n}=e,{image:r,transforms:s}=t,{interpolation:i,fillMode:o,fillValue:l,outputShape:u}=n,[p,c,d,h]=r.shape,[m,f]=u!=null?u:[c,d],g=[p,m,f,h],y=new kte(c,d,i,o,l,g);return a.runWebGLProgram(y,[r,s],"float32")}var Ste={kernelName:Qo,backendName:"webgl",kernelFunc:Ite};function Cte(e){let{inputs:t,attrs:a,backend:n}=e,{axis:r}=a,{x:s}=t;qu(s,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");let i=n.readSync(s.dataId),{outputValues:o,outputShape:l,indices:u}=kj(i,r,s.shape,s.dtype);return[n.makeTensorInfo(l,s.dtype,o),n.makeTensorInfo([u.length],"int32",u)]}var Tte={kernelName:Ep,backendName:"webgl",kernelFunc:Cte};function Nte(e){let{inputs:t,backend:a,attrs:n}=e,{value:r}=t,{axis:s}=n;s<0&&(s+=r.shape.length);let i=r,o=i.shape.length,l=r.shape[s],u=new Array(o-1),p=0;for(let f=0;f<o;f++)f!==s&&(u[p++]=i.shape[f]);let c=[],d=new Array(o).fill(0),h=i.shape.slice();h[s]=1;let m=new Array(l);for(let f=0;f<m.length;f++){d[s]=f;let g=ed({inputs:{x:i},backend:a,attrs:{begin:d,size:h}}),y=pe({inputs:{x:g},backend:a,attrs:{shape:u}});m[f]=y,c.push(g)}return c.forEach(f=>a.disposeIntermediateTensorInfo(f)),m}var Rte={kernelName:Bu,backendName:"webgl",kernelFunc:Nte},Ete=class{constructor(e,t){this.variableNames=["x","segmentIds"];let a=e.windowSize,n=e.batchSize,r=e.inSize,s=e.numSegments,i=s*Math.ceil(r/a);this.outputShape=[n,i];let o="0.0",l="sumValue",u=Math.floor(a/4)*4,p=a%4,c=`
        sumValue += dot(values, segFilter);
    `,d="";r%a>0&&(d=`
        if (inIdx < 0 || inIdx >= ${r}) {
          return initializationValue;
        }
      `);let h="";r%a>0&&(h=`
        if (inIdx < 0 || inIdx >= ${r}) {
          return -1.0;
        }
      `),this.userCode=`
      const float initializationValue = ${o};

      float getValue(int batch, int inIdx) {
        ${d}
        return getX(batch, inIdx);
      }

      float getSegmentIdAtIndex(int inIdx) {
        ${h}
        return getSegmentIds(inIdx);
      }

      void main() {
        ivec2 coords = getOutputCoords();
        int batch = coords[0];
        int outIdx = coords[1];
        int inOffset = int(floor(float(outIdx) / float(
          ${s})) * float(${a}));
        int currentSeg = int(mod(float(outIdx), float(${s})));

        float sumValue = 0.0;

        for (int i = 0; i < ${u}; i += 4) {
          int inIdx = inOffset + i;
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2),
            getValue(batch, inIdx + 3)
          );

          vec4 segFilter = vec4(
            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,
            int(getSegmentIdAtIndex(inIdx + 3)) == currentSeg ? 1 : 0
          );

          ${c}
        }

        int inIdx = inOffset + ${u};
        if (${p===1}) {
          vec4 values = vec4(
            getValue(batch, inIdx),
            initializationValue,
            initializationValue,
            initializationValue
          );

          int inIdxSeg = int(getSegmentIdAtIndex(inIdx));

          vec4 segFilter = vec4(
            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
            0,
            0,
            0
          );

          ${c}
        } else if (${p===2}) {
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            initializationValue,
            initializationValue
          );

          vec4 segFilter = vec4(
            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
              0,
              0
          );

          ${c}
        } else if (${p===3}) {
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2),
            initializationValue
          );

          vec4 segFilter = vec4(
            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,
            0
          );

          ${c}
        }
        setOutput(${l});
      }
    `}};function Mte(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,segmentIds:s}=t,{numSegments:i}=n,o=r.shape.length,l=[],u=0,p=C.getAxesPermutation([u],o),c=r;p!=null&&(c=Ca({inputs:{x:r},backend:a,attrs:{perm:p}}),l.push(c),u=C.getInnerMostAxes(1,o)[0]);let d=C.segment_util.computeOutShape(c.shape,u,i),h=v.sizeFromShape([c.shape[u]]),m=pe({inputs:{x:c},backend:a,attrs:{shape:[-1,h]}});l.push(m);let f=_p(r.dtype),g=(b,w,I,T,N)=>{let M=b.shape[0],$=b.shape[1],E=C.segment_util.segOpComputeOptimalWindowSize($,N),S={windowSize:E,inSize:$,batchSize:M,numSegments:N},_=new Ete(S,w),O=a.compileAndRun(_,[b,I],T);if(l.push(O),O.shape[1]===N)return O;let W=j8({backend:a,attrs:{start:0,stop:N,step:1,dtype:"float32"}}),P=q8({inputs:{x:W},backend:a,attrs:{reps:[$/E]}});return l.push(W),l.push(P),g(O,w,P,T,N)},y=g(m,"unsortedSegmentSum",s,f,i),x=pe({inputs:{x:y},backend:a,attrs:{shape:d}}),A=x;if(p!=null){l.push(x);let b=C.getUndoAxesPermutation(p);A=Ca({inputs:{x:A},backend:a,attrs:{perm:b}})}return l.forEach(b=>a.disposeIntermediateTensorInfo(b)),A}var $te={kernelName:Mp,backendName:"webgl",kernelFunc:Mte},Pte=[gq,xq,vq,Iq,Cq,Rq,Mq,Pq,Oq,Lq,Vq,Hq,Xq,Jq,tX,nX,sX,uX,pX,hX,yX,IX,CX,EX,$X,zX,WX,GX,Qj,qX,JX,aK,lK,pK,hK,fK,yK,vK,IK,TK,RK,MK,PK,DK,zK,VK,GK,qK,YK,JK,aY,iY,dY,hY,gY,yY,AY,vY,kY,SY,TY,MY,_Y,OY,LY,VY,HY,KY,QY,Jj,tZ,YX,rZ,oZ,dZ,tq,mZ,xZ,bZ,IZ,TZ,MZ,_Z,zZ,VZ,HZ,qZ,ZZ,QZ,tJ,sJ,oJ,uJ,pJ,hJ,yJ,vJ,SJ,PJ,rq,OJ,WJ,UJ,jJ,_X,KJ,ZJ,QJ,aQ,iQ,nq,lQ,dQ,cQ,mQ,fQ,FX,RJ,xQ,wQ,CQ,iq,EQ,PQ,OQ,WQ,GQ,jQ,KQ,JQ,tee,ree,oee,dee,mee,yee,vee,Iee,wX,MJ,Tee,Ree,Mee,Pee,Fee,Oee,Lee,Bee,Uee,jee,Xee,Yee,Jee,tte,nte,ste,ote,EJ,hq,dte,hte,fte,xte,wte,Ste,mq,Tte,Rte,$te,YJ];for(let e of Pte)xn(e);var nt;(function(e){e[e.float32=0]="float32",e[e.int32=1]="int32",e[e.bool=2]="bool",e[e.string=3]="string",e[e.complex64=4]="complex64"})(nt||(nt={}));var rp;(function(e){e[e.linear=0]="linear",e[e.relu=1]="relu",e[e.relu6=2]="relu6",e[e.prelu=3]="prelu",e[e.leakyrelu=4]="leakyrelu",e[e.sigmoid=5]="sigmoid",e[e.elu=6]="elu"})(rp||(rp={}));var X8;function _te(e){X8=e.wasm.cwrap(Zr,null,["number","array","number","number","array","number","number","number","number","number","number","number","number"])}function Fte(e){let{inputs:t,backend:a,attrs:n}=e,{a:r,b:s,bias:i,preluActivationWeights:o}=t;if(r.dtype!=="float32"||s.dtype!=="float32")throw new Error("_FusedMatMul for non non-float32 tensors not yet supported.");let{transposeA:l,transposeB:u,activation:p,leakyreluAlpha:c}=n,d=a.dataIdMap.get(r.dataId).id,h=a.dataIdMap.get(s.dataId).id,m=0;if(i!=null){let N=a.dataIdMap.get(i.dataId);if(N.shape.length!==1)throw new Error(`_FusedMatMul only supports rank-1 bias but got rank ${N.shape.length}.`);m=N.id}let f=o==null?0:a.dataIdMap.get(o.dataId).id,g=rp[p];if(g==null)throw new Error(`${p} activation not yet supported for FusedConv2D in the wasm backend.`);let y=l?r.shape[2]:r.shape[1],x=u?s.shape[1]:s.shape[2],A=nl.assertAndGetBroadcastShape(r.shape.slice(0,-2),s.shape.slice(0,-2)),b=a.makeOutput([...A,y,x],r.dtype),w=a.dataIdMap.get(b.dataId).id,I=new Uint8Array(new Int32Array(r.shape).buffer),T=new Uint8Array(new Int32Array(s.shape).buffer);return X8(d,I,r.shape.length,h,T,s.shape.length,l,u,g,m,f,c||0,w),b}var Dte={kernelName:Zr,backendName:"wasm",setupFunc:_te,kernelFunc:Fte};function Qe(e,t){let a;function n(s){a=s.wasm.cwrap(e,null,["number","number","number"])}function r(s){let{backend:i,inputs:{x:o}}=s,l=i.dataIdMap.get(o.dataId).id,u=i.makeOutput(o.shape,t||o.dtype),p=i.dataIdMap.get(u.dataId).id;return v.sizeFromShape(u.shape)===0||a(l,nt[o.dtype],p),u}return{kernelName:e,backendName:"wasm",setupFunc:n,kernelFunc:r}}var Ote=Qe(ou),zte=Qe(oi),Lte=Qe(li);function Gt(e,t,a){let n;function r(i){n=i.wasm.cwrap(e,null,["number","array","number","number","array","number","number","number"])}function s(i){let{backend:o,inputs:l}=i,{a:u,b:p}=l,c=o.dataIdMap.get(u.dataId).id,d=o.dataIdMap.get(p.dataId).id,h=a!=null?a:u.dtype,m=C.assertAndGetBroadcastShape(u.shape,p.shape),f=o.makeOutput(m,h);if(v.sizeFromShape(m)===0)return f;let g=new Uint8Array(new Int32Array(u.shape).buffer),y=new Uint8Array(new Int32Array(p.shape).buffer),x=o.dataIdMap.get(f.dataId).id;return n(c,g,u.shape.length,d,y,p.shape.length,nt[u.dtype],x),f}return{kernelName:e,backendName:"wasm",setupFunc:r,kernelFunc:s}}var Wte=!0,Bte=Gt(ls,Wte),K8;function Vte(e){K8=e.wasm.cwrap(ui,null,["array","number","number","number"])}function Ute(e){let{inputs:t,backend:a}=e,n=a.makeOutput(t[0].shape,t[0].dtype);if(v.sizeFromShape(n.shape)===0)return n;let r=t.map(o=>a.dataIdMap.get(o.dataId).id),s=new Uint8Array(new Int32Array(r).buffer),i=a.dataIdMap.get(n.dataId).id;return K8(s,r.length,nt[n.dtype],i),n}var Gte={kernelName:ui,backendName:"wasm",setupFunc:Vte,kernelFunc:Ute};function l0(e){let{inputs:{x:t},backend:a}=e;if(t.dtype==="string")return Ve(a.readSync(t.dataId),t.shape,t.dtype);let n=a.makeOutput(t.shape,t.dtype),r=a.typedArrayFromHeap(t);return a.typedArrayFromHeap(n).set(r),n}var Hte={kernelName:qi,backendName:"wasm",kernelFunc:l0},Y8;function jte(e){Y8=e.wasm.cwrap(Ir,null,["number","array","number","number","number","array","number"])}function os(e){let{inputs:t,backend:a,attrs:n}=e,[r,s]=Xte(t.x.shape,n.perm),i=!0;for(let m=0;m<s.length;m++)s[m]!==m&&(i=!1);let o=qte(t.x.shape,n.perm),l={dataId:t.x.dataId,shape:r,dtype:t.x.dtype};if(i){let m=l0({inputs:t,backend:a});return m.shape=o,m}let u=a.makeOutput(o,l.dtype),p=a.dataIdMap.get(l.dataId).id,c=a.dataIdMap.get(u.dataId).id,d=new Uint8Array(new Int32Array(s).buffer),h=new Uint8Array(new Int32Array(l.shape).buffer);return Y8(p,h,l.shape.length,nt[l.dtype],c,d,s.length),u}function qte(e,t){let a=new Array(e.length);for(let n=0;n<a.length;n++)a[n]=e[t[n]];return a}function Xte(e,t){let a=[],n=[];for(let r=0;r<e.length;++r)e[r]!==1&&a.push(e[r]),e[t[r]]!==1&&n.push(t[r]);for(let r=0;r<n.length;++r){let s=-1;for(let i=0;i<n.length;++i)n[i]>=r&&(s===-1||n[s]>n[i])&&(s=i);n[s]=r}return[a,n]}var Kte={kernelName:Ir,backendName:"wasm",kernelFunc:os,setupFunc:jte};function gs(e,t,a){let n=e.shape,r=e.shape.length,s=v.parseAxisParam(t,n),i=s,o=C.getAxesPermutation(i,r),l=null,u=!1;if(o!=null){let p=new Array(r);for(let d=0;d<p.length;d++)p[d]=n[o[d]];i=C.getInnerMostAxes(i.length,r),l=os({inputs:{x:e},attrs:{perm:o},backend:a});let c=a.dataIdMap.get(e.dataId).id;a.dataIdMap.get(l.dataId).id!==c&&(u=!0)}return{transposed:l,originalAxes:s,axes:i,inputWasTransposed:u}}var Z8;function Yte(e){Z8=e.wasm.cwrap(di,null,["number, number, number"])}function Zte(e){let{backend:t,inputs:a,attrs:n}=e,{axis:r,keepDims:s}=n,{x:i}=a,o=t.dataIdMap.get(i.dataId).id,l=i,{transposed:u,axes:p,originalAxes:c,inputWasTransposed:d}=gs(i,r,t);if(d){let x=t.dataIdMap.get(u.dataId).id;l=u,o=x}let h=l.shape.length;C.assertAxesAreInnerMostDims("all",p,h);let[m,f]=C.computeOutAndReduceShapes(l.shape,p),g=v.sizeFromShape(f),y=t.makeOutput(m,i.dtype);if(v.sizeFromShape(l.shape)!==0){let x=t.dataIdMap.get(y.dataId).id;Z8(o,g,x)}if(d&&t.disposeData(u.dataId),s){let x=C.expandShapeToKeepDim(y.shape,c);y.shape=x}return y}var Jte={kernelName:di,backendName:"wasm",setupFunc:Yte,kernelFunc:Zte},J8;function Qte(e){J8=e.wasm.cwrap(pi,null,["number, number, number"])}function eae(e){let{backend:t,inputs:a,attrs:n}=e,{axis:r,keepDims:s}=n,{x:i}=a,o=t.dataIdMap.get(i.dataId).id,l=i,{transposed:u,axes:p,originalAxes:c,inputWasTransposed:d}=gs(i,r,t);if(d){let x=t.dataIdMap.get(u.dataId).id;l=u,o=x}let h=l.shape.length;C.assertAxesAreInnerMostDims("any",p,h);let[m,f]=C.computeOutAndReduceShapes(l.shape,p),g=v.sizeFromShape(f),y=t.makeOutput(m,i.dtype);if(v.sizeFromShape(l.shape)!==0){let x=t.dataIdMap.get(y.dataId).id;J8(o,g,x)}if(d&&t.disposeData(u.dataId),s){let x=C.expandShapeToKeepDim(y.shape,c);y.shape=x}return y}var tae={kernelName:pi,backendName:"wasm",setupFunc:Qte,kernelFunc:eae};function Q8(e){let t;function a(r){t=r.wasm.cwrap(e,null,["number","number","number","number","number"])}function n(r){let{backend:s,inputs:i,attrs:o}=r,{axis:l}=o,{x:u}=i,p=s.dataIdMap.get(u.dataId).id,c=p,d=u,{transposed:h,axes:m,inputWasTransposed:f}=gs(u,l,s);if(f){let w=s.dataIdMap.get(h.dataId).id;w!==p&&(d=h,c=w)}let g=d.shape.slice(0,-1),y=s.makeOutput(g,"int32"),x=s.dataIdMap.get(y.dataId).id,A=v.sizeFromShape(y.shape),b=d.shape[m[0]];return t(c,nt[d.dtype],A,b,x),f&&s.disposeData(h.dataId),y}return{kernelName:e,backendName:"wasm",setupFunc:a,kernelFunc:n}}var aae=Q8(lu),nae=Q8(uu),rae=Qe(ci),sae=Qe(hi),iae=Qe(mi),oae=Gt(gi,!1),lae=Qe(fi),ew;function uae(e){ew=e.wasm.cwrap(yi,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function dae(e){let{inputs:t,attrs:a,backend:n}=e,r=t.x,s=n.dataIdMap.get(r.dataId).id,{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=a,p=C.computePool2DInfo(r.shape,i,o,1,l,u),c=p.filterHeight,d=p.filterWidth,h=p.padInfo.top,m=p.padInfo.right,f=p.padInfo.bottom,g=p.padInfo.left,y=p.strideHeight,x=p.strideWidth,A=p.inChannels;if(p.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${p.dataFormat}'. Please use 'channelsLast'.`);if(p.dilationWidth!==1||p.dilationHeight!==1)throw new Error(`was backend only supports average pooling with dilation = [1, 1], got [${p.dilationHeight}, ${p.dilationWidth}].`);let b=n.makeOutput(p.outShape,"float32"),w=n.dataIdMap.get(b.dataId).id;return ew(s,r.shape[0],r.shape[1],r.shape[2],c,d,h,m,f,g,y,x,A,w),b}var pae={kernelName:yi,backendName:"wasm",setupFunc:uae,kernelFunc:dae},tw;function cae(e){tw=e.wasm.cwrap("AvgPool3D",null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function hae(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:u}=n,p=C.computePool3DInfo(r.shape,s,i,1,o,l,u),c=a.makeOutput(p.outShape,r.dtype);return tw(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(c.dataId).id,p.batchSize,p.inChannels,p.inDepth,p.inHeight,p.inWidth,p.outDepth,p.outHeight,p.outWidth,p.strideDepth,p.strideHeight,p.strideWidth,p.dilationDepth,p.dilationHeight,p.dilationWidth,p.effectiveFilterDepth,p.effectiveFilterHeight,p.effectiveFilterWidth,p.padInfo.front,p.padInfo.top,p.padInfo.left),c}var mae={kernelName:du,backendName:"wasm",setupFunc:cae,kernelFunc:hae},aw;function fae(e){aw=e.wasm.cwrap("AvgPool3DGrad",null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function gae(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=n,p=C.computePool3DInfo(s.shape,i,o,1,l,u),c=a.makeOutput(s.shape,s.dtype);return aw(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(c.dataId).id,p.batchSize,p.inChannels,p.inDepth,p.inHeight,p.inWidth,p.outDepth,p.outHeight,p.outWidth,p.strideDepth,p.strideHeight,p.strideWidth,p.dilationDepth,p.dilationHeight,p.dilationWidth,p.effectiveFilterDepth,p.effectiveFilterHeight,p.effectiveFilterWidth,p.padInfo.front,p.padInfo.top,p.padInfo.left,p.filterDepth,p.filterHeight,p.filterWidth),c}var yae={kernelName:pp,backendName:"wasm",setupFunc:fae,kernelFunc:gae},nw;function xae(e){nw=e.wasm.cwrap("AvgPoolGrad",null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Aae(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,{filterSize:i,strides:o,pad:l}=n,u=C.computePool2DInfo(s.shape,i,o,1,l),p=a.makeOutput(s.shape,s.dtype);return nw(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(p.dataId).id,u.batchSize,u.inChannels,u.inHeight,u.inWidth,u.outHeight,u.outWidth,u.strideHeight,u.strideWidth,u.dilationHeight,u.dilationWidth,u.effectiveFilterHeight,u.effectiveFilterWidth,u.padInfo.top,u.padInfo.left,u.filterHeight,u.filterWidth),p}var bae={kernelName:dp,backendName:"wasm",setupFunc:xae,kernelFunc:Aae};function La(e){let{inputs:t,attrs:a}=e,{x:n}=t,{shape:r}=a,s=v.sizeFromShape(n.shape),i=v.inferFromImplicitShape(r,s);return v.assert(s===v.sizeFromShape(i),()=>`new shape: ${i}, old shape: ${n.shape}. New shape and old shape must have the same number of elements.`),e.backend.incRef(n.dataId),{dataId:n.dataId,shape:i,dtype:n.dtype}}var vae={kernelName:Eu,backendName:"wasm",kernelFunc:La},rw;function wae(e){rw=e.wasm.cwrap(xi,null,["number","array","number","number","array","number","number","number","number"])}function kae(e){let{inputs:t,backend:a,attrs:n}=e,{a:r,b:s}=t,{transposeA:i,transposeB:o}=n;if(r.dtype!=="float32"||s.dtype!=="float32")throw new Error("BatchMatMul for non non-float32 tensors not yet supported.");let l=r.shape.length,u=s.shape.length,p=i?r.shape[l-2]:r.shape[l-1],c=o?s.shape[u-1]:s.shape[u-2],d=i?r.shape[l-1]:r.shape[l-2],h=o?s.shape[u-2]:s.shape[u-1],m=r.shape.slice(0,-2),f=s.shape.slice(0,-2),g=v.sizeFromShape(m),y=v.sizeFromShape(f),x=nl.assertAndGetBroadcastShape(r.shape.slice(0,-2),s.shape.slice(0,-2)).concat([d,h]);v.assert(p===c,()=>`Error in matMul: inner shapes (${p}) and (${c}) of Tensors with shapes ${r.shape} and ${s.shape} and transposeA=${i} and transposeB=${o} must match.`);let A=i?[g,p,d]:[g,d,p],b=o?[y,h,c]:[y,c,h],w=La({inputs:{x:r},backend:a,attrs:{shape:A}}),I=La({inputs:{x:s},backend:a,attrs:{shape:b}}),T=a.dataIdMap.get(w.dataId).id,N=a.dataIdMap.get(I.dataId).id,M=i?w.shape[2]:w.shape[1],$=o?I.shape[1]:I.shape[2],E=Math.max(g,y),S=a.makeOutput([E,M,$],w.dtype),_=a.dataIdMap.get(S.dataId).id,O=new Uint8Array(new Int32Array(w.shape).buffer),W=new Uint8Array(new Int32Array(I.shape).buffer);return rw(T,O,w.shape.length,N,W,I.shape.length,i,o,_),a.disposeData(w.dataId),a.disposeData(I.dataId),S.shape=x,S}var Iae={kernelName:xi,backendName:"wasm",setupFunc:wae,kernelFunc:kae};function si(e){let{inputs:{x:t},attrs:{begin:a,size:n},backend:r}=e,[s,i]=Nt.parseSliceParams(t,a,n),o=Nt.isSliceContinous(t.shape,s,i),l=r.readSync(t.dataId),u=r.makeOutput(i,t.dtype),p=v.computeStrides(t.shape),c=r.dataIdMap.get(u.dataId);if(o){let m=Nt.computeFlatOffset(s,p);return t.dtype==="string"?c.stringBytes=l.slice(m,m+v.sizeFromShape(i)):r.typedArrayFromHeap(u).set(l.subarray(m,m+v.sizeFromShape(i))),u}if(t.dtype==="string"){let m=Ah(l,s,i,t.shape,t.dtype);return c.stringBytes=m,u}let d=r.typedArrayFromHeap(u),h=t.shape.length;if(h===2)Sae(l,p[0],d,s,i);else if(h===3)Cae(l,p[0],p[1],d,s,i);else if(h===4)Tae(l,p[0],p[1],p[2],d,s,i);else{let m=Ah(l,s,i,t.shape,t.dtype);d.set(m)}return u}function Sae(e,t,a,n,r){let s=0,i=n[0],o=n[1],l=i+r[0];for(let u=i;u<l;u++){let p=u*t+o;a.set(e.subarray(p,p+r[1]),s),s+=r[1]}}function Cae(e,t,a,n,r,s){let i=0,o=r[0],l=r[1],u=r[2],p=o+s[0],c=l+s[1];for(let d=o;d<p;d++)for(let h=l;h<c;h++){let m=d*t+h*a+u;n.set(e.subarray(m,m+s[2]),i),i+=s[2]}}function Tae(e,t,a,n,r,s,i){let o=0,l=s[0],u=s[1],p=s[2],c=l+i[0],d=u+i[1],h=p+i[2],m=s[3];for(let f=l;f<c;f++)for(let g=u;g<d;g++)for(let y=p;y<h;y++){let x=f*t+g*a+y*n+m;r.set(e.subarray(x,x+i[3]),o),o+=i[3]}}var Nae={kernelName:_u,backendName:"wasm",kernelFunc:si};function Rae(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockShape:s,crops:i}=n,o=s.reduce((y,x)=>y*x),l=C.getReshaped(r.shape,s,o),u=C.getPermuted(l.length,s.length),p=C.getReshapedPermuted(r.shape,s,o),c=C.getSliceBeginCoords(i,s.length),d=C.getSliceSize(p,i,s.length),h=La({inputs:{x:r},backend:a,attrs:{shape:l}}),m=os({inputs:{x:h},backend:a,attrs:{perm:u}}),f=La({inputs:{x:m},backend:a,attrs:{shape:p}}),g=si({inputs:{x:f},backend:a,attrs:{begin:c,size:d}});return a.disposeData(h.dataId),a.disposeData(m.dataId),a.disposeData(f.dataId),g}var Eae={kernelName:pu,backendName:"wasm",kernelFunc:Rae},sw;function Mae(e){sw=e.wasm.cwrap(Ai,null,["number","number","boolean","number","number","number"])}function $ae(e){let{backend:t,inputs:a,attrs:n}=e,{x:r,weights:s}=a,{size:i}=n,o=s.shape.reduce((c,d)=>c*d,1)!==0,l=r.shape.length===1?[i]:[r.shape[0],i],u=t.makeOutput(l,s.dtype);function p(c){return t.dataIdMap.get(c.dataId).id}return sw(p(r),i,o,p(s),nt[s.dtype],p(u)),u}var Pae={kernelName:Ai,backendName:"wasm",setupFunc:Mae,kernelFunc:$ae},_ae=!0,Fae=Gt(cu,_ae);function Dae(e){let{inputs:t,backend:a}=e,{s0:n,s1:r}=t,s=a.typedArrayFromHeap(n),i=a.typedArrayFromHeap(r),o=C.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return a.makeOutput([o.length],"int32",void 0,new Int32Array(o))}var Oae={kernelName:hu,backendName:"wasm",kernelFunc:Dae};function ys(e){let{inputs:{x:t},attrs:{dtype:a},backend:n}=e,r=n.makeOutput(t.shape,a),s=n.typedArrayFromHeap(t);return n.typedArrayFromHeap(r).set(s),r}var zae={kernelName:bi,backendName:"wasm",kernelFunc:ys},Lae=Qe(vi),iw;function Wae(e){iw=e.wasm.cwrap(us,null,["number","number","number","number"])}function Bae(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{clipValueMin:s,clipValueMax:i}=n,o=a.dataIdMap.get(r.dataId).id,l=a.makeOutput(r.shape,r.dtype),u=a.dataIdMap.get(l.dataId).id;return iw(o,s,i,u),l}var Vae={kernelName:us,backendName:"wasm",setupFunc:Wae,kernelFunc:Bae};function ow(e){let{inputs:t,backend:a}=e,n=v.parseAxisParam(e.attrs.axis,t[0].shape)[0],r=t.map(h=>h.shape);C.assertParamsConsistent(r,n);let s=C.computeOutShape(t.map(h=>h.shape),n),i=t.filter(h=>v.sizeFromShape(h.shape)>0);if(i.length===1)return l0({inputs:{x:i[0]},backend:a});let o=a.makeOutput(s,t[0].dtype);if(v.sizeFromShape(s)===0)return o;if(i[0].dtype==="string"){let h=i.map(A=>{let b=[-1,v.sizeFromShape(A.shape.slice(n))];return La({inputs:{x:A},backend:a,attrs:{shape:b}})}),m=h.map(A=>({vals:a.readSync(A.dataId),shape:A.shape}));s=C.computeOutShape(h.map(A=>A.shape),1);let f=h[0].shape[0]===1,g=m3(m,s,t[0].dtype,f),y=C.computeOutShape(i.map(A=>A.shape),n);o.shape=y;let x=a.dataIdMap.get(o.dataId);return x.stringBytes=C.fromStringArrayToUint8(g),h.forEach(A=>a.disposeData(A.dataId)),o}let l=v.sizeFromShape(i[0].shape.slice(0,n)),u=0,p=i.map(h=>{let m=v.sizeFromShape(h.shape.slice(n));return u+=m,m}),c=i.map(h=>a.typedArrayFromHeap(h)),d=a.typedArrayFromHeap(o);for(let h=0;h<l;h++){let m=h*u;for(let f=0;f<c.length;f++){let g=p[f],y=h*g,x=c[f].subarray(y,y+g);d.set(x,m),m+=g}}return o}var Uae={kernelName:mu,backendName:"wasm",kernelFunc:ow},lw;function Gae(e){lw=e.wasm.cwrap(wi,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Hae(e){let{inputs:t,attrs:a,backend:n}=e,{x:r,filter:s}=t,i=n.dataIdMap.get(r.dataId).id,o=n.dataIdMap.get(s.dataId).id,{strides:l,dilations:u,pad:p,dimRoundingMode:c,dataFormat:d}=a,h=C.convertConv2DDataFormat(d),m=C.computeConv2DInfo(r.shape,s.shape,l,u,p,c,!1,h),f=m.filterHeight,g=m.filterWidth,y=m.padInfo.top,x=m.padInfo.right,A=m.padInfo.bottom,b=m.padInfo.left,w=m.dilationHeight,I=m.dilationWidth,T=m.strideHeight,N=m.strideWidth,M=m.inChannels,$=m.outChannels,E=m.padInfo.type==="SAME"?1:0;if(m.dataFormat!=="channelsLast")throw new Error(`wasm backend Conv2D does not support dataFormat:'${m.dataFormat}'. Please use 'channelsLast'.`);let S=n.makeOutput(m.outShape,"float32"),_=n.dataIdMap.get(S.dataId).id;return lw(i,r.shape[0],r.shape[1],r.shape[2],o,f,g,y,x,A,b,E,w,I,T,N,M,$,_),S}var jae={kernelName:wi,backendName:"wasm",setupFunc:Gae,kernelFunc:Hae},uw;function qae(e){uw=e.wasm.cwrap(ki,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Xae(e){let{backend:t,inputs:a,attrs:n}=e,{dy:r,filter:s}=a,{strides:i,pad:o,dataFormat:l,dimRoundingMode:u,inputShape:p}=n,c=1,d=C.convertConv2DDataFormat(l),h=C.computeConv2DInfo(p,s.shape,i,c,o,u,!1,d),{batchSize:m,filterHeight:f,filterWidth:g,inChannels:y,inHeight:x,inWidth:A,outChannels:b,outHeight:w,outWidth:I,strideHeight:T,strideWidth:N}=h,M=f-1-h.padInfo.top,$=g-1-h.padInfo.left,E=h.dataFormat==="channelsLast",S=v.computeStrides(h.inShape),_=v.computeStrides(r.shape),[O,W,P]=v.computeStrides(s.shape),U=S[0],G=E?S[1]:S[2],q=E?S[2]:1,H=E?1:S[1],V=_[0],Z=E?_[1]:_[2],X=E?_[2]:1,re=E?1:_[1],ee=t.makeOutput(h.inShape,"float32"),ge=t.dataIdMap.get(ee.dataId).id,ie=t.dataIdMap.get(r.dataId).id,be=t.dataIdMap.get(s.dataId).id;return uw(ie,be,m,f,g,x,A,y,w,I,b,T,N,M,$,O,W,P,U,G,q,H,V,Z,X,re,ge),ee}var Kae={kernelName:ki,backendName:"wasm",setupFunc:qae,kernelFunc:Xae},dw;function Yae(e){dw=e.wasm.cwrap(Ii,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Zae(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=n;if(r.dtype!=="float32")throw new Error(`Tensor x must have dtype float32, got ${r.dtype}`);if(s.dtype!=="float32")throw new Error(`Tensor filter must have dtype float32, got ${s.dtype}`);let u=C.computeConv3DInfo(r.shape,s.shape,i,l,o),p=a.makeOutput(u.outShape,r.dtype);return dw(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(s.dataId).id,a.dataIdMap.get(p.dataId).id,u.batchSize,u.inDepth,u.inHeight,u.inWidth,u.inChannels,u.outDepth,u.outHeight,u.outWidth,u.outChannels,u.strideDepth,u.strideHeight,u.strideWidth,u.dilationDepth,u.dilationHeight,u.dilationWidth,u.filterDepth,u.filterHeight,u.filterWidth,u.padInfo.front,u.padInfo.top,u.padInfo.left),p}var Jae={kernelName:Ii,backendName:"wasm",setupFunc:Yae,kernelFunc:Zae},pw;function Qae(e){pw=e.wasm.cwrap(fu,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function ene(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,dy:s}=t,{strides:i,pad:o,filterShape:l}=n;if(r.dtype!=="float32")throw new Error(`Tensor dy must have dtype float32, got ${r.dtype}`);if(s.dtype!=="float32")throw new Error(`Tensor filter must have dtype float32, got ${s.dtype}`);let u=C.computeConv3DInfo(r.shape,l,i,1,o),p=a.makeOutput(u.filterShape,s.dtype);return pw(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(s.dataId).id,a.dataIdMap.get(p.dataId).id,u.batchSize,u.inDepth,u.inHeight,u.inWidth,u.inChannels,u.outDepth,u.outHeight,u.outWidth,u.outChannels,u.strideDepth,u.strideHeight,u.strideWidth,u.dilationDepth,u.dilationHeight,u.dilationWidth,u.filterDepth,u.filterHeight,u.filterWidth,u.padInfo.front,u.padInfo.top,u.padInfo.left),p}var tne={kernelName:fu,backendName:"wasm",setupFunc:Qae,kernelFunc:ene},cw;function ane(e){cw=e.wasm.cwrap(Si,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function nne(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,filter:s}=t,{pad:i,strides:o,inputShape:l}=n;if(r.dtype!=="float32")throw new Error(`Tensor dy must have dtype float32, got ${r.dtype}`);if(s.dtype!=="float32")throw new Error(`Tensor filter must have dtype float32, got ${s.dtype}`);let u=C.computeConv3DInfo(l,s.shape,o,1,i),p=a.makeOutput(u.inShape,r.dtype);return cw(a.dataIdMap.get(s.dataId).id,a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(p.dataId).id,u.batchSize,u.inDepth,u.inHeight,u.inWidth,u.inChannels,u.outDepth,u.outHeight,u.outWidth,u.outChannels,u.strideDepth,u.strideHeight,u.strideWidth,u.dilationDepth,u.dilationHeight,u.dilationWidth,u.filterDepth,u.filterHeight,u.filterWidth,u.padInfo.front,u.padInfo.top,u.padInfo.left),p}var rne={kernelName:Si,backendName:"wasm",setupFunc:ane,kernelFunc:nne},sne=Qe(Ci),ine=Qe(Ti),V1;(function(e){e[e.bilinear=0]="bilinear",e[e.nearest=1]="nearest"})(V1||(V1={}));var hw;function one(e){hw=e.wasm.cwrap(Ei,null,["number","number","number","number","array","number","number","number","number","number"])}function lne(e){let{backend:t,inputs:a,attrs:n}=e,{method:r,extrapolationValue:s,cropSize:i}=n,{image:o,boxes:l,boxInd:u}=a,p=l.shape[0],[c,d]=i,h=[p,c,d,o.shape[3]],m=t.dataIdMap.get(o.dataId),f;o.dtype!=="float32"&&(f=ys({backend:t,inputs:{x:o},attrs:{dtype:"float32"}}),m=t.dataIdMap.get(f.dataId));let g=m.id,y=t.dataIdMap.get(l.dataId).id,x=t.dataIdMap.get(u.dataId).id,A=t.makeOutput(h,"float32"),b=t.dataIdMap.get(A.dataId).id,w=new Uint8Array(new Int32Array(o.shape).buffer);return hw(g,y,x,p,w,c,d,V1[r],s,b),f!=null&&t.disposeData(f.dataId),A}var une={kernelName:Ei,backendName:"wasm",setupFunc:one,kernelFunc:lne},mw;function dne(e){mw=e.wasm.cwrap(Ni,null,["number","number","number","number","number","number"])}function pne(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=n,l=r.shape.length;v.assert(r.dtype==="float32"||r.dtype==="int32",()=>`cumprod does not support ${r.dtype} tensors in the WASM backend`);let u=C.getAxesPermutation([s],l),p=r;u!==null&&(p=os({inputs:{x:r},attrs:{perm:u},backend:a}));let c=C.getInnerMostAxes(1,l)[0];C.assertAxesAreInnerMostDims("cumprod",[c],l);let d=a.makeOutput(p.shape,p.dtype),h=p.shape[c],m=a.dataIdMap.get(p.dataId).id,f=a.dataIdMap.get(d.dataId).id;mw(m,i?1:0,o?1:0,h,f,nt[r.dtype]);let g=d;if(u!==null){let y=C.getUndoAxesPermutation(u);g=os({inputs:{x:d},attrs:{perm:y},backend:a}),a.disposeData(p.dataId),a.disposeData(d.dataId)}return g}var cne={kernelName:Ni,backendName:"wasm",setupFunc:dne,kernelFunc:pne},fw;function hne(e){fw=e.wasm.cwrap(Ri,null,["number","number","number","number","number","number"])}function mne(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=n,l=r.shape.length;v.assert(r.dtype==="float32"||r.dtype==="int32",()=>`cumsum does not support ${r.dtype} tensors in the WASM backend`);let u=C.getAxesPermutation([s],l),p=r;u!==null&&(p=os({inputs:{x:r},attrs:{perm:u},backend:a}));let c=C.getInnerMostAxes(1,l)[0];C.assertAxesAreInnerMostDims("cumsum",[c],l);let d=a.makeOutput(p.shape,p.dtype),h=p.shape[c],m=a.dataIdMap.get(p.dataId).id,f=a.dataIdMap.get(d.dataId).id;fw(m,i?1:0,o?1:0,h,f,nt[r.dtype]);let g=d;if(u!==null){let y=C.getUndoAxesPermutation(u);g=os({inputs:{x:d},attrs:{perm:y},backend:a}),a.disposeData(p.dataId),a.disposeData(d.dataId)}return g}var fne={kernelName:Ri,backendName:"wasm",setupFunc:hne,kernelFunc:mne},gw;function gne(e){gw=e.wasm.cwrap("DenseBincount",null,["number","array","number","number","boolean","number","number","boolean","number"])}function yne(e){let{backend:t,inputs:a,attrs:n}=e,{x:r,weights:s}=a,{size:i,binaryOutput:o}=n,l=s.shape.reduce((d,h)=>d*h,1)!==0,u=r.shape.length===1?[i]:[r.shape[0],i],p=t.makeOutput(u,s.dtype);function c(d){return t.dataIdMap.get(d.dataId).id}return gw(c(r),new Uint8Array(new Int32Array(r.shape).buffer),r.shape.length,i,l,c(s),nt[s.dtype],o,c(p)),p}var xne={kernelName:gu,backendName:"wasm",setupFunc:gne,kernelFunc:yne},yw;function Ane(e){yw=e.wasm.cwrap(Mi,null,["number","number","number","array","number","array","array","number","number"])}function bne(e){let{backend:t,inputs:a,attrs:n}=e,{x:r}=a,{blockSize:s,dataFormat:i}=n,o=r.shape[0],l=i==="NHWC"?r.shape[1]:r.shape[2],u=i==="NHWC"?r.shape[2]:r.shape[3],p=i==="NHWC"?r.shape[3]:r.shape[1],c=l*s,d=u*s,h=p/(s*s),m=i==="NHWC"?[o,c,d,h]:[o,h,c,d],f=t.makeOutput(m,"float32"),g=t.dataIdMap.get(r.dataId).id,y=new Uint8Array(new Int32Array(v.computeStrides(r.shape)).buffer),x=new Uint8Array(new Int32Array(m).buffer),A=new Uint8Array(new Int32Array(v.computeStrides(m)).buffer),b=t.dataIdMap.get(f.dataId).id;return yw(g,s,i==="NHWC"?1:0,y,r.shape.length-1,x,A,m.length,b),f}var vne={kernelName:Mi,backendName:"wasm",setupFunc:Ane,kernelFunc:bne},xw;function wne(e){xw=e.wasm.cwrap($i,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function kne(e){let{inputs:t,attrs:a,backend:n}=e,{x:r,filter:s}=t,i=n.dataIdMap.get(r.dataId).id,o=n.dataIdMap.get(s.dataId).id,{strides:l,dilations:u,pad:p,dimRoundingMode:c}=a,d=u==null?[1,1]:u,h=C.computeConv2DInfo(r.shape,s.shape,l,d,p,c,!0),m=h.filterHeight,f=h.filterWidth,g=h.padInfo.top,y=h.padInfo.right,x=h.padInfo.bottom,A=h.padInfo.left,b=h.dilationHeight,w=h.dilationWidth,I=h.strideHeight,T=h.strideWidth,N=h.inChannels,M=h.outChannels,$=h.padInfo.type==="SAME"?1:0;if(h.dataFormat!=="channelsLast")throw new Error(`wasm backend DepthwiseConv2dNative does not support dataFormat:'${h.dataFormat}'. Please use 'channelsLast'.`);let E=n.makeOutput(h.outShape,"float32"),S=n.dataIdMap.get(E.dataId).id;return xw(i,r.shape[0],r.shape[1],r.shape[2],o,m,f,g,y,x,A,$,b,w,I,T,N,M,S),E}var Ine={kernelName:$i,backendName:"wasm",setupFunc:wne,kernelFunc:kne},Aw;function Sne(e){Aw=e.wasm.cwrap("Diag",null,["number","number","number","number"])}function Cne(e){let{inputs:t,backend:a}=e,{x:n}=t,r=v.sizeFromShape(n.shape),s=a.makeOutput([...n.shape,...n.shape],n.dtype);return Aw(a.dataIdMap.get(n.dataId).id,nt[n.dtype],r,a.dataIdMap.get(s.dataId).id),s}var Tne={kernelName:yu,backendName:"wasm",setupFunc:Sne,kernelFunc:Cne},bw;function Nne(e){bw=e.wasm.cwrap(Pi,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Rne(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=n;if(r.dtype!==s.dtype)throw new Error(`Dilation2D error: x must have the same dtype as filter. Got ${r.dtype} and ${s.dtype}`);let u=C.computeDilation2DInfo(r.shape,s.shape,i,o,"NHWC",l),p=a.makeOutput(u.outShape,r.dtype);return bw(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(s.dataId).id,a.dataIdMap.get(p.dataId).id,nt[r.dtype],u.batchSize,u.inChannels,u.inHeight,u.inWidth,u.outHeight,u.outWidth,u.strideHeight,u.strideWidth,u.dilationHeight,u.dilationWidth,u.filterHeight,u.filterWidth,u.padInfo.top,u.padInfo.left),p}var Ene={kernelName:Pi,backendName:"wasm",setupFunc:Nne,kernelFunc:Rne},vw;function Mne(e){vw=e.wasm.cwrap(Xl,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function $ne(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s,dy:i}=t,{strides:o,pad:l,dilations:u}=n;if(r.dtype!==s.dtype||r.dtype!==i.dtype)throw new Error(`Dilation2DBackpropFilter error: x must have the same dtype as filter and dy. Got ${r.dtype}, ${s.dtype}, and ${i.dtype}`);let p=C.computeDilation2DInfo(r.shape,s.shape,o,l,"NHWC",u),c=a.makeOutput(s.shape,s.dtype);return vw(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(s.dataId).id,a.dataIdMap.get(i.dataId).id,a.dataIdMap.get(c.dataId).id,nt[r.dtype],p.batchSize,p.inChannels,p.inHeight,p.inWidth,p.outHeight,p.outWidth,p.strideHeight,p.strideWidth,p.dilationHeight,p.dilationWidth,p.filterHeight,p.filterWidth,p.padInfo.top,p.padInfo.left),c}var Pne={kernelName:Xl,backendName:"wasm",setupFunc:Mne,kernelFunc:$ne},ww;function _ne(e){ww=e.wasm.cwrap(ql,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Fne(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s,dy:i}=t,{strides:o,pad:l,dilations:u}=n;if(r.dtype!==s.dtype||r.dtype!==i.dtype)throw new Error(`Dilation2DBackpropInput error: x must have the same dtype as filter and dy. Got ${r.dtype}, ${s.dtype}, and ${i.dtype}`);let p=C.computeDilation2DInfo(r.shape,s.shape,o,l,"NHWC",u),c=a.makeOutput(r.shape,r.dtype);return ww(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(s.dataId).id,a.dataIdMap.get(i.dataId).id,a.dataIdMap.get(c.dataId).id,nt[r.dtype],p.batchSize,p.inChannels,p.inHeight,p.inWidth,p.outHeight,p.outWidth,p.strideHeight,p.strideWidth,p.dilationHeight,p.dilationWidth,p.filterHeight,p.filterWidth,p.padInfo.top,p.padInfo.left),c}var Dne={kernelName:ql,backendName:"wasm",setupFunc:_ne,kernelFunc:Fne},One=Qe(Fi),kw;function zne(e){kw=e.wasm.cwrap(xu,null,["number","number","number"])}function Lne(e){let{inputs:t,backend:a}=e,{dy:n,y:r}=t,s=a.makeOutput(r.shape,"float32"),i=o=>a.dataIdMap.get(o.dataId).id;return kw(i(r),i(n),i(s)),s}var Wne={kernelName:xu,backendName:"wasm",setupFunc:zne,kernelFunc:Lne},Bne=!1,Vne=Gt(Oi,Bne,"bool"),Une=Qe(Di),Gne=Qe(zi,"float32");function U1(e){let{inputs:t,attrs:a,backend:n}=e,{input:r}=t,{dim:s}=a,i=r.shape.length,o=r.shape.slice(),l=s;return s<0&&(v.assert(-(i+1)<=s,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+s+1),o.splice(l,0,1),La({inputs:{x:r},backend:n,attrs:{shape:o}})}var Hne={kernelName:Au,backendName:"wasm",kernelFunc:U1},jne=Qe(Li,"float32");function Iw(e){let{attrs:{shape:t,value:a},backend:n}=e,{attrs:{dtype:r}}=e;r=r||v.inferDtype(a);let s=n.makeOutput(t,r);return n.typedArrayFromHeap(s).fill(a),s}var qne={kernelName:bu,backendName:"wasm",kernelFunc:Iw},Sw;function Xne(e){Sw=e.wasm.cwrap(Wi,null,["number","number","number","number","number","number"])}function Kne(e){let{inputs:t,backend:a}=e,{image:n}=t,r=a.makeOutput(n.shape,n.dtype),s=a.dataIdMap.get(n.dataId).id,i=a.dataIdMap.get(r.dataId).id,[o,l,u,p]=n.shape;return Sw(s,o,l,u,p,i),r}var Yne={kernelName:Wi,backendName:"wasm",kernelFunc:Kne,setupFunc:Xne},Zne=Qe(Bi),Jne=!1,Qne=Gt(Vi,Jne),Cw;function ere(e){Cw=e.wasm.cwrap(Ui,null,["number","number","number","number","number","number","number"])}function tre(e){let{backend:t,inputs:a,attrs:n}=e,{varianceEpsilon:r}=n,{x:s,mean:i,variance:o,offset:l,scale:u}=a,p=t.dataIdMap.get(s.dataId).id,c=t.dataIdMap.get(i.dataId).id,d=t.dataIdMap.get(o.dataId).id,h=l!=null?t.dataIdMap.get(l.dataId).id:0,m=u!=null?t.dataIdMap.get(u.dataId).id:0,f=t.makeOutput(s.shape,s.dtype);if(v.sizeFromShape(s.shape)===0)return f;let g=t.dataIdMap.get(f.dataId).id;return Cw(p,c,d,h,m,r,g),f}var are={kernelName:Ui,backendName:"wasm",setupFunc:ere,kernelFunc:tre},Tw;function nre(e){Tw=e.wasm.cwrap(Jr,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function rre(e){let{inputs:t,attrs:a,backend:n}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:p,dataFormat:c,dimRoundingMode:d,activation:h,leakyreluAlpha:m}=a,f=C.computeConv2DInfo(r.shape,s.shape,l,p,u,d),g=rp[h];if(g==null)throw new Error(`${h} activation not yet supported for FusedConv2D in the wasm backend.`);let y=n.dataIdMap.get(r.dataId).id,x=n.dataIdMap.get(s.dataId).id,A=f.outChannels,b=0;if(i!=null){let X=n.dataIdMap.get(i.dataId);if(X.shape.length!==1)throw new Error(`FusedConv2D only supports rank-1 bias but got rank ${X.shape.length}.`);if(X.shape[0]!==A)throw new Error(`FusedConv2D bias shape (${X.shape}) does not match the number of output channels (${A})`);b=X.id}let w=f.filterHeight,I=f.filterWidth,T=f.padInfo.top,N=f.padInfo.right,M=f.padInfo.bottom,$=f.padInfo.left,E=f.dilationHeight,S=f.dilationWidth,_=f.strideHeight,O=f.strideWidth,W=f.inChannels,P=f.padInfo.type==="SAME"?1:0,U=f.batchSize,G=f.inHeight,q=f.inWidth;if(c!=="NHWC")throw new Error(`wasm backend FusedConv2D does not support dataFormat:'${c}'. Please use 'NHWC'.`);let H=n.makeOutput(f.outShape,"float32"),V=n.dataIdMap.get(H.dataId).id,Z=o==null?0:n.dataIdMap.get(o.dataId).id;return Tw(y,U,G,q,x,w,I,b,T,N,M,$,P,E,S,_,O,W,A,g,Z,m||0,V),H}var sre={kernelName:Jr,backendName:"wasm",setupFunc:nre,kernelFunc:rre},Nw;function ire(e){Nw=e.wasm.cwrap(Qr,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function ore(e){let{inputs:t,attrs:a,backend:n}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:p,dataFormat:c,dimRoundingMode:d,activation:h,leakyreluAlpha:m}=a,f=C.computeConv2DInfo(r.shape,s.shape,l,p,u,d,!0),g=rp[h];if(g==null)throw new Error(`${h} activation not yet supported for FusedDepthwiseConv2D in the wasm backend.`);let y=n.dataIdMap.get(r.dataId).id,x=n.dataIdMap.get(s.dataId).id,A=f.outChannels,b=0;if(i!=null){let X=n.dataIdMap.get(i.dataId);if(X.shape.length!==1)throw new Error(`FusedDepthwiseConv2D only supports rank-1 bias but got rank ${X.shape.length}.`);if(X.shape[0]!==A)throw new Error(`FusedDepthwiseConv2D bias shape (${X.shape}) does not match the number of output channels (${A})`);b=X.id}let w=f.filterHeight,I=f.filterWidth,T=f.padInfo.top,N=f.padInfo.right,M=f.padInfo.bottom,$=f.padInfo.left,E=f.dilationHeight,S=f.dilationWidth,_=f.strideHeight,O=f.strideWidth,W=f.inChannels,P=f.padInfo.type==="SAME"?1:0,U=f.batchSize,G=f.inHeight,q=f.inWidth;if(c!=="NHWC")throw new Error(`wasm backend FusedDepthwiseConv2D does not support dataFormat:'${c}'. Please use 'NHWC'.`);let H=n.makeOutput(f.outShape,"float32"),V=n.dataIdMap.get(H.dataId).id,Z=o==null?0:n.dataIdMap.get(o.dataId).id;return Nw(y,U,G,q,x,w,I,b,T,N,M,$,P,E,S,_,O,W,A,g,Z,m||0,V),H}var lre={kernelName:Qr,backendName:"wasm",setupFunc:ire,kernelFunc:ore},Rw;function ure(e){Rw=e.wasm.cwrap(Gi,null,["number","number","number","number","number","number","array","number"])}function dre(e){let{backend:t,inputs:a}=e,{params:n,indices:r}=a,[s,i,o,l]=s3.prepareAndValidate(n,r),u=t.makeOutput(s,n.dtype);if(i===0)return u;let p=r.shape,c=p[p.length-1],d=t.dataIdMap.get(n.dataId).id,h=t.dataIdMap.get(r.dataId).id,m=new Uint8Array(new Int32Array(l).buffer),f=t.dataIdMap.get(u.dataId).id;return Rw(d,nt[n.dtype],h,i,c,o,m,f),u}var pre={kernelName:Gi,backendName:"wasm",setupFunc:ure,kernelFunc:dre},Ew;function cre(e){Ew=e.wasm.cwrap("Gather",null,["number","number","array","number","number","number","array","number"])}function hre(e){let{backend:t,inputs:a,attrs:n}=e,{x:r,indices:s}=a,{axis:i,batchDims:o}=n,l=v.parseAxisParam(i,r.shape)[0],u=t.readSync(s.dataId),p=r.shape[l];for(let T=0;T<u.length;++T){let N=u[T];v.assert(N<=p-1&&N>=0,()=>`GatherV2: the index value ${N} is not in [0, ${p-1}]`)}let c=C.segment_util.collectGatherOpShapeInfo(r,s,l,o),d=La({inputs:{x:r},attrs:{shape:[c.batchSize,c.outerSize,c.dimSize,c.sliceSize]},backend:t}),h=v.sizeFromShape(s.shape),m=La({inputs:{x:s},attrs:{shape:[c.batchSize,h/c.batchSize]},backend:t}),f=[c.batchSize,c.outerSize,h/c.batchSize,c.sliceSize],g=t.makeOutput(f,r.dtype);if(v.sizeFromShape(r.shape)===0)return g;let y=d.shape.length-1,x=t.dataIdMap.get(d.dataId).id,A=t.dataIdMap.get(m.dataId).id,b=t.dataIdMap.get(g.dataId).id,w=new Uint8Array(new Int32Array(v.computeStrides(d.shape)).buffer),I=new Uint8Array(new Int32Array(v.computeStrides(f)).buffer);return Ew(x,nt[r.dtype],w,y,A,c.batchSize,I,b),t.disposeData(d.dataId),t.disposeData(m.dataId),g.shape=c.outputShape,g}var mre={kernelName:vu,backendName:"wasm",setupFunc:cre,kernelFunc:hre},fre=!1,gre=Gt(Hi,fre,"bool"),yre=!1,xre=Gt(ji,yre,"bool"),Are=Qe(Xi,"bool"),bre=Qe(Ki,"bool"),vre=Qe(Yi,"bool"),Mw;function wre(e){Mw=e.wasm.cwrap(Zi,null,["number","number","number","number"])}function kre(e){let{inputs:{x:t},attrs:{alpha:a},backend:n}=e,r=n.dataIdMap.get(t.dataId).id,s=n.makeOutput(t.shape,"float32");if(v.sizeFromShape(t.shape)!==0){let i=n.dataIdMap.get(s.dataId).id;Mw(r,nt[t.dtype],a,i)}return s}var Ire={kernelName:Zi,backendName:"wasm",setupFunc:wre,kernelFunc:kre},Sre=!1,Cre=Gt(Ji,Sre,"bool"),Tre=!1,Nre=Gt(Qi,Tre,"bool"),$w;function Rre(e){$w=e.wasm.cwrap(eo,null,["number","number","number","number"])}function Ere(e){let{attrs:t,backend:a}=e,{start:n,stop:r,num:s}=t,i=Math.floor(s),o=a.makeOutput([i],"float32");return $w(a.dataIdMap.get(o.dataId).id,n,r,i),o}var Mre={kernelName:eo,backendName:"wasm",setupFunc:Rre,kernelFunc:Ere},$re=Qe(to),Pre=Qe(ao),_re=!1,Fre=Gt(no,_re,"bool"),Dre=Qe(ro),Ore=!1,zre=Gt(so,Ore,"bool"),Lre=!1,Wre=Gt(RA,Lre,"bool"),Pw;function Bre(e){Pw=e.wasm.cwrap(io,null,["number","number","number","number","number","number","number"])}function Vre(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=n;if(r.dtype!=="float32")throw new Error("LRN error: x must have dtype float32");let u=a.makeOutput(r.shape,r.dtype);return Pw(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(u.dataId).id,r.shape[3],s,i,o,l),u}var Ure={kernelName:io,backendName:"wasm",setupFunc:Bre,kernelFunc:Vre},_w;function Gre(e){_w=e.wasm.cwrap(wu,null,["number","number","number","number","number","number","number","number","number"])}function Hre(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:u,beta:p}=n;if(r.dtype!=="float32"||s.dtype!=="float32"||i.dtype!=="float32")throw new Error("LRNGrad error: x, y, and dy must have dtype float32");let c=a.makeOutput(r.shape,r.dtype);return _w(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(s.dataId).id,a.dataIdMap.get(i.dataId).id,a.dataIdMap.get(c.dataId).id,i.shape[3],o,l,u,p),c}var jre={kernelName:wu,backendName:"wasm",setupFunc:Gre,kernelFunc:Hre},Fw;function qre(e){Fw=e.wasm.cwrap(oo,null,["number","number","number","number"])}function Xre(e){let{backend:t,inputs:a,attrs:n}=e,{reductionIndices:r,keepDims:s}=n,{x:i}=a,o=t.dataIdMap.get(i.dataId).id,l=i,{transposed:u,axes:p,originalAxes:c,inputWasTransposed:d}=gs(i,r,t);if(d){let x=t.dataIdMap.get(u.dataId).id;l=u,o=x}let h=l.shape.length;C.assertAxesAreInnerMostDims("max",p,h);let[m,f]=C.computeOutAndReduceShapes(l.shape,p),g=v.sizeFromShape(f),y=t.makeOutput(m,i.dtype);if(v.sizeFromShape(l.shape)!==0){let x=t.dataIdMap.get(y.dataId).id;Fw(o,nt[i.dtype],g,x)}if(d&&t.disposeData(u.dataId),s){let x=C.expandShapeToKeepDim(y.shape,c);y.shape=x}return y}var Kre={kernelName:oo,backendName:"wasm",setupFunc:qre,kernelFunc:Xre},Yre=!1,Zre=Gt(lo,Yre),Dw;function Jre(e){Dw=e.wasm.cwrap(uo,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Qre(e){let{inputs:t,attrs:a,backend:n}=e,r=t.x,s=n.dataIdMap.get(r.dataId).id;v.assert(r.dtype==="float32",()=>`Error in MaxPool: only float32 input is supported. Got ${r.dtype}.`);let{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=a,p=C.computePool2DInfo(r.shape,i,o,1,l,u),c=p.filterHeight,d=p.filterWidth,h=p.padInfo.top,m=p.padInfo.right,f=p.padInfo.bottom,g=p.padInfo.left,y=p.dilationHeight,x=p.dilationWidth,A=p.strideHeight,b=p.strideWidth,w=p.inChannels,I=p.outChannels;if(p.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${p.dataFormat}'. Please use 'channelsLast'.`);let T=n.makeOutput(p.outShape,"float32"),N=n.dataIdMap.get(T.dataId).id;return Dw(s,r.shape[0],r.shape[1],r.shape[2],c,d,h,m,f,g,y,x,A,b,w,I,N),T}var ese={kernelName:uo,backendName:"wasm",setupFunc:Jre,kernelFunc:Qre},Ow;function tse(e){Ow=e.wasm.cwrap("MaxPool3D",null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function ase(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:u}=n,p=C.computePool3DInfo(r.shape,s,i,1,o,l,u),c=a.makeOutput(p.outShape,r.dtype);return Ow(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(c.dataId).id,p.batchSize,p.inChannels,p.inDepth,p.inHeight,p.inWidth,p.outDepth,p.outHeight,p.outWidth,p.strideDepth,p.strideHeight,p.strideWidth,p.dilationDepth,p.dilationHeight,p.dilationWidth,p.effectiveFilterDepth,p.effectiveFilterHeight,p.effectiveFilterWidth,p.padInfo.front,p.padInfo.top,p.padInfo.left),c}var nse={kernelName:ku,backendName:"wasm",setupFunc:tse,kernelFunc:ase},zw;function rse(e){zw=e.wasm.cwrap("MaxPool3DGrad",null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function sse(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=n,p=C.computePool3DInfo(s.shape,i,o,1,l,u),c=a.makeOutput(s.shape,s.dtype);return zw(a.dataIdMap.get(s.dataId).id,a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(c.dataId).id,p.batchSize,p.inChannels,p.inDepth,p.inHeight,p.inWidth,p.outDepth,p.outHeight,p.outWidth,p.strideDepth,p.strideHeight,p.strideWidth,p.dilationDepth,p.dilationHeight,p.dilationWidth,p.effectiveFilterDepth,p.effectiveFilterHeight,p.effectiveFilterWidth,p.padInfo.front,p.padInfo.top,p.padInfo.left),c}var ise={kernelName:kp,backendName:"wasm",setupFunc:rse,kernelFunc:sse},Lw;function ose(e){Lw=e.wasm.cwrap("MaxPoolGrad",null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function lse(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=n,p=C.computePool2DInfo(s.shape,i,o,1,l,u),c=a.makeOutput(s.shape,s.dtype);return Lw(a.dataIdMap.get(s.dataId).id,a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(c.dataId).id,p.batchSize,p.inChannels,p.inHeight,p.inWidth,p.outHeight,p.outWidth,p.strideHeight,p.strideWidth,p.dilationHeight,p.dilationWidth,p.effectiveFilterHeight,p.effectiveFilterWidth,p.padInfo.top,p.padInfo.left),c}var use={kernelName:wp,backendName:"wasm",setupFunc:ose,kernelFunc:lse},Ww;function dse(e){Ww=e.wasm.cwrap("MaxPoolWithArgmax",null,["number","number","number","number","boolean","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function pse(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,includeBatchInIndex:l}=n;v.assert(r.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${r.shape.length}.`);let u=[1,1];v.assert(C.eitherStridesOrDilationsAreOne(i,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let p=C.computePool2DInfo(r.shape,s,i,[1,1],o),c=a.makeOutput(p.outShape,r.dtype),d=a.makeOutput(p.outShape,"int32");return Ww(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(c.dataId).id,a.dataIdMap.get(d.dataId).id,nt[r.dtype],l,p.batchSize,p.inChannels,p.inHeight,p.inWidth,p.outHeight,p.outWidth,p.strideHeight,p.strideWidth,p.dilationHeight,p.dilationWidth,p.effectiveFilterHeight,p.effectiveFilterWidth,p.padInfo.top,p.padInfo.left),[c,d]}var cse={kernelName:Iu,backendName:"wasm",setupFunc:dse,kernelFunc:pse},Bw;function hse(e){Bw=e.wasm.cwrap(po,null,["number, number, number"])}function mse(e){let{backend:t,inputs:a,attrs:n}=e,{axis:r,keepDims:s}=n,{x:i}=a,o=t.dataIdMap.get(i.dataId).id,l=o,u=i,{transposed:p,axes:c,originalAxes:d,inputWasTransposed:h}=gs(i,r,t),m=c;if(h){let b=t.dataIdMap.get(p.dataId).id;b!==o&&(u=p,l=b,m=C.getInnerMostAxes(m.length,u.shape.length))}C.assertAxesAreInnerMostDims("mean",m,u.shape.length);let[f,g]=C.computeOutAndReduceShapes(u.shape,m),y=v.sizeFromShape(g),x=u;u.dtype!=="float32"&&(x=ys({backend:t,inputs:{x:u},attrs:{dtype:"float32"}}),l=t.dataIdMap.get(x.dataId).id);let A=t.makeOutput(f,"float32");if(v.sizeFromShape(u.shape)!==0){let b=t.dataIdMap.get(A.dataId).id;Bw(l,y,b)}if(h&&t.disposeData(p.dataId),s){let b=C.expandShapeToKeepDim(A.shape,d);A.shape=b}return u.dtype!=="float32"&&t.disposeData(x.dataId),A}var fse={kernelName:po,backendName:"wasm",setupFunc:hse,kernelFunc:mse},Vw;function gse(e){Vw=e.wasm.cwrap(co,null,["number","number","number","number"])}function yse(e){let{backend:t,inputs:a,attrs:n}=e,{axis:r,keepDims:s}=n,{x:i}=a,o=t.dataIdMap.get(i.dataId).id,l=o,u=i,{transposed:p,axes:c,originalAxes:d,inputWasTransposed:h}=gs(i,r,t);if(h){let A=t.dataIdMap.get(p.dataId).id;A!==o&&(u=p,l=A)}let m=u.shape.length;C.assertAxesAreInnerMostDims("min",c,m);let[f,g]=C.computeOutAndReduceShapes(u.shape,c),y=v.sizeFromShape(g),x=t.makeOutput(f,u.dtype);if(v.sizeFromShape(u.shape)!==0){let A=t.dataIdMap.get(x.dataId).id;Vw(l,nt[i.dtype],y,A)}if(h&&t.disposeData(p.dataId),s){let A=C.expandShapeToKeepDim(x.shape,d);x.shape=A}return x}var xse={kernelName:co,backendName:"wasm",setupFunc:gse,kernelFunc:yse},Ase=!1,bse=Gt(ho,Ase),G1;(function(e){e[e.reflect=0]="reflect",e[e.symmetric=1]="symmetric"})(G1||(G1={}));var Uw;function vse(e){Uw=e.wasm.cwrap(mo,null,["number","array","number","number","array","array","number","number"])}function wse(e){let{inputs:{x:t},backend:a,attrs:{paddings:n,mode:r}}=e,s=n.map((m,f)=>m[0]+t.shape[f]+m[1]),i=a.dataIdMap.get(t.dataId).id,o=a.makeOutput(s,t.dtype),l=a.dataIdMap.get(o.dataId).id,u=new Uint8Array(new Int32Array(t.shape).buffer),p=n.map(m=>m[0]),c=n.map(m=>m[1]),d=new Uint8Array(new Int32Array(p).buffer),h=new Uint8Array(new Int32Array(c).buffer);return Uw(i,u,t.shape.length,nt[t.dtype],d,h,G1[r],l),o}var kse={kernelName:mo,backendName:"wasm",kernelFunc:wse,setupFunc:vse},Gw;function Ise(e){Gw=e.wasm.cwrap(Ho,null,["number","number","number","number"])}function Hw(e){let{backend:t,inputs:{logits:a},attrs:{dim:n}}=e,r=t.dataIdMap.get(a.dataId).id,s=t.makeOutput(a.shape,a.dtype),i=t.dataIdMap.get(s.dataId).id,o=a.shape[n],l=v.sizeFromShape(a.shape)/o;return v.sizeFromShape(s.shape)===0||Gw(r,i,o,l),s}var Sse={kernelName:Ho,backendName:"wasm",setupFunc:Ise,kernelFunc:Hw},jw;function Cse(e){jw=e.wasm.cwrap(go,null,["number","number","number","number","number","number"])}function Tse(e){let{inputs:t,backend:a,attrs:n}=e,{logits:r}=t,{numSamples:s,seed:i,normalized:o}=n;if(r.dtype!=="float32")throw new Error(`Tensor logits must have dtype float32, got ${r.dtype}`);let l=o?r:Hw({inputs:{logits:r},backend:a,attrs:{dim:r.shape.length-1}}),[u,p]=l.shape,c=a.makeOutput([u,s],"int32");return jw(a.dataIdMap.get(l.dataId).id,u,p,s,i,a.dataIdMap.get(c.dataId).id),o||a.disposeData(l.dataId),c}var Nse={kernelName:go,backendName:"wasm",setupFunc:Cse,kernelFunc:Tse},Rse=Gt(fo,!0),Ese=!0,Mse=Gt(yo,Ese),$se=Qe(Su);function V3(e,t){let a=new Int32Array(e.wasm.HEAPU8.buffer,t,4),n=a[0],r=a[1],s=a[2],i=a[3];return e.wasm._free(t),{pSelectedIndices:n,selectedSize:r,pSelectedScores:s,pValidOutputs:i}}var qw;function Pse(e){qw=e.wasm.cwrap(Ao,"number",["number","number","number","number","number"])}function _se(e){let{backend:t,inputs:a,attrs:n}=e,{iouThreshold:r,maxOutputSize:s,scoreThreshold:i}=n,{boxes:o,scores:l}=a,u=t.dataIdMap.get(o.dataId).id,p=t.dataIdMap.get(l.dataId).id,c=qw(u,p,s,r,i),{pSelectedIndices:d,selectedSize:h,pSelectedScores:m,pValidOutputs:f}=V3(t,c);return t.wasm._free(m),t.wasm._free(f),t.makeOutput([h],"int32",d)}var Fse={kernelName:Ao,backendName:"wasm",setupFunc:Pse,kernelFunc:_se},Xw;function Dse(e){Xw=e.wasm.cwrap(Cu,"number",["number","number","number","number","number","bool"])}function Ose(e){let{backend:t,inputs:a,attrs:n}=e,{iouThreshold:r,maxOutputSize:s,scoreThreshold:i,padToMaxOutputSize:o}=n,{boxes:l,scores:u}=a,p=t.dataIdMap.get(l.dataId).id,c=t.dataIdMap.get(u.dataId).id,d=Xw(p,c,s,r,i,o),{pSelectedIndices:h,selectedSize:m,pSelectedScores:f,pValidOutputs:g}=V3(t,d);t.wasm._free(f);let y=t.makeOutput([m],"int32",h),x=t.makeOutput([],"int32",g);return[y,x]}var zse={kernelName:Cu,backendName:"wasm",setupFunc:Dse,kernelFunc:Ose},Kw;function Lse(e){Kw=e.wasm.cwrap(bo,"number",["number","number","number","number","number","number"])}function Wse(e){let{backend:t,inputs:a,attrs:n}=e,{iouThreshold:r,maxOutputSize:s,scoreThreshold:i,softNmsSigma:o}=n,{boxes:l,scores:u}=a,p=t.dataIdMap.get(l.dataId).id,c=t.dataIdMap.get(u.dataId).id,d=Kw(p,c,s,r,i,o),{pSelectedIndices:h,selectedSize:m,pSelectedScores:f,pValidOutputs:g}=V3(t,d);t.wasm._free(g);let y=t.makeOutput([m],"int32",h),x=t.makeOutput([m],"float32",f);return[y,x]}var Bse={kernelName:bo,backendName:"wasm",setupFunc:Lse,kernelFunc:Wse},Vse=!1,Use=Gt(xo,Vse,"bool"),Yw;function Gse(e){Yw=e.wasm.cwrap(vo,null,["number","number","number","number","number"])}function Hse(e){let{inputs:t,backend:a,attrs:n}=e,{indices:r}=t,{dtype:s,depth:i,onValue:o,offValue:l}=n,u=a.makeOutput([...r.shape,i],s),p=a.dataIdMap.get(u.dataId).id,c=a.dataIdMap.get(r.dataId).id;return Yw(c,i,o,l,p),u}var jse={kernelName:vo,backendName:"wasm",setupFunc:Gse,kernelFunc:Hse};function qse(e){let{inputs:{x:t},backend:a}=e,n=a.makeOutput(t.shape,t.dtype);return a.typedArrayFromHeap(n).fill(1),n}var Xse={kernelName:Tu,backendName:"wasm",kernelFunc:qse};function Kse(e){let{inputs:t,backend:a,attrs:n}=e,{axis:r}=n;if(t.length===1)return U1({inputs:{input:t[0]},backend:a,attrs:{dim:r}});let s=t[0].shape,i=t[0].dtype;t.forEach(p=>{v.assertShapesMatch(s,p.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===p.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(p=>{let c=U1({inputs:{input:p},backend:a,attrs:{dim:r}});return o.push(c),c}),u=ow({inputs:l,backend:a,attrs:{axis:r}});return o.forEach(p=>a.disposeData(p.dataId)),u}var Yse={kernelName:Nu,backendName:"wasm",kernelFunc:Kse},Zw;function Zse(e){Zw=e.wasm.cwrap(wo,null,["number","array","number","number","array","array","number","number"])}function Jse(e){let{inputs:{x:t},backend:a,attrs:{paddings:n,constantValue:r}}=e,s=n.map((m,f)=>m[0]+t.shape[f]+m[1]);if(v.sizeFromShape(t.shape)===0)return Iw({backend:a,attrs:{shape:s,value:r,dtype:t.dtype}});let i=a.dataIdMap.get(t.dataId).id,o=a.makeOutput(s,t.dtype),l=a.dataIdMap.get(o.dataId).id,u=new Uint8Array(new Int32Array(t.shape).buffer),p=n.map(m=>m[0]),c=n.map(m=>m[1]),d=new Uint8Array(new Int32Array(p).buffer),h=new Uint8Array(new Int32Array(c).buffer);return Zw(i,u,t.shape.length,nt[t.dtype],d,h,r,l),o}var Jw={kernelName:wo,backendName:"wasm",kernelFunc:Jse,setupFunc:Zse},Qse=!1,eie=Gt(ko,Qse),Qw;function tie(e){Qw=e.wasm.cwrap(Io,null,["number","number","number"])}function aie(e){let{inputs:t,backend:a}=e,{x:n,alpha:r}=t,s=a.dataIdMap.get(n.dataId).id,i=a.dataIdMap.get(r.dataId).id,o=s,l=n,u=l;l.dtype!=="float32"&&(u=ys({backend:a,inputs:{x:n},attrs:{dtype:"float32"}}),o=a.dataIdMap.get(u.dataId).id);let p=a.makeOutput(n.shape,"float32"),c=a.dataIdMap.get(p.dataId).id;return Qw(o,i,c),l.dtype!=="float32"&&a.disposeData(u.dataId),p}var nie={kernelName:Io,backendName:"wasm",setupFunc:tie,kernelFunc:aie},ek;function rie(e){ek=e.wasm.cwrap(So,null,["number","number","number","number"])}function sie(e){let{backend:t,inputs:a,attrs:n}=e,{axis:r,keepDims:s}=n,{x:i}=a,o=t.dataIdMap.get(i.dataId).id,l=o,u=i,{transposed:p,axes:c,originalAxes:d,inputWasTransposed:h}=gs(i,r,t),m=c;if(h){let A=t.dataIdMap.get(p.dataId).id;A!==o&&(u=p,l=A,m=C.getInnerMostAxes(m.length,u.shape.length))}C.assertAxesAreInnerMostDims("prod",m,u.shape.length);let[f,g]=C.computeOutAndReduceShapes(u.shape,m),y=v.sizeFromShape(g),x=t.makeOutput(f,u.dtype);if(v.sizeFromShape(u.shape)!==0){let A=t.dataIdMap.get(x.dataId).id;ek(l,y,nt[x.dtype],A)}if(h&&t.disposeData(p.dataId),s){let A=C.expandShapeToKeepDim(x.shape,d);x.shape=A}return x}var iie={kernelName:So,backendName:"wasm",setupFunc:rie,kernelFunc:sie},oie=e=>{let{backend:t,attrs:a}=e,{start:n,stop:r,step:s,dtype:i}=a,o=y3(n,r,s,i),l=t.makeOutput([o.length],i);return t.typedArrayFromHeap(l).set(o),l},lie={kernelName:Ru,backendName:"wasm",kernelFunc:oie},uie=!0,die=Gt(_i,uie),pie=Qe(Co),cie=Qe(To),hie=Qe(Eo),tk;function mie(e){tk=e.wasm.cwrap(Ro,null,["number","number","number","number","number","number","number","number","number","number"])}function fie(e){let{backend:t,inputs:a,attrs:n}=e,{images:r}=a,{alignCorners:s,halfPixelCenters:i,size:o}=n,[l,u]=o,[p,c,d,h]=r.shape,m=[p,l,u,h],f=t.dataIdMap.get(r.dataId),g;f.dtype!=="float32"&&(g=ys({backend:t,inputs:{x:r},attrs:{dtype:"float32"}}),f=t.dataIdMap.get(g.dataId));let y=f.id,x=t.makeOutput(m,"float32");if(v.sizeFromShape(r.shape)===0)return x;let A=t.dataIdMap.get(x.dataId).id;return tk(y,p,c,d,h,l,u,s?1:0,i?1:0,A),g!=null&&t.disposeData(g.dataId),x}var gie={kernelName:Ro,backendName:"wasm",setupFunc:mie,kernelFunc:fie},ak;function yie(e){ak=e.wasm.cwrap($u,null,["number","number","number","array","array","boolean"])}function xie(e){let{inputs:t,backend:a,attrs:n}=e,{images:r,dy:s}=t,{alignCorners:i}=n,o=a.makeOutput(r.shape,"float32"),l=a.dataIdMap.get(r.dataId),u;return l.dtype!=="float32"&&(u=ys({backend:a,inputs:{x:r},attrs:{dtype:"float32"}}),l=a.dataIdMap.get(u.dataId)),ak(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(s.dataId).id,a.dataIdMap.get(o.dataId).id,new Uint8Array(new Int32Array(r.shape).buffer),new Uint8Array(new Int32Array(s.shape).buffer),i),u!=null&&a.disposeData(u.dataId),o}var Aie={kernelName:$u,backendName:"wasm",setupFunc:yie,kernelFunc:xie},nk;function bie(e){nk=e.wasm.cwrap(No,null,["number","number","number","number","number","number","number","number","number","number"])}function vie(e){let{backend:t,inputs:a,attrs:n}=e,{images:r}=a,{alignCorners:s,halfPixelCenters:i,size:o}=n,[l,u]=o,[p,c,d,h]=r.shape,m=[p,l,u,h],f=t.makeOutput(m,"float32");if(v.sizeFromShape(r.shape)===0)return f;let g=t.dataIdMap.get(r.dataId),y;g.dtype!=="float32"&&(y=ys({backend:t,inputs:{x:r},attrs:{dtype:"float32"}}),g=t.dataIdMap.get(y.dataId));let x=g.id,A=t.dataIdMap.get(f.dataId).id;return nk(x,p,c,d,h,l,u,s?1:0,i?1:0,A),y!=null&&t.disposeData(y.dataId),f}var wie={kernelName:No,backendName:"wasm",setupFunc:bie,kernelFunc:vie},rk;function kie(e){rk=e.wasm.cwrap(Mu,null,["number","number","number","array","array","boolean"])}function Iie(e){let{inputs:t,backend:a,attrs:n}=e,{images:r,dy:s}=t,{alignCorners:i}=n,o=a.makeOutput(r.shape,"float32"),l=a.dataIdMap.get(r.dataId),u;return l.dtype!=="float32"&&(u=ys({backend:a,inputs:{x:r},attrs:{dtype:"float32"}}),l=a.dataIdMap.get(u.dataId)),rk(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(s.dataId).id,a.dataIdMap.get(o.dataId).id,new Uint8Array(new Int32Array(r.shape).buffer),new Uint8Array(new Int32Array(s.shape).buffer),i),u!=null&&a.disposeData(u.dataId),o}var Sie={kernelName:Mu,backendName:"wasm",setupFunc:kie,kernelFunc:Iie},sk;function Cie(e){sk=e.wasm.cwrap(Mo,null,["number","array","number","array","number","number"])}function Tie(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{dims:s}=n,i=v.parseAxisParam(s,r.shape);if(r.shape.length===0)return l0({inputs:{x:r},backend:a});let o=a.makeOutput(r.shape,r.dtype),l=a.dataIdMap.get(r.dataId).id,u=a.dataIdMap.get(o.dataId).id,p=new Uint8Array(new Int32Array(i).buffer),c=new Uint8Array(new Int32Array(r.shape).buffer);sk(l,p,i.length,c,r.shape.length,u);let d=La({inputs:{x:o},attrs:{shape:r.shape},backend:a});return a.disposeData(o.dataId),d}var Nie={kernelName:Mo,backendName:"wasm",kernelFunc:Tie,setupFunc:Cie},ik;function Rie(e){ik=e.wasm.cwrap(el,null,["number","number","number","number","number","number","number","number","array","number","number"])}function Eie(e){let{inputs:t,backend:a,attrs:n}=e,{image:r}=t,{radians:s,fillValue:i,center:o}=n,l=a.makeOutput(r.shape,r.dtype),u=a.dataIdMap.get(r.dataId).id,p=a.dataIdMap.get(l.dataId).id,[c,d,h,m]=r.shape,[f,g]=C.getImageCenter(o,d,h),y=i===0,x=255,A=typeof i=="number"?[i,i,i,y?0:x]:[...i,x],b=new Uint8Array(new Int32Array(A).buffer);return ik(u,c,d,h,m,s,f,g,b,A.length,p),l}var Mie={kernelName:el,backendName:"wasm",kernelFunc:Eie,setupFunc:Rie},$ie=Qe($o),Pie=Qe(Po),ok;function _ie(e){ok=e.wasm.cwrap(_o,null,["number","number","number","number","number","number","array","number","number"])}function Fie(e){let{backend:t,inputs:a,attrs:n}=e,{indices:r,updates:s}=a,{shape:i}=n,o=t.makeOutput(i,s.dtype);if(v.sizeFromShape(i)===0)return o;let{sliceRank:l,numUpdates:u,sliceSize:p,strides:c,outputSize:d}=jh.calculateShapes(s,r,i),h=t.dataIdMap.get(r.dataId).id,m=t.dataIdMap.get(s.dataId).id,f=new Uint8Array(new Int32Array(c).buffer),g=t.dataIdMap.get(o.dataId).id;return ok(h,m,nt[s.dtype],l,u,p,f,d,g),o}var Die={kernelName:_o,backendName:"wasm",setupFunc:_ie,kernelFunc:Fie},lk;function Oie(e){lk=e.wasm.cwrap(Do,null,["number","number","number","number","number","number","bool","number"])}function zie(e){let{inputs:t,backend:a,attrs:n}=e,{sortedSequence:r,values:s}=t,{side:i}=n;if(r.dtype!==s.dtype)throw new Error(`SearchSorted error: sorted_sequence must have the same dtype as values. Got ${r.dtype} and ${s.dtype}`);let o=a.makeOutput(s.shape,"int32");function l(u){return a.dataIdMap.get(u.dataId).id}return lk(l(r),l(s),r.shape[0],r.shape[1],s.shape[1],nt[r.dtype],i==="left",l(o)),o}var Lie={kernelName:Do,backendName:"wasm",setupFunc:Oie,kernelFunc:zie},uk;function Wie(e){uk=e.wasm.cwrap("SelectV2",null,["number","number","number","number","number"])}function Bie(e){let{inputs:t,backend:a}=e,{condition:n,t:r,e:s}=t,i=a.dataIdMap.get(n.dataId).id,o=a.dataIdMap.get(r.dataId).id,l=a.dataIdMap.get(s.dataId).id,u=a.makeOutput(r.shape,r.dtype),p=a.dataIdMap.get(u.dataId).id,c=n.shape.length,d=r.shape.length,h=c===0||c>1||d===1?1:v.sizeFromShape(r.shape.slice(1));return uk(i,o,l,h,p),u}var Vie={kernelName:Pu,backendName:"wasm",kernelFunc:Bie,setupFunc:Wie},Uie=Qe(Oo),dk;function Gie(e){dk=e.wasm.cwrap(Bo,null,["number","number"])}function Hie(e){let{backend:t,inputs:{x:a}}=e,n=t.dataIdMap.get(a.dataId).id,r=t.makeOutput(a.shape,a.dtype),s=t.dataIdMap.get(r.dataId).id;return v.sizeFromShape(r.shape)===0||dk(n,s),r}var jie={kernelName:"Sigmoid",backendName:"wasm",setupFunc:Gie,kernelFunc:Hie},qie=Qe(Wo),Xie=Qe(zo),Kie=Qe(Lo),Yie=Qe(Vo);function Zie(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockShape:s,paddings:i}=n,o=v.sizeFromShape(s),l=[[0,0]];l.push(...i);for(let g=1+s.length;g<r.shape.length;++g)l.push([0,0]);let u=Jw.kernelFunc({inputs:{x:r},backend:a,attrs:{paddings:l,constantValue:0}}),p=C.getReshaped(u.shape,s,o,!1),c=C.getPermuted(p.length,s.length,!1),d=C.getReshapedPermuted(u.shape,s,o,!1),h=La({inputs:{x:u},backend:a,attrs:{shape:p}}),m=os({inputs:{x:h},backend:a,attrs:{perm:c}}),f=La({inputs:{x:m},backend:a,attrs:{shape:d}});return a.disposeData(u.dataId),a.disposeData(h.dataId),a.disposeData(m.dataId),f}var Jie={kernelName:Fu,backendName:"wasm",kernelFunc:Zie},pk;function Qie(e){pk=e.wasm.cwrap("SparseFillEmptyRows","number",["number","number","number","number","number","number","number","number","number","number","number","number"])}function eoe(e){let{backend:t,inputs:a}=e,{indices:n,values:r,denseShape:s,defaultValue:i}=a,o=n.shape[0],l=n.shape[1],u=t.readSync(s.dataId)[0],p=[o+u,l],c=t.dataIdMap.get(n.dataId).id,d=t.dataIdMap.get(r.dataId).id,h=t.dataIdMap.get(i.dataId).id,m=t.makeOutput(p,n.dtype),f=t.dataIdMap.get(m.dataId).id,g=t.makeOutput(p.slice(0,1),r.dtype),y=t.dataIdMap.get(g.dataId).id,x=t.makeOutput([u],"bool"),A=t.dataIdMap.get(x.dataId).id,b=t.makeOutput([o],n.dtype),w=t.dataIdMap.get(b.dataId).id,I=t.makeOutput([4],"int32"),T=t.dataIdMap.get(I.dataId).id,N=pk(c,d,nt[r.dtype],o,u,l,h,f,y,A,w,T),M=t.readSync(I.dataId),$;switch(M[0]){case 1:{$=C.getSparseFillEmptyRowsIndicesDenseShapeMismatch(M[1]);break}case 2:{$=C.getSparseFillEmptyRowsNegativeIndexErrorMessage(M[1],M[2]);break}case 3:$=C.getSparseFillEmptyRowsOutOfRangeIndexErrorMessage(M[1],M[2],M[3]);break;default:$=""}if(t.disposeData(I.dataId),$)throw t.disposeData(m.dataId),t.disposeData(g.dataId),t.disposeData(x.dataId),t.disposeData(b.dataId),new Error($);let E=m,S=g;return N!==p[0]&&(E=si({inputs:{x:m},attrs:{begin:0,size:[N,l]},backend:t}),S=si({inputs:{x:g},attrs:{begin:0,size:N},backend:t}),t.disposeData(m.dataId),t.disposeData(g.dataId)),[E,S,x,b]}var toe={kernelName:Sp,backendName:"wasm",setupFunc:Qie,kernelFunc:eoe},ck;function aoe(e){ck=e.wasm.cwrap(Ou,null,["number","number","number","number","number","number","number"])}function noe(e){let{backend:t,inputs:a}=e,{inputIndices:n,inputShape:r,newShape:s}=a;if(n.shape.length!==2)throw new Error(`Input indices should be a matrix but received shape
        ${n.shape}`);if(r.shape.length!==1)throw new Error(`Input shape should be a vector but received shape
        ${r.shape}`);if(s.shape.length!==1)throw new Error(`Target shape should be a vector but received shape ${s.shape}`);let i=t.dataIdMap.get(n.dataId).id,o=t.dataIdMap.get(r.dataId).id,l=t.dataIdMap.get(s.dataId).id,u=n.shape[0],p=v.sizeFromShape(s.shape),c=t.makeOutput([u,p],n.dtype),d=t.dataIdMap.get(c.dataId).id,h=t.makeOutput([p],s.dtype),m=t.dataIdMap.get(h.dataId).id,f=t.makeOutput([3],"int32"),g=t.dataIdMap.get(f.dataId).id;ck(i,o,l,u,d,m,g);let y=t.readSync(f.dataId),x;switch(y[0]){case 0:{x=C.getSparseReshapeMultipleNegativeOneOutputDimErrorMessage(y[1],y[2]);break}case 1:{x=C.getSparseReshapeNegativeOutputDimErrorMessage(y[1],y[2]);break}case 2:x=C.getSparseReshapeEmptyTensorZeroOutputDimErrorMessage();break;case 3:{let A=Array.from(t.readSync(r.dataId)),b=Array.from(t.readSync(h.dataId));x=C.getSparseReshapeInputOutputMultipleErrorMessage(A,b);break}case 4:{let A=Array.from(t.readSync(r.dataId)),b=Array.from(t.readSync(h.dataId));x=C.getSparseReshapeInputOutputMismatchErrorMessage(A,b);break}default:x=""}if(t.disposeData(f.dataId),x)throw t.disposeData(c.dataId),t.disposeData(h.dataId),new Error(x);return[c,h]}var roe={kernelName:Ou,backendName:"wasm",setupFunc:aoe,kernelFunc:noe},hk;function mk(e){hk=e.wasm.cwrap("SparseSegmentReduction",null,["number","number","number","number","number","number","number","number","number"])}function fk(e,t){let{backend:a,inputs:n}=e,{data:r,indices:s,segmentIds:i}=n,o=s.shape[0],l=a.readSync(i.dataId,o-1,o)[0],u=o>0?l+1:0;if(u<0)throw new Error(C.getSparseSegmentReductionNegativeSegmentIdsErrorMessage());let p=r.shape.slice();p[0]=u;let c=a.dataIdMap.get(r.dataId).id,d=a.dataIdMap.get(s.dataId).id,h=a.dataIdMap.get(i.dataId).id,m=a.makeOutput(p,r.dtype),f=a.dataIdMap.get(m.dataId).id,g=a.makeOutput([4],"int32"),y=a.dataIdMap.get(g.dataId).id;hk(c,nt[r.dtype],r.shape[0],d,h,f,y,t,0);let x=a.readSync(g.dataId),A;switch(x[0]){case 0:{A=C.getSparseSegmentReductionNegativeSegmentIdsErrorMessage();break}case 1:{A=C.getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage();break}case 2:A=C.getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage(x[1],x[2]);break;case 3:A=C.getSparseSegmentReductionIndicesOutOfRangeErrorMessage(x[1],x[2],x[3]);break;default:A=""}if(a.disposeData(g.dataId),A)throw a.disposeData(m.dataId),new Error(A);return m}function soe(e){return fk(e,!0)}var ioe={kernelName:zu,backendName:"wasm",setupFunc:mk,kernelFunc:soe};function ooe(e){return fk(e,!1)}var loe={kernelName:Lu,backendName:"wasm",setupFunc:mk,kernelFunc:ooe},gk;function uoe(e){gk=e.wasm.cwrap(jo,null,["number","number","number","number","number","number","number","number","array","number","number"])}function doe(e){let{backend:t,inputs:a,attrs:n}=e,{sparseIndices:r,sparseValues:s,defaultValue:i}=a,{outputShape:o}=n,l=t.makeOutput(o,i.dtype);if(v.sizeFromShape(o)===0)return l;let{sliceRank:u,numUpdates:p,sliceSize:c,strides:d,outputSize:h}=C.calculateShapes(s,r,o),m=t.dataIdMap.get(r.dataId).id,f=t.dataIdMap.get(s.dataId).id,g=t.dataIdMap.get(i.dataId).id,y=new Uint8Array(new Int32Array(d).buffer),x=t.dataIdMap.get(l.dataId).id;return gk(m,f,s.shape.length,g,nt[i.dtype],u,p,c,y,h,x),l}var poe={kernelName:jo,backendName:"wasm",setupFunc:uoe,kernelFunc:doe};function coe(e){let{inputs:t,attrs:a,backend:n}=e,{x:r}=t,{numOrSizeSplits:s,axis:i}=a,o=v.parseAxisParam(i,r.shape)[0],l=C.prepareSplitSize(r,s,o),u=new Array(r.shape.length).fill(0),p=r.shape.slice();return l.map(c=>{let d=[...p];d[o]=c;let h=si({inputs:{x:r},attrs:{begin:u,size:d},backend:n});return u[o]+=c,h})}var hoe={kernelName:Du,backendName:"wasm",kernelFunc:coe},moe=Qe(Uo),foe=Qe(Cp),goe=!0,yoe=Gt(qo,goe),yk;function xoe(e){yk=e.wasm.cwrap(ps,null,["number","number","number","number"])}function Aoe(e){let{backend:t,inputs:a,attrs:n}=e,{alpha:r}=n,{x:s}=a,i=t.dataIdMap.get(s.dataId).id,o=t.makeOutput(s.shape,s.dtype),l=t.dataIdMap.get(o.dataId).id;return yk(i,r,nt[s.dtype],l),o}var boe={kernelName:ps,backendName:"wasm",setupFunc:xoe,kernelFunc:Aoe},xk;function voe(e){xk=e.wasm.cwrap(Xo,null,["number","array","number","array","array","array","array","array","number","number"])}function woe(e){let{backend:t,inputs:a,attrs:n}=e,{x:r}=a,{begin:s,end:i,strides:o,beginMask:l,endMask:u,ellipsisMask:p,newAxisMask:c,shrinkAxisMask:d}=n,{finalShapeSparse:h,finalShape:m,isIdentity:f,sliceDim0:g,isSimpleSlice:y,begin:x,end:A,strides:b}=Nt.sliceInfo(r.shape,s,i,o,l,u,p,c,d),w;if(f)w=La({inputs:{x:r},backend:t,attrs:{shape:m}});else if(g||y){v.assert(r.shape.length>=1,()=>`Input must have rank at least 1, got: ${r.shape.length}`);let I=Nt.computeOutShape(x,A,b),T=si({inputs:{x:r},backend:t,attrs:{begin:x,size:I}});w=La({inputs:{x:T},backend:t,attrs:{shape:m}}),t.disposeData(T.dataId)}else{let I=t.makeOutput(h,"float32"),T=t.dataIdMap.get(r.dataId).id,N=new Uint8Array(new Int32Array(v.computeStrides(r.shape)).buffer),M=new Uint8Array(new Int32Array(x).buffer),$=new Uint8Array(new Int32Array(A).buffer),E=new Uint8Array(new Int32Array(b).buffer),S=new Uint8Array(new Int32Array(h).buffer),_=new Uint8Array(new Int32Array(v.computeStrides(h)).buffer),O=t.dataIdMap.get(I.dataId).id;xk(T,N,r.shape.length,M,$,E,S,_,h.length,O),w=La({inputs:{x:I},backend:t,attrs:{shape:m}}),t.disposeData(I.dataId)}return w}var koe={kernelName:Xo,backendName:"wasm",setupFunc:voe,kernelFunc:woe};function Ioe(e){let{backend:t,inputs:a,attrs:n}=e,{data:r,dataSplits:s}=a,{separator:i,nGramWidths:o,leftPad:l,rightPad:u,padWidth:p,preserveShortSequences:c}=n,d=t.readSync(r.dataId),h=t.readSync(s.dataId),[m,f]=A3(d,h,i,o,l,u,p,c),g=t.makeOutput([m.length],"string"),y=t.dataIdMap.get(g.dataId);y.stringBytes=m;let x=t.makeOutput(s.shape,"int32");return t.typedArrayFromHeap(x).set(f),[g,x]}var Soe={kernelName:Wu,backendName:"wasm",kernelFunc:Ioe};function Coe(e){let{backend:t,inputs:a,attrs:n}=e,{input:r,delimiter:s}=a,{skipEmpty:i}=n,o=t.readSync(r.dataId),l=t.readSync(s.dataId),[u,p,c]=b3(o,l[0],i),d=p.length,h=t.makeOutput([d,2],"int32");t.typedArrayFromHeap(h).set(u);let m=t.makeOutput([d],"string"),f=t.dataIdMap.get(m.dataId);f.stringBytes=p;let g=t.makeOutput([2],"int32");return t.typedArrayFromHeap(g).set(c),[h,m,g]}var Toe={kernelName:Np,backendName:"wasm",kernelFunc:Coe};function Noe(e){let{backend:t,inputs:a,attrs:n}=e,{input:r}=a,{numBuckets:s}=n,i=t.readSync(r.dataId),o=v3(i,s),l=t.makeOutput(r.shape,"int32");return t.typedArrayFromHeap(l).set(o),l}var Roe={kernelName:Rp,backendName:"wasm",kernelFunc:Noe},Eoe=!0,Moe=Gt(Ko,Eoe),Ak;function $oe(e){Ak=e.wasm.cwrap(Go,null,["number","number","number","number"])}function Poe(e){let{backend:t,inputs:a,attrs:n}=e,{axis:r,keepDims:s}=n,{x:i}=a,o=t.dataIdMap.get(i.dataId).id,l=o,u=i,{transposed:p,axes:c,originalAxes:d,inputWasTransposed:h}=gs(i,r,t),m=c;if(h){let A=t.dataIdMap.get(p.dataId).id;A!==o&&(u=p,l=A,m=C.getInnerMostAxes(m.length,u.shape.length))}C.assertAxesAreInnerMostDims("sum",m,u.shape.length);let[f,g]=C.computeOutAndReduceShapes(u.shape,m),y=v.sizeFromShape(g),x=t.makeOutput(f,u.dtype);if(v.sizeFromShape(u.shape)!==0){let A=t.dataIdMap.get(x.dataId).id;Ak(l,y,nt[x.dtype],A)}if(h&&t.disposeData(p.dataId),s){let A=C.expandShapeToKeepDim(x.shape,d);x.shape=A}return x}var _oe={kernelName:Go,backendName:"wasm",setupFunc:$oe,kernelFunc:Poe},Foe=Qe(Yo),Doe=Qe(Zo),bk;function Ooe(e){bk=e.wasm.cwrap(Fo,null,["number","number","number","number","number","number","array","number","number","number"])}function zoe(e){let{backend:t,inputs:a,attrs:n}=e,{tensor:r,indices:s,updates:i}=a,{}=n,o=t.makeOutput(r.shape,r.dtype);if(v.sizeFromShape(r.shape)===0)return o;let{sliceRank:l,numUpdates:u,sliceSize:p,strides:c,outputSize:d}=jh.calculateShapes(i,s,r.shape),h=t.dataIdMap.get(s.dataId).id,m=t.dataIdMap.get(i.dataId).id,f=t.dataIdMap.get(r.dataId).id,g=new Uint8Array(new Int32Array(c).buffer),y=t.dataIdMap.get(o.dataId).id;return bk(h,m,nt[i.dtype],l,u,p,g,d,y,f),o}var Loe={kernelName:Fo,backendName:"wasm",setupFunc:Ooe,kernelFunc:zoe},vk;function Woe(e){vk=e.wasm.cwrap(ds,null,["number","array","number","array","number","number"])}function Boe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,s=a.dataIdMap.get(r.dataId).id,{reps:i}=n,o=new Array(r.shape.length);for(let d=0;d<o.length;d++)o[d]=r.shape[d]*i[d];let l=new Uint8Array(new Int32Array(r.shape).buffer),u=new Uint8Array(new Int32Array(o).buffer),p=a.makeOutput(o,r.dtype),c=a.dataIdMap.get(p.dataId).id;return vk(s,l,r.shape.length,u,o.length,nt[p.dtype],c),p}var Voe={kernelName:ds,backendName:"wasm",setupFunc:Woe,kernelFunc:Boe},wk;function Uoe(e){wk=e.wasm.cwrap(Jo,null,["number","array","number","number","number","bool","number","number"])}var Goe=({inputs:e,backend:t,attrs:a})=>{let{x:n}=e,{k:r,sorted:s}=a,i=t.dataIdMap.get(n.dataId).id,o=new Uint8Array(new Int32Array(n.shape).buffer),l=n.shape.slice();l[l.length-1]=r;let u=t.makeOutput(l,n.dtype),p=t.dataIdMap.get(u.dataId).id,c=t.makeOutput(l,"int32"),d=t.dataIdMap.get(c.dataId).id;return wk(i,o,n.shape.length,nt[n.dtype],r,s,p,d),[u,c]},Hoe={kernelName:Jo,backendName:"wasm",setupFunc:Uoe,kernelFunc:Goe},kk;function joe(e){kk=e.wasm.cwrap(Qo,null,["number","number","bool","number","number","number","number","number","number","array","number","array","number","number","number","number","number"])}function qoe(e){let{backend:t,inputs:a,attrs:n}=e,{image:r,transforms:s}=a,{interpolation:i,fillMode:o,fillValue:l,outputShape:u}=n,[p,c,d,h]=r.shape,[m,f]=u!=null?u:[c,d],g=[p,m,f,h],y=new Uint8Array(new Int32Array(v.computeStrides(r.shape)).buffer),x=new Uint8Array(new Int32Array(v.computeStrides(g)).buffer),A=t.makeOutput(g,r.dtype),b=t.dataIdMap.get(A.dataId).id,w=t.dataIdMap.get(r.dataId).id,I=t.dataIdMap.get(s.dataId).id,T=i==="nearest"?1:2,N;switch(o){case"constant":N=1;break;case"reflect":N=2;break;case"wrap":N=3;break;case"nearest":N=4;break;default:N=1;break}return kk(w,I,s.shape[0]>1,p,m,f,h,d,c,y,r.shape.length-1,x,g.length-1,T,N,l,b),A}var Xoe={kernelName:Qo,backendName:"wasm",setupFunc:joe,kernelFunc:qoe};function Koe(e){let{inputs:t,attrs:a,backend:n}=e,{axis:r}=a,{x:s}=t,{outputValues:i,outputShape:o,indices:l}=k3(n.readSync(s.dataId),r,s.shape,s.dtype);return[n.makeOutput(o,s.dtype,void 0,i),n.makeOutput([l.length],"int32",void 0,l)]}var Yoe={kernelName:Ep,backendName:"wasm",kernelFunc:Koe};function Zoe(e){let{inputs:t,backend:a,attrs:n}=e,{value:r}=t,{axis:s}=n;s<0&&(s+=r.shape.length);let i=r.shape[s],o=r.shape.length,l=new Array(o-1),u=0;for(let h=0;h<o;h++)h!==s&&(l[u++]=r.shape[h]);let p=new Array(i),c=new Array(o).fill(0),d=r.shape.slice();d[s]=1;for(let h=0;h<p.length;h++)c[s]=h,p[h]=si({inputs:{x:r},attrs:{begin:c,size:d},backend:a});return p.map(({dataId:h,dtype:m})=>({dataId:h,dtype:m,shape:l}))}var Joe={kernelName:Bu,backendName:"wasm",kernelFunc:Zoe};function Qoe(e){let{inputs:{x:t},backend:a}=e,n=a.makeOutput(t.shape,t.dtype);return a.typedArrayFromHeap(n).fill(0),n}var ele={kernelName:Vu,backendName:"wasm",kernelFunc:Qoe},tle=[Dte,Ote,zte,Lte,Bte,Gte,Jte,tae,aae,nae,rae,sae,iae,oae,lae,pae,bae,mae,yae,Iae,Eae,Pae,Fae,Oae,zae,Lae,Vae,Uae,jae,Kae,Jae,tne,rne,sne,ine,une,cne,fne,xne,vne,Ine,Tne,Ene,Pne,Dne,One,Wne,Vne,Une,Gne,Hne,jne,qne,Yne,Zne,Qne,are,sre,lre,pre,mre,gre,xre,Hte,Are,bre,vre,Ire,Cre,Nre,Mre,Pre,$re,Fre,Dre,zre,Wre,Ure,jre,Kre,Zre,ese,nse,ise,use,cse,fse,xse,bse,kse,Nse,Rse,Mse,$se,Fse,zse,Bse,Use,jse,Xse,Yse,Jw,eie,nie,iie,lie,die,pie,cie,hie,vae,gie,Aie,wie,Sie,Nie,Mie,$ie,Pie,Die,Lie,Vie,Uie,jie,qie,Xie,Kie,Nae,Sse,Yie,Jie,toe,roe,ioe,loe,poe,hoe,moe,foe,yoe,boe,koe,Soe,Toe,Roe,Moe,_oe,Foe,Doe,Loe,Voe,Hoe,Xoe,Kte,Yoe,Joe,ele];for(let e of tle)xn(e);var H1=B();H1.registerFlag("WASM_HAS_SIMD_SUPPORT",async()=>{try{return WebAssembly.validate(new Uint8Array([0,97,115,109,1,0,0,0,1,4,1,96,0,0,3,2,1,0,10,9,1,7,0,65,0,253,15,26,11]))}catch(e){return!1}});H1.registerFlag("WASM_HAS_MULTITHREAD_SUPPORT",async()=>{if(H1.get("IS_NODE"))return!1;try{return new MessageChannel().port1.postMessage(new SharedArrayBuffer(1)),WebAssembly.validate(new Uint8Array([0,97,115,109,1,0,0,0,1,4,1,96,0,0,3,2,1,0,5,4,1,3,1,1,10,11,1,9,0,65,0,254,16,2,0,26,11]))}catch(e){return!1}});var K5=ru(nT()),ale=ru(rT()),Y5=ru(sT()),Z5=K5.default||K5,nle=Y5.default||Y5,Ik=class extends su{constructor(e){super(),this.wasm=e,this.dataIdNextNumber=1,this.wasm.tfjs.initWithThreadsCount(Sk),j1=this.wasm.tfjs.getThreadsCount(),this.dataIdMap=new op(this,It())}write(e,t,a){let n={id:this.dataIdNextNumber++};return this.move(n,e,t,a,1),n}numDataIds(){return this.dataIdMap.numDataIds()}async time(e){let t=v.now();return e(),{kernelMs:v.now()-t}}move(e,t,a,n,r){let s=this.dataIdNextNumber++;if(n==="string"){let u=t;this.dataIdMap.set(e,{id:s,stringBytes:u,shape:a,dtype:n,memoryOffset:null,refCount:r});return}let i=v.sizeFromShape(a),o=i*v.bytesPerElement(n),l=this.wasm._malloc(o)>>>0;this.dataIdMap.set(e,{id:s,memoryOffset:l,shape:a,dtype:n,refCount:r}),this.wasm.tfjs.registerTensor(s,i,l),t!=null&&this.wasm.HEAPU8.set(new Uint8Array(t.buffer,t.byteOffset,o),l)}async read(e){return this.readSync(e)}readSync(e,t,a){let{memoryOffset:n,dtype:r,shape:s,stringBytes:i}=this.dataIdMap.get(e);if(r==="string")return(t==null||t===0)&&(a==null||a>=i.length)?i:i.slice(t,a);t=t||0,a=a||v.sizeFromShape(s);let o=v.bytesPerElement(r),l=this.wasm.HEAPU8.slice(n+t*o,n+a*o);return ile(l.buffer,r)}disposeData(e,t=!1){if(this.dataIdMap.has(e)){let a=this.dataIdMap.get(e);if(a.refCount--,!t&&a.refCount>0)return!1;this.wasm._free(a.memoryOffset),this.wasm.tfjs.disposeData(a.id),this.dataIdMap.delete(e)}return!0}refCount(e){return this.dataIdMap.has(e)?this.dataIdMap.get(e).refCount:0}incRef(e){let t=this.dataIdMap.get(e);t!=null&&t.refCount++}floatPrecision(){return 32}getMemoryOffset(e){return this.dataIdMap.get(e).memoryOffset}dispose(){this.wasm.tfjs.dispose(),"PThread"in this.wasm&&this.wasm.PThread.terminateAllThreads(),this.wasm=null}memory(){return{unreliable:!1}}makeOutput(e,t,a,n){let r;if(a==null)r=this.write(n!=null?n:null,e,t);else{let s=this.dataIdNextNumber++;r={id:s},this.dataIdMap.set(r,{id:s,memoryOffset:a,shape:e,dtype:t,refCount:1});let i=v.sizeFromShape(e);this.wasm.tfjs.registerTensor(s,i,a)}return{dataId:r,shape:e,dtype:t}}typedArrayFromHeap({shape:e,dtype:t,dataId:a}){let n=this.wasm.HEAPU8.buffer,{memoryOffset:r}=this.dataIdMap.get(a),s=v.sizeFromShape(e);switch(t){case"float32":return new Float32Array(n,r,s);case"int32":return new Int32Array(n,r,s);case"bool":return new Uint8Array(n,r,s);default:throw new Error(`Unknown dtype ${t}`)}}};function rle(e){return(t,a)=>(v.fetch(e,{credentials:"same-origin"}).then(n=>{n.ok||t.env.a(`failed to load wasm binary file at '${e}'`),n.arrayBuffer().then(r=>{WebAssembly.instantiate(r,t).then(s=>{a(s.instance,s.module)})})}),{})}function J5(e,t,a){if(Ch!=null)return Ch;let n="tfjs-backend-wasm.wasm";return e&&t?n="tfjs-backend-wasm-threaded-simd.wasm":e&&(n="tfjs-backend-wasm-simd.wasm"),Dd!=null&&Dd[n]!=null?Dd[n]:a+n}async function sle(){let[e,t]=await Promise.all([B().getAsync("WASM_HAS_SIMD_SUPPORT"),B().getAsync("WASM_HAS_MULTITHREAD_SUPPORT")]);return new Promise((a,n)=>{let r={};r.locateFile=(o,l)=>{if(o.endsWith(".worker.js")){let u=ale.wasmWorkerContents.replace(/\n/g,"\\n"),p=new Blob([u],{type:"application/javascript"});return URL.createObjectURL(p)}return o.endsWith(".wasm")?J5(e,t,Pd!=null?Pd:l):l+o},U3&&(r.instantiateWasm=rle(J5(e,t,Pd!=null?Pd:"")));let s=!1;r.onAbort=()=>{s||Od||(Od=!0,n({message:"Make sure the server can serve the `.wasm` file relative to the bundled js file. For more details see https://github.com/tensorflow/tfjs/blob/master/tfjs-backend-wasm/README.md#using-bundlers"}))};let i;t&&e&&Ch==null?(r.mainScriptUrlOrBlob=new Blob(["var WasmBackendModuleThreadedSimd = "+Z5.toString()],{type:"text/javascript"}),i=Z5(r)):i=nle(r),i.then(o=>{s=!0,Od=!1;let l=null;o.tfjs={init:o.cwrap("init",null,[]),initWithThreadsCount:o.cwrap("init_with_threads_count",null,["number"]),getThreadsCount:o.cwrap("get_threads_count","number",[]),registerTensor:o.cwrap("register_tensor",null,["number","number","number"]),disposeData:o.cwrap("dispose_data",l,["number"]),dispose:o.cwrap("dispose",l,[])},a({wasm:o})}).catch(n)})}function ile(e,t){switch(t){case"float32":return new Float32Array(e);case"int32":return new Int32Array(e);case"bool":return new Uint8Array(e);default:throw new Error(`Unknown dtype ${t}`)}}var ole=["tfjs-backend-wasm.wasm","tfjs-backend-wasm-simd.wasm","tfjs-backend-wasm-threaded-simd.wasm"],Ch=null,Pd=null,Dd={},Od=!1,U3=!1;function lle(e,t=!1){if(og("setWasmPath has been deprecated in favor of setWasmPaths and will be removed in a future release."),Od)throw new Error("The WASM backend was already initialized. Make sure you call `setWasmPath()` before you call `tf.setBackend()` or `tf.ready()`");Ch=e,U3=t}function u0(e,t=!1){if(Od)throw new Error("The WASM backend was already initialized. Make sure you call `setWasmPaths()` before you call `tf.setBackend()` or `tf.ready()`");if(typeof e=="string")Pd=e;else{Dd=e;let a=ole.filter(n=>Dd[n]==null);if(a.length>0)throw new Error(`There were no entries found for the following binaries: ${a.join(",")}. Please either call setWasmPaths with a map providing a path for each binary, or with a string indicating the directory where all the binaries can be found.`)}U3=t}var Sk=-1,j1=-1;function ule(e){Sk=e}function dle(){if(j1===-1)throw new Error("WASM backend not initialized.");return j1}var ple="4.22.0",cle=2;al("wasm",async()=>{let{wasm:e}=await sle();return new Ik(e)},cle);var An=B();An.registerFlag("WEBGPU_DEFERRED_SUBMIT_BATCH_SIZE",()=>15);An.registerFlag("WEBGPU_CPU_FORWARD",()=>!0);An.registerFlag("WEBGPU_MATMUL_PROGRAM_TYPE",()=>-1);An.registerFlag("WEBGPU_USE_NAIVE_CONV2D_TRANSPOSE",()=>!0);An.registerFlag("WEBGPU_USE_LOW_POWER_GPU",()=>!1);An.registerFlag("WEBGPU_CPU_HANDOFF_SIZE_THRESHOLD",()=>1e3);An.registerFlag("WEBGPU_USE_PROFILE_TOOL",()=>!1);An.registerFlag("WEBGPU_IMPORT_EXTERNAL_TEXTURE",()=>!0);An.registerFlag("WEBGPU_USE_NAIVE_CONV2D_DEBUG",()=>!1);An.registerFlag("WEBGPU_THRESHOLD_TO_INCREASE_WORKGROUPS_FOR_MATMUL",()=>-1);An.registerFlag("WEBGPU_CONV_SEPARATE_IM2COL_SHADER",()=>!1);An.registerFlag("WEBGPU_PRINT_SHADER",()=>"");An.registerFlag("WEBGPU_ENGINE_COMPILE_ONLY",()=>!1);var hle=class{constructor(e){e&&(this.vendor=e.vendor,this.architecture=e.architecture,this.intelGPUGeneration=this.getIntelGPUGeneration())}getIntelGPUGeneration(){if(this.isIntel()){if(this.architecture.startsWith("gen"))return Number(this.architecture.match(/\d+/));if(this.architecture.startsWith("xe"))return 12}return 0}isIntel(){return this.vendor==="intel"}},mle=class{constructor(e){this.device=e,this.numUsedBuffers=0,this.numFreeBuffers=0,this.freeBuffers=new Map,this.usedBuffers=new Map,this.numBytesUsed=0,this.numBytesAllocated=0}acquireBuffer(e,t,a=!1,n=!0){let r,s=Q5(e,t);return n?(this.freeBuffers.has(s)||this.freeBuffers.set(s,[]),this.freeBuffers.get(s).length>0?(r=this.freeBuffers.get(s).pop(),this.numFreeBuffers--):(r=this.device.createBuffer({size:e,usage:t,mappedAtCreation:a}),this.numBytesAllocated+=e)):(r=this.device.createBuffer({size:e,usage:t,mappedAtCreation:a}),this.numBytesAllocated+=e),this.usedBuffers.has(s)||this.usedBuffers.set(s,[]),this.usedBuffers.get(s).push(r),this.numUsedBuffers++,this.numBytesUsed+=e,r}releaseBuffer(e,t=!0){if(this.freeBuffers.size===0)return;let a=e.size,n=e.usage,r=Q5(a,n),s=this.usedBuffers.get(r),i=s.indexOf(e);if(i<0)throw new Error("Cannot find the buffer in buffer manager");s[i]=s[s.length-1],s.pop(),this.numUsedBuffers--,this.numBytesUsed-=a,t?(this.freeBuffers.get(r).push(e),this.numFreeBuffers++):(e.destroy(),this.numBytesAllocated-=a)}getNumUsedBuffers(){return this.numUsedBuffers}getNumFreeBuffers(){return this.numFreeBuffers}dispose(){this.freeBuffers.forEach((e,t)=>{e.forEach(a=>{a.destroy()})}),this.usedBuffers.forEach((e,t)=>{e.forEach(a=>{a.destroy()})}),this.freeBuffers=new Map,this.usedBuffers=new Map,this.numUsedBuffers=0,this.numFreeBuffers=0,this.numBytesUsed=0,this.numBytesAllocated=0}};function Q5(e,t){return`${e}_${t}`}var fle=class{constructor(e){this.device=e,this.numUsedTextures=0,this.numFreeTextures=0,this.freeTextures=new Map,this.usedTextures=new Map,this.numBytesUsed=0,this.numBytesAllocated=0}acquireTexture(e,t,a,n){let r=tA(a),s=e*t*r,i=eA(e,t,a,n);if(this.freeTextures.has(i)||this.freeTextures.set(i,[]),this.usedTextures.has(i)||this.usedTextures.set(i,[]),this.numBytesUsed+=s,this.numUsedTextures++,this.freeTextures.get(i).length>0){this.numFreeTextures--;let l=this.freeTextures.get(i).shift();return this.usedTextures.get(i).push(l),l}this.numBytesAllocated+=s;let o=this.device.createTexture({size:[e,t],format:a,usage:n});return this.usedTextures.get(i).push(o),o}releaseTexture(e){if(this.freeTextures.size===0)return;let t=e.width,a=e.height,n=e.format,r=e.usage,s=eA(t,a,n,r);this.freeTextures.has(s)||this.freeTextures.set(s,[]),this.freeTextures.get(s).push(e),this.numFreeTextures++,this.numUsedTextures--;let i=this.usedTextures.get(s),o=i.indexOf(e);if(o<0)throw new Error("Cannot release a texture that was never provided by this texture manager");i.splice(o,1);let l=tA(n),u=t*a*l;this.numBytesUsed-=u}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){this.freeTextures.forEach((e,t)=>{e.forEach(a=>{a.destroy()})}),this.usedTextures.forEach((e,t)=>{e.forEach(a=>{a.destroy()})}),this.freeTextures=new Map,this.usedTextures=new Map,this.numUsedTextures=0,this.numFreeTextures=0,this.numBytesUsed=0,this.numBytesAllocated=0}};function eA(e,t,a,n){return`${e}_${t}_${a}_${n}`}function tA(e){if(e==="rgba8unorm")return 16;throw new Error(`${e} is not supported!`)}function gle(e,t){if(Math.max(...e)>5)throw new Error("Cannot symbolically compute strides for rank > 6 tensor.");let a=e.length,n="xyzwuv",r=e.map(i=>`${t}.${n[i]}`),s=new Array(a-1);s[a-2]=r[a-1];for(let i=a-3;i>=0;--i)s[i]=`(${s[i+1]} * ${r[i+1]})`;return s}var xs=(e,t,a)=>a==="int32"?`atomicAdd(${e}, bitcast<i32>(${t}));`:`
          {
            var oldValue = 0;
            loop {
              let newValueF32 = bitcast<f32>(oldValue) + (${t});
              let newValue = bitcast<i32>(newValueF32);
              let res = atomicCompareExchangeWeak(${e}, oldValue, newValue);
              if res.exchanged {
                break;
              }
              oldValue = res.old_value;
            }
          }`,nu;(function(e){e[e.FROM_PIXELS=0]="FROM_PIXELS",e[e.DRAW=1]="DRAW"})(nu||(nu={}));var yle=(e,t,a,n,r)=>{let s={dtype:n.dtype,shape:n.shape},i=Ale(a,s,t),o=e.createShaderModule({code:i,label:t.constructor.name}),l=B().get("WEBGPU_PRINT_SHADER");if(l!==""){l=l.toLowerCase();let u=l.split(",");(l==="all"||u.some(p=>t.shaderKey.toLowerCase().includes(p)))&&(console.group(t.shaderKey),console.debug(i),console.groupEnd())}return r?e.createComputePipelineAsync({compute:{module:o,entryPoint:"_start"},label:t.constructor.name,layout:"auto"}):e.createComputePipeline({compute:{module:o,entryPoint:"_start"},label:t.constructor.name,layout:"auto"})},Xe=(e,t="f32")=>{switch(e){case 1:return`${t}`;case 2:return`vec2<${t}>`;case 3:return`vec3<${t}>`;case 4:return`vec4<${t}>`;default:throw new Error(`${e}-component ${t} is not supported.`)}};function Pt(e){if(e<=1)return"i32";if(e===2)return"vec2<i32>";if(e===3)return"vec3<i32>";if(e===4)return"vec4<i32>";if(e===5)return"vec5";if(e===6)return"vec6";throw Error(`GPU for rank ${e} is not yet supported`)}function Cr(e){if(e===0)return"x";if(e===1)return"y";if(e===2)return"z";if(e===3)return"w";if(e===4)return"u";if(e===5)return"v";throw Error(`Index ${e} is not yet supported`)}function ue(...e){let t;switch(e.length){case 0:t=`
        fn main()
      `;break;case 1:t=`
        fn main(${e[0]} : i32)
      `;break;default:throw Error("Unreachable")}return t}function aA(e,t){let a;return a=`
     ${xle(t)}
      fn _start(@builtin(local_invocation_id) LocalId : vec3<u32>,
                @builtin(global_invocation_id) GlobalId : vec3<u32>,
                @builtin(local_invocation_index) LocalIndex: u32,
                @builtin(workgroup_id) WorkgroupId : vec3<u32>,
                @builtin(num_workgroups) NumWorkgroups : vec3<u32>) {
        localId = LocalId;
        localIndex = LocalIndex;
        globalId = GlobalId;
        numWorkgroups = NumWorkgroups;
        workgroupId = WorkgroupId;
        ${e?"main(getGlobalIndex());":"main();"};
      }
    `,a}function xle(e){return`
  @compute @workgroup_size(${e.workgroupSize[0]}, ${e.workgroupSize[1]}, ${e.workgroupSize[2]})
`}function Ale(e,t,a){let n=[],r=a.workgroupSize[0]*a.workgroupSize[1]*a.workgroupSize[2];if(a.outputComponent=a.outputComponent?a.outputComponent:1,n.push(`

      var<private> localId: vec3<u32>;
      var<private> localIndex: u32;
      var<private> globalId: vec3<u32>;
      var<private> numWorkgroups: vec3<u32>;
      var<private> workgroupId: vec3<u32>;

      // Only used when the y/z dimension of workgroup size is 1.
      fn getGlobalIndex() -> i32 {
        ${Ck(a)?"  return i32(globalId.x);":`  return i32((workgroupId.z * numWorkgroups.x * numWorkgroups.y +
                workgroupId.y * numWorkgroups.x + workgroupId.x) * ${r}u +
                localIndex);
        `}
      }
    `),a.pixelsOpType!=null){let h=a.pixelsOpType===nu.FROM_PIXELS?`@group(0) @binding(0) var<storage, read_write> result: array<${Hs(t.dtype,a.outputComponent)}>;`:`@group(0) @binding(1) var<storage, read> inBuf : array<${Hs(e[0].dtype,a.outputComponent)}>;`,m=t.shape.length===3?"vec2<i32>":"i32";n.push(`
        struct Uniform {
          outShapeStrides : ${m},
          size            : i32,
          numChannels     : i32,
          alpha           : f32,
        };

        ${h}
        @group(0) @binding(2) var<uniform> uniforms: Uniform;
      `);let f=rA(a);return[nA,n.join(`
`),lh(t.shape),a.getUserCode(),aA(f,a)].join(`
`)}let s,i,o="struct Uniforms { NAN : f32, INFINITY : f32, ";a.variableNames.forEach((h,m)=>{let f=Pt(e[m].shape.length);o+=`${h.charAt(0).toLowerCase()+h.slice(1)}Shape : ${f}, `,s=e[m].shape.length-1,i=Pt(s),o+=`${h.charAt(0).toLowerCase()+h.slice(1)}ShapeStrides: ${i}, `});let l=Pt(t.shape.length);o+=`outShape : ${l}, `,s=t.shape.length-1,i=Pt(s),o+=`
         outShapeStrides: ${i}, `,a.size&&(o+="size : i32, "),a.uniforms&&(o+=a.uniforms),o+="};",o=Nle(o),n.push(o),a.atomic?n.push(`
      @group(0) @binding(0) var<storage, read_write> result: array<atomic<i32>>;
    `):n.push(`
      @group(0) @binding(0) var<storage, read_write> result: array<${Hs(t.dtype,a.outputComponent)}>;
    `),a.variableNames.forEach((h,m)=>{n.push(`
      @group(0) @binding(${1+m}) var<storage, read> ${h}: array<${a.variableComponents?Hs(e[m].dtype,a.variableComponents[m]):Hs(e[m].dtype,a.outputComponent)}>;
        `)}),o!==""&&n.push(`
      @group(0) @binding(${1+a.variableNames.length}) var<uniform> uniforms: Uniforms;
      `);let u=Sle(t.shape,a.dispatchLayout),p=[nA,n.join(`
`)+vle,lh(t.shape),u,Cle(t.shape.length)];a.atomic||p.push(Tle(t.shape,t.dtype,a.outputComponent)),a.variableNames.forEach((h,m)=>{p.push(`${lh(e[m].shape,h)}`)});let c=e.map((h,m)=>Ile(h,t.shape,a.variableComponents?a.variableComponents[m]:a.outputComponent,a.dispatchLayout.x.length===t.shape.length)).join(`
`);p.push(c),p.push(a.getUserCode());let d=rA(a);return p.push(aA(d,a)),p.join(`
`)}function ble(e,t,a){let n=e.shaderKey;if(e.pixelsOpType!=null)return n;let r=[],s=[];t.forEach(p=>{r.push(p.shape),s.push(p.dtype)}),r.push(a.shape),s.push(a.dtype);let i=t.map(p=>C.getBroadcastDims(p.shape,a.shape)),o=t.map(p=>v.arraysEqual(p.shape,a.shape)).join("_"),l=i.map(p=>p.join("_")).join(";"),u=Ck(e)?"flatDispatch":"";return n+="_"+(e.workgroupSize?e.workgroupSize.join(","):"")+r.map(p=>p.length).join(",")+s.join(",")+e.variableNames.join(",")+l+o+u,n}var nA=`
  struct vec5 {x: i32, y: i32, z: i32, w: i32, u: i32};
  struct vec6 {x: i32, y: i32, z: i32, w: i32, u: i32, v: i32};

  // Checks whether coordinates lie within the bounds of the shape.
  fn coordsInBounds2D(coord : vec2<i32>, shape : vec2<i32>) -> bool {
    return all(coord >= vec2<i32>(0)) && all(coord < shape);
  }
  fn coordsInBounds3D(coord : vec3<i32>, shape : vec3<i32>) -> bool {
    return all(coord >= vec3<i32>(0)) && all(coord < shape);
  }
  fn coordsInBounds4D(coord : vec4<i32>, shape : vec4<i32>) -> bool {
    return all(coord >= vec4<i32>(0)) && all(coord < shape);
  }

  fn getIndexFromCoords1D(coord : i32, shape : i32) -> i32 {
    return coord;
  }
  fn getIndexFromCoords2D(coords : vec2<i32>, shape : vec2<i32>) -> i32 {
    return dot(coords, vec2<i32>(shape.y, 1));
  }
  fn getIndexFromCoords3D(coords : vec3<i32>, shape : vec3<i32>) -> i32 {
    return dot(coords, vec3<i32>(shape.y * shape.z, shape.z, 1));
  }
  fn getIndexFromCoords4D(coords : vec4<i32>, shape : vec4<i32>) -> i32 {
    return dot(coords, vec4<i32>(
        shape.y * shape.z * shape.w, shape.z * shape.w, shape.w, 1));
  }
  fn getIndexFromCoords5D(coords : vec5, shape : vec5) -> i32 {
    let shapeStrides: vec5 = vec5(shape.y * shape.z * shape.w * shape.u, shape.z * shape.w * shape.u, shape.w * shape.u, shape.u, 1);
    return coords.x*shapeStrides.x + coords.y*shapeStrides.y + coords.z*shapeStrides.z + coords.w*shapeStrides.w + coords.u*shapeStrides.u;
  }
  fn getIndexFromCoords6D(coords : vec6, shape : vec6) -> i32 {
    let shapeStrides: vec6 = vec6(shape.y * shape.z * shape.w * shape.u * shape.v, shape.z * shape.w * shape.u * shape.v, shape.w * shape.u * shape.v, shape.u * shape.v, shape.v, 1);
    return coords.x*shapeStrides.x + coords.y*shapeStrides.y + coords.z*shapeStrides.z + coords.w*shapeStrides.w + coords.u*shapeStrides.u + coords.v*shapeStrides.v;
  }

  // NaN defination in IEEE 754-1985 is :
  //   - sign = either 0 or 1.
  //   - biased exponent = all 1 bits.
  //   - fraction = anything except all 0 bits (since all 0 bits represents infinity).
  // https://en.wikipedia.org/wiki/IEEE_754-1985#Representation_of_non-numbers
  fn isnan(val: f32) -> bool {
    let floatToUint: u32 = bitcast<u32>(val);
    return (floatToUint & 0x7fffffffu) > 0x7f800000u;
  }
  fn isnanVec4(val : vec4<f32>) -> vec4<bool> {
    let floatToUint: vec4<u32> = bitcast<vec4<u32>>(val);
    return (floatToUint & vec4<u32>(0x7fffffffu)) > vec4<u32>(0x7f800000u);
  }
`,vle=`
  fn isinf(val: f32) -> bool {
    return abs(val) == uniforms.INFINITY;
  }
`;function lh(e,t=""){let a=e.length,n=t!==""?`get${t.charAt(0).toUpperCase()+t.slice(1)}CoordsFromIndex`:"getCoordsFromIndex",r=t!==""?`${t.charAt(0).toLowerCase()+t.slice(1)}ShapeStrides`:"outShapeStrides";if(a<=1)return`fn ${n}(index : i32) -> i32 { return index; }`;let s=v.computeStrides(e),i=Pt(a),o=[];for(let u=0;u<a;u++)o.push(`d${u}`);if(s.length===1)return`    fn ${n}(index : i32) -> vec2<i32> {
      let d0 = index / uniforms.${r}; let d1 = index - d0 * uniforms.${r};
      return vec2<i32>(d0, d1);
    }`;let l;return l="var index2 = index;"+s.map((u,p)=>{let c=`let ${o[p]} = index2 / uniforms.${r}.${Cr(p)}`,d=p===s.length-1?`let ${o[p+1]} = index2 - ${o[p]} * uniforms.${r}.${Cr(p)}`:`index2 = index2 - ${o[p]} * uniforms.${r}.${Cr(p)}`;return`${c}; ${d};`}).join(""),`
    fn ${n}(index : i32) -> ${i} {
      ${l}
      return ${i}(${o.join(",")});
    }
  `}function wle(e,t){let a=e.name,n=e.shape.length,r=Pt(n),s="get"+a.charAt(0).toUpperCase()+a.slice(1),i=["d0","d1","d2","d3","d4","d5"].slice(0,n),o=i.map(p=>`${p} : i32`).join(", ");if(n<1)return`
      fn ${s}() -> ${Xe(t)} {
        return ${Xe(t)}(${a}[0]);
      }
    `;let l=`uniforms.${a.charAt(0).toLowerCase()+a.slice(1)}Shape`,u=`${n}D`;return n===0&&(u="1D"),`
    fn ${s}(${o}) -> ${Xe(t)} {
      return ${Xe(t)}(${a}[getIndexFromCoords${u}(${r}(${i.join(",")}),
        ${l})${t===1?"":` / ${t}`}]);
    }
   `}function kle(e,t,a,n){let r=e.name,s=r.charAt(0).toUpperCase()+r.slice(1),i="get"+s+"ByOutput",o=e.shape.length,l=t.length,u=Pt(l);if(v.arraysEqual(e.shape,t)&&n)return`
    fn ${i}Index(globalIndex : i32) -> ${Xe(a)} {
      return ${Xe(a)}(${r}[globalIndex]);
    }

    fn ${i}Coords(coords : ${u}) -> ${Xe(a)} {
      return ${Xe(a)}(${r}[${l>1?"getOutputIndexFromCoords(coords)":"coords"}${a===1?"":` / ${a}`}]);
    }
    `;let p=C.getBroadcastDims(e.shape,t),c=l-o,d="";if(o===0)return`
    fn ${i}Index(globalIndex : i32) -> ${Xe(a)}{
      return get${s}();
    }

    fn ${i}Coords(coords : ${u}) -> ${Xe(a)}{
      return get${s}();
    }
  `;l<2&&p.length>=1?d="coords = 0;":d=p.map(g=>`coords.${Cr(g+c)} = 0;`).join(`
`);let h="";if(l<2&&o>0)h="coords";else if(l>1){let g=Pt(o),y=e.shape.map((x,A)=>`coords.${Cr(A+c)}`).join(", ");h=`${g}(${y})`}else h="coords";let m=`uniforms.${r.charAt(0).toLowerCase()+r.slice(1)}Shape`,f=`${o}D`;return`
  fn ${i}Index(globalIndex : i32) -> ${Xe(a)} {
    var coords = getCoordsFromIndex(globalIndex);
    ${d}
    return ${Xe(a)}(${r}[getIndexFromCoords${f}(${h}, ${m})${a===1?"":` / ${a}`}]);
  }

  fn ${i}Coords(coordsIn : ${u}) -> ${Xe(a)} {
    var coords = coordsIn;
    ${d}
    return ${Xe(a)}(${r}[getIndexFromCoords${f}(${h}, ${m})${a===1?"":` / ${a}`}]);
  }
`}function Ile(e,t,a,n){let r=wle(e,a);return e.shape.length<=t.length&&(r+=kle(e,t,a,n)),r}function Sle(e,t){let{x:a,y:n=[],z:r=[]}=t,s=e.length,i=a.length+n.length+r.length;if(i!==s)return"";if(a.length===s)return`fn getOutputCoords() -> ${Pt(s)}{
    let globalIndex = getGlobalIndex();
    return getCoordsFromIndex(globalIndex);
  }
  `;let o="",l=[a,n,r];for(let d=0;d<l.length;d++){let h=l[d];if(h.length!==0)if(h.length===1)o+=`let d${h[0]} = i32(globalId[${d}]);`;else{let m=gle(h,"uniforms.outShape");o+=`var index${d} = i32(globalId[${d}]);`;for(let f=0;f<m.length;f++)o+=`let d${h[f]} = index${d} / ${m[f]};`,f===m.length-1?o+=`let d${h[f+1]} = index${d} - d${h[f]} * ${m[f]};`:o+=`index${d} = index${d} - d${h[f]} * ${m[f]};`}}let u=[];for(let d=0;d<i;d++)u.push(`d${d}`);let p=Pt(i),c=`fn getOutputCoords() -> ${p} {
  ${o}
`;return u.length===0?c+=`return ${p}(0); }`:c+=`return ${p}(${u.join(",")}); }`,c}function Cle(e){let t="";switch(e){case 0:case 1:t+=`
        fn getOutputIndexFromCoords(coords : i32) -> i32 {
          return coords;
        }
        `;break;case 2:t+=`
        fn getOutputIndexFromCoords(coords : vec2<i32>) -> i32 {
          return dot(coords, vec2<i32>(uniforms.outShapeStrides, 1));
        }
        `;break;case 3:t+=`
        fn getOutputIndexFromCoords(coords : vec3<i32>) -> i32 {
          return dot(coords, vec3<i32>(uniforms.outShapeStrides.x, uniforms.outShapeStrides.y, 1));
        }
        `;break;case 4:t+=`
        fn getOutputIndexFromCoords(coords : vec4<i32>) -> i32 {
          return dot(coords, vec4<i32>(
            uniforms.outShapeStrides.x, uniforms.outShapeStrides.y, uniforms.outShapeStrides.z, 1));
        }
        `;break;case 5:t+=`
        fn getOutputIndexFromCoords(coords : vec5) -> i32 {
          return coords.x * uniforms.outShapeStrides.x +
              coords.y * uniforms.outShapeStrides.y +
              coords.z * uniforms.outShapeStrides.z +
              coords.w * uniforms.outShapeStrides.w +
              coords.u;
        }
        `;break;case 6:t+=`
        fn getOutputIndexFromCoords(coords : vec6) -> i32 {
          return coords.x * uniforms.outShapeStrides.x +
              coords.y * uniforms.outShapeStrides.y +
              coords.z * uniforms.outShapeStrides.z +
              coords.w * uniforms.outShapeStrides.w +
              coords.u * uniforms.outShapeStrides.u +
              coords.v;
        }
        `;break;default:v.assert(!1,()=>`Unsupported ${e}D shape`);break}return t}function Ck(e){return e.dispatch[1]===1&&e.dispatch[2]===1}function Hs(e,t=1){if(e==="float32")return Xe(t,"f32");if(e==="int32"||e==="bool")return Xe(t,"i32");throw new Error(`type ${e} is not supported.`)}function Tle(e,t,a){let n=e.length,r=Hs(t,a),s=`fn setOutputAtIndex(flatIndex : i32, value : ${Xe(a)}) {
      result[flatIndex] = ${r}(value);
    }

    fn setOutputAtIndexI32(flatIndex : i32, value : ${Xe(a,"i32")}) {
      result[flatIndex] = ${r}(value);
    }
    `;if(n>=2){let i=["d0","d1","d2","d3","d4","d5"].slice(0,n),o=Pt(n);s+=`
      fn setOutputAtCoords(${i.map(l=>`${l} : i32`).join(", ")}, value : ${Xe(a)}) {
        let flatIndex = getOutputIndexFromCoords(${o}(${i.join(", ")}));
        setOutputAtIndex(flatIndex${a===1?"":` / ${a}`}, value);
      }
      fn setOutputAtCoordsI32(${i.map(l=>`${l} : i32`).join(", ")}, value : ${Xe(a,"i32")}) {
        let flatIndex = getOutputIndexFromCoords(${o}(${i.join(", ")}));
        setOutputAtIndexI32(flatIndex${a===1?"":` / ${a}`}, value);
      }
    `}return s}function Nle(e){let t=/(\w+)\s*:\s*vec(5|6)/g;e=e.replace(t,n=>"@align(16) "+n);let a=/vec(5|6)\s*,\s*(\w+)/g;return e=e.replace(a,(n,r,s)=>`vec${r}, @align(16) ${s}`),e}function rA(e){return!(e.dispatchLayout.hasOwnProperty("y")&&e.dispatchLayout.y.length!==0||e.dispatchLayout.hasOwnProperty("z")&&e.dispatchLayout.z.length!==0)}var Tk={};Ze(Tk,{GPUBytesPerElement:()=>q1,MatMulProgramType:()=>On,assertNotComplex:()=>q3,computeDispatch:()=>de,computeWorkPerThreadForConv2d:()=>H3,computeWorkgroupInfoForMatMul:()=>Nk,computeWorkgroupSizeForConv2d:()=>G3,flatDispatchLayout:()=>me,isWebGPUSupported:()=>j3,tilesFitEvenlyIntoShape:()=>Rle});var Xs=e=>{let t=1;for(let a=0;a<e.length;a++)t*=e[a];return t};function Rle(e,t){if(e.length!==t.length)throw new Error(`Cannot compute whether rank ${e.length} tiles fit evenly into rank ${t.length} shape - ranks must match.`);return t.every((a,n)=>a%e[n]===0)}function de(e,t,a=[1,1,1],n=[1,1,1]){let[r,s,i]=[Math.ceil(Xs(e.x.map(o=>t[o]))/(a[0]*n[0])),e.y?Math.ceil(Xs(e.y.map(o=>t[o]))/(a[1]*n[1])):1,e.z?Math.ceil(Xs(e.z.map(o=>t[o]))/(a[2]*n[2])):1];return[r,s,i]}function Nk(e,t,a,n=!1){let r=[8,8,1],s=[4,4,1];return n||(e<=8&&(s[1]=1),t<=16&&a<=16&&(r[0]=4)),{workgroupSize:r,elementsPerThread:s}}function G3(e,t,a=!1){if(a)return[8,8,1];let n=Xs(e.x.map(s=>t[s])),r=Xs(e.y.map(s=>t[s]));return n<=4?[4,16,1]:r<=4?[16,4,1]:[16,16,1]}function H3(e,t,a=!1){if(a)return[4,4,1];let n=Xs(e.x.map(s=>t[s])),r=Xs(e.y.map(s=>t[s]));return n<=4?[1,2,1]:r<=4?[2,1,1]:[2,2,1]}function me(e){return{x:e.map((t,a)=>a)}}function q1(e){if(e==="float32"||e==="int32"||e==="bool"||e==="string")return 4;if(e==="complex64")return 8;throw new Error(`Unknown dtype ${e}`)}function j3(){return!!(typeof globalThis!="undefined"&&globalThis.navigator&&globalThis.navigator.gpu)}function q3(e,t){Array.isArray(e)||(e=[e]),e.forEach(a=>{a!=null&&v.assert(a.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the WebGPU backend.`)})}var On;(function(e){e[e.MatMulReduceProgram=0]="MatMulReduceProgram",e[e.MatMulSplitKProgram=1]="MatMulSplitKProgram",e[e.MatMulSmallOutputSizeProgram=2]="MatMulSmallOutputSizeProgram",e[e.MatMulPackedProgram=3]="MatMulPackedProgram",e[e.MatMulMax=4]="MatMulMax"})(On||(On={}));var Ele=B().getNumber("WEBGPU_CPU_HANDOFF_SIZE_THRESHOLD"),Mle=(e,t)=>{let a=e.limits.maxComputeWorkgroupsPerDimension,n=t.dispatchLayout,r=t.dispatch;if(r.every(i=>i<=a))return r;v.assert(r[0]>a&&n.y===void 0&&n.z===void 0,()=>"Dispatch size exceeds WebGPU limits in Y or Z dimension.");let s=Math.ceil(Math.sqrt(r[0]));return s>a?(s=Math.ceil(Math.cbrt(r[0])),v.assert(s<=a,()=>"Total dispatch size exceeds WebGPU maximum."),[s,s,s]):[s,s,1]},X3=class Rk extends su{nextDataId(){return Rk.nextDataId++}constructor(t,a){if(super(),this.commandQueueOwnedIds=new WeakSet,this.dispatchCountInPass=0,this.disposed=!1,this.downloadWaitMs=0,this.tensorDataPendingDisposal=[],this.queryResolveBuffer=null,this.querySet=null,this.querySetCount=2,this.stagingPendingDisposal=[],this.uniformPendingDisposal=[],this.uploadWaitMs=0,this.hasReadSyncWarned=!1,this.hasTimestampQueryWarned=!1,!j3())throw new Error("WebGPU is not supported on this device");this.pipelineCache={},this.device=t,this.queue=t.queue,this.commandEncoder=null,this.computePassEncoder=null,this.adapterInfo=new hle(a),this.supportTimestampQuery=this.device.features.has("timestamp-query"),this.thresholdToIncreaseWorkgroups=this.adapterInfo.intelGPUGeneration>=12?16:8,this.bufferManager=new mle(this.device),this.textureManager=new fle(this.device),this.tensorMap=new op(this,It()),B().getBool("WEBGPU_USE_PROFILE_TOOL")&&(this.dummyCanvas=document.createElement("canvas"),this.dummyCanvas.width=1,this.dummyCanvas.height=1,this.dummyContext=this.dummyCanvas.getContext("webgpu"),this.dummyContext.configure({device:t,format:"bgra8unorm"}),document.body.appendChild(this.dummyCanvas))}floatPrecision(){return 32}disposeData(t,a=!1){if(!this.tensorMap.has(t))return!0;let n=this.tensorMap.get(t);return a?n.refCount=0:n.refCount--,n.refCount>0?!1:(n.complexTensorInfos!=null&&(this.disposeData(n.complexTensorInfos.real.dataId),this.disposeData(n.complexTensorInfos.imag.dataId)),this.commandQueueOwnedIds.has(t)?(this.tensorDataPendingDisposal.push(t),!0):(this.releaseResource(t),this.tensorMap.delete(t),!0))}memory(){return{numBytesInGPU:this.bufferManager.numBytesUsed,numBytesAllocatedInGPU:this.bufferManager.numBytesAllocated,unreliable:!1}}releaseResource(t){let a=this.tensorMap.get(t);if(!(!a||!a.resource)){if(a.external){a.resource=null;return}a.resource instanceof GPUBuffer?this.bufferManager.releaseBuffer(a.resource):a.resource instanceof GPUTexture&&this.textureManager.releaseTexture(a.resource),a.resource=null}}refCount(t){return this.tensorMap.has(t)?this.tensorMap.get(t).refCount:0}incRef(t){let a=this.tensorMap.get(t);a.refCount++}decRef(t){if(this.tensorMap.has(t)){let a=this.tensorMap.get(t);a.refCount--}}write(t,a,n){if(n==="complex64"&&t!=null)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let r={id:this.nextDataId()};return this.tensorMap.set(r,{dtype:n,shape:a,values:t,refCount:1}),r}move(t,a,n,r,s){if(r==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.tensorMap.set(t,{dtype:r,shape:n,values:a,refCount:s})}submitQueue(){this.queue.submit([this.commandEncoder.finish()]),this.commandEncoder=null,this.dispatchCountInPass=0,this.commandQueueOwnedIds=new WeakSet,this.tensorDataPendingDisposal.forEach(t=>{this.releaseResource(t),this.tensorMap.delete(t)}),this.uniformPendingDisposal.forEach(t=>this.bufferManager.releaseBuffer(t)),this.stagingPendingDisposal.forEach(t=>this.bufferManager.releaseBuffer(t,!1)),this.tensorDataPendingDisposal=[],this.uniformPendingDisposal=[],this.stagingPendingDisposal=[]}ensureCommandEncoderReady(){this.commandEncoder||(this.commandEncoder=this.device.createCommandEncoder())}endComputePassEncoder(){this.computePassEncoder&&(this.computePassEncoder.end(),this.computePassEncoder=null)}async checkCompileCompletionAsync(){let t;try{t=await Promise.all(Object.values(this.pipelineCache))}catch(a){throw new Error(a.message)}Object.keys(this.pipelineCache).map((a,n)=>{this.pipelineCache[a]=t[n]})}async getBufferData(t){if(B().getBool("WEBGPU_ENGINE_COMPILE_ONLY"))return console.warn("The data may be invalid since WEBGPU_ENGINE_COMPILE_ONLY is true, this can only be called when WEBGPU_ENGINE_COMPILE_ONLY is false"),null;let a=t.size,n=this.bufferManager.acquireBuffer(a,GPUBufferUsage.COPY_DST|GPUBufferUsage.MAP_READ);this.ensureCommandEncoderReady(),this.endComputePassEncoder(),this.commandEncoder.copyBufferToBuffer(t,0,n,0,a),this.submitQueue(),await n.mapAsync(GPUMapMode.READ);let r=n.getMappedRange().slice(0);return n.unmap(),n!=null&&this.bufferManager.releaseBuffer(n),B().getBool("WEBGPU_USE_PROFILE_TOOL")&&(v.assert(this.dummyContext!==void 0,()=>"Fail to get context for profiling tool"),this.dummyContext.getCurrentTexture()),r}convertAndCacheOnCPU(t,a){let n=this.tensorMap.get(t);return n.values=a,n.values}readSync(t){let a=this.tensorMap.get(t),{values:n,complexTensorInfos:r}=a;if(n!=null||a.dtype==="string")return n;if(a.dtype==="complex64"){let f=this.readSync(r.real.dataId),g=this.readSync(r.imag.dataId),y=v.convertBackendValuesAndArrayBuffer(C.mergeRealAndImagArrays(f,g).buffer,"float32");return this.convertAndCacheOnCPU(t,y),y}this.hasReadSyncWarned||(this.hasReadSyncWarned=!0,console.warn("The performance of synchronously reading data from GPU to CPU is poor on the webgpu backend, please use asynchronous APIs instead."));let s=["opaque","premultiplied"],i=a.resource,o=i.size;v.assert(o%4===0,()=>"Because there is 4 bytes for one pixel, buffer size must be multiple of 4.");let l=o/4,u=new ArrayBuffer(o),p=256,c=256,d=s.map(f=>new OffscreenCanvas(p,c)),h=new OffscreenCanvas(p,c);this.endComputePassEncoder(),d.map((f,g)=>{let y=f.getContext("webgpu");return y.configure({device:this.device,format:"bgra8unorm",usage:GPUTextureUsage.COPY_DST,alphaMode:s[g]}),y.getCurrentTexture()}).map((f,g)=>{let y=p*4,x=(N,M,$)=>{this.ensureCommandEncoderReady(),this.commandEncoder.copyBufferToTexture({buffer:i,bytesPerRow:y,offset:$},{texture:f},{width:N,height:M}),this.submitQueue();let E=h.getContext("2d",{willReadFrequently:!0});E.clearRect(0,0,N,M),E.drawImage(d[g],0,0);let S=E.getImageData(0,0,N,M).data,_=s[g],O=new Uint8ClampedArray(u,$,N*M*4);for(let W=0;W<O.length;W+=4)if(_==="premultiplied")O[W+3]=S[W+3];else{let P=S[W];O[W]=S[W+2],O[W+1]=S[W+1],O[W+2]=P}},A=Math.floor(l/(p*c)),b=p,w=c,I=0;for(let N=0;N<A;N++)x(b,w,I),I+=p*c*4;let T=l%(p*c);w=Math.floor(T/p),w>0&&(x(b,w,I),I+=w*(p*4)),b=T%p,b>0&&x(b,1,I)});let m=v.convertBackendValuesAndArrayBuffer(u,a.dtype);return this.convertAndCacheOnCPU(t,m),m}async read(t){if(!this.tensorMap.has(t))throw new Error(`Tensor ${t} was not registered!`);let a=this.tensorMap.get(t),{values:n}=a;if(n!=null)return n;let r;if(a.dtype==="complex64"){let s=await Promise.all([this.read(a.complexTensorInfos.real.dataId),this.read(a.complexTensorInfos.imag.dataId)]),i=s[0],o=s[1];r=C.mergeRealAndImagArrays(i,o)}else{let s=await this.getBufferData(a.resource);r=v.convertBackendValuesAndArrayBuffer(s,a.dtype)}return this.convertAndCacheOnCPU(t,r),r}copyBuffer(t){let a=t.size,n=t.usage,r=this.bufferManager.acquireBuffer(a,n);return this.ensureCommandEncoderReady(),this.endComputePassEncoder(),this.commandEncoder.copyBufferToBuffer(t,0,r,0,a),this.submitQueue(),r}createTensorFromGPUData(t,a,n){let r=t.buffer;if(n==="complex64")throw new Error("Cannot write to a complex64 dtype. ");let s={id:this.nextDataId()};this.tensorMap.set(s,{dtype:n,shape:a,values:null,refCount:1,external:t.zeroCopy});let i=this.tensorMap.get(s),o=q1(i.dtype)*v.sizeFromShape(i.shape);if(t.buffer.size<o)throw new Error(`GPUBuffer size(${t.buffer.size}) is smaller than tensor size(${o})!`);if((t.buffer.usage&(GPUBufferUsage.STORAGE|GPUBufferUsage.COPY_SRC))!==(GPUBufferUsage.STORAGE|GPUBufferUsage.COPY_SRC))throw new Error("GPUBuffer.usage should include GPUBufferUsage.STORAGE | GPUBufferUsage.COPY_SRC!");return t.zeroCopy!==!0&&(r=this.copyBuffer(r)),i.resource=r,It().makeTensorFromDataId(s,a,n,this)}readToGPU(t){let a=this.tensorMap.get(t),{values:n,dtype:r,shape:s,resource:i}=a;if(r==="complex64")throw new Error("Does not support reading buffer for complex64 dtype.");if(i==null)throw n!=null?new Error("Data is not on GPU but on CPU."):new Error("There is no data on GPU or CPU.");let o=i,l=o.size,u=o.usage,p=this.bufferManager.acquireBuffer(l,u);this.ensureCommandEncoderReady(),this.endComputePassEncoder(),this.commandEncoder.copyBufferToBuffer(i,0,p,0,l),this.submitQueue();let c=this.makeTensorInfo(s,r),d=It().makeTensorFromTensorInfo(c),h=this.tensorMap.get(c.dataId);return h.resource=p,{tensorRef:d,buffer:p}}bufferSync(t){let a=this.readSync(t.dataId);if(t.dtype==="string")try{let n=a.map(r=>v.decodeString(r));return _e(t.shape,t.dtype,n)}catch(n){throw new Error("Failed to decode encoded string bytes into utf-8")}return _e(t.shape,t.dtype,a)}async time(t){!this.supportTimestampQuery&&!this.hasTimestampQueryWarned&&(console.warn("This device doesn't support timestamp-query extension. Start Chrome browser with flag --enable-dawn-features=allow_unsafe_apis to try it again. Otherwise, zero will be shown for the kernel time when profiling mode is enabled."),this.hasTimestampQueryWarned=!0);let a=this.activeTimers,n=[],r=!1;this.programTimersStack==null?(this.programTimersStack=n,r=!0):this.activeTimers.push(n),this.activeTimers=n,t();let s=v.flatten(this.activeTimers.map(u=>u.query)).filter(u=>u!=null),i=v.flatten(this.activeTimers.map(u=>u.name)).filter(u=>u!=null);this.activeTimers=a,r&&(this.programTimersStack=null);let o={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null},l=await Promise.all(s);return o.kernelMs=v.sum(l),o.getExtraProfileInfo=()=>l.map((u,p)=>({name:i[p],ms:u})).map(u=>`${u.name}: ${u.ms}`).join(", "),this.uploadWaitMs=0,this.downloadWaitMs=0,o}makeTensorInfo(t,a,n){return a==="string"&&n!=null&&n.length>0&&v.isString(n[0])&&(n=n.map(r=>v.encodeString(r))),{dataId:this.write(n,t,a),shape:t,dtype:a}}tensorToBinding(t){if(!t)return null;let a=this.tensorMap.get(t.dataId).resource;return a instanceof GPUBuffer?{buffer:a}:a instanceof GPUTexture?a.createView():a}uploadToGPU(t){let a=this.tensorMap.get(t);if(a.resource!=null)return;let n=q1(a.dtype)*v.sizeFromShape(a.shape),r,s=GPUBufferUsage.STORAGE|GPUBufferUsage.COPY_SRC|GPUBufferUsage.COPY_DST;if(a.values){if(r=this.bufferManager.acquireBuffer(n,s,!0),r.mapState==="unmapped"){let i=this.bufferManager.acquireBuffer(n,GPUBufferUsage.MAP_WRITE|GPUBufferUsage.COPY_SRC,!0,!1),o=i.getMappedRange();a.dtype==="int32"||a.dtype==="bool"?new Int32Array(o).set(a.values):new Float32Array(o).set(a.values),i.unmap(),this.ensureCommandEncoderReady(),this.endComputePassEncoder(),this.commandEncoder.copyBufferToBuffer(i,0,r,0,n),this.stagingPendingDisposal.push(i)}else{let i=r.getMappedRange();a.dtype==="int32"||a.dtype==="bool"?new Int32Array(i).set(a.values):new Float32Array(i).set(a.values),r.unmap()}a.values=null}else r=this.bufferManager.acquireBuffer(n,s);a.resource=r}makeUniforms(t){let a=0,n=0,r=[],s=1;t.forEach(l=>{l.data.length===0&&(l.data=[1]);let u;switch(l.data.length){case 1:u=4;break;case 2:u=8;break;case 3:u=16;break;case 4:u=16;break;case 5:u=16;break;case 6:u=16;break;default:v.assert(!1,()=>`Unsupported ${l.data.length}D shape`)}(n===5||n===6)&&(u=16),u>s&&(s=u),a=Math.ceil(a/u)*u,n=l.data.length,r.push(a),a+=l.data.length*4}),a=Math.ceil(a/s)*s;let i=new ArrayBuffer(a);t.forEach((l,u)=>{let p=r[u];l.type==="int32"?new Int32Array(i,p,l.data.length).set(l.data):l.type==="uint32"?new Uint32Array(i,p,l.data.length).set(l.data):new Float32Array(i,p,l.data.length).set(l.data)});let o=this.bufferManager.acquireBuffer(a,GPUBufferUsage.COPY_DST|GPUBufferUsage.UNIFORM);return this.queue.writeBuffer(o,0,i,0,a),this.uniformPendingDisposal.push(o),{offset:0,size:a,buffer:o}}runWebGPUProgram(t,a,n,r,s){if(s||(s=this.makeTensorInfo(t.outputShape,n)),v.sizeFromShape(s.shape)===0)return this.tensorMap.get(s.dataId).values=v.getTypedArrayFromDType(s.dtype,0),s;this.uploadToGPU(s.dataId),t.dispatch=Mle(this.device,t);let i=a.map((l,u)=>{if(l.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");return this.uploadToGPU(l.dataId),{dtype:this.tensorMap.get(l.dataId).dtype,shape:l.shape,name:t.variableNames[u]}});t.shaderKey=ble(t,i,s);let o=B().getBool("WEBGPU_ENGINE_COMPILE_ONLY");return t.shaderKey in this.pipelineCache||(this.pipelineCache[t.shaderKey]=yle(this.device,t,i,s,o)),t.pipeline=this.pipelineCache[t.shaderKey],o||this.recordAndSubmit(t,s,a,r),s}recordAndSubmit(t,a,n,r){if(t.pipeline instanceof Promise)throw new Error("Please call checkCompileCompletionAsync to ensure parallel compilation is done!");let s=[],i=[],o="int32";if(t.pixelsOpType==null){s.push({type:"float32",data:[NaN]},{type:"float32",data:[1/0]}),i=n.concat(a).map(h=>h.shape);let d="int32";i.map(h=>{s.push({type:d,data:h});let m=v.computeStrides(h);s.push({type:d,data:m})})}else{let d=v.computeStrides(a.shape);s.push({type:o,data:d})}if(t.size){let d=v.sizeFromShape(t.outputShape);s.push({type:o,data:[t.outputComponent?d/t.outputComponent:d]})}r&&(s=[...s,...r]);let l=[this.tensorToBinding(a),...n.map(d=>this.tensorToBinding(d)),this.makeUniforms(s)];n.forEach(d=>{this.commandQueueOwnedIds.add(d.dataId)}),this.commandQueueOwnedIds.add(a.dataId);let u=this.device.createBindGroup({layout:t.pipeline.getBindGroupLayout(0),entries:l.map((d,h)=>({binding:h,resource:d}))}),p=this.activeTimers!=null;this.ensureCommandEncoderReady();let c={};p&&this.supportTimestampQuery?(this.endComputePassEncoder(),this.querySet==null&&(this.querySet=this.device.createQuerySet({type:"timestamp",count:this.querySetCount})),c.timestampWrites={querySet:this.querySet,beginningOfPassWriteIndex:0,endOfPassWriteIndex:1},this.computePassEncoder=this.commandEncoder.beginComputePass(c)):this.computePassEncoder||(this.computePassEncoder=this.commandEncoder.beginComputePass(c)),this.computePassEncoder.setPipeline(t.pipeline),this.computePassEncoder.setBindGroup(0,u),this.computePassEncoder.dispatchWorkgroups(t.dispatch[0],t.dispatch[1],t.dispatch[2]),this.dispatchCountInPass++,(p||B().get("WEBGPU_DEFERRED_SUBMIT_BATCH_SIZE")<=this.dispatchCountInPass||t.pixelsOpType===nu.DRAW)&&(this.endComputePassEncoder(),p?this.activeTimers.push({name:t.constructor.name,query:this.getQueryTime()}):this.submitQueue())}async getQueryTime(){if(!this.supportTimestampQuery)return 0;this.queryResolveBuffer==null&&(this.queryResolveBuffer=this.bufferManager.acquireBuffer(this.querySetCount*8,GPUBufferUsage.COPY_SRC|GPUBufferUsage.COPY_DST|GPUBufferUsage.QUERY_RESOLVE)),this.commandEncoder.resolveQuerySet(this.querySet,0,this.querySetCount,this.queryResolveBuffer,0);let t=this.bufferManager.acquireBuffer(this.querySetCount*8,GPUBufferUsage.MAP_READ|GPUBufferUsage.COPY_DST);this.commandEncoder.copyBufferToBuffer(this.queryResolveBuffer,0,t,0,this.querySetCount*8),this.submitQueue(),await t.mapAsync(GPUMapMode.READ);let a=new BigUint64Array(t.getMappedRange()),n=Number(a[1]-a[0])/1e6;return t.unmap(),this.bufferManager.releaseBuffer(t),n}shouldExecuteOnCPU(t,a=Ele){return B().getBool("WEBGPU_CPU_FORWARD")&&t.every(n=>this.tensorMap.get(n.dataId).resource==null&&v.sizeFromShape(n.shape)<a)}numDataIds(){return this.tensorMap.numDataIds()-this.tensorDataPendingDisposal.length}dispose(){this.disposed||(this.querySet!=null&&this.querySet.destroy(),this.bufferManager.dispose(),this.textureManager.dispose(),this.disposed=!0)}};X3.nextDataId=0;j3()&&al("webgpu",async()=>{let e={powerPreference:B().get("WEBGPU_USE_LOW_POWER_GPU")?"low-power":"high-performance"},t=await navigator.gpu.requestAdapter(e),a={},n=[];t.features.has("timestamp-query")&&n.push("timestamp-query"),t.features.has("bgra8unorm-storage")&&n.push(["bgra8unorm-storage"]),a.requiredFeatures=n;let r=t.limits;a.requiredLimits={maxComputeWorkgroupStorageSize:r.maxComputeWorkgroupStorageSize,maxComputeWorkgroupsPerDimension:r.maxComputeWorkgroupsPerDimension,maxStorageBufferBindingSize:r.maxStorageBufferBindingSize,maxBufferSize:r.maxBufferSize,maxComputeWorkgroupSizeX:r.maxComputeWorkgroupSizeX,maxComputeInvocationsPerWorkgroup:r.maxComputeInvocationsPerWorkgroup};let s=await t.requestDevice(a),i="info"in t?t.info:"requestAdapterInfo"in t?await t.requestAdapterInfo():void 0;return new X3(s,i)},3);var Pe;(function(e){e[e.ADD=0]="ADD",e[e.ATAN2=1]="ATAN2",e[e.COMPLEX_MULTIPLY_IMAG=2]="COMPLEX_MULTIPLY_IMAG",e[e.COMPLEX_MULTIPLY_REAL=3]="COMPLEX_MULTIPLY_REAL",e[e.DIV=4]="DIV",e[e.ELU_DER=5]="ELU_DER",e[e.EQUAL=6]="EQUAL",e[e.FLOOR_DIV=7]="FLOOR_DIV",e[e.GREATER=8]="GREATER",e[e.GREATER_EQUAL=9]="GREATER_EQUAL",e[e.LESS=10]="LESS",e[e.LESS_EQUAL=11]="LESS_EQUAL",e[e.LOGICAL_AND=12]="LOGICAL_AND",e[e.LOGICAL_OR=13]="LOGICAL_OR",e[e.MAX=14]="MAX",e[e.MIN=15]="MIN",e[e.MOD=16]="MOD",e[e.MUL=17]="MUL",e[e.NOT_EQUAL=18]="NOT_EQUAL",e[e.POW=19]="POW",e[e.PRELU=20]="PRELU",e[e.SQUARED_DIFFERENCE=21]="SQUARED_DIFFERENCE",e[e.SUB=22]="SUB"})(Pe||(Pe={}));var $le="let resultTemp = a + b;",Ple="let resultTemp = atan2(a, b);",_le="let resultTemp = areal * breal - aimag * bimag;",Fle="let resultTemp = areal * bimag + aimag * breal;",Dle="let resultTemp = a / b;",Ole="let resultTemp = select(a * (b + 1.0), a, b >= b - b);",zle=`
  let zero = sign(a) * 0 + 0;
  let one = sign(b) * 0 + 1;
  let resultTemp = select(zero, one, a == b);
`,Lle=`
  let remainder =
      select(a % b, round(a % b), (round(a) == a) & (round(b) == b));
  let quotient = (a - remainder) / b;
  let resultTemp =
      round(select(quotient, quotient - 1, sign(remainder) == -sign(b)));
`,Wle=`
  let zero = sign(a) * 0 + 0;
  let one = sign(b) * 0 + 1;
  let resultTemp = select(zero, one, a > b);
`,Ble=`
  let zero = sign(a) * 0 + 0;
  let one = sign(b) * 0 + 1;
  let resultTemp = select(zero, one, a >= b);
`,Vle=`
  let zero = sign(a) * 0 + 0;
  let one = sign(b) * 0 + 1;
  let resultTemp = select(zero, one, a < b);
`,Ule=`
  let zero = sign(a) * 0 + 0;
  let one = sign(b) * 0 + 1;
  let resultTemp = select(zero, one, a <= b);
`,Gle="return f32(a >= 1.0 && b >= 1.0);",Hle=`return (vec4<f32>(a >= vec4<f32>(1.0)) *
  vec4<f32>(b >= vec4<f32>(1.0)));`,jle="return f32(a >= 1.0 || b >= 1.0);",qle=`return min(vec4<f32>(a >= vec4<f32>(1.0)) +
  vec4<f32>(b >= vec4<f32>(1.0)), vec4<f32>(1.0));`,Xle="let resultTemp = max(a, b);",Kle="let resultTemp = min(a, b);",Yle=`
  let isNaN = b == 0.;
  var resultTemp = a % b;
  resultTemp = select((resultTemp + b) % b, resultTemp,
      (a < 0. && b < 0.) || (a >= 0. && b > 0.));
`,Zle=`
  let isNaN = !vec4<bool>(b);
  var resultTemp = vec4<f32>(a % b);
  if (!((a[0] < 0. && b[0] < 0.) || (a[0] >= 0. && b[0] > 0.))) {
    resultTemp[0] = (resultTemp[0] + b[0]) % b[0];
  }
  if (!((a[1] < 0. && b[1] < 0.) || (a[1] >= 0. && b[1] > 0.))) {
    resultTemp[1] = (resultTemp[1] + b[1]) % b[1];
  }
  if (!((a[2] < 0. && b[2] < 0.) || (a[2] >= 0. && b[2] > 0.))) {
    resultTemp[2] = (resultTemp[2] + b[2]) % b[2];
  }
  if (!((a[3] < 0. && b[3] < 0.) || (a[3] >= 0. && b[3] > 0.))) {
    resultTemp[3] = (resultTemp[3] + b[3]) % b[3];
  }
`,Jle="let resultTemp = a * b;",Qle=`
  var resultTemp = f32(a != b);
  let valueForNaN = 1.0;
`,eue=`
  var resultTemp = vec4<f32>(a != b);
  let valueForNaN = 1.0;
`,tue=`
  let isNaN = a < 0.0 && floor(b) < b;
  if (b == 0.0) {
    return 1.0;
  }
  var resultTemp = select(sign(a) * pow(abs(a), b), pow(abs(a), b),
      round(abs(b) % 2.0) != 1.0);
`,aue=`
  let isModRound1Bool = vec4<i32>(round(abs(b) % vec4<f32>(2.0))) == vec4<i32>(1);
  let isModRound1 = vec4<f32>(isModRound1Bool);
  let multiplier = sign(a) * isModRound1 + (vec4<f32>(1.0) - isModRound1);
  var resultTemp = multiplier * pow(abs(a), b);

  // Ensure that a^0 = 1, including 0^0 = 1 as this correspond to TF and JS
  let isExpZero = b == vec4<f32>(0.0);
  if (isExpZero.r) {
    resultTemp.r = 1.0;
  }
  if (isExpZero.g) {
    resultTemp.g = 1.0;
  }
  if (isExpZero.b) {
    resultTemp.b = 1.0;
  }
  if (isExpZero.a) {
    resultTemp.a = 1.0;
  }
  let isNaN = (a < vec4<f32>(0.0)) & (floor(b) < b);
`,nue="if (a < 0.0) { return b * a; }  return a;",rue=`
  let aLessThanZero = vec4<f32>(a < vec4<f32>(0.0));
  return (aLessThanZero * (b * a)) + ((vec4<f32>(1.0) - aLessThanZero) * a);
`,sue="let resultTemp = (a - b) * (a - b);",iue="let resultTemp = a - b;";function K3(e,t){let a;do{switch(e){case Pe.ATAN2:a=Ple;break;case Pe.MAX:a=Xle;break;case Pe.MIN:a=Kle;break;case Pe.MOD:a=t?Zle:Yle;break;case Pe.NOT_EQUAL:a=t?eue:Qle;break;case Pe.POW:a=t?aue:tue;break;default:continue}let n,r,s;return t?(n="isnanVec4",r="vec4<f32>",s="vec4<bool>"):(n="isnan",r="f32",s="bool"),`
      let aIsNaN = ${n}(a);
      let aPostLegalization = select(a, ${r}(42), aIsNaN);
      let bIsNaN = ${n}(b);
      let bPostLegalization = select(b, ${r}(42), bIsNaN);
      let isNaN = false;
      let valueForNaN = uniforms.NAN;
      {
        let a = aPostLegalization;
        let b = bPostLegalization;
        ${a}
        return select(
            resultTemp, ${r}(valueForNaN),
            ${s}(isNaN) | aIsNaN | bIsNaN);
      }
    `}while(!1);switch(e){case Pe.ADD:a=$le;break;case Pe.COMPLEX_MULTIPLY_IMAG:a=Fle;break;case Pe.COMPLEX_MULTIPLY_REAL:a=_le;break;case Pe.DIV:a=Dle;break;case Pe.ELU_DER:a=Ole;break;case Pe.EQUAL:a=zle;break;case Pe.FLOOR_DIV:a=Lle;break;case Pe.GREATER:a=Wle;break;case Pe.GREATER_EQUAL:a=Ble;break;case Pe.LESS:a=Vle;break;case Pe.LESS_EQUAL:a=Ule;break;case Pe.LOGICAL_AND:return t?Hle:Gle;case Pe.LOGICAL_OR:return t?qle:jle;case Pe.MUL:a=Jle;break;case Pe.PRELU:return t?rue:nue;case Pe.SQUARED_DIFFERENCE:a=sue;break;case Pe.SUB:a=iue;break;default:}return`
    ${a}
    return resultTemp;
  `}var le;(function(e){e[e.ABS=0]="ABS",e[e.ACOS=1]="ACOS",e[e.ACOSH=2]="ACOSH",e[e.ASIN=3]="ASIN",e[e.ASINH=4]="ASINH",e[e.ATAN=5]="ATAN",e[e.ATANH=6]="ATANH",e[e.CEIL=7]="CEIL",e[e.COS=8]="COS",e[e.COSH=9]="COSH",e[e.ELU=10]="ELU",e[e.ERF=11]="ERF",e[e.EXP=12]="EXP",e[e.EXPM1=13]="EXPM1",e[e.FLOOR=14]="FLOOR",e[e.IS_FINITE=15]="IS_FINITE",e[e.IS_INF=16]="IS_INF",e[e.IS_NAN=17]="IS_NAN",e[e.LINEAR=18]="LINEAR",e[e.LOG=19]="LOG",e[e.LOG1P=20]="LOG1P",e[e.LOGICAL_NOT=21]="LOGICAL_NOT",e[e.NEG=22]="NEG",e[e.RELU=23]="RELU",e[e.RELU6=24]="RELU6",e[e.LEAKYRELU=25]="LEAKYRELU",e[e.RECIPROCAL=26]="RECIPROCAL",e[e.ROUND=27]="ROUND",e[e.RSQRT=28]="RSQRT",e[e.SELU=29]="SELU",e[e.SIGMOID=30]="SIGMOID",e[e.SIGN=31]="SIGN",e[e.SIN=32]="SIN",e[e.SINH=33]="SINH",e[e.SOFTPLUS=34]="SOFTPLUS",e[e.SQRT=35]="SQRT",e[e.SQUARE=36]="SQUARE",e[e.STEP=37]="STEP",e[e.TAN=38]="TAN",e[e.TANH=39]="TANH",e[e.TO_INT=40]="TO_INT"})(le||(le={}));var oue="return abs(a);",lue=`
  if (abs(a) > 1.) {
    return uniforms.NAN;
  }
  return acos(a);
`,uue=`
  if (a < 1.) {
    return uniforms.NAN;
  }
  return acosh(a);
`,due=`
  if (abs(a) > 1.) {
    return uniforms.NAN;
  }
  return asin(a);
`,pue="return asinh(a);",cue=`
  if (isnan(a)) {
    return uniforms.NAN;
  }
  return atan(a);
`,hue=`
  if (abs(a) > 1.) {
    return uniforms.NAN;
  }
  if (a == 1.) {
    return uniforms.INFINITY;
  }
  if (a == -1.) {
    return -uniforms.INFINITY;
  }
  return atanh(a);
`,mue="return ceil(a);",fue="return cos(a);",gue=`
  let e2x = exp(-a);
  return (e2x + 1.0 / e2x) / 2.0;
`,yue="return exp(a) - 1.0;",xue="if (a >= 0.0) { return a; }  return (exp(a) - 1.0);",Aue=`
  var resFloat = exp(a) - vec4<f32>(1.0);
  if (a.r >= 0.0) {
    resFloat.r = a.r;
  }
  if (a.g >= 0.0) {
    resFloat.g = a.g;
  }
  if (a.b >= 0.0) {
    resFloat.b = a.b;
  }
  if (a.a >= 0.0) {
    resFloat.a = a.a;
  }
  return resFloat;
`,bue=`
  // Error function is calculated approximately with elementary function.
  // See "Handbook of Mathematical Functions with Formulas,
  // Graphs, and Mathematical Tables", Abramowitz and Stegun.
  let p = ${C.ERF_P};
  let a1 = ${C.ERF_A1};
  let a2 = ${C.ERF_A2};
  let a3 = ${C.ERF_A3};
  let a4 = ${C.ERF_A4};
  let a5 = ${C.ERF_A5};

  let sign = sign(a);
  let absA = abs(a);
  let t = 1.0 / (1.0 + p * absA);
  return sign * (1.0 - (((((a5 * t + a4) * t) + a3) * t + a2) * t + a1) * t * exp(-absA * absA));
`,vue="return exp(a);",wue="return floor(a);",kue="return f32(!isnan(a) && !isinf(a));",Iue="return f32(isinf(a));",Sue="return f32(isnan(a));",Cue="return a;",Tue=`if (a < 0.0) { return uniforms.NAN; }
  return log(a);`,Nue=`
  if (isnan(a)) { return a; }
  return log(1.0 + a);
`,Rue="return f32(!(a >= 1.0));",Eue="return -a;",Mue="if (a < 0.0) { return uniforms.alpha * a; } return a;",$ue=`
  let aLessThanZero = vec4<f32>(a < vec4<f32>(0.0));
  return (aLessThanZero * (uniforms.alpha * a)) + ((vec4<f32>(1.0) - aLessThanZero) * a);
`,Pue="return 1.0 / a;",_ue="return select(a, 0.0, a < 0.0);",Fue="return clamp(a, 0.0, 6.0);",Due="return clamp(a, vec4<f32>(0.0, 0.0, 0.0, 0.0), vec4<f32>(6.0, 6.0, 6.0, 6.0));",Oue=`
  return select(a, vec4<f32>(0.0), a < vec4<f32>(0.0));
`,zue="return round(a);",Lue="return inverseSqrt(a);",Wue=`
  if (a >= 0.0) {
    return ${C.SELU_SCALE} * a;
  } else {
    return ${C.SELU_SCALEALPHA} * (exp(a) - 1.0);
  }
`,Bue="return 1.0 / (1.0 + exp(-1.0 * a));",Vue="return sign(a);",Uue="return sin(a);",Gue=`
  let e2x = exp(a);
  return (e2x - 1.0 / e2x) / 2.0;
`,Hue=`
  let epsilon = 1.1920928955078125e-7;
  let threshold = log(epsilon) + 2.0;

  let too_large = a > -threshold;
  let too_small = a < threshold;
  let exp_a = exp(a);

  if (too_large) {
    return a;
  } else if (too_small) {
    return exp_a;
  } else {
    return log(exp_a + 1.0);
  }
`,jue="return sqrt(a);",que="return a * a;",Xue=`
  if (isnan(a)) {
    return a;
  }

  return select(uniforms.stepAlpha, 1.0, a > 0.0);
`,Kue="return tan(a);",Yue=`
  let e2x = exp(-2.0 * abs(a));
  return sign(a) * (1.0 - e2x) / (1.0 + e2x);
`,Zue="return f32(i32((a)));";function Ws(e,t){switch(e){case le.ABS:return oue;case le.ACOS:return lue;case le.ACOSH:return uue;case le.ASIN:return due;case le.ASINH:return pue;case le.ATAN:return cue;case le.ATANH:return hue;case le.COS:return fue;case le.COSH:return gue;case le.CEIL:return mue;case le.ELU:return t?Aue:xue;case le.ERF:return bue;case le.EXP:return vue;case le.EXPM1:return yue;case le.FLOOR:return wue;case le.IS_FINITE:return kue;case le.IS_INF:return Iue;case le.IS_NAN:return Sue;case le.LINEAR:return Cue;case le.LOG:return Tue;case le.LOG1P:return Nue;case le.LOGICAL_NOT:return Rue;case le.NEG:return Eue;case le.LEAKYRELU:return t?$ue:Mue;case le.RECIPROCAL:return Pue;case le.RELU:return t?Oue:_ue;case le.RELU6:return t?Due:Fue;case le.ROUND:return zue;case le.RSQRT:return Lue;case le.SELU:return Wue;case le.SIGMOID:return Bue;case le.SIGN:return Vue;case le.SIN:return Uue;case le.SINH:return Gue;case le.SOFTPLUS:return Hue;case le.SQRT:return jue;case le.SQUARE:return que;case le.STEP:return Xue;case le.TAN:return Kue;case le.TANH:return Yue;case le.TO_INT:return Zue;default:throw new Error(`BinaryType ${e} is not implemented!`)}}function Pr(e,t=!1,a=!1,n=3){if(e===null)return"";let r="";if(e==="linear")r=Ws(le.LINEAR);else if(e==="relu")r=Ws(le.RELU,a);else if(e==="elu")r=Ws(le.ELU,a);else if(e==="relu6")r=Ws(le.RELU6,a);else if(e==="prelu")r=K3(Pe.PRELU,a);else if(e==="sigmoid")r=Ws(le.SIGMOID,a);else if(e==="leakyrelu")r=Ws(le.LEAKYRELU,a);else throw new Error(`Activation ${e} has not been implemented for the WebGPU backend.`);let s=Xe(a?4:1),i="";return t?i=`
      fn activation(a : ${s}, coords : vec${n}<i32>) -> ${s} {
        let b = getPreluActivationWeightsByOutputCoords(coords);
        ${r}
      }`:i=`
      fn activation(a : ${s}, coords : vec${n}<i32>) -> ${s} {
        ${r}
      }`,i}function ll(e,t){return`
      ${e?"value = value + getBiasByOutputCoords(coords);":""}
      ${t?"value = activation(value, coords);":""}
      `}function Ek(e,t,a=!1,n=!1,r=!1,s=1){v.assert(e&&s===1||!e,()=>`transposeA ${e} is not compatible with component size ${s}`);let i=`
      ${e?"value = getA(batch, col, row);":"value = getA(batch, row, col);"}

    `,o=t?"value = getB(batch, col, row);":"value = getB(batch, row, col);";return`
  fn mm_readA(batch: i32, row: i32, col: i32) -> ${Xe(s)} {
    var value = ${Xe(s)}(0.0);
    ${a&&r?i:`
    ${e?"if(row < uniforms.dimAOuter && col < uniforms.dimInner)":"if(row < uniforms.aShape[1] && col < uniforms.aShape[2])"}
    {
      ${i}
    }
    `}
    return value;
  }

  fn mm_readB(batch: i32, row: i32, col: i32) -> ${Xe(s)} {
    var value = ${Xe(s)}(0.0);
    ${o}
    return value;
  }
  `}function Y3(e,t,a,n,r=!1,s=!1,i=!1,o=1){return`
  ${Ek(a,n,r,s,i,o)}
  fn mm_write(batch: i32, row: i32, col: i32, valueIn: ${Xe(o)}) {
    ${r&&s?"":"if (row < uniforms.dimAOuter && col < uniforms.dimBOuter)"}
    {
      var value = valueIn;
      let coords = vec3<i32>(batch, row, col);
      ${ll(e,t)}
      setOutputAtCoords(coords[0], coords[1], coords[2], value);
    }
  }
  `}var Jue=(e,t)=>e?`
        mm_Asub[inputRow][inputCol] = mm_readA(batchA,
          kStart + inputRow,
          globalRowStart + inputCol * ${t});
        `:`
        mm_Asub[inputRow][inputCol] = mm_readA(batchA,
          globalRow + innerRow,
          kStart + inputCol * ${t});
        `,Que=(e,t,a,n)=>{if(e)return`
      for (var k = 0; k < ${n}; k++) {
        let BCached0 = mm_Bsub[k][tileCol];
        let ACached0 = mm_Asub[k][localRow];
        for (var i = 0; i < ${a}; i++) {
          acc[i] = fma(BCached0, vec4<f32>(ACached0[i]), acc[i]);
        }
      }`;{let r="",s="";for(let i=0;i<t;i++)r+=`let BCached${i} = mm_Bsub[k * ${t} + ${i}][tileCol];`,s+=`acc[i] = fma(BCached${i}, vec4<f32>(ACached[${i}]), acc[i]);`;return`
      for (var k = 0; k < ${n/t}; k++) {
        ${r}
        for (var i = 0; i < ${a}; i++) {
          let ACached = mm_Asub[tileRow + i][k];
          ${s}
        }
      }`}};function d0(e,t,a=!1,n=32,r=!1,s=32,i=!1){let o=t[1]*e[1],l=t[0]*e[0],u=a?o:n,p=a?n:o,c=u/t[0],d=n/t[1],h=e[1],m=e[0];return v.assert((a&&c===4&&e[1]===4||!a&&(c===3||c===4))&&u%t[0]===0&&n%t[1]===0&&e[0]===4,()=>`If transposeA ${a} is true, innerElementSize ${c} and workPerThread[1] ${e[1]} must be 4.
          Otherwise, innerElementSize ${c} must be 3 or 4.
      tileAWidth ${u} must be divisible by workgroupSize[0]${t[0]}. tileInner ${n} must be divisible by workgroupSize[1] ${t[1]}. colPerThread ${e[0]} must be 4.`),`
  var<workgroup> mm_Asub : array<array<vec${c}<f32>, ${u/c}>, ${p}>;
  var<workgroup> mm_Bsub : array<array<vec4<f32>, ${l/e[0]}>, ${n}>;

  ${ue()} {
    let localRow = i32(localId.y);
    let tileRow = localRow * ${h};
    let tileCol = i32(localId.x);

    let globalRow = i32(globalId.y) * ${h};
    let globalCol = i32(globalId.x) * ${m};
    let batch = ${r?"0":"i32(globalId.z)"};
    let batchA = ${r||!i?"batch":"batch % uniforms.aShape[0]"};
    let batchB = ${r||!i?"batch":"batch % uniforms.bShape[0]"};
    let globalRowStart = i32(workgroupId.y) * ${o};

    let numTiles = ${r?`${Math.ceil(s/n)}`:`(uniforms.dimInner - 1) / ${n} + 1`};
    var kStart = ${r?`i32(globalId.z) * ${s}`:"0"};

    var acc: array<vec4<f32>, ${h}>;

    // Loop over shared dimension.
    let tileRowB = localRow * ${d};
    for (var t = 0; t < numTiles; t++) {
        // Load one tile of A into local memory.
        for (var innerRow = 0; innerRow < ${h}; innerRow++) {
            let inputRow = tileRow + innerRow;
            let inputCol = tileCol;
            ${Jue(a,c)}
        }

        // Load one tile of B into local memory.
        for (var innerRow = 0; innerRow < ${d}; innerRow++) {
            let inputRow = tileRowB + innerRow;
            let inputCol = tileCol;
            mm_Bsub[inputRow][inputCol] = mm_readB(batchB, kStart + inputRow, globalCol);
        }
        kStart = kStart + ${n};
        workgroupBarrier();

        // Compute acc values for a single thread.
        ${Que(a,c,h,n)}
        workgroupBarrier();
    }

    for (var innerRow = 0; innerRow < ${h}; innerRow++) {
        mm_write(batch, globalRow + innerRow, globalCol, acc[innerRow]);
    }
  }`}var sA=e=>e?`
        mm_Asub[inputRow][inputCol] = mm_readA(batchA,
          kStart + inputRow,
          globalRowStart + inputCol);
        `:`
        mm_Asub[inputRow][inputCol] = mm_readA(batchA,
          globalRowStart + inputRow,
          kStart + inputCol);
        `,ede=e=>e?"let ACached = mm_Asub[k][tileRow + innerRow];":"let ACached = mm_Asub[tileRow + innerRow][k];";function p0(e,t,a=!1,n=32,r=!1,s=32,i=!1,o=!1){let l=e[1]*t[1],u=e[0]*t[0],p=a?l:n,c=a?n:l;v.assert(c%t[1]===0&&p%t[0]===0&&n%t[1]===0,()=>`tileAHight ${c} must be divisible by workgroupSize[1]${t[1]}, tileAWidth ${p} must be divisible by workgroupSize[0]${t[0]}, tileInner ${n} must be divisible by workgroupSize[1]${t[1]}`);let d=c/t[1],h=p/t[0],m=n/t[1],f=e[1],g=e[0],y=i?`
      let localRow = i32(localId.y);
      let localCol = i32(localId.x);
      let globalRowStart = i32(workgroupId.y) * ${l};
      let globalColStart = i32(workgroupId.x) * ${u};

      // Loop over shared dimension.
      for (var t = 0; t < numTiles; t++) {
        // Load one tile of A into local memory.
        for (var inputRow = localRow; inputRow < ${c}; inputRow = inputRow + ${t[1]}) {
          for (var inputCol = localCol; inputCol < ${p}; inputCol = inputCol + ${t[0]}) {
            ${sA(a)}
          }
        }
        // Load one tile of B into local memory.
        for (var inputRow = localRow; inputRow < ${n}; inputRow = inputRow + ${t[1]}) {
              for (var inputCol = localCol; inputCol < ${u}; inputCol = inputCol + ${t[0]}) {
            mm_Bsub[inputRow][inputCol] = mm_readB(batchB,
              kStart + inputRow,
              globalColStart + inputCol);
          }
        }
        kStart = kStart + ${n};
        workgroupBarrier();

        // Compute acc values for a single thread.
        var BCached : array<f32, ${g}>;
        for (var k = 0; k < ${n}; k++) {
          for (var inner = 0; inner < ${g}; inner++) {
            BCached[inner] = mm_Bsub[k][localCol + inner * ${t[0]}];
          }
          for (var innerRow = 0; innerRow < ${f}; innerRow++) {
            let ACached = ${a?`mm_Asub[k][localRow + innerRow * ${t[1]}];`:`mm_Asub[localRow + innerRow * ${t[1]}][k];`}
            for (var innerCol = 0; innerCol < ${g}; innerCol++) {
              acc[innerRow][innerCol] =
                  fma(ACached, BCached[innerCol], acc[innerRow][innerCol]);
            }
          }
        }
        workgroupBarrier();
      }
      for (var innerRow = 0; innerRow < ${f}; innerRow++) {
        let gRow = globalRowStart + localRow + innerRow * ${t[1]};
        for (var innerCol = 0; innerCol < ${g}; innerCol++) {
          let gCol = globalColStart + localCol + innerCol * ${t[0]};
          mm_write(batch, gRow, gCol, acc[innerRow][innerCol]);
        }
      }
      `:`
  let tileRow = i32(localId.y) * ${f};
  let tileCol = i32(localId.x) * ${g};

  let globalRow = i32(globalId.y) * ${f};
  let globalCol = i32(globalId.x) * ${g};
  let globalRowStart = i32(workgroupId.y) * ${l};

  let tileRowA = i32(localId.y) * ${d};
  let tileColA = i32(localId.x) * ${h};
  let tileRowB = i32(localId.y) * ${m};
  // Loop over shared dimension.
  for (var t = 0; t < numTiles; t++) {
    // Load one tile of A into local memory.
    for (var innerRow = 0; innerRow < ${d}; innerRow++) {
      for (var innerCol = 0; innerCol < ${h}; innerCol++) {
        let inputRow = tileRowA + innerRow;
        let inputCol = tileColA + innerCol;
        ${sA(a)}
      }
    }

    // Load one tile of B into local memory.
    for (var innerRow = 0; innerRow < ${m}; innerRow++) {
      for (var innerCol = 0; innerCol < ${g}; innerCol++) {
        let inputRow = tileRowB + innerRow;
        let inputCol = tileCol + innerCol;
        mm_Bsub[inputRow][inputCol] = mm_readB(batchB,
          kStart + inputRow,
          globalCol + innerCol);
      }
    }
    kStart = kStart + ${n};
    workgroupBarrier();

    // Compute acc values for a single thread.
    var BCached : array<f32, ${g}>;
    for (var k = 0; k < ${n}; k++) {
      for (var inner = 0; inner < ${g}; inner++) {
        BCached[inner] = mm_Bsub[k][tileCol + inner];
      }

      for (var innerRow = 0; innerRow < ${f}; innerRow++) {
        ${ede(a)}
        for (var innerCol = 0; innerCol < ${g}; innerCol++) {
          acc[innerRow][innerCol] =
              fma(ACached, BCached[innerCol], acc[innerRow][innerCol]);
        }
      }
    }

    workgroupBarrier();
  }

  for (var innerRow = 0; innerRow < ${f}; innerRow++) {
    for (var innerCol = 0; innerCol < ${g}; innerCol++) {
      mm_write(batch, globalRow + innerRow, globalCol + innerCol,
          acc[innerRow][innerCol]);
    }
  }
  `;return`
    var<workgroup> mm_Asub : array<array<f32, ${p}>, ${c}>;
    var<workgroup> mm_Bsub : array<array<f32, ${u}>, ${n}>;

    ${ue()} {
      let batch = ${r?"0":"i32(globalId.z)"};
      let batchA = ${r||!o?"batch":"batch % uniforms.aShape[0]"};
      let batchB = ${r||!o?"batch":"batch % uniforms.bShape[0]"};
      let numTiles = ${r?`${Math.ceil(s/n)}`:`(uniforms.dimInner - 1) / ${n} + 1`};
      var kStart = ${r?`i32(globalId.z) * ${s}`:"0"};

      var acc : array<array<f32, ${g}>, ${f}>;

      // Without this initialization strange values show up in acc.
      for (var innerRow = 0; innerRow < ${f}; innerRow++) {
        for (var innerCol = 0; innerCol < ${g}; innerCol++) {
          acc[innerRow][innerCol] = 0.0;
        }
      }
      ${y}
    }
  `}var tde=e=>e?`
      mm_readA(batchA, colA, globalRow),
      mm_readA(batchA, colA + 1, globalRow),
      mm_readA(batchA, colA + 2, globalRow),
      mm_readA(batchA, colA + 3, globalRow)
  `:`
      mm_readA(batchA, globalRow, colA),
      mm_readA(batchA, globalRow, colA + 1),
      mm_readA(batchA, globalRow, colA + 2),
      mm_readA(batchA, globalRow, colA + 3)
  `;function ade(e,t=!1){v.assert(e[1]===1&&e[2]===1,()=>`A linear work group size is required. But got ${e}.`);let a=e[0]*4;return`
    var<workgroup> mm_Asub : array<vec4<f32>, ${e[0]}>;

    ${ue()} {
      let tileCol = i32(localId.x);
      let globalCol = i32(globalId.x);
      let globalRow = i32(globalId.y);

      let numTiles = (uniforms.dimInner - 1) / ${a} + 1;
      let batch = i32(globalId.z);
      let batchA = batch % uniforms.aShape[0];
      let batchB = batch % uniforms.bShape[0];
      // Without this initialization strange values show up in acc.
      var acc = 0.0;

      // Loop over shared dimension.
      for (var t = 0; t < numTiles; t++) {
        // Load one tile of A into local memory.
        let colA = t * ${a} + tileCol * 4;
        mm_Asub[tileCol] = vec4<f32>(${tde(t)});
        workgroupBarrier();

        // Compute acc values for a single thread.
        for (var k = 0; k < ${a/4}; k++) {
          let rowB = t * ${a} + k * 4;
          let BCached = vec4<f32>(mm_readB(batchB, rowB, globalCol),
                              mm_readB(batchB, rowB + 1, globalCol),
                              mm_readB(batchB, rowB + 2, globalCol),
                              mm_readB(batchB, rowB + 3, globalCol));

          let ACached = mm_Asub[k];
          acc = acc + dot(ACached, BCached);
        }

        workgroupBarrier();
      }

      mm_write(batch, globalRow, globalCol, acc);
    }
  `}var nde=class{constructor(e,t,a=!1,n=!1,r=null,s=null,i=null,o=!1){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.outputShape=t,this.dispatchLayout={x:[2],y:[1],z:[0]};let l=a?e[1]:e[2];if(this.isVec4=(l%4===0&&!a||t[1]%4===0&&a)&&t[2]%4===0&&!n,this.outputComponent=this.isVec4?4:1,this.isVectorA=t[1]===1&&!a,!this.isVec4&&this.isVectorA)this.elementsPerThread=[1,1,1],this.workgroupSize=[32,1,1];else{let c=Nk(t[1],l,t[2],a);this.workgroupSize=c.workgroupSize,this.elementsPerThread=c.elementsPerThread}this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,this.elementsPerThread);let u=r!=null,p=i!=null;u&&this.variableNames.push("bias"),p&&this.variableNames.push("preluActivationWeights"),this.sequentialAccessByThreads=o,this.transposeA=a,this.transposeB=n,this.addBias=u,this.activation=s,this.hasPreluActivationWeights=p,[this.fitAOuter,this.fitBOuter,this.fitInner]=this.getShapeFit(t[1],t[2],l),this.shaderKey=`matMulPacked_${this.elementsPerThread}_${a}_${n}_${this.activation}_${this.fitAOuter}_${this.fitBOuter}_${this.fitInner}_${this.isVec4}_${this.isVectorA}_${this.sequentialAccessByThreads}`}getShapeFit(e,t,a){let n=this.workgroupSize[1]*this.elementsPerThread[1],r=this.workgroupSize[0]*this.elementsPerThread[0];!this.isVec4&&this.isVectorA?this.tileInner=this.workgroupSize[0]*4:this.tileInner=r;let s=e%n===0,i=t%r===0,o=a%this.tileInner===0;return[s,i,o]}getUserCode(){return`
      ${Pr(this.activation,this.hasPreluActivationWeights,this.isVec4)}
      ${Y3(this.addBias,this.activation,!1,this.transposeB,this.fitAOuter,this.fitBOuter,this.fitInner,this.isVec4?4:1)}
      ${this.isVec4?d0(this.elementsPerThread,this.workgroupSize,this.transposeA,this.tileInner,!1,null,!0):this.isVectorA?ade(this.workgroupSize,this.transposeA):p0(this.elementsPerThread,this.workgroupSize,this.transposeA,this.tileInner,!1,null,this.sequentialAccessByThreads,!0)}
    `}};function rde(e){return`
    var<workgroup> sumValues : array<f32, ${e}>;
    ${ue()} {
      let coords = getOutputCoords();
      let batch = coords[0];
      let batchA = batch % uniforms.aShape[0];
      let batchB = batch % uniforms.bShape[0];
      let row = coords[1];
      let col = coords[2];
      var sum = 0.0;
      let Length = uniforms.dimInner;
      for (var k = i32(localId.x); k < Length; k = k + ${e}) {
        let dataA = mm_readA(batchA, row, k);
        let dataB = mm_readB(batchB, k, col);
        sum = sum + dataA * dataB;
      }
      sumValues[localId.x] = sum;
      workgroupBarrier();

      for(var currentSize = ${e/2}u; currentSize > 1u;
          currentSize = currentSize / 2u) {
        if (localId.x < currentSize)
        {
          sumValues[localId.x] = sumValues[localId.x] + sumValues[localId.x + currentSize];
        }
        workgroupBarrier();
      }

      if (localId.x == 0u) {
        sum = sumValues[0] + sumValues[1];
        mm_write(batch, row, col, sum);
      }
    }
  `}var sde=class{constructor(e,t=!1,a=!1,n=null,r=null,s=null){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workgroupSize=[256,1,1],this.outputShape=e,this.dispatchLayout={x:[],y:[1,2],z:[0]},this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize);let i=n!=null,o=s!=null;i&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),this.transposeA=t,this.transposeB=a,this.addBias=i,this.activation=r,this.hasPreluActivationWeights=o,this.shaderKey=`matMulReduce_${this.activation}_${t}_${a}`}getUserCode(){return`
      ${Pr(this.activation,this.hasPreluActivationWeights)}
      ${Y3(this.addBias,this.activation,this.transposeA,this.transposeB)}
      ${rde(this.workgroupSize[0])}
    `}};function ide(e){let t=e[1],a=e[0],n=t>a?t:a;return`
  var<workgroup> mm_Asub : array<array<f32, ${n}>, ${t}>;
  var<workgroup> mm_Bsub : array<array<f32, ${a}>, ${n}>;

  // If the output size is small for matrix multiplication, avoid to use vec4
  // and handle some elements per thread to optimally utilize the ALU.
  // Read data from global memory to registers firstly, then store them into
  // shared memory, so it is instruction-Level parallelism for arithmetic
  // operations and others handle IO operations between barrier api, makes ALU
  // and load/store units work simultaneously, could improves the performance.
  ${ue()} {
    let tileRow = i32(localId.y);
    let tileCol = i32(localId.x);
    let globalRow = i32(globalId.y);
    let globalCol = i32(globalId.x);
    let batch = i32(globalId.z);
    let batchA = batch % uniforms.aShape[0];
    let batchB = batch % uniforms.bShape[0];

    // uniforms.dimInner should be greater than 0.
    let numTiles = (uniforms.dimInner - 1) / ${n} + 1;
    var acc = 0.0;

    var globalColA = tileCol;
    var globalRowB = 0;
    var regA = mm_readA(batchA, globalRow, globalColA);
    var regB0 = mm_readB(batchB, globalRowB + 2 * tileRow, globalCol);
    var regB1 = mm_readB(batchB, globalRowB + 2 * tileRow + 1, globalCol);
    globalColA = globalColA + ${n};
    globalRowB = globalRowB + ${n};

    for (var t = 0; t < numTiles; t = t + 1) {
      mm_Asub[tileRow][tileCol] = regA;
      mm_Bsub[2 * tileRow][tileCol] = regB0;
      mm_Bsub[2 * tileRow + 1][tileCol] = regB1;

      workgroupBarrier();

      regA = mm_readA(batchA, globalRow, globalColA);
      regB0 = mm_readB(batchB, globalRowB + 2 * tileRow, globalCol);
      regB1 = mm_readB(batchB, globalRowB + 2 * tileRow + 1, globalCol);
      globalColA = globalColA + ${n};
      globalRowB = globalRowB + ${n};

      for (var k = 0; k < ${n}; k = k + 1) {
        acc = acc + mm_Asub[tileRow][k] * mm_Bsub[k][tileCol];
      }
      workgroupBarrier();
    }

    mm_write(batch, globalRow, globalCol, acc);
  }
  `}var ode=class{constructor(e,t,a,n=!1,r=!1,s=null,i=null,o=null){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workgroupSize=[16,8,1],this.outputShape=a,this.dispatchLayout={x:[2],y:[1],z:[0]},this.dispatch=[Math.ceil(a[2]/this.workgroupSize[0]),Math.ceil(a[1]/this.workgroupSize[1]),a[0]];let l=s!=null;l&&this.variableNames.push("bias");let u=o!=null;u&&this.variableNames.push("preluActivationWeights"),this.transposeA=n,this.transposeB=r,this.addBias=l,this.activation=i,this.hasPreluActivationWeights=u,this.shaderKey=`matMulSmallOutputSize_${this.activation}_${n}_${r}`}getUserCode(){return`
      ${Pr(this.activation,this.hasPreluActivationWeights)}
      ${Y3(this.addBias,this.activation,this.transposeA,this.transposeB)}
      ${ide(this.workgroupSize)}
    `}},lde=class{constructor(e,t,a=!1,n=!1){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workgroupSize=[8,8,1],this.atomic=!0,this.splitedDimInner=128,v.assert(e[0]===1,()=>"MatMulSplitKProgram only supports batch = 1."),this.outputShape=e,this.dispatchLayout={x:[2],y:[1],z:[0,3]};let r=(a&&this.outputShape[1]%4===0||!a&&t%4===0)&&this.outputShape[2]%4===0;this.elementsPerThread=[4,4,this.splitedDimInner],this.outputComponent=r?4:1,r||(this.outputShape[1]<16&&(this.elementsPerThread[1]=1),this.outputShape[2]<16&&(this.elementsPerThread[0]=1)),this.dispatch=de(this.dispatchLayout,[this.outputShape[0],this.outputShape[1],this.outputShape[2],t],this.workgroupSize,this.elementsPerThread),this.transposeA=a,this.transposeB=n,this.shaderKey=`matMulSplitK_${a}_${n}_${this.elementsPerThread}_${this.outputComponent}`}getUserCode(){let e=this.outputComponent;return`
      ${Ek(!1,this.transposeB,!1,!1,!1,e)}
      fn mm_write(batch: i32, row : i32, col : i32, value : ${Xe(e)}) {
        if (row < uniforms.dimAOuter && col < uniforms.dimBOuter) {
          let coords = vec3<i32>(batch, row, col);
          let flatIndex = getOutputIndexFromCoords(coords);
          // The problem is that we should initialize output to zero before using.
          // Otherwise, the original value will be added to the result.
          for (var i = 0; i < ${e}; i = i + 1) {
            ${xs("&result[flatIndex + i]",`${e>1?"value[i]":"value"}`,"float32")}
          }
        }
      }
      ${e===4?d0(this.elementsPerThread,this.workgroupSize,this.transposeA,32,!0,this.splitedDimInner):p0(this.elementsPerThread,this.workgroupSize,this.transposeA,32,!0,this.splitedDimInner)}
    `}},ude=class{constructor(e,t=null,a=null,n=null){this.uniforms="",this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.addBias=t!=null,this.hasPreluActivationWeights=n!=null,this.activation=a,this.addBias&&this.variableNames.push("bias"),this.hasPreluActivationWeights&&this.variableNames.push("preluActivationWeights"),this.shaderKey=`biasActivation_${a}`}getUserCode(){return`
    ${Pr(this.activation,this.hasPreluActivationWeights)}
    ${ue("index")} {
      if (index < uniforms.size) {
        let coords = getCoordsFromIndex(index);
        var value = getXByOutputIndex(index);
        ${ll(this.addBias,this.activation)}
        setOutputAtIndex(index, value);
      }
    }
    `}},dde=class{constructor(e){this.variableNames=[],this.outputShape=[],this.uniforms="value : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="fill"}getUserCode(){return`
    ${ue("index")} {
      if (index < uniforms.size) {
        setOutputAtIndex(index, uniforms.value);
      }
    }
  `}};function Wa(e){let{backend:t,attrs:a}=e,{shape:n,value:r}=a,{dtype:s}=a;if(s=s||v.inferDtype(r),s==="string"){let i=v.getArrayFromDType(s,v.sizeFromShape(n));return i.fill(r),t.makeTensorInfo(n,s,i)}else{let i=new dde(n),o=[{type:"float32",data:[r]}];return t.runWebGPUProgram(i,[],s,o)}}var pde={kernelName:bu,backendName:"webgpu",kernelFunc:Wa};function ke(e){let{inputs:t,attrs:a}=e,{x:n}=t,{shape:r}=a,s=v.sizeFromShape(n.shape),i=v.inferFromImplicitShape(r,s),o=v.sizeFromShape(i);return v.assert(s===o,()=>`The new shape (${i}) has ${o} elements and the old shape (${n.shape}) has ${s} elements. The new shape and old shape must have the same number of elements.`),e.backend.incRef(n.dataId),{dataId:n.dataId,shape:i,dtype:n.dtype}}var cde={kernelName:Eu,backendName:"webgpu",kernelFunc:ke};function c0({a:e,b:t,transposeA:a,transposeB:n,backend:r,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:o=0,activation:l=null}){let u=e.shape.length,p=t.shape.length,c=a?e.shape[u-2]:e.shape[u-1],d=n?t.shape[p-1]:t.shape[p-2],h=a?e.shape[u-1]:e.shape[u-2],m=n?t.shape[p-2]:t.shape[p-1],f=e.shape.slice(0,-2),g=t.shape.slice(0,-2),y=v.sizeFromShape(f),x=v.sizeFromShape(g),A=nl.assertAndGetBroadcastShape(e.shape.slice(0,-2),t.shape.slice(0,-2)).concat([h,m]);v.assert(c===d,()=>`Error in matMul: inner shapes (${c}) and (${d}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${a} and transposeB=${n} must match.`);let b=a?[y,c,h]:[y,h,c],w=n?[x,m,d]:[x,d,m],I=ke({inputs:{x:e},backend:r,attrs:{shape:b}}),T=ke({inputs:{x:t},backend:r,attrs:{shape:w}}),N=[I,T],M=Math.max(y,x),$=[I,T],E=[{type:"int32",data:[h]},{type:"int32",data:[m]},{type:"int32",data:[c]}],S,_,O=[M,h,m],W=B().get("WEBGPU_MATMUL_PROGRAM_TYPE");if(W<0){let U=B().getNumber("WEBGPU_THRESHOLD_TO_INCREASE_WORKGROUPS_FOR_MATMUL"),G=U>0?U:r.thresholdToIncreaseWorkgroups,q=M*Math.ceil(h/32)*Math.ceil(m/32);q<=G||h<=8&&q<=G*2?M*h*m<=128?W=On.MatMulReduceProgram:M===1&&d>=2e3?W=On.MatMulSplitKProgram:W=On.MatMulSmallOutputSizeProgram:W=On.MatMulPackedProgram}switch(W){case On.MatMulReduceProgram:S=new sde(O,a,n,s,l,i);break;case On.MatMulSplitKProgram:{if(_=Wa({backend:r,attrs:{shape:O,value:0,dtype:e.dtype}}),S=new lde(O,d,a,n),s||l){_=r.runWebGPUProgram(S,$,e.dtype,E,_);let G=new ude(_.shape,s,l,i),q=null,H=[_];s&&H.push(s),i&&H.push(i),l==="leakyrelu"&&(q=[{type:"float32",data:[o]}],G.uniforms+=" alpha : f32,");let V=r.runWebGPUProgram(G,H,_.dtype,q);N.push(_);let Z=ke({inputs:{x:V},backend:r,attrs:{shape:A}});N.push(V);for(let X of N)r.disposeData(X.dataId);return Z}break}case On.MatMulSmallOutputSizeProgram:S=new ode(b,w,O,a,n,s,l,i);break;case On.MatMulPackedProgram:let U=r.adapterInfo.isIntel();S=new nde(b,O,a,n,s,l,i,U);break;default:throw new Error(`Unsupported MatMulProgramType ${W}.`)}s&&$.push(s),i&&$.push(i),l==="leakyrelu"&&(E.push({type:"float32",data:[o]}),S.uniforms+=" alpha : f32,"),_=r.runWebGPUProgram(S,$,e.dtype,E,_);let P=ke({inputs:{x:_},backend:r,attrs:{shape:A}});N.push(_);for(let U of N)r.disposeData(U.dataId);return P}function hde(e){let{inputs:t,backend:a,attrs:n}=e,{a:r,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:u,activation:p,leakyreluAlpha:c}=n;return c0({a:r,b:s,transposeA:l,transposeB:u,backend:a,bias:i,preluActivationWeights:o,leakyreluAlpha:c,activation:p})}var mde={kernelName:Zr,backendName:"webgpu",kernelFunc:hde},iA=class{constructor(e,t,a){this.variableNames=["AReal","AImag","BReal","BImag"],this.workgroupSize=[128,1,1],this.size=!0,this.outputShape=C.assertAndGetBroadcastShape(t,a),this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey=`binaryOpComplex_${e}`,this.op=e}getUserCode(){return`
      fn binaryOpComplex(
          areal : f32, aimag : f32, breal : f32, bimag : f32) -> f32 {
        ${K3(this.op,!1)}
      }

      ${ue("index")} {
        if(index < uniforms.size) {
          let areal = getARealByOutputIndex(index);
          let aimag = getAImagByOutputIndex(index);
          let breal = getBRealByOutputIndex(index);
          let bimag = getBImagByOutputIndex(index);
          setOutputAtIndex(index, binaryOpComplex(areal, aimag, breal, bimag));
        }
      }
    `}},Th=class{constructor(e,t,a){if(this.size=!0,this.variableNames=["A","B"],this.outputShape=C.assertAndGetBroadcastShape(t,a),this.dispatchLayout=me(this.outputShape),this.op=e,this.useSharedMemoryWithA=t.length<=1&&a.length>1&&t[0]<128,this.useSharedMemoryWithB=a.length<=1&&t.length>1&&a[0]<128,this.useSharedMemoryWithA||this.useSharedMemoryWithB)this.outputComponent=1,this.variableComponents=[1,1],this.lastDimensionSize=this.useSharedMemoryWithB?a[0]:t[0],this.shaderKey=`binary_${e}_${this.lastDimensionSize}`,this.type="shared",this.workgroupSize=[256,1,1];else{let n=t.length>0&&t[t.length-1]%4===0,r=a.length>0&&a[a.length-1]%4===0;n&&r?(this.outputComponent=4,this.variableComponents=[4,4]):n&&(v.isScalarShape(a)||a[a.length-1]===1)||r&&(v.isScalarShape(t)||t[t.length-1]===1)?(this.outputComponent=4,this.variableComponents=n?[4,1]:[1,4]):(this.outputComponent=1,this.variableComponents=[1,1]),this.type="nonshared",this.shaderKey=`binary_${e}_${this.variableComponents}`,this.workgroupSize=[128,1,1]}this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.outputComponent,1,1])}getUserCode(){let e,t=this.outputComponent===4?"vec4<f32>":"f32",a=`
    fn binaryOperation(a : ${t}, b : ${t}) -> ${t} {
      ${K3(this.op,this.outputComponent===4)}
    };
    `;if(this.type==="shared"){let n=this.lastDimensionSize>1?`coords[${this.outputShape.length-1}]`:"0",r=this.useSharedMemoryWithB?`let a = getAByOutputIndex(index);
          let b = sharedBuf[${n}];`:`let a = sharedBuf[${n}];
          let b = getBByOutputIndex(index);`;e=`
        ${a}
        var<workgroup> sharedBuf : array<f32, ${this.lastDimensionSize}>;
        ${ue("index")} {
          // Fill in the shared memory buffer.
          let localIndex = i32(localId.x);
          if(localIndex < ${this.lastDimensionSize}) {
            sharedBuf[localIndex] = f32(${this.useSharedMemoryWithB?"B":"A"}[localIndex]);
          }
          workgroupBarrier();

          if(index < uniforms.size) {
            let coords = getCoordsFromIndex(index);
            ${r}
            setOutputAtIndex(index, binaryOperation(a, b));
          }
        }
        `}else e=`
       ${a}
       ${ue("index")} {
         if (index < uniforms.size) {
           let coords = getCoordsFromIndex(index * ${this.outputComponent});
           let a = ${t}(getAByOutputCoords(coords));
           let b = ${t}(getBByOutputCoords(coords));
           setOutputAtIndex(index, binaryOperation(a, b));
         }
       }
       `;return e}};function tn(e){let{inputs:t}=e,{x:a}=t;return e.backend.incRef(a.dataId),{dataId:a.dataId,shape:a.shape,dtype:a.dtype}}var fde={kernelName:qi,backendName:"webgpu",kernelFunc:tn};function ul(e){let{inputs:t,backend:a}=e,{real:n,imag:r}=t,s=a.makeTensorInfo(n.shape,"complex64"),i=a.tensorMap.get(s.dataId),o=tn({inputs:{x:n},backend:a}),l=tn({inputs:{x:r},backend:a});return i.complexTensorInfos={real:o,imag:l},s}var gde={kernelName:cp,backendName:"webgpu",kernelFunc:ul},td=class{constructor(e,t,a=""){this.variableNames=["A"],this.size=!0;let n=128;this.workgroupSize=[n,1,1],this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.op=t,a!==""&&(this.uniforms=a),this.shaderKey=`unary_${t}`}getUserCode(){return`
      fn unaryOperation(a : f32) -> f32 {
        ${Ws(this.op,!1)}
      }
      ${ue("index")} {
        if (index < uniforms.size) {
          let a = getAByOutputIndex(index);
          setOutputAtIndex(index, unaryOperation(a));
        }
      }
      `}};function at({opType:e,cpuKernelImpl:t,dtype:a}){return({inputs:n,backend:r})=>{let{x:s}=n,i=r,o=a||s.dtype;if(i.shouldExecuteOnCPU([s])&&t!=null){let u=i.tensorMap.get(s.dataId),p=t(u.values,o);return i.makeTensorInfo(s.shape,o,p)}let l=new td(s.shape,e);return i.runWebGPUProgram(l,[s],o)}}function aa({opType:e,cpuKernelImpl:t,supportsComplex:a=!1,dtype:n}){return({inputs:r,backend:s})=>{let{a:i,b:o}=r,l=s;if(a&&i.dtype==="complex64"){let c=l.tensorMap.get(i.dataId),d=l.tensorMap.get(o.dataId),h,m;if(e!==Pe.MUL)[h,m]=[[c.complexTensorInfos.real,d.complexTensorInfos.real],[c.complexTensorInfos.imag,d.complexTensorInfos.imag]].map(g=>{let[y,x]=g,A={dataId:y.dataId,dtype:y.dtype,shape:i.shape},b={dataId:x.dataId,dtype:x.dtype,shape:o.shape},w=new Th(e,i.shape,o.shape);return l.runWebGPUProgram(w,[A,b],ca(y.dtype,x.dtype))});else{let g=new iA(Pe.COMPLEX_MULTIPLY_REAL,i.shape,o.shape),y=new iA(Pe.COMPLEX_MULTIPLY_IMAG,i.shape,o.shape),x=[{dataId:c.complexTensorInfos.real.dataId,dtype:c.complexTensorInfos.real.dtype,shape:i.shape},{dataId:c.complexTensorInfos.imag.dataId,dtype:c.complexTensorInfos.imag.dtype,shape:i.shape},{dataId:d.complexTensorInfos.real.dataId,dtype:d.complexTensorInfos.real.dtype,shape:o.shape},{dataId:d.complexTensorInfos.imag.dataId,dtype:d.complexTensorInfos.imag.dtype,shape:o.shape}];h=l.runWebGPUProgram(g,x,"float32"),m=l.runWebGPUProgram(y,x,"float32")}let f=ul({inputs:{real:h,imag:m},backend:l});return l.disposeData(h.dataId),l.disposeData(m.dataId),f}let u=n||ca(i.dtype,o.dtype);if((i.dtype==="string"||o.dtype==="string"||l.shouldExecuteOnCPU([i,o]))&&t!=null){let c=l.tensorMap.get(i.dataId).values,d=l.tensorMap.get(o.dataId).values,h=i.dtype==="string"?C.fromUint8ToStringArray(c):c,m=i.dtype==="string"?C.fromUint8ToStringArray(d):d,[f,g]=t(i.shape,o.shape,h,m,u);return l.makeTensorInfo(g,u,f)}let p=new Th(e,i.shape,o.shape);return l.runWebGPUProgram(p,[i,o],u)}}var{addImpl:yde,castImpl:xde,ceilImpl:Ade,concatImpl:bde,equalImpl:vde,expImpl:wde,expm1Impl:kde,floorImpl:Ide,floorDivImpl:Sde,gatherNdImpl:Cde,gatherV2Impl:Tde,greaterEqualImpl:Nde,greaterImpl:Rde,lessEqualImpl:Ede,lessImpl:Mde,logImpl:$de,maxImpl:Pde,maximumImpl:_de,minimumImpl:Fde,multiplyImpl:Dde,negImpl:Ode,notEqualImpl:zde,prodImpl:Lde,rangeImpl:Wde,rsqrtImpl:Bde,scatterImpl:Vde,simpleAbsImpl:Ude,sliceImpl:Gde,stridedSliceImpl:Hde,stringNGramsImpl:jde,subImpl:qde,tileImpl:Xde,topKImpl:Kde,transposeImpl:Yde,uniqueImpl:cye}=t0,Zde=at({opType:le.ABS,cpuKernelImpl:Ude}),Jde={kernelName:ou,backendName:"webgpu",kernelFunc:Zde},Qde=at({opType:le.ACOS}),epe={kernelName:oi,backendName:"webgpu",kernelFunc:Qde},tpe=at({opType:le.ACOSH}),ape={kernelName:li,backendName:"webgpu",kernelFunc:tpe},npe=aa({opType:Pe.ADD,cpuKernelImpl:yde,supportsComplex:!0}),rpe={kernelName:ls,backendName:"webgpu",kernelFunc:npe},spe=class{constructor(e){this.workPerThread=1,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e[0],this.variableNames=e.map((t,a)=>`T${a}`),this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1]),this.shaderKey="addN"}getUserCode(){let e=[];this.variableNames.forEach(a=>{e.push(`let v${a} = get${a}ByOutputCoords(coords);`)});let t=this.variableNames.map(a=>`v${a}`).join(" + ");return`
      ${ue("index")} {
        for (var i = 0; i < ${this.workPerThread}; i = i + 1) {
          let flatIndex = index * ${this.workPerThread} + i;
          if (flatIndex < uniforms.size) {
            let coords = getCoordsFromIndex(flatIndex);
            ${e.join(`
        `)}
            setOutputAtIndex(flatIndex, ${t});
          }
        }
      }
    `}};function ipe(e){let{inputs:t,backend:a}=e,n=t;if(n.length===1)return tn({inputs:{x:n[0]},backend:a});let r=n.map(o=>o.dtype).reduce((o,l)=>ca(o,l)),s=n.map(o=>o.shape),i=new spe(s);return a.runWebGPUProgram(i,n,r)}var ope={kernelName:ui,backendName:"webgpu",kernelFunc:ipe},lpe=class{constructor(e,t){this.variableNames=["A"],this.workgroupSize=[16,16,1];let a=new Array(e.length);for(let n=0;n<a.length;n++)a[n]=e[t[n]];this.outputShape=a,this.dispatchLayout={x:[0],y:[1]},this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,[1,1,1]),this.shaderKey="transposeShared"}getUserCode(){v.assert(this.workgroupSize[0]===this.workgroupSize[1],()=>`Must be a square tile, current tile shape is ${this.workgroupSize[0]} x ${this.workgroupSize[1]}`);let e=this.workgroupSize[0];return`
      var<workgroup> tile : array<array<f32, ${this.workgroupSize[0]+1}>, ${this.workgroupSize[0]}>;
      ${ue()} {
        var x = i32(workgroupId.x) * ${e} + i32(localId.x);
        var y = i32(workgroupId.y) * ${e} + i32(localId.y);
        let width = uniforms.outShape[0];
        let height = uniforms.outShape[1];
        if (x < width && y < height) {
          tile[localId.y][localId.x] = f32(A[y * width + x]);
        }
        workgroupBarrier();

        x = i32(workgroupId.y) * ${e} + i32(localId.x);
        y = i32(workgroupId.x) * ${e} + i32(localId.y);
        if (x < height && y < width) {
          setOutputAtIndex((y * height + x), tile[localId.x]
            [localId.y]);
        }
      }
    `}},upe=class{constructor(e,t){this.variableNames=["A"],this.workPerThread=1,this.workgroupSize=[64,1,1],this.size=!0;let a=new Array(e.length);for(let n=0;n<a.length;n++)a[n]=e[t[n]];this.outputShape=a,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1]),this.newDim=t,this.shaderKey=`transpose_${t}`}getUserCode(){let e=Pt(this.outputShape.length),t=Mk(this.newDim);return`
      ${ue("index")} {
        for(var i = 0; i < ${this.workPerThread}; i = i + 1) {
          let flatIndex = index * ${this.workPerThread} + i;
          if(flatIndex < uniforms.size) {
            let coords = getCoordsFromIndex(flatIndex);
            setOutputAtIndex(flatIndex, A[getIndexFromCoords${this.outputShape.length}D(
              ${e}(${t}), uniforms.aShape)]);
          }
        }
      }
    `}};function Mk(e){let t=e.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let a=new Array(t);for(let n=0;n<e.length;n++)a[e[n]]=`coords.${Cr(n)}`;return a.join()}function sr(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{perm:s}=n,i=a,o=r.shape.length,l=new Array(o);for(let p=0;p<l.length;p++)l[p]=r.shape[s[p]];if(a.shouldExecuteOnCPU([r])){let p=i.tensorMap.get(r.dataId).values,c=Yde(p,r.shape,r.dtype,s,l);return a.makeTensorInfo(l,r.dtype,c)}if(r.shape.length===2&&v.arraysEqual(s,[1,0])){let p=new lpe(r.shape,s);return i.runWebGPUProgram(p,[r],r.dtype)}let u=new upe(r.shape,s);return i.runWebGPUProgram(u,[r],r.dtype)}var dpe={kernelName:Ir,backendName:"webgpu",kernelFunc:sr},ppe=class{constructor(e,t,a){this.variableNames=["x"],this.uniforms="reduceSize : i32,",this.size=!0,this.inputShape=[e.batchSize,e.inSize];let[n]=C.computeOutAndReduceShapes(this.inputShape,[1]);this.outputShape=n.length===0?[1]:n,e.inSize>=32768&&a>=512?this.workgroupSize=[512,1,1]:e.inSize>=4096?this.workgroupSize=[256,1,1]:this.workgroupSize=[64,1,1],this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,[1,1,1]),this.reduceType=t,this.shaderKey=`reduce_${t}`}getUserCode(){let e="",t="0.0",a=this.workgroupSize[0];this.reduceType==="min"||this.reduceType==="max"?(e=`
         if (isnan(candidate)) {
          bestValue = uniforms.NAN;
         } else if (!isnan(bestValue) && candidate ${this.reduceType==="min"?"<":">"} bestValue)
           {  bestValue = candidate; }`,t="f32(x[offset])"):this.reduceType==="sum"||this.reduceType==="mean"?e=" bestValue = bestValue + candidate; ":this.reduceType==="prod"?(e=" bestValue = bestValue * candidate; ",t="1.0"):this.reduceType==="all"?(e=" bestValue = f32(bestValue >= 1.0 && candidate >= 1.0); ",t="1.0"):this.reduceType==="any"&&(e=" bestValue = f32(bestValue >= 1.0 || candidate >= 1.0); ",t="0.0");let n=this.reduceType==="mean"?"setOutputAtIndex(outputIndex, bestValue / f32(uniforms.reduceSize));":"setOutputAtIndex(outputIndex, bestValue);";return`
       fn DIV_CEIL(a : u32, b : u32) -> u32 {
        return ((a - 1u) / b + 1u);
       }

       ${`
         var<workgroup> xBestValues : array<f32, ${a}>;
       `}
       fn getOffset(outputIndex : i32) -> i32 {
         let outputCoords = getCoordsFromIndex(outputIndex);
         let offset = ${this.outputShape.length===1?"outputCoords":"outputCoords[0]"} * uniforms.reduceSize;
          return offset;
       }
       ${ue("index")} {
         let outputIndex = index / ${a};
         let offset = getOffset(outputIndex);
         var bestValue = ${t};
         let Length = uniforms.reduceSize;
         let WorkPerThread = DIV_CEIL(u32(Length), ${a}u);
         for (var k = i32(localId.x); k < Length && outputIndex < uniforms.size;
             k = k + ${a}) {
           let candidate = f32(x[offset + k]);
           ${e}
         }
         xBestValues[localId.x] = bestValue;
         workgroupBarrier();

         var reduceSize = min(u32(Length), ${a}u);
         for (var currentSize = reduceSize / 2u; reduceSize > 1u;
             currentSize = reduceSize / 2u) {
           let interval = DIV_CEIL(reduceSize, 2u);
           if (localId.x < currentSize) {
            let candidate = xBestValues[localId.x + interval];
            ${e}
            xBestValues[localId.x] = bestValue;
           }
           reduceSize = interval;
           workgroupBarrier();
         }

         if (localId.x == 0u && outputIndex < uniforms.size) {
          ${n}
        }
       }
     `}},cpe={mean:"float32",all:"bool",any:"bool"};function dl(e,t,a,n,r){let s=e.shape.length,i=[],o=v.parseAxisParam(t,e.shape),l=o,u=C.getAxesPermutation(l,s),p=e;u!=null&&(p=sr({inputs:{x:e},attrs:{perm:u},backend:r}),l=C.getInnerMostAxes(l.length,s),i.push(p)),C.assertAxesAreInnerMostDims(n,l,s);let[c,d]=C.computeOutAndReduceShapes(p.shape,l),h=c;a&&(h=C.expandShapeToKeepDim(c,o));let m;if((n==="max"||n==="prod")&&r.shouldExecuteOnCPU([p])){let f=r.tensorMap.get(p.dataId).values;switch(n){case"max":let g=Pde(f,v.sizeFromShape(d),h,e.dtype);m=r.makeTensorInfo(h,e.dtype,g);break;case"prod":let{outVals:y,outShape:x,outDtype:A}=Lde(p.shape,p.dtype,f,l);m=r.makeTensorInfo(x,A,y);break;default:throw new Error(`${n} CPU implementation is not yet supported.`)}}else{let f=v.sizeFromShape(d),g=v.sizeFromShape(p.shape)/f,y={windowSize:f,inSize:f,batchSize:g,outSize:1},x=cpe[n]||_p(e.dtype),A=[{type:"int32",data:[f]}],b=new ppe(y,n,r.device.limits.maxComputeWorkgroupSizeX),w=r.runWebGPUProgram(b,[p],x,A);i.push(w),m=ke({inputs:{x:w},attrs:{shape:h},backend:r})}return i.forEach(f=>r.disposeData(f.dataId)),m}function hpe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{keepDims:s,axis:i}=n;return dl(r,i,s,"all",a)}var mpe={kernelName:di,backendName:"webgpu",kernelFunc:hpe};function fpe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{keepDims:s,axis:i}=n;return dl(r,i,s,"any",a)}var gpe={kernelName:pi,backendName:"webgpu",kernelFunc:fpe},$k=class{constructor(e,t,a){this.workgroupSize=[64,1,1],this.variableNames=["x"],this.uniforms="infinityValue : f32,",this.size=!0;let n=[t];this.op=a==="min"?"<":">";let[r,s]=C.computeOutAndReduceShapes(e,n);this.outputShape=r.length===0?[1]:r,this.dispatchLayout=me(this.outputShape),v.sizeFromShape(s)<32?(this.type="plain",this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize)):(this.type="shared",this.dispatch=de(this.dispatchLayout,this.outputShape,[1,1,1])),this.inputShape=e,this.shaderKey=`argMinMax_${this.op}_${this.type}`}getUserCode(){let e=this.workgroupSize[0],t=()=>this.inputShape.length===1?"uniforms.xShape":`uniforms.xShape.${Cr(this.inputShape.length-1)}`,a=()=>{let n="";if(this.outputShape.length===1)this.inputShape.length!==1&&(n+="outputCoords,");else for(let r=0;r<this.outputShape.length;r++)n+=`outputCoords.${Cr(r)},`;return n};return this.type==="shared"?`
      fn DIV_CEIL(a : u32, b : u32) -> u32 {
        return ((a - 1u) / b + 1u);
      }

      ${`
      var<workgroup> xBestIndices : array<i32, ${e}>;
      var<workgroup> xBestValues : array<f32, ${e}>;
    `}

      ${ue("index")} {
        let outputIndex = index / ${e};
        let reduceLength = ${t()};

        var bestIndex = i32(localId.x);
        var bestValue = uniforms.infinityValue;
        let outputCoords = getCoordsFromIndex(outputIndex);
        for (var k = i32(localId.x); k < reduceLength && outputIndex < uniforms.size;
            k = k + ${e}) {
          let candidate = getX(${a()} k);
          if (!isnan(candidate) && candidate ${this.op} bestValue) {
            bestValue = candidate;
            bestIndex = k;
          }
        }
        xBestValues[localId.x] = bestValue;
        xBestIndices[localId.x] = bestIndex;
        workgroupBarrier();

        var reduceSize = min(u32(reduceLength), ${e}u);
        for (var currentSize = reduceSize / 2u; reduceSize > 1u;
            currentSize = reduceSize / 2u) {
          let interval = DIV_CEIL(reduceSize, 2u);
          if (localId.x < currentSize) {
            let candidate = xBestValues[localId.x + interval];
            if (candidate ${this.op} bestValue) {
              bestValue = candidate;
              xBestValues[localId.x] = bestValue;
              xBestIndices[localId.x] = xBestIndices[localId.x + interval];
            }
          }
          reduceSize = interval;
          workgroupBarrier();
        }

        if (localId.x == 0u && outputIndex < uniforms.size) {
          setOutputAtIndexI32(outputIndex, xBestIndices[localId.x]);
        }
      }
    `:`
      ${ue("index")} {
        if (index < uniforms.size) {
          let outputCoords = getCoordsFromIndex(index);
          var bestIndex = 0;
          var bestValue = getX(${a()} 0);
          let reduceLength = ${t()};
          for (var i = 1; i < reduceLength; i++) {
            let candidate = getX(${a()} i);
            if (candidate ${this.op} bestValue) {
              bestValue = candidate;
              bestIndex = i;
            }
          }
          setOutputAtIndexI32(index, bestIndex);
        }
      }
      `}};function ype(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s}=n,i=v.parseAxisParam(s,r.shape),o=C.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=sr({inputs:{x:r},backend:a,attrs:{perm:o}}),u.push(l),i=C.getInnerMostAxes(i.length,l.shape.length)),C.assertAxesAreInnerMostDims("argMax",[i[0]],l.shape.length);let p=new $k(l.shape,i[0],"max"),c=[{type:"float32",data:[Number.NEGATIVE_INFINITY]}],d=a.runWebGPUProgram(p,[l],"int32",c);return u.forEach(h=>a.disposeData(h.dataId)),d}var xpe={kernelName:lu,backendName:"webgpu",kernelFunc:ype};function Ape(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s}=n,i=v.parseAxisParam(s,r.shape),o=C.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=sr({inputs:{x:r},backend:a,attrs:{perm:o}}),u.push(l),i=C.getInnerMostAxes(i.length,l.shape.length)),C.assertAxesAreInnerMostDims("argMin",[i[0]],l.shape.length);let p=new $k(l.shape,i[0],"min"),c=[{type:"float32",data:[Number.POSITIVE_INFINITY]}],d=a.runWebGPUProgram(p,[l],"int32",c);return u.forEach(h=>a.disposeData(h.dataId)),d}var bpe={kernelName:uu,backendName:"webgpu",kernelFunc:Ape},vpe=at({opType:le.ASIN}),wpe={kernelName:ci,backendName:"webgpu",kernelFunc:vpe},kpe=at({opType:le.ASINH}),Ipe={kernelName:hi,backendName:"webgpu",kernelFunc:kpe},Spe=at({opType:le.ATAN}),Cpe={kernelName:mi,backendName:"webgpu",kernelFunc:Spe},Tpe=aa({opType:Pe.ATAN2}),Npe={kernelName:gi,backendName:"webgpu",kernelFunc:Tpe},Rpe=at({opType:le.ATANH}),Epe={kernelName:fi,backendName:"webgpu",kernelFunc:Rpe},Mpe=class{constructor(e){this.variableNames=["x"],this.uniforms="strides : vec2<i32>,",this.workgroupSize=[256,1,1],this.size=!0,this.outputShape=e.outShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="poolWithFilterSizeEqualsOne"}getUserCode(){return`
      ${ue("index")} {
        if (index < uniforms.size) {
          let coords = getCoordsFromIndex(index);
          let batch = coords[0];
          let d = coords[3];

          let xRCCorner = coords.yz * uniforms.strides;
          let xRCorner = xRCCorner.x;
          let xCCorner = xRCCorner.y;

          let value = getX(batch, xRCorner, xCCorner, d);
          setOutputAtIndex(index, value);
        }
      }
    `}},sp=class{constructor(e,t,a=!1,n=!1,r=!1){if(this.variableNames=["x"],this.uniforms="strides : vec2<i32>, pads : vec2<i32>, dilations : vec2<i32>, convDims : vec2<i32>, filterDims : vec2<i32>,",this.workgroupSize=[128,1,1],this.size=!0,t==="avg"&&a)throw new Error("Cannot compute positions for average pool.");this.outputShape=e.outShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.poolType=t,this.computePositions=a,this.flattenPositions=n,this.includeBatchIndex=r,this.shaderKey=`pool2D_${t}_${a}_${n}_${r}`}getUserCode(){let e;this.poolType==="avg"?e="resultValue = resultValue + value; count = count + 1.0;":this.computePositions?e=`let currMaxValue = mix(value, maxValue, maxValueFound);
      if (value >= currMaxValue) {
        maxValue = value;
        maxValueFound = 1.0;
        maxPosition = ${this.flattenPositions?this.includeBatchIndex?"((batch * uniforms.xShape[1] + xR) * uniforms.xShape[2] + xC) * uniforms.xShape[3] + d":"(xR * uniforms.xShape[2] + xC) * uniforms.xShape[3] + d":"wR * uniforms.filterDims.y + wC"};
      }`:e="resultValue = max(value, resultValue);";let t="resultValue";return this.poolType==="avg"&&(t="resultValue / max(count, 1.0)"),`
      ${ue("index")} {
      if (index < uniforms.size) {
        let coords = getCoordsFromIndex(index);
          let batch = coords[0];
          let d = coords[3];
          let xRCCorner = vec2<i32>(coords.yz) * uniforms.strides - uniforms.pads;
          let xRCorner = xRCCorner.x;
          let xCCorner = xRCCorner.y;

          ${this.computePositions?`var maxValue = 0.0;
            var maxValueFound = 0.0;
            var maxPosition = 0;`:`var resultValue = ${this.poolType==="avg"?"0.0":"-1.0 / pow(10.0, -20.0)"};`}

          var count = 0.0;
          for (var wR = 0; wR < uniforms.filterDims.x; wR = wR + uniforms.dilations.x) {
            let xR = xRCorner + wR;

            if (xR < 0 || xR >= uniforms.convDims.x) {
              continue;
            }

            for (var wC = 0; wC < uniforms.filterDims.y; wC = wC + uniforms.dilations.y) {
              let xC = xCCorner + wC;
              if (xC < 0 || xC >= uniforms.convDims.y) {
                continue;
              }

              let value = getX(batch, xR, xC, d);
              ${e}
            }
          }

          ${this.computePositions?"setOutputAtIndexI32(index, maxPosition);":`setOutputAtIndex(index, ${t});`}
        }
      }
    `}},Z3=class{constructor(e,t,a=!1,n=!1,r=!1){if(this.variableNames=["x"],this.uniforms="strides : vec3<i32>, pads : vec3<i32>, convDims : vec3<i32>, filterDims : vec3<i32>,",this.workgroupSize=[128,1,1],this.size=!0,t==="avg"&&a)throw new Error("Cannot compute positions for average pool.");this.outputShape=e.outShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.poolType=t,this.computePositions=a,this.flattenPositions=n,this.includeBatchIndex=r,this.shaderKey=`pool3D_${t}_${a}_${n}_${r}`}getUserCode(){let e;this.poolType==="avg"?e="resultValue += value; count += 1.0;":this.computePositions?e=`let currMaxValue = mix(value, maxValue, maxValueFound);
      if (value >= currMaxValue) {
        maxValue = value;
        maxValueFound = 1.0;
        maxPosition = ${this.flattenPositions?this.includeBatchIndex?"(((batch * uniforms.xShape.y + xD) * uniforms.xShape.z + xR) * uniforms.xShape.w + xC) * uniforms.xShape.u + ch":"((xD * uniforms.xShape.z + xR) * uniforms.xShape.w + xC) * uniforms.xShape.u + ch":"wD * uniforms.filterDims.y * uniforms.filterDims.y + wR * uniforms.filterDims.z + wC"};
      }`:e="resultValue = max(value, resultValue);";let t="resultValue";return this.poolType==="avg"&&(t="resultValue / max(count, 1.0)"),`
      ${ue("index")} {
        if (index < uniforms.size) {
          let coords = getCoordsFromIndex(index);
          let batch = coords.x;
          let ch = coords.u;

          let xCorner = vec3<i32>(coords.y, coords.z, coords.w) * uniforms.strides - uniforms.pads;
          let xDCorner = xCorner.x;
          let xRCorner = xCorner.y;
          let xCCorner = xCorner.z;

          ${this.computePositions?`var maxValue = 0.0;
            var maxValueFound = 0.0;
            var maxPosition = 0;`:`var resultValue = ${this.poolType==="avg"?"0.0":"-1.0 / pow(10.0, -20.0)"};`}

          var count = 0.0;
          for (var wD = 0; wD < uniforms.filterDims.x; wD++) {
            let xD = xDCorner + wD;
            if (xD < 0 || xD >= uniforms.convDims.x) {
              continue;
            }

            for (var wR = 0; wR < uniforms.filterDims.y; wR++) {
              let xR = xRCorner + wR;
              if (xR < 0 || xR >= uniforms.convDims.y) {
                continue;
              }

              for (var wC = 0; wC < uniforms.filterDims.z; wC++) {
                let xC = xCCorner + wC;
                if (xC < 0 || xC >= uniforms.convDims.z) {
                  continue;
                }

                let value = getX(batch, xD, xR, xC, ch);
                ${e}
              }
            }
          }

          ${this.computePositions?"setOutputAtIndexI32(index, maxPosition);":`setOutputAtIndex(index, ${t});`}
        }
      }
    `}};function Pk(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{reductionIndices:s,keepDims:i}=n;return dl(r,s,i,"max",a)}var $pe={kernelName:oo,backendName:"webgpu",kernelFunc:Pk};function _k(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{keepDims:s,axis:i}=n;return dl(r,i,s,"mean",a)}var Ppe={kernelName:po,backendName:"webgpu",kernelFunc:_k};function Fk(e,t,a,n){if(t.filterWidth===1&&t.filterHeight===1&&v.arraysEqual(t.inShape,t.outShape))return tn({inputs:{x:e},backend:n});if(t.filterWidth===t.inWidth&&t.filterHeight===t.inHeight&&t.batchSize===1&&t.padInfo.type==="VALID"){let i=e.shape.length,o=ke({inputs:{x:e},backend:n,attrs:{shape:[e.shape[i-3]*e.shape[i-2],e.shape[i-1]]}}),l;a==="avg"?l=_k({inputs:{x:o},backend:n,attrs:{axis:0,keepDims:!1}}):(v.assert(a==="max",()=>`Invalid pool type ${a}`),l=Pk({inputs:{x:o},backend:n,attrs:{reductionIndices:0,keepDims:!1}}));let u=ke({inputs:{x:l},backend:n,attrs:{shape:t.outShape}});return n.disposeData(o.dataId),n.disposeData(l.dataId),u}let r,s=[{type:"int32",data:[t.strideHeight,t.strideWidth]}];return t.filterHeight===1&&t.filterWidth===1?r=new Mpe(t):(a==="avg"?r=new sp(t,"avg"):(v.assert(a==="max",()=>`Invalid pool type ${a}`),r=new sp(t,"max")),s.push({type:"int32",data:[t.padInfo.top,t.padInfo.left]},{type:"int32",data:[t.dilationHeight,t.dilationWidth]},{type:"int32",data:[t.inHeight,t.inWidth]},{type:"int32",data:[t.effectiveFilterHeight,t.effectiveFilterWidth]})),n.runWebGPUProgram(r,[e],e.dtype,s)}function _pe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=n,u=C.computePool2DInfo(r.shape,s,i,1,o,l);return Fk(r,u,"avg",a)}var Fpe={kernelName:yi,backendName:"webgpu",kernelFunc:_pe};function Dpe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dataFormat:l,dimRoundingMode:u}=n,p=[1,1,1],c=C.computePool3DInfo(r.shape,s,i,p,o,u,l),d=new Z3(c,"avg"),h=[{type:"int32",data:[c.strideDepth,c.strideHeight,c.strideWidth]},{type:"int32",data:[c.padInfo.front,c.padInfo.top,c.padInfo.left]},{type:"int32",data:[c.inDepth,c.inHeight,c.inWidth]},{type:"int32",data:[c.effectiveFilterDepth,c.effectiveFilterHeight,c.effectiveFilterWidth]}];return a.runWebGPUProgram(d,[r],r.dtype,h)}var Ope={kernelName:du,backendName:"webgpu",kernelFunc:Dpe},zpe=class{constructor(e){this.variableNames=["dy"],this.uniforms=`strides : vec2<i32>, pads : vec2<i32>, dilations : vec2<i32>, filterDims : vec2<i32>,
       outHeight : i32, outWidth : i32, avgMultiplier : f32,`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.inShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="avgPool2DBackprop"}getUserCode(){return`
      ${ue("index")} {
      if (index < uniforms.size) {
        let coords = getCoordsFromIndex(index);
        let batch = coords[0];
        let d = coords[3];

        let dyRCCorner = vec2<i32>(coords.yz) - uniforms.pads;
        let dyRCorner = dyRCCorner.x;
        let dyCCorner = dyRCCorner.y;

        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).
        // ? = to be determined. : = across all values in that axis.
        var dotProd = 0.0;
        for (var wR = 0; wR < uniforms.filterDims[0]; wR = wR + uniforms.dilations[0]) {
          let dyR = f32(dyRCorner + wR) / f32(uniforms.strides[0]);

          if (dyR < 0.0 || dyR >= f32(uniforms.outHeight) || fract(dyR) > 0.0) {
            continue;
          }
          let idyR = i32(dyR);

          for (var wC = 0; wC < uniforms.filterDims[1]; wC = wC + uniforms.dilations[1]) {
            let dyC = f32(dyCCorner + wC) / f32(uniforms.strides[1]);

            if (dyC < 0.0 || dyC >= f32(uniforms.outWidth) || fract(dyC) > 0.0) {
              continue;
            }
            let idyC = i32(dyC);

            let dyValue = getDy(batch, idyR, idyC, d);

            dotProd = dotProd + dyValue * uniforms.avgMultiplier;
          }
        }
        setOutputAtIndex(index, dotProd);
      }
    }
    `}},Lpe=class{constructor(e){this.variableNames=["dy"],this.uniforms=`strides : vec3<i32>, pads : vec3<i32>, filterDims : vec3<i32>,
       outDepth : i32, outHeight : i32, outWidth : i32, avgMultiplier : f32,`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.inShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="avgPool3DBackprop"}getUserCode(){return`
      ${ue("index")} {
      if (index < uniforms.size) {
        let coords = getCoordsFromIndex(index);
        let batch = coords.x;
        let ch = coords.u;

        let dyCorner = vec3<i32>(coords.y, coords.z, coords.w) - uniforms.pads;
        let dyDCorner = dyCorner.x;
        let dyRCorner = dyCorner.y;
        let dyCCorner = dyCorner.z;

        // Convolve dy(?, ?, ?, d) with pos mask(:, :, :, ch) to get
        // dx(xD, xR, xC, ch).
        // ? = to be determined. : = across all values in that axis.
        var dotProd = 0.0;
        for (var wD = 0; wD < uniforms.filterDims[0]; wD++) {
          let dyD = f32(dyDCorner + wD) / f32(uniforms.strides[0]);

          if (dyD < 0.0 || dyD >= f32(uniforms.outDepth) || fract(dyD) > 0.0) {
            continue;
          }
          let idyD = i32(dyD);

          for (var wR = 0; wR < uniforms.filterDims[1]; wR++) {
            let dyR = f32(dyRCorner + wR) / f32(uniforms.strides[1]);

            if (dyR < 0.0 || dyR >= f32(uniforms.outHeight) || fract(dyR) > 0.0) {
              continue;
            }
            let idyR = i32(dyR);

            for (var wC = 0; wC < uniforms.filterDims[2]; wC++) {
              let dyC = f32(dyCCorner + wC) / f32(uniforms.strides[2]);

              if (dyC < 0.0 || dyC >= f32(uniforms.outWidth) || fract(dyC) > 0.0) {
                continue;
              }
              let idyC = i32(dyC);

              let dyValue = getDy(batch, idyD, idyR, idyC, ch);
              dotProd += dyValue * uniforms.avgMultiplier;
            }
          }
        }
        setOutputAtIndex(index, dotProd);
      }
    }
    `}};function Wpe(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,i=s,{filterSize:o,strides:l,pad:u,dimRoundingMode:p}=n,c=C.computePool3DInfo(i.shape,o,l,1,u,p),d=new Lpe(c),h=1/(c.filterDepth*c.filterHeight*c.filterWidth),m=[{type:"int32",data:[c.strideDepth,c.strideHeight,c.strideWidth]},{type:"int32",data:[c.effectiveFilterDepth-1-c.padInfo.front,c.effectiveFilterHeight-1-c.padInfo.top,c.effectiveFilterWidth-1-c.padInfo.left]},{type:"int32",data:[c.effectiveFilterDepth,c.effectiveFilterHeight,c.effectiveFilterWidth]},{type:"int32",data:[c.outDepth]},{type:"int32",data:[c.outHeight]},{type:"int32",data:[c.outWidth]},{type:"float32",data:[h]}];return a.runWebGPUProgram(d,[r],i.dtype,m)}var Bpe={kernelName:pp,backendName:"webgpu",kernelFunc:Wpe};function Vpe(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,i=s;q3([r,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:u}=n,p=C.computePool2DInfo(i.shape,o,l,1,u),c=new zpe(p),d=1/(p.filterHeight*p.filterWidth),h=[{type:"int32",data:[p.strideHeight,p.strideWidth]},{type:"int32",data:[p.effectiveFilterHeight-1-p.padInfo.top,p.effectiveFilterWidth-1-p.padInfo.left]},{type:"int32",data:[p.dilationHeight,p.dilationWidth]},{type:"int32",data:[p.effectiveFilterHeight,p.effectiveFilterWidth]},{type:"int32",data:[p.outHeight]},{type:"int32",data:[p.outWidth]},{type:"float32",data:[d]}];return a.runWebGPUProgram(c,[r],i.dtype,h)}var Upe={kernelName:dp,backendName:"webgpu",kernelFunc:Vpe};function Gpe(e){let{inputs:t,backend:a,attrs:n}=e,{a:r,b:s}=t,{transposeA:i,transposeB:o}=n;return c0({a:r,b:s,transposeA:i,transposeB:o,backend:a})}var Hpe={kernelName:xi,backendName:"webgpu",kernelFunc:Gpe},jpe=class{constructor(e,t){this.variableNames=["source"],this.workPerThread=1,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.rank=t.length,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1]),this.start=e,this.uniforms=`start : ${Pt(e.length)}, `,this.shaderKey="slice"}getUserCode(){let e=Pt(this.rank),t=qpe(this.rank),a;return this.start.length===1?a=this.outputShape.map((n,r)=>"sourceLoc = uniforms.start + coords;"):a=this.outputShape.map((n,r)=>`sourceLoc.${X1[r]} = uniforms.start.${Cr(r)} + coords.${X1[r]};`),`
      ${ue("index")} {
        if (index < uniforms.size) {
          var sourceLoc : ${e};
          let coords = getCoordsFromIndex(index);
          ${a.join(`
`)}
          setOutputAtIndex(index, getSource(${t}));
        }
      }
    `}},X1=["x","y","z","w","u","v"];function qpe(e){if(e===1)return"sourceLoc";if(e<=6)return X1.slice(0,e).map(t=>`sourceLoc.${t}`).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}function ad(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{begin:s,size:i}=n,[o,l]=Nt.parseSliceParams(r,s,i);if(Nt.assertParamsValid(r,o,l),a.shouldExecuteOnCPU([r])||r.dtype==="string"){let c=a.tensorMap.get(r.dataId),d=Gde(c.values,o,l,r.shape,r.dtype);return a.makeTensorInfo(l,r.dtype,d)}if(v.sizeFromShape(l)===0)return a.makeTensorInfo(l,r.dtype,[]);let u=new jpe(o,l),p=[{type:"int32",data:o}];return a.runWebGPUProgram(u,[r],r.dtype,p)}var Xpe={kernelName:_u,backendName:"webgpu",kernelFunc:ad},Kpe=e=>{let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockShape:s,crops:i}=n;v.assert(r.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGPU backend not implemented yet");let o=s.reduce((x,A)=>x*A),l=C.getReshaped(r.shape,s,o),u=C.getPermuted(l.length,s.length),p=C.getReshapedPermuted(r.shape,s,o),c=C.getSliceBeginCoords(i,s.length),d=C.getSliceSize(p,i,s.length),h=[],m=ke({inputs:{x:r},backend:a,attrs:{shape:l}}),f=sr({inputs:{x:m},backend:a,attrs:{perm:u}}),g=ke({inputs:{x:f},backend:a,attrs:{shape:p}}),y=ad({inputs:{x:g},backend:a,attrs:{begin:c,size:d}});return h.push(m),h.push(f),h.push(g),h.forEach(x=>a.disposeData(x.dataId)),y},Ype={kernelName:pu,backendName:"webgpu",kernelFunc:Kpe},Zpe=`
  fn bincount_write(index: i32, value: f32) {
    ${xs("&result[index]","value","float32")}
  }
`,Jpe=`
  fn bincount_write(index: i32, value: f32) {
    atomicStore(&result[index], bitcast<i32>(value));
  }
`,Dk=class{constructor(e,t,a=!1){this.outputShape=[],this.variableNames=["x"],this.uniforms="binCountSize : i32,",this.workgroupSize=[64,1,1],this.atomic=!0,this.hasWeights=!0,this.binaryOutput=!1,this.outputShape=e,this.rank=e.length,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.binaryOutput=a,a&&(this.atomic=!1),this.hasWeights=t,this.hasWeights&&this.variableNames.push("w"),this.shaderKey=`bincount_${this.hasWeights}_${this.binaryOutput}_${this.rank}`}getUserCode(){return`
    ${this.binaryOutput?Jpe:Zpe}
  ${ue("index")} {
    ${this.rank===1?`if (index < uniforms.xShape) {
      let indexVal = i32(getX(index));
      if (indexVal < uniforms.binCountSize) {
        let value = ${this.binaryOutput?1:this.hasWeights?"getW(index)":"1."};
        bincount_write(indexVal, value);
      }
    }`:`let coord = getCoordsFromIndex(index);
    if (coordsInBounds2D(coord, uniforms.xShape)) {
      let indexVal = i32(getX(coord[0], coord[1]));
      if (indexVal < uniforms.binCountSize) {
        let value = ${this.binaryOutput?1:this.hasWeights?"getW(coord[0], coord[1])":"1."};
        bincount_write(coord.x * uniforms.binCountSize + indexVal, value);
      }
    }`}
  }
  `}};function Qpe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,weights:s}=t,{size:i}=n,o=v.sizeFromShape(r.shape),l=v.sizeFromShape(s.shape)>0,u=[i],p=s.dtype,c=Wa({backend:a,attrs:{shape:u,value:0,dtype:p}}),d=new Dk([o],l),h=[{type:"int32",data:[i]}],m=l?[r,s]:[r];return a.runWebGPUProgram(d,m,p,h,c)}var ece={kernelName:Ai,backendName:"webgpu",kernelFunc:Qpe},tce=class{constructor(e){this.outputShape=[],this.variableNames=["s0","s1"],this.uniforms="s0Size : i32, s1Size : i32, ",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=[e],this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="broadcastArgs"}getUserCode(){return`
  ${ue("index")} {
    if (index < uniforms.size) {
      var s0 = 1.0;
      var s1 = 1.0;
      let indexS0 = index - uniforms.size + uniforms.s0Size;
      let indexS1 = index - uniforms.size + uniforms.s1Size;
      if (indexS0 >= 0) {
        s0 = getS0(indexS0);
      }
      if (indexS1 >= 0) {
        s1 = getS1(indexS1);
      }

      if (s0 == 1.0) {
        setOutputAtIndex(index, s1);
      } else if (s1 == 1.0) {
        setOutputAtIndex(index, s0);
      } else if (s0 != s1) {
        setOutputAtIndex(index, uniforms.NAN);
      } else {
        setOutputAtIndex(index, s0);
      }
    }
  }
  `}};function ace(e){let{inputs:t,backend:a}=e,{s0:n,s1:r}=t;if(a.shouldExecuteOnCPU([n,r])){let p=a.tensorMap.get(n.dataId),c=a.tensorMap.get(r.dataId),d=p.values,h=c.values,m=C.assertAndGetBroadcastShape(Array.from(d),Array.from(h));return a.makeTensorInfo([m.length],"int32",Int32Array.from(m))}let s=v.sizeFromShape(n.shape),i=v.sizeFromShape(r.shape),o=Math.max(s,i),l=new tce(o),u=[{type:"int32",data:[s]},{type:"int32",data:[i]}];return a.runWebGPUProgram(l,[n,r],"int32",u)}var nce={kernelName:hu,backendName:"webgpu",kernelFunc:ace},Ok=aa({opType:Pe.NOT_EQUAL,dtype:"bool",cpuKernelImpl:zde}),rce={kernelName:xo,backendName:"webgpu",kernelFunc:Ok};function tc(e){let{inputs:t,backend:a}=e,{input:n}=t,r=a.tensorMap.get(n.dataId);return tn({inputs:{x:r.complexTensorInfos.real},backend:a})}var sce={kernelName:Ip,backendName:"webgpu",kernelFunc:tc};function ice(e,t){let a=new td(e.shape,le.TO_INT),n=t.runWebGPUProgram(a,[e],"int32");return{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}function K1(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{dtype:s}=n;if(s==="complex64"){if(r.dtype==="complex64")return tn({inputs:{x:r},backend:a});let i=yn(r.shape),o=K1({inputs:{x:r},backend:a,attrs:{dtype:"float32"}}),l=ul({inputs:{real:o,imag:i},backend:a});return i.dispose(),a.disposeData(o.dataId),l}if(r.dtype==="complex64"){let i=tc({inputs:{input:r},backend:a}),o=K1({inputs:{x:i},backend:a,attrs:{dtype:s}});return a.disposeData(i.dataId),o}if(!v.hasEncodingLoss(r.dtype,s)){let i=tn({inputs:{x:r},backend:a});return{dataId:i.dataId,shape:i.shape,dtype:s}}if(a.shouldExecuteOnCPU([r])){let i=a.tensorMap.get(r.dataId).values,[o,l,u]=xde(i,r.shape,r.dtype,s);return a.makeTensorInfo(o,l,u)}if(s==="int32")return ice(r,a);if(s==="bool"){let i=a.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),o=Ok({inputs:{a:r,b:i},backend:a});return a.disposeData(i.dataId),o}throw new Error(`Error in Cast: failed to cast ${r.dtype} to ${s}`)}var oce={kernelName:bi,backendName:"webgpu",kernelFunc:K1},lce=at({opType:le.CEIL,cpuKernelImpl:Ade}),uce={kernelName:vi,backendName:"webgpu",kernelFunc:lce},dce=class{constructor(e){this.variableNames=["A"],this.uniforms="minVal : f32, maxVal : f32,",this.workPerThread=4,this.workgroupSize=[64,1,1],this.outputComponent=4,this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1]),this.shaderKey="clipVec4"}getUserCode(){return`
      ${ue("index")} {
        if(index < uniforms.size) {
          let value = getAByOutputIndex(index);
          var clampedValue = clamp(
              value, vec4<f32>(uniforms.minVal), vec4<f32>(uniforms.maxVal));
          clampedValue = select(clampedValue, value, isnanVec4(value));
          setOutputAtIndex(index, clampedValue);
        }
      }
    `}},pce=class{constructor(e){this.variableNames=["A"],this.uniforms="minVal : f32, maxVal : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="clip"}getUserCode(){return`
      ${ue("index")} {
        if(index < uniforms.size) {
          let value = getAByOutputIndex(index);
          if (isnan(value)) {
            setOutputAtIndex(index, value);
            return;
          }
          setOutputAtIndex(index, clamp(value, uniforms.minVal, uniforms.maxVal));
        }
      }
    `}};function cce(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{clipValueMin:s,clipValueMax:i}=n,o,l=[{type:"float32",data:[s]},{type:"float32",data:[i]}];return v.sizeFromShape(r.shape)%4===0?o=new dce(r.shape):o=new pce(r.shape),a.runWebGPUProgram(o,[r],r.dtype,l)}var hce={kernelName:us,backendName:"webgpu",kernelFunc:cce},mce=class{constructor(e){this.outputShape=[],this.variableNames=["real","imag"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="complexAbs"}getUserCode(){return`
    ${ue("index")} {
      if (index < uniforms.size) {
        let re = abs(getRealByOutputIndex(index));
        let im = abs(getImagByOutputIndex(index));
        let mx = max(re, im);

        // The length function in wgsl may be not underflow-safe on some GPUs.
        // So the safe solution is to ensure underflow-safety in all cases.
        setOutputAtIndex(index, select(mx * length(vec2<f32>(1, min(re, im)/mx)), 0.0, mx == 0.0));
      }
    }
  `}};function oA(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function fce(e){let{inputs:t,backend:a}=e,{x:n}=t,r=a.tensorMap.get(n.dataId),s=new mce(n.shape),i=[oA(n,r.complexTensorInfos.real),oA(n,r.complexTensorInfos.imag)];return a.runWebGPUProgram(s,i,i[0].dtype)}var gce={kernelName:hp,backendName:"webgpu",kernelFunc:fce},yce=class{constructor(e){this.uniforms="",this.workPerThread=1,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=C.computeOutShape(e,1),this.variableNames=e.map((t,a)=>`T${a}`),this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1]),this.offsetLength=e.length-1;for(let t=0;t<this.offsetLength;t++)this.uniforms+=`offset${t} : i32,`;this.shaderKey="concat"}getUserCode(){let e=[];if(this.offsetLength>0){e.push("if (yC < uniforms.offset0){ setOutputAtCoords(coords.x, coords.y, getT0(yR, yC)); }");for(let n=1;n<this.offsetLength;n++)e.push(`else if (yC < uniforms.offset${[n]}){ setOutputAtCoords(coords.x, coords.y, getT${n}(yR, yC - uniforms.offset${n-1})); }`);let t=this.offsetLength,a=this.offsetLength-1;e.push(`else { setOutputAtCoords(coords.x, coords.y, getT${t}(yR, yC - uniforms.offset${a})); }`)}else e.push("setOutputAtCoords(coords.x, coords.y, getT0(yR, yC));");return`
      ${ue("index")} {
        for(var i = 0; i < ${this.workPerThread}; i = i + 1) {
          let flatIndex = index * ${this.workPerThread} + i;
          if(flatIndex < uniforms.size) {
            let coords = getCoordsFromIndex(flatIndex);
            let yR = coords.x;
            let yC = coords.y;

            ${e.join(`
        `)}
          }
        }
      }
    `}};function h0(e){let{inputs:t,backend:a}=e,{input:n}=t,r=a.tensorMap.get(n.dataId);return tn({inputs:{x:r.complexTensorInfos.imag},backend:a})}var xce={kernelName:vp,backendName:"webgpu",kernelFunc:h0};function _d(e,t,a){let n=e[0].dtype;if(n==="complex64"){let m=e.map(A=>tc({inputs:{input:A},backend:a})),f=e.map(A=>h0({inputs:{input:A},backend:a})),g=_d(m,t,a),y=_d(f,t,a),x=ul({inputs:{real:g,imag:y},backend:a});return m.forEach(A=>a.disposeData(A.dataId)),f.forEach(A=>a.disposeData(A.dataId)),a.disposeData(g.dataId),a.disposeData(y.dataId),x}let r=a.shouldExecuteOnCPU(e);if(n==="string"&&(r=!0),r){let m=e.map(w=>{let I=[-1,v.sizeFromShape(w.shape.slice(t))];return ke({inputs:{x:w},backend:a,attrs:{shape:I}})}),f=m.map(w=>({vals:a.readSync(w.dataId),shape:w.shape})),g=C.computeOutShape(m.map(w=>w.shape),1),y=m[0].shape[0]===1,x=bde(f,g,n,y),A=C.computeOutShape(e.map(w=>w.shape),t),b=a.makeTensorInfo(A,n,x);return m.forEach(w=>a.disposeData(w.dataId)),b}let s=a.device.limits.maxStorageBuffersPerShaderStage-1;if(e.length>s){let m=[];for(let g=0;g<e.length;g+=s){let y=e.slice(g,g+s);m.push(_d(y,t,a))}let f=_d(m,t,a);for(let g of m)a.disposeData(g.dataId);return f}let{tensors2D:i,outShape:o}=Ace(e,t,a),l=i.map(m=>m.shape),u=new yce(l),p=[],c=new Array(l.length-1);if(c.length>0){c[0]=l[0][1],p.push({type:"int32",data:[c[0]]});for(let m=1;m<c.length;m++)c[m]=c[m-1]+l[m][1],p.push({type:"int32",data:[c[m]]})}let d=a.runWebGPUProgram(u,i,i[0].dtype,p);i.forEach(m=>a.disposeData(m.dataId));let h=ke({inputs:{x:d},backend:a,attrs:{shape:o}});return a.disposeData(d.dataId),h}function Ace(e,t,a){let n=C.computeOutShape(e.map(r=>r.shape),t);return{tensors2D:e.map(r=>ke({inputs:{x:r},backend:a,attrs:{shape:[v.sizeFromShape(r.shape.slice(0,t)),v.sizeFromShape(r.shape.slice(t))]}})),outShape:n}}function zk(e){let{inputs:t,backend:a,attrs:n}=e,{axis:r}=n,s=v.parseAxisParam(r,t[0].shape)[0],i=t.map(u=>u.shape);C.assertParamsConsistent(i,s);let o=C.computeOutShape(t.map(u=>u.shape),s);if(v.sizeFromShape(o)===0)return a.makeTensorInfo(o,t[0].dtype,[]);let l=t.filter(u=>v.sizeFromShape(u.shape)>0);return l.length===1?tn({inputs:{x:l[0]},backend:a}):_d(l,s,a)}var bce={kernelName:mu,backendName:"webgpu",kernelFunc:zk};function vce(e,t,a,n,r=!1,s=null,i=!1,o=4,l=4,u=4){let p=N=>{switch(N){case 1:return"resData = f32(x[xIndex]);";case 3:return"resData = vec3<f32>(x[xIndex], x[xIndex + 1], x[xIndex + 2]);";case 4:return"resData = vec4<f32>(x[xIndex / 4]);";default:throw new Error(`innerElementSize ${N} is not supported.`)}},c=N=>{switch(N){case 1:return"return f32(W[row * uniforms.wShape[3] + col]);";case 4:return"return vec4<f32>(W[(row * uniforms.wShape[3] + col) / 4]);";default:throw new Error(`innerElementSize ${N} is not supported.`)}},d=e?`
      let coord = vec4<i32>(batch, xRow, xCol, xCh);
      `:`
      let coord = vec4<i32>(batch, xCh, xRow, xCol);
      `,h=e?`
      let coords = vec4<i32>(
        batch,
        row / outWidth,
        row % outWidth,
        col);
      `:`
      let coords = vec4<i32>(
        batch,
        row,
        col / outWidth,
        col % outWidth);
      `,m=e?"uniforms.xShape[1]":"uniforms.xShape[2]",f=e?"uniforms.xShape[2]":"uniforms.xShape[3]",g=e?"row":"col",y=e?"col":"row",x=`
      let inChannels = uniforms.wShape[2];
      let outWidth = ${e?"uniforms.outShape[2]":"uniforms.outShape[3]"};
      let outRow = ${g} / outWidth;
      let outCol = ${g} % outWidth;

      let WRow = ${y} / (uniforms.filterDims[1] * inChannels);
      let WCol = ${y} / inChannels % uniforms.filterDims[1];
      let xRow = outRow * uniforms.strides[0] + uniforms.dilations[0] * WRow - uniforms.pads[0];
      let xCol = outCol * uniforms.strides[1] + uniforms.dilations[1] * WCol - uniforms.pads[1];
      let xCh = ${y} % inChannels;
      var resData = ${Xe(o)}(0.0);
      // The bounds checking is always needed since we use it to pad zero for
      // the 'same' padding type.
      if (xRow >= 0 && xRow < ${m} && xCol >= 0 && xCol < ${f}) {
        ${d}
        let xIndex = getIndexFromCoords4D(coord, uniforms.xShape);
        ${p(o)}
      }
      return resData;`,A=e?t&&n?`
      ${x}`:`
      if (row < uniforms.dimAOuter && col < uniforms.dimInner) {
        ${x}
      }
      return ${Xe(o)}(0.0);`:n&&a?`
      ${x}`:`
      if (row < uniforms.dimInner && col < uniforms.dimBOuter) {
        ${x}
      }
      return ${Xe(o)}(0.0);`,b=`${c(l)}`,w=Xe(u),I=Xe(e?o:l),T=Xe(e?l:o);return`
      ${Pr(s,i,u===4,4)}
      fn mm_readA(batch: i32, row : i32, col : i32) -> ${I} {
        ${e?A:b}
      }

      fn mm_readB(batch: i32, row : i32, col : i32) -> ${T} {
        ${e?b:A}
      }

      fn mm_write(batch: i32, row : i32, col : i32, valueIn : ${w}) {
        if (row < uniforms.dimAOuter && col < uniforms.dimBOuter)
        {
        var value = valueIn;
        let outWidth = ${e?"uniforms.outShape[2]":"uniforms.outShape[3]"};
        ${h}
        ${ll(r,s)}
        setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
        }
      }`}var wce=class{constructor(e,t,a,n,r=!1,s=null,i=!1,o=!1){this.variableNames=["x","W"],this.uniforms="filterDims : vec2<i32>, pads : vec2<i32>, strides : vec2<i32>, dilations : vec2<i32>, dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.outputShape=e.outShape,this.isChannelsLast=e.dataFormat==="channelsLast",this.isVec4=((e.inChannels%4===0||e.inChannels%3===0)&&this.isChannelsLast||e.outWidth%4===0&&!this.isChannelsLast)&&e.outChannels%4===0,this.dispatchLayout=this.isChannelsLast?{x:[3],y:[1,2],z:[0]}:{x:[2,3],y:[1],z:[0]},this.workgroupSize=G3(this.dispatchLayout,this.outputShape,this.isVec4),this.elementsPerThread=H3(this.dispatchLayout,this.outputShape,this.isVec4),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,this.elementsPerThread),this.isVec4?(this.outputComponent=4,this.isChannelsLast&&e.inChannels%4!==0?(this.innerElementSize=3,this.variableComponents=[1,4]):(this.innerElementSize=4,this.variableComponents=[4,4]),r&&(this.variableNames.push("bias"),this.variableComponents.push(4)),i&&(this.variableNames.push("preluActivationWeights"),this.variableComponents.push(4))):(this.innerElementSize=this.elementsPerThread[0],r&&this.variableNames.push("bias"),i&&this.variableNames.push("preluActivationWeights")),this.sequentialAccessByThreads=o,this.addBias=r,this.activation=s,this.hasPreluActivationWeights=i,this.tileAOuter=this.workgroupSize[1]*this.elementsPerThread[1],this.tileBOuter=this.workgroupSize[0]*this.elementsPerThread[0],this.tileInner=Math.max(this.workgroupSize[0]*this.innerElementSize,this.workgroupSize[1]),this.fitAOuter=t%this.tileAOuter===0,this.fitBOuter=a%this.tileBOuter===0,this.fitInner=n%this.tileInner===0,this.shaderKey=`conv2DMM_${this.elementsPerThread}_${this.activation}}_${this.fitAOuter}_${this.fitBOuter}_${this.fitInner}_${this.isVec4}_${this.innerElementSize}_${this.isChannelsLast}_${this.sequentialAccessByThreads}`}getUserCode(){let e=this.isVec4?d0(this.elementsPerThread,this.workgroupSize,!this.isChannelsLast,this.tileInner):p0(this.elementsPerThread,this.workgroupSize,!this.isChannelsLast,this.tileInner,!1,null,this.sequentialAccessByThreads),t=this.isVec4?[this.innerElementSize,4,4]:[1,1,1];return`
    ${vce(this.isChannelsLast,this.fitAOuter,this.fitBOuter,this.fitInner,this.addBias,this.activation,this.hasPreluActivationWeights,t[0],t[1],t[2])}
    ${e}
  `}},kce=class{constructor(e,t=!1,a=null,n=!1){this.variableNames=["x","W"],this.uniforms="filterDims: vec2<i32>, pads: vec2<i32>, strides: vec2<i32>, dilations: vec2<i32>,",this.workgroupSize=[4,4,8],this.outputShape=e.outShape,this.isChannelsLast=e.dataFormat==="channelsLast",this.dispatchLayout=this.isChannelsLast?{x:[2],y:[1],z:[0,3]}:{x:[3],y:[2],z:[0,1]},this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.addBias=t,this.activation=a,this.hasPreluActivationWeights=n,t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),this.shaderKey=`conv2dnaive_${this.activation}_${this.isChannelsLast}`}getUserCode(){return`
       ${Pr(this.activation,this.hasPreluActivationWeights,!1,4)}
       fn readInp(batch : i32, row : i32, col : i32, chan : i32) -> f32{
         let coords = vec4<i32>(batch, row, col, chan);
         if (coordsInBounds4D(coords, uniforms.xShape)) {
           return  getX(batch, row, col, chan);
         } else {
          return 0.0;
         }
       }
       fn readFilt(row : i32, col : i32, xChannel : i32, outChannel : i32) -> f32{
         let coords = vec4<i32>(row, col, xChannel, outChannel);
         if(coordsInBounds4D(coords, uniforms.wShape)) {
           return getW(row, col, xChannel, outChannel);
          } else {
            return 0.0;
          }
       }
       fn writeResult(batch : i32, row : i32, col : i32, chan : i32, valueIn : f32) {
         let coords = ${this.isChannelsLast?"vec4<i32>(batch, row, col, chan);":"vec4<i32>(batch, chan, row, col);"}
         if (coordsInBounds4D(coords, uniforms.outShape)) {
           var value = valueIn;
           ${ll(this.addBias,this.activation)}
           setOutputAtCoords(coords.x, coords.y, coords.z, coords.w, value);
         }
       }
       ${ue("index")} {
         let coords = getOutputCoords();
         let batch = coords[0];
         let outChannel = ${this.isChannelsLast?"coords[3];":"coords[1];"}
         let outRow = ${this.isChannelsLast?"coords[1];":"coords[2];"}
         let outCol = ${this.isChannelsLast?"coords[2];":"coords[3];"}
         var acc : f32 = 0.0;
         for (var row = 0; row < uniforms.filterDims[0]; row = row + 1) {
           for (var col = 0; col < uniforms.filterDims[1]; col = col + 1) {
             let xRow = outRow * uniforms.strides[0] + uniforms.dilations[0] * row - uniforms.pads[0];
             let xCol = outCol * uniforms.strides[1] + uniforms.dilations[1] * col - uniforms.pads[1];
             for (var xChannel = 0; xChannel < ${this.isChannelsLast?"uniforms.xShape[3];":"uniforms.xShape[1];"} xChannel = xChannel + 1) {
               ${this.isChannelsLast?"let v = readInp(batch, xRow, xCol, xChannel);":"let v = readInp(batch, xChannel, xRow, xCol);"}
               let f = readFilt(row, col, xChannel, outChannel);
               acc = acc + v * f;
             }
           }
         }
         writeResult(batch, outRow, outCol, outChannel, acc);
       }
     `}},Ice=class{constructor(e,t){this.variableNames=["x"],this.uniforms=`pads : vec2<i32>, strides : vec2<i32>, dilations : vec2<i32>, outWidth : i32, itemsPerBlockRow : i32,
       inChannels : i32,`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.isChannelsLast=t,this.shaderKey=`im2col_${this.isChannelsLast}`}getUserCode(){let e=this.isChannelsLast?1:2,t=this.isChannelsLast?2:3,a=this.isChannelsLast?"coords[1]":"coords[2]",n=this.isChannelsLast?"coords[2]":"coords[1]",r=this.isChannelsLast?"getX(batch, xRow, xCol, ch)":"getX(batch, ch, xRow, xCol)";return`
    ${ue("index")} {
      let coords = getCoordsFromIndex(index);
      if(index < uniforms.size) {
        let batch = coords[0];
        let row = ${a};
        let col = ${n};
        let offsetY = (row / uniforms.outWidth) * uniforms.strides[0] - uniforms.pads[0];
        let xRow = offsetY + uniforms.dilations[0] * (col / uniforms.itemsPerBlockRow);
        var value = 0.0;
        if(xRow < uniforms.xShape[${e}] && xRow >= 0) {
          let offsetX = (row % uniforms.outWidth) * uniforms.strides[1] -
              uniforms.pads[1];
          let xCol = offsetX + uniforms.dilations[1] * ((col %
              uniforms.itemsPerBlockRow) / uniforms.inChannels);
          let ch = col % uniforms.inChannels;
          if(xCol < uniforms.xShape[${t}] && xCol >= 0) {
            value = ${r};
          }
        }
        setOutputAtIndex(index, value);
      }
    }
   `}};function Nh(e,t){let a=e.length;return a>=3?t?[...e.slice(0,-3),e[a-3]*e[a-2],e[a-1]]:[...e.slice(0,-3),e[a-3],e[a-2]*e[a-1]]:!t&&a===1&&e[0]>1?[e[0],1]:null}function Sce({x:e,filter:t,convInfo:a,backend:n,bias:r=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let l=a.dataFormat==="channelsLast",u=!l,p=!1,c=l&&a.filterHeight===a.inHeight&&a.filterWidth===a.inWidth&&a.padInfo.type==="VALID",d=[],h,m;if(c){let y=a.inHeight*a.inWidth*a.inChannels;h=ke({inputs:{x:e},backend:n,attrs:{shape:[1,a.batchSize,y]}}),m=ke({inputs:{x:t},backend:n,attrs:{shape:[1,y,a.outChannels]}})}else h=ke({inputs:{x:e},backend:n,attrs:{shape:l?[a.batchSize,a.inHeight*a.inWidth,a.inChannels]:[a.batchSize,a.inChannels,a.inHeight*a.inWidth]}}),m=ke({inputs:{x:t},backend:n,attrs:{shape:[1,a.inChannels,a.outChannels]}});if(d.push(h),d.push(m),s!=null){let y=Nh(s.shape,l);y!=null&&(s=ke({inputs:{x:s},backend:n,attrs:{shape:y}}),d.push(s))}if(r!=null){let y=Nh(r.shape,l);y!=null&&(r=ke({inputs:{x:r},backend:n,attrs:{shape:y}}),d.push(r))}let f=c0({a:l?h:m,b:l?m:h,transposeA:u,transposeB:p,backend:n,bias:r,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),g=ke({inputs:{x:f},backend:n,attrs:{shape:a.outShape}});d.push(f);for(let y of d)n.disposeData(y.dataId);return g}function Cce({x:e,filter:t,convInfo:a,backend:n,bias:r=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let{filterWidth:l,filterHeight:u,inChannels:p,strideWidth:c,strideHeight:d,padInfo:h,outWidth:m,outHeight:f,dilationWidth:g,dilationHeight:y,dataFormat:x}=a,A=x==="channelsLast",b=l*u*p,w=f*m,I=A?[a.batchSize,w,b]:[a.batchSize,b,w],T=new Ice(I,A),N=[{type:"int32",data:[h.top,h.left]},{type:"int32",data:[d,c]},{type:"int32",data:[y,g]},{type:"int32",data:[m]},{type:"int32",data:[p*l]},{type:"int32",data:[p]}],M=n.runWebGPUProgram(T,[e],e.dtype,N),$=[];$.push(M);let E=ke({inputs:{x:t},backend:n,attrs:{shape:[1,b,-1]}});if($.push(E),s!=null){let O=Nh(s.shape,A);O!=null&&(s=ke({inputs:{x:s},backend:n,attrs:{shape:O}}),$.push(s))}if(r!=null){let O=Nh(r.shape,A);O!=null&&(r=ke({inputs:{x:r},backend:n,attrs:{shape:O}}),$.push(r))}let S=c0({a:A?M:E,b:A?E:M,transposeA:!A,transposeB:!1,backend:n,bias:r,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),_=ke({inputs:{x:S},backend:n,attrs:{shape:a.outShape}});$.push(S);for(let O of $)n.disposeData(O.dataId);return _}function Lk({x:e,filter:t,convInfo:a,backend:n,bias:r=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let l=r!=null,u=s!=null,p=a.dataFormat==="channelsLast",c=p&&a.filterHeight===a.inHeight&&a.filterWidth===a.inWidth&&a.padInfo.type==="VALID",d=B().getBool("WEBGPU_USE_NAIVE_CONV2D_DEBUG");if(!d&&(c||a.filterHeight===1&&a.filterWidth===1&&a.dilationHeight===1&&a.dilationWidth===1&&a.strideHeight===1&&a.strideWidth===1&&(a.padInfo.type==="SAME"||a.padInfo.type==="VALID")))return Sce({x:e,filter:t,convInfo:a,backend:n,bias:r,activation:o,preluActivationWeights:s,leakyreluAlpha:i});let h=B().getNumber("WEBGPU_THRESHOLD_TO_INCREASE_WORKGROUPS_FOR_MATMUL"),m=h>-1?h:n.thresholdToIncreaseWorkgroups,f=a.batchSize*Math.ceil(a.outHeight*a.outWidth/32)*Math.ceil(a.outChannels/32);if(B().getBool("WEBGPU_CONV_SEPARATE_IM2COL_SHADER")||f<=m)return Cce({x:e,filter:t,convInfo:a,backend:n,bias:r,preluActivationWeights:s,leakyreluAlpha:i,activation:o});let g,y=[a.padInfo.top,a.padInfo.left],x=[{type:"int32",data:[a.filterHeight,a.filterWidth]},{type:"int32",data:[...y]},{type:"int32",data:[a.strideHeight,a.strideWidth]},{type:"int32",data:[a.dilationHeight,a.dilationWidth]}];if(d)g=new kce(a,l,o,u);else{let I=p?a.outHeight*a.outWidth:a.outChannels,T=p?a.outChannels:a.outHeight*a.outWidth,N=a.filterHeight*a.filterWidth*a.inChannels;x.push({type:"int32",data:[I]},{type:"int32",data:[T]},{type:"int32",data:[N]});let M=n.adapterInfo.isIntel();g=new wce(a,I,T,N,l,o,u,M)}let A=[],b=[e,t];l&&(!p&&r.shape.length===1&&(r=ke({inputs:{x:r},backend:n,attrs:{shape:[r.shape[0],1,1]}}),A.push(r)),b.push(r)),u&&(!p&&s.shape.length===1&&(s=ke({inputs:{x:s},backend:n,attrs:{shape:[s.shape[0],1,1]}}),A.push(s)),b.push(s)),o==="leakyrelu"&&(x.push({type:"float32",data:[i]}),g.uniforms+=" alpha : f32,");let w=n.runWebGPUProgram(g,b,e.dtype,x);for(let I of A)n.disposeData(I.dataId);return w}function Tce(e){let{inputs:t,attrs:a,backend:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:u,dimRoundingMode:p}=a,c=C.convertConv2DDataFormat(l),d=C.computeConv2DInfo(r.shape,s.shape,i,u,o,p,!1,c);return Lk({x:r,filter:s,convInfo:d,backend:n})}var Nce={kernelName:wi,backendName:"webgpu",kernelFunc:Tce},Rce=class{constructor(e){this.variableNames=["dy","W"],this.uniforms="filterDims : vec2<i32>, pads : vec2<i32>, strides : vec2<i32>, outBackprop : vec4<i32>,",this.workgroupSize=[64,1,1],this.size=!1,this.isVec4=!1,this.workPerThread=1,this.outputShape=e.inShape,this.isChannelsLast=e.dataFormat==="channelsLast",this.isVec4=this.isChannelsLast&&e.outChannels%4===0&&e.inChannels%4===0,this.isVec4?(this.workPerThread=2,this.outputComponent=4,this.workgroupSize=[4,4,4],this.dispatchLayout={x:[3],y:[2],z:[0,1]},this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,[4,this.workPerThread,1])):(this.size=!0,this.workPerThread=1,this.workgroupSize=[64,1,1],this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize)),this.shaderKey=`conv2DDerInput_${this.isChannelsLast}_${this.isVec4}_${this.workPerThread}`}getUserCode(){let e=this.isChannelsLast?1:2,t=this.isChannelsLast?2:3,a=this.isChannelsLast?3:1,n=`
    ${ue()} {
      let batch = i32(globalId.z) / uniforms.outShape[1];
      let r = i32(globalId.z) % uniforms.outShape[1];
      let c = i32(globalId.y) * ${this.workPerThread};
      let d1 = i32(globalId.x) * 4;

      let dyCorner = vec2<i32>(r, c) - uniforms.pads;

      // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).
      // ? = to be determined. : = across all values in that axis.
      var dotProd: array<vec4<f32>, ${this.workPerThread}>;
      for (var i = 0; i < ${this.workPerThread}; i++) {
        dotProd[i] = vec4<f32>(0.0);
      }
      for (var wR = 0; wR < uniforms.filterDims.x; wR = wR + 1) {
        let dyR = f32(dyCorner.x + wR) / f32(uniforms.strides.x);
        let wRPerm = uniforms.filterDims.x - 1 - wR;
        if (dyR < 0.0 || dyR >= f32(uniforms.outBackprop[1]) ||
            fract(dyR) > 0.0) {
          continue;
        }
        let idyR = i32(dyR);

        for (var wC = 0; wC < uniforms.filterDims.y; wC = wC + 1) {
          let dyC = f32(dyCorner.y + wC) / f32(uniforms.strides.y);
          let dyC2 = f32(dyCorner.y + 1 + wC) / f32(uniforms.strides.y);
          let wCPerm = uniforms.filterDims.y - 1 - wC;
          var bDyCVal = true;
          var bDyCVal2 = true;
          if (dyC < 0.0 || dyC >= f32(uniforms.outBackprop[2]) ||
              fract(dyC) > 0.0) {
            bDyCVal = false;
          }
          if (dyC2 < 0.0 || dyC2 >= f32(uniforms.outBackprop[2]) ||
              fract(dyC2) > 0.0) {
            bDyCVal2 = false;
          }

          let idyC = i32(dyC);
          let idyC2 = i32(dyC2);
          if (bDyCVal && bDyCVal2) {
            let d2Length = uniforms.outBackprop[3];
            for (var d2 = 0; d2 < d2Length; d2 = d2 + 4) {
              let wValue0 = getW(wRPerm, wCPerm, d1, d2);
              let wValue1 = getW(wRPerm, wCPerm, d1 + 1, d2);
              let wValue2 = getW(wRPerm, wCPerm, d1 + 2, d2);
              let wValue3 = getW(wRPerm, wCPerm, d1 + 3, d2);
              var xValue =  getDy(batch, idyR, idyC, d2);
              let tmpval = vec4<f32>(dot(xValue, wValue0),
                                     dot(xValue, wValue1),
                                     dot(xValue, wValue2),
                                     dot(xValue, wValue3));
              dotProd[0] = dotProd[0] + tmpval;
              xValue = getDy(batch, idyR, idyC2, d2);
              dotProd[1] = dotProd[1] + vec4<f32>(dot(xValue, wValue0),
                                                  dot(xValue, wValue1),
                                                  dot(xValue, wValue2),
                                                  dot(xValue, wValue3));
            }
          } else if (bDyCVal) {
            let d2Length = uniforms.outBackprop[3];
            for (var d2 = 0; d2 < d2Length; d2 = d2 + 4) {
              let wValue0 = getW(wRPerm, wCPerm, d1, d2);
              let wValue1 = getW(wRPerm, wCPerm, d1 + 1, d2);
              let wValue2 = getW(wRPerm, wCPerm, d1 + 2, d2);
              let wValue3 = getW(wRPerm, wCPerm, d1 + 3, d2);
              var xValue =  getDy(batch, idyR, idyC, d2);
              let tmpval = vec4<f32>(dot(xValue, wValue0),
                                     dot(xValue, wValue1),
                                     dot(xValue, wValue2),
                                     dot(xValue, wValue3));
              dotProd[0] = dotProd[0] + tmpval;
            }
          } else if (bDyCVal2) {
            let d2Length = uniforms.outBackprop[3];
            for (var d2 = 0; d2 < d2Length; d2 = d2 + 4) {
              let wValue0 = getW(wRPerm, wCPerm, d1, d2);
              let wValue1 = getW(wRPerm, wCPerm, d1 + 1, d2);
              let wValue2 = getW(wRPerm, wCPerm, d1 + 2, d2);
              let wValue3 = getW(wRPerm, wCPerm, d1 + 3, d2);
              var xValue =  getDy(batch, idyR, idyC2, d2);
              let tmpval = vec4<f32>(dot(xValue, wValue0),
                                     dot(xValue, wValue1),
                                     dot(xValue, wValue2),
                                     dot(xValue, wValue3));
              dotProd[1] = dotProd[1] + tmpval;
            }
          }
        }
      }

      for (var i = 0; i < ${this.workPerThread}; i = i + 1) {
        let coords = vec4<i32>(batch, r, c + i, d1);
        if (coordsInBounds4D(coords, uniforms.outShape)) {
          setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], dotProd[i]);
        }
      }
    }
    `;return this.isVec4?`
    ${n}
    `:`
    ${ue("index")} {
      if(index < uniforms.size) {
        let coords = getCoordsFromIndex(index);
        let batch = coords[0];
        let d1 = coords[${a}];

        let dyCorner = vec2<i32>(coords[${e}], coords[${t}]) - uniforms.pads;
        let dyRCorner = dyCorner.x;
        let dyCCorner = dyCorner.y;

        // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).
        // ? = to be determined. : = across all values in that axis.
        var dotProd = 0.0;
        for (var wR = 0; wR < uniforms.filterDims.x; wR = wR + 1) {
          let dyR = (f32(dyRCorner) + f32(wR)) / f32(uniforms.strides.x);
          let wRPerm = uniforms.filterDims.x - 1 - wR;
          if (dyR < 0.0 || dyR >= f32(uniforms.outBackprop[1]) || fract(dyR) > 0.0 ||
              wRPerm < 0) {
            continue;
          }
          let idyR = i32(dyR);

          for (var wC = 0; wC < uniforms.filterDims.y; wC = wC + 1) {
            let dyC = (f32(dyCCorner) + f32(wC)) / f32(uniforms.strides.y);
            let wCPerm = uniforms.filterDims.y - 1 - wC;
            if (dyC < 0.0 || dyC >= f32(uniforms.outBackprop[2]) ||
                fract(dyC) > 0.0 || wCPerm < 0) {
              continue;
            }
            let idyC = i32(dyC);

            for (var d2 = 0; d2 < uniforms.outBackprop[3]; d2 = d2 + 1) {
              let xValue = ${this.isChannelsLast?"getDy(batch, idyR, idyC, d2)":"getDy(batch, d2, idyR, idyC)"};
              let wValue = getW(wRPerm, wCPerm, d1, d2);
              dotProd = dotProd + xValue * wValue;
            }
          }
        }
        setOutputAtIndex(index, dotProd);
      }
    }
  `}},Ece=class{constructor(e){this.variableNames=["x","dy"],this.uniforms="pads : vec2<i32>, strides : vec2<i32>, batchSize : i32, outHeight : i32, outWidth : i32, inHeight : i32, inWidth : i32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.filterShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.isChannelsLast=e.dataFormat==="channelsLast",this.shaderKey=`conv2DDerFilter_${this.isChannelsLast}`}getUserCode(){return`
    ${ue("index")} {
      if(index < uniforms.size) {
        let coords = getCoordsFromIndex(index);
        let wR = coords[0];
        let wC = coords[1];
        let d1 = coords[2];
        let d2 = coords[3];

        // Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2).
        // ? = to be determined. : = across all values in that axis.
        var dotProd = 0.0;
        for (var b = 0; b < uniforms.batchSize; b = b + 1) {
          for (var yR = 0; yR < uniforms.outHeight; yR = yR + 1) {
            let xR = wR + yR * uniforms.strides[0] - uniforms.pads[0];
            if (xR < 0 || xR >= uniforms.inHeight) {
              continue;
            }

            for (var yC = 0; yC < uniforms.outWidth; yC = yC + 1) {
              let xC = wC + yC * uniforms.strides[1] - uniforms.pads[1];

              if (xC < 0 || xC >= uniforms.inWidth) {
                continue;
              }

              if (${this.isChannelsLast}) {
                let dyValue = getDy(b, yR, yC, d2);
                let xValue = getX(b, xR, xC, d1);
                dotProd = dotProd + xValue * dyValue;
              } else {
                let dyValue = getDy(b, d2, yR, yC);
                let xValue = getX(b, d1, xR, xC);
                dotProd = dotProd + xValue * dyValue;
              }
            }
          }
        }
        setOutputAtIndex(index, dotProd);
      }
    }
  `}},Mce=class{constructor(e){this.variableNames=["x","dy"],this.uniforms=`pads : vec3<i32>, strides : vec3<i32>, batchSize : i32, outDepth : i32,
       outHeight : i32, outWidth : i32, inDepth : i32, inHeight : i32, inWidth : i32,`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.filterShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="conv3DDerFilter"}getUserCode(){return`
    ${ue("index")} {
      if(index < uniforms.size) {
        let coords = getCoordsFromIndex(index);
        let wF = coords.x;
        let wR = coords.y;
        let wC = coords.z;
        let d1 = coords.w;
        let d2 = coords.u;

        var dotProd = 0.0;
        for (var b = 0; b < uniforms.batchSize; b++) {
          for (var yF = 0; yF < uniforms.outDepth; yF++) {
            let xF = wF + yF * uniforms.strides[0] - uniforms.pads[0];
            if (xF < 0 || xF >= uniforms.inDepth) {
              continue;
            }

            for (var yR = 0; yR < uniforms.outHeight; yR++) {
              let xR = wR + yR * uniforms.strides[1] - uniforms.pads[1];
              if (xR < 0 || xR >= uniforms.inHeight) {
                continue;
              }

              for (var yC = 0; yC < uniforms.outWidth; yC++) {
                let xC = wC + yC * uniforms.strides[2] - uniforms.pads[2];
                if (xC < 0 || xC >= uniforms.inWidth) {
                  continue;
                }

                let dyValue = getDy(b, yF, yR, yC, d2);
                let xValue = getX(b, xF, xR, xC, d1);
                dotProd += xValue * dyValue;
              }
            }
          }
        }
        setOutputAtIndex(index, dotProd);
      }
    }
  `}},$ce=class{constructor(e){this.variableNames=["dy","W"],this.uniforms=`filterDims : vec3<i32>, pads : vec3<i32>, strides : vec3<i32>,
      outDepth : i32, outHeight : i32, outWidth : i32, outChannels : i32,`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.inShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="conv3DDerInput"}getUserCode(){return`
    ${ue("index")} {
      if(index < uniforms.size) {
        let coords = getCoordsFromIndex(index);
        let batch = coords.x;
        let d1 = coords.u;

        let dyCorner = vec3<i32>(coords.y, coords.z, coords.w) - uniforms.pads;
        let dyFCorner = dyCorner.x;
        let dyRCorner = dyCorner.y;
        let dyCCorner = dyCorner.z;

        var dotProd = 0.0;
        for (var wF = 0; wF < uniforms.filterDims[0]; wF++) {
          let dyF = f32(dyFCorner + wF) / f32(uniforms.strides[0]);
          if (dyF < 0.0 || dyF >= f32(uniforms.outDepth) || fract(dyF) > 0.0) {
            continue;
          }
          let idyF = i32(dyF);

          let wFPerm = uniforms.filterDims[0] - 1 - wF;

          for (var wR = 0; wR < uniforms.filterDims[1]; wR++) {
            let dyR = f32(dyRCorner + wR) / f32(uniforms.strides[1]);

            if (dyR < 0.0 || dyR >= f32(uniforms.outHeight) || fract(dyR) > 0.0) {
              continue;
            }
            let idyR = i32(dyR);

            let wRPerm = uniforms.filterDims[1] - 1 - wR;

            for (var wC = 0; wC < uniforms.filterDims[2]; wC++) {
              let dyC = f32(dyCCorner + wC) / f32(uniforms.strides[2]);

              if (dyC < 0.0 || dyC >= f32(uniforms.outWidth) || fract(dyC) > 0.0) {
                continue;
              }
              let idyC = i32(dyC);

              let wCPerm = uniforms.filterDims[2] - 1 - wC;

              for (var d2 = 0; d2 < uniforms.outChannels; d2++) {
                let xValue = getDy(batch, idyF, idyR, idyC, d2);
                let wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);
                dotProd += xValue * wValue;
              }
            }
          }
        }
        setOutputAtIndex(index, dotProd);
      }
    }
  `}};function Pce(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:u,filterShape:p}=n,c=C.convertConv2DDataFormat(l),d=C.computeConv2DInfo(r.shape,p,i,1,o,u,!1,c),h=new Ece(d),m=[{type:"int32",data:[d.padInfo.top,d.padInfo.left]},{type:"int32",data:[d.strideHeight,d.strideWidth]},{type:"int32",data:[d.batchSize]},{type:"int32",data:[d.outHeight]},{type:"int32",data:[d.outWidth]},{type:"int32",data:[d.inHeight]},{type:"int32",data:[d.inWidth]}];return a.runWebGPUProgram(h,[r,s],r.dtype,m)}var _ce={kernelName:mp,backendName:"webgpu",kernelFunc:Pce};function Fce(e=4){let t=n=>{switch(n){case 1:return"return W[getIndexFromCoords4D(coord, uniforms.wShape)];";case 4:return`
            let coord1 = vec4<i32>(coordX, coordY, col + 1, rowInner);
            let coord2 = vec4<i32>(coordX, coordY, col + 2, rowInner);
            let coord3 = vec4<i32>(coordX, coordY, col + 3, rowInner);
            let v0 = W[getIndexFromCoords4D(coord, uniforms.wShape)];
            let v1 = W[getIndexFromCoords4D(coord1, uniforms.wShape)];
            let v2 = W[getIndexFromCoords4D(coord2, uniforms.wShape)];
            let v3 = W[getIndexFromCoords4D(coord3, uniforms.wShape)];
            return vec4<f32>(v0, v1, v2, v3);
            `;default:throw new Error(`innerElementSize ${n} is not supported.`)}},a=`if (row < uniforms.dimAOuter && col < uniforms.dimInner) {
        ${`
      let outRow = row / uniforms.outShape[2];
      let outCol = row % uniforms.outShape[2];

      let WRow = col / (uniforms.filterDims[1] * uniforms.outBackprop[3]);
      let WCol = col / uniforms.outBackprop[3] % uniforms.filterDims[1];
      let xR = f32(outRow - uniforms.pads[0] + WRow) / f32(uniforms.strides[0]);
      let xC = f32(outCol - uniforms.pads[1] + WCol) / f32(uniforms.strides[1]);
      if (xR < 0.0 || xR >= f32(uniforms.outBackprop[1]) || fract(xR) > 0.0) {
        return ${Xe(e)}(0.0);
      }
      if (xC < 0.0 || xC >= f32(uniforms.outBackprop[2]) || fract(xC) > 0.0) {
        return ${Xe(e)}(0.0);
      }
      let coord = vec4<i32>(
          batch,
          i32(xR),
          i32(xC),
          col % uniforms.outBackprop[3]);
      return x[getIndexFromCoords4D(coord, uniforms.xShape)/${e}];`}
      }
      return ${Xe(e)}(0.0);`;return`
  fn mm_readA(batch: i32, row : i32, col : i32) -> ${Xe(e)} {
    ${a}
  }

  fn mm_readB(batch: i32, row : i32, col : i32) -> ${Xe(e)} {
    let coordX = uniforms.filterDims.x - 1 -
        row / (uniforms.filterDims[1] * uniforms.outBackprop[3]);
    let coordY = uniforms.filterDims.y - 1 -
        (row / uniforms.outBackprop[3]) % uniforms.filterDims[1];
    if (row < uniforms.dimInner && col < uniforms.dimBOuter &&
        coordX >= 0 && coordY >= 0) {
      let rowInner = row % uniforms.outBackprop[3];
      let coord = vec4<i32>(coordX, coordY, col, rowInner);
      ${t(e)}
    }
    return ${Xe(e)}(0.0);
  }

  fn mm_write(batch: i32, row : i32, col : i32, valueInput : ${Xe(e)}) {
    if (row < uniforms.dimAOuter && col < uniforms.dimBOuter) {
      var value = valueInput;
      let outCoord = vec4<i32>(
          batch,
          row / uniforms.outShape[2],
          row % uniforms.outShape[2],
          col);
      result[getIndexFromCoords4D(outCoord, uniforms.outShape)/${e}] = value;
    }
  }`}var Dce=class{constructor(e){this.variableNames=["x","W"],this.uniforms="filterDims : vec2<i32>, pads : vec2<i32>, strides : vec2<i32>, outBackprop : vec4<i32>, dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.outputShape=e.inShape,v.assert(e.dataFormat==="channelsLast",()=>"TODO: NCHW is unimplemented"),this.isVec4=e.inChannels%4===0&&e.outChannels%4===0,this.dispatchLayout={x:[3],y:[1,2],z:[0]},this.workgroupSize=G3(this.dispatchLayout,this.outputShape,this.isVec4),this.elementsPerThread=H3(this.dispatchLayout,this.outputShape,this.isVec4),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,this.elementsPerThread),this.isVec4&&(this.outputComponent=4,this.variableComponents=[4,1]),this.shaderKey=`conv2DDerInputMM_${this.isVec4}_${this.elementsPerThread}`}getUserCode(){let e=this.isVec4?d0(this.elementsPerThread,this.workgroupSize):p0(this.elementsPerThread,this.workgroupSize);return`
    ${Fce(this.isVec4?4:1)}
    ${e}
    `}};function Oce(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:u,dimRoundingMode:p}=n,c=C.convertConv2DDataFormat(u),d=C.computeConv2DInfo(i,s.shape,o,1,l,p,!1,c),h=[{type:"int32",data:[d.filterHeight,d.filterWidth]},{type:"int32",data:[d.filterHeight-1-d.padInfo.top,d.filterWidth-1-d.padInfo.left]},{type:"int32",data:[d.strideHeight,d.strideWidth]},{type:"int32",data:[d.batchSize,d.outHeight,d.outWidth,d.outChannels]}],m;if(B().getBool("WEBGPU_USE_NAIVE_CONV2D_TRANSPOSE")||d.dataFormat!=="channelsLast")m=new Rce(d);else{m=new Dce(d);let f=d.inHeight*d.inWidth,g=d.inChannels,y=d.filterHeight*d.filterWidth*d.outChannels;h.push({type:"uint32",data:[f]},{type:"uint32",data:[g]},{type:"uint32",data:[y]})}return a.runWebGPUProgram(m,[r,s],"float32",h)}var zce={kernelName:ki,backendName:"webgpu",kernelFunc:Oce},Lce=class{constructor(e){this.variableNames=["x","W"],this.uniforms="filterDims: vec3<i32>, pads: vec3<i32>, strides: vec3<i32>, dilations: vec3<i32>,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.outShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="conv3dnaive"}getUserCode(){return`
    ${ue("index")} {
      if (index < uniforms.size) {
        let coords = getOutputCoords();
        let batch = coords.x;
        let d2 = coords.u;

        let xFRCCorner = vec3<i32>(coords.y, coords.z, coords.w) * uniforms.strides - uniforms.pads;
        let xFCorner = xFRCCorner.x;
        let xRCorner = xFRCCorner.y;
        let xCCorner = xFRCCorner.z;

        let inputDepthNearestVec4 = (uniforms.xShape.u / 4) * 4;
        let inputDepthVec4Remainder = uniforms.xShape.u % 4;

        var dotProd = 0.0;
        for (var wF = 0; wF < uniforms.filterDims[0]; wF++) {
          let xF = xFCorner + wF * uniforms.dilations[0];
          if (xF < 0 || xF >= uniforms.xShape.y) {
            continue;
          }

          for (var wR = 0; wR < uniforms.filterDims[1]; wR++) {
            let xR = xRCorner + wR * uniforms.dilations[1];
            if (xR < 0 || xR >= uniforms.xShape.z) {
              continue;
            }

            for (var wC = 0; wC < uniforms.filterDims[2]; wC++) {
              let xC = xCCorner + wC * uniforms.dilations[2];
              if (xC < 0 || xC >= uniforms.xShape.w) {
                continue;
              }

              for (var d1 = 0; d1 < inputDepthNearestVec4; d1 += 4) {
                let xValues = vec4<f32>(
                  getX(batch, xF, xR, xC, d1),
                  getX(batch, xF, xR, xC, d1 + 1),
                  getX(batch, xF, xR, xC, d1 + 2),
                  getX(batch, xF, xR, xC, d1 + 3)
                );
                let wValues = vec4<f32>(
                  getW(wF, wR, wC, d1, d2),
                  getW(wF, wR, wC, d1 + 1, d2),
                  getW(wF, wR, wC, d1 + 2, d2),
                  getW(wF, wR, wC, d1 + 3, d2)
                );

                dotProd += dot(xValues, wValues);
              }

              if (inputDepthVec4Remainder == 1) {
                dotProd += getX(batch, xF, xR, xC, inputDepthNearestVec4) *
                  getW(wF, wR, wC, inputDepthNearestVec4, d2);
              } else if (inputDepthVec4Remainder == 2) {
                let xValues = vec2<f32>(
                  getX(batch, xF, xR, xC, inputDepthNearestVec4),
                  getX(batch, xF, xR, xC, inputDepthNearestVec4 + 1)
                );
                let wValues = vec2<f32>(
                  getW(wF, wR, wC, inputDepthNearestVec4, d2),
                  getW(wF, wR, wC, inputDepthNearestVec4 + 1, d2)
                );
                dotProd += dot(xValues, wValues);
              } else if (inputDepthVec4Remainder == 3) {
                let xValues = vec3<f32>(
                  getX(batch, xF, xR, xC, inputDepthNearestVec4),
                  getX(batch, xF, xR, xC, inputDepthNearestVec4 + 1),
                  getX(batch, xF, xR, xC, inputDepthNearestVec4 + 2)
                );
                let wValues = vec3<f32>(
                  getW(wF, wR, wC, inputDepthNearestVec4, d2),
                  getW(wF, wR, wC, inputDepthNearestVec4 + 1, d2),
                  getW(wF, wR, wC, inputDepthNearestVec4 + 2, d2)
                );
                dotProd += dot(xValues, wValues);
              }
            }
          }
        }
        setOutputAtIndex(index, dotProd);
      }
    }`}};function Wce(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=n,u=C.computeConv3DInfo(r.shape,s.shape,i,l,o),p=[u.padInfo.front,u.padInfo.top,u.padInfo.left],c=[{type:"int32",data:[u.filterDepth,u.filterHeight,u.filterWidth]},{type:"int32",data:[...p]},{type:"int32",data:[u.strideDepth,u.strideHeight,u.strideWidth]},{type:"int32",data:[u.dilationDepth,u.dilationHeight,u.dilationWidth]}],d=new Lce(u),h=ca(r.dtype,s.dtype);return a.runWebGPUProgram(d,[r,s],h,c)}var Bce={kernelName:Ii,backendName:"webgpu",kernelFunc:Wce};function Vce(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,dy:s}=t,{strides:i,pad:o,filterShape:l}=n,u=C.computeConv3DInfo(r.shape,l,i,1,o),p=new Mce(u),c=[{type:"int32",data:[u.padInfo.front,u.padInfo.top,u.padInfo.left]},{type:"int32",data:[u.strideDepth,u.strideHeight,u.strideWidth]},{type:"int32",data:[u.batchSize]},{type:"int32",data:[u.outDepth]},{type:"int32",data:[u.outHeight]},{type:"int32",data:[u.outWidth]},{type:"int32",data:[u.inDepth]},{type:"int32",data:[u.inHeight]},{type:"int32",data:[u.inWidth]}];return a.runWebGPUProgram(p,[r,s],s.dtype,c)}var Uce={kernelName:fu,backendName:"webgpu",kernelFunc:Vce};function Gce(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,filter:s}=t,{strides:i,pad:o,inputShape:l}=n,u=C.computeConv3DInfo(l,s.shape,i,1,o),p=new $ce(u),c=[{type:"int32",data:[u.filterDepth,u.filterHeight,u.filterWidth]},{type:"int32",data:[u.filterDepth-1-u.padInfo.front,u.filterHeight-1-u.padInfo.top,u.filterWidth-1-u.padInfo.left]},{type:"int32",data:[u.strideDepth,u.strideHeight,u.strideWidth]},{type:"int32",data:[u.outDepth]},{type:"int32",data:[u.outHeight]},{type:"int32",data:[u.outWidth]},{type:"int32",data:[u.outChannels]}];return a.runWebGPUProgram(p,[r,s],r.dtype,c)}var Hce={kernelName:Si,backendName:"webgpu",kernelFunc:Gce},jce=at({opType:le.COS}),qce={kernelName:Ci,backendName:"webgpu",kernelFunc:jce},Xce=at({opType:le.COSH}),Kce={kernelName:Ti,backendName:"webgpu",kernelFunc:Xce},Yce=class{constructor(e,t,a,n){this.variableNames=["Image","Boxes","BoxInd"],this.uniforms="extrapolationValue : f32,",this.workgroupSize=[64,1,1],this.size=!0;let[r]=t;this.outputShape=[r,a[0],a[1],e],this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.methodId=n==="bilinear"?1:0,this.cropHeightBiggerThan1=this.outputShape[1]>1,this.cropWidthBiggerThan1=this.outputShape[2]>1,this.shaderKey=`cropAndResize_${this.methodId}_${this.cropHeightBiggerThan1}_${this.cropWidthBiggerThan1}`}getUserCode(){let[e,t]=["f32(uniforms.imageShape[1] - 1)","f32(uniforms.imageShape[2] - 1)"],[a,n,r]=this.cropHeightBiggerThan1?[`(${e} / f32(uniforms.outShape[1] - 1))`,"(y2-y1) * height_ratio",`y1*${e} + f32(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${e}`],[s,i,o]=this.cropWidthBiggerThan1?[`(${t} / f32(uniforms.outShape[2] - 1))`,"(x2-x1) * width_ratio",`x1*${t} + f32(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${t}`];return`
    ${ue("index")} {
      if (index < uniforms.size) {
        let coords = getCoordsFromIndex(index);
        let height_ratio = f32(${a});
        let width_ratio = f32(${s});
        let b = coords[0];
        let y = coords[1];
        let x = coords[2];
        let d = coords[3];
        // get box vals
        let y1 = getBoxes(b, 0);
        let x1 = getBoxes(b, 1);
        let y2 = getBoxes(b, 2);
        let x2 = getBoxes(b, 3);
        // get image in batch index
        let bInd = i32(round(getBoxInd(b)));
        if(bInd < 0 || bInd >= uniforms.outShape[0]) {
          return;
        }
        let height_scale = ${n};
        let width_scale = ${i};
        let in_y = ${r};
        if( in_y < 0.0 || in_y > ${e} ) {
          setOutputAtIndex(index, uniforms.extrapolationValue);
          return;
        }
        let in_x = ${o};
        if( in_x < 0.0 || in_x > ${t} ) {
          setOutputAtIndex(index, uniforms.extrapolationValue);
          return;
        }
        let sourceFracIndexCR = vec2<f32>(in_x,in_y);
        if(${this.methodId} == 1) {
          // Compute the four integer indices.
          let sourceFloorCR = vec2<i32>(sourceFracIndexCR);
          let sourceCeilCR = vec2<i32>(ceil(sourceFracIndexCR));
          let topLeft = getImage(bInd, sourceFloorCR.y, sourceFloorCR.x, d);
          let bottomLeft = getImage(bInd, sourceCeilCR.y, sourceFloorCR.x, d);
          let topRight = getImage(bInd, sourceFloorCR.y, sourceCeilCR.x, d);
          let bottomRight = getImage(bInd, sourceCeilCR.y, sourceCeilCR.x, d);
          let fracCR = sourceFracIndexCR - vec2<f32>(sourceFloorCR);
          let top = topLeft + (topRight - topLeft) * fracCR.x;
          let bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;
          let newValue = top + (bottom - top) * fracCR.y;
          setOutputAtIndex(index, newValue);
        } else {
          // Compute the coordinators of nearest neighbor point.
          let sourceNearestCR = vec2<i32>(floor(
            sourceFracIndexCR + vec2<f32>(0.5,0.5)));
          let newValue = getImage(
            bInd, sourceNearestCR.y, sourceNearestCR.x, d);
          setOutputAtIndex(index, newValue);
        }
      }
    }
    `}},Zce=e=>{let{inputs:t,backend:a,attrs:n}=e,{image:r,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:u}=n,p=new Yce(r.shape[3],s.shape,o,l),c=[{type:"float32",data:[u]}];return a.runWebGPUProgram(p,[r,s,i],"float32",c)},Jce={kernelName:Ei,backendName:"webgpu",kernelFunc:Zce},ip;(function(e){e.Prod="*",e.Sum="+"})(ip||(ip={}));var lA=class{constructor(e,t,a,n){this.variableNames=["x"],this.uniforms="index : f32,",this.size=!0,this.workgroupSize=[128,1,1],this.outputShape=t,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.exclusive=a,this.reverse=n,this.op=e,this.shaderKey=`cum_${this.op}_${this.exclusive}_${this.reverse}`}getUserCode(){let e=this.outputShape.length,t=this.op===ip.Prod?"1.0":"0.0",a=this.exclusive?t:`getX(${uA(e,"coords",this.op)})`,n=this.outputShape[this.outputShape.length-1],r="",s="";return this.exclusive?(r=this.reverse?`end != ${n-1}`:"end != 0",s=this.reverse?"end + 1":"end - 1"):(r=this.reverse?`end + pow2 < ${n}`:"end >= pow2",s=this.reverse?"end + pow2":"end - pow2"),`
      ${ue("index")} {
       if (index < uniforms.size) {
         var coords = getCoordsFromIndex(index);

         let end = ${dA(e,"coords",this.op)};
         var val = ${a};
         let pow2 = i32(pow(2.0, uniforms.index));
         if (${r}) {
           let idx = ${s};
           ${dA(e,"coords",this.op)} = idx;
           val ${this.op}= getX(${uA(e,"coords",this.op)});
         }
         setOutputAtIndex(index, val);
       }
      }
    `}};function uA(e,t,a){if(e===1)return`${t}`;if(e===2)return`${t}.x, ${t}.y`;if(e===3)return`${t}.x, ${t}.y, ${t}.z`;if(e===4)return`${t}.x, ${t}.y, ${t}.z, ${t}.w`;throw Error(`Cumulative ${a} for rank ${e} is not yet supported`)}function dA(e,t,a){if(e===1)return`${t}`;if(e===2)return`${t}.y`;if(e===3)return`${t}.z`;if(e===4)return`${t}.w`;throw Error(`Cumulative ${a} for rank ${e} is not yet supported`)}function Wk(e,t,a,n,r,s){let i=t.shape.length,o=C.getAxesPermutation([n],i),l=t;o!=null&&(l=sr({inputs:{x:t},backend:a,attrs:{perm:o}}));let u=C.getInnerMostAxes(1,i)[0];if(u!==i-1)throw new Error(`WebGPU cumprod shader expects an inner-most axis=${t.shape.length-1} but got axis=${n}`);let p=l.shape[u],c=tn({inputs:{x:l},backend:a});for(let d=0;d<=Math.ceil(Math.log2(p))-1;d++){let h=new lA(e,l.shape,!1,s),m=c,f=[{type:"float32",data:[d]}];c=a.runWebGPUProgram(h,[c],c.dtype,f),a.disposeData(m.dataId)}if(r){let d=new lA(e,l.shape,r,s),h=c,m=[{type:"float32",data:[0]}];c=a.runWebGPUProgram(d,[c],c.dtype,m),a.disposeData(h.dataId)}if(o!=null){let d=C.getUndoAxesPermutation(o),h=sr({inputs:{x:c},backend:a,attrs:{perm:d}});return a.disposeData(c.dataId),a.disposeData(l.dataId),h}return c}function Qce(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=n;return Wk(ip.Prod,r,a,s,i,o)}var ehe={kernelName:Ni,backendName:"webgpu",kernelFunc:Qce};function the(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=n;return Wk(ip.Sum,r,a,s,i,o)}var ahe={kernelName:Ri,backendName:"webgpu",kernelFunc:the};function nhe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,weights:s}=t,{size:i,binaryOutput:o}=n,l=r.shape.length===1,u=v.sizeFromShape(s.shape)>0,p=s.dtype,c=l?[r.shape[0]]:[r.shape[0],r.shape[1]],d=l?[i]:[r.shape[0],i],h=Wa({backend:a,attrs:{shape:d,value:0,dtype:p}}),m=new Dk(c,u,o),f=[{type:"int32",data:[i]}],g=u?[r,s]:[r];return a.runWebGPUProgram(m,g,p,f,h)}var rhe={kernelName:gu,backendName:"webgpu",kernelFunc:nhe},she=class{constructor(e,t){this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.uniforms="blockSize : i32,",this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey=`depthToSpace_${t}`,this.dataFormat=t}getUserCode(){return`
      ${ue("index")} {
        if (index < uniforms.size) {
          let coords = getCoordsFromIndex(index);
          let b = coords[0];
          let h = ${this.getHeightCoordString()};
          let w = ${this.getWidthCoordString()};
          let d = ${this.getDepthCoordString()};

          let in_h = h / uniforms.blockSize;
          let offset_h = h % uniforms.blockSize;
          let in_w = w / uniforms.blockSize;
          let offset_w = w % uniforms.blockSize;
          let offset_d = (offset_h * uniforms.blockSize + offset_w) *
            ${this.getOutputDepthSize()};
          let in_d = d + offset_d;

          let rlt = ${this.getInputSamplingString()};
          setOutputAtIndex(index, rlt);
        }
      }`}getHeightCoordString(){return this.dataFormat==="NHWC"?"coords[1]":"coords[2]"}getWidthCoordString(){return this.dataFormat==="NHWC"?"coords[2]":"coords[3]"}getDepthCoordString(){return this.dataFormat==="NHWC"?"coords[3]":"coords[1]"}getOutputDepthSize(){return this.dataFormat==="NHWC"?"uniforms.outShape[3]":"uniforms.outShape[1]"}getInputSamplingString(){return this.dataFormat==="NHWC"?"getX(b, in_h, in_w, in_d)":"getX(b, in_d, in_h, in_w)"}};function ihe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockSize:s,dataFormat:i}=n,o=r.shape[0],l=i==="NHWC"?r.shape[1]:r.shape[2],u=i==="NHWC"?r.shape[2]:r.shape[3],p=i==="NHWC"?r.shape[3]:r.shape[1],c=l*s,d=u*s,h=p/(s*s),m=i==="NHWC"?[o,c,d,h]:[o,h,c,d],f=[{type:"int32",data:[s]}],g=new she(m,i);return a.runWebGPUProgram(g,[r],r.dtype,f)}var ohe={kernelName:Mi,backendName:"webgpu",kernelFunc:ihe},lhe=class{constructor(e,t,a,n=!1,r=null,s=!1){this.variableNames=["x","W"],this.uniforms="pads : vec2<i32>, inDims : vec2<i32>,",this.workgroupSize=[16,16,1],this.outputShape=e,this.dispatchLayout={x:[3],y:[2],z:[0,1]},this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),n&&this.variableNames.push("bias"),s&&this.variableNames.push("preluActivationWeights"),this.addBias=n,this.activation=r,this.hasPreluActivation=s,this.filterHeight=t,this.filterWidth=a,this.shaderKey=`depthwiseNCHW_${this.activation}_${this.filterHeight}_${this.filterWidth}`}getUserCode(){let e=this.filterWidth*this.filterHeight,t=this.workgroupSize[0]*this.workgroupSize[1]*this.workgroupSize[2],a=this.workgroupSize[1]+this.filterHeight-1,n=this.workgroupSize[0]+this.filterWidth-1;return`
      ${Pr(this.activation,this.hasPreluActivation,!1,4)}

      var<workgroup> mm_Asub : array<array<f32, ${n}>, ${a}>;
      var<workgroup> mm_Bsub : array<array<f32, ${this.filterWidth}>, ${this.filterHeight}>;
      fn readX(batch : i32, channel : i32, row : i32, col : i32) -> f32 {
        var value = 0.0;
        if (row >=0 && row < uniforms.inDims[0] && col >=0 && col < uniforms.inDims[1])
        {
          value = getX(batch, channel, row, col);
        }
        return value;
      }

      ${ue()} {
        let coords = getOutputCoords();
        let batch = coords[0];
        let xRCCorner = vec2<i32>(coords.zw) - uniforms.pads;
        let channelMul = uniforms.wShape[3];
        let d1 = coords[1] / channelMul;
        let q = coords[1] % channelMul;

        let inputRowStart = xRCCorner.x;
        let inputColStart = xRCCorner.y;

        let localRow = i32(localId.y);
        let localCol = i32(localId.x);

        // Load one tile of X into local memory.
        for (var inputRow = localRow; inputRow < ${a}; inputRow = inputRow + ${this.workgroupSize[1]}) {
          for (var inputCol = localCol; inputCol < ${n}; inputCol = inputCol + ${this.workgroupSize[0]}) {
            let rowOffset = inputRow - localRow;
            let colOffset = inputCol - localCol;
            mm_Asub[inputRow][inputCol] = readX(batch, d1, inputRowStart + rowOffset, inputColStart + colOffset);
          }
        }

        // Load one tile of W into local memory.
        var wIndex = i32(localIndex);
        ${e<t?`if (wIndex < ${e})`:`for(; wIndex < ${e}; wIndex = wIndex + ${t})`}

        {
          let wRow = wIndex / ${this.filterWidth};
          let wCol = wIndex % ${this.filterWidth};
          mm_Bsub[wRow][wCol] = getW(wRow, wCol, d1, q);
        }

        workgroupBarrier();

        var value = 0.0;
        for (var wR = 0; wR < ${this.filterHeight}; wR = wR + 1) {
          for (var wC = 0; wC < ${this.filterWidth}; wC = wC + 1) {
            let xVal = mm_Asub[localRow + wR][localCol + wC];
            let wVal = mm_Bsub[wR][wC];
            value = fma(xVal, wVal, value);
          }
        }
        ${ll(this.addBias,this.activation)}
        if (coordsInBounds4D(coords, uniforms.outShape)) {
          setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
        }
      }
    `}},Bk=class{constructor(e,t=!1,a=null,n=!1){this.variableNames=["x","W"],this.uniforms="pads : vec2<i32>, inDims : vec2<i32>, virtualWidth : i32,",this.workgroupSize=[64,1,1],this.workPerThread=4,this.outputComponent=4,this.outputShape=e.outShape,this.virtualWidth=Math.ceil(this.outputShape[2]/this.workPerThread)*this.workPerThread;let r=[this.outputShape[0],this.outputShape[1],this.virtualWidth,this.outputShape[3]];this.dispatchLayout=me(r),this.dispatch=de(this.dispatchLayout,r,this.workgroupSize,[this.outputComponent*this.workPerThread,1,1]),v.assert(e.dataFormat==="channelsLast",()=>"TODO: NCHW is unimplemented"),t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),this.convInfo=e,this.addBias=t,this.activation=a,this.hasPreluActivation=n,this.shaderKey=`depthwiseVec4_${a}_${this.convInfo.filterHeight}_${this.convInfo.filterWidth}_${this.convInfo.strideHeight}_${this.convInfo.strideWidth}_${this.workPerThread}`}getUserCode(){let e=(this.workPerThread-1)*this.convInfo.strideWidth+this.convInfo.filterWidth,t=this.convInfo.strideHeight,a=this.convInfo.strideWidth;return`
      ${Pr(this.activation,this.hasPreluActivation,!0,4)}
      fn readX(batch : i32, row : i32, col : i32, channel : i32) -> vec4<f32> {
        var value = vec4<f32>(0.0);
        if (col >=0 && col < uniforms.inDims[1]) {
          value = getX(batch, row, col, channel);
        }
        return value;
      }

      ${ue("index")} {
        let width0 = uniforms.outShape[3] / ${this.outputComponent};
        let d1 = (index % width0) * ${this.outputComponent};
        var index1 = index / width0;
        let width1 = uniforms.virtualWidth / ${this.workPerThread};
        let c = (index1 % width1) * ${this.workPerThread};
        index1 = index1 / width1;
        let r = index1 % uniforms.outShape[1];
        let batch = index1 / uniforms.outShape[1];

        let xRCCorner = vec2<i32>(r, c) * vec2<i32>(${t}, ${a}) - uniforms.pads;

        let xRCorner = xRCCorner.x;
        let xCCorner = xRCCorner.y;
        var xVals : array<vec4<f32>, ${e}>;
        var dotProd : array<vec4<f32>, ${this.workPerThread}>;
        for (var i = 0; i < ${this.workPerThread}; i++) {
          dotProd[i] = vec4<f32>(0.0);
        }

        // Use constant instead of uniform can give better performance.
        for (var wR = 0; wR < ${this.convInfo.filterHeight}; wR = wR + 1) {
          let xR = xRCorner + wR;
          if (xR >=0 && xR < uniforms.inDims[0]) {
            for (var i = 0; i < ${e}; i++) {
              xVals[i] = readX(batch, xR, xCCorner + i, d1);
            }
            for (var wC = 0; wC < ${this.convInfo.filterWidth}; wC = wC + 1) {
              let wValue = getW(wR, wC, d1, 0);
              for (var i = 0; i < ${this.workPerThread}; i++) {
                dotProd[i] = fma(xVals[i * ${a} + wC], wValue, dotProd[i]);
              }
            }
          }
        }

        for (var i = 0; i < ${this.workPerThread}; i = i + 1) {
          let coords = vec4<i32>(batch, r, c + i, d1);
          if (coordsInBounds4D(coords, uniforms.outShape)) {
            var value = dotProd[i];
            ${ll(this.addBias,this.activation)}
            setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
          }
        }
      }
    `}},Vk=class{constructor(e,t=!1,a=null,n=!1){this.variableNames=["x","W"],this.uniforms=`pads : vec2<i32>, inDims : vec2<i32>, filterHeight : i32,
      filterWidth : i32, strides : vec2<i32>, dilations : vec2<i32>,`,this.workgroupSize=[256,1,1],this.size=!0,this.outputShape=e.outShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.isChannelsLast=e.dataFormat==="channelsLast",t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),this.convInfo=e,this.addBias=t,this.activation=a,this.hasPreluActivation=n,this.shaderKey=`depthwise_${this.activation}_${this.isChannelsLast}`}getUserCode(){let e=this.isChannelsLast?"getX(batch, xR, xC, d1);":"getX(batch, d1, xR, xC);";return`
      ${Pr(this.activation,this.hasPreluActivation,!1,4)}

      ${ue("index")} {
        if (index < uniforms.size) {
          let coords = getOutputCoords();
          let batch = coords[0];
          let xRCCorner = vec2<i32>(coords.${this.isChannelsLast?"yz":"zw"}) * uniforms.strides - uniforms.pads;
          let d2 = coords[${this.isChannelsLast?3:1}];
          let channelMul = uniforms.wShape[3];
          let d1 = d2 / channelMul;
          let q = d2 % channelMul;

          let inputRowStart = xRCCorner.x;
          let inputColStart = xRCCorner.y;
          let inputRowEnd = inputRowStart + uniforms.filterHeight *
              uniforms.dilations[0];
          let inputColEnd = inputColStart + uniforms.filterWidth *
              uniforms.dilations[1];

          // Convolve x(?, ?, d1)|x(d1, ?, ?) with w(:, :, d1, q) to get
          // y(yR, yC, d2)|y(d2, yR, yC). ? = to be determined. : = across all
          // values in that axis. x(?, ?, d1) and y(yR, yC, d2) is for NHWC.
          // x(d1, ?, ?) and y(d2, yR, yC) is for NCHW.
          var value = 0.0;

          // Extract if checking out of for loop for performance.
          if (inputRowStart >= 0 && inputColStart >= 0 &&
            inputRowEnd < uniforms.inDims[0] &&
                inputColEnd < uniforms.inDims[1]) {
              for (var wR = 0; wR < uniforms.filterHeight; wR = wR + 1) {
                let xR = inputRowStart + wR * uniforms.dilations[0];

                for (var wC = 0; wC < uniforms.filterWidth; wC = wC + 1) {
                  let xC = inputColStart + wC * uniforms.dilations[1];

                  let xVal = ${e};
                  let wVal = getW(wR, wC, d1, q);
                  value = value + xVal * wVal;
                }
              }
            } else {
              for (var wR = 0; wR < uniforms.filterHeight; wR = wR + 1) {
                let xR = inputRowStart + wR * uniforms.dilations[0];

                if (xR < 0 || xR >= uniforms.inDims[0]) {
                  continue;
                }

                for (var wC = 0; wC < uniforms.filterWidth; wC = wC + 1) {
                  let xC = inputColStart + wC * uniforms.dilations[1];

                  if (xC < 0 || xC >= uniforms.inDims[1]) {
                    continue;
                  }

                  let xVal = ${e};
                  let wVal = getW(wR, wC, d1, q);
                  value = value + xVal * wVal;
                }
              }
            }
            ${ll(this.addBias,this.activation)}
          setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
        }
      }
    `}};function uhe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:u,dimRoundingMode:p}=n,c=C.convertConv2DDataFormat(l),d=u;d==null&&(d=[1,1]);let h=C.computeConv2DInfo(r.shape,s.shape,i,d,o,p,!0,c),m=[{type:"int32",data:[h.padInfo.top,h.padInfo.left]},{type:"int32",data:[h.inHeight,h.inWidth]}],f=h.dataFormat==="channelsLast",g;return!f&&h.inHeight>16&&h.inWidth>16&&h.strideHeight===1&&h.strideWidth===1&&h.dilationWidth===1&&h.dilationHeight===1&&h.inChannels===h.outChannels?g=new lhe(h.outShape,h.filterHeight,h.filterWidth):f&&h.outHeight>4&&h.outWidth>4&&h.strideWidth<=2&&h.inChannels===h.outChannels&&h.dilationHeight===1&&h.dilationWidth===1&&h.inChannels%4===0?(g=new Bk(h),m.push({type:"int32",data:[g.virtualWidth]})):(g=new Vk(h),m.push({type:"int32",data:[h.filterHeight]},{type:"int32",data:[h.filterWidth]},{type:"int32",data:[h.strideHeight,h.strideWidth]},{type:"int32",data:[h.dilationHeight,h.dilationWidth]})),a.runWebGPUProgram(g,[r,s],r.dtype,m)}var dhe={kernelName:$i,backendName:"webgpu",kernelFunc:uhe},phe=class{constructor(e){this.variableNames=["x","dy"],this.uniforms=`strides : vec2<i32>, pads : vec2<i32>, filterDims : vec2<i32>, outHeight : i32,
      outWidth : i32, inHeight : i32, inWidth : i32, batchSize : i32, channelMul : i32,`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.filterShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="depthwise_conv2d_backprop_filter"}getUserCode(){return`
      ${ue("index")} {
      if (index < uniforms.size) {
        let coords = getCoordsFromIndex(index);
        let wR = coords[0];
        let wC = coords[1];
        let d1 = coords[2];
        let dm = coords[3];
        let d2 = d1 * uniforms.channelMul + dm;

        var dotProd = 0.0;
        for (var b = 0; b < uniforms.batchSize; b++) {
          for (var yR = 0; yR < uniforms.outHeight; yR++) {
            let xR = wR + yR * uniforms.strides[0] - uniforms.pads[0];

            if (xR < 0 || xR >= uniforms.inHeight) {
              continue;
            }

            for (var yC = 0; yC < uniforms.outWidth; yC++) {
              let xC = wC + yC * uniforms.strides[1] - uniforms.pads[1];

              if (xC < 0 || xC >= uniforms.inWidth) {
                continue;
              }

              let dyValue = getDy(b, yR, yC, d2);
              let xValue = getX(b, xR, xC, d1);
              dotProd += xValue * dyValue;
            }
          }
        }
        setOutputAtIndex(index, dotProd);
      }
    }
    `}},che=class{constructor(e){this.variableNames=["dy","W"],this.uniforms=`strides : vec2<i32>, pads : vec2<i32>, filterDims : vec2<i32>,
       outHeight : i32, outWidth : i32, channelMul : i32,`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.inShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="depthwise_conv2d_backprop_input"}getUserCode(){return`
      ${ue("index")} {
      if (index < uniforms.size) {
        let coords = getCoordsFromIndex(index);
        let batch = coords[0];
        let d1 = coords[3];
        let dyCorner = coords.yz - uniforms.pads;
        let dyRCorner = dyCorner.x;
        let dyCCorner = dyCorner.y;

        var dotProd = 0.0;
        for (var wR = 0; wR < uniforms.filterDims[0]; wR++) {
          let dyR = f32(dyRCorner + wR) / f32(uniforms.strides[0]);

          if (dyR < 0.0 || dyR >= f32(uniforms.outHeight) || fract(dyR) > 0.0) {
            continue;
          }

          let idyR = i32(dyR);
          let wRPerm = uniforms.filterDims[0] - 1 - wR;

          for (var wC = 0; wC < uniforms.filterDims[1]; wC++) {
            let dyC = f32(dyCCorner + wC) / f32(uniforms.strides[1]);

            if (dyC < 0.0 || dyC >= f32(uniforms.outWidth) || fract(dyC) > 0.0) {
              continue;
            }

            let idyC = i32(dyC);
            let wCPerm = uniforms.filterDims[1] - 1 - wC;

            for (var dm = 0; dm < uniforms.channelMul; dm++) {
              let d2 = d1 * uniforms.channelMul + dm;
              let xValue = getDy(batch, idyR, idyC, d2);
              let wValue = getW(wRPerm, wCPerm, d1, dm);
              dotProd += xValue * wValue;
            }
          }
        }
        setOutputAtIndex(index, dotProd);
      }
    }
    `}};function hhe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,filterShape:p}=n,c=C.computeConv2DInfo(r.shape,p,i,o,l,u,!0),d=new phe(c),h=[{type:"int32",data:[c.strideHeight,c.strideWidth]},{type:"int32",data:[c.padInfo.top,c.padInfo.left]},{type:"int32",data:[c.filterHeight,c.filterWidth]},{type:"int32",data:[c.outHeight]},{type:"int32",data:[c.outWidth]},{type:"int32",data:[c.inHeight]},{type:"int32",data:[c.inWidth]},{type:"int32",data:[c.batchSize]},{type:"int32",data:[c.outChannels/c.inChannels]}];return a.runWebGPUProgram(d,[r,s],"float32",h)}var mhe={kernelName:fp,backendName:"webgpu",kernelFunc:hhe};function fhe(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,inputShape:p}=n,c=C.computeConv2DInfo(p,s.shape,i,o,l,u,!0),d=new che(c),h=[{type:"int32",data:[c.strideHeight,c.strideWidth]},{type:"int32",data:[c.filterHeight-1-c.padInfo.top,c.filterWidth-1-c.padInfo.left]},{type:"int32",data:[c.filterHeight,c.filterWidth]},{type:"int32",data:[c.outHeight]},{type:"int32",data:[c.outWidth]},{type:"int32",data:[c.outChannels/c.inChannels]}];return a.runWebGPUProgram(d,[r,s],r.dtype,h)}var ghe={kernelName:gp,backendName:"webgpu",kernelFunc:fhe},yhe=class{constructor(e){this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=[e,e],this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="diag"}getUserCode(){return`
      ${ue("index")} {
        if (index < uniforms.size) {
          let coords = getOutputCoords();
          let value = select(0.0, getX(coords[0]), coords[0] == coords[1]);
          setOutputAtIndex(index, value);
        }
      }
    `}};function xhe(e){let{inputs:t,backend:a}=e,{x:n}=t,r=[...n.shape,...n.shape],s=v.sizeFromShape(n.shape),i=ke({inputs:{x:n},backend:a,attrs:{shape:[s]}}),o=new yhe(s),l=a.runWebGPUProgram(o,[i],i.dtype),u=ke({inputs:{x:l},backend:a,attrs:{shape:r}});return a.disposeData(i.dataId),a.disposeData(l.dataId),u}var Ahe={kernelName:yu,backendName:"webgpu",kernelFunc:xhe},bhe=class{constructor(e){this.variableNames=["x","w"],this.uniforms="filterDims: vec2<i32>, pads: vec2<i32>, strides: vec2<i32>, dilations: vec2<i32>",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.outShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="dilation2d"}getUserCode(){return`
       ${ue("index")} {
         if (index < uniforms.size) {
           let neg_infinity = -3.4e38;
           let coords = getOutputCoords();
           let batch = coords.x;
           let d1 = coords.w;
           let outTopLeftCorner = coords.yz * uniforms.strides - uniforms.pads;
           let hBeg = outTopLeftCorner.x;
           let wBeg = outTopLeftCorner.y;

           var curVal = neg_infinity;
           for (var h = 0; h < uniforms.filterDims[0]; h = h + 1) {
             let hIn = hBeg + h * uniforms.dilations[0];

             if (hIn >= 0 && hIn < uniforms.xShape[1]) {
               for (var w = 0; w < uniforms.filterDims[1]; w = w + 1) {
                 let wIn = wBeg + w * uniforms.dilations[1];

                 if (wIn >= 0 && wIn < uniforms.xShape[2]) {
                   let val = getX(batch, hIn, wIn, d1) + getW(h, w, d1);
                   if (val > curVal) {
                     curVal = val;
                   }
                 }
               }
             }
           }

           setOutputAtIndex(index, curVal);
         }
       }
     `}};function vhe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=n,u=C.computeDilation2DInfo(r.shape,s.shape,i,o,"NHWC",l),p=[u.padInfo.top,u.padInfo.left],c=[{type:"int32",data:[u.filterHeight,u.filterWidth]},{type:"int32",data:[...p]},{type:"int32",data:[u.strideHeight,u.strideWidth]},{type:"int32",data:[u.dilationHeight,u.dilationWidth]}],d=new bhe(u);return a.runWebGPUProgram(d,[r,s],r.dtype,c)}var whe={kernelName:Pi,backendName:"webgpu",kernelFunc:vhe},khe=class{constructor(e,t){if(this.variableNames=["x","w","dy"],this.uniforms="filterDims: vec2<i32>, pads: vec2<i32>, strides: vec2<i32>, dilations: vec2<i32>, dySize: i32,",this.workgroupSize=[64,1,1],this.atomic=!0,this.outputShape=e.inShape,this.dispatchLayout=me(e.outShape),this.dispatch=de(this.dispatchLayout,e.outShape,this.workgroupSize),t!=="float32"&&t!=="int32")throw new Error(`Dilation2DBackpropInput only supports float32 and int32
          types, does not support ${t} type.`);this.type=t,this.shaderKey="dilation2DBackpropInput"}getUserCode(){return`
       ${ue("index")} {
         if (index < uniforms.dySize) {
           let coords = getDyCoordsFromIndex(index);
           let b = coords[0];
           let r = coords[1];
           let c = coords[2];
           let d = coords[3];

           let dyCorner = vec2<i32>(r, c) * uniforms.strides - uniforms.pads;
           var curVal = -3.4e38;  // neg_infinity
           var xRMax = 0;
           var xCMax = 0;

           // In the case of multiple argmax branches, we only back-propagate
           // along the last branch, i.e., the one with largest value of
           // 'wR * uniforms.filterDims[1] + wC', similarly to the max-pooling
           // backward routines.
           for (var wR = 0; wR < uniforms.filterDims[0]; wR++) {
             let xR = dyCorner.x + wR * uniforms.dilations[0];

             if (xR >= 0 && xR < uniforms.xShape[1]) {
               for (var wC = 0; wC < uniforms.filterDims[1]; wC++) {
                 let xC = dyCorner.y + wC * uniforms.dilations[1];

                 if (xC >= 0 && xC < uniforms.xShape[2]) {
                   let val = getX(b, xR, xC, d) + getW(wR, wC, d);
                   if (val > curVal) {
                     curVal = val;
                     xRMax = xR;
                     xCMax = xC;
                   }
                 }
               }
             }
           }

           let flatIndexIn = d + uniforms.xShape[3] *
               (xCMax + uniforms.xShape[2] * (xRMax + uniforms.xShape[1] * b));
           let value = getDy(b, r, c, d);
           ${xs("&result[flatIndexIn]","value",this.type)}
         }
       }
     `}},Ihe=class{constructor(e,t,a){if(this.variableNames=["x","w","dy"],this.uniforms="filterDims: vec2<i32>, pads: vec2<i32>, strides: vec2<i32>, dilations: vec2<i32>, dySize: i32,",this.workgroupSize=[64,1,1],this.atomic=!0,this.outputShape=e.filterShape,this.dispatchLayout=me(e.outShape),this.dispatch=de(this.dispatchLayout,e.outShape,this.workgroupSize),a!=="float32"&&a!=="int32")throw new Error(`Dilation2DBackpropFilter only supports float32 and int32
          types, does not support ${a} type.`);this.type=a,this.shaderKey="dilation2DBackpropFilter"}getUserCode(){return`
       ${ue("index")} {
         if (index < uniforms.dySize) {
           let coords = getDyCoordsFromIndex(index);
           let b = coords[0];
           let r = coords[1];
           let c = coords[2];
           let d = coords[3];

           let dyCorner = vec2<i32>(r, c) * uniforms.strides - uniforms.pads;
           var curVal = -3.4e38;  // neg_infinity
           var wRMax = 0;
           var wCMax = 0;

           // In the case of multiple argmax branches, we only back-propagate
           // along the last branch, i.e., the one with largest value of
           // 'wR * uniforms.filterDims[1] + wC', similarly to the max-pooling
           // backward routines.
           for (var wR = 0; wR < uniforms.filterDims[0]; wR++) {
             let xR = dyCorner.x + wR * uniforms.dilations[0];

             if (xR >= 0 && xR < uniforms.xShape[1]) {
               for (var wC = 0; wC < uniforms.filterDims[1]; wC++) {
                 let xC = dyCorner.y + wC * uniforms.dilations[1];

                 if (xC >= 0 && xC < uniforms.xShape[2]) {
                   let val = getX(b, xR, xC, d) + getW(wR, wC, d);
                   if (val > curVal) {
                     curVal = val;
                     wRMax = wR;
                     wCMax = wC;
                   }
                 }
               }
             }
           }

           let flatIndexIn = d + uniforms.wShape[2] * (wCMax + wRMax * uniforms.wShape[1]);
           let value = getDy(b, r, c, d);
           ${xs("&result[flatIndexIn]","value",this.type)}
         }
       }
     `}};function She(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s,dy:i}=t,{strides:o,pad:l,dilations:u}=n,p=C.computeDilation2DInfo(r.shape,s.shape,o,l,"NHWC",u),c=s.dtype,d=new Ihe(p,s.shape,c),h=[{type:"int32",data:[p.filterHeight,p.filterWidth]},{type:"int32",data:[p.padInfo.top,p.padInfo.left]},{type:"int32",data:[p.strideHeight,p.strideWidth]},{type:"int32",data:[p.dilationHeight,p.dilationWidth]},{type:"int32",data:[v.sizeFromShape(p.outShape)]}],m=Wa({backend:a,attrs:{shape:s.shape,value:0,dtype:c}});return a.runWebGPUProgram(d,[r,s,i],c,h,m)}var Che={kernelName:Xl,backendName:"webgpu",kernelFunc:She};function The(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s,dy:i}=t,{strides:o,pad:l,dilations:u}=n,p=C.computeDilation2DInfo(r.shape,s.shape,o,l,"NHWC",u),c=r.dtype,d=new khe(p,c),h=[{type:"int32",data:[p.filterHeight,p.filterWidth]},{type:"int32",data:[p.padInfo.top,p.padInfo.left]},{type:"int32",data:[p.strideHeight,p.strideWidth]},{type:"int32",data:[p.dilationHeight,p.dilationWidth]},{type:"int32",data:[v.sizeFromShape(p.outShape)]}],m=Wa({backend:a,attrs:{shape:p.inShape,value:0,dtype:c}});return a.runWebGPUProgram(d,[r,s,i],c,h,m)}var Nhe={kernelName:ql,backendName:"webgpu",kernelFunc:The},Rhe=class{constructor(e,t,a){this.variableNames=["Image"],this.uniforms="alpha: f32,",this.workgroupSize=[64,1,1],this.pixelsOpType=nu.DRAW,this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.type=t,this.textureFormat=a,this.shaderKey=`draw_${t}_${a}`}getUserCode(){let e,t=this.type==="float32"?"value":"value / 255.0";return e=`
      if (uniforms.numChannels == 1) {
        rgba[0] = ${t};
        rgba[1] = ${t};
        rgba[2] = ${t};
      } else {
        rgba[d] = ${t};
      }`,`
       @group(0) @binding(0) var outImage : texture_storage_2d<${this.textureFormat}, write>;
       ${ue("index")} {
         if (index < uniforms.size) {
           var rgba = vec4<f32>(0.0, 0.0, 0.0, uniforms.alpha);
           for (var d = 0; d < uniforms.numChannels; d = d + 1) {
             let value = f32(inBuf[index * uniforms.numChannels + d]);
             ${e}
           }
           rgba.x = rgba.x * rgba.w;
           rgba.y = rgba.y * rgba.w;
           rgba.z = rgba.z * rgba.w;
           let coords = getCoordsFromIndex(index);
           textureStore(outImage, vec2<i32>(coords.yx), rgba);
         }
       }
      `}};function Ehe(e){let{inputs:t,backend:a,attrs:n}=e,{image:r}=t,{canvas:s,options:i}=n,[o,l]=r.shape.slice(0,2),{imageOptions:u}=i||{},p=(u==null?void 0:u.alpha)||1,c=a.device.features.has("bgra8unorm-storage")?"bgra8unorm":"rgba8unorm",d=[o,l],h=new Rhe(d,r.dtype,c);s.width=l,s.height=o;let m="webgpu",f=s.getContext(m),g;f||(g=new OffscreenCanvas(l,o),f=g.getContext(m));let y=r.shape.length===3?r.shape[2]:1;f.configure({device:a.device,format:c,usage:GPUTextureUsage.STORAGE_BINDING,alphaMode:"premultiplied"});let x="int32",A=a.makeTensorInfo(d,x),b=a.tensorMap.get(A.dataId);b.resource=f.getCurrentTexture(),b.external=!0;let w=[{type:"uint32",data:[y]},{type:"float32",data:[p]}];if(a.runWebGPUProgram(h,[r],x,w,A),g){let I=s.getContext("2d");if(!I)throw new Error("Please make sure this canvas has only been used for 2d or webgpu context!");I.drawImage(g,0,0)}return a.disposeData(A.dataId),r}var Mhe={kernelName:yp,backendName:"webgpu",kernelFunc:Ehe},Uk=aa({opType:Pe.MUL,cpuKernelImpl:Dde,supportsComplex:!0}),$he={kernelName:yo,backendName:"webgpu",kernelFunc:Uk};function Gk(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;return dl(r,s,i,"sum",a)}var Phe={kernelName:Go,backendName:"webgpu",kernelFunc:Gk};function _he(e){let{inputs:t,backend:a,attrs:n}=e,{equation:r}=n,s=t,{allDims:i,summedDims:o,idDims:l}=C.decodeEinsumEquation(r,s.length);C.checkEinsumDimSizes(i.length,l,s);let{path:u,steps:p}=C.getEinsumComputePath(o,l),c=p.length,d=null,h=i.length,m=[];for(let f=0;f<c;++f){for(let g of p[f]){let{permutationIndices:y,expandDims:x}=C.getEinsumPermutation(h,l[g]),A;C.isIdentityPermutation(y)?A=s[g]:(A=sr({inputs:{x:s[g]},backend:a,attrs:{perm:y}}),m.push(A));let b=A.shape.slice();for(let w=0;w<x.length;++w)b.splice(x[w],0,1);v.arraysEqual(A.shape,b)||(A=ke({inputs:{x:A},backend:a,attrs:{shape:b}}),m.push(A)),d===null?d=A:(d=Uk({inputs:{a:A,b:d},backend:a}),m.push(d))}f<c-1&&(u[f]>=0&&(d=Gk({inputs:{x:d},backend:a,attrs:{axis:u[f]-(i.length-h),keepDims:!1}}),m.push(d)),h--)}for(let f of m)f!==d&&a.disposeData(f.dataId);return d}var Fhe={kernelName:xp,backendName:"webgpu",kernelFunc:_he},Dhe=at({opType:le.ELU}),Ohe={kernelName:Fi,backendName:"webgpu",kernelFunc:Dhe},zhe=e=>{let{inputs:t,backend:a}=e,{dy:n,y:r}=t,s=new Th(Pe.ELU_DER,n.shape,r.shape);return a.runWebGPUProgram(s,[n,r],n.dtype)},Lhe={kernelName:xu,backendName:"webgpu",kernelFunc:zhe},Whe=aa({opType:Pe.EQUAL,dtype:"bool",cpuKernelImpl:vde}),Bhe={kernelName:Oi,backendName:"webgpu",kernelFunc:Whe},Vhe=at({opType:le.ERF}),Uhe={kernelName:Di,backendName:"webgpu",kernelFunc:Vhe},Ghe=at({opType:le.EXP,cpuKernelImpl:wde,dtype:"float32"}),Hhe={kernelName:zi,backendName:"webgpu",kernelFunc:Ghe};function Y1(e){let{inputs:t,attrs:a,backend:n}=e,{dim:r}=a,{input:s}=t,i=s.shape.length,o=s.shape.slice(),l=r;return r<0&&(v.assert(-(i+1)<=r,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+r+1),o.splice(l,0,1),ke({inputs:{x:s},backend:n,attrs:{shape:o}})}var jhe={kernelName:Au,backendName:"webgpu",kernelFunc:Y1},qhe=at({opType:le.EXPM1,cpuKernelImpl:kde}),Xhe={kernelName:Li,backendName:"webgpu",kernelFunc:qhe},pA=class{constructor(e,t){this.variableNames=["real","imag"],this.outputShape=[],this.uniforms="exponentMultiplier : f32, denominator: f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.component=e,this.shaderKey=`fft_${e}`}getUserCode(){return`
    fn unaryOpComplex(real: f32, expR: f32, imag: f32, expI: f32) -> f32 {
      ${this.component==="real"?"return real * expR - imag * expI;":"return real * expI + imag * expR;"}
    }

    fn mulMatDFT(batch: i32, index: i32) -> f32 {
      let indexRatio = f32(index) / f32(uniforms.realShape[1]);
      let exponentMultiplierTimesIndexRatio =
          uniforms.exponentMultiplier * indexRatio;

      var result = 0.0;

      for (var i = 0; i < uniforms.realShape[1]; i = i + 1) {
        // x = (-2|2 * PI / N) * index * i;
        let x = exponentMultiplierTimesIndexRatio * f32(i);
        let expR = cos(x);
        let expI = sin(x);
        let real = getReal(batch, i);
        let imag = getImag(batch, i);

        result = result +
            unaryOpComplex(real, expR, imag, expI) / uniforms.denominator;
      }

      return result;
    }

    ${ue("index")} {
      if (index < uniforms.size) {
        let coords = getOutputCoords();
        setOutputAtIndex(index, mulMatDFT(coords[0], coords[1]));
      }
    }
  `}};function Hk(e,t,a){let n=a.tensorMap.get(e.dataId),r=v.sizeFromShape(e.shape),s=e.shape[e.shape.length-1],i=r/s,o=[],l=ke({inputs:{x:e},backend:a,attrs:{shape:[i,s]}});o.push(l);let u=l.shape,p=new pA("real",u),c=new pA("imag",u),d=[{dataId:n.complexTensorInfos.real.dataId,dtype:n.complexTensorInfos.real.dtype,shape:u},{dataId:n.complexTensorInfos.imag.dataId,dtype:n.complexTensorInfos.imag.dtype,shape:u}],h=t?2*Math.PI:-2*Math.PI,m=t?u[1]:1,f=[{type:"float32",data:[h]},{type:"float32",data:[m]}],g=a.runWebGPUProgram(p,d,"float32",f);o.push(g);let y=a.runWebGPUProgram(c,d,"float32",f);o.push(y);let x=ul({inputs:{real:g,imag:y},backend:a});o.push(x);let A=ke({inputs:{x},backend:a,attrs:{shape:e.shape}});return o.forEach(b=>a.disposeData(b.dataId)),A}function Khe(e){let{inputs:t,backend:a}=e,{input:n}=t;return Hk(n,!1,a)}var Yhe={kernelName:Ap,backendName:"webgpu",kernelFunc:Khe},Zhe=class{constructor(e){this.outputShape=[],this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="flipLeftRight"}getUserCode(){return`
      ${ue("index")} {
        if (index < uniforms.size) {
          let coords = getCoordsFromIndex(index);
          let coordX = uniforms.xShape[2] - coords[2] - 1;
          let outputValue = getX(coords[0], coords[1], coordX, coords[3]);
          setOutputAtIndex(index, outputValue);
        }
      }
    `}},Jhe={kernelName:Wi,backendName:"webgpu",kernelFunc:({inputs:e,backend:t})=>{let{image:a}=e,n=t,r=new Zhe(a.shape);return n.runWebGPUProgram(r,[a],a.dtype)}},Qhe=at({opType:le.FLOOR,cpuKernelImpl:Ide}),e0e={kernelName:Bi,backendName:"webgpu",kernelFunc:Qhe},t0e=aa({opType:Pe.FLOOR_DIV,cpuKernelImpl:Sde,dtype:"int32"}),a0e={kernelName:Vi,backendName:"webgpu",kernelFunc:t0e},n0e=class{constructor(e,t,a=!1){this.pixelsOpType=nu.FROM_PIXELS,this.outputShape=[0],this.variableNames=[],this.workgroupSize=[256,1,1],this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,[t,1,1]),this.importVideo=a,this.shaderKey=`fromPixels_${this.importVideo}`}getUserCode(){let e=this.importVideo?"textureLoad(src, vec2<i32>(coords.yx));":"textureLoad(src, vec2<i32>(coords.yx), 0)";return`
      @binding(1) @group(0) var src: ${this.importVideo?"texture_external":"texture_2d<f32>"};
      ${ue("index")} {
        let flatIndex = index * uniforms.numChannels;
        if (flatIndex < uniforms.size) {
          let coords = getCoordsFromIndex(flatIndex);
          let values = ${e};
          for (var i = 0; i < uniforms.numChannels; i = i + 1) {
            result[flatIndex + i] = i32(floor(255.0 * values[i]));
          }
        }
      }
  `}},r0e={kernelName:Wd,backendName:"webgpu",kernelFunc:s0e},Dl,e1=B().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");function s0e(e){let{inputs:t,backend:a,attrs:n}=e,{pixels:r}=t,{numChannels:s}=n;if(r==null)throw new Error("pixels passed to tf.browser.fromPixels() can not be null");let i=typeof HTMLVideoElement!="undefined"&&r instanceof HTMLVideoElement,o=typeof HTMLImageElement!="undefined"&&r instanceof HTMLImageElement,l=typeof HTMLCanvasElement!="undefined"&&r instanceof HTMLCanvasElement||typeof OffscreenCanvas!="undefined"&&r instanceof OffscreenCanvas,u=typeof ImageBitmap!="undefined"&&r instanceof ImageBitmap,[p,c]=i?[r.videoWidth,r.videoHeight]:[r.width,r.height],d=[c,p,s],h=B().getBool("WEBGPU_IMPORT_EXTERNAL_TEXTURE")&&i,m=i||o;if(u||l||m){let x;if(h)x=a.device.importExternalTexture({source:r});else{if(m){let S=B().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");(Dl==null||S!==e1)&&(e1=S,Dl=document.createElement("canvas").getContext("2d",{willReadFrequently:e1})),Dl.canvas.width=p,Dl.canvas.height=c,Dl.drawImage(r,0,0,p,c),r=Dl.canvas}let $=GPUTextureUsage.COPY_DST|GPUTextureUsage.RENDER_ATTACHMENT|GPUTextureUsage.TEXTURE_BINDING,E=a.textureManager.acquireTexture(d[1],d[0],"rgba8unorm",$);a.queue.copyExternalImageToTexture({source:r},{texture:E},[d[1],d[0]]),x=E}let A=v.sizeFromShape(d),b=v.computeStrides(d),w=new n0e(d,s,h),I=[{type:"uint32",data:[A]},{type:"uint32",data:[s]},{type:"uint32",data:[...b]}],T=a.makeTensorInfo([c,p],"int32"),N=a.tensorMap.get(T.dataId);N.resource=x;let M=a.runWebGPUProgram(w,[T],"int32",I);return a.disposeData(T.dataId),M}let f=r.data,g=f;if(s!=null&&s!==4){g=new Uint8Array(r.width*r.height*s);let x=f.length,A=0;for(let b=0;b<x;b++)b%4<s&&(g[A++]=f[b])}let y=a.makeTensorInfo(d,"int32",new Int32Array(g));return a.uploadToGPU(y.dataId),y}var i0e=class{constructor(e,t,a,n,r){this.uniforms="varianceEpsilon : f32,",this.workgroupSize=[128,1,1],this.size=!0,this.variableNames=["x","mean","variance"],C.assertAndGetBroadcastShape(e,t),C.assertAndGetBroadcastShape(e,a),this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),n!=null&&(C.assertAndGetBroadcastShape(e,n),this.variableNames.push("offset")),r!=null&&(C.assertAndGetBroadcastShape(e,r),this.variableNames.push("scale")),this.offsetShape=n,this.scaleShape=r,this.shaderKey="batchNorm"}getUserCode(){let e="0.0";this.offsetShape!=null&&(e="getOffsetByOutputIndex(index)");let t="1.0";return this.scaleShape!=null&&(t="getScaleByOutputIndex(index)"),`
      ${ue("index")} {
        if (index < uniforms.size)
        {
          let xValue = getXByOutputIndex(index);
          let meanValue = getMeanByOutputIndex(index);
          let varianValue = getVarianceByOutputIndex(index);
          let offsetValue = ${e};
          let scaleValue = ${t};
          let inv = scaleValue * inverseSqrt(varianValue + f32(uniforms.varianceEpsilon));
          setOutputAtIndex(index,dot(vec3<f32>(xValue, -meanValue, offsetValue), vec3<f32>(inv, inv, 1.0)));
        }
      }
  `}},o0e={kernelName:Ui,backendName:"webgpu",kernelFunc:({inputs:e,attrs:t,backend:a})=>{let{x:n,scale:r,offset:s,mean:i,variance:o}=e,{varianceEpsilon:l}=t,u=a,p=[n,i,o],c=null;s!=null&&(c=s.shape,p.push(s));let d=null;r!=null&&(d=r.shape,p.push(r));let h=new i0e(n.shape,i.shape,o.shape,c,d),m=[{type:"float32",data:[l]}];return u.runWebGPUProgram(h,p,n.dtype,m)}};function l0e(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dataFormat:p,dilations:c,dimRoundingMode:d,activation:h,leakyreluAlpha:m}=n,f=C.convertConv2DDataFormat(p),g=C.computeConv2DInfo(r.shape,s.shape,l,c,u,d,!1,f);return Lk({x:r,filter:s,convInfo:g,backend:a,bias:i,preluActivationWeights:o,leakyreluAlpha:m,activation:h})}var u0e={kernelName:Jr,backendName:"webgpu",kernelFunc:l0e};function d0e(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:p,dimRoundingMode:c,activation:d,leakyreluAlpha:h}=n,m=p;m==null&&(m=[1,1]),v.assert(C.eitherStridesOrDilationsAreOne(l,m),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${m}'`);let f=C.computeConv2DInfo(r.shape,s.shape,l,m,u,c,!0),g=[r,s],y=i!=null,x=o!=null;y&&g.push(i),x&&g.push(o);let A=[{type:"int32",data:[f.padInfo.top,f.padInfo.left]},{type:"int32",data:[f.inHeight,f.inWidth]}],b;return f.outHeight>4&&f.outWidth>4&&f.strideWidth<=2&&f.inChannels===f.outChannels&&f.dilationHeight===1&&f.dilationWidth===1&&f.inChannels%4===0?(b=new Bk(f,y,d,x),A.push({type:"int32",data:[b.virtualWidth]})):(b=new Vk(f,y,d,x),A.push({type:"int32",data:[f.filterHeight]},{type:"int32",data:[f.filterWidth]},{type:"int32",data:[f.strideHeight,f.strideWidth]},{type:"int32",data:[f.dilationHeight,f.dilationWidth]})),d==="leakyrelu"&&(A.push({type:"float32",data:[h]}),b.uniforms+=" alpha : f32,"),a.runWebGPUProgram(b,g,"float32",A)}var p0e={kernelName:Qr,backendName:"webgpu",kernelFunc:d0e},c0e=class{constructor(e,t){this.variableNames=["A","indices"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey=`gathernd_${e}`,this.sliceDim=e,this.uniforms=`sliceDim : i32, strides : ${Pt(e)},`}getUserCode(){let e;return this.sliceDim>1?e="uniforms.strides[j]":e="uniforms.strides",`
      ${ue("index")} {
        if (index < uniforms.size) {
          let coords = getCoordsFromIndex(index);
          var flattenIndex = 0;
          for (var j = 0; j < uniforms.sliceDim; j = j + 1) {
            let indexTemp = i32(round(getIndices(coords[0], j)));
            let strideNum = ${e};
            flattenIndex = flattenIndex + indexTemp * strideNum;
          }

          setOutputAtIndex(index, getA(flattenIndex, coords[1]));
        }
      }
      `}};function h0e(e){let{inputs:t,backend:a}=e,{params:n,indices:r}=t,s=r.shape,i=s[s.length-1],o=v.sizeFromShape(n.shape),[l,u,p,c]=C.prepareAndValidate(n,r),d=ke({inputs:{x:r},backend:a,attrs:{shape:[u,i]}}),h=ke({inputs:{x:n},backend:a,attrs:{shape:[v.sizeFromShape(n.shape)/p,p]}});if(a.shouldExecuteOnCPU([n,r])||n.dtype==="string"){let x=a.readSync(r.dataId),A=a.bufferSync(n),b=Cde(x,A,n.dtype,u,i,p,c,n.shape,o);return a.makeTensorInfo(l,n.dtype,b.values)}let m=new c0e(i,[u,p]),f=[{type:"int32",data:[i]},{type:"int32",data:c}],g=a.runWebGPUProgram(m,[h,d],h.dtype,f),y=ke({inputs:{x:g},backend:a,attrs:{shape:l}});return a.disposeData(d.dataId),a.disposeData(h.dataId),a.disposeData(g.dataId),y}var m0e={kernelName:Gi,backendName:"webgpu",kernelFunc:h0e},f0e=class{constructor(e,t){this.variableNames=["A","indices"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.slice(),this.aShape=e,this.outputShape=t,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="gather"}getUserCode(){let e=g0e(this.aShape);return`
      ${ue("index")} {
        if (index < uniforms.size) {
          let resRC = getCoordsFromIndex(index);
          let indexZ = i32(getIndices(resRC.x, resRC.z));
          let inBounds = select(0.0, 1.0, indexZ >= 0 && indexZ < uniforms.aShape[2]);
          setOutputAtIndex(index, inBounds * getA(${e}));
        }
      }
    `}};function g0e(e){let t=["resRC.x","resRC.y","resRC.z","resRC.w"],a=[];for(let n=0;n<e.length;n++)n===2?a.push("indexZ"):a.push(`${t[n]}`);return a.join()}function jk(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,indices:s}=t,{axis:i,batchDims:o}=n,l=v.parseAxisParam(i,r.shape)[0],u=C.segment_util.collectGatherOpShapeInfo(r,s,l,o),p=v.sizeFromShape(s.shape),c=[],d=ke({inputs:{x:r},backend:a,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),h=ke({inputs:{x:s},backend:a,attrs:{shape:[u.batchSize,p/u.batchSize]}});c.push(d),c.push(h);let m=[u.batchSize,u.outerSize,p/u.batchSize,u.sliceSize];if(a.shouldExecuteOnCPU([r,s])){let x=a.tensorMap.get(h.dataId).values,A=_e(h.shape,h.dtype,x),b=a.tensorMap.get(d.dataId).values,w=_e(d.shape,d.dtype,b),I=Tde(w,A,m);return c.forEach(T=>a.disposeData(T.dataId)),a.makeTensorInfo(u.outputShape,I.dtype,I.values)}let f=new f0e(d.shape,m),g=a.runWebGPUProgram(f,[d,h],d.dtype);c.push(g);let y=ke({inputs:{x:g},backend:a,attrs:{shape:u.outputShape}});return c.forEach(x=>a.disposeData(x.dataId)),y}var y0e={kernelName:vu,backendName:"webgpu",kernelFunc:jk},x0e=aa({opType:Pe.GREATER,cpuKernelImpl:Rde,dtype:"bool"}),A0e={kernelName:Hi,backendName:"webgpu",kernelFunc:x0e},b0e=aa({opType:Pe.GREATER_EQUAL,dtype:"bool",cpuKernelImpl:Nde}),v0e={kernelName:ji,backendName:"webgpu",kernelFunc:b0e};function w0e(e){let{inputs:t,backend:a}=e,{input:n}=t;return Hk(n,!0,a)}var k0e={kernelName:bp,backendName:"webgpu",kernelFunc:w0e},I0e=at({opType:le.IS_FINITE,dtype:"bool"}),S0e={kernelName:Xi,backendName:"webgpu",kernelFunc:I0e},C0e=at({opType:le.IS_INF,dtype:"bool"}),T0e={kernelName:Ki,backendName:"webgpu",kernelFunc:C0e},N0e=at({opType:le.IS_NAN,dtype:"bool"}),R0e={kernelName:Yi,backendName:"webgpu",kernelFunc:N0e};function E0e(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{alpha:s}=n,i=[{type:"float32",data:[s]}],o=new td(r.shape,le.LEAKYRELU,"alpha : f32,");return a.runWebGPUProgram(o,[r],"float32",i)}var M0e={kernelName:Zi,backendName:"webgpu",kernelFunc:E0e},$0e=aa({opType:Pe.LESS,dtype:"bool",cpuKernelImpl:Mde}),P0e={kernelName:Ji,backendName:"webgpu",kernelFunc:$0e},_0e=aa({opType:Pe.LESS_EQUAL,dtype:"bool",cpuKernelImpl:Ede}),F0e={kernelName:Qi,backendName:"webgpu",kernelFunc:_0e},D0e=class{constructor(e){this.variableNames=[],this.outputShape=[],this.uniforms="start : f32, step : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=[e],this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="linSpace"}getUserCode(){return`
      ${ue("index")} {
        if (index < uniforms.size) {
          setOutputAtIndex(index, uniforms.start + f32(index) * uniforms.step);
        }
      }
    `}};function O0e(e){let{backend:t,attrs:a}=e,{start:n,stop:r,num:s}=a,i=(r-n)/(s-1),o=new D0e(s),l=[{type:"float32",data:[n]},{type:"float32",data:[i]}];return t.runWebGPUProgram(o,[],"float32",l)}var z0e={kernelName:eo,backendName:"webgpu",kernelFunc:O0e},L0e=at({opType:le.LOG,cpuKernelImpl:$de}),W0e={kernelName:to,backendName:"webgpu",kernelFunc:L0e},B0e=at({opType:le.LOG1P}),V0e={kernelName:ao,backendName:"webgpu",kernelFunc:B0e},U0e=aa({opType:Pe.LOGICAL_AND,dtype:"bool"}),G0e={kernelName:no,backendName:"webgpu",kernelFunc:U0e},H0e=at({opType:le.LOGICAL_NOT}),j0e={kernelName:ro,backendName:"webgpu",kernelFunc:H0e},q0e=aa({opType:Pe.LOGICAL_OR}),X0e={kernelName:so,backendName:"webgpu",kernelFunc:q0e},qk=`
  var powValue = 0.0;
  let basis = uniforms.bias + uniforms.alpha * sum;
  if (uniforms.beta == 0.5) {
    powValue = inverseSqrt(basis);
  } else if (uniforms.beta == 1.0) {
    powValue = 1.0 / basis;
  } else {
    powValue = exp(log(basis) * (-uniforms.beta));
  }
`,K0e=class{constructor(e){this.outputShape=[],this.variableNames=["x"],this.uniforms="radius : i32, bias : f32, alpha : f32, beta : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="lrn"}getUserCode(){return`
    ${ue("index")} {
      if (index < uniforms.size) {
        let coords = getOutputCoords();
        let b = coords[0];
        let r = coords[1];
        let c = coords[2];
        let d = coords[3];

        let x = getX(b, r, c, d);
        var sum = 0.0;
        for (var i = -uniforms.radius; i <= uniforms.radius; i = i + 1) {
          let idx = d + i;
          if (idx >= 0 && idx < uniforms.xShape[3]) {
            let z = getX(b, r, c, idx);
            sum = sum + z * z;
          }
        }
        ${qk}

        setOutputAtIndex(index, x * powValue);
      }
    }
  `}},Y0e=class{constructor(e,t){this.outputShape=[],this.variableNames=["x"],this.uniforms="radius : i32, bias : f32, alpha : f32, beta : f32,",this.workgroupSize=[256,1,1],this.maxAllowRadius=16,v.assert(t<=this.maxAllowRadius,()=>`Radius must be less than or equal to ${this.maxAllowRadius}, current radius is ${t}`),this.outputShape=e,this.elementsPerWorkgroup=this.workgroupSize[0]-2*this.maxAllowRadius,this.dispatchLayout={x:[3],y:[2],z:[0,1]},this.dispatch=de(this.dispatchLayout,this.outputShape,[this.elementsPerWorkgroup,this.workgroupSize[1],this.workgroupSize[2]]),this.shaderKey="lrn_shared"}getUserCode(){return`
    var <workgroup>lrnSub: array<f32, ${this.workgroupSize[0]}>;
    const elementsPerWorkgroup = ${this.elementsPerWorkgroup};
    const maxAllowRadius = ${this.maxAllowRadius};

    ${ue()} {
      let localDepth = i32(localId.x);
      let workgroupDepth = i32(workgroupId.x) * elementsPerWorkgroup;
      let xDepth = workgroupDepth + localDepth - maxAllowRadius;
      let b = i32(globalId.z) / uniforms.xShape[1];
      let r = i32(globalId.z) - b * uniforms.xShape[1];
      let c = i32(globalId.y);
      let d = workgroupDepth + localDepth;

      var x = 0.0;
      if (xDepth >= 0 && xDepth < uniforms.xShape[3]) {
        x = getX(b, r, c, xDepth);
      }
      lrnSub[localDepth] = x;
      workgroupBarrier();

      if (localDepth < elementsPerWorkgroup && d < uniforms.outShape[3]) {
        var sum = 0.0;
        let index = localDepth + maxAllowRadius;
        for (var i = -uniforms.radius; i <= uniforms.radius; i = i + 1) {
          let z = lrnSub[index + i];
          sum = sum + z * z;
        }
        ${qk}

        setOutputAtCoords(b, r, c, d, lrnSub[index] * powValue);
      }
    } `}};function Z0e(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=n,u;s>16?u=new K0e(r.shape):u=new Y0e(r.shape,s);let p=[{type:"int32",data:[s]},{type:"float32",data:[i]},{type:"float32",data:[o]},{type:"float32",data:[l]}];return a.runWebGPUProgram(u,[r],r.dtype,p)}var J0e={kernelName:io,backendName:"webgpu",kernelFunc:Z0e},Q0e=class{constructor(e){this.outputShape=[],this.variableNames=["inputImage","outputImage","dy"],this.uniforms="depthRadius : i32, bias : f32, alpha : f32, beta : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="lrn_grad"}getUserCode(){return`
    ${ue("index")} {
      if (index < uniforms.size) {
        let coords = getOutputCoords();
        let b = coords[0];
        let r = coords[1];
        let c = coords[2];

        let MIN_DEPTH_BEGIN = 0;
        let MAX_DEPTH_END = uniforms.outShape[3];
        var result = 0.0;
        for (var d = MIN_DEPTH_BEGIN; d < MAX_DEPTH_END; d++) {
          let depthBegin = max(MIN_DEPTH_BEGIN, d - uniforms.depthRadius);
          let depthEnd = min(MAX_DEPTH_END, d + uniforms.depthRadius + 1);

          var norm = 0.0;
          for (var k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; k++) {
            if (k < depthBegin) {
              continue;
            } else if (k >= depthBegin && k < depthEnd) {
              norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k);
            } else {
              break;
            }
          }

          norm = uniforms.alpha * norm + uniforms.bias;

          for (var k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; k++) {
            if (k < depthBegin) {
              continue;
            } else if (k >= depthBegin && k < depthEnd) {
              var dyi = -2.0 * uniforms.alpha * uniforms.beta
                * getInputImage(b, r, c, k) * getOutputImage(b, r, c, d) / norm;
              if (k == d) {
                dyi += pow(norm, -1.0 * uniforms.beta);
              }
              if (k == coords[3]) {
                dyi *= getDy(b, r, c, d);
                result += dyi;
              }
            } else {
              break;
            }
          }
        }

        setOutputAtIndex(index, result);
      }
    }
  `}};function eme(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:u,beta:p}=n,c=new Q0e(r.shape),d=[{type:"int32",data:[o]},{type:"float32",data:[l]},{type:"float32",data:[u]},{type:"float32",data:[p]}];return a.runWebGPUProgram(c,[r,s,i],r.dtype,d)}var tme={kernelName:wu,backendName:"webgpu",kernelFunc:eme},ame=aa({opType:Pe.MAX,cpuKernelImpl:_de}),nme={kernelName:lo,backendName:"webgpu",kernelFunc:ame};function rme(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=n,u=C.computePool2DInfo(r.shape,s,i,1,o,l);return Fk(r,u,"max",a)}var sme={kernelName:uo,backendName:"webgpu",kernelFunc:rme};function ime(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dataFormat:l,dimRoundingMode:u}=n,p=[1,1,1],c=C.computePool3DInfo(r.shape,s,i,p,o,u,l),d=new Z3(c,"max"),h=[{type:"int32",data:[c.strideDepth,c.strideHeight,c.strideWidth]},{type:"int32",data:[c.padInfo.front,c.padInfo.top,c.padInfo.left]},{type:"int32",data:[c.inDepth,c.inHeight,c.inWidth]},{type:"int32",data:[c.effectiveFilterDepth,c.effectiveFilterHeight,c.effectiveFilterWidth]}];return a.runWebGPUProgram(d,[r],r.dtype,h)}var ome={kernelName:ku,backendName:"webgpu",kernelFunc:ime},lme=class{constructor(e){this.variableNames=["dy","maxPos"],this.uniforms=`strides : vec2<i32>, pads : vec2<i32>, dilations : vec2<i32>, filterDims : vec2<i32>,
       outHeight : i32, outWidth : i32`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.inShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="maxPool2DBackprop"}getUserCode(){return`
      ${ue("index")} {
      if (index < uniforms.size) {
        let coords = getCoordsFromIndex(index);
        let batch = coords[0];
        let d = coords[3];

        let dyRCCorner = vec2<i32>(coords.yz) - uniforms.pads;
        let dyRCorner = dyRCCorner.x;
        let dyCCorner = dyRCCorner.y;

        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).
        // ? = to be determined. : = across all values in that axis.
        var dotProd = 0.0;
        let lastIndex = uniforms.filterDims[0] * uniforms.filterDims[1] - 1;
        for (var wR = 0; wR < uniforms.filterDims[0]; wR += uniforms.dilations[0]) {
          let dyR = f32(dyRCorner + wR) / f32(uniforms.strides[0]);

          if (dyR < 0.0 || dyR >= f32(uniforms.outHeight) || fract(dyR) > 0.0) {
            continue;
          }
          let idyR = i32(dyR);

          for (var wC = 0; wC < uniforms.filterDims[1]; wC += uniforms.dilations[1]) {
            let dyC = f32(dyCCorner + wC) / f32(uniforms.strides[1]);

            if (dyC < 0.0 || dyC >= f32(uniforms.outWidth) || fract(dyC) > 0.0) {
              continue;
            }
            let idyC = i32(dyC);

            let dyValue = getDy(batch, idyR, idyC, d);
            let maxPosValue = lastIndex - i32(getMaxPos(batch, idyR, idyC, d));

            // Get the current value, check it against the value from the
            // position matrix.
            let curPosValue = wR * uniforms.filterDims[1] + wC;
            let mask = select(0.0, 1.0, maxPosValue == curPosValue);
            dotProd += dyValue * mask;
          }
        }
        setOutputAtIndex(index, dotProd);
      }
    }
    `}},ume=class{constructor(e){this.variableNames=["dy","maxPos"],this.uniforms=`strides : vec3<i32>, pads : vec3<i32>, filterDims : vec3<i32>,
      outDepth : i32, outHeight : i32, outWidth : i32`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.inShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="maxPool3DBackprop"}getUserCode(){return`
      ${ue("index")} {
      if (index < uniforms.size) {
        let coords = getCoordsFromIndex(index);
        let batch = coords.x;
        let ch = coords.u;

        let dyCorner = vec3<i32>(coords.y, coords.z, coords.w) - uniforms.pads;
        let dyDCorner = dyCorner.x;
        let dyRCorner = dyCorner.y;
        let dyCCorner = dyCorner.z;

        // Convolve dy(?, ?, ?, ch) with pos mask(:, :, :, d) to get
        // dx(xD, xR, xC, ch).
        // ? = to be determined. : = across all values in that axis.
        var dotProd = 0.0;
        let lastIndex = uniforms.filterDims[0] * uniforms.filterDims[1] * uniforms.filterDims[2] - 1;

        for (var wD = 0; wD < uniforms.filterDims[0]; wD++) {
          let dyD = f32(dyDCorner + wD) / f32(uniforms.strides[0]);

          if (dyD < 0.0 || dyD >= f32(uniforms.outDepth) || fract(dyD) > 0.0) {
            continue;
          }
          let idyD = i32(dyD);

          for (var wR = 0; wR < uniforms.filterDims[1]; wR++) {
            let dyR = f32(dyRCorner + wR) / f32(uniforms.strides[1]);

            if (dyR < 0.0 || dyR >= f32(uniforms.outHeight) || fract(dyR) > 0.0) {
              continue;
            }
            let idyR = i32(dyR);

            for (var wC = 0; wC < uniforms.filterDims[2]; wC++) {
              let dyC = f32(dyCCorner + wC) / f32(uniforms.strides[2]);

              if (dyC < 0.0 || dyC >= f32(uniforms.outWidth) || fract(dyC) > 0.0) {
                continue;
              }
              let idyC = i32(dyC);

              let dyValue = getDy(batch, idyD, idyR, idyC, ch);
              let maxPosValue = lastIndex - i32(getMaxPos(batch, idyD, idyR, idyC, ch));

              // Get the current value, check it against the value from the
              // position matrix.
              let curPosValue = wD * uniforms.filterDims[1] * uniforms.filterDims[2] + wR * uniforms.filterDims[2] + wC;
              let mask = select(0.0, 1.0, maxPosValue == curPosValue);
              dotProd += dyValue * mask;
            }
          }
        }

        setOutputAtIndex(index, dotProd);
      }
    }
    `}};function dme(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,i=s,{filterSize:o,strides:l,pad:u,dimRoundingMode:p}=n,c=[1,1,1],d=C.computePool3DInfo(i.shape,o,l,c,u,p),h=new Z3(d,"max",!0),m=[{type:"int32",data:[d.strideDepth,d.strideHeight,d.strideWidth]},{type:"int32",data:[d.padInfo.front,d.padInfo.top,d.padInfo.left]},{type:"int32",data:[d.inDepth,d.inHeight,d.inWidth]},{type:"int32",data:[d.effectiveFilterDepth,d.effectiveFilterHeight,d.effectiveFilterWidth]}],f=a.runWebGPUProgram(h,[i],"int32",m),g=new ume(d);m=[{type:"int32",data:[d.strideDepth,d.strideHeight,d.strideWidth]},{type:"int32",data:[d.effectiveFilterDepth-1-d.padInfo.front,d.effectiveFilterHeight-1-d.padInfo.top,d.effectiveFilterWidth-1-d.padInfo.left]},{type:"int32",data:[d.effectiveFilterDepth,d.effectiveFilterHeight,d.effectiveFilterWidth]},{type:"int32",data:[d.outDepth]},{type:"int32",data:[d.outHeight]},{type:"int32",data:[d.outWidth]}];let y=a.runWebGPUProgram(g,[r,f],i.dtype,m);return a.disposeData(f.dataId),y}var pme={kernelName:kp,backendName:"webgpu",kernelFunc:dme};function cme(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s,output:i}=t,o=s;q3([s,i],"maxPoolGrad");let{filterSize:l,strides:u,pad:p,dimRoundingMode:c}=n,d=C.computePool2DInfo(o.shape,l,u,1,p,c),h=new sp(d,"max",!0),m=[{type:"int32",data:[d.strideHeight,d.strideWidth]},{type:"int32",data:[d.padInfo.top,d.padInfo.left]},{type:"int32",data:[d.dilationHeight,d.dilationWidth]},{type:"int32",data:[d.inHeight,d.inWidth]},{type:"int32",data:[d.effectiveFilterHeight,d.effectiveFilterWidth]}],f=a.runWebGPUProgram(h,[o],"int32",m),g=new lme(d);m=[{type:"int32",data:[d.strideHeight,d.strideWidth]},{type:"int32",data:[d.effectiveFilterHeight-1-d.padInfo.top,d.effectiveFilterWidth-1-d.padInfo.left]},{type:"int32",data:[d.dilationHeight,d.dilationWidth]},{type:"int32",data:[d.effectiveFilterHeight,d.effectiveFilterWidth]},{type:"int32",data:[d.outHeight]},{type:"int32",data:[d.outWidth]}];let y=a.runWebGPUProgram(g,[r,f],o.dtype,m);return a.disposeData(f.dataId),y}var hme={kernelName:wp,backendName:"webgpu",kernelFunc:cme};function mme(e){let{inputs:t,backend:a,attrs:n}=e,{filterSize:r,strides:s,pad:i,includeBatchInIndex:o}=n,{x:l}=t;v.assert(l.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${l.shape.length}.`);let u=[1,1];v.assert(C.eitherStridesOrDilationsAreOne(s,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${u}'`);let p=C.computePool2DInfo(l.shape,r,s,u,i),c=[{type:"int32",data:[p.strideHeight,p.strideWidth]},{type:"int32",data:[p.padInfo.top,p.padInfo.left]},{type:"int32",data:[p.dilationHeight,p.dilationWidth]},{type:"int32",data:[p.inHeight,p.inWidth]},{type:"int32",data:[p.effectiveFilterHeight,p.effectiveFilterWidth]}],d=new sp(p,"max",!1),h=a.runWebGPUProgram(d,[l],l.dtype,c);d=new sp(p,"max",!0,!0,o);let m=a.runWebGPUProgram(d,[l],"int32",c);return[h,m]}var fme={kernelName:Iu,backendName:"webgpu",kernelFunc:mme};function gme(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;return dl(r,s,i,"min",a)}var yme={kernelName:co,backendName:"webgpu",kernelFunc:gme},xme=aa({opType:Pe.MIN,cpuKernelImpl:Fde}),Ame={kernelName:ho,backendName:"webgpu",kernelFunc:xme},bme=class{constructor(e,t,a){this.uniforms="",this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=t.map((n,r)=>n[0]+e[r]+n[1]),this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.xShape=e,t.map((n,r)=>{this.uniforms+=` pad${r} : vec2<i32>,`}),this.offset=a==="reflect"?0:1,this.shaderKey=`mirrorPad_${a}`}getUserCode(){let e=this.xShape.length,t=this.xShape.map((l,u)=>`uniforms.pad${u}[0]`).join(","),a=this.xShape.map((l,u)=>`uniforms.pad${u}[0] + uniforms.xShape${e>1?`[${u}]`:""}`).join(","),n=e===1?"start":"start[i]",r=e===1?"end":"end[i]",s=e===1?"outC":"outC[i]",i=Pt(e),o=e>1?["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,e):"coords";return`
      ${ue("index")} {
        if (index < uniforms.size) {
          let start = ${i}(${t});
          let end = ${i}(${a});
          var outC = getCoordsFromIndex(index);
          for (var i = 0; i < ${e}; i = i + 1) {
            if (${s} < ${n}) {
              ${s} = ${n} * 2 - ${s} - ${this.offset};
            } else if(${s} >= ${r}) {
              ${s} = (${r} - 1) * 2 - ${s} + ${this.offset};
            }
          }
          let coords = outC - start;
          setOutputAtIndex(index, getX(${o}));
        }
      }
    `}},vme={kernelName:mo,backendName:"webgpu",kernelFunc:({inputs:e,attrs:t,backend:a})=>{let{x:n}=e,{paddings:r,mode:s}=t,i=a,o=r.map(u=>({type:"int32",data:[u[0],u[1]]})),l=new bme(n.shape,r,s);return i.runWebGPUProgram(l,[n],n.dtype,o)}},wme=aa({opType:Pe.MOD}),kme={kernelName:fo,backendName:"webgpu",kernelFunc:wme},Ime=class{constructor(e,t){this.variableNames=["probs"],this.outputShape=[],this.uniforms="seed : f32, numOutcomes: i32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=[e,t],this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="multinomial"}getUserCode(){return`
    //Based on the work of Dave Hoskins
    //https://www.shadertoy.com/view/4djSRW
    fn random (seed : f32, resultUV : vec2<f32>) -> f32 {
      let HASHSCALE1 = 443.8975;
      let p = resultUV * seed;
      var p3  = fract(vec3<f32>(p.xyx) * HASHSCALE1);
      p3 = p3 + dot(p3, p3.yzx + 19.19);
      return fract((p3.x + p3.y) * p3.z);
    }

    ${ue("index")} {
      if (index < uniforms.size) {
        let coords = getOutputCoords();
        let batch = coords[0];

        let resUV = vec2<f32>(f32(coords[1]) / f32(uniforms.outShape[1]),
            f32(coords[0]) / f32(uniforms.outShape[0]));
        let r = random(uniforms.seed, resUV);
        var cdf = 0.0;
        for (var i = 0; i < uniforms.numOutcomes - 1; i = i + 1) {
          cdf = cdf + getProbs(batch, i);

          if (r < cdf) {
            setOutputAtIndexI32(index, i);
            return;
          }
        }

        // If no other event happened, last event happened.
        setOutputAtIndexI32(index, uniforms.numOutcomes - 1);
      }
    }
  `}},Sme=class{constructor(e){this.variableNames=["logits"],this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=[this.outputShape[0],1,1],this.outputShape[1]>=4096?this.workgroupSize=[256,1,1]:this.workgroupSize=[64,1,1],this.shaderKey="softmax"}getUserCode(){return`
    var<workgroup> buf : array<f32, ${this.workgroupSize[0]}>;
    var<workgroup> rowMaxShared : f32;
    var<workgroup> rowSumShared : f32;
    const blockSize = ${this.workgroupSize[0]};
    ${ue("index")} {
      let row = index / blockSize;
      let tid = i32(localId.x);
      let cols = uniforms.outShape[1];

      var threadMax = -3.402823e+38f;
      for (var col = tid; col < cols; col += blockSize) {
        let value = getLogits(row, col);
        threadMax = max(threadMax, value);
      }
      if (tid < cols) {
        buf[tid] = threadMax;
      }
      workgroupBarrier();

      var reduceSize = min(cols, blockSize);
      for (var currSize = reduceSize >> 1;  currSize > 0; currSize = reduceSize >> 1) {
        reduceSize = currSize + (reduceSize & 1);
        if (tid < currSize) {
          buf[tid] = max(buf[tid], buf[tid + reduceSize]);
        }
        workgroupBarrier();
      }

      if (tid == 0) {
        rowMaxShared = buf[0];
      }
      workgroupBarrier();

      var threadSum = 0.0;
      for (var col = tid; col < cols; col += blockSize) {
        let subExp = exp(getLogits(row, col) - rowMaxShared);
        threadSum += subExp;
      }
      buf[tid] = threadSum;
      workgroupBarrier();

      for (var currSize = blockSize >> 1;  currSize > 0; currSize = currSize >> 1) {
        if (tid < currSize) {
          buf[tid] = buf[tid] + buf[tid + currSize];
        }
        workgroupBarrier();
      }

      if (tid == 0) {
        rowSumShared = buf[0];
      }
      workgroupBarrier();

      for (var col = tid; col < cols; col += blockSize) {
        let value = exp(getLogits(row, col) - rowMaxShared) / rowSumShared;
        setOutputAtCoords(row, col, value);
      }
  }
    `}};function Xk(e){let{inputs:t,backend:a,attrs:n}=e,{logits:r}=t,{dim:s}=n,i=ke({inputs:{x:r},backend:a,attrs:{shape:[v.sizeFromShape(r.shape)/r.shape[s],r.shape[s]]}}),o=new Sme(i.shape),l=a.runWebGPUProgram(o,[i],r.dtype),u=ke({inputs:{x:l},backend:a,attrs:{shape:r.shape}});return a.disposeData(i.dataId),a.disposeData(l.dataId),u}var Cme={kernelName:Ho,backendName:"webgpu",kernelFunc:Xk};function Tme(e){let{inputs:t,backend:a,attrs:n}=e,{logits:r}=t,{numSamples:s,seed:i,normalized:o}=n,l=o?r:Xk({inputs:{logits:r},backend:a,attrs:{dim:r.shape.length-1}}),u=l.shape[0],p=l.shape[1],c=new Ime(u,s),d=[{type:"float32",data:[i]},{type:"int32",data:[p]}],h=a.runWebGPUProgram(c,[l],"int32",d);return o||a.disposeData(l.dataId),h}var Nme={kernelName:go,backendName:"webgpu",kernelFunc:Tme};function Rme(e){let{inputs:t,backend:a}=e,{x:n}=t;if(a.shouldExecuteOnCPU([n])){let s=a.tensorMap.get(n.dataId),[i,o]=Ode(s.values,n.shape,n.dtype);return a.makeTensorInfo(o,n.dtype,i)}let r=new td(n.shape,le.NEG);return a.runWebGPUProgram(r,[n],n.dtype)}var Eme={kernelName:Su,backendName:"webgpu",kernelFunc:Rme};function Mme(e){console.warn("tf.nonMaxSuppression() in webgpu locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:a,attrs:n}=e,{boxes:r,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l}=n,u=a.readSync(r.dataId),p=a.readSync(s.dataId),{selectedIndices:c}=En.nonMaxSuppressionV3Impl(u,p,i,o,l);return a.makeTensorInfo([c.length],"int32",new Int32Array(c))}var $me={kernelName:Ao,backendName:"webgpu",kernelFunc:Mme};function Pme(e){console.warn("tf.nonMaxSuppression() in webgpu locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:a,attrs:n}=e,{boxes:r,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,softNmsSigma:u}=n,p=a.readSync(r.dataId),c=a.readSync(s.dataId),d=i,h=o,m=l,f=u,{selectedIndices:g,selectedScores:y}=En.nonMaxSuppressionV5Impl(p,c,d,h,m,f);return[a.makeTensorInfo([g.length],"int32",new Int32Array(g)),a.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var _me={kernelName:bo,backendName:"webgpu",kernelFunc:Pme},Fme=class{constructor(e,t){this.variableNames=["x"],this.uniforms="onValue : f32, offValue : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=[e,t],this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="onehot"}getUserCode(){return`
      ${ue("index")} {
        if(index < uniforms.size) {
          let coords = getCoordsFromIndex(index);
          setOutputAtIndex(index, mix(uniforms.offValue, uniforms.onValue,
                                      f32(i32(round(getX(coords.x))) == coords.y)));
        }
      }
    `}};function Dme(e){let{inputs:t,backend:a,attrs:n}=e,{indices:r}=t,{dtype:s,depth:i,onValue:o,offValue:l}=n,u=v.sizeFromShape(r.shape),p=new Fme(u,i),c=ke({inputs:{x:r},backend:a,attrs:{shape:[u]}}),d=[{type:"float32",data:[o]},{type:"float32",data:[l]}],h=a.runWebGPUProgram(p,[c],s,d);a.disposeData(c.dataId);let m=[...r.shape,i],f=ke({inputs:{x:h},backend:a,attrs:{shape:m}});return a.disposeData(h.dataId),f}var Ome={kernelName:vo,backendName:"webgpu",kernelFunc:Dme};function Rh(e){let{inputs:t,backend:a}=e,{x:n}=t;if(n.dtype==="complex64"){let r=tc({inputs:{input:n},backend:a}),s=Rh({inputs:{x:r},backend:a}),i=h0({inputs:{input:n},backend:a}),o=Rh({inputs:{x:i},backend:a}),l=ul({inputs:{real:s,imag:o},backend:a});return a.disposeData(r.dataId),a.disposeData(s.dataId),a.disposeData(i.dataId),a.disposeData(o.dataId),l}else return Wa({attrs:{shape:n.shape,dtype:n.dtype,value:n.dtype==="string"?"":0},backend:a})}var zme={kernelName:Vu,backendName:"webgpu",kernelFunc:Rh};function Kk(e){let{inputs:t,backend:a}=e,{x:n}=t;if(n.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(n.dtype==="complex64"){let r=tc({inputs:{input:n},backend:a}),s=Kk({inputs:{x:r},backend:a}),i=h0({inputs:{input:n},backend:a}),o=Rh({inputs:{x:i},backend:a}),l=ul({inputs:{real:s,imag:o},backend:a});return a.disposeData(r.dataId),a.disposeData(s.dataId),a.disposeData(i.dataId),a.disposeData(o.dataId),l}else return Wa({attrs:{shape:n.shape,dtype:n.dtype,value:1},backend:a})}var Lme={kernelName:Tu,backendName:"webgpu",kernelFunc:Kk};function Wme(e){let{inputs:t,backend:a,attrs:n}=e,{axis:r}=n;if(t.length===1)return Y1({inputs:{input:t[0]},backend:a,attrs:{dim:r}});let s=t[0].shape,i=t[0].dtype;t.forEach(p=>{v.assertShapesMatch(s,p.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===p.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(p=>{let c=Y1({inputs:{input:p},backend:a,attrs:{dim:r}});return o.push(c),c}),u=zk({inputs:l,backend:a,attrs:{axis:r}});return o.forEach(p=>a.disposeData(p.dataId)),u}var Bme={kernelName:Nu,backendName:"webgpu",kernelFunc:Wme};function Yk(e,t=!1){let a=e.length,n=Pt(a),r=e.map((c,d)=>`uniforms.pad${d}[0]`).join(","),s=e.map((c,d)=>`uniforms.pad${d}[0] + uniforms.xShape${a>1?`[${d}]`:""}`).join(","),i=a>1?`${n}(${r})`:`${r}`,o=a>1?`${n}(${s})`:`${s}`,l=a>1?"any(paddedCoords < start)":"paddedCoords < start",u=a>1?"any(paddedCoords >= end)":"paddedCoords >= end",p=a>1?["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,a):"coords";return`
        let start = ${i};
        let end = ${o};
        if (${l} || ${u}) {
          setOutputAtIndex(index, ${t?0:"uniforms.constantValue"});
        } else {
          let coords = paddedCoords - start;
          setOutputAtIndex(index, getX(${p}));
        }
  `}var Vme=class{constructor(e,t){this.variableNames=["x"],this.uniforms="constantValue : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=t.map((a,n)=>a[0]+e[n]+a[1]),this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),t.map((a,n)=>{this.uniforms+=` pad${n} : vec2<i32>,`}),this.xShape=e,this.shaderKey="pad"}getUserCode(){return`
      ${ue("index")} {
        if (index < uniforms.size) {
          let paddedCoords = getCoordsFromIndex(index);
          ${Yk(this.xShape)}
        }
      }
    `}},Ume=e=>{let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{paddings:s,constantValue:i}=n;if(s.every(u=>v.arraysEqual(u,[0,0])))return tn({inputs:{x:r},backend:a});if(v.sizeFromShape(r.shape)===0){let u=s.map((p,c)=>p[0]+r.shape[c]+p[1]);return Wa({backend:a,attrs:{shape:u,value:i,dtype:r.dtype}})}let o=[{type:"float32",data:[i]}];s.map(u=>o.push({type:"int32",data:[u[0],u[1]]}));let l=new Vme(r.shape,s);return a.runWebGPUProgram(l,[r],r.dtype,o)},Gme={kernelName:wo,backendName:"webgpu",kernelFunc:Ume},Hme=aa({opType:Pe.POW}),jme={kernelName:ko,backendName:"webgpu",kernelFunc:Hme};function qme(e){let{inputs:t,backend:a}=e,{x:n,alpha:r}=t,s=new Th(Pe.PRELU,n.shape,r.shape);return a.runWebGPUProgram(s,[n,r],"float32")}var Xme={kernelName:Io,backendName:"webgpu",kernelFunc:qme};function Kme(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;return dl(r,s,i,"prod",a)}var Yme={kernelName:So,backendName:"webgpu",kernelFunc:Kme},Zme=e=>{let{backend:t,attrs:a}=e,{start:n,stop:r,step:s,dtype:i}=a,o=Wde(n,r,s,i);return t.makeTensorInfo([o.length],i,o)},Jme={kernelName:Ru,backendName:"webgpu",kernelFunc:Zme},Qme=aa({opType:Pe.DIV}),efe={kernelName:_i,backendName:"webgpu",kernelFunc:Qme},tfe=at({opType:le.RECIPROCAL}),afe={kernelName:Co,backendName:"webgpu",kernelFunc:tfe},nfe=at({opType:le.RELU}),rfe={kernelName:To,backendName:"webgpu",kernelFunc:nfe},sfe=at({opType:le.RELU6}),ife={kernelName:Eo,backendName:"webgpu",kernelFunc:sfe},ofe=class{constructor(e,t,a){this.variableNames=["x"],this.uniforms="adjustHeightWidth : vec2<f32>, halfPixelCenters : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=[e[0],t,a,e[3]],this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="resizeBilinear"}getUserCode(){return`
      ${ue("index")} {
        if (index < uniforms.size) {
        let coords = getCoordsFromIndex(index);
          let b = coords[0];
          let d = coords[3];
          let rc = coords.yz;

          let effectiveInSize = vec2<f32>(
            f32(uniforms.xShape.y) - uniforms.adjustHeightWidth[0],
            f32(uniforms.xShape.z) - uniforms.adjustHeightWidth[1]);

          let effectiveOutSize = vec2<f32>(
            f32(uniforms.outShape.y) - uniforms.adjustHeightWidth[0],
            f32(uniforms.outShape.z) - uniforms.adjustHeightWidth[1]);

          let effectiveInputOverOutputRatioRC =
              effectiveInSize / effectiveOutSize;

          // Fractional source index
          let sourceFracIndexRC =
            (vec2<f32>(rc) + vec2<f32>(uniforms.halfPixelCenters)) *
            effectiveInputOverOutputRatioRC - vec2<f32>(uniforms.halfPixelCenters);

          // Compute the four integer indices.
          let sourceFloorRC = vec2<i32>(sourceFracIndexRC);
          let sourceCeilRC = vec2<i32>(
            min(vec2<f32>(uniforms.xShape.yz) - vec2<f32>(1.0), ceil(sourceFracIndexRC)));

          let topLeft = getX(b, sourceFloorRC.x, sourceFloorRC.y, d);
          let bottomLeft = getX(b, sourceCeilRC.x, sourceFloorRC.y, d);
          let topRight = getX(b, sourceFloorRC.x, sourceCeilRC.y, d);
          let bottomRight = getX(b, sourceCeilRC.x, sourceCeilRC.y, d);

          let fracRC = sourceFracIndexRC - vec2<f32>(sourceFloorRC);

          let top = topLeft + (topRight - topLeft) * fracRC.y;
          let bottom = bottomLeft + (bottomRight - bottomLeft) * fracRC.y;
          let newValue = top + (bottom - top) * fracRC.x;

          setOutputAtIndex(index, newValue);
        }
      }
    `}};function lfe(e){let{inputs:t,backend:a,attrs:n}=e,{images:r}=t,{alignCorners:s,size:i,halfPixelCenters:o}=n,[l,u]=i,p=s&&l>1?1:0,c=s&&u>1?1:0,d=[{type:"float32",data:[p,c]},{type:"float32",data:[o?.5:0]}],h=new ofe(r.shape,l,u);return a.runWebGPUProgram(h,[r],"float32",d)}var ufe={kernelName:Ro,backendName:"webgpu",kernelFunc:lfe},dfe=class{constructor(e,t){this.variableNames=["dy"],this.uniforms=`effectiveXSize : vec2<i32>, effectiveYSize : vec2<i32>, heightScale : f32, widthScale : f32,
       invHeightScale : f32, invWidthScale : f32, winHeight : i32, winWidth : i32,`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.alignCorners=t,this.shaderKey=`resizeBilinearBackprop_${t}`}getUserCode(){return`
      ${ue("index")} {
        if (index < uniforms.size) {
          let coords = getOutputCoords();
          let b = coords[0];
          let d = coords[3];
          let r = coords[1];
          let c = coords[2];

          var accumulator = 0.0;

          // Compute bounds for where in dy we will look
          let startRLerp = floor(f32(r) * uniforms.invHeightScale);
          let startDyR = i32(startRLerp - f32(uniforms.winHeight / 2));

          let startCLerp = floor(f32(c) * uniforms.invWidthScale);
          let startDyC = i32(startCLerp - f32(uniforms.winWidth / 2));

          // Loop over dy
          for (var dyROffset = 0; dyROffset < uniforms.winHeight; dyROffset++) {
            let dyR = startDyR + dyROffset;

            // Guard against the window exceeding the bounds of dy
            if (dyR < 0 || dyR >= uniforms.dyShape[1]) {
              continue;
            }

            for (var dyCOffset = 0; dyCOffset < uniforms.winWidth; dyCOffset++) {
              let dyC = startDyC + dyCOffset;

              // Guard against the window exceeding the bounds of dy
              if (dyC < 0 || dyC >= uniforms.dyShape[2]) {
                continue;
              }

              let dxR = f32(dyR) * uniforms.heightScale;
              let topDxRIndex = i32(floor(dxR));
              let bottomDxRIndex = i32(min(ceil(dxR), f32(uniforms.outShape[1] - 1)));
              let dxRLerp = dxR - f32(topDxRIndex);
              let inverseDxRLerp = 1.0 - dxRLerp;

              let dxC = f32(dyC) * uniforms.widthScale;
              let leftDxCIndex = i32(floor(dxC));
              let rightDxCIndex = i32(min(ceil(dxC), f32(uniforms.outShape[2] - 1)));
              let dxCLerp = dxC - f32(leftDxCIndex);
              let inverseDxCLerp = 1.0 - dxCLerp;

              if (r == topDxRIndex && c == leftDxCIndex) {
                // topLeft
                accumulator +=
                  getDy(b, dyR, dyC, d) * inverseDxRLerp * inverseDxCLerp;
              }

              if (r == topDxRIndex && c == rightDxCIndex) {
                // topRight
                accumulator += getDy(b, dyR, dyC, d) * inverseDxRLerp * dxCLerp;
              }

              if (r == bottomDxRIndex && c == leftDxCIndex) {
                // bottomLeft
                accumulator += getDy(b, dyR, dyC, d) * dxRLerp * inverseDxCLerp;
              }

              if (r == bottomDxRIndex && c == rightDxCIndex) {
                // bottomRight
                accumulator += getDy(b, dyR, dyC, d) * dxRLerp * dxCLerp;
              }
            }
          }
          // End loop over dy

          setOutputAtIndex(index, accumulator);
        }
      }
    `}};function pfe(e){let{inputs:t,backend:a,attrs:n}=e,{images:r,dy:s}=t,{alignCorners:i}=n,[,o,l]=r.shape,[,u,p]=s.shape,c=[i&&u>1?o-1:o,i&&p>1?l-1:l],d=[i&&u>1?u-1:u,i&&p>1?p-1:p],h=c[0]/d[0],m=c[1]/d[1],f=1/h,g=1/m,y=Math.ceil(f)*2+2,x=Math.ceil(g)*2+2,A=new dfe(r.shape,i),b=[{type:"int32",data:c},{type:"int32",data:d},{type:"float32",data:[h]},{type:"float32",data:[m]},{type:"float32",data:[f]},{type:"float32",data:[g]},{type:"int32",data:[y]},{type:"int32",data:[x]}];return a.runWebGPUProgram(A,[s],s.dtype,b)}var cfe={kernelName:$u,backendName:"webgpu",kernelFunc:pfe},hfe=class{constructor(e,t,a,n){this.variableNames=["x"],this.uniforms="adjustHeightWidth : vec2<f32>, roundBase : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=[e[0],t,a,e[3]],this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.halfPixelCenters=n,this.shaderKey=`resizeNearest_${n}`}getUserCode(){let e;return this.halfPixelCenters?e="max((vec2<f32>(rc) + vec2<f32>(0.5)) * effectiveInputOverOutputRatioRC, vec2<f32>(0.0))":e="vec2<f32>(rc) * effectiveInputOverOutputRatioRC",`
      ${ue("index")} {
        if (index < uniforms.size) {
          let coords = getCoordsFromIndex(index);
          let b = coords[0];
          let d = coords[3];
          let rc = coords.yz;

          let effectiveInSize = vec2<f32>(
            f32(uniforms.xShape.y) - uniforms.adjustHeightWidth[0],
            f32(uniforms.xShape.z) - uniforms.adjustHeightWidth[1]);

          let effectiveOutSize = vec2<f32>(
            f32(uniforms.outShape.y) - uniforms.adjustHeightWidth[0],
            f32(uniforms.outShape.z) - uniforms.adjustHeightWidth[1]);

          let effectiveInputOverOutputRatioRC =
              effectiveInSize / effectiveOutSize;

          // Fractional source index
          let sourceFracIndexRC = ${e};

          // Compute the coordinators of nearest neighbor point.
          let inputShapeRC = vec2<f32>(f32(uniforms.xShape.y), f32(uniforms.xShape.z));
          let sourceNearestRC = vec2<i32>(
            min(inputShapeRC - 1.0, floor(sourceFracIndexRC + uniforms.roundBase)));
          let newValue = getX(b, sourceNearestRC.x, sourceNearestRC.y, d);

          setOutputAtIndex(index, newValue);
        }
      }
    `}};function mfe(e){let{inputs:t,backend:a,attrs:n}=e,{images:r}=t,{alignCorners:s,halfPixelCenters:i,size:o}=n,[l,u]=o,p=s&&l>1?1:0,c=s&&u>1?1:0,d=[{type:"float32",data:[p,c]},{type:"float32",data:[s?.5:0]}],h=new hfe(r.shape,l,u,i);return a.runWebGPUProgram(h,[r],r.dtype,d)}var ffe={kernelName:No,backendName:"webgpu",kernelFunc:mfe},gfe=class{constructor(e,t){this.variableNames=["dy"],this.uniforms=`effectiveXSize : vec2<i32>, effectiveYSize : vec2<i32>, invHeightScale : f32, invWidthScale : f32,
       winHeight : i32, winWidth : i32,`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.alignCorners=t,this.shaderKey=`resizeNearestNeigborBackprop_${t}`}getUserCode(){return`
      ${ue("index")} {
        if (index < uniforms.size) {
          let coords = getOutputCoords();
          let b = coords[0];
          let d = coords[3];
          let r = coords[1];
          let c = coords[2];

          var accumulator = 0.0;

          // Compute bounds for where in dy we will look
          let startRLerp = floor(f32(r) * uniforms.invHeightScale);
          let startDyR = i32(floor(startRLerp - f32(uniforms.winHeight / 2)));

          let startCLerp = floor(f32(c) * uniforms.invWidthScale);
          let startDyC = i32(floor(startCLerp - f32(uniforms.winWidth / 2)));

          // Loop over dy
          for (var dyROffset = 0; dyROffset < uniforms.winHeight; dyROffset++) {
            let dyR = startDyR + dyROffset;

            // Guard against the window exceeding the bounds of dy
            if (dyR < 0 || dyR >= uniforms.dyShape[1]) {
              continue;
            }

            for (var dyCOffset = 0; dyCOffset < uniforms.winWidth; dyCOffset++) {
              let dyC = startDyC + dyCOffset;

              // Guard against the window exceeding the bounds of dy
              if (dyC < 0 || dyC >= uniforms.dyShape[2]) {
                continue;
              }

              let sourceFracRow = f32(uniforms.effectiveXSize[0]) *
                  (f32(dyR) / f32(uniforms.effectiveYSize[0]));

              let sourceFracCol = f32(uniforms.effectiveXSize[1]) *
                  (f32(dyC) / f32(uniforms.effectiveYSize[1]));

              let sourceNearestRow =
                  i32(min(f32(uniforms.outShape[1] - 1),
                  ${this.alignCorners?"floor(sourceFracRow + 0.5)":"floor(sourceFracRow)"}));

              let sourceNearestCol =
                  i32(min(f32(uniforms.outShape[2] - 1),
                  ${this.alignCorners?"floor(sourceFracCol + 0.5)":"floor(sourceFracCol)"}));

              if (r == sourceNearestRow && c == sourceNearestCol) {
                accumulator += getDy(b, dyR, dyC, d);
              }
            }
          }
          // End loop over dy

          setOutputAtIndex(index, accumulator);
        }
      }
    `}};function yfe(e){let{inputs:t,backend:a,attrs:n}=e,{images:r,dy:s}=t,{alignCorners:i}=n,[,o,l]=r.shape,[,u,p]=s.shape,c=[i&&u>1?o-1:o,i&&p>1?l-1:l],d=[i&&u>1?u-1:u,i&&p>1?p-1:p],h=c[0]/d[0],m=c[1]/d[1],f=1/h,g=1/m,y=Math.ceil(f)*2+2,x=Math.ceil(g)*2+2,A=new gfe(r.shape,i),b=[{type:"int32",data:c},{type:"int32",data:d},{type:"float32",data:[f]},{type:"float32",data:[g]},{type:"int32",data:[y]},{type:"int32",data:[x]}];return a.runWebGPUProgram(A,[s],s.dtype,b)}var xfe={kernelName:Mu,backendName:"webgpu",kernelFunc:yfe},Afe=class{constructor(e){this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.uniforms=" axis : vec4<i32>,",this.shaderKey="reverse"}getUserCode(){return`
      
      // Using uniform variables as judging conditions, so the function has
      // coherent execution within all threads.
      fn getReverseCoords(coords : vec4<i32>) -> vec4<i32> {
        var reverseCoords = coords;
        if (uniforms.axis[0] == 1) {
          reverseCoords[0] = uniforms.xShape[0] - coords[0] - 1;
        }
        if (uniforms.axis[1] == 1) {
          reverseCoords[1] = uniforms.xShape[1] - coords[1] - 1;
        }
        if (uniforms.axis[2] == 1) {
          reverseCoords[2] = uniforms.xShape[2] - coords[2] - 1;
        }
        if (uniforms.axis[3] == 1) {
          reverseCoords[3] = uniforms.xShape[3] - coords[3] - 1;
        }

        return reverseCoords;
      }
    
      ${ue("index")} {
        if (index < uniforms.size) {
          let coords = getCoordsFromIndex(index);
          let reverseCoords = getReverseCoords(coords);
          setOutputAtIndex(index, getX(reverseCoords[0],
              reverseCoords[1], reverseCoords[2], reverseCoords[3]));
        }
      }
    `}};function bfe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{dims:s}=n,i=r.shape.length;if(i===0)return tn({inputs:{x:r},backend:a});let o=r.shape,l=[1,1,1,1];o.forEach((g,y)=>{let x=y+4-i;l[x]=g});let u=v.parseAxisParam(s,r.shape),p=[0,0,0,0];u.forEach(g=>{let y=g+4-i;p[y]=1});let c=[{type:"int32",data:p}],d=ke({inputs:{x:r},backend:a,attrs:{shape:l}}),h=new Afe(l),m=a.runWebGPUProgram(h,[d],d.dtype,c);a.disposeData(d.dataId);let f=ke({inputs:{x:m},backend:a,attrs:{shape:o}});return a.disposeData(m.dataId),f}var vfe={kernelName:Mo,backendName:"webgpu",kernelFunc:bfe},wfe=class{constructor(e,t){this.outputShape=[],this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.uniforms=`centerX : f32, centerY : f32, sinRadians : f32,
          cosRadians : f32,`,this.shaderKey="rotate",this.outputShape=e,typeof t=="number"?(this.uniforms+=" fillValue : f32,",this.fillSnippet="var outputValue = uniforms.fillValue;",this.shaderKey+="_float"):(this.uniforms+=" fillValue : vec3<f32>,",this.fillSnippet="var outputValue = uniforms.fillValue[coords[3]];",this.shaderKey+="_vec3")}getUserCode(){return`
        ${ue("index")} {
          if (index < uniforms.size) {
            let coords = getCoordsFromIndex(index);
            let coordXFloat = (f32(coords[2]) - uniforms.centerX) *
                uniforms.cosRadians - (f32(coords[1]) - uniforms.centerY) *
                uniforms.sinRadians;
            let coordYFloat = (f32(coords[2]) - uniforms.centerX) *
                uniforms.sinRadians + (f32(coords[1]) - uniforms.centerY) *
                uniforms.cosRadians;
            let coordX = i32(round(coordXFloat + uniforms.centerX));
            let coordY = i32(round(coordYFloat + uniforms.centerY));
            ${this.fillSnippet}
            if(coordX >= 0 && coordX < uniforms.xShape[2] && coordY >= 0 &&
                coordY < uniforms.xShape[1]) {
              outputValue = getX(coords[0], coordY, coordX, coords[3]);
            }
            setOutputAtIndex(index, outputValue);
          }
        }
      `}},kfe={kernelName:el,backendName:"webgpu",kernelFunc:({inputs:e,attrs:t,backend:a})=>{let{image:n}=e,{radians:r,fillValue:s,center:i}=t,o=a,l=new wfe(n.shape,s),[u,p]=C.getImageCenter(i,n.shape[1],n.shape[2]),c=[{type:"float32",data:[u]},{type:"float32",data:[p]},{type:"float32",data:[Math.sin(r)]},{type:"float32",data:[Math.cos(r)]}];return typeof s=="number"?c.push({type:"float32",data:[Number.parseFloat(s.toFixed(2))]}):c.push({type:"float32",data:s}),o.runWebGPUProgram(l,[n],n.dtype,c)}},Ife=at({opType:le.ROUND}),Sfe={kernelName:$o,backendName:"webgpu",kernelFunc:Ife},Cfe=at({opType:le.RSQRT,cpuKernelImpl:Bde}),Tfe={kernelName:Po,backendName:"webgpu",kernelFunc:Cfe},zd=class{constructor(e,t,a,n,r,s,i,o=!0){this.variableNames=["updates","indices"],this.workgroupSize=[64,1,1],this.atomic=!0,this.outputShape=s,this.type=i,this.sumDupeIndices=o,this.dispatchLayout=me(e),this.dispatch=de(this.dispatchLayout,e,this.workgroupSize),this.sliceDimGreaterThanOne=t>1,this.shaderKey=`scatter_${a}_${n}_${this.sliceDimGreaterThanOne}_${i}_${o}_${r.length}`;let l=Pt(r.length);this.uniforms=`sliceDim : i32, strides: ${l}, updatesSize: i32,`,this.updatesRank=n,this.indicesRank=a}getUserCode(){let e="";this.indicesRank===1?e="coords[0]":this.indicesRank===2&&(e="coords[0], j");let t=`getIndices(${e})`,a=this.sliceDimGreaterThanOne?"uniforms.strides[j]":"uniforms.strides",n="",r="";this.dispatchLayout.x.length===1?(n="flattenedIndex",r=`
      fn getUpdatesCoordsFromFlatIndex(index : i32) -> i32 {
        return index;
      }
      `):this.dispatchLayout.x.length===2&&(n="vec2<i32>(flattenedIndex, coords[1])",r=`
      fn getUpdatesCoordsFromFlatIndex(index : i32) -> vec2<i32> {
        // N.B. |updates| could be a scalar tensor, conceptually representing a
        // 2D tensor with all values equal to that. By design, its size must be
        // the same as |outShape[1]| in one dimension, and |indicesShape[0]|
        // gives the other.
        let sliceSize = uniforms.outShape[1];
        let d0 = index / sliceSize;
        let d1 = index - d0 * sliceSize;
        return vec2<i32>(d0, d1);
      }
      `);let s=`getUpdates(${Array.from({length:this.updatesRank},(i,o)=>`coords[${o}]`).join(", ")})`;return`
    ${r}
      ${ue("index")} {
        if (index < uniforms.updatesSize) {
          let coords = getUpdatesCoordsFromFlatIndex(index);
          var flattenedIndex = 0;
          for (var j = 0; j < uniforms.sliceDim; j = j + 1) {
            let indexInside = i32(round(${t}));
            flattenedIndex = flattenedIndex + indexInside * ${a};
          }
          let updateValue =
              ${Hs(this.type)}(${s});
          let flatIndex = getOutputIndexFromCoords(${n});

          ${this.sumDupeIndices?xs("&result[flatIndex]","updateValue",this.type):"atomicStore(&result[flatIndex], bitcast<i32>(updateValue));"}
        }
      }`}};function Nfe(e){let{inputs:t,backend:a,attrs:n}=e,{indices:r,updates:s}=t,{shape:i}=n,{sliceRank:o,numUpdates:l,sliceSize:u,strides:p,outputSize:c}=C.calculateShapes(s,r,i),d=[c/u,u];if(c===0)return a.makeTensorInfo(i,r.dtype);let h=ke({inputs:{x:r},backend:a,attrs:{shape:[l,o]}}),m=ke({inputs:{x:s},backend:a,attrs:{shape:[l,u]}}),f=m.dtype,g=Wa({backend:a,attrs:{shape:d,value:0,dtype:f}}),y=v.sizeFromShape(m.shape),x=[{type:"int32",data:[o]},{type:"int32",data:p},{type:"int32",data:[y]}],A=new zd(m.shape,o,h.shape.length,m.shape.length,p,d,f),b=a.runWebGPUProgram(A,[m,h],f,x,g),w=ke({inputs:{x:b},backend:a,attrs:{shape:i}});return a.disposeData(h.dataId),a.disposeData(m.dataId),a.disposeData(b.dataId),w}var Rfe={kernelName:_o,backendName:"webgpu",kernelFunc:Nfe},Efe=class{constructor(e,t){this.outputShape=[],this.variableNames=["sortedSequence","values"],this.uniforms="numInputs : i32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.side=t,this.shaderKey=`search_sorted_${t}`}getUserCode(){return`
      fn findBound(batch: i32, value: f32) -> i32 {
        var left = i32(0);
        var right = uniforms.numInputs;
        while (left < right) {
          var mid = (left + right) / 2;
          if (getSortedSequence(batch, mid) ${this.side==="left"?"<":"<="} value) {
            left = mid + 1;
          } else {
            right = mid;
          }
        }
        return right;
      }

      ${ue("index")} {
        if (index < uniforms.size) {
          let coords = getCoordsFromIndex(index);
          let value = getValuesByOutputIndex(index);
          setOutputAtIndexI32(index, findBound(coords[0], value));
        }
      }
    `}};function Mfe(e){let{inputs:t,backend:a,attrs:n}=e,{sortedSequence:r,values:s}=t,{side:i}=n,o=new Efe([s.shape[0],s.shape[1]],i),l=[{type:"int32",data:[r.shape[1]]}];return a.runWebGPUProgram(o,[r,s],"int32",l)}var $fe={kernelName:Do,backendName:"webgpu",kernelFunc:Mfe},Pfe=class{constructor(e,t,a){this.variableNames=["c","a","b"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.cRank=e,this.rank=a,this.shaderKey="select"}getUserCode(){let e,t;if(this.rank>4)throw Error(`Where for rank ${this.rank} is not yet supported`);if(this.rank===1)t="resRC",e="resRC";else{let a=["resRC.x","resRC.y","resRC.z","resRC.w"],n=[],r=[];for(let s=0;s<this.outputShape.length;s++)r.push(`${a[s]}`),s<this.cRank&&n.push(`${a[s]}`);e=n.join(),t=r.join()}return`
      ${ue("index")} {
        if (index < uniforms.size) {
          let resRC = getCoordsFromIndex(index);
          let cVal = getC(${e});
          if (cVal >= 1.0) {
            setOutputAtIndex(index, getA(${t}));
          } else {
            setOutputAtIndex(index, getB(${t}));
          }
        }
      }
    `}};function _fe(e){let{inputs:t,backend:a}=e,{condition:n,t:r,e:s}=t,i=new Pfe(n.shape.length,r.shape,r.shape.length);return a.runWebGPUProgram(i,[n,r,s],ca(r.dtype,s.dtype))}var Ffe={kernelName:Pu,backendName:"webgpu",kernelFunc:_fe},Dfe=at({opType:le.SELU}),Ofe={kernelName:Oo,backendName:"webgpu",kernelFunc:Dfe},zfe=at({opType:le.SIGMOID}),Lfe={kernelName:Bo,backendName:"webgpu",kernelFunc:zfe},Wfe=at({opType:le.SIGN}),Bfe={kernelName:Wo,backendName:"webgpu",kernelFunc:Wfe},Vfe=at({opType:le.SIN}),Ufe={kernelName:zo,backendName:"webgpu",kernelFunc:Vfe},Gfe=at({opType:le.SINH}),Hfe={kernelName:Lo,backendName:"webgpu",kernelFunc:Gfe},jfe=at({opType:le.SOFTPLUS}),qfe={kernelName:Vo,backendName:"webgpu",kernelFunc:jfe},Xfe=class{constructor(e,t,a,n,r,s){this.variableNames=["x"],this.outputShape=[],this.uniforms="",this.workgroupSize=[64,1,1],this.size=!0;let i=new Array(n.length);for(let o=0;o<i.length;o++)i[o]=n[r[o]];this.outputShape=i,this.newDim=r,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.xShape=e,this.paddedXShape=t,this.uniforms+=`reshapedPaddedXShape : ${Pt(n.length)}, paddedXShapeStrides : ${Pt(s)}, `,a.map((o,l)=>{this.uniforms+=` pad${l} : vec2<i32>,`}),this.shaderKey=`spaceToBatchND_${r}`}getUserCode(){let e=Pt(this.outputShape.length),t=Mk(this.newDim);return`
      ${lh(this.paddedXShape,"PaddedX")}
      ${ue("index")} {
        if(index < uniforms.size) {
          let coords = getCoordsFromIndex(index);
          let switchedIndex = getIndexFromCoords${this.outputShape.length}D(${e}(${t}), uniforms.reshapedPaddedXShape);
          let paddedCoords = getPaddedXCoordsFromIndex(switchedIndex);
          ${Yk(this.xShape,!0)}
        }
      }
    `}},Kfe=e=>{let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockShape:s,paddings:i}=n;v.assert(r.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGPU backend not implemented yet");let o=s.reduce((x,A)=>x*A),l=[[0,0]];l.push(...i);for(let x=1+s.length;x<r.shape.length;++x)l.push([0,0]);let u=l.map((x,A)=>x[0]+r.shape[A]+x[1]),p=C.getReshaped(u,s,o,!1),c=C.getPermuted(p.length,s.length,!1),d=C.getReshapedPermuted(u,s,o,!1),h=v.computeStrides(u),m=new Xfe(r.shape,u,l,p,c,h.length),f=[{type:"int32",data:p},{type:"int32",data:h}];l.map(x=>f.push({type:"int32",data:[x[0],x[1]]}));let g=a.runWebGPUProgram(m,[r],r.dtype,f),y=ke({inputs:{x:g},backend:a,attrs:{shape:d}});return a.disposeData(g.dataId),y},Yfe={kernelName:Fu,backendName:"webgpu",kernelFunc:Kfe},Zfe=class{constructor(e,t,a){this.variableNames=["input","indices","segmentIds"],this.outputShape=[],this.uniforms="segmentSize : i32, sparseSize : i32,",this.workgroupSize=[64,1,1],this.atomic=!0,this.outputShape=e,this.type=a,this.dispatchLayout=me([t]),this.dispatch=de(this.dispatchLayout,[t],this.workgroupSize),this.shaderKey="sparseSegmentSum"}getUserCode(){return`
    ${ue("index")} {
      if (index < uniforms.sparseSize) {
        let indexInSegmentIds = index / uniforms.segmentSize;
        let indexInSegment = index % uniforms.segmentSize;
        let indexInInput = indices[indexInSegmentIds];
        let segmentId = segmentIds[indexInSegmentIds];

        let value = input[indexInInput * uniforms.segmentSize + indexInSegment];
        let outIndex = segmentId * uniforms.segmentSize + indexInSegment;
        ${xs("&result[outIndex]","value",this.type)}
      }
    }
  `}},Jfe=class{constructor(e,t){this.variableNames=["segmentIds"],this.outputShape=[],this.workgroupSize=[64,1,1],this.atomic=!0,this.outputShape=[e],this.dispatchLayout=me(t),this.dispatch=de(this.dispatchLayout,t,this.workgroupSize),this.shaderKey="sparseSegmentIdCountProgram"}getUserCode(){return`
    ${ue("index")} {
      if (index < uniforms.segmentIdsShape) {
        let segmentId = segmentIds[index];
        ${xs("&result[segmentId]","1","int32")}
      }
    }
  `}},Qfe=class{constructor(e,t){this.variableNames=["segmentSum","sameSegmentIdCount"],this.outputShape=[],this.uniforms="segmentSize : i32",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.type=t,this.dispatchLayout=me(e),this.dispatch=de(this.dispatchLayout,e,this.workgroupSize),this.shaderKey="sparseSegmentMean"}getUserCode(){return`
    ${ue("index")} {
      if (index < uniforms.size) {
        let segmentId = index / uniforms.segmentSize;
        let count = sameSegmentIdCount[segmentId];
        if (count != 0) {
          ${this.type==="float32"?"setOutputAtIndex(index, segmentSum[index] / f32(count));":"setOutputAtIndexI32(index, segmentSum[index] / count);"}
        }
      }
    }
  `}};function Zk(e,t,a,n=!1,r){let s=v.sizeFromShape(e.shape)/e.shape[0],i=e.dtype,o=v.sizeFromShape(t.shape),l=r.readSync(a.dataId),u=o>0?l[o-1]+1:0,p,c=e.shape.slice();c[0]=u;let d=o*s,h=Wa({backend:r,attrs:{shape:c,value:0,dtype:i}});p=new Zfe(c,d,i);let m=[{type:"int32",data:[s]},{type:"int32",data:[d]}],f=r.runWebGPUProgram(p,[e,t,a],i,m,h);if(n)return f;let g=Wa({backend:r,attrs:{shape:[u],value:0,dtype:"int32"}});p=new Jfe(u,a.shape);let y=r.runWebGPUProgram(p,[a],"int32",null,g),x=Wa({backend:r,attrs:{shape:c,value:0,dtype:i}});p=new Qfe(c,i),m=[{type:"int32",data:[s]}];let A=r.runWebGPUProgram(p,[f,y],i,m,x);return r.disposeData(f.dataId),r.disposeData(y.dataId),A}function e2e(e){let{inputs:t,backend:a}=e,{data:n,indices:r,segmentIds:s}=t;return Zk(n,r,s,!1,a)}var t2e={kernelName:zu,backendName:"webgpu",kernelFunc:e2e};function a2e(e){let{inputs:t,backend:a}=e,{data:n,indices:r,segmentIds:s}=t;return Zk(n,r,s,!0,a)}var n2e={kernelName:Lu,backendName:"webgpu",kernelFunc:a2e},r2e=class{constructor(e,t){this.variableNames=["A"],this.workgroupSize=[64,1,1],this.size=!0;let a=new Array(e.length);for(let n=0;n<a.length;n++)a[n]=e[n]*t[n];this.outputShape=a,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.rank=this.outputShape.length,this.shaderKey="tile"}getUserCode(){let e=s2e(this.rank,"uniforms.");return`
      ${ue("index")} {
        if (index < uniforms.size) {
          let resRC = getCoordsFromIndex(index);
          setOutputAtIndex(index, getA(${e}));
        }
      }
    `}};function s2e(e,t=""){if(e>=5)throw Error(`Tile for rank ${e} is not yet supported`);if(e===1)return`(resRC % ${t}aShape)`;let a=["resRC.x","resRC.y","resRC.z","resRC.w"],n=[];for(let r=0;r<e;r++)n.push(`(${a[r]} % ${t}aShape[${r}])`);return n.join()}function J3(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{reps:s}=n;if(a.shouldExecuteOnCPU([r])||r.dtype==="string"||r.shape.length>=5){let o=a.readSync(r.dataId),l=r.dtype==="string"?o.map(c=>v.decodeString(c)):o,u=_e(r.shape,r.dtype,l),p=Xde(u,s);return a.makeTensorInfo(p.shape,p.dtype,p.values)}let i=new r2e(r.shape,s);return a.runWebGPUProgram(i,[r],r.dtype)}var i2e={kernelName:ds,backendName:"webgpu",kernelFunc:J3};function o2e(e){let{inputs:t,backend:a,attrs:n}=e,{sparseIndices:r,sparseValues:s,defaultValue:i}=t,{outputShape:o}=n,{sliceRank:l,numUpdates:u,sliceSize:p,strides:c,outputSize:d}=C.calculateShapes(s,r,o),h=!1;if(s.dtype==="string"){let N=a.bufferSync(r),M=a.bufferSync(s),$=v.decodeString(a.readSync(i.dataId)[0]),E=Vde(N,M,o,d,p,u,l,c,$,h);return a.makeTensorInfo(o,E.dtype,E.values)}let m=[d/p,p],f=ke({inputs:{x:r},backend:a,attrs:{shape:[u,l]}}),g=s.shape.length?ke({inputs:{x:s},backend:a,attrs:{shape:[u,p]}}):tn({inputs:{x:s},backend:a}),y=g.dtype,x=a.makeTensorInfo([],y,v.makeZerosTypedArray(1,y)),A=ke({inputs:{x:i},backend:a,attrs:{shape:Array(m.length).fill(1)}}),b=J3({inputs:{x:A},backend:a,attrs:{reps:m}}),w=v.sizeFromShape([u,p]),I=[{type:"int32",data:[l]},{type:"int32",data:c},{type:"int32",data:[w]}];switch(u){case 0:break;case 1:{let N=new zd([u,p],l,f.shape.length,g.shape.length,c,m,y,h);a.runWebGPUProgram(N,[g,f],y,I,b)}break;default:{let N=new zd([u,p],l,f.shape.length,x.shape.length,c,m,y,h);a.runWebGPUProgram(N,[x,f],y,I,b)}{let N=new zd([u,p],l,f.shape.length,g.shape.length,c,m,y);a.runWebGPUProgram(N,[g,f],y,I,b)}}let T=ke({inputs:{x:b},backend:a,attrs:{shape:o}});return a.disposeData(f.dataId),a.disposeData(g.dataId),a.disposeData(A.dataId),a.disposeData(x.dataId),a.disposeData(b.dataId),T}var l2e={kernelName:jo,backendName:"webgpu",kernelFunc:o2e};function u2e(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{numOrSizeSplits:s,axis:i}=n,o=v.parseAxisParam(i,r.shape)[0],l=C.prepareSplitSize(r,s,o),u=r.shape.length,p=new Array(u).fill(0),c=r.shape.slice();return l.map(d=>{let h=[...c];h[o]=d;let m=ad({inputs:{x:r},backend:a,attrs:{begin:p,size:h}});return p[o]+=d,m})}var d2e={kernelName:Du,backendName:"webgpu",kernelFunc:u2e},p2e=at({opType:le.SQRT}),c2e={kernelName:Uo,backendName:"webgpu",kernelFunc:p2e},h2e={kernelName:Cp,backendName:"webgpu",kernelFunc:({inputs:e,backend:t})=>{let{x:a}=e,n=t,r=new td(a.shape,le.SQUARE);return n.runWebGPUProgram(r,[a],a.dtype)}},m2e=aa({opType:Pe.SQUARED_DIFFERENCE}),f2e={kernelName:qo,backendName:"webgpu",kernelFunc:m2e};function g2e({inputs:e,attrs:t,backend:a}){let{x:n}=e,r=new td(n.shape,le.STEP,"stepAlpha : f32,"),s=[{type:"float32",data:[t.alpha]}];return a.runWebGPUProgram(r,[n],n.dtype,s)}var y2e={kernelName:ps,backendName:"webgpu",kernelFunc:g2e},x2e=class{constructor(e){this.variableNames=["x"],this.workPerThread=1,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1]);let t=Pt(this.outputShape.length);this.uniforms=`begin : ${t},  strides : ${t}, `,this.shaderKey="stridedSlice"}getUserCode(){let e=this.outputShape.length,t="";if(e===1)t="coords * uniforms.strides + uniforms.begin";else{let a=0;t=this.outputShape.map((n,r)=>(a++,this.outputShape.length===1?`coords * uniforms.strides[${r}] + uniforms.begin[${r}]`:`coords[${a-1}] * uniforms.strides[${r}] + uniforms.begin[${r}]`)).join(",")}return`
       ${ue("index")} {
         if (index < uniforms.size) {
           let coords = getCoordsFromIndex(index);
           setOutputAtIndex(index, getX(${t}));
         }
       }
     `}};function A2e(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{begin:s,end:i,strides:o,beginMask:l,endMask:u,ellipsisMask:p,newAxisMask:c,shrinkAxisMask:d}=n,{finalShapeSparse:h,finalShape:m,isIdentity:f,sliceDim0:g,isSimpleSlice:y,begin:x,end:A,strides:b}=Nt.sliceInfo(r.shape,s,i,o,l,u,p,c,d),w;if(f)w=ke({inputs:{x:r},backend:a,attrs:{shape:m}});else if(g||y){v.assert(r.shape.length>=1,()=>`Input must have rank at least 1, got: ${r.shape.length}`);let I=Nt.computeOutShape(x,A,b),T=ad({inputs:{x:r},backend:a,attrs:{begin:x,size:I}});w=ke({inputs:{x:T},backend:a,attrs:{shape:m}}),a.disposeData(T.dataId)}else if(a.shouldExecuteOnCPU([r])){let I=a.readSync(r.dataId),T=_e(r.shape,r.dtype,I),N=Hde(h,T,b,x);w=a.makeTensorInfo(m,r.dtype,N.values)}else{let I=new x2e(h),T=[{type:"int32",data:x},{type:"int32",data:b}],N=a.runWebGPUProgram(I,[r],r.dtype,T);w=ke({inputs:{x:N},backend:a,attrs:{shape:m}}),a.disposeData(N.dataId)}return w}var b2e={kernelName:Xo,backendName:"webgpu",kernelFunc:A2e};function v2e(e){let{inputs:t,backend:a,attrs:n}=e,{separator:r,nGramWidths:s,leftPad:i,rightPad:o,padWidth:l,preserveShortSequences:u}=n,{data:p,dataSplits:c}=t,d=a.readSync(p.dataId),h=a.readSync(c.dataId),[m,f]=jde(d,h,r,s,i,o,l,u);return[a.makeTensorInfo([m.length],"string",m),a.makeTensorInfo(c.shape,"int32",f)]}var w2e={kernelName:Wu,backendName:"webgpu",kernelFunc:v2e},k2e=aa({opType:Pe.SUB,cpuKernelImpl:qde,supportsComplex:!0}),I2e={kernelName:Ko,backendName:"webgpu",kernelFunc:k2e},S2e=at({opType:le.TAN}),C2e={kernelName:Yo,backendName:"webgpu",kernelFunc:S2e},T2e=at({opType:le.TANH}),N2e={kernelName:Zo,backendName:"webgpu",kernelFunc:T2e};function R2e(e){let{inputs:t,backend:a,attrs:n}=e,{tensor:r,indices:s,updates:i}=t,{}=n,{sliceRank:o,numUpdates:l,sliceSize:u,strides:p,outputSize:c}=C.calculateShapes(i,s,r.shape),d=[c/u,u];if(c===0)return a.makeTensorInfo(r.shape,s.dtype);let h=[],m=ke({inputs:{x:s},backend:a,attrs:{shape:[l,o]}});h.push(m);let f=ke({inputs:{x:i},backend:a,attrs:{shape:[l,u]}});h.push(f);let g=ke({inputs:{x:r},backend:a,attrs:{shape:d}});h.push(g);let y=J3({inputs:{x:g},backend:a,attrs:{reps:Array(d.length).fill(1)}}),x=new zd([l,u],o,m.shape.length,f.shape.length,p,d,r.dtype,!1),A=v.sizeFromShape([l,u]),b=[{type:"int32",data:[o]},{type:"int32",data:p},{type:"int32",data:[A]}],w=a.runWebGPUProgram(x,[f,m],g.dtype,b,y);h.push(w);let I=ke({inputs:{x:w},backend:a,attrs:{shape:r.shape}});return h.forEach(T=>a.disposeData(T.dataId)),I}var E2e={kernelName:Fo,backendName:"webgpu",kernelFunc:R2e},M2e=class{constructor(e){this.variableNames=["x","indices"],this.workgroupSize=[256,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.uniforms=`inputSize : i32, firstPass : i32, negativeInf : f32,
        dir : i32, inc : i32,`,this.shaderKey="swap"}getUserCode(){return`
        ${ue("index")} {
          if (index < uniforms.size) {
            let outC = getCoordsFromIndex(index);
            let batch = outC[0];
            let elemIdx = outC[1];
            // We compare elements pair-wise within a group of size 2 * inc.
            // The comparing rule for each group alternates between ascending
            // and descending. Within each group, we compare each pair at
            // positions i and i+inc. To decide whether an element at position i
            // is x0 or x1, we mod it by 2 * inc, if the result is smaller than
            // inc, it is in the first half of the group, we denote it as x0,
            // otherwise we denote it as x1.
            // For example, as shown in the Bitonic top K paper referenced
            // above, Figure5(a) shows that element[1] is in the second half of
            // the group when group size is 2, but it is in the first half of
            // the group when group size is 4.
            let isFirstInPair = elemIdx % (2 * uniforms.inc) < uniforms.inc;
            var i = 0;
            if (isFirstInPair) {
              i = elemIdx;
            } else {
              i = elemIdx - uniforms.inc;
            }

            var i0 = 0;
            if (uniforms.firstPass == 1) {
              i0 = i;
            } else {
              i0 = i32(getIndices(batch, i));
            }

            var i1 = 0;
            if (uniforms.firstPass == 1) {
              i1 = i + uniforms.inc;
            } else {
              i1 = i32(getIndices(batch, i + uniforms.inc));
            }

            var x0 = f32(0.0);
            var x1 = f32(0.0);
            if (i0 < uniforms.inputSize) {
              x0 = getX(batch, i0);
            } else {
              x0 = uniforms.negativeInf;
            }
            if (i1 < uniforms.inputSize) {
              x1 = getX(batch, i1);
            } else {
              x1 = uniforms.negativeInf;
            }

            let reverse = elemIdx % (2 * uniforms.dir) >= uniforms.dir;
            let isGreater = x0 > x1 || (x0 == x1 && i1 > i0);
            if (reverse == isGreater) {
              // Elements in opposite order of direction
              let iTemp = i0;
              i0 = i1;
              i1 = iTemp;
            }
            if (isFirstInPair) {
              setOutputAtIndex(index, f32(i0));
            } else {
              setOutputAtIndex(index, f32(i1));
            }
          }
        }
      `}},$2e=class{constructor(e){this.variableNames=["x","indices"],this.workgroupSize=[256,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.uniforms="inputSize : i32, firstPass : i32, k : i32,",this.shaderKey="merge"}getUserCode(){return`
        ${ue("index")} {
          if (index < uniforms.size) {
            let outC = getCoordsFromIndex(index);
            let batch = outC[0];
            let elemIdx = outC[1];
            // The output size is half of the previous size.
            // If the previous sequence is | | | | _ _ _ _  | | | |  _ _ _ _
            // (k=4), we only need to output the indices at positions |, the
            // indices at positions _ can be thrown away, see Figure5(b) After
            // Phase 2 (Merge phase) in the Bitonic Top K paper referenced
            // above.
            // For example, the paper shows we only need to output the orange
            // bars. The output sequence should look like this | | | | | | | |.
            // Because the sequence is halved, to map the output index back to
            // the previous sequence to find the corresponding value, we need
            // to double the index. When we double the index, we basically
            // interpolate a position, so 2i looks like
            // | _ | _ | _ | _ | _ | _ | _. We move the | to the first k
            // position of each 2k positions by - elemIdx % k. E.g. for output
            // at index 4,5,6,7, we want to get the corresponding element at
            // original index 8,9,10,11, for output at index 8,9,10,11,
            // we want to get the corresponding element at original index
            // 16,17,18,19, so on and so forth.

            var i = 0;
            if (elemIdx < uniforms.k) {
              i = elemIdx;
            } else {
              i = elemIdx * 2 - elemIdx % uniforms.k;
            }
            var i0 = 0;
            if (uniforms.firstPass == 1) {
              i0 = i;
            } else {
              i0 = i32(getIndices(batch, i));
            }
            var i1 = 0;
            if (uniforms.firstPass == 1) {
              i1 = i + uniforms.k;
            } else {
              i1 = i32(getIndices(batch, i + uniforms.k));
            }

            let x0 = getX(batch, i0);
            var x1 = f32(0.0);
            if (i1 < uniforms.inputSize) {
              x1 = getX(batch, i1);
            } else {
              x1 = x0;
            }

            if (x0 >= x1) {
              setOutputAtIndex(index, f32(i0));
            } else {
              setOutputAtIndex(index, f32(i1));
            }
          }
        }
      `}};function Ol(e,t){t!==null&&e.disposeData(t.dataId)}function cA(e){let t=1;for(;t<e;)t*=2;return t}function P2e(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{k:s,sorted:i}=n,o=r.shape,l=o[o.length-1];if(a.shouldExecuteOnCPU([r])){let b=a.readSync(r.dataId),[w,I]=Kde(b,o,r.dtype,s,i);return[a.makeTensorInfo(w.shape,w.dtype,w.values),a.makeTensorInfo(I.shape,I.dtype,I.values)]}if(s===0)return o[o.length-1]=0,[a.makeTensorInfo(o,r.dtype,[]),a.makeTensorInfo(o,"int32",[])];if(l===1)return[r,Wa({attrs:{shape:o,dtype:"int32",value:0},backend:a})];let u=v.sizeFromShape(o)/l,p=ke({inputs:{x:r},attrs:{shape:[u,l]},backend:a}),c=cA(s),d=cA(l),h=null,m=()=>h===null?[p,p]:[p,h],f=(b,w,I)=>{let T=m(),N=new M2e(I),M=[{type:"int32",data:[l]},{type:"int32",data:[h===null?1:0]},{type:"float32",data:[Number.NEGATIVE_INFINITY]},{type:"int32",data:[b]},{type:"int32",data:[w]}],$=h;h=a.runWebGPUProgram(N,T,"int32",M),Ol(a,$)};for(let b=1;b<c;b*=2){let w=b*2;for(let I=b;I>=1;I/=2)f(w,I,[u,d])}for(let b=d;b>c;b/=2){let w=m(),I=new $2e([u,b/2]),T=[{type:"int32",data:[l]},{type:"int32",data:[h===null?1:0]},{type:"int32",data:[c]}],N=h;h=a.runWebGPUProgram(I,w,"int32",T),Ol(a,N);let M=c/2,$=M*2;for(let E=M;E>=1;E/=2)f($,E,h.shape)}let g=h;h=ad({inputs:{x:h},backend:a,attrs:{begin:0,size:[u,s]}}),Ol(a,g);let y=jk({inputs:{x:p,indices:h},backend:a,attrs:{axis:1,batchDims:1}});Ol(a,p);let x=o.slice(0,-1);x.push(s),g=h,h=ke({inputs:{x:h},attrs:{shape:x},backend:a}),Ol(a,g);let A=y;return y=ke({inputs:{x:y},attrs:{shape:x},backend:a}),Ol(a,A),[y,h]}var _2e={kernelName:Jo,backendName:"webgpu",kernelFunc:P2e},F2e=class{constructor(e){this.variableNames=["Image","Transforms"],this.uniforms="interpolationModeId : i32, fillModeId : i32, fillValue : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="transform"}getUserCode(){return`
          fn mapCoord(outCoord : f32, len : f32) -> f32{
            var inCoord = outCoord;
            if(uniforms.fillModeId == 2) {
              if (inCoord < 0.0) {
                if (len <= 1.0) {
                  inCoord = 0.0;
                } else {
                  let sz2 = 2.0 * len;
                  if (inCoord < sz2) {
                    inCoord = sz2 * f32(i32(f32(-inCoord / sz2))) +
                    inCoord;
                  }
                  if (inCoord < -len) {
                    inCoord = inCoord + sz2;
                  } else {
                    inCoord = -inCoord - 1.0;
                  }
                }
              } else if (inCoord > len - 1.0) {
                if (len <= 1.0) {
                  inCoord = 0.0;
                } else {
                  let sz2 = 2.0 * len;
                  inCoord = inCoord - sz2 * f32(i32(f32(inCoord / sz2)));
                  if (inCoord >= len) {
                    inCoord = sz2 - inCoord - 1.0;
                  }
                }
              }
              return clamp(inCoord, 0.0, len - 1.0);
            } else if (uniforms.fillModeId == 3) {
              if (inCoord < 0.0) {
                if (len <= 1.0) {
                  inCoord = 0.0;
                } else {
                  let sz = len - 1.0;
                  inCoord = inCoord + len * (f32(i32(f32(-inCoord / sz))) + 1.0);
                }
              } else if (inCoord > len - 1.0) {
                if (len <= 1.0) {
                  inCoord = 0.0;
                } else {
                  let sz = len - 1.0;
                  inCoord = inCoord - len * f32(i32(f32(inCoord / sz)));
                }
              }
              return clamp(inCoord, 0.0, len - 1.0);
            } else if (uniforms.fillModeId == 4) {
              return clamp(outCoord, 0.0, len - 1.0);
            }
            return outCoord;
          }
          fn readWithFillValue(batch : i32, coordY : i32, coordX : i32,
            channel : i32) -> f32 {
            var outputValue : f32;
            if (0 <= coordY && coordY < uniforms.imageShape[1] && 0 <= coordX && coordX < uniforms.imageShape[2]) {
                outputValue = getImage(batch, coordY, coordX, channel);
            } else {
              outputValue = uniforms.fillValue;
            }
            return outputValue;
          }

          ${ue("index")} {
            if (index < uniforms.size) {
              let coords = getCoordsFromIndex(index);
              var outputValue : f32;
              let batch = coords[0];
              let x = coords[2];
              let y = coords[1];
              let channel = coords[3];
              let xf = f32(x);
              let yf = f32(y);
              let a1 = getTransforms(batch, 0);
              let a2 = getTransforms(batch, 1);
              let a3 = getTransforms(batch, 2);
              let b1 = getTransforms(batch, 3);
              let b2 = getTransforms(batch, 4);
              let b3 = getTransforms(batch, 5);
              let c1 = getTransforms(batch, 6);
              let c2 = getTransforms(batch, 7);
              let projection = c1 * xf + c2 * yf + 1.0;
              if (projection == 0.0) {
                outputValue = uniforms.fillValue;
              } else {
                let inX = (a1 * xf + a2 * yf + a3) / projection;
                let inY = (b1 * xf + b2 * yf + b3) / projection;
                let mapX = mapCoord(inX, f32(uniforms.imageShape[2]));
                let mapY = mapCoord(inY, f32(uniforms.imageShape[1]));

                if (uniforms.interpolationModeId == 1) {
                  let coordY = i32(round(mapY));
                  let coordX = i32(round(mapX));
                  outputValue = readWithFillValue(batch, coordY, coordX,
                    channel);
                } else {
                  let yFloor = floor(mapY);
                  let xFloor = floor(mapX);
                  let yCeil = yFloor + 1.0;
                  let xCeil = xFloor + 1.0;
                  let valueYFloor = (xCeil - mapX) *
                  readWithFillValue(batch, i32(yFloor), i32(xFloor), channel) +
                  (mapX - xFloor) *
                  readWithFillValue(batch, i32(yFloor), i32(xCeil), channel);
                  let valueYCeil = (xCeil - mapX) *
                  readWithFillValue(batch, i32(yCeil), i32(xFloor), channel) +
                  (mapX - xFloor) *
                  readWithFillValue(batch, i32(yCeil), i32(xCeil), channel);
                  outputValue = (yCeil - mapY) * valueYFloor +
                  (mapY - yFloor) * valueYCeil;
                }
              }
              setOutputAtIndex(index, outputValue);
            }
          }
        `}};function D2e(e){let{inputs:t,backend:a,attrs:n}=e,{image:r,transforms:s}=t,{interpolation:i,fillMode:o,fillValue:l,outputShape:u}=n,[p,c,d,h]=r.shape,[m,f]=u!=null?u:[c,d],g=[p,m,f,h],y=new F2e(g),x=i==="nearest"?1:2,A;switch(o){case"constant":A=1;break;case"reflect":A=2;break;case"wrap":A=3;break;case"nearest":A=4;break;default:A=1;break}let b=[{type:"int32",data:[x]},{type:"int32",data:[A]},{type:"float32",data:[l]}];return a.runWebGPUProgram(y,[r,s],"float32",b)}var O2e={kernelName:Qo,backendName:"webgpu",kernelFunc:D2e};function z2e(e){let{inputs:t,backend:a,attrs:n}=e,{value:r}=t,{axis:s}=n;s<0&&(s+=r.shape.length);let i=r,o=i.shape.length,l=r.shape[s],u=new Array(o-1),p=0;for(let f=0;f<o;f++)f!==s&&(u[p++]=i.shape[f]);let c=[],d=new Array(o).fill(0),h=i.shape.slice();h[s]=1;let m=new Array(l);for(let f=0;f<m.length;f++){d[s]=f;let g=ad({inputs:{x:i},backend:a,attrs:{begin:d,size:h}}),y=ke({inputs:{x:g},backend:a,attrs:{shape:u}});m[f]=y,c.push(g)}return c.forEach(f=>a.disposeData(f.dataId)),m}var L2e={kernelName:Bu,backendName:"webgpu",kernelFunc:z2e},W2e=class{constructor(e,t,a){if(this.outputShape=[],this.variableNames=["x","segmentIds"],this.uniforms="numSegments : i32, xSize: i32,",this.workgroupSize=[64,1,1],this.atomic=!0,this.outputShape=t,this.dispatchLayout=me(e),this.dispatch=de(this.dispatchLayout,e,this.workgroupSize),a!=="float32"&&a!=="int32")throw new Error(`UnsortedSegmentSum only supports float32 and int32
              types, does not support ${a} type.`);this.type=a,this.shaderKey="unsortedSegmentSum"}getUserCode(){return`
    ${ue("index")} {
      if (index < uniforms.xSize) {
        let coords = getXCoordsFromIndex(index);
        let b = coords[0];
        let inCol = coords[1];

        let segmentId = i32(getSegmentIds(inCol));
        if (segmentId >= 0) {
          let flatIndex = b * uniforms.numSegments + segmentId % uniforms.numSegments;
          let value = getX(b, inCol);

          ${xs("&result[flatIndex]","value",this.type)}
        }
      }
    }
  `}};function B2e(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,segmentIds:s}=t,{numSegments:i}=n,o=r.shape.length,l=[],u=0,p=C.getAxesPermutation([u],o),c=r;p!=null&&(c=sr({inputs:{x:r},backend:a,attrs:{perm:p}}),l.push(c),u=C.getInnerMostAxes(1,o)[0]);let d=C.segment_util.computeOutShape(c.shape,u,i),h=v.sizeFromShape([c.shape[u]]),m=ke({inputs:{x:c},backend:a,attrs:{shape:[-1,h]}});l.push(m);let f=r.dtype,g=[m.shape[0],i],y=Wa({backend:a,attrs:{shape:g,value:0,dtype:f}}),x=new W2e(m.shape,g,f),A=[{type:"int32",data:[i]},{type:"int32",data:[v.sizeFromShape(m.shape)]}],b=a.runWebGPUProgram(x,[m,s],f,A,y),w=ke({inputs:{x:b},backend:a,attrs:{shape:d}});l.push(b);let I=w;if(p!=null){l.push(w);let T=C.getUndoAxesPermutation(p);I=sr({inputs:{x:I},backend:a,attrs:{perm:T}})}return l.forEach(T=>a.disposeData(T.dataId)),I}var V2e={kernelName:Mp,backendName:"webgpu",kernelFunc:B2e},U2e=[mde,Jde,epe,ape,rpe,ope,mpe,gpe,xpe,bpe,wpe,Ipe,Cpe,Npe,Epe,Fpe,Ope,Bpe,Upe,Hpe,Ype,ece,nce,oce,uce,hce,gde,gce,bce,Nce,_ce,zce,Bce,Uce,Hce,qce,Kce,Jce,ehe,ahe,rhe,ohe,mhe,ghe,dhe,Ahe,whe,Che,Nhe,Mhe,Fhe,Ohe,Lhe,Bhe,Uhe,Hhe,jhe,Xhe,Yhe,pde,Jhe,r0e,e0e,a0e,o0e,u0e,p0e,m0e,y0e,A0e,v0e,fde,k0e,xce,S0e,T0e,R0e,M0e,P0e,F0e,z0e,V0e,W0e,G0e,j0e,X0e,J0e,tme,$pe,nme,sme,hme,ome,pme,fme,Ppe,yme,Ame,vme,kme,Nme,$he,Eme,$me,_me,rce,Ome,Lme,Bme,Gme,jme,Xme,Yme,Jme,sce,efe,afe,rfe,ife,cde,ufe,cfe,ffe,xfe,vfe,kfe,Sfe,Tfe,Rfe,$fe,Ffe,Ofe,Lfe,Bfe,Ufe,Hfe,Xpe,y2e,b2e,w2e,Cme,qfe,Yfe,t2e,n2e,l2e,d2e,c2e,h2e,f2e,I2e,Phe,C2e,N2e,E2e,i2e,_2e,O2e,dpe,L2e,V2e,zme];for(let e of U2e)xn(e);var hA="4.22.0",G2e="4.22.0",H2e="4.22.0",j2e="4.22.0",q2e="4.22.0",X2e="4.22.0",ac={tfjs:hA,"tfjs-core":hA,"tfjs-converter":G2e,"tfjs-backend-cpu":H2e,"tfjs-backend-webgl":j2e,"tfjs-backend-wasm":q2e,"tfjs-backend-webgpu":X2e},Q3=void 0;function K(...e){let t=new Date,a=`${t.getHours().toString().padStart(2,"0")}:${t.getMinutes().toString().padStart(2,"0")}:${t.getSeconds().toString().padStart(2,"0")}.${t.getMilliseconds().toString().padStart(3,"0")}`;e&&console.log(a,"Human:",...e)}function Jk(e,t){let a=e.endsWith("/")?"":"/",r=t.startsWith(".")||t.startsWith("/")||t.startsWith("http:")||t.startsWith("https:")||t.startsWith("file:")?`${t}`:`${e}${a}${t}`;if(!r.toLocaleLowerCase().includes(".json"))throw new Error(`modelpath error: expecting json file: ${r}`);return r}var ae=()=>typeof performance!="undefined"?performance.now():parseInt((Number(process.hrtime.bigint())/1e3/1e3).toString());function ey(e,t,a="config",n=[]){for(let r of Object.keys(t))if(typeof t[r]=="object")ey(e[r],t[r],r,n);else{let s=e&&typeof e[r]!="undefined";s||n.push({reason:"unknown property",where:`${a}.${r} = ${t[r]}`});let i=e&&typeof e[r]==typeof t[r];s&&!i&&n.push({reason:"property type mismatch",where:`${a}.${r} = ${t[r]}`,expected:typeof e[r]})}return t.debug&&a==="config"&&n.length>0&&K("invalid configuration",n),n}function Et(...e){let t=a=>a&&typeof a=="object";return e.reduce((a,n)=>(Object.keys(n||{}).forEach(r=>{let s=a[r],i=n[r];Array.isArray(s)&&Array.isArray(i)?a[r]=s.concat(...i):t(s)&&t(i)?a[r]=Et(s,i):a[r]=i}),a),{})}var pl={backend:"",modelBasePath:"",cacheModels:!0,validateModels:!0,wasmPath:"",wasmPlatformFetch:!1,debug:!1,async:!0,warmup:"full",cacheSensitivity:.7,skipAllowed:!1,deallocate:!1,flags:{},softwareKernels:!1,filter:{enabled:!0,equalization:!1,width:0,height:0,flip:!1,return:!0,autoBrightness:!0,brightness:0,contrast:0,sharpness:0,blur:0,saturation:0,hue:0,negative:!1,sepia:!1,vintage:!1,kodachrome:!1,technicolor:!1,polaroid:!1,pixelate:0},gesture:{enabled:!0},face:{enabled:!0,detector:{modelPath:"blazeface.json",rotation:!1,maxDetected:1,skipFrames:99,skipTime:2500,minConfidence:.2,minSize:0,iouThreshold:.1,scale:1.4,mask:!1,return:!1},mesh:{enabled:!0,modelPath:"facemesh.json",keepInvalid:!1},attention:{enabled:!1,modelPath:"facemesh-attention.json"},iris:{enabled:!0,scale:2.3,modelPath:"iris.json"},emotion:{enabled:!0,minConfidence:.1,skipFrames:99,skipTime:1500,modelPath:"emotion.json"},description:{enabled:!0,modelPath:"faceres.json",skipFrames:99,skipTime:3e3,minConfidence:.1},antispoof:{enabled:!1,skipFrames:99,skipTime:4e3,modelPath:"antispoof.json"},liveness:{enabled:!1,skipFrames:99,skipTime:4e3,modelPath:"liveness.json"}},body:{enabled:!0,modelPath:"movenet-lightning.json",maxDetected:-1,minConfidence:.3,skipFrames:1,skipTime:200},hand:{enabled:!0,rotation:!0,skipFrames:99,skipTime:1e3,minConfidence:.5,iouThreshold:.2,maxDetected:-1,landmarks:!0,detector:{modelPath:"handtrack.json"},skeleton:{modelPath:"handlandmark-lite.json"}},object:{enabled:!1,modelPath:"centernet.json",minConfidence:.2,iouThreshold:.4,maxDetected:10,skipFrames:99,skipTime:2e3},segmentation:{enabled:!1,modelPath:"rvm.json",ratio:.5,mode:"default"}};var Qk=`
  precision highp float;
  attribute vec2 pos;
  attribute vec2 uv;
  varying vec2 vUv;
  uniform float flipY;
  void main(void) {
    vUv = uv;
    gl_Position = vec4(pos.x, pos.y*flipY, 0.0, 1.);
  }
`;var e9=`
  precision highp float;
  varying vec2 vUv;
  uniform sampler2D texture;
  uniform float m[20];
  void main(void) {
    vec4 c = texture2D(texture, vUv);
    gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[3] * c.a + m[4];
    gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[8] * c.a + m[9];
    gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[13] * c.a + m[14];
    gl_FragColor.a = m[15] * c.r + m[16] * c.g + m[17] * c.b + m[18] * c.a + m[19];
  }
`,t9=`
  precision highp float;
  varying vec2 vUv;
  uniform sampler2D texture;
  uniform float m[20];
  void main(void) {
    vec4 c = texture2D(texture, vUv);
    gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[4];
    gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[9];
    gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[14];
    gl_FragColor.a = c.a;
  }
`,a9=`
  precision highp float;
  varying vec2 vUv;
  uniform vec2 size;
  uniform sampler2D texture;
  vec2 pixelate(vec2 coord, vec2 size) {
    return floor( coord / size ) * size;
  }
  void main(void) {
    gl_FragColor = vec4(0.0);
    vec2 coord = pixelate(vUv, size);
    gl_FragColor += texture2D(texture, coord);
  }
`,n9=`
  precision highp float;
  varying vec2 vUv;
  uniform sampler2D texture;
  uniform vec2 px;
  void main(void) {
    gl_FragColor = vec4(0.0);
    gl_FragColor += texture2D(texture, vUv + vec2(-7.0*px.x, -7.0*px.y))*0.0044299121055113265;
    gl_FragColor += texture2D(texture, vUv + vec2(-6.0*px.x, -6.0*px.y))*0.00895781211794;
    gl_FragColor += texture2D(texture, vUv + vec2(-5.0*px.x, -5.0*px.y))*0.0215963866053;
    gl_FragColor += texture2D(texture, vUv + vec2(-4.0*px.x, -4.0*px.y))*0.0443683338718;
    gl_FragColor += texture2D(texture, vUv + vec2(-3.0*px.x, -3.0*px.y))*0.0776744219933;
    gl_FragColor += texture2D(texture, vUv + vec2(-2.0*px.x, -2.0*px.y))*0.115876621105;
    gl_FragColor += texture2D(texture, vUv + vec2(-1.0*px.x, -1.0*px.y))*0.147308056121;
    gl_FragColor += texture2D(texture, vUv                             )*0.159576912161;
    gl_FragColor += texture2D(texture, vUv + vec2( 1.0*px.x,  1.0*px.y))*0.147308056121;
    gl_FragColor += texture2D(texture, vUv + vec2( 2.0*px.x,  2.0*px.y))*0.115876621105;
    gl_FragColor += texture2D(texture, vUv + vec2( 3.0*px.x,  3.0*px.y))*0.0776744219933;
    gl_FragColor += texture2D(texture, vUv + vec2( 4.0*px.x,  4.0*px.y))*0.0443683338718;
    gl_FragColor += texture2D(texture, vUv + vec2( 5.0*px.x,  5.0*px.y))*0.0215963866053;
    gl_FragColor += texture2D(texture, vUv + vec2( 6.0*px.x,  6.0*px.y))*0.00895781211794;
    gl_FragColor += texture2D(texture, vUv + vec2( 7.0*px.x,  7.0*px.y))*0.0044299121055113265;
  }
`,r9=`
  precision highp float;
  varying vec2 vUv;
  uniform sampler2D texture;
  uniform vec2 px;
  uniform float m[9];
  void main(void) {
    vec4 c11 = texture2D(texture, vUv - px); // top left
    vec4 c12 = texture2D(texture, vec2(vUv.x, vUv.y - px.y)); // top center
    vec4 c13 = texture2D(texture, vec2(vUv.x + px.x, vUv.y - px.y)); // top right
    vec4 c21 = texture2D(texture, vec2(vUv.x - px.x, vUv.y) ); // mid left
    vec4 c22 = texture2D(texture, vUv); // mid center
    vec4 c23 = texture2D(texture, vec2(vUv.x + px.x, vUv.y) ); // mid right
    vec4 c31 = texture2D(texture, vec2(vUv.x - px.x, vUv.y + px.y) ); // bottom left
    vec4 c32 = texture2D(texture, vec2(vUv.x, vUv.y + px.y) ); // bottom center
    vec4 c33 = texture2D(texture, vUv + px ); // bottom right
    gl_FragColor = 
    c11 * m[0] + c12 * m[1] + c22 * m[2] +
    c21 * m[3] + c22 * m[4] + c23 * m[5] +
    c31 * m[6] + c32 * m[7] + c33 * m[8];
    gl_FragColor.a = c22.a;
  }
`;var ty=(e,t,a)=>{let n=new RegExp("\\b"+t+" \\w+ (\\w+)","ig");e.replace(n,(r,s)=>(a[s]=0,r))},ay=class{constructor(t,a,n){he(this,"uniform",{});he(this,"attribute",{});he(this,"gl");he(this,"id");he(this,"compile",(t,a)=>{let n=this.gl.createShader(a);return n?(this.gl.shaderSource(n,t),this.gl.compileShader(n),this.gl.getShaderParameter(n,this.gl.COMPILE_STATUS)?n:(K(`filter: gl compile failed: ${this.gl.getShaderInfoLog(n)||"unknown"}`),null)):(K("filter: could not create shader"),null)});this.gl=t;let r=this.compile(a,this.gl.VERTEX_SHADER),s=this.compile(n,this.gl.FRAGMENT_SHADER);if(this.id=this.gl.createProgram(),!(!r||!s)){if(!this.id){K("filter: could not create webgl program");return}if(this.gl.attachShader(this.id,r),this.gl.attachShader(this.id,s),this.gl.linkProgram(this.id),!this.gl.getProgramParameter(this.id,this.gl.LINK_STATUS)){K(`filter: gl link failed: ${this.gl.getProgramInfoLog(this.id)||"unknown"}`);return}this.gl.useProgram(this.id),ty(a,"attribute",this.attribute);for(let i in this.attribute)this.attribute[i]=this.gl.getAttribLocation(this.id,i);ty(a,"uniform",this.uniform),ty(n,"uniform",this.uniform);for(let i in this.uniform)this.uniform[i]=this.gl.getUniformLocation(this.id,i)}}};function s9(){let e=0,t=null,a=!1,n=-1,r=[null,null],s=[],i=null,o=null,l=$n(100,100),u={},p={INTERMEDIATE:1},c=l.getContext("webgl");if(!c){K("filter: cannot get webgl context");return}this.gl=c;function d(x,A){if(!(x===l.width&&A===l.height)){if(l.width=x,l.height=A,!i){let b=new Float32Array([-1,-1,0,1,1,-1,1,1,-1,1,0,0,-1,1,0,0,1,-1,1,1,1,1,1,0]);i=c.createBuffer(),c.bindBuffer(c.ARRAY_BUFFER,i),c.bufferData(c.ARRAY_BUFFER,b,c.STATIC_DRAW),c.pixelStorei(c.UNPACK_PREMULTIPLY_ALPHA_WEBGL,!0)}c.viewport(0,0,l.width,l.height),r=[null,null]}}function h(x,A){let b=c.createFramebuffer();c.bindFramebuffer(c.FRAMEBUFFER,b);let w=c.createRenderbuffer();c.bindRenderbuffer(c.RENDERBUFFER,w);let I=c.createTexture();return c.bindTexture(c.TEXTURE_2D,I),c.texImage2D(c.TEXTURE_2D,0,c.RGBA,x,A,0,c.RGBA,c.UNSIGNED_BYTE,null),c.texParameteri(c.TEXTURE_2D,c.TEXTURE_MAG_FILTER,c.LINEAR),c.texParameteri(c.TEXTURE_2D,c.TEXTURE_MIN_FILTER,c.LINEAR),c.texParameteri(c.TEXTURE_2D,c.TEXTURE_WRAP_S,c.CLAMP_TO_EDGE),c.texParameteri(c.TEXTURE_2D,c.TEXTURE_WRAP_T,c.CLAMP_TO_EDGE),c.framebufferTexture2D(c.FRAMEBUFFER,c.COLOR_ATTACHMENT0,c.TEXTURE_2D,I,0),c.bindTexture(c.TEXTURE_2D,null),c.bindFramebuffer(c.FRAMEBUFFER,null),{fbo:b,texture:I}}function m(x){return r[x]=r[x]||h(l.width,l.height),r[x]}function f(x=0){if(!o)return;let A=null,b=null,w=!1;e===0?A=t:A=m(n).texture||null,e++,a&&!(x&p.INTERMEDIATE)?(b=null,w=e%2===0):(n=(n+1)%2,b=m(n).fbo||null),c.bindTexture(c.TEXTURE_2D,A),c.bindFramebuffer(c.FRAMEBUFFER,b),c.uniform1f(o.uniform.flipY,w?-1:1),c.drawArrays(c.TRIANGLES,0,6)}function g(x){if(u[x])return o=u[x],c.useProgram((o?o.id:null)||null),o;if(o=new ay(c,Qk,x),!o)return K("filter: could not get webgl program"),null;let A=Float32Array.BYTES_PER_ELEMENT,b=4*A;return c.enableVertexAttribArray(o.attribute.pos),c.vertexAttribPointer(o.attribute.pos,2,c.FLOAT,!1,b,0*A),c.enableVertexAttribArray(o.attribute.uv),c.vertexAttribPointer(o.attribute.uv,2,c.FLOAT,!1,b,2*A),u[x]=o,o}let y={colorMatrix:x=>{let A=new Float32Array(x);A[4]/=255,A[9]/=255,A[14]/=255,A[19]/=255;let b=A[18]===1&&A[3]===0&&A[8]===0&&A[13]===0&&A[15]===0&&A[16]===0&&A[17]===0&&A[19]===0?t9:e9,w=g(b);w&&(c.uniform1fv(w.uniform.m,A),f())},brightness:x=>{let A=(x||0)+1;y.colorMatrix([A,0,0,0,0,0,A,0,0,0,0,0,A,0,0,0,0,0,1,0])},saturation:x=>{let A=(x||0)*2/3+1,b=(A-1)*-.5;y.colorMatrix([A,b,b,0,0,b,A,b,0,0,b,b,A,0,0,0,0,0,1,0])},desaturate:()=>{y.saturation(-1)},contrast:x=>{let A=(x||0)+1,b=-128*(A-1);y.colorMatrix([A,0,0,0,b,0,A,0,0,b,0,0,A,0,b,0,0,0,1,0])},negative:()=>{y.contrast(-2)},hue:x=>{x=(x||0)/180*Math.PI;let A=Math.cos(x),b=Math.sin(x),w=.213,I=.715,T=.072;y.colorMatrix([w+A*(1-w)+b*-w,I+A*-I+b*-I,T+A*-T+b*(1-T),0,0,w+A*-w+b*.143,I+A*(1-I)+b*.14,T+A*-T+b*-.283,0,0,w+A*-w+b*-(1-w),I+A*-I+b*I,T+A*(1-T)+b*T,0,0,0,0,0,1,0])},desaturateLuminance:()=>{y.colorMatrix([.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,0,0,0,1,0])},sepia:()=>{y.colorMatrix([.393,.7689999,.18899999,0,0,.349,.6859999,.16799999,0,0,.272,.5339999,.13099999,0,0,0,0,0,1,0])},brownie:()=>{y.colorMatrix([.5997023498159715,.34553243048391263,-.2708298674538042,0,47.43192855600873,-.037703249837783157,.8609577587992641,.15059552388459913,0,-36.96841498319127,.24113635128153335,-.07441037908422492,.44972182064877153,0,-7.562075277591283,0,0,0,1,0])},vintagePinhole:()=>{y.colorMatrix([.6279345635605994,.3202183420819367,-.03965408211312453,0,9.651285835294123,.02578397704808868,.6441188644374771,.03259127616149294,0,7.462829176470591,.0466055556782719,-.0851232987247891,.5241648018700465,0,5.159190588235296,0,0,0,1,0])},kodachrome:()=>{y.colorMatrix([1.1285582396593525,-.3967382283601348,-.03992559172921793,0,63.72958762196502,-.16404339962244616,1.0835251566291304,-.05498805115633132,0,24.732407896706203,-.16786010706155763,-.5603416277695248,1.6014850761964943,0,35.62982807460946,0,0,0,1,0])},technicolor:()=>{y.colorMatrix([1.9125277891456083,-.8545344976951645,-.09155508482755585,0,11.793603434377337,-.3087833385928097,1.7658908555458428,-.10601743074722245,0,-70.35205161461398,-.231103377548616,-.7501899197440212,1.847597816108189,0,30.950940869491138,0,0,0,1,0])},polaroid:()=>{y.colorMatrix([1.438,-.062,-.062,0,0,-.122,1.378,-.122,0,0,-.016,-.016,1.483,0,0,0,0,0,1,0])},shiftToBGR:()=>{y.colorMatrix([0,0,1,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1,0])},convolution:x=>{let A=new Float32Array(x),b=1/l.width,w=1/l.height,I=g(r9);I&&(c.uniform1fv(I.uniform.m,A),c.uniform2f(I.uniform.px,b,w),f())},detectEdges:()=>{y.convolution.call(this,[0,1,0,1,-4,1,0,1,0])},sobelX:()=>{y.convolution.call(this,[-1,0,1,-2,0,2,-1,0,1])},sobelY:()=>{y.convolution.call(this,[-1,-2,-1,0,0,0,1,2,1])},sharpen:x=>{let A=x||1;y.convolution.call(this,[0,-1*A,0,-1*A,1+4*A,-1*A,0,-1*A,0])},emboss:x=>{let A=x||1;y.convolution.call(this,[-2*A,-1*A,0,-1*A,1,1*A,0,1*A,2*A])},blur:x=>{let A=x/7/l.width,b=x/7/l.height,w=g(n9);w&&(c.uniform2f(w.uniform.px,0,b),f(p.INTERMEDIATE),c.uniform2f(w.uniform.px,A,0),f())},pixelate:x=>{let A=x/l.width,b=x/l.height,w=g(a9);w&&(c.uniform2f(w.uniform.size,A,b),f())}};this.add=function(x){let A=Array.prototype.slice.call(arguments,1),b=y[x];s.push({func:b,args:A})},this.reset=function(){s=[]},this.get=function(){return s},this.apply=function(x){d(x.width,x.height),e=0,t||(t=c.createTexture()),c.bindTexture(c.TEXTURE_2D,t),c.texParameteri(c.TEXTURE_2D,c.TEXTURE_WRAP_S,c.CLAMP_TO_EDGE),c.texParameteri(c.TEXTURE_2D,c.TEXTURE_WRAP_T,c.CLAMP_TO_EDGE),c.texParameteri(c.TEXTURE_2D,c.TEXTURE_MIN_FILTER,c.NEAREST),c.texParameteri(c.TEXTURE_2D,c.TEXTURE_MAG_FILTER,c.NEAREST),c.texImage2D(c.TEXTURE_2D,0,c.RGBA,c.RGBA,c.UNSIGNED_BYTE,x);for(let A=0;A<s.length;A++){a=A===s.length-1;let b=s[A];b.func.apply(this,b.args||[])}return l},this.draw=function(x){return this.add("brightness",0),this.apply(x)}}async function m0(e){let t=e.shape.length===4?Oe(e):e,a=Sa(t,3,2),n=[ns(a[0]),ns(a[1]),ns(a[2])],r=[ga(a[0]),ga(a[1]),ga(a[2])],s=await Promise.all(r.map(p=>p.data())),i=Math.max(s[0][0],s[1][0],s[2][0]),l=(i>1?255:1)/i,u;if(l>1){let p=[xe(a[0],n[0]),xe(a[1],n[1]),xe(a[2],n[2])],c=[xe(r[0],n[0]),xe(r[1],n[1]),xe(r[2],n[2])],d=[te(p[0],l),te(p[1],l),te(p[2],l)],h=ha([d[0],d[1],d[2]],2);u=Q(h,[1,t.shape[0]||0,t.shape[1]||0,3]),J([...p,...c,...d,h])}else u=Wt(t,0);return J([...a,...n,...r,a,t,e]),u}var f0=3840,na=null,ra=null,nd=null,vt,bn={inputSum:0,cacheDiff:1,sumMethod:0,inputTensor:void 0};function ny(){bn.inputSum=0,bn.cacheDiff=1,bn.sumMethod=0,bn.inputTensor=void 0}function $n(e,t){let a;if(ne.browser)if(ne.worker){if(typeof OffscreenCanvas=="undefined")throw new Error("canvas error: attempted to run in web worker but OffscreenCanvas is not supported");a=new OffscreenCanvas(e,t)}else if(typeof document!="undefined")a=document.createElement("canvas"),a.width=e,a.height=t;else if(typeof navigator!="undefined"&&navigator.product==="ReactNative")if(typeof ne.Canvas!="undefined")a=new ne.Canvas(e,t);else if(typeof globalThis.Canvas!="undefined")a=new globalThis.Canvas(e,t);else throw new Error("canvas error: attempted to use canvas in react-native without canvas support installed");else throw new Error("canvas error: attempted to run in browser but DOM is not defined");else typeof ne.Canvas!="undefined"?a=new ne.Canvas(e,t):typeof globalThis.Canvas!="undefined"&&(a=new globalThis.Canvas(e,t));return a}function g0(e,t){let a=t||$n(e.width,e.height);return a.getContext("2d").drawImage(e,0,0),a}async function y0(e,t,a=!0){var d,h,m;if(!e)return t.debug&&K("input error: input is missing"),{tensor:null,canvas:null};if(!(e instanceof yt)&&!(typeof Image!="undefined"&&e instanceof Image)&&!(typeof globalThis.Canvas!="undefined"&&e instanceof globalThis.Canvas)&&!(typeof ImageData!="undefined"&&e instanceof ImageData)&&!(typeof ImageBitmap!="undefined"&&e instanceof ImageBitmap)&&!(typeof HTMLImageElement!="undefined"&&e instanceof HTMLImageElement)&&!(typeof HTMLMediaElement!="undefined"&&e instanceof HTMLMediaElement)&&!(typeof HTMLVideoElement!="undefined"&&e instanceof HTMLVideoElement)&&!(typeof HTMLCanvasElement!="undefined"&&e instanceof HTMLCanvasElement)&&!(typeof OffscreenCanvas!="undefined"&&e instanceof OffscreenCanvas))throw new Error("input error: type not recognized");if(e instanceof yt){let f=null;if(e.isDisposedInternal)throw new Error("input error: attempted to use tensor but it is disposed");if(!e.shape)throw new Error("input error: attempted to use tensor without a shape");if(e.shape.length===3){if(e.shape[2]===3)f=Wt(e,0);else if(e.shape[2]===4){let g=qp(e,[0,0,0],[-1,-1,3]);f=Wt(g,0),J(g)}}else e.shape.length===4&&(e.shape[3]===3?f=Ia(e):e.shape[3]===4&&(f=Vh(e,[0,0,0,0],[-1,-1,-1,3])));if(f==null||f.shape.length!==4||f.shape[0]!==1||f.shape[3]!==3)throw new Error(`input error: attempted to use tensor with unrecognized shape: ${e.shape.toString()}`);if(f.dtype==="int32"){let g=Ue(f,"float32");J(f),f=g}return{tensor:f,canvas:t.filter.return?ra:null}}if(typeof e.readyState!="undefined"&&e.readyState<=2)return t.debug&&K("input stream is not ready"),{tensor:null,canvas:na};let n=e.naturalWidth||e.videoWidth||e.width||e.shape&&e.shape[1]>0,r=e.naturalHeight||e.videoHeight||e.height||e.shape&&e.shape[2]>0;if(!n||!r)return t.debug&&K("cannot determine input dimensions"),{tensor:null,canvas:na};let s=n,i=r;if(s>f0&&(s=f0,i=Math.trunc(s*r/n)),i>f0&&(i=f0,s=Math.trunc(i*n/r)),(((d=t.filter)==null?void 0:d.width)||0)>0?s=t.filter.width:(((h=t.filter)==null?void 0:h.height)||0)>0&&(s=n*((t.filter.height||0)/r)),(t.filter.height||0)>0?i=t.filter.height:(t.filter.width||0)>0&&(i=r*((t.filter.width||0)/n)),!s||!i)throw new Error("input error: cannot determine dimension");(!na||na.width!==s||na.height!==i)&&(na=$n(s,i));let o=na.getContext("2d");if(typeof ImageData!="undefined"&&e instanceof ImageData?o.putImageData(e,0,0):t.filter.flip&&typeof o.translate!="undefined"?(o.translate(n,0),o.scale(-1,1),o.drawImage(e,0,0,n,r,0,0,na.width,na.height),o.setTransform(1,0,0,1,0,0)):o.drawImage(e,0,0,n,r,0,0,na.width,na.height),(!ra||na.width!==ra.width||na.height!==ra.height)&&(ra=$n(na.width,na.height)),t.filter.enabled&&ne.webgl.supported?(vt||(vt=ne.browser?new s9:null),ne.filter=!!vt,vt!=null&&vt.add?(vt.reset(),t.filter.brightness!==0&&vt.add("brightness",t.filter.brightness),t.filter.contrast!==0&&vt.add("contrast",t.filter.contrast),t.filter.sharpness!==0&&vt.add("sharpen",t.filter.sharpness),t.filter.blur!==0&&vt.add("blur",t.filter.blur),t.filter.saturation!==0&&vt.add("saturation",t.filter.saturation),t.filter.hue!==0&&vt.add("hue",t.filter.hue),t.filter.negative&&vt.add("negative"),t.filter.sepia&&vt.add("sepia"),t.filter.vintage&&vt.add("brownie"),t.filter.sepia&&vt.add("sepia"),t.filter.kodachrome&&vt.add("kodachrome"),t.filter.technicolor&&vt.add("technicolor"),t.filter.polaroid&&vt.add("polaroid"),t.filter.pixelate!==0&&vt.add("pixelate",t.filter.pixelate),((m=vt.get())==null?void 0:m.length)>1?ra=vt.apply(na):ra=vt.draw(na)):(t.debug&&K("input process error: cannot initialize filters"),ne.webgl.supported=!1,t.filter.enabled=!1,g0(na,ra))):(g0(na,ra),vt&&(vt=null),ne.filter=!!vt),!a)return{tensor:null,canvas:ra};if(!ra)throw new Error("canvas error: cannot create output");let l,u=3;if(typeof ImageData!="undefined"&&e instanceof ImageData||e.data&&e.width&&e.height)if(ne.browser&&Un)l=Un?Un.fromPixels(e):null;else{u=e.data.length/e.height/e.width;let f=new Uint8Array(e.data.buffer);l=Ve(f,[e.height,e.width,u],"int32")}else if((!nd||ra.width!==nd.width||ra.height!==nd.height)&&(nd=$n(ra.width,ra.height)),Un&&ne.browser)t.backend==="webgl"||t.backend==="humangl"||t.backend==="webgpu"?l=Un.fromPixels(ra):(nd=g0(ra),l=Un.fromPixels(nd));else{let y=g0(ra).getContext("2d").getImageData(0,0,s,i);u=y.data.length/s/i;let x=new Uint8Array(y.data.buffer);l=Ve(x,[s,i,u])}if(u===4){let f=qp(l,[0,0,0],[-1,-1,3]);J(l),l=f}if(!l)throw new Error("input error: cannot create tensor");let p=Ue(l,"float32"),c=t.filter.equalization?await m0(p):Wt(p,0);if(J([l,p]),t.filter.autoBrightness){let f=ga(c),g=await f.data();t.filter.brightness=g[0]>1?1-g[0]/255:1-g[0],J(f)}return{tensor:c,canvas:t.filter.return?ra:null}}async function i9(e,t){let a=!1;if(e.cacheSensitivity===0||!t.shape||t.shape.length!==4||t.shape[1]>3840||t.shape[2]>2160)return a;if(!bn.inputTensor)bn.inputTensor=Ia(t);else if(bn.inputTensor.shape[1]!==t.shape[1]||bn.inputTensor.shape[2]!==t.shape[2])J(bn.inputTensor),bn.inputTensor=Ia(t);else{let n={};n.diff=xe(t,bn.inputTensor),n.squared=te(n.diff,n.diff),n.sum=ot(n.squared);let s=(await n.sum.data())[0]/(t.shape[1]||1)/(t.shape[2]||1)/255/3;J([bn.inputTensor,n.diff,n.squared,n.sum]),bn.inputTensor=Ia(t),a=s<=(e.cacheSensitivity||0)}return a}async function o9(e,t,a){let n={};if(!t||!a||t.shape.length!==4||t.shape.length!==a.shape.length)return e.debug||K("invalid input tensor or tensor shapes do not match:",t.shape,a.shape),0;if(t.shape[0]!==1||a.shape[0]!==1||t.shape[3]!==3||a.shape[3]!==3)return e.debug||K("input tensors must be of shape [1, height, width, 3]:",t.shape,a.shape),0;n.input1=Ia(t),n.input2=t.shape[1]!==a.shape[1]||t.shape[2]!==a.shape[2]?fe.resizeBilinear(a,[t.shape[1],t.shape[2]]):Ia(a),n.diff=xe(n.input1,n.input2),n.squared=te(n.diff,n.diff),n.sum=ot(n.squared);let s=(await n.sum.data())[0]/(t.shape[1]||1)/(t.shape[2]||1)/255/3;return J([n.input1,n.input2,n.diff,n.squared,n.sum]),s}var rc,sc,ic,nc=class{constructor(){he(this,"browser");he(this,"node");he(this,"worker");he(this,"platform","");he(this,"agent","");he(this,"backends",[]);he(this,"initial");he(this,"filter");he(this,"tfjs");he(this,"offscreen");he(this,"perfadd",!1);he(this,"tensorflow",{version:void 0,gpu:void 0});he(this,"wasm",{supported:void 0,backend:void 0,simd:void 0,multithread:void 0});he(this,"webgl",{supported:void 0,backend:void 0,version:void 0,renderer:void 0,shader:void 0,vendor:void 0});he(this,"webgpu",{supported:void 0,backend:void 0,adapter:void 0});he(this,"cpu",{model:void 0,flags:[]});he(this,"kernels",[]);Kn(this,rc);Kn(this,sc);Kn(this,ic);if(this.browser=typeof navigator!="undefined"&&typeof navigator.appVersion!="undefined",this.node=typeof process!="undefined"&&typeof process.versions!="undefined"&&typeof process.versions.node!="undefined",this.tfjs={version:ac["tfjs-core"]},this.offscreen=typeof OffscreenCanvas!="undefined",this.initial=!0,this.worker=this.browser&&this.offscreen?typeof WorkerGlobalScope!="undefined":void 0,typeof navigator!="undefined"&&typeof navigator.userAgent!="undefined"){let t=navigator.userAgent||"",a=t.match(/\(([^()]+)\)/g);if(a!=null&&a[0]){let n=a[0].match(/\(([^()]+)\)/g);this.platform=n!=null&&n[0]?n[0].replace(/\(|\)/g,""):"",this.agent=t.replace(a[0],""),this.platform[1]&&(this.agent=this.agent.replace(a[1],"")),this.agent=this.agent.replace(/  /g," ")}}else typeof process!="undefined"&&(this.platform=`${process.platform} ${process.arch}`,this.agent=`NodeJS ${process.version}`)}get Canvas(){return qa(this,rc)}set Canvas(t){br(this,rc,t),globalThis.Canvas=t}get Image(){return qa(this,sc)}set Image(t){br(this,sc,t),globalThis.Image=t}get ImageData(){return qa(this,ic)}set ImageData(t){br(this,ic,t),globalThis.ImageData=t}async updateBackend(){this.backends=Object.keys(It().registryFactory);try{this.tensorflow={version:Vn().binding?Vn().binding.TF_Version:void 0,gpu:Vn().binding?Vn().binding.isUsingGpuDevice():void 0}}catch(n){}this.wasm.supported=typeof WebAssembly!="undefined",this.wasm.backend=this.backends.includes("wasm"),this.wasm.supported&&this.wasm.backend&&(this.wasm.simd=await B().getAsync("WASM_HAS_SIMD_SUPPORT"),this.wasm.multithread=await B().getAsync("WASM_HAS_MULTITHREAD_SUPPORT"));let t=$n(100,100),a=t?t.getContext("webgl2"):void 0;this.webgl.supported=typeof a!="undefined",this.webgl.backend=this.backends.includes("webgl"),this.webgl.supported&&this.webgl.backend&&a&&(this.webgl.version=a.getParameter(a.VERSION),this.webgl.vendor=a.getParameter(a.VENDOR),this.webgl.renderer=a.getParameter(a.RENDERER),this.webgl.shader=a.getParameter(a.SHADING_LANGUAGE_VERSION)),this.webgpu.supported=this.browser&&typeof navigator!="undefined"&&typeof navigator.gpu!="undefined",this.webgpu.backend=this.backends.includes("webgpu");try{if(this.webgpu.supported){let n=await navigator.gpu.requestAdapter();n&&("requestAdapterInfo"in n?this.webgpu.adapter=await n.requestAdapterInfo():this.webgpu.adapter=await n.info)}}catch(n){this.webgpu.supported=!1}try{this.kernels=er(ea()).map(n=>n.kernelName.toLowerCase())}catch(n){}}updateCPU(){let t={model:"",flags:[]};this.node&&this.platform.startsWith("linux"),this.cpu?this.cpu=t:Object.defineProperty(this,"cpu",{value:t})}};rc=new WeakMap,sc=new WeakMap,ic=new WeakMap;var ne=new nc;var A0=class{constructor(){he(this,"config");he(this,"element");he(this,"stream");he(this,"devices",[]);he(this,"enumerate",async()=>{try{let t=await navigator.mediaDevices.enumerateDevices();this.devices=t.filter(a=>a.kind==="videoinput")}catch(t){this.devices=[]}return this.devices});he(this,"start",async t=>{var r,s;if(t!=null&&t.debug&&(this.config.debug=t==null?void 0:t.debug),t!=null&&t.crop&&(this.config.crop=t==null?void 0:t.crop),t!=null&&t.mode&&(this.config.mode=t==null?void 0:t.mode),t!=null&&t.width&&(this.config.width=t==null?void 0:t.width),t!=null&&t.height&&(this.config.height=t==null?void 0:t.height),t!=null&&t.id&&(this.config.id=t==null?void 0:t.id),t!=null&&t.element)if(typeof t.element=="string"){let i=document.getElementById(t.element);if(i&&i instanceof HTMLVideoElement)this.element=i;else return this.config.debug&&K("webcam","cannot get dom element",t.element),`webcam error: cannot get dom element: ${t.element}`}else if(t.element instanceof HTMLVideoElement)this.element=t.element;else return this.config.debug&&K("webcam","unknown dom element",t.element),`webcam error: unknown dom element: ${t.element}`;else this.element=document.createElement("video");let a={audio:!1,video:{facingMode:this.config.mode==="front"?"user":"environment",resizeMode:this.config.crop?"crop-and-scale":"none"}};if(((r=this.config)==null?void 0:r.width)>0&&(a.video.width={ideal:this.config.width}),((s=this.config)==null?void 0:s.height)>0&&(a.video.height={ideal:this.config.height}),this.config.id&&(a.video.deviceId=this.config.id),this.element.addEventListener("play",()=>{this.config.debug&&K("webcam","play")}),this.element.addEventListener("pause",()=>{this.config.debug&&K("webcam","pause")}),this.element.addEventListener("click",async()=>{!this.element||!this.stream||(this.element.paused?await this.element.play():this.element.pause())}),!(navigator!=null&&navigator.mediaDevices))return this.config.debug&&K("webcam error","no devices"),"webcam error: no devices";try{this.stream=await navigator.mediaDevices.getUserMedia(a)}catch(i){return K("webcam",i),`webcam error: ${i}`}return this.stream?(this.element.srcObject=this.stream,await new Promise(i=>{this.element?this.element.onloadeddata=()=>i(!0):i(!1)}),await this.element.play(),this.config.debug&&K("webcam",{width:this.width,height:this.height,label:this.label,stream:this.stream,track:this.track,settings:this.settings,constraints:this.constraints,capabilities:this.capabilities}),`webcam: ${this.label}`):(this.config.debug&&K("webcam error","no stream"),"webcam error no stream")});he(this,"pause",()=>{this.element&&this.element.pause()});he(this,"play",async()=>{this.element&&await this.element.play()});he(this,"stop",()=>{this.config.debug&&K("webcam","stop"),this.track&&this.track.stop()});this.config={element:void 0,debug:!0,mode:"front",crop:!1,width:0,height:0}}get track(){if(this.stream)return this.stream.getVideoTracks()[0]}get capabilities(){if(this.track)return this.track.getCapabilities?this.track.getCapabilities():void 0}get constraints(){if(this.track)return this.track.getConstraints?this.track.getConstraints():void 0}get settings(){if(!this.stream)return;let t=this.stream.getVideoTracks()[0];return t.getSettings?t.getSettings():void 0}get label(){return this.track?this.track.label:""}get paused(){var t;return((t=this.element)==null?void 0:t.paused)||!1}get width(){var t;return((t=this.element)==null?void 0:t.videoWidth)||0}get height(){var t;return((t=this.element)==null?void 0:t.videoHeight)||0}};var ry={};Ar(ry,{"affectnet-mobilenet":()=>d1e,age:()=>p1e,"anti-spoofing":()=>U1e,antispoof:()=>J2e,blazeface:()=>Q2e,"blazeface-back":()=>c1e,"blazeface-front":()=>h1e,"blazepose-detector":()=>m1e,"blazepose-full":()=>f1e,"blazepose-heavy":()=>g1e,"blazepose-lite":()=>y1e,centernet:()=>e1e,default:()=>age,efficientpose:()=>x1e,"efficientpose-i-lite":()=>G1e,"efficientpose-ii-lite":()=>H1e,"efficientpose-iv":()=>j1e,emotion:()=>t1e,faceboxes:()=>A1e,facemesh:()=>a1e,"facemesh-attention":()=>v1e,"facemesh-attention-pinto":()=>b1e,"facemesh-detection-full":()=>w1e,"facemesh-detection-short":()=>k1e,faceres:()=>n1e,"faceres-deep":()=>I1e,gear:()=>T1e,"gear-e1":()=>S1e,"gear-e2":()=>C1e,gender:()=>R1e,"gender-ssrnet-imdb":()=>N1e,handdetect:()=>E1e,"handlandmark-full":()=>M1e,"handlandmark-lite":()=>r1e,"handlandmark-sparse":()=>$1e,handskeleton:()=>P1e,handtrack:()=>s1e,"insightface-efficientnet-b0":()=>q1e,"insightface-ghostnet-strides1":()=>X1e,"insightface-ghostnet-strides2":()=>K1e,"insightface-mobilenet-emore":()=>Y1e,"insightface-mobilenet-swish":()=>Z1e,iris:()=>i1e,liveness:()=>o1e,meet:()=>_1e,mobileface:()=>F1e,mobilefacenet:()=>D1e,models:()=>l1e,"movenet-lightning":()=>u1e,"movenet-multipose":()=>O1e,"movenet-thunder":()=>z1e,nanodet:()=>L1e,"nanodet-e":()=>J1e,"nanodet-g":()=>Q1e,"nanodet-m":()=>ege,"nanodet-t":()=>tge,posenet:()=>W1e,rvm:()=>B1e,selfie:()=>V1e});var J2e=853098,Q2e=538928,e1e=4030290,t1e=820516,a1e=1477958,n1e=6978814,r1e=2023432,s1e=2964837,i1e=2599092,o1e=592976,l1e=0,u1e=4650216,d1e=6920630,p1e=161240,c1e=538928,h1e=402048,m1e=5928856,f1e=6339202,g1e=27502466,y1e=2726402,x1e=5651240,A1e=2013002,b1e=2387598,v1e=2382414,w1e=1026192,k1e=201268,I1e=13957620,S1e=112438,C1e=112438,T1e=1498916,N1e=161236,R1e=201808,E1e=3515612,M1e=5431368,$1e=5286322,P1e=5502280,_1e=372228,F1e=2183192,D1e=5171976,O1e=9448838,z1e=12477112,L1e=7574558,W1e=5032780,B1e=3739355,V1e=212886,U1e=853098,G1e=2269064,H1e=5651240,j1e=25643252,q1e=13013224,X1e=8093408,K1e=8049584,Y1e=6938536,Z1e=12168584,J1e=12319156,Q1e=7574558,ege=1887474,tge=5294216,age={antispoof:J2e,blazeface:Q2e,centernet:e1e,emotion:t1e,facemesh:a1e,faceres:n1e,"handlandmark-lite":r1e,handtrack:s1e,iris:i1e,liveness:o1e,models:l1e,"movenet-lightning":u1e,"affectnet-mobilenet":d1e,age:p1e,"blazeface-back":c1e,"blazeface-front":h1e,"blazepose-detector":m1e,"blazepose-full":f1e,"blazepose-heavy":g1e,"blazepose-lite":y1e,efficientpose:x1e,faceboxes:A1e,"facemesh-attention-pinto":b1e,"facemesh-attention":v1e,"facemesh-detection-full":w1e,"facemesh-detection-short":k1e,"faceres-deep":I1e,"gear-e1":S1e,"gear-e2":C1e,gear:T1e,"gender-ssrnet-imdb":N1e,gender:R1e,handdetect:E1e,"handlandmark-full":M1e,"handlandmark-sparse":$1e,handskeleton:P1e,meet:_1e,mobileface:F1e,mobilefacenet:D1e,"movenet-multipose":O1e,"movenet-thunder":z1e,nanodet:L1e,posenet:W1e,rvm:B1e,selfie:V1e,"anti-spoofing":U1e,"efficientpose-i-lite":G1e,"efficientpose-ii-lite":H1e,"efficientpose-iv":j1e,"insightface-efficientnet-b0":q1e,"insightface-ghostnet-strides1":X1e,"insightface-ghostnet-strides2":K1e,"insightface-mobilenet-emore":Y1e,"insightface-mobilenet-swish":Z1e,"nanodet-e":J1e,"nanodet-g":Q1e,"nanodet-m":ege,"nanodet-t":tge};var Ea={cacheModels:!0,cacheSupported:!0,verbose:!0,debug:!1,modelBasePath:""},Yt={};async function nge(e,t){return Ea.debug&&K("load model fetch:",e,t),fetch(e,t)}function l9(e){Ea.cacheModels=e.cacheModels,Ea.verbose=e.debug,Ea.modelBasePath=e.modelBasePath}async function $e(e){var l,u,p,c,d,h;let t=Jk(Ea.modelBasePath,e||"");t.toLowerCase().endsWith(".json")||(t+=".json");let a=t.includes("/")?t.split("/"):t.split("\\"),n=a[a.length-1].replace(".json",""),r="indexeddb://"+n;Yt[n]={name:n,loaded:!1,sizeFromManifest:0,sizeLoadedWeights:0,sizeDesired:ry[n],inCache:!1,url:""},Ea.cacheSupported=typeof indexedDB!="undefined";let s={};try{s=Ea.cacheSupported&&Ea.cacheModels?await Zn.listModels():{}}catch(m){Ea.cacheSupported=!1}Yt[n].inCache=Ea.cacheSupported&&Ea.cacheModels&&Object.keys(s).includes(r),Yt[n].url=Yt[n].inCache?r:t;let i=typeof fetch=="undefined"?{}:{fetchFunc:(m,f)=>nge(m,f)},o=new Xp(Yt[n].url,i);Yt[n].loaded=!1;try{o.findIOHandler(),Ea.debug&&K("model load handler:",o.handler)}catch(m){K("error finding model i/o handler:",t,m)}try{let m=await((l=o.handler)==null?void 0:l.load())||null;Yt[n].sizeFromManifest=((u=m==null?void 0:m.weightData)==null?void 0:u.byteLength)||0,m?o.loadSync(m):o=await d3(Yt[n].inCache?r:t,i),Yt[n].sizeLoadedWeights=((c=(p=o.artifacts)==null?void 0:p.weightData)==null?void 0:c.byteLength)||((h=(d=o.artifacts)==null?void 0:d.weightData)==null?void 0:h[0].byteLength)||0,Ea.verbose&&K("load:",{model:n,url:o.modelUrl,bytes:Yt[n].sizeLoadedWeights}),Yt[n].loaded=!0}catch(m){K("error loading model:",t,m)}if(Yt[n].loaded&&Ea.cacheModels&&Ea.cacheSupported&&!Yt[n].inCache)try{let m=await o.save(r);Ea.debug&&K("model saved:",r,m)}catch(m){K("error saving model:",t,m)}return o}var sy="3.3.5";var St={name:"humangl",priority:999,canvas:null,gl:null,extensions:[],webGLattr:{alpha:!1,antialias:!1,premultipliedAlpha:!1,preserveDrawingBuffer:!1,depth:!1,stencil:!1,failIfMajorPerformanceCaveat:!1,desynchronized:!0}};function ige(){let e=St.gl;e&&(St.extensions=e.getSupportedExtensions())}function u9(e){var t;if(e.config.backend==="humangl"&&(St.name in It().registry&&!((t=St==null?void 0:St.gl)!=null&&t.getParameter(St.gl.VERSION))&&(K("humangl error: backend invalid context"),e.models.reset()),!lg(St.name))){try{St.canvas=$n(100,100)}catch(r){K("humangl error: cannot create canvas:",r);return}try{if(St.gl=St.canvas.getContext("webgl2",St.webGLattr),!St.gl){K("humangl error: cannot get webgl context");return}if(!St.gl.getParameter(St.gl.VERSION).includes("2.0")){K("backend override: using fallback webgl backend as webgl 2.0 is not detected"),e.config.backend="webgl";return}St.canvas&&(St.canvas.addEventListener("webglcontextlost",s=>{throw K("humangl error:",s.type),K("possible browser memory leak using webgl or conflict with multiple backend registrations"),e.emit("error"),new Error("backend error: webgl context lost")}),St.canvas.addEventListener("webglcontextrestored",s=>{K("humangl error: context restored:",s)}),St.canvas.addEventListener("webglcontextcreationerror",s=>{K("humangl error: context create:",s)}))}catch(r){K("humangl error: cannot get webgl context:",r);return}try{n0(2,St.gl)}catch(r){K("humangl error: cannot set webgl context:",r);return}try{let r=new Hl(St.gl);al(St.name,()=>new Jp(r),St.priority)}catch(r){K("humangl error: cannot register webgl backend:",r);return}try{er("webgl").forEach(s=>{let i={...s,backendName:St.name};xn(i)})}catch(r){K("humangl error: cannot update webgl backend registration:",r);return}try{B().flagRegistry.WEBGL_VERSION&&B().set("WEBGL_VERSION",2)}catch(r){K("humangl error: cannot set WebGL backend flags:",r);return}ige();let a=Vn(),n=typeof a.gpgpu!="undefined"?a.getGPGPUContext().gl:null;n?e.config.debug&&K("humangl backend registered:",{webgl:n.getParameter(n.VERSION),renderer:n.getParameter(n.RENDERER)}):K("humangl error: no current gl context:",n,St.gl)}}var ze={tf255:255,tf1:1,tf2:2,tf05:.5,tf127:127.5,rgb:[.2989,.587,.114]};function d9(){ze.tf255=Ge(255,"float32"),ze.tf1=Ge(1,"float32"),ze.tf2=Ge(2,"float32"),ze.tf05=Ge(.5,"float32"),ze.tf127=Ge(127.5,"float32"),ze.rgb=Bt([.2989,.587,.114],"float32")}async function uge(){var e;return await ne.updateBackend(),(e=ne.tensorflow)!=null&&e.version?"tensorflow":ne.webgpu.supported&&ne.webgpu.backend?"webgpu":ne.webgl.supported&&ne.webgl.backend?"webgl":ne.wasm.supported&&ne.wasm.backend?"wasm":"cpu"}function dge(e){let t=[];if(!ne.kernels.includes("mod")){let a={kernelName:"Mod",backendName:ea(),kernelFunc:n=>De(()=>xe(n.inputs.a,te(ve(n.inputs.a,n.inputs.b),n.inputs.b)))};xn(a),ne.kernels.push("mod"),t.push("mod")}if(!ne.kernels.includes("floormod")){let a={kernelName:"FloorMod",backendName:ea(),kernelFunc:n=>De(()=>we(te(zp(n.inputs.a,n.inputs.b),n.inputs.b),Gu(n.inputs.a,n.inputs.b)))};xn(a),ne.kernels.push("floormod"),t.push("floormod")}if(!ne.kernels.includes("rotatewithoffset")&&e.softwareKernels){let a={kernelName:"RotateWithOffset",backendName:ea(),kernelFunc:n=>De(()=>{let r=ea();Dp("cpu");let s=fe.rotateWithOffset(n.inputs.image,n.attrs.radians,n.attrs.fillValue,n.attrs.center);return Dp(r),s})};xn(a),ne.kernels.push("rotatewithoffset"),t.push("rotatewithoffset")}t.length>0&&e.debug&&K("registered kernels:",t)}var p9={};async function oc(e,t=!1){var a,n;if(e.state="backend",((a=e.config.backend)==null?void 0:a.length)===0&&(e.config.backend=await uge()),t||ne.initial||e.config.backend&&e.config.backend.length>0&&ea()!==e.config.backend){let r=ae();if(e.config.backend&&e.config.backend.length>0){typeof window=="undefined"&&typeof WorkerGlobalScope!="undefined"&&e.config.debug&&e.config.debug&&K("running inside web worker"),typeof navigator!="undefined"&&((n=navigator==null?void 0:navigator.userAgent)!=null&&n.toLowerCase().includes("electron"))&&e.config.debug&&K("running inside electron");let s=Object.keys(It().registryFactory);if(e.config.backend==="humangl"&&!s.includes("humangl")&&(u9(e),s=Object.keys(It().registryFactory)),e.config.debug&&K("available backends:",s),ne.browser&&!ne.node&&e.config.backend==="tensorflow"&&s.includes("webgl")&&(e.config.debug&&K("override: backend set to tensorflow while running in browser"),e.config.backend="webgl"),ne.node&&!ne.browser&&(e.config.backend==="webgl"||e.config.backend==="humangl")&&s.includes("tensorflow")&&(e.config.debug&&K(`override: backend set to ${e.config.backend} while running in nodejs`),e.config.backend="tensorflow"),ne.browser&&e.config.backend==="webgpu")if(typeof navigator=="undefined"||typeof navigator.gpu=="undefined")K("override: backend set to webgpu but browser does not support webgpu"),e.config.backend="webgl";else{let i=await navigator.gpu.requestAdapter();if(e.config.debug&&K("enumerated webgpu adapter:",i),!i)K("override: backend set to webgpu but browser reports no available gpu"),e.config.backend="webgl";else{let o;"requestAdapterInfo"in i?o=await(i==null?void 0:i.requestAdapterInfo()):o=i.info,K("webgpu adapter info:",o)}}if(s.includes(e.config.backend)||(K(`error: backend ${e.config.backend} not found in registry`),e.config.backend=ne.node?"tensorflow":"webgl",e.config.debug&&K(`override: setting backend ${e.config.backend}`)),e.config.debug&&K("setting backend:",[e.config.backend]),e.config.backend==="wasm"){if(B().flagRegistry.CANVAS2D_WILL_READ_FREQUENTLY&&B().set("CANVAS2D_WILL_READ_FREQUENTLY",!0),e.config.debug&&K("wasm path:",e.config.wasmPath),typeof u0!="undefined")u0(e.config.wasmPath,e.config.wasmPlatformFetch);else throw new Error("backend error: attempting to use wasm backend but wasm path is not set");let i=!1,o=!1;try{i=await B().getAsync("WASM_HAS_MULTITHREAD_SUPPORT"),o=await B().getAsync("WASM_HAS_SIMD_SUPPORT"),e.config.debug&&K(`wasm execution: ${o?"simd":"no simd"} ${i?"multithreaded":"singlethreaded"}`),e.config.debug&&!o&&K("warning: wasm simd support is not enabled")}catch(l){K("wasm detection failed")}}try{await Dp(e.config.backend),await tl()}catch(i){return K("error: cannot set backend:",e.config.backend,i),!1}e.config.debug&&(p9=JSON.parse(JSON.stringify(B().flags)))}if((ea()==="humangl"||ea()==="webgl")&&(B().flagRegistry.WEBGL_USE_SHAPES_UNIFORMS&&B().set("WEBGL_USE_SHAPES_UNIFORMS",!0),B().flagRegistry.WEBGL_EXP_CONV&&B().set("WEBGL_EXP_CONV",!0),e.config.debug&&typeof e.config.deallocate!="undefined"&&e.config.deallocate&&(K("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",!0),B().set("WEBGL_DELETE_TEXTURE_THRESHOLD",0))),ea(),e.config.debug){let s=B().flags,i={};for(let o of Object.keys(s))p9[o]!==s[o]&&(i[o]=s[o]);e.config.debug&&Object.keys(i).length>0&&K("backend:",ea(),"flags:",i)}if(e.config.flags&&Object.keys(e.config.flags).length>0){e.config.debug&&K("flags:",e.config.flags);for(let[s,i]of Object.entries(e.config.flags))B().set(s,i)}ig(),d9(),e.performance.initBackend=Math.trunc(ae()-r),e.config.backend=ea(),await ne.updateBackend(),dge(e.config)}return!0}function b0(e,t){for(let a of e){let n={kernelName:a,backendName:t.backend,kernelFunc:r=>{var s;return t.debug&&K("kernelFunc",a,t.backend,r),(s=r==null?void 0:r.inputs)==null?void 0:s.info}};xn(n)}ne.kernels=er(ea()).map(a=>a.kernelName.toLowerCase())}var C0={};Ar(C0,{all:()=>Vge,body:()=>w0,canvas:()=>Wge,face:()=>v0,gesture:()=>S0,hand:()=>k0,init:()=>cy,object:()=>I0,options:()=>Ft,person:()=>Lge,tensor:()=>Bge});var vn=e=>{if(!e)K("draw error: invalid canvas");else if(!e.getContext)K("draw error: canvas context not defined");else{let t=e.getContext("2d",{willReadFrequently:!0});if(!t)K("draw error: cannot get canvas context");else return t}return null},cl=e=>Math.round(e*180/Math.PI),ut=(e,t,a)=>e.replace(t,typeof a=="number"?a.toFixed(1):a),hl=(e,t)=>{if(!t.useDepth||typeof e=="undefined")return t.color;let a=Uint8ClampedArray.from([127+2*e,127-2*e,255]);return`rgba(${a[0]}, ${a[1]}, ${a[2]}, ${t.alpha})`};function wn(e,t,a,n,r){let s=t.replace(/\[.*\]/g,"").split(`
`).map(o=>o.trim()),i=Math.max(0,a);for(let o=s.length-1;o>=0;o--){let l=o*r.lineHeight+n;r.shadowColor&&r.shadowColor!==""&&(e.fillStyle=r.shadowColor,e.fillText(s[o],i+5,l+16)),e.fillStyle=r.labelColor,e.fillText(s[o],i+4,l+15)}}function ur(e,t,a,n,r){e.fillStyle=hl(n,r),e.beginPath(),e.arc(t,a,r.pointSize,0,2*Math.PI),e.fill()}function dr(e,t,a,n,r,s){if(e.beginPath(),e.lineWidth=s.lineWidth,s.useCurves){let i=(t+t+n)/2,o=(a+a+r)/2;e.ellipse(i,o,n/2,r/2,0,0,2*Math.PI)}else e.moveTo(t+s.roundRect,a),e.lineTo(t+n-s.roundRect,a),e.quadraticCurveTo(t+n,a,t+n,a+s.roundRect),e.lineTo(t+n,a+r-s.roundRect),e.quadraticCurveTo(t+n,a+r,t+n-s.roundRect,a+r),e.lineTo(t+s.roundRect,a+r),e.quadraticCurveTo(t,a+r,t,a+r-s.roundRect),e.lineTo(t,a+s.roundRect),e.quadraticCurveTo(t,a,t+s.roundRect,a),e.closePath();e.stroke()}function iy(e,t,a){if(!(t.length<2)){e.beginPath(),e.moveTo(t[0][0],t[0][1]);for(let n of t)e.strokeStyle=hl(n[2]||0,a),e.lineTo(Math.trunc(n[0]),Math.trunc(n[1]));e.stroke(),a.fillPolygons&&(e.closePath(),e.fill())}}function h9(e,t,a){if(!(t.length<2)){if(e.lineWidth=a.lineWidth,!a.useCurves||t.length<=2){iy(e,t,a);return}e.moveTo(t[0][0],t[0][1]);for(let n=0;n<t.length-2;n++){let r=(t[n][0]+t[n+1][0])/2,s=(t[n][1]+t[n+1][1])/2;e.quadraticCurveTo(t[n][0],t[n][1],r,s)}e.quadraticCurveTo(t[t.length-2][0],t[t.length-2][1],t[t.length-1][0],t[t.length-1][1]),e.stroke(),a.fillPolygons&&(e.closePath(),e.fill())}}function oy(e,t,a,n=5){let r,s,i;e.beginPath(),e.moveTo(t[0],t[1]),e.lineTo(a[0],a[1]),r=Math.atan2(a[1]-t[1],a[0]-t[0]),s=n*Math.cos(r)+a[0],i=n*Math.sin(r)+a[1],e.moveTo(s,i),r+=1/3*(2*Math.PI),s=n*Math.cos(r)+a[0],i=n*Math.sin(r)+a[1],e.lineTo(s,i),r+=1/3*(2*Math.PI),s=n*Math.cos(r)+a[0],i=n*Math.sin(r)+a[1],e.lineTo(s,i),e.closePath(),e.stroke(),e.fill()}var Ft={color:"rgba(173, 216, 230, 0.6)",labelColor:"rgba(173, 216, 230, 1)",shadowColor:"black",alpha:.5,font:'small-caps 16px "Segoe UI"',lineHeight:18,lineWidth:4,pointSize:2,roundRect:8,drawPoints:!1,drawLabels:!0,drawBoxes:!0,drawAttention:!0,drawGestures:!0,drawPolygons:!0,drawGaze:!0,fillPolygons:!1,useDepth:!0,useCurves:!1,faceLabels:"",bodyLabels:"",bodyPartLabels:"",objectLabels:"",handLabels:"",fingerLabels:"",gestureLabels:""};var Pn={silhouette:[10,338,297,332,284,251,389,356,454,323,361,288,397,365,379,378,400,377,152,148,176,149,150,136,172,58,132,93,234,127,162,21,54,103,67,109],lipsUpperOuter:[185,40,39,37,0,267,269,270,409],lipsLowerOuter:[61,146,91,181,84,17,314,405,321,375,291],lipsUpperInner:[191,80,81,82,13,312,311,310,415],lipsLowerInner:[78,95,88,178,87,14,317,402,318,324,308],lipsLowerSemiOuter:[76,77,90,180,85,16,315,404,320,307,306],lipsUpperSemiOuter:[184,74,73,72,11,302,303,304,408],lipsLowerSemiInner:[62,96,89,179,86,15,316,403,319,325,292],lipsUpperSemiInner:[183,42,41,38,12,268,271,272,407],rightEyeUpper0:[246,161,160,159,158,157,173],rightEyeLower0:[33,7,163,144,145,153,154,155,133],rightEyeUpper1:[247,30,29,27,28,56,190],rightEyeLower1:[130,25,110,24,23,22,26,112,243],rightEyeUpper2:[113,225,224,223,222,221,189],rightEyeLower2:[226,31,228,229,230,231,232,233,244],rightEyeLower3:[143,111,117,118,119,120,121,128,245],rightEyebrowUpper:[156,70,63,105,66,107,55,193],rightEyebrowLower:[35,124,46,53,52,65],rightEyeIris:[473,474,475,476,477],leftEyeUpper0:[466,388,387,386,385,384,398],leftEyeLower0:[263,249,390,373,374,380,381,382,362],leftEyeUpper1:[467,260,259,257,258,286,414],leftEyeLower1:[359,255,339,254,253,252,256,341,463],leftEyeUpper2:[342,445,444,443,442,441,413],leftEyeLower2:[446,261,448,449,450,451,452,453,464],leftEyeLower3:[372,340,346,347,348,349,350,357,465],leftEyebrowUpper:[383,300,293,334,296,336,285,417],leftEyebrowLower:[265,353,276,283,282,295],leftEyeIris:[468,469,470,471,472],midwayBetweenEyes:[168],noseTip:[1],noseBottom:[2],noseRightCorner:[98],noseLeftCorner:[327],rightCheek:[205],leftCheek:[425]},ly={count:468,mouth:13,symmetryLine:[13,Pn.midwayBetweenEyes[0]]},ml={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},uy=[{key:"EyeUpper0",indices:[9,10,11,12,13,14,15]},{key:"EyeUpper1",indices:[25,26,27,28,29,30,31]},{key:"EyeUpper2",indices:[41,42,43,44,45,46,47]},{key:"EyeLower0",indices:[0,1,2,3,4,5,6,7,8]},{key:"EyeLower1",indices:[16,17,18,19,20,21,22,23,24]},{key:"EyeLower2",indices:[32,33,34,35,36,37,38,39,40]},{key:"EyeLower3",indices:[54,55,56,57,58,59,60,61,62]},{key:"EyebrowUpper",indices:[63,64,65,66,67,68,69,70]},{key:"EyebrowLower",indices:[48,49,50,51,52,53]}],lc=[[.499976992607117,.652534008026123],[.500025987625122,.547487020492554],[.499974012374878,.602371990680695],[.482113003730774,.471979022026062],[.500150978565216,.527155995368958],[.499909996986389,.498252987861633],[.499523013830185,.40106201171875],[.289712011814117,.380764007568359],[.499954998493195,.312398016452789],[.499987006187439,.269918978214264],[.500023007392883,.107050001621246],[.500023007392883,.666234016418457],[.5000159740448,.679224014282227],[.500023007392883,.692348003387451],[.499976992607117,.695277988910675],[.499976992607117,.70593398809433],[.499976992607117,.719385027885437],[.499976992607117,.737019002437592],[.499967992305756,.781370997428894],[.499816000461578,.562981009483337],[.473773002624512,.573909997940063],[.104906998574734,.254140973091125],[.365929991006851,.409575998783112],[.338757991790771,.41302502155304],[.311120003461838,.409460008144379],[.274657994508743,.389131009578705],[.393361985683441,.403706014156342],[.345234006643295,.344011008739471],[.370094001293182,.346076011657715],[.319321990013123,.347265005111694],[.297903001308441,.353591024875641],[.24779200553894,.410809993743896],[.396889001131058,.842755019664764],[.280097991228104,.375599980354309],[.106310002505779,.399955987930298],[.2099249958992,.391353011131287],[.355807989835739,.534406006336212],[.471751004457474,.65040397644043],[.474155008792877,.680191993713379],[.439785003662109,.657229006290436],[.414617002010345,.66654098033905],[.450374007225037,.680860996246338],[.428770989179611,.682690978050232],[.374971002340317,.727805018424988],[.486716985702515,.547628998756409],[.485300987958908,.527395009994507],[.257764995098114,.314490020275116],[.401223003864288,.455172002315521],[.429818987846375,.548614978790283],[.421351999044418,.533740997314453],[.276895999908447,.532056987285614],[.483370006084442,.499586999416351],[.33721199631691,.282882988452911],[.296391993761063,.293242990970612],[.169294998049736,.193813979625702],[.447580009698868,.302609980106354],[.392390012741089,.353887975215912],[.354490011930466,.696784019470215],[.067304998636246,.730105042457581],[.442739009857178,.572826027870178],[.457098007202148,.584792017936707],[.381974011659622,.694710969924927],[.392388999462128,.694203019142151],[.277076005935669,.271932005882263],[.422551989555359,.563233017921448],[.385919004678726,.281364023685455],[.383103013038635,.255840003490448],[.331431001424789,.119714021682739],[.229923993349075,.232002973556519],[.364500999450684,.189113974571228],[.229622006416321,.299540996551514],[.173287004232407,.278747975826263],[.472878992557526,.666198015213013],[.446828007698059,.668527007102966],[.422762006521225,.673889994621277],[.445307999849319,.580065965652466],[.388103008270264,.693961024284363],[.403039008378983,.706539988517761],[.403629004955292,.693953037261963],[.460041999816895,.557139039039612],[.431158006191254,.692366003990173],[.452181994915009,.692366003990173],[.475387006998062,.692366003990173],[.465828001499176,.779190003871918],[.472328990697861,.736225962638855],[.473087012767792,.717857003211975],[.473122000694275,.704625964164734],[.473033010959625,.695277988910675],[.427942007780075,.695277988910675],[.426479011774063,.703539967536926],[.423162013292313,.711845993995667],[.4183090031147,.720062971115112],[.390094995498657,.639572978019714],[.013953999616206,.560034036636353],[.499913990497589,.58014702796936],[.413199990987778,.69539999961853],[.409626007080078,.701822996139526],[.468080013990402,.601534962654114],[.422728985548019,.585985004901886],[.463079988956451,.593783974647522],[.37211999297142,.47341400384903],[.334562003612518,.496073007583618],[.411671012639999,.546965003013611],[.242175996303558,.14767599105835],[.290776997804642,.201445996761322],[.327338010072708,.256527006626129],[.399509996175766,.748921036720276],[.441727995872498,.261676013469696],[.429764986038208,.187834024429321],[.412198007106781,.108901023864746],[.288955003023148,.398952007293701],[.218936994671822,.435410976409912],[.41278201341629,.398970007896423],[.257135003805161,.355440020561218],[.427684992551804,.437960982322693],[.448339998722076,.536936044692993],[.178560003638268,.45755398273468],[.247308000922203,.457193970680237],[.286267012357712,.467674970626831],[.332827985286713,.460712015628815],[.368755996227264,.447206974029541],[.398963987827301,.432654976844788],[.476410001516342,.405806005001068],[.189241006970406,.523923993110657],[.228962004184723,.348950982093811],[.490725994110107,.562400996685028],[.404670000076294,.485132992267609],[.019469000399113,.401564002037048],[.426243007183075,.420431017875671],[.396993011236191,.548797011375427],[.266469985246658,.376977026462555],[.439121007919312,.51895797252655],[.032313998788595,.644356966018677],[.419054001569748,.387154996395111],[.462783008813858,.505746960639954],[.238978996872902,.779744982719421],[.198220998048782,.831938028335571],[.107550002634525,.540755033493042],[.183610007166862,.740257024765015],[.134409993886948,.333683013916016],[.385764002799988,.883153975009918],[.490967005491257,.579378008842468],[.382384985685349,.508572995662689],[.174399003386497,.397670984268188],[.318785011768341,.39623498916626],[.343364000320435,.400596976280212],[.396100014448166,.710216999053955],[.187885001301765,.588537991046906],[.430987000465393,.944064974784851],[.318993002176285,.898285031318665],[.266247987747192,.869701027870178],[.500023007392883,.190576016902924],[.499976992607117,.954452991485596],[.366169989109039,.398822009563446],[.393207013607025,.39553701877594],[.410373002290726,.391080021858215],[.194993004202843,.342101991176605],[.388664990663528,.362284004688263],[.365961998701096,.355970978736877],[.343364000320435,.355356991291046],[.318785011768341,.35834002494812],[.301414996385574,.363156020641327],[.058132998645306,.319076001644135],[.301414996385574,.387449026107788],[.499987989664078,.618434011936188],[.415838003158569,.624195992946625],[.445681989192963,.566076993942261],[.465844005346298,.620640993118286],[.49992299079895,.351523995399475],[.288718998432159,.819945991039276],[.335278987884521,.852819979190826],[.440512001514435,.902418971061707],[.128294005990028,.791940987110138],[.408771991729736,.373893976211548],[.455606997013092,.451801002025604],[.499877005815506,.908990025520325],[.375436991453171,.924192011356354],[.11421000212431,.615022003650665],[.448662012815475,.695277988910675],[.4480200111866,.704632043838501],[.447111994028091,.715808033943176],[.444831997156143,.730794012546539],[.430011987686157,.766808986663818],[.406787008047104,.685672998428345],[.400738000869751,.681069016456604],[.392399996519089,.677703022956848],[.367855995893478,.663918972015381],[.247923001646996,.601333022117615],[.452769994735718,.420849978923798],[.43639200925827,.359887003898621],[.416164010763168,.368713974952698],[.413385987281799,.692366003990173],[.228018000721931,.683571994304657],[.468268007040024,.352671027183533],[.411361992359161,.804327011108398],[.499989002943039,.469825029373169],[.479153990745544,.442654013633728],[.499974012374878,.439637005329132],[.432112008333206,.493588984012604],[.499886006116867,.866917014122009],[.49991300702095,.821729004383087],[.456548988819122,.819200992584229],[.344549000263214,.745438992977142],[.37890899181366,.574010014533997],[.374292999505997,.780184984207153],[.319687992334366,.570737957954407],[.357154995203018,.604269981384277],[.295284003019333,.621580958366394],[.447750002145767,.862477004528046],[.410986006259918,.508723020553589],[.31395098567009,.775308012962341],[.354128003120422,.812552988529205],[.324548006057739,.703992962837219],[.189096003770828,.646299958229065],[.279776990413666,.71465802192688],[.1338230073452,.682700991630554],[.336768001317978,.644733011722565],[.429883986711502,.466521978378296],[.455527991056442,.548622965812683],[.437114000320435,.558896005153656],[.467287987470627,.529924988746643],[.414712011814117,.335219979286194],[.37704598903656,.322777986526489],[.344107985496521,.320150971412659],[.312875986099243,.32233202457428],[.283526003360748,.333190023899078],[.241245999932289,.382785975933075],[.102986000478268,.468762993812561],[.267612010240555,.424560010433197],[.297879010438919,.433175981044769],[.333433985710144,.433878004550934],[.366427004337311,.426115989685059],[.396012008190155,.416696012020111],[.420121014118195,.41022801399231],[.007561000064015,.480777025222778],[.432949006557465,.569517970085144],[.458638995885849,.479089021682739],[.473466008901596,.545744001865387],[.476087987422943,.563830018043518],[.468472003936768,.555056989192963],[.433990985155106,.582361996173859],[.483518004417419,.562983989715576],[.482482999563217,.57784903049469],[.42645001411438,.389798998832703],[.438998997211456,.39649498462677],[.450067013502121,.400434017181396],[.289712011814117,.368252992630005],[.276670008897781,.363372981548309],[.517862021923065,.471948027610779],[.710287988185883,.380764007568359],[.526226997375488,.573909997940063],[.895093023777008,.254140973091125],[.634069979190826,.409575998783112],[.661242008209229,.41302502155304],[.688880026340485,.409460008144379],[.725341975688934,.389131009578705],[.606630027294159,.40370500087738],[.654766023159027,.344011008739471],[.629905998706818,.346076011657715],[.680678009986877,.347265005111694],[.702096998691559,.353591024875641],[.75221198797226,.410804986953735],[.602918028831482,.842862963676453],[.719901978969574,.375599980354309],[.893692970275879,.399959981441498],[.790081977844238,.391354024410248],[.643998026847839,.534487962722778],[.528249025344849,.65040397644043],[.525849997997284,.680191040039062],[.560214996337891,.657229006290436],[.585384011268616,.66654098033905],[.549625992774963,.680860996246338],[.57122802734375,.682691991329193],[.624852001667023,.72809898853302],[.513050019741058,.547281980514526],[.51509702205658,.527251958847046],[.742246985435486,.314507007598877],[.598631024360657,.454979002475739],[.570338010787964,.548575043678284],[.578631997108459,.533622980117798],[.723087012767792,.532054007053375],[.516445994377136,.499638974666595],[.662801027297974,.282917976379395],[.70362401008606,.293271005153656],[.830704987049103,.193813979625702],[.552385985851288,.302568018436432],[.607609987258911,.353887975215912],[.645429015159607,.696707010269165],[.932694971561432,.730105042457581],[.557260990142822,.572826027870178],[.542901992797852,.584792017936707],[.6180260181427,.694710969924927],[.607590973377228,.694203019142151],[.722943007946014,.271963000297546],[.577413976192474,.563166975975037],[.614082992076874,.281386971473694],[.616907000541687,.255886018276215],[.668509006500244,.119913995265961],[.770092010498047,.232020974159241],[.635536015033722,.189248979091644],[.77039098739624,.299556016921997],[.826722025871277,.278755009174347],[.527121007442474,.666198015213013],[.553171992301941,.668527007102966],[.577238023281097,.673889994621277],[.554691970348358,.580065965652466],[.611896991729736,.693961024284363],[.59696102142334,.706539988517761],[.596370995044708,.693953037261963],[.539958000183105,.557139039039612],[.568841993808746,.692366003990173],[.547818005084991,.692366003990173],[.52461302280426,.692366003990173],[.534089982509613,.779141008853912],[.527670979499817,.736225962638855],[.526912987232208,.717857003211975],[.526877999305725,.704625964164734],[.526966989040375,.695277988910675],[.572058022022247,.695277988910675],[.573521018028259,.703539967536926],[.57683801651001,.711845993995667],[.581691026687622,.720062971115112],[.609944999217987,.639909982681274],[.986046016216278,.560034036636353],[.5867999792099,.69539999961853],[.590372025966644,.701822996139526],[.531915009021759,.601536989212036],[.577268004417419,.585934996604919],[.536915004253387,.593786001205444],[.627542972564697,.473352015018463],[.665585994720459,.495950996875763],[.588353991508484,.546862006187439],[.757824003696442,.14767599105835],[.709249973297119,.201507985591888],[.672684013843536,.256581008434296],[.600408971309662,.74900496006012],[.55826598405838,.261672019958496],[.570303976535797,.187870979309082],[.588165998458862,.109044015407562],[.711045026779175,.398952007293701],[.781069993972778,.435405015945435],[.587247014045715,.398931980133057],[.742869973182678,.355445981025696],[.572156012058258,.437651991844177],[.55186802148819,.536570012569427],[.821442008018494,.457556009292603],[.752701997756958,.457181990146637],[.71375697851181,.467626988887787],[.66711300611496,.460672974586487],[.631101012229919,.447153985500336],[.6008620262146,.432473003864288],[.523481011390686,.405627012252808],[.810747981071472,.523926019668579],[.771045982837677,.348959028720856],[.509127020835876,.562718033790588],[.595292985439301,.485023975372314],[.980530977249146,.401564002037048],[.573499977588654,.420000016689301],[.602994978427887,.548687994480133],[.733529984951019,.376977026462555],[.560611009597778,.519016981124878],[.967685997486115,.644356966018677],[.580985009670258,.387160003185272],[.537728011608124,.505385041236877],[.760966002941132,.779752969741821],[.801778972148895,.831938028335571],[.892440974712372,.54076099395752],[.816350996494293,.740260004997253],[.865594983100891,.333687007427216],[.614073991775513,.883246004581451],[.508952975273132,.579437971115112],[.617941975593567,.508316040039062],[.825608015060425,.397674977779388],[.681214988231659,.39623498916626],[.656635999679565,.400596976280212],[.603900015354156,.710216999053955],[.81208598613739,.588539004325867],[.56801301240921,.944564998149872],[.681007981300354,.898285031318665],[.733752012252808,.869701027870178],[.633830010890961,.398822009563446],[.606792986392975,.39553701877594],[.589659988880157,.391062021255493],[.805015981197357,.342108011245728],[.611334979534149,.362284004688263],[.634037971496582,.355970978736877],[.656635999679565,.355356991291046],[.681214988231659,.35834002494812],[.698584973812103,.363156020641327],[.941866993904114,.319076001644135],[.698584973812103,.387449026107788],[.584177017211914,.624107003211975],[.554318010807037,.566076993942261],[.534153997898102,.62064003944397],[.711217999458313,.819975018501282],[.664629995822906,.852871000766754],[.559099972248077,.902631998062134],[.871706008911133,.791940987110138],[.591234028339386,.373893976211548],[.544341027736664,.451583981513977],[.624562978744507,.924192011356354],[.88577002286911,.615028977394104],[.551338016986847,.695277988910675],[.551980018615723,.704632043838501],[.552887976169586,.715808033943176],[.555167973041534,.730794012546539],[.569944024085999,.767035007476807],[.593203008174896,.685675978660583],[.599261999130249,.681069016456604],[.607599973678589,.677703022956848],[.631937980651855,.663500010967255],[.752032995223999,.601315021514893],[.547226011753082,.420395016670227],[.563543975353241,.359827995300293],[.583841025829315,.368713974952698],[.586614012718201,.692366003990173],[.771915018558502,.683578014373779],[.531597018241882,.352482974529266],[.588370978832245,.804440975189209],[.52079701423645,.442565023899078],[.567984998226166,.493479013442993],[.543282985687256,.819254994392395],[.655317008495331,.745514988899231],[.621008992195129,.574018001556396],[.625559985637665,.78031200170517],[.680198013782501,.570719003677368],[.64276397228241,.604337990283966],[.704662978649139,.621529996395111],[.552012026309967,.862591981887817],[.589071989059448,.508637011051178],[.685944974422455,.775357007980347],[.645735025405884,.812640011310577],[.675342977046967,.703978002071381],[.810858011245728,.646304965019226],[.72012197971344,.714666962623596],[.866151988506317,.682704985141754],[.663187026977539,.644596993923187],[.570082008838654,.466325998306274],[.544561982154846,.548375964164734],[.562758982181549,.558784961700439],[.531987011432648,.530140042304993],[.585271000862122,.335177004337311],[.622952997684479,.32277899980545],[.655896008014679,.320163011550903],[.687132000923157,.322345972061157],[.716481983661652,.333200991153717],[.758756995201111,.382786989212036],[.897013008594513,.468769013881683],[.732392013072968,.424547016620636],[.70211398601532,.433162987232208],[.66652500629425,.433866024017334],[.633504986763,.426087975502014],[.603875994682312,.416586995124817],[.579657971858978,.409945011138916],[.992439985275269,.480777025222778],[.567192018032074,.569419980049133],[.54136598110199,.478899002075195],[.526564002037048,.546118021011353],[.523913025856018,.563830018043518],[.531529009342194,.555056989192963],[.566035985946655,.582329034805298],[.51631098985672,.563053965568542],[.5174720287323,.577877044677734],[.573594987392426,.389806985855103],[.560697972774506,.395331978797913],[.549755990505219,.399751007556915],[.710287988185883,.368252992630005],[.723330020904541,.363372981548309]],fl=[127,34,139,11,0,37,232,231,120,72,37,39,128,121,47,232,121,128,104,69,67,175,171,148,157,154,155,118,50,101,73,39,40,9,151,108,48,115,131,194,204,211,74,40,185,80,42,183,40,92,186,230,229,118,202,212,214,83,18,17,76,61,146,160,29,30,56,157,173,106,204,194,135,214,192,203,165,98,21,71,68,51,45,4,144,24,23,77,146,91,205,50,187,201,200,18,91,106,182,90,91,181,85,84,17,206,203,36,148,171,140,92,40,39,193,189,244,159,158,28,247,246,161,236,3,196,54,68,104,193,168,8,117,228,31,189,193,55,98,97,99,126,47,100,166,79,218,155,154,26,209,49,131,135,136,150,47,126,217,223,52,53,45,51,134,211,170,140,67,69,108,43,106,91,230,119,120,226,130,247,63,53,52,238,20,242,46,70,156,78,62,96,46,53,63,143,34,227,173,155,133,123,117,111,44,125,19,236,134,51,216,206,205,154,153,22,39,37,167,200,201,208,36,142,100,57,212,202,20,60,99,28,158,157,35,226,113,160,159,27,204,202,210,113,225,46,43,202,204,62,76,77,137,123,116,41,38,72,203,129,142,64,98,240,49,102,64,41,73,74,212,216,207,42,74,184,169,170,211,170,149,176,105,66,69,122,6,168,123,147,187,96,77,90,65,55,107,89,90,180,101,100,120,63,105,104,93,137,227,15,86,85,129,102,49,14,87,86,55,8,9,100,47,121,145,23,22,88,89,179,6,122,196,88,95,96,138,172,136,215,58,172,115,48,219,42,80,81,195,3,51,43,146,61,171,175,199,81,82,38,53,46,225,144,163,110,246,33,7,52,65,66,229,228,117,34,127,234,107,108,69,109,108,151,48,64,235,62,78,191,129,209,126,111,35,143,163,161,246,117,123,50,222,65,52,19,125,141,221,55,65,3,195,197,25,7,33,220,237,44,70,71,139,122,193,245,247,130,33,71,21,162,153,158,159,170,169,150,188,174,196,216,186,92,144,160,161,2,97,167,141,125,241,164,167,37,72,38,12,145,159,160,38,82,13,63,68,71,226,35,111,158,153,154,101,50,205,206,92,165,209,198,217,165,167,97,220,115,218,133,112,243,239,238,241,214,135,169,190,173,133,171,208,32,125,44,237,86,87,178,85,86,179,84,85,180,83,84,181,201,83,182,137,93,132,76,62,183,61,76,184,57,61,185,212,57,186,214,207,187,34,143,156,79,239,237,123,137,177,44,1,4,201,194,32,64,102,129,213,215,138,59,166,219,242,99,97,2,94,141,75,59,235,24,110,228,25,130,226,23,24,229,22,23,230,26,22,231,112,26,232,189,190,243,221,56,190,28,56,221,27,28,222,29,27,223,30,29,224,247,30,225,238,79,20,166,59,75,60,75,240,147,177,215,20,79,166,187,147,213,112,233,244,233,128,245,128,114,188,114,217,174,131,115,220,217,198,236,198,131,134,177,132,58,143,35,124,110,163,7,228,110,25,356,389,368,11,302,267,452,350,349,302,303,269,357,343,277,452,453,357,333,332,297,175,152,377,384,398,382,347,348,330,303,304,270,9,336,337,278,279,360,418,262,431,304,408,409,310,415,407,270,409,410,450,348,347,422,430,434,313,314,17,306,307,375,387,388,260,286,414,398,335,406,418,364,367,416,423,358,327,251,284,298,281,5,4,373,374,253,307,320,321,425,427,411,421,313,18,321,405,406,320,404,405,315,16,17,426,425,266,377,400,369,322,391,269,417,465,464,386,257,258,466,260,388,456,399,419,284,332,333,417,285,8,346,340,261,413,441,285,327,460,328,355,371,329,392,439,438,382,341,256,429,420,360,364,394,379,277,343,437,443,444,283,275,440,363,431,262,369,297,338,337,273,375,321,450,451,349,446,342,467,293,334,282,458,461,462,276,353,383,308,324,325,276,300,293,372,345,447,382,398,362,352,345,340,274,1,19,456,248,281,436,427,425,381,256,252,269,391,393,200,199,428,266,330,329,287,273,422,250,462,328,258,286,384,265,353,342,387,259,257,424,431,430,342,353,276,273,335,424,292,325,307,366,447,345,271,303,302,423,266,371,294,455,460,279,278,294,271,272,304,432,434,427,272,407,408,394,430,431,395,369,400,334,333,299,351,417,168,352,280,411,325,319,320,295,296,336,319,403,404,330,348,349,293,298,333,323,454,447,15,16,315,358,429,279,14,15,316,285,336,9,329,349,350,374,380,252,318,402,403,6,197,419,318,319,325,367,364,365,435,367,397,344,438,439,272,271,311,195,5,281,273,287,291,396,428,199,311,271,268,283,444,445,373,254,339,263,466,249,282,334,296,449,347,346,264,447,454,336,296,299,338,10,151,278,439,455,292,407,415,358,371,355,340,345,372,390,249,466,346,347,280,442,443,282,19,94,370,441,442,295,248,419,197,263,255,359,440,275,274,300,383,368,351,412,465,263,467,466,301,368,389,380,374,386,395,378,379,412,351,419,436,426,322,373,390,388,2,164,393,370,462,461,164,0,267,302,11,12,374,373,387,268,12,13,293,300,301,446,261,340,385,384,381,330,266,425,426,423,391,429,355,437,391,327,326,440,457,438,341,382,362,459,457,461,434,430,394,414,463,362,396,369,262,354,461,457,316,403,402,315,404,403,314,405,404,313,406,405,421,418,406,366,401,361,306,408,407,291,409,408,287,410,409,432,436,410,434,416,411,264,368,383,309,438,457,352,376,401,274,275,4,421,428,262,294,327,358,433,416,367,289,455,439,462,370,326,2,326,370,305,460,455,254,449,448,255,261,446,253,450,449,252,451,450,256,452,451,341,453,452,413,464,463,441,413,414,258,442,441,257,443,442,259,444,443,260,445,444,467,342,445,459,458,250,289,392,290,290,328,460,376,433,435,250,290,392,411,416,433,341,463,464,453,464,465,357,465,412,343,412,399,360,363,440,437,399,456,420,456,363,401,435,288,372,383,353,339,255,249,448,261,255,133,243,190,133,155,112,33,246,247,33,130,25,398,384,286,362,398,414,362,463,341,263,359,467,263,249,255,466,467,260,75,60,166,238,239,79,162,127,139,72,11,37,121,232,120,73,72,39,114,128,47,233,232,128,103,104,67,152,175,148,173,157,155,119,118,101,74,73,40,107,9,108,49,48,131,32,194,211,184,74,185,191,80,183,185,40,186,119,230,118,210,202,214,84,83,17,77,76,146,161,160,30,190,56,173,182,106,194,138,135,192,129,203,98,54,21,68,5,51,4,145,144,23,90,77,91,207,205,187,83,201,18,181,91,182,180,90,181,16,85,17,205,206,36,176,148,140,165,92,39,245,193,244,27,159,28,30,247,161,174,236,196,103,54,104,55,193,8,111,117,31,221,189,55,240,98,99,142,126,100,219,166,218,112,155,26,198,209,131,169,135,150,114,47,217,224,223,53,220,45,134,32,211,140,109,67,108,146,43,91,231,230,120,113,226,247,105,63,52,241,238,242,124,46,156,95,78,96,70,46,63,116,143,227,116,123,111,1,44,19,3,236,51,207,216,205,26,154,22,165,39,167,199,200,208,101,36,100,43,57,202,242,20,99,56,28,157,124,35,113,29,160,27,211,204,210,124,113,46,106,43,204,96,62,77,227,137,116,73,41,72,36,203,142,235,64,240,48,49,64,42,41,74,214,212,207,183,42,184,210,169,211,140,170,176,104,105,69,193,122,168,50,123,187,89,96,90,66,65,107,179,89,180,119,101,120,68,63,104,234,93,227,16,15,85,209,129,49,15,14,86,107,55,9,120,100,121,153,145,22,178,88,179,197,6,196,89,88,96,135,138,136,138,215,172,218,115,219,41,42,81,5,195,51,57,43,61,208,171,199,41,81,38,224,53,225,24,144,110,105,52,66,118,229,117,227,34,234,66,107,69,10,109,151,219,48,235,183,62,191,142,129,126,116,111,143,7,163,246,118,117,50,223,222,52,94,19,141,222,221,65,196,3,197,45,220,44,156,70,139,188,122,245,139,71,162,145,153,159,149,170,150,122,188,196,206,216,92,163,144,161,164,2,167,242,141,241,0,164,37,11,72,12,144,145,160,12,38,13,70,63,71,31,226,111,157,158,154,36,101,205,203,206,165,126,209,217,98,165,97,237,220,218,237,239,241,210,214,169,140,171,32,241,125,237,179,86,178,180,85,179,181,84,180,182,83,181,194,201,182,177,137,132,184,76,183,185,61,184,186,57,185,216,212,186,192,214,187,139,34,156,218,79,237,147,123,177,45,44,4,208,201,32,98,64,129,192,213,138,235,59,219,141,242,97,97,2,141,240,75,235,229,24,228,31,25,226,230,23,229,231,22,230,232,26,231,233,112,232,244,189,243,189,221,190,222,28,221,223,27,222,224,29,223,225,30,224,113,247,225,99,60,240,213,147,215,60,20,166,192,187,213,243,112,244,244,233,245,245,128,188,188,114,174,134,131,220,174,217,236,236,198,134,215,177,58,156,143,124,25,110,7,31,228,25,264,356,368,0,11,267,451,452,349,267,302,269,350,357,277,350,452,357,299,333,297,396,175,377,381,384,382,280,347,330,269,303,270,151,9,337,344,278,360,424,418,431,270,304,409,272,310,407,322,270,410,449,450,347,432,422,434,18,313,17,291,306,375,259,387,260,424,335,418,434,364,416,391,423,327,301,251,298,275,281,4,254,373,253,375,307,321,280,425,411,200,421,18,335,321,406,321,320,405,314,315,17,423,426,266,396,377,369,270,322,269,413,417,464,385,386,258,248,456,419,298,284,333,168,417,8,448,346,261,417,413,285,326,327,328,277,355,329,309,392,438,381,382,256,279,429,360,365,364,379,355,277,437,282,443,283,281,275,363,395,431,369,299,297,337,335,273,321,348,450,349,359,446,467,283,293,282,250,458,462,300,276,383,292,308,325,283,276,293,264,372,447,346,352,340,354,274,19,363,456,281,426,436,425,380,381,252,267,269,393,421,200,428,371,266,329,432,287,422,290,250,328,385,258,384,446,265,342,386,387,257,422,424,430,445,342,276,422,273,424,306,292,307,352,366,345,268,271,302,358,423,371,327,294,460,331,279,294,303,271,304,436,432,427,304,272,408,395,394,431,378,395,400,296,334,299,6,351,168,376,352,411,307,325,320,285,295,336,320,319,404,329,330,349,334,293,333,366,323,447,316,15,315,331,358,279,317,14,316,8,285,9,277,329,350,253,374,252,319,318,403,351,6,419,324,318,325,397,367,365,288,435,397,278,344,439,310,272,311,248,195,281,375,273,291,175,396,199,312,311,268,276,283,445,390,373,339,295,282,296,448,449,346,356,264,454,337,336,299,337,338,151,294,278,455,308,292,415,429,358,355,265,340,372,388,390,466,352,346,280,295,442,282,354,19,370,285,441,295,195,248,197,457,440,274,301,300,368,417,351,465,251,301,389,385,380,386,394,395,379,399,412,419,410,436,322,387,373,388,326,2,393,354,370,461,393,164,267,268,302,12,386,374,387,312,268,13,298,293,301,265,446,340,380,385,381,280,330,425,322,426,391,420,429,437,393,391,326,344,440,438,458,459,461,364,434,394,428,396,262,274,354,457,317,316,402,316,315,403,315,314,404,314,313,405,313,421,406,323,366,361,292,306,407,306,291,408,291,287,409,287,432,410,427,434,411,372,264,383,459,309,457,366,352,401,1,274,4,418,421,262,331,294,358,435,433,367,392,289,439,328,462,326,94,2,370,289,305,455,339,254,448,359,255,446,254,253,449,253,252,450,252,256,451,256,341,452,414,413,463,286,441,414,286,258,441,258,257,442,257,259,443,259,260,444,260,467,445,309,459,250,305,289,290,305,290,460,401,376,435,309,250,392,376,411,433,453,341,464,357,453,465,343,357,412,437,343,399,344,360,440,420,437,456,360,420,363,361,401,288,265,372,353,390,339,249,339,448,255];var pge=[127,234,132,58,172,150,149,148,152,377,378,379,397,288,361,454,356,70,63,105,66,107,336,296,334,293,300,168,6,195,4,98,97,2,326,327,33,160,158,133,153,144,362,385,387,263,373,380,57,40,37,0,267,270,287,321,314,17,84,91,78,81,13,311,308,402,14,178],cge=[33,133,362,263,1,62,308,159,145,386,374,6,102,331,2,13,14,70,105,107,336,334,300,54,10,284,50,280,234,454,58,288,152],hge=[33,133,362,263,1,78,308],Wbe=pge.map(e=>lc[e]),Bbe=cge.map(e=>lc[e]),Vbe=hge.map(e=>lc[e]);function As(e){let t=e.map(a=>a[0]);return t.push(e[e.length-1][1]),t}var mge=[[61,146],[146,91],[91,181],[181,84],[84,17],[17,314],[314,405],[405,321],[321,375],[375,291],[61,185],[185,40],[40,39],[39,37],[37,0],[0,267],[267,269],[269,270],[270,409],[409,291],[78,95],[95,88],[88,178],[178,87],[87,14],[14,317],[317,402],[402,318],[318,324],[324,308],[78,191],[191,80],[80,81],[81,82],[82,13],[13,312],[312,311],[311,310],[310,415],[415,308]],fge=[[263,249],[249,390],[390,373],[373,374],[374,380],[380,381],[381,382],[382,362],[263,466],[466,388],[388,387],[387,386],[386,385],[385,384],[384,398],[398,362]],gge=[[276,283],[283,282],[282,295],[295,285],[300,293],[293,334],[334,296],[296,336]],yge=[[474,475],[475,476],[476,477],[477,474]],xge=[[33,7],[7,163],[163,144],[144,145],[145,153],[153,154],[154,155],[155,133],[33,246],[246,161],[161,160],[160,159],[159,158],[158,157],[157,173],[173,133]],Age=[[46,53],[53,52],[52,65],[65,55],[70,63],[63,105],[105,66],[66,107]],bge=[[469,470],[470,471],[471,472],[472,469]],vge=[[10,338],[338,297],[297,332],[332,284],[284,251],[251,389],[389,356],[356,454],[454,323],[323,361],[361,288],[288,397],[397,365],[365,379],[379,378],[378,400],[400,377],[377,152],[152,148],[148,176],[176,149],[149,150],[150,136],[136,172],[172,58],[58,132],[132,93],[93,234],[234,127],[127,162],[162,21],[21,54],[54,103],[103,67],[67,109],[109,10]],Ube={lips:As(mge),leftEye:As(fge),leftEyebrow:As(gge),leftIris:As(yge),rightEye:As(xge),rightEyebrow:As(Age),rightIris:As(bge),faceOval:As(vge)};var wge=[[61,146],[146,91],[91,181],[181,84],[84,17],[17,314],[314,405],[405,321],[321,375],[375,291],[61,185],[185,40],[40,39],[39,37],[37,0],[0,267],[267,269],[269,270],[270,409],[409,291],[78,95],[95,88],[88,178],[178,87],[87,14],[14,317],[317,402],[402,318],[318,324],[324,308],[78,191],[191,80],[80,81],[81,82],[82,13],[13,312],[312,311],[311,310],[310,415],[415,308]],kge=[[263,249],[249,390],[390,373],[373,374],[374,380],[380,381],[381,382],[382,362],[263,466],[466,388],[388,387],[387,386],[386,385],[385,384],[384,398],[398,362]],Ige=[[276,283],[283,282],[282,295],[295,285],[300,293],[293,334],[334,296],[296,336]],Sge=[[474,475],[475,476],[476,477],[477,474]],Cge=[[33,7],[7,163],[163,144],[144,145],[145,153],[153,154],[154,155],[155,133],[33,246],[246,161],[161,160],[160,159],[159,158],[158,157],[157,173],[173,133]],Tge=[[46,53],[53,52],[52,65],[65,55],[70,63],[63,105],[105,66],[66,107]],Nge=[[469,470],[470,471],[471,472],[472,469]],Rge=[[10,338],[338,297],[297,332],[332,284],[284,251],[251,389],[389,356],[356,454],[454,323],[323,361],[361,288],[288,397],[397,365],[365,379],[379,378],[378,400],[400,377],[377,152],[152,148],[148,176],[176,149],[149,150],[150,136],[136,172],[172,58],[58,132],[132,93],[93,234],[234,127],[127,162],[162,21],[21,54],[54,103],[103,67],[67,109],[109,10]];function bs(e){let t=e.map(a=>a[0]);return t.push(e[e.length-1][1]),t}var Ege={lips:bs(wge),leftEye:bs(kge),leftEyebrow:bs(Ige),leftIris:bs(Sge),rightEye:bs(Cge),rightEyebrow:bs(Tge),rightIris:bs(Nge),faceOval:bs(Rge)},Mge=Object.entries(Ege).map(([e,t])=>t.map(a=>[a,e])).flat(),Gbe=new Map(Mge),uc=[61,146,91,181,84,17,314,405,321,375,291,185,40,39,37,0,267,269,270,409,78,95,88,178,87,14,317,402,318,324,308,191,80,81,82,13,312,311,310,415,76,77,90,180,85,16,315,404,320,307,306,184,74,73,72,11,302,303,304,408,62,96,89,179,86,15,316,403,319,325,292,183,42,41,38,12,268,271,272,407],gl=[33,7,163,144,145,153,154,155,133,246,161,160,159,158,157,173,130,25,110,24,23,22,26,112,243,247,30,29,27,28,56,190,226,31,228,229,230,231,232,233,244,113,225,224,223,222,221,189,35,124,46,53,52,65,143,111,117,118,119,120,121,128,245,156,70,63,105,66,107,55,193],yl=[263,249,390,373,374,380,381,382,362,466,388,387,386,385,384,398,359,255,339,254,253,252,256,341,463,467,260,259,257,258,286,414,446,261,448,449,450,451,452,453,464,342,445,444,443,442,441,413,265,353,276,283,282,295,372,340,346,347,348,349,350,357,465,383,300,293,334,296,336,285,417];var rt;function $ge(e,t){var n,r,s,i,o,l,u,p,c;if(!rt.drawLabels||((n=rt.faceLabels)==null?void 0:n.length)===0)return;let a=rt.faceLabels.slice();if(a=ut(a,"[id]",e.id.toFixed(0)),e.score&&(a=ut(a,"[score]",100*e.score)),e.gender&&(a=ut(a,"[gender]",e.gender)),e.genderScore&&(a=ut(a,"[genderScore]",100*e.genderScore)),e.age&&(a=ut(a,"[age]",e.age)),e.distance&&(a=ut(a,"[distance]",100*e.distance)),e.real&&(a=ut(a,"[real]",100*e.real)),e.live&&(a=ut(a,"[live]",100*e.live)),e.emotion&&e.emotion.length>0){let d=e.emotion.map(h=>`${Math.trunc(100*h.score)}% ${h.emotion}`);d.length>3&&(d.length=3),a=ut(a,"[emotions]",d.join(" "))}(s=(r=e.rotation)==null?void 0:r.angle)!=null&&s.roll&&(a=ut(a,"[roll]",cl(e.rotation.angle.roll))),(o=(i=e.rotation)==null?void 0:i.angle)!=null&&o.yaw&&(a=ut(a,"[yaw]",cl(e.rotation.angle.yaw))),(u=(l=e.rotation)==null?void 0:l.angle)!=null&&u.pitch&&(a=ut(a,"[pitch]",cl(e.rotation.angle.pitch))),(c=(p=e.rotation)==null?void 0:p.gaze)!=null&&c.bearing&&(a=ut(a,"[gaze]",cl(e.rotation.gaze.bearing))),wn(t,a,e.box[0],e.box[1],rt)}function Pge(e,t){var a,n,r,s;if((a=e.annotations)!=null&&a.leftEyeIris&&((n=e.annotations)!=null&&n.leftEyeIris[0])){t.strokeStyle=rt.useDepth?"rgba(255, 200, 255, 0.3)":rt.color,t.beginPath();let i=Math.abs(e.annotations.leftEyeIris[3][0]-e.annotations.leftEyeIris[1][0])/2,o=Math.abs(e.annotations.leftEyeIris[4][1]-e.annotations.leftEyeIris[2][1])/2;t.ellipse(e.annotations.leftEyeIris[0][0],e.annotations.leftEyeIris[0][1],i,o,0,0,2*Math.PI),t.stroke(),rt.fillPolygons&&(t.fillStyle=rt.useDepth?"rgba(255, 255, 200, 0.3)":rt.color,t.fill())}if((r=e.annotations)!=null&&r.rightEyeIris&&((s=e.annotations)!=null&&s.rightEyeIris[0])){t.strokeStyle=rt.useDepth?"rgba(255, 200, 255, 0.3)":rt.color,t.beginPath();let i=Math.abs(e.annotations.rightEyeIris[3][0]-e.annotations.rightEyeIris[1][0])/2,o=Math.abs(e.annotations.rightEyeIris[4][1]-e.annotations.rightEyeIris[2][1])/2;t.ellipse(e.annotations.rightEyeIris[0][0],e.annotations.rightEyeIris[0][1],i,o,0,0,2*Math.PI),t.stroke(),rt.fillPolygons&&(t.fillStyle=rt.useDepth?"rgba(255, 255, 200, 0.3)":rt.color,t.fill())}}function _ge(e,t){var a;if(rt.drawGaze&&((a=e.rotation)!=null&&a.angle)&&typeof Path2D!="undefined"){t.strokeStyle="pink";let n=e.box[0]+e.box[2]/2-e.box[3]*cl(e.rotation.angle.yaw)/90,r=e.box[1]+e.box[3]/2+e.box[2]*cl(e.rotation.angle.pitch)/90,s=new Path2D(`
      M ${e.box[0]+e.box[2]/2} ${e.box[1]}
      C
        ${n} ${e.box[1]},
        ${n} ${e.box[1]+e.box[3]},
        ${e.box[0]+e.box[2]/2} ${e.box[1]+e.box[3]}
    `),i=new Path2D(`
      M ${e.box[0]} ${e.box[1]+e.box[3]/2}
      C 
        ${e.box[0]} ${r},
        ${e.box[0]+e.box[2]} ${r},
        ${e.box[0]+e.box[2]} ${e.box[1]+e.box[3]/2}
    `);t.stroke(i),t.stroke(s)}}function Fge(e,t){var a;if(rt.drawGaze&&((a=e.rotation)!=null&&a.gaze.strength)&&e.rotation.gaze.bearing&&e.annotations.leftEyeIris&&e.annotations.rightEyeIris&&e.annotations.leftEyeIris[0]&&e.annotations.rightEyeIris[0]){t.strokeStyle="pink",t.fillStyle="pink";let n=[e.annotations.leftEyeIris[0][0]+Math.sin(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[3],e.annotations.leftEyeIris[0][1]+Math.cos(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[2]];oy(t,[e.annotations.leftEyeIris[0][0],e.annotations.leftEyeIris[0][1]],[n[0],n[1]],4);let r=[e.annotations.rightEyeIris[0][0]+Math.sin(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[3],e.annotations.rightEyeIris[0][1]+Math.cos(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[2]];oy(t,[e.annotations.rightEyeIris[0][0],e.annotations.rightEyeIris[0][1]],[r[0],r[1]],4)}}function Dge(e,t){if(rt.drawPolygons&&e.mesh.length>=468){t.lineWidth=1;for(let a=0;a<fl.length/3;a++){let n=[fl[a*3+0],fl[a*3+1],fl[a*3+2]].map(r=>e.mesh[r]);iy(t,n,rt)}Pge(e,t)}}function Oge(e,t){if(rt.drawPoints)if((e==null?void 0:e.mesh.length)>=468)for(let a=0;a<e.mesh.length;a++)ur(t,e.mesh[a][0],e.mesh[a][1],e.mesh[a][2],rt),rt.drawAttention&&(uc.includes(a)&&ur(t,e.mesh[a][0],e.mesh[a][1],e.mesh[a][2]+127,rt),gl.includes(a)&&ur(t,e.mesh[a][0],e.mesh[a][1],e.mesh[a][2]-127,rt),yl.includes(a)&&ur(t,e.mesh[a][0],e.mesh[a][1],e.mesh[a][2]-127,rt));else for(let[a,n]of Object.entries((e==null?void 0:e.annotations)||{})){if(!(n!=null&&n[0]))continue;let r=n[0];ur(t,r[0],r[1],0,rt),rt.drawLabels&&wn(t,a,r[0],r[1],rt)}}function zge(e,t){rt.drawBoxes&&dr(t,e.box[0],e.box[1],e.box[2],e.box[3],rt)}function v0(e,t,a){if(rt=Et(Ft,a),!t||!e)return;let n=vn(e);if(n){n.font=rt.font,n.strokeStyle=rt.color,n.fillStyle=rt.color;for(let r of t)zge(r,n),$ge(r,n),r.mesh&&r.mesh.length>0&&(Oge(r,n),Dge(r,n),_ge(r,n),Fge(r,n))}}function w0(e,t,a){var s,i;let n=Et(Ft,a);if(!t||!e)return;let r=vn(e);if(r){r.lineJoin="round";for(let o=0;o<t.length;o++){if(r.strokeStyle=n.color,r.fillStyle=n.color,r.lineWidth=n.lineWidth,r.font=n.font,n.drawBoxes&&t[o].box&&t[o].box.length===4&&(dr(r,t[o].box[0],t[o].box[1],t[o].box[2],t[o].box[3],n),n.drawLabels&&((s=n.bodyLabels)==null?void 0:s.length)>0)){let l=n.bodyLabels.slice();l=ut(l,"[id]",t[o].id.toFixed(0)),l=ut(l,"[score]",100*t[o].score),wn(r,l,t[o].box[0],t[o].box[1],n)}if(n.drawPoints&&t[o].keypoints)for(let l=0;l<t[o].keypoints.length;l++)!t[o].keypoints[l].score||t[o].keypoints[l].score===0||(r.fillStyle=hl(t[o].keypoints[l].position[2],n),ur(r,t[o].keypoints[l].position[0],t[o].keypoints[l].position[1],0,n));if(n.drawLabels&&((i=n.bodyPartLabels)==null?void 0:i.length)>0&&t[o].keypoints){r.font=n.font;for(let l of t[o].keypoints){if(!l.score||l.score===0)continue;let u=n.bodyPartLabels.slice();u=ut(u,"[label]",l.part),u=ut(u,"[score]",100*l.score),wn(r,u,l.position[0],l.position[1],n)}}if(n.drawPolygons&&t[o].keypoints&&t[o].annotations)for(let l of Object.values(t[o].annotations))for(let u of l)h9(r,u,n)}}}function k0(e,t,a){var s,i;let n=Et(Ft,a);if(!t||!e)return;let r=vn(e);if(r){r.lineJoin="round",r.font=n.font;for(let o of t){if(n.drawBoxes){if(r.strokeStyle=n.color,r.fillStyle=n.color,dr(r,o.box[0],o.box[1],o.box[2],o.box[3],n),n.drawLabels&&((s=n.handLabels)==null?void 0:s.length)>0){let l=n.handLabels.slice();l=ut(l,"[id]",o.id.toFixed(0)),l=ut(l,"[label]",o.label),l=ut(l,"[score]",100*o.score),wn(r,l,o.box[0],o.box[1],n)}r.stroke()}if(n.drawPoints&&o.keypoints&&o.keypoints.length>0)for(let l of o.keypoints)r.fillStyle=hl(l[2],n),ur(r,l[0],l[1],0,n);if(n.drawLabels&&o.annotations&&((i=n.fingerLabels)==null?void 0:i.length)>0)for(let[l,u]of Object.entries(o.annotations)){let p=n.fingerLabels.slice();p=ut(p,"[label]",l),wn(r,p,u[u.length-1][0],u[u.length-1][1],n)}if(n.drawPolygons&&o.annotations){let l=u=>{if(!(!u||u.length===0||!u[0]))for(let p=0;p<u.length;p++){r.beginPath();let c=u[p][2]||0;r.strokeStyle=hl(p*c,n),r.moveTo(u[p>0?p-1:0][0],u[p>0?p-1:0][1]),r.lineTo(u[p][0],u[p][1]),r.stroke()}};r.lineWidth=n.lineWidth,l(o.annotations.index),l(o.annotations.middle),l(o.annotations.ring),l(o.annotations.pinky),l(o.annotations.thumb)}}}}function I0(e,t,a){var s;let n=Et(Ft,a);if(!t||!e)return;let r=vn(e);if(r){r.lineJoin="round",r.font=n.font;for(let i of t)if(n.drawBoxes){if(r.strokeStyle=n.color,r.fillStyle=n.color,dr(r,i.box[0],i.box[1],i.box[2],i.box[3],n),n.drawLabels&&((s=n.objectLabels)==null?void 0:s.length)>0){let o=n.objectLabels.slice();o=ut(o,"[id]",i.id.toFixed(0)),o=ut(o,"[label]",i.label),o=ut(o,"[score]",100*i.score),wn(r,o,i.box[0],i.box[1],n)}r.stroke()}}}function S0(e,t,a){var r;let n=Et(Ft,a);if(!(!t||!e)&&n.drawGestures&&((r=n.gestureLabels)==null?void 0:r.length)>0){let s=vn(e);if(!s)return;s.font=n.font,s.fillStyle=n.color;let i=1;for(let o=0;o<t.length;o++){let[l,u]=Object.entries(t[o]);if(u.length>1&&u[1].length>0){let p=l[1]>0?`#${l[1]}`:"",c=n.gestureLabels.slice();c=ut(c,"[where]",l[0]),c=ut(c,"[who]",p),c=ut(c,"[what]",u[1]),wn(s,c,8,2+i*n.lineHeight,n),i+=1}}}}var vs={face:`face
    confidence: [score]%
    [gender] [genderScore]%
    age: [age] years
    distance: [distance]cm
    real: [real]%
    live: [live]%
    [emotions]
    roll: [roll]\xB0 yaw:[yaw]\xB0 pitch:[pitch]\xB0
    gaze: [gaze]\xB0`,body:"body [score]%",bodyPart:"[label] [score]%",object:"[label] [score]%",hand:"[label] [score]%",finger:"[label]",gesture:"[where] [who]: [what]"};var py=0;function Lge(e,t,a){let n=Et(Ft,a);if(!t||!e)return;let r=vn(e);if(r){r.lineJoin="round",r.font=n.font;for(let s=0;s<t.length;s++)if(n.drawBoxes){if(r.strokeStyle=n.color,r.fillStyle=n.color,dr(r,t[s].box[0],t[s].box[1],t[s].box[2],t[s].box[3],n),n.drawLabels){let i=`person #${s}`;n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(i,t[s].box[0]+3,1+t[s].box[1]+n.lineHeight,t[s].box[2])),r.fillStyle=n.labelColor,r.fillText(i,t[s].box[0]+2,0+t[s].box[1]+n.lineHeight,t[s].box[2])}r.stroke()}}}function Wge(e,t){if(!e||!t)return;let a=vn(t);a&&a.drawImage(e,0,0)}async function Bge(e,t){!e||!t||ne.browser&&await Un.toPixels(e,t)}async function Vge(e,t,a){if(!(t!=null&&t.performance)||!e)return null;let n=ae(),r=Et(Ft,a),s=Promise.all([v0(e,t.face,r),w0(e,t.body,r),k0(e,t.hand,r),I0(e,t.object,r),S0(e,t.gesture,r)]);return py=ne.perfadd?py+Math.round(ae()-n):Math.round(ae()-n),t.performance.draw=py,s}function cy(){Ft.faceLabels=vs.face,Ft.bodyLabels=vs.body,Ft.bodyPartLabels=vs.bodyPart,Ft.handLabels=vs.hand,Ft.fingerLabels=vs.finger,Ft.objectLabels=vs.object,Ft.gestureLabels=vs.gesture}var T0={};Ar(T0,{connected:()=>my,kpt:()=>hy});var hy=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftPinky","rightPinky","leftIndex","rightIndex","leftThumb","rightThumb","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle","leftHeel","rightHeel","leftFoot","rightFoot","bodyCenter","bodyTop","leftPalm","leftHand","rightPalm","rightHand"],my={shoulders:["leftShoulder","rightShoulder"],hips:["rightHip","leftHip"],mouth:["leftMouth","rightMouth"],leftLegUpper:["leftHip","leftKnee"],leftLegLower:["leftKnee","leftAnkle"],leftFoot:["leftAnkle","leftHeel","leftFoot"],leftTorso:["leftShoulder","leftHip"],leftArmUpper:["leftShoulder","leftElbow"],leftArmLower:["leftElbow","leftWrist"],leftHand:["leftWrist","leftPalm"],leftHandPinky:["leftPalm","leftPinky"],leftHandIndex:["leftPalm","leftIndex"],leftHandThumb:["leftPalm","leftThumb"],leftEyeOutline:["leftEyeInside","leftEyeOutside"],rightLegUpper:["rightHip","rightKnee"],rightLegLower:["rightKnee","rightAnkle"],rightFoot:["rightAnkle","rightHeel","rightFoot"],rightTorso:["rightShoulder","rightHip"],rightArmUpper:["rightShoulder","rightElbow"],rightArmLower:["rightElbow","rightWrist"],rightHand:["rightWrist","rightPalm"],rightHandPinky:["rightPalm","rightPinky"],rightHandIndex:["rightPalm","rightIndex"],rightHandThumb:["rightPalm","rightThumb"],rightEyeOutline:["rightEyeInside","rightEyeOutside"]};var kn,xl=224,g9,Uge=5,N0=[8,16,32,32,32];function Gge(){let e=[],t=0;for(;t<Uge;){let a=0,n=t;for(;n<N0.length&&N0[n]===N0[t];)a+=2,n++;let r=N0[t],s=Math.ceil(xl/r),i=Math.ceil(xl/r);for(let o=0;o<s;++o)for(let l=0;l<i;++l)for(let u=0;u<a;++u)e.push({x:(l+.5)/i,y:(o+.5)/s});t=n}g9={x:Bt(e.map(a=>a.x)),y:Bt(e.map(a=>a.y))}}async function y9(e){if(ne.initial&&(kn=null),!kn&&e.body.detector&&e.body.detector.modelPath){kn=await $e(e.body.detector.modelPath);let t=kn!=null&&kn.executor?Object.values(kn.modelSignature.inputs):void 0;xl=Array.isArray(t)?parseInt(t[0].tensorShape.dim[1].size):0}else e.debug&&kn&&K("cached model:",kn.modelUrl);return Gge(),kn}var f9=[5,5];function Hge(e,t){return De(()=>{let a=Sa(e,12,1),n=Oe(a[0]),r=Oe(a[1]),s=Oe(a[2]),i=Oe(a[3]);n=we(ve(n,xl),t.x),r=we(ve(r,xl),t.y),s=te(ve(s,xl),f9[0]),i=te(ve(i,xl),f9[1]);let o=xe(n,ve(s,2)),l=xe(r,ve(i,2)),u=we(o,s),p=we(l,i);return ha([o,l,u,p],1)})}async function jge(e,t,a,n){var u,p;let r=[],s={};s.boxes=Hge(e,g9),s.scores=za(t),s.nms=await fe.nonMaxSuppressionAsync(s.boxes,s.scores,1,((u=a.body.detector)==null?void 0:u.minConfidence)||.1,((p=a.body.detector)==null?void 0:p.iouThreshold)||.1);let i=await s.nms.data(),o=await s.scores.data(),l=await s.boxes.array();for(let c of Array.from(i)){let d=o[c],h=l[c],m=[Math.round(h[0]*n[0]),Math.round(h[1]*n[1]),Math.round(h[2]*n[0]),Math.round(h[3]*n[1])],f={score:d,boxRaw:h,box:m};r.push(f)}return Object.keys(s).forEach(c=>J(s[c])),r}async function x9(e,t,a){let n={};n.res=kn==null?void 0:kn.execute(e,["Identity"]),n.logitsRaw=Fe(n.res,[0,0,0],[1,-1,1]),n.boxesRaw=Fe(n.res,[0,0,1],[1,-1,-1]),n.logits=Oe(n.logitsRaw),n.boxes=Oe(n.boxesRaw);let r=await jge(n.boxes,n.logits,t,a);return Object.keys(n).forEach(s=>J(n[s])),r}function ws(e,t=[1,1]){let a=[e.map(o=>o[0]),e.map(o=>o[1])],n=[Math.min(...a[0]),Math.min(...a[1])],r=[Math.max(...a[0]),Math.max(...a[1])],s=[n[0],n[1],r[0]-n[0],r[1]-n[1]],i=[s[0]/t[0],s[1]/t[1],s[2]/t[0],s[3]/t[1]];return{box:s,boxRaw:i}}function A9(e,t=[1,1]){let a=[e.map(u=>u[0]),e.map(u=>u[1])],n=[Math.min(...a[0]),Math.min(...a[1])],r=[Math.max(...a[0]),Math.max(...a[1])],s=[(n[0]+r[0])/2,(n[1]+r[1])/2],i=Math.max(s[0]-n[0],s[1]-n[1],-s[0]+r[0],-s[1]+r[1]),o=[Math.trunc(s[0]-i),Math.trunc(s[1]-i),Math.trunc(2*i),Math.trunc(2*i)],l=[o[0]/t[0],o[1]/t[1],o[2]/t[0],o[3]/t[1]];return{box:o,boxRaw:l}}function R0(e,t){let a=[e[2]*t,e[3]*t];return[e[0]-(a[0]-e[2])/2,e[1]-(a[1]-e[3])/2,a[0],a[1]]}var Ua,gy=256,fy=Number.MAX_SAFE_INTEGER,qge={landmarks:["ld_3d","activation_segmentation","activation_heatmap","world_3d","output_poseflag"],detector:[]},M0=[],ks=[[0,0],[0,0],[0,0],[0,0]],b9=0,v9=e=>1-1/(1+Math.exp(e)),k9=e=>y9(e);async function I9(e){if(ne.initial&&(Ua=null),Ua)e.debug&&K("cached model:",Ua.modelUrl);else{Ua=await $e(e.body.modelPath);let t=Ua!=null&&Ua.executor?Object.values(Ua.modelSignature.inputs):void 0;gy=Array.isArray(t)?parseInt(t[0].tensorShape.dim[1].size):0}return Ua}function w9(e,t,a){var s,i;let n={};if(!((s=e==null?void 0:e.shape)!=null&&s[1])||!((i=e==null?void 0:e.shape)!=null&&i[2]))return e;let r;if(a&&(n.cropped=fe.cropAndResize(e,[a],[0],[e.shape[1],e.shape[2]])),e.shape[1]!==e.shape[2]){let o=[e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0,e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0],l=[e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0,e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0];ks=[[0,0],o,l,[0,0]],n.pad=Rn(n.cropped||e,ks),n.resize=fe.resizeBilinear(n.pad,[t,t]),r=ve(n.resize,ze.tf255)}else e.shape[1]!==t?(n.resize=fe.resizeBilinear(n.cropped||e,[t,t]),r=ve(n.resize,ze.tf255)):r=ve(n.cropped||e,ze.tf255);return Object.keys(n).forEach(o=>J(n[o])),r}function Xge(e,t,a){for(let n of e)n.position=[Math.trunc(n.position[0]*(t[0]+ks[2][0]+ks[2][1])/t[0]-ks[2][0]),Math.trunc(n.position[1]*(t[1]+ks[1][0]+ks[1][1])/t[1]-ks[1][0]),n.position[2]],n.positionRaw=[n.position[0]/t[0],n.position[1]/t[1],2*n.position[2]/(t[0]+t[1])];if(a){let n=a[2]-a[0],r=a[3]-a[1];for(let s of e)s.positionRaw=[s.positionRaw[0]/r+a[1],s.positionRaw[1]/n+a[0],s.positionRaw[2]],s.position=[Math.trunc(s.positionRaw[0]*t[0]),Math.trunc(s.positionRaw[1]*t[1]),s.positionRaw[2]]}return e}function Kge(e){let t=e.find(o=>o.part==="leftPalm"),a=e.find(o=>o.part==="leftWrist"),n=e.find(o=>o.part==="leftIndex");t.position[2]=((a.position[2]||0)+(n.position[2]||0))/2;let r=e.find(o=>o.part==="rightPalm"),s=e.find(o=>o.part==="rightWrist"),i=e.find(o=>o.part==="rightIndex");r.position[2]=((s.position[2]||0)+(i.position[2]||0))/2}async function Yge(e,t,a){if(!(Ua!=null&&Ua.executor))return null;let n={};[n.ld,n.segmentation,n.heatmap,n.world,n.poseflag]=Ua==null?void 0:Ua.execute(e,qge.landmarks);let r=(await n.poseflag.data())[0],s=await n.ld.data(),i=await n.world.data();Object.keys(n).forEach(m=>J(n[m]));let o=[],l=5;for(let m=0;m<s.length/l;m++){let f=v9(s[l*m+3]),g=v9(s[l*m+4]),y=Math.trunc(100*f*g*r)/100,x=[s[l*m+0]/gy,s[l*m+1]/gy,s[l*m+2]+0],A=[Math.trunc(a[0]*x[0]),Math.trunc(a[1]*x[1]),x[2]],b=[i[l*m+0],i[l*m+1],i[l*m+2]+0];o.push({part:hy[m],positionRaw:x,position:A,distance:b,score:y})}if(r<(t.body.minConfidence||0))return null;Kge(o);let u=Xge(o,a),p=u.map(m=>m.position),c=ws(p,[a[0],a[1]]),d={};for(let[m,f]of Object.entries(my)){let g=[];for(let y=0;y<f.length-1;y++){let x=u.find(b=>b.part===f[y]),A=u.find(b=>b.part===f[y+1]);x&&A&&g.push([x.position,A.position])}d[m]=g}return{id:0,score:Math.trunc(100*r)/100,box:c.box,boxRaw:c.boxRaw,keypoints:u,annotations:d}}async function yy(e,t){var s,i,o;let a=[e.shape[2]||0,e.shape[1]||0],n=(t.body.skipTime||0)>ae()-b9,r=fy<(t.body.skipFrames||0);if(t.skipAllowed&&n&&r&&M0!==null)fy++;else{let l=[];if((i=(s=t.body)==null?void 0:s.detector)!=null&&i.enabled){let u=w9(e,224);l=await x9(u,t,a),J(u)}else l=[{box:[0,0,0,0],boxRaw:[0,0,1,1],score:0}];for(let u=0;u<l.length;u++){let p=w9(e,256,(o=l[u])==null?void 0:o.boxRaw);M0.length=0;let c=await Yge(p,t,a);J(p),c&&(c.id=u,M0.push(c))}b9=ae(),fy=0}return M0}var rd=[{class:1,label:"person"},{class:2,label:"bicycle"},{class:3,label:"car"},{class:4,label:"motorcycle"},{class:5,label:"airplane"},{class:6,label:"bus"},{class:7,label:"train"},{class:8,label:"truck"},{class:9,label:"boat"},{class:10,label:"traffic light"},{class:11,label:"fire hydrant"},{class:12,label:"stop sign"},{class:13,label:"parking meter"},{class:14,label:"bench"},{class:15,label:"bird"},{class:16,label:"cat"},{class:17,label:"dog"},{class:18,label:"horse"},{class:19,label:"sheep"},{class:20,label:"cow"},{class:21,label:"elephant"},{class:22,label:"bear"},{class:23,label:"zebra"},{class:24,label:"giraffe"},{class:25,label:"backpack"},{class:26,label:"umbrella"},{class:27,label:"handbag"},{class:28,label:"tie"},{class:29,label:"suitcase"},{class:30,label:"frisbee"},{class:31,label:"skis"},{class:32,label:"snowboard"},{class:33,label:"sports ball"},{class:34,label:"kite"},{class:35,label:"baseball bat"},{class:36,label:"baseball glove"},{class:37,label:"skateboard"},{class:38,label:"surfboard"},{class:39,label:"tennis racket"},{class:40,label:"bottle"},{class:41,label:"wine glass"},{class:42,label:"cup"},{class:43,label:"fork"},{class:44,label:"knife"},{class:45,label:"spoon"},{class:46,label:"bowl"},{class:47,label:"banana"},{class:48,label:"apple"},{class:49,label:"sandwich"},{class:50,label:"orange"},{class:51,label:"broccoli"},{class:52,label:"carrot"},{class:53,label:"hot dog"},{class:54,label:"pizza"},{class:55,label:"donut"},{class:56,label:"cake"},{class:57,label:"chair"},{class:58,label:"couch"},{class:59,label:"potted plant"},{class:60,label:"bed"},{class:61,label:"dining table"},{class:62,label:"toilet"},{class:63,label:"tv"},{class:64,label:"laptop"},{class:65,label:"mouse"},{class:66,label:"remote"},{class:67,label:"keyboard"},{class:68,label:"cell phone"},{class:69,label:"microwave"},{class:70,label:"oven"},{class:71,label:"toaster"},{class:72,label:"sink"},{class:73,label:"refrigerator"},{class:74,label:"book"},{class:75,label:"clock"},{class:76,label:"vase"},{class:77,label:"scissors"},{class:78,label:"teddy bear"},{class:79,label:"hair drier"},{class:80,label:"toothbrush"}];var Ga,Al=0,xy=[],C9=0,Ay=Number.MAX_SAFE_INTEGER;async function T9(e){if(ne.initial&&(Ga=null),Ga)e.debug&&K("cached model:",Ga.modelUrl);else{Ga=await $e(e.object.modelPath);let t=Ga!=null&&Ga.executor?Object.values(Ga.modelSignature.inputs):void 0;Al=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}return Ga}async function Zge(e,t,a){if(!e)return[];let n={},r=[],s=await e.array();n.squeeze=Oe(e);let i=Sa(n.squeeze,6,1);n.stack=ha([i[1],i[0],i[3],i[2]],1),n.boxes=Oe(n.stack),n.scores=Oe(i[4]),n.classes=Oe(i[5]),J([e,...i]),n.nms=await fe.nonMaxSuppressionAsync(n.boxes,n.scores,a.object.maxDetected||0,a.object.iouThreshold,a.object.minConfidence||0);let o=await n.nms.data(),l=0;for(let u of Array.from(o)){let p=Math.trunc(100*s[0][u][4])/100,c=s[0][u][5];if(Number.isNaN(c))continue;let d=rd[c].label,[h,m]=[s[0][u][0]/Al,s[0][u][1]/Al],f=[h,m,s[0][u][2]/Al-h,s[0][u][3]/Al-m],g=[Math.trunc(f[0]*t[0]),Math.trunc(f[1]*t[1]),Math.trunc(f[2]*t[0]),Math.trunc(f[3]*t[1])];r.push({id:l++,score:p,class:c,label:d,box:g,boxRaw:f})}return Object.keys(n).forEach(u=>J(n[u])),r}async function by(e,t){if(!(Ga!=null&&Ga.executor))return[];let a=(t.object.skipTime||0)>ae()-C9,n=Ay<(t.object.skipFrames||0);return t.skipAllowed&&a&&n&&xy.length>0?(Ay++,xy):(Ay=0,new Promise(async r=>{let s=[e.shape[2]||0,e.shape[1]||0],i=fe.resizeBilinear(e,[Al,Al]),o=t.object.enabled?Ga==null?void 0:Ga.execute(i,["tower_0/detections"]):null;C9=ae(),J(i);let l=await Zge(o,s,t);xy=l,r(l)}))}var $0={};Ar($0,{connected:()=>wy,kpt:()=>vy});var vy=["head","neck","rightShoulder","rightElbow","rightWrist","chest","leftShoulder","leftElbow","leftWrist","bodyCenter","rightHip","rightKnee","rightAnkle","leftHip","leftKnee","leftAnkle"],wy={leftLeg:["leftHip","leftKnee","leftAnkle"],rightLeg:["rightHip","rightKnee","rightAnkle"],torso:["leftShoulder","rightShoulder","rightHip","leftHip","leftShoulder"],leftArm:["leftShoulder","leftElbow","leftWrist"],rightArm:["rightShoulder","rightElbow","rightWrist"],head:[]};var Mt,R9=0,Ma={id:0,keypoints:[],box:[0,0,0,0],boxRaw:[0,0,0,0],score:0,annotations:{}},ky=Number.MAX_SAFE_INTEGER;async function E9(e){return ne.initial&&(Mt=null),Mt?e.debug&&K("cached model:",Mt.modelUrl):Mt=await $e(e.body.modelPath),Mt}async function Jge(e,t){let[a,n]=e.shape,r=Q(e,[n*a]),s=ga(r,0),i=(await s.data())[0];if(i>t){let o=ir(r,0),l=Gu(o,a),u=(await l.data())[0],p=ve(o,a),c=(await p.data())[0];return J([r,s,o,l,p]),[u,c,i]}return J([r,s]),[0,0,i]}async function Iy(e,t){if(!(Mt!=null&&Mt.executor)||!(Mt!=null&&Mt.inputs[0].shape))return[];let a=(t.body.skipTime||0)>ae()-R9,n=ky<(t.body.skipFrames||0);return t.skipAllowed&&a&&n&&Object.keys(Ma.keypoints).length>0?(ky++,[Ma]):(ky=0,new Promise(async r=>{let s=De(()=>{var m,f;let c=fe.resizeBilinear(e,[((m=Mt==null?void 0:Mt.inputs[0].shape)==null?void 0:m[2])||0,((f=Mt==null?void 0:Mt.inputs[0].shape)==null?void 0:f[1])||0],!1),d=te(c,ze.tf2);return xe(d,ze.tf1)}),i;if(t.body.enabled&&(i=Mt==null?void 0:Mt.execute(s)),R9=ae(),J(s),i){Ma.keypoints.length=0;let c=Oe(i);J(i);let d=Na(c,2);J(c);for(let h=0;h<d.length;h++){let[m,f,g]=await Jge(d[h],t.body.minConfidence);g>(t.body.minConfidence||0)&&Ma.keypoints.push({score:Math.round(100*g)/100,part:vy[h],positionRaw:[m/Mt.inputs[0].shape[2],f/Mt.inputs[0].shape[1]],position:[Math.round(e.shape[2]*m/Mt.inputs[0].shape[2]),Math.round(e.shape[1]*f/Mt.inputs[0].shape[1])]})}d.forEach(h=>J(h))}Ma.score=Ma.keypoints.reduce((c,d)=>d.score>c?d.score:c,0);let o=Ma.keypoints.map(c=>c.position[0]),l=Ma.keypoints.map(c=>c.position[1]);Ma.box=[Math.min(...o),Math.min(...l),Math.max(...o)-Math.min(...o),Math.max(...l)-Math.min(...l)];let u=Ma.keypoints.map(c=>c.positionRaw[0]),p=Ma.keypoints.map(c=>c.positionRaw[1]);Ma.boxRaw=[Math.min(...u),Math.min(...p),Math.max(...u)-Math.min(...u),Math.max(...p)-Math.min(...p)];for(let[c,d]of Object.entries(wy)){let h=[];for(let m=0;m<d.length-1;m++){let f=Ma.keypoints.find(y=>y.part===d[m]),g=Ma.keypoints.find(y=>y.part===d[m+1]);f&&g&&f.score>(t.body.minConfidence||0)&&g.score>(t.body.minConfidence||0)&&h.push([f.position,g.position])}Ma.annotations[c]=h}r([Ma])}))}var sd=e=>[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])],P0=e=>[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2,1],_0=(e,t)=>e?[Math.trunc(Math.max(0,e.startPoint[0])),Math.trunc(Math.max(0,e.startPoint[1])),Math.trunc(Math.min(t.shape[2]||0,e.endPoint[0])-Math.max(0,e.startPoint[0])),Math.trunc(Math.min(t.shape[1]||0,e.endPoint[1])-Math.max(0,e.startPoint[1]))]:[0,0,0,0],F0=(e,t)=>e?[e.startPoint[0]/(t.shape[2]||0),e.startPoint[1]/(t.shape[1]||0),(e.endPoint[0]-e.startPoint[0])/(t.shape[2]||0),(e.endPoint[1]-e.startPoint[1])/(t.shape[1]||0)]:[0,0,0,0],_9=(e,t,a)=>{let n=[e.startPoint[0]*t[0],e.startPoint[1]*t[1]],r=[e.endPoint[0]*t[0],e.endPoint[1]*t[1]],s=e.landmarks.map(i=>[(i[0]+a[0])*t[0],(i[1]+a[1])*t[1]]);return{startPoint:n,endPoint:r,landmarks:s,confidence:e.confidence}},Sy=(e,t,a)=>{let n=t.shape[1],r=t.shape[2],s=[e.startPoint[1]/n,e.startPoint[0]/r,e.endPoint[1]/n,e.endPoint[0]/r],i=fe.cropAndResize(t,[s],[0],a),o=ve(i,ze.tf255);return J(i),o},D0=(e,t)=>{let a=P0(e),n=sd(e),r=[t*n[0]/2,t*n[1]/2];return{startPoint:[a[0]-r[0],a[1]-r[1]],endPoint:[a[0]+r[0],a[1]+r[1]],landmarks:e.landmarks,confidence:e.confidence,size:n}},O0=e=>{let t=P0(e),a=sd(e),n=Math.max(...a)/2;return{startPoint:[Math.round(t[0]-n),Math.round(t[1]-n)],endPoint:[Math.round(t[0]+n),Math.round(t[1]+n)],landmarks:e.landmarks,confidence:e.confidence,size:[Math.round(a[0]),Math.round(a[1])]}},F9=e=>{let t=e.map(n=>n[0]),a=e.map(n=>n[1]);return{startPoint:[Math.min(...t),Math.min(...a)],endPoint:[Math.max(...t),Math.max(...a)],landmarks:e}},Cy=[[1,0,0],[0,1,0],[0,0,1]],Qge=e=>e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI)),e3e=(e,t)=>Qge(Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]));var $9=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]],bl=(e,t)=>{let a=0;for(let n=0;n<e.length;n++)a+=e[n]*t[n];return a},t3e=(e,t)=>{let a=[];for(let n=0;n<e.length;n++)a.push(e[n][t]);return a},P9=(e,t)=>{let a=[],n=e.length;for(let r=0;r<n;r++){a.push([]);for(let s=0;s<n;s++)a[r].push(bl(e[r],t3e(t,s)))}return a},D9=(e,t)=>{let a=Math.cos(e),n=Math.sin(e),r=[[a,-n,0],[n,a,0],[0,0,1]],s=$9(t[0],t[1]),i=P9(s,r),o=$9(-t[0],-t[1]);return P9(i,o)},a3e=e=>{let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],a=[e[0][2],e[1][2]],n=[-bl(t[0],a),-bl(t[1],a)];return[t[0].concat(n[0]),t[1].concat(n[1]),[0,0,1]]},n3e=(e,t)=>[bl(e,t[0]),bl(e,t[1])];function O9(e){let t=e===192?{strides:[4],anchors:[1]}:{strides:[e/16,e/8],anchors:[2,6]},a=[];for(let n=0;n<t.strides.length;n++){let r=t.strides[n],s=Math.floor((e+r-1)/r),i=Math.floor((e+r-1)/r),o=t.anchors[n];for(let l=0;l<s;l++){let u=r*(l+.5);for(let p=0;p<i;p++){let c=r*(p+.5);for(let d=0;d<o;d++)a.push([c,u])}}}return a}function z9(e,t,a,n,r){let s=sd(t),i=e.map(h=>[s[0]/r*(h[0]-r/2),s[1]/r*(h[1]-r/2),h[2]||0]),o=a&&a!==0&&Math.abs(a)>.2,l=o?D9(a,[0,0]):Cy,u=o?i.map(h=>[...n3e(h,l),h[2]]):i,p=o?a3e(n):Cy,c=P0(t),d=[bl(c,p[0]),bl(c,p[1])];return u.map(h=>[Math.trunc(h[0]+d[0]),Math.trunc(h[1]+d[1]),Math.trunc(h[2]||0)])}function L9(e,t,a,n){let r=t.landmarks.length>=ly.count?ly.symmetryLine:ml.symmetryLine,s=0,i=Cy,o;if(e&&ne.kernels.includes("rotatewithoffset"))if(s=e3e(t.landmarks[r[0]],t.landmarks[r[1]]),s&&s!==0&&Math.abs(s)>.2){let u=P0(t),p=[u[0]/a.shape[2],u[1]/a.shape[1]],c=fe.rotateWithOffset(a,s,0,[p[0],p[1]]);i=D9(-s,u),o=Sy(t,c,[n,n]),J(c)}else o=Sy(t,a,[n,n]);else o=Sy(t,a,[n,n]);return[s,i,o]}var r3e=e=>{let t=e.map(n=>n[0]),a=e.map(n=>n[1]);return[Math.min(...t)+(Math.max(...t)-Math.min(...t))/2,Math.min(...a)+(Math.max(...a)-Math.min(...a))/2]},W9=(e,t)=>{let a=r3e(e),n=sd(t);return{startPoint:[a[0]-n[0]/2,a[1]-n[1]/2],endPoint:[a[0]+n[0]/2,a[1]+n[1]/2]}};var B9=6,Gn,z0=null,pr=0,id=null,V9=()=>pr;async function U9(e){var t;return ne.initial&&(Gn=null),Gn?e.debug&&K("cached model:",Gn.modelUrl):Gn=await $e((t=e.face.detector)==null?void 0:t.modelPath),pr=Gn.executor&&Gn.inputs[0].shape?Gn.inputs[0].shape[2]:256,id=Ge(pr,"int32"),z0=Qn(O9(pr)),Gn}function s3e(e){if(!z0||!id)return yn([0,0]);let t={};t.boxStarts=Fe(e,[0,1],[-1,2]),t.centers=we(t.boxStarts,z0),t.boxSizes=Fe(e,[0,3],[-1,2]),t.boxSizesNormalized=ve(t.boxSizes,id),t.centersNormalized=ve(t.centers,id),t.halfBoxSize=ve(t.boxSizesNormalized,ze.tf2),t.starts=xe(t.centersNormalized,t.halfBoxSize),t.ends=we(t.centersNormalized,t.halfBoxSize),t.startNormalized=te(t.starts,id),t.endNormalized=te(t.ends,id);let a=Uu([t.startNormalized,t.endNormalized],1);return Object.keys(t).forEach(n=>J(t[n])),a}async function G9(e,t){var u,p,c,d,h,m,f,g,y;if(!e||e.isDisposedInternal||e.shape.length!==4||e.shape[1]<1||e.shape[2]<1)return[];let a={},n=[0,0],r=[1,1];if((p=(u=t==null?void 0:t.face)==null?void 0:u.detector)!=null&&p.square){let x=Math.max(e.shape[2],e.shape[1]);n=[Math.floor((x-e.shape[2])/2),Math.floor((x-e.shape[1])/2)],a.padded=Rn(e,[[0,0],[n[1],n[1]],[n[0],n[0]],[0,0]]),r=[e.shape[2]/x,e.shape[1]/x],n=[n[0]/pr,n[1]/pr]}else a.padded=e.clone();a.resized=fe.resizeBilinear(a.padded,[pr,pr]),a.div=ve(a.resized,ze.tf127),a.normalized=xe(a.div,ze.tf1);let s=Gn==null?void 0:Gn.execute(a.normalized);if(Array.isArray(s)&&s.length>2){let x=s.sort((A,b)=>A.size-b.size);a.concat384=lt([x[0],x[2]],2),a.concat512=lt([x[1],x[3]],2),a.concat=lt([a.concat512,a.concat384],1),a.batch=Oe(a.concat,[0])}else Array.isArray(s)?a.batch=Oe(s[0]):a.batch=Oe(s);J(s),a.boxes=s3e(a.batch),a.logits=Fe(a.batch,[0,0],[-1,1]),a.sigmoid=za(a.logits),a.scores=Oe(a.sigmoid),a.nms=await fe.nonMaxSuppressionAsync(a.boxes,a.scores,((c=t.face.detector)==null?void 0:c.maxDetected)||0,((d=t.face.detector)==null?void 0:d.iouThreshold)||0,((h=t.face.detector)==null?void 0:h.minConfidence)||0);let i=await a.nms.array(),o=[],l=await a.scores.data();for(let x=0;x<i.length;x++){let A=l[i[x]];if(A>(((m=t.face.detector)==null?void 0:m.minConfidence)||0)){let b={};b.bbox=Fe(a.boxes,[i[x],0],[1,-1]),b.slice=Fe(a.batch,[i[x],B9-1],[1,-1]),b.squeeze=Oe(b.slice),b.landmarks=Q(b.squeeze,[B9,-1]);let w=await b.bbox.data(),I=[w[0]*r[0]-n[0],w[1]*r[1]-n[1],w[2]*r[0]-n[0],w[3]*r[1]-n[1]],T={startPoint:[I[0],I[1]],endPoint:[I[2],I[3]],landmarks:await b.landmarks.array(),confidence:A};b.anchor=Fe(z0,[i[x],0],[1,2]);let N=await b.anchor.data(),M=_9(T,[(e.shape[2]||0)/pr,(e.shape[1]||0)/pr],N),$=D0(M,((f=t.face.detector)==null?void 0:f.scale)||1.4),E=O0($);E.size[0]>(((g=t.face.detector)==null?void 0:g.minSize)||0)&&E.size[1]>(((y=t.face.detector)==null?void 0:y.minSize)||0)&&o.push(E),Object.keys(b).forEach(S=>J(b[S]))}}return Object.keys(a).forEach(x=>J(a[x])),o}var nn,Is=0,Ny=Pn.leftEyeLower0,Ry=Pn.rightEyeLower0,od={leftBounds:[Ny[0],Ny[Ny.length-1]],rightBounds:[Ry[0],Ry[Ry.length-1]]},ld={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};async function K9(e){var t,a;return ne.initial&&(nn=null),nn?e.debug&&K("cached model:",nn.modelUrl):nn=await $e((t=e.face.iris)==null?void 0:t.modelPath),Is=nn!=null&&nn.executor&&((a=nn.inputs)!=null&&a[0].shape)?nn.inputs[0].shape[2]:0,Is===-1&&(Is=64),nn}function L0(e,t,a,n){for(let r=0;r<uy.length;r++){let{key:s,indices:i}=uy[r],o=Pn[`${a}${s}`];if(!n||n.includes(s))for(let l=0;l<i.length;l++){let u=i[l];e[o[l]]=[t[u][0],t[u][1],(t[u][2]+e[o[l]][2])/2]}}}var i3e=e=>{let t=e[od.leftBounds[0]][2],a=e[od.rightBounds[0]][2];return t-a},j9=(e,t,a,n,r,s=!1,i=2.3)=>{let o=O0(D0(F9([e[a],e[n]]),i)),l=sd(o),u=fe.cropAndResize(t,[[o.startPoint[1]/r,o.startPoint[0]/r,o.endPoint[1]/r,o.endPoint[0]/r]],[0],[Is,Is]);if(s&&ne.kernels.includes("flipleftright")){let p=fe.flipLeftRight(u);J(u),u=p}return{box:o,boxSize:l,crop:u}},q9=(e,t,a,n=!1)=>{let r=[];for(let s=0;s<ld.numCoordinates;s++){let i=e[s*3],o=e[s*3+1],l=e[s*3+2];r.push([(n?1-i/Is:i/Is)*a[0]+t.startPoint[0],o/Is*a[1]+t.startPoint[1],l])}return{rawCoords:r,iris:r.slice(ld.index)}},X9=(e,t,a)=>{let n=e[Pn[`${a}EyeUpper0`][ld.upperCenter]][2],r=e[Pn[`${a}EyeLower0`][ld.lowerCenter]][2],s=(n+r)/2;return t.map((i,o)=>{let l=s;return o===2?l=n:o===4&&(l=r),[i[0],i[1],l]})};async function Y9(e,t,a,n){var T,N;if(!(nn!=null&&nn.executor))return e;let{box:r,boxSize:s,crop:i}=j9(e,t,od.leftBounds[0],od.leftBounds[1],a,!0,((T=n.face.iris)==null?void 0:T.scale)||2.3),{box:o,boxSize:l,crop:u}=j9(e,t,od.rightBounds[0],od.rightBounds[1],a,!0,((N=n.face.iris)==null?void 0:N.scale)||2.3),p=lt([i,u]);J(i),J(u);let c=nn.execute(p);J(p);let d=await c.data();J(c);let h=d.slice(0,ld.numCoordinates*3),{rawCoords:m,iris:f}=q9(h,r,s,!0),g=d.slice(ld.numCoordinates*3),{rawCoords:y,iris:x}=q9(g,o,l,!1),A=i3e(e);Math.abs(A)<30?(L0(e,m,"left",null),L0(e,y,"right",null)):A<1?L0(e,m,"left",["EyeUpper0","EyeLower0"]):L0(e,y,"right",["EyeUpper0","EyeLower0"]);let b=X9(e,f,"left"),w=X9(e,x,"right");return e.concat(b).concat(w)}async function J9(e,t){var s,i,o,l,u,p,c,d,h,m;let a={lips:await((i=(s=t.filter(f=>f.size===160))==null?void 0:s[0])==null?void 0:i.data()),irisL:await((l=(o=t.filter(f=>f.size===10))==null?void 0:o[0])==null?void 0:l.data()),eyeL:await((p=(u=t.filter(f=>f.size===142))==null?void 0:u[0])==null?void 0:p.data()),irisR:await((d=(c=t.filter(f=>f.size===10))==null?void 0:c[1])==null?void 0:d.data()),eyeR:await((m=(h=t.filter(f=>f.size===142))==null?void 0:h[1])==null?void 0:m.data())};for(let f of Object.values(a))if(!f)return e;let n=gl.reduce((f,g)=>f+=e[g][2],0)/gl.length;for(let f=0;f<a.irisL.length/2;f++)e.push([a.irisL[2*f+0],a.irisL[2*f+1],n]);let r=yl.reduce((f,g)=>f+=e[g][2],0)/yl.length;for(let f=0;f<a.irisR.length/2;f++)e.push([a.irisR[2*f+0],a.irisR[2*f+1],r]);for(let f=0;f<a.eyeL.length/2;f++)e[gl[f]]=[a.eyeL[2*f+0],a.eyeL[2*f+1],e[gl[f]][2]];for(let f=0;f<a.eyeR.length/2;f++)e[yl[f]]=[a.eyeR[2*f+0],a.eyeR[2*f+1],e[yl[f]][2]];for(let f=0;f<a.lips.length/2;f++)e[uc[f]]=[a.lips[2*f+0],a.lips[2*f+1],e[uc[f]][2]];return e}var cr={boxes:[],skipped:Number.MAX_SAFE_INTEGER,timestamp:0},Ct=null,dc=0;async function Q9(e,t){var l,u,p,c,d,h,m,f,g,y;let a=(((l=t.face.detector)==null?void 0:l.skipTime)||0)>ae()-cr.timestamp,n=cr.skipped<(((u=t.face.detector)==null?void 0:u.skipFrames)||0);!t.skipAllowed||!a||!n||cr.boxes.length===0?(cr.boxes=await G9(e,t),cr.timestamp=ae(),cr.skipped=0):cr.skipped++;let r=[],s=[],i=0,o=dc;for(let x=0;x<cr.boxes.length;x++){let A=cr.boxes[x],b=0,w,I={id:i++,mesh:[],meshRaw:[],box:[0,0,0,0],boxRaw:[0,0,0,0],score:0,boxScore:0,faceScore:0,size:[0,0],annotations:{}};if([b,w,I.tensor]=L9((p=t.face.detector)==null?void 0:p.rotation,A,e,(c=t.face.mesh)!=null&&c.enabled?dc:V9()),t.filter.equalization){let T=I.tensor?await m0(I.tensor):void 0;J(I.tensor),T&&(I.tensor=T)}if(I.boxScore=Math.round(100*A.confidence)/100,!((d=t.face.mesh)!=null&&d.enabled)||!(Ct!=null&&Ct.executor)){I.box=_0(A,e),I.boxRaw=F0(A,e),I.score=I.boxScore,I.size=A.size,I.mesh=A.landmarks,I.meshRaw=I.mesh.map(T=>[T[0]/(e.shape[2]||0),T[1]/(e.shape[1]||0),(T[2]||0)/o]);for(let T of Object.keys(ml))I.annotations[T]=[I.mesh[ml[T]]]}else if(!Ct)t.debug&&K("face mesh detection requested, but model is not loaded");else{if((h=t.face.attention)!=null&&h.enabled&&!ne.kernels.includes("atan2"))return t.face.attention.enabled=!1,J(I.tensor),r;let T=Ct.execute(I.tensor),M=await T.find($=>$.shape[$.shape.length-1]===1).data();if(I.faceScore=Math.round(100*M[0])/100,I.faceScore<(((m=t.face.detector)==null?void 0:m.minConfidence)||1)){if(A.confidence=I.faceScore,t.face.mesh.keepInvalid){I.box=_0(A,e),I.boxRaw=F0(A,e),I.size=A.size,I.score=I.boxScore,I.mesh=A.landmarks,I.meshRaw=I.mesh.map($=>[$[0]/(e.shape[2]||1),$[1]/(e.shape[1]||1),($[2]||0)/o]);for(let $ of Object.keys(ml))I.annotations[$]=[I.mesh[ml[$]]]}}else{let $=T.find(O=>O.shape[O.shape.length-1]===1404),E=Q($,[-1,3]),S=await E.array();J(E),(f=t.face.attention)!=null&&f.enabled?S=await J9(S,T):(g=t.face.iris)!=null&&g.enabled&&(S=await Y9(S,I.tensor,dc,t)),I.mesh=z9(S,A,b,w,dc),I.meshRaw=I.mesh.map(O=>[O[0]/(e.shape[2]||0),O[1]/(e.shape[1]||0),(O[2]||0)/o]);for(let O of Object.keys(Pn))I.annotations[O]=Pn[O].map(W=>I.mesh[W]);I.score=I.faceScore;let _={...W9(I.mesh,A),confidence:A.confidence,landmarks:A.landmarks,size:A.size};I.box=_0(_,e),I.boxRaw=F0(_,e),I.size=_.size,s.push(_)}J(T)}I.score>(((y=t.face.detector)==null?void 0:y.minConfidence)||1)?r.push(I):J(I.tensor)}return cr.boxes=s,r}async function eI(e){var t,a,n,r,s,i;return ne.initial&&(Ct=null),(t=e.face.attention)!=null&&t.enabled&&(Ct!=null&&Ct.signature)&&Object.keys(((a=Ct==null?void 0:Ct.signature)==null?void 0:a.outputs)||{}).length<6&&(Ct=null),Ct?e.debug&&K("cached model:",Ct.modelUrl):(n=e.face.attention)!=null&&n.enabled?Ct=await $e(e.face.attention.modelPath):Ct=await $e((r=e.face.mesh)==null?void 0:r.modelPath),dc=Ct.executor&&((s=Ct==null?void 0:Ct.inputs)!=null&&s[0].shape)?(i=Ct==null?void 0:Ct.inputs)==null?void 0:i[0].shape[2]:256,Ct}var tI=fl,aI=lc;var $y=[],sa,W0=[],nI=0,rI=0,My=Number.MAX_SAFE_INTEGER,Py=!1;async function sI(e){var t,a,n;return ne.initial&&(sa=null),sa?e.debug&&K("cached model:",sa.modelUrl):(sa=await $e((t=e.face.emotion)==null?void 0:t.modelPath),Py=((n=(a=sa==null?void 0:sa.inputs)==null?void 0:a[0].shape)==null?void 0:n[3])===3,Py?$y=["angry","disgust","fear","happy","neutral","sad","surprise"]:$y=["angry","disgust","fear","happy","sad","surprise","neutral"]),sa}async function _y(e,t,a,n){var i,o;if(!sa)return[];let r=My<(((i=t.face.emotion)==null?void 0:i.skipFrames)||0),s=(((o=t.face.emotion)==null?void 0:o.skipTime)||0)>ae()-rI;return t.skipAllowed&&s&&r&&nI===n&&W0[a]&&W0[a].length>0?(My++,W0[a]):(My=0,new Promise(async l=>{var p,c,d;let u=[];if((p=t.face.emotion)!=null&&p.enabled){let h={},m=sa!=null&&sa.inputs[0].shape?sa.inputs[0].shape[2]:0;if(((c=t.face.emotion)==null?void 0:c.crop)>0){let g=(d=t.face.emotion)==null?void 0:d.crop,y=[[g,g,1-g,1-g]];h.resize=fe.cropAndResize(e,y,[0],[m,m])}else h.resize=fe.resizeBilinear(e,[m,m],!1);Py?(h.mul=te(h.resize,255),h.normalize=xe(h.mul,[103.939,116.779,123.68]),h.emotion=sa==null?void 0:sa.execute(h.normalize)):(h.channels=te(h.resize,ze.rgb),h.grayscale=ot(h.channels,3,!0),h.grayscaleSub=xe(h.grayscale,ze.tf05),h.grayscaleMul=te(h.grayscaleSub,ze.tf2),h.emotion=sa==null?void 0:sa.execute(h.grayscaleMul)),rI=ae();let f=await h.emotion.data();for(let g=0;g<f.length;g++)f[g]>(t.face.emotion.minConfidence||0)&&u.push({score:Math.min(.99,Math.trunc(100*f[g])/100),emotion:$y[g]});u.sort((g,y)=>y.score-g.score),Object.keys(h).forEach(g=>J(h[g]))}W0[a]=u,nI=n,l(u)}))}var ia,Ss=[],oI=0,lI=0,Fy=Number.MAX_SAFE_INTEGER;async function uI(e){var t;return ne.initial&&(ia=null),ia?e.debug&&K("cached model:",ia.modelUrl):ia=await $e((t=e.face.description)==null?void 0:t.modelPath),ia}function l3e(e,t){var s,i;let a=e.image||e.tensor||e;if(!(ia!=null&&ia.inputs[0].shape))return a;let n;if(((s=t.face.description)==null?void 0:s.crop)>0){let o=(i=t.face.description)==null?void 0:i.crop,l=[[o,o,1-o,1-o]];n=fe.cropAndResize(a,l,[0],[ia.inputs[0].shape[2],ia.inputs[0].shape[1]])}else n=fe.resizeBilinear(a,[ia.inputs[0].shape[2],ia.inputs[0].shape[1]],!1);let r=te(n,ze.tf255);return J(n),r}async function Dy(e,t,a,n){var o,l,u,p;let r={age:0,gender:"unknown",genderScore:0,descriptor:[]};if(!(ia!=null&&ia.executor))return r;let s=Fy<(((o=t.face.description)==null?void 0:o.skipFrames)||0),i=(((l=t.face.description)==null?void 0:l.skipTime)||0)>ae()-oI;return t.skipAllowed&&s&&i&&lI===n&&((u=Ss==null?void 0:Ss[a])==null?void 0:u.age)>0&&((p=Ss==null?void 0:Ss[a])==null?void 0:p.genderScore)>0?(Fy++,Ss[a]):(Fy=0,new Promise(async c=>{var d;if((d=t.face.description)!=null&&d.enabled){let h=l3e(e,t),m=ia==null?void 0:ia.execute(h);oI=ae(),J(h);let g=await m.find(N=>N.shape[1]===1).data(),y=Math.trunc(200*Math.abs(g[0]-.5))/100;y>(t.face.description.minConfidence||0)&&(r.gender=g[0]<=.5?"female":"male",r.genderScore=Math.min(.99,y));let x=ir(m.find(N=>N.shape[1]===100),1),A=(await x.data())[0];J(x);let w=await m.find(N=>N.shape[1]===100).data();r.age=Math.round(w[A-1]>w[A+1]?10*A-100*w[A-1]:10*A+100*w[A+1])/10,(Number.isNaN(g[0])||Number.isNaN(w[0]))&&K("faceres error:",{model:ia,result:m});let I=m.find(N=>N.shape[1]===1024),T=I?await I.data():[];r.descriptor=Array.from(T),m.forEach(N=>J(N))}Ss[a]=r,lI=n,c(r)}))}var ud=.1,Oy=.5;function u3e(e,t,a){let n=!1,r=a.length-1;for(let s=0;s<a.length;r=s++)a[s].y>t!=a[r].y>t&&e<(a[r].x-a[s].x)*(t-a[s].y)/(a[r].y-a[s].y)+a[s].x&&(n=!n);return n}async function pI(e){if(!e.tensor||!e.mesh||e.mesh.length<100)return e.tensor;let t=e.tensor.shape[2]||0,a=e.tensor.shape[1]||0,n=await e.tensor.buffer(),r=[];for(let i of Pn.silhouette)r.push({x:(e.mesh[i][0]-e.box[0])/e.box[2],y:(e.mesh[i][1]-e.box[1])/e.box[3]});ud&&ud>0&&(r=r.map(i=>({x:i.x>.5?i.x+ud:i.x-ud,y:i.y>.5?i.y+ud:i.y-ud})));for(let i=0;i<t;i++)for(let o=0;o<a;o++)u3e(i/t,o/t,r)||(n.set(Oy*n.get(0,o,i,0),0,o,i,0),n.set(Oy*n.get(0,o,i,1),0,o,i,1),n.set(Oy*n.get(0,o,i,2),0,o,i,2));return n.toTensor()}var oa,B0=[],zy=Number.MAX_SAFE_INTEGER,cI=0,hI=0;async function mI(e){var t;return ne.initial&&(oa=null),oa?e.debug&&K("cached model:",oa.modelUrl):oa=await $e((t=e.face.antispoof)==null?void 0:t.modelPath),oa}async function Ly(e,t,a,n){var i,o;if(!(oa!=null&&oa.executor))return 0;let r=(((i=t.face.antispoof)==null?void 0:i.skipTime)||0)>ae()-hI,s=zy<(((o=t.face.antispoof)==null?void 0:o.skipFrames)||0);return t.skipAllowed&&r&&s&&cI===n&&B0[a]?(zy++,B0[a]):(zy=0,new Promise(async l=>{let u=fe.resizeBilinear(e,[oa!=null&&oa.inputs[0].shape?oa.inputs[0].shape[2]:0,oa!=null&&oa.inputs[0].shape?oa.inputs[0].shape[1]:0],!1),p=oa==null?void 0:oa.execute(u),c=(await p.data())[0];B0[a]=Math.round(100*c)/100,cI=n,hI=ae(),J([u,p]),l(B0[a])}))}var la,V0=[],Wy=Number.MAX_SAFE_INTEGER,gI=0,yI=0;async function xI(e){var t;return ne.initial&&(la=null),la?e.debug&&K("cached model:",la.modelUrl):la=await $e((t=e.face.liveness)==null?void 0:t.modelPath),la}async function By(e,t,a,n){var i,o;if(!(la!=null&&la.executor))return 0;let r=(((i=t.face.liveness)==null?void 0:i.skipTime)||0)>ae()-yI,s=Wy<(((o=t.face.liveness)==null?void 0:o.skipFrames)||0);return t.skipAllowed&&r&&s&&gI===n&&V0[a]?(Wy++,V0[a]):(Wy=0,new Promise(async l=>{let u=fe.resizeBilinear(e,[la!=null&&la.inputs[0].shape?la.inputs[0].shape[2]:0,la!=null&&la.inputs[0].shape?la.inputs[0].shape[1]:0],!1),p=la==null?void 0:la.execute(u),c=(await p.data())[0];V0[a]=Math.round(100*c)/100,gI=n,yI=ae(),J([u,p]),l(V0[a])}))}var _n,Vy=[],p3e=["white","black","asian","indian","other"],c3e=[15,23,28,35.5,45.5,55.5,65],bI=0,vI=0,Uy=Number.MAX_SAFE_INTEGER;async function wI(e){var t;return ne.initial&&(_n=null),_n?e.debug&&K("cached model:",_n.modelUrl):_n=await $e((t=e.face.gear)==null?void 0:t.modelPath),_n}async function Gy(e,t,a,n){var i,o;if(!_n)return{age:0,gender:"unknown",genderScore:0,race:[]};let r=Uy<(((i=t.face.gear)==null?void 0:i.skipFrames)||0),s=(((o=t.face.gear)==null?void 0:o.skipTime)||0)>ae()-vI;return t.skipAllowed&&s&&r&&bI===n&&Vy[a]?(Uy++,Vy[a]):(Uy=0,new Promise(async l=>{var y,x,A,b;if(!(_n!=null&&_n.inputs[0].shape))return;let u={},p=[[0,.1,.9,.9]];if(((y=t.face.gear)==null?void 0:y.crop)>0){let w=(x=t.face.gear)==null?void 0:x.crop;p=[[w,w,1-w,1-w]]}u.resize=fe.cropAndResize(e,p,[0],[_n.inputs[0].shape[2],_n.inputs[0].shape[1]]);let c={age:0,gender:"unknown",genderScore:0,race:[]};(A=t.face.gear)!=null&&A.enabled&&([u.age,u.gender,u.race]=_n.execute(u.resize,["age_output","gender_output","race_output"]));let d=await u.gender.data();c.gender=d[0]>d[1]?"male":"female",c.genderScore=Math.round(100*(d[0]>d[1]?d[0]:d[1]))/100;let h=await u.race.data();for(let w=0;w<h.length;w++)h[w]>(((b=t.face.gear)==null?void 0:b.minConfidence)||.2)&&c.race.push({score:Math.round(100*h[w])/100,race:p3e[w]});c.race.sort((w,I)=>I.score-w.score);let f=Array.from(await u.age.data()).map((w,I)=>[c3e[I],w]).sort((w,I)=>I[1]-w[1]),g=f[0][0];for(let w=1;w<f.length;w++)g+=f[w][1]*(f[w][0]-g);c.age=Math.round(10*g)/10,Object.keys(u).forEach(w=>J(u[w])),Vy[a]=c,bI=n,vI=ae(),l(c)}))}var $a,U0=[],II=0,SI=0,Hy=Number.MAX_SAFE_INTEGER;async function CI(e){return ne.initial&&($a=null),$a?e.debug&&K("cached model:",$a.modelUrl):$a=await $e(e.face.ssrnet.modelPathAge),$a}async function jy(e,t,a,n){var i,o,l,u;if(!$a)return{age:0};let r=Hy<(((i=t.face.ssrnet)==null?void 0:i.skipFrames)||0),s=(((o=t.face.ssrnet)==null?void 0:o.skipTime)||0)>ae()-SI;return t.skipAllowed&&r&&s&&II===n&&((l=U0[a])!=null&&l.age)&&((u=U0[a])==null?void 0:u.age)>0?(Hy++,U0[a]):(Hy=0,new Promise(async p=>{var h,m,f;if(!($a!=null&&$a.inputs)||!$a.inputs[0]||!$a.inputs[0].shape)return;let c={};if(((h=t.face.ssrnet)==null?void 0:h.crop)>0){let g=(m=t.face.ssrnet)==null?void 0:m.crop,y=[[g,g,1-g,1-g]];c.resize=fe.cropAndResize(e,y,[0],[$a.inputs[0].shape[2],$a.inputs[0].shape[1]])}else c.resize=fe.resizeBilinear(e,[$a.inputs[0].shape[2],$a.inputs[0].shape[1]],!1);c.enhance=te(c.resize,ze.tf255);let d={age:0};if((f=t.face.ssrnet)!=null&&f.enabled&&(c.age=$a.execute(c.enhance)),c.age){let g=await c.age.data();d.age=Math.trunc(10*g[0])/10}Object.keys(c).forEach(g=>J(c[g])),U0[a]=d,II=n,SI=ae(),p(d)}))}var xa,G0=[],NI=0,RI=0,qy=Number.MAX_SAFE_INTEGER,Xy=[.2989,.587,.114];async function EI(e){var t;return ne.initial&&(xa=null),xa?e.debug&&K("cached model:",xa.modelUrl):xa=await $e((t=e.face.ssrnet)==null?void 0:t.modelPathGender),xa}async function Ky(e,t,a,n){var i,o,l,u;if(!xa)return{gender:"unknown",genderScore:0};let r=qy<(((i=t.face.ssrnet)==null?void 0:i.skipFrames)||0),s=(((o=t.face.ssrnet)==null?void 0:o.skipTime)||0)>ae()-RI;return t.skipAllowed&&r&&s&&NI===n&&((l=G0[a])!=null&&l.gender)&&((u=G0[a])==null?void 0:u.genderScore)>0?(qy++,G0[a]):(qy=0,new Promise(async p=>{var m,f,g;if(!(xa!=null&&xa.inputs[0].shape))return;let c={};if(((m=t.face.ssrnet)==null?void 0:m.crop)>0){let y=(f=t.face.ssrnet)==null?void 0:f.crop,x=[[y,y,1-y,1-y]];c.resize=fe.cropAndResize(e,x,[0],[xa.inputs[0].shape[2],xa.inputs[0].shape[1]])}else c.resize=fe.resizeBilinear(e,[xa.inputs[0].shape[2],xa.inputs[0].shape[1]],!1);c.enhance=De(()=>{var x,A;let y;if(((A=(x=xa==null?void 0:xa.inputs)==null?void 0:x[0].shape)==null?void 0:A[3])===1){let[b,w,I]=Sa(c.resize,3,3),T=te(b,Xy[0]),N=te(w,Xy[1]),M=te(I,Xy[2]),$=Dh([T,N,M]);y=te(xe($,ze.tf05),2)}else y=te(xe(c.resize,ze.tf05),2);return y});let d={gender:"unknown",genderScore:0};(g=t.face.ssrnet)!=null&&g.enabled&&(c.gender=xa.execute(c.enhance));let h=await c.gender.data();d.gender=h[0]>h[1]?"female":"male",d.genderScore=h[0]>h[1]?Math.trunc(100*h[0])/100:Math.trunc(100*h[1])/100,Object.keys(c).forEach(y=>J(c[y])),G0[a]=d,NI=n,RI=ae(),p(d)}))}var rn,Yy=[],$I=0,PI=0,_I=Number.MAX_SAFE_INTEGER;async function FI(e){var t;return ne.initial&&(rn=null),rn?e.debug&&K("cached model:",rn.modelUrl):rn=await $e((t=e.face.mobilefacenet)==null?void 0:t.modelPath),rn}async function Zy(e,t,a,n){var i,o;if(!(rn!=null&&rn.executor))return[];let r=_I<(((i=t.face.mobilefacenet)==null?void 0:i.skipFrames)||0),s=(((o=t.face.mobilefacenet)==null?void 0:o.skipTime)||0)>ae()-PI;return t.skipAllowed&&s&&r&&$I===n&&Yy[a]?(_I++,Yy[a]):new Promise(async l=>{var p;let u=[];if((p=t.face.mobilefacenet)!=null&&p.enabled&&(rn!=null&&rn.inputs[0].shape)){let c={};c.crop=fe.resizeBilinear(e,[rn.inputs[0].shape[2],rn.inputs[0].shape[1]],!1),c.data=rn.execute(c.crop);let d=await c.data.data();u=Array.from(d),Object.keys(c).forEach(h=>J(c[h]))}Yy[a]=u,$I=n,PI=ae(),l(u)})}var sn,Jy=[],OI=0,zI=0,LI=Number.MAX_SAFE_INTEGER;async function WI(e){return ne.initial&&(sn=null),sn?e.debug&&K("cached model:",sn.modelUrl):sn=await $e(e.face.insightface.modelPath),sn}async function Qy(e,t,a,n){var i,o;if(!(sn!=null&&sn.executor))return[];let r=LI<(((i=t.face.insightface)==null?void 0:i.skipFrames)||0),s=(((o=t.face.insightface)==null?void 0:o.skipTime)||0)>ae()-zI;return t.skipAllowed&&s&&r&&OI===n&&Jy[a]?(LI++,Jy[a]):new Promise(async l=>{var p;let u=[];if((p=t.face.insightface)!=null&&p.enabled&&(sn!=null&&sn.inputs[0].shape)){let c={};c.crop=fe.resizeBilinear(e,[sn.inputs[0].shape[2],sn.inputs[0].shape[1]],!1),c.data=sn.execute(c.crop);let d=await c.data.data();u=Array.from(d),Object.keys(c).forEach(h=>J(c[h]))}Jy[a]=u,OI=n,zI=ae(),l(u)})}var h3e=e=>{let t=(c,d)=>Math.atan2(c[1]-d[1],c[0]-d[0]);if(!e.annotations.rightEyeIris||!e.annotations.leftEyeIris)return{bearing:0,strength:0};let a=[0,-.1],n=1,r=(e.mesh[33][2]||0)>(e.mesh[263][2]||0),s=r?e.mesh[473]:e.mesh[468],i=r?[(e.mesh[133][0]+e.mesh[33][0])/2,(e.mesh[133][1]+e.mesh[33][1])/2]:[(e.mesh[263][0]+e.mesh[362][0])/2,(e.mesh[263][1]+e.mesh[362][1])/2],o=r?[e.mesh[133][0]-e.mesh[33][0],e.mesh[23][1]-e.mesh[27][1]]:[e.mesh[263][0]-e.mesh[362][0],e.mesh[253][1]-e.mesh[257][1]],l=[(i[0]-s[0])/o[0]-a[0],n*(s[1]-i[1])/o[1]-a[1]],u=Math.sqrt(l[0]*l[0]+l[1]*l[1]);return u=Math.min(u,e.boxRaw[2]/2,e.boxRaw[3]/2),{bearing:(t([0,0],l)+Math.PI/2)%Math.PI,strength:u}},VI=(e,t)=>{let a=f=>{let g=Math.sqrt(f[0]*f[0]+f[1]*f[1]+f[2]*f[2]);return f[0]/=g,f[1]/=g,f[2]/=g,f},n=(f,g)=>{let y=f[0]-g[0],x=f[1]-g[1],A=f[2]-g[2];return[y,x,A]},r=(f,g)=>{let y=f[1]*g[2]-f[2]*g[1],x=f[2]*g[0]-f[0]*g[2],A=f[0]*g[1]-f[1]*g[0];return[y,x,A]},s=f=>{let[g,y,x,A,b,w,I,T,N]=f,M,$,E;if(A<1)if(A>-1){let S=Math.sqrt(g*g+I*I);E=Math.atan2(A,S),$=Math.atan2(-I,g),M=Math.atan2(-w,b)}else E=-Math.PI/2,$=-Math.atan2(T,N),M=0;else E=Math.PI/2,$=Math.atan2(T,N),M=0;return Number.isNaN(M)&&(M=0),Number.isNaN($)&&($=0),Number.isNaN(E)&&(E=0),{pitch:-M,yaw:-$,roll:-E}},i=e.meshRaw;if(!i||i.length<300)return{angle:{pitch:0,yaw:0,roll:0},matrix:[1,0,0,0,1,0,0,0,1],gaze:{bearing:0,strength:0}};let o=Math.max(e.boxRaw[2]*t[0],e.boxRaw[3]*t[1])/1.5,l=[i[10],i[152],i[234],i[454]].map(f=>[f[0]*t[0]/o,f[1]*t[1]/o,f[2]]),u=a(n(l[1],l[0])),p=a(n(l[3],l[2])),c=a(r(p,u));p=r(u,c);let d=[p[0],p[1],p[2],u[0],u[1],u[2],c[0],c[1],c[2]],h=s(d),m=i.length===478?h3e(e):{bearing:0,strength:0};return{angle:h,matrix:d,gaze:m}};function UI(e,t){let a=e==null?void 0:e.annotations;if(!(a!=null&&a.leftEyeIris)||!(a!=null&&a.rightEyeIris))return 0;let n=Math.max(Math.abs(a.leftEyeIris[3][0]-a.leftEyeIris[1][0]),Math.abs(a.rightEyeIris[3][0]-a.rightEyeIris[1][0]))/t;return Math.round(1.17/n)/100}var ex=async(e,t)=>{var m,f,g,y,x,A,b,w,I,T,N,M,$,E,S,_,O,W,P,U,G,q,H;let a=ae(),n,r,s,i,o,l,u,p,c,d=[];e.state="run:face";let h=await Q9(t,e.config);if(e.performance.face=ne.perfadd?(e.performance.face||0)+Math.trunc(ae()-a):Math.trunc(ae()-a),!t.shape||t.shape.length!==4)return[];if(!h)return[];for(let V=0;V<h.length;V++){if(e.analyze("Get Face"),!h[V].tensor||h[V].tensor.isDisposedInternal){K("Face object is disposed:",h[V].tensor);continue}if((m=e.config.face.detector)!=null&&m.mask){let ge=await pI(h[V]);J(h[V].tensor),ge&&(h[V].tensor=ge)}let Z=h[V].mesh&&h[V].mesh.length>200?VI(h[V],[t.shape[2],t.shape[1]]):null;e.analyze("Start Emotion:"),e.config.async?i=(f=e.config.face.emotion)!=null&&f.enabled?_y(h[V].tensor||Ve([]),e.config,V,h.length):[]:(e.state="run:emotion",a=ae(),i=(g=e.config.face.emotion)!=null&&g.enabled?await _y(h[V].tensor||Ve([]),e.config,V,h.length):[],e.performance.emotion=ne.perfadd?(e.performance.emotion||0)+Math.trunc(ae()-a):Math.trunc(ae()-a)),e.analyze("End Emotion:"),e.analyze("Start AntiSpoof:"),e.config.async?u=(y=e.config.face.antispoof)!=null&&y.enabled?Ly(h[V].tensor||Ve([]),e.config,V,h.length):0:(e.state="run:antispoof",a=ae(),u=(x=e.config.face.antispoof)!=null&&x.enabled?await Ly(h[V].tensor||Ve([]),e.config,V,h.length):0,e.performance.antispoof=ne.perfadd?(e.performance.antispoof||0)+Math.trunc(ae()-a):Math.trunc(ae()-a)),e.analyze("End AntiSpoof:"),e.analyze("Start Liveness:"),e.config.async?p=(A=e.config.face.liveness)!=null&&A.enabled?By(h[V].tensor||Ve([]),e.config,V,h.length):0:(e.state="run:liveness",a=ae(),p=(b=e.config.face.liveness)!=null&&b.enabled?await By(h[V].tensor||Ve([]),e.config,V,h.length):0,e.performance.liveness=ne.perfadd?(e.performance.antispoof||0)+Math.trunc(ae()-a):Math.trunc(ae()-a)),e.analyze("End Liveness:"),e.analyze("Start GEAR:"),e.config.async?r=(w=e.config.face.gear)!=null&&w.enabled?Gy(h[V].tensor||Ve([]),e.config,V,h.length):null:(e.state="run:gear",a=ae(),r=(I=e.config.face.gear)!=null&&I.enabled?await Gy(h[V].tensor||Ve([]),e.config,V,h.length):null,e.performance.gear=Math.trunc(ae()-a)),e.analyze("End GEAR:"),e.analyze("Start SSRNet:"),e.config.async?(n=(T=e.config.face.ssrnet)!=null&&T.enabled?jy(h[V].tensor||Ve([]),e.config,V,h.length):null,s=(N=e.config.face.ssrnet)!=null&&N.enabled?Ky(h[V].tensor||Ve([]),e.config,V,h.length):null):(e.state="run:ssrnet",a=ae(),n=(M=e.config.face.ssrnet)!=null&&M.enabled?await jy(h[V].tensor||Ve([]),e.config,V,h.length):null,s=($=e.config.face.ssrnet)!=null&&$.enabled?await Ky(h[V].tensor||Ve([]),e.config,V,h.length):null,e.performance.ssrnet=Math.trunc(ae()-a)),e.analyze("End SSRNet:"),e.analyze("Start MobileFaceNet:"),e.config.async?o=(E=e.config.face.mobilefacenet)!=null&&E.enabled?Zy(h[V].tensor||Ve([]),e.config,V,h.length):null:(e.state="run:mobilefacenet",a=ae(),o=(S=e.config.face.mobilefacenet)!=null&&S.enabled?await Zy(h[V].tensor||Ve([]),e.config,V,h.length):null,e.performance.mobilefacenet=Math.trunc(ae()-a)),e.analyze("End MobileFaceNet:"),e.analyze("Start InsightFace:"),e.config.async?l=(_=e.config.face.insightface)!=null&&_.enabled?Qy(h[V].tensor||Ve([]),e.config,V,h.length):null:(e.state="run:mobilefacenet",a=ae(),l=(O=e.config.face.insightface)!=null&&O.enabled?await Qy(h[V].tensor||Ve([]),e.config,V,h.length):null,e.performance.mobilefacenet=Math.trunc(ae()-a)),e.analyze("End InsightFace:"),e.analyze("Start Description:"),e.config.async?c=Dy(h[V].tensor||Ve([]),e.config,V,h.length):(e.state="run:description",a=ae(),c=await Dy(h[V].tensor||Ve([]),e.config,V,h.length),e.performance.description=ne.perfadd?(e.performance.description||0)+Math.trunc(ae()-a):Math.trunc(ae()-a)),e.analyze("End Description:"),e.config.async&&([n,s,i,o,l,c,r,u,p]=await Promise.all([n,s,i,o,l,c,r,u,p])),e.analyze("Finish Face:"),(W=e.config.face.ssrnet)!=null&&W.enabled&&n&&s&&(c={...c,age:n.age,gender:s.gender,genderScore:s.genderScore}),(P=e.config.face.gear)!=null&&P.enabled&&r&&(c={...c,age:r.age,gender:r.gender,genderScore:r.genderScore,race:r.race}),(U=e.config.face.mobilefacenet)!=null&&U.enabled&&o&&(c.descriptor=o),(G=e.config.face.insightface)!=null&&G.enabled&&l&&(c.descriptor=l);let X=(q=e.config.face.iris)!=null&&q.enabled?UI(h[V],t.shape[2]):0,re=(H=e.config.face.detector)!=null&&H.return?Oe(h[V].tensor):null;J(h[V].tensor),h[V].tensor&&delete h[V].tensor;let ee={...h[V],id:V};c.age&&(ee.age=c.age),c.gender&&(ee.gender=c.gender),c.genderScore&&(ee.genderScore=c.genderScore),c.descriptor&&(ee.embedding=c.descriptor),c.race&&(ee.race=c.race),i&&(ee.emotion=i),u&&(ee.real=u),p&&(ee.live=p),X>0&&(ee.distance=X),Z&&(ee.rotation=Z),re&&(ee.tensor=re),d.push(ee),e.analyze("End Face")}return e.analyze("End FaceMesh:"),e.config.async&&(e.performance.face&&delete e.performance.face,e.performance.age&&delete e.performance.age,e.performance.gender&&delete e.performance.gender,e.performance.emotion&&delete e.performance.emotion),d};var Pa={thumb:0,index:1,middle:2,ring:3,pinky:4,all:[0,1,2,3,4],nameMapping:{0:"thumb",1:"index",2:"middle",3:"ring",4:"pinky"},pointsMapping:{0:[[0,1],[1,2],[2,3],[3,4]],1:[[0,5],[5,6],[6,7],[7,8]],2:[[0,9],[9,10],[10,11],[11,12]],3:[[0,13],[13,14],[14,15],[15,16]],4:[[0,17],[17,18],[18,19],[19,20]]},getName:e=>Pa.nameMapping[e],getPoints:e=>Pa.pointsMapping[e]},Ts={none:0,half:1,full:2,nameMapping:{0:"none",1:"half",2:"full"},getName:e=>Ts.nameMapping[e]},$t={verticalUp:0,verticalDown:1,horizontalLeft:2,horizontalRight:3,diagonalUpRight:4,diagonalUpLeft:5,diagonalDownRight:6,diagonalDownLeft:7,nameMapping:{0:"verticalUp",1:"verticalDown",2:"horizontalLeft",3:"horizontalRight",4:"diagonalUpRight",5:"diagonalUpLeft",6:"diagonalDownRight",7:"diagonalDownLeft"},getName:e=>$t.nameMapping[e]},Cs=class{constructor(t){he(this,"name");he(this,"curls");he(this,"directions");he(this,"weights");he(this,"weightsRelative");this.name=t,this.curls={},this.directions={},this.weights=[1,1,1,1,1],this.weightsRelative=[1,1,1,1,1]}curl(t,a,n){typeof this.curls[t]=="undefined"&&(this.curls[t]=[]),this.curls[t].push([a,n])}direction(t,a,n){this.directions[t]||(this.directions[t]=[]),this.directions[t].push([a,n])}weight(t,a){this.weights[t]=a;let n=this.weights.reduce((r,s)=>r+s,0);this.weightsRelative=this.weights.map(r=>r*5/n)}matchAgainst(t,a){let n=0;for(let r in t){let s=t[r],i=this.curls[r];if(typeof i=="undefined"){n+=this.weightsRelative[r];continue}for(let[o,l]of i)if(s===o){n+=l*this.weightsRelative[r];break}}for(let r in a){let s=a[r],i=this.directions[r];if(typeof i=="undefined"){n+=this.weightsRelative[r];continue}for(let[o,l]of i)if(s===o){n+=l*this.weightsRelative[r];break}}return n/10}};var{thumb:Hn,index:_r,middle:Fr,ring:vl,pinky:wl}=Pa,{none:jn,half:f3e,full:qn}=Ts,{verticalUp:dd,verticalDown:X7e,horizontalLeft:tx,horizontalRight:g3e,diagonalUpRight:y3e,diagonalUpLeft:pd,diagonalDownRight:K7e,diagonalDownLeft:Y7e}=$t,Ns=new Cs("thumbs up");Ns.curl(Hn,jn,1);Ns.direction(Hn,dd,1);Ns.direction(Hn,pd,.25);Ns.direction(Hn,y3e,.25);for(let e of[Pa.index,Pa.middle,Pa.ring,Pa.pinky])Ns.curl(e,qn,1),Ns.direction(e,tx,1),Ns.direction(e,g3e,1);var Ht=new Cs("victory");Ht.curl(Hn,f3e,.5);Ht.curl(Hn,jn,.5);Ht.direction(Hn,dd,1);Ht.direction(Hn,pd,1);Ht.curl(_r,jn,1);Ht.direction(_r,dd,.75);Ht.direction(_r,pd,1);Ht.curl(Fr,jn,1);Ht.direction(Fr,dd,1);Ht.direction(Fr,pd,.75);Ht.curl(vl,qn,1);Ht.direction(vl,dd,.2);Ht.direction(vl,pd,1);Ht.direction(vl,tx,.2);Ht.curl(wl,qn,1);Ht.direction(wl,dd,.2);Ht.direction(wl,pd,1);Ht.direction(wl,tx,.2);Ht.weight(_r,2);Ht.weight(Fr,2);var Rs=new Cs("point");Rs.curl(Hn,qn,1);Rs.curl(_r,jn,.5);Rs.curl(Fr,qn,.5);Rs.curl(vl,qn,.5);Rs.curl(wl,qn,.5);Rs.weight(_r,2);Rs.weight(Fr,2);var Es=new Cs("middle finger");Es.curl(Hn,jn,1);Es.curl(_r,qn,.5);Es.curl(Fr,qn,.5);Es.curl(vl,qn,.5);Es.curl(wl,qn,.5);Es.weight(_r,2);Es.weight(Fr,2);var cd=new Cs("open palm");cd.curl(Hn,jn,.75);cd.curl(_r,jn,.75);cd.curl(Fr,jn,.75);cd.curl(vl,jn,.75);cd.curl(wl,jn,.75);var GI=[Ns,Ht,Rs,Es,cd];var x3e=.7,kl={HALF_CURL_START_LIMIT:60,NO_CURL_START_LIMIT:130,DISTANCE_VOTE_POWER:1.1,SINGLE_ANGLE_VOTE_POWER:.9,TOTAL_ANGLE_VOTE_POWER:1.6};function HI(e,t,a,n){let r=(t-n)/(e-a),s=Math.atan(r)*180/Math.PI;return s<=0?s=-s:s>0&&(s=180-s),s}function qI(e,t){if(!e||!t)return[0,0];let a=HI(e[0],e[1],t[0],t[1]);if(e.length===2)return a;let n=HI(e[1],e[2],t[1],t[2]);return[a,n]}function jI(e,t=1){let a=0,n=0,r=0;return e>=75&&e<=105?a=1*t:e>=25&&e<=155?n=1*t:r=1*t,[a,n,r]}function A3e(e,t,a){let n=e[0]-t[0],r=e[0]-a[0],s=t[0]-a[0],i=e[1]-t[1],o=e[1]-a[1],l=t[1]-a[1],u=e[2]-t[2],p=e[2]-a[2],c=t[2]-a[2],d=Math.sqrt(n*n+i*i+u*u),h=Math.sqrt(r*r+o*o+p*p),m=Math.sqrt(s*s+l*l+c*c),f=(m*m+d*d-h*h)/(2*m*d);f>1?f=1:f<-1&&(f=-1);let g=Math.acos(f);g=57.2958*g%180;let y;return g>kl.NO_CURL_START_LIMIT?y=Ts.none:g>kl.HALF_CURL_START_LIMIT?y=Ts.half:y=Ts.full,y}function XI(e,t,a,n){let r;return n===Math.abs(e)?e>0?r=$t.horizontalLeft:r=$t.horizontalRight:n===Math.abs(t)?t>0?r=$t.horizontalLeft:r=$t.horizontalRight:a>0?r=$t.horizontalLeft:r=$t.horizontalRight,r}function KI(e,t,a,n){let r;return n===Math.abs(e)?e<0?r=$t.verticalDown:r=$t.verticalUp:n===Math.abs(t)?t<0?r=$t.verticalDown:r=$t.verticalUp:a<0?r=$t.verticalDown:r=$t.verticalUp,r}function b3e(e,t,a,n,r,s,i,o){let l,u=KI(e,t,a,n),p=XI(r,s,i,o);return u===$t.verticalUp?p===$t.horizontalLeft?l=$t.diagonalUpLeft:l=$t.diagonalUpRight:p===$t.horizontalLeft?l=$t.diagonalDownLeft:l=$t.diagonalDownRight,l}function v3e(e,t,a,n){let r=e[0]-t[0],s=e[0]-a[0],i=t[0]-a[0],o=e[1]-t[1],l=e[1]-a[1],u=t[1]-a[1],p=Math.max(Math.abs(r),Math.abs(s),Math.abs(i)),c=Math.max(Math.abs(o),Math.abs(l),Math.abs(u)),d=0,h=0,m=0,f=c/(p+1e-5);f>1.5?d+=kl.DISTANCE_VOTE_POWER:f>.66?h+=kl.DISTANCE_VOTE_POWER:m+=kl.DISTANCE_VOTE_POWER;let g=Math.sqrt(r*r+o*o),y=Math.sqrt(s*s+l*l),x=Math.sqrt(i*i+u*u),A=Math.max(g,y,x),b=e[0],w=e[1],I=a[0],T=a[1];A===g?(I=a[0],T=a[1]):A===x&&(b=t[0],w=t[1]);let $=qI([b,w],[I,T]),E=jI($,kl.TOTAL_ANGLE_VOTE_POWER);d+=E[0],h+=E[1],m+=E[2];for(let _ of n){let O=jI(_,kl.SINGLE_ANGLE_VOTE_POWER);d+=O[0],h+=O[1],m+=O[2]}let S;return d===Math.max(d,h,m)?S=KI(l,o,u,c):m===Math.max(h,m)?S=XI(s,r,i,p):S=b3e(l,o,u,c,s,r,i,p),S}function YI(e){let t=[],a=[],n=[],r=[];if(!e)return{curls:n,directions:r};for(let s of Pa.all){let i=Pa.getPoints(s),o=[],l=[];for(let u of i){let p=e[u[0]],c=e[u[1]],d=qI(p,c),h=d[0],m=d[1];o.push(h),l.push(m)}t.push(o),a.push(l)}for(let s of Pa.all){let i=s===Pa.thumb?1:0,o=Pa.getPoints(s),l=e[o[i][0]],u=e[o[i+1][1]],p=e[o[3][1]],c=A3e(l,u,p),d=v3e(l,u,p,t[s].slice(i));n[s]=c,r[s]=d}return{curls:n,directions:r}}function H0(e){if(!e||e.length===0)return null;let t=YI(e),a={};for(let n of Pa.all)a[Pa.getName(n)]={curl:Ts.getName(t.curls[n]),direction:$t.getName(t.directions[n])};return a}function ZI(e){let t=[];if(!e||e.length===0)return t;let a=YI(e);for(let n of GI){let r=n.matchAgainst(a.curls,a.directions);r>=x3e&&t.push({name:n.name,confidence:r})}return t}var JI=e=>{if(!e)return[];let t=[];for(let a=0;a<e.length;a++){let n=e[a].keypoints.find(l=>l.part==="leftWrist"),r=e[a].keypoints.find(l=>l.part==="rightWrist"),s=e[a].keypoints.find(l=>l.part==="nose");s&&n&&r&&n.position[1]<s.position[1]&&r.position[1]<s.position[1]?t.push({body:a,gesture:"i give up"}):s&&n&&n.position[1]<s.position[1]?t.push({body:a,gesture:"raise left hand"}):s&&r&&r.position[1]<s.position[1]&&t.push({body:a,gesture:"raise right hand"});let i=e[a].keypoints.find(l=>l.part==="leftShoulder"),o=e[a].keypoints.find(l=>l.part==="rightShoulder");i&&o&&Math.abs(i.positionRaw[1]-o.positionRaw[1])>.1&&t.push({body:a,gesture:`leaning ${i.position[1]>o.position[1]?"left":"right"}`})}return t},QI=e=>{if(!e)return[];let t=[];for(let a=0;a<e.length;a++)if(e[a].mesh&&e[a].mesh.length>450){let n=(e[a].mesh[33][2]||0)-(e[a].mesh[263][2]||0),r=e[a].mesh[33][0]-e[a].mesh[263][0];Math.abs(n/r)<=.15?t.push({face:a,gesture:"facing center"}):t.push({face:a,gesture:`facing ${n<0?"left":"right"}`}),Math.abs(e[a].mesh[374][1]-e[a].mesh[386][1])/Math.abs(e[a].mesh[443][1]-e[a].mesh[450][1])<.2&&t.push({face:a,gesture:"blink left eye"}),Math.abs(e[a].mesh[145][1]-e[a].mesh[159][1])/Math.abs(e[a].mesh[223][1]-e[a].mesh[230][1])<.2&&t.push({face:a,gesture:"blink right eye"});let o=Math.min(100,500*Math.abs(e[a].mesh[13][1]-e[a].mesh[14][1])/Math.abs(e[a].mesh[10][1]-e[a].mesh[152][1]));o>10&&t.push({face:a,gesture:`mouth ${Math.trunc(o)}% open`});let l=e[a].mesh[152][2]||0;Math.abs(l)>10&&t.push({face:a,gesture:`head ${l<0?"up":"down"}`})}return t},eS=e=>{var a,n,r,s;if(!e)return[];let t=[];for(let i=0;i<e.length;i++){if(!((n=(a=e[i].annotations)==null?void 0:a.leftEyeIris)!=null&&n[0])||!((s=(r=e[i].annotations)==null?void 0:r.rightEyeIris)!=null&&s[0]))continue;let o=e[i].annotations.leftEyeIris[3][0]-e[i].annotations.leftEyeIris[1][0],l=e[i].annotations.leftEyeIris[4][1]-e[i].annotations.leftEyeIris[2][1],u=Math.abs(o*l),p=e[i].annotations.rightEyeIris[3][0]-e[i].annotations.rightEyeIris[1][0],c=e[i].annotations.rightEyeIris[4][1]-e[i].annotations.rightEyeIris[2][1],d=Math.abs(p*c),h=!1;Math.abs(u-d)/Math.max(u,d)<.25&&(h=!0,t.push({iris:i,gesture:"facing center"}));let f=Math.abs(e[i].mesh[263][0]-e[i].annotations.leftEyeIris[0][0])/e[i].box[2],g=Math.abs(e[i].mesh[33][0]-e[i].annotations.rightEyeIris[0][0])/e[i].box[2];(f>.06||g>.06)&&(h=!1),f>g?g>.04&&t.push({iris:i,gesture:"looking right"}):f>.04&&t.push({iris:i,gesture:"looking left"});let y=Math.abs(e[i].mesh[145][1]-e[i].annotations.rightEyeIris[0][1])/e[i].box[3],x=Math.abs(e[i].mesh[374][1]-e[i].annotations.leftEyeIris[0][1])/e[i].box[3];(x<.01||y<.01||x>.022||y>.022)&&(h=!1),(x<.01||y<.01)&&t.push({iris:i,gesture:"looking down"}),(x>.022||y>.022)&&t.push({iris:i,gesture:"looking up"}),h&&t.push({iris:i,gesture:"looking center"})}return t},tS=e=>{if(!e)return[];let t=[];for(let a=0;a<e.length;a++){let n=[];if(e[a].annotations)for(let[r,s]of Object.entries(e[a].annotations))r!=="palmBase"&&Array.isArray(s)&&s[0]&&n.push({name:r.toLowerCase(),position:s[0]});if(n&&n.length>0){let r=n.reduce((i,o)=>(i.position[2]||0)<(o.position[2]||0)?i:o);t.push({hand:a,gesture:`${r.name} forward`});let s=n.reduce((i,o)=>i.position[1]<o.position[1]?i:o);t.push({hand:a,gesture:`${s.name} up`})}if(e[a].keypoints){let r=ZI(e[a].keypoints);for(let s of r)t.push({hand:a,gesture:s.name})}}return t};function j0(e){return[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])]}function pc(e){return[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2]}function rS(e,t,a){let n=t.shape[1],r=t.shape[2],s=[[e.startPoint[1]/n,e.startPoint[0]/r,e.endPoint[1]/n,e.endPoint[0]/r]];return fe.cropAndResize(t,s,[0],a)}function sS(e,t){let a=[e.startPoint[0]*t[0],e.startPoint[1]*t[1]],n=[e.endPoint[0]*t[0],e.endPoint[1]*t[1]],r=e.palmLandmarks.map(s=>[s[0]*t[0],s[1]*t[1]]);return{startPoint:a,endPoint:n,palmLandmarks:r,confidence:e.confidence}}function q0(e,t=1.5){let a=pc(e),n=j0(e),r=[t*n[0]/2,t*n[1]/2],s=[a[0]-r[0],a[1]-r[1]],i=[a[0]+r[0],a[1]+r[1]];return{startPoint:s,endPoint:i,palmLandmarks:e.palmLandmarks}}function X0(e){let t=pc(e),a=j0(e),r=Math.max(...a)/2,s=[t[0]-r,t[1]-r],i=[t[0]+r,t[1]+r];return{startPoint:s,endPoint:i,palmLandmarks:e.palmLandmarks}}function k3e(e){return e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI))}function iS(e,t){let a=Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]);return k3e(a)}var aS=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]];function Ms(e,t){let a=0;for(let n=0;n<e.length;n++)a+=e[n]*t[n];return a}function I3e(e,t){let a=[];for(let n=0;n<e.length;n++)a.push(e[n][t]);return a}function nS(e,t){let a=[],n=e.length;for(let r=0;r<n;r++){a.push([]);for(let s=0;s<n;s++)a[r].push(Ms(e[r],I3e(t,s)))}return a}function nx(e,t){let a=Math.cos(e),n=Math.sin(e),r=[[a,-n,0],[n,a,0],[0,0,1]],s=aS(t[0],t[1]),i=nS(s,r),o=aS(-t[0],-t[1]);return nS(i,o)}function oS(e){let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],a=[e[0][2],e[1][2]],n=[-Ms(t[0],a),-Ms(t[1],a)];return[t[0].concat(n[0]),t[1].concat(n[1]),[0,0,1]]}function rx(e,t){return[Ms(e,t[0]),Ms(e,t[1])]}var uS=[{x:.015625,y:.015625},{x:.015625,y:.015625},{x:.046875,y:.015625},{x:.046875,y:.015625},{x:.078125,y:.015625},{x:.078125,y:.015625},{x:.109375,y:.015625},{x:.109375,y:.015625},{x:.140625,y:.015625},{x:.140625,y:.015625},{x:.171875,y:.015625},{x:.171875,y:.015625},{x:.203125,y:.015625},{x:.203125,y:.015625},{x:.234375,y:.015625},{x:.234375,y:.015625},{x:.265625,y:.015625},{x:.265625,y:.015625},{x:.296875,y:.015625},{x:.296875,y:.015625},{x:.328125,y:.015625},{x:.328125,y:.015625},{x:.359375,y:.015625},{x:.359375,y:.015625},{x:.390625,y:.015625},{x:.390625,y:.015625},{x:.421875,y:.015625},{x:.421875,y:.015625},{x:.453125,y:.015625},{x:.453125,y:.015625},{x:.484375,y:.015625},{x:.484375,y:.015625},{x:.515625,y:.015625},{x:.515625,y:.015625},{x:.546875,y:.015625},{x:.546875,y:.015625},{x:.578125,y:.015625},{x:.578125,y:.015625},{x:.609375,y:.015625},{x:.609375,y:.015625},{x:.640625,y:.015625},{x:.640625,y:.015625},{x:.671875,y:.015625},{x:.671875,y:.015625},{x:.703125,y:.015625},{x:.703125,y:.015625},{x:.734375,y:.015625},{x:.734375,y:.015625},{x:.765625,y:.015625},{x:.765625,y:.015625},{x:.796875,y:.015625},{x:.796875,y:.015625},{x:.828125,y:.015625},{x:.828125,y:.015625},{x:.859375,y:.015625},{x:.859375,y:.015625},{x:.890625,y:.015625},{x:.890625,y:.015625},{x:.921875,y:.015625},{x:.921875,y:.015625},{x:.953125,y:.015625},{x:.953125,y:.015625},{x:.984375,y:.015625},{x:.984375,y:.015625},{x:.015625,y:.046875},{x:.015625,y:.046875},{x:.046875,y:.046875},{x:.046875,y:.046875},{x:.078125,y:.046875},{x:.078125,y:.046875},{x:.109375,y:.046875},{x:.109375,y:.046875},{x:.140625,y:.046875},{x:.140625,y:.046875},{x:.171875,y:.046875},{x:.171875,y:.046875},{x:.203125,y:.046875},{x:.203125,y:.046875},{x:.234375,y:.046875},{x:.234375,y:.046875},{x:.265625,y:.046875},{x:.265625,y:.046875},{x:.296875,y:.046875},{x:.296875,y:.046875},{x:.328125,y:.046875},{x:.328125,y:.046875},{x:.359375,y:.046875},{x:.359375,y:.046875},{x:.390625,y:.046875},{x:.390625,y:.046875},{x:.421875,y:.046875},{x:.421875,y:.046875},{x:.453125,y:.046875},{x:.453125,y:.046875},{x:.484375,y:.046875},{x:.484375,y:.046875},{x:.515625,y:.046875},{x:.515625,y:.046875},{x:.546875,y:.046875},{x:.546875,y:.046875},{x:.578125,y:.046875},{x:.578125,y:.046875},{x:.609375,y:.046875},{x:.609375,y:.046875},{x:.640625,y:.046875},{x:.640625,y:.046875},{x:.671875,y:.046875},{x:.671875,y:.046875},{x:.703125,y:.046875},{x:.703125,y:.046875},{x:.734375,y:.046875},{x:.734375,y:.046875},{x:.765625,y:.046875},{x:.765625,y:.046875},{x:.796875,y:.046875},{x:.796875,y:.046875},{x:.828125,y:.046875},{x:.828125,y:.046875},{x:.859375,y:.046875},{x:.859375,y:.046875},{x:.890625,y:.046875},{x:.890625,y:.046875},{x:.921875,y:.046875},{x:.921875,y:.046875},{x:.953125,y:.046875},{x:.953125,y:.046875},{x:.984375,y:.046875},{x:.984375,y:.046875},{x:.015625,y:.078125},{x:.015625,y:.078125},{x:.046875,y:.078125},{x:.046875,y:.078125},{x:.078125,y:.078125},{x:.078125,y:.078125},{x:.109375,y:.078125},{x:.109375,y:.078125},{x:.140625,y:.078125},{x:.140625,y:.078125},{x:.171875,y:.078125},{x:.171875,y:.078125},{x:.203125,y:.078125},{x:.203125,y:.078125},{x:.234375,y:.078125},{x:.234375,y:.078125},{x:.265625,y:.078125},{x:.265625,y:.078125},{x:.296875,y:.078125},{x:.296875,y:.078125},{x:.328125,y:.078125},{x:.328125,y:.078125},{x:.359375,y:.078125},{x:.359375,y:.078125},{x:.390625,y:.078125},{x:.390625,y:.078125},{x:.421875,y:.078125},{x:.421875,y:.078125},{x:.453125,y:.078125},{x:.453125,y:.078125},{x:.484375,y:.078125},{x:.484375,y:.078125},{x:.515625,y:.078125},{x:.515625,y:.078125},{x:.546875,y:.078125},{x:.546875,y:.078125},{x:.578125,y:.078125},{x:.578125,y:.078125},{x:.609375,y:.078125},{x:.609375,y:.078125},{x:.640625,y:.078125},{x:.640625,y:.078125},{x:.671875,y:.078125},{x:.671875,y:.078125},{x:.703125,y:.078125},{x:.703125,y:.078125},{x:.734375,y:.078125},{x:.734375,y:.078125},{x:.765625,y:.078125},{x:.765625,y:.078125},{x:.796875,y:.078125},{x:.796875,y:.078125},{x:.828125,y:.078125},{x:.828125,y:.078125},{x:.859375,y:.078125},{x:.859375,y:.078125},{x:.890625,y:.078125},{x:.890625,y:.078125},{x:.921875,y:.078125},{x:.921875,y:.078125},{x:.953125,y:.078125},{x:.953125,y:.078125},{x:.984375,y:.078125},{x:.984375,y:.078125},{x:.015625,y:.109375},{x:.015625,y:.109375},{x:.046875,y:.109375},{x:.046875,y:.109375},{x:.078125,y:.109375},{x:.078125,y:.109375},{x:.109375,y:.109375},{x:.109375,y:.109375},{x:.140625,y:.109375},{x:.140625,y:.109375},{x:.171875,y:.109375},{x:.171875,y:.109375},{x:.203125,y:.109375},{x:.203125,y:.109375},{x:.234375,y:.109375},{x:.234375,y:.109375},{x:.265625,y:.109375},{x:.265625,y:.109375},{x:.296875,y:.109375},{x:.296875,y:.109375},{x:.328125,y:.109375},{x:.328125,y:.109375},{x:.359375,y:.109375},{x:.359375,y:.109375},{x:.390625,y:.109375},{x:.390625,y:.109375},{x:.421875,y:.109375},{x:.421875,y:.109375},{x:.453125,y:.109375},{x:.453125,y:.109375},{x:.484375,y:.109375},{x:.484375,y:.109375},{x:.515625,y:.109375},{x:.515625,y:.109375},{x:.546875,y:.109375},{x:.546875,y:.109375},{x:.578125,y:.109375},{x:.578125,y:.109375},{x:.609375,y:.109375},{x:.609375,y:.109375},{x:.640625,y:.109375},{x:.640625,y:.109375},{x:.671875,y:.109375},{x:.671875,y:.109375},{x:.703125,y:.109375},{x:.703125,y:.109375},{x:.734375,y:.109375},{x:.734375,y:.109375},{x:.765625,y:.109375},{x:.765625,y:.109375},{x:.796875,y:.109375},{x:.796875,y:.109375},{x:.828125,y:.109375},{x:.828125,y:.109375},{x:.859375,y:.109375},{x:.859375,y:.109375},{x:.890625,y:.109375},{x:.890625,y:.109375},{x:.921875,y:.109375},{x:.921875,y:.109375},{x:.953125,y:.109375},{x:.953125,y:.109375},{x:.984375,y:.109375},{x:.984375,y:.109375},{x:.015625,y:.140625},{x:.015625,y:.140625},{x:.046875,y:.140625},{x:.046875,y:.140625},{x:.078125,y:.140625},{x:.078125,y:.140625},{x:.109375,y:.140625},{x:.109375,y:.140625},{x:.140625,y:.140625},{x:.140625,y:.140625},{x:.171875,y:.140625},{x:.171875,y:.140625},{x:.203125,y:.140625},{x:.203125,y:.140625},{x:.234375,y:.140625},{x:.234375,y:.140625},{x:.265625,y:.140625},{x:.265625,y:.140625},{x:.296875,y:.140625},{x:.296875,y:.140625},{x:.328125,y:.140625},{x:.328125,y:.140625},{x:.359375,y:.140625},{x:.359375,y:.140625},{x:.390625,y:.140625},{x:.390625,y:.140625},{x:.421875,y:.140625},{x:.421875,y:.140625},{x:.453125,y:.140625},{x:.453125,y:.140625},{x:.484375,y:.140625},{x:.484375,y:.140625},{x:.515625,y:.140625},{x:.515625,y:.140625},{x:.546875,y:.140625},{x:.546875,y:.140625},{x:.578125,y:.140625},{x:.578125,y:.140625},{x:.609375,y:.140625},{x:.609375,y:.140625},{x:.640625,y:.140625},{x:.640625,y:.140625},{x:.671875,y:.140625},{x:.671875,y:.140625},{x:.703125,y:.140625},{x:.703125,y:.140625},{x:.734375,y:.140625},{x:.734375,y:.140625},{x:.765625,y:.140625},{x:.765625,y:.140625},{x:.796875,y:.140625},{x:.796875,y:.140625},{x:.828125,y:.140625},{x:.828125,y:.140625},{x:.859375,y:.140625},{x:.859375,y:.140625},{x:.890625,y:.140625},{x:.890625,y:.140625},{x:.921875,y:.140625},{x:.921875,y:.140625},{x:.953125,y:.140625},{x:.953125,y:.140625},{x:.984375,y:.140625},{x:.984375,y:.140625},{x:.015625,y:.171875},{x:.015625,y:.171875},{x:.046875,y:.171875},{x:.046875,y:.171875},{x:.078125,y:.171875},{x:.078125,y:.171875},{x:.109375,y:.171875},{x:.109375,y:.171875},{x:.140625,y:.171875},{x:.140625,y:.171875},{x:.171875,y:.171875},{x:.171875,y:.171875},{x:.203125,y:.171875},{x:.203125,y:.171875},{x:.234375,y:.171875},{x:.234375,y:.171875},{x:.265625,y:.171875},{x:.265625,y:.171875},{x:.296875,y:.171875},{x:.296875,y:.171875},{x:.328125,y:.171875},{x:.328125,y:.171875},{x:.359375,y:.171875},{x:.359375,y:.171875},{x:.390625,y:.171875},{x:.390625,y:.171875},{x:.421875,y:.171875},{x:.421875,y:.171875},{x:.453125,y:.171875},{x:.453125,y:.171875},{x:.484375,y:.171875},{x:.484375,y:.171875},{x:.515625,y:.171875},{x:.515625,y:.171875},{x:.546875,y:.171875},{x:.546875,y:.171875},{x:.578125,y:.171875},{x:.578125,y:.171875},{x:.609375,y:.171875},{x:.609375,y:.171875},{x:.640625,y:.171875},{x:.640625,y:.171875},{x:.671875,y:.171875},{x:.671875,y:.171875},{x:.703125,y:.171875},{x:.703125,y:.171875},{x:.734375,y:.171875},{x:.734375,y:.171875},{x:.765625,y:.171875},{x:.765625,y:.171875},{x:.796875,y:.171875},{x:.796875,y:.171875},{x:.828125,y:.171875},{x:.828125,y:.171875},{x:.859375,y:.171875},{x:.859375,y:.171875},{x:.890625,y:.171875},{x:.890625,y:.171875},{x:.921875,y:.171875},{x:.921875,y:.171875},{x:.953125,y:.171875},{x:.953125,y:.171875},{x:.984375,y:.171875},{x:.984375,y:.171875},{x:.015625,y:.203125},{x:.015625,y:.203125},{x:.046875,y:.203125},{x:.046875,y:.203125},{x:.078125,y:.203125},{x:.078125,y:.203125},{x:.109375,y:.203125},{x:.109375,y:.203125},{x:.140625,y:.203125},{x:.140625,y:.203125},{x:.171875,y:.203125},{x:.171875,y:.203125},{x:.203125,y:.203125},{x:.203125,y:.203125},{x:.234375,y:.203125},{x:.234375,y:.203125},{x:.265625,y:.203125},{x:.265625,y:.203125},{x:.296875,y:.203125},{x:.296875,y:.203125},{x:.328125,y:.203125},{x:.328125,y:.203125},{x:.359375,y:.203125},{x:.359375,y:.203125},{x:.390625,y:.203125},{x:.390625,y:.203125},{x:.421875,y:.203125},{x:.421875,y:.203125},{x:.453125,y:.203125},{x:.453125,y:.203125},{x:.484375,y:.203125},{x:.484375,y:.203125},{x:.515625,y:.203125},{x:.515625,y:.203125},{x:.546875,y:.203125},{x:.546875,y:.203125},{x:.578125,y:.203125},{x:.578125,y:.203125},{x:.609375,y:.203125},{x:.609375,y:.203125},{x:.640625,y:.203125},{x:.640625,y:.203125},{x:.671875,y:.203125},{x:.671875,y:.203125},{x:.703125,y:.203125},{x:.703125,y:.203125},{x:.734375,y:.203125},{x:.734375,y:.203125},{x:.765625,y:.203125},{x:.765625,y:.203125},{x:.796875,y:.203125},{x:.796875,y:.203125},{x:.828125,y:.203125},{x:.828125,y:.203125},{x:.859375,y:.203125},{x:.859375,y:.203125},{x:.890625,y:.203125},{x:.890625,y:.203125},{x:.921875,y:.203125},{x:.921875,y:.203125},{x:.953125,y:.203125},{x:.953125,y:.203125},{x:.984375,y:.203125},{x:.984375,y:.203125},{x:.015625,y:.234375},{x:.015625,y:.234375},{x:.046875,y:.234375},{x:.046875,y:.234375},{x:.078125,y:.234375},{x:.078125,y:.234375},{x:.109375,y:.234375},{x:.109375,y:.234375},{x:.140625,y:.234375},{x:.140625,y:.234375},{x:.171875,y:.234375},{x:.171875,y:.234375},{x:.203125,y:.234375},{x:.203125,y:.234375},{x:.234375,y:.234375},{x:.234375,y:.234375},{x:.265625,y:.234375},{x:.265625,y:.234375},{x:.296875,y:.234375},{x:.296875,y:.234375},{x:.328125,y:.234375},{x:.328125,y:.234375},{x:.359375,y:.234375},{x:.359375,y:.234375},{x:.390625,y:.234375},{x:.390625,y:.234375},{x:.421875,y:.234375},{x:.421875,y:.234375},{x:.453125,y:.234375},{x:.453125,y:.234375},{x:.484375,y:.234375},{x:.484375,y:.234375},{x:.515625,y:.234375},{x:.515625,y:.234375},{x:.546875,y:.234375},{x:.546875,y:.234375},{x:.578125,y:.234375},{x:.578125,y:.234375},{x:.609375,y:.234375},{x:.609375,y:.234375},{x:.640625,y:.234375},{x:.640625,y:.234375},{x:.671875,y:.234375},{x:.671875,y:.234375},{x:.703125,y:.234375},{x:.703125,y:.234375},{x:.734375,y:.234375},{x:.734375,y:.234375},{x:.765625,y:.234375},{x:.765625,y:.234375},{x:.796875,y:.234375},{x:.796875,y:.234375},{x:.828125,y:.234375},{x:.828125,y:.234375},{x:.859375,y:.234375},{x:.859375,y:.234375},{x:.890625,y:.234375},{x:.890625,y:.234375},{x:.921875,y:.234375},{x:.921875,y:.234375},{x:.953125,y:.234375},{x:.953125,y:.234375},{x:.984375,y:.234375},{x:.984375,y:.234375},{x:.015625,y:.265625},{x:.015625,y:.265625},{x:.046875,y:.265625},{x:.046875,y:.265625},{x:.078125,y:.265625},{x:.078125,y:.265625},{x:.109375,y:.265625},{x:.109375,y:.265625},{x:.140625,y:.265625},{x:.140625,y:.265625},{x:.171875,y:.265625},{x:.171875,y:.265625},{x:.203125,y:.265625},{x:.203125,y:.265625},{x:.234375,y:.265625},{x:.234375,y:.265625},{x:.265625,y:.265625},{x:.265625,y:.265625},{x:.296875,y:.265625},{x:.296875,y:.265625},{x:.328125,y:.265625},{x:.328125,y:.265625},{x:.359375,y:.265625},{x:.359375,y:.265625},{x:.390625,y:.265625},{x:.390625,y:.265625},{x:.421875,y:.265625},{x:.421875,y:.265625},{x:.453125,y:.265625},{x:.453125,y:.265625},{x:.484375,y:.265625},{x:.484375,y:.265625},{x:.515625,y:.265625},{x:.515625,y:.265625},{x:.546875,y:.265625},{x:.546875,y:.265625},{x:.578125,y:.265625},{x:.578125,y:.265625},{x:.609375,y:.265625},{x:.609375,y:.265625},{x:.640625,y:.265625},{x:.640625,y:.265625},{x:.671875,y:.265625},{x:.671875,y:.265625},{x:.703125,y:.265625},{x:.703125,y:.265625},{x:.734375,y:.265625},{x:.734375,y:.265625},{x:.765625,y:.265625},{x:.765625,y:.265625},{x:.796875,y:.265625},{x:.796875,y:.265625},{x:.828125,y:.265625},{x:.828125,y:.265625},{x:.859375,y:.265625},{x:.859375,y:.265625},{x:.890625,y:.265625},{x:.890625,y:.265625},{x:.921875,y:.265625},{x:.921875,y:.265625},{x:.953125,y:.265625},{x:.953125,y:.265625},{x:.984375,y:.265625},{x:.984375,y:.265625},{x:.015625,y:.296875},{x:.015625,y:.296875},{x:.046875,y:.296875},{x:.046875,y:.296875},{x:.078125,y:.296875},{x:.078125,y:.296875},{x:.109375,y:.296875},{x:.109375,y:.296875},{x:.140625,y:.296875},{x:.140625,y:.296875},{x:.171875,y:.296875},{x:.171875,y:.296875},{x:.203125,y:.296875},{x:.203125,y:.296875},{x:.234375,y:.296875},{x:.234375,y:.296875},{x:.265625,y:.296875},{x:.265625,y:.296875},{x:.296875,y:.296875},{x:.296875,y:.296875},{x:.328125,y:.296875},{x:.328125,y:.296875},{x:.359375,y:.296875},{x:.359375,y:.296875},{x:.390625,y:.296875},{x:.390625,y:.296875},{x:.421875,y:.296875},{x:.421875,y:.296875},{x:.453125,y:.296875},{x:.453125,y:.296875},{x:.484375,y:.296875},{x:.484375,y:.296875},{x:.515625,y:.296875},{x:.515625,y:.296875},{x:.546875,y:.296875},{x:.546875,y:.296875},{x:.578125,y:.296875},{x:.578125,y:.296875},{x:.609375,y:.296875},{x:.609375,y:.296875},{x:.640625,y:.296875},{x:.640625,y:.296875},{x:.671875,y:.296875},{x:.671875,y:.296875},{x:.703125,y:.296875},{x:.703125,y:.296875},{x:.734375,y:.296875},{x:.734375,y:.296875},{x:.765625,y:.296875},{x:.765625,y:.296875},{x:.796875,y:.296875},{x:.796875,y:.296875},{x:.828125,y:.296875},{x:.828125,y:.296875},{x:.859375,y:.296875},{x:.859375,y:.296875},{x:.890625,y:.296875},{x:.890625,y:.296875},{x:.921875,y:.296875},{x:.921875,y:.296875},{x:.953125,y:.296875},{x:.953125,y:.296875},{x:.984375,y:.296875},{x:.984375,y:.296875},{x:.015625,y:.328125},{x:.015625,y:.328125},{x:.046875,y:.328125},{x:.046875,y:.328125},{x:.078125,y:.328125},{x:.078125,y:.328125},{x:.109375,y:.328125},{x:.109375,y:.328125},{x:.140625,y:.328125},{x:.140625,y:.328125},{x:.171875,y:.328125},{x:.171875,y:.328125},{x:.203125,y:.328125},{x:.203125,y:.328125},{x:.234375,y:.328125},{x:.234375,y:.328125},{x:.265625,y:.328125},{x:.265625,y:.328125},{x:.296875,y:.328125},{x:.296875,y:.328125},{x:.328125,y:.328125},{x:.328125,y:.328125},{x:.359375,y:.328125},{x:.359375,y:.328125},{x:.390625,y:.328125},{x:.390625,y:.328125},{x:.421875,y:.328125},{x:.421875,y:.328125},{x:.453125,y:.328125},{x:.453125,y:.328125},{x:.484375,y:.328125},{x:.484375,y:.328125},{x:.515625,y:.328125},{x:.515625,y:.328125},{x:.546875,y:.328125},{x:.546875,y:.328125},{x:.578125,y:.328125},{x:.578125,y:.328125},{x:.609375,y:.328125},{x:.609375,y:.328125},{x:.640625,y:.328125},{x:.640625,y:.328125},{x:.671875,y:.328125},{x:.671875,y:.328125},{x:.703125,y:.328125},{x:.703125,y:.328125},{x:.734375,y:.328125},{x:.734375,y:.328125},{x:.765625,y:.328125},{x:.765625,y:.328125},{x:.796875,y:.328125},{x:.796875,y:.328125},{x:.828125,y:.328125},{x:.828125,y:.328125},{x:.859375,y:.328125},{x:.859375,y:.328125},{x:.890625,y:.328125},{x:.890625,y:.328125},{x:.921875,y:.328125},{x:.921875,y:.328125},{x:.953125,y:.328125},{x:.953125,y:.328125},{x:.984375,y:.328125},{x:.984375,y:.328125},{x:.015625,y:.359375},{x:.015625,y:.359375},{x:.046875,y:.359375},{x:.046875,y:.359375},{x:.078125,y:.359375},{x:.078125,y:.359375},{x:.109375,y:.359375},{x:.109375,y:.359375},{x:.140625,y:.359375},{x:.140625,y:.359375},{x:.171875,y:.359375},{x:.171875,y:.359375},{x:.203125,y:.359375},{x:.203125,y:.359375},{x:.234375,y:.359375},{x:.234375,y:.359375},{x:.265625,y:.359375},{x:.265625,y:.359375},{x:.296875,y:.359375},{x:.296875,y:.359375},{x:.328125,y:.359375},{x:.328125,y:.359375},{x:.359375,y:.359375},{x:.359375,y:.359375},{x:.390625,y:.359375},{x:.390625,y:.359375},{x:.421875,y:.359375},{x:.421875,y:.359375},{x:.453125,y:.359375},{x:.453125,y:.359375},{x:.484375,y:.359375},{x:.484375,y:.359375},{x:.515625,y:.359375},{x:.515625,y:.359375},{x:.546875,y:.359375},{x:.546875,y:.359375},{x:.578125,y:.359375},{x:.578125,y:.359375},{x:.609375,y:.359375},{x:.609375,y:.359375},{x:.640625,y:.359375},{x:.640625,y:.359375},{x:.671875,y:.359375},{x:.671875,y:.359375},{x:.703125,y:.359375},{x:.703125,y:.359375},{x:.734375,y:.359375},{x:.734375,y:.359375},{x:.765625,y:.359375},{x:.765625,y:.359375},{x:.796875,y:.359375},{x:.796875,y:.359375},{x:.828125,y:.359375},{x:.828125,y:.359375},{x:.859375,y:.359375},{x:.859375,y:.359375},{x:.890625,y:.359375},{x:.890625,y:.359375},{x:.921875,y:.359375},{x:.921875,y:.359375},{x:.953125,y:.359375},{x:.953125,y:.359375},{x:.984375,y:.359375},{x:.984375,y:.359375},{x:.015625,y:.390625},{x:.015625,y:.390625},{x:.046875,y:.390625},{x:.046875,y:.390625},{x:.078125,y:.390625},{x:.078125,y:.390625},{x:.109375,y:.390625},{x:.109375,y:.390625},{x:.140625,y:.390625},{x:.140625,y:.390625},{x:.171875,y:.390625},{x:.171875,y:.390625},{x:.203125,y:.390625},{x:.203125,y:.390625},{x:.234375,y:.390625},{x:.234375,y:.390625},{x:.265625,y:.390625},{x:.265625,y:.390625},{x:.296875,y:.390625},{x:.296875,y:.390625},{x:.328125,y:.390625},{x:.328125,y:.390625},{x:.359375,y:.390625},{x:.359375,y:.390625},{x:.390625,y:.390625},{x:.390625,y:.390625},{x:.421875,y:.390625},{x:.421875,y:.390625},{x:.453125,y:.390625},{x:.453125,y:.390625},{x:.484375,y:.390625},{x:.484375,y:.390625},{x:.515625,y:.390625},{x:.515625,y:.390625},{x:.546875,y:.390625},{x:.546875,y:.390625},{x:.578125,y:.390625},{x:.578125,y:.390625},{x:.609375,y:.390625},{x:.609375,y:.390625},{x:.640625,y:.390625},{x:.640625,y:.390625},{x:.671875,y:.390625},{x:.671875,y:.390625},{x:.703125,y:.390625},{x:.703125,y:.390625},{x:.734375,y:.390625},{x:.734375,y:.390625},{x:.765625,y:.390625},{x:.765625,y:.390625},{x:.796875,y:.390625},{x:.796875,y:.390625},{x:.828125,y:.390625},{x:.828125,y:.390625},{x:.859375,y:.390625},{x:.859375,y:.390625},{x:.890625,y:.390625},{x:.890625,y:.390625},{x:.921875,y:.390625},{x:.921875,y:.390625},{x:.953125,y:.390625},{x:.953125,y:.390625},{x:.984375,y:.390625},{x:.984375,y:.390625},{x:.015625,y:.421875},{x:.015625,y:.421875},{x:.046875,y:.421875},{x:.046875,y:.421875},{x:.078125,y:.421875},{x:.078125,y:.421875},{x:.109375,y:.421875},{x:.109375,y:.421875},{x:.140625,y:.421875},{x:.140625,y:.421875},{x:.171875,y:.421875},{x:.171875,y:.421875},{x:.203125,y:.421875},{x:.203125,y:.421875},{x:.234375,y:.421875},{x:.234375,y:.421875},{x:.265625,y:.421875},{x:.265625,y:.421875},{x:.296875,y:.421875},{x:.296875,y:.421875},{x:.328125,y:.421875},{x:.328125,y:.421875},{x:.359375,y:.421875},{x:.359375,y:.421875},{x:.390625,y:.421875},{x:.390625,y:.421875},{x:.421875,y:.421875},{x:.421875,y:.421875},{x:.453125,y:.421875},{x:.453125,y:.421875},{x:.484375,y:.421875},{x:.484375,y:.421875},{x:.515625,y:.421875},{x:.515625,y:.421875},{x:.546875,y:.421875},{x:.546875,y:.421875},{x:.578125,y:.421875},{x:.578125,y:.421875},{x:.609375,y:.421875},{x:.609375,y:.421875},{x:.640625,y:.421875},{x:.640625,y:.421875},{x:.671875,y:.421875},{x:.671875,y:.421875},{x:.703125,y:.421875},{x:.703125,y:.421875},{x:.734375,y:.421875},{x:.734375,y:.421875},{x:.765625,y:.421875},{x:.765625,y:.421875},{x:.796875,y:.421875},{x:.796875,y:.421875},{x:.828125,y:.421875},{x:.828125,y:.421875},{x:.859375,y:.421875},{x:.859375,y:.421875},{x:.890625,y:.421875},{x:.890625,y:.421875},{x:.921875,y:.421875},{x:.921875,y:.421875},{x:.953125,y:.421875},{x:.953125,y:.421875},{x:.984375,y:.421875},{x:.984375,y:.421875},{x:.015625,y:.453125},{x:.015625,y:.453125},{x:.046875,y:.453125},{x:.046875,y:.453125},{x:.078125,y:.453125},{x:.078125,y:.453125},{x:.109375,y:.453125},{x:.109375,y:.453125},{x:.140625,y:.453125},{x:.140625,y:.453125},{x:.171875,y:.453125},{x:.171875,y:.453125},{x:.203125,y:.453125},{x:.203125,y:.453125},{x:.234375,y:.453125},{x:.234375,y:.453125},{x:.265625,y:.453125},{x:.265625,y:.453125},{x:.296875,y:.453125},{x:.296875,y:.453125},{x:.328125,y:.453125},{x:.328125,y:.453125},{x:.359375,y:.453125},{x:.359375,y:.453125},{x:.390625,y:.453125},{x:.390625,y:.453125},{x:.421875,y:.453125},{x:.421875,y:.453125},{x:.453125,y:.453125},{x:.453125,y:.453125},{x:.484375,y:.453125},{x:.484375,y:.453125},{x:.515625,y:.453125},{x:.515625,y:.453125},{x:.546875,y:.453125},{x:.546875,y:.453125},{x:.578125,y:.453125},{x:.578125,y:.453125},{x:.609375,y:.453125},{x:.609375,y:.453125},{x:.640625,y:.453125},{x:.640625,y:.453125},{x:.671875,y:.453125},{x:.671875,y:.453125},{x:.703125,y:.453125},{x:.703125,y:.453125},{x:.734375,y:.453125},{x:.734375,y:.453125},{x:.765625,y:.453125},{x:.765625,y:.453125},{x:.796875,y:.453125},{x:.796875,y:.453125},{x:.828125,y:.453125},{x:.828125,y:.453125},{x:.859375,y:.453125},{x:.859375,y:.453125},{x:.890625,y:.453125},{x:.890625,y:.453125},{x:.921875,y:.453125},{x:.921875,y:.453125},{x:.953125,y:.453125},{x:.953125,y:.453125},{x:.984375,y:.453125},{x:.984375,y:.453125},{x:.015625,y:.484375},{x:.015625,y:.484375},{x:.046875,y:.484375},{x:.046875,y:.484375},{x:.078125,y:.484375},{x:.078125,y:.484375},{x:.109375,y:.484375},{x:.109375,y:.484375},{x:.140625,y:.484375},{x:.140625,y:.484375},{x:.171875,y:.484375},{x:.171875,y:.484375},{x:.203125,y:.484375},{x:.203125,y:.484375},{x:.234375,y:.484375},{x:.234375,y:.484375},{x:.265625,y:.484375},{x:.265625,y:.484375},{x:.296875,y:.484375},{x:.296875,y:.484375},{x:.328125,y:.484375},{x:.328125,y:.484375},{x:.359375,y:.484375},{x:.359375,y:.484375},{x:.390625,y:.484375},{x:.390625,y:.484375},{x:.421875,y:.484375},{x:.421875,y:.484375},{x:.453125,y:.484375},{x:.453125,y:.484375},{x:.484375,y:.484375},{x:.484375,y:.484375},{x:.515625,y:.484375},{x:.515625,y:.484375},{x:.546875,y:.484375},{x:.546875,y:.484375},{x:.578125,y:.484375},{x:.578125,y:.484375},{x:.609375,y:.484375},{x:.609375,y:.484375},{x:.640625,y:.484375},{x:.640625,y:.484375},{x:.671875,y:.484375},{x:.671875,y:.484375},{x:.703125,y:.484375},{x:.703125,y:.484375},{x:.734375,y:.484375},{x:.734375,y:.484375},{x:.765625,y:.484375},{x:.765625,y:.484375},{x:.796875,y:.484375},{x:.796875,y:.484375},{x:.828125,y:.484375},{x:.828125,y:.484375},{x:.859375,y:.484375},{x:.859375,y:.484375},{x:.890625,y:.484375},{x:.890625,y:.484375},{x:.921875,y:.484375},{x:.921875,y:.484375},{x:.953125,y:.484375},{x:.953125,y:.484375},{x:.984375,y:.484375},{x:.984375,y:.484375},{x:.015625,y:.515625},{x:.015625,y:.515625},{x:.046875,y:.515625},{x:.046875,y:.515625},{x:.078125,y:.515625},{x:.078125,y:.515625},{x:.109375,y:.515625},{x:.109375,y:.515625},{x:.140625,y:.515625},{x:.140625,y:.515625},{x:.171875,y:.515625},{x:.171875,y:.515625},{x:.203125,y:.515625},{x:.203125,y:.515625},{x:.234375,y:.515625},{x:.234375,y:.515625},{x:.265625,y:.515625},{x:.265625,y:.515625},{x:.296875,y:.515625},{x:.296875,y:.515625},{x:.328125,y:.515625},{x:.328125,y:.515625},{x:.359375,y:.515625},{x:.359375,y:.515625},{x:.390625,y:.515625},{x:.390625,y:.515625},{x:.421875,y:.515625},{x:.421875,y:.515625},{x:.453125,y:.515625},{x:.453125,y:.515625},{x:.484375,y:.515625},{x:.484375,y:.515625},{x:.515625,y:.515625},{x:.515625,y:.515625},{x:.546875,y:.515625},{x:.546875,y:.515625},{x:.578125,y:.515625},{x:.578125,y:.515625},{x:.609375,y:.515625},{x:.609375,y:.515625},{x:.640625,y:.515625},{x:.640625,y:.515625},{x:.671875,y:.515625},{x:.671875,y:.515625},{x:.703125,y:.515625},{x:.703125,y:.515625},{x:.734375,y:.515625},{x:.734375,y:.515625},{x:.765625,y:.515625},{x:.765625,y:.515625},{x:.796875,y:.515625},{x:.796875,y:.515625},{x:.828125,y:.515625},{x:.828125,y:.515625},{x:.859375,y:.515625},{x:.859375,y:.515625},{x:.890625,y:.515625},{x:.890625,y:.515625},{x:.921875,y:.515625},{x:.921875,y:.515625},{x:.953125,y:.515625},{x:.953125,y:.515625},{x:.984375,y:.515625},{x:.984375,y:.515625},{x:.015625,y:.546875},{x:.015625,y:.546875},{x:.046875,y:.546875},{x:.046875,y:.546875},{x:.078125,y:.546875},{x:.078125,y:.546875},{x:.109375,y:.546875},{x:.109375,y:.546875},{x:.140625,y:.546875},{x:.140625,y:.546875},{x:.171875,y:.546875},{x:.171875,y:.546875},{x:.203125,y:.546875},{x:.203125,y:.546875},{x:.234375,y:.546875},{x:.234375,y:.546875},{x:.265625,y:.546875},{x:.265625,y:.546875},{x:.296875,y:.546875},{x:.296875,y:.546875},{x:.328125,y:.546875},{x:.328125,y:.546875},{x:.359375,y:.546875},{x:.359375,y:.546875},{x:.390625,y:.546875},{x:.390625,y:.546875},{x:.421875,y:.546875},{x:.421875,y:.546875},{x:.453125,y:.546875},{x:.453125,y:.546875},{x:.484375,y:.546875},{x:.484375,y:.546875},{x:.515625,y:.546875},{x:.515625,y:.546875},{x:.546875,y:.546875},{x:.546875,y:.546875},{x:.578125,y:.546875},{x:.578125,y:.546875},{x:.609375,y:.546875},{x:.609375,y:.546875},{x:.640625,y:.546875},{x:.640625,y:.546875},{x:.671875,y:.546875},{x:.671875,y:.546875},{x:.703125,y:.546875},{x:.703125,y:.546875},{x:.734375,y:.546875},{x:.734375,y:.546875},{x:.765625,y:.546875},{x:.765625,y:.546875},{x:.796875,y:.546875},{x:.796875,y:.546875},{x:.828125,y:.546875},{x:.828125,y:.546875},{x:.859375,y:.546875},{x:.859375,y:.546875},{x:.890625,y:.546875},{x:.890625,y:.546875},{x:.921875,y:.546875},{x:.921875,y:.546875},{x:.953125,y:.546875},{x:.953125,y:.546875},{x:.984375,y:.546875},{x:.984375,y:.546875},{x:.015625,y:.578125},{x:.015625,y:.578125},{x:.046875,y:.578125},{x:.046875,y:.578125},{x:.078125,y:.578125},{x:.078125,y:.578125},{x:.109375,y:.578125},{x:.109375,y:.578125},{x:.140625,y:.578125},{x:.140625,y:.578125},{x:.171875,y:.578125},{x:.171875,y:.578125},{x:.203125,y:.578125},{x:.203125,y:.578125},{x:.234375,y:.578125},{x:.234375,y:.578125},{x:.265625,y:.578125},{x:.265625,y:.578125},{x:.296875,y:.578125},{x:.296875,y:.578125},{x:.328125,y:.578125},{x:.328125,y:.578125},{x:.359375,y:.578125},{x:.359375,y:.578125},{x:.390625,y:.578125},{x:.390625,y:.578125},{x:.421875,y:.578125},{x:.421875,y:.578125},{x:.453125,y:.578125},{x:.453125,y:.578125},{x:.484375,y:.578125},{x:.484375,y:.578125},{x:.515625,y:.578125},{x:.515625,y:.578125},{x:.546875,y:.578125},{x:.546875,y:.578125},{x:.578125,y:.578125},{x:.578125,y:.578125},{x:.609375,y:.578125},{x:.609375,y:.578125},{x:.640625,y:.578125},{x:.640625,y:.578125},{x:.671875,y:.578125},{x:.671875,y:.578125},{x:.703125,y:.578125},{x:.703125,y:.578125},{x:.734375,y:.578125},{x:.734375,y:.578125},{x:.765625,y:.578125},{x:.765625,y:.578125},{x:.796875,y:.578125},{x:.796875,y:.578125},{x:.828125,y:.578125},{x:.828125,y:.578125},{x:.859375,y:.578125},{x:.859375,y:.578125},{x:.890625,y:.578125},{x:.890625,y:.578125},{x:.921875,y:.578125},{x:.921875,y:.578125},{x:.953125,y:.578125},{x:.953125,y:.578125},{x:.984375,y:.578125},{x:.984375,y:.578125},{x:.015625,y:.609375},{x:.015625,y:.609375},{x:.046875,y:.609375},{x:.046875,y:.609375},{x:.078125,y:.609375},{x:.078125,y:.609375},{x:.109375,y:.609375},{x:.109375,y:.609375},{x:.140625,y:.609375},{x:.140625,y:.609375},{x:.171875,y:.609375},{x:.171875,y:.609375},{x:.203125,y:.609375},{x:.203125,y:.609375},{x:.234375,y:.609375},{x:.234375,y:.609375},{x:.265625,y:.609375},{x:.265625,y:.609375},{x:.296875,y:.609375},{x:.296875,y:.609375},{x:.328125,y:.609375},{x:.328125,y:.609375},{x:.359375,y:.609375},{x:.359375,y:.609375},{x:.390625,y:.609375},{x:.390625,y:.609375},{x:.421875,y:.609375},{x:.421875,y:.609375},{x:.453125,y:.609375},{x:.453125,y:.609375},{x:.484375,y:.609375},{x:.484375,y:.609375},{x:.515625,y:.609375},{x:.515625,y:.609375},{x:.546875,y:.609375},{x:.546875,y:.609375},{x:.578125,y:.609375},{x:.578125,y:.609375},{x:.609375,y:.609375},{x:.609375,y:.609375},{x:.640625,y:.609375},{x:.640625,y:.609375},{x:.671875,y:.609375},{x:.671875,y:.609375},{x:.703125,y:.609375},{x:.703125,y:.609375},{x:.734375,y:.609375},{x:.734375,y:.609375},{x:.765625,y:.609375},{x:.765625,y:.609375},{x:.796875,y:.609375},{x:.796875,y:.609375},{x:.828125,y:.609375},{x:.828125,y:.609375},{x:.859375,y:.609375},{x:.859375,y:.609375},{x:.890625,y:.609375},{x:.890625,y:.609375},{x:.921875,y:.609375},{x:.921875,y:.609375},{x:.953125,y:.609375},{x:.953125,y:.609375},{x:.984375,y:.609375},{x:.984375,y:.609375},{x:.015625,y:.640625},{x:.015625,y:.640625},{x:.046875,y:.640625},{x:.046875,y:.640625},{x:.078125,y:.640625},{x:.078125,y:.640625},{x:.109375,y:.640625},{x:.109375,y:.640625},{x:.140625,y:.640625},{x:.140625,y:.640625},{x:.171875,y:.640625},{x:.171875,y:.640625},{x:.203125,y:.640625},{x:.203125,y:.640625},{x:.234375,y:.640625},{x:.234375,y:.640625},{x:.265625,y:.640625},{x:.265625,y:.640625},{x:.296875,y:.640625},{x:.296875,y:.640625},{x:.328125,y:.640625},{x:.328125,y:.640625},{x:.359375,y:.640625},{x:.359375,y:.640625},{x:.390625,y:.640625},{x:.390625,y:.640625},{x:.421875,y:.640625},{x:.421875,y:.640625},{x:.453125,y:.640625},{x:.453125,y:.640625},{x:.484375,y:.640625},{x:.484375,y:.640625},{x:.515625,y:.640625},{x:.515625,y:.640625},{x:.546875,y:.640625},{x:.546875,y:.640625},{x:.578125,y:.640625},{x:.578125,y:.640625},{x:.609375,y:.640625},{x:.609375,y:.640625},{x:.640625,y:.640625},{x:.640625,y:.640625},{x:.671875,y:.640625},{x:.671875,y:.640625},{x:.703125,y:.640625},{x:.703125,y:.640625},{x:.734375,y:.640625},{x:.734375,y:.640625},{x:.765625,y:.640625},{x:.765625,y:.640625},{x:.796875,y:.640625},{x:.796875,y:.640625},{x:.828125,y:.640625},{x:.828125,y:.640625},{x:.859375,y:.640625},{x:.859375,y:.640625},{x:.890625,y:.640625},{x:.890625,y:.640625},{x:.921875,y:.640625},{x:.921875,y:.640625},{x:.953125,y:.640625},{x:.953125,y:.640625},{x:.984375,y:.640625},{x:.984375,y:.640625},{x:.015625,y:.671875},{x:.015625,y:.671875},{x:.046875,y:.671875},{x:.046875,y:.671875},{x:.078125,y:.671875},{x:.078125,y:.671875},{x:.109375,y:.671875},{x:.109375,y:.671875},{x:.140625,y:.671875},{x:.140625,y:.671875},{x:.171875,y:.671875},{x:.171875,y:.671875},{x:.203125,y:.671875},{x:.203125,y:.671875},{x:.234375,y:.671875},{x:.234375,y:.671875},{x:.265625,y:.671875},{x:.265625,y:.671875},{x:.296875,y:.671875},{x:.296875,y:.671875},{x:.328125,y:.671875},{x:.328125,y:.671875},{x:.359375,y:.671875},{x:.359375,y:.671875},{x:.390625,y:.671875},{x:.390625,y:.671875},{x:.421875,y:.671875},{x:.421875,y:.671875},{x:.453125,y:.671875},{x:.453125,y:.671875},{x:.484375,y:.671875},{x:.484375,y:.671875},{x:.515625,y:.671875},{x:.515625,y:.671875},{x:.546875,y:.671875},{x:.546875,y:.671875},{x:.578125,y:.671875},{x:.578125,y:.671875},{x:.609375,y:.671875},{x:.609375,y:.671875},{x:.640625,y:.671875},{x:.640625,y:.671875},{x:.671875,y:.671875},{x:.671875,y:.671875},{x:.703125,y:.671875},{x:.703125,y:.671875},{x:.734375,y:.671875},{x:.734375,y:.671875},{x:.765625,y:.671875},{x:.765625,y:.671875},{x:.796875,y:.671875},{x:.796875,y:.671875},{x:.828125,y:.671875},{x:.828125,y:.671875},{x:.859375,y:.671875},{x:.859375,y:.671875},{x:.890625,y:.671875},{x:.890625,y:.671875},{x:.921875,y:.671875},{x:.921875,y:.671875},{x:.953125,y:.671875},{x:.953125,y:.671875},{x:.984375,y:.671875},{x:.984375,y:.671875},{x:.015625,y:.703125},{x:.015625,y:.703125},{x:.046875,y:.703125},{x:.046875,y:.703125},{x:.078125,y:.703125},{x:.078125,y:.703125},{x:.109375,y:.703125},{x:.109375,y:.703125},{x:.140625,y:.703125},{x:.140625,y:.703125},{x:.171875,y:.703125},{x:.171875,y:.703125},{x:.203125,y:.703125},{x:.203125,y:.703125},{x:.234375,y:.703125},{x:.234375,y:.703125},{x:.265625,y:.703125},{x:.265625,y:.703125},{x:.296875,y:.703125},{x:.296875,y:.703125},{x:.328125,y:.703125},{x:.328125,y:.703125},{x:.359375,y:.703125},{x:.359375,y:.703125},{x:.390625,y:.703125},{x:.390625,y:.703125},{x:.421875,y:.703125},{x:.421875,y:.703125},{x:.453125,y:.703125},{x:.453125,y:.703125},{x:.484375,y:.703125},{x:.484375,y:.703125},{x:.515625,y:.703125},{x:.515625,y:.703125},{x:.546875,y:.703125},{x:.546875,y:.703125},{x:.578125,y:.703125},{x:.578125,y:.703125},{x:.609375,y:.703125},{x:.609375,y:.703125},{x:.640625,y:.703125},{x:.640625,y:.703125},{x:.671875,y:.703125},{x:.671875,y:.703125},{x:.703125,y:.703125},{x:.703125,y:.703125},{x:.734375,y:.703125},{x:.734375,y:.703125},{x:.765625,y:.703125},{x:.765625,y:.703125},{x:.796875,y:.703125},{x:.796875,y:.703125},{x:.828125,y:.703125},{x:.828125,y:.703125},{x:.859375,y:.703125},{x:.859375,y:.703125},{x:.890625,y:.703125},{x:.890625,y:.703125},{x:.921875,y:.703125},{x:.921875,y:.703125},{x:.953125,y:.703125},{x:.953125,y:.703125},{x:.984375,y:.703125},{x:.984375,y:.703125},{x:.015625,y:.734375},{x:.015625,y:.734375},{x:.046875,y:.734375},{x:.046875,y:.734375},{x:.078125,y:.734375},{x:.078125,y:.734375},{x:.109375,y:.734375},{x:.109375,y:.734375},{x:.140625,y:.734375},{x:.140625,y:.734375},{x:.171875,y:.734375},{x:.171875,y:.734375},{x:.203125,y:.734375},{x:.203125,y:.734375},{x:.234375,y:.734375},{x:.234375,y:.734375},{x:.265625,y:.734375},{x:.265625,y:.734375},{x:.296875,y:.734375},{x:.296875,y:.734375},{x:.328125,y:.734375},{x:.328125,y:.734375},{x:.359375,y:.734375},{x:.359375,y:.734375},{x:.390625,y:.734375},{x:.390625,y:.734375},{x:.421875,y:.734375},{x:.421875,y:.734375},{x:.453125,y:.734375},{x:.453125,y:.734375},{x:.484375,y:.734375},{x:.484375,y:.734375},{x:.515625,y:.734375},{x:.515625,y:.734375},{x:.546875,y:.734375},{x:.546875,y:.734375},{x:.578125,y:.734375},{x:.578125,y:.734375},{x:.609375,y:.734375},{x:.609375,y:.734375},{x:.640625,y:.734375},{x:.640625,y:.734375},{x:.671875,y:.734375},{x:.671875,y:.734375},{x:.703125,y:.734375},{x:.703125,y:.734375},{x:.734375,y:.734375},{x:.734375,y:.734375},{x:.765625,y:.734375},{x:.765625,y:.734375},{x:.796875,y:.734375},{x:.796875,y:.734375},{x:.828125,y:.734375},{x:.828125,y:.734375},{x:.859375,y:.734375},{x:.859375,y:.734375},{x:.890625,y:.734375},{x:.890625,y:.734375},{x:.921875,y:.734375},{x:.921875,y:.734375},{x:.953125,y:.734375},{x:.953125,y:.734375},{x:.984375,y:.734375},{x:.984375,y:.734375},{x:.015625,y:.765625},{x:.015625,y:.765625},{x:.046875,y:.765625},{x:.046875,y:.765625},{x:.078125,y:.765625},{x:.078125,y:.765625},{x:.109375,y:.765625},{x:.109375,y:.765625},{x:.140625,y:.765625},{x:.140625,y:.765625},{x:.171875,y:.765625},{x:.171875,y:.765625},{x:.203125,y:.765625},{x:.203125,y:.765625},{x:.234375,y:.765625},{x:.234375,y:.765625},{x:.265625,y:.765625},{x:.265625,y:.765625},{x:.296875,y:.765625},{x:.296875,y:.765625},{x:.328125,y:.765625},{x:.328125,y:.765625},{x:.359375,y:.765625},{x:.359375,y:.765625},{x:.390625,y:.765625},{x:.390625,y:.765625},{x:.421875,y:.765625},{x:.421875,y:.765625},{x:.453125,y:.765625},{x:.453125,y:.765625},{x:.484375,y:.765625},{x:.484375,y:.765625},{x:.515625,y:.765625},{x:.515625,y:.765625},{x:.546875,y:.765625},{x:.546875,y:.765625},{x:.578125,y:.765625},{x:.578125,y:.765625},{x:.609375,y:.765625},{x:.609375,y:.765625},{x:.640625,y:.765625},{x:.640625,y:.765625},{x:.671875,y:.765625},{x:.671875,y:.765625},{x:.703125,y:.765625},{x:.703125,y:.765625},{x:.734375,y:.765625},{x:.734375,y:.765625},{x:.765625,y:.765625},{x:.765625,y:.765625},{x:.796875,y:.765625},{x:.796875,y:.765625},{x:.828125,y:.765625},{x:.828125,y:.765625},{x:.859375,y:.765625},{x:.859375,y:.765625},{x:.890625,y:.765625},{x:.890625,y:.765625},{x:.921875,y:.765625},{x:.921875,y:.765625},{x:.953125,y:.765625},{x:.953125,y:.765625},{x:.984375,y:.765625},{x:.984375,y:.765625},{x:.015625,y:.796875},{x:.015625,y:.796875},{x:.046875,y:.796875},{x:.046875,y:.796875},{x:.078125,y:.796875},{x:.078125,y:.796875},{x:.109375,y:.796875},{x:.109375,y:.796875},{x:.140625,y:.796875},{x:.140625,y:.796875},{x:.171875,y:.796875},{x:.171875,y:.796875},{x:.203125,y:.796875},{x:.203125,y:.796875},{x:.234375,y:.796875},{x:.234375,y:.796875},{x:.265625,y:.796875},{x:.265625,y:.796875},{x:.296875,y:.796875},{x:.296875,y:.796875},{x:.328125,y:.796875},{x:.328125,y:.796875},{x:.359375,y:.796875},{x:.359375,y:.796875},{x:.390625,y:.796875},{x:.390625,y:.796875},{x:.421875,y:.796875},{x:.421875,y:.796875},{x:.453125,y:.796875},{x:.453125,y:.796875},{x:.484375,y:.796875},{x:.484375,y:.796875},{x:.515625,y:.796875},{x:.515625,y:.796875},{x:.546875,y:.796875},{x:.546875,y:.796875},{x:.578125,y:.796875},{x:.578125,y:.796875},{x:.609375,y:.796875},{x:.609375,y:.796875},{x:.640625,y:.796875},{x:.640625,y:.796875},{x:.671875,y:.796875},{x:.671875,y:.796875},{x:.703125,y:.796875},{x:.703125,y:.796875},{x:.734375,y:.796875},{x:.734375,y:.796875},{x:.765625,y:.796875},{x:.765625,y:.796875},{x:.796875,y:.796875},{x:.796875,y:.796875},{x:.828125,y:.796875},{x:.828125,y:.796875},{x:.859375,y:.796875},{x:.859375,y:.796875},{x:.890625,y:.796875},{x:.890625,y:.796875},{x:.921875,y:.796875},{x:.921875,y:.796875},{x:.953125,y:.796875},{x:.953125,y:.796875},{x:.984375,y:.796875},{x:.984375,y:.796875},{x:.015625,y:.828125},{x:.015625,y:.828125},{x:.046875,y:.828125},{x:.046875,y:.828125},{x:.078125,y:.828125},{x:.078125,y:.828125},{x:.109375,y:.828125},{x:.109375,y:.828125},{x:.140625,y:.828125},{x:.140625,y:.828125},{x:.171875,y:.828125},{x:.171875,y:.828125},{x:.203125,y:.828125},{x:.203125,y:.828125},{x:.234375,y:.828125},{x:.234375,y:.828125},{x:.265625,y:.828125},{x:.265625,y:.828125},{x:.296875,y:.828125},{x:.296875,y:.828125},{x:.328125,y:.828125},{x:.328125,y:.828125},{x:.359375,y:.828125},{x:.359375,y:.828125},{x:.390625,y:.828125},{x:.390625,y:.828125},{x:.421875,y:.828125},{x:.421875,y:.828125},{x:.453125,y:.828125},{x:.453125,y:.828125},{x:.484375,y:.828125},{x:.484375,y:.828125},{x:.515625,y:.828125},{x:.515625,y:.828125},{x:.546875,y:.828125},{x:.546875,y:.828125},{x:.578125,y:.828125},{x:.578125,y:.828125},{x:.609375,y:.828125},{x:.609375,y:.828125},{x:.640625,y:.828125},{x:.640625,y:.828125},{x:.671875,y:.828125},{x:.671875,y:.828125},{x:.703125,y:.828125},{x:.703125,y:.828125},{x:.734375,y:.828125},{x:.734375,y:.828125},{x:.765625,y:.828125},{x:.765625,y:.828125},{x:.796875,y:.828125},{x:.796875,y:.828125},{x:.828125,y:.828125},{x:.828125,y:.828125},{x:.859375,y:.828125},{x:.859375,y:.828125},{x:.890625,y:.828125},{x:.890625,y:.828125},{x:.921875,y:.828125},{x:.921875,y:.828125},{x:.953125,y:.828125},{x:.953125,y:.828125},{x:.984375,y:.828125},{x:.984375,y:.828125},{x:.015625,y:.859375},{x:.015625,y:.859375},{x:.046875,y:.859375},{x:.046875,y:.859375},{x:.078125,y:.859375},{x:.078125,y:.859375},{x:.109375,y:.859375},{x:.109375,y:.859375},{x:.140625,y:.859375},{x:.140625,y:.859375},{x:.171875,y:.859375},{x:.171875,y:.859375},{x:.203125,y:.859375},{x:.203125,y:.859375},{x:.234375,y:.859375},{x:.234375,y:.859375},{x:.265625,y:.859375},{x:.265625,y:.859375},{x:.296875,y:.859375},{x:.296875,y:.859375},{x:.328125,y:.859375},{x:.328125,y:.859375},{x:.359375,y:.859375},{x:.359375,y:.859375},{x:.390625,y:.859375},{x:.390625,y:.859375},{x:.421875,y:.859375},{x:.421875,y:.859375},{x:.453125,y:.859375},{x:.453125,y:.859375},{x:.484375,y:.859375},{x:.484375,y:.859375},{x:.515625,y:.859375},{x:.515625,y:.859375},{x:.546875,y:.859375},{x:.546875,y:.859375},{x:.578125,y:.859375},{x:.578125,y:.859375},{x:.609375,y:.859375},{x:.609375,y:.859375},{x:.640625,y:.859375},{x:.640625,y:.859375},{x:.671875,y:.859375},{x:.671875,y:.859375},{x:.703125,y:.859375},{x:.703125,y:.859375},{x:.734375,y:.859375},{x:.734375,y:.859375},{x:.765625,y:.859375},{x:.765625,y:.859375},{x:.796875,y:.859375},{x:.796875,y:.859375},{x:.828125,y:.859375},{x:.828125,y:.859375},{x:.859375,y:.859375},{x:.859375,y:.859375},{x:.890625,y:.859375},{x:.890625,y:.859375},{x:.921875,y:.859375},{x:.921875,y:.859375},{x:.953125,y:.859375},{x:.953125,y:.859375},{x:.984375,y:.859375},{x:.984375,y:.859375},{x:.015625,y:.890625},{x:.015625,y:.890625},{x:.046875,y:.890625},{x:.046875,y:.890625},{x:.078125,y:.890625},{x:.078125,y:.890625},{x:.109375,y:.890625},{x:.109375,y:.890625},{x:.140625,y:.890625},{x:.140625,y:.890625},{x:.171875,y:.890625},{x:.171875,y:.890625},{x:.203125,y:.890625},{x:.203125,y:.890625},{x:.234375,y:.890625},{x:.234375,y:.890625},{x:.265625,y:.890625},{x:.265625,y:.890625},{x:.296875,y:.890625},{x:.296875,y:.890625},{x:.328125,y:.890625},{x:.328125,y:.890625},{x:.359375,y:.890625},{x:.359375,y:.890625},{x:.390625,y:.890625},{x:.390625,y:.890625},{x:.421875,y:.890625},{x:.421875,y:.890625},{x:.453125,y:.890625},{x:.453125,y:.890625},{x:.484375,y:.890625},{x:.484375,y:.890625},{x:.515625,y:.890625},{x:.515625,y:.890625},{x:.546875,y:.890625},{x:.546875,y:.890625},{x:.578125,y:.890625},{x:.578125,y:.890625},{x:.609375,y:.890625},{x:.609375,y:.890625},{x:.640625,y:.890625},{x:.640625,y:.890625},{x:.671875,y:.890625},{x:.671875,y:.890625},{x:.703125,y:.890625},{x:.703125,y:.890625},{x:.734375,y:.890625},{x:.734375,y:.890625},{x:.765625,y:.890625},{x:.765625,y:.890625},{x:.796875,y:.890625},{x:.796875,y:.890625},{x:.828125,y:.890625},{x:.828125,y:.890625},{x:.859375,y:.890625},{x:.859375,y:.890625},{x:.890625,y:.890625},{x:.890625,y:.890625},{x:.921875,y:.890625},{x:.921875,y:.890625},{x:.953125,y:.890625},{x:.953125,y:.890625},{x:.984375,y:.890625},{x:.984375,y:.890625},{x:.015625,y:.921875},{x:.015625,y:.921875},{x:.046875,y:.921875},{x:.046875,y:.921875},{x:.078125,y:.921875},{x:.078125,y:.921875},{x:.109375,y:.921875},{x:.109375,y:.921875},{x:.140625,y:.921875},{x:.140625,y:.921875},{x:.171875,y:.921875},{x:.171875,y:.921875},{x:.203125,y:.921875},{x:.203125,y:.921875},{x:.234375,y:.921875},{x:.234375,y:.921875},{x:.265625,y:.921875},{x:.265625,y:.921875},{x:.296875,y:.921875},{x:.296875,y:.921875},{x:.328125,y:.921875},{x:.328125,y:.921875},{x:.359375,y:.921875},{x:.359375,y:.921875},{x:.390625,y:.921875},{x:.390625,y:.921875},{x:.421875,y:.921875},{x:.421875,y:.921875},{x:.453125,y:.921875},{x:.453125,y:.921875},{x:.484375,y:.921875},{x:.484375,y:.921875},{x:.515625,y:.921875},{x:.515625,y:.921875},{x:.546875,y:.921875},{x:.546875,y:.921875},{x:.578125,y:.921875},{x:.578125,y:.921875},{x:.609375,y:.921875},{x:.609375,y:.921875},{x:.640625,y:.921875},{x:.640625,y:.921875},{x:.671875,y:.921875},{x:.671875,y:.921875},{x:.703125,y:.921875},{x:.703125,y:.921875},{x:.734375,y:.921875},{x:.734375,y:.921875},{x:.765625,y:.921875},{x:.765625,y:.921875},{x:.796875,y:.921875},{x:.796875,y:.921875},{x:.828125,y:.921875},{x:.828125,y:.921875},{x:.859375,y:.921875},{x:.859375,y:.921875},{x:.890625,y:.921875},{x:.890625,y:.921875},{x:.921875,y:.921875},{x:.921875,y:.921875},{x:.953125,y:.921875},{x:.953125,y:.921875},{x:.984375,y:.921875},{x:.984375,y:.921875},{x:.015625,y:.953125},{x:.015625,y:.953125},{x:.046875,y:.953125},{x:.046875,y:.953125},{x:.078125,y:.953125},{x:.078125,y:.953125},{x:.109375,y:.953125},{x:.109375,y:.953125},{x:.140625,y:.953125},{x:.140625,y:.953125},{x:.171875,y:.953125},{x:.171875,y:.953125},{x:.203125,y:.953125},{x:.203125,y:.953125},{x:.234375,y:.953125},{x:.234375,y:.953125},{x:.265625,y:.953125},{x:.265625,y:.953125},{x:.296875,y:.953125},{x:.296875,y:.953125},{x:.328125,y:.953125},{x:.328125,y:.953125},{x:.359375,y:.953125},{x:.359375,y:.953125},{x:.390625,y:.953125},{x:.390625,y:.953125},{x:.421875,y:.953125},{x:.421875,y:.953125},{x:.453125,y:.953125},{x:.453125,y:.953125},{x:.484375,y:.953125},{x:.484375,y:.953125},{x:.515625,y:.953125},{x:.515625,y:.953125},{x:.546875,y:.953125},{x:.546875,y:.953125},{x:.578125,y:.953125},{x:.578125,y:.953125},{x:.609375,y:.953125},{x:.609375,y:.953125},{x:.640625,y:.953125},{x:.640625,y:.953125},{x:.671875,y:.953125},{x:.671875,y:.953125},{x:.703125,y:.953125},{x:.703125,y:.953125},{x:.734375,y:.953125},{x:.734375,y:.953125},{x:.765625,y:.953125},{x:.765625,y:.953125},{x:.796875,y:.953125},{x:.796875,y:.953125},{x:.828125,y:.953125},{x:.828125,y:.953125},{x:.859375,y:.953125},{x:.859375,y:.953125},{x:.890625,y:.953125},{x:.890625,y:.953125},{x:.921875,y:.953125},{x:.921875,y:.953125},{x:.953125,y:.953125},{x:.953125,y:.953125},{x:.984375,y:.953125},{x:.984375,y:.953125},{x:.015625,y:.984375},{x:.015625,y:.984375},{x:.046875,y:.984375},{x:.046875,y:.984375},{x:.078125,y:.984375},{x:.078125,y:.984375},{x:.109375,y:.984375},{x:.109375,y:.984375},{x:.140625,y:.984375},{x:.140625,y:.984375},{x:.171875,y:.984375},{x:.171875,y:.984375},{x:.203125,y:.984375},{x:.203125,y:.984375},{x:.234375,y:.984375},{x:.234375,y:.984375},{x:.265625,y:.984375},{x:.265625,y:.984375},{x:.296875,y:.984375},{x:.296875,y:.984375},{x:.328125,y:.984375},{x:.328125,y:.984375},{x:.359375,y:.984375},{x:.359375,y:.984375},{x:.390625,y:.984375},{x:.390625,y:.984375},{x:.421875,y:.984375},{x:.421875,y:.984375},{x:.453125,y:.984375},{x:.453125,y:.984375},{x:.484375,y:.984375},{x:.484375,y:.984375},{x:.515625,y:.984375},{x:.515625,y:.984375},{x:.546875,y:.984375},{x:.546875,y:.984375},{x:.578125,y:.984375},{x:.578125,y:.984375},{x:.609375,y:.984375},{x:.609375,y:.984375},{x:.640625,y:.984375},{x:.640625,y:.984375},{x:.671875,y:.984375},{x:.671875,y:.984375},{x:.703125,y:.984375},{x:.703125,y:.984375},{x:.734375,y:.984375},{x:.734375,y:.984375},{x:.765625,y:.984375},{x:.765625,y:.984375},{x:.796875,y:.984375},{x:.796875,y:.984375},{x:.828125,y:.984375},{x:.828125,y:.984375},{x:.859375,y:.984375},{x:.859375,y:.984375},{x:.890625,y:.984375},{x:.890625,y:.984375},{x:.921875,y:.984375},{x:.921875,y:.984375},{x:.953125,y:.984375},{x:.953125,y:.984375},{x:.984375,y:.984375},{x:.984375,y:.984375},{x:.03125,y:.03125},{x:.03125,y:.03125},{x:.09375,y:.03125},{x:.09375,y:.03125},{x:.15625,y:.03125},{x:.15625,y:.03125},{x:.21875,y:.03125},{x:.21875,y:.03125},{x:.28125,y:.03125},{x:.28125,y:.03125},{x:.34375,y:.03125},{x:.34375,y:.03125},{x:.40625,y:.03125},{x:.40625,y:.03125},{x:.46875,y:.03125},{x:.46875,y:.03125},{x:.53125,y:.03125},{x:.53125,y:.03125},{x:.59375,y:.03125},{x:.59375,y:.03125},{x:.65625,y:.03125},{x:.65625,y:.03125},{x:.71875,y:.03125},{x:.71875,y:.03125},{x:.78125,y:.03125},{x:.78125,y:.03125},{x:.84375,y:.03125},{x:.84375,y:.03125},{x:.90625,y:.03125},{x:.90625,y:.03125},{x:.96875,y:.03125},{x:.96875,y:.03125},{x:.03125,y:.09375},{x:.03125,y:.09375},{x:.09375,y:.09375},{x:.09375,y:.09375},{x:.15625,y:.09375},{x:.15625,y:.09375},{x:.21875,y:.09375},{x:.21875,y:.09375},{x:.28125,y:.09375},{x:.28125,y:.09375},{x:.34375,y:.09375},{x:.34375,y:.09375},{x:.40625,y:.09375},{x:.40625,y:.09375},{x:.46875,y:.09375},{x:.46875,y:.09375},{x:.53125,y:.09375},{x:.53125,y:.09375},{x:.59375,y:.09375},{x:.59375,y:.09375},{x:.65625,y:.09375},{x:.65625,y:.09375},{x:.71875,y:.09375},{x:.71875,y:.09375},{x:.78125,y:.09375},{x:.78125,y:.09375},{x:.84375,y:.09375},{x:.84375,y:.09375},{x:.90625,y:.09375},{x:.90625,y:.09375},{x:.96875,y:.09375},{x:.96875,y:.09375},{x:.03125,y:.15625},{x:.03125,y:.15625},{x:.09375,y:.15625},{x:.09375,y:.15625},{x:.15625,y:.15625},{x:.15625,y:.15625},{x:.21875,y:.15625},{x:.21875,y:.15625},{x:.28125,y:.15625},{x:.28125,y:.15625},{x:.34375,y:.15625},{x:.34375,y:.15625},{x:.40625,y:.15625},{x:.40625,y:.15625},{x:.46875,y:.15625},{x:.46875,y:.15625},{x:.53125,y:.15625},{x:.53125,y:.15625},{x:.59375,y:.15625},{x:.59375,y:.15625},{x:.65625,y:.15625},{x:.65625,y:.15625},{x:.71875,y:.15625},{x:.71875,y:.15625},{x:.78125,y:.15625},{x:.78125,y:.15625},{x:.84375,y:.15625},{x:.84375,y:.15625},{x:.90625,y:.15625},{x:.90625,y:.15625},{x:.96875,y:.15625},{x:.96875,y:.15625},{x:.03125,y:.21875},{x:.03125,y:.21875},{x:.09375,y:.21875},{x:.09375,y:.21875},{x:.15625,y:.21875},{x:.15625,y:.21875},{x:.21875,y:.21875},{x:.21875,y:.21875},{x:.28125,y:.21875},{x:.28125,y:.21875},{x:.34375,y:.21875},{x:.34375,y:.21875},{x:.40625,y:.21875},{x:.40625,y:.21875},{x:.46875,y:.21875},{x:.46875,y:.21875},{x:.53125,y:.21875},{x:.53125,y:.21875},{x:.59375,y:.21875},{x:.59375,y:.21875},{x:.65625,y:.21875},{x:.65625,y:.21875},{x:.71875,y:.21875},{x:.71875,y:.21875},{x:.78125,y:.21875},{x:.78125,y:.21875},{x:.84375,y:.21875},{x:.84375,y:.21875},{x:.90625,y:.21875},{x:.90625,y:.21875},{x:.96875,y:.21875},{x:.96875,y:.21875},{x:.03125,y:.28125},{x:.03125,y:.28125},{x:.09375,y:.28125},{x:.09375,y:.28125},{x:.15625,y:.28125},{x:.15625,y:.28125},{x:.21875,y:.28125},{x:.21875,y:.28125},{x:.28125,y:.28125},{x:.28125,y:.28125},{x:.34375,y:.28125},{x:.34375,y:.28125},{x:.40625,y:.28125},{x:.40625,y:.28125},{x:.46875,y:.28125},{x:.46875,y:.28125},{x:.53125,y:.28125},{x:.53125,y:.28125},{x:.59375,y:.28125},{x:.59375,y:.28125},{x:.65625,y:.28125},{x:.65625,y:.28125},{x:.71875,y:.28125},{x:.71875,y:.28125},{x:.78125,y:.28125},{x:.78125,y:.28125},{x:.84375,y:.28125},{x:.84375,y:.28125},{x:.90625,y:.28125},{x:.90625,y:.28125},{x:.96875,y:.28125},{x:.96875,y:.28125},{x:.03125,y:.34375},{x:.03125,y:.34375},{x:.09375,y:.34375},{x:.09375,y:.34375},{x:.15625,y:.34375},{x:.15625,y:.34375},{x:.21875,y:.34375},{x:.21875,y:.34375},{x:.28125,y:.34375},{x:.28125,y:.34375},{x:.34375,y:.34375},{x:.34375,y:.34375},{x:.40625,y:.34375},{x:.40625,y:.34375},{x:.46875,y:.34375},{x:.46875,y:.34375},{x:.53125,y:.34375},{x:.53125,y:.34375},{x:.59375,y:.34375},{x:.59375,y:.34375},{x:.65625,y:.34375},{x:.65625,y:.34375},{x:.71875,y:.34375},{x:.71875,y:.34375},{x:.78125,y:.34375},{x:.78125,y:.34375},{x:.84375,y:.34375},{x:.84375,y:.34375},{x:.90625,y:.34375},{x:.90625,y:.34375},{x:.96875,y:.34375},{x:.96875,y:.34375},{x:.03125,y:.40625},{x:.03125,y:.40625},{x:.09375,y:.40625},{x:.09375,y:.40625},{x:.15625,y:.40625},{x:.15625,y:.40625},{x:.21875,y:.40625},{x:.21875,y:.40625},{x:.28125,y:.40625},{x:.28125,y:.40625},{x:.34375,y:.40625},{x:.34375,y:.40625},{x:.40625,y:.40625},{x:.40625,y:.40625},{x:.46875,y:.40625},{x:.46875,y:.40625},{x:.53125,y:.40625},{x:.53125,y:.40625},{x:.59375,y:.40625},{x:.59375,y:.40625},{x:.65625,y:.40625},{x:.65625,y:.40625},{x:.71875,y:.40625},{x:.71875,y:.40625},{x:.78125,y:.40625},{x:.78125,y:.40625},{x:.84375,y:.40625},{x:.84375,y:.40625},{x:.90625,y:.40625},{x:.90625,y:.40625},{x:.96875,y:.40625},{x:.96875,y:.40625},{x:.03125,y:.46875},{x:.03125,y:.46875},{x:.09375,y:.46875},{x:.09375,y:.46875},{x:.15625,y:.46875},{x:.15625,y:.46875},{x:.21875,y:.46875},{x:.21875,y:.46875},{x:.28125,y:.46875},{x:.28125,y:.46875},{x:.34375,y:.46875},{x:.34375,y:.46875},{x:.40625,y:.46875},{x:.40625,y:.46875},{x:.46875,y:.46875},{x:.46875,y:.46875},{x:.53125,y:.46875},{x:.53125,y:.46875},{x:.59375,y:.46875},{x:.59375,y:.46875},{x:.65625,y:.46875},{x:.65625,y:.46875},{x:.71875,y:.46875},{x:.71875,y:.46875},{x:.78125,y:.46875},{x:.78125,y:.46875},{x:.84375,y:.46875},{x:.84375,y:.46875},{x:.90625,y:.46875},{x:.90625,y:.46875},{x:.96875,y:.46875},{x:.96875,y:.46875},{x:.03125,y:.53125},{x:.03125,y:.53125},{x:.09375,y:.53125},{x:.09375,y:.53125},{x:.15625,y:.53125},{x:.15625,y:.53125},{x:.21875,y:.53125},{x:.21875,y:.53125},{x:.28125,y:.53125},{x:.28125,y:.53125},{x:.34375,y:.53125},{x:.34375,y:.53125},{x:.40625,y:.53125},{x:.40625,y:.53125},{x:.46875,y:.53125},{x:.46875,y:.53125},{x:.53125,y:.53125},{x:.53125,y:.53125},{x:.59375,y:.53125},{x:.59375,y:.53125},{x:.65625,y:.53125},{x:.65625,y:.53125},{x:.71875,y:.53125},{x:.71875,y:.53125},{x:.78125,y:.53125},{x:.78125,y:.53125},{x:.84375,y:.53125},{x:.84375,y:.53125},{x:.90625,y:.53125},{x:.90625,y:.53125},{x:.96875,y:.53125},{x:.96875,y:.53125},{x:.03125,y:.59375},{x:.03125,y:.59375},{x:.09375,y:.59375},{x:.09375,y:.59375},{x:.15625,y:.59375},{x:.15625,y:.59375},{x:.21875,y:.59375},{x:.21875,y:.59375},{x:.28125,y:.59375},{x:.28125,y:.59375},{x:.34375,y:.59375},{x:.34375,y:.59375},{x:.40625,y:.59375},{x:.40625,y:.59375},{x:.46875,y:.59375},{x:.46875,y:.59375},{x:.53125,y:.59375},{x:.53125,y:.59375},{x:.59375,y:.59375},{x:.59375,y:.59375},{x:.65625,y:.59375},{x:.65625,y:.59375},{x:.71875,y:.59375},{x:.71875,y:.59375},{x:.78125,y:.59375},{x:.78125,y:.59375},{x:.84375,y:.59375},{x:.84375,y:.59375},{x:.90625,y:.59375},{x:.90625,y:.59375},{x:.96875,y:.59375},{x:.96875,y:.59375},{x:.03125,y:.65625},{x:.03125,y:.65625},{x:.09375,y:.65625},{x:.09375,y:.65625},{x:.15625,y:.65625},{x:.15625,y:.65625},{x:.21875,y:.65625},{x:.21875,y:.65625},{x:.28125,y:.65625},{x:.28125,y:.65625},{x:.34375,y:.65625},{x:.34375,y:.65625},{x:.40625,y:.65625},{x:.40625,y:.65625},{x:.46875,y:.65625},{x:.46875,y:.65625},{x:.53125,y:.65625},{x:.53125,y:.65625},{x:.59375,y:.65625},{x:.59375,y:.65625},{x:.65625,y:.65625},{x:.65625,y:.65625},{x:.71875,y:.65625},{x:.71875,y:.65625},{x:.78125,y:.65625},{x:.78125,y:.65625},{x:.84375,y:.65625},{x:.84375,y:.65625},{x:.90625,y:.65625},{x:.90625,y:.65625},{x:.96875,y:.65625},{x:.96875,y:.65625},{x:.03125,y:.71875},{x:.03125,y:.71875},{x:.09375,y:.71875},{x:.09375,y:.71875},{x:.15625,y:.71875},{x:.15625,y:.71875},{x:.21875,y:.71875},{x:.21875,y:.71875},{x:.28125,y:.71875},{x:.28125,y:.71875},{x:.34375,y:.71875},{x:.34375,y:.71875},{x:.40625,y:.71875},{x:.40625,y:.71875},{x:.46875,y:.71875},{x:.46875,y:.71875},{x:.53125,y:.71875},{x:.53125,y:.71875},{x:.59375,y:.71875},{x:.59375,y:.71875},{x:.65625,y:.71875},{x:.65625,y:.71875},{x:.71875,y:.71875},{x:.71875,y:.71875},{x:.78125,y:.71875},{x:.78125,y:.71875},{x:.84375,y:.71875},{x:.84375,y:.71875},{x:.90625,y:.71875},{x:.90625,y:.71875},{x:.96875,y:.71875},{x:.96875,y:.71875},{x:.03125,y:.78125},{x:.03125,y:.78125},{x:.09375,y:.78125},{x:.09375,y:.78125},{x:.15625,y:.78125},{x:.15625,y:.78125},{x:.21875,y:.78125},{x:.21875,y:.78125},{x:.28125,y:.78125},{x:.28125,y:.78125},{x:.34375,y:.78125},{x:.34375,y:.78125},{x:.40625,y:.78125},{x:.40625,y:.78125},{x:.46875,y:.78125},{x:.46875,y:.78125},{x:.53125,y:.78125},{x:.53125,y:.78125},{x:.59375,y:.78125},{x:.59375,y:.78125},{x:.65625,y:.78125},{x:.65625,y:.78125},{x:.71875,y:.78125},{x:.71875,y:.78125},{x:.78125,y:.78125},{x:.78125,y:.78125},{x:.84375,y:.78125},{x:.84375,y:.78125},{x:.90625,y:.78125},{x:.90625,y:.78125},{x:.96875,y:.78125},{x:.96875,y:.78125},{x:.03125,y:.84375},{x:.03125,y:.84375},{x:.09375,y:.84375},{x:.09375,y:.84375},{x:.15625,y:.84375},{x:.15625,y:.84375},{x:.21875,y:.84375},{x:.21875,y:.84375},{x:.28125,y:.84375},{x:.28125,y:.84375},{x:.34375,y:.84375},{x:.34375,y:.84375},{x:.40625,y:.84375},{x:.40625,y:.84375},{x:.46875,y:.84375},{x:.46875,y:.84375},{x:.53125,y:.84375},{x:.53125,y:.84375},{x:.59375,y:.84375},{x:.59375,y:.84375},{x:.65625,y:.84375},{x:.65625,y:.84375},{x:.71875,y:.84375},{x:.71875,y:.84375},{x:.78125,y:.84375},{x:.78125,y:.84375},{x:.84375,y:.84375},{x:.84375,y:.84375},{x:.90625,y:.84375},{x:.90625,y:.84375},{x:.96875,y:.84375},{x:.96875,y:.84375},{x:.03125,y:.90625},{x:.03125,y:.90625},{x:.09375,y:.90625},{x:.09375,y:.90625},{x:.15625,y:.90625},{x:.15625,y:.90625},{x:.21875,y:.90625},{x:.21875,y:.90625},{x:.28125,y:.90625},{x:.28125,y:.90625},{x:.34375,y:.90625},{x:.34375,y:.90625},{x:.40625,y:.90625},{x:.40625,y:.90625},{x:.46875,y:.90625},{x:.46875,y:.90625},{x:.53125,y:.90625},{x:.53125,y:.90625},{x:.59375,y:.90625},{x:.59375,y:.90625},{x:.65625,y:.90625},{x:.65625,y:.90625},{x:.71875,y:.90625},{x:.71875,y:.90625},{x:.78125,y:.90625},{x:.78125,y:.90625},{x:.84375,y:.90625},{x:.84375,y:.90625},{x:.90625,y:.90625},{x:.90625,y:.90625},{x:.96875,y:.90625},{x:.96875,y:.90625},{x:.03125,y:.96875},{x:.03125,y:.96875},{x:.09375,y:.96875},{x:.09375,y:.96875},{x:.15625,y:.96875},{x:.15625,y:.96875},{x:.21875,y:.96875},{x:.21875,y:.96875},{x:.28125,y:.96875},{x:.28125,y:.96875},{x:.34375,y:.96875},{x:.34375,y:.96875},{x:.40625,y:.96875},{x:.40625,y:.96875},{x:.46875,y:.96875},{x:.46875,y:.96875},{x:.53125,y:.96875},{x:.53125,y:.96875},{x:.59375,y:.96875},{x:.59375,y:.96875},{x:.65625,y:.96875},{x:.65625,y:.96875},{x:.71875,y:.96875},{x:.71875,y:.96875},{x:.78125,y:.96875},{x:.78125,y:.96875},{x:.84375,y:.96875},{x:.84375,y:.96875},{x:.90625,y:.96875},{x:.90625,y:.96875},{x:.96875,y:.96875},{x:.96875,y:.96875},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375}];var K0=class{constructor(t){he(this,"model");he(this,"anchors");he(this,"anchorsTensor");he(this,"inputSize");he(this,"inputSizeTensor");he(this,"doubleInputSizeTensor");var a,n,r,s;this.model=t,this.anchors=uS.map(i=>[i.x,i.y]),this.anchorsTensor=Qn(this.anchors),this.inputSize=((s=(r=(n=(a=this==null?void 0:this.model)==null?void 0:a.inputs)==null?void 0:n[0])==null?void 0:r.shape)==null?void 0:s[2])||0,this.inputSizeTensor=Bt([this.inputSize,this.inputSize]),this.doubleInputSizeTensor=Bt([this.inputSize*2,this.inputSize*2])}normalizeBoxes(t){let a={};a.boxOffsets=Fe(t,[0,0],[-1,2]),a.boxSizes=Fe(t,[0,2],[-1,2]),a.div=ve(a.boxOffsets,this.inputSizeTensor),a.boxCenterPoints=we(a.div,this.anchorsTensor),a.halfBoxSizes=ve(a.boxSizes,this.doubleInputSizeTensor),a.sub=xe(a.boxCenterPoints,a.halfBoxSizes),a.startPoints=te(a.sub,this.inputSizeTensor),a.add=we(a.boxCenterPoints,a.halfBoxSizes),a.endPoints=te(a.add,this.inputSizeTensor);let n=Uu([a.startPoints,a.endPoints],1);return Object.keys(a).forEach(r=>J(a[r])),n}normalizeLandmarks(t,a){let n={};n.reshape=Q(t,[-1,7,2]),n.div=ve(n.reshape,this.inputSizeTensor),n.landmarks=we(n.div,this.anchors[a]?this.anchors[a]:0);let r=te(n.landmarks,this.inputSizeTensor);return Object.keys(n).forEach(s=>J(n[s])),r}async predict(t,a){var o;let n={};n.resize=fe.resizeBilinear(t,[this.inputSize,this.inputSize]),n.div=ve(n.resize,ze.tf127),n.image=xe(n.div,ze.tf1),n.batched=this.model.execute(n.image),n.predictions=Oe(n.batched),n.slice=Fe(n.predictions,[0,0],[-1,1]),n.sigmoid=za(n.slice),n.scores=Oe(n.sigmoid);let r=await n.scores.data();n.boxes=Fe(n.predictions,[0,1],[-1,4]),n.norm=this.normalizeBoxes(n.boxes),n.nms=await fe.nonMaxSuppressionAsync(n.norm,n.scores,3*(((o=a.hand)==null?void 0:o.maxDetected)||1),a.hand.iouThreshold,a.hand.minConfidence);let s=await n.nms.array(),i=[];for(let l of s){let u={};u.box=Fe(n.norm,[l,0],[1,-1]),u.slice=Fe(n.predictions,[l,5],[1,14]),u.norm=this.normalizeLandmarks(u.slice,l),u.palmLandmarks=Q(u.norm,[-1,2]);let p=await u.box.data(),c=p.slice(0,2),d=p.slice(2,4),h=await u.palmLandmarks.array(),m={startPoint:c,endPoint:d,palmLandmarks:h,confidence:r[l]},f=sS(m,[(t.shape[2]||1)/this.inputSize,(t.shape[1]||0)/this.inputSize]);i.push(f),Object.keys(u).forEach(g=>J(u[g]))}return Object.keys(n).forEach(l=>J(n[l])),i}};var T3e=5,dS=1.65,pS=[0,5,9,13,17,1,2],N3e=0,R3e=2,cS=0,Y0=class{constructor(t,a){he(this,"handDetector");he(this,"handPoseModel");he(this,"inputSize");he(this,"storedBoxes");he(this,"skipped");he(this,"detectedHands");var n,r,s;this.handDetector=t,this.handPoseModel=a,this.inputSize=((s=(r=(n=this.handPoseModel)==null?void 0:n.inputs)==null?void 0:r[0].shape)==null?void 0:s[2])||0,this.storedBoxes=[],this.skipped=Number.MAX_SAFE_INTEGER,this.detectedHands=0}calculateLandmarksBoundingBox(t){let a=t.map(i=>i[0]),n=t.map(i=>i[1]),r=[Math.min(...a),Math.min(...n)],s=[Math.max(...a),Math.max(...n)];return{startPoint:r,endPoint:s}}getBoxForPalmLandmarks(t,a){let n=t.map(s=>rx([...s,1],a)),r=this.calculateLandmarksBoundingBox(n);return q0(X0(r),T3e)}getBoxForHandLandmarks(t){let a=this.calculateLandmarksBoundingBox(t),n=q0(X0(a),dS);n.palmLandmarks=[];for(let r=0;r<pS.length;r++)n.palmLandmarks.push(t[pS[r]].slice(0,2));return n}transformRawCoords(t,a,n,r){let s=j0(a),i=[s[0]/this.inputSize,s[1]/this.inputSize,(s[0]+s[1])/this.inputSize/2],o=t.map(h=>[i[0]*(h[0]-this.inputSize/2),i[1]*(h[1]-this.inputSize/2),i[2]*h[2]]),l=nx(n,[0,0]),u=o.map(h=>[...rx(h,l),h[2]]),p=oS(r),c=[...pc(a),1],d=[Ms(c,p[0]),Ms(c,p[1])];return u.map(h=>[Math.trunc(h[0]+d[0]),Math.trunc(h[1]+d[1]),Math.trunc(h[2])])}async estimateHands(t,a){let n=!1,r,s=(a.hand.skipTime||0)>ae()-cS,i=this.skipped<(a.hand.skipFrames||0);a.skipAllowed&&s&&i?this.skipped++:(r=await this.handDetector.predict(t,a),this.skipped=0),r&&r.length>0&&(r.length!==this.detectedHands&&this.detectedHands!==a.hand.maxDetected||!a.hand.landmarks)&&(this.detectedHands=0,this.storedBoxes=[...r],this.storedBoxes.length>0&&(n=!0));let o=[];for(let l=0;l<this.storedBoxes.length;l++){let u=this.storedBoxes[l];if(u)if(a.hand.landmarks){let p=a.hand.rotation?iS(u.palmLandmarks[N3e],u.palmLandmarks[R3e]):0,c=pc(u),d=[c[0]/t.shape[2],c[1]/t.shape[1]],h=a.hand.rotation&&ne.kernels.includes("rotatewithoffset")?fe.rotateWithOffset(t,p,0,d):t.clone(),m=nx(-p,c),f=n?this.getBoxForPalmLandmarks(u.palmLandmarks,m):u,g=rS(f,h,[this.inputSize,this.inputSize]),y=ve(g,ze.tf255);J(g),J(h);let[x,A]=this.handPoseModel.execute(y);cS=ae(),J(y);let b=(await x.data())[0];if(J(x),b>=a.hand.minConfidence/4){let w=Q(A,[-1,3]),I=await w.array();J(A),J(w);let T=this.transformRawCoords(I,f,p,m),N=this.getBoxForHandLandmarks(T);this.storedBoxes[l]={...N,confidence:b};let M={landmarks:T,confidence:b,boxConfidence:u.confidence,fingerConfidence:b,box:{topLeft:N.startPoint,bottomRight:N.endPoint}};o.push(M)}else this.storedBoxes[l]=null;J(A)}else{let p=q0(X0(u),dS),c={confidence:u.confidence,boxConfidence:u.confidence,fingerConfidence:0,box:{topLeft:p.startPoint,bottomRight:p.endPoint},landmarks:[]};o.push(c)}}return this.storedBoxes=this.storedBoxes.filter(l=>l!==null),this.detectedHands=o.length,o.length>a.hand.maxDetected&&(o.length=a.hand.maxDetected),o}};var hS={thumb:[1,2,3,4],index:[5,6,7,8],middle:[9,10,11,12],ring:[13,14,15,16],pinky:[17,18,19,20],palm:[0]},Il,Sl,sx;function M3e(){let e=Il?new K0(Il):void 0;e&&Sl&&(sx=new Y0(e,Sl))}async function ix(e,t){sx||M3e();let a=await sx.estimateHands(e,t);if(!a)return[];let n=[];for(let r=0;r<a.length;r++){let s={};if(a[r].landmarks)for(let p of Object.keys(hS))s[p]=hS[p].map(c=>a[r].landmarks[c]);let i=a[r].landmarks,o=[Number.MAX_SAFE_INTEGER,Number.MAX_SAFE_INTEGER,0,0],l=[0,0,0,0];if(i&&i.length>0){for(let p of i)p[0]<o[0]&&(o[0]=p[0]),p[1]<o[1]&&(o[1]=p[1]),p[0]>o[2]&&(o[2]=p[0]),p[1]>o[3]&&(o[3]=p[1]);o[2]-=o[0],o[3]-=o[1],l=[o[0]/(e.shape[2]||0),o[1]/(e.shape[1]||0),o[2]/(e.shape[2]||0),o[3]/(e.shape[1]||0)]}else o=a[r].box?[Math.trunc(Math.max(0,a[r].box.topLeft[0])),Math.trunc(Math.max(0,a[r].box.topLeft[1])),Math.trunc(Math.min(e.shape[2]||0,a[r].box.bottomRight[0])-Math.max(0,a[r].box.topLeft[0])),Math.trunc(Math.min(e.shape[1]||0,a[r].box.bottomRight[1])-Math.max(0,a[r].box.topLeft[1]))]:[0,0,0,0],l=[a[r].box.topLeft[0]/(e.shape[2]||0),a[r].box.topLeft[1]/(e.shape[1]||0),(a[r].box.bottomRight[0]-a[r].box.topLeft[0])/(e.shape[2]||0),(a[r].box.bottomRight[1]-a[r].box.topLeft[1])/(e.shape[1]||0)];let u=H0(i);n.push({id:r,score:Math.round(100*a[r].confidence)/100,boxScore:Math.round(100*a[r].boxConfidence)/100,fingerScore:Math.round(100*a[r].fingerConfidence)/100,label:"hand",box:o,boxRaw:l,keypoints:i,annotations:s,landmarks:u})}return n}async function mS(e){var t;return ne.initial&&(Il=null),Il?e.debug&&K("cached model:",Il.modelUrl):Il=await $e((t=e.hand.detector)==null?void 0:t.modelPath),Il}async function fS(e){var t;return ne.initial&&(Sl=null),Sl?e.debug&&K("cached model:",Sl.modelUrl):Sl=await $e((t=e.hand.skeleton)==null?void 0:t.modelPath),Sl}var Ot=[null,null],$3e=["StatefulPartitionedCall/Postprocessor/Slice","StatefulPartitionedCall/Postprocessor/ExpandDims_1"],$s=[[0,0],[0,0]],P3e=["hand","fist","pinch","point","face","tip","pinchtip"],yS=4,xS=1.6,_3e=512,F3e=1.4,Z0=Number.MAX_SAFE_INTEGER,ox=0,Dr=[0,0],Dt={boxes:[],hands:[]},AS={thumb:[1,2,3,4],index:[5,6,7,8],middle:[9,10,11,12],ring:[13,14,15,16],pinky:[17,18,19,20],base:[0],palm:[0,17,13,9,5,1,0]};async function bS(e){var t;if(ne.initial&&(Ot[0]=null),Ot[0])e.debug&&K("cached model:",Ot[0].modelUrl);else{b0(["tensorlistreserve","enter","tensorlistfromtensor","merge","loopcond","switch","exit","tensorliststack","nextiteration","tensorlistsetitem","tensorlistgetitem","reciprocal","shape","split","where"],e),Ot[0]=await $e((t=e.hand.detector)==null?void 0:t.modelPath);let a=Ot[0].executor?Object.values(Ot[0].modelSignature.inputs):void 0;$s[0][0]=Array.isArray(a)?parseInt(a[0].tensorShape.dim[1].size):0,$s[0][1]=Array.isArray(a)?parseInt(a[0].tensorShape.dim[2].size):0}return Ot[0]}async function vS(e){var t;if(ne.initial&&(Ot[1]=null),Ot[1])e.debug&&K("cached model:",Ot[1].modelUrl);else{Ot[1]=await $e((t=e.hand.skeleton)==null?void 0:t.modelPath);let a=Ot[1].executor?Object.values(Ot[1].modelSignature.inputs):void 0;$s[1][0]=Array.isArray(a)?parseInt(a[0].tensorShape.dim[1].size):0,$s[1][1]=Array.isArray(a)?parseInt(a[0].tensorShape.dim[2].size):0}return Ot[1]}async function D3e(e,t){let a=[];if(!e||!Ot[0])return a;let n={},r=(e.shape[2]||1)/(e.shape[1]||1),s=Math.min(Math.round((e.shape[1]||0)/8)*8,_3e),i=Math.round(s*r/8)*8;n.resize=fe.resizeBilinear(e,[s,i]),n.cast=Ue(n.resize,"int32"),[n.rawScores,n.rawBoxes]=await Ot[0].executeAsync(n.cast,$3e),n.boxes=Oe(n.rawBoxes,[0,2]),n.scores=Oe(n.rawScores,[0]);let o=Na(n.scores,1);J(o[yS]),o.splice(yS,1),n.filtered=ha(o,1),J(o),n.max=ga(n.filtered,1),n.argmax=ir(n.filtered,1);let l=0;n.nms=await fe.nonMaxSuppressionAsync(n.boxes,n.max,(t.hand.maxDetected||0)+1,t.hand.iouThreshold||0,t.hand.minConfidence||1);let u=await n.nms.data(),p=await n.max.data(),c=await n.argmax.data();for(let d of Array.from(u)){let h=Fe(n.boxes,d,1),m=await h.data();J(h);let f=[m[1],m[0],m[3]-m[1],m[2]-m[0]],g=R0(f,F3e),y=[Math.trunc(f[0]*Dr[0]),Math.trunc(f[1]*Dr[1]),Math.trunc(f[2]*Dr[0]),Math.trunc(f[3]*Dr[1])],x=p[d],A=P3e[c[d]],b={id:l++,score:x,box:y,boxRaw:g,label:A};a.push(b)}return Object.keys(n).forEach(d=>J(n[d])),a.sort((d,h)=>h.score-d.score),a.length>(t.hand.maxDetected||1)&&(a.length=t.hand.maxDetected||1),a}async function lx(e,t,a){let n={id:t.id,score:Math.round(100*t.score)/100,boxScore:Math.round(100*t.score)/100,fingerScore:0,box:t.box,boxRaw:t.boxRaw,label:t.label,keypoints:[],landmarks:{},annotations:{}};if(e&&Ot[1]&&a.hand.landmarks&&t.score>(a.hand.minConfidence||0)){let r={},s=[t.boxRaw[1],t.boxRaw[0],t.boxRaw[3]+t.boxRaw[1],t.boxRaw[2]+t.boxRaw[0]];r.crop=fe.cropAndResize(e,[s],[0],[$s[1][0],$s[1][1]],"bilinear"),r.div=ve(r.crop,ze.tf255),[r.score,r.keypoints]=Ot[1].execute(r.div,["Identity_1","Identity"]);let i=(await r.score.data())[0],o=(100-Math.trunc(100/(1+Math.exp(i))))/100;if(o>=(a.hand.minConfidence||0)){n.fingerScore=o,r.reshaped=Q(r.keypoints,[-1,3]);let p=(await r.reshaped.array()).map(c=>[c[0]/$s[1][1],c[1]/$s[1][0],c[2]||0]).map(c=>[c[0]*t.boxRaw[2],c[1]*t.boxRaw[3],c[2]||0]);n.keypoints=p.map(c=>[Dr[0]*(c[0]+t.boxRaw[0]),Dr[1]*(c[1]+t.boxRaw[1]),c[2]||0]),n.landmarks=H0(n.keypoints);for(let c of Object.keys(AS))n.annotations[c]=AS[c].map(d=>n.landmarks&&n.keypoints[d]?n.keypoints[d]:null)}Object.keys(r).forEach(l=>J(r[l]))}return n}async function ux(e,t){var r,s;if(!((r=Ot[0])!=null&&r.executor)||!((s=Ot[1])!=null&&s.executor)||!Ot[0].inputs[0].shape||!Ot[1].inputs[0].shape)return[];Dr=[e.shape[2]||0,e.shape[1]||0],Z0++;let a=(t.hand.skipTime||0)>ae()-ox,n=Z0<(t.hand.skipFrames||0);return t.skipAllowed&&a&&n?Dt.hands:new Promise(async i=>{let o=3*(t.hand.skipTime||0)>ae()-ox,l=Z0<3*(t.hand.skipFrames||0);t.skipAllowed&&Dt.hands.length===t.hand.maxDetected?Dt.hands=await Promise.all(Dt.boxes.map(p=>lx(e,p,t))):t.skipAllowed&&o&&l&&Dt.hands.length>0?Dt.hands=await Promise.all(Dt.boxes.map(p=>lx(e,p,t))):(Dt.boxes=await D3e(e,t),ox=ae(),Dt.hands=await Promise.all(Dt.boxes.map(p=>lx(e,p,t))),Z0=0);let u=[...Dt.boxes];if(Dt.boxes.length=0,t.cacheSensitivity>0)for(let p=0;p<Dt.hands.length;p++){let c=A9(Dt.hands[p].keypoints,Dr);if(c.box[2]/(e.shape[2]||1)>.05&&c.box[3]/(e.shape[1]||1)>.05&&Dt.hands[p].fingerScore&&Dt.hands[p].fingerScore>(t.hand.minConfidence||0)){let d=R0(c.box,xS),h=R0(c.boxRaw,xS);Dt.boxes.push({...u[p],box:d,boxRaw:h})}}for(let p=0;p<Dt.hands.length;p++){let c=ws(Dt.hands[p].keypoints,Dr);Dt.hands[p].box=c.box,Dt.hands[p].boxRaw=c.boxRaw}i(Dt.hands)})}var hr=(e=null)=>({face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0,width:0,height:0,error:e});var cc={};Ar(cc,{connected:()=>Q0,horizontal:()=>dx,kpt:()=>J0,relative:()=>cx,vertical:()=>px});var J0=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],dx=[["leftEye","rightEye"],["leftEar","rightEar"],["leftShoulder","rightShoulder"],["leftElbow","rightElbow"],["leftWrist","rightWrist"],["leftHip","rightHip"],["leftKnee","rightKnee"],["leftAnkle","rightAnkle"]],px=[["leftKnee","leftShoulder"],["rightKnee","rightShoulder"],["leftAnkle","leftKnee"],["rightAnkle","rightKnee"]],cx=[[["leftHip","rightHip"],["leftShoulder","rightShoulder"]],[["leftElbow","rightElbow"],["leftShoulder","rightShoulder"]]],Q0={leftLeg:["leftHip","leftKnee","leftAnkle"],rightLeg:["rightHip","rightKnee","rightAnkle"],torso:["leftShoulder","rightShoulder","rightHip","leftHip","leftShoulder"],leftArm:["leftShoulder","leftElbow","leftWrist"],rightArm:["rightShoulder","rightElbow","rightWrist"],head:[]};var Ae=hr(),hx=0;function kS(e,t){var i,o,l,u,p,c,d,h,m,f,g,y,x,A,b,w,I,T,N,M,$,E,S,_,O,W;let a=ae();if(!e)return hr();let n=Date.now()-e.timestamp,r=n<1e3?8-Math.log(n+1):1;if(e.canvas&&(Ae.canvas=e.canvas),e.error&&(Ae.error=e.error),!Ae.body||e.body.length!==Ae.body.length)Ae.body=JSON.parse(JSON.stringify(e.body));else for(let P=0;P<e.body.length;P++){let U=e.body[P].box.map((Z,X)=>((r-1)*Ae.body[P].box[X]+Z)/r),G=e.body[P].boxRaw.map((Z,X)=>((r-1)*Ae.body[P].boxRaw[X]+Z)/r),q=e.body[P].keypoints.map((Z,X)=>{var re,ee,ge,ie,be,Ce,Re,Le,qe;return{score:Z.score,part:Z.part,position:[Ae.body[P].keypoints[X]?((r-1)*(Ae.body[P].keypoints[X].position[0]||0)+(Z.position[0]||0))/r:Z.position[0],Ae.body[P].keypoints[X]?((r-1)*(Ae.body[P].keypoints[X].position[1]||0)+(Z.position[1]||0))/r:Z.position[1],Ae.body[P].keypoints[X]?((r-1)*(Ae.body[P].keypoints[X].position[2]||0)+(Z.position[2]||0))/r:Z.position[2]],positionRaw:[Ae.body[P].keypoints[X]?((r-1)*(Ae.body[P].keypoints[X].positionRaw[0]||0)+(Z.positionRaw[0]||0))/r:Z.positionRaw[0],Ae.body[P].keypoints[X]?((r-1)*(Ae.body[P].keypoints[X].positionRaw[1]||0)+(Z.positionRaw[1]||0))/r:Z.positionRaw[1],Ae.body[P].keypoints[X]?((r-1)*(Ae.body[P].keypoints[X].positionRaw[2]||0)+(Z.positionRaw[2]||0))/r:Z.positionRaw[2]],distance:[Ae.body[P].keypoints[X]?((r-1)*(((re=Ae.body[P].keypoints[X].distance)==null?void 0:re[0])||0)+(((ee=Z.distance)==null?void 0:ee[0])||0))/r:(ge=Z.distance)==null?void 0:ge[0],Ae.body[P].keypoints[X]?((r-1)*(((ie=Ae.body[P].keypoints[X].distance)==null?void 0:ie[1])||0)+(((be=Z.distance)==null?void 0:be[1])||0))/r:(Ce=Z.distance)==null?void 0:Ce[1],Ae.body[P].keypoints[X]?((r-1)*(((Re=Ae.body[P].keypoints[X].distance)==null?void 0:Re[2])||0)+(((Le=Z.distance)==null?void 0:Le[2])||0))/r:(qe=Z.distance)==null?void 0:qe[2]]}}),H={},V={connected:{}};(i=t.body.modelPath)!=null&&i.includes("efficientpose")?V=$0:(o=t.body.modelPath)!=null&&o.includes("blazepose")?V=T0:(l=t.body.modelPath)!=null&&l.includes("movenet")&&(V=cc);for(let[Z,X]of Object.entries(V.connected)){let re=[];for(let ee=0;ee<X.length-1;ee++){let ge=q.find(be=>be.part===X[ee]),ie=q.find(be=>be.part===X[ee+1]);ge&&ie&&re.push([ge.position,ie.position])}H[Z]=re}Ae.body[P]={...e.body[P],box:U,boxRaw:G,keypoints:q,annotations:H}}if(!Ae.hand||e.hand.length!==Ae.hand.length)Ae.hand=JSON.parse(JSON.stringify(e.hand));else for(let P=0;P<e.hand.length;P++){let U=e.hand[P].box.map((V,Z)=>((r-1)*Ae.hand[P].box[Z]+V)/r),G=e.hand[P].boxRaw.map((V,Z)=>((r-1)*Ae.hand[P].boxRaw[Z]+V)/r);Ae.hand[P].keypoints.length!==e.hand[P].keypoints.length&&(Ae.hand[P].keypoints=e.hand[P].keypoints);let q=e.hand[P].keypoints&&e.hand[P].keypoints.length>0?e.hand[P].keypoints.map((V,Z)=>V.map((X,re)=>((r-1)*(Ae.hand[P].keypoints[Z][re]||1)+(X||0))/r)):[],H={};if(Object.keys(Ae.hand[P].annotations).length!==Object.keys(e.hand[P].annotations).length)Ae.hand[P].annotations=e.hand[P].annotations,H=Ae.hand[P].annotations;else if(e.hand[P].annotations)for(let V of Object.keys(e.hand[P].annotations))H[V]=(c=(p=(u=e.hand[P])==null?void 0:u.annotations)==null?void 0:p[V])!=null&&c[0]?e.hand[P].annotations[V].map((Z,X)=>Z.map((re,ee)=>((r-1)*Ae.hand[P].annotations[V][X][ee]+re)/r)):null;Ae.hand[P]={...e.hand[P],box:U,boxRaw:G,keypoints:q,annotations:H}}if(!Ae.face||e.face.length!==Ae.face.length)Ae.face=JSON.parse(JSON.stringify(e.face));else for(let P=0;P<e.face.length;P++){let U=e.face[P].box.map((H,V)=>((r-1)*Ae.face[P].box[V]+H)/r),G=e.face[P].boxRaw.map((H,V)=>((r-1)*Ae.face[P].boxRaw[V]+H)/r),q=e.face[P].annotations;if(Object.keys(Ae.face[P].annotations).length!==Object.keys(e.face[P].annotations).length)Ae.face[P].annotations=e.face[P].annotations,q=Ae.face[P].annotations;else if(e.face[P].annotations)for(let H of Object.keys(e.face[P].annotations))q[H]=(m=(h=(d=e.face[P])==null?void 0:d.annotations)==null?void 0:h[H])!=null&&m[0]?e.face[P].annotations[H].map((V,Z)=>V.map((X,re)=>((r-1)*Ae.face[P].annotations[H][Z][re]+X)/r)):null;if(e.face[P].rotation){let H={matrix:[0,0,0,0,0,0,0,0,0],angle:{roll:0,yaw:0,pitch:0},gaze:{bearing:0,strength:0}};H.matrix=(f=e.face[P].rotation)==null?void 0:f.matrix,H.angle={roll:((r-1)*(((y=(g=Ae.face[P].rotation)==null?void 0:g.angle)==null?void 0:y.roll)||0)+(((A=(x=e.face[P].rotation)==null?void 0:x.angle)==null?void 0:A.roll)||0))/r,yaw:((r-1)*(((w=(b=Ae.face[P].rotation)==null?void 0:b.angle)==null?void 0:w.yaw)||0)+(((T=(I=e.face[P].rotation)==null?void 0:I.angle)==null?void 0:T.yaw)||0))/r,pitch:((r-1)*(((M=(N=Ae.face[P].rotation)==null?void 0:N.angle)==null?void 0:M.pitch)||0)+(((E=($=e.face[P].rotation)==null?void 0:$.angle)==null?void 0:E.pitch)||0))/r},H.gaze={bearing:((r-1)*(((S=Ae.face[P].rotation)==null?void 0:S.gaze.bearing)||0)+(((_=e.face[P].rotation)==null?void 0:_.gaze.bearing)||0))/r,strength:((r-1)*(((O=Ae.face[P].rotation)==null?void 0:O.gaze.strength)||0)+(((W=e.face[P].rotation)==null?void 0:W.gaze.strength)||0))/r},Ae.face[P]={...e.face[P],rotation:H,box:U,boxRaw:G,annotations:q}}else Ae.face[P]={...e.face[P],box:U,boxRaw:G,annotations:q}}if(!Ae.object||e.object.length!==Ae.object.length)Ae.object=JSON.parse(JSON.stringify(e.object));else for(let P=0;P<e.object.length;P++){let U=e.object[P].box.map((q,H)=>((r-1)*Ae.object[P].box[H]+q)/r),G=e.object[P].boxRaw.map((q,H)=>((r-1)*Ae.object[P].boxRaw[H]+q)/r);Ae.object[P]={...e.object[P],box:U,boxRaw:G}}if(e.persons){let P=e.persons;if(!Ae.persons||P.length!==Ae.persons.length)Ae.persons=JSON.parse(JSON.stringify(P));else for(let U=0;U<P.length;U++)Ae.persons[U].box=P[U].box.map((G,q)=>((r-1)*Ae.persons[U].box[q]+G)/r)}e.gesture&&(Ae.gesture=e.gesture),Ae.width=e.width,Ae.height=e.height;let s=ae();return hx=ne.perfadd?hx+Math.round(s-a):Math.round(s-a),e.performance&&(Ae.performance={...e.performance,interpolate:hx}),Ae}var Aa;async function mx(e){return!Aa||ne.initial?Aa=await $e(e.segmentation.modelPath):e.debug&&K("cached model:",Aa.modelUrl),Aa}async function IS(e,t){var r;if(Aa||(Aa=await mx(t)),!(Aa!=null&&Aa.executor)||!((r=Aa==null?void 0:Aa.inputs)!=null&&r[0].shape))return null;let a={};a.resize=fe.resizeBilinear(e,[Aa.inputs[0].shape?Aa.inputs[0].shape[1]:0,Aa.inputs[0].shape?Aa.inputs[0].shape[2]:0],!1),a.norm=ve(a.resize,ze.tf255),a.res=Aa.execute(a.norm),a.squeeze=Oe(a.res,[0]),[a.bgRaw,a.fgRaw]=Na(a.squeeze,2),a.fg=Uh(a.fgRaw),a.mul=te(a.fg,ze.tf255),a.expand=Wt(a.mul,2),a.output=fe.resizeBilinear(a.expand,[e.shape[1]||0,e.shape[2]||0]);let n;switch(t.segmentation.mode||"default"){case"default":a.input=Oe(e),a.concat=lt([a.input,a.output],-1),n=Ue(a.concat,"int32");break;case"alpha":n=Ue(a.output,"int32");break;default:n=Ve(0)}return Object.keys(a).forEach(s=>J(a[s])),n}var em={};Ar(em,{distance:()=>fx,find:()=>L3e,similarity:()=>z3e});function fx(e,t,a={order:2,multiplier:25}){if(!e||!e)return Number.MAX_SAFE_INTEGER;let n=0;for(let s=0;s<e.length;s++){let i=!a.order||a.order===2?e[s]-t[s]:Math.abs(e[s]-t[s]);n+=!a.order||a.order===2?i*i:i**a.order}return Math.round(100*(a.multiplier||20)*n)/100}var CS=(e,t,a,n)=>{if(e===0)return 1;let s=(1-(t===2?Math.sqrt(e):e**(1/t))/100-a)/(n-a);return Math.round(100*Math.max(Math.min(s,1),0))/100};function z3e(e,t,a={order:2,multiplier:25,min:.2,max:.8}){let n=fx(e,t,a);return CS(n,a.order||2,a.min||0,a.max||1)}function L3e(e,t,a={order:2,multiplier:25,threshold:0,min:.2,max:.8}){if(!Array.isArray(e)||!Array.isArray(t)||e.length<64||t.length===0)return{index:-1,distance:Number.POSITIVE_INFINITY,similarity:0};let n=Number.MAX_SAFE_INTEGER,r=-1;for(let i=0;i<t.length;i++){let o=t[i].length===e.length?fx(e,t[i],a):Number.MAX_SAFE_INTEGER;if(o<n&&(n=o,r=i),n<(a.threshold||0))break}let s=CS(n,a.order||2,a.min||0,a.max||1);return{index:r,distance:n,similarity:s}}var Ex={};Ar(Ex,{Models:()=>fc,validateModel:()=>om});var TS=.005,on={keypoints:[],padding:[[0,0],[0,0],[0,0],[0,0]]};function gx(e){for(let t of dx){let a=e.keypoints.findIndex(r=>r.part===t[0]),n=e.keypoints.findIndex(r=>r.part===t[1]);if(e.keypoints[a]&&e.keypoints[n]&&e.keypoints[a].position[0]<e.keypoints[n].position[0]){let r=e.keypoints[a];e.keypoints[a]=e.keypoints[n],e.keypoints[n]=r}}for(let t of px){let a=e.keypoints.findIndex(r=>r&&r.part===t[0]),n=e.keypoints.findIndex(r=>r&&r.part===t[1]);e.keypoints[a]&&e.keypoints[n]&&e.keypoints[a].position[1]<e.keypoints[n].position[1]&&e.keypoints.splice(a,1)}for(let[t,a]of cx){let n=e.keypoints.findIndex(u=>u&&u.part===t[0]),r=e.keypoints.findIndex(u=>u&&u.part===t[1]),s=e.keypoints.findIndex(u=>u&&u.part===a[0]),i=e.keypoints.findIndex(u=>u&&u.part===a[1]);if(!e.keypoints[s]||!e.keypoints[i])continue;let o=e.keypoints[n]?[Math.abs(e.keypoints[s].position[0]-e.keypoints[n].position[0]),Math.abs(e.keypoints[i].position[0]-e.keypoints[n].position[0])]:[0,0],l=e.keypoints[r]?[Math.abs(e.keypoints[i].position[0]-e.keypoints[r].position[0]),Math.abs(e.keypoints[s].position[0]-e.keypoints[r].position[0])]:[0,0];if(o[0]>o[1]||l[0]>l[1]){let u=e.keypoints[n];e.keypoints[n]=e.keypoints[r],e.keypoints[r]=u}}}function NS(e){for(let t=0;t<e.length;t++)if(e[t]&&on.keypoints[t]){let a=[Math.abs(e[t].positionRaw[0]-on.keypoints[t].positionRaw[0]),Math.abs(e[t].positionRaw[1]-on.keypoints[t].positionRaw[1])];a[0]<TS&&a[1]<TS?e[t]=on.keypoints[t]:on.keypoints[t]=e[t]}else on.keypoints[t]=e[t];return e}function RS(e,t){var r,s;let a={};if(!((r=e==null?void 0:e.shape)!=null&&r[1])||!((s=e==null?void 0:e.shape)!=null&&s[2]))return e;on.padding=[[0,0],[e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0,e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0],[e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0,e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0],[0,0]],a.pad=Rn(e,on.padding),a.resize=fe.resizeBilinear(a.pad,[t,t]);let n=Ue(a.resize,"int32");return Object.keys(a).forEach(i=>J(a[i])),n}function ES(e,t){e.keypoints=e.keypoints.filter(n=>n==null?void 0:n.position);for(let n of e.keypoints)n.position=[n.position[0]*(t[0]+on.padding[2][0]+on.padding[2][1])/t[0]-on.padding[2][0],n.position[1]*(t[1]+on.padding[1][0]+on.padding[1][1])/t[1]-on.padding[1][0]],n.positionRaw=[n.position[0]/t[0],n.position[1]/t[1]];let a=ws(e.keypoints.map(n=>n.position),t);return e.box=a.box,e.boxRaw=a.boxRaw,e}var jt,tm=0,yx=Number.MAX_SAFE_INTEGER,Cl={boxes:[],bodies:[],last:0};async function MS(e){var t;return ne.initial&&(jt=null),jt?e.debug&&K("cached model:",jt.modelUrl):(b0(["size"],e),jt=await $e(e.body.modelPath)),tm=jt!=null&&jt.executor&&((t=jt==null?void 0:jt.inputs)!=null&&t[0].shape)?jt.inputs[0].shape[2]:0,tm<64&&(tm=256),B().flagRegistry.WEBGL_USE_SHAPES_UNIFORMS&&B().set("WEBGL_USE_SHAPES_UNIFORMS",!1),jt}function B3e(e,t,a){let n=e[0][0],r=[],s=0;for(let p=0;p<n.length;p++)if(s=n[p][2],s>t.body.minConfidence){let c=[n[p][1],n[p][0]];r.push({score:Math.round(100*s)/100,part:J0[p],positionRaw:c,position:[Math.round((a.shape[2]||0)*c[0]),Math.round((a.shape[1]||0)*c[1])]})}s=r.reduce((p,c)=>c.score>p?c.score:p,0);let i=[],o=ws(r.map(p=>p.position),[a.shape[2],a.shape[1]]),l={};for(let[p,c]of Object.entries(Q0)){let d=[];for(let h=0;h<c.length-1;h++){let m=r.find(g=>g.part===c[h]),f=r.find(g=>g.part===c[h+1]);m&&f&&m.score>(t.body.minConfidence||0)&&f.score>(t.body.minConfidence||0)&&d.push([m.position,f.position])}l[p]=d}let u={id:0,score:s,box:o.box,boxRaw:o.boxRaw,keypoints:r,annotations:l};return gx(u),i.push(u),i}function V3e(e,t,a){let n=[];for(let r=0;r<e[0].length;r++){let s=e[0][r],i=Math.round(100*s[55])/100;if(i>t.body.minConfidence){let o=[];for(let d=0;d<17;d++){let h=s[3*d+2];if(h>t.body.minConfidence){let m=[s[3*d+1],s[3*d+0]];o.push({part:J0[d],score:Math.round(100*h)/100,positionRaw:m,position:[Math.round((a.shape[2]||0)*m[0]),Math.round((a.shape[1]||0)*m[1])]})}}let l=[s[52],s[51],s[54]-s[52],s[53]-s[51]],u=[Math.trunc(l[0]*(a.shape[2]||0)),Math.trunc(l[1]*(a.shape[1]||0)),Math.trunc(l[2]*(a.shape[2]||0)),Math.trunc(l[3]*(a.shape[1]||0))],p={};for(let[d,h]of Object.entries(Q0)){let m=[];for(let f=0;f<h.length-1;f++){let g=o.find(x=>x.part===h[f]),y=o.find(x=>x.part===h[f+1]);g&&y&&g.score>(t.body.minConfidence||0)&&y.score>(t.body.minConfidence||0)&&m.push([g.position,y.position])}p[d]=m}let c={id:r,score:i,box:u,boxRaw:l,keypoints:[...o],annotations:p};gx(c),n.push(c)}}return n.sort((r,s)=>s.score-r.score),n.length>t.body.maxDetected&&(n.length=t.body.maxDetected),n}async function xx(e,t){var r;if(!(jt!=null&&jt.executor)||!((r=jt==null?void 0:jt.inputs)!=null&&r[0].shape))return[];t.skipAllowed||(Cl.boxes.length=0),yx++;let a=(t.body.skipTime||0)>ae()-Cl.last,n=yx<(t.body.skipFrames||0);return t.skipAllowed&&a&&n?Cl.bodies:new Promise(async s=>{let i={};yx=0,i.input=RS(e,tm),i.res=jt==null?void 0:jt.execute(i.input),Cl.last=ae();let o=await i.res.array();Cl.bodies=i.res.shape[2]===17?B3e(o,t,e):V3e(o,t,e);for(let l of Cl.bodies)ES(l,[e.shape[2]||1,e.shape[1]||1]),NS(l.keypoints);Object.keys(i).forEach(l=>J(i[l])),s(Cl.bodies)})}var Fn,am=[],PS=0,Ax=Number.MAX_SAFE_INTEGER,rm=0,nm=2.5;async function _S(e){if(!Fn||ne.initial){Fn=await $e(e.object.modelPath);let t=Fn!=null&&Fn.executor?Object.values(Fn.modelSignature.inputs):void 0;rm=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):416}else e.debug&&K("cached model:",Fn.modelUrl);return Fn}async function U3e(e,t,a){var u,p;let n=0,r=[],s=rm;for(let c of[1,2,4]){let d=c*13,h=Oe(e.find(A=>A.shape[1]===d**2&&(A.shape[2]||0)===rd.length)),m=await h.array(),f=Oe(e.find(A=>A.shape[1]===d**2&&(A.shape[2]||0)<rd.length)),g=Q(f,[-1,4,(((u=f.shape)==null?void 0:u[1])||0)/4]),y=ir(g,2),x=await y.array();for(let A=0;A<h.shape[0];A++)for(let b=0;b<(((p=h.shape)==null?void 0:p[1])||0);b++){let w=m[A][b];if(w>(a.object.minConfidence||0)&&b!==61){let I=(.5+Math.trunc(A%d))/d,T=(.5+Math.trunc(A/d))/d,N=x[A].map(P=>P*(d/c/s)),[M,$]=[I-nm/c*N[0],T-nm/c*N[1]],[E,S]=[I+nm/c*N[2]-M,T+nm/c*N[3]-$],_=[M,$,E,S];_=_.map(P=>Math.max(0,Math.min(P,1)));let O=[_[0]*t[0],_[1]*t[1],_[2]*t[0],_[3]*t[1]],W={id:n++,score:Math.round(100*w)/100,class:b+1,label:rd[b].label,box:O.map(P=>Math.trunc(P)),boxRaw:_};r.push(W)}}J([h,f,g,y])}let i=r.map(c=>[c.boxRaw[1],c.boxRaw[0],c.boxRaw[3],c.boxRaw[2]]),o=r.map(c=>c.score),l=[];if(i&&i.length>0){let c=await fe.nonMaxSuppressionAsync(i,o,a.object.maxDetected||0,a.object.iouThreshold,a.object.minConfidence);l=Array.from(await c.data()),J(c)}return r=r.filter((c,d)=>l.includes(d)).sort((c,d)=>d.score-c.score),r}async function bx(e,t){if(!(Fn!=null&&Fn.executor))return[];let a=(t.object.skipTime||0)>ae()-PS,n=Ax<(t.object.skipFrames||0);return t.skipAllowed&&a&&n&&am.length>0?(Ax++,am):(Ax=0,!ne.kernels.includes("mod")||!ne.kernels.includes("sparsetodense")?am:new Promise(async r=>{let s=[e.shape[2]||0,e.shape[1]||0],i=fe.resizeBilinear(e,[rm,rm],!1),o=ve(i,ze.tf255),l=Qs(o,[0,3,1,2]),u;t.object.enabled&&(u=Fn.execute(l)),PS=ae();let p=await U3e(u,s,t);am=p,J([i,o,l,...u]),r(p)}))}var mc=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],G3e=mc.length,hc=mc.reduce((e,t,a)=>(e[t]=a,e),{}),H3e=[["leftHip","leftShoulder"],["leftElbow","leftShoulder"],["leftElbow","leftWrist"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["rightHip","rightShoulder"],["rightElbow","rightShoulder"],["rightElbow","rightWrist"],["rightHip","rightKnee"],["rightKnee","rightAnkle"],["leftShoulder","rightShoulder"],["leftHip","rightHip"]],V6e=H3e.map(([e,t])=>[hc[e],hc[t]]),DS=[["nose","leftEye"],["leftEye","leftEar"],["nose","rightEye"],["rightEye","rightEar"],["nose","leftShoulder"],["leftShoulder","leftElbow"],["leftElbow","leftWrist"],["leftShoulder","leftHip"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["nose","rightShoulder"],["rightShoulder","rightElbow"],["rightElbow","rightWrist"],["rightShoulder","rightHip"],["rightHip","rightKnee"],["rightKnee","rightAnkle"]];function OS(e){let t=e.reduce(({maxX:a,maxY:n,minX:r,minY:s},{position:{x:i,y:o}})=>({maxX:Math.max(a,i),maxY:Math.max(n,o),minX:Math.min(r,i),minY:Math.min(s,o)}),{maxX:Number.NEGATIVE_INFINITY,maxY:Number.NEGATIVE_INFINITY,minX:Number.POSITIVE_INFINITY,minY:Number.POSITIVE_INFINITY});return[t.minX,t.minY,t.maxX-t.minX,t.maxY-t.minY]}function zS(e,[t,a],[n,r]){let s=t/n,i=a/r,o=(u,p)=>({id:p,score:u.score,boxRaw:[u.box[0]/r,u.box[1]/n,u.box[2]/r,u.box[3]/n],box:[Math.trunc(u.box[0]*i),Math.trunc(u.box[1]*s),Math.trunc(u.box[2]*i),Math.trunc(u.box[3]*s)],keypoints:u.keypoints.map(({score:c,part:d,position:h})=>({score:c,part:d,position:[Math.trunc(h.x*i),Math.trunc(h.y*s)],positionRaw:[h.x/n,h.y/n]})),annotations:{}});return e.map((u,p)=>o(u,p))}var sm=class{constructor(t,a){he(this,"priorityQueue");he(this,"numberOfElements");he(this,"getElementValue");this.priorityQueue=new Array(t),this.numberOfElements=-1,this.getElementValue=a}enqueue(t){this.priorityQueue[++this.numberOfElements]=t,this.swim(this.numberOfElements)}dequeue(){let t=this.priorityQueue[0];return this.exchange(0,this.numberOfElements--),this.sink(0),this.priorityQueue[this.numberOfElements+1]=null,t}empty(){return this.numberOfElements===-1}size(){return this.numberOfElements+1}all(){return this.priorityQueue.slice(0,this.numberOfElements+1)}max(){return this.priorityQueue[0]}swim(t){for(;t>0&&this.less(Math.floor(t/2),t);)this.exchange(t,Math.floor(t/2)),t=Math.floor(t/2)}sink(t){for(;2*t<=this.numberOfElements;){let a=2*t;if(a<this.numberOfElements&&this.less(a,a+1)&&a++,!this.less(t,a))break;this.exchange(t,a),t=a}}getValueAt(t){return this.getElementValue(this.priorityQueue[t])}less(t,a){return this.getValueAt(t)<this.getValueAt(a)}exchange(t,a){let n=this.priorityQueue[t];this.priorityQueue[t]=this.priorityQueue[a],this.priorityQueue[a]=n}};function vx(e,t,a,n){return{y:n.get(e,t,a),x:n.get(e,t,a+G3e)}}function wx(e,t,a){let{heatmapY:n,heatmapX:r,id:s}=e,{y:i,x:o}=vx(n,r,s,a);return{x:e.heatmapX*t+o,y:e.heatmapY*t+i}}function kx(e,t,a){return e<t?t:e>a?a:e}function LS(e,t,a,n){let r=a-e,s=n-t;return r*r+s*s}function Ix(e,t){return{x:e.x+t.x,y:e.y+t.y}}var ln,q3e=["MobilenetV1/offset_2/BiasAdd","MobilenetV1/heatmap_2/BiasAdd","MobilenetV1/displacement_fwd_2/BiasAdd","MobilenetV1/displacement_bwd_2/BiasAdd"],im=1,hd=16,X3e=50**2;function WS(e,t,a,n,r,s,i=2){let o=y=>({y:s.get(y.y,y.x,e),x:s.get(y.y,y.x,s.shape[2]/2+e)}),l=(y,x,A)=>({y:kx(Math.round(y.y/hd),0,x-1),x:kx(Math.round(y.x/hd),0,A-1)}),[u,p]=n.shape,c=l(t.position,u,p),d=o(c),m=Ix(t.position,d);for(let y=0;y<i;y++){let x=l(m,u,p),A=vx(x.y,x.x,a,r);m=Ix({x:x.x*hd,y:x.y*hd},{x:A.x,y:A.y})}let f=l(m,u,p),g=n.get(f.y,f.x,a);return{position:m,part:mc[a],score:g}}function K3e(e,t,a,n,r){let s=DS.map(([d,h])=>[hc[d],hc[h]]),i=s.map(([,d])=>d),o=s.map(([d])=>d),l=t.shape[2],u=i.length,p=new Array(l),c=wx(e.part,hd,a);p[e.part.id]={score:e.score,part:mc[e.part.id],position:c};for(let d=u-1;d>=0;--d){let h=i[d],m=o[d];p[h]&&!p[m]&&(p[m]=WS(d,p[h],m,t,a,r))}for(let d=0;d<u;++d){let h=o[d],m=i[d];p[h]&&!p[m]&&(p[m]=WS(d,p[h],m,t,a,n))}return p}function Y3e(e,t,a,n,r){let[s,i]=r.shape,o=!0,l=Math.max(a-im,0),u=Math.min(a+im+1,s);for(let p=l;p<u;++p){let c=Math.max(n-im,0),d=Math.min(n+im+1,i);for(let h=c;h<d;++h)if(r.get(p,h,e)>t){o=!1;break}if(!o)break}return o}function Z3e(e,t){let[a,n,r]=t.shape,s=new sm(a*n*r,({score:i})=>i);for(let i=0;i<a;++i)for(let o=0;o<n;++o)for(let l=0;l<r;++l){let u=t.get(i,o,l);u<e||Y3e(l,u,i,o,t)&&s.enqueue({score:u,part:{heatmapY:i,heatmapX:o,id:l}})}return s}function BS(e,{x:t,y:a},n){return e.some(({keypoints:r})=>{var i;let s=(i=r[n])==null?void 0:i.position;return s?LS(a,t,s.y,s.x)<=X3e:!1})}function J3e(e,t){return t.reduce((n,{position:r,score:s},i)=>(BS(e,r,i)||(n+=s),n),0)/t.length}function Q3e(e,t,a,n,r,s){let i=[],o=Z3e(s,t);for(;i.length<r&&!o.empty();){let l=o.dequeue(),u=wx(l.part,hd,e);if(BS(i,u,l.part.id))continue;let p=K3e(l,t,e,a,n);p=p.filter(h=>h.score>s);let c=J3e(i,p),d=OS(p);c>s&&i.push({keypoints:p,box:d,score:Math.round(100*c)/100})}return i}async function Sx(e,t){if(!(ln!=null&&ln.executor))return[];let a=De(()=>{if(!ln.inputs[0].shape)return[];let i=fe.resizeBilinear(e,[ln.inputs[0].shape[2],ln.inputs[0].shape[1]]),o=xe(ve(Ue(i,"float32"),127.5),1),u=ln.execute(o,q3e).map(p=>Oe(p,[0]));return u[1]=za(u[1]),u}),n=await Promise.all(a.map(i=>i.buffer()));for(let i of a)J(i);let r=Q3e(n[0],n[1],n[2],n[3],t.body.maxDetected,t.body.minConfidence);return ln.inputs[0].shape?zS(r,[e.shape[1],e.shape[2]],[ln.inputs[0].shape[2],ln.inputs[0].shape[1]]):[]}async function VS(e){return!ln||ne.initial?ln=await $e(e.body.modelPath):e.debug&&K("cached model:",ln.modelUrl),ln}var mr,eye=["fgr","pha","r1o","r2o","r3o","r4o"],qt={},Tx=0;function HS(e){J([qt.r1i,qt.r2i,qt.r3i,qt.r4i,qt.downsample_ratio]),qt.r1i=Ve(0),qt.r2i=Ve(0),qt.r3i=Ve(0),qt.r4i=Ve(0),Tx=e.segmentation.ratio||.5,qt.downsample_ratio=Ve(Tx)}async function Nx(e){return!mr||ne.initial?mr=await $e(e.segmentation.modelPath):e.debug&&K("cached model:",mr.modelUrl),HS(e),mr}var GS=e=>De(()=>{let t=Oe(e,[0]),a=te(t,ze.tf255);return Ue(a,"int32")});function Cx(e,t){let a=e?GS(e):or([t.shape[1]||0,t.shape[2]||0,3],255,"int32"),n=t?GS(t):or([e.shape[1]||0,e.shape[2]||0,1],255,"int32"),r=lt([a,n],-1);return J([a,n]),r}function tye(e){return De(()=>{let t={};return t.unstack=Na(e,-1),t.concat=lt(t.unstack,1),t.split=Sa(t.concat,4,1),t.stack=lt(t.split,2),t.squeeze=Oe(t.stack,[0]),t.expand=Wt(t.squeeze,-1),t.add=we(t.expand,1),t.mul=te(t.add,127.5),t.cast=Ue(t.mul,"int32"),t.tile=Kr(t.cast,[1,1,3]),t.alpha=or([t.tile.shape[0]||0,t.tile.shape[1]||0,1],255,"int32"),lt([t.tile,t.alpha],-1)})}async function jS(e,t){if(mr||(mr=await Nx(t)),!(mr!=null&&mr.executor))return null;qt.src=ve(e,255),Tx!==t.segmentation.ratio&&HS(t);let[a,n,r,s,i,o]=await mr.executeAsync(qt,eye),l;switch(t.segmentation.mode||"default"){case"default":l=Cx(a,n);break;case"alpha":l=Cx(null,n);break;case"foreground":l=Cx(a,null);break;case"state":l=tye(r);break;default:l=Ve(0)}return J([qt.src,a,n,qt.r1i,qt.r2i,qt.r3i,qt.r4i]),[qt.r1i,qt.r2i,qt.r3i,qt.r4i]=[r,s,i,o],l}var ba;async function Rx(e){return!ba||ne.initial?ba=await $e(e.segmentation.modelPath):e.debug&&K("cached model:",ba.modelUrl),ba}async function XS(e,t){var r;if(ba||(ba=await Rx(t)),!(ba!=null&&ba.executor)||!((r=ba==null?void 0:ba.inputs)!=null&&r[0].shape))return null;let a={};a.resize=fe.resizeBilinear(e,[ba.inputs[0].shape?ba.inputs[0].shape[1]:0,ba.inputs[0].shape?ba.inputs[0].shape[2]:0],!1),a.norm=ve(a.resize,ze.tf255),a.res=ba.execute(a.norm),a.squeeze=Oe(a.res,[0]),a.alpha=fe.resizeBilinear(a.squeeze,[e.shape[1]||0,e.shape[2]||0]),a.mul=te(a.alpha,ze.tf255);let n;switch(t.segmentation.mode||"default"){case"default":a.input=Oe(e),a.concat=lt([a.input,a.mul],-1),n=Ue(a.concat,"int32");break;case"alpha":n=Ue(a.mul,"int32");break;default:n=Ve(0)}return Object.keys(a).forEach(s=>J(a[s])),n}function om(e,t,a){var u,p;if(!t||!((u=e==null?void 0:e.config)!=null&&u.validateModels))return null;let n=["const","placeholder","noop","pad","squeeze","add","sub","mul","div"],r=["biasadd","fusedbatchnormv3","matmul","switch","shape","merge","split","broadcastto"],s=[],i=[],o=t.modelUrl,l=t.executor;if((p=l==null?void 0:l.graph)!=null&&p.nodes)for(let c of Object.values(l.graph.nodes)){let d=c.op.toLowerCase();s.includes(d)||s.push(d)}else!l&&e.config.debug&&K("model not loaded",a);for(let c of s)!n.includes(c)&&!r.includes(c)&&!e.env.kernels.includes(c)&&!e.env.kernels.includes(c.replace("_",""))&&!e.env.kernels.includes(c.replace("native",""))&&!e.env.kernels.includes(c.replace("v2",""))&&i.push(c);return e.config.debug&&i.length>0&&K("model validation failed:",a,i),i.length>0?{name:a,missing:i,ops:s,url:o}:null}var fc=class{constructor(t){he(this,"instance");he(this,"models",{});this.models={},this.instance=t}stats(){let t=0,a=0,n=0;for(let s of Object.values(Yt))t+=Number.isNaN(+s.sizeFromManifest)?0:s.sizeFromManifest,a+=Number.isNaN(+s.sizeLoadedWeights)?0:s.sizeLoadedWeights,n+=Number.isNaN(+s.sizeDesired)?0:s.sizeDesired;let r=n>0?a/n:0;return{numLoadedModels:Object.values(Yt).filter(s=>s==null?void 0:s.loaded).length,numDefinedModels:Object.keys(this.models).length,percentageLoaded:r,totalSizeFromManifest:t,totalSizeWeights:a,totalSizeLoading:n,modelStats:Object.values(Yt)}}reset(){for(let t of Object.keys(this.models))this.models[t]=null}async load(t){var n,r,s,i,o,l,u,p,c,d,h,m,f,g,y,x,A,b,w,I,T,N,M,$,E,S,_;ne.initial&&this.reset(),t&&(this.instance=t);let a={};a.blazeface=this.instance.config.face.enabled&&!this.models.blazeface?U9(this.instance.config):null,a.antispoof=this.instance.config.face.enabled&&((n=this.instance.config.face.antispoof)!=null&&n.enabled)&&!this.models.antispoof?mI(this.instance.config):null,a.liveness=this.instance.config.face.enabled&&((r=this.instance.config.face.liveness)!=null&&r.enabled)&&!this.models.liveness?xI(this.instance.config):null,a.faceres=this.instance.config.face.enabled&&((s=this.instance.config.face.description)!=null&&s.enabled)&&!this.models.faceres?uI(this.instance.config):null,a.emotion=this.instance.config.face.enabled&&((i=this.instance.config.face.emotion)!=null&&i.enabled)&&!this.models.emotion?sI(this.instance.config):null,a.iris=this.instance.config.face.enabled&&((o=this.instance.config.face.iris)!=null&&o.enabled)&&!((l=this.instance.config.face.attention)!=null&&l.enabled)&&!this.models.iris?K9(this.instance.config):null,a.facemesh=this.instance.config.face.enabled&&((u=this.instance.config.face.mesh)!=null&&u.enabled)&&!this.models.facemesh?eI(this.instance.config):null,a.gear=this.instance.config.face.enabled&&((p=this.instance.config.face.gear)!=null&&p.enabled)&&!this.models.gear?wI(this.instance.config):null,a.ssrnetage=this.instance.config.face.enabled&&((c=this.instance.config.face.ssrnet)!=null&&c.enabled)&&!this.models.ssrnetage?CI(this.instance.config):null,a.ssrnetgender=this.instance.config.face.enabled&&((d=this.instance.config.face.ssrnet)!=null&&d.enabled)&&!this.models.ssrnetgender?EI(this.instance.config):null,a.mobilefacenet=this.instance.config.face.enabled&&((h=this.instance.config.face.mobilefacenet)!=null&&h.enabled)&&!this.models.mobilefacenet?FI(this.instance.config):null,a.insightface=this.instance.config.face.enabled&&((m=this.instance.config.face.insightface)!=null&&m.enabled)&&!this.models.insightface?WI(this.instance.config):null,a.blazepose=this.instance.config.body.enabled&&!this.models.blazepose&&((f=this.instance.config.body.modelPath)!=null&&f.includes("blazepose"))?I9(this.instance.config):null,a.blazeposedetect=this.instance.config.body.enabled&&!this.models.blazeposedetect&&this.instance.config.body.detector&&this.instance.config.body.detector.modelPath?k9(this.instance.config):null,a.efficientpose=this.instance.config.body.enabled&&!this.models.efficientpose&&((g=this.instance.config.body.modelPath)!=null&&g.includes("efficientpose"))?E9(this.instance.config):null,a.movenet=this.instance.config.body.enabled&&!this.models.movenet&&((y=this.instance.config.body.modelPath)!=null&&y.includes("movenet"))?MS(this.instance.config):null,a.posenet=this.instance.config.body.enabled&&!this.models.posenet&&((x=this.instance.config.body.modelPath)!=null&&x.includes("posenet"))?VS(this.instance.config):null,a.handtrack=this.instance.config.hand.enabled&&!this.models.handtrack&&((b=(A=this.instance.config.hand.detector)==null?void 0:A.modelPath)!=null&&b.includes("handtrack"))?bS(this.instance.config):null,a.handskeleton=this.instance.config.hand.enabled&&this.instance.config.hand.landmarks&&!this.models.handskeleton&&((I=(w=this.instance.config.hand.detector)==null?void 0:w.modelPath)!=null&&I.includes("handtrack"))?vS(this.instance.config):null,this.instance.config.hand.enabled&&!this.models.handdetect&&((N=(T=this.instance.config.hand.detector)==null?void 0:T.modelPath)!=null&&N.includes("handdetect"))&&(a.handdetect=mS(this.instance.config),a.handskeleton=fS(this.instance.config)),a.centernet=this.instance.config.object.enabled&&!this.models.centernet&&((M=this.instance.config.object.modelPath)!=null&&M.includes("centernet"))?T9(this.instance.config):null,a.nanodet=this.instance.config.object.enabled&&!this.models.nanodet&&(($=this.instance.config.object.modelPath)!=null&&$.includes("nanodet"))?_S(this.instance.config):null,a.selfie=this.instance.config.segmentation.enabled&&!this.models.selfie&&((E=this.instance.config.segmentation.modelPath)!=null&&E.includes("selfie"))?Rx(this.instance.config):null,a.meet=this.instance.config.segmentation.enabled&&!this.models.meet&&((S=this.instance.config.segmentation.modelPath)!=null&&S.includes("meet"))?mx(this.instance.config):null,a.rvm=this.instance.config.segmentation.enabled&&!this.models.rvm&&((_=this.instance.config.segmentation.modelPath)!=null&&_.includes("rvm"))?Nx(this.instance.config):null;for(let[O,W]of Object.entries(a))W!=null&&W.then&&W.then(P=>this.models[O]=P);await Promise.all(Object.values(a))}list(){let t=Object.keys(this.models).map(a=>{var n;return{name:a,loaded:this.models[a]!==null,size:0,url:this.models[a]?(n=this.models[a])==null?void 0:n.modelUrl:null}});for(let a of t){let n=Object.keys(Yt).find(r=>r.startsWith(a.name));n&&(a.size=Yt[n].sizeLoadedWeights,a.url=Yt[n].url)}return t}loaded(){return this.list().filter(n=>n.loaded).map(n=>n.name)}validate(){let t=[];for(let a of Object.keys(this.models)){let n=this.models[a];if(!n)continue;let r=om(this.instance,n,a);r&&t.push(r)}return t}};function YS(e,t,a,n,r){var o,l,u,p,c,d;let s=0,i=[];for(let h of e){let m={id:s++,face:h,body:null,hands:{left:null,right:null},gestures:[],box:[0,0,0,0]};for(let b of t)h.box[0]>b.box[0]&&h.box[0]<b.box[0]+b.box[2]&&h.box[1]+h.box[3]>b.box[1]&&h.box[1]+h.box[3]<b.box[1]+b.box[3]&&(m.body=b);if(m.body)for(let b of a)b.box[0]+b.box[2]>m.body.box[0]&&b.box[0]+b.box[2]<m.body.box[0]+m.body.box[2]&&b.box[1]+b.box[3]>m.body.box[1]&&b.box[1]+b.box[3]<m.body.box[1]+m.body.box[3]&&m.hands&&(m.hands.left=b),b.box[0]<m.body.box[0]+m.body.box[2]&&b.box[0]>m.body.box[0]&&b.box[1]+b.box[3]>m.body.box[1]&&b.box[1]+b.box[3]<m.body.box[1]+m.body.box[3]&&m.hands&&(m.hands.right=b);for(let b of n)(b.face!==void 0&&b.face===h.id||b.iris!==void 0&&b.iris===h.id||b.body!==void 0&&b.body===((o=m.body)==null?void 0:o.id)||b.hand!==void 0&&b.hand===((l=m.hands.left)==null?void 0:l.id)||b.hand!==void 0&&b.hand===((u=m.hands.right)==null?void 0:u.id))&&m.gestures.push(b);let f=[],g=[],y=b=>{b&&b.length===4&&(f.push(b[0],b[0]+b[2]),g.push(b[1],b[1]+b[3]))};y(m.face.box),y((p=m.body)==null?void 0:p.box),y((c=m.hands.left)==null?void 0:c.box),y((d=m.hands.right)==null?void 0:d.box);let x=Math.min(...f),A=Math.min(...g);m.box=[x,A,Math.max(...f)-x,Math.max(...g)-A],r!=null&&r[1]&&(r!=null&&r[2])&&(m.boxRaw=[m.box[0]/r[2],m.box[1]/r[1],m.box[2]/r[2],m.box[3]/r[1]]),i.push(m)}return i}var lm=`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==`,um=`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`;async function rye(e){let t=(r,s="application/octet-stream")=>fetch(`data:${s};base64,${r}`).then(i=>i.blob()),a,n;switch(e.config.warmup){case"face":a=await t(lm);break;case"body":case"full":a=await t(um);break;default:a=null}if(a){let r=await createImageBitmap(a);n=await e.detect(r,e.config),r.close()}return n}async function sye(e){return new Promise(t=>{let a;switch(e.config.warmup){case"face":a="data:image/jpeg;base64,"+lm;break;case"full":case"body":a="data:image/jpeg;base64,"+um;break;default:a=""}let n;if(typeof Image!="undefined")n=new Image;else if(ne.Image)n=new ne.Image;else{t(void 0);return}n.onload=async()=>{let r=$n(n.naturalWidth,n.naturalHeight);if(!r)K("Warmup: Canvas not found"),t(void 0);else{let s=r.getContext("2d");s&&s.drawImage(n,0,0);let i=await e.image(r,!0),o=i.tensor?await e.detect(i.tensor,e.config):void 0;t(o)}},a?n.src=a:t(void 0)})}async function iye(e){let t=r=>Buffer.from(r,"base64"),a;e.config.warmup==="face"?a=t(lm):a=t(um);let n;if("node"in Ke&&ea()==="tensorflow"){let r=Q3.decodeJpeg(a),s=Wt(r,0);e.tf.dispose(r),n=await e.detect(s,e.config),e.tf.dispose(s)}else e.config.debug&&K("Warmup tfjs-node not loaded");return n}async function oye(e){let t;return typeof createImageBitmap=="function"?t=await rye(e):typeof Image!="undefined"||ne.Canvas!==void 0?t=await sye(e):t=await iye(e),t}async function lye(e){var o,l,u,p;if(!B().flagRegistry.ENGINE_COMPILE_ONLY)return;let t=ea(),a=Vn();if(t!=="webgl"&&t!=="humangl"||!(a!=null&&a.checkCompileCompletion))return;B().set("ENGINE_COMPILE_ONLY",!0);let n=It().state.numTensors,r=[];for(let[c,d]of Object.entries(e.models.models)){if(!d)continue;let h=d!=null&&d.modelSignature&&((l=(o=d==null?void 0:d.inputs)==null?void 0:o[0])!=null&&l.shape)?[...d.inputs[0].shape]:[1,64,64,3],m=d!=null&&d.modelSignature&&((p=(u=d==null?void 0:d.inputs)==null?void 0:u[0])!=null&&p.dtype)?d.inputs[0].dtype:"float32";for(let g=0;g<h.length;g++)h[g]===-1&&(h[g]=g===0?1:64);let f=yn(h,m);try{let g=d.execute(f);r.push(c),Array.isArray(g)?g.forEach(y=>J(y)):J(g)}catch(g){e.config.debug&&K("compile fail model:",c)}J(f)}let s=await a.checkCompileCompletionAsync();a.getUniformLocations(),e.config.debug&&K("compile pass:",{models:r,kernels:s.length}),B().set("ENGINE_COMPILE_ONLY",!1);let i=It().state.numTensors;i-n>0&&K("tensor leak:",i-n)}async function ZS(e,t){await oc(e,!1);let a=ae();return e.state="warmup",t&&(e.config=Et(e.config,t)),!e.config.warmup||e.config.warmup.length===0||e.config.warmup==="none"?hr():new Promise(async n=>{await e.models.load(),await tl(),await lye(e);let r=await oye(e),s=ae();e.config.debug&&K("warmup",e.config.warmup,Math.round(s-a),"ms"),e.emit("warmup"),n(r)})}var md,gc,yc,dm,Ps,Mx=class{constructor(t){he(this,"version");he(this,"config");he(this,"result");he(this,"state");he(this,"process");he(this,"tf");he(this,"env",ne);he(this,"draw",C0);he(this,"match",em);he(this,"models");he(this,"events");he(this,"faceTriangulation");he(this,"faceUVMap");he(this,"performance");Kn(this,md);Kn(this,gc);Kn(this,yc);he(this,"analyze",(...t)=>{if(!qa(this,gc))return;let a=this.tf.engine().state.numTensors,n=qa(this,md);br(this,md,a);let r=a-n;r!==0&&K(...t,r)});Kn(this,dm,t=>{if(!qa(this,yc))return null;if(!t)return"input is not defined";if(this.env.node&&!(t instanceof yt))return"input must be a tensor";try{this.tf.getBackend()}catch(a){return"backend not loaded"}return null});he(this,"webcam",new A0);he(this,"emit",t=>{var a;(a=this.events)!=null&&a.dispatchEvent&&this.events.dispatchEvent(new Event(t))});Kn(this,Ps,{});let a=(ac.tfjs||i3).replace(/-(.*)/,"");pl.wasmPath=`https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@${a}/dist/`,pl.modelBasePath=ne.browser?"../models/":"file://models/",this.version=sy,Object.defineProperty(this,"version",{value:sy}),this.config=JSON.parse(JSON.stringify(pl)),Object.seal(this.config),this.config.cacheModels=typeof indexedDB!="undefined",t&&(this.config=Et(this.config,t)),l9(this.config),this.tf=Ke,this.state="idle",br(this,md,0),br(this,gc,!1),br(this,yc,!1),this.performance={},this.events=typeof EventTarget!="undefined"?new EventTarget:void 0,this.models=new fc(this),cy(),this.result=hr(),this.process={tensor:null,canvas:null},this.faceTriangulation=tI,this.faceUVMap=aI,om(this,null,""),this.emit("create"),(this.config.debug||this.env.browser)&&K(`version: ${this.version}`),this.config.debug&&K(`tfjs version: ${this.tf.version["tfjs-core"]}`);let n=JSON.parse(JSON.stringify(this.env));delete n.kernels,delete n.initial,delete n.perfadd,this.config.debug&&K("environment:",n)}reset(){let t=this.config.backend;this.config=JSON.parse(JSON.stringify(pl)),this.config.backend=t,ny(),ne.initial=!0}validate(t){let a=ey(pl,t||this.config);return a.length===0&&(this.config=Et(this.config,t)),a}now(){return ae()}image(t,a=!1){return y0(t,this.config,a)}async segmentation(t,a){var s,i,o;if(a&&(this.config=Et(this.config,a)),!this.config.segmentation.enabled)return null;let n=await y0(t,this.config);if(!n.tensor)return null;let r=null;return(s=this.config.segmentation.modelPath)!=null&&s.includes("rvm")&&(r=await jS(n.tensor,this.config)),(i=this.config.segmentation.modelPath)!=null&&i.includes("meet")&&(r=await IS(n.tensor,this.config)),(o=this.config.segmentation.modelPath)!=null&&o.includes("selfie")&&(r=await XS(n.tensor,this.config)),J(n.tensor),r}compare(t,a){return o9(this.config,t,a)}async init(){await oc(this,!0),await this.tf.ready(),ny()}async load(t){this.state="load";let a=ae(),n=Object.values(this.models.models).filter(i=>i).length;t&&(this.config=Et(this.config,t)),this.env.initial&&(await oc(this,!1)||K("error: backend check failed"),await tl(),this.env.browser&&(this.config.debug&&K("configuration:",this.config),this.config.debug&&K("tf flags:",this.tf.ENV.flags))),await this.models.load(this),this.env.initial&&this.config.debug&&K("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),this.env.initial=!1,Object.values(this.models.models).filter(i=>i).length!==n&&(this.models.validate(),this.emit("load"));let s=Math.trunc(ae()-a);s>(this.performance.loadModels||0)&&(this.performance.loadModels=this.env.perfadd?(this.performance.loadModels||0)+s:s)}next(t=this.result){return kS(t,this.config)}async warmup(t){let a=ae(),n=await ZS(this,t),r=ae();return this.performance.warmup=Math.trunc(r-a),n}async profile(t,a){let n=await this.tf.profile(()=>this.detect(t,a)),r={},s=0;for(let o of n.kernels){let l=Number(o.kernelTimeMs)||0;r[o.name]?r[o.name]+=l:r[o.name]=l,s+=l}let i=[];Object.entries(r).forEach(o=>i.push({kernel:o[0],time:o[1],perc:0}));for(let o of i)o.perc=Math.round(1e3*o.time/s)/1e3,o.time=Math.round(1e3*o.time)/1e3;return i.sort((o,l)=>l.time-o.time),i.length=20,i}async detect(t,a){return this.state="detect",new Promise(async n=>{var g,y,x,A,b,w,I,T,N,M,$,E,S,_,O,W,P,U,G,q,H;this.state="config";let r;this.config=Et(this.config,a),this.state="check";let s=qa(this,dm).call(this,t);s&&(K(s,t),this.emit("error"),n(hr(s)));let i=ae();await this.load(),r=ae(),this.state="image";let o=await y0(t,this.config);if(this.process=o,this.performance.inputProcess=this.env.perfadd?(this.performance.inputProcess||0)+Math.trunc(ae()-r):Math.trunc(ae()-r),this.analyze("Get Image:"),!o.tensor){this.config.debug&&K("could not convert input to tensor"),this.emit("error"),n(hr("could not convert input to tensor"));return}this.emit("image"),r=ae(),this.config.skipAllowed=await i9(this.config,o.tensor),this.config.filter.autoBrightness=(this.config.filter.autoBrightness||!1)&&this.config.skipAllowed,this.performance.totalFrames||(this.performance.totalFrames=0),this.performance.cachedFrames||(this.performance.cachedFrames=0),this.performance.totalFrames++,this.config.skipAllowed&&this.performance.cachedFrames++,this.performance.cacheCheck=this.env.perfadd?(this.performance.cacheCheck||0)+Math.trunc(ae()-r):Math.trunc(ae()-r),this.analyze("Check Changed:");let l=[],u=[],p=[],c=[];this.state="detect:face",this.config.async?(l=this.config.face.enabled?ex(this,o.tensor):[],this.performance.face&&delete this.performance.face):(r=ae(),l=this.config.face.enabled?await ex(this,o.tensor):[],this.performance.face=this.env.perfadd?(this.performance.face||0)+Math.trunc(ae()-r):Math.trunc(ae()-r)),this.config.async&&(this.config.body.maxDetected===-1||this.config.hand.maxDetected===-1)&&(l=await l),this.analyze("Start Body:"),this.state="detect:body";let d=this.config.body.maxDetected===-1?Et(this.config,{body:{maxDetected:this.config.face.enabled?1*l.length:1}}):this.config;this.config.async?((g=this.config.body.modelPath)!=null&&g.includes("posenet")?u=this.config.body.enabled?Sx(o.tensor,d):[]:(y=this.config.body.modelPath)!=null&&y.includes("blazepose")?u=this.config.body.enabled?yy(o.tensor,d):[]:(x=this.config.body.modelPath)!=null&&x.includes("efficientpose")?u=this.config.body.enabled?Iy(o.tensor,d):[]:(A=this.config.body.modelPath)!=null&&A.includes("movenet")&&(u=this.config.body.enabled?xx(o.tensor,d):[]),this.performance.body&&delete this.performance.body):(r=ae(),(b=this.config.body.modelPath)!=null&&b.includes("posenet")?u=this.config.body.enabled?await Sx(o.tensor,d):[]:(w=this.config.body.modelPath)!=null&&w.includes("blazepose")?u=this.config.body.enabled?await yy(o.tensor,d):[]:(I=this.config.body.modelPath)!=null&&I.includes("efficientpose")?u=this.config.body.enabled?await Iy(o.tensor,d):[]:(T=this.config.body.modelPath)!=null&&T.includes("movenet")&&(u=this.config.body.enabled?await xx(o.tensor,d):[]),this.performance.body=this.env.perfadd?(this.performance.body||0)+Math.trunc(ae()-r):Math.trunc(ae()-r)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.state="detect:hand";let h=this.config.hand.maxDetected===-1?Et(this.config,{hand:{maxDetected:this.config.face.enabled?2*l.length:1}}):this.config;this.config.async?((M=(N=this.config.hand.detector)==null?void 0:N.modelPath)!=null&&M.includes("handdetect")?p=this.config.hand.enabled?ix(o.tensor,h):[]:(E=($=this.config.hand.detector)==null?void 0:$.modelPath)!=null&&E.includes("handtrack")&&(p=this.config.hand.enabled?ux(o.tensor,h):[]),this.performance.hand&&delete this.performance.hand):(r=ae(),(_=(S=this.config.hand.detector)==null?void 0:S.modelPath)!=null&&_.includes("handdetect")?p=this.config.hand.enabled?await ix(o.tensor,h):[]:(W=(O=this.config.hand.detector)==null?void 0:O.modelPath)!=null&&W.includes("handtrack")&&(p=this.config.hand.enabled?await ux(o.tensor,h):[]),this.performance.hand=this.env.perfadd?(this.performance.hand||0)+Math.trunc(ae()-r):Math.trunc(ae()-r)),this.analyze("End Hand:"),this.analyze("Start Object:"),this.state="detect:object",this.config.async?((P=this.config.object.modelPath)!=null&&P.includes("nanodet")?c=this.config.object.enabled?bx(o.tensor,this.config):[]:(U=this.config.object.modelPath)!=null&&U.includes("centernet")&&(c=this.config.object.enabled?by(o.tensor,this.config):[]),this.performance.object&&delete this.performance.object):(r=ae(),(G=this.config.object.modelPath)!=null&&G.includes("nanodet")?c=this.config.object.enabled?await bx(o.tensor,this.config):[]:(q=this.config.object.modelPath)!=null&&q.includes("centernet")&&(c=this.config.object.enabled?await by(o.tensor,this.config):[]),this.performance.object=this.env.perfadd?(this.performance.object||0)+Math.trunc(ae()-r):Math.trunc(ae()-r)),this.analyze("End Object:"),this.state="detect:await",this.config.async&&([l,u,p,c]=await Promise.all([l,u,p,c])),this.state="detect:gesture";let m=[];this.config.gesture.enabled&&(r=ae(),m=[...QI(l),...JI(u),...tS(p),...eS(l)],this.config.async?this.performance.gesture&&delete this.performance.gesture:this.performance.gesture=this.env.perfadd?(this.performance.gesture||0)+Math.trunc(ae()-r):Math.trunc(ae()-r)),this.performance.total=this.env.perfadd?(this.performance.total||0)+Math.trunc(ae()-i):Math.trunc(ae()-i);let f=((H=this.process.tensor)==null?void 0:H.shape)||[0,0,0,0];this.result={face:l,body:u,hand:p,gesture:m,object:c,performance:this.performance,canvas:this.process.canvas,timestamp:Date.now(),error:null,width:f[2],height:f[1],get persons(){return YS(l,u,p,m,f)}},J(o.tensor),this.emit("detect"),this.state="idle",n(this.result)})}async sleep(t){return new Promise(a=>{setTimeout(a,t)})}async video(t,a=!0,n=0){a?(qa(this,Ps)[t.id]||(this.config.debug&&K("video start",t.id),qa(this,Ps)[t.id]=!0),!t.paused&&qa(this,Ps)[t.id]&&t.readyState>=2&&await this.detect(t),n>0&&await this.sleep(n),qa(this,Ps)[t.id]&&requestAnimationFrame(()=>this.video(t,a,n))):(this.config.debug&&K("video stop",t.id),qa(this,Ps)[t.id]=!1)}};md=new WeakMap,gc=new WeakMap,yc=new WeakMap,dm=new WeakMap,Ps=new WeakMap;return DC(dye);})();