mirror of https://github.com/vladmandic/human
8290 lines
1.4 MiB
8290 lines
1.4 MiB
/*
|
|
Human
|
|
homepage: <https://github.com/vladmandic/human>
|
|
author: <https://github.com/vladmandic>'
|
|
*/
|
|
|
|
"use strict";var Human=(()=>{var lc=Object.defineProperty;var RI=Object.getOwnPropertyDescriptor;var MI=Object.getOwnPropertyNames;var $I=Object.prototype.hasOwnProperty;var _I=(e,t,a)=>t in e?lc(e,t,{enumerable:!0,configurable:!0,writable:!0,value:a}):e[t]=a;var fr=(e,t)=>{for(var a in t)lc(e,a,{get:t[a],enumerable:!0})},PI=(e,t,a,n)=>{if(t&&typeof t=="object"||typeof t=="function")for(let r of MI(t))!$I.call(e,r)&&r!==a&&lc(e,r,{get:()=>t[r],enumerable:!(n=RI(t,r))||n.enumerable});return e};var FI=e=>PI(lc({},"__esModule",{value:!0}),e);var de=(e,t,a)=>(_I(e,typeof t!="symbol"?t+"":t,a),a),_5=(e,t,a)=>{if(!t.has(e))throw TypeError("Cannot "+a)};var ja=(e,t,a)=>(_5(e,t,"read from private field"),a?a.call(e):t.get(e)),Gn=(e,t,a)=>{if(t.has(e))throw TypeError("Cannot add the same private member more than once");t instanceof WeakSet?t.add(e):t.set(e,a)},mr=(e,t,a,n)=>(_5(e,t,"write to private field"),n?n.call(e,a):t.set(e,a),a);var dfe={};fr(dfe,{Env:()=>Ap,Human:()=>b5,default:()=>b5,defaults:()=>So,draw:()=>e0,empty:()=>lr,env:()=>ne,match:()=>N0,models:()=>A5});var je={};fr(je,{Abs:()=>vl,Acos:()=>kl,Acosh:()=>wl,AdadeltaOptimizer:()=>j1,AdagradOptimizer:()=>q1,AdamOptimizer:()=>X1,AdamaxOptimizer:()=>K1,Add:()=>ts,AddN:()=>Ks,All:()=>Zs,Any:()=>Ys,ArgMax:()=>Js,ArgMin:()=>Id,Asin:()=>Il,Asinh:()=>Sl,Atan:()=>Tl,Atan2:()=>Nl,Atanh:()=>Cl,AvgPool:()=>Qs,AvgPool3D:()=>Kc,AvgPool3DGrad:()=>L2,AvgPoolGrad:()=>Xc,BackendWasm:()=>w8,BatchMatMul:()=>ei,BatchToSpaceND:()=>El,Bincount:()=>Sd,BroadcastArgs:()=>Zc,BroadcastTo:()=>TS,Cast:()=>ti,Ceil:()=>ai,ClipByValue:()=>as,Complex:()=>Td,ComplexAbs:()=>Yc,Concat:()=>Rl,Conv2D:()=>ni,Conv2DBackpropFilter:()=>Cd,Conv2DBackpropInput:()=>ri,Conv3D:()=>Jc,Conv3DBackpropFilterV2:()=>B2,Conv3DBackpropInputV2:()=>Qc,Cos:()=>si,Cosh:()=>ii,CropAndResize:()=>ui,Cumprod:()=>oi,Cumsum:()=>li,DataStorage:()=>kd,DenseBincount:()=>Nd,DepthToSpace:()=>di,DepthwiseConv2dNative:()=>pi,DepthwiseConv2dNativeBackpropFilter:()=>eh,DepthwiseConv2dNativeBackpropInput:()=>th,Diag:()=>Ed,Dilation2D:()=>Rd,Dilation2DBackpropFilter:()=>Bm,Dilation2DBackpropInput:()=>Lm,ENV:()=>D2,Einsum:()=>Md,Elu:()=>hi,EluGrad:()=>W2,Environment:()=>cx,Equal:()=>fi,Erf:()=>Ml,Exp:()=>mi,ExpandDims:()=>$l,Expm1:()=>_l,FFT:()=>$d,Fill:()=>Pl,FlipLeftRight:()=>gi,Floor:()=>yi,FloorDiv:()=>xi,FromPixels:()=>nd,FusedBatchNorm:()=>Ai,FusedConv2D:()=>jr,FusedDepthwiseConv2D:()=>qr,GPGPUContext:()=>sl,GatherNd:()=>bi,GatherV2:()=>Fl,GraphModel:()=>up,Greater:()=>vi,GreaterEqual:()=>ki,IFFT:()=>_d,Identity:()=>wi,Imag:()=>Pd,IsFinite:()=>Ol,IsInf:()=>Dl,IsNan:()=>Ii,KernelBackend:()=>Al,LRN:()=>Od,LRNGrad:()=>V2,LeakyRelu:()=>Si,Less:()=>Ti,LessEqual:()=>Ci,LinSpace:()=>Fd,Log:()=>Ni,Log1p:()=>zl,LogSoftmax:()=>CS,LogicalAnd:()=>Ei,LogicalNot:()=>Ri,LogicalOr:()=>Mi,LogicalXor:()=>fx,LowerBound:()=>NS,MathBackendCPU:()=>Th,MathBackendWebGL:()=>fu,Max:()=>$i,MaxPool:()=>Pi,MaxPool3D:()=>ah,MaxPool3DGrad:()=>G2,MaxPoolGrad:()=>U2,MaxPoolWithArgmax:()=>nh,Maximum:()=>_i,Mean:()=>Fi,Min:()=>Oi,Minimum:()=>Di,MirrorPad:()=>zi,Mod:()=>Ll,MomentumOptimizer:()=>Z1,Multinomial:()=>rh,Multiply:()=>Li,Neg:()=>Bl,NonMaxSuppressionV3:()=>Wi,NonMaxSuppressionV4:()=>Wl,NonMaxSuppressionV5:()=>Vi,NotEqual:()=>Bi,OP_SCOPE_SUFFIX:()=>K2,OneHot:()=>Ui,OnesLike:()=>Vl,Optimizer:()=>is,OptimizerConstructors:()=>x4,Pack:()=>Ul,PadV2:()=>Gi,Pool:()=>ES,Pow:()=>Hi,Prelu:()=>ji,Prod:()=>qi,RMSPropOptimizer:()=>Y1,RaggedGather:()=>sh,RaggedRange:()=>ih,RaggedTensorToTensor:()=>oh,Range:()=>Gl,Rank:()=>Um,Real:()=>Dd,RealDiv:()=>ci,Reciprocal:()=>Xi,Reduction:()=>ba,Relu:()=>Ki,Relu6:()=>Ji,Reshape:()=>Hl,ResizeBilinear:()=>Yi,ResizeBilinearGrad:()=>j2,ResizeNearestNeighbor:()=>Zi,ResizeNearestNeighborGrad:()=>H2,Reverse:()=>Qi,RotateWithOffset:()=>go,Round:()=>eo,Rsqrt:()=>to,SGDOptimizer:()=>Sh,ScatterNd:()=>ao,SearchSorted:()=>zd,Select:()=>jl,Selu:()=>ql,Sigmoid:()=>ro,Sign:()=>Zl,Sin:()=>no,Sinh:()=>Kl,Slice:()=>Xl,Softmax:()=>oo,Softplus:()=>Yl,SpaceToBatchND:()=>Jl,SparseFillEmptyRows:()=>Ld,SparseReshape:()=>eu,SparseSegmentMean:()=>Bd,SparseSegmentSum:()=>Wd,SparseToDense:()=>Vd,SplitV:()=>Ql,Sqrt:()=>so,Square:()=>Ud,SquaredDifference:()=>lo,Step:()=>rs,StridedSlice:()=>uo,StringNGrams:()=>tu,StringSplit:()=>Gd,StringToHashBucketFast:()=>Hd,Sub:()=>po,Sum:()=>io,Tan:()=>co,Tanh:()=>ho,Tensor:()=>pt,TensorBuffer:()=>jt,Tile:()=>ns,TopK:()=>fo,Transform:()=>mo,Transpose:()=>Ar,Unique:()=>lh,Unpack:()=>au,UnsortedSegmentSum:()=>uh,UpperBound:()=>RS,Variable:()=>id,WebGPUBackend:()=>Oh,ZerosLike:()=>nu,_FusedMatMul:()=>Hr,abs:()=>Ka,acos:()=>Fx,acosh:()=>Ox,add:()=>be,addN:()=>ph,all:()=>Dx,any:()=>zx,argMax:()=>ar,argMin:()=>Lx,asin:()=>Bx,asinh:()=>Wx,atan:()=>Vx,atan2:()=>Ux,atanh:()=>Gx,avgPool:()=>r1,avgPool3d:()=>Xx,backend:()=>tr,backend_util:()=>T,basicLSTMCell:()=>Kx,batchNorm:()=>tp,batchNorm2d:()=>Zx,batchNorm3d:()=>Yx,batchNorm4d:()=>Jx,batchToSpaceND:()=>s1,bincount:()=>i1,booleanMaskAsync:()=>Pb,broadcastArgs:()=>Qx,broadcastTo:()=>rl,broadcast_util:()=>xo,browser:()=>Sr,buffer:()=>_e,cast:()=>Xe,ceil:()=>eA,clipByValue:()=>tA,clone:()=>wa,complex:()=>vr,concat:()=>st,concat1d:()=>aA,concat2d:()=>ru,concat3d:()=>nA,concat4d:()=>rA,conv1d:()=>sA,conv2d:()=>ap,conv2dTranspose:()=>oA,conv3d:()=>lA,conv3dTranspose:()=>uA,copyRegisteredKernels:()=>FS,cos:()=>dA,cosh:()=>pA,cosineWindow:()=>bh,cumprod:()=>cA,cumsum:()=>hA,customGrad:()=>Qn,denseBincount:()=>fA,deprecationWarn:()=>t1,depthToSpace:()=>mA,depthwiseConv2d:()=>ch,deregisterOp:()=>vP,device_util:()=>Kd,diag:()=>gA,dilation2d:()=>yA,disableDeprecationWarnings:()=>HT,dispose:()=>J,disposeVariables:()=>jT,div:()=>xe,divNoNan:()=>AA,dot:()=>bA,dropout:()=>Bb,einsum:()=>vA,elu:()=>u1,enableDebugMode:()=>GT,enableProdMode:()=>e1,enclosingPowerOfTwo:()=>U1,engine:()=>vt,env:()=>V,equal:()=>l1,erf:()=>kA,euclideanNorm:()=>SA,exp:()=>Zr,expandDims:()=>Gt,expm1:()=>TA,eye:()=>p1,fft:()=>xh,fill:()=>nr,findBackend:()=>a1,findBackendFactory:()=>YT,floor:()=>c1,floorDiv:()=>Qd,forceHalfFloat:()=>U6,fused:()=>G1,gather:()=>h1,gatherND:()=>Lb,gather_util:()=>e3,getBackend:()=>ua,getGradient:()=>Wm,getKernel:()=>Nc,getKernelsForBackend:()=>Zn,getThreadsCount:()=>Mne,gpgpu_util:()=>v6,grad:()=>KN,grads:()=>ZN,greater:()=>sp,greaterEqual:()=>f1,ifft:()=>fd,imag:()=>ip,image:()=>ye,inTopKAsync:()=>Wb,io:()=>jn,irfft:()=>F1,isFinite:()=>CA,isInf:()=>NA,isNaN:()=>EA,keep:()=>On,kernel_impls:()=>Nn,leakyRelu:()=>m1,less:()=>RA,lessEqual:()=>hh,linalg:()=>Kb,linspace:()=>MA,loadGraphModel:()=>s3,loadGraphModelSync:()=>SF,localResponseNormalization:()=>$A,log:()=>ul,log1p:()=>g1,logSigmoid:()=>PA,logSoftmax:()=>FA,logSumExp:()=>x1,logicalAnd:()=>cd,logicalNot:()=>A1,logicalOr:()=>b1,logicalXor:()=>OA,losses:()=>Zb,lowerBound:()=>DA,matMul:()=>ot,math:()=>o4,max:()=>ha,maxPool:()=>v1,maxPool3d:()=>zA,maxPoolWithArgmax:()=>LA,maximum:()=>k1,mean:()=>hd,memory:()=>qT,meshgrid:()=>BA,min:()=>Kr,minimum:()=>w1,mirrorPad:()=>WA,mod:()=>su,moments:()=>VA,movingAverage:()=>Fb,mul:()=>te,multiRNNCell:()=>UA,multinomial:()=>GA,neg:()=>Xn,nextFrame:()=>A4,norm:()=>rp,notEqual:()=>I1,oneHot:()=>$c,ones:()=>Br,onesLike:()=>HA,op:()=>z,outerProduct:()=>jA,pad:()=>rr,pad1d:()=>qA,pad2d:()=>XA,pad3d:()=>KA,pad4d:()=>ZA,pool:()=>YA,pow:()=>ll,prelu:()=>T1,print:()=>Q2,prod:()=>JA,profile:()=>XT,raggedGather:()=>QA,raggedRange:()=>eb,raggedTensorToTensor:()=>tb,rand:()=>ab,randomGamma:()=>ib,randomNormal:()=>M1,randomStandardNormal:()=>ob,randomUniform:()=>$1,range:()=>dl,ready:()=>Jd,real:()=>pl,reciprocal:()=>lb,registerBackend:()=>yo,registerGradient:()=>$S,registerKernel:()=>yn,registerOp:()=>bP,relu:()=>op,relu6:()=>_1,removeBackend:()=>ZT,reshape:()=>Q,reverse:()=>Yr,reverse1d:()=>ub,reverse2d:()=>db,reverse3d:()=>pb,reverse4d:()=>cb,rfft:()=>Ah,round:()=>P1,rsqrt:()=>hb,scalar:()=>ze,scatterND:()=>Db,scatter_util:()=>B1,searchSorted:()=>mh,selu:()=>fb,separableConv2d:()=>mb,serialization:()=>Qb,setBackend:()=>Yd,setPlatform:()=>JT,setThreadsCount:()=>Rne,setWasmPath:()=>Ene,setWasmPaths:()=>Fh,setWebGLContext:()=>Eh,setdiff1dAsync:()=>gb,shared:()=>Ch,sigmoid:()=>za,sign:()=>yb,signal:()=>Xb,sin:()=>xb,sinh:()=>Ab,slice:()=>Fe,slice1d:()=>bb,slice2d:()=>vb,slice3d:()=>lp,slice4d:()=>gh,slice_util:()=>St,softmax:()=>yh,softplus:()=>y1,spaceToBatchND:()=>S1,sparse:()=>Yb,sparseToDense:()=>zb,spectral:()=>qb,split:()=>Ia,sqrt:()=>Jn,square:()=>Tn,squaredDifference:()=>O1,squeeze:()=>De,stack:()=>la,step:()=>D1,stridedSlice:()=>kb,string:()=>Jb,sub:()=>fe,sum:()=>rt,sumOutType:()=>Xd,tan:()=>wb,tanh:()=>Mc,tensor:()=>Ue,tensor1d:()=>Ht,tensor2d:()=>Kn,tensor3d:()=>z1,tensor4d:()=>Ib,tensor5d:()=>Sb,tensor6d:()=>Tb,tensor_util:()=>xx,test_util:()=>nb,tidy:()=>Oe,tile:()=>Ur,time:()=>KT,topk:()=>Cb,train:()=>y_,transpose:()=>Vs,truncatedNormal:()=>Nb,unique:()=>Eb,unregisterGradient:()=>PS,unregisterKernel:()=>_S,unsortedSegmentSum:()=>Rb,unstack:()=>Ca,upcastType:()=>fa,upperBound:()=>Mb,util:()=>v,valueAndGrad:()=>YN,valueAndGrads:()=>JN,variable:()=>$b,variableGrads:()=>_A,version:()=>xp,version_converter:()=>CF,version_core:()=>t3,version_cpu:()=>PO,version_wasm:()=>$ne,version_webgl:()=>bG,webgl:()=>vG,webgl_util:()=>H7,webgpu_util:()=>T8,where:()=>Ws,whereAsync:()=>L1,zeros:()=>gn,zerosLike:()=>Ya});var OI=Object.create,F2=Object.defineProperty,DI=Object.getOwnPropertyDescriptor,zI=Object.getOwnPropertyNames,LI=Object.getPrototypeOf,BI=Object.prototype.hasOwnProperty,qt=(e,t)=>()=>(t||e((t={exports:{}}).exports,t),t.exports),Ze=(e,t)=>{for(var a in t)F2(e,a,{get:t[a],enumerable:!0})},WI=(e,t,a,n)=>{if(t&&typeof t=="object"||typeof t=="function")for(let r of zI(t))!BI.call(e,r)&&r!==a&&F2(e,r,{get:()=>t[r],enumerable:!(n=DI(t,r))||n.enumerable});return e},xl=(e,t,a)=>(a=e!=null?OI(LI(e)):{},WI(t||!e||!e.__esModule?F2(a,"default",{value:e,enumerable:!0}):a,e)),VI=qt((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(I){}function n(I,_,D){this.low=I|0,this.high=_|0,this.unsigned=!!D}n.prototype.__isLong__,Object.defineProperty(n.prototype,"__isLong__",{value:!0});function r(I){return(I&&I.__isLong__)===!0}n.isLong=r;var s={},i={};function o(I,_){var D,W,P;return _?(I>>>=0,(P=0<=I&&I<256)&&(W=i[I],W)?W:(D=u(I,(I|0)<0?-1:0,!0),P&&(i[I]=D),D)):(I|=0,(P=-128<=I&&I<128)&&(W=s[I],W)?W:(D=u(I,I<0?-1:0,!1),P&&(s[I]=D),D))}n.fromInt=o;function l(I,_){if(isNaN(I))return _?b:A;if(_){if(I<0)return b;if(I>=g)return $}else{if(I<=-y)return M;if(I+1>=y)return N}return I<0?l(-I,_).neg():u(I%m|0,I/m|0,_)}n.fromNumber=l;function u(I,_,D){return new n(I,_,D)}n.fromBits=u;var p=Math.pow;function c(I,_,D){if(I.length===0)throw Error("empty string");if(I==="NaN"||I==="Infinity"||I==="+Infinity"||I==="-Infinity")return A;if(typeof _=="number"?(D=_,_=!1):_=!!_,D=D||10,D<2||36<D)throw RangeError("radix");var W;if((W=I.indexOf("-"))>0)throw Error("interior hyphen");if(W===0)return c(I.substring(1),_,D).neg();for(var P=l(p(D,8)),U=A,G=0;G<I.length;G+=8){var q=Math.min(8,I.length-G),H=parseInt(I.substring(G,G+q),D);if(q<8){var B=l(p(D,q));U=U.mul(B).add(l(H))}else U=U.mul(P),U=U.add(l(H))}return U.unsigned=_,U}n.fromString=c;function d(I,_){return typeof I=="number"?l(I,_):typeof I=="string"?c(I,_):u(I.low,I.high,typeof _=="boolean"?_:I.unsigned)}n.fromValue=d;var h=1<<16,f=1<<24,m=h*h,g=m*m,y=g/2,x=o(f),A=o(0);n.ZERO=A;var b=o(0,!0);n.UZERO=b;var k=o(1);n.ONE=k;var S=o(1,!0);n.UONE=S;var C=o(-1);n.NEG_ONE=C;var N=u(-1,2147483647,!1);n.MAX_VALUE=N;var $=u(-1,-1,!0);n.MAX_UNSIGNED_VALUE=$;var M=u(0,-2147483648,!1);n.MIN_VALUE=M;var R=n.prototype;R.toInt=function(){return this.unsigned?this.low>>>0:this.low},R.toNumber=function(){return this.unsigned?(this.high>>>0)*m+(this.low>>>0):this.high*m+(this.low>>>0)},R.toString=function(I){if(I=I||10,I<2||36<I)throw RangeError("radix");if(this.isZero())return"0";if(this.isNegative())if(this.eq(M)){var _=l(I),D=this.div(_),W=D.mul(_).sub(this);return D.toString(I)+W.toInt().toString(I)}else return"-"+this.neg().toString(I);for(var P=l(p(I,6),this.unsigned),U=this,G="";;){var q=U.div(P),H=U.sub(q.mul(P)).toInt()>>>0,B=H.toString(I);if(U=q,U.isZero())return B+G;for(;B.length<6;)B="0"+B;G=""+B+G}},R.getHighBits=function(){return this.high},R.getHighBitsUnsigned=function(){return this.high>>>0},R.getLowBits=function(){return this.low},R.getLowBitsUnsigned=function(){return this.low>>>0},R.getNumBitsAbs=function(){if(this.isNegative())return this.eq(M)?64:this.neg().getNumBitsAbs();for(var I=this.high!=0?this.high:this.low,_=31;_>0&&!(I&1<<_);_--);return this.high!=0?_+33:_+1},R.isZero=function(){return this.high===0&&this.low===0},R.eqz=R.isZero,R.isNegative=function(){return!this.unsigned&&this.high<0},R.isPositive=function(){return this.unsigned||this.high>=0},R.isOdd=function(){return(this.low&1)===1},R.isEven=function(){return(this.low&1)===0},R.equals=function(I){return r(I)||(I=d(I)),this.unsigned!==I.unsigned&&this.high>>>31===1&&I.high>>>31===1?!1:this.high===I.high&&this.low===I.low},R.eq=R.equals,R.notEquals=function(I){return!this.eq(I)},R.neq=R.notEquals,R.ne=R.notEquals,R.lessThan=function(I){return this.comp(I)<0},R.lt=R.lessThan,R.lessThanOrEqual=function(I){return this.comp(I)<=0},R.lte=R.lessThanOrEqual,R.le=R.lessThanOrEqual,R.greaterThan=function(I){return this.comp(I)>0},R.gt=R.greaterThan,R.greaterThanOrEqual=function(I){return this.comp(I)>=0},R.gte=R.greaterThanOrEqual,R.ge=R.greaterThanOrEqual,R.compare=function(I){if(r(I)||(I=d(I)),this.eq(I))return 0;var _=this.isNegative(),D=I.isNegative();return _&&!D?-1:!_&&D?1:this.unsigned?I.high>>>0>this.high>>>0||I.high===this.high&&I.low>>>0>this.low>>>0?-1:1:this.sub(I).isNegative()?-1:1},R.comp=R.compare,R.negate=function(){return!this.unsigned&&this.eq(M)?M:this.not().add(k)},R.neg=R.negate,R.add=function(I){r(I)||(I=d(I));var _=this.high>>>16,D=this.high&65535,W=this.low>>>16,P=this.low&65535,U=I.high>>>16,G=I.high&65535,q=I.low>>>16,H=I.low&65535,B=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+=D+G,B+=Z>>>16,Z&=65535,B+=_+U,B&=65535,u(X<<16|re,B<<16|Z,this.unsigned)},R.subtract=function(I){return r(I)||(I=d(I)),this.add(I.neg())},R.sub=R.subtract,R.multiply=function(I){if(this.isZero())return A;if(r(I)||(I=d(I)),a){var _=a.mul(this.low,this.high,I.low,I.high);return u(_,a.get_high(),this.unsigned)}if(I.isZero())return A;if(this.eq(M))return I.isOdd()?M:A;if(I.eq(M))return this.isOdd()?M:A;if(this.isNegative())return I.isNegative()?this.neg().mul(I.neg()):this.neg().mul(I).neg();if(I.isNegative())return this.mul(I.neg()).neg();if(this.lt(x)&&I.lt(x))return l(this.toNumber()*I.toNumber(),this.unsigned);var D=this.high>>>16,W=this.high&65535,P=this.low>>>16,U=this.low&65535,G=I.high>>>16,q=I.high&65535,H=I.low>>>16,B=I.low&65535,Z=0,X=0,re=0,ee=0;return ee+=U*B,re+=ee>>>16,ee&=65535,re+=P*B,X+=re>>>16,re&=65535,re+=U*H,X+=re>>>16,re&=65535,X+=W*B,Z+=X>>>16,X&=65535,X+=P*H,Z+=X>>>16,X&=65535,X+=U*q,Z+=X>>>16,X&=65535,Z+=D*B+W*H+P*q+U*G,Z&=65535,u(re<<16|ee,Z<<16|X,this.unsigned)},R.mul=R.multiply,R.divide=function(I){if(r(I)||(I=d(I)),I.isZero())throw Error("division by zero");if(a){if(!this.unsigned&&this.high===-2147483648&&I.low===-1&&I.high===-1)return this;var _=(this.unsigned?a.div_u:a.div_s)(this.low,this.high,I.low,I.high);return u(_,a.get_high(),this.unsigned)}if(this.isZero())return this.unsigned?b:A;var D,W,P;if(this.unsigned){if(I.unsigned||(I=I.toUnsigned()),I.gt(this))return b;if(I.gt(this.shru(1)))return S;P=b}else{if(this.eq(M)){if(I.eq(k)||I.eq(C))return M;if(I.eq(M))return k;var U=this.shr(1);return D=U.div(I).shl(1),D.eq(A)?I.isNegative()?k:C:(W=this.sub(I.mul(D)),P=D.add(W.div(I)),P)}else if(I.eq(M))return this.unsigned?b:A;if(this.isNegative())return I.isNegative()?this.neg().div(I.neg()):this.neg().div(I).neg();if(I.isNegative())return this.div(I.neg()).neg();P=A}for(W=this;W.gte(I);){D=Math.max(1,Math.floor(W.toNumber()/I.toNumber()));for(var G=Math.ceil(Math.log(D)/Math.LN2),q=G<=48?1:p(2,G-48),H=l(D),B=H.mul(I);B.isNegative()||B.gt(W);)D-=q,H=l(D,this.unsigned),B=H.mul(I);H.isZero()&&(H=k),P=P.add(H),W=W.sub(B)}return P},R.div=R.divide,R.modulo=function(I){if(r(I)||(I=d(I)),a){var _=(this.unsigned?a.rem_u:a.rem_s)(this.low,this.high,I.low,I.high);return u(_,a.get_high(),this.unsigned)}return this.sub(this.div(I).mul(I))},R.mod=R.modulo,R.rem=R.modulo,R.not=function(){return u(~this.low,~this.high,this.unsigned)},R.and=function(I){return r(I)||(I=d(I)),u(this.low&I.low,this.high&I.high,this.unsigned)},R.or=function(I){return r(I)||(I=d(I)),u(this.low|I.low,this.high|I.high,this.unsigned)},R.xor=function(I){return r(I)||(I=d(I)),u(this.low^I.low,this.high^I.high,this.unsigned)},R.shiftLeft=function(I){return r(I)&&(I=I.toInt()),(I&=63)===0?this:I<32?u(this.low<<I,this.high<<I|this.low>>>32-I,this.unsigned):u(0,this.low<<I-32,this.unsigned)},R.shl=R.shiftLeft,R.shiftRight=function(I){return r(I)&&(I=I.toInt()),(I&=63)===0?this:I<32?u(this.low>>>I|this.high<<32-I,this.high>>I,this.unsigned):u(this.high>>I-32,this.high>=0?0:-1,this.unsigned)},R.shr=R.shiftRight,R.shiftRightUnsigned=function(I){if(r(I)&&(I=I.toInt()),I&=63,I===0)return this;var _=this.high;if(I<32){var D=this.low;return u(D>>>I|_<<32-I,_>>>I,this.unsigned)}else return I===32?u(_,0,this.unsigned):u(_>>>I-32,0,this.unsigned)},R.shru=R.shiftRightUnsigned,R.shr_u=R.shiftRightUnsigned,R.toSigned=function(){return this.unsigned?u(this.low,this.high,!1):this},R.toUnsigned=function(){return this.unsigned?this:u(this.low,this.high,!0)},R.toBytes=function(I){return I?this.toBytesLE():this.toBytesBE()},R.toBytesLE=function(){var I=this.high,_=this.low;return[_&255,_>>>8&255,_>>>16&255,_>>>24,I&255,I>>>8&255,I>>>16&255,I>>>24]},R.toBytesBE=function(){var I=this.high,_=this.low;return[I>>>24,I>>>16&255,I>>>8&255,I&255,_>>>24,_>>>16&255,_>>>8&255,_&255]},n.fromBytes=function(I,_,D){return D?n.fromBytesLE(I,_):n.fromBytesBE(I,_)},n.fromBytesLE=function(I,_){return new n(I[0]|I[1]<<8|I[2]<<16|I[3]<<24,I[4]|I[5]<<8|I[6]<<16|I[7]<<24,_)},n.fromBytesBE=function(I,_){return new n(I[4]<<24|I[5]<<16|I[6]<<8|I[7],I[0]<<24|I[1]<<16|I[2]<<8|I[3],_)}}),UI=qt(()=>{}),GI=qt(()=>{}),HI=qt((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)}),jI=qt((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,f=(p.next()>>>0)/4294967296,m=(h+f)/(1<<21);while(m===0);return m},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)}),qI=qt((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,f=(p.next()>>>0)/4294967296,m=(h+f)/(1<<21);while(m===0);return m},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)}),XI=qt((e,t)=>{(function(a,n,r){function s(l){var u=this;u.next=function(){var c=u.x,d=u.i,h,f,m;return h=c[d],h^=h>>>7,f=h^h<<24,h=c[d+1&7],f^=h^h>>>10,h=c[d+3&7],f^=h^h>>>3,h=c[d+4&7],f^=h^h<<7,h=c[d+7&7],h=h^h<<13,f^=h^h<<9,c[d]=f,u.i=d+1&7,f};function p(c,d){var h,f,m=[];if(d===(d|0))f=m[0]=d;else for(d=""+d,h=0;h<d.length;++h)m[h&7]=m[h&7]<<15^d.charCodeAt(h)+m[h+1&7]<<13;for(;m.length<8;)m.push(0);for(h=0;h<8&&m[h]===0;++h);for(h==8?f=m[7]=-1:f=m[h],c.x=m,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,f=(p.next()>>>0)/4294967296,m=(h+f)/(1<<21);while(m===0);return m},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)}),KI=qt((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,f,m;return u.w=c=c+1640531527|0,m=d[h+34&127],f=d[h=h+1&127],m^=m<<13,f^=f<<17,m^=m>>>15,f^=f>>>12,m=d[h]=m^f,u.i=h,m+(c^c>>>16)|0};function p(c,d){var h,f,m,g,y,x=[],A=128;for(d===(d|0)?(f=d,d=null):(d=d+"\0",f=0,A=Math.max(A,d.length)),m=0,g=-32;g<A;++g)d&&(f^=d.charCodeAt((g+32)%d.length)),g===0&&(y=f),f^=f<<10,f^=f>>>15,f^=f<<4,f^=f>>>13,g>=0&&(y=y+1640531527|0,h=x[g&127]^=f+y,m=h==0?m+1:0);for(m>=128&&(x[(d&&d.length||0)&127]=-1),m=127,g=4*128;g>0;--g)f=x[m+34&127],h=x[m=m+1&127],f^=f<<13,h^=h<<17,f^=f>>>15,h^=h>>>12,x[m]=f^h;c.w=y,c.X=x,c.i=m}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,f=(p.next()>>>0)/4294967296,m=(h+f)/(1<<21);while(m===0);return m},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)}),ZI=qt((e,t)=>{(function(a,n,r){function s(l){var u=this,p="";u.next=function(){var d=u.b,h=u.c,f=u.d,m=u.a;return d=d<<25^d>>>7^h,h=h-f|0,f=f<<24^f>>>8^m,m=m-d|0,u.b=d=d<<20^d>>>12^h,u.c=h=h-f|0,u.d=f<<16^h>>>16^m,u.a=m-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,f=(p.next()>>>0)/4294967296,m=(h+f)/(1<<21);while(m===0);return m},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)}),YI=qt(()=>{}),JI=qt((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 f(k,S,C){var N=[];S=S==!0?{entropy:!0}:S||{};var $=x(y(S.entropy?[k,b(n)]:k==null?A():k,3),N),M=new m(N),R=function(){for(var I=M.g(i),_=u,D=0;I<p;)I=(I+D)*s,_*=s,D=M.g(1);for(;I>=c;)I/=2,_/=2,D>>>=1;return(I+D)/_};return R.int32=function(){return M.g(4)|0},R.quick=function(){return M.g(4)/4294967296},R.double=R,x(b(M.S),n),(S.pass||C||function(I,_,D,W){return W&&(W.S&&g(W,M),I.state=function(){return g(M,{})}),D?(r[l]=I,_):I})(R,$,"global"in S?S.global:this==r,S.state)}function m(k){var S,C=k.length,N=this,$=0,M=N.i=N.j=0,R=N.S=[];for(C||(k=[C++]);$<s;)R[$]=$++;for($=0;$<s;$++)R[$]=R[M=d&M+k[$%C]+(S=R[$])],R[M]=S;(N.g=function(I){for(var _,D=0,W=N.i,P=N.j,U=N.S;I--;)_=U[W=d&W+1],D=D*s+U[d&(U[W]=U[P=d&P+_])+(U[P]=_)];return N.i=W,N.j=P,D})(s)}function g(k,S){return S.i=k.i,S.j=k.j,S.S=k.S.slice(),S}function y(k,S){var C=[],N=typeof k,$;if(S&&N=="object")for($ in k)try{C.push(y(k[$],S-1))}catch(M){}return C.length?C:N=="string"?k:k+"\0"}function x(k,S){for(var C=k+"",N,$=0;$<C.length;)S[d&$]=d&(N^=S[d&$]*19)+C.charCodeAt($++);return b(S)}function A(){try{var k;return h&&(k=h.randomBytes)?k=k(s):(k=new Uint8Array(s),(a.crypto||a.msCrypto).getRandomValues(k)),b(k)}catch(N){var S=a.navigator,C=S&&S.plugins;return[+new Date,a,C,a.screen,b(n)]}}function b(k){return String.fromCharCode.apply(0,k)}if(x(r.random(),n),typeof t=="object"&&t.exports){t.exports=f;try{h=YI()}catch(k){}}else typeof define=="function"&&define.amd?define(function(){return f}):r["seed"+l]=f})(typeof self!="undefined"?self:e,[],Math)}),Qy=qt((e,t)=>{var a=HI(),n=jI(),r=qI(),s=XI(),i=KI(),o=ZI(),l=JI();l.alea=a,l.xor128=n,l.xorwow=r,l.xorshift7=s,l.xor4096=i,l.tychei=o,t.exports=l}),ex=qt(()=>{}),tx=qt(()=>{}),QI=qt(()=>{}),eS=qt(()=>{}),tS=qt(()=>{}),aS=qt((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!=Ge&&ut(ie.buffer),ht}function i(){return ie.buffer!=Ge&&ut(ie.buffer),Ga}function o(){return ie.buffer!=Ge&&ut(ie.buffer),Ot}function l(){return ie.buffer!=Ge&&ut(ie.buffer),ra}function u(){return ie.buffer!=Ge&&ut(ie.buffer),_a}function p(){return ie.buffer!=Ge&&ut(ie.buffer),un}function c(){return ie.buffer!=Ge&&ut(ie.buffer),Pa}var d=typeof r!="undefined"?r:{},h,f;d.ready=new Promise(function(O,j){h=O,f=j});var m;typeof process!="undefined"&&process.listeners&&(m={uncaughtException:process.listeners("uncaughtException"),unhandledRejection:process.listeners("unhandledRejection")});var g=Object.assign({},d),y=[],x="./this.program",A=(O,j)=>{throw j},b=typeof window=="object",k=typeof importScripts=="function",S=typeof process=="object"&&typeof process.versions=="object"&&typeof process.versions.node=="string",C=d.ENVIRONMENT_IS_PTHREAD||!1,N="";function $(O){return d.locateFile?d.locateFile(O,N):N+O}var M,R,I,_;function D(O){O instanceof Cs||H("exiting due to exception: "+O)}if(S){var W=ex(),P=tx();k?N=P.dirname(N)+"/":N=__dirname+"/",M=(j,oe)=>(j=Uo(j)?new URL(j):P.normalize(j),W.readFileSync(j,oe?void 0:"utf8")),I=j=>{var oe=M(j,!0);return oe.buffer||(oe=new Uint8Array(oe)),oe},R=(j,oe,Re)=>{j=Uo(j)?new URL(j):P.normalize(j),W.readFile(j,function(He,Ve){He?Re(He):oe(Ve.buffer)})},process.argv.length>1&&(x=process.argv[1].replace(/\\/g,"/")),y=process.argv.slice(2),process.on("uncaughtException",function(j){if(!(j instanceof Cs))throw j}),process.on("unhandledRejection",function(j){throw j}),A=(j,oe)=>{if(kn())throw process.exitCode=j,oe;D(oe),process.exit(j)},d.inspect=function(){return"[Emscripten Module object]"};let O;try{O=QI()}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=O.Worker}else(b||k)&&(k?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="",S||(M=O=>{var j=new XMLHttpRequest;return j.open("GET",O,!1),j.send(null),j.responseText},k&&(I=O=>{var j=new XMLHttpRequest;return j.open("GET",O,!1),j.responseType="arraybuffer",j.send(null),new Uint8Array(j.response)}),R=(O,j,oe)=>{var Re=new XMLHttpRequest;Re.open("GET",O,!0),Re.responseType="arraybuffer",Re.onload=()=>{if(Re.status==200||Re.status==0&&Re.response){j(Re.response);return}oe()},Re.onerror=oe,Re.send(null)}),_=O=>document.title=O);S&&typeof performance=="undefined"&&(global.performance=eS().performance);var U=console.log.bind(console),G=console.warn.bind(console);S&&(U=O=>W.writeSync(1,O+`
|
|
`),G=O=>W.writeSync(2,O+`
|
|
`));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 B=4,Z=Atomics.load,X=Atomics.store,re=Atomics.compareExchange,ee;d.wasmBinary&&(ee=d.wasmBinary);var ce=d.noExitRuntime||!0;typeof WebAssembly!="object"&&Ts("no native wasm support detected");var ie,ge,Se=!1,Ne;function Be(O,j){O||Ts(j)}var qe=typeof TextDecoder!="undefined"?new TextDecoder("utf8"):void 0;function dt(O,j,oe){for(var Re=j+oe,He=j;O[He]&&!(He>=Re);)++He;if(He-j>16&&O.buffer&&qe)return qe.decode(O.buffer instanceof SharedArrayBuffer?O.slice(j,He):O.subarray(j,He));for(var Ve="";j<He;){var he=O[j++];if(!(he&128)){Ve+=String.fromCharCode(he);continue}var Ce=O[j++]&63;if((he&224)==192){Ve+=String.fromCharCode((he&31)<<6|Ce);continue}var It=O[j++]&63;if((he&240)==224?he=(he&15)<<12|Ce<<6|It:he=(he&7)<<18|Ce<<12|It<<6|O[j++]&63,he<65536)Ve+=String.fromCharCode(he);else{var pn=he-65536;Ve+=String.fromCharCode(55296|pn>>10,56320|pn&1023)}}return Ve}function it(O,j){return O?dt(i(),O,j):""}function at(O,j,oe,Re){if(!(Re>0))return 0;for(var He=oe,Ve=oe+Re-1,he=0;he<O.length;++he){var Ce=O.charCodeAt(he);if(Ce>=55296&&Ce<=57343){var It=O.charCodeAt(++he);Ce=65536+((Ce&1023)<<10)|It&1023}if(Ce<=127){if(oe>=Ve)break;j[oe++]=Ce}else if(Ce<=2047){if(oe+1>=Ve)break;j[oe++]=192|Ce>>6,j[oe++]=128|Ce&63}else if(Ce<=65535){if(oe+2>=Ve)break;j[oe++]=224|Ce>>12,j[oe++]=128|Ce>>6&63,j[oe++]=128|Ce&63}else{if(oe+3>=Ve)break;j[oe++]=240|Ce>>18,j[oe++]=128|Ce>>12&63,j[oe++]=128|Ce>>6&63,j[oe++]=128|Ce&63}}return j[oe]=0,oe-He}function nt(O,j,oe){return at(O,i(),j,oe)}var Ge,ht,Ga,Ot,ln,ra,_a,un,Pa;C&&(Ge=d.buffer);function ut(O){Ge=O,d.HEAP8=ht=new Int8Array(O),d.HEAP16=Ot=new Int16Array(O),d.HEAP32=ra=new Int32Array(O),d.HEAPU8=Ga=new Uint8Array(O),d.HEAPU16=ln=new Uint16Array(O),d.HEAPU32=_a=new Uint32Array(O),d.HEAPF32=un=new Float32Array(O),d.HEAPF64=Pa=new Float64Array(O)}var Fa=d.INITIAL_MEMORY||16777216;if(C)ie=d.wasmMemory,Ge=d.buffer;else if(d.wasmMemory)ie=d.wasmMemory;else if(ie=new WebAssembly.Memory({initial:Fa/65536,maximum:32768,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"),S&&H("(on node you may need: --experimental-wasm-threads --experimental-wasm-bulk-memory and/or recent version)"),Error("bad memory");ie&&(Ge=ie.buffer),Fa=Ge.byteLength,ut(Ge);var Ha,dr=[],Wo=[],Un=[],$u=!1;function kn(){return ce}function $r(){if(d.preRun)for(typeof d.preRun=="function"&&(d.preRun=[d.preRun]);d.preRun.length;)L0(d.preRun.shift());Pu(dr)}function Xt(){$u=!0,!C&&Pu(Wo)}function Pp(){if(!C){if(d.postRun)for(typeof d.postRun=="function"&&(d.postRun=[d.postRun]);d.postRun.length;)v5(d.postRun.shift());Pu(Un)}}function L0(O){dr.unshift(O)}function B0(O){Wo.unshift(O)}function v5(O){Un.unshift(O)}var _r=0,Vo=null,pr=null;function W0(O){_r++,d.monitorRunDependencies&&d.monitorRunDependencies(_r)}function Fp(O){if(_r--,d.monitorRunDependencies&&d.monitorRunDependencies(_r),_r==0&&(Vo!==null&&(clearInterval(Vo),Vo=null),pr)){var j=pr;pr=null,j()}}function Ts(O){d.onAbort&&d.onAbort(O),O="Aborted("+O+")",H(O),Se=!0,Ne=1,O+=". Build with -sASSERTIONS for more info.";var j=new WebAssembly.RuntimeError(O);throw f(j),j}var V0="data:application/octet-stream;base64,";function Op(O){return O.startsWith(V0)}function Uo(O){return O.startsWith("file://")}var ca;ca="tfjs-backend-wasm-threaded-simd.wasm",Op(ca)||(ca=$(ca));function Dp(O){try{if(O==ca&&ee)return new Uint8Array(ee);if(I)return I(O);throw"both async and sync fetching of the wasm failed"}catch(j){Ts(j)}}function U0(){if(!ee&&(b||k)){if(typeof fetch=="function"&&!Uo(ca))return fetch(ca,{credentials:"same-origin"}).then(function(O){if(!O.ok)throw"failed to load wasm binary file at '"+ca+"'";return O.arrayBuffer()}).catch(function(){return Dp(ca)});if(R)return new Promise(function(O,j){R(ca,function(oe){O(new Uint8Array(oe))},j)})}return Promise.resolve().then(function(){return Dp(ca)})}function G0(){var O={env:Zp,wasi_snapshot_preview1:Zp};function j(he,Ce){var It=he.exports;if(d.asm=It,Q0(d.asm._emscripten_tls_init),Ha=d.asm.__indirect_function_table,B0(d.asm.__wasm_call_ctors),ge=Ce,!C){var pn=We.unusedWorkers.length;We.unusedWorkers.forEach(function(hr){We.loadWasmModuleToWorker(hr,function(){--pn||Fp("wasm-instantiate")})})}}C||W0("wasm-instantiate");function oe(he){j(he.instance,he.module)}function Re(he){return U0().then(function(Ce){return WebAssembly.instantiate(Ce,O)}).then(function(Ce){return Ce}).then(he,function(Ce){H("failed to asynchronously prepare wasm: "+Ce),Ts(Ce)})}function He(){return!ee&&typeof WebAssembly.instantiateStreaming=="function"&&!Op(ca)&&!Uo(ca)&&!S&&typeof fetch=="function"?fetch(ca,{credentials:"same-origin"}).then(function(he){var Ce=WebAssembly.instantiateStreaming(he,O);return Ce.then(oe,function(It){return H("wasm streaming compile failed: "+It),H("falling back to ArrayBuffer instantiation"),Re(oe)})}):Re(oe)}if(d.instantiateWasm)try{var Ve=d.instantiateWasm(O,j);return Ve}catch(he){H("Module.instantiateWasm callback failed with error: "+he),f(he)}return He().catch(f),{}}var k5,w5,zp={};function Cs(O){this.name="ExitStatus",this.message="Program terminated with exit("+O+")",this.status=O}function H0(O){var j=We.pthreads[O];delete We.pthreads[O],j.terminate(),Sm(O),We.runningWorkers.splice(We.runningWorkers.indexOf(j),1),j.pthread_ptr=0}function j0(O){var j=We.pthreads[O];j.postMessage({cmd:"cancel"})}function _u(O){var j=We.pthreads[O];Be(j),We.returnWorkerToPool(j)}function q0(O){var j=We.getNewWorker();if(!j)return 6;We.runningWorkers.push(j),We.pthreads[O.pthread_ptr]=j,j.pthread_ptr=O.pthread_ptr;var oe={cmd:"run",start_routine:O.startRoutine,arg:O.arg,pthread_ptr:O.pthread_ptr};return j.runPthread=()=>{S&&j.ref(),j.postMessage(oe,O.transferList),delete j.runPthread},j.loaded&&j.runPthread(),0}var Lp={varargs:void 0,get:function(){Lp.varargs+=4;var O=l()[Lp.varargs-4>>2];return O},getStr:function(O){var j=it(O);return j}};function Bp(O){if(C)return Pr(1,1,O);Ne=O,kn()||(We.terminateAllThreads(),d.onExit&&d.onExit(O),Se=!0),A(O,new Cs(O))}function X0(O,j){if(Ne=O,!j&&C)throw Vp(O),"unwind";Bp(O)}var Wp=X0;function K0(O){if(O instanceof Cs||O=="unwind")return Ne;A(1,O)}var We={unusedWorkers:[],runningWorkers:[],tlsInitFunctions:[],pthreads:{},init:function(){C?We.initWorker():We.initMainThread()},initMainThread:function(){for(var O=8;O--;)We.allocateUnusedWorker()},initWorker:function(){ce=!1},setExitStatus:function(O){Ne=O},terminateAllThreads:function(){for(var O of Object.values(We.pthreads))We.returnWorkerToPool(O);for(var O of We.unusedWorkers)O.terminate();We.unusedWorkers=[]},returnWorkerToPool:function(O){var j=O.pthread_ptr;delete We.pthreads[j],We.unusedWorkers.push(O),We.runningWorkers.splice(We.runningWorkers.indexOf(O),1),O.pthread_ptr=0,S&&O.unref(),Sm(j)},receiveObjectTransfer:function(O){},threadInitTLS:function(){We.tlsInitFunctions.forEach(O=>O())},loadWasmModuleToWorker:function(O,j){O.onmessage=Ve=>{var he=Ve.data,Ce=he.cmd;if(O.pthread_ptr&&(We.currentProxiedOperationCallerThread=O.pthread_ptr),he.targetThread&&he.targetThread!=ac()){var It=We.pthreads[he.targetThread];It?It.postMessage(he,he.transferList):H('Internal error! Worker sent a message "'+Ce+'" to target pthread '+he.targetThread+", but that thread no longer exists!"),We.currentProxiedOperationCallerThread=void 0;return}Ce==="processProxyingQueue"?Fu(he.queue):Ce==="spawnThread"?q0(he):Ce==="cleanupThread"?_u(he.thread):Ce==="killThread"?H0(he.thread):Ce==="cancelThread"?j0(he.thread):Ce==="loaded"?(O.loaded=!0,S&&O.unref(),j&&j(O),O.runPthread&&O.runPthread()):Ce==="print"?q("Thread "+he.threadId+": "+he.text):Ce==="printErr"?H("Thread "+he.threadId+": "+he.text):Ce==="alert"?alert("Thread "+he.threadId+": "+he.text):he.target==="setimmediate"?O.postMessage(he):Ce==="callHandler"?d[he.handler](...he.args):Ce&&H("worker sent an unknown command "+Ce),We.currentProxiedOperationCallerThread=void 0},O.onerror=Ve=>{var he="worker sent an error!";throw H(he+" "+Ve.filename+":"+Ve.lineno+": "+Ve.message),Ve},S&&(O.on("message",function(Ve){O.onmessage({data:Ve})}),O.on("error",function(Ve){O.onerror(Ve)}),O.on("detachedExit",function(){}));var oe=[],Re=["onExit","onAbort","print","printErr"];for(var He of Re)d.hasOwnProperty(He)&&oe.push(He);O.postMessage({cmd:"load",handlers:oe,urlOrBlob:d.mainScriptUrlOrBlob||n,wasmMemory:ie,wasmModule:ge})},allocateUnusedWorker:function(){var O,j=$("tfjs-backend-wasm-threaded-simd.worker.js");O=new Worker(j),We.unusedWorkers.push(O)},getNewWorker:function(){return We.unusedWorkers.length==0&&(We.allocateUnusedWorker(),We.loadWasmModuleToWorker(We.unusedWorkers[0])),We.unusedWorkers.pop()}};d.PThread=We;function Pu(O){for(;O.length>0;)O.shift()(d)}function Z0(){var O=ac(),j=l()[O+52>>2],oe=l()[O+56>>2],Re=j-oe;E5(j,Re),nc(j)}d.establishStackSpace=Z0;function Vp(O){if(C)return Pr(2,0,O);try{Wp(O)}catch(j){K0(j)}}var Go=[];function Y0(O){var j=Go[O];return j||(O>=Go.length&&(Go.length=O+1),Go[O]=j=Ha.get(O)),j}function J0(O,j){var oe=Y0(O)(j);kn()?We.setExitStatus(oe):N5(oe)}d.invokeEntryPoint=J0;function Q0(O){We.tlsInitFunctions.push(O)}function ef(O){S5(O,!k,1,!b),We.threadInitTLS()}function tf(O){C?postMessage({cmd:"cleanupThread",thread:O}):_u(O)}function Up(O,j,oe,Re){return C?Pr(3,1,O,j,oe,Re):Gp(O,j,oe,Re)}function Gp(O,j,oe,Re){if(typeof SharedArrayBuffer=="undefined")return H("Current environment does not support SharedArrayBuffer, pthreads are not available!"),6;var He=[],Ve=0;if(C&&(He.length===0||Ve))return Up(O,j,oe,Re);if(Ve)return Ve;var he={startRoutine:oe,pthread_ptr:O,arg:Re,transferList:He};return C?(he.cmd="spawnThread",postMessage(he,He),0):q0(he)}function af(){return 65536}var nf=!0;function rf(){return nf}function Fu(O){Atomics.store(l(),O>>2,1),ac()&&C5(O),Atomics.compareExchange(l(),O>>2,1,0)}d.executeNotifiedProxyingQueue=Fu;function sf(O,j,oe,Re){if(O==j)setTimeout(()=>Fu(Re));else if(C)postMessage({targetThread:O,cmd:"processProxyingQueue",queue:Re});else{var He=We.pthreads[O];if(!He)return;He.postMessage({cmd:"processProxyingQueue",queue:Re})}return 1}function of(O,j,oe){return-1}function lf(){Ts("")}function Ns(O){Ns.shown||(Ns.shown={}),Ns.shown[O]||(Ns.shown[O]=1,S&&(O="warning: "+O),H(O))}function uf(){S||k||Ns("Blocking on the main thread is very dangerous, see https://emscripten.org/docs/porting/pthreads.html#blocking-on-the-main-browser-thread")}function df(){return Date.now()}function Hp(){return 2147483648}function pf(){return Hp()}var Ou;S?Ou=()=>{var O=process.hrtime();return O[0]*1e3+O[1]/1e6}:Ou=()=>performance.timeOrigin+performance.now();function cf(O,j,oe){i().copyWithin(O,j,j+oe)}function hf(){return S?tS().cpus().length:navigator.hardwareConcurrency}function ff(O){var j=Tm(),oe=O();return nc(j),oe}function Pr(O,j){var oe=arguments.length-2,Re=arguments;return ff(()=>{for(var He=oe,Ve=rc(He*8),he=Ve>>3,Ce=0;Ce<oe;Ce++){var It=Re[2+Ce];c()[he+Ce]=It}return T5(O,He,Ve,j)})}var Du=[];function mf(O,j,oe){Du.length=j;for(var Re=oe>>3,He=0;He<j;He++)Du[He]=c()[Re+He];var Ve=O<0,he=Ve?zp[-O-1]:If[O];return he.apply(null,Du)}function gf(O){try{return ie.grow(O-Ge.byteLength+65535>>>16),ut(ie.buffer),1}catch(j){}}function yf(O){var j=i().length;if(O=O>>>0,O<=j)return!1;var oe=Hp();if(O>oe)return!1;let Re=(It,pn)=>It+(pn-It%pn)%pn;for(var He=1;He<=4;He*=2){var Ve=j*(1+.2/He);Ve=Math.min(Ve,O+100663296);var he=Math.min(oe,Re(Math.max(O,Ve),65536)),Ce=gf(he);if(Ce)return!0}return!1}function xf(){throw"unwind"}function jp(O){return C?Pr(4,1,O):52}function qp(O,j,oe,Re,He){return C?Pr(5,1,O,j,oe,Re,He):70}var Af=[null,[],[]];function bf(O,j){var oe=Af[O];j===0||j===10?((O===1?q:H)(dt(oe,0)),oe.length=0):oe.push(j)}function Xp(O,j,oe,Re){if(C)return Pr(6,1,O,j,oe,Re);for(var He=0,Ve=0;Ve<oe;Ve++){var he=u()[j>>2],Ce=u()[j+4>>2];j+=8;for(var It=0;It<Ce;It++)bf(O,i()[he+It]);He+=Ce}return u()[Re>>2]=He,0}function Kp(O){var j=d["_"+O];return j}function vf(O,j){s().set(O,j)}function kf(O,j,oe,Re,He){var Ve={string:cn=>{var Xo=0;if(cn!=null&&cn!==0){var $5=(cn.length<<2)+1;Xo=rc($5),nt(cn,Xo,$5)}return Xo},array:cn=>{var Xo=rc(cn.length);return vf(cn,Xo),Xo}};function he(cn){return j==="string"?it(cn):j==="boolean"?Boolean(cn):cn}var Ce=Kp(O),It=[],pn=0;if(Re)for(var hr=0;hr<Re.length;hr++){var M5=Ve[oe[hr]];M5?(pn===0&&(pn=Tm()),It[hr]=M5(Re[hr])):It[hr]=Re[hr]}var Cm=Ce.apply(null,It);function EI(cn){return pn!==0&&nc(pn),he(cn)}return Cm=EI(Cm),Cm}function wf(O,j,oe,Re){oe=oe||[];var He=oe.every(he=>he==="number"||he==="boolean"),Ve=j!=="string";return Ve&&He&&!Re?Kp(O):function(){return kf(O,j,oe,arguments,Re)}}We.init();var If=[null,Bp,Vp,Up,jp,qp,Xp],Zp={__emscripten_init_main_thread_js:ef,__emscripten_thread_cleanup:tf,__pthread_create_js:Gp,_emscripten_default_pthread_stack_size:af,_emscripten_get_now_is_monotonic:rf,_emscripten_notify_task_queue:sf,_emscripten_set_offscreencanvas_size:of,abort:lf,emscripten_check_blocking_allowed:uf,emscripten_date_now:df,emscripten_get_heap_max:pf,emscripten_get_now:Ou,emscripten_memcpy_big:cf,emscripten_num_logical_cores:hf,emscripten_receive_on_main_thread_js:mf,emscripten_resize_heap:yf,emscripten_unwind_to_js_event_loop:xf,exit:Wp,fd_close:jp,fd_seek:qp,fd_write:Xp,memory:ie||d.wasmMemory},I5=G0(),Sf=d.___wasm_call_ctors=function(){return(Sf=d.___wasm_call_ctors=d.asm.__wasm_call_ctors).apply(null,arguments)},Tf=d._init=function(){return(Tf=d._init=d.asm.init).apply(null,arguments)},Cf=d._init_with_threads_count=function(){return(Cf=d._init_with_threads_count=d.asm.init_with_threads_count).apply(null,arguments)},Nf=d._get_threads_count=function(){return(Nf=d._get_threads_count=d.asm.get_threads_count).apply(null,arguments)},Ef=d._register_tensor=function(){return(Ef=d._register_tensor=d.asm.register_tensor).apply(null,arguments)},Rf=d._dispose_data=function(){return(Rf=d._dispose_data=d.asm.dispose_data).apply(null,arguments)},Mf=d._dispose=function(){return(Mf=d._dispose=d.asm.dispose).apply(null,arguments)},$f=d._Abs=function(){return($f=d._Abs=d.asm.Abs).apply(null,arguments)},_f=d._Add=function(){return(_f=d._Add=d.asm.Add).apply(null,arguments)},Pf=d._AddN=function(){return(Pf=d._AddN=d.asm.AddN).apply(null,arguments)},Ff=d._All=function(){return(Ff=d._All=d.asm.All).apply(null,arguments)},Of=d._Any=function(){return(Of=d._Any=d.asm.Any).apply(null,arguments)},Df=d._ArgMax=function(){return(Df=d._ArgMax=d.asm.ArgMax).apply(null,arguments)},zf=d._AvgPool=function(){return(zf=d._AvgPool=d.asm.AvgPool).apply(null,arguments)},Lf=d._BatchMatMul=function(){return(Lf=d._BatchMatMul=d.asm.BatchMatMul).apply(null,arguments)},Bf=d._Ceil=function(){return(Bf=d._Ceil=d.asm.Ceil).apply(null,arguments)},Wf=d._ClipByValue=function(){return(Wf=d._ClipByValue=d.asm.ClipByValue).apply(null,arguments)},Vf=d._Conv2D=function(){return(Vf=d._Conv2D=d.asm.Conv2D).apply(null,arguments)},Uf=d._Conv2DBackpropInput=function(){return(Uf=d._Conv2DBackpropInput=d.asm.Conv2DBackpropInput).apply(null,arguments)},Gf=d._Cos=function(){return(Gf=d._Cos=d.asm.Cos).apply(null,arguments)},Hf=d._Cosh=function(){return(Hf=d._Cosh=d.asm.Cosh).apply(null,arguments)},jf=d._CropAndResize=function(){return(jf=d._CropAndResize=d.asm.CropAndResize).apply(null,arguments)},qf=d._Cumprod=function(){return(qf=d._Cumprod=d.asm.Cumprod).apply(null,arguments)},Xf=d._Cumsum=function(){return(Xf=d._Cumsum=d.asm.Cumsum).apply(null,arguments)},Kf=d._DepthToSpace=function(){return(Kf=d._DepthToSpace=d.asm.DepthToSpace).apply(null,arguments)},Zf=d._DepthwiseConv2dNative=function(){return(Zf=d._DepthwiseConv2dNative=d.asm.DepthwiseConv2dNative).apply(null,arguments)},Yf=d._Elu=function(){return(Yf=d._Elu=d.asm.Elu).apply(null,arguments)},Jf=d._Equal=function(){return(Jf=d._Equal=d.asm.Equal).apply(null,arguments)},Qf=d._Exp=function(){return(Qf=d._Exp=d.asm.Exp).apply(null,arguments)},em=d._FlipLeftRight=function(){return(em=d._FlipLeftRight=d.asm.FlipLeftRight).apply(null,arguments)},tm=d._Floor=function(){return(tm=d._Floor=d.asm.Floor).apply(null,arguments)},am=d._FloorDiv=function(){return(am=d._FloorDiv=d.asm.FloorDiv).apply(null,arguments)},nm=d._FusedBatchNorm=function(){return(nm=d._FusedBatchNorm=d.asm.FusedBatchNorm).apply(null,arguments)},rm=d._FusedConv2D=function(){return(rm=d._FusedConv2D=d.asm.FusedConv2D).apply(null,arguments)},sm=d._FusedDepthwiseConv2D=function(){return(sm=d._FusedDepthwiseConv2D=d.asm.FusedDepthwiseConv2D).apply(null,arguments)},im=d._Gather=function(){return(im=d._Gather=d.asm.Gather).apply(null,arguments)},om=d._GatherNd=function(){return(om=d._GatherNd=d.asm.GatherNd).apply(null,arguments)},lm=d._Greater=function(){return(lm=d._Greater=d.asm.Greater).apply(null,arguments)},um=d._GreaterEqual=function(){return(um=d._GreaterEqual=d.asm.GreaterEqual).apply(null,arguments)},dm=d._IsNan=function(){return(dm=d._IsNan=d.asm.IsNan).apply(null,arguments)},pm=d._LeakyRelu=function(){return(pm=d._LeakyRelu=d.asm.LeakyRelu).apply(null,arguments)},cm=d._Less=function(){return(cm=d._Less=d.asm.Less).apply(null,arguments)},hm=d._LessEqual=function(){return(hm=d._LessEqual=d.asm.LessEqual).apply(null,arguments)},fm=d._Log=function(){return(fm=d._Log=d.asm.Log).apply(null,arguments)},mm=d._LogicalAnd=function(){return(mm=d._LogicalAnd=d.asm.LogicalAnd).apply(null,arguments)},gm=d._LogicalNot=function(){return(gm=d._LogicalNot=d.asm.LogicalNot).apply(null,arguments)},ym=d._LogicalOr=function(){return(ym=d._LogicalOr=d.asm.LogicalOr).apply(null,arguments)},xm=d._LogicalXor=function(){return(xm=d._LogicalXor=d.asm.LogicalXor).apply(null,arguments)},Am=d._Max=function(){return(Am=d._Max=d.asm.Max).apply(null,arguments)},bm=d._MaxPool=function(){return(bm=d._MaxPool=d.asm.MaxPool).apply(null,arguments)},Yp=d._Maximum=function(){return(Yp=d._Maximum=d.asm.Maximum).apply(null,arguments)},Jp=d._Mean=function(){return(Jp=d._Mean=d.asm.Mean).apply(null,arguments)},zu=d._Min=function(){return(zu=d._Min=d.asm.Min).apply(null,arguments)},vm=d._Minimum=function(){return(vm=d._Minimum=d.asm.Minimum).apply(null,arguments)},km=d._MirrorPad=function(){return(km=d._MirrorPad=d.asm.MirrorPad).apply(null,arguments)},Ho=d._Multiply=function(){return(Ho=d._Multiply=d.asm.Multiply).apply(null,arguments)},Qp=d._Neg=function(){return(Qp=d._Neg=d.asm.Neg).apply(null,arguments)},jo=d._NonMaxSuppressionV3=function(){return(jo=d._NonMaxSuppressionV3=d.asm.NonMaxSuppressionV3).apply(null,arguments)},qo=d._NonMaxSuppressionV4=function(){return(qo=d._NonMaxSuppressionV4=d.asm.NonMaxSuppressionV4).apply(null,arguments)},wm=d._NonMaxSuppressionV5=function(){return(wm=d._NonMaxSuppressionV5=d.asm.NonMaxSuppressionV5).apply(null,arguments)},Y=d._NotEqual=function(){return(Y=d._NotEqual=d.asm.NotEqual).apply(null,arguments)},se=d._OneHot=function(){return(se=d._OneHot=d.asm.OneHot).apply(null,arguments)},Ee=d._PadV2=function(){return(Ee=d._PadV2=d.asm.PadV2).apply(null,arguments)},Je=d._Pow=function(){return(Je=d._Pow=d.asm.Pow).apply(null,arguments)},At=d._Prelu=function(){return(At=d._Prelu=d.asm.Prelu).apply(null,arguments)},bt=d._Prod=function(){return(bt=d._Prod=d.asm.Prod).apply(null,arguments)},Ye=d._RealDiv=function(){return(Ye=d._RealDiv=d.asm.RealDiv).apply(null,arguments)},Ke=d._Reciprocal=function(){return(Ke=d._Reciprocal=d.asm.Reciprocal).apply(null,arguments)},Dt=d._Relu=function(){return(Dt=d._Relu=d.asm.Relu).apply(null,arguments)},dn=d._Relu6=function(){return(dn=d._Relu6=d.asm.Relu6).apply(null,arguments)},cr=d._ResizeBilinear=function(){return(cr=d._ResizeBilinear=d.asm.ResizeBilinear).apply(null,arguments)},ec=d._ResizeNearestNeighbor=function(){return(ec=d._ResizeNearestNeighbor=d.asm.ResizeNearestNeighbor).apply(null,arguments)},Lu=d._Reverse=function(){return(Lu=d._Reverse=d.asm.Reverse).apply(null,arguments)},Im=d._RotateWithOffset=function(){return(Im=d._RotateWithOffset=d.asm.RotateWithOffset).apply(null,arguments)},Oa=d._Round=function(){return(Oa=d._Round=d.asm.Round).apply(null,arguments)},Fr=d._Rsqrt=function(){return(Fr=d._Rsqrt=d.asm.Rsqrt).apply(null,arguments)},tc=d._ScatterNd=function(){return(tc=d._ScatterNd=d.asm.ScatterNd).apply(null,arguments)},Yw=d._SelectV2=function(){return(Yw=d._SelectV2=d.asm.SelectV2).apply(null,arguments)},Jw=d._Sigmoid=function(){return(Jw=d._Sigmoid=d.asm.Sigmoid).apply(null,arguments)},Qw=d._Sin=function(){return(Qw=d._Sin=d.asm.Sin).apply(null,arguments)},eI=d._Softmax=function(){return(eI=d._Softmax=d.asm.Softmax).apply(null,arguments)},tI=d._SparseFillEmptyRows=function(){return(tI=d._SparseFillEmptyRows=d.asm.SparseFillEmptyRows).apply(null,arguments)},aI=d._SparseReshape=function(){return(aI=d._SparseReshape=d.asm.SparseReshape).apply(null,arguments)},nI=d._SparseSegmentReduction=function(){return(nI=d._SparseSegmentReduction=d.asm.SparseSegmentReduction).apply(null,arguments)},rI=d._Sqrt=function(){return(rI=d._Sqrt=d.asm.Sqrt).apply(null,arguments)},sI=d._Square=function(){return(sI=d._Square=d.asm.Square).apply(null,arguments)},iI=d._SquaredDifference=function(){return(iI=d._SquaredDifference=d.asm.SquaredDifference).apply(null,arguments)},oI=d._Step=function(){return(oI=d._Step=d.asm.Step).apply(null,arguments)},lI=d._StridedSlice=function(){return(lI=d._StridedSlice=d.asm.StridedSlice).apply(null,arguments)},uI=d._Sub=function(){return(uI=d._Sub=d.asm.Sub).apply(null,arguments)},dI=d._Sum=function(){return(dI=d._Sum=d.asm.Sum).apply(null,arguments)},pI=d._Tan=function(){return(pI=d._Tan=d.asm.Tan).apply(null,arguments)},cI=d._Tanh=function(){return(cI=d._Tanh=d.asm.Tanh).apply(null,arguments)},hI=d._Tile=function(){return(hI=d._Tile=d.asm.Tile).apply(null,arguments)},fI=d._TopK=function(){return(fI=d._TopK=d.asm.TopK).apply(null,arguments)},mI=d._Transform=function(){return(mI=d._Transform=d.asm.Transform).apply(null,arguments)},gI=d._Transpose=function(){return(gI=d._Transpose=d.asm.Transpose).apply(null,arguments)},yI=d.__FusedMatMul=function(){return(yI=d.__FusedMatMul=d.asm._FusedMatMul).apply(null,arguments)},xI=d._malloc=function(){return(xI=d._malloc=d.asm.malloc).apply(null,arguments)},AI=d._free=function(){return(AI=d._free=d.asm.free).apply(null,arguments)},bI=d.__emscripten_tls_init=function(){return(bI=d.__emscripten_tls_init=d.asm._emscripten_tls_init).apply(null,arguments)},ac=d._pthread_self=function(){return(ac=d._pthread_self=d.asm.pthread_self).apply(null,arguments)},vI=d.___errno_location=function(){return(vI=d.___errno_location=d.asm.__errno_location).apply(null,arguments)},S5=d.__emscripten_thread_init=function(){return(S5=d.__emscripten_thread_init=d.asm._emscripten_thread_init).apply(null,arguments)},kI=d.__emscripten_thread_crashed=function(){return(kI=d.__emscripten_thread_crashed=d.asm._emscripten_thread_crashed).apply(null,arguments)},wI=d._emscripten_main_thread_process_queued_calls=function(){return(wI=d._emscripten_main_thread_process_queued_calls=d.asm.emscripten_main_thread_process_queued_calls).apply(null,arguments)},II=d._emscripten_main_browser_thread_id=function(){return(II=d._emscripten_main_browser_thread_id=d.asm.emscripten_main_browser_thread_id).apply(null,arguments)},T5=d._emscripten_run_in_main_runtime_thread_js=function(){return(T5=d._emscripten_run_in_main_runtime_thread_js=d.asm.emscripten_run_in_main_runtime_thread_js).apply(null,arguments)},SI=d._emscripten_dispatch_to_thread_=function(){return(SI=d._emscripten_dispatch_to_thread_=d.asm.emscripten_dispatch_to_thread_).apply(null,arguments)},C5=d.__emscripten_proxy_execute_task_queue=function(){return(C5=d.__emscripten_proxy_execute_task_queue=d.asm._emscripten_proxy_execute_task_queue).apply(null,arguments)},Sm=d.__emscripten_thread_free_data=function(){return(Sm=d.__emscripten_thread_free_data=d.asm._emscripten_thread_free_data).apply(null,arguments)},N5=d.__emscripten_thread_exit=function(){return(N5=d.__emscripten_thread_exit=d.asm._emscripten_thread_exit).apply(null,arguments)},E5=d._emscripten_stack_set_limits=function(){return(E5=d._emscripten_stack_set_limits=d.asm.emscripten_stack_set_limits).apply(null,arguments)},Tm=d.stackSave=function(){return(Tm=d.stackSave=d.asm.stackSave).apply(null,arguments)},nc=d.stackRestore=function(){return(nc=d.stackRestore=d.asm.stackRestore).apply(null,arguments)},rc=d.stackAlloc=function(){return(rc=d.stackAlloc=d.asm.stackAlloc).apply(null,arguments)},TI=d.dynCall_iijjiiii=function(){return(TI=d.dynCall_iijjiiii=d.asm.dynCall_iijjiiii).apply(null,arguments)},CI=d.dynCall_jiji=function(){return(CI=d.dynCall_jiji=d.asm.dynCall_jiji).apply(null,arguments)};d.keepRuntimeAlive=kn,d.wasmMemory=ie,d.cwrap=wf,d.ExitStatus=Cs,d.PThread=We;var sc;pr=function O(){sc||R5(),sc||(pr=O)};function R5(O){if(O=O||y,_r>0)return;if(C){h(d),Xt(),startWorker(d);return}if($r(),_r>0)return;function j(){sc||(sc=!0,d.calledRun=!0,!Se&&(Xt(),h(d),d.onRuntimeInitialized&&d.onRuntimeInitialized(),Pp()))}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()();R5();var ic;m&&(ic={uncaughtException:process.listeners("uncaughtException").filter(function(O){return!m.uncaughtException.indexOf(O)>-1}),unhandledRejection:process.listeners("unhandledRejection").filter(function(O){return!m.unhandledRejection.indexOf(O)>-1})});var oc;if(typeof WasmBackendModule!="undefined")oc=WasmBackendModule;else if(typeof r!="undefined")oc=r;else throw new Error("Could not find wasm module in post.js");if(ic){var NI=oc._dispose;oc._dispose=function(){NI(),ic.uncaughtException.forEach(function(O){process.removeListener("uncaughtException",O)}),ic.unhandledRejection.forEach(function(O){process.removeListener("unhandledRejection",O)})}}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)}),nS=qt((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}};`}),rS=qt((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",f=typeof importScripts=="function",m=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,k;function S(Y){Y instanceof Vo||M("exiting due to exception: "+Y)}if(m){var C=ex(),N=tx();f?g=N.dirname(g)+"/":g=__dirname+"/",x=(Y,se)=>(Y=$r(Y)?new URL(Y):N.normalize(Y),C.readFileSync(Y,se?void 0:"utf8")),b=Y=>{var se=x(Y,!0);return se.buffer||(se=new Uint8Array(se)),se},A=(Y,se,Ee)=>{Y=$r(Y)?new URL(Y):N.normalize(Y),C.readFile(Y,function(Je,At){Je?Ee(Je):se(At.buffer)})},process.argv.length>1&&(c=process.argv[1].replace(/\\/g,"/")),p=process.argv.slice(2),process.on("uncaughtException",function(Y){if(!(Y instanceof Vo))throw Y}),process.on("unhandledRejection",function(Y){throw Y}),d=(Y,se)=>{if(Ga())throw process.exitCode=Y,se;S(se),process.exit(Y)},s.inspect=function(){return"[Emscripten Module object]"}}else(h||f)&&(f?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},f&&(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 Je=new XMLHttpRequest;Je.open("GET",Y,!0),Je.responseType="arraybuffer",Je.onload=()=>{if(Je.status==200||Je.status==0&&Je.response){se(Je.response);return}Ee()},Je.onerror=Ee,Je.send(null)},k=Y=>document.title=Y);var $=s.print||console.log.bind(console),M=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 R=4,I;s.wasmBinary&&(I=s.wasmBinary);var _=s.noExitRuntime||!0;typeof WebAssembly!="object"&&Un("no native wasm support detected");var D,W=!1,P;function U(Y,se){Y||Un(se)}var G=typeof TextDecoder!="undefined"?new TextDecoder("utf8"):void 0;function q(Y,se,Ee){for(var Je=se+Ee,At=se;Y[At]&&!(At>=Je);)++At;if(At-se>16&&Y.buffer&&G)return G.decode(Y.subarray(se,At));for(var bt="";se<At;){var Ye=Y[se++];if(!(Ye&128)){bt+=String.fromCharCode(Ye);continue}var Ke=Y[se++]&63;if((Ye&224)==192){bt+=String.fromCharCode((Ye&31)<<6|Ke);continue}var Dt=Y[se++]&63;if((Ye&240)==224?Ye=(Ye&15)<<12|Ke<<6|Dt:Ye=(Ye&7)<<18|Ke<<12|Dt<<6|Y[se++]&63,Ye<65536)bt+=String.fromCharCode(Ye);else{var dn=Ye-65536;bt+=String.fromCharCode(55296|dn>>10,56320|dn&1023)}}return bt}function H(Y,se){return Y?q(ee,Y,se):""}function B(Y,se,Ee,Je){if(!(Je>0))return 0;for(var At=Ee,bt=Ee+Je-1,Ye=0;Ye<Y.length;++Ye){var Ke=Y.charCodeAt(Ye);if(Ke>=55296&&Ke<=57343){var Dt=Y.charCodeAt(++Ye);Ke=65536+((Ke&1023)<<10)|Dt&1023}if(Ke<=127){if(Ee>=bt)break;se[Ee++]=Ke}else if(Ke<=2047){if(Ee+1>=bt)break;se[Ee++]=192|Ke>>6,se[Ee++]=128|Ke&63}else if(Ke<=65535){if(Ee+2>=bt)break;se[Ee++]=224|Ke>>12,se[Ee++]=128|Ke>>6&63,se[Ee++]=128|Ke&63}else{if(Ee+3>=bt)break;se[Ee++]=240|Ke>>18,se[Ee++]=128|Ke>>12&63,se[Ee++]=128|Ke>>6&63,se[Ee++]=128|Ke&63}}return se[Ee]=0,Ee-At}function Z(Y,se,Ee){return B(Y,ee,se,Ee)}var X,re,ee,ce,ie,ge,Se,Ne,Be;function qe(Y){X=Y,s.HEAP8=re=new Int8Array(Y),s.HEAP16=ce=new Int16Array(Y),s.HEAP32=ge=new Int32Array(Y),s.HEAPU8=ee=new Uint8Array(Y),s.HEAPU16=ie=new Uint16Array(Y),s.HEAPU32=Se=new Uint32Array(Y),s.HEAPF32=Ne=new Float32Array(Y),s.HEAPF64=Be=new Float64Array(Y)}var dt=s.INITIAL_MEMORY||16777216,it,at=[],nt=[],Ge=[],ht=!1;function Ga(){return _}function Ot(){if(s.preRun)for(typeof s.preRun=="function"&&(s.preRun=[s.preRun]);s.preRun.length;)_a(s.preRun.shift());pr(at)}function ln(){ht=!0,pr(nt)}function ra(){if(s.postRun)for(typeof s.postRun=="function"&&(s.postRun=[s.postRun]);s.postRun.length;)Pa(s.postRun.shift());pr(Ge)}function _a(Y){at.unshift(Y)}function un(Y){nt.unshift(Y)}function Pa(Y){Ge.unshift(Y)}var ut=0,Fa=null,Ha=null;function dr(Y){ut++,s.monitorRunDependencies&&s.monitorRunDependencies(ut)}function Wo(Y){if(ut--,s.monitorRunDependencies&&s.monitorRunDependencies(ut),ut==0&&(Fa!==null&&(clearInterval(Fa),Fa=null),Ha)){var se=Ha;Ha=null,se()}}function Un(Y){s.onAbort&&s.onAbort(Y),Y="Aborted("+Y+")",M(Y),W=!0,P=1,Y+=". Build with -sASSERTIONS for more info.";var se=new WebAssembly.RuntimeError(Y);throw o(se),se}var $u="data:application/octet-stream;base64,";function kn(Y){return Y.startsWith($u)}function $r(Y){return Y.startsWith("file://")}var Xt;Xt="tfjs-backend-wasm.wasm",kn(Xt)||(Xt=y(Xt));function Pp(Y){try{if(Y==Xt&&I)return new Uint8Array(I);if(b)return b(Y);throw"both async and sync fetching of the wasm failed"}catch(se){Un(se)}}function L0(){if(!I&&(h||f)){if(typeof fetch=="function"&&!$r(Xt))return fetch(Xt,{credentials:"same-origin"}).then(function(Y){if(!Y.ok)throw"failed to load wasm binary file at '"+Xt+"'";return Y.arrayBuffer()}).catch(function(){return Pp(Xt)});if(A)return new Promise(function(Y,se){A(Xt,function(Ee){Y(new Uint8Array(Ee))},se)})}return Promise.resolve().then(function(){return Pp(Xt)})}function B0(){var Y={env:_u,wasi_snapshot_preview1:_u};function se(Ye,Ke){var Dt=Ye.exports;s.asm=Dt,D=s.asm.memory,qe(D.buffer),it=s.asm.__indirect_function_table,un(s.asm.__wasm_call_ctors),Wo("wasm-instantiate")}dr("wasm-instantiate");function Ee(Ye){se(Ye.instance)}function Je(Ye){return L0().then(function(Ke){return WebAssembly.instantiate(Ke,Y)}).then(function(Ke){return Ke}).then(Ye,function(Ke){M("failed to asynchronously prepare wasm: "+Ke),Un(Ke)})}function At(){return!I&&typeof WebAssembly.instantiateStreaming=="function"&&!kn(Xt)&&!$r(Xt)&&!m&&typeof fetch=="function"?fetch(Xt,{credentials:"same-origin"}).then(function(Ye){var Ke=WebAssembly.instantiateStreaming(Ye,Y);return Ke.then(Ee,function(Dt){return M("wasm streaming compile failed: "+Dt),M("falling back to ArrayBuffer instantiation"),Je(Ee)})}):Je(Ee)}if(s.instantiateWasm)try{var bt=s.instantiateWasm(Y,se);return bt}catch(Ye){M("Module.instantiateWasm callback failed with error: "+Ye),o(Ye)}return At().catch(o),{}}var v5,_r;function Vo(Y){this.name="ExitStatus",this.message="Program terminated with exit("+Y+")",this.status=Y}function pr(Y){for(;Y.length>0;)Y.shift()(s)}function W0(){Un("")}function Fp(){return 2147483648}function Ts(){return Fp()}function V0(Y,se,Ee){ee.copyWithin(Y,se,se+Ee)}function Op(Y){try{return D.grow(Y-X.byteLength+65535>>>16),qe(D.buffer),1}catch(se){}}function Uo(Y){var se=ee.length;Y=Y>>>0;var Ee=Fp();if(Y>Ee)return!1;let Je=(Dt,dn)=>Dt+(dn-Dt%dn)%dn;for(var At=1;At<=4;At*=2){var bt=se*(1+.2/At);bt=Math.min(bt,Y+100663296);var Ye=Math.min(Ee,Je(Math.max(Y,bt),65536)),Ke=Op(Ye);if(Ke)return!0}return!1}var ca={varargs:void 0,get:function(){ca.varargs+=4;var Y=ge[ca.varargs-4>>2];return Y},getStr:function(Y){var se=H(Y);return se}};function Dp(Y){return 52}function U0(Y,se,Ee,Je,At){return 70}var G0=[null,[],[]];function k5(Y,se){var Ee=G0[Y];se===0||se===10?((Y===1?$:M)(q(Ee,0)),Ee.length=0):Ee.push(se)}function w5(Y,se,Ee,Je){for(var At=0,bt=0;bt<Ee;bt++){var Ye=Se[se>>2],Ke=Se[se+4>>2];se+=8;for(var Dt=0;Dt<Ke;Dt++)k5(Y,ee[Ye+Dt]);At+=Ke}return Se[Je>>2]=At,0}function zp(Y){var se=s["_"+Y];return se}function Cs(Y,se){re.set(Y,se)}function H0(Y,se,Ee,Je,At){var bt={string:Oa=>{var Fr=0;if(Oa!=null&&Oa!==0){var tc=(Oa.length<<2)+1;Fr=zu(tc),Z(Oa,Fr,tc)}return Fr},array:Oa=>{var Fr=zu(Oa.length);return Cs(Oa,Fr),Fr}};function Ye(Oa){return se==="string"?H(Oa):se==="boolean"?Boolean(Oa):Oa}var Ke=zp(Y),Dt=[],dn=0;if(Je)for(var cr=0;cr<Je.length;cr++){var ec=bt[Ee[cr]];ec?(dn===0&&(dn=Yp()),Dt[cr]=ec(Je[cr])):Dt[cr]=Je[cr]}var Lu=Ke.apply(null,Dt);function Im(Oa){return dn!==0&&Jp(dn),Ye(Oa)}return Lu=Im(Lu),Lu}function j0(Y,se,Ee,Je){Ee=Ee||[];var At=Ee.every(Ye=>Ye==="number"||Ye==="boolean"),bt=se!=="string";return bt&&At&&!Je?zp(Y):function(){return H0(Y,se,Ee,arguments,Je)}}var _u={abort:W0,emscripten_get_heap_max:Ts,emscripten_memcpy_big:V0,emscripten_resize_heap:Uo,fd_close:Dp,fd_seek:U0,fd_write:w5},q0=B0(),Lp=s.___wasm_call_ctors=function(){return(Lp=s.___wasm_call_ctors=s.asm.__wasm_call_ctors).apply(null,arguments)},Bp=s._init=function(){return(Bp=s._init=s.asm.init).apply(null,arguments)},X0=s._init_with_threads_count=function(){return(X0=s._init_with_threads_count=s.asm.init_with_threads_count).apply(null,arguments)},Wp=s._get_threads_count=function(){return(Wp=s._get_threads_count=s.asm.get_threads_count).apply(null,arguments)},K0=s._register_tensor=function(){return(K0=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)},Pu=s._dispose=function(){return(Pu=s._dispose=s.asm.dispose).apply(null,arguments)},Z0=s._Abs=function(){return(Z0=s._Abs=s.asm.Abs).apply(null,arguments)},Vp=s._Add=function(){return(Vp=s._Add=s.asm.Add).apply(null,arguments)},Go=s._AddN=function(){return(Go=s._AddN=s.asm.AddN).apply(null,arguments)},Y0=s._All=function(){return(Y0=s._All=s.asm.All).apply(null,arguments)},J0=s._Any=function(){return(J0=s._Any=s.asm.Any).apply(null,arguments)},Q0=s._ArgMax=function(){return(Q0=s._ArgMax=s.asm.ArgMax).apply(null,arguments)},ef=s._AvgPool=function(){return(ef=s._AvgPool=s.asm.AvgPool).apply(null,arguments)},tf=s._BatchMatMul=function(){return(tf=s._BatchMatMul=s.asm.BatchMatMul).apply(null,arguments)},Up=s._Ceil=function(){return(Up=s._Ceil=s.asm.Ceil).apply(null,arguments)},Gp=s._ClipByValue=function(){return(Gp=s._ClipByValue=s.asm.ClipByValue).apply(null,arguments)},af=s._Conv2D=function(){return(af=s._Conv2D=s.asm.Conv2D).apply(null,arguments)},nf=s._Conv2DBackpropInput=function(){return(nf=s._Conv2DBackpropInput=s.asm.Conv2DBackpropInput).apply(null,arguments)},rf=s._Cos=function(){return(rf=s._Cos=s.asm.Cos).apply(null,arguments)},Fu=s._Cosh=function(){return(Fu=s._Cosh=s.asm.Cosh).apply(null,arguments)},sf=s._CropAndResize=function(){return(sf=s._CropAndResize=s.asm.CropAndResize).apply(null,arguments)},of=s._Cumprod=function(){return(of=s._Cumprod=s.asm.Cumprod).apply(null,arguments)},lf=s._Cumsum=function(){return(lf=s._Cumsum=s.asm.Cumsum).apply(null,arguments)},Ns=s._DepthToSpace=function(){return(Ns=s._DepthToSpace=s.asm.DepthToSpace).apply(null,arguments)},uf=s._DepthwiseConv2dNative=function(){return(uf=s._DepthwiseConv2dNative=s.asm.DepthwiseConv2dNative).apply(null,arguments)},df=s._Elu=function(){return(df=s._Elu=s.asm.Elu).apply(null,arguments)},Hp=s._Equal=function(){return(Hp=s._Equal=s.asm.Equal).apply(null,arguments)},pf=s._Exp=function(){return(pf=s._Exp=s.asm.Exp).apply(null,arguments)},Ou=s._FlipLeftRight=function(){return(Ou=s._FlipLeftRight=s.asm.FlipLeftRight).apply(null,arguments)},cf=s._Floor=function(){return(cf=s._Floor=s.asm.Floor).apply(null,arguments)},hf=s._FloorDiv=function(){return(hf=s._FloorDiv=s.asm.FloorDiv).apply(null,arguments)},ff=s._FusedBatchNorm=function(){return(ff=s._FusedBatchNorm=s.asm.FusedBatchNorm).apply(null,arguments)},Pr=s._FusedConv2D=function(){return(Pr=s._FusedConv2D=s.asm.FusedConv2D).apply(null,arguments)},Du=s._FusedDepthwiseConv2D=function(){return(Du=s._FusedDepthwiseConv2D=s.asm.FusedDepthwiseConv2D).apply(null,arguments)},mf=s._Gather=function(){return(mf=s._Gather=s.asm.Gather).apply(null,arguments)},gf=s._GatherNd=function(){return(gf=s._GatherNd=s.asm.GatherNd).apply(null,arguments)},yf=s._Greater=function(){return(yf=s._Greater=s.asm.Greater).apply(null,arguments)},xf=s._GreaterEqual=function(){return(xf=s._GreaterEqual=s.asm.GreaterEqual).apply(null,arguments)},jp=s._IsNan=function(){return(jp=s._IsNan=s.asm.IsNan).apply(null,arguments)},qp=s._LeakyRelu=function(){return(qp=s._LeakyRelu=s.asm.LeakyRelu).apply(null,arguments)},Af=s._Less=function(){return(Af=s._Less=s.asm.Less).apply(null,arguments)},bf=s._LessEqual=function(){return(bf=s._LessEqual=s.asm.LessEqual).apply(null,arguments)},Xp=s._Log=function(){return(Xp=s._Log=s.asm.Log).apply(null,arguments)},Kp=s._LogicalAnd=function(){return(Kp=s._LogicalAnd=s.asm.LogicalAnd).apply(null,arguments)},vf=s._LogicalNot=function(){return(vf=s._LogicalNot=s.asm.LogicalNot).apply(null,arguments)},kf=s._LogicalOr=function(){return(kf=s._LogicalOr=s.asm.LogicalOr).apply(null,arguments)},wf=s._LogicalXor=function(){return(wf=s._LogicalXor=s.asm.LogicalXor).apply(null,arguments)},If=s._Max=function(){return(If=s._Max=s.asm.Max).apply(null,arguments)},Zp=s._MaxPool=function(){return(Zp=s._MaxPool=s.asm.MaxPool).apply(null,arguments)},I5=s._Maximum=function(){return(I5=s._Maximum=s.asm.Maximum).apply(null,arguments)},Sf=s._Mean=function(){return(Sf=s._Mean=s.asm.Mean).apply(null,arguments)},Tf=s._Min=function(){return(Tf=s._Min=s.asm.Min).apply(null,arguments)},Cf=s._Minimum=function(){return(Cf=s._Minimum=s.asm.Minimum).apply(null,arguments)},Nf=s._MirrorPad=function(){return(Nf=s._MirrorPad=s.asm.MirrorPad).apply(null,arguments)},Ef=s._Multiply=function(){return(Ef=s._Multiply=s.asm.Multiply).apply(null,arguments)},Rf=s._Neg=function(){return(Rf=s._Neg=s.asm.Neg).apply(null,arguments)},Mf=s._NonMaxSuppressionV3=function(){return(Mf=s._NonMaxSuppressionV3=s.asm.NonMaxSuppressionV3).apply(null,arguments)},$f=s._NonMaxSuppressionV4=function(){return($f=s._NonMaxSuppressionV4=s.asm.NonMaxSuppressionV4).apply(null,arguments)},_f=s._NonMaxSuppressionV5=function(){return(_f=s._NonMaxSuppressionV5=s.asm.NonMaxSuppressionV5).apply(null,arguments)},Pf=s._NotEqual=function(){return(Pf=s._NotEqual=s.asm.NotEqual).apply(null,arguments)},Ff=s._OneHot=function(){return(Ff=s._OneHot=s.asm.OneHot).apply(null,arguments)},Of=s._PadV2=function(){return(Of=s._PadV2=s.asm.PadV2).apply(null,arguments)},Df=s._Pow=function(){return(Df=s._Pow=s.asm.Pow).apply(null,arguments)},zf=s._Prelu=function(){return(zf=s._Prelu=s.asm.Prelu).apply(null,arguments)},Lf=s._Prod=function(){return(Lf=s._Prod=s.asm.Prod).apply(null,arguments)},Bf=s._RealDiv=function(){return(Bf=s._RealDiv=s.asm.RealDiv).apply(null,arguments)},Wf=s._Reciprocal=function(){return(Wf=s._Reciprocal=s.asm.Reciprocal).apply(null,arguments)},Vf=s._Relu=function(){return(Vf=s._Relu=s.asm.Relu).apply(null,arguments)},Uf=s._Relu6=function(){return(Uf=s._Relu6=s.asm.Relu6).apply(null,arguments)},Gf=s._ResizeBilinear=function(){return(Gf=s._ResizeBilinear=s.asm.ResizeBilinear).apply(null,arguments)},Hf=s._ResizeNearestNeighbor=function(){return(Hf=s._ResizeNearestNeighbor=s.asm.ResizeNearestNeighbor).apply(null,arguments)},jf=s._Reverse=function(){return(jf=s._Reverse=s.asm.Reverse).apply(null,arguments)},qf=s._RotateWithOffset=function(){return(qf=s._RotateWithOffset=s.asm.RotateWithOffset).apply(null,arguments)},Xf=s._Round=function(){return(Xf=s._Round=s.asm.Round).apply(null,arguments)},Kf=s._Rsqrt=function(){return(Kf=s._Rsqrt=s.asm.Rsqrt).apply(null,arguments)},Zf=s._ScatterNd=function(){return(Zf=s._ScatterNd=s.asm.ScatterNd).apply(null,arguments)},Yf=s._SelectV2=function(){return(Yf=s._SelectV2=s.asm.SelectV2).apply(null,arguments)},Jf=s._Sigmoid=function(){return(Jf=s._Sigmoid=s.asm.Sigmoid).apply(null,arguments)},Qf=s._Sin=function(){return(Qf=s._Sin=s.asm.Sin).apply(null,arguments)},em=s._Softmax=function(){return(em=s._Softmax=s.asm.Softmax).apply(null,arguments)},tm=s._SparseFillEmptyRows=function(){return(tm=s._SparseFillEmptyRows=s.asm.SparseFillEmptyRows).apply(null,arguments)},am=s._SparseReshape=function(){return(am=s._SparseReshape=s.asm.SparseReshape).apply(null,arguments)},nm=s._SparseSegmentReduction=function(){return(nm=s._SparseSegmentReduction=s.asm.SparseSegmentReduction).apply(null,arguments)},rm=s._Sqrt=function(){return(rm=s._Sqrt=s.asm.Sqrt).apply(null,arguments)},sm=s._Square=function(){return(sm=s._Square=s.asm.Square).apply(null,arguments)},im=s._SquaredDifference=function(){return(im=s._SquaredDifference=s.asm.SquaredDifference).apply(null,arguments)},om=s._Step=function(){return(om=s._Step=s.asm.Step).apply(null,arguments)},lm=s._StridedSlice=function(){return(lm=s._StridedSlice=s.asm.StridedSlice).apply(null,arguments)},um=s._Sub=function(){return(um=s._Sub=s.asm.Sub).apply(null,arguments)},dm=s._Sum=function(){return(dm=s._Sum=s.asm.Sum).apply(null,arguments)},pm=s._Tan=function(){return(pm=s._Tan=s.asm.Tan).apply(null,arguments)},cm=s._Tanh=function(){return(cm=s._Tanh=s.asm.Tanh).apply(null,arguments)},hm=s._Tile=function(){return(hm=s._Tile=s.asm.Tile).apply(null,arguments)},fm=s._TopK=function(){return(fm=s._TopK=s.asm.TopK).apply(null,arguments)},mm=s._Transform=function(){return(mm=s._Transform=s.asm.Transform).apply(null,arguments)},gm=s._Transpose=function(){return(gm=s._Transpose=s.asm.Transpose).apply(null,arguments)},ym=s.__FusedMatMul=function(){return(ym=s.__FusedMatMul=s.asm._FusedMatMul).apply(null,arguments)},xm=s._malloc=function(){return(xm=s._malloc=s.asm.malloc).apply(null,arguments)},Am=s._free=function(){return(Am=s._free=s.asm.free).apply(null,arguments)},bm=s.___errno_location=function(){return(bm=s.___errno_location=s.asm.__errno_location).apply(null,arguments)},Yp=s.stackSave=function(){return(Yp=s.stackSave=s.asm.stackSave).apply(null,arguments)},Jp=s.stackRestore=function(){return(Jp=s.stackRestore=s.asm.stackRestore).apply(null,arguments)},zu=s.stackAlloc=function(){return(zu=s.stackAlloc=s.asm.stackAlloc).apply(null,arguments)},vm=s.dynCall_iijjiiii=function(){return(vm=s.dynCall_iijjiiii=s.asm.dynCall_iijjiiii).apply(null,arguments)},km=s.dynCall_jiji=function(){return(km=s.dynCall_jiji=s.asm.dynCall_jiji).apply(null,arguments)};s.cwrap=j0;var Ho;Ha=function Y(){Ho||Qp(),Ho||(Ha=Y)};function Qp(Y){if(Y=Y||p,ut>0||(Ot(),ut>0))return;function se(){Ho||(Ho=!0,s.calledRun=!0,!W&&(ln(),i(s),s.onRuntimeInitialized&&s.onRuntimeInitialized(),ra()))}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()();Qp();var jo;l&&(jo={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 qo;if(typeof r!="undefined")qo=r;else if(typeof WasmBackendModuleThreadedSimd!="undefined")qo=WasmBackendModuleThreadedSimd;else throw new Error("Could not find wasm module in post.js");if(jo){var wm=qo._dispose;qo._dispose=function(){wm(),jo.uncaughtException.forEach(function(Y){process.removeListener("uncaughtException",Y)}),jo.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)}),kd=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}},Al=class{refCount(e){return qa("refCount")}incRef(e){return qa("incRef")}timerAvailable(){return!0}time(e){return qa("time")}read(e){return qa("read")}readSync(e){return qa("readSync")}readToGPU(e,t){return qa("readToGPU")}numDataIds(){return qa("numDataIds")}disposeData(e,t){return qa("disposeData")}write(e,t,a){return qa("write")}move(e,t,a,n,r){return qa("move")}createTensorFromGPUData(e,t,a){return qa("createTensorFromGPUData")}memory(){return qa("memory")}floatPrecision(){return qa("floatPrecision")}epsilon(){return this.floatPrecision()===32?1e-7:1e-4}dispose(){return qa("dispose")}};function qa(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 ax(e){let t=e.length,a=0;for(;t>0;)a=Math.random()*t|0,t--,Sc(e,t,a)}function sS(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--,Sc(e,a,n),Sc(t,a,n)}function ad(e,t,a){return Math.max(e,Math.min(t,a))}function iS(e){return e%2===0?e:e+1}function Sc(e,t,a){let n=e[t];e[t]=e[a],e[a]=n}function oS(e){let t=0;for(let a=0;a<e.length;a++)t+=e[a];return t}function lS(e,t){let a=Math.random();return t*a+(1-a)*e}function uS(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(es(e,t),()=>a+` Shapes ${e} and ${t} must match`)}function Xs(e){F(e!=null,()=>"The input to the tensor constructor must be a non-null value.")}function xt(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 dS(e){return e.length===0}function es(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 il(e){return e%1===0}function pS(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 cS(e){let t=Math.ceil(Math.sqrt(e));return[t,Math.ceil(e/t)]}function hS(e){let t=new Uint32Array(e);for(let a=0;a<e;++a)t[a]=a;return ax(t),t}function Ju(e,t){return t<=e.length?e:e+" ".repeat(t-e.length)}function fS(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 mS(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} / ${a}`);let r=e.slice();return r[n]=t/a,r}function wd(e,t){let a=t.length;return e=e==null?t.map((n,r)=>r):[].concat(e),F(e.every(n=>n>=-a&&n<a),()=>`All values in axis param must be in range [-${a}, ${a}) but got axis ${e}`),F(e.every(n=>il(n)),()=>`All values in axis param must be integers but got axis ${e}`),e.map(n=>n<0?a+n:n)}function nx(e,t){let a=[],n=[],r=t!=null&&Array.isArray(t)&&t.length===0,s=t==null||r?null:wd(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 rx(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 throw new Error(`Unknown data type ${e}`);return a}function sx(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 ix(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 ox(e){return e==="bool"||e==="complex64"||e==="float32"||e==="int32"||e==="string"}function gS(e,t){return!(t==="complex64"||t==="float32"&&e!=="complex64"||t==="int32"&&e!=="float32"&&e!=="complex64"||t==="bool"&&e==="bool")}function Tc(e){if(e==="float32"||e==="int32")return 4;if(e==="complex64")return 8;if(e==="bool")return 1;throw new Error(`Unknown dtype ${e}`)}function lx(e){if(e==null)return 0;let t=0;return e.forEach(a=>t+=a.length),t}function zr(e){return typeof e=="string"||e instanceof String}function ux(e){return typeof e=="boolean"}function dx(e){return typeof e=="number"}function Hc(e){return Array.isArray(e)?Hc(e[0]):e instanceof Float32Array?"float32":e instanceof Int32Array||e instanceof Uint8Array||e instanceof Uint8ClampedArray?"int32":dx(e)?"float32":zr(e)?"string":ux(e)?"bool":"float32"}function Gr(e){return!!(e&&e.constructor&&e.call&&e.apply)}function Cc(e,t){for(let a=t;a<e;++a)if(e%a===0)return a;return e}function bl(e){let t=e.length;if(t<2)return[];let a=new Array(t-1);a[t-2]=e[t-1];for(let n=t-3;n>=0;--n)a[n]=a[n+1]*e[n+1];return a}function px(e,t,a,n=!1){let r=new Array;if(t.length===1){let s=t[0]*(n?2:1);for(let i=0;i<s;i++)r[i]=a[e+i]}else{let s=t[0],i=t.slice(1),o=i.reduce((l,u)=>l*u)*(n?2:1);for(let l=0;l<s;l++)r[l]=px(e+l*o,i,a,n)}return r}function tl(e,t,a=!1){if(e.length===0)return t[0];let n=e.reduce((r,s)=>r*s)*(a?2:1);if(n===0)return[];if(n!==t.length)throw new Error(`[${e}] does not match the input size ${t.length}${a?" for a complex tensor":""}.`);return px(0,e,t,a)}function yS(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 O2(e,t){let a=jc(e,t);for(let n=0;n<a.length;n++)a[n]=1;return a}function jc(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 xS(e,t){let a=e.reduce((n,r)=>n*r,1);if(t==null||t==="float32")return tl(e,new Float32Array(a));if(t==="int32")return tl(e,new Int32Array(a));if(t==="bool")return tl(e,new Uint8Array(a));throw new Error(`Unknown data type ${t}`)}function en(e){e.forEach(t=>{F(Number.isInteger(t)&&t>=0,()=>`Tensor must have a shape comprised of positive integers but got shape [${e}].`)})}function AS(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 bS(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 qc(e){return e&&e.then&&typeof e.then=="function"}var P5="tfjsflags",cx=class{constructor(e){this.global=e,this.flags={},this.flagRegistry={},this.urlFlags={},this.getQueryParams=vS,this.populateURLFlags()}setPlatform(e,t){this.platform!=null&&(V().getBool("IS_TEST")||V().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];V().getBool("IS_TEST")||V().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(qc(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)}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);P5 in e&&e[P5].split(",").forEach(t=>{let[a,n]=t.split(":");this.urlFlags[a]=wS(a,n)})}};function vS(e){let t={};return e.replace(/[?&]([^=?&]+)(?:=([^&]*))?/g,(a,...n)=>(kS(t,n[0],n[1]),n.join("="))),t}function kS(e,t,a){e[decodeURIComponent(t)]=decodeURIComponent(a||"")}function wS(e,t){if(t=t.toLowerCase(),t==="true"||t==="false")return t==="true";if(`${+t}`===t)return+t;throw new Error(`Could not parse value flag value ${t} for flag ${e}.`)}function V(){return D2}var D2=null;function IS(e){D2=e}var Nm;function hx(){if(Nm==null){let e;if(typeof window!="undefined")e=window;else if(typeof global!="undefined")e=global;else if(typeof process!="undefined")e=process;else if(typeof self!="undefined")e=self;else throw new Error("Could not find a global object");Nm=e}return Nm}function SS(){let e=hx();return e._tfGlobals==null&&(e._tfGlobals=new Map),e._tfGlobals}function z2(e,t){let a=SS();if(a.has(e))return a.get(e);{let n=t();return a.set(e,n),a.get(e)}}var vl="Abs",kl="Acos",wl="Acosh",ts="Add",Ks="AddN",Zs="All",Ys="Any",Js="ArgMax",Id="ArgMin",Il="Asin",Sl="Asinh",Tl="Atan",Cl="Atanh",Nl="Atan2",Qs="AvgPool",Xc="AvgPoolGrad",Kc="AvgPool3D",L2="AvgPool3DGrad",ei="BatchMatMul",El="BatchToSpaceND",Sd="Bincount",TS="BroadcastTo",Zc="BroadcastArgs",ti="Cast",ai="Ceil",as="ClipByValue",Td="Complex",Yc="ComplexAbs",Rl="Concat",ni="Conv2D",Cd="Conv2DBackpropFilter",ri="Conv2DBackpropInput",Jc="Conv3D",B2="Conv3DBackpropFilterV2",Qc="Conv3DBackpropInputV2",si="Cos",ii="Cosh",oi="Cumprod",li="Cumsum",ui="CropAndResize",Nd="DenseBincount",di="DepthToSpace",pi="DepthwiseConv2dNative",eh="DepthwiseConv2dNativeBackpropFilter",th="DepthwiseConv2dNativeBackpropInput",Ed="Diag",Rd="Dilation2D",Lm="Dilation2DBackpropInput",Bm="Dilation2DBackpropFilter",ci="RealDiv",Md="Einsum",hi="Elu",W2="EluGrad",Ml="Erf",fi="Equal",mi="Exp",$l="ExpandDims",_l="Expm1",$d="FFT",Pl="Fill",gi="FlipLeftRight",yi="Floor",xi="FloorDiv",Ai="FusedBatchNorm",Fl="GatherV2",bi="GatherNd",vi="Greater",ki="GreaterEqual",wi="Identity",_d="IFFT",Pd="Imag",Ol="IsFinite",Dl="IsInf",Ii="IsNan",Si="LeakyRelu",Ti="Less",Ci="LessEqual",Fd="LinSpace",Ni="Log",zl="Log1p",Ei="LogicalAnd",Ri="LogicalNot",Mi="LogicalOr",fx="LogicalXor",CS="LogSoftmax",NS="LowerBound",Od="LRN",V2="LRNGrad",$i="Max",_i="Maximum",Pi="MaxPool",U2="MaxPoolGrad",ah="MaxPool3D",G2="MaxPool3DGrad",nh="MaxPoolWithArgmax",Fi="Mean",Oi="Min",Di="Minimum",zi="MirrorPad",Ll="Mod",rh="Multinomial",Li="Multiply",Bl="Neg",Bi="NotEqual",Wi="NonMaxSuppressionV3",Wl="NonMaxSuppressionV4",Vi="NonMaxSuppressionV5",Vl="OnesLike",Ui="OneHot",Ul="Pack",Gi="PadV2",ES="Pool",Hi="Pow",ji="Prelu",qi="Prod",sh="RaggedGather",ih="RaggedRange",oh="RaggedTensorToTensor",Gl="Range",Dd="Real",Xi="Reciprocal",Ki="Relu",Hl="Reshape",Zi="ResizeNearestNeighbor",H2="ResizeNearestNeighborGrad",Yi="ResizeBilinear",j2="ResizeBilinearGrad",Ji="Relu6",Qi="Reverse",eo="Round",to="Rsqrt",ao="ScatterNd",zd="SearchSorted",jl="Select",ql="Selu",Xl="Slice",no="Sin",Kl="Sinh",Zl="Sign",ro="Sigmoid",Yl="Softplus",so="Sqrt",io="Sum",Jl="SpaceToBatchND",Ql="SplitV",oo="Softmax",Ld="SparseFillEmptyRows",eu="SparseReshape",Bd="SparseSegmentMean",Wd="SparseSegmentSum",Vd="SparseToDense",lo="SquaredDifference",Ud="Square",uo="StridedSlice",tu="StringNGrams",Gd="StringSplit",Hd="StringToHashBucketFast",po="Sub",co="Tan",ho="Tanh",ns="Tile",fo="TopK",mo="Transform",Ar="Transpose",lh="Unique",au="Unpack",uh="UnsortedSegmentSum",RS="UpperBound",nu="ZerosLike",rs="Step",nd="FromPixels",go="RotateWithOffset",Hr="_FusedMatMul",jr="FusedConv2D",qr="FusedDepthwiseConv2D";function Dr(...e){V().getBool("IS_TEST")||V().getBool("PROD")||console.warn(...e)}function MS(...e){V().getBool("IS_TEST")||V().getBool("PROD")||console.log(...e)}var ol=z2("kernelRegistry",()=>new Map),rd=z2("gradRegistry",()=>new Map);function Nc(e,t){let a=q2(e,t);return ol.get(a)}function Wm(e){return rd.get(e)}function Zn(e){let t=ol.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 yn(e){let{kernelName:t,backendName:a}=e,n=q2(t,a);ol.has(n)&&Dr(`The kernel '${t}' for backend '${a}' is already registered`),ol.set(n,e)}function $S(e){let{kernelName:t}=e;rd.has(t)&&V().getBool("DEBUG")&&Dr(`Overriding the gradient for '${t}'`),rd.set(t,e)}function _S(e,t){let a=q2(e,t);if(!ol.has(a))throw new Error(`The kernel '${e}' for backend '${t}' is not registered`);ol.delete(a)}function PS(e){if(!rd.has(e))throw new Error(`The gradient '${e}' for backend is not registered`);rd.delete(e)}function FS(e,t){Zn(e).forEach(a=>{let n=Object.assign({},a,{backendName:t});yn(n)})}function q2(e,t){return`${t}_${e}`}var v={};Ze(v,{arraysEqual:()=>es,assert:()=>F,assertNonNegativeIntegerDimensions:()=>en,assertNonNull:()=>Xs,assertShapesMatch:()=>Ta,bytesFromStringArray:()=>lx,bytesPerElement:()=>Tc,checkConversionForErrors:()=>ix,clamp:()=>ad,computeStrides:()=>bl,convertBackendValuesAndArrayBuffer:()=>yS,createScalarValue:()=>WS,createShuffledIndices:()=>hS,decodeString:()=>Ec,distSquared:()=>uS,encodeString:()=>qd,fetch:()=>US,fingerPrint64:()=>BS,flatten:()=>Xr,getArrayFromDType:()=>sx,getTypedArrayFromDType:()=>rx,hasEncodingLoss:()=>gS,hexToLong:()=>jd,indexToLoc:()=>bS,inferDtype:()=>Hc,inferFromImplicitShape:()=>mS,isBoolean:()=>ux,isFunction:()=>Gr,isInt:()=>il,isNumber:()=>dx,isPromise:()=>qc,isScalarShape:()=>dS,isString:()=>zr,isTypedArray:()=>sa,isValidDtype:()=>ox,locToIndex:()=>AS,makeOnesTypedArray:()=>O2,makeZerosNestedTypedArray:()=>xS,makeZerosTypedArray:()=>jc,nearestDivisor:()=>Cc,nearestLargerEven:()=>iS,now:()=>sd,parseAxisParam:()=>wd,randUniform:()=>lS,repeatedTry:()=>fS,rightPad:()=>Ju,shuffle:()=>ax,shuffleCombo:()=>sS,sizeFromShape:()=>xt,sizeToSquarishShape:()=>cS,squeezeShape:()=>nx,sum:()=>oS,swap:()=>Sc,tanh:()=>pS,toNestedArray:()=>tl,toTypedArray:()=>dh});var F5=xl(VI()),_s=F5.default||F5;function jd(e){return _s.fromString(e,!0,16)}var mx=jd("c3a5c85c97cb3127"),Ms=jd("b492b66fbe98f273"),Aa=jd("9ae16a3b2f90404f");function Vm(e){return e.xor(e.shru(47))}function gx(e,t,a){let n=e.slice(t,t+a);return _s.fromBytes(Array.from(n),!0,!0)}function ft(e,t){return gx(e,t,8)}function O5(e,t){return gx(e,t,4)}function Kt(e,t){return t===0?e:e.shru(t).or(e.shl(64-t))}function Vr(e,t,a=jd("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 OS(e,t,a,n,r,s){r=r.add(e),s=Kt(s.add(r).add(n),21);let i=r;return r=r.add(t),r=r.add(a),s=s.add(Kt(r,44)),[r.add(n),s.add(i)]}function uc(e,t,a,n){return OS(ft(e,t),ft(e,t+8),ft(e,t+16),ft(e,t+24),a,n)}function DS(e,t=e.length){if(t>=8){let a=Aa.add(t*2),n=ft(e,0).add(Aa),r=ft(e,t-8),s=Kt(r,37).mul(a).add(n),i=Kt(n,25).add(r).mul(a);return Vr(s,i,a)}if(t>=4){let a=Aa.add(t*2),n=O5(e,0);return Vr(n.shl(3).add(t),O5(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 Vm(Aa.mul(s).xor(mx.mul(i))).mul(Aa)}return Aa}function zS(e,t=e.length){let a=Aa.add(t*2),n=ft(e,0).mul(Ms),r=ft(e,8),s=ft(e,t-8).mul(a),i=ft(e,t-16).mul(Aa);return Vr(Kt(n.add(r),43).add(Kt(s,30)).add(i),n.add(Kt(r.add(Aa),18)).add(s),a)}function LS(e,t=e.length){let a=Aa.add(t*2),n=ft(e,0).mul(Aa),r=ft(e,8),s=ft(e,t-8).mul(a),i=ft(e,t-16).mul(Aa),o=Kt(n.add(r),43).add(Kt(s,30)).add(i),l=Vr(o,n.add(Kt(r.add(Aa),18)).add(s),a),u=ft(e,16).mul(a),p=ft(e,24),c=o.add(ft(e,t-32)).mul(a),d=l.add(ft(e,t-24)).mul(a);return Vr(Kt(u.add(p),43).add(Kt(c,30)).add(d),u.add(Kt(p.add(n),18)).add(c),a)}function BS(e,t=e.length){let a=_s.fromNumber(81,!0);if(t<=32)return t<=16?DS(e,t):zS(e,t);if(t<=64)return LS(e,t);let n=a,r=a.mul(Ms).add(113),s=Vm(r.mul(Aa).add(113)).mul(Aa),i=[_s.UZERO,_s.UZERO],o=[_s.UZERO,_s.UZERO];n=n.mul(Aa).add(ft(e,0));let l=0,u=(t-1>>6)*64,p=u+(t-1&63)-63;do n=Kt(n.add(r).add(i[0]).add(ft(e,l+8)),37).mul(Ms),r=Kt(r.add(i[1]).add(ft(e,l+48)),42).mul(Ms),n=n.xor(o[1]),r=r.add(i[0]).add(ft(e,l+40)),s=Kt(s.add(o[0]),33).mul(Ms),i=uc(e,l,i[1].mul(Ms),n.add(o[0])),o=uc(e,l+32,s.add(o[1]),r.add(ft(e,l+16))),[s,n]=[n,s],l+=64;while(l!==u);let c=Ms.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=Kt(n.add(r).add(i[0]).add(ft(e,l+8)),37).mul(c),r=Kt(r.add(i[1]).add(ft(e,l+48)),42).mul(c),n=n.xor(o[1].mul(9)),r=r.add(i[0].mul(9).add(ft(e,l+40))),s=Kt(s.add(o[0]),33).mul(c),i=uc(e,l,i[1].mul(c),n.add(o[0])),o=uc(e,l+32,s.add(o[1]),r.add(ft(e,l+16))),[s,n]=[n,s],Vr(Vr(i[0],o[0],c).add(Vm(r).mul(mx)).add(s),Vr(i[1],o[1],c).add(n),c)}function WS(e,t){return t==="string"?qd(e):dh([e],t)}function VS(e,t){return e instanceof Float32Array&&t==="float32"||e instanceof Int32Array&&t==="int32"||e instanceof Uint8Array&&t==="bool"}function dh(e,t){if(t==="string")throw new Error("Cannot convert a string[] to a TypedArray");if(Array.isArray(e)&&(e=Xr(e)),V().getBool("DEBUG")&&ix(e,t),VS(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 ${t}`)}function sd(){return V().platform.now()}function US(e,t){return V().platform.fetch(e,t)}function qd(e,t="utf-8"){return t=t||"utf-8",V().platform.encode(e,t)}function Ec(e,t="utf-8"){return t=t||"utf-8",V().platform.decode(e,t)}function sa(e){return V().platform.isTypedArray(e)}function Xr(e,t=[],a=!1){if(t==null&&(t=[]),typeof e=="boolean"||typeof e=="number"||typeof e=="string"||qc(e)||e==null||sa(e)&&a)t.push(e);else if(Array.isArray(e)||sa(e))for(let n=0;n<e.length;++n)Xr(e[n],t,a);else{let n=-1;for(let r of Object.keys(e))/^([1-9]+[0-9]*|0)$/.test(r)&&(n=Math.max(n,Number(r)));for(let r=0;r<=n;r++)Xr(e[r],t,a)}return t}var GS=class{constructor(e,t){this.backendTimer=e,this.logger=t,t==null&&(this.logger=new jS)}profileKernel(e,t,a){let n,r=()=>{n=a()},s,i=sd();if(this.backendTimer.timerAvailable())s=this.backendTimer.time(r);else{r();for(let o of n)o.dataSync();s=Promise.resolve({kernelMs:sd()-i})}if(V().getBool("CHECK_COMPUTATION_FOR_ERRORS"))for(let o=0;o<n.length;o++){let l=n[o];l.data().then(u=>{HS(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 HS(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 jS=class{logKernelProfile(e,t,a,n,r,s){let i=typeof n=="number"?Ju(`${n}ms`,9):n.error,o=Ju(e,25),l=t.rank,u=t.size,p=Ju(t.shape.toString(),14),c="";for(let d in r){let h=r[d];if(h!=null){let f=h.shape||t.shape,m=f.length;c+=`${d}: ${m}D ${m>0?f:""} `}}console.log(`%c${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 qS(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 f=0;f<t.length;f++)if(n[d.id]){u.outputs.forEach(m=>n[m.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 XS(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(!es(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 D5=20,Bu=3,Em=7;function KS(e,t,a,n){let r=bl(t),s=ZS(e,t,a,r),i=t.length,o=gc(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 ZS(e,t,a,n){let r=xt(t),s=n[n.length-1],i=new Array(s).fill(0),o=t.length,l=a==="complex64"?Uu(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],Vu(l[p+c],0,a).length)}return i}function Vu(e,t,a){let n;return Array.isArray(e)?n=`${parseFloat(e[0].toFixed(Em))} + ${parseFloat(e[1].toFixed(Em))}j`:zr(e)?n=`'${e}'`:a==="bool"?n=yx(e):n=parseFloat(e.toFixed(Em)).toString(),Ju(n,t)}function yx(e){return e===0?"false":"true"}function gc(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 m=Uu(e);return[Vu(m[0],0,a)]}return a==="bool"?[yx(e[0])]:[e[0].toString()]}if(l===1){if(o>D5){let m=Bu*i,g=Array.from(e.slice(0,m)),y=Array.from(e.slice((o-Bu)*i,o*i));return a==="complex64"&&(g=Uu(g),y=Uu(y)),["["+g.map((x,A)=>Vu(x,r[A],a)).join(", ")+", ..., "+y.map((x,A)=>Vu(x,r[o-Bu+A],a)).join(", ")+"]"]}return["["+(a==="complex64"?Uu(e):Array.from(e)).map((m,g)=>Vu(m,r[g],a)).join(", ")+"]"]}let u=t.slice(1),p=n.slice(1),c=n[0]*i,d=[];if(o>D5){for(let m=0;m<Bu;m++){let g=m*c,y=g+c;d.push(...gc(e.slice(g,y),u,a,p,r,!1))}d.push("...");for(let m=o-Bu;m<o;m++){let g=m*c,y=g+c;d.push(...gc(e.slice(g,y),u,a,p,r,m===o-1))}}else for(let m=0;m<o;m++){let g=m*c,y=g+c;d.push(...gc(e.slice(g,y),u,a,p,r,m===o-1))}let h=l===2?",":"";d[0]="["+(o>0?d[0]+h:"");for(let m=1;m<d.length-1;m++)d[m]=" "+d[m]+h;let f=`,
|
|
`;for(let m=2;m<l;m++)f+=`
|
|
`;return d[d.length-1]=" "+d[d.length-1]+"]"+(s?"":f),d}function Uu(e){let t=[];for(let a=0;a<e.length;a+=2)t.push([e[a],e[a+1]]);return t}var jt=class{constructor(e,t,a){if(this.dtype=t,this.shape=e.slice(),this.size=xt(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||sx(t,this.size),this.strides=bl(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 Fn().makeTensor(this.values,this.shape,this.dtype)}},Fn=null,Jo=null,YS=null;function JS(e){Fn=e}function QS(e){Jo=e}function eT(e){YS=e}var pt=class{constructor(e,t,a,n){this.kept=!1,this.isDisposedInternal=!1,this.shape=e.slice(),this.dtype=t||"float32",this.size=xt(e),this.strides=bl(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 Jo.buffer(this.shape,this.dtype,e)}bufferSync(){return Jo.buffer(this.shape,this.dtype,this.dataSync())}async array(){let e=await this.data();return tl(this.shape,e,this.dtype==="complex64")}arraySync(){return tl(this.shape,this.dataSync(),this.dtype==="complex64")}async data(){this.throwIfDisposed();let e=Fn().read(this.dataId);if(this.dtype==="string"){let t=await e;try{return t.map(a=>Ec(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(),Fn().readToGPU(this.dataId,e)}dataSync(){this.throwIfDisposed();let e=Fn().readSync(this.dataId);if(this.dtype==="string")try{return e.map(t=>Ec(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 Fn().read(this.dataId);return this.dtype==="string"?e:new Uint8Array(e.buffer)}dispose(){this.isDisposed||(Fn().disposeTensor(this),this.isDisposedInternal=!0)}get isDisposed(){return this.isDisposedInternal}throwIfDisposed(){if(this.isDisposed)throw new Error("Tensor is disposed.")}print(e=!1){return Jo.print(this,e)}clone(){return this.throwIfDisposed(),Jo.clone(this)}toString(e=!1){let t=this.dataSync();return KS(t,this.shape,this.dtype,e)}cast(e){return this.throwIfDisposed(),Jo.cast(this,e)}variable(e=!0,t,a){return this.throwIfDisposed(),Fn().makeVariable(this,e,t,a)}};Object.defineProperty(pt,Symbol.hasInstance,{value:e=>!!e&&e.data!=null&&e.dataSync!=null&&e.throwIfDisposed!=null});function tT(){return z2("Tensor",()=>pt)}tT();var id=class extends pt{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(!es(e.shape,this.shape))throw new Error(`shape of the new value (${e.shape}) and previous value (${this.shape}) must match`);Fn().disposeTensor(this),this.dataId=e.dataId,Fn().incRef(this,null)}dispose(){Fn().disposeVariable(this),this.isDisposedInternal=!0}};Object.defineProperty(id,Symbol.hasInstance,{value:e=>e instanceof pt&&e.assign!=null&&e.assign instanceof Function});var xx={};Ze(xx,{assertTypesMatch:()=>Ax,getTensorsInContainer:()=>X2,isTensorInList:()=>nT,makeTypesMatch:()=>Tt});var Um;(function(e){e.R0="R0",e.R1="R1",e.R2="R2",e.R3="R3",e.R4="R4",e.R5="R5",e.R6="R6"})(Um||(Um={}));var Gm;(function(e){e.float32="float32",e.int32="int32",e.bool="int32",e.complex64="complex64"})(Gm||(Gm={}));var Hm;(function(e){e.float32="float32",e.int32="int32",e.bool="bool",e.complex64="complex64"})(Hm||(Hm={}));var jm;(function(e){e.float32="float32",e.int32="float32",e.bool="float32",e.complex64="complex64"})(jm||(jm={}));var qm;(function(e){e.float32="complex64",e.int32="complex64",e.bool="complex64",e.complex64="complex64"})(qm||(qm={}));var aT={float32:jm,int32:Gm,bool:Hm,complex64:qm};function fa(e,t){if(e==="string"||t==="string"){if(e==="string"&&t==="string")return"string";throw new Error(`Can not upcast ${e} with ${t}`)}return aT[e][t]}function Xd(e){return fa(e,"int32")}function Tt(e,t){if(e.dtype===t.dtype)return[e,t];let a=fa(e.dtype,t.dtype);return[e.cast(a),t.cast(a)]}function Ax(e,t){F(e.dtype===t.dtype,()=>`The dtypes of the first(${e.dtype}) and second(${t.dtype}) input must match`)}function nT(e,t){return t.some(a=>a.id===e.id)}function X2(e){let t=[];return bx(e,t,new Set),t}function bx(e,t,a){if(e==null)return;if(e instanceof pt){t.push(e);return}if(!rT(e))return;let n=e;for(let r in n){let s=n[r];a.has(s)||(a.add(s),bx(s,t,a))}}function rT(e){return Array.isArray(e)||typeof e=="object"}function Rm(e){return e.kernelName!=null}var z5=class{constructor(){this.registeredVariables={},this.nextTapeNodeId=0,this.numBytes=0,this.numTensors=0,this.numStringTensors=0,this.numDataBuffers=0,this.gradientDepth=0,this.kernelDepth=0,this.scopeStack=[],this.numDataMovesStack=[],this.nextScopeId=0,this.tensorInfo=new WeakMap,this.profiling=!1,this.activeProfile={newBytes:0,newTensors:0,peakBytes:0,kernels:[],result:null,get kernelNames(){return Array.from(new Set(this.kernels.map(e=>e.name)))}}}dispose(){for(let e in this.registeredVariables)this.registeredVariables[e].dispose()}},od=class{constructor(e){this.ENV=e,this.registry={},this.registryFactory={},this.pendingBackendInitId=0,this.state=new z5}async ready(){if(this.pendingBackendInit!=null)return this.pendingBackendInit.then(()=>{});if(this.backendInstance!=null)return;let e=this.getSortedBackends();for(let t=0;t<e.length;t++){let a=e[t];if(await this.initializeBackend(a).success){await this.setBackend(a);return}}throw new Error("Could not initialize any backends, all backend initializations failed.")}get backend(){if(this.pendingBackendInit!=null)throw new Error(`Backend '${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:e,asyncInit:t}=this.initializeBackendsAndReturnBest();if(t)throw new Error(`The highest priority backend '${e}' has not yet been initialized. Make sure to await tf.ready() or await tf.setBackend() before calling other methods`);this.setBackend(e)}return this.backendInstance}backendNames(){return Object.keys(this.registryFactory)}findBackend(e){if(!(e in this.registry))if(e in this.registryFactory){let{asyncInit:t}=this.initializeBackend(e);if(t)return null}else return null;return this.registry[e]}findBackendFactory(e){return e in this.registryFactory?this.registryFactory[e].factory:null}registerBackend(e,t,a=1){return e in this.registryFactory?(Dr(`${e} backend was already registered. Reusing existing backend factory.`),!1):(this.registryFactory[e]={factory:t,priority:a},!0)}async setBackend(e){if(this.registryFactory[e]==null)throw new Error(`Backend name '${e}' not found in registry`);if(this.backendName=e,this.registry[e]==null){this.backendInstance=null;let{success:t,asyncInit:a}=this.initializeBackend(e);if(!(a?await t:t))return!1}return this.backendInstance=this.registry[e],this.setupRegisteredKernels(),this.profiler=new GS(this.backendInstance),!0}setupRegisteredKernels(){Zn(this.backendName).forEach(e=>{e.setupFunc!=null&&e.setupFunc(this.backendInstance)})}disposeRegisteredKernels(e){Zn(e).forEach(t=>{t.disposeFunc!=null&&t.disposeFunc(this.registry[e])})}initializeBackend(e){let t=this.registryFactory[e];if(t==null)throw new Error(`Cannot initialize backend ${e}, no registration found.`);try{let a=t.factory();if(a&&!(a instanceof Al)&&typeof a.then=="function"){let n=++this.pendingBackendInitId,r=a.then(s=>n<this.pendingBackendInitId?!1:(this.registry[e]=s,this.pendingBackendInit=null,!0)).catch(s=>(n<this.pendingBackendInitId||(this.pendingBackendInit=null,Dr(`Initialization of backend ${e} failed`),Dr(s.stack||s.message)),!1));return this.pendingBackendInit=r,{success:r,asyncInit:!0}}else return this.registry[e]=a,{success:!0,asyncInit:!1}}catch(a){return Dr(`Initialization of backend ${e} failed`),Dr(a.stack||a.message),{success:!1,asyncInit:!1}}}removeBackend(e){if(!(e in this.registryFactory))throw new Error(`${e} backend not found in registry`);this.backendName===e&&this.pendingBackendInit!=null&&this.pendingBackendInitId++,e in this.registry&&(this.disposeRegisteredKernels(e),this.registry[e].dispose(),delete this.registry[e]),delete this.registryFactory[e],this.backendName===e&&(this.pendingBackendInit=null,this.backendName=null,this.backendInstance=null)}getSortedBackends(){if(Object.keys(this.registryFactory).length===0)throw new Error("No backend found in registry.");return Object.keys(this.registryFactory).sort((e,t)=>this.registryFactory[t].priority-this.registryFactory[e].priority)}initializeBackendsAndReturnBest(){let e=this.getSortedBackends();for(let t=0;t<e.length;t++){let a=e[t],{success:n,asyncInit:r}=this.initializeBackend(a);if(r||n)return{name:a,asyncInit:r}}throw new Error("Could not initialize any backends, all backend initializations failed.")}moveData(e,t){let a=this.state.tensorInfo.get(t),n=a.backend,r=this.readSync(t),s=n.refCount(t);n.disposeData(t,!0),a.backend=e,e.move(t,r,a.shape,a.dtype,s),this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack[this.state.numDataMovesStack.length-1]++}tidy(e,t){let a=null;if(t==null){if(typeof e!="function")throw new Error("Please provide a function to tidy()");t=e}else{if(typeof e!="string"&&!(e instanceof String))throw new Error("When calling with two arguments, the first argument to tidy() must be a string");if(typeof t!="function")throw new Error("When calling with two arguments, the 2nd argument to tidy() must be a function");a=e}let n;return this.scopedRun(()=>this.startScope(a),()=>this.endScope(n),()=>(n=t(),n instanceof Promise&&console.error("Cannot return a Promise inside of tidy."),n))}scopedRun(e,t,a){e();try{let n=a();return t(),n}catch(n){throw t(),n}}nextTensorId(){return od.nextTensorId++}nextVariableId(){return od.nextVariableId++}clone(e){let t=L.runKernel(wi,{x:e}),a={x:e},n=s=>({x:()=>{let i="float32",o={x:s},l={dtype:i};return L.runKernel(ti,o,l)}}),r=[];return this.addTapeNode(this.state.activeScope.name,a,[t],n,r,{}),t}runKernel(e,t,a){if(this.backendName==null&&this.backend,Nc(e,this.backendName)==null)throw new Error(`Kernel '${e}' not registered for backend '${this.backendName}'`);return this.runKernelFunc({kernelName:e,inputs:t,attrs:a})}shouldCheckForMemLeaks(){return this.ENV.getBool("IS_TEST")}checkKernelForMemLeak(e,t,a){let n=this.backend.numDataIds(),r=0;a.forEach(o=>{r+=o.dtype==="complex64"?3:1});let s=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],i=n-t-r-s;if(i>0)throw new Error(`Backend '${this.backendName}' has an internal memory leak (${i} data ids) after running '${e}'`)}runKernelFunc(e){let t,a=[],n=this.isTapeOn(),r=this.state.numBytes,s=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);let i;this.backendName==null&&this.backend;let o,l=Rm(e)?e.kernelName:this.state.activeScope!=null?this.state.activeScope.name:"";if(Rm(e)){let{kernelName:h,inputs:f,attrs:m}=e;this.backendName==null&&this.backend;let g=Nc(h,this.backendName);F(g!=null,()=>`Cannot find registered kernel '${h}' for backend '${this.backendName}'`),i=()=>{let y=this.backend.numDataIds();o=g.kernelFunc({inputs:f,attrs:m,backend:this.backend});let x=Array.isArray(o)?o:[o];this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(h,y,x);let A=x.map(b=>b.rank!=null?b:this.makeTensorFromTensorInfo(b));if(n){let b=this.getTensorsForGradient(h,f,A);a=this.saveTensorsForBackwardMode(b)}return A}}else{let{forwardFunc:h}=e,f=m=>{n&&(a=m.map(g=>this.keep(this.clone(g))))};i=()=>{let m=this.backend.numDataIds();o=this.tidy(()=>h(this.backend,f));let g=Array.isArray(o)?o:[o];return this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(l,m,g),g}}let{inputs:u,attrs:p}=e,c=Rm(e)?null:e.backwardsFunc,d;return this.scopedRun(()=>this.state.kernelDepth++,()=>this.state.kernelDepth--,()=>{!this.ENV.getBool("DEBUG")&&!this.state.profiling?t=i():(d=this.profiler.profileKernel(l,u,()=>i()),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(d),t=d.outputs)}),n&&this.addTapeNode(l,u,t,c,a,p),this.state.profiling&&this.state.activeProfile.kernels.push({name:l,bytesAdded:this.state.numBytes-r,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-s,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(u).map(h=>u[h]!=null?u[h].shape:null),outputShapes:t.map(h=>h.shape),kernelTimeMs:d.timeMs,extraInfo:d.extraInfo}),Array.isArray(o)?t:t[0]}saveTensorsForBackwardMode(e){return e.map(t=>this.keep(this.clone(t)))}getTensorsForGradient(e,t,a){let n=Wm(e);if(n!=null){let r=n.inputsToSave||[],s=n.outputsToSave||[],i;n.saveAllInputs?(F(Array.isArray(t),()=>"saveAllInputs is true, expected inputs to be an array."),i=Object.keys(t).map(l=>t[l])):i=r.map(l=>t[l]);let o=a.filter((l,u)=>s[u]);return i.concat(o)}return[]}makeTensor(e,t,a,n){if(e==null)throw new Error("Values passed to engine.makeTensor() are null");a=a||"float32",n=n||this.backend;let r=e;a==="string"&&zr(e[0])&&(r=e.map(o=>qd(o)));let s=n.write(r,t,a),i=new pt(t,a,s,this.nextTensorId());if(this.trackTensor(i,n),a==="string"){let o=this.state.tensorInfo.get(s),l=lx(r);this.state.numBytes+=l-o.bytes,o.bytes=l}return i}makeTensorFromDataId(e,t,a,n){a=a||"float32";let r={dataId:e,shape:t,dtype:a};return this.makeTensorFromTensorInfo(r,n)}makeTensorFromTensorInfo(e,t){let{dataId:a,shape:n,dtype:r}=e,s=new pt(n,r,a,this.nextTensorId());return this.trackTensor(s,t),s}makeVariable(e,t=!0,a,n){a=a||this.nextVariableId().toString(),n!=null&&n!==e.dtype&&(e=e.cast(n));let r=new id(e,t,a,this.nextTensorId());if(this.state.registeredVariables[r.name]!=null)throw new Error(`Variable with name ${r.name} was already registered`);return this.state.registeredVariables[r.name]=r,this.incRef(r,this.backend),r}trackTensor(e,t){this.state.numTensors++,e.dtype==="string"&&this.state.numStringTensors++;let a=0;e.dtype!=="complex64"&&e.dtype!=="string"&&(a=e.size*Tc(e.dtype)),this.state.numBytes+=a,this.state.tensorInfo.has(e.dataId)||(this.state.numDataBuffers++,this.state.tensorInfo.set(e.dataId,{backend:t||this.backend,dtype:e.dtype,shape:e.shape,bytes:a})),e instanceof id||this.track(e)}incRef(e,t){this.trackTensor(e,t),this.backend.incRef(e.dataId)}removeDataId(e,t){this.state.tensorInfo.has(e)&&this.state.tensorInfo.get(e).backend===t&&(this.state.tensorInfo.delete(e),this.state.numDataBuffers--)}disposeTensor(e){if(!this.state.tensorInfo.has(e.dataId))return;let t=this.state.tensorInfo.get(e.dataId);if(this.state.numTensors--,e.dtype==="string"&&(this.state.numStringTensors--,this.state.numBytes-=t.bytes),e.dtype!=="complex64"&&e.dtype!=="string"){let a=e.size*Tc(e.dtype);this.state.numBytes-=a}t.backend.disposeData(e.dataId)&&this.removeDataId(e.dataId,t.backend)}disposeVariables(){for(let e in this.state.registeredVariables){let t=this.state.registeredVariables[e];this.disposeVariable(t)}}disposeVariable(e){this.disposeTensor(e),this.state.registeredVariables[e.name]!=null&&delete this.state.registeredVariables[e.name]}memory(){let e=this.backend.memory();return e.numTensors=this.state.numTensors,e.numDataBuffers=this.state.numDataBuffers,e.numBytes=this.state.numBytes,this.state.numStringTensors>0&&(e.unreliable=!0,e.reasons==null&&(e.reasons=[]),e.reasons.push("Memory usage by string tensors is approximate (2 bytes per character)")),e}async profile(e){this.state.profiling=!0;let t=this.state.numBytes,a=this.state.numTensors;this.state.activeProfile.kernels=[],this.state.activeProfile.result=await e(),this.state.profiling=!1,this.state.activeProfile.peakBytes=Math.max(...this.state.activeProfile.kernels.map(n=>n.totalBytesSnapshot)),this.state.activeProfile.newBytes=this.state.numBytes-t,this.state.activeProfile.newTensors=this.state.numTensors-a;for(let n of this.state.activeProfile.kernels)n.kernelTimeMs=await n.kernelTimeMs,n.extraInfo=await n.extraInfo;return this.state.activeProfile}isTapeOn(){return this.state.gradientDepth>0&&this.state.kernelDepth===0}addTapeNode(e,t,a,n,r,s){let i={id:this.state.nextTapeNodeId++,kernelName:e,inputs:t,outputs:a,saved:r},o=Wm(e);o!=null&&(n=o.gradFunc),n!=null&&(i.gradient=l=>(l=l.map((u,p)=>{if(u==null){let c=a[p],d=jc(c.size,c.dtype);return this.makeTensor(d,c.shape,c.dtype)}return u}),n(l.length>1?l:l[0],r,s))),this.state.activeTape.push(i)}keep(e){return e.kept=!0,e}startTape(){this.state.gradientDepth===0&&(this.state.activeTape=[]),this.state.gradientDepth++}endTape(){this.state.gradientDepth--}startScope(e){let t={track:[],name:"unnamed scope",id:this.state.nextScopeId++};e&&(t.name=e),this.state.scopeStack.push(t),this.state.activeScope=t}endScope(e){let t=X2(e),a=new Set(t.map(r=>r.id));for(let r=0;r<this.state.activeScope.track.length;r++){let s=this.state.activeScope.track[r];!s.kept&&!a.has(s.id)&&s.dispose()}let n=this.state.scopeStack.pop();this.state.activeScope=this.state.scopeStack.length===0?null:this.state.scopeStack[this.state.scopeStack.length-1],t.forEach(r=>{!r.kept&&r.scopeId===n.id&&this.track(r)})}gradients(e,t,a,n=!1){if(F(t.length>0,()=>"gradients() received an empty list of xs."),a!=null&&a.dtype!=="float32")throw new Error(`dy must have 'float32' dtype, but has '${a.dtype}'`);let r=this.scopedRun(()=>this.startTape(),()=>this.endTape(),()=>this.tidy("forward",e));F(r instanceof pt,()=>"The result y returned by f() must be a tensor.");let s=qS(this.state.activeTape,t,r);if(!n&&s.length===0&&t.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 i={};i[r.id]=a==null?sT(r.shape):a,XS(i,s,l=>this.tidy(l),iT);let o=t.map(l=>i[l.id]);return this.state.gradientDepth===0&&(this.state.activeTape.forEach(l=>{for(let u of l.saved)u.dispose()}),this.state.activeTape=null),{value:r,grads:o}})}customGrad(e){return F(Gr(e),()=>"The f passed in customGrad(f) must be a function."),(...t)=>{F(t.every(i=>i instanceof pt),()=>"The args passed in customGrad(f)(x1, x2,...) must all be tensors");let a,n={};t.forEach((i,o)=>{n[o]=i});let r=(i,o)=>(a=e(...t,o),F(a.value instanceof pt,()=>"The function f passed in customGrad(f) must return an object where `obj.value` is a tensor"),F(Gr(a.gradFunc),()=>"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function."),a.value),s=(i,o)=>{let l=a.gradFunc(i,o),u=Array.isArray(l)?l:[l];F(u.length===t.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(u.every(c=>c instanceof pt),()=>"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 p={};return u.forEach((c,d)=>{p[d]=()=>c}),p};return this.runKernelFunc({forwardFunc:r,backwardsFunc:s,inputs:n})}}readSync(e){return this.state.tensorInfo.get(e).backend.readSync(e)}read(e){return this.state.tensorInfo.get(e).backend.read(e)}readToGPU(e,t){return this.state.tensorInfo.get(e).backend.readToGPU(e,t)}async time(e){let t=sd(),a=await this.backend.time(e);return a.wallMs=sd()-t,a}track(e){return this.state.activeScope!=null&&(e.scopeId=this.state.activeScope.id,this.state.activeScope.track.push(e)),e}get registeredVariables(){return this.state.registeredVariables}reset(){this.pendingBackendInitId++,this.state.dispose(),this.ENV.reset(),this.state=new z5;for(let e in this.registry)this.disposeRegisteredKernels(e),this.registry[e].dispose(),delete this.registry[e];this.backendName=null,this.backendInstance=null,this.pendingBackendInit=null}};od.nextTensorId=0;od.nextVariableId=0;function sT(e){let t=O2(xt(e),"float32");return L.makeTensor(t,e,"float32")}function vx(){let e=hx();if(e._tfengine==null){let t=new cx(e);e._tfengine=new od(t)}return IS(e._tfengine.ENV),JS(()=>e._tfengine),e._tfengine}var L=vx();function iT(e,t){let a={a:e,b:t};return L.runKernel(ts,a)}var Kd={};Ze(Kd,{isBrowser:()=>kx,isMobile:()=>uT,mockIsMobile:()=>lT});function oT(){return typeof navigator!="undefined"&&navigator!=null}var Xm;function lT(e){Xm=e}function uT(e){if(Xm!==void 0)return Xm;if(e||oT()){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 kx(){return typeof window!="undefined"&&window.document!=null||typeof WorkerGlobalScope!="undefined"}var mn=V();mn.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.")});mn.registerFlag("IS_BROWSER",()=>kx());mn.registerFlag("IS_NODE",()=>typeof process!="undefined"&&typeof process.versions!="undefined"&&typeof process.versions.node!="undefined");mn.registerFlag("IS_CHROME",()=>typeof navigator!="undefined"&&navigator!=null&&navigator.userAgent!=null&&/Chrome/.test(navigator.userAgent)&&/Google Inc/.test(navigator.vendor));mn.registerFlag("PROD",()=>!1);mn.registerFlag("TENSORLIKE_CHECK_SHAPE_CONSISTENCY",()=>mn.getBool("DEBUG"));mn.registerFlag("DEPRECATION_WARNINGS_ENABLED",()=>!0);mn.registerFlag("IS_TEST",()=>!1);mn.registerFlag("CHECK_COMPUTATION_FOR_ERRORS",()=>!0);mn.registerFlag("WRAP_TO_IMAGEBITMAP",()=>!1);mn.registerFlag("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU",()=>!1);mn.registerFlag("USE_SETTIMEOUTCUSTOM",()=>!1);function Yn(e,t){let a=e;if(sa(e))return t==="string"?[]:[e.length];if(typeof e=="object"){if("texture"in e){let r=e.channels||"RGBA";return[e.height,e.width*r.length]}else if("buffer"in e&&!(e.buffer instanceof ArrayBuffer))return[e.buffer.size/(t==null?4:Tc(t))]}if(!Array.isArray(e))return[];let n=[];for(;Array.isArray(a)||sa(a)&&t!=="string";)n.push(a.length),a=a[0];return Array.isArray(e)&&V().getBool("TENSORLIKE_CHECK_SHAPE_CONSISTENCY")&&wx(e,n,[]),n}function wx(e,t,a){if(a=a||[],!Array.isArray(e)&&!sa(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 ${e.length} elements`);let n=t.slice(1);for(let r=0;r<e.length;++r)wx(e[r],n,a.concat(r))}function L5(e,t,a,n){if(e!=="string_or_numeric"){if(e==null)throw new Error("Expected dtype cannot be null.");if(e!=="numeric"&&e!==t||e==="numeric"&&t==="string")throw new Error(`Argument '${a}' passed to '${n}' must be ${e} tensor, but got ${t} tensor`)}}function E(e,t,a,n="numeric"){if(e instanceof pt)return L5(n,e.dtype,t,a),e;let r=Hc(e);if(r!=="string"&&["bool","int32","float32"].indexOf(n)>=0&&(r=n),L5(n,r,t,a),e==null||!sa(e)&&!Array.isArray(e)&&typeof e!="number"&&typeof e!="boolean"&&typeof e!="string"){let o=e==null?"null":e.constructor.name;throw new Error(`Argument '${t}' passed to '${a}' must be a Tensor or TensorLike, but got '${o}'`)}let s=Yn(e,r);!sa(e)&&!Array.isArray(e)&&(e=[e]);let i=r!=="string"?dh(e,r):Xr(e,[],!0);return L.makeTensor(i,s,r)}function ld(e,t,a,n="numeric"){if(!Array.isArray(e))throw new Error(`Argument ${t} passed to ${a} must be a \`Tensor[]\` or \`TensorLike[]\``);return e.map((r,s)=>E(r,`${t}[${s}]`,a,n))}var K2="__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+K2;let r=(...s)=>{L.startScope(a);try{let i=n(...s);return qc(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 dT(e,t){let a=E(e,"real","complex"),n=E(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(Td,r)}var vr=z({complex_:dT});function ss(e,t,a,n){if(n==null)n=Hc(e);else if(n==="complex64")throw new Error("Cannot construct a complex64 tensor directly. Please use tf.complex(real, imag).");if(typeof e=="object"&&("texture"in e||"buffer"in e&&!(e.buffer instanceof ArrayBuffer))){if(n!=="float32"&&n!=="int32")throw new Error(`Creating tensor from GPU data only supports 'float32'|'int32' dtype, while the dtype is ${n}.`);return L.backend.createTensorFromGPUData(e,t||a,n)}if(!sa(e)&&!Array.isArray(e)&&typeof e!="number"&&typeof e!="boolean"&&typeof e!="string")throw new Error("values passed to tensor(values) must be a number/boolean/string or an array of numbers/booleans/strings, or a TypedArray");if(t!=null){en(t);let r=xt(t),s=xt(a);F(r===s,()=>`Based on the provided shape, [${t}], the tensor should have ${r} values but has ${s}`);for(let i=0;i<a.length;++i){let o=a[i],l=i===a.length-1?o!==xt(t.slice(i)):!0;F(a[i]===t[i]||!l,()=>`Error creating a new Tensor. Inferred shape (${a}) does not match the provided shape (${t}). `)}}return!sa(e)&&!Array.isArray(e)&&(e=[e]),t=t||a,e=n!=="string"?dh(e,n):Xr(e,[],!0),L.makeTensor(e,t,n)}function Ue(e,t,a){let n=Yn(e,a);return ss(e,t,n,a)}var Km={float32:4,float16:2,int32:4,uint16:2,uint8:1,bool:1,complex64:8},Rc=4;async function pT(e,t){let a=[],n=[],r=Array.isArray(e)?e.map(i=>i.name):Object.keys(e);for(let i=0;i<r.length;++i){let o=r[i],l=Array.isArray(e)?e[i].tensor:e[o];if(l.dtype!=="float32"&&l.dtype!=="int32"&&l.dtype!=="bool"&&l.dtype!=="string"&&l.dtype!=="complex64")throw new Error(`Unsupported dtype in weight '${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)+Rc*d.length,f=new Uint8Array(h),m=0;for(let g=0;g<d.length;g++){let y=d[g],x=new Uint8Array(new Uint32Array([y.length]).buffer);f.set(x,m),m+=Rc,f.set(y,m),m+=y.length}c(f)});n.push(p)}else n.push(l.data());t!=null&&(u.group=t),a.push(u)}let s=await Promise.all(n);return{data:cT(s),specs:a}}function Ix(e,t){let a={},n,r=0;for(let s of t){let i=s.name,o=s.dtype,l=s.shape,u=xt(l),p;if("quantization"in s){let c=s.quantization;if(c.dtype==="uint8"||c.dtype==="uint16"){if(!("min"in c&&"scale"in c))throw new Error(`Weight ${s.name} with quantization ${c.dtype} doesn't have corresponding metadata min and scale.`)}else if(c.dtype==="float16"){if(o!=="float32")throw new Error(`Weight ${s.name} is quantized with ${c.dtype} which only supports weights of type float32 not ${o}.`)}else throw new Error(`Weight ${s.name} has unknown quantization dtype ${c.dtype}. Supported quantization dtypes are: 'uint8', 'uint16', and 'float16'.`);let d=Km[c.dtype],h=e.slice(r,r+u*d),f=c.dtype==="uint8"?new Uint8Array(h):new Uint16Array(h);if(o==="float32")if(c.dtype==="uint8"||c.dtype==="uint16"){p=new Float32Array(f.length);for(let m=0;m<f.length;m++){let g=f[m];p[m]=g*c.scale+c.min}}else if(c.dtype==="float16")n===void 0&&(n=xT()),p=n(f);else throw new Error(`Unsupported quantization type ${c.dtype} for weight type float32.`);else if(o==="int32"){if(c.dtype!=="uint8"&&c.dtype!=="uint16")throw new Error(`Unsupported quantization type ${c.dtype} for weight type int32.`);p=new Int32Array(f.length);for(let m=0;m<f.length;m++){let g=f[m];p[m]=Math.round(g*c.scale+c.min)}}else throw new Error(`Unsupported dtype in weight '${i}': ${o}`);r+=u*d}else if(o==="string"){let c=xt(s.shape);p=[];for(let d=0;d<c;d++){let h=new Uint32Array(e.slice(r,r+Rc))[0];r+=Rc;let f=new Uint8Array(e.slice(r,r+h));p.push(f),r+=h}}else{let c=Km[o],d=e.slice(r,r+u*c);if(o==="float32")p=new Float32Array(d);else if(o==="int32")p=new Int32Array(d);else if(o==="bool")p=new Uint8Array(d);else if(o==="complex64"){p=new Float32Array(d);let h=new Float32Array(p.length/2),f=new Float32Array(p.length/2);for(let y=0;y<h.length;y++)h[y]=p[y*2],f[y]=p[y*2+1];let m=Ue(h,l,"float32"),g=Ue(f,l,"float32");a[i]=vr(m,g),m.dispose(),g.dispose()}else throw new Error(`Unsupported dtype in weight '${i}': ${o}`);r+=u*c}o!=="complex64"&&(a[i]=Ue(p,l,o))}return a}function cT(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 Z2=typeof Buffer!="undefined"&&(typeof Blob=="undefined"||typeof atob=="undefined"||typeof btoa=="undefined");function B5(e){return Z2?Buffer.byteLength(e):new Blob([e]).size}function hT(e){if(Z2)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 fT(e){if(Z2){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 Y2(e){if(e.length===1)return e[0];let t=0;e.forEach(r=>{t+=r.byteLength});let a=new Uint8Array(t),n=0;return e.forEach(r=>{a.set(new Uint8Array(r),n),n+=r.byteLength}),a.buffer}function W5(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 Sx(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 Tx(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 J2(e,t){let a,n;return e.weightsManifest!=null&&([a,n]=await t(e.weightsManifest)),Tx(e,a,n)}function Zd(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:B5(JSON.stringify(e.modelTopology)),weightSpecsBytes:e.weightSpecs==null?0:B5(JSON.stringify(e.weightSpecs)),weightDataBytes:e.weightData==null?0:e.weightData.byteLength}}function Cx(e){let t=[];for(let a of e)t.push(...a.weights);return t}function mT(){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 gT(){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 yT(){let e=new Uint32Array(64);for(let t=0;t<64;t++)e[t]=1024;return e[0]=e[32]=0,e}function xT(){let e=mT(),t=gT(),a=yT();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 Mt=class{constructor(){this.saveRouters=[],this.loadRouters=[]}static getInstance(){return Mt.instance==null&&(Mt.instance=new Mt),Mt.instance}static registerSaveRouter(e){Mt.getInstance().saveRouters.push(e)}static registerLoadRouter(e){Mt.getInstance().loadRouters.push(e)}static getSaveHandlers(e){return Mt.getHandlers(e,"save")}static getLoadHandlers(e,t){return Mt.getHandlers(e,"load",t)}static getHandlers(e,t,a){let n=[];return(t==="load"?Mt.getInstance().loadRouters:Mt.getInstance().saveRouters).forEach(r=>{let s=r(e,a);s!==null&&n.push(s)}),n}},AT=e=>Mt.registerSaveRouter(e),bT=e=>Mt.registerLoadRouter(e),vT=e=>Mt.getSaveHandlers(e),kT=(e,t)=>Mt.getLoadHandlers(e,t),Zm="tensorflowjs",Ym=1,Os="models_store",Lr="model_info_store";function Nx(){if(!V().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 Jm(e){let t=e.result;t.createObjectStore(Os,{keyPath:"modelPath"}),t.createObjectStore(Lr,{keyPath:"modelPath"})}var zs=class{constructor(e){if(this.indexedDB=Nx(),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(Zm,Ym);r.onupgradeneeded=()=>Jm(r),r.onsuccess=()=>{let s=r.result;if(t==null){let i=s.transaction(Os,"readonly"),o=i.objectStore(Os).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{let i=Zd(t),o=s.transaction(Lr,"readwrite"),l=o.objectStore(Lr),u=l.put({modelPath:this.modelPath,modelArtifactsInfo:i}),p;u.onsuccess=()=>{p=s.transaction(Os,"readwrite");let c=p.objectStore(Os).put({modelPath:this.modelPath,modelArtifacts:t,modelArtifactsInfo:i});c.onsuccess=()=>a({modelArtifactsInfo:i}),c.onerror=d=>{l=o.objectStore(Lr);let h=l.delete(this.modelPath);h.onsuccess=()=>(s.close(),n(c.error)),h.onerror=f=>(s.close(),n(c.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)})}};zs.URL_SCHEME="indexeddb://";var Ex=e=>V().getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(zs.URL_SCHEME)?wT(e.slice(zs.URL_SCHEME.length)):null;Mt.registerSaveRouter(Ex);Mt.registerLoadRouter(Ex);function wT(e){return new zs(e)}function IT(e){return e.startsWith(zs.URL_SCHEME)?e.slice(zs.URL_SCHEME.length):e}var ST=class{constructor(){this.indexedDB=Nx()}async listModels(){return new Promise((e,t)=>{let a=this.indexedDB.open(Zm,Ym);a.onupgradeneeded=()=>Jm(a),a.onsuccess=()=>{let n=a.result,r=n.transaction(Lr,"readonly"),s=r.objectStore(Lr).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=IT(e),new Promise((t,a)=>{let n=this.indexedDB.open(Zm,Ym);n.onupgradeneeded=()=>Jm(n),n.onsuccess=()=>{let r=n.result,s=r.transaction(Lr,"readwrite"),i=s.objectStore(Lr),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(Os,"readwrite");let c=l.objectStore(Os).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)})}},xr="/",Qo="tensorflowjs_models",Rx="info",TT="model_topology",CT="weight_specs",NT="weight_data",ET="model_metadata";function Mx(e){return{info:[Qo,e,Rx].join(xr),topology:[Qo,e,TT].join(xr),weightSpecs:[Qo,e,CT].join(xr),weightData:[Qo,e,NT].join(xr),modelMetadata:[Qo,e,ET].join(xr)}}function $x(e){for(let t of Object.values(e))window.localStorage.removeItem(t)}function RT(e){let t=e.split(xr);if(t.length<3)throw new Error(`Invalid key format: ${e}`);return t.slice(1,t.length-1).join(xr)}function MT(e){return e.startsWith(Ls.URL_SCHEME)?e.slice(Ls.URL_SCHEME.length):e}var Ls=class{constructor(e){if(!V().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=Mx(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=Zd(e);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,hT(e.weightData));let r={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(r)),{modelArtifactsInfo:n}}catch(r){throw $x(this.keys),new Error(`Failed to save model '${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 '${this.modelPath}' are missing.`);return t.weightData=fT(s),t}};Ls.URL_SCHEME="localstorage://";var _x=e=>V().getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(Ls.URL_SCHEME)?$T(e.slice(Ls.URL_SCHEME.length)):null;Mt.registerSaveRouter(_x);Mt.registerLoadRouter(_x);function $T(e){return new Ls(e)}var _T=class{constructor(){F(V().getBool("IS_BROWSER"),()=>"Current environment is not a web browser"),F(typeof window=="undefined"||typeof window.localStorage!="undefined",()=>"Current browser does not appear to support localStorage"),this.LS=window.localStorage}async listModels(){let e={},t=Qo+xr,a=xr+Rx;for(let n=0;n<this.LS.length;++n){let r=this.LS.key(n);if(r.startsWith(t)&&r.endsWith(a)){let s=RT(r);e[s]=JSON.parse(this.LS.getItem(r))}}return e}async removeModel(e){e=MT(e);let t=Mx(e);if(this.LS.getItem(t.info)==null)throw new Error(`Cannot find model at path '${e}'`);let a=JSON.parse(this.LS.getItem(t.info));return $x(t),a}},al="://",Da=class{constructor(){this.managers={}}static getInstance(){return Da.instance==null&&(Da.instance=new Da),Da.instance}static registerManager(e,t){F(e!=null,()=>"scheme must not be undefined or null."),e.endsWith(al)&&(e=e.slice(0,e.indexOf(al))),F(e.length>0,()=>"scheme must not be an empty string.");let a=Da.getInstance();F(a.managers[e]==null,()=>`A model store manager is already registered for scheme '${e}'.`),a.managers[e]=t}static getManager(e){let t=Da.getInstance().managers[e];if(t==null)throw new Error(`Cannot find model manager for scheme '${e}'`);return t}static getSchemes(){return Object.keys(Da.getInstance().managers)}};function yc(e){if(e.indexOf(al)===-1)throw new Error(`The url string provided does not contain a scheme. Supported schemes are: ${Da.getSchemes().join(",")}`);return{scheme:e.split(al)[0],path:e.split(al)[1]}}async function Px(e,t,a=!1){F(e!==t,()=>`Old path and new path are the same: '${e}'`);let n=Mt.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=Mt.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=yc(e).scheme,l=yc(e).path,u=o===yc(e).scheme,p=await r.load();a&&u&&await Da.getManager(o).removeModel(l);let c=await i.save(p);return a&&!u&&await Da.getManager(o).removeModel(l),c.modelArtifactsInfo}async function PT(){let e=Da.getSchemes(),t={};for(let a of e){let n=await Da.getManager(a).listModels();for(let r in n){let s=a+al+r;t[s]=n[r]}}return t}async function FT(e){let t=yc(e);return Da.getManager(t.scheme).removeModel(t.path)}async function OT(e,t){return Px(e,t,!1)}async function DT(e,t){return Px(e,t,!0)}var zT=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"||!V().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 e instanceof Float32Array||e instanceof Int32Array||e instanceof Uint8Array||e instanceof Uint8ClampedArray}};if(V().get("IS_BROWSER")){V().setPlatform("browser",new zT);try{Da.registerManager(Ls.URL_SCHEME,new _T)}catch(e){}try{Da.registerManager(zs.URL_SCHEME,new ST)}catch(e){}}var LT={importFetch:()=>UI()},Mm,BT=class{constructor(){this.util=GI(),this.textEncoder=new this.util.TextEncoder}fetch(e,t){return V().global.fetch!=null?V().global.fetch(e,t):(Mm==null&&(Mm=LT.importFetch()),Mm(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)}};V().get("IS_NODE")&&!V().get("IS_BROWSER")&&V().setPlatform("node",new BT);function _e(e,t="float32",a){return t=t||"float32",en(e),new jt(e,t,a)}function WT(e,t){let a=E(e,"x","cast");if(!ox(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(ti,n,r)}var Xe=z({cast_:WT});function VT(e){let t={x:E(e,"x","clone","string_or_numeric")};return L.runKernel(wi,t)}var wa=z({clone_:VT});function Q2(e,t=!1){console.log(e.toString(t))}vx();var UT={buffer:_e,cast:Xe,clone:wa,print:Q2};QS(UT);function e1(){V().set("PROD",!0)}function GT(){V().set("DEBUG",!0)}function HT(){V().set("DEPRECATION_WARNINGS_ENABLED",!1),console.warn("TensorFlow.js deprecation warnings have been disabled.")}function t1(e){V().getBool("DEPRECATION_WARNINGS_ENABLED")&&console.warn(e+" You can disable deprecation warnings with tf.disableDeprecationWarnings().")}eT(t1);function jT(){L.disposeVariables()}function vt(){return L}function qT(){return L.memory()}function XT(e){return L.profile(e)}function Oe(e,t){return L.tidy(e,t)}function J(e){X2(e).forEach(t=>t.dispose())}function On(e){return L.keep(e)}function KT(e){return L.time(e)}function Yd(e){return L.setBackend(e)}function Jd(){return L.ready()}function ua(){return L.backendName}function ZT(e){L.removeBackend(e)}function a1(e){return L.findBackend(e)}function YT(e){return L.findBackendFactory(e)}function yo(e,t,a=1){return L.registerBackend(e,t,a)}function tr(){return L.backend}function JT(e,t){V().setPlatform(e,t)}function QT(e,t){let a=E(e,"a","add"),n=E(t,"b","add");[a,n]=Tt(a,n);let r={a,b:n};return L.runKernel(ts,r)}var be=z({add_:QT});function eC(e,t){let a=E(e,"a","floorDiv"),n=E(t,"b","floorDiv");[a,n]=Tt(a,n);let r={a,b:n};return L.runKernel(xi,r)}var Qd=z({floorDiv_:eC});function tC(e,t){let a=E(e,"a","div"),n=E(t,"b","div");if([a,n]=Tt(a,n),a.dtype==="int32"&&n.dtype==="int32")return Qd(a,n);let r={a,b:n},s={};return L.runKernel(ci,r,s)}var xe=z({div_:tC});function aC(e,t){let a=E(e,"a","mul"),n=E(t,"b","mul");[a,n]=Tt(a,n);let r={a,b:n};return L.runKernel(Li,r)}var te=z({mul_:aC});function nC(e){let t=E(e,"x","abs");if(t.dtype==="complex64"){let a={x:t};return L.runKernel(Yc,a)}else{let a={x:t};return L.runKernel(vl,a)}}var Ka=z({abs_:nC});function rC(e){let t={x:E(e,"x","acos")};return L.runKernel(kl,t)}var Fx=z({acos_:rC});function sC(e){let t={x:E(e,"x","acosh")};return L.runKernel(wl,t)}var Ox=z({acosh_:sC});function iC(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 ${e.length}`);let t=e.map((r,s)=>E(r,`tensors${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(!es(r.shape,a.shape))throw new Error("All tensors passed to tf.addN() must have the same shape")});let n=t;return L.runKernel(Ks,n)}var ph=z({addN_:iC});function oC(e,t=null,a=!1){let n={x:E(e,"x","all","bool")},r={axis:t,keepDims:a};return L.runKernel(Zs,n,r)}var Dx=z({all_:oC});function lC(e,t=null,a=!1){let n={x:E(e,"x","any","bool")},r={axis:t,keepDims:a};return L.runKernel(Ys,n,r)}var zx=z({any_:lC});function uC(e,t=0){let a={x:E(e,"x","argMax")},n={axis:t};return L.runKernel(Js,a,n)}var ar=z({argMax_:uC});function dC(e,t=0){let a={x:E(e,"x","argMin")},n={axis:t};return L.runKernel(Id,a,n)}var Lx=z({argMin_:dC});function pC(e){let t={x:E(e,"x","asin")};return L.runKernel(Il,t)}var Bx=z({asin_:pC});function cC(e){let t={x:E(e,"x","asinh")};return L.runKernel(Sl,t)}var Wx=z({asinh_:cC});function hC(e){let t={x:E(e,"x","atan")};return L.runKernel(Tl,t)}var Vx=z({atan_:hC});function fC(e,t){let a=E(e,"a","atan2"),n=E(t,"b","atan2");[a,n]=Tt(a,n);let r={a,b:n};return L.runKernel(Nl,r)}var Ux=z({atan2_:fC});function mC(e){let t={x:E(e,"x","atanh")};return L.runKernel(Cl,t)}var Gx=z({atanh_:mC});function gC(e,t,a,n,r="NHWC",s){let i=e[3],o=[...t,i],l=qx(r);return ep(e,o,a,s,n,null,null,l)}function Hx(e,t,a,n,r,s,i="channelsLast"){let[o,l]=ud(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 ep(e,u,a,n,r,s,!1,i)}function yC(e,t,a,n,r,s,i="NDHWC"){let[o,l,u]=Qm(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 jx(e,p,a,n,r,!1,c,s)}function ep(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 ${o}`);let[d,h,,f]=t,[m,g]=ud(a),[y,x]=ud(n),A=nl(d,y),b=nl(h,x),{padInfo:k,outHeight:S,outWidth:C}=bC(r,u,p,m,g,A,b,s,o),N=i?f*c:f,$;return o==="channelsFirst"?$=[l,N,S,C]:o==="channelsLast"&&($=[l,S,C,N]),{batchSize:l,dataFormat:o,inHeight:u,inWidth:p,inChannels:c,outHeight:S,outWidth:C,outChannels:N,padInfo:k,strideHeight:m,strideWidth:g,filterHeight:d,filterWidth:h,effectiveFilterHeight:A,effectiveFilterWidth:b,dilationHeight:y,dilationWidth:x,inShape:e,outShape:$,filterShape:t}}function jx(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 ${i}`);let[h,f,m,,g]=t,[y,x,A]=Qm(a),[b,k,S]=Qm(n),C=nl(h,b),N=nl(f,k),$=nl(m,S),{padInfo:M,outDepth:R,outHeight:I,outWidth:_}=vC(r,u,p,c,y,x,A,C,N,$,o),D=s?g*d:g,W;return i==="channelsFirst"?W=[l,D,R,I,_]:i==="channelsLast"&&(W=[l,R,I,_,D]),{batchSize:l,dataFormat:i,inDepth:u,inHeight:p,inWidth:c,inChannels:d,outDepth:R,outHeight:I,outWidth:_,outChannels:D,padInfo:M,strideDepth:y,strideHeight:x,strideWidth:A,filterDepth:h,filterHeight:f,filterWidth:m,effectiveFilterDepth:C,effectiveFilterHeight:N,effectiveFilterWidth:$,dilationDepth:b,dilationHeight:k,dilationWidth:S,inShape:e,outShape:W,filterShape:t}}function xC(e,t,a,n,r){n==null&&(n=n1(e,t,a));let s=e[0],i=e[1],o=dd((s-t+2*n)/a+1,r),l=dd((i-t+2*n)/a+1,r);return[o,l]}function AC(e,t,a,n,r,s){r==null&&(r=n1(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]=dd((e[o]-t[o]+2*r)/n[o]+1,s));return i}function n1(e,t,a,n=1){let r=nl(t,n);return Math.floor((e[0]*(a-1)-a+r)/2)}function ud(e){return typeof e=="number"?[e,e,e]:e.length===2?[e[0],e[1],1]:e}function Qm(e){return typeof e=="number"?[e,e,e]:e}function nl(e,t){return t<=1?e:e+(e-1)*(t-1)}function bC(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=xC([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),f=Math.floor(d/2),m=d-f,g=Math.floor(h/2),y=h-g;u={top:f,bottom:m,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],f=l==="channelsLast"?e[2][0]:e[3][0],m=l==="channelsLast"?e[2][1]:e[3][1];u={top:d,bottom:h,left:f,right:m,type:d===0&&h===0&&f===0&&m===0?"VALID":"EXPLICIT"},p=dd((t-s+d+h)/n+1,o),c=dd((a-i+f+m)/r+1,o)}else throw Error(`Unknown padding parameter: ${e}`);return{padInfo:u,outHeight:p,outWidth:c}}function vC(e,t,a,n,r,s,i,o,l,u,p){let c,d,h,f;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 m=AC([t,a,n,1],[o,l,u],1,[r,s,i],e,p);d=m[0],h=m[1],f=m[2]}else if(e==="same"){d=Math.ceil(t/r),h=Math.ceil(a/s),f=Math.ceil(n/i);let m=(d-1)*r+o-t,g=(h-1)*s+l-a,y=(f-1)*i+u-n,x=Math.floor(m/2),A=m-x,b=Math.floor(g/2),k=g-b,S=Math.floor(y/2),C=y-S;c={top:b,bottom:k,left:S,right:C,front:x,back:A,type:"SAME"}}else throw Error(`Unknown padding parameter: ${e}`);return{padInfo:c,outDepth:d,outHeight:h,outWidth:f}}function dd(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 pd(e){let[t,a,n]=ud(e);return t===1&&a===1&&n===1}function wr(e,t){return pd(e)||pd(t)}function Bs(e){return ud(e).every(t=>t>0)}function qx(e){if(e==="NHWC")return"channelsLast";if(e==="NCHW")return"channelsFirst";throw new Error(`Unknown dataFormat ${e}`)}function Cn(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(il(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(il(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 kC(e,t){let a={x:E(e,"x","reshape","string_or_numeric")},n={shape:t};return L.runKernel(Hl,a,n)}var Q=z({reshape_:kC});function wC(e,t,a,n,r){let s=E(e,"x","avgPool","float32"),i=1;F(wr(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}.`),Cn("avgPool",n,r);let u={x:o},p={filterSize:t,strides:a,pad:n,dimRoundingMode:r},c=L.runKernel(Qs,u,p);return c=Xe(c,s.dtype),l?Q(c,[c.shape[1],c.shape[2],c.shape[3]]):c}var r1=z({avgPool_:wC});function IC(e,t,a,n,r,s="NDHWC"){let i=E(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}'`),Cn("avgPool3d",n,r);let u={x:o},p={filterSize:t,strides:a,pad:n,dimRoundingMode:r,dataFormat:s},c=L.runKernel(Kc,u,p);return c=Xe(c,o.dtype),l?Q(c,[c.shape[1],c.shape[2],c.shape[3],c.shape[4]]):c}var Xx=z({avgPool3d_:IC});function SC(e,t=0){F(e.length>=1,()=>"Pass at least one tensor to concat");let a=ld(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 wa(a[0]);let n=a,r={axis:t};return L.runKernel(Rl,n,r)}var st=z({concat_:SC});function TC(e,t,a=!1,n=!1){let r=E(e,"a","matMul"),s=E(t,"b","matMul");[r,s]=Tt(r,s);let i={a:r,b:s},o={transposeA:a,transposeB:n};return L.runKernel(ei,i,o)}var ot=z({matMul_:TC});function CC(e){let t={x:E(e,"x","sigmoid","float32")};return L.runKernel(ro,t)}var za=z({sigmoid_:CC});function NC(e,t,a){let n=E(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(Xl,r,s)}var Fe=z({slice_:NC});function EC(e){let t={x:E(e,"x","tanh","float32")};return L.runKernel(ho,t)}var Mc=z({tanh_:EC});function RC(e,t,a,n,r,s){let i=E(e,"forgetBias","basicLSTMCell"),o=E(t,"lstmKernel","basicLSTMCell"),l=E(a,"lstmBias","basicLSTMCell"),u=E(n,"data","basicLSTMCell"),p=E(r,"c","basicLSTMCell"),c=E(s,"h","basicLSTMCell"),d=st([u,c],1),h=ot(d,o),f=be(h,l),m=f.shape[0],g=f.shape[1]/4,y=[m,g],x=Fe(f,[0,0],y),A=Fe(f,[0,g],y),b=Fe(f,[0,g*2],y),k=Fe(f,[0,g*3],y),S=be(te(za(x),Mc(A)),te(p,za(be(i,b)))),C=te(Mc(S),za(k));return[S,C]}var Kx=z({basicLSTMCell_:RC});function MC(e,t,a){let n=E(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(El,s,i)}var s1=z({batchToSpaceND_:MC});function $C(e){let t;return e.rank===0||e.rank===1?t=Q(e,[1,1,1,e.size]):e.rank===2?t=Q(e,[1,1,e.shape[0],e.shape[1]]):e.rank===3?t=Q(e,[1,e.shape[0],e.shape[1],e.shape[2]]):t=e,t}function _C(e,t,a,n,r,s){s==null&&(s=.001);let i=E(e,"x","batchNorm"),o=E(t,"mean","batchNorm"),l=E(a,"variance","batchNorm"),u;r!=null&&(u=E(r,"scale","batchNorm"));let p;n!=null&&(p=E(n,"offset","batchNorm")),F(o.rank===l.rank,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),F(p==null||o.rank===p.rank,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),F(u==null||o.rank===u.rank,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let c={x:$C(i),scale:u,offset:p,mean:o,variance:l},d={varianceEpsilon:s},h=L.runKernel(Ai,c,d);return Q(h,i.shape)}var tp=z({batchNorm_:_C});function PC(e,t,a,n,r,s){let i=E(e,"x","batchNorm"),o=E(t,"mean","batchNorm"),l=E(a,"variance","batchNorm"),u;r!=null&&(u=E(r,"scale","batchNorm"));let p;return n!=null&&(p=E(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}.`),tp(i,o,l,p,u,s)}var Zx=z({batchNorm2d_:PC});function FC(e,t,a,n,r,s){let i=E(e,"x","batchNorm"),o=E(t,"mean","batchNorm"),l=E(a,"variance","batchNorm"),u;r!=null&&(u=E(r,"scale","batchNorm"));let p;return n!=null&&(p=E(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}.`),tp(i,o,l,p,u,s)}var Yx=z({batchNorm3d_:FC});function OC(e,t,a,n,r,s){let i=E(e,"x","batchNorm"),o=E(t,"mean","batchNorm"),l=E(a,"variance","batchNorm"),u;r!=null&&(u=E(r,"scale","batchNorm"));let p;return n!=null&&(p=E(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}.`),tp(i,o,l,p,u,s)}var Jx=z({batchNorm4d_:OC});function DC(e,t,a){let n=E(e,"x","bincount"),r=E(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(Sd,s,i)}var i1=z({bincount_:DC});function zC(e,t){let a=E(e,"s0","broadcastArgs","int32"),n=E(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 ${n.rank}`);let r={s0:a,s1:n};return L.runKernel(Zc,r)}var Qx=z({broadcastArgs_:zC});function LC(e,t){let a=E(e,"broadcastTo","x"),n=a.shape;if(en(t),t.length<a.rank)throw new Error(`broadcastTo(): shape.length=${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 [${t}].`);if(s.map((l,u)=>l>1?u:-1).filter(l=>l>=0).length===0)return wa(a);let i={x:a},o={reps:s};return L.runKernel(ns,i,o)}var rl=z({broadcastTo_:LC});function BC(e){let t={x:E(e,"x","ceil","float32")};return L.runKernel(ai,t)}var eA=z({ceil_:BC});function nr(e,t,a){en(e);let n={shape:e,value:t,dtype:a};return L.runKernel(Pl,{},n)}function WC(e,t,a){let n=E(e,"x","clipByValue");if(F(t<=a,()=>`Error in clip: min (${t}) must be less than or equal to max (${a}).`),t===a)return nr(n.shape,t,n.dtype);let r={x:n},s={clipValueMin:t,clipValueMax:a};return L.runKernel(as,r,s)}var tA=z({clipByValue_:WC});function VC(e){return st(e,0)}var aA=z({concat1d_:VC});function UC(e,t){return st(e,t)}var ru=z({concat2d_:UC});function GC(e,t){return st(e,t)}var nA=z({concat3d_:GC});function HC(e,t){return st(e,t)}var rA=z({concat4d_:HC});function jC(e,t,a,n,r="NHWC",s=[1,1],i){let o=E(e,"x","conv2d","float32"),l=E(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 ${l.rank}.`),Cn("conv2d",n,i);let c=r==="NHWC"?u.shape[3]:u.shape[1];F(c===l.shape[2],()=>`Error in conv2d: depth of input (${c}) must match input depth for filter ${l.shape[2]}.`),F(wr(a,s),()=>`Error in conv2D: Either strides or dilations must be 1. Got strides ${a} and dilations '${s}'`),F(Bs(s),()=>"Error in conv2D: Dilated rates should be larger than 0."),F(Bs(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},f=L.runKernel(ni,d,h);return p?Q(f,[f.shape[1],f.shape[2],f.shape[3]]):f}var ap=z({conv2d_:jC});function qC(e,t,a,n,r="NWC",s=1,i){let o=E(e,"x","conv1d"),l=E(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 ${l.rank}.`),Cn("conv1d",n,i),F(u.shape[2]===l.shape[1],()=>`Error in conv1d: depth of input (${u.shape[2]}) must match input depth for filter ${l.shape[1]}.`),F(wr(a,s),()=>`Error in conv1D: Either stride or dilation must be 1. Got stride ${a} and dilation '${s}'`),F(Bs(s),()=>"Error in conv1D: Dilated rates should be larger than 0."),F(Bs(a),()=>"Error in conv1D: Stride should be larger than 0."),F(r==="NWC",()=>`Error in conv1d: got dataFormat of ${r} but only NWC is currently supported.`);let c=Q(l,[1,l.shape[0],l.shape[1],l.shape[2]]),d=Q(u,[u.shape[0],1,u.shape[1],u.shape[2]]),h=ap(d,c,[1,a],n,"NHWC",[1,s],i);return p?Q(h,[h.shape[2],h.shape[3]]):Q(h,[h.shape[0],h.shape[2],h.shape[3]])}var sA=z({conv1d_:qC});function XC(e,t,a,n,r,s="NHWC",i){F(e.length===t.rank,()=>`Length of inShape (${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]}.`),Cn("conv2dDerInput",r,i);let d={dy:l,filter:a},h={strides:n,pad:r,dataFormat:s,dimRoundingMode:i,inputShape:o},f=L.runKernel(ri,d,h);return u?Q(f,[f.shape[1],f.shape[2],f.shape[3]]):f}var iA=z({conv2DBackpropInput_:XC});function KC(e,t,a,n,r,s){let i=E(e,"x","conv2dTranspose"),o=E(t,"filter","conv2dTranspose");return iA(a,i,o,n,r,"NHWC",s)}var oA=z({conv2dTranspose_:KC});function ZC(e,t,a,n,r="NDHWC",s=[1,1,1]){let i=E(e,"x","conv3d"),o=E(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(wr(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 ${r} but only NDHWC is currently supported.`),F(Bs(s),()=>"Error in conv3D: Dilated rates should be larger than 0."),F(Bs(a),()=>"Error in conv3D: Strides should be larger than 0.");let p={x:l,filter:o},c={strides:a,pad:n,dataFormat:r,dilations:s},d=L.runKernel(Jc,p,c);return u?Q(d,[d.shape[1],d.shape[2],d.shape[3],d.shape[4]]):d}var lA=z({conv3d_:ZC});function YC(e,t,a,n,r){F(e.length===t.rank,()=>`Length of inShape (${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(Qc,p,c);return o?Q(d,[d.shape[1],d.shape[2],d.shape[3],d.shape[4]]):d}var JC=z({conv3DBackpropInput_:YC});function QC(e,t,a,n,r){let s=E(e,"x","conv3dTranspose"),i=E(t,"filter","conv3dTranspose");return JC(a,s,i,n,r)}var uA=z({conv3dTranspose_:QC});function eN(e){let t={x:E(e,"x","cos","float32")};return L.runKernel(si,t)}var dA=z({cos_:eN});function tN(e){let t={x:E(e,"x","cosh","float32")};return L.runKernel(ii,t)}var pA=z({cosh_:tN});function aN(e,t=0,a=!1,n=!1){let r={x:E(e,"x","cumprod")},s={axis:t,exclusive:a,reverse:n};return L.runKernel(oi,r,s)}var cA=z({cumprod_:aN});function nN(e,t=0,a=!1,n=!1){let r={x:E(e,"x","cumsum")},s={axis:t,exclusive:a,reverse:n};return L.runKernel(li,r,s)}var hA=z({cumsum_:nN});function rN(e,t,a,n=!1){let r=E(e,"x","denseBincount"),s=E(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(Nd,i,o)}var fA=z({denseBincount_:rN});function sN(e,t,a="NHWC"){let n=E(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(di,o,l)}var mA=z({depthToSpace_:sN});function iN(e,t,a,n,r="NHWC",s=[1,1],i){let o=E(e,"x","depthwiseConv2d","float32"),l=E(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]}.`),Cn("depthwiseConv2d",n,i);let d={x:u,filter:l},h={strides:a,pad:n,dataFormat:r,dilations:s,dimRoundingMode:i},f=L.runKernel(pi,d,h);return p?Q(f,[f.shape[1],f.shape[2],f.shape[3]]):f}var ch=z({depthwiseConv2d_:iN});function oN(e){let t={x:E(e,"x","diag")};return L.runKernel(Ed,t)}var gA=z({diag_:oN});function lN(e,t,a,n,r=[1,1],s="NHWC"){let i=E(e,"x","dilation2d"),o=E(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(Rd,p,c);return u?Q(d,[d.shape[1],d.shape[2],d.shape[3]]):d}var yA=z({dilation2d_:lN}),xo={};Ze(xo,{assertAndGetBroadcastShape:()=>zt,getBroadcastDims:()=>xA,getReductionAxes:()=>o1});function xA(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 o1(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 zt(e,t){let a=[],n=Math.max(e.length,t.length);for(let r=0;r<n;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)a.unshift(i);else if(i===1)a.unshift(s);else if(s!==i){let o=`Operands could not be broadcast together with shapes ${e} and ${t}.`;throw Error(o)}else a.unshift(s)}return a}function uN(e,t){let a=E(e,"a","equal","string_or_numeric"),n=E(t,"b","equal","string_or_numeric");[a,n]=Tt(a,n),zt(a.shape,n.shape);let r={a,b:n};return L.runKernel(fi,r)}var l1=z({equal_:uN});function dN(e,t,a){let n=E(t,"a","where"),r=E(a,"b","where"),s=E(e,"condition","where","bool"),i=zt(zt(s.shape,n.shape),r.shape),o=rl(s,i),l=rl(n,i),u=rl(r,i),p={condition:o,t:l,e:u};return L.runKernel(jl,p)}var Ws=z({where_:dN});function pN(e){let t={x:E(e,"x","zerosLike")};return L.runKernel(nu,t)}var Ya=z({zerosLike_:pN});function cN(e,t){let a=E(e,"a","div"),n=E(t,"b","div");[a,n]=Tt(a,n);let r=xe(a,n),s=Ya(r),i=l1(n,s);return Ws(i,s,r)}var AA=z({divNoNan_:cN});function hN(e,t){let a=E(e,"t1","dot"),n=E(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 ${s}.`),a.rank===1&&n.rank===1){let i=Q(a,[1,-1]),o=Q(n,[-1,1]),l=ot(i,o);return Q(l,[])}else if(a.rank===1&&n.rank===2){let i=Q(a,[1,-1]),o=Q(n,[n.shape[0],n.shape[1]]),l=ot(i,o);return Q(l,[l.size])}else if(a.rank===2&&n.rank===1){let i=Q(n,[-1,1]),o=ot(a,i);return Q(o,[o.size])}else{let i=Q(n,[n.shape[0],n.shape[1]]);return ot(a,i)}}var bA=z({dot_:hN});function fN(e,...t){let a=t.map((r,s)=>E(r,`tensors${s}`,"einsum")),n={equation:e};return L.runKernel(Md,a,n)}var vA=z({einsum_:fN});function mN(e){let t={x:E(e,"x","elu","float32")};return L.runKernel(hi,t)}var u1=z({elu_:mN});function gN(e){let t=E(e,"x","erf");F(t.dtype==="int32"||t.dtype==="float32",()=>"Input dtype must be `int32` or `float32`."),t.dtype==="int32"&&(t=Xe(t,"float32"));let a={x:t};return L.runKernel(Ml,a)}var kA=z({erf_:gN});function d1(e,t){for(let a=0;a<e.length;++a)if(e[e.length-a-1]!==t-1-a)return!1;return!0}function wA(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 yN(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 np(e,t){let a=t.map(n=>1);return wA(e,a,t)}function xN(e,t,a){F(d1(t,a),()=>`${e} supports only inner-most axes for now. Got axes ${t} and rank-${a} input.`)}function AN(e,t){if(d1(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 bN(e){return e.map((t,a)=>[a,t]).sort((t,a)=>t[1]-a[1]).map(t=>t[0])}function vN(e,t){let a=[];for(let n=t-e;n<t;++n)a.push(n);return a}function kN(e,t=null,a=!1){let n={x:E(e,"x","max")},r={reductionIndices:t,keepDims:a};return L.runKernel($i,n,r)}var ha=z({max_:kN});function wN(e,t=null,a=!1){let n={x:E(e,"x","min")},r={axis:t,keepDims:a};return L.runKernel(Oi,n,r)}var Kr=z({min_:wN});function IN(e,t){let a=E(e,"base","pow"),n=E(t,"exp","pow");[a,n]=Tt(a,n);let r={a,b:n};return L.runKernel(Hi,r)}var ll=z({pow_:IN});function ze(e,t){if((sa(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"&&sa(e)&&!(e instanceof Uint8Array))throw new Error("When making a scalar from encoded string, the value must be `Uint8Array`.");return ss(e,[],[],t)}function SN(e){let t={x:E(e,"x","sqrt","float32")};return L.runKernel(so,t)}var Jn=z({sqrt_:SN});function TN(e){let t=E(e,"x","square"),a={};return L.runKernel("Square",{x:t},a)}var Tn=z({square_:TN});function CN(e,t=null,a=!1){let n=E(e,"x","sum");n.dtype==="bool"&&(n=Xe(n,"int32"));let r={x:n},s={axis:t,keepDims:a};return L.runKernel(io,r,s)}var rt=z({sum_:CN});function NN(e,t="euclidean",a=null,n=!1){e=E(e,"x","norm");let r=IA(e,t,a),s=r.shape;if(n){let i=wd(a,e.shape);s=np(r.shape,i)}return Q(r,s)}function IA(e,t,a=null){if(e.rank===0)return Ka(e);if(e.rank!==1&&a===null)return IA(Q(e,[-1]),t,a);if(e.rank===1||typeof a=="number"||Array.isArray(a)&&a.length===1){if(t===1)return rt(Ka(e),a);if(t===1/0)return ha(Ka(e),a);if(t===-1/0)return Kr(Ka(e),a);if(t==="euclidean"||t===2)return Jn(rt(ll(Ka(e),ze(2,"int32")),a));throw new Error(`Error in norm: invalid ord value: ${t}`)}if(Array.isArray(a)&&a.length===2){if(t===1)return ha(rt(Ka(e),a[0]),a[1]-1);if(t===1/0)return ha(rt(Ka(e),a[1]),a[0]);if(t===-1/0)return Kr(rt(Ka(e),a[1]),a[0]);if(t==="fro"||t==="euclidean")return Jn(rt(Tn(e),a));throw new Error(`Error in norm: invalid ord value: ${t}`)}throw new Error(`Error in norm: invalid axis: ${a}`)}var rp=z({norm_:NN});function EN(e,t=null,a=!1){return rp(e,"euclidean",t,a)}var SA=z({euclideanNorm_:EN});function RN(e){let t={x:E(e,"x","exp")};return L.runKernel(mi,t)}var Zr=z({exp_:RN});function MN(e,t=0){let a=E(e,"x","expandDims","string_or_numeric");F(t<=a.rank,()=>"Axis must be <= rank of the tensor");let n={input:a},r={dim:t};return L.runKernel($l,n,r)}var Gt=z({expandDims_:MN});function $N(e){let t={x:E(e,"x","expm1")};return L.runKernel(_l,t)}var TA=z({expm1_:$N});function _N(e,t){let a=E(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(ns,n,r)}var Ur=z({tile_:_N});function PN(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 Ur(Gt(i,0),[a[0],1,1]);if(a.length===2)return Ur(Gt(Gt(i,0),0),[a[0],a[1],1,1]);if(a.length===3)return Ur(Gt(Gt(Gt(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 p1=z({eye_:PN});function FN(e){let t={x:E(e,"x","floor","float32")};return L.runKernel(yi,t)}var c1=z({floor_:FN});function ON(e,t,a=0,n=0){let r=E(e,"x","gather"),s=E(t,"indices","gather","int32"),i={x:r,indices:s},o={axis:a,batchDims:n};return L.runKernel(Fl,i,o)}var h1=z({gather_:ON});function DN(e,t){let a=E(e,"a","greater","string_or_numeric"),n=E(t,"b","greater","string_or_numeric");[a,n]=Tt(a,n),zt(a.shape,n.shape);let r={a,b:n};return L.runKernel(vi,r)}var sp=z({greater_:DN});function zN(e,t){let a=E(e,"a","greaterEqual","string_or_numeric"),n=E(t,"b","greaterEqual","string_or_numeric");[a,n]=Tt(a,n),zt(a.shape,n.shape);let r={a,b:n};return L.runKernel(ki,r)}var f1=z({greaterEqual_:zN});function LN(e){let t={input:E(e,"input","imag")};return L.runKernel(Pd,t)}var ip=z({imag_:LN});function BN(e){let t={x:E(e,"x","isFinite")};return L.runKernel(Ol,t)}var CA=z({isFinite_:BN});function WN(e){let t={x:E(e,"x","isInf")};return L.runKernel(Dl,t)}var NA=z({isInf_:WN});function VN(e){let t={x:E(e,"x","isNaN")};return L.runKernel(Ii,t)}var EA=z({isNaN_:VN});function UN(e,t=.2){let a={x:E(e,"x","leakyRelu")},n={alpha:t};return L.runKernel(Si,a,n)}var m1=z({leakyRelu_:UN});function GN(e,t){let a=E(e,"a","less","string_or_numeric"),n=E(t,"b","less","string_or_numeric");[a,n]=Tt(a,n),zt(a.shape,n.shape);let r={a,b:n};return L.runKernel(Ti,r)}var RA=z({less_:GN});function HN(e,t){let a=E(e,"a","lessEqual","string_or_numeric"),n=E(t,"b","lessEqual","string_or_numeric");[a,n]=Tt(a,n),zt(a.shape,n.shape);let r={a,b:n};return L.runKernel(Ci,r)}var hh=z({lessEqual_:HN});function MA(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(Fd,{},n)}function jN(e,t=5,a=1,n=1,r=.5){let s=E(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(il(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(Od,l,u);return o?Q(p,[p.shape[1],p.shape[2],p.shape[3]]):p}var $A=z({localResponseNormalization_:jN});function qN(e){let t={x:E(e,"x","log","float32")};return L.runKernel(Ni,t)}var ul=z({log_:qN});function XN(e){let t={x:E(e,"x","log1p")};return L.runKernel(zl,t)}var g1=z({log1p_:XN});function KN(e){return F(Gr(e),()=>"The f passed in grad(f) must be a function"),(t,a)=>{let n=E(t,"x","tf.grad","string_or_numeric"),r=a!=null?E(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)"),fh(i),i[0]})}}function ZN(e){return F(Gr(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=ld(t,"args","tf.grads","string_or_numeric"),r=a!=null?E(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,...])"),fh(i),i})}}function YN(e){return F(Gr(e),()=>"The f passed in valueAndGrad(f) must be a function"),(t,a)=>{F(t instanceof pt,()=>"The x passed in valueAndGrad(f)(x) must be a tensor"),F(a==null||a instanceof pt,()=>"The dy passed in valueAndGrad(f)(x, dy) must be a tensor");let{grads:n,value:r}=L.gradients(()=>e(t),[t],a);return fh(n),{grad:n[0],value:r}}}function JN(e){return F(Gr(e),()=>"The f passed in valueAndGrads(f) must be a function"),(t,a)=>{F(Array.isArray(t)&&t.every(r=>r instanceof pt),()=>"The args passed in valueAndGrads(f)(args) must be array of tensors"),F(a==null||a instanceof pt,()=>"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,...])"),fh(n.grads),n}}function _A(e,t){F(Gr(e),()=>"The f passed in variableGrads(f) must be a function"),F(t==null||Array.isArray(t)&&t.every(u=>u instanceof id),()=>"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 Qn(e){return L.customGrad(e)}function fh(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 QN(e){let t={x:E(e,"x","neg")};return L.runKernel(Bl,t)}var Xn=z({neg_:QN});function eE(e){let t={x:E(e,"x","softplus")};return L.runKernel(Yl,t)}var y1=z({softplus_:eE});function tE(e){let t=E(e,"x","logSigmoid");return Qn(a=>({value:Xn(y1(Xn(a))),gradFunc:n=>te(n,za(Xn(a)))}))(t)}var PA=z({logSigmoid_:tE});function aE(e,t){let a=E(e,"a","sub"),n=E(t,"b","sub");[a,n]=Tt(a,n);let r={a,b:n};return L.runKernel(po,r)}var fe=z({sub_:aE});function nE(e,t=-1){let a=E(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 Qn((n,r)=>{let s=ha(n,t,!0),i=fe(n,s),o=fe(Xe(i,"float32"),ul(rt(Zr(i),t,!0)));return r([o]),{value:o,gradFunc:(l,u)=>{let[p]=u,c=!0,d=Zr(p);return fe(l,te(rt(l,t,c),d))}}})(a)}var FA=z({logSoftmax_:nE});function rE(e,t=null,a=!1){let n=E(e,"x","logSumExp"),r=wd(t,n.shape),s=ha(n,r,!0),i=fe(n,s),o=Zr(i),l=rt(o,r),u=ul(l),p=be(Q(s,u.shape),u);if(a){let c=np(p.shape,r);return Q(p,c)}return p}var x1=z({logSumExp_:rE});function sE(e,t){let a=E(e,"a","logicalAnd","bool"),n=E(t,"b","logicalAnd","bool");zt(a.shape,n.shape);let r={a,b:n};return L.runKernel(Ei,r)}var cd=z({logicalAnd_:sE});function iE(e){let t={x:E(e,"x","logicalNot","bool")};return L.runKernel(Ri,t)}var A1=z({logicalNot_:iE});function oE(e,t){let a=E(e,"a","logicalOr","bool"),n=E(t,"b","logicalOr","bool");zt(a.shape,n.shape);let r={a,b:n};return L.runKernel(Mi,r)}var b1=z({logicalOr_:oE});function lE(e,t){let a=E(e,"a","logicalXor","bool"),n=E(t,"b","logicalXor","bool");return zt(a.shape,n.shape),cd(b1(e,t),A1(cd(e,t)))}var OA=z({logicalXor_:lE}),dc=2147483648;function uE(e,t,a="left"){let n=E(e,"sortedSequence","searchSorted"),r=E(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(xt(l.shape)>=dc)throw new Error(`values tensor size must less than ${dc}`);if(o.shape[1]>=dc)throw new Error(`trailing dim_size must less than ${dc} for int32 output type, was ${o.shape[1]}`);let u={sortedSequence:o,values:l},p={side:a};return L.runKernel(zd,u,p)}var mh=z({searchSorted_:uE});function DA(e,t){return mh(e,t,"left")}function dE(e,t,a,n,r){let s=E(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(wr(a,i),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${a} and dilations '${i}'`),Cn("maxPool",n,r);let u={x:o},p={filterSize:t,strides:a,pad:n,dimRoundingMode:r},c=L.runKernel(Pi,u,p);return l?Q(c,[c.shape[1],c.shape[2],c.shape[3]]):c}var v1=z({maxPool_:dE});function pE(e,t=[1,1,1],a,n,r,s="NDHWC"){let i=E(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 ${s}`),Cn("maxPool3d",n,r);let u={x:o},p={filterSize:t,strides:a,pad:n,dimRoundingMode:r,dataFormat:s},c=L.runKernel(ah,u,p);return l?Q(c,[c.shape[1],c.shape[2],c.shape[3],c.shape[4]]):c}var zA=z({maxPool3d_:pE});function cE(e,t,a,n,r=!1){let s={x:E(e,"x","maxPoolWithArgmax")},i={filterSize:t,strides:a,pad:n,includeBatchInIndex:r},o=L.runKernel(nh,s,i);return{result:o[0],indexes:o[1]}}var LA=z({maxPoolWithArgmax_:cE});function hE(e,t){let a=E(e,"a","maximum"),n=E(t,"b","maximum");[a,n]=Tt(a,n),a.dtype==="bool"&&(a=Xe(a,"int32"),n=Xe(n,"int32")),zt(a.shape,n.shape);let r={a,b:n};return L.runKernel(_i,r)}var k1=z({maximum_:hE});function fE(e,t=null,a=!1){let n={x:E(e,"x","mean")},r={axis:t,keepDims:a};return L.runKernel(Fi,n,r)}var hd=z({mean_:fE});function gn(e,t="float32"){if(en(e),t==="complex64"){let n=gn(e,"float32"),r=gn(e,"float32");return vr(n,r)}let a=jc(xt(e),t);return L.makeTensor(a,e,t)}function Br(e,t="float32"){if(en(e),t==="complex64"){let n=Br(e,"float32"),r=gn(e,"float32");return vr(n,r)}let a=O2(xt(e),t);return L.makeTensor(a,e,t)}function BA(e,t,{indexing:a="xy"}={}){if(a!=="xy"&&a!=="ij")throw new TypeError(`${a} is not a valid third argument to meshgrid`);if(e===void 0)return[];let n=E(e,"x","meshgrid",e instanceof pt?e.dtype:"float32");if(t===void 0)return[n];let r=E(t,"y","meshgrid",t instanceof pt?t.dtype:"float32"),s=xt(n.shape),i=xt(r.shape);return a==="xy"?(n=Q(n,[1,-1]),r=Q(r,[-1,1]),[ot(Br([i,1],n.dtype),n),ot(r,Br([1,s],r.dtype))]):(n=Q(n,[-1,1]),r=Q(r,[1,-1]),[ot(n,Br([1,i],n.dtype)),ot(Br([s,1],r.dtype),r)])}function mE(e,t){let a=E(e,"a","minimum"),n=E(t,"b","minimum");[a,n]=Tt(a,n),a.dtype==="bool"&&(a=Xe(a,"int32"),n=Xe(n,"int32")),zt(a.shape,n.shape);let r={a,b:n};return L.runKernel(Di,r)}var w1=z({minimum_:mE});function gE(e,t,a){F(a==="reflect"||a==="symmetric",()=>`Invalid mode. Mode must be either reflect or symmetric. Got ${a}.`);let n=E(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(zi,i,s)}var WA=z({mirrorPad_:gE});function yE(e,t){let a=E(e,"a","mod"),n=E(t,"b","mod");[a,n]=Tt(a,n);let r={a,b:n};return L.runKernel(Ll,r)}var su=z({mod_:yE});function xE(e,t=null,a=!1){e=E(e,"x","moments");let n=wd(t,e.shape),r=hd(e,n,a),s=r.shape;a||(s=np(r.shape,n));let i=Tn(fe(Xe(e,"float32"),Q(r,s))),o=hd(i,n,a);return{mean:r,variance:o}}var VA=z({moments_:xE});function AE(e,t,a,n){let r=E(t,"data","multiRNNCell"),s=ld(a,"c","multiRNNCell"),i=ld(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 UA=z({multiRNNCell_:AE});function bE(e,t,a,n=!1){let r=E(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(rh,o,l);return i===1?Q(u,[u.size]):u}var GA=z({multinomial_:bE});function vE(e,t){let a=E(e,"a","notEqual","string_or_numeric"),n=E(t,"b","notEqual","string_or_numeric");[a,n]=Tt(a,n),zt(a.shape,n.shape);let r={a,b:n};return L.runKernel(Bi,r)}var I1=z({notEqual_:vE});function kE(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:E(e,"indices","oneHot","int32")},i={dtype:r,depth:t,onValue:a,offValue:n};return L.runKernel(Ui,s,i)}var $c=z({oneHot_:kE});function wE(e){let t={x:E(e,"x","onesLike")};return L.runKernel(Vl,t)}var HA=z({onesLike_:wE});function IE(e,t){let a=E(e,"v1","outerProduct"),n=E(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 ot(r,s)}var jA=z({outerProduct_:IE});function SE(e,t,a=0){let n=E(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(Gi,s,r)}var rr=z({pad_:SE});function TE(e,t,a=0){return F(t.length===2,()=>"Invalid number of paddings. Must be length of 2."),rr(e,[t],a)}var qA=z({pad1d_:TE});function CE(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."),rr(e,t,a)}var XA=z({pad2d_:CE});function NE(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."),rr(e,t,a)}var KA=z({pad3d_:NE});function EE(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."),rr(e,t,a)}var ZA=z({pad4d_:EE});function RE(e,t,a){let n=E(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(Jl,r,s)}var S1=z({spaceToBatchND_:RE});function ME(e,t,a,n,r,s,i){r==null&&(r=[1,1]),s==null&&(s=1),n===0&&(n="valid");let o=E(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(wr(s,r),()=>`Error in pool: Either strides or dilations must be 1. Got strides ${s} and dilations '${r}'`);let p=Hx(l.shape,t,s,r,n),c=[p.dilationHeight,p.dilationWidth],d;n==="same"?d=_E([p.filterHeight,p.filterWidth],c):d=[[0,0],[0,0]];let h=c[0]===1&&c[1]===1,[f,m]=$E([p.inHeight,p.inWidth],c,d),g=h?n:"valid",y=h?l:S1(l,c,f),x=(a==="avg"?()=>r1(y,t,s,g,i):()=>v1(y,t,s,g,i))(),A=h?x:s1(x,c,m);return u?Q(A,[A.shape[1],A.shape[2],A.shape[3]]):A}function $E(e,t,a){let n=a.map(p=>p[0]),r=a.map(p=>p[1]),s=e.concat(n,r),i=t.map((p,c)=>(p-s[c]%p)%p),o=r.map((p,c)=>p+i[c]),l=t.map((p,c)=>[n[c],o[c]]),u=t.map((p,c)=>[0,i[c]]);return[l,u]}function _E(e,t){let a=e.map((s,i)=>s+(s-1)*(t[i]-1)).map(s=>s-1),n=a.map(s=>Math.floor(s/2)),r=a.map((s,i)=>s-n[i]);return a.map((s,i)=>[n[i],r[i]])}var YA=z({pool_:ME});function PE(e,t){let a=E(e,"x","prelu"),n=E(t,"alpha","prelu"),r={x:a,alpha:n};return L.runKernel(ji,r)}var T1=z({prelu_:PE});function FE(e,t=null,a=!1){let n=E(e,"x","prod");n.dtype==="bool"&&(n=Xe(n,"int32"));let r={x:n},s={axis:t,keepDims:a};return L.runKernel(qi,r,s)}var JA=z({prod_:FE});function OE(e,t,a,n){let r=e.map((p,c)=>E(p,`tensors${c}`,"raggedGather","int32")),s=E(t,"paramsDenseValues","raggedGather"),i=E(a,"indices","raggedGather","int32"),o={paramsNestedSplits:r,paramsDenseValues:s,indices:i},l={outputRaggedRank:n},u=L.runKernel(sh,o,l);return{outputNestedSplits:u.slice(0,u.length-1),outputDenseValues:u[u.length-1]}}var QA=z({raggedGather_:OE});function DE(e,t,a){let n=E(e,"starts","raggedRange"),r=E(t,"limits","raggedRange",n.dtype),s=E(a,"deltas","raggedRange",n.dtype),i={starts:n,limits:r,deltas:s},o=L.runKernel(ih,i);return{rtNestedSplits:o[0],rtDenseValues:o[1]}}var eb=z({raggedRange_:DE});function zE(e,t,a,n,r){let s=E(e,"shape","raggedTensorToTensor","int32"),i=E(t,"values","raggedTensorToTensor"),o=E(a,"defaultValue","raggedTensorToTensor",i.dtype),l=n.map((c,d)=>E(c,`tensors${d}`,"raggedTensorToTensor","int32")),u={shape:s,values:i,defaultValue:o,rowPartitionTensors:l},p={rowPartitionTypes:r};return L.runKernel(oh,u,p)}var tb=z({raggedTensorToTensor_:zE});function LE(e,t,a){en(e);let n=xt(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 ab=z({rand_:LE}),C1=xl(Qy()),nb={};Ze(nb,{TEST_EPSILON_FLOAT16:()=>rb,createVideoElement:()=>qE,encodeStrings:()=>sb,expectArrayBuffersEqual:()=>jE,expectArraysClose:()=>WE,expectArraysEqual:()=>UE,expectNumbersClose:()=>GE,expectPromiseToFail:()=>VE,expectValuesInRange:()=>HE,play:()=>XE,testEpsilon:()=>N1});var BE=.001,rb=.1;function WE(e,t,a){return a==null&&(a=N1()),e2(e,t,(n,r)=>E1(n,r,a))}function N1(){return L.backend.floatPrecision()===32?BE:rb}function e2(e,t,a){let n=!0;if((sa(e)||sa(t))&&(n=!1),sa(e)&&sa(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: ${o}`)}if(Array.isArray(e)&&Array.isArray(t)){let i=Yn(e),o=Yn(t);if(!es(i,o))throw new Error(`Arrays have different shapes. Actual: [${i}]. Expected: [${o}]`)}let r=sa(e)?e:Xr(e),s=sa(t)?t:Xr(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 VE(e,t){e().then(()=>t.fail(),()=>t()),typeof expect!="undefined"&&expect().nothing()}function UE(e,t){let a=typeof t=="string"||typeof t=="number"||typeof t=="boolean"?[t]:t;return zr(e)||zr(e[0])||zr(t)||zr(t[0])?e2(e,a,(n,r)=>n==r):e2(e,t,(n,r)=>E1(n,r,0))}function GE(e,t,a){if(a==null&&(a=N1()),!E1(e,t,a))throw new Error(`Numbers differ: actual === ${e}, expected === ${t}`);typeof expect!="undefined"&&expect().nothing()}function E1(e,t,a){return!isFinite(e)&&!isFinite(t)?!0:!(isNaN(e)||isNaN(t)||Math.abs(e-t)>a)}function HE(e,t,a){for(let n=0;n<e.length;n++)if(e[n]<t||e[n]>a)throw new Error(`Value out of range:${e[n]} low: ${t}, high: ${a}`)}function jE(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 sb(e){for(let t=0;t<e.length;t++){let a=e[t];Array.isArray(a)?sb(a):e[t]=qd(a)}return e}function qE(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 XE(e){await e.play(),"requestVideoFrameCallback"in e&&await new Promise(t=>{e.requestVideoFrameCallback(t)})}var R1=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=C1.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}},KE=class{constructor(e,t,a,n){this.alpha=e,this.beta=1/t,this.dtype=a;let r=n||Math.random();this.randu=C1.alea(r.toString()),this.randn=new R1(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)}},ZE=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=C1.alea(n)}convertValue(e){return this.canReturnFloat()?e:Math.round(e)}nextValue(){return this.convertValue(this.min+this.range*this.random())}};function YE(e,t,a=1,n="float32",r){if(en(e),a==null&&(a=1),n==null&&(n="float32"),n!=="float32"&&n!=="int32")throw new Error(`Unsupported data type ${n}`);let s=new KE(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 ib=z({randomGamma_:YE});function JE(e,t=0,a=1,n,r){if(en(e),n!=null&&n==="bool")throw new Error(`Unsupported data type ${n}`);let s=new R1(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 M1=z({randomNormal_:JE});function QE(e,t,a){if(t!=null&&t==="bool")throw new Error(`Unsupported data type ${t}`);return M1(e,0,1,t,a)}var ob=z({randomStandardNormal_:QE});function eR(e,t=0,a=1,n="float32",r){en(e);let s=_e(e,n),i=new ZE(t,a,null,r);for(let o=0;o<s.values.length;o++)s.values[o]=i.nextValue();return s.toTensor()}var $1=z({randomUniform_:eR});function dl(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(Gl,{},r)}function tR(e){let t={input:E(e,"input","real")};return L.runKernel(Dd,t)}var pl=z({real_:tR});function aR(e){let t={x:E(e,"x","reciprocal")};return L.runKernel(Xi,t)}var lb=z({reciprocal_:aR});function nR(e){let t={x:E(e,"x","relu")};return L.runKernel(Ki,t)}var op=z({relu_:nR});function rR(e){let t={x:E(e,"x","relu6")};return L.runKernel(Ji,t)}var _1=z({relu6_:rR});function sR(e,t){let a={x:E(e,"x","reverse")},n={dims:t};return L.runKernel(Qi,a,n)}var Yr=z({reverse_:sR});function iR(e){let t=E(e,"x","reverse");return F(t.rank===1,()=>`Error in reverse1D: x must be rank 1 but got rank ${t.rank}.`),Yr(t,0)}var ub=z({reverse1d_:iR});function oR(e,t){let a=E(e,"x","reverse");return F(a.rank===2,()=>`Error in reverse2D: x must be rank 2 but got rank ${a.rank}.`),Yr(a,t)}var db=z({reverse2d_:oR});function lR(e,t){let a=E(e,"x","reverse");return F(a.rank===3,()=>`Error in reverse3D: x must be rank 3 but got rank ${a.rank}.`),Yr(a,t)}var pb=z({reverse3d_:lR});function uR(e,t){let a=E(e,"x","reverse");return F(a.rank===4,()=>`Error in reverse4D: x must be rank 4 but got rank ${a.rank}.`),Yr(a,t)}var cb=z({reverse4d_:uR});function dR(e){let t={x:E(e,"x","round")};return L.runKernel(eo,t)}var P1=z({round_:dR});function pR(e){let t={x:E(e,"x","rsqrt","float32")};return L.runKernel(to,t)}var hb=z({rsqrt_:pR});function cR(e){let t={x:E(e,"x","selu")};return L.runKernel(ql,t)}var fb=z({selu_:cR});function hR(e,t,a,n,r,s=[1,1],i="NHWC"){let o=E(e,"x","separableConv2d"),l=E(t,"depthwiseFilter","separableConv2d"),u=E(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 ${u.shape[2]}.`);let f=ch(p,l,n,r,i,s),m=ap(f,u,1,"valid",i);return c?Q(m,[m.shape[1],m.shape[2],m.shape[3]]):m}var mb=z({separableConv2d_:hR});async function fR(e,t){let a=E(e,"x","setdiff1d"),n=E(t,"y","setdiff1d");F(a.dtype===n.dtype,()=>`x and y should have the same dtype, but got x (${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 (${n.shape}).`);let r=await a.data(),s=await n.data(),i=new Set(s),o=0;for(let p=0;p<r.length;p++)i.has(r[p])||o++;let l=new jt([o],a.dtype),u=new jt([o],"int32");for(let p=0,c=0;p<r.length;p++)i.has(r[p])||(l.values[c]=r[p],u.values[c]=p,c++);return[l.toTensor(),u.toTensor()]}var gb=fR;function mR(e){let t={x:E(e,"x","sign")};return L.runKernel(Zl,t)}var yb=z({sign_:mR});function gR(e){let t={x:E(e,"x","sin","float32")};return L.runKernel(no,t)}var xb=z({sin_:gR});function yR(e){let t={x:E(e,"x","sinh")};return L.runKernel(Kl,t)}var Ab=z({sinh_:yR});function xR(e,t,a){let n=E(e,"x","slice1d");return F(n.rank===1,()=>`slice1d expects a rank-1 tensor, but got a rank-${n.rank} tensor`),Fe(n,[t],[a])}var bb=z({slice1d_:xR});function AR(e,t,a){let n=E(e,"x","slice2d");return F(n.rank===2,()=>`slice2d expects a rank-2 tensor, but got a rank-${n.rank} tensor`),Fe(n,t,a)}var vb=z({slice2d_:AR});function bR(e,t,a){let n=E(e,"x","slice3d");return F(n.rank===3,()=>`slice3d expects a rank-3 tensor, but got a rank-${n.rank} tensor`),Fe(n,t,a)}var lp=z({slice3d_:bR});function vR(e,t,a){let n=E(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 gh=z({slice4d_:vR});function kR(e,t=-1){let a=E(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(oo,n,r)}var yh=z({softmax_:kR});function wR(e){F(e.dtype==="complex64",()=>`The dtype for tf.spectral.fft() must be complex64 but got ${e.dtype}.`);let t={input:e};return L.runKernel($d,t)}var xh=z({fft_:wR});function IR(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(_d,t)}var fd=z({ifft_:IR});function SR(e){let t=e.shape[e.shape.length-1],a=e.size/t,n;if(t<=2){let r=Q(e,[a,t]);n=fd(r)}else{let r=[a,2*(t-1)],s=Q(pl(e),[a,t]),i=Q(ip(e),[a,t]),o=Yr(Fe(s,[0,1],[a,t-2]),1),l=te(Yr(Fe(i,[0,1],[a,t-2]),1),ze(-1)),u=st([s,o],1),p=st([i,l],1),c=Q(vr(u,p),[r[0],r[1]]);n=fd(c)}if(n=pl(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 F1=z({irfft_:SR});function TR(e,t,a=0){let n={x:E(e,"x","split")},r={numOrSizeSplits:t,axis:a};return L.runKernel(Ql,n,r)}var Ia=z({split_:TR});function CR(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 f=e.shape.map(g=>0),m=e.shape.map(g=>g);m[e.shape.length-1]=t,r=Fe(e,f,m),a=t}else if(t!=null&&t>a){let f=e.shape.map(m=>m);f[e.shape.length-1]=t-a,r=st([e,gn(f)],e.shape.length-1),a=t}else r=e;let s=Ya(r),i=Q(vr(r,s),[n,a]),o=xh(i),l=Math.floor(a/2)+1,u=pl(o),p=ip(o),c=Ia(u,[l,a-l],u.shape.length-1),d=Ia(p,[l,a-l],p.shape.length-1),h=r.shape.slice();return h[r.shape.length-1]=l,Q(vr(c[0],d[0]),h)}var Ah=z({rfft_:CR});function NR(e,t){let a=E(e,"a","squaredDifference"),n=E(t,"b","squaredDifference");[a,n]=Tt(a,n),zt(a.shape,n.shape);let r={a,b:n},s={};return L.runKernel(lo,r,s)}var O1=z({squaredDifference_:NR});function ER(e,t){let a=E(e,"x","squeeze","string_or_numeric");return Q(a,nx(a.shape,t).newShape)}var De=z({squeeze_:ER});function RR(e,t=0){let a=ld(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(Ul,n,r)}var la=z({stack_:RR});function MR(e,t=0){let a={x:E(e,"x","step")},n={alpha:t};return L.runKernel(rs,a,n)}var D1=z({step_:MR});function $R(e,t,a,n,r=0,s=0,i=0,o=0,l=0){let u={x:E(e,"x","stridedSlice","string_or_numeric")},p={begin:t,end:a,strides:n,beginMask:r,endMask:s,ellipsisMask:i,newAxisMask:o,shrinkAxisMask:l};return L.runKernel(uo,u,p)}var kb=z({stridedSlice_:$R});function _R(e){let t={x:E(e,"x","tan","float32")};return L.runKernel(co,t)}var wb=z({tan_:_R});function Ht(e,t){Xs(e);let a=Yn(e,t);if(a.length!==1)throw new Error("tensor1d() requires values to be a flat/TypedArray");return ss(e,null,a,t)}function Kn(e,t,a){if(Xs(e),t!=null&&t.length!==2)throw new Error("tensor2d() requires shape to have two numbers");let n=Yn(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 ss(e,t,n,a)}function z1(e,t,a){if(Xs(e),t!=null&&t.length!==3)throw new Error("tensor3d() requires shape to have three numbers");let n=Yn(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 ss(e,t,n,a)}function Ib(e,t,a){if(Xs(e),t!=null&&t.length!==4)throw new Error("tensor4d() requires shape to have four numbers");let n=Yn(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 ss(e,t,n,a)}function Sb(e,t,a){if(Xs(e),t!=null&&t.length!==5)throw new Error("tensor5d() requires shape to have five numbers");let n=Yn(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 ss(e,t,n,a)}function Tb(e,t,a){if(Xs(e),t!=null&&t.length!==6)throw new Error("tensor6d() requires shape to have six numbers");let n=Yn(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,ss(e,t,n,a)}function PR(e,t=1,a=!0){let n=E(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(fo,s,i);return{values:o,indices:l}}var Cb=z({topk_:PR});function FR(e,t=0,a=1,n,r){if(en(e),n!=null&&n==="bool")throw new Error("Unsupported data type $ { dtype }");let s=new R1(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 Nb=z({truncatedNormal_:FR});function OR(e,t=0){let a=E(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(lh,n,r);return{values:s,indices:i}}var Eb=z({unique_:OR});function DR(e,t,a){let n=E(e,"x","unsortedSegmentSum"),r=E(t,"segmentIds","unsortedSegmentSum","int32");F(il(a),()=>"numSegments must be of dtype int");let s={x:n,segmentIds:r},i={numSegments:a};return L.runKernel(uh,s,i)}var Rb=z({unsortedSegmentSum_:DR});function zR(e,t=0){let a=E(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(au,n,r)}var Ca=z({unstack_:zR});function Mb(e,t){return mh(e,t,"right")}function $b(e,t=!0,a,n){return L.makeVariable(e,t,a,n)}function _b(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 LR(e){let t=E(e,"condition","whereAsync","bool"),a=await t.data(),n=_b(t.shape,a);return e!==t&&t.dispose(),n}var L1=LR;async function BR(e,t,a){let n=E(e,"tensor","boolMask"),r=E(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 m=s;m<s+i;m++)l*=o[m];let u=o.slice(0,s).concat([l],o.slice(s+i)),p=Q(n,u),c=Q(r,[-1]),d=await L1(c),h=De(d,[1]),f=h1(p,h,s);return e!==n&&n.dispose(),t!==r&&r.dispose(),h.dispose(),p.dispose(),c.dispose(),d.dispose(),f}var Pb=BR;function WR(e,t,a){let n=E(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"?Oe(()=>{let i=pl(n),o=ip(n);return i=L.runKernel(Ar,{x:i},s),o=L.runKernel(Ar,{x:o},s),a&&(o=Xn(o)),vr(i,o)}):L.runKernel(Ar,r,s)}var Vs=z({transpose_:WR});function VR(e,t,a,n,r=!0){let s=E(e,"v","movingAverage"),i=E(t,"x","movingAverage"),o=E(a,"decay","movingAverage");Ax(s,i),F(es(s.shape,i.shape),()=>"Shape mismatch in v and x");let l=ze(1),u=fe(l,o),p=te(fe(i,s),u);if(r){F(n!=null,()=>"When using zeroDebias: true, step is required.");let c=E(n,"step","movingAverage");p=xe(p,fe(l,ll(o,c)))}return be(s,p)}var Fb=z({movingAverage_:VR}),B1={};Ze(B1,{calculateShapes:()=>Ob,validateInput:()=>V1,validateUpdateShape:()=>W1});function W1(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 V1(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}`)}W1(a,t,e)}function Ob(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=xt(t.shape)/o,u=[...bl(a.slice(0,r)),1],p=xt(a);return{sliceRank:r,numUpdates:l,sliceSize:i,strides:u,outputSize:p}}function UR(e,t,a){en(a);let n=E(e,"indices","scatterND","int32"),r=E(t,"updates","scatterND");V1(r,n,a);let s={indices:n,updates:r},i={shape:a};return L.runKernel(ao,s,i)}var Db=z({scatterND_:UR});function GR(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 HR(e,t,a,n=0){en(a);let r=E(e,"sparseIndices","sparseToDense","int32"),s=E(t,"sparseValues","sparseToDense","string_or_numeric"),i=E(n,"defaultValue","sparseToDense",s.dtype);GR(r,s,a,i);let o={sparseIndices:r,sparseValues:s,defaultValue:i},l={outputShape:a};return L.runKernel(Vd,o,l)}var zb=z({sparseToDense_:HR});function jR(e,t){let a=E(t,"indices","gatherND","int32"),n={params:E(e,"x","gatherND","string_or_numeric"),indices:a};return L.runKernel(bi,n)}var Lb=z({gatherND_:jR});function qR(e,t){if(t==null)return e.shape.slice();if(es(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 XR(e,t,a,n){let r=E(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 pt?r.clone():r;let s=qR(r,a),i=1-t,o=xe(c1(be($1(s,0,1,"float32",n),i)),i);return te(r,o)}var Bb=z({dropout_:XR});function U1(e){return Math.floor(Math.pow(2,Math.ceil(Math.log(e)/Math.log(2))))}function bh(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 Ht(r,"float32")}async function KR(e,t,a=1){let n=E(e,"predictions","inTopK"),r=E(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=rx("bool",l);for(let c=0;c<l;c++){let d=c*u,h=i.subarray(d,d+u),f=[];for(let m=0;m<h.length;m++)f.push({value:h[m],index:m});f.sort((m,g)=>g.value-m.value),p[c]=0;for(let m=0;m<a;m++)if(f[m].index===o[c]){p[c]=1;break}}return e!==n&&n.dispose(),t!==r&&r.dispose(),Ue(p,r.shape,"bool")}var Wb=KR,G1={};Ze(G1,{conv2d:()=>QR,depthwiseConv2d:()=>sM,matMul:()=>oM});function ZR(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]}).`),Cn("conv2dDerFilter",r,i);let c={x:o,dy:l},d={strides:n,pad:r,dataFormat:s,dimRoundingMode:i,filterShape:a};return L.runKernel(Cd,c,d)}var YR=z({conv2DBackpropFilter_:ZR});function vh(e,t,a){if(a==null||a==="linear")return e;if(a==="relu")return te(e,D1(t));throw new Error(`Cannot compute gradient for fused activation ${a}.`)}function kh(e,t){let a=t,n=o1(e.shape,t.shape);return n.length>0&&(a=rt(a,n)),Q(a,e.shape)}function wh(e,t,a,n){if(t==="linear")return e;if(t==="relu")return op(e);if(t==="elu")return u1(e);if(t==="relu6")return _1(e);if(t==="prelu")return T1(e,a);if(t==="leakyrelu")return m1(e,n);if(t==="sigmoid")return za(e);throw new Error(`Unknown fused activation ${t}.`)}var Ih=(e,t)=>!(e>0)||t==="linear";function JR({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",Ih(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 S=ap(e,t,a,n,r,s,i);return o!=null&&(S=be(S,o)),wh(S,l,u,p)}let c=E(e,"x","conv2d","float32"),d=E(t,"filter","conv2d","float32"),h=c,f=!1;c.rank===3&&(f=!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 ${d.rank}.`),Cn("fused conv2d",n,i);let m=r==="NHWC"?h.shape[3]:h.shape[1];F(d.shape[2]===m,()=>`Error in conv2d: depth of input (${m}) must match input depth for filter ${d.shape[2]}.`),F(wr(a,s),()=>`Error in conv2D: Either strides or dilations must be 1. Got strides ${a} and dilations '${s}'`);let g=ep(h.shape,d.shape,a,s,n,i),y;o!=null&&(y=E(o,"bias","fused conv2d"),[y]=Tt(y,c),r==="NHWC"?zt(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 (${g.outChannels})`)));let x;if(u!=null){let S=u.shape;if(F(S.length<=1||S.length===3,()=>`Error in fused conv2d: only supports scalar, 1-D Tensor or 3-D Tensor PReLU activation weights but got a tensor of rank-${S.length}.`),S.length===1)F(S[0]===1||S[0]===g.outChannels,()=>`Error in fused conv2d: PReLU activation weights (${S}) is not compatible with the number of output channels (${g.outChannels}).`);else if(S.length===3)try{zt(S,g.outShape)}catch(C){let N=`Error in fused conv2d: PReLU activation weights (${S}) is not compatible with the output shape of the conv2d (${g.outShape}).`;throw Error(N)}x=E(u,"prelu weights","fused conv2d")}let A=(S,C)=>{F(r==="NHWC",()=>`Error in gradient of fused conv2D: got dataFormat of ${r} but only NHWC is currently supported.`);let[N,$,M,R]=C,I=vh(S,M,l);F(pd(s),()=>`Error in gradient of fused conv2D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '${s}'`);let _=iA($.shape,I,N,a,n),D=YR($,I,N.shape,a,n),W=[_,D];if(R!=null){let P=kh(R,I);W.push(P)}return W},b={x:h,filter:d,bias:y,preluActivationWeights:x},k={strides:a,pad:n,dataFormat:r,dilations:s,dimRoundingMode:i,activation:l,leakyreluAlpha:p};return o==null?Qn((S,C,N)=>{let $=L.runKernel(jr,b,k);return N([C,S,$]),f&&($=Q($,[$.shape[1],$.shape[2],$.shape[3]])),{value:$,gradFunc:A}})(h,d):Qn((S,C,N,$)=>{let M=L.runKernel(jr,b,k);return $([C,S,M,N]),f&&(M=Q(M,[M.shape[1],M.shape[2],M.shape[3]])),{value:M,gradFunc:A}})(h,d,y)}var QR=z({fusedConv2d_:JR});function eM(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(eh,u,p)}var tM=z({depthwiseConv2dNativeBackpropFilter_:eM});function aM(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(th,u,p);return l?Q(c,[c.shape[1],c.shape[2],c.shape[3]]):c}var nM=z({depthwiseConv2dNativeBackpropInput_:aM});function rM({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(Ih(L.state.gradientDepth,l)===!1){let k=ch(e,t,a,n,r,s,i);return o!=null&&(k=be(k,o)),wh(k,l,u,p)}let c=E(e,"x","depthwiseConv2d","float32"),d=E(t,"filter","depthwiseConv2d","float32"),h=c,f=!1;c.rank===3&&(f=!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(wr(a,s),()=>`Error in fused depthwiseConv2d: Either strides or dilations must be 1. Got strides ${a} and dilations '${s}'`),Cn("fused depthwiseConv2d",n,i);let m=ep(h.shape,d.shape,a,s,n,i,!0),g;o!=null&&(g=E(o,"bias","fused conv2d"),[g]=Tt(g,c),zt(m.outShape,g.shape));let y;u!=null&&(y=E(u,"prelu weights","fused depthwiseConv2d"));let x=(k,S)=>{F(pd(s),()=>`Error in gradient of fused depthwiseConv2d: dilation rates greater than 1 are not yet supported. Got dilations '${s}'`);let[C,N,$,M]=S,R=vh(k,$,l),I=nM(N.shape,R,C,a,n,s,i),_=tM(N,R,C.shape,a,n,s,i);if(M!=null){let D=kh(g,R);return[I,_,D]}return[I,_]},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?Qn((k,S,C)=>{let N=L.runKernel(qr,A,b);return C([S,k,N]),f&&(N=Q(N,[N.shape[1],N.shape[2],N.shape[3]])),{value:N,gradFunc:x}})(h,d):Qn((k,S,C,N)=>{let $=L.runKernel(qr,A,b);return N([S,k,$,C]),f&&($=Q($,[$.shape[1],$.shape[2],$.shape[3]])),{value:$,gradFunc:x}})(h,d,g)}var sM=z({fusedDepthwiseConv2d_:rM});function iM({a:e,b:t,transposeA:a=!1,transposeB:n=!1,bias:r,activation:s="linear",preluActivationWeights:i,leakyreluAlpha:o=.2}){if(Ih(L.state.gradientDepth,s)===!1){let M=ot(e,t,a,n);return r!=null&&(M=be(M,r)),wh(M,s,i,o)}let l=E(e,"a","fused matMul"),u=E(t,"b","fused matMul");[l,u]=Tt(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],f=l.shape.slice(0,-2),m=u.shape.slice(0,-2),g=xt(f),y=xt(m);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=${n} must match.`);let x=zt(l.shape.slice(0,-2),u.shape.slice(0,-2)).concat([d,h]),A=a?Q(l,[g,p,d]):Q(l,[g,d,p]),b=n?Q(u,[y,h,c]):Q(u,[y,c,h]),k;r!=null&&(k=E(r,"bias","fused matMul"),[k]=Tt(k,l),zt(x,k.shape));let S;i!=null&&(S=E(i,"prelu weights","fused matMul"));let C=(M,R)=>{let[I,_,D,W]=R,P=vh(Q(M,D.shape),D,s),U,G;if(!a&&!n?(U=ot(P,_,!1,!0),G=ot(I,P,!0,!1)):!a&&n?(U=ot(P,_,!1,!1),G=ot(P,I,!0,!1)):a&&!n?(U=ot(_,P,!1,!0),G=ot(I,P,!1,!1)):(U=ot(_,P,!0,!0),G=ot(P,I,!0,!0)),r!=null){let q=kh(W,P);return[U,G,q]}else return[U,G]},N={a:A,b,bias:k,preluActivationWeights:S},$={transposeA:a,transposeB:n,activation:s,leakyreluAlpha:o};return r==null?Qn((M,R,I)=>{let _=L.runKernel(Hr,N,$);return I([M,R,_]),{value:Q(_,x),gradFunc:C}})(A,b):Qn((M,R,I,_)=>{let D=L.runKernel(Hr,N,$);return _([M,R,D,I]),{value:Q(D,x),gradFunc:C}})(A,b,k)}var oM=z({fusedMatMul_:iM});function lM(e){return bh(e,.54,.46)}var uM=z({hammingWindow_:lM});function dM(e){return bh(e,.5,.5)}var Vb=z({hannWindow_:dM});function pM(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=st([Fe(e,s,t-o),nr([o],r)]);i.push(l),s+=a}return i.length===0?Kn([],[0,t]):Q(st(i),[i.length,t])}var Ub=z({frame_:pM});function cM(e,t,a,n,r=Vb){n==null&&(n=U1(t));let s=Ub(e,t,a),i=te(s,r(t));return Ah(i,n)}var hM=z({stft_:cM});function fM(e,t,a,n,r="bilinear",s=0){let i=E(e,"image","cropAndResize"),o=E(t,"boxes","cropAndResize","float32"),l=E(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(ui,p,c)}var mM=z({cropAndResize_:fM});function gM(e){let t=E(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(gi,a,{})}var yM=z({flipLeftRight_:gM});function xM(e){let t=E(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,Ur(t,r)}var AM=z({grayscaleToRGB_:xM});function bM(e,t,a=0,n=.5){let r=E(e,"image","rotateWithOffset","float32");F(r.rank===4,()=>`Error in rotateWithOffset: image must be rank 4,but got rank ${r.rank}.`);let s={image:r},i={radians:t,fillValue:a,center:n};return L.runKernel(go,s,i)}var vM=z({rotateWithOffset_:bM});function iu(e,t,a,n,r,s){n==null&&(n=.5),r==null&&(r=Number.NEGATIVE_INFINITY),s==null&&(s=0);let i=e.shape[0];return a=Math.min(a,i),F(0<=n&&n<=1,()=>`iouThreshold must be in [0, 1], but was '${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 kM(e,t,a,n=.5,r=Number.NEGATIVE_INFINITY){let s=E(e,"boxes","nonMaxSuppression","float32"),i=E(t,"scores","nonMaxSuppression","float32"),o=iu(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(Wi,{boxes:s,scores:i},l)}var wM=z({nonMaxSuppression_:kM});function IM(e,t,a){let n=SM(e,t,a),r=n<0?-(n+1):n;e.splice(r,0,t)}function SM(e,t,a){return CM(e,t,a||TM)}function TM(e,t){return e>t?1:e<t?-1:0}function CM(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 Gb(e,t,a,n,r){return H1(e,t,a,n,r,0)}function Hb(e,t,a,n,r,s){return H1(e,t,a,n,r,0,!1,s,!0)}function jb(e,t,a,n,r,s){return H1(e,t,a,n,r,s,!0)}function H1(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(V5);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 k=c.length-1;k>=A;--k){let S=NM(e,x,c[k]);if(S>=n){b=!0;break}if(g.score=g.score*EM(n,p,S),g.score<=r)break}g.suppressBeginIndex=c.length,b||(g.score===y?(c.push(x),d.push(g.score)):g.score>r&&IM(u,g,V5))}let h=c.length,f=a-h;o&&f>0&&(c.push(...new Array(f).fill(0)),d.push(...new Array(f).fill(0)));let m={selectedIndices:c};return i&&(m.selectedScores=d),l&&(m.validOutputs=h),m}function NM(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),f=(c-u)*(d-p);if(h<=0||f<=0)return 0;let m=Math.max(s,u),g=Math.max(i,p),y=Math.min(o,c),x=Math.min(l,d),A=Math.max(y-m,0)*Math.max(x-g,0);return A/(h+f-A)}function EM(e,t,a){let n=Math.exp(t*a*a);return a<=e?n:0}function V5(e,t){return e.score-t.score||e.score===t.score&&t.boxIndex-e.boxIndex}async function RM(e,t,a,n=.5,r=Number.NEGATIVE_INFINITY){let s=E(e,"boxes","nonMaxSuppressionAsync"),i=E(t,"scores","nonMaxSuppressionAsync"),o=iu(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}=Gb(u,p,a,n,r);return s!==e&&s.dispose(),i!==t&&i.dispose(),Ht(c,"int32")}var MM=RM;function $M(e,t,a,n=.5,r=Number.NEGATIVE_INFINITY,s=0){let i=E(e,"boxes","nonMaxSuppression"),o=E(t,"scores","nonMaxSuppression"),l=iu(i,o,a,n,r,s);a=l.maxOutputSize,n=l.iouThreshold,r=l.scoreThreshold,s=l.softNmsSigma;let u={boxes:i,scores:o},p={maxOutputSize:a,iouThreshold:n,scoreThreshold:r,softNmsSigma:s},c=L.runKernel(Vi,u,p);return{selectedIndices:c[0],selectedScores:c[1]}}var _M=z({nonMaxSuppressionWithScore_:$M});async function PM(e,t,a,n=.5,r=Number.NEGATIVE_INFINITY,s=0){let i=E(e,"boxes","nonMaxSuppressionAsync"),o=E(t,"scores","nonMaxSuppressionAsync"),l=iu(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}=jb(p,c,a,n,r,s);return i!==e&&i.dispose(),o!==t&&o.dispose(),{selectedIndices:Ht(d,"int32"),selectedScores:Ht(h)}}var FM=PM;function OM(e,t,a,n=.5,r=Number.NEGATIVE_INFINITY,s=!1){let i=E(e,"boxes","nonMaxSuppression"),o=E(t,"scores","nonMaxSuppression"),l=iu(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},f=L.runKernel(Wl,d,h);return{selectedIndices:f[0],validOutputs:f[1]}}var DM=z({nonMaxSuppressionPadded_:OM});async function zM(e,t,a,n=.5,r=Number.NEGATIVE_INFINITY,s=!1){let i=E(e,"boxes","nonMaxSuppressionAsync"),o=E(t,"scores","nonMaxSuppressionAsync"),l=iu(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:f,validOutputs:m}=Hb(d,h,u,p,c,s);return i!==e&&i.dispose(),o!==t&&o.dispose(),{selectedIndices:Ht(f,"int32"),validOutputs:ze(m,"int32")}}var LM=zM;function BM(e,t,a=!1,n=!1){let r=E(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(Yi,o,l);return i?Q(u,[u.shape[1],u.shape[2],u.shape[3]]):u}var WM=z({resizeBilinear_:BM});function VM(e,t,a=!1,n=!1){let r=E(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(Zi,o,l);return i?Q(u,[u.shape[1],u.shape[2],u.shape[3]]):u}var UM=z({resizeNearestNeighbor_:VM});function GM(e,t="binary",a=!1,n=.5){let r=E(e,"image","threshold"),s=.2989,i=.587,o=.114,l=r.shape[0]*r.shape[1],u=te(Ht([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]=Ia(r,[1,1,1],-1);let m=te(p,s),g=te(c,i),y=te(d,o);h=be(be(m,g),y)}else h=e;if(t==="otsu"){let m=i1(Xe(P1(h),"int32"),Ue([]),256);u=HM(m,l)}let f=a?hh(h,u):sp(h,u);return Xe(te(f,255),"int32")}function HM(e,t){let a=Ht([-1]),n=Ht([0]),r=Ht([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=xe(rt(s),t),p=xe(rt(i),t);let d=rt(te(s,dl(0,s.size)));o=xe(d,rt(s));let h=nr(i.shape,s.size),f=be(dl(0,i.size),h),m=te(i,f);l=xe(rt(m),rt(i));let g=fe(o,l),y=fe(o,l),x=te(u,p);r=te(te(x,g),y);let A=sp(r,n);n=Ws(A,r,n),a=Ws(A,Ht([c]),a)}return a}var jM=z({threshold_:GM});function qM(e,t,a="nearest",n="constant",r=0,s){let i=E(e,"image","transform","float32"),o=E(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(mo,l,u)}var XM=z({transform_:qM});function KM(e,t,a){F(t%1===0,()=>`bandPart(): numLower must be an integer, got ${t}.`),F(a%1===0,()=>`bandPart(): numUpper must be an integer, got ${a}.`);let n=E(e,"a","bandPart");F(n.rank>=2,()=>`bandPart(): Rank must be at least 2, got ${n.rank}.`);let r=n.shape,[s,i]=n.shape.slice(-2);if(!(t<=s))throw new Error(`bandPart(): numLower (${t}) must not be greater than the number of rows (${s}).`);if(!(a<=i))throw new Error(`bandPart(): numUpper (${a}) must not be greater than the number of columns (${i}).`);t<0&&(t=s),a<0&&(a=i);let o=Q(dl(0,s,1,"int32"),[-1,1]),l=dl(0,i,1,"int32"),u=fe(o,l),p=cd(hh(u,ze(+t,"int32")),f1(u,ze(-a,"int32"))),c=gn([s,i],n.dtype);return Q(la(Ca(Q(n,[-1,s,i])).map(d=>Ws(p,d,c))),r)}var ZM=z({bandPart_:KM});function YM(e){let t;if(Array.isArray(e)){t=!1,F(e!=null&&e.length>0,()=>"Gram-Schmidt process: input must not be null, undefined, or empty");let r=e[0].shape[0];for(let s=1;s<e.length;++s)F(e[s].shape[0]===r,()=>`Gram-Schmidt: Non-unique lengths found in the input vectors: (${e[s].shape[0]} vs. ${r})`)}else t=!0,e=Ia(e,e.shape[0],0).map(r=>De(r,[0]));F(e.length<=e[0].shape[0],()=>`Gram-Schmidt: Number of vectors (${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(rt(te(a[i],s)),a[i]);s=fe(s,o)}return xe(s,rp(s,"euclidean"))}));return t?la(a,0):a}var JM=z({gramSchmidt_:YM});function QM(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 U5(e,t);{let a=e.shape.slice(0,e.shape.length-2).reduce((l,u)=>l*u),n=Ca(Q(e,[a,e.shape[e.shape.length-2],e.shape[e.shape.length-1]]),0),r=[],s=[];n.forEach(l=>{let[u,p]=U5(l,t);r.push(u),s.push(p)});let i=Q(la(r,0),e.shape),o=Q(la(s,0),e.shape);return[i,o]}}function U5(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=p1(a),s=wa(e),i=Kn([[1]],[1,1]),o=wa(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]),f=rp(h),m=Fe(s,[u,u],[1,1]),g=Ws(sp(m,0),Kn([[-1]]),Kn([[1]])),y=fe(m,te(g,f)),x=xe(h,y);x.shape[0]===1?o=wa(i):o=st([i,Fe(x,[1,0],[x.shape[0]-1,x.shape[1]])],0);let A=Xn(xe(ot(g,y),f)),b=Fe(s,[u,0],[a-u,n]),k=te(A,o),S=Vs(o);if(u===0)s=fe(b,ot(k,ot(S,b)));else{let $=fe(b,ot(k,ot(S,b)));s=st([Fe(s,[0,0],[u,n]),$],0)}let C=Vs(k),N=Fe(r,[0,u],[a,r.shape[1]-u]);if(u===0)r=fe(N,ot(ot(N,o),C));else{let $=fe(N,ot(ot(N,o),C));r=st([Fe(r,[0,0],[a,u]),$],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 e$=z({qr_:QM}),ba;(function(e){e[e.NONE=0]="NONE",e[e.MEAN=1]="MEAN",e[e.SUM=2]="SUM",e[e.SUM_BY_NONZERO_WEIGHTS=3]="SUM_BY_NONZERO_WEIGHTS"})(ba||(ba={}));function t$(e,t,a=ba.SUM_BY_NONZERO_WEIGHTS){let n=E(e,"losses","computeWeightedLoss"),r=null;t!=null&&(r=E(t,"weights","computeWeightedLoss"));let s=r==null?n:te(n,r);if(a===ba.NONE)return s;if(a===ba.SUM)return rt(s);if(a===ba.MEAN){if(r==null)return hd(s);{let i=n.size/r.size,o=xe(rt(s),rt(r));return i>1?xe(o,ze(i)):o}}if(a===ba.SUM_BY_NONZERO_WEIGHTS){if(r==null)return xe(rt(s),ze(n.size));{let i=te(r,Br(n.shape)),o=Xe(rt(I1(i,ze(0))),"float32");return xe(rt(s),o)}}throw Error(`Unknown reduction: ${a}`)}var Ir=z({computeWeightedLoss_:t$});function a$(e,t,a,n=ba.SUM_BY_NONZERO_WEIGHTS){let r=E(e,"labels","absoluteDifference"),s=E(t,"predictions","absoluteDifference"),i=null;a!=null&&(i=E(a,"weights","absoluteDifference")),Ta(r.shape,s.shape,"Error in absoluteDifference: ");let o=Ka(fe(r,s));return Ir(o,i,n)}var n$=z({absoluteDifference_:a$});function r$(e,t,a,n,r=ba.SUM_BY_NONZERO_WEIGHTS){let s=E(e,"labels","cosineDistance"),i=E(t,"predictions","cosineDistance"),o=null;n!=null&&(o=E(n,"weights","cosineDistance")),Ta(s.shape,i.shape,"Error in cosineDistance: ");let l=ze(1),u=fe(l,rt(te(s,i),a,!0));return Ir(u,o,r)}var s$=z({cosineDistance_:r$});function i$(e,t,a,n=ba.SUM_BY_NONZERO_WEIGHTS){let r=E(e,"labels","hingeLoss"),s=E(t,"predictions","hingeLoss"),i=null;a!=null&&(i=E(a,"weights","hingeLoss")),Ta(r.shape,s.shape,"Error in hingeLoss: ");let o=ze(1);r=fe(te(ze(2),r),o);let l=op(fe(o,te(r,s)));return Ir(l,i,n)}var o$=z({hingeLoss_:i$});function l$(e,t,a,n=1,r=ba.SUM_BY_NONZERO_WEIGHTS){let s=E(e,"labels","huberLoss"),i=E(t,"predictions","huberLoss"),o=null;a!=null&&(o=E(a,"weights","huberLoss")),Ta(s.shape,i.shape,"Error in huberLoss: ");let l=ze(n),u=Ka(fe(i,s)),p=w1(u,l),c=fe(u,p),d=be(te(ze(.5),Tn(p)),te(l,c));return Ir(d,o,r)}var u$=z({huberLoss_:l$});function d$(e,t,a,n=1e-7,r=ba.SUM_BY_NONZERO_WEIGHTS){let s=E(e,"labels","logLoss"),i=E(t,"predictions","logLoss"),o=null;a!=null&&(o=E(a,"weights","logLoss")),Ta(s.shape,i.shape,"Error in logLoss: ");let l=ze(1),u=ze(n),p=Xn(te(s,ul(be(i,u)))),c=te(fe(l,s),ul(be(fe(l,i),u))),d=fe(p,c);return Ir(d,o,r)}var p$=z({logLoss_:d$});function c$(e,t,a,n=ba.SUM_BY_NONZERO_WEIGHTS){let r=E(e,"labels","meanSquaredError"),s=E(t,"predictions","meanSquaredError"),i=null;a!=null&&(i=E(a,"weights","meanSquaredError")),Ta(r.shape,s.shape,"Error in meanSquaredError: ");let o=O1(r,s);return Ir(o,i,n)}var h$=z({meanSquaredError_:c$});function f$(e,t){let a=E(e,"labels","sigmoidCrossEntropyWithLogits"),n=E(t,"logits","sigmoidCrossEntropyWithLogits");Ta(a.shape,n.shape,"Error in sigmoidCrossEntropyWithLogits: ");let r=op(n),s=te(n,a),i=g1(Zr(Xn(Ka(n))));return be(fe(r,s),i)}function m$(e,t,a,n=0,r=ba.SUM_BY_NONZERO_WEIGHTS){let s=E(e,"multiClassLabels","sigmoidCrossEntropy"),i=E(t,"logits","sigmoidCrossEntropy"),o=null;if(a!=null&&(o=E(a,"weights","sigmoidCrossEntropy")),Ta(s.shape,i.shape,"Error in sigmoidCrossEntropy: "),n>0){let u=ze(n),p=ze(1),c=ze(.5);s=be(te(s,fe(p,u)),te(c,u))}let l=f$(s,i);return Ir(l,o,r)}var g$=z({sigmoidCrossEntropy_:m$});function y$(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 ${a}`);return Qn((n,r,s)=>{let i=x1(r,[a],!0),o=fe(Xe(r,"float32"),i);s([n,o]);let l=Xn(te(o,n));return{value:rt(l,[a]),gradFunc:(u,p)=>{let[c,d]=p,h=np(u.shape,[a]);return[te(Q(u,h),fe(Xe(c,"float32"),Zr(d))),te(Q(u,h),fe(Zr(d),Xe(c,"float32")))]}}})(e,t)}function x$(e,t,a,n=0,r=ba.SUM_BY_NONZERO_WEIGHTS){let s=E(e,"onehotLabels","softmaxCrossEntropy"),i=E(t,"logits","softmaxCrossEntropy"),o=null;if(a!=null&&(o=E(a,"weights","softmaxCrossEntropy")),Ta(s.shape,i.shape,"Error in softmaxCrossEntropy: "),n>0){let u=ze(n),p=ze(1),c=ze(s.shape[1]);s=be(te(s,fe(p,u)),xe(u,c))}let l=y$(s,i);return Ir(l,o,r)}var A$=z({softmaxCrossEntropy_:x$});function b$(e,t,a,n){let r=E(e,"indices","sparseFillEmptyRows","int32"),s=E(t,"values","sparseFillEmptyRows"),i=E(a,"denseShape","sparseFillEmptyRows","int32"),o=E(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 ${o.shape}`);let l={indices:r,values:s,denseShape:i,defaultValue:o},u=L.runKernel(Ld,l);return{outputIndices:u[0],outputValues:u[1],emptyRowIndicator:u[2],reverseIndexMap:u[3]}}var v$=z({sparseFillEmptyRows_:b$});function k$(e,t,a){let n=E(e,"inputIndices","sparseReshape","int32"),r=E(t,"inputShape","sparseReshape","int32"),s=E(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 ${s.shape}`);let i={inputIndices:n,inputShape:r,newShape:s},o=L.runKernel(eu,i);return{outputIndices:o[0],outputShape:o[1]}}var w$=z({sparseReshape_:k$});function I$(e,t,a){let n=E(e,"data","sparseSegmentMean"),r=E(t,"indices","sparseSegmentMean","int32"),s=E(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
|
|
${s.shape}`);let i={data:n,indices:r,segmentIds:s};return L.runKernel(Bd,i)}var S$=z({sparseSegmentMean_:I$});function T$(e,t,a){let n=E(e,"data","sparseSegmentSum"),r=E(t,"indices","sparseSegmentSum","int32"),s=E(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
|
|
${s.shape}`);let i={data:n,indices:r,segmentIds:s};return L.runKernel(Wd,i)}var C$=z({sparseSegmentSum_:T$});function N$(e,t,a,n,r,s,i,o){let l=E(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: ${l.shape}`);let u=E(t,"dataSplits","stringNGrams");if(u.dtype!=="int32")throw new Error("Data splits must be of datatype int32");let p={separator:a,nGramWidths:n,leftPad:r,rightPad:s,padWidth:i,preserveShortSequences:o},c={data:l,dataSplits:u},d=L.runKernel(tu,c,p);return{nGrams:d[0],nGramsSplits:d[1]}}var E$=z({stringNGrams_:N$});function R$(e,t,a=!0){let n=E(e,"input","stringSplit","string"),r=E(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 ${r.shape}`);let s={skipEmpty:a},i={input:n,delimiter:r},o=L.runKernel(Gd,i,s);return{indices:o[0],values:o[1],shape:o[2]}}var M$=z({stringSplit_:R$});function $$(e,t){let a=E(e,"input","stringToHashBucketFast","string"),n={numBuckets:t};if(t<=0)throw new Error("Number of buckets must be at least 1");let r={input:a};return L.runKernel(Hd,r,n)}var _$=z({stringToHashBucketFast_:$$}),qb={fft:xh,ifft:fd,rfft:Ah,irfft:F1},Xb={hammingWindow:uM,hannWindow:Vb,frame:Ub,stft:hM},ye={flipLeftRight:yM,grayscaleToRGB:AM,resizeNearestNeighbor:UM,resizeBilinear:WM,rotateWithOffset:vM,cropAndResize:mM,nonMaxSuppression:wM,nonMaxSuppressionAsync:MM,nonMaxSuppressionWithScore:_M,nonMaxSuppressionWithScoreAsync:FM,nonMaxSuppressionPadded:DM,nonMaxSuppressionPaddedAsync:LM,threshold:jM,transform:XM},Kb={bandPart:ZM,gramSchmidt:JM,qr:e$},Zb={absoluteDifference:n$,computeWeightedLoss:Ir,cosineDistance:s$,hingeLoss:o$,huberLoss:u$,logLoss:p$,meanSquaredError:h$,sigmoidCrossEntropy:g$,softmaxCrossEntropy:A$},Yb={sparseFillEmptyRows:v$,sparseReshape:w$,sparseSegmentMean:S$,sparseSegmentSum:C$},Jb={stringNGrams:E$,stringSplit:M$,stringToHashBucketFast:_$},Qb={};Ze(Qb,{Serializable:()=>e4,SerializationMap:()=>Ps,registerClass:()=>t4});var e4=class{getClassName(){return this.constructor.className}static fromConfig(e,t){return new e(t)}},Ps=class{constructor(){this.classNameMap={}}static getMap(){return Ps.instance==null&&(Ps.instance=new Ps),Ps.instance}static register(e){Ps.getMap().classNameMap[e.className]=[e,e.fromConfig]}};function t4(e){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."),Ps.register(e)}var is=class extends e4{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 _A(e,t)}dispose(){this.iterations_!=null&&J(this.iterations_)}async saveIterations(){return this.iterations_==null&&(this.iterations_=0),{name:"iter",tensor:ze(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 ${this.getClassName()}`)}async extractIterations(e){return this.iterations_=(await e[0].tensor.data())[0],e.slice(1)}};Object.defineProperty(is,Symbol.hasInstance,{value:e=>e.minimize!=null&&e.computeGradients!=null&&e.applyGradients!=null});var j1=class extends is{constructor(e,t,a=null){super(),this.learningRate=e,this.rho=t,this.epsilon=a,this.accumulatedGrads=[],this.accumulatedUpdates=[],a==null&&(this.epsilon=L.backend.epsilon())}static get className(){return"Adadelta"}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,a)=>{let n=L.registeredVariables[t],r=!1;this.accumulatedGrads[a]==null&&(this.accumulatedGrads[a]={originalName:`${t}/accum_grad`,variable:Oe(()=>Ya(n).variable(r))}),this.accumulatedUpdates[a]==null&&(this.accumulatedUpdates[a]={originalName:`${t}/accum_var`,variable:Oe(()=>Ya(n).variable(r))});let s=Array.isArray(e)?e[a].tensor:e[t];if(s==null)return;let i=this.accumulatedGrads[a].variable,o=this.accumulatedUpdates[a].variable;Oe(()=>{let l=be(te(i,this.rho),te(Tn(s),1-this.rho)),u=te(xe(Jn(be(o,this.epsilon)),Jn(be(i,this.epsilon))),s),p=be(te(o,this.rho),te(Tn(u),1-this.rho));i.assign(l),o.assign(p);let c=be(te(u,-this.learningRate),n);n.assign(c)})}),this.incrementIterations()}dispose(){this.accumulatedUpdates!=null&&(J(this.accumulatedGrads.map(e=>e.variable)),J(this.accumulatedUpdates.map(e=>e.variable)))}async getWeights(){let e=[...this.accumulatedGrads,...this.accumulatedUpdates];return[await this.saveIterations()].concat(e.map(t=>({name:t.originalName,tensor:t.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=e.length/2,a=!1;this.accumulatedGrads=e.slice(0,t).map(n=>({originalName:n.name,variable:n.tensor.variable(a)})),this.accumulatedUpdates=e.slice(t,t*2).map(n=>({originalName:n.name,variable:n.tensor.variable(a)}))}getConfig(){return{learningRate:this.learningRate,rho:this.rho,epsilon:this.epsilon}}static fromConfig(e,t){return new e(t.learningRate,t.rho,t.epsilon)}},q1=class extends is{constructor(e,t=.1){super(),this.learningRate=e,this.initialAccumulatorValue=t,this.accumulatedGrads=[]}static get className(){return"Adagrad"}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,a)=>{let n=L.registeredVariables[t];this.accumulatedGrads[a]==null&&(this.accumulatedGrads[a]={originalName:`${t}/accumulator`,variable:Oe(()=>nr(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;Oe(()=>{let i=be(s,Tn(r));s.assign(i);let o=be(te(xe(r,Jn(be(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)}},X1=class extends is{constructor(e,t,a,n=null){super(),this.learningRate=e,this.beta1=t,this.beta2=a,this.epsilon=n,this.accumulatedFirstMoment=[],this.accumulatedSecondMoment=[],Oe(()=>{this.accBeta1=ze(t).variable(),this.accBeta2=ze(a).variable()}),n==null&&(this.epsilon=L.backend.epsilon())}static get className(){return"Adam"}applyGradients(e){let t=Array.isArray(e)?e.map(a=>a.name):Object.keys(e);Oe(()=>{let a=fe(1,this.accBeta1),n=fe(1,this.accBeta2);t.forEach((r,s)=>{let i=L.registeredVariables[r],o=!1;this.accumulatedFirstMoment[s]==null&&(this.accumulatedFirstMoment[s]={originalName:`${r}/m`,variable:Oe(()=>Ya(i).variable(o))}),this.accumulatedSecondMoment[s]==null&&(this.accumulatedSecondMoment[s]={originalName:`${r}/v`,variable:Oe(()=>Ya(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=be(te(u,this.beta1),te(l,1-this.beta1)),d=be(te(p,this.beta2),te(Tn(l),1-this.beta2)),h=xe(c,a),f=xe(d,n);u.assign(c),p.assign(d);let m=be(te(xe(h,be(Jn(f),this.epsilon)),-this.learningRate),i);i.assign(m)}),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),Oe(()=>{this.accBeta1.assign(ll(this.beta1,this.iterations_+1)),this.accBeta2.assign(ll(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)}},K1=class extends is{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=[],Oe(()=>{this.iteration=ze(0).variable(),this.accBeta1=ze(t).variable()}),n==null&&(this.epsilon=L.backend.epsilon())}static get className(){return"Adamax"}applyGradients(e){let t=Array.isArray(e)?e.map(a=>a.name):Object.keys(e);Oe(()=>{let a=fe(1,this.accBeta1),n=xe(-this.learningRate,be(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:`${r}/m`,variable:Ya(i).variable(o)}),this.accumulatedWeightedInfNorm[s]==null&&(this.accumulatedWeightedInfNorm[s]={originalName:`${r}/v`,variable:Ya(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=be(te(u,this.beta1),te(l,1-this.beta1)),d=te(p,this.beta2),h=Ka(l),f=k1(d,h);u.assign(c),p.assign(f);let m=be(te(xe(n,a),xe(c,be(f,this.epsilon))),i);i.assign(m)}),this.iteration.assign(be(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)}},Sh=class extends is{constructor(e){super(),this.learningRate=e,this.setLearningRate(e)}static get className(){return"SGD"}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];Oe(()=>{let s=be(te(this.c,n),r);r.assign(s)})}),this.incrementIterations()}setLearningRate(e){this.learningRate=e,this.c!=null&&this.c.dispose(),this.c=On(ze(-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)}},Z1=class extends Sh{constructor(e,t,a=!1){super(e),this.learningRate=e,this.momentum=t,this.useNesterov=a,this.accumulations=[],this.m=ze(this.momentum)}static get className(){return"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:`${t}/momentum`,variable:Oe(()=>Ya(n).variable(!1))});let r=this.accumulations[a].variable,s=Array.isArray(e)?e[a].tensor:e[t];s!=null&&Oe(()=>{let i,o=be(te(this.m,r),s);this.useNesterov?i=be(te(this.c,be(s,te(o,this.m))),n):i=be(te(this.c,o),n),r.assign(o),n.assign(i)})}),this.incrementIterations()}dispose(){this.m.dispose(),this.accumulations!=null&&J(this.accumulations.map(e=>e.variable))}setMomentum(e){this.momentum=e}async getWeights(){return[await this.saveIterations()].concat(this.accumulations.map(e=>({name:e.originalName,tensor:e.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=!1;this.accumulations=e.map(a=>({originalName:a.name,variable:a.tensor.variable(t)}))}getConfig(){return{learningRate:this.learningRate,momentum:this.momentum,useNesterov:this.useNesterov}}static fromConfig(e,t){return new e(t.learningRate,t.momentum,t.useNesterov)}},Y1=class extends is{constructor(e,t=.9,a=0,n=null,r=!1){if(super(),this.learningRate=e,this.decay=t,this.momentum=a,this.epsilon=n,this.accumulatedMeanSquares=[],this.accumulatedMoments=[],this.accumulatedMeanGrads=[],this.centered=r,n==null&&(this.epsilon=L.backend.epsilon()),e==null)throw new Error("learningRate for RMSPropOptimizer must be defined.")}static get className(){return"RMSProp"}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,a)=>{let n=L.registeredVariables[t],r=!1;this.accumulatedMeanSquares[a]==null&&(this.accumulatedMeanSquares[a]={originalName:`${t}/rms`,variable:Oe(()=>Ya(n).variable(r))}),this.accumulatedMoments[a]==null&&(this.accumulatedMoments[a]={originalName:`${t}/momentum`,variable:Oe(()=>Ya(n).variable(r))}),this.accumulatedMeanGrads[a]==null&&this.centered&&(this.accumulatedMeanGrads[a]={originalName:`${t}/mg`,variable:Oe(()=>Ya(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;Oe(()=>{let l=be(te(i,this.decay),te(Tn(s),1-this.decay));if(this.centered){let u=this.accumulatedMeanGrads[a].variable,p=be(te(u,this.decay),te(s,1-this.decay)),c=xe(te(s,this.learningRate),Jn(fe(l,be(Tn(p),this.epsilon)))),d=be(te(o,this.momentum),c);i.assign(l),u.assign(p),o.assign(d);let h=fe(n,d);n.assign(h)}else{let u=be(te(i,this.decay),te(Tn(s),1-this.decay)),p=be(te(o,this.momentum),xe(te(s,this.learningRate),Jn(be(u,this.epsilon))));i.assign(u),o.assign(p);let c=fe(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)}},P$=[j1,q1,X1,K1,Z1,Y1,Sh];function F$(){for(let e of P$)t4(e)}var jn={};Ze(jn,{browserFiles:()=>V$,browserHTTPRequest:()=>q$,concatenateArrayBuffers:()=>Y2,copyModel:()=>OT,decodeWeights:()=>Ix,encodeWeights:()=>pT,fromMemory:()=>K$,fromMemorySync:()=>i4,getLoadHandlers:()=>kT,getModelArtifactsForJSON:()=>J2,getModelArtifactsForJSONSync:()=>Tx,getModelArtifactsInfoForJSON:()=>Zd,getSaveHandlers:()=>vT,getWeightSpecs:()=>Cx,http:()=>Q1,isHTTPScheme:()=>t2,listModels:()=>PT,loadWeights:()=>U$,moveModel:()=>DT,registerLoadRouter:()=>bT,registerSaveRouter:()=>AT,removeModel:()=>FT,weightsLoaderFactory:()=>n4,withSaveHandler:()=>Z$,withSaveHandlerSync:()=>Y$});var O$="model",D$=".json",z$=".weights.bin";function G5(e){return new Promise(t=>setTimeout(t)).then(e)}var cl=class{constructor(e){if(!V().getBool("IS_BROWSER"))throw new Error("browserDownloads() cannot proceed because the current environment is not a browser.");e.startsWith(cl.URL_SCHEME)&&(e=e.slice(cl.URL_SCHEME.length)),(e==null||e.length===0)&&(e=O$),this.modelJsonFileName=e+D$,this.weightDataFileName=e+z$}async save(e){if(typeof document=="undefined")throw new Error("Browser downloads are not supported in this environment since `document` is not present");let t=window.URL.createObjectURL(new Blob([e.weightData],{type:"application/octet-stream"}));if(e.modelTopology instanceof ArrayBuffer)throw new Error("BrowserDownloads.save() does not support saving model topology in binary formats yet.");{let a=[{paths:["./"+this.weightDataFileName],weights:e.weightSpecs}],n=Sx(e,a),r=window.URL.createObjectURL(new Blob([JSON.stringify(n)],{type:"application/json"})),s=this.modelJsonAnchor==null?document.createElement("a"):this.modelJsonAnchor;if(s.download=this.modelJsonFileName,s.href=r,await G5(()=>s.dispatchEvent(new MouseEvent("click"))),e.weightData!=null){let i=this.weightDataAnchor==null?document.createElement("a"):this.weightDataAnchor;i.download=this.weightDataFileName,i.href=t,await G5(()=>i.dispatchEvent(new MouseEvent("click")))}return{modelArtifactsInfo:Zd(e)}}}};cl.URL_SCHEME="downloads://";var L$=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 ${this.jsonFile.name}`));return}if(this.weightsFiles.length===0){e({modelTopology:s});return}let i=J2(r,o=>this.loadWeights(o));e(i)},a.onerror=n=>t(`Failed to read model topology and weights manifest JSON from file '${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,Y2(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 '${e}'.`),r.readAsArrayBuffer(t)})}checkManifestAndWeightFiles(e){let t=[],a=this.weightsFiles.map(r=>W5(r.name)),n={};for(let r of e)r.paths.forEach(s=>{let i=W5(s);if(t.indexOf(i)!==-1)throw new Error(`Duplicate file basename found in weights manifest: '${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 (${this.weightsFiles.length}).`);return n}},B$=e=>V().getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(cl.URL_SCHEME)?W$(e.slice(cl.URL_SCHEME.length)):null;Mt.registerSaveRouter(B$);function W$(e="model"){return new cl(e)}function V$(e){return new L$(e)}function H5(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 ${u}`)}return Promise.all(e.map(s))}async function a4(e,t){t==null&&(t={});let a=t.fetchFunc==null?V().platform.fetch:t.fetchFunc,n=e.map(u=>a(u,t.requestInit,{isBinary:!0})),r=0,s=.5,i=(t.onProgress==null?await Promise.all(n):await H5(n,t.onProgress,r,s)).map(u=>u.arrayBuffer()),o=.5,l=1;return t.onProgress==null?await Promise.all(i):await H5(i,t.onProgress,o,l)}async function U$(e,t="",a,n){return n4(r=>a4(r,{requestInit:n}))(e,t,a)}function n4(e){return async(t,a="",n)=>{let r=t.map(()=>!1),s={},i=n!=null?n.map(()=>!1):[],o=[];if(t.forEach((h,f)=>{let m=0;h.weights.forEach(g=>{let y="quantization"in g?g.quantization.dtype:g.dtype,x=Km[y]*xt(g.shape),A=()=>{r[f]=!0,s[f]==null&&(s[f]=[]),s[f].push({manifestEntry:g,groupOffset:m,sizeBytes:x})};n!=null?n.forEach((b,k)=>{b===g.name&&(A(),i[k]=!0)}):A(),o.push(g.name),m+=x})}),!i.every(h=>h)){let h=n.filter((f,m)=>!i[m]);throw new Error(`Could not find weights in manifest with names: ${h.join(", ")}.
|
|
Manifest JSON has weights with names: ${o.join(", ")}.`)}let l=r.reduce((h,f,m)=>(f&&h.push(m),h),[]),u=[];l.forEach(h=>{t[h].paths.forEach(f=>{let m=a+(a.endsWith("/")?"":"/")+f;u.push(m)})});let p=await e(u),c={},d=0;return l.forEach(h=>{let f=t[h].paths.length,m=0;for(let A=0;A<f;A++)m+=p[d+A].byteLength;let g=new ArrayBuffer(m),y=new Uint8Array(g),x=0;for(let A=0;A<f;A++){let b=new Uint8Array(p[d+A]);y.set(b,x),x+=b.byteLength}s[h].forEach(A=>{let b=g.slice(A.groupOffset,A.groupOffset+A.sizeBytes),k=Ix(b,[A.manifestEntry]);for(let S in k)c[S]=k[S]}),d+=f}),c}}var G$="application/octet-stream",H$="application/json",J1=class{constructor(e,t){if(this.DEFAULT_METHOD="POST",t==null&&(t={}),this.weightPathPrefix=t.weightPathPrefix,this.onProgress=t.onProgress,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=V().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 ${e.length}).`),this.path=e,t.requestInit!=null&&t.requestInit.body!=null)throw new Error("requestInit is expected to have no pre-existing body, but has one.");this.requestInit=t.requestInit||{}}async save(e){if(e.modelTopology instanceof ArrayBuffer)throw new Error("BrowserHTTPRequest.save() does not support saving model topology in binary formats yet.");let t=Object.assign({method:this.DEFAULT_METHOD},this.requestInit);t.body=new FormData;let a=[{paths:["./model.weights.bin"],weights:e.weightSpecs}],n=Sx(e,a);t.body.append("model.json",new Blob([JSON.stringify(n)],{type:H$}),"model.json"),e.weightData!=null&&t.body.append("model.weights.bin",new Blob([e.weightData],{type:G$}),"model.weights.bin");let r=await this.fetch(this.path,t);if(r.ok)return{modelArtifactsInfo:Zd(e),responses:[r]};throw new Error(`BrowserHTTPRequest.save() failed due to HTTP response status ${r.status}.`)}async load(){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 ${this.path} contains neither model topology or manifest for weights.`);return J2(t,r=>this.loadWeights(r))}async loadWeights(e){let t=Array.isArray(this.path)?this.path[1]:this.path,[a,n]=j$(t),r=this.weightPathPrefix||a,s=Cx(e),i=[],o=[];for(let u of e)for(let p of u.paths)this.weightUrlConverter!=null?o.push(this.weightUrlConverter(p)):i.push(r+p+n);this.weightUrlConverter&&i.push(...await Promise.all(o));let l=await a4(i,{requestInit:this.requestInit,fetchFunc:this.fetch,onProgress:this.onProgress});return[s,Y2(l)]}};J1.URL_SCHEME_REGEX=/^https?:\/\//;function j$(e){let t=e.lastIndexOf("/"),a=e.lastIndexOf("?"),n=e.substring(0,t),r=a>t?e.substring(a):"";return[n+"/",r]}function t2(e){return e.match(J1.URL_SCHEME_REGEX)!=null}var r4=(e,t)=>{if(typeof fetch=="undefined"&&(t==null||t.fetchFunc==null))return null;{let a=!0;if(Array.isArray(e)?a=e.every(n=>t2(n)):a=t2(e),a)return Q1(e,t)}return null};Mt.registerSaveRouter(r4);Mt.registerLoadRouter(r4);function Q1(e,t){return new J1(e,t)}function q$(e,t){return Q1(e,t)}var $m=class{constructor(e){this.modelArtifacts=e}load(){return this.modelArtifacts}},s4=class{constructor(e){this.saveHandler=e}save(e){return this.saveHandler(e)}},X$=class{constructor(e){e.load&&(this.load=()=>Promise.resolve(e.load())),e.save&&(this.save=t=>Promise.resolve(e.save(t)))}};function K$(e,t,a,n){let r=arguments;return new X$(i4(...r))}function i4(e,t,a,n){return arguments.length===1?e.modelTopology!=null||e.weightSpecs!=null?new $m(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 $m({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 $m({modelTopology:e,weightSpecs:t,weightData:a,trainingConfig:n}))}function Z$(e){return new s4(e)}function Y$(e){return new s4(e)}var o4={};Ze(o4,{confusionMatrix:()=>Q$});function J$(e,t,a){let n=E(e,"labels","confusionMatrix"),r=E(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 ${a}`);let s=$c(Xe(n,"int32"),a),i=$c(Xe(r,"int32"),a),o=Vs(s),l=ot(o,i);return Xe(l,"int32")}var Q$=z({confusionMatrix_:J$}),Sr={};Ze(Sr,{fromPixels:()=>i_,fromPixelsAsync:()=>r_,toPixels:()=>s_});var Es;function l4(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(Nc(nd,L.backendName)!=null){let d={pixels:e},h={numChannels:t};return L.runKernel(nd,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(Es==null)if(typeof document=="undefined")if(typeof OffscreenCanvas!="undefined"&&typeof OffscreenCanvasRenderingContext2D!="undefined")Es=new OffscreenCanvas(1,1).getContext("2d");else throw new Error("Cannot parse input in current context. Reason: OffscreenCanvas Context2D rendering is not supported.");else Es=document.createElement("canvas").getContext("2d",{willReadFrequently:!0});Es.canvas.width=l,Es.canvas.height=u,Es.drawImage(e,0,0,l,u),p=Es.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 f=0;f<t;++f)c[h*t+f]=p[h*4+f]}return z1(c,[u,l,t],"int32")}function e_(e){return e!=null&&e.data instanceof Uint8Array}function t_(){return typeof window!="undefined"&&typeof ImageBitmap!="undefined"&&window.hasOwnProperty("createImageBitmap")}function a_(e){return e!=null&&e.width!==0&&e.height!==0}function n_(e){return t_()&&!(e instanceof ImageBitmap)&&a_(e)&&!e_(e)}async function r_(e,t=3){let a=null;if(V().getBool("WRAP_TO_IMAGEBITMAP")&&n_(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 l4(a,t)}async function s_(e,t){let a=E(e,"img","toPixels");if(!(e instanceof pt)){let u=a;a=Xe(u,"int32"),u.dispose()}if(a.rank!==2&&a.rank!==3)throw new Error(`toPixels only supports rank 2 or 3 tensors, got rank ${a.rank}.`);let[n,r]=a.shape.slice(0,2),s=a.rank===2?1:a.shape[2];if(s>4||s===2)throw new Error(`toPixels only supports depth of size 1, 3 or 4 but got ${s}`);if(a.dtype!=="float32"&&a.dtype!=="int32")throw new Error(`Unsupported type for toPixels: ${a.dtype}. Please use float32 or int32 tensors.`);let 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){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}var i_=z({fromPixels_:l4}),e3={};Ze(e3,{prepareAndValidate:()=>u4});function u4(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(xt(e.shape)===0)throw new Error(`Requested more than 0 entries, but input is empty. Input shape: ${e.shape}.`);let r=t.shape,s=r[r.length-1],i=1;for(let c=0;c<r.length-1;++c)i*=r[c];let o=e.shape,l=r.slice();l.pop();let u=1;for(let c=s;c<a;++c)u*=o[c],l.push(o[c]);let p=[...bl(e.shape).map(c=>c/u),1].slice(0,s);return[l,i,u,p]}var St={};Ze(St,{assertParamsValid:()=>l_,computeFlatOffset:()=>h_,computeOutShape:()=>d_,getNormalizedAxes:()=>p_,isSliceContinous:()=>c_,maskToAxes:()=>u_,parseSliceParams:()=>f_,sliceInfo:()=>m_,startForAxis:()=>g4,startIndicesWithElidedDims:()=>h4,stopForAxis:()=>y4,stopIndicesWithElidedDims:()=>f4,stridesForAxis:()=>m4,stridesWithElidedDims:()=>d4});var a2=-2,o_=-1;function l_(e,t,a){let n=e.shape.length;F(n===t.length,()=>`Error in slice${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 u_(e){let t=[],a=0;for(;e>0;)e&1&&t.push(a),e/=2,a++;return t}function d_(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 d4(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 p4(e,t,a){return a<=e?a:a-(t-1)}function c4(e,t){let a=[];for(let n=0;n<e;n++)a.push(t+n);return a}function p_(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],f=a+1;p=h4(i,h,f,n,e),c=f4(o,h,f,r,e),d=d4(s,h,f,e)}else for(let h=0;h<u;h++)p[h]=g4(i,n,s,e,h,l),c[h]=y4(o,r,s,e,h,l),d[h]=m4(s,h,l);return{begin:p,end:c,strides:d}}function h4(e,t,a,n,r){let s=[...r],i=c4(a,t);for(let o=0;o<s.length;o++)if(i.indexOf(o)>-1)s[o]=0;else{let l=p4(t,a,o),u=n[l];e&1<<l&&(u=0),s[o]=u}return s}function f4(e,t,a,n,r){let s=[...r],i=c4(a,t);for(let o=0;o<s.length;o++)if(i.indexOf(o)>-1)s[o]=Number.MAX_SAFE_INTEGER;else{let l=p4(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]=ad(0,s[o],r[o])}return s}function m4(e,t,a){let n=e[t];return(a&1<<t||n==null)&&(n=1),n}function g4(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=ad(0,i,l-1),i}function y4(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=ad(0,i,l):i=ad(-1,i,l-1),i}function c_(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 h_(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 ${o}.`),e.shape[o]-n[o])),[n,s]}function m_(e,t,a,n,r,s,i,o,l){let u;if(n==null?(u=new Array(t.length),u.fill(1)):u=n,i!=null&&i&i-1)throw new Error("Multiple ellipses in slice is not allowed.");let p=!1,c={dims:u.length,numAddAxisAfterEllipsis:0,begin:t.slice(),end:a.slice(),strides:u.slice(),beginMask:r,endMask:s,ellipsisMask:i,newAxisMask:o,shrinkAxisMask:l};for(let x=0;x<c.dims;x++)p&&1<<x&o&&c.numAddAxisAfterEllipsis++,1<<x&i&&(p=!0);p||(c.ellipsisMask|=1<<c.dims,c.dims++);let d={dims:e.length,beginMask:0,endMask:0,beginValid:!1,endValid:!1};g_(c,d);let h=!0,f=!0,m=!0,g=[],y=[];for(let x=0;x<e.length;++x){if(d.strides[x]===0)throw Error(`strides[${x}] must be non-zero`);let A=!!(d.shrinkAxisMask&1<<x),b=e[x];if(b===-1){g.push(A?1:-1);continue}let k=[d.beginMask&1<<x,d.endMask&1<<x],S=[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.");m=m&&d.strides[x]===1;let C=!!(d.beginMask&1<<x&&d.endMask&1<<x);if(d.beginValid&&d.endValid){if(A){let R=d.begin[x]<0?b+d.begin[x]:d.begin[x];if(d.begin[x]=R,d.end[x]=d.begin[x]+1,R<0||R>=b)throw Error(`slice index ${d.begin[x]} of dimension ${x} out of bounds.`)}else d.begin[x]=j5(d.begin[x],0,d.strides[x],b,k,S),d.end[x]=j5(d.end[x],1,d.strides[x],b,k,S);let M=d.strides[x]===1&&d.begin[x]===0&&d.end[x]===b;h=h&&M,f=f&&(x===0&&d.strides[x]===1||M)}else h=h&&d.strides[x]===1&&C,f=f&&(x===0&&d.strides[x]===1||C);let N,$=!1;if(d.beginValid&&d.endValid?(N=d.end[x]-d.begin[x],$=!0):A?(N=1,$=!0):C&&b>=0&&(d.strides[x]<0?N=-b:N=b,$=!0),$){let M;N===0||N<0!=d.strides[x]<0?M=0:M=Math.trunc(N/d.strides[x])+(N%d.strides[x]!==0?1:0),g.push(M)}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===a2&&y.push(1)}return{finalShapeSparse:y.filter((x,A)=>d.finalShapeGatherIndices[A]!==a2),finalShape:y,isIdentity:h,sliceDim0:f,isSimpleSlice:m,begin:d.begin,end:d.end,strides:d.strides}}function g_(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(a2),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, ${t.begin.length}.`);e.begin!=null&&(t.begin[a]=e.begin[n]),e.end!=null&&(t.end[a]=e.end[n]),t.strides[a]=e.strides[n],e.beginMask&1<<n&&(t.beginMask|=1<<a),e.endMask&1<<n&&(t.endMask|=1<<a),e.shrinkAxisMask&1<<n?(t.finalShapeGatherIndices.push(o_),t.finalShapeGatherIndicesSparse.push(-1),t.shrinkAxisMask|=1<<a):(t.finalShapeGatherIndices.push(a),t.finalShapeGatherIndicesSparse.push(n)),t.inputShapeGatherIndicesSparse[a]=n,a++}}function j5(e,t,a,n,r,s){if(r[t])return a>0?s[t]:s[t+1&1];{let i=e<0?n+e:e;return i<s[0]?s[0]:i>s[1]?s[1]:i}}var t3="4.2.0",x4=class{static sgd(e){return new Sh(e)}static momentum(e,t,a=!1){return new Z1(e,t,a)}static rmsprop(e,t=.9,a=0,n=null,r=!1){return new Y1(e,t,a,n,r)}static adam(e=.001,t=.9,a=.999,n=null){return new X1(e,t,a,n)}static adadelta(e=.001,t=.95,a=null){return new j1(e,t,a)}static adamax(e=.002,t=.9,a=.999,n=null,r=0){return new K1(e,t,a,n,r)}static adagrad(e,t=.1){return new q1(e,t)}},y_=x4,x_=(()=>typeof requestAnimationFrame!="undefined"?requestAnimationFrame:typeof setImmediate!="undefined"?setImmediate:e=>e())();function A4(){return new Promise(e=>x_(()=>e()))}var T={};Ze(T,{ERF_A1:()=>F_,ERF_A2:()=>O_,ERF_A3:()=>D_,ERF_A4:()=>z_,ERF_A5:()=>L_,ERF_P:()=>P_,PARALLELIZE_THRESHOLD:()=>a3,RowPartitionType:()=>Hn,SELU_SCALE:()=>__,SELU_SCALEALPHA:()=>$_,applyActivation:()=>wh,assertAndGetBroadcastShape:()=>zt,assertAxesAreInnerMostDims:()=>xN,assertParamsConsistent:()=>A_,assignToTypedArray:()=>H_,axesAreInnerMostDims:()=>d1,calculateShapes:()=>Ob,checkEinsumDimSizes:()=>Y_,checkPadOnDimRoundingMode:()=>Cn,combineLocations:()=>wA,combineRaggedTensorToTensorShapes:()=>v_,complexWithEvenIndex:()=>V_,complexWithOddIndex:()=>U_,computeConv2DInfo:()=>ep,computeConv3DInfo:()=>jx,computeDefaultPad:()=>n1,computeDilation2DInfo:()=>gC,computeOptimalWindowSize:()=>S_,computeOutAndReduceShapes:()=>yN,computeOutShape:()=>b_,computePool2DInfo:()=>Hx,computePool3DInfo:()=>yC,convertConv2DDataFormat:()=>qx,decodeEinsumEquation:()=>K_,eitherStridesOrDilationsAreOne:()=>wr,expandShapeToKeepDim:()=>np,exponent:()=>q_,exponents:()=>j_,fromStringArrayToUint8:()=>xP,fromUint8ToStringArray:()=>yP,getAxesPermutation:()=>AN,getBroadcastDims:()=>xA,getComplexWithIndex:()=>G_,getEinsumComputePath:()=>J_,getEinsumPermutation:()=>Z_,getFusedBiasGradient:()=>kh,getFusedDyActivation:()=>vh,getImageCenter:()=>T_,getInnerMostAxes:()=>vN,getPermuted:()=>N_,getRaggedRank:()=>w_,getReductionAxes:()=>o1,getReshaped:()=>C_,getReshapedPermuted:()=>E_,getRowPartitionTypesHelper:()=>k_,getSliceBeginCoords:()=>R_,getSliceSize:()=>M_,getSparseFillEmptyRowsIndicesDenseShapeMismatch:()=>aP,getSparseFillEmptyRowsNegativeIndexErrorMessage:()=>nP,getSparseFillEmptyRowsOutOfRangeIndexErrorMessage:()=>rP,getSparseReshapeEmptyTensorZeroOutputDimErrorMessage:()=>oP,getSparseReshapeInputOutputMismatchErrorMessage:()=>uP,getSparseReshapeInputOutputMultipleErrorMessage:()=>lP,getSparseReshapeMultipleNegativeOneOutputDimErrorMessage:()=>sP,getSparseReshapeNegativeOutputDimErrorMessage:()=>iP,getSparseSegmentReductionIndicesOutOfRangeErrorMessage:()=>hP,getSparseSegmentReductionNegativeSegmentIdsErrorMessage:()=>dP,getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage:()=>pP,getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage:()=>cP,getUndoAxesPermutation:()=>bN,isIdentityPermutation:()=>Q_,log:()=>MS,mergeRealAndImagArrays:()=>B_,prepareAndValidate:()=>u4,prepareSplitSize:()=>tP,segment_util:()=>b4,shouldFuse:()=>Ih,slice_util:()=>St,splitRealAndImagArrays:()=>W_,stridesOrDilationsArePositive:()=>Bs,tupleValuesAreOne:()=>pd,upcastType:()=>fa,validateDefaultValueShape:()=>I_,validateInput:()=>V1,validateUpdateShape:()=>W1,warn:()=>Dr});function A_(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 ${s}.`)})}function b_(e,t){let a=e[0].slice();for(let n=1;n<e.length;n++)a[t]+=e[n][t];return a}var Hn;(function(e){e[e.FIRST_DIM_SIZE=0]="FIRST_DIM_SIZE",e[e.VALUE_ROWIDS=1]="VALUE_ROWIDS",e[e.ROW_LENGTHS=2]="ROW_LENGTHS",e[e.ROW_SPLITS=3]="ROW_SPLITS",e[e.ROW_LIMITS=4]="ROW_LIMITS",e[e.ROW_STARTS=5]="ROW_STARTS"})(Hn||(Hn={}));function v_(e,t,a){let n=new Array;if(a==null&&t==null)return n;if(t==null)for(;n.length<e+a.length;)n.push(-1);else n=t.slice();if(a==null)return n;if(e+a.length!==n.length)throw new Error(`rt input.shape and shape=${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}] = ${o}`)}else n[i]=s}return n}function k_(e){let t={FIRST_DIM_SIZE:Hn.FIRST_DIM_SIZE,VALUE_ROWIDS:Hn.VALUE_ROWIDS,ROW_LENGTHS:Hn.ROW_LENGTHS,ROW_SPLITS:Hn.ROW_SPLITS,ROW_LIMITS:Hn.ROW_LIMITS,ROW_STARTS:Hn.ROW_STARTS},a=[];for(let n of e)if(n in t)a.push(t[n]);else break;return a}function w_(e){return e.length===0?0:e[0]===Hn.FIRST_DIM_SIZE?e.length-1:e.length}function I_(e,t){if(e==null||t==null)return;let a=e.length,n=t.length;if(a>=n)throw new Error(`defaultValue.shape=${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 a3=30;function S_(e){return e<=a3?e:Cc(e,Math.floor(Math.sqrt(e)))}function T_(e,t,a){let n=a*(typeof e=="number"?e:e[0]),r=t*(typeof e=="number"?e:e[1]);return[n,r]}function C_(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 N_(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 E_(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 R_(e,t){let a=[0];for(let n=0;n<t;++n)a.push(e[n][0]);return a}function M_(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 $_=1.7580993408473768,__=1.0507009873554805,P_=.3275911,F_=.254829592,O_=-.284496736,D_=1.421413741,z_=-1.453152027,L_=1.061405429;function B_(e,t){if(e.length!==t.length)throw new Error(`Cannot merge real and imag arrays of different lengths. real:${e.length}, imag: ${t.length}.`);let a=new Float32Array(e.length*2);for(let n=0;n<a.length;n+=2)a[n]=e[n/2],a[n+1]=t[n/2];return a}function W_(e){let t=new Float32Array(e.length/2),a=new Float32Array(e.length/2);for(let n=0;n<e.length;n+=2)t[n/2]=e[n],a[n/2]=e[n+1];return{real:t,imag:a}}function V_(e){let t=Math.ceil(e.length/4),a=new Float32Array(t),n=new Float32Array(t);for(let r=0;r<e.length;r+=4)a[Math.floor(r/4)]=e[r],n[Math.floor(r/4)]=e[r+1];return{real:a,imag:n}}function U_(e){let t=Math.floor(e.length/4),a=new Float32Array(t),n=new Float32Array(t);for(let r=2;r<e.length;r+=4)a[Math.floor(r/4)]=e[r],n[Math.floor(r/4)]=e[r+1];return{real:a,imag:n}}function G_(e,t){let a=e[t*2],n=e[t*2+1];return{real:a,imag:n}}function H_(e,t,a,n){e[n*2]=t,e[n*2+1]=a}function j_(e,t){let a=new Float32Array(e/2),n=new Float32Array(e/2);for(let r=0;r<Math.ceil(e/2);r++){let s=(t?2:-2)*Math.PI*(r/e);a[r]=Math.cos(s),n[r]=Math.sin(s)}return{real:a,imag:n}}function q_(e,t,a){let n=(a?2:-2)*Math.PI*(e/t),r=Math.cos(n),s=Math.sin(n);return{real:r,imag:s}}var _m="->",X_=/->/g,q5=",",X5="...";function K_(e,t){e=e.replace(/\s/g,"");let a=(e.length-e.replace(X_,"").length)/_m.length;if(a<1)throw new Error("Equations without an arrow are not supported.");if(a>1)throw new Error(`Equation must contain exactly one arrow ("${_m}").`);let[n,r]=e.split(_m);F(n.indexOf(X5)===-1,()=>`The ellipsis notation ("${X5}") is not supported yet.`);let s=n.split(q5),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(f=>f.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!==q5&&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 Z_(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 Y_(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 J_(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=eP(t,o);for(let u of l)s.indexOf(u)===-1&&(n[i].push(u),s.push(u))}return{path:a,steps:n}}function Q_(e){return e.every((t,a)=>t===a)}function eP(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 tP(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 aP(e){return`Received SparseTensor with denseShape[0] = 0 but
|
|
indices.shape[0] = ${e}`}function nP(e,t){return`indices(${e}, 0) is invalid: ${t} < 0`}function rP(e,t,a){return`indices(${e}, 0) is invalid: ${t} >= ${a}`}function sP(e,t){return`only one output dimension may be -1, not both ${e} and ${t}`}function iP(e,t){return`size ${e} must be non-negative, not ${t}`}function oP(){return"reshape cannot infer the missing input size for an empty tensor unless all specified input sizes are non-zero"}function lP(e,t){let a=xt(e),n=xt(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 uP(e,t){let a=xt(e),n=xt(t);return`Input to reshape is a tensor with ${a} dense values, but the requested shape has ${n}. inputShape=${e} outputShape=${t}`}function dP(){return"segment ids must be >= 0"}function pP(){return"segment ids are not increasing"}function cP(e,t){return`Segment id ${e} out of range [0, ${t}), possibly because segmentIds input is not sorted.`}function hP(e,t,a){return`Bad: indices[${e}] == ${t} out of range [0, ${a})`}var b4={};Ze(b4,{collectGatherOpShapeInfo:()=>gP,computeOutShape:()=>mP,segOpComputeOptimalWindowSize:()=>fP});function fP(e,t){let a=!1,n;for(e<=a3?(n=e,a=!0):n=Cc(e,Math.floor(Math.sqrt(e)));!a;)n>t||n===e?a=!0:n=Cc(e,n+1);return n}function mP(e,t,a){let n=[],r=e.length;for(let s=0;s<r;s++)s!==t?n.push(e[s]):n.push(a);return n}function gP(e,t,a,n){let r=t.shape.length,s=e.shape.length;if(n!==0&&(n<-r||n>r))throw new Error(`Expect batchDims in the range of [-${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 yP(e){try{return e.map(t=>Ec(t))}catch(t){throw new Error(`Failed to decode encoded string bytes into utf-8, error: ${t}`)}}function xP(e){return e.map(t=>qd(t))}var Nn={};Ze(Nn,{nonMaxSuppressionV3Impl:()=>Gb,nonMaxSuppressionV4Impl:()=>Hb,nonMaxSuppressionV5Impl:()=>jb,whereImpl:()=>_b});F$();var AP=V();AP.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 In;(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"})(In||(In={}));var K5;(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={}))})(K5||(K5={}));var n3={};function bP(e,t){let a={tfOpName:e,category:"custom",inputs:[],attrs:[],customExecutor:t};n3[e]=a}function v4(e){return n3[e]}function vP(e){delete n3[e]}function w(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;if(s.type==="tensor")return va(t.inputNames[s.inputIndexStart],a,n,r);if(s.type==="tensors")return t.inputNames.slice(o,l).map(c=>va(c,a,n,r));let u=va(t.inputNames.slice(o)[0],a,n,r),p=u.dataSync();return s.type==="number"?p[0]:v.toNestedArray(u.shape,p)}let i=t.attrParams[e];return i&&i.value}function va(e,t,a,n){let[r,s]=Xa(e);if(n!=null){let o=n.getHashTableHandleByName(r);if(o!=null)return o}let i=a.currentContextIds.find(o=>!!t[_c(r,o)]);return i!==void 0?t[_c(r,i)][s]:void 0}function kP(e,t,a){return t[_c(e,a.currentContextId)]}function gr(e,t){let[a,n,r]=Xa(e);return[_c(a,t&&t.currentContextId),n,r]}function _c(e,t){return t?`${e}-${t}`:e}function Xa(e){let t=e.split(":");if(t.length===1)return[e,0,void 0];let a=t[0],n=t.length===3?t[1]:void 0,r=Number(t[t.length-1]);return[a,r,n]}function xc(e,t,a){let n=w("pad",e,t,a);if(n==="explicit"){n=w("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 yr(e){return e.kept?e:wa(e)}var k4={};Ze(k4,{json:()=>wP});var wP=[{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}]}],w4={};Ze(w4,{json:()=>IP});var IP=[{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:"Prod",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axes",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool",notSupported:!0},{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}]}],I4={};Ze(I4,{json:()=>SP});var SP=[{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"}]}],S4={};Ze(S4,{json:()=>TP});var TP=[{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"}]}],T4={};Ze(T4,{json:()=>CP});var CP=[{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:"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"}]}],C4={};Ze(C4,{json:()=>NP});var NP=[{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}]}],N4={};Ze(N4,{json:()=>EP});var EP=[{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"}]}],E4={};Ze(E4,{json:()=>RP});var RP=[{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"}]}],R4={};Ze(R4,{json:()=>MP});var MP=[{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"}]}],M4={};Ze(M4,{json:()=>$P});var $P=[{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"}]}],$4={};Ze($4,{json:()=>_P});var _P=[{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}]}],_4={};Ze(_4,{json:()=>PP});var PP=[{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"}]}],P4={};Ze(P4,{json:()=>FP});var FP=[{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"}]},{tfOpName:"SparseToDense",category:"normalization",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:!0,notSupported:!0}]}],F4={};Ze(F4,{json:()=>OP});var OP=[{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"}]},{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"}]}],O4={};Ze(O4,{json:()=>DP});var DP=[{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}]}],D4={};Ze(D4,{json:()=>zP});var zP=[{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"}]}],z4={};Ze(z4,{json:()=>LP});var LP=[{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}]}],L4={};Ze(L4,{json:()=>BP});var BP=[{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"}]}],B4={};Ze(B4,{json:()=>WP});var WP=[{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:"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:[]}],Z5=class{constructor(){let e=[k4,w4,I4,S4,T4,C4,N4,E4,R4,M4,$4,_4,P4,F4,O4,D4,z4,L4,B4],t=[].concat(...e.map(a=>a.json));this.opMappers=t.reduce((a,n)=>(a[n.tfOpName]=n,a),{})}static get Instance(){return this._instance||(this._instance=new this)}transformGraph(e,t={}){let a=e.node,n=[],r=[],s=[],i=a.reduce((f,m)=>(f[m.name]=this.mapNode(m),m.op.startsWith("Placeholder")?n.push(f[m.name]):m.op==="Const"?r.push(f[m.name]):(m.input==null||m.input.length===0)&&s.push(f[m.name]),f),{}),o=[],l=[],u={},p={};t!=null&&(u=this.mapSignatureEntries(t.inputs),p=this.mapSignatureEntries(t.outputs));let c=Object.keys(i);c.forEach(f=>{let m=i[f];m.inputNames.forEach((g,y)=>{let[x,,A]=gr(g),b=i[x];if(b.outputs!=null){let k=b.outputs.indexOf(A);if(k!==-1){let S=`${x}:${k}`;m.inputNames[y]=S}}m.inputs.push(b),b.children.push(m)})}),Object.keys(p).length===0?c.forEach(f=>{let m=i[f];m.children.length===0&&l.push(m)}):Object.keys(p).forEach(f=>{let[m]=gr(f),g=i[m];g!=null&&(g.signatureKey=p[f],l.push(g))}),Object.keys(u).length>0?Object.keys(u).forEach(f=>{let[m]=gr(f),g=i[m];g&&(g.signatureKey=u[f],o.push(g))}):o=n;let d={};e.library!=null&&e.library.function!=null&&(d=e.library.function.reduce((f,m)=>(f[m.signature.name]=this.mapFunction(m),f),{}));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=v4(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=n2(e.attr,r.tfName,r.defaultValue),i===void 0&&r.tfDeprecatedName&&(i=n2(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"string[]":i=d2(e.attr,r.tfName,r.defaultValue),i===void 0&&r.tfDeprecatedName&&(i=d2(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"number":i=s2(e.attr,r.tfName,r.defaultValue||0),i===void 0&&r.tfDeprecatedName&&(i=s2(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"number[]":i=u2(e.attr,r.tfName,r.defaultValue),i===void 0&&r.tfDeprecatedName&&(i=u2(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"bool":i=r2(e.attr,r.tfName,r.defaultValue),i===void 0&&r.tfDeprecatedName&&(i=r2(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"bool[]":i=c2(e.attr,r.tfName,r.defaultValue),i===void 0&&r.tfDeprecatedName&&(i=c2(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"shape":i=l2(e.attr,r.tfName,r.defaultValue),i===void 0&&r.tfDeprecatedName&&(i=l2(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"shape[]":i=p2(e.attr,r.tfName,r.defaultValue),i===void 0&&r.tfDeprecatedName&&(i=p2(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"dtype":i=i2(e.attr,r.tfName,r.defaultValue),i===void 0&&r.tfDeprecatedName&&(i=i2(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"dtype[]":i=o2(e.attr,r.tfName,r.defaultValue),i===void 0&&r.tfDeprecatedName&&(i=o2(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"func":i=Y5(e.attr,r.tfName,r.defaultValue),i===void 0&&r.tfDeprecatedName&&(i=Y5(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"tensor":case"tensors":break;default:throw new Error(`Unsupported param type: ${r.type} for op: ${e.op}`)}return n[r.name]={value:i,type:s},n},{})),a}mapFunction(e){let t=e.nodeDef,a=[],n=[],r={};t!=null&&(r=t.reduce((u,p)=>(u[p.name]=this.mapNode(p),p.op==="Const"&&n.push(u[p.name]),u),{}));let s=[],i=[];e.signature.inputArg.forEach(u=>{let[p]=gr(u.name),c={name:p,op:"Placeholder",inputs:[],inputNames:[],category:"graph",inputParams:{},attrParams:{dtype:{value:r3(u.type),type:"dtype"}},children:[]};c.signatureKey=u.name,s.push(c),r[p]=c}),Object.keys(r).forEach(u=>{let p=r[u];p.inputNames.forEach((c,d)=>{let[h,,f]=gr(c),m=r[h];if(m.outputs!=null){let g=m.outputs.indexOf(f);if(g!==-1){let y=`${h}:${g}`;p.inputNames[d]=y}}p.inputs.push(m),m.children.push(p)})});let o=e.ret;e.signature.outputArg.forEach(u=>{let[p,c]=gr(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 VP(e){let t=V().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 W4(e,t){let a=Array.isArray(e)?String.fromCharCode.apply(null,e):VP(e);return t?a:a.toLowerCase()}function n2(e,t,a,n=!1){let r=e[t];return r!=null?W4(r.s,n):a}function r2(e,t,a){let n=e[t];return n?n.b:a}function s2(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 r3(e){switch(typeof e=="string"&&(e=In[e]),e){case In.DT_FLOAT:case In.DT_HALF:return"float32";case In.DT_INT32:case In.DT_INT64:case In.DT_INT8:case In.DT_UINT8:return"int32";case In.DT_BOOL:return"bool";case In.DT_DOUBLE:return"float32";case In.DT_STRING:return"string";default:return null}}function Y5(e,t,a){let n=e[t];return n&&n.func?n.func.name:a}function i2(e,t,a){let n=e[t];return n&&n.type?r3(n.type):a}function o2(e,t,a){let n=e[t];return n&&n.list&&n.list.type?n.list.type.map(r=>r3(r)):a}function V4(e){if(!e.unknownRank)return e.dim!=null?e.dim.map(t=>typeof t.size=="number"?t.size:parseInt(t.size,10)):[]}function l2(e,t,a){let n=e[t];return n&&n.shape?V4(n.shape):a}function u2(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 d2(e,t,a,n=!1){let r=e[t];return r&&r.list&&r.list.s?r.list.s.map(s=>W4(s,n)):a}function p2(e,t,a){let n=e[t];return n&&n.list&&n.list.shape?n.list.shape.map(r=>V4(r)):a}function c2(e,t,a){let n=e[t];return n&&n.list&&n.list.b?n.list.b:a}var UP=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 va(e,this.tensorMap,this.context)}getAttr(e,t){let a=this.node.rawAttrs[e];if(a.tensor!=null)return va(e,this.tensorMap,this.context);if(a.i!=null||a.f!=null)return s2(this.node.rawAttrs,e,t);if(a.s!=null)return n2(this.node.rawAttrs,e,t);if(a.b!=null)return r2(this.node.rawAttrs,e,t);if(a.shape!=null)return l2(this.node.rawAttrs,e,t);if(a.type!=null)return i2(this.node.rawAttrs,e,t);if(a.list!=null){if(a.list.i!=null||a.list.f!=null)return u2(this.node.rawAttrs,e,t);if(a.list.s!=null)return d2(this.node.rawAttrs,e,t);if(a.list.shape!=null)return p2(this.node.rawAttrs,e,t);if(a.list.b!=null)return c2(this.node.rawAttrs,e,t);if(a.list.type!=null)return o2(this.node.rawAttrs,e,t)}return t}},Zt={};Ze(Zt,{OP_SCOPE_SUFFIX:()=>K2,abs:()=>Ka,acos:()=>Fx,acosh:()=>Ox,add:()=>be,addN:()=>ph,all:()=>Dx,any:()=>zx,argMax:()=>ar,argMin:()=>Lx,asin:()=>Bx,asinh:()=>Wx,atan:()=>Vx,atan2:()=>Ux,atanh:()=>Gx,avgPool:()=>r1,avgPool3d:()=>Xx,basicLSTMCell:()=>Kx,batchNorm:()=>tp,batchNorm2d:()=>Zx,batchNorm3d:()=>Yx,batchNorm4d:()=>Jx,batchToSpaceND:()=>s1,bincount:()=>i1,booleanMaskAsync:()=>Pb,broadcastArgs:()=>Qx,broadcastTo:()=>rl,buffer:()=>_e,cast:()=>Xe,ceil:()=>eA,clipByValue:()=>tA,clone:()=>wa,complex:()=>vr,concat:()=>st,concat1d:()=>aA,concat2d:()=>ru,concat3d:()=>nA,concat4d:()=>rA,conv1d:()=>sA,conv2d:()=>ap,conv2dTranspose:()=>oA,conv3d:()=>lA,conv3dTranspose:()=>uA,cos:()=>dA,cosh:()=>pA,cosineWindow:()=>bh,cumprod:()=>cA,cumsum:()=>hA,denseBincount:()=>fA,depthToSpace:()=>mA,depthwiseConv2d:()=>ch,diag:()=>gA,dilation2d:()=>yA,div:()=>xe,divNoNan:()=>AA,dot:()=>bA,dropout:()=>Bb,einsum:()=>vA,elu:()=>u1,enclosingPowerOfTwo:()=>U1,equal:()=>l1,erf:()=>kA,euclideanNorm:()=>SA,exp:()=>Zr,expandDims:()=>Gt,expm1:()=>TA,eye:()=>p1,fft:()=>xh,fill:()=>nr,floor:()=>c1,floorDiv:()=>Qd,fused:()=>G1,gather:()=>h1,gatherND:()=>Lb,greater:()=>sp,greaterEqual:()=>f1,ifft:()=>fd,imag:()=>ip,image:()=>ye,inTopKAsync:()=>Wb,irfft:()=>F1,isFinite:()=>CA,isInf:()=>NA,isNaN:()=>EA,leakyRelu:()=>m1,less:()=>RA,lessEqual:()=>hh,linalg:()=>Kb,linspace:()=>MA,localResponseNormalization:()=>$A,log:()=>ul,log1p:()=>g1,logSigmoid:()=>PA,logSoftmax:()=>FA,logSumExp:()=>x1,logicalAnd:()=>cd,logicalNot:()=>A1,logicalOr:()=>b1,logicalXor:()=>OA,losses:()=>Zb,lowerBound:()=>DA,matMul:()=>ot,max:()=>ha,maxPool:()=>v1,maxPool3d:()=>zA,maxPoolWithArgmax:()=>LA,maximum:()=>k1,mean:()=>hd,meshgrid:()=>BA,min:()=>Kr,minimum:()=>w1,mirrorPad:()=>WA,mod:()=>su,moments:()=>VA,movingAverage:()=>Fb,mul:()=>te,multiRNNCell:()=>UA,multinomial:()=>GA,neg:()=>Xn,norm:()=>rp,notEqual:()=>I1,oneHot:()=>$c,ones:()=>Br,onesLike:()=>HA,op:()=>z,outerProduct:()=>jA,pad:()=>rr,pad1d:()=>qA,pad2d:()=>XA,pad3d:()=>KA,pad4d:()=>ZA,pool:()=>YA,pow:()=>ll,prelu:()=>T1,print:()=>Q2,prod:()=>JA,raggedGather:()=>QA,raggedRange:()=>eb,raggedTensorToTensor:()=>tb,rand:()=>ab,randomGamma:()=>ib,randomNormal:()=>M1,randomStandardNormal:()=>ob,randomUniform:()=>$1,range:()=>dl,real:()=>pl,reciprocal:()=>lb,relu:()=>op,relu6:()=>_1,reshape:()=>Q,reverse:()=>Yr,reverse1d:()=>ub,reverse2d:()=>db,reverse3d:()=>pb,reverse4d:()=>cb,rfft:()=>Ah,round:()=>P1,rsqrt:()=>hb,scalar:()=>ze,scatterND:()=>Db,searchSorted:()=>mh,selu:()=>fb,separableConv2d:()=>mb,setdiff1dAsync:()=>gb,sigmoid:()=>za,sign:()=>yb,signal:()=>Xb,sin:()=>xb,sinh:()=>Ab,slice:()=>Fe,slice1d:()=>bb,slice2d:()=>vb,slice3d:()=>lp,slice4d:()=>gh,softmax:()=>yh,softplus:()=>y1,spaceToBatchND:()=>S1,sparse:()=>Yb,sparseToDense:()=>zb,spectral:()=>qb,split:()=>Ia,sqrt:()=>Jn,square:()=>Tn,squaredDifference:()=>O1,squeeze:()=>De,stack:()=>la,step:()=>D1,stridedSlice:()=>kb,string:()=>Jb,sub:()=>fe,sum:()=>rt,tan:()=>wb,tanh:()=>Mc,tensor:()=>Ue,tensor1d:()=>Ht,tensor2d:()=>Kn,tensor3d:()=>z1,tensor4d:()=>Ib,tensor5d:()=>Sb,tensor6d:()=>Tb,tile:()=>Ur,topk:()=>Cb,transpose:()=>Vs,truncatedNormal:()=>Nb,unique:()=>Eb,unsortedSegmentSum:()=>Rb,unstack:()=>Ca,upperBound:()=>Mb,variable:()=>$b,where:()=>Ws,whereAsync:()=>L1,zeros:()=>gn,zerosLike:()=>Ya});var GP=(e,t,a,n=Zt)=>{switch(e.op){case"BiasAdd":case"AddV2":case"Add":return[n.add(w("a",e,t,a),w("b",e,t,a))];case"AddN":return[n.addN(w("tensors",e,t,a))];case"FloorMod":case"Mod":return[n.mod(w("a",e,t,a),w("b",e,t,a))];case"Mul":return[n.mul(w("a",e,t,a),w("b",e,t,a))];case"RealDiv":case"Div":return[n.div(w("a",e,t,a),w("b",e,t,a))];case"DivNoNan":return[n.divNoNan(w("a",e,t,a),w("b",e,t,a))];case"FloorDiv":return[n.floorDiv(w("a",e,t,a),w("b",e,t,a))];case"Sub":return[n.sub(w("a",e,t,a),w("b",e,t,a))];case"Minimum":return[n.minimum(w("a",e,t,a),w("b",e,t,a))];case"Maximum":return[n.maximum(w("a",e,t,a),w("b",e,t,a))];case"Pow":return[n.pow(w("a",e,t,a),w("b",e,t,a))];case"SquaredDifference":return[n.squaredDifference(w("a",e,t,a),w("b",e,t,a))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},HP=(e,t,a,n=Zt)=>{switch(e.op){case"Abs":case"ComplexAbs":return[n.abs(w("x",e,t,a))];case"Acos":return[n.acos(w("x",e,t,a))];case"Acosh":return[n.acosh(w("x",e,t,a))];case"Asin":return[n.asin(w("x",e,t,a))];case"Asinh":return[n.asinh(w("x",e,t,a))];case"Atan":return[n.atan(w("x",e,t,a))];case"Atan2":return[n.atan2(w("x",e,t,a),w("y",e,t,a))];case"Atanh":return[n.atanh(w("x",e,t,a))];case"Ceil":return[n.ceil(w("x",e,t,a))];case"Complex":return[n.complex(w("real",e,t,a),w("imag",e,t,a))];case"Cos":return[n.cos(w("x",e,t,a))];case"Cosh":return[n.cosh(w("x",e,t,a))];case"Elu":return[n.elu(w("x",e,t,a))];case"Erf":return[n.erf(w("x",e,t,a))];case"Exp":return[n.exp(w("x",e,t,a))];case"Expm1":return[n.expm1(w("x",e,t,a))];case"Floor":return[n.floor(w("x",e,t,a))];case"Log":return[n.log(w("x",e,t,a))];case"Log1p":return[n.log1p(w("x",e,t,a))];case"Imag":return[n.imag(w("x",e,t,a))];case"Neg":return[n.neg(w("x",e,t,a))];case"Reciprocal":return[n.reciprocal(w("x",e,t,a))];case"Real":return[n.real(w("x",e,t,a))];case"Relu":return[n.relu(w("x",e,t,a))];case"Round":return[n.round(w("x",e,t,a))];case"Selu":return[n.selu(w("x",e,t,a))];case"Sigmoid":return[n.sigmoid(w("x",e,t,a))];case"Sin":return[n.sin(w("x",e,t,a))];case"Sign":return[n.sign(w("x",e,t,a))];case"Sinh":return[n.sinh(w("x",e,t,a))];case"Softplus":return[n.softplus(w("x",e,t,a))];case"Sqrt":return[n.sqrt(w("x",e,t,a))];case"Square":return[n.square(w("x",e,t,a))];case"Tanh":return[n.tanh(w("x",e,t,a))];case"Tan":return[n.tan(w("x",e,t,a))];case"ClipByValue":return[n.clipByValue(w("x",e,t,a),w("clipValueMin",e,t,a),w("clipValueMax",e,t,a))];case"Relu6":return[n.relu6(w("x",e,t,a))];case"Rsqrt":return[n.rsqrt(va(e.inputNames[0],t,a))];case"Prod":return[n.prod(w("x",e,t,a),w("axes",e,t,a))];case"LeakyRelu":return[n.leakyRelu(w("x",e,t,a),w("alpha",e,t,a))];case"Prelu":return[n.prelu(w("x",e,t,a),w("alpha",e,t,a))];case"IsNan":return[n.isNaN(va(e.inputNames[0],t,a))];default:throw TypeError(`Node type ${e.op} is not implemented`)}};function Sn(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 J5(e){return!(typeof e=="number"||e.some(t=>t<0))}function Wu(e,t,a){let n=h2(e,a),r=!J5(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=h2(s.shape,n)}),!J5(n))throw new Error(`Non-fully-defined elementShape: ${n}`);return n}function h2(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 jP=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=ze(0),On(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),Sn(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,On(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 Ue([],[0].concat(this.elementShape));let a=this.readMany(e);return Sn(this.elementShape,a[0].shape,"TensorArray shape mismatch: "),la(a,0)}concat(e){if(e&&e!==this.dtype)throw new Error(`TensorArray dtype is ${this.dtype} but concat requested dtype ${e}`);if(this.size()===0)return Ue([],[0].concat(this.elementShape));let t=[];for(let n=0;n<this.size();n++)t.push(n);let a=this.readMany(t);return Sn(this.elementShape,a[0].shape,`TensorArray shape mismatch: tensor array shape (${this.elementShape}) vs first tensor shape (${a[0].shape})`),st(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,Ca(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=[];Oe(()=>{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)}},hl=class{constructor(e,t,a,n=-1){this.tensors=e,this.elementShape=t,this.elementDtype=a,e!=null&&e.forEach(r=>{if(a!==r.dtype)throw new Error(`Invalid data types; op elements ${a}, but list elements ${r.dtype}`);Sn(t,r.shape,"TensorList shape mismatch: "),On(r)}),this.idTensor=ze(0),this.maxNumElements=n,On(this.idTensor)}get id(){return this.idTensor.id}copy(){return new hl([...this.tensors],this.elementShape,this.elementDtype)}clearAndClose(e){this.tensors.forEach(t=>{(e==null||!e.has(t.id))&&t.dispose()}),this.tensors.length=0,this.idTensor.dispose()}size(){return this.tensors.length}stack(e,t,a=-1){if(t!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t}, but list elements ${this.elementDtype}`);if(a!==-1&&this.tensors.length!==a)throw new Error(`Operation expected a list with ${a} elements but got a list with ${this.tensors.length} elements.`);Sn(e,this.elementShape,"TensorList shape mismatch: ");let n=Wu(this.elementShape,this.tensors,e);return Oe(()=>{let r=this.tensors.map(s=>Q(s,n));return la(r,0)})}popBack(e,t){if(t!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t}, but list elements ${this.elementDtype}`);if(this.size()===0)throw new Error("Trying to pop from an empty list.");let a=Wu(this.elementShape,this.tensors,e),n=this.tensors.pop();return n.kept=!1,Sn(n.shape,e,"TensorList shape mismatch: "),Q(n,a)}pushBack(e){if(e.dtype!==this.elementDtype)throw new Error(`Invalid data types; op elements ${e.dtype}, but list elements ${this.elementDtype}`);if(Sn(e.shape,this.elementShape,"TensorList shape mismatch: "),this.maxNumElements===this.size())throw new Error("Trying to push element into a full list.");On(e),this.tensors.push(e)}resize(e){if(e<0)throw new Error(`TensorListResize expects size to be non-negative. Got: ${e}`);if(this.maxNumElements!==-1&&e>this.maxNumElements)throw new Error(`TensorListResize input size ${e} is greater maxNumElement ${this.maxNumElements}.`);let t=new hl([],this.elementShape,this.elementDtype,this.maxNumElements);t.tensors.length=e;for(let a=0;a<Math.min(this.tensors.length,e);++a)t.tensors[a]=this.tensors[a];return t}getItem(e,t,a){if(a!==this.elementDtype)throw new Error(`Invalid data types; op elements ${a}, but list elements ${this.elementDtype}`);if(e<0||e>this.tensors.length)throw new Error(`Trying to access element ${e} in a list with ${this.tensors.length} elements.`);if(this.tensors[e]==null)throw new Error(`element at index ${e} is null.`);Sn(this.tensors[e].shape,t,"TensorList shape mismatch: ");let n=Wu(this.elementShape,this.tensors,t);return Q(this.tensors[e],n)}setItem(e,t){if(t.dtype!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t.dtype}, but list elements ${this.elementDtype}`);if(e<0||this.maxNumElements!==-1&&e>=this.maxNumElements)throw new Error(`Trying to set element ${e} in a list with max ${this.maxNumElements} elements.`);Sn(this.elementShape,t.shape,"TensorList shape mismatch: "),On(t),this.tensors[e]!=null&&(this.tensors[e].kept=!1),this.tensors[e]=t}gather(e,t,a){if(t!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t}, but list elements ${this.elementDtype}`);Sn(this.elementShape,a,"TensorList shape mismatch: "),e=e.slice(0,this.size());let n=Wu(this.elementShape,this.tensors,a);return e.length===0?Ue([],[0].concat(n)):Oe(()=>{let r=e.map(s=>Q(this.tensors[s],n));return la(r,0)})}concat(e,t){if(e&&e!==this.elementDtype)throw new Error(`TensorList dtype is ${this.elementDtype} but concat requested dtype ${e}`);Sn(this.elementShape,t,"TensorList shape mismatch: ");let a=Wu(this.elementShape,this.tensors,t);return this.size()===0?Ue([],[0].concat(a)):Oe(()=>{let n=this.tensors.map(r=>Q(r,a));return st(n,0)})}};function qP(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);Sn(r,t,"TensorList shape mismatch: ");let s=Ca(e);return new hl(s,t,n)}function XP(e,t,a,n){return new hl([],e,t,n)}function KP(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 hl([],a,e.dtype,n),i=Ca(e,0);return t.forEach((o,l)=>{s.setItem(o,i[l])}),s}function ZP(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=h2(s,a),o=n===0?0:e.size/n,l=Oe(()=>{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 hl([],a,e.dtype,t.length);for(let p=0;p<l.length;p++)u.setItem(p,l[p]);return u}var YP=async(e,t,a)=>{switch(e.op){case"If":case"StatelessIf":{let n=w("thenBranch",e,t,a),r=w("elseBranch",e,t,a),s=w("cond",e,t,a),i=w("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=w("body",e,t,a),r=w("cond",e,t,a),s=w("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=w("pred",e,t,a);return[yr(n)]}case"Switch":{let n=w("pred",e,t,a),r=w("data",e,t,a);return r.kept||(r=yr(r)),(await n.data())[0]?[void 0,r]:[r,void 0]}case"Merge":{let n=e.inputNames.find(r=>va(r,t,a)!==void 0);if(n){let r=va(n,t,a);return[yr(r)]}return}case"Enter":{let n=w("frameName",e,t,a),r=w("tensor",e,t,a);return a.enterFrame(n),[yr(r)]}case"Exit":{let n=w("tensor",e,t,a);return a.exitFrame(),[yr(n)]}case"NextIteration":{let n=w("tensor",e,t,a);return a.nextIteration(),[yr(n)]}case"TensorArrayV3":{let n=w("size",e,t,a),r=w("dtype",e,t,a),s=w("elementShape",e,t,a),i=w("dynamicSize",e,t,a),o=w("clearAfterRead",e,t,a),l=w("identicalElementShapes",e,t,a),u=w("name",e,t,a),p=new jP(u,r,n,s,l,i,o);return a.addTensorArray(p),[p.idTensor,ze(1)]}case"TensorArrayWriteV3":{let n=w("tensorArrayId",e,t,a),r=w("index",e,t,a),s=w("tensor",e,t,a),i=a.getTensorArray(n.id);return i.write(r,s),[i.idTensor]}case"TensorArrayReadV3":{let n=w("tensorArrayId",e,t,a),r=w("index",e,t,a);return[a.getTensorArray(n.id).read(r)]}case"TensorArrayGatherV3":{let n=w("tensorArrayId",e,t,a),r=w("indices",e,t,a),s=w("dtype",e,t,a);return[a.getTensorArray(n.id).gather(r,s)]}case"TensorArrayScatterV3":{let n=w("tensorArrayId",e,t,a),r=w("indices",e,t,a),s=w("tensor",e,t,a),i=a.getTensorArray(n.id);return i.scatter(r,s),[i.idTensor]}case"TensorArrayConcatV3":{let n=w("tensorArrayId",e,t,a),r=a.getTensorArray(n.id),s=w("dtype",e,t,a);return[r.concat(s)]}case"TensorArraySplitV3":{let n=w("tensorArrayId",e,t,a),r=w("tensor",e,t,a),s=w("lengths",e,t,a),i=a.getTensorArray(n.id);return i.split(s,r),[i.idTensor]}case"TensorArraySizeV3":{let n=w("tensorArrayId",e,t,a),r=a.getTensorArray(n.id);return[ze(r.size(),"int32")]}case"TensorArrayCloseV3":{let n=w("tensorArrayId",e,t,a),r=a.getTensorArray(n.id);return r.clearAndClose(),[r.idTensor]}case"TensorListSetItem":{let n=w("tensorListId",e,t,a),r=w("index",e,t,a),s=w("tensor",e,t,a),i=a.getTensorList(n.id);return i.setItem(r,s),[i.idTensor]}case"TensorListGetItem":{let n=w("tensorListId",e,t,a),r=w("index",e,t,a),s=w("elementShape",e,t,a),i=w("elementDType",e,t,a);return[a.getTensorList(n.id).getItem(r,s,i)]}case"TensorListScatterV2":case"TensorListScatter":{let n=w("indices",e,t,a),r=w("tensor",e,t,a),s=w("elementShape",e,t,a),i=w("numElements",e,t,a),o=KP(r,n,s,i);return a.addTensorList(o),[o.idTensor]}case"TensorListReserve":case"EmptyTensorList":{let n=w("elementShape",e,t,a),r=w("elementDType",e,t,a),s;e.op==="TensorListReserve"?s="numElements":s="maxNumElements";let i=w(s,e,t,a),o=e.op==="TensorListReserve"?-1:i,l=XP(n,r,i,o);return a.addTensorList(l),[l.idTensor]}case"TensorListGather":{let n=w("tensorListId",e,t,a),r=w("indices",e,t,a),s=w("elementShape",e,t,a),i=w("elementDType",e,t,a);return[a.getTensorList(n.id).gather(r,i,s)]}case"TensorListStack":{let n=w("tensorListId",e,t,a),r=w("elementShape",e,t,a),s=w("elementDType",e,t,a),i=w("numElements",e,t,a);return[a.getTensorList(n.id).stack(r,s,i)]}case"TensorListFromTensor":{let n=w("tensor",e,t,a),r=w("elementShape",e,t,a),s=w("elementDType",e,t,a),i=qP(n,r,s);return a.addTensorList(i),[i.idTensor]}case"TensorListConcat":case"TensorListConcatV2":{let n=w("tensorListId",e,t,a),r=a.getTensorList(n.id),s=w("dtype",e,t,a),i=w("elementShape",e,t,a);return[r.concat(s,i)]}case"TensorListPushBack":{let n=w("tensorListId",e,t,a),r=w("tensor",e,t,a),s=a.getTensorList(n.id);return s.pushBack(r),[s.idTensor]}case"TensorListPopBack":{let n=w("tensorListId",e,t,a),r=w("elementShape",e,t,a),s=w("elementDType",e,t,a);return[a.getTensorList(n.id).popBack(r,s)]}case"TensorListSplit":{let n=w("tensor",e,t,a),r=w("elementShape",e,t,a),s=w("lengths",e,t,a),i=ZP(n,s,r);return a.addTensorList(i),[i.idTensor]}case"TensorListLength":{let n=w("tensorListId",e,t,a),r=a.getTensorList(n.id);return[ze(r.size(),"int32")]}case"TensorListResize":{let n=w("tensorListId",e,t,a),r=w("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 Q5(e,t,a){let[n,r]=w("fusedOps",e,t,a),s=n==="biasadd",i=!s,o=r==="prelu",l=n==="fusedbatchnorm",u=w("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=w("strides",e,t,a),c=xc(e,t,a),d=w("dataFormat",e,t,a).toUpperCase(),h=w("dilations",e,t,a),[f,m]=w("args",e,t,a);i&&(m=f,f=void 0);let g=w("leakyreluAlpha",e,t,a);return{stride:p,pad:c,dataFormat:d,dilations:h,biasArg:f,preluArg:m,activationFunc:r,leakyreluAlpha:g}}var JP=(e,t,a,n=Zt)=>{switch(e.op){case"Conv1D":{let r=w("stride",e,t,a),s=w("pad",e,t,a),i=w("dataFormat",e,t,a).toUpperCase(),o=w("dilation",e,t,a);return[n.conv1d(w("x",e,t,a),w("filter",e,t,a),r,s,i,o)]}case"Conv2D":{let r=w("strides",e,t,a),s=xc(e,t,a),i=w("dataFormat",e,t,a).toUpperCase(),o=w("dilations",e,t,a);return[n.conv2d(w("x",e,t,a),w("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}=Q5(e,t,a);return[n.fused.conv2d({x:w("x",e,t,a),filter:w("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}=Q5(e,t,a);return[n.fused.depthwiseConv2d({x:w("x",e,t,a),filter:w("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=w("outputShape",e,t,a),s=w("strides",e,t,a),i=xc(e,t,a);return[n.conv2dTranspose(w("x",e,t,a),w("filter",e,t,a),r,[s[1],s[2]],i)]}case"DepthwiseConv2dNative":case"DepthwiseConv2d":{let r=w("strides",e,t,a),s=xc(e,t,a),i=w("dilations",e,t,a),o=w("dataFormat",e,t,a).toUpperCase();return[n.depthwiseConv2d(w("input",e,t,a),w("filter",e,t,a),[r[1],r[2]],s,o,[i[1],i[2]])]}case"Conv3D":{let r=w("strides",e,t,a),s=w("pad",e,t,a),i=w("dataFormat",e,t,a).toUpperCase(),o=w("dilations",e,t,a);return[n.conv3d(w("x",e,t,a),w("filter",e,t,a),[r[1],r[2],r[3]],s,i,[o[1],o[2],o[3]])]}case"AvgPool":{let r=w("strides",e,t,a),s=w("pad",e,t,a),i=w("kernelSize",e,t,a);return[n.avgPool(w("x",e,t,a),[i[1],i[2]],[r[1],r[2]],s)]}case"MaxPool":{let r=w("strides",e,t,a),s=w("pad",e,t,a),i=w("kernelSize",e,t,a);return[n.maxPool(w("x",e,t,a),[i[1],i[2]],[r[1],r[2]],s)]}case"MaxPoolWithArgmax":{let r=w("strides",e,t,a),s=w("pad",e,t,a),i=w("kernelSize",e,t,a),o=w("includeBatchInIndex",e,t,a),{result:l,indexes:u}=n.maxPoolWithArgmax(w("x",e,t,a),[i[1],i[2]],[r[1],r[2]],s,o);return[l,u]}case"AvgPool3D":{let r=w("strides",e,t,a),s=w("pad",e,t,a),i=w("kernelSize",e,t,a);return[n.avgPool3d(w("x",e,t,a),[i[1],i[2],i[3]],[r[1],r[2],r[3]],s)]}case"MaxPool3D":{let r=w("strides",e,t,a),s=w("pad",e,t,a),i=w("kernelSize",e,t,a);return[n.maxPool3d(w("x",e,t,a),[i[1],i[2],i[3]],[r[1],r[2],r[3]],s)]}case"Dilation2D":{let r=w("strides",e,t,a),s=w("pad",e,t,a),i=w("dilations",e,t,a),o=r[1],l=r[2],u=i[1],p=i[2];return[n.dilation2d(w("x",e,t,a),w("filter",e,t,a),[o,l],s,[u,p],"NHWC")]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},QP=(e,t,a,n=Zt)=>{switch(e.op){case"Fill":{let r=w("shape",e,t,a),s=w("dtype",e,t,a),i=w("value",e,t,a);return[n.fill(r,i,s)]}case"LinSpace":{let r=w("start",e,t,a),s=w("stop",e,t,a),i=w("num",e,t,a);return[n.linspace(r,s,i)]}case"Multinomial":{let r=w("logits",e,t,a),s=w("numSamples",e,t,a),i=w("seed",e,t,a);return[n.multinomial(r,s,i)]}case"OneHot":{let r=w("indices",e,t,a),s=w("depth",e,t,a),i=w("onValue",e,t,a),o=w("offValue",e,t,a),l=w("dtype",e,t,a);return[n.oneHot(r,s,i,o,l)]}case"Ones":return[n.ones(w("shape",e,t,a),w("dtype",e,t,a))];case"OnesLike":return[n.onesLike(w("x",e,t,a))];case"RandomStandardNormal":return[n.randomStandardNormal(w("shape",e,t,a),w("dtype",e,t,a),w("seed",e,t,a))];case"RandomUniform":return[n.randomUniform(w("shape",e,t,a),w("minval",e,t,a),w("maxval",e,t,a),w("dtype",e,t,a))];case"Range":{let r=w("start",e,t,a),s=w("stop",e,t,a),i=w("step",e,t,a);return[n.range(r,s,i,w("dtype",e,t,a))]}case"TruncatedNormal":{let r=w("shape",e,t,a),s=w("mean",e,t,a),i=w("stdDev",e,t,a),o=w("seed",e,t,a);return[n.truncatedNormal(r,s,i,w("dtype",e,t,a),o)]}case"Zeros":return[n.zeros(w("shape",e,t,a),w("dtype",e,t,a))];case"ZerosLike":return[n.zerosLike(w("x",e,t,a))];default:throw TypeError(`Node type ${e.op} is not implemented`)}};function Pm(e,t,a){let n=w("boxes",e,t,a),r=w("scores",e,t,a),s=w("maxOutputSize",e,t,a),i=w("iouThreshold",e,t,a),o=w("scoreThreshold",e,t,a),l=w("softNmsSigma",e,t,a);return{boxes:n,scores:r,maxOutputSize:s,iouThreshold:i,scoreThreshold:o,softNmsSigma:l}}var eF=async(e,t,a,n,r=Zt)=>{switch(e.op){case"NonMaxSuppressionV5":{let{boxes:s,scores:i,maxOutputSize:o,iouThreshold:l,scoreThreshold:u,softNmsSigma:p}=Pm(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}=Pm(e,t,a),p=w("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}=Pm(e,t,a);return[await r.image.nonMaxSuppressionAsync(s,i,o,l,u)]}case"Where":{let s=r.cast(w("condition",e,t,a),"bool"),i=[await r.whereAsync(s)];return s.dispose(),i}case"ListDiff":return r.setdiff1dAsync(w("x",e,t,a),w("y",e,t,a));default:throw TypeError(`Node type ${e.op} is not implemented`)}},tF=(e,t,a,n=Zt)=>{switch(e.op){case"LowerBound":{let r=w("sortedSequence",e,t,a),s=w("values",e,t,a);return[n.lowerBound(r,s)]}case"TopKV2":{let r=w("x",e,t,a),s=w("k",e,t,a),i=w("sorted",e,t,a),o=n.topk(r,s,i);return[o.values,o.indices]}case"UpperBound":{let r=w("sortedSequence",e,t,a),s=w("values",e,t,a);return[n.upperBound(r,s)]}case"Unique":{let r=w("x",e,t,a),s=n.unique(r);return[s.values,s.indices]}case"UniqueV2":{let r=w("x",e,t,a),s=w("axis",e,t,a),i=n.unique(r,s);return[i.values,i.indices]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},aF=(e,t,a,n=Zt)=>{switch(e.op){case"Const":return t[e.name];case"PlaceholderWithDefault":let r=w("default",e,t,a);return[va(e.name,t,a)||r];case"Placeholder":return[va(e.name,t,a)];case"Identity":case"StopGradient":case"FakeQuantWithMinMaxVars":{let p=w("x",e,t,a);return[yr(p)]}case"IdentityN":return w("x",e,t,a).map(p=>yr(p));case"Snapshot":let s=w("x",e,t,a);return[yr(s)];case"Shape":return[n.tensor1d(w("x",e,t,a).shape,"int32")];case"ShapeN":return w("x",e,t,a).map(p=>n.tensor1d(p.shape));case"Size":return[n.scalar(w("x",e,t,a).size,"int32")];case"Rank":return[n.scalar(w("x",e,t,a).rank,"int32")];case"NoOp":return[n.scalar(1)];case"Print":let i=w("x",e,t,a),o=w("data",e,t,a),l=w("message",e,t,a),u=w("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`)}},nF=class{constructor(e,t){this.keyDType=e,this.valueDType=t,this.handle=ze(0),this.tensorMap=new Map,On(this.handle)}get id(){return this.handle.id}clearAndClose(){this.tensorMap.forEach(e=>e.dispose()),this.tensorMap.clear(),this.handle.dispose()}size(){return this.tensorMap.size}tensorSize(){return ze(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(),Oe(()=>{let n=Ca(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];On(l),this.tensorMap.set(o,l)}return this.handle})}async find(e,t){this.checkKeyAndValueTensor(e,t);let a=await e.data();return Oe(()=>{let n=[];for(let r=0;r<a.length;r++){let s=a[r],i=this.findWithDefault(s,t);n.push(i)}return la(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}`)}},rF=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=w("keyDType",e,t,a),i=w("valueDType",e,t,a),o=new nF(s,i);return n.addHashTable(e.name,o),[o.handle]}}case"InitializeTable":case"InitializeTableV2":case"LookupTableImport":case"LookupTableImportV2":{let r=w("tableHandle",e,t,a,n),s=w("keys",e,t,a),i=w("values",e,t,a);return[await n.getHashTableById(r.id).import(s,i)]}case"LookupTableFind":case"LookupTableFindV2":{let r=w("tableHandle",e,t,a,n),s=w("keys",e,t,a),i=w("defaultValue",e,t,a);return[await n.getHashTableById(r.id).find(s,i)]}case"LookupTableSize":case"LookupTableSizeV2":{let r=w("tableHandle",e,t,a,n);return[n.getHashTableById(r.id).tensorSize()]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},sF=(e,t,a,n=Zt)=>{switch(e.op){case"ResizeBilinear":{let r=w("images",e,t,a),s=w("size",e,t,a),i=w("alignCorners",e,t,a),o=w("halfPixelCenters",e,t,a);return[n.image.resizeBilinear(r,[s[0],s[1]],i,o)]}case"ResizeNearestNeighbor":{let r=w("images",e,t,a),s=w("size",e,t,a),i=w("alignCorners",e,t,a),o=w("halfPixelCenters",e,t,a);return[n.image.resizeNearestNeighbor(r,[s[0],s[1]],i,o)]}case"CropAndResize":{let r=w("image",e,t,a),s=w("boxes",e,t,a),i=w("boxInd",e,t,a),o=w("cropSize",e,t,a),l=w("method",e,t,a),u=w("extrapolationValue",e,t,a);return[n.image.cropAndResize(r,s,i,o,l,u)]}case"ImageProjectiveTransformV3":{let r=w("images",e,t,a),s=w("transforms",e,t,a),i=w("outputShape",e,t,a),o=w("fillValue",e,t,a),l=w("interpolation",e,t,a),u=w("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`)}},iF=(e,t,a,n=Zt)=>{switch(e.op){case"Equal":return[n.equal(w("a",e,t,a),w("b",e,t,a))];case"NotEqual":return[n.notEqual(w("a",e,t,a),w("b",e,t,a))];case"Greater":return[n.greater(w("a",e,t,a),w("b",e,t,a))];case"GreaterEqual":return[n.greaterEqual(w("a",e,t,a),w("b",e,t,a))];case"Less":return[n.less(w("a",e,t,a),w("b",e,t,a))];case"LessEqual":return[n.lessEqual(w("a",e,t,a),w("b",e,t,a))];case"LogicalAnd":return[n.logicalAnd(w("a",e,t,a),w("b",e,t,a))];case"LogicalNot":return[n.logicalNot(w("a",e,t,a))];case"LogicalOr":return[n.logicalOr(w("a",e,t,a),w("b",e,t,a))];case"Select":case"SelectV2":return[n.where(w("condition",e,t,a),w("a",e,t,a),w("b",e,t,a))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},oF=(e,t,a,n=Zt)=>{switch(e.op){case"BatchMatMul":case"BatchMatMulV2":case"MatMul":return[n.matMul(w("a",e,t,a),w("b",e,t,a),w("transposeA",e,t,a),w("transposeB",e,t,a))];case"Einsum":return[n.einsum(w("equation",e,t,a),...w("tensors",e,t,a))];case"Transpose":return[n.transpose(w("x",e,t,a),w("perm",e,t,a))];case"_FusedMatMul":let[r,s]=w("fusedOps",e,t,a),i=r==="biasadd",o=s==="prelu",l=w("numArgs",e,t,a),u=w("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]=w("args",e,t,a);return[n.fused.matMul({a:w("a",e,t,a),b:w("b",e,t,a),transposeA:w("transposeA",e,t,a),transposeB:w("transposeB",e,t,a),bias:p,activation:s,preluActivationWeights:c,leakyreluAlpha:u})];default:throw TypeError(`Node type ${e.op} is not implemented`)}},lF=(e,t,a,n=Zt)=>{switch(e.op){case"EuclideanNorm":return[n.euclideanNorm(w("x",e,t,a),w("axis",e,t,a),w("keepDims",e,t,a))];case"FusedBatchNorm":case"FusedBatchNormV2":return[n.batchNorm(w("x",e,t,a),w("mean",e,t,a),w("variance",e,t,a),w("offset",e,t,a),w("scale",e,t,a),w("epsilon",e,t,a))];case"FusedBatchNormV3":return[n.batchNorm(w("x",e,t,a),w("mean",e,t,a),w("variance",e,t,a),w("offset",e,t,a),w("scale",e,t,a),w("epsilon",e,t,a))];case"LRN":return[n.localResponseNormalization(w("x",e,t,a),w("radius",e,t,a),w("bias",e,t,a),w("alpha",e,t,a),w("beta",e,t,a))];case"Softmax":return[n.softmax(w("x",e,t,a))];case"LogSoftmax":return[n.logSoftmax(w("x",e,t,a))];case"SparseToDense":return[n.sparseToDense(w("sparseIndices",e,t,a),w("outputShape",e,t,a),w("sparseValues",e,t,a),w("defaultValue",e,t,a))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},uF=(e,t,a,n=Zt)=>{switch(e.op){case"RaggedGather":{let{outputNestedSplits:r,outputDenseValues:s}=n.raggedGather(w("paramsNestedSplits",e,t,a),w("paramsDenseValues",e,t,a),w("indices",e,t,a),w("outputRaggedRank",e,t,a));return r.concat(s)}case"RaggedRange":{let{rtNestedSplits:r,rtDenseValues:s}=n.raggedRange(w("starts",e,t,a),w("limits",e,t,a),w("splits",e,t,a));return[r,s]}case"RaggedTensorToTensor":return[n.raggedTensorToTensor(w("shape",e,t,a),w("values",e,t,a),w("defaultValue",e,t,a),w("rowPartitionTensors",e,t,a),w("rowPartitionTypes",e,t,a))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},dF=(e,t,a,n=Zt)=>{switch(e.op){case"Max":{let o=w("axis",e,t,a),l=w("keepDims",e,t,a);return[n.max(w("x",e,t,a),o,l)]}case"Mean":{let o=w("axis",e,t,a),l=w("keepDims",e,t,a);return[n.mean(w("x",e,t,a),o,l)]}case"Min":{let o=w("axis",e,t,a),l=w("keepDims",e,t,a);return[n.min(w("x",e,t,a),o,l)]}case"Sum":{let o=w("axis",e,t,a),l=w("keepDims",e,t,a);return[n.sum(w("x",e,t,a),o,l)]}case"All":{let o=w("axis",e,t,a),l=w("keepDims",e,t,a);return[n.all(w("x",e,t,a),o,l)]}case"Any":{let o=w("axis",e,t,a),l=w("keepDims",e,t,a);return[n.any(w("x",e,t,a),o,l)]}case"ArgMax":{let o=w("axis",e,t,a);return[n.argMax(w("x",e,t,a),o)]}case"ArgMin":{let o=w("axis",e,t,a);return[n.argMin(w("x",e,t,a),o)]}case"Prod":{let o=w("axis",e,t,a),l=w("keepDims",e,t,a);return[n.prod(w("x",e,t,a),o,l)]}case"Cumprod":{let o=w("axis",e,t,a),l=w("exclusive",e,t,a),u=w("reverse",e,t,a);return[n.cumprod(w("x",e,t,a),o,l,u)]}case"Cumsum":{let o=w("axis",e,t,a),l=w("exclusive",e,t,a),u=w("reverse",e,t,a);return[n.cumsum(w("x",e,t,a),o,l,u)]}case"Bincount":let r=w("x",e,t,a),s=w("weights",e,t,a),i=w("size",e,t,a);return[n.bincount(r,s,i)];case"DenseBincount":{let o=w("x",e,t,a),l=w("weights",e,t,a),u=w("size",e,t,a),p=w("binaryOutput",e,t,a);return[n.denseBincount(o,l,u,p)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},pF=(e,t,a,n=Zt)=>{switch(e.op){case"ConcatV2":case"Concat":{let r=w("n",e,t,a),s=w("axis",e,t,a),i=w("tensors",e,t,a);return i=i.slice(0,r),[n.concat(i,s)]}case"Gather":{let r=w("x",e,t,a),s=w("indices",e,t,a);return[n.gather(r,n.cast(s,"int32"),0)]}case"GatherV2":{let r=w("axis",e,t,a),s=w("batchDims",e,t,a),i=w("x",e,t,a),o=w("indices",e,t,a);return[n.gather(i,n.cast(o,"int32"),r,s)]}case"Reverse":{let r=w("dims",e,t,a),s=[];for(let o=0;o<r.length;o++)r[o]&&s.push(o);let i=w("x",e,t,a);return[n.reverse(i,s)]}case"ReverseV2":{let r=w("axis",e,t,a),s=w("x",e,t,a);return[n.reverse(s,r)]}case"Slice":{let r=w("begin",e,t,a),s=w("size",e,t,a);return[n.slice(w("x",e,t,a),r,s)]}case"StridedSlice":{let r=w("begin",e,t,a),s=w("end",e,t,a),i=w("strides",e,t,a),o=w("beginMask",e,t,a),l=w("endMask",e,t,a),u=w("ellipsisMask",e,t,a),p=w("newAxisMask",e,t,a),c=w("shrinkAxisMask",e,t,a),d=w("x",e,t,a);return[n.stridedSlice(d,r,s,i,o,l,u,p,c)]}case"Pack":return Oe(()=>{let r=w("axis",e,t,a),s=w("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=w("axis",e,t,a),s=w("tensor",e,t,a);return n.unstack(s,r)}case"Tile":{let r=w("reps",e,t,a);return[n.tile(w("x",e,t,a),r)]}case"Split":case"SplitV":{let r=w("axis",e,t,a),s=w("numOrSizeSplits",e,t,a),i=w("x",e,t,a);return n.split(i,s,r)}case"ScatterNd":{let r=w("indices",e,t,a),s=w("values",e,t,a),i=w("shape",e,t,a);return[n.scatterND(r,s,i)]}case"GatherNd":{let r=w("x",e,t,a),s=w("indices",e,t,a);return[n.gatherND(r,s)]}case"SparseToDense":{let r=w("sparseIndices",e,t,a),s=w("outputShape",e,t,a),i=w("sparseValues",e,t,a),o=w("defaultValue",e,t,a);return[n.sparseToDense(r,i,s,i.dtype===o.dtype?o:n.cast(o,i.dtype))]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},cF=(e,t,a,n=Zt)=>{switch(e.op){case"SparseFillEmptyRows":{let{outputIndices:r,outputValues:s,emptyRowIndicator:i,reverseIndexMap:o}=n.sparse.sparseFillEmptyRows(w("indices",e,t,a),w("values",e,t,a),w("denseShape",e,t,a),w("defaultValue",e,t,a));return[r,s,i,o]}case"SparseReshape":{let{outputIndices:r,outputShape:s}=n.sparse.sparseReshape(w("inputIndices",e,t,a),w("inputShape",e,t,a),w("newShape",e,t,a));return[r,s]}case"SparseSegmentMean":return[n.sparse.sparseSegmentMean(w("data",e,t,a),w("indices",e,t,a),w("segmentIds",e,t,a))];case"SparseSegmentSum":return[n.sparse.sparseSegmentSum(w("data",e,t,a),w("indices",e,t,a),w("segmentIds",e,t,a))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},hF=(e,t,a,n=Zt)=>{switch(e.op){case"FFT":return[n.fft(w("x",e,t,a))];case"IFFT":return[n.ifft(w("x",e,t,a))];case"RFFT":return[n.rfft(w("x",e,t,a))];case"IRFFT":return[n.irfft(w("x",e,t,a))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},fF=(e,t,a,n=Zt)=>{switch(e.op){case"StringNGrams":{let{nGrams:r,nGramsSplits:s}=n.string.stringNGrams(w("data",e,t,a),w("dataSplits",e,t,a),w("separator",e,t,a),w("nGramWidths",e,t,a),w("leftPad",e,t,a),w("rightPad",e,t,a),w("padWidth",e,t,a),w("preserveShortSequences",e,t,a));return[r,s]}case"StringSplit":{let{indices:r,values:s,shape:i}=n.string.stringSplit(w("input",e,t,a),w("delimiter",e,t,a),w("skipEmpty",e,t,a));return[r,s,i]}case"StringToHashBucketFast":return[n.string.stringToHashBucketFast(w("input",e,t,a),w("numBuckets",e,t,a))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},mF=(e,t,a,n=Zt)=>{switch(e.op){case"Cast":return[n.cast(w("x",e,t,a),w("dtype",e,t,a))];case"ExpandDims":{let r=w("axis",e,t,a);return[n.expandDims(w("x",e,t,a),r)]}case"Squeeze":{let r=w("axis",e,t,a);return[n.squeeze(w("x",e,t,a),r)]}case"Reshape":return[n.reshape(w("x",e,t,a),w("shape",e,t,a))];case"MirrorPad":return[n.mirrorPad(w("x",e,t,a),w("padding",e,t,a),w("mode",e,t,a))];case"PadV2":case"Pad":return[n.pad(w("x",e,t,a),w("padding",e,t,a),w("constantValue",e,t,a))];case"SpaceToBatchND":{let r=w("blockShape",e,t,a),s=w("paddings",e,t,a);return[n.spaceToBatchND(w("x",e,t,a),r,s)]}case"BatchToSpaceND":{let r=w("blockShape",e,t,a),s=w("crops",e,t,a);return[n.batchToSpaceND(w("x",e,t,a),r,s)]}case"DepthToSpace":{let r=w("blockSize",e,t,a),s=w("dataFormat",e,t,a).toUpperCase();return[n.depthToSpace(w("x",e,t,a),r,s)]}case"BroadcastTo":return[n.broadcastTo(w("x",e,t,a),w("shape",e,t,a))];case"BroadcastArgs":return[n.broadcastArgs(w("s0",e,t,a),w("s1",e,t,a))];default:throw TypeError(`Node type ${e.op} is not implemented`)}};function ey(e,t,a,n,r=Oe){let s=((i,o,l)=>{switch(i.category){case"arithmetic":return r(()=>GP(i,o,l));case"basic_math":return r(()=>HP(i,o,l));case"control":return YP(i,o,l);case"convolution":return r(()=>JP(i,o,l));case"creation":return r(()=>QP(i,o,l));case"dynamic":return eF(i,o,l);case"evaluation":return r(()=>tF(i,o,l));case"image":return r(()=>sF(i,o,l));case"graph":return r(()=>aF(i,o,l));case"logical":return r(()=>iF(i,o,l));case"matrices":return r(()=>oF(i,o,l));case"normalization":return r(()=>lF(i,o,l));case"ragged":return r(()=>uF(i,o,l));case"reduction":return r(()=>dF(i,o,l));case"slice_join":return r(()=>pF(i,o,l));case"sparse":return r(()=>cF(i,o,l));case"spectral":return r(()=>hF(i,o,l));case"string":return r(()=>fF(i,o,l));case"transformation":return r(()=>mF(i,o,l));case"hash_table":return rF(i,o,l,n);case"custom":let u=v4(i.op);if(u&&u.customExecutor)return u.customExecutor(new UP(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 ty=class{constructor(e={},t={},a={},n={}){this.weightMap=e,this.tensorArrayMap=t,this.tensorListMap=a,this.functionMap=n,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 ay(e,t,a,n){let r=new Set,s=[],i=null,o=null,l=new Set,u=Object.keys(e).map(d=>Xa(d)[0]),p=[];n!=null&&(p=n.map(d=>Xa(d.name)[0]));let c=[...t];for(;c.length>0;){let d=c.pop();if((U4(d)||bF(d)||vF(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.indexOf(d.name)===-1&&p.indexOf(d.name)===-1){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 gF(e,t,a){let{usedNodes:n,inputs:r}=a,s=[],i=Object.keys(r).map(p=>Xa(p)[0]).map(p=>e.nodes[p]),o=e.initNodes;i.forEach(p=>{n.has(p.name)&&s.push(p)}),e.weights.forEach(p=>{n.has(p.name)&&s.push(p)}),o!=null&&o.forEach(p=>{n.has(p.name)&&s.push(p)});let l=new Set,u=[];for(;s.length>0;){let p=s.pop();l.add(p.name),t[p.name]||u.push(p),p.children.forEach(c=>{!l.has(c.name)&&n.has(c.name)&&c.inputs.every(d=>l.has(d.name))&&s.push(c)})}return u}var yF=["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"],xF=["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"],AF=["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2","LookupTableSize","LookupTableSizeV2"];function U4(e){return yF.indexOf(e.op)>=0}function bF(e){return xF.indexOf(e.op)>=0}function vF(e){return AF.indexOf(e.op)>=0}var f2=class{constructor(e,t){this.graph=e,this.parent=t,this.compiledMap=new Map,this._weightMap={},this.SEPERATOR=",",this._functions={},this._functionExecutorMap={},this.keepIntermediateTensors=!1,this._outputs=e.outputs,this._inputs=e.inputs,this._initNodes=e.initNodes,this._signature=e.signature,this._functions=e.functions,e.functions!=null&&Object.keys(e.functions).forEach(a=>{this._functionExecutorMap[a]=new f2(e.functions[a],this)})}get weightIds(){return this.parent?this.parent.weightIds:this._weightIds}get functionExecutorMap(){return this.parent?this.parent.functionExecutorMap:this._functionExecutorMap}get weightMap(){return this.parent?this.parent.weightMap:this._weightMap}set weightMap(e){let t=Object.keys(e).map(a=>e[a].map(n=>n.id));this._weightIds=[].concat(...t),this._weightMap=e}set resourceManager(e){this._resourceManager=e}get inputs(){return this._inputs.map(e=>({name:e.name,shape:e.attrParams.shape?e.attrParams.shape.value:void 0,dtype:e.attrParams.dtype?e.attrParams.dtype.value:void 0}))}get outputs(){return this._outputs.map(e=>({name:e.name,shape:e.attrParams.shape?e.attrParams.shape.value:void 0,dtype:e.attrParams.dtype?e.attrParams.dtype.value:void 0}))}get inputNodes(){return this._inputs.map(e=>e.signatureKey||e.name)}get outputNodes(){return this._outputs.map(e=>{let t=e.signatureKey||e.name;return e.defaultOutput?`${t}:${e.defaultOutput}`:t})}get functions(){return Object.keys(this._functions).reduce((e,t)=>(e[t]=this._functions[t].signature,e),{})}getCompilationKey(e,t){let a=e.map(r=>r.name).sort(),n=t.map(r=>r.name).sort();return a.join(this.SEPERATOR)+"--"+n.join(this.SEPERATOR)}compile(e,t){let a=ay(e,t,this.weightMap,this._initNodes),{missingInputs:n,dynamicNode:r,syncInputs:s}=a;if(r!=null)throw new Error(`This execution contains the node '${r.name}', which has the dynamic op '${r.op}'. Please use model.executeAsync() instead. Alternatively, to avoid the dynamic ops, specify the inputs [${s}]`);if(n.length>0){let i=t.map(l=>l.name),o=Object.keys(e);throw new Error(`Cannot compute the outputs [${i}] from the provided inputs [${o}]. Missing the following inputs: [${n}]`)}return gF(this.graph,this.weightMap,a)}cloneAndKeepTensor(e){if(e==null)return null;let t=e.clone();return On(t),t}cloneTensorList(e){return e?e.map(t=>this.cloneAndKeepTensor(t)):null}cloneTensorMap(e){return Object.fromEntries(Object.entries(e).map(([t,a])=>[t,this.cloneTensorList(a)]))}execute(e,t){this.disposeIntermediateTensors(),e=this.mapInputs(e);let a=Object.keys(e).sort();this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t);let n=a.map(p=>this.graph.nodes[Xa(p)[0]]),r=t.map(p=>Xa(p)[0]),s=r.map(p=>this.graph.nodes[p]);s.length===0&&(s=this._outputs);let i=this.getCompilationKey(n,s),o=this.compiledMap.get(i);o==null&&(o=this.compile(e,s),this.compiledMap.set(i,o));try{this.keepIntermediateTensors=V().getBool("KEEP_INTERMEDIATE_TENSORS")}catch(p){this.keepIntermediateTensors=!1,console.warn(p.message)}let l={},u={};return Oe(()=>{let p=new ty(this.weightMap,l,u,this.functionExecutorMap),c=Object.assign({},this.weightMap);this.keepIntermediateTensors&&(this.clonedTensorsMap=this.cloneTensorMap(this.weightMap)),Object.keys(e).forEach(f=>{let[m,g]=Xa(f),y=[];y[g]=e[f],c[m]=y,this.keepIntermediateTensors&&(this.clonedTensorsMap[m]=this.cloneTensorList(y))});let d=this.getFrozenTensorIds(c),h={};for(let f=0;f<o.length;f++){let m=o[f];if(!c[m.name]){let g=ey(m,c,p,this._resourceManager);if(v.isPromise(g))throw new Error(`The execution of the op '${m.op}' returned a promise. Please use model.executeAsync() instead.`);c[m.name]=g,this.keepIntermediateTensors&&(this.clonedTensorsMap[m.name]=this.cloneTensorList(g)),this.checkTensorForDisposal(m.name,m,c,p,d,r,h)}}return this.parent==null&&p.dispose(d),t.map(f=>va(f,c,p))})}getFrozenTensorIds(e){let t=[].concat.apply([],Object.keys(e).map(a=>e[a]).map(a=>a.map(n=>n.id)));return new Set(t)}checkTensorForDisposal(e,t,a,n,r,s,i){t.category==="control"||s.indexOf(e)!==-1||(a[e].forEach(o=>{o!=null&&(i[o.id]=(i[o.id]||0)+t.children.length)}),t.inputs.forEach(o=>{if(o.category!=="control"){let l=kP(o.name,a,n);l!=null&&l.forEach(u=>{if(u&&!u.kept&&!r.has(u.id)){let p=i[u.id];p===1?(u.dispose(),delete i[u.id]):p!=null&&i[u.id]--}})}}))}async executeAsync(e,t){return this._executeAsync(e,t)}disposeIntermediateTensors(){this.clonedTensorsMap&&(Object.values(this.clonedTensorsMap).forEach(e=>{for(let t of e)t&&!t.isDisposed&&t.dispose()}),this.clonedTensorsMap=null)}getIntermediateTensors(){return this.clonedTensorsMap}async _executeAsync(e,t,a=!1,n={},r={}){this.disposeIntermediateTensors(),a||(e=this.mapInputs(e),this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t));try{this.keepIntermediateTensors=V().getBool("KEEP_INTERMEDIATE_TENSORS")}catch(c){this.keepIntermediateTensors=!1,console.warn(c.message)}let s=new ty(this.weightMap,n,r,this.functionExecutorMap);this.keepIntermediateTensors&&(this.clonedTensorsMap=this.cloneTensorMap(this.weightMap));let i=await this.executeWithControlFlow(e,s,t,a),o=t.map(c=>va(c,i,s)),l=o.map(c=>c.id),u=Object.keys(e).map(c=>e[c].id),p=new Set([...l,...u,...this.weightIds]);return Object.values(i).forEach(c=>{c.forEach(d=>{d&&!d.isDisposed&&!p.has(d.id)&&d.dispose()})}),this.parent==null&&s.dispose(p),o}async executeFunctionAsync(e,t,a){let n=e.reduce((r,s,i)=>(r[this.inputs[i].name]=s,r),{});return this._executeAsync(n,this.outputNodes,!0,t,a)}async executeWithControlFlow(e,t,a,n){let r=Object.keys(e),s=r.map(x=>this.graph.nodes[Xa(x)[0]]),i=a.map(x=>Xa(x)[0]),o=i.map(x=>this.graph.nodes[x]);o.length===0&&(o=this._outputs);let{usedNodes:l,missingInputs:u,dynamicNode:p,syncInputs:c}=ay(e,o,this.weightMap,this._initNodes),d=[...s,...this.graph.weights,...this._initNodes||[]].map(x=>({node:x,contexts:t.currentContext})),h=Object.assign({},this.weightMap);Object.keys(e).forEach(x=>{let[A,b]=Xa(x),k=[];k[b]=e[x],h[A]=k});let f={},m=this.getFrozenTensorIds(h),g={};for(;d.length>0;){let x=this.processStack(s,d,t,h,g,m,i,f,l);await Promise.all(x)}p==null&&!n&&console.warn("This model execution did not contain any nodes with control flow or dynamic output shapes. You can use model.execute() instead.");let y=o.filter(x=>!U4(x)&&!va(x.name,h,t)).map(x=>x.name);if(y.length>0){let x="";throw p!=null&&(x=`Alternatively, to avoid the dynamic ops, use model.execute() and specify the inputs [${c}]`),new Error(`Cannot compute the outputs [${y}] from the provided inputs [${r}]. Consider providing the following inputs: [${u}]. ${x}`)}return h}processStack(e,t,a,n,r,s,i,o,l){let u=[];for(;t.length>0;){let p=t.pop();a.currentContext=p.contexts;let c="";if(p.node.op==="Enter"&&w("isConstant",p.node,n,a)&&([c]=gr(p.node.name,a)),n[p.node.name]==null){let d=ey(p.node,n,a,this._resourceManager);c||([c]=gr(p.node.name,a));let h=a.currentContext;v.isPromise(d)?u.push(d.then(f=>(n[c]=f,this.keepIntermediateTensors&&(this.clonedTensorsMap[c]=this.cloneTensorList(f)),a.currentContext=h,this.checkTensorForDisposal(c,p.node,n,a,s,i,o),this.processChildNodes(p.node,t,a,n,r,l),f))):(n[c]=d,this.keepIntermediateTensors&&(this.clonedTensorsMap[c]=this.cloneTensorList(d)),this.checkTensorForDisposal(c,p.node,n,a,s,i,o),this.processChildNodes(p.node,t,a,n,r,l))}else this.processChildNodes(p.node,t,a,n,r,l)}return u}processChildNodes(e,t,a,n,r,s){e.children.forEach(i=>{let[o]=gr(i.name,a);r[o]||!s.has(i.name)||(i.op==="Merge"?i.inputNames.some(l=>!!va(l,n,a))&&(r[o]=!0,t.push({contexts:a.currentContext,node:i})):i.inputNames.every(l=>!!va(l,n,a))&&(r[o]=!0,t.push({contexts:a.currentContext,node:i})))})}dispose(){Object.keys(this.weightMap).forEach(e=>this.weightMap[e].forEach(t=>t.dispose()))}checkInputShapeAndType(e){Object.keys(e).forEach(t=>{let a=e[t],[n]=Xa(t),r=this.graph.nodes[n];if(r.attrParams.shape&&r.attrParams.shape.value){let s=r.attrParams.shape.value,i=s.length===a.shape.length&&a.shape.every((o,l)=>s[l]===-1||s[l]===o);v.assert(i,()=>`The shape of dict['${r.name}'] provided in model.execute(dict) must be [${s}], but was [${a.shape}]`)}r.attrParams.dtype&&r.attrParams.dtype.value&&v.assert(a.dtype===r.attrParams.dtype.value,()=>`The dtype of dict['${r.name}'] provided in model.execute(dict) must be ${r.attrParams.dtype.value}, but was ${a.dtype}`)})}mapInputs(e){var t,a;let n={};for(let r in e){let s=(a=(t=this._signature)===null||t===void 0?void 0:t.inputs)===null||a===void 0?void 0:a[r];s!=null?n[s.name]=e[r]:n[r]=e[r]}return n}checkInputs(e){let t=Object.keys(e).filter(a=>{let[n]=Xa(a);return this.graph.nodes[n]==null});if(t.length>0)throw new Error(`The dict provided in model.execute(dict) has keys: [${t}] that are not part of graph`)}mapOutputs(e){return e.map(t=>{var a,n;let r=(n=(a=this._signature)===null||a===void 0?void 0:a.outputs)===null||n===void 0?void 0:n[t];return r!=null?r.name:t},{})}checkOutputs(e){e.forEach(t=>{let[a]=Xa(t);if(!this.graph.nodes[a])throw new Error(`The output '${t}' is not found in the graph`)})}},kF=class{constructor(e={},t={}){this.hashTableNameToHandle=e,this.hashTableMap=t}addHashTable(e,t){this.hashTableNameToHandle[e]=t.handle,this.hashTableMap[t.id]=t}getHashTableHandleByName(e){return this.hashTableNameToHandle[e]}getHashTableById(e){return this.hashTableMap[e]}dispose(){for(let e in this.hashTableMap)this.hashTableMap[e].clearAndClose(),delete this.hashTableMap[e];for(let e in this.hashTableNameToHandle)this.hashTableNameToHandle[e].dispose(),delete this.hashTableNameToHandle[e]}},wF="?tfjs-format=file",IF="model.json",up=class{constructor(e,t={},a=jn){this.modelUrl=e,this.loadOptions=t,this.version="n/a",this.io=a,t==null&&(this.loadOptions={}),this.resourceManager=new kF}get modelVersion(){return this.version}get inputNodes(){return this.executor.inputNodes}get outputNodes(){return this.executor.outputNodes}get inputs(){return this.executor.inputs}get outputs(){return this.executor.outputs}get weights(){return this.executor.weightMap}get metadata(){return this.artifacts.userDefinedMetadata}get modelSignature(){return this.signature}get modelStructuredOutputKeys(){return this.structuredOutputKeys}findIOHandler(){let e=this.modelUrl;if(e.load!=null)this.handler=e;else if(this.loadOptions.requestInit!=null)this.handler=this.io.browserHTTPRequest(e,this.loadOptions);else{let t=this.io.getLoadHandlers(e,this.loadOptions);if(t.length===0)t.push(this.io.browserHTTPRequest(e,this.loadOptions));else if(t.length>1)throw new Error(`Found more than one (${t.length}) load handlers for URL '${[e]}'`);this.handler=t[0]}}load(){if(this.findIOHandler(),this.handler.load==null)throw new Error("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");let e=this.handler.load();return v.isPromise(e)?e.then(t=>this.loadSync(t)):this.loadSync(e)}loadSync(e){this.artifacts=e;let t=this.artifacts.modelTopology,a=this.artifacts.signature;if(this.artifacts.userDefinedMetadata!=null){let r=this.artifacts.userDefinedMetadata;r.signature!=null&&(a=r.signature),r.structuredOutputKeys!=null&&(this.structuredOutputKeys=r.structuredOutputKeys)}this.signature=a,this.version=`${t.versions.producer}.${t.versions.minConsumer}`;let n=this.io.decodeWeights(this.artifacts.weightData,this.artifacts.weightSpecs);if(this.executor=new f2(Z5.Instance.transformGraph(t,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(n),this.executor.resourceManager=this.resourceManager,e.modelInitializer!=null&&e.modelInitializer.node!=null){let r=Z5.Instance.transformGraph(e.modelInitializer);this.initializer=new f2(r),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializerSignature=e.initializerSignature}return!0}async save(e,t){if(typeof e=="string"){let a=this.io.getSaveHandlers(e);if(a.length===0)throw new Error(`Cannot find any save handlers for URL '${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 pt?[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 pt)&&!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 s3(e,t={},a=jn){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=TF(e));let n=new up(e,t,a);return await n.load(),n}function SF(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=jn.getWeightSpecs(n.weightsManifest),i=jn.getModelArtifactsForJSONSync(n,s,r);t=jn.fromMemorySync(i)}else if("load"in e)t=e;else if("modelTopology"in e&&"weightSpecs"in e&&"weightData"in e)t=jn.fromMemorySync(e);else throw new Error("Unknown model format");let a=new up(t);return a.load(),a}function TF(e){return e.endsWith("/")||(e=e+"/"),`${e}${IF}${wF}`}var CF="4.2.0";function Ae(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 NF=Nn.whereImpl,Th=class extends Al{constructor(){super(),this.blockSize=48,this.firstUse=!0,this.data=new kd(this,vt())}nextDataId(){return Th.nextDataId++}write(e,t,a){this.firstUse&&(this.firstUse=!1,V().get("IS_NODE")&&T.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 n={id:this.nextDataId()};return this.data.set(n,{values:e,dtype:a,refCount:1}),n}makeTensorInfo(e,t,a){let n;if(t==="string"&&a!=null&&a.length>0&&v.isString(a[0])){let r=a.map(s=>v.encodeString(s));n=this.write(r,e,t)}else n=this.write(a,e,t);return{dataId:n,shape:e,dtype:t}}refCount(e){return this.data.has(e)?this.data.get(e).refCount:0}incRef(e){let t=this.data.get(e);t.refCount++}decRef(e){if(this.data.has(e)){let t=this.data.get(e);t.refCount--}}move(e,t,a,n,r){this.data.set(e,{values:t,dtype:n,refCount:r})}numDataIds(){return this.data.numDataIds()}async read(e){return this.readSync(e)}readSync(e){let{dtype:t,complexTensorInfos:a}=this.data.get(e);if(t==="complex64"){let n=this.readSync(a.real.dataId),r=this.readSync(a.imag.dataId);return T.mergeRealAndImagArrays(n,r)}return v.convertBackendValuesAndArrayBuffer(this.data.get(e).values,t)}bufferSync(e){let t=this.readSync(e.dataId);if(e.dtype==="string")try{let a=t.map(n=>v.decodeString(n));return _e(e.shape,e.dtype,a)}catch(a){throw new Error("Failed to decode encoded string bytes into utf-8")}return _e(e.shape,e.dtype,t)}makeOutput(e,t,a){return vt().makeTensorFromTensorInfo(this.makeTensorInfo(t,a,e),this)}disposeData(e,t=!1){if(this.data.has(e)){if(this.data.get(e).refCount--,!t&&this.data.get(e).refCount>0)return!1;let{complexTensorInfos:a}=this.data.get(e);a!=null&&(this.disposeData(a.real.dataId,!0),this.disposeData(a.imag.dataId,!0)),this.data.delete(e)}return!0}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}async time(e){let t=v.now();return e(),{kernelMs:v.now()-t}}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(e){Ae([e],"where");let t=this.readSync(e.dataId);return NF(e.shape,t)}dispose(){}floatPrecision(){return 32}epsilon(){return super.epsilon()}};Th.nextDataId=0;var Ch={};Ze(Ch,{addImpl:()=>j4,bincountImpl:()=>o3,bincountReduceImpl:()=>q4,castImpl:()=>H4,ceilImpl:()=>X4,concatImpl:()=>l3,equalImpl:()=>K4,expImpl:()=>Y4,expm1Impl:()=>Q4,floorImpl:()=>e7,gatherNdImpl:()=>t7,gatherV2Impl:()=>a7,greaterEqualImpl:()=>r7,greaterImpl:()=>n7,lessEqualImpl:()=>i7,lessImpl:()=>s7,linSpaceImpl:()=>o7,logImpl:()=>l7,maxImpl:()=>u7,maximumImpl:()=>d7,minimumImpl:()=>p7,multiplyImpl:()=>u3,negImpl:()=>c7,notEqualImpl:()=>h7,prodImpl:()=>f7,raggedGatherImpl:()=>m7,raggedRangeImpl:()=>g7,raggedTensorToTensorImpl:()=>y7,rangeImpl:()=>p3,rsqrtImpl:()=>x7,scatterImpl:()=>el,sigmoidImpl:()=>kO,simpleAbsImpl:()=>G4,sliceImpl:()=>Fc,sparseFillEmptyRowsImpl:()=>b7,sparseReshapeImpl:()=>v7,sparseSegmentReductionImpl:()=>c3,sqrtImpl:()=>SO,squaredDifferenceImpl:()=>k7,stridedSliceImpl:()=>w7,stringNGramsImpl:()=>h3,stringSplitImpl:()=>f3,stringToHashBucketFastImpl:()=>m3,subImpl:()=>I7,tileImpl:()=>S7,topKImpl:()=>C7,transposeImpl:()=>d3,uniqueImpl:()=>N7});function G4(e){let t=new Float32Array(e.length);for(let a=0;a<e.length;++a)t[a]=Math.abs(e[a]);return t}var EF=e=>{let{x:t}=e.inputs,a=e.backend;Ae(t,"abs");let n=new Float32Array(v.sizeFromShape(t.shape)),r=a.data.get(t.dataId).values;return n=G4(r),a.makeOutput(n,t.shape,t.dtype)},RF={kernelName:vl,backendName:"cpu",kernelFunc:EF};function Lt(e){return(t,a,n,r,s)=>{let i=T.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),f=v.computeStrides(a),m=T.getBroadcastDims(t,i),g=T.getBroadcastDims(a,i);if(m.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);m.forEach(C=>A[C]=0);let b=v.locToIndex(A,c,h),k=x.slice(-d);g.forEach(C=>k[C]=0);let S=v.locToIndex(k,d,f);p[y]=e(n[b],r[S])}return[p,i]}}function Za(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 MF={kernelName:Td,backendName:"cpu",kernelFunc:Za};function Pc(e,t,a="float32"){if(a==="complex64"){let r=Pc(e,t,"float32"),s=Pc(e,t,"float32");return Za({inputs:{real:r,imag:s},backend:e})}let n=v.makeZerosTypedArray(v.sizeFromShape(t),a);return e.makeTensorInfo(t,a,n)}function er(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 $F={kernelName:wi,backendName:"cpu",kernelFunc:er};function Us(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 _F={kernelName:Dd,backendName:"cpu",kernelFunc:Us};function H4(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]=Lt((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 ${n}`)}function Jr(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{dtype:s}=n;if(s==="complex64"){if(r.dtype==="complex64")return er({inputs:{x:r},backend:a});let p=Pc(a,r.shape,r.dtype),c=Jr({inputs:{x:r},backend:a,attrs:{dtype:"float32"}}),d=Za({inputs:{real:c,imag:p},backend:a});return a.disposeIntermediateTensorInfo(p),a.disposeIntermediateTensorInfo(c),d}if(r.dtype==="complex64"){let p=Us({inputs:{input:r},backend:a}),c=Jr({inputs:{x:p},backend:a,attrs:{dtype:s}});return a.disposeIntermediateTensorInfo(p),c}if(!v.hasEncodingLoss(r.dtype,s)){let p=er({inputs:{x:r},backend:a});return{dataId:p.dataId,shape:p.shape,dtype:s}}let i=a.data.get(r.dataId).values,[o,l,u]=H4(i,r.shape,r.dtype,s);return a.makeTensorInfo(o,l,u)}var PF={kernelName:ti,backendName:"cpu",kernelFunc:Jr};function Yt(e,t,a,n){return a==null?({inputs:r,backend:s})=>{let{a:i,b:o}=r,l=s;Ae([i,o],e);let u=l.data.get(i.dataId).values,p=l.data.get(o.dataId).values,c=i.dtype==="string"?T.fromUint8ToStringArray(u):u,d=i.dtype==="string"?T.fromUint8ToStringArray(p):p,h=n||i.dtype,[f,m]=t(i.shape,o.shape,c,d,h);return l.makeTensorInfo(m,h,f)}:({inputs:r,backend:s})=>{let{a:i,b:o}=r,l=s;if(i.dtype==="complex64"||o.dtype==="complex64"){let u=Jr({inputs:{x:i},backend:l,attrs:{dtype:"complex64"}}),p=l.data.get(u.dataId),c=p.complexTensorInfos.real,d=p.complexTensorInfos.imag,h=l.data.get(c.dataId).values,f=l.data.get(d.dataId).values,m=Jr({inputs:{x:o},backend:l,attrs:{dtype:"complex64"}}),g=l.data.get(m.dataId),y=g.complexTensorInfos.real,x=g.complexTensorInfos.imag,A=l.data.get(y.dataId).values,b=l.data.get(x.dataId).values,[k,S,C]=a(i.shape,o.shape,h,f,A,b),N=l.makeTensorInfo(C,"float32",k),$=l.makeTensorInfo(C,"float32",S),M=Za({inputs:{real:N,imag:$},backend:l});return l.disposeIntermediateTensorInfo(u),l.disposeIntermediateTensorInfo(m),l.disposeIntermediateTensorInfo(N),l.disposeIntermediateTensorInfo($),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 i3(e){return(t,a,n,r,s,i)=>{let o=T.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=T.getBroadcastDims(t,o),f=T.getBroadcastDims(a,o),m=T.mergeRealAndImagArrays(n,r),g=T.mergeRealAndImagArrays(s,i),y=t.length,x=v.computeStrides(t),A=a.length,b=v.computeStrides(a);if(h.length+f.length===0)for(let k=0;k<c.length;k++){let S=k%m.length,C=k%g.length,N=e(m[S*2],m[S*2+1],g[C*2],g[C*2+1]);c[k]=N.real,d[k]=N.imag}else for(let k=0;k<c.length;k++){let S=v.indexToLoc(k,u,p),C=S.slice(-y);h.forEach(I=>C[I]=0);let N=v.locToIndex(C,y,x),$=S.slice(-A);f.forEach(I=>$[I]=0);let M=v.locToIndex($,A,b),R=e(m[N*2],m[N*2+1],g[M*2],g[M*2+1]);c[k]=R.real,d[k]=R.imag}return[c,d,o]}}var j4=Lt((e,t)=>e+t),FF=i3((e,t,a,n)=>({real:e+a,imag:t+n})),fl=Yt(ts,j4,FF),OF={kernelName:ts,backendName:"cpu",kernelFunc:fl};function o3(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 q4(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}function os(e){return(t,a,n)=>{let r=v.getTypedArrayFromDType(a,t.length);for(let s=0;s<t.length;++s)r[s]=e(t[s],n);return r}}function lt(e,t,a){return({inputs:n,attrs:r,backend:s})=>{let{x:i}=n;if(Ae(i,e),i.dtype==="string"||a==="string")throw new Error("unaryKernelFunc does not support string input/output");let o=s,l=o.data.get(i.dataId).values,u=v.sizeFromShape(i.shape),p=a||i.dtype,c=v.getArrayFromDType(p,u);for(let d=0;d<u;++d)c[d]=t(l[d],r);return o.makeTensorInfo(i.shape,p,c)}}function ou(e,t,a){return({inputs:n,attrs:r,backend:s})=>{let{x:i}=n;if(Ae(i,e),i.dtype==="string"||a==="string")throw new Error("unaryKernelFunc does not support string input/output");let o=s,l=o.data.get(i.dataId).values,u=a||i.dtype,p=t(l,u,r);return o.makeTensorInfo(i.shape,u,p)}}var X4=os(e=>Math.ceil(e)),DF=ou(ai,X4),zF={kernelName:ai,backendName:"cpu",kernelFunc:DF};function l3(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"?T.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 K4=Lt((e,t)=>e===t?1:0),Z4=Yt(fi,K4,null,"bool"),LF={kernelName:fi,backendName:"cpu",kernelFunc:Z4},Y4=os(e=>Math.exp(e)),J4=ou(mi,Y4,"float32"),BF={kernelName:mi,backendName:"cpu",kernelFunc:J4},Q4=os(e=>Math.expm1(e)),WF=ou(_l,Q4),VF={kernelName:_l,backendName:"cpu",kernelFunc:WF},e7=os(e=>Math.floor(e)),UF=ou(yi,e7),GF={kernelName:yi,backendName:"cpu",kernelFunc:UF};function t7(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 f=e[p*r+h];d+=f*i[h],c.push(f)}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 a7(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 n7=Lt((e,t)=>e>t?1:0),HF=Yt(vi,n7,null,"bool"),jF={kernelName:vi,backendName:"cpu",kernelFunc:HF},r7=Lt((e,t)=>e>=t?1:0),qF=Yt(ki,r7,null,"bool"),XF={kernelName:ki,backendName:"cpu",kernelFunc:qF},s7=Lt((e,t)=>e<t?1:0),KF=Yt(Ti,s7,null,"bool"),ZF={kernelName:Ti,backendName:"cpu",kernelFunc:KF},i7=Lt((e,t)=>e<=t?1:0),YF=Yt(Ci,i7,null,"bool"),JF={kernelName:Ci,backendName:"cpu",kernelFunc:YF};function o7(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 l7=os(e=>Math.log(e)),QF=ou(Ni,l7),eO={kernelName:Ni,backendName:"cpu",kernelFunc:QF};function u7(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 d7=Lt((e,t)=>Math.max(e,t)),tO=Yt(_i,d7),aO={kernelName:_i,backendName:"cpu",kernelFunc:tO},p7=Lt((e,t)=>Math.min(e,t)),nO=Yt(Di,p7),rO={kernelName:Di,backendName:"cpu",kernelFunc:nO},u3=Lt((e,t)=>e*t),sO=i3((e,t,a,n)=>({real:e*a-t*n,imag:e*n+t*a})),Nh=Yt(Li,u3,sO),iO={kernelName:Li,backendName:"cpu",kernelFunc:Nh};function c7(e,t,a){let n=v.createScalarValue(-1,a);return u3([],t,n,e,a)}function oO(e){let{inputs:t,backend:a}=e,{x:n}=t;Ae(n,"neg");let r=a.data.get(n.dataId).values,[s,i]=c7(r,n.shape,n.dtype);return a.makeTensorInfo(i,n.dtype,s)}var lO={kernelName:Bl,backendName:"cpu",kernelFunc:oO},h7=Lt((e,t)=>e!==t?1:0),uO=Yt(Bi,h7,null,"bool"),dO={kernelName:Bi,backendName:"cpu",kernelFunc:uO};function d3(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 f=0;f<d.length;f++)d[f]=c[n[f]];let h=v.locToIndex(d,s,l);u[h]=e[p]}return u}function Ba(e){let{inputs:t,attrs:a,backend:n}=e,{x:r}=t,{perm:s}=a;Ae(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=d3(l,r.shape,r.dtype,s,o);return{dataId:n.write(u,o,r.dtype),shape:o,dtype:r.dtype}}var pO={kernelName:Ar,backendName:"cpu",kernelFunc:Ba};function f7(e,t,a,n){let[r,s]=T.computeOutAndReduceShapes(e,n),i=fa(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 cO(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;Ae(r,"prod");let o=r.shape.length,l=v.parseAxisParam(s,r.shape),u=T.getAxesPermutation(l,o),p=l,c=r,d=[];u!=null&&(c=Ba({inputs:{x:r},backend:a,attrs:{perm:u}}),d.push(c),p=T.getInnerMostAxes(p.length,o));let h=a.data.get(c.dataId).values,{outVals:f,outShape:m,outDtype:g}=f7(c.shape,c.dtype,h,p),y=m;return i&&(y=T.expandShapeToKeepDim(m,l)),d.forEach(x=>a.disposeIntermediateTensorInfo(x)),a.makeTensorInfo(y,g,f)}var hO={kernelName:qi,backendName:"cpu",kernelFunc:cO};function fO(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 mO(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 gO(e,t,a,n){let r=[],s=0,i=t.length-1+a.length,o=new Array(i).fill(null).map(()=>[0]);mO(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],f=d+t.length-1;if(f>=0){let m=o[f],g=m[m.length-1]-h[p];for(let y=p;y<c;++y)o[f].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 yO(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 ny(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 xO(e,t,a,n,r,s){let i=ny(t,2)[1],o=ny(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 AO(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 xO(e,t,n,l,i,s),[i,s]}function m7(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(fO(s,i,l),n.length===0)throw new Error("params.rank must be nonzero");let u=n[0],{outSplits:p,valueSlices:c,numValues:d}=gO(s,i,e,u),h=yO(p),f=AO(a,n,r,c,d);return[h,f[0],f[1]]}var ry=2147483647;function g7(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>ry)throw new Error(`Requires ((limit - start) / delta) <= ${ry}`);d[g+1]=d[g]+b}let h=d[c],f=v.getArrayFromDType(a,h),m=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)f[m++]=x,x+=A}return[d,f]}var wn=T.RowPartitionType,m2=class{constructor(e,t,a,n,r,s,i,o,l,u){this.shape=e,this.shapeShape=t,this.values=a,this.valuesShape=n,this.valuesDType=r,this.defaultValue=s,this.defaultValueShape=i,this.rowPartitionValues=o,this.rowPartitionValuesShapes=l,this.rowPartitionTypes=T.getRowPartitionTypesHelper(u),this.raggedRank=T.getRaggedRank(this.rowPartitionTypes)}getRowPartitionTypeByDimension(e){return this.rowPartitionTypes[0]===wn.FIRST_DIM_SIZE?this.rowPartitionTypes[e+1]:this.rowPartitionTypes[e]}getRowPartitionTensor(e){return this.rowPartitionTypes[0]===wn.FIRST_DIM_SIZE?this.rowPartitionValues[e+1]:this.rowPartitionValues[e]}getMaxWidth(e){let t=this.getRowPartitionTensor(e-1);switch(this.getRowPartitionTypeByDimension(e-1)){case wn.VALUE_ROWIDS:return m2.getMaxWidthValueRowID(t);case wn.ROW_SPLITS:return m2.getMaxWidthRowSplit(t);default:throw new Error(`Cannot handle partition type ${wn[this.getRowPartitionTypeByDimension(e-1)]}`)}}static getMaxWidthRowSplit(e){let t=e.length;if(t===0||t===1)return 0;let a=0;for(let n=0;n<t-1;++n){let r=e[n+1]-e[n];r>a&&(a=r)}return a}static getMaxWidthValueRowID(e){let t=e.length;if(t===0)return 0;let a=0,n=e[0],r=0;for(let s=1;s<t;++s){let i=e[s];i!==n&&(n=i,r=Math.max(s-a,r),a=s)}return Math.max(t-a,r)}tensorShapeFromTensor(e,t,a=!0){if(t.length===0){if(e[0]===-1)return[];throw new Error("The only valid scalar shape tensor is the fully unknown shape specified as -1.")}return iy(e,a)}calculateOutputSize(e){let t=this.valuesShape,a=this.defaultValueShape;T.validateDefaultValueShape(a,t);let n=this.tensorShapeFromTensor(this.shape,this.shapeShape),r=T.combineRaggedTensorToTensorShapes(this.raggedRank,n,t);r[0]<0&&(r[0]=e);for(let s=1;s<=this.raggedRank;++s)r[s]<0&&(r[s]=this.getMaxWidth(s));return r}calculateFirstParentOutputIndex(e,t,a){let n=Math.min(e,a),r=[],s=0;for(let i=0;i<n;++i,s+=t)r.push(s);for(let i=n;i<e;++i)r.push(-1);return v.assert(r.length===e,()=>"Final length of result must be equal to firstDimension."),r}calculateOutputIndexRowSplit(e,t,a,n){let r=e.length,s=[];for(let i=0;i<r-1;++i){let o=e[i+1]-e[i],l=Math.min(n,o),u=t[i];u===-1&&(l=0);for(let p=0;p<l;++p)s.push(u),u+=a;for(let p=0;p<o-l;++p)s.push(-1)}if(r>0&&s.length!==e[r-1])throw new Error("Invalid row split size.");return s}calculateOutputIndexValueRowID(e,t,a,n){let r=e.length,s=[];if(r===0)return[];let i=0,o=e[0];if(o>=t.length)throw new Error(`Got currentValueRowId=${o}, which is not less than ${t.length}`);let l=t[o];s.push(l);for(let u=1;u<r;++u){let p=e[u];if(p===o)l>=0&&(++i,i<n?l+=a:l=-1);else{if(i=0,o=p,p>=t.length)throw new Error(`Got nextValueRowId=${p} which is not less than ${t.length}`);l=t[p]}s.push(l)}if(s.length!==e.length)throw new Error("Invalid row ids.");return s}calculateOutputIndex(e,t,a,n){let r=this.getRowPartitionTensor(e),s=this.getRowPartitionTypeByDimension(e);switch(s){case wn.VALUE_ROWIDS:return this.calculateOutputIndexValueRowID(r,t,a,n);case wn.ROW_SPLITS:if(r.length-1>t.length)throw new Error(`Row partition size is greater than output size: ${r.length-1} > ${t.length}`);return this.calculateOutputIndexRowSplit(r,t,a,n);default:throw new Error(`Unsupported partition type: ${wn[s]}`)}}getFirstDimensionSize(){let e=this.rowPartitionValues[0];if(this.rowPartitionTypes.length===0)throw new Error("No row_partition_types given.");let t=this.rowPartitionTypes[0];switch(t){case wn.FIRST_DIM_SIZE:return e[0];case wn.VALUE_ROWIDS:throw new Error("Cannot handle VALUE_ROWIDS in first dimension.");case wn.ROW_SPLITS:return this.rowPartitionValuesShapes[0][0]-1;default:throw new Error(`Cannot handle type ${wn[t]}`)}}compute(){if(this.rowPartitionValues[0].length<=0)throw new Error("Invalid first partition input. Tensor requires at least one element.");let e=this.getFirstDimensionSize(),t=this.calculateOutputSize(e),a=new Array(this.raggedRank+1);a[a.length-1]=1;for(let s=a.length-2;s>=0;--s)a[s]=a[s+1]*t[s+1];let n=iy(t,!1),r=v.getArrayFromDType(this.valuesDType,v.sizeFromShape(n));if(a[0]*t[0]>0){let s=this.calculateFirstParentOutputIndex(e,a[0],t[0]);for(let i=1;i<=this.raggedRank;++i)s=this.calculateOutputIndex(i-1,s,a[i],t[i]);this.setOutput(this.raggedRank,s,r,n)}return[n,r]}setOutput(e,t,a,n){if(a.length===0)return;let r=this.values,s=a,i=n.slice();i=i.slice(e+1);let o=v.sizeFromShape(i),l=t.length,u=this.defaultValue;if(u.length!==o&&u.length!==1){let h=this.defaultValueShape;Oe(()=>{let f=Q(u,h);u=rl(f,i).dataSync()})}let p=0,c=0,d=0;for(let h=0;h<=l;++h){let f=h<l?t[h]:-1;if(f===d){++d;continue}if(c<d){let m=r.subarray(p*o),g=s.subarray(c*o),y=(d-c)*o;sy(g,m,y)}if(h>=l){let m=a.length;f=Math.floor(m/o)}if(f>d)if(this.defaultValue.length===1)s.subarray(d*o,f*o).fill(this.defaultValue[0]),d=f;else for(;f>d;){let m=s.slice(d*o);sy(m,u,o),++d}f<0?(p=h+1,c=d):(p=h,c=d,d=c+1)}}};function sy(e,t,a){for(let n=0;n<a;n++)e[n]=t[n]}function iy(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 y7(e,t,a,n,r,s,i,o,l,u){return new m2(e,t,a,n,r,s,i,o,l,u).compute()}function p3(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 x7=os(e=>1/Math.sqrt(e)),bO=ou(to,x7),vO={kernelName:to,backendName:"cpu",kernelFunc:bO};function el(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=_e(p,t.dtype);typeof l=="string"||typeof l=="number"?h.values.fill(l):typeof l=="boolean"&&h.values.fill(+l);for(let f=0;f<s;f++){let m=[],g=0;for(let y=0;y<i;y++){let x=c[f*i+y];m.push(x),g+=x*o[y]}if(g<0||g>=n/r)throw new Error(`Invalid indices: ${m} does not index into ${a}`);for(let y=0;y<r;y++)u?h.values[g*r+y]+=d[f*r+y]:h.values[g*r+y]=t.rank===0?d[0]:d[f*r+y]}return h}var kO=os(e=>1/(1+Math.exp(-e))),A7=lt(ro,e=>1/(1+Math.exp(-e))),wO={kernelName:ro,backendName:"cpu",kernelFunc:A7};function Fc(e,t,a,n,r){let s=St.isSliceContinous(n,t,a),i=v.sizeFromShape(a),o=v.computeStrides(n);if(s){let c=St.computeFlatOffset(t,o);return r==="string"?e.slice(c,c+i):e.subarray(c,c+i)}let l=r==="string"?T.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((f,m)=>f+t[m]);p.set(u.get(...h),...d)}return r==="string"?T.fromStringArrayToUint8(p.values):p.values}function Gs(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{begin:s,size:i}=n;Ae(r,"slice");let[o,l]=St.parseSliceParams(r,s,i);St.assertParamsValid(r,o,l);let u=a.data.get(r.dataId).values,p=Fc(u,o,l,r.shape,r.dtype);return a.makeTensorInfo(l,r.dtype,p)}var IO={kernelName:Xl,backendName:"cpu",kernelFunc:Gs};function b7(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(T.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,f=new Array(l).fill(0);for(let g=0;g<o;++g){let y=e[g*c];if(y<0)throw new Error(T.getSparseFillEmptyRowsNegativeIndexErrorMessage(g,y));if(y>=l)throw new Error(T.getSparseFillEmptyRowsOutOfRangeIndexErrorMessage(g,y,l));++f[y],d=d&&y>=h,h=y}let m=!0;for(let g=0;g<l;++g){let y=f[g]===0;u[g]=y,m=m&&!y,f[g]=Math.max(f[g],1),g>0&&(f[g]+=f[g-1])}if(m&&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=f[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 k=e[b*c],S=A[k],C=(k===0?0:f[k-1])+S;A[k]++;for(let N=0;N<c;++N)y[C*c+N]=e[b*c+N];x[C]=n[b],p[b]=C}for(let b=0;b<l;++b)if(A[b]===0){let k=b===0?0:f[b-1];y[k*c+0]=b;for(let S=1;S<c;++S)y[k*c+S]=0;x[k]=i}return[y,[g,c],x,u,p]}}function v7(e,t,a,n,r){let s=v.sizeFromShape(n),i=t[0],o=r.length,l=[],u=1,p=-1;for(let m=0;m<o;++m){let g=r[m];if(g===-1){if(p!==-1)throw new Error(T.getSparseReshapeMultipleNegativeOneOutputDimErrorMessage(p,m));p=m,l.push(1)}else{if(g<0)throw new Error(T.getSparseReshapeNegativeOutputDimErrorMessage(m,g));u*=g,l.push(g)}}if(p!==-1){if(u<=0)throw new Error(T.getSparseReshapeEmptyTensorZeroOutputDimErrorMessage());let m=Math.trunc(s/u);if(u*m!==s)throw new Error(T.getSparseReshapeInputOutputMultipleErrorMessage(n,l));l[p]=m}if(v.sizeFromShape(l)!==s)throw new Error(T.getSparseReshapeInputOutputMismatchErrorMessage(n,l));let c=n.length,d=[];if(c>0){d[c-1]=1;for(let m=c-2;m>=0;--m)d[m]=d[m+1]*n[m+1]}let h=[];if(o>0){h[o-1]=1;for(let m=o-2;m>=0;--m)h[m]=h[m+1]*l[m+1]}let f=v.getArrayFromDType(a,i*o);for(let m=0;m<i;++m){let g=0;for(let y=0;y<c;++y)g+=e[m*c+y]*d[y];for(let y=0;y<o;++y)f[m*o+y]=Math.trunc(g/h[y]),g%=h[y]}return[f,[i,o],l]}function c3(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(T.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(T.getSparseSegmentReductionNegativeSegmentIdsErrorMessage());let f=0,m=1,g=0,y=r[f];for(;;){let x=0;if(m<o){if(x=r[m],y===x){++m;continue}if(y>=x)throw new Error(T.getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage())}if(y<0||y>=p)throw new Error(T.getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage(y,p));y>g&&h.fill(i,g*u,y*u);for(let A=f;A<m;++A){let b=n[A];if(b<0||b>=l[0])throw new Error(T.getSparseSegmentReductionIndicesOutOfRangeErrorMessage(A,n[A],l[0]));for(let k=0;k<u;k++)h[y*u+k]+=e[b*u+k]}if(s)for(let A=0;A<u;A++)h[y*u+A]/=m-f;if(f=m,++m,g=y+1,y=x,m>o)break}return g<p&&h.fill(i,g*u,p*u),[h,c]}var SO=os(e=>Math.sqrt(e)),TO=lt(so,e=>Math.sqrt(e)),CO={kernelName:so,backendName:"cpu",kernelFunc:TO},k7=Lt((e,t)=>{let a=e-t;return a*a}),NO=Yt(lo,k7),EO={kernelName:lo,backendName:"cpu",kernelFunc:NO};function w7(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 RO=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 f=a[n+i],m=0,g=y=>y.forEach(x=>f[m++]=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 ${o}`)}let r=n-1,s=v.getArrayFromDType("int32",n);if(a===0||n===0){let o=new Array(a);for(let l=0;l<=r;++l)s[l]=0;return[o,s]}s[0]=0;for(let o=1;o<=r;++o){let l=t[o]-t[o-1],u=0;this.nGramWidths.forEach(p=>{u+=this.getNumNGrams(l,p)}),this.preserveShort&&l>0&&u===0&&(u=1),s[o]=s[o-1]+u}let i=new Array(s[r]);for(let o=0;o<r;++o){let l=t[o],u=s[o];if(this.nGramWidths.forEach(p=>{let c=t[o+1]-t[o],d=this.getNumNGrams(c,p);this.createNGrams(e,l,i,u,d,p),u+=d}),this.preserveShort&&u===s[o]){let p=t[o+1]-t[o];if(p===0)continue;let c=p+2*this.padWidth,d=1;this.createNGrams(e,l,i,u,d,c)}}return[i,s]}};function h3(e,t,a,n,r,s,i,o){return new RO(a,n,r,s,i,o).compute(e,t)}function MO(e,t,a,n){if(!e.length)return;if(t.length===0){for(let s=0;s<e.length;++s)n.push(e.subarray(s,s+1));return}if(t.length===1){let s=t[0],i=e.indexOf(s);for(;i!==-1;){let o=e.subarray(0,i);(!a||o.length!==0)&&n.push(o),e=e.subarray(i+1),i=e.indexOf(s)}(!a||e.length!==0)&&n.push(e);return}let r=0;for(let s=0;s<e.length+1;s++)if(s===e.length||t.indexOf(e[s])!==-1){let i=e.subarray(r,s);(!a||i.length!==0)&&n.push(i),r=s+1}}function f3(e,t,a){let n=e.length,r=[],s=0,i=0,o=new Array(n);for(let d=0;d<n;++d){let h=r.length;MO(e[d],t,a,r);let f=r.length-h;o[d]=f,s+=f,i=Math.max(i,f)}let l=v.getArrayFromDType("int32",s*2),u=new Array(s),p=[n,i],c=0;for(let d=0;d<n;++d)for(let h=0;h<o[d];++h)l[c*2]=d,l[c*2+1]=h,u[c]=r[c],++c;return[l,u,p]}function m3(e,t){let a=v.getArrayFromDType("int32",e.length);for(let n=0;n<e.length;++n)a[n]=v.fingerPrint64(e[n]).modulo(t).getLowBitsUnsigned();return a}var I7=Lt((e,t)=>e-t),$O=i3((e,t,a,n)=>({real:e-a,imag:t-n})),g3=Yt(po,I7,$O),_O={kernelName:po,backendName:"cpu",kernelFunc:g3};function S7(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 Gu=(e,t)=>{let a=t.value-e.value;return a===0?e.index-t.index:a};function T7(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));T7(e,t,d,h)}let r=e[t],s=a,i=n;for(v.swap(e,a,t),Gu(e[n],r)>0&&v.swap(e,a,n);s<i;){for(v.swap(e,s,i),s++,i--;Gu(e[s],r)<0;)s=s+1;for(;Gu(e[i],r)>0;)i=i-1}Gu(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 C7(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),f=new Array(h.length);h.forEach((x,A)=>f[A]={value:x,index:A}),n<f.length&&(T7(f,n),f=f.slice(0,n)),r&&f.sort(Gu);let m=c*n,g=l.subarray(m,m+n),y=u.subarray(m,m+n);for(let x=0;x<n;x++)g[x]=f[x].value,y[x]=f[x].index}let p=t.slice();return p[p.length-1]=n,[_e(p,a,l),_e(p,"int32",u)]}function N7(e,t,a,n){let r=v.parseAxisParam(t,a)[0],s=[1,a[0],1];for(let f=0;f<r;f++)s[0]*=a[f];s[1]=a[r];for(let f=r+1;f<a.length;f++)s[2]*=a[f];let i={},o=new Int32Array(a[r]),l=new jt(s,n,e),u=[],p=s[0]===1&&s[2]===1;for(let f=0;f<a[r];f++){let m;if(p)m=e[f].toString();else{let g=[];for(let y=0;y<s[0];y++)for(let x=0;x<s[2];x++)g.push(l.get(y,f,x));m=g.join(",")}if(i[m]!==void 0)o[f]=i[m];else{let g=Object.keys(i).length;i[m]=g,o[f]=g,u.push(f)}}let c=s.slice();c[1]=Object.keys(i).length;let d=new jt(c,n);u.forEach((f,m)=>{for(let g=0;g<s[0];g++)for(let y=0;y<s[2];y++)d.set(l.get(g,f,y),g,m,y)});let h=a.slice();return h[r]=c[1],{outputValues:d.values,outputShape:h,indices:o}}var PO="4.2.0";yo("cpu",()=>new Th,1);var E7=lt(hi,e=>e>=0?e:Math.exp(e)-1),FO={kernelName:hi,backendName:"cpu",kernelFunc:E7};function R7(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{alpha:s}=n;Ae([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 OO={kernelName:Si,backendName:"cpu",kernelFunc:R7},DO=Lt((e,t)=>e<0?t*e:e);function M7(e){let{inputs:t,backend:a}=e,{x:n,alpha:r}=t;Ae([n,r],"prelu");let s=a.data.get(n.dataId).values,i=a.data.get(r.dataId).values,[o,l]=DO(n.shape,r.shape,s,i,"float32");return a.makeTensorInfo(l,"float32",o)}var zO={kernelName:ji,backendName:"cpu",kernelFunc:M7},$7=lt(Ki,e=>Math.max(0,e)),LO={kernelName:Ki,backendName:"cpu",kernelFunc:$7},_7=lt(Ji,e=>Math.min(Math.max(0,e),6)),BO={kernelName:Ji,backendName:"cpu",kernelFunc:_7};function Oc(e,t,a,n,r){if(a==="linear")return er({inputs:{x:t},backend:e});if(a==="relu")return $7({inputs:{x:t},backend:e});if(a==="elu")return E7({inputs:{x:t},backend:e});if(a==="relu6")return _7({inputs:{x:t},backend:e});if(a==="prelu")return M7({inputs:{x:t,alpha:n},backend:e});if(a==="leakyrelu")return R7({inputs:{x:t},backend:e,attrs:{alpha:r}});if(a==="sigmoid")return A7({inputs:{x:t},backend:e});throw new Error(`Activation ${a} has not been implemented for the CPU backend.`)}function mt(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{shape:s}=n,i=v.sizeFromShape(r.shape),o=v.inferFromImplicitShape(s,i),l=v.sizeFromShape(o);v.assert(i===l,()=>`The new shape (${o}) has ${l} elements and the old shape (${r.shape}) has ${i} elements. The new shape and old shape must have the same number of elements.`),a.incRef(r.dataId);let u=a.data.get(r.dataId);if(u.complexTensorInfos!=null){let p=u.complexTensorInfos.real,c=u.complexTensorInfos.imag;p.shape=o,c.shape=o}return{dataId:r.dataId,shape:o,dtype:r.dtype}}var WO={kernelName:Hl,backendName:"cpu",kernelFunc:mt};function P7(e){let{inputs:t,backend:a,attrs:n}=e,{a:r,b:s}=t,{transposeA:i,transposeB:o}=n;Ae([r,s],"matMul");let l=r.shape.length,u=s.shape.length,p=i?r.shape[l-2]:r.shape[l-1],c=o?s.shape[u-1]:s.shape[u-2],d=i?r.shape[l-1]:r.shape[l-2],h=o?s.shape[u-2]:s.shape[u-1],f=r.shape.slice(0,-2),m=s.shape.slice(0,-2),g=v.sizeFromShape(f),y=v.sizeFromShape(m),x=xo.assertAndGetBroadcastShape(r.shape.slice(0,-2),s.shape.slice(0,-2)).concat([d,h]);v.assert(p===c,()=>`Error in matMul: inner shapes (${p}) and (${c}) of Tensors with shapes ${r.shape} and ${s.shape} and transposeA=${i} and transposeB=${o} must match.`);let A=i?[g,p,d]:[g,d,p],b=o?[y,h,c]:[y,c,h],k=mt({inputs:{x:r},backend:a,attrs:{shape:A}}),S=mt({inputs:{x:s},backend:a,attrs:{shape:b}}),C=i?k.shape[1]:k.shape[2],N=i?k.shape[2]:k.shape[1],$=o?S.shape[1]:S.shape[2],M=Math.max(g,y),R=a.data.get(k.dataId).values,I=a.data.get(S.dataId).values,_=v.computeStrides(k.shape),D=v.computeStrides(S.shape),[W,P,U]=i?[_[0],1,_[1]]:[_[0],_[1],1],[G,q,H]=o?[1,D[1],D[0]]:[D[1],1,D[0]],B=N*$,Z=_e([M,N,$],k.dtype),X=Z.values,re=a.blockSize;for(let ee=0;ee<M;ee++){let ce=ee%g,ie=ee%y;for(let ge=0;ge<N;ge+=re){let Se=Math.min(ge+re,N);for(let Ne=0;Ne<$;Ne+=re){let Be=Math.min(Ne+re,$);for(let qe=0;qe<C;qe+=re){let dt=Math.min(qe+re,C);for(let it=ge;it<Se;it++)for(let at=Ne;at<Be;at++){let nt=0;for(let Ge=qe;Ge<dt;Ge++){let ht=R[ce*W+it*P+Ge*U],Ga=I[Ge*G+at*q+ie*H];nt+=ht*Ga}X[ee*B+(it*$+at)]+=nt}}}}}return a.disposeIntermediateTensorInfo(k),a.disposeIntermediateTensorInfo(S),a.makeTensorInfo(x,Z.dtype,Z.values)}var VO={kernelName:ei,backendName:"cpu",kernelFunc:P7};function UO(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,f,m=[];d=P7({inputs:{a:r,b:s},attrs:{transposeA:l,transposeB:u},backend:a}),i&&(h=fl({inputs:{a:d,b:i},backend:a}),m.push(d),d=h),p&&(f=Oc(a,d,p,o,c),m.push(d),d=f);for(let g of m)a.disposeIntermediateTensorInfo(g);return d}var GO={kernelName:Hr,backendName:"cpu",kernelFunc:UO},HO=lt(kl,e=>Math.acos(e)),jO={kernelName:kl,backendName:"cpu",kernelFunc:HO},qO=lt(wl,e=>Math.acosh(e)),XO={kernelName:wl,backendName:"cpu",kernelFunc:qO};function KO(e){let{inputs:t,backend:a}=e,n=t;Ae(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 ZO={kernelName:Ks,backendName:"cpu",kernelFunc:KO};function YO(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;Ae(r,"all");let o=v.parseAxisParam(s,r.shape),l=o,u=T.getAxesPermutation(l,r.shape.length),p=r;u!=null&&(p=Ba({inputs:{x:r},backend:a,attrs:{perm:u}}),l=T.getInnerMostAxes(l.length,r.shape.length)),T.assertAxesAreInnerMostDims("all",l,p.shape.length);let[c,d]=T.computeOutAndReduceShapes(p.shape,l),h=v.sizeFromShape(d),f=v.makeZerosTypedArray(v.sizeFromShape(c),p.dtype),m=a.data.get(p.dataId).values;for(let y=0;y<f.length;++y){let x=y*h,A=m[x];for(let b=0;b<h;++b){let k=m[x+b];A=A&&k}f[y]=A}u!=null&&a.disposeIntermediateTensorInfo(p);let g=a.makeTensorInfo(c,p.dtype,f);if(i){let y=T.expandShapeToKeepDim(c,o),x=mt({inputs:{x:g},backend:a,attrs:{shape:y}});return a.disposeIntermediateTensorInfo(g),x}return g}var JO={kernelName:Zs,backendName:"cpu",kernelFunc:YO};function QO(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;Ae(r,"any");let o=v.parseAxisParam(s,r.shape),l=o,u=T.getAxesPermutation(l,r.shape.length),p=r;u!=null&&(p=Ba({inputs:{x:r},backend:a,attrs:{perm:u}}),l=T.getInnerMostAxes(l.length,r.shape.length)),T.assertAxesAreInnerMostDims("any",l,p.shape.length);let[c,d]=T.computeOutAndReduceShapes(p.shape,l),h=v.sizeFromShape(d),f=v.makeZerosTypedArray(v.sizeFromShape(c),p.dtype),m=a.data.get(p.dataId).values;for(let y=0;y<f.length;++y){let x=y*h,A=m[x];for(let b=0;b<h;++b){let k=m[x+b];A=A||k}f[y]=A}u!=null&&a.disposeIntermediateTensorInfo(p);let g=a.makeTensorInfo(c,p.dtype,f);if(i){let y=T.expandShapeToKeepDim(c,o),x=mt({inputs:{x:g},backend:a,attrs:{shape:y}});return a.disposeIntermediateTensorInfo(g),x}return g}var eD={kernelName:Ys,backendName:"cpu",kernelFunc:QO};function tD(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s}=n;Ae(r,"argMax");let i=v.parseAxisParam(s,r.shape),o=T.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=Ba({inputs:{x:r},backend:a,attrs:{perm:o}}),u.push(l),i=T.getInnerMostAxes(i.length,l.shape.length)),i=[i[0]],T.assertAxesAreInnerMostDims("argMax",i,l.shape.length);let[p,c]=T.computeOutAndReduceShapes(l.shape,i),d=v.sizeFromShape(p),h=v.makeZerosTypedArray(d,"int32"),f=v.sizeFromShape(c),m=a.data.get(l.dataId).values;for(let g=0;g<h.length;++g){let y=g*f,x=m[y],A=0;for(let b=0;b<f;++b){let k=m[y+b];k>x&&(x=k,A=b)}h[g]=A}return u.forEach(g=>a.disposeIntermediateTensorInfo(g)),a.makeTensorInfo(p,"int32",h)}var aD={kernelName:Js,backendName:"cpu",kernelFunc:tD};function nD(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s}=n;Ae(r,"argMin");let i=v.parseAxisParam(s,r.shape),o=T.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=Ba({inputs:{x:r},backend:a,attrs:{perm:o}}),u.push(l),i=T.getInnerMostAxes(i.length,l.shape.length)),i=[i[0]],T.assertAxesAreInnerMostDims("argMin",i,l.shape.length);let[p,c]=T.computeOutAndReduceShapes(l.shape,i),d=v.sizeFromShape(p),h=v.makeZerosTypedArray(d,"int32"),f=v.sizeFromShape(c),m=a.data.get(l.dataId).values;for(let g=0;g<h.length;++g){let y=g*f,x=m[y],A=0;for(let b=0;b<f;++b){let k=m[y+b];k<x&&(x=k,A=b)}h[g]=A}return u.forEach(g=>a.disposeIntermediateTensorInfo(g)),a.makeTensorInfo(p,"int32",h)}var rD={kernelName:Id,backendName:"cpu",kernelFunc:nD},sD=lt(Il,e=>Math.asin(e)),iD={kernelName:Il,backendName:"cpu",kernelFunc:sD},oD=lt(Sl,e=>Math.asinh(e)),lD={kernelName:Sl,backendName:"cpu",kernelFunc:oD},uD=lt(Tl,e=>Math.atan(e)),dD={kernelName:Tl,backendName:"cpu",kernelFunc:uD},pD=Lt((e,t)=>Math.atan2(e,t)),cD=Yt(Nl,pD),hD={kernelName:Nl,backendName:"cpu",kernelFunc:cD},fD=lt(Cl,e=>Math.atanh(e)),mD={kernelName:Cl,backendName:"cpu",kernelFunc:fD};function y3(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,f=s==="max"?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,m=_e(r.outShape,a),g=m.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 k=b*y,S=b*n[0];for(let C=0;C<r.inChannels;++C)for(let N=0;N<r.outHeight;++N){let $=N*i-d,M=Math.max(0,$),R=Math.min(r.inHeight,p+$),I=k+N*x;for(let _=0;_<r.outWidth;++_){let D=_*o-h,W=Math.max(0,D),P=Math.min(r.inWidth,c+D),U=f,G=0,q=0;for(let B=M;B<R;B+=l){let Z=S+B*n[1];for(let X=W;X<P;X+=u){let re=Z+X*n[2],ee=e[re+C];s==="max"&&ee>U?U=ee:s==="avg"&&(G+=ee,q++)}if(isNaN(U))break}let H=I+_*A+C;g[H]=s==="avg"?G/q:U}}}return m}function F7(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,f=n.padInfo.left,m=_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 k=Math.min(n.inHeight,c+A);for(let S=0;S<n.outWidth;++S){let C=S*l-f,N=C;for(;N<0;)N+=p;let $=Math.min(n.inWidth,d+C),M=Number.NEGATIVE_INFINITY,R=-1;for(let I=b;I<k;I+=u){let _=I-A;for(let D=N;D<$;D+=p){let W=D-C,P=m.get(g,I,D,y);P>M&&(M=P,r?R=s?((g*n.inHeight+I)*n.inWidth+D)*n.inChannels+y:(I*n.inWidth+D)*n.inChannels+y:R=_*d+W)}}i.set(R,g,x,S,y)}}return i}function O7(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,f=r.effectiveFilterWidth,m=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,k=r.outShape[1]*r.outShape[2]*r.outShape[3]*r.outShape[4],S=r.outShape[2]*r.outShape[3]*r.outShape[4],C=r.outShape[3]*r.outShape[4],N=r.outShape[4];for(let $=0;$<r.batchSize;++$){let M=$*k,R=$*n[0];for(let I=0;I<r.inChannels;++I)for(let _=0;_<r.outDepth;++_){let D=_*i-m,W=D;for(;W<0;)W+=u;let P=Math.min(r.inDepth,d+D),U=M+_*S;for(let G=0;G<r.outHeight;++G){let q=G*o-g,H=q;for(;H<0;)H+=p;let B=Math.min(r.inHeight,h+q),Z=U+G*C;for(let X=0;X<r.outWidth;++X){let re=X*l-y,ee=re;for(;ee<0;)ee+=c;let ce=Math.min(r.inWidth,f+re),ie=Z+X*N,ge=x,Se=0,Ne=0;for(let qe=W;qe<P;qe+=u){let dt=R+qe*n[1];for(let it=H;it<B;it+=p){let at=dt+it*n[2];for(let nt=ee;nt<ce;nt+=c){let Ge=at+nt*n[3],ht=e[Ge+I];if(s==="max"&&ht>ge?ge=ht:s==="avg"&&(Se+=ht,Ne++),isNaN(ge))break}if(isNaN(ge))break}if(isNaN(ge))break}let Be=ie+I;b[Be]=s==="avg"?Se/Math.max(Ne,1):ge}}}}return A}function gD(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,f=t.padInfo.left;for(let m=0;m<t.batchSize;++m)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 k=0;k<t.outHeight;++k){let S=k*r-h,C=S;for(;C<0;)C+=o;let N=Math.min(t.inHeight,p+S);for(let $=0;$<t.outWidth;++$){let M=$*s-f,R=M;for(;R<0;)R+=l;let I=Math.min(t.inWidth,c+M),_=Number.NEGATIVE_INFINITY,D=-1;for(let W=A;W<b;W+=i){let P=W-x;for(let U=C;U<N;U+=o){let G=U-S;for(let q=R;q<I;q+=l){let H=q-M,B=e.get(m,W,U,q,g);B>=_&&(_=B,D=P*p*c+G*p+H)}}}a.set(D,m,y,k,$,g)}}}return a}function yD(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t;Ae(r,"avgPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=n,u=1;v.assert(T.eitherStridesOrDilationsAreOne(i,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let p=T.computePool2DInfo(r.shape,s,i,u,o,l),c;if(p.filterWidth===1&&p.filterHeight===1&&v.arraysEqual(p.inShape,p.outShape))c=er({inputs:{x:r},backend:a});else{let d=a.data.get(r.dataId).values,h=v.computeStrides(r.shape),f=y3(d,r.shape,r.dtype,h,p,"avg");c=a.makeTensorInfo(p.outShape,r.dtype,f.values)}return c}var xD={kernelName:Qs,backendName:"cpu",kernelFunc:yD};function AD(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:u}=n;Ae(r,"avgPool3d");let p=T.computePool3DInfo(r.shape,s,i,1,o,l,u),c=a.data.get(r.dataId).values,d=O7(c,r.shape,r.dtype,v.computeStrides(r.shape),p,"avg");return a.makeTensorInfo(d.shape,"float32",d.values)}var bD={kernelName:Kc,backendName:"cpu",kernelFunc:AD};function vD(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=n;Ae([r,s],"avgPool3DGrad");let p=T.computePool3DInfo(s.shape,i,o,1,l,u),c=p.strideDepth,d=p.strideHeight,h=p.strideWidth,f=p.filterDepth,m=p.filterHeight,g=p.filterWidth,y=p.dilationDepth,x=p.dilationHeight,A=p.dilationWidth,b=p.effectiveFilterDepth,k=p.effectiveFilterHeight,S=p.effectiveFilterWidth,C=b-1-p.padInfo.front,N=S-1-p.padInfo.left,$=k-1-p.padInfo.top,M=_e(s.shape,"float32"),R=1/(f*m*g),I=a.bufferSync(r);for(let _=0;_<p.batchSize;++_)for(let D=0;D<p.inChannels;++D)for(let W=0;W<p.inDepth;++W)for(let P=0;P<p.inHeight;++P)for(let U=0;U<p.inWidth;++U){let G=W-C,q=P-$,H=U-N,B=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<k;re+=x){let ee=(q+re)/d;if(!(ee<0||ee>=p.outHeight||Math.floor(ee)!==ee))for(let ce=0;ce<S;ce+=A){let ie=(H+ce)/h;if(ie<0||ie>=p.outWidth||Math.floor(ie)!==ie)continue;let ge=I.get(_,X,ee,ie,D);B+=ge}}}M.set(B*R,_,W,P,U,D)}return a.makeTensorInfo(M.shape,M.dtype,M.values)}var kD={kernelName:L2,backendName:"cpu",kernelFunc:vD};function wD(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,i=s;Ae([r,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:u}=n,p=T.computePool2DInfo(i.shape,o,l,1,u),c=p.strideHeight,d=p.strideWidth,h=p.filterHeight,f=p.filterWidth,m=p.dilationHeight,g=p.dilationWidth,y=p.effectiveFilterHeight,x=p.effectiveFilterWidth,A=x-1-p.padInfo.left,b=y-1-p.padInfo.top,k=_e(i.shape,"float32"),S=1/(h*f),C=a.data.get(r.dataId).values,N=_e(r.shape,"float32",C);for(let $=0;$<p.batchSize;++$)for(let M=0;M<p.inChannels;++M)for(let R=0;R<p.inHeight;++R)for(let I=0;I<p.inWidth;++I){let _=R-b,D=I-A,W=0;for(let P=0;P<y;P+=m){let U=(_+P)/c;if(!(U<0||U>=p.outHeight||Math.floor(U)!==U))for(let G=0;G<x;G+=g){let q=(D+G)/d;if(q<0||q>=p.outWidth||Math.floor(q)!==q)continue;let H=N.get($,U,q,M);W+=H}}k.set(W*S,$,R,I,M)}return a.makeTensorInfo(k.shape,k.dtype,k.values)}var ID={kernelName:Xc,backendName:"cpu",kernelFunc:wD};function SD(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."),Ae([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]),f=i?a.data.get(i.dataId).values:new Float32Array([0]),m=new Float32Array(p.length),g=f.length,y=h.length,x=d.length,A=c.length,b=0,k=0,S=0,C=0;for(let N=0;N<p.length;++N)m[N]=f[b++]+(p[N]-c[k++])*h[S++]/Math.sqrt(d[C++]+u),b>=g&&(b=0),k>=A&&(k=0),S>=y&&(S=0),C>=x&&(C=0);return a.makeTensorInfo(r.shape,r.dtype,m)}var TD={kernelName:Ai,backendName:"cpu",kernelFunc:SD};function CD(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockShape:s,crops:i}=n;Ae([r],"batchToSpaceND");let o=s.reduce((y,x)=>y*x),l=T.getReshaped(r.shape,s,o),u=T.getPermuted(l.length,s.length),p=T.getReshapedPermuted(r.shape,s,o),c=T.getSliceBeginCoords(i,s.length),d=T.getSliceSize(p,i,s.length),h=mt({inputs:{x:r},backend:a,attrs:{shape:l}}),f=Ba({inputs:{x:h},backend:a,attrs:{perm:u}}),m=mt({inputs:{x:f},backend:a,attrs:{shape:p}}),g=Gs({inputs:{x:m},backend:a,attrs:{begin:c,size:d}});return a.disposeIntermediateTensorInfo(h),a.disposeIntermediateTensorInfo(f),a.disposeIntermediateTensorInfo(m),g}var ND={kernelName:El,backendName:"cpu",kernelFunc:CD};function ED(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=o3(o,l,s.dtype,s.shape,i);return a.makeTensorInfo([i],s.dtype,u)}var RD={kernelName:Sd,backendName:"cpu",kernelFunc:ED};function MD(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=T.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return a.makeTensorInfo([o.length],"int32",Int32Array.from(o))}var $D={kernelName:Zc,backendName:"cpu",kernelFunc:MD},_D=lt(as,(e,t)=>{let a=t;return e>a.clipValueMax?a.clipValueMax:e<a.clipValueMin?a.clipValueMin:e}),PD={kernelName:as,backendName:"cpu",kernelFunc:_D},FD=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")},OD={kernelName:Yc,backendName:"cpu",kernelFunc:FD};function ml(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 DD={kernelName:Pd,backendName:"cpu",kernelFunc:ml};function gl(e){let{inputs:t,backend:a,attrs:n}=e,{axis:r}=n,s=v.parseAxisParam(r,t[0].shape)[0],i=t.map(m=>m.shape);T.assertParamsConsistent(i,s);let o=T.computeOutShape(t.map(m=>m.shape),s);if(v.sizeFromShape(o)===0)return a.makeTensorInfo(o,t[0].dtype,[]);let l=t.filter(m=>v.sizeFromShape(m.shape)>0);if(l.length===1)return er({inputs:{x:l[0]},backend:a});if(l[0].dtype==="complex64"){let m=l.map(b=>Us({inputs:{input:b},backend:a})),g=l.map(b=>ml({inputs:{input:b},backend:a})),y=gl({inputs:m,backend:a,attrs:{axis:s}}),x=gl({inputs:g,backend:a,attrs:{axis:s}}),A=Za({inputs:{real:y,imag:x},backend:a});return m.forEach(b=>a.disposeIntermediateTensorInfo(b)),g.forEach(b=>a.disposeIntermediateTensorInfo(b)),a.disposeIntermediateTensorInfo(y),a.disposeIntermediateTensorInfo(x),A}let u=l.map(m=>{let g=[-1,v.sizeFromShape(m.shape.slice(s))];return mt({inputs:{x:m},backend:a,attrs:{shape:g}})}),p=u.map(m=>({vals:a.data.get(m.dataId).values,shape:m.shape}));o=T.computeOutShape(u.map(m=>m.shape),1);let c=u[0].shape[0]===1,d=l3(p,o,t[0].dtype,c),h=T.computeOutShape(l.map(m=>m.shape),s),f=a.makeTensorInfo(h,t[0].dtype,d);return u.forEach(m=>a.disposeIntermediateTensorInfo(m)),f}var zD={kernelName:Rl,backendName:"cpu",kernelFunc:gl};function D7(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;Ae([r,s],"conv2d");let c=T.convertConv2DDataFormat(l),d=T.computeConv2DInfo(r.shape,s.shape,i,u,o,p,!1,c),h=d.filterHeight,f=d.filterWidth,m=d.dilationHeight,g=d.dilationWidth,y=d.padInfo.left,x=d.padInfo.top,A=d.dataFormat==="channelsLast",b=new jt(d.outShape,r.dtype),k=v.computeStrides(r.shape),S=v.computeStrides(s.shape),C=k[0],N=A?k[1]:k[2],$=A?k[2]:1,M=A?1:k[1],R=b.strides[0],I=A?b.strides[1]:b.strides[2],_=A?b.strides[2]:1,D=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*C,H=G*R;for(let B=0;B<d.outHeight;++B){let Z=H+B*I,X=B*d.strideHeight-x;for(let re=0;re<h;++re){let ee=X+re*m;if(ee<0||ee>=d.inHeight)continue;let ce=re*S[0],ie=q+ee*N;for(let ge=0;ge<d.outWidth;++ge){let Se=Z+ge*_,Ne=ge*d.strideWidth-y;for(let Be=0;Be<f;++Be){let qe=Ne+Be*g;if(qe<0||qe>=d.inWidth)continue;let dt=ce+Be*S[1],it=ie+qe*$,at=dt;for(let nt=0;nt<d.inChannels;++nt){let Ge=W[it+nt*M];for(let ht=0;ht<d.outChannels;++ht)U[Se+ht*D]+=Ge*P[at+ht];at+=d.outChannels}}}}}}return a.makeTensorInfo(b.shape,b.dtype,U)}var LD={kernelName:ni,backendName:"cpu",kernelFunc:D7};function BD(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;Ae([r,s],"conv2dBackpropFilter");let c=T.convertConv2DDataFormat(l),d=T.computeConv2DInfo(r.shape,p,i,1,o,u,!1,c),{strideHeight:h,strideWidth:f,filterHeight:m,filterWidth:g}=d,y=d.dataFormat==="channelsLast",x=new jt(d.filterShape,"float32"),A=d.padInfo.left,b=d.padInfo.top,k=a.data.get(r.dataId).values,S=a.data.get(s.dataId).values,C=new jt(r.shape,r.dtype,k),N=new jt(s.shape,s.dtype,S);for(let $=0;$<m;++$){let M=Math.max(0,Math.ceil((b-$)/h)),R=Math.min(d.outHeight,(d.inHeight+b-$)/h);for(let I=0;I<g;++I){let _=Math.max(0,Math.ceil((A-I)/f)),D=Math.min(d.outWidth,(d.inWidth+A-I)/f);for(let W=0;W<d.inChannels;++W)for(let P=0;P<d.outChannels;++P){let U=0;for(let G=0;G<d.batchSize;++G)for(let q=M;q<R;++q){let H=$+q*h-b;for(let B=_;B<D;++B){let Z=I+B*f-A;y?U+=C.get(G,H,Z,W)*N.get(G,q,B,P):U+=C.get(G,W,H,Z)*N.get(G,P,q,B)}}x.set(U,$,I,W,P)}}}return a.makeTensorInfo(x.shape,x.dtype,x.values)}var WD={kernelName:Cd,backendName:"cpu",kernelFunc:BD};function VD(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:u,dimRoundingMode:p}=n;Ae([r,s],"conv2dBackpropInput");let c=v.computeStrides(s.shape),d=v.computeStrides(r.shape),h=T.convertConv2DDataFormat(u),f=T.computeConv2DInfo(i,s.shape,o,1,l,p,!1,h),m=new jt(f.inShape,"float32"),g=m.values,y=a.data.get(r.dataId).values,x=a.data.get(s.dataId).values,[A,b,k]=c,{batchSize:S,filterHeight:C,filterWidth:N,inChannels:$,inHeight:M,inWidth:R,outChannels:I,outHeight:_,outWidth:D,strideHeight:W,strideWidth:P}=f;h=f.dataFormat;let U=C-1-f.padInfo.top,G=N-1-f.padInfo.left,q=h==="channelsLast",H=m.strides[0],B=q?m.strides[1]:m.strides[2],Z=q?m.strides[2]:1,X=q?1:m.strides[1],re=d[0],ee=q?d[1]:d[2],ce=q?d[2]:1,ie=q?1:d[1];for(let ge=0;ge<S;++ge)for(let Se=0;Se<$;++Se)for(let Ne=0;Ne<M;++Ne){let Be=Ne-U,qe=Math.max(0,Math.ceil(Be/W)),dt=Math.min(_,(C+Be)/W);for(let it=0;it<R;++it){let at=it-G,nt=Math.max(0,Math.ceil(at/P)),Ge=Math.min(D,(N+at)/P),ht=0;for(let Ot=qe;Ot<dt;++Ot){let ln=Ot*W-Be;for(let ra=nt;ra<Ge;++ra){let _a=ra*P-at,un=re*ge+ee*Ot+ce*ra,Pa=A*(C-1-ln)+b*(N-1-_a)+k*Se;for(let ut=0;ut<I;++ut){let Fa=y[un+ie*ut],Ha=x[Pa+ut];ht+=Fa*Ha}}}let Ga=H*ge+B*Ne+Z*it+X*Se;g[Ga]=ht}}return a.makeTensorInfo(m.shape,m.dtype,m.values)}var UD={kernelName:ri,backendName:"cpu",kernelFunc:VD};function GD(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=n;Ae([r,s],"conv3d");let u=T.computeConv3DInfo(r.shape,s.shape,i,l,o),{filterDepth:p,filterHeight:c,filterWidth:d,dilationDepth:h,dilationHeight:f,dilationWidth:m,padInfo:g}=u,y=g.front,x=g.left,A=g.top,b=new jt(u.outShape,r.dtype),k=a.data.get(r.dataId).values,S=a.data.get(s.dataId).values,C=b.values,N=v.computeStrides(r.shape),$=v.computeStrides(s.shape);for(let M=0;M<u.batchSize;++M){let R=M*N[0],I=M*b.strides[0];for(let _=0;_<u.outDepth;++_){let D=I+_*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*$[0],q=R+U*N[1];for(let H=0;H<u.outHeight;++H){let B=D+H*b.strides[2],Z=H*u.strideHeight-A;for(let X=0;X<c;++X){let re=Z+X*f;if(re<0||re>=u.inHeight)continue;let ee=G+X*$[1],ce=q+re*N[2];for(let ie=0;ie<u.outWidth;++ie){let ge=B+ie*u.outChannels,Se=ie*u.strideWidth-x;for(let Ne=0;Ne<d;++Ne){let Be=Se+Ne*m;if(Be<0||Be>=u.inWidth)continue;let qe=ee+Ne*$[2],dt=ce+Be*u.inChannels,it=qe;for(let at=0;at<u.inChannels;++at){let nt=k[dt+at];for(let Ge=0;Ge<u.outChannels;++Ge)C[ge+Ge]+=nt*S[it+Ge];it+=u.outChannels}}}}}}}}return a.makeTensorInfo(b.shape,b.dtype,b.values)}var HD={kernelName:Jc,backendName:"cpu",kernelFunc:GD};function jD(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,dy:s}=t,{strides:i,pad:o,filterShape:l}=n;Ae([r,s],"conv3dBackpropFilterV2");let u=v.computeStrides(r.shape),p=v.computeStrides(s.shape),c=T.computeConv3DInfo(r.shape,l,i,1,o),d=c.strideDepth,h=c.strideHeight,f=c.strideWidth,m=c.filterDepth,g=c.filterHeight,y=c.filterWidth,x=new jt(c.filterShape,"float32"),A=x.values,[b,k,S,C]=x.strides,N=a.data.get(s.dataId).values,[$,M,R,I]=p,_=a.data.get(r.dataId).values,[D,W,P,U]=u,G=c.padInfo.front,q=c.padInfo.left,H=c.padInfo.top;for(let B=0;B<m;++B){let Z=Math.max(0,Math.ceil((G-B)/d)),X=Math.min(c.outDepth,(c.inDepth+G-B)/d),re=B*b;for(let ee=0;ee<g;++ee){let ce=Math.max(0,Math.ceil((H-ee)/h)),ie=Math.min(c.outHeight,(c.inHeight+H-ee)/h),ge=ee*k+re;for(let Se=0;Se<y;++Se){let Ne=Math.max(0,Math.ceil((q-Se)/f)),Be=Math.min(c.outWidth,(c.inWidth+q-Se)/f),qe=Se*S+ge;for(let dt=0;dt<c.inChannels;++dt){let it=dt*C+qe;for(let at=0;at<c.outChannels;++at){let nt=0;for(let Ge=0;Ge<c.batchSize;++Ge){let ht=Ge*D,Ga=Ge*$;for(let Ot=Z;Ot<X;++Ot){let ln=(B+Ot*d-G)*W+ht,ra=Ot*M+Ga;for(let _a=ce;_a<ie;++_a){let un=(ee+_a*h-H)*P+ln,Pa=_a*R+ra;for(let ut=Ne;ut<Be;++ut){let Fa=(Se+ut*f-q)*U+un,Ha=ut*I+Pa;nt+=_[Fa+dt]*N[Ha+at]}}}}A[it+at]=nt}}}}}return a.makeTensorInfo(x.shape,x.dtype,x.values)}var qD={kernelName:B2,backendName:"cpu",kernelFunc:jD};function XD(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,filter:s}=t,{pad:i,strides:o,inputShape:l}=n;Ae([r],"conv3dBackpropInputV2");let u=v.computeStrides(r.shape),p=v.computeStrides(s.shape),c=T.computeConv3DInfo(l,s.shape,o,1,i),d=new jt(c.inShape,"float32"),h=d.values,[f,m,g,y]=d.strides,x=a.data.get(r.dataId).values,[A,b,k,S]=u,C=a.data.get(s.dataId).values,[N,$,M,R]=p,{batchSize:I,filterDepth:_,filterHeight:D,filterWidth:W,inChannels:P,inDepth:U,inHeight:G,inWidth:q,outChannels:H,outDepth:B,outHeight:Z,outWidth:X,strideDepth:re,strideHeight:ee,strideWidth:ce}=c,ie=_-1-c.padInfo.front,ge=D-1-c.padInfo.top,Se=W-1-c.padInfo.left;for(let Ne=0;Ne<I;++Ne)for(let Be=0;Be<P;++Be)for(let qe=0;qe<U;++qe){let dt=qe-ie,it=Math.max(0,Math.ceil(dt/re)),at=Math.min(B,(_+dt)/re);for(let nt=0;nt<G;++nt){let Ge=nt-ge,ht=Math.max(0,Math.ceil(Ge/ee)),Ga=Math.min(Z,(D+Ge)/ee);for(let Ot=0;Ot<q;++Ot){let ln=Ot-Se,ra=Math.max(0,Math.ceil(ln/ce)),_a=Math.min(X,(W+ln)/ce),un=0;for(let Pa=it;Pa<at;++Pa){let ut=Pa*re-dt;for(let Fa=ht;Fa<Ga;++Fa){let Ha=Fa*ee-Ge;for(let dr=ra;dr<_a;++dr){let Wo=dr*ce-ln,Un=A*Ne+b*Pa+k*Fa+S*dr,$u=N*(_-1-ut)+$*(D-1-Ha)+M*(W-1-Wo)+R*Be;for(let kn=0;kn<H;++kn){let $r=x[Un+kn],Xt=C[$u+kn];un+=$r*Xt}}}}h[f*Ne+m*qe+g*nt+y*Ot+Be]=un}}}return a.makeTensorInfo(d.shape,d.dtype,d.values)}var KD={kernelName:Qc,backendName:"cpu",kernelFunc:XD},ZD=lt(si,e=>Math.cos(e)),YD={kernelName:si,backendName:"cpu",kernelFunc:ZD},JD=lt(ii,e=>Math.cosh(e)),QD={kernelName:ii,backendName:"cpu",kernelFunc:JD};function ez(e){let{inputs:t,backend:a,attrs:n}=e,{image:r,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:u}=n,[p,c,d,h]=r.shape,f=s.shape[0],[m,g]=o,y=_e([f,m,g,h],"float32"),x=a.data.get(s.dataId).values,A=a.data.get(i.dataId).values,b=a.data.get(r.dataId).values,k=v.computeStrides(r.shape),S=v.computeStrides(y.shape);for(let C=0;C<f;C++){let N=C*4,$=x[N],M=x[N+1],R=x[N+2],I=x[N+3],_=A[C];if(_>=p)continue;let D=m>1?(R-$)*(c-1)/(m-1):0,W=g>1?(I-M)*(d-1)/(g-1):0;for(let P=0;P<m;P++){let U=m>1?$*(c-1)+P*D:.5*($+R)*(c-1);if(U<0||U>c-1){for(let G=0;G<g;G++)for(let q=0;q<h;q++){let H=q+G*S[2]+P*S[1]+C*S[0];y.values[H]=u}continue}if(l==="bilinear"){let G=Math.floor(U),q=Math.ceil(U),H=U-G;for(let B=0;B<g;B++){let Z=g>1?M*(d-1)+B*W:.5*(M+I)*(d-1);if(Z<0||Z>d-1){for(let ce=0;ce<h;ce++){let ie=ce+B*S[2]+P*S[1]+C*S[0];y.values[ie]=u}continue}let X=Math.floor(Z),re=Math.ceil(Z),ee=Z-X;for(let ce=0;ce<h;ce++){let ie=ce+X*k[2]+G*k[1]+_*k[0],ge=b[ie];ie=ce+re*k[2]+G*k[1]+_*k[0];let Se=b[ie];ie=ce+X*k[2]+q*k[1]+_*k[0];let Ne=b[ie];ie=ce+re*k[2]+q*k[1]+_*k[0];let Be=b[ie],qe=ge+(Se-ge)*ee,dt=Ne+(Be-Ne)*ee;ie=ce+B*S[2]+P*S[1]+C*S[0],y.values[ie]=qe+(dt-qe)*H}}}else for(let G=0;G<g;++G){let q=g>1?M*(d-1)+G*W:.5*(M+I)*(d-1);if(q<0||q>d-1){for(let Z=0;Z<h;Z++){let X=Z+G*S[2]+P*S[1]+C*S[0];y.values[X]=u}continue}let H=Math.round(q),B=Math.round(U);for(let Z=0;Z<h;Z++){let X=Z+H*k[2]+B*k[1]+_*k[0],re=Z+G*S[2]+P*S[1]+C*S[0];y.values[re]=b[X]}}}}return a.makeTensorInfo(y.shape,y.dtype,y.values)}var tz={kernelName:ui,backendName:"cpu",kernelFunc:ez};function az(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=n;Ae(r,"cumprod");let l=T.getAxesPermutation([s],r.shape.length),u=r;l!=null&&(u=Ba({inputs:{x:r},backend:a,attrs:{perm:l}}));let p=T.getInnerMostAxes(1,r.shape.length)[0];if(p!==u.shape.length-1)throw new Error(`backend.cumprod in CPU expects an inner-most axis=${u.shape.length-1} but got axis=${p}`);let c=fa(u.dtype,"int32"),d=v.makeOnesTypedArray(v.sizeFromShape(u.shape),c),h=a.data.get(u.dataId).values,f=u.shape[u.shape.length-1],m=o?(y,x)=>y+f-x-1:(y,x)=>y+x;for(let y=0;y<h.length;y+=f)for(let x=0;x<f;x++){let A=m(y,x);if(x===0)d[A]=i?1:h[A];else{let b=m(y,x-1);d[A]=i?h[b]*d[b]:h[A]*d[b]}}let g=a.makeTensorInfo(u.shape,c,d);if(l!=null){let y=T.getUndoAxesPermutation(l),x=Ba({inputs:{x:g},backend:a,attrs:{perm:y}});return a.disposeIntermediateTensorInfo(g),a.disposeIntermediateTensorInfo(u),x}return g}var nz={kernelName:oi,backendName:"cpu",kernelFunc:az};function rz(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=n;Ae(r,"cumsum");let l=T.getAxesPermutation([s],r.shape.length),u=r;l!=null&&(u=Ba({inputs:{x:r},backend:a,attrs:{perm:l}}));let p=T.getInnerMostAxes(1,r.shape.length)[0];if(p!==u.shape.length-1)throw new Error(`backend.cumsum in CPU expects an inner-most axis=${u.shape.length-1} but got axis=${p}`);let c=fa(u.dtype,"int32"),d=v.makeZerosTypedArray(v.sizeFromShape(u.shape),c),h=a.data.get(u.dataId).values,f=u.shape[u.shape.length-1],m=o?(y,x)=>y+f-x-1:(y,x)=>y+x;for(let y=0;y<h.length;y+=f)for(let x=0;x<f;x++){let A=m(y,x);if(x===0)d[A]=i?0:h[A];else{let b=m(y,x-1);d[A]=i?h[b]+d[b]:h[A]+d[b]}}let g=a.makeTensorInfo(u.shape,c,d);if(l!=null){let y=T.getUndoAxesPermutation(l),x=Ba({inputs:{x:g},backend:a,attrs:{perm:y}});return a.disposeIntermediateTensorInfo(g),a.disposeIntermediateTensorInfo(u),x}return g}var sz={kernelName:li,backendName:"cpu",kernelFunc:rz};function iz(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,weights:s}=t,{size:i,binaryOutput:o}=n;if(r.shape.length===1){let l=a.data.get(r.dataId).values,u=a.data.get(s.dataId).values,p=o3(l,u,s.dtype,s.shape,i);return a.makeTensorInfo([i],s.dtype,p)}else if(r.shape.length===2){let l=a.bufferSync(r),u=a.bufferSync(s),p=q4(l,u,i,o);return a.makeTensorInfo(p.shape,s.dtype,p.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${r.shape.length}.`)}var oz={kernelName:Nd,backendName:"cpu",kernelFunc:iz};function lz(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),f=a.data.get(r.dataId).values,m=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 k=0;k<d;++k){let S=Math.floor(k/s),C=k%s,N=(b*s+C)*h;for(let $=0;$<h;++$){let M=$+N+p*(S+u*(A+l*y));m[g++]=f[M]}}}return a.makeTensorInfo([o,c,d,h],r.dtype,m)}var uz={kernelName:di,backendName:"cpu",kernelFunc:lz};function z7(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l,dimRoundingMode:u}=n;Ae([r,s],"depthwiseConv2DNative");let p=v.computeStrides(r.shape),c=v.computeStrides(s.shape),d=l;d==null&&(d=[1,1]),v.assert(T.eitherStridesOrDilationsAreOne(i,d),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${d}'`);let h=T.computeConv2DInfo(r.shape,s.shape,i,d,o,u,!0),{filterHeight:f,filterWidth:m,dilationHeight:g,dilationWidth:y,padInfo:x}=h,A=x.left,b=x.top,k=h.outChannels/h.inChannels,S=new jt(h.outShape,r.dtype),C=a.data.get(r.dataId).values,N=a.data.get(s.dataId).values,$=S.values;for(let M=0;M<h.batchSize;++M){let R=M*p[0],I=M*S.strides[0];for(let _=0;_<h.outHeight;++_){let D=I+_*S.strides[1],W=_*h.strideHeight-b;for(let P=0;P<f;++P){let U=W+P*g;if(U<0||U>=h.inHeight)continue;let G=P*c[0],q=R+U*p[1];for(let H=0;H<h.outWidth;++H){let B=D+H*S.strides[2],Z=H*h.strideWidth-A;for(let X=0;X<m;++X){let re=Z+X*y;if(re<0||re>=h.inWidth)continue;let ee=G+X*c[1],ce=q+re*h.inChannels,ie=B,ge=ee;for(let Se=0;Se<h.inChannels;++Se){let Ne=C[ce+Se];for(let Be=0;Be<k;++Be)$[ie+Be]+=Ne*N[ge+Be];ie+=k,ge+=k}}}}}}return a.makeTensorInfo(S.shape,S.dtype,S.values)}var dz={kernelName:pi,backendName:"cpu",kernelFunc:z7};function pz(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;Ae([r,s],"depthwiseConv2dNativeBackpropFilter");let c=T.computeConv2DInfo(r.shape,p,i,o,l,u,!0),{strideHeight:d,strideWidth:h,filterHeight:f,filterWidth:m}=c,g=new jt(c.filterShape,"float32"),y=c.padInfo.left,x=c.padInfo.top,A=c.outChannels/c.inChannels,b=a.data.get(r.dataId).values,k=new jt(r.shape,r.dtype,b),S=a.data.get(s.dataId).values,C=new jt(s.shape,s.dtype,S);for(let N=0;N<f;++N){let $=Math.max(0,Math.ceil((x-N)/d)),M=Math.min(c.outHeight,(c.inHeight+x-N)/d);for(let R=0;R<m;++R){let I=Math.max(0,Math.ceil((y-R)/h)),_=Math.min(c.outWidth,(c.inWidth+y-R)/h);for(let D=0;D<c.outChannels;++D){let W=Math.trunc(D/A),P=D%A,U=0;for(let G=0;G<c.batchSize;++G)for(let q=$;q<M;++q){let H=N+q*d-x;for(let B=I;B<_;++B){let Z=R+B*h-y;U+=k.get(G,H,Z,W)*C.get(G,q,B,D)}}g.set(U,N,R,W,P)}}}return a.makeTensorInfo(g.shape,g.dtype,g.values)}var cz={kernelName:eh,backendName:"cpu",kernelFunc:pz};function hz(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;Ae([r,s],"depthwiseConv2DNativeBackpropInput");let c=v.computeStrides(r.shape),d=v.computeStrides(s.shape),h=T.computeConv2DInfo(p,s.shape,i,o,l,u,!0),f=new jt(h.inShape,"float32"),m=f.values,[g,y,x]=f.strides,A=a.data.get(r.dataId).values,[b,k,S]=c,C=a.data.get(s.dataId).values,[N,$,M]=d,{batchSize:R,filterHeight:I,filterWidth:_,inChannels:D,inHeight:W,inWidth:P,outChannels:U,outHeight:G,outWidth:q,strideHeight:H,strideWidth:B}=h,Z=I-1-h.padInfo.top,X=_-1-h.padInfo.left,re=U/D;for(let ee=0;ee<R;++ee)for(let ce=0;ce<D;++ce)for(let ie=0;ie<W;++ie){let ge=ie-Z,Se=Math.max(0,Math.ceil(ge/H)),Ne=Math.min(G,(I+ge)/H);for(let Be=0;Be<P;++Be){let qe=Be-X,dt=Math.max(0,Math.ceil(qe/B)),it=Math.min(q,(_+qe)/B),at=0;for(let nt=Se;nt<Ne;++nt){let Ge=nt*H-ge;for(let ht=dt;ht<it;++ht){let Ga=ht*B-qe,Ot=b*ee+k*nt+S*ht,ln=N*(I-1-Ge)+$*(_-1-Ga)+M*ce;for(let ra=0;ra<re;++ra){let _a=ce*re+ra,un=A[Ot+_a],Pa=C[ln+ra];at+=un*Pa}}}m[g*ee+y*ie+x*Be+ce]=at}}return a.makeTensorInfo(f.shape,f.dtype,f.values)}var fz={kernelName:th,backendName:"cpu",kernelFunc:hz};function mz(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 gz={kernelName:Ed,backendName:"cpu",kernelFunc:mz},yz={kernelName:Rd,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:f,inWidth:m,inChannels:g,outHeight:y,outWidth:x,padInfo:A,strideHeight:b,strideWidth:k,filterHeight:S,filterWidth:C,dilationHeight:N,dilationWidth:$,outShape:M}=T.computeDilation2DInfo(n.shape,r.shape,s,i,"NHWC",o),R=v.sizeFromShape(M),I=M.length,_=v.getArrayFromDType(n.dtype,R);for(let D=0;D<h;++D)for(let W=0;W<y;++W){let P=W*b-A.top;for(let U=0;U<x;++U){let G=U*k-A.left;for(let q=0;q<g;++q){let H=Number.MIN_SAFE_INTEGER;for(let Z=0;Z<S;++Z){let X=P+Z*N;if(X>=0&&X<f)for(let re=0;re<C;++re){let ee=G+re*$;if(ee>=0&&ee<m){let ce=v.locToIndex([D,X,ee,q],p,v.computeStrides(n.shape)),ie=v.locToIndex([Z,re,q],d,v.computeStrides(r.shape)),ge=u[ce]+c[ie];ge>H&&(H=ge)}}}let B=v.locToIndex([D,W,U,q],I,v.computeStrides(M));_[B]=H}}}return{dataId:l.write(v.toTypedArray(_,n.dtype),M,n.dtype),shape:M,dtype:n.dtype}}},xz={kernelName:Bm,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:f,inChannels:m,outHeight:g,outWidth:y,padInfo:x,strideHeight:A,strideWidth:b,filterHeight:k,filterWidth:S,dilationHeight:C,dilationWidth:N,outShape:$}=T.computeDilation2DInfo(n.shape,r.shape,i,o,"NHWC",l);v.assert(s.rank===$.length,()=>`Error in ${Bm}, dy must have the same rank as output ${$.length}, but got ${s.rank}`);let M=v.toNestedArray($,u.data.get(s.dataId).values),R=v.makeZerosNestedTypedArray(r.shape,r.dtype);for(let I=0;I<d;++I)for(let _=0;_<g;++_){let D=_*A-x.top;for(let W=0;W<y;++W){let P=W*b-x.left;for(let U=0;U<m;++U){let G=Number.MIN_SAFE_INTEGER,q=0,H=0;for(let B=0;B<k;++B){let Z=D+B*C;if(Z>=0&&Z<h)for(let X=0;X<S;++X){let re=P+X*N;if(re>=0&&re<f){let ee=p[I][Z][re][U]+c[B][X][U];ee>G&&(G=ee,q=B,H=X)}}}R[q][H][U]+=M[I][_][W][U]}}}return{dataId:u.write(v.toTypedArray(R,n.dtype),r.shape,r.dtype),shape:r.shape,dtype:r.dtype}}},Az={kernelName:Lm,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:f,inChannels:m,outHeight:g,outWidth:y,padInfo:x,strideHeight:A,strideWidth:b,filterHeight:k,filterWidth:S,dilationHeight:C,dilationWidth:N,outShape:$}=T.computeDilation2DInfo(n.shape,r.shape,i,o,"NHWC",l);v.assert(s.rank===$.length,()=>`Error in ${Lm}, dy must have the same rank as output ${$.length}, but got ${s.rank}`);let M=v.toNestedArray($,u.data.get(s.dataId).values),R=v.makeZerosNestedTypedArray(n.shape,n.dtype);for(let I=0;I<d;++I)for(let _=0;_<g;++_){let D=_*A-x.top;for(let W=0;W<y;++W){let P=W*b-x.left;for(let U=0;U<m;++U){let G=Number.MIN_SAFE_INTEGER,q=D<0?0:D,H=P<0?0:P;for(let B=0;B<k;++B){let Z=D+B*C;if(Z>=0&&Z<h)for(let X=0;X<S;++X){let re=P+X*N;if(re>=0&&re<f){let ee=p[I][Z][re][U]+c[B][X][U];ee>G&&(G=ee,q=Z,H=re)}}}R[I][q][H][U]+=M[I][_][W][U]}}}return{dataId:u.write(v.toTypedArray(R,n.dtype),n.shape,n.dtype),shape:n.shape,dtype:n.dtype}}};function dp(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;Ae(r,"sum");let o;r.dtype==="bool"?o=Jr({inputs:{x:r},backend:a,attrs:{dtype:"int32"}}):o=er({inputs:{x:r},backend:a});let l=o.shape.length,u=v.parseAxisParam(s,o.shape),p=T.getAxesPermutation(u,l),c=u,d=o;p!=null&&(d=Ba({inputs:{x:o},backend:a,attrs:{perm:p}}),c=T.getInnerMostAxes(c.length,l)),T.assertAxesAreInnerMostDims("sum",c,d.shape.length);let[h,f]=T.computeOutAndReduceShapes(d.shape,c),m=T.upcastType(d.dtype,"int32"),g=Pc(a,h,m),y=v.sizeFromShape(f),x=a.data.get(g.dataId).values,A=a.data.get(d.dataId).values;for(let b=0;b<x.length;++b){let k=b*y,S=0;for(let C=0;C<y;++C)S+=A[k+C];x[b]=S}if(i){let b=T.expandShapeToKeepDim(g.shape,u),k=g;g=mt({inputs:{x:g},backend:a,attrs:{shape:b}}),a.disposeIntermediateTensorInfo(k)}return a.disposeIntermediateTensorInfo(o),p!=null&&a.disposeIntermediateTensorInfo(d),g}var bz={kernelName:io,backendName:"cpu",kernelFunc:dp};function vz(e){let{inputs:t,backend:a,attrs:n}=e,{equation:r}=n,s=t,{allDims:i,summedDims:o,idDims:l}=T.decodeEinsumEquation(r,s.length);T.checkEinsumDimSizes(i.length,l,s);let{path:u,steps:p}=T.getEinsumComputePath(o,l),c=p.length,d=null,h=i.length,f=[];for(let m=0;m<c;++m){for(let g of p[m]){let{permutationIndices:y,expandDims:x}=T.getEinsumPermutation(h,l[g]),A;T.isIdentityPermutation(y)?A=s[g]:(A=Ba({inputs:{x:s[g]},backend:a,attrs:{perm:y}}),f.push(A));let b=A.shape.slice();for(let k=0;k<x.length;++k)b.splice(x[k],0,1);v.arraysEqual(A.shape,b)||(A=mt({inputs:{x:A},backend:a,attrs:{shape:b}}),f.push(A)),d===null?d=A:(d=Nh({inputs:{a:A,b:d},backend:a}),f.push(d))}m<c-1&&(u[m]>=0&&(d=dp({inputs:{x:d},backend:a,attrs:{axis:u[m]-(i.length-h),keepDims:!1}}),f.push(d)),h--)}for(let m of f)m!==d&&a.disposeIntermediateTensorInfo(m);return d}var kz={kernelName:Md,backendName:"cpu",kernelFunc:vz};function wz(e){let{inputs:t,backend:a}=e,{dy:n,y:r}=t;Ae([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>=1?s[l]=o[l]:s[l]=o[l]*(u+1)}return a.makeTensorInfo(r.shape,"float32",s)}var Iz={kernelName:W2,backendName:"cpu",kernelFunc:wz},Sz=T.ERF_P,Tz=T.ERF_A1,Cz=T.ERF_A2,Nz=T.ERF_A3,Ez=T.ERF_A4,Rz=T.ERF_A5,Mz=lt(Ml,e=>{let t=Math.sign(e),a=Math.abs(e),n=1/(1+Sz*a);return t*(1-((((Rz*n+Ez)*n+Nz)*n+Cz)*n+Tz)*n*Math.exp(-a*a))}),$z={kernelName:Ml,backendName:"cpu",kernelFunc:Mz};function Dc(e){let{inputs:t,backend:a,attrs:n}=e,{input:r}=t,{dim:s}=n,i=r.shape.length,o=r.shape.slice(),l=s;return s<0&&(v.assert(-(i+1)<=s,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+s+1),o.splice(l,0,1),mt({inputs:{x:r},backend:a,attrs:{shape:o}})}var _z={kernelName:$l,backendName:"cpu",kernelFunc:Dc},Pz=Lt((e,t)=>e/t),x3=Yt(ci,Pz),g2={kernelName:ci,backendName:"cpu",kernelFunc:x3};function L7(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=Gs({inputs:{x:o},backend:a,attrs:{begin:[g,0],size:[1,s]}}),x=Gs({inputs:{x:l},backend:a,attrs:{begin:[g,0],size:[1,s]}}),A=Za({inputs:{real:y,imag:x},backend:a}),{real:b,imag:k}=Fz(A,t,a),S=T.mergeRealAndImagArrays(b,k);for(let C=0;C<s;C++){let N=T.getComplexWithIndex(S,C);c[g*s+C]=N.real,d[g*s+C]=N.imag}a.disposeIntermediateTensorInfo(y),a.disposeIntermediateTensorInfo(x),a.disposeIntermediateTensorInfo(A)}let h=a.makeTensorInfo(u,"float32",c),f=a.makeTensorInfo(u,"float32",d),m=Za({inputs:{real:h,imag:f},backend:a});return a.disposeIntermediateTensorInfo(h),a.disposeIntermediateTensorInfo(f),m}function Fz(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(Oz(n)){let o=y2(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=er({inputs:{x:c},backend:a}),h=g2.kernelFunc({inputs:{a:u,b:c},backend:a}),f=g2.kernelFunc({inputs:{a:p,b:d},backend:a}),m=a.data.get(h.dataId).values,g=a.data.get(f.dataId).values;return a.disposeIntermediateTensorInfo(u),a.disposeIntermediateTensorInfo(p),a.disposeIntermediateTensorInfo(c),a.disposeIntermediateTensorInfo(d),a.disposeIntermediateTensorInfo(h),a.disposeIntermediateTensorInfo(f),{real:m,imag:g}}return o}else{let o=T.mergeRealAndImagArrays(s,i),l=Dz(o,n,t);return T.splitRealAndImagArrays(l)}}function Oz(e){return(e&e-1)===0}function y2(e,t,a,n,r){if(a===1)return{real:e,imag:t};let s=T.mergeRealAndImagArrays(e,t),i=a/2,o=T.complexWithEvenIndex(s),l=o.real,u=o.imag,p=[l.length],c=r.makeTensorInfo(p,"float32",l),d=r.makeTensorInfo(p,"float32",u),h=Za({inputs:{real:c,imag:d},backend:r}),f=T.complexWithOddIndex(s),m=f.real,g=f.imag,y=[m.length],x=r.makeTensorInfo(y,"float32",m),A=r.makeTensorInfo(y,"float32",g),b=Za({inputs:{real:x,imag:A},backend:r}),k=y2(l,u,i,n,r),S=k.real,C=k.imag,N=[S.length],$=r.makeTensorInfo(N,"float32",S),M=r.makeTensorInfo(N,"float32",C),R=Za({inputs:{real:$,imag:M},backend:r}),I=y2(m,g,i,n,r),_=I.real,D=I.imag,W=[_.length],P=r.makeTensorInfo(W,"float32",_),U=r.makeTensorInfo(W,"float32",D),G=Za({inputs:{real:P,imag:U},backend:r}),q=T.exponents(a,n),H=[q.real.length],B=r.makeTensorInfo(H,"float32",q.real),Z=r.makeTensorInfo(H,"float32",q.imag),X=Za({inputs:{real:B,imag:Z},backend:r}),re=Nh({inputs:{a:X,b:G},backend:r}),ee=fl({inputs:{a:R,b:re},backend:r}),ce=g3({inputs:{a:R,b:re},backend:r}),ie=Us({inputs:{input:ee},backend:r}),ge=Us({inputs:{input:ce},backend:r}),Se=ml({inputs:{input:ee},backend:r}),Ne=ml({inputs:{input:ce},backend:r}),Be=gl({inputs:[ie,ge],backend:r,attrs:{axis:0}}),qe=gl({inputs:[Se,Ne],backend:r,attrs:{axis:0}}),dt=r.data.get(Be.dataId).values,it=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($),r.disposeIntermediateTensorInfo(M),r.disposeIntermediateTensorInfo(R),r.disposeIntermediateTensorInfo(P),r.disposeIntermediateTensorInfo(U),r.disposeIntermediateTensorInfo(G),r.disposeIntermediateTensorInfo(B),r.disposeIntermediateTensorInfo(Z),r.disposeIntermediateTensorInfo(X),r.disposeIntermediateTensorInfo(re),r.disposeIntermediateTensorInfo(ee),r.disposeIntermediateTensorInfo(ce),r.disposeIntermediateTensorInfo(ie),r.disposeIntermediateTensorInfo(Se),r.disposeIntermediateTensorInfo(ge),r.disposeIntermediateTensorInfo(Ne),r.disposeIntermediateTensorInfo(Be),r.disposeIntermediateTensorInfo(qe),{real:dt,imag:it}}function Dz(e,t,a){let n=new Float32Array(t*2);for(let r=0;r<t;r++){let s=0,i=0;for(let o=0;o<t;o++){let l=T.exponent(r*o,t,a),u=T.getComplexWithIndex(e,o);s+=u.real*l.real-u.imag*l.imag,i+=u.real*l.imag+u.imag*l.real}a&&(s/=t,i/=t),T.assignToTypedArray(n,s,i,r)}return n}function zz(e){let{inputs:t,backend:a}=e,{input:n}=t,r=v.sizeFromShape(n.shape),s=n.shape[n.shape.length-1],i=r/s,o=mt({inputs:{x:n},backend:a,attrs:{shape:[i,s]}}),l=L7(o,!1,a),u=mt({inputs:{x:l},backend:a,attrs:{shape:n.shape}});return a.disposeIntermediateTensorInfo(o),a.disposeIntermediateTensorInfo(l),u}var Lz={kernelName:$d,backendName:"cpu",kernelFunc:zz};function A3(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 Wz(o,r,i),t.makeTensorInfo(n,i,o)}var Bz={kernelName:Pl,backendName:"cpu",kernelFunc:A3};function Wz(e,t,a){e.fill(t)}var Vz={kernelName:gi,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 f=h*(l*u);for(let m=0;m<l;m++){let g=m*u;for(let y=0;y<u;y++){let x=Math.round(l-m-1),A=d+f+g+y,b=p[A];if(x>=0&&x<l){let k=x*u,S=d+f+k+y;b=p[S]}s[A]=b}}}}return{dataId:r.write(s,n.shape,n.dtype),shape:n.shape,dtype:n.dtype}}},Uz=Lt((e,t)=>Math.floor(e/t)),Gz=Yt(xi,Uz,null,"int32"),Hz={kernelName:xi,backendName:"cpu",kernelFunc:Gz};function jz(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:f}=n,m=D7({inputs:{x:r,filter:s},backend:a,attrs:{strides:l,pad:u,dataFormat:p,dilations:c,dimRoundingMode:d}});if(i){let g=m;if(p==="NCHW"&&i.shape.length===1&&i.shape[0]!==1){let y=mt({inputs:{x:i},backend:a,attrs:{shape:[i.shape[0],1,1]}});m=fl({inputs:{a:m,b:y},backend:a}),a.disposeIntermediateTensorInfo(y)}else m=fl({inputs:{a:m,b:i},backend:a});a.disposeIntermediateTensorInfo(g)}if(h){let g=m;if(p==="NCHW"&&h==="prelu"&&o.shape.length===1&&o.shape[0]!==1){let y=mt({inputs:{x:o},backend:a,attrs:{shape:[o.shape[0],1,1]}});m=Oc(a,m,h,y,f),a.disposeIntermediateTensorInfo(y)}else m=Oc(a,m,h,o,f);a.disposeIntermediateTensorInfo(g)}return m}var qz={kernelName:jr,backendName:"cpu",kernelFunc:jz};function Xz(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:f}=n,m=z7({inputs:{x:r,filter:s},backend:a,attrs:{strides:l,pad:u,dataFormat:p,dilations:c,dimRoundingMode:d}});if(i){let g=m;m=fl({inputs:{a:m,b:i},backend:a}),a.disposeIntermediateTensorInfo(g)}if(h){let g=m;m=Oc(a,m,h,o,f),a.disposeIntermediateTensorInfo(g)}return m}var Kz={kernelName:qr,backendName:"cpu",kernelFunc:Xz};function Zz(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]=T.prepareAndValidate(n,r);if(u===0)return a.makeTensorInfo(l,n.dtype,[]);let d=a.data.get(r.dataId).values,h=a.bufferSync(n),f=t7(d,h,n.dtype,u,o,p,c,n.shape,s);return a.makeTensorInfo(l,n.dtype,f.values)}var Yz={kernelName:bi,backendName:"cpu",kernelFunc:Zz};function Jz(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,indices:s}=t,{axis:i,batchDims:o}=n;Ae([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 k=u[b];v.assert(k<=p-1&&k>=0,()=>`GatherV2: the index value ${k} is not in [0, ${p-1}]`)}let c=o;o==null&&(c=0);let d=v.sizeFromShape(s.shape),h=T.segment_util.collectGatherOpShapeInfo(r,s,l,c),f=mt({inputs:{x:r},backend:a,attrs:{shape:[h.batchSize,h.outerSize,h.dimSize,h.sliceSize]}}),m=mt({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(m),x=a.bufferSync(f),A=a7(x,y,g);return a.disposeIntermediateTensorInfo(f),a.disposeIntermediateTensorInfo(m),a.makeTensorInfo(h.outputShape,A.dtype,A.values)}var Qz={kernelName:Fl,backendName:"cpu",kernelFunc:Jz};function eL(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=mt({inputs:{x:n},backend:a,attrs:{shape:[i,s]}}),l=L7(o,!0,a),u=mt({inputs:{x:l},backend:a,attrs:{shape:n.shape}});return a.disposeIntermediateTensorInfo(o),a.disposeIntermediateTensorInfo(l),u}var tL={kernelName:_d,backendName:"cpu",kernelFunc:eL},aL=lt(Ol,e=>Number.isFinite(e)?1:0,"bool"),nL={kernelName:Ol,backendName:"cpu",kernelFunc:aL},rL=lt(Dl,e=>Math.abs(e)===1/0?1:0,"bool"),sL={kernelName:Dl,backendName:"cpu",kernelFunc:rL},iL=lt(Ii,e=>Number.isNaN(e)?1:0,"bool"),oL={kernelName:Ii,backendName:"cpu",kernelFunc:iL};function lL(e){let{backend:t,attrs:a}=e,{start:n,stop:r,num:s}=a,i=o7(n,r,s);return t.makeTensorInfo([i.length],"float32",i)}var uL={kernelName:Fd,backendName:"cpu",kernelFunc:lL},dL=lt(zl,e=>Math.log1p(e)),pL={kernelName:zl,backendName:"cpu",kernelFunc:dL},cL=Lt((e,t)=>e&&t),hL=Yt(Ei,cL,null,"bool"),fL={kernelName:Ei,backendName:"cpu",kernelFunc:hL},mL=lt(Ri,e=>e?0:1,"bool"),gL={kernelName:Ri,backendName:"cpu",kernelFunc:mL},yL=Lt((e,t)=>e||t),xL=Yt(Mi,yL,null,"bool"),AL={kernelName:Mi,backendName:"cpu",kernelFunc:xL};function bL(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=n;Ae(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 f(m){let g=m%u,y=m-g+Math.max(0,g-s),x=m-g+Math.min(g+s,p),A=0;for(;y<=x;y++){let b=c[y];A+=b*b}return A}for(let m=0;m<d;m++){let g=f(m),y=c[m]*Math.pow(i+o*g,-l);h[m]=y}return a.makeTensorInfo(r.shape,r.dtype,h)}var vL={kernelName:Od,backendName:"cpu",kernelFunc:bL};function kL(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;Ae(i,"LRNGrad");let c=v.sizeFromShape(i.shape),d=i.shape[3],h=a.data.get(i.dataId).values,f=a.data.get(r.dataId).values,m=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),k=x-A+Math.min(d,A+o+1),S=0;for(let C=b;C<k;C++)S+=Math.pow(f[C],2);S=u*S+l;for(let C=b;C<k;C++){let N=-2*u*p*f[C]*m[x]/S;x===C&&(N+=Math.pow(S,-p)),N*=h[x],g[C]+=N}}return a.makeTensorInfo(i.shape,r.dtype,g)}var wL={kernelName:V2,backendName:"cpu",kernelFunc:kL};function B7(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=T.getAxesPermutation(c,u),h=o.data.get(r.dataId).values;if(d!=null){let b=new Array(u);for(let k=0;k<b.length;k++)b[k]=l[d[k]];h=d3(h,l,r.dtype,d,b),c=T.getInnerMostAxes(c.length,u),l=b}Ae(r,"max"),T.assertAxesAreInnerMostDims("max",c,u);let[f,m]=T.computeOutAndReduceShapes(l,c),g=v.sizeFromShape(m),y=u7(h,g,f,r.dtype),x=o.write(y,f,r.dtype),A=f;return i&&(A=T.expandShapeToKeepDim(f,p)),{dataId:x,shape:A,dtype:r.dtype}}var IL={kernelName:$i,backendName:"cpu",kernelFunc:B7};function SL(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t;Ae(r,"maxPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=n,u=1;v.assert(T.eitherStridesOrDilationsAreOne(i,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let p=T.computePool2DInfo(r.shape,s,i,u,o,l),c;if(p.filterWidth===1&&p.filterHeight===1&&v.arraysEqual(p.inShape,p.outShape))c=er({inputs:{x:r},backend:a});else{let d=a.data.get(r.dataId).values,h=v.computeStrides(r.shape),f=y3(d,r.shape,r.dtype,h,p,"max");c=a.makeTensorInfo(p.outShape,r.dtype,f.values)}return c}var TL={kernelName:Pi,backendName:"cpu",kernelFunc:SL};function CL(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:u}=n;Ae(r,"maxPool3d");let p=T.computePool3DInfo(r.shape,s,i,1,o,l,u),c=a.data.get(r.dataId).values,d=O7(c,r.shape,r.dtype,v.computeStrides(r.shape),p,"max");return a.makeTensorInfo(d.shape,"float32",d.values)}var NL={kernelName:ah,backendName:"cpu",kernelFunc:CL};function EL(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=n;Ae([r,s],"maxPool3DGrad");let p=T.computePool3DInfo(s.shape,i,o,1,l,u),c=a.bufferSync(s),d=gD(c,p),h=p.strideDepth,f=p.strideHeight,m=p.strideWidth,g=p.dilationDepth,y=p.dilationHeight,x=p.dilationWidth,A=p.effectiveFilterDepth,b=p.effectiveFilterHeight,k=p.effectiveFilterWidth,S=A-1-p.padInfo.front,C=k-1-p.padInfo.left,N=b-1-p.padInfo.top,$=_e(s.shape,"float32"),M=a.bufferSync(r);for(let R=0;R<p.batchSize;++R)for(let I=0;I<p.inChannels;++I)for(let _=0;_<p.inDepth;++_)for(let D=0;D<p.inHeight;++D)for(let W=0;W<p.inWidth;++W){let P=_-S,U=D-N,G=W-C,q=0;for(let H=0;H<A;H+=g){let B=(P+H)/h;if(!(B<0||B>=p.outDepth||Math.floor(B)!==B))for(let Z=0;Z<b;Z+=y){let X=(U+Z)/f;if(!(X<0||X>=p.outHeight||Math.floor(X)!==X))for(let re=0;re<k;re+=x){let ee=(G+re)/m;if(ee<0||ee>=p.outWidth||Math.floor(ee)!==ee)continue;let ce=A*b*k-1-d.get(R,B,X,ee,I),ie=H*b*k+Z*k+re,ge=ce===ie?1:0;if(ge===0)continue;let Se=M.get(R,B,X,ee,I);q+=Se*ge}}}$.set(q,R,_,D,W,I)}return a.makeTensorInfo($.shape,$.dtype,$.values)}var RL={kernelName:G2,backendName:"cpu",kernelFunc:EL};function ML(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s,output:i}=t,o=s;Ae([s,i],"maxPoolGrad");let{filterSize:l,strides:u,pad:p,dimRoundingMode:c}=n,d=T.computePool2DInfo(o.shape,l,u,1,p,c),h=a.data.get(o.dataId).values,f=_e(d.outShape,o.dtype,F7(h,o.shape,o.dtype,d).values),m=d.strideHeight,g=d.strideWidth,y=d.dilationHeight,x=d.dilationWidth,A=d.effectiveFilterHeight,b=d.effectiveFilterWidth,k=b-1-d.padInfo.left,S=A-1-d.padInfo.top,C=_e(o.shape,"float32"),N=a.data.get(r.dataId).values,$=_e(r.shape,"float32",N);for(let M=0;M<d.batchSize;++M)for(let R=0;R<d.inChannels;++R)for(let I=0;I<d.inHeight;++I)for(let _=0;_<d.inWidth;++_){let D=I-S,W=_-k,P=0;for(let U=0;U<A;U+=y){let G=(D+U)/m;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 B=A*b-1-f.get(M,G,H,R),Z=U*b+q,X=B===Z?1:0;if(X===0)continue;let re=$.get(M,G,H,R);P+=re*X}}C.set(P,M,I,_,R)}return a.makeTensorInfo(C.shape,C.dtype,C.values)}var $L={kernelName:U2,backendName:"cpu",kernelFunc:ML};function _L(e,t,a,n,r){let s=v.computeStrides(t),i=y3(e,t,a,s,r,"max"),o=F7(e,t,a,r,!0,n);return[i.values,o.values]}var PL={kernelName:nh,backendName:"cpu",kernelFunc:({inputs:e,attrs:t,backend:a})=>{let{x:n}=e,{filterSize:r,strides:s,pad:i,includeBatchInIndex:o}=t,l=a;Ae(n,"MaxPoolWithArgmax");let u=l.data.get(n.dataId).values,p=T.computePool2DInfo(n.shape,r,s,[1,1],i),[c,d]=_L(u,n.shape,n.dtype,o,p),h=l.write(c,p.outShape,n.dtype),f=l.write(d,p.outShape,n.dtype);return[{dataId:h,shape:p.outShape,dtype:n.dtype},{dataId:f,shape:p.outShape,dtype:"int32"}]}};function FL(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n,o=v.parseAxisParam(s,r.shape),l=T.computeOutAndReduceShapes(r.shape,o)[1],u=v.sizeFromShape(l),p=[],c=a.makeTensorInfo([],"float32",new Float32Array([u]));p.push(c);let d=Jr({inputs:{x:r},backend:a,attrs:{dtype:"float32"}});p.push(d);let h=x3({inputs:{a:d,b:c},backend:a});p.push(h);let f=dp({inputs:{x:h},backend:a,attrs:{axis:s,keepDims:i}});return p.forEach(m=>a.disposeIntermediateTensorInfo(m)),f}var OL={kernelName:Fi,backendName:"cpu",kernelFunc:FL};function DL(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;Ae(r,"min");let o=v.parseAxisParam(s,r.shape),l=o,u=T.getAxesPermutation(l,r.shape.length),p=r;u!=null&&(p=Ba({inputs:{x:r},backend:a,attrs:{perm:u}}),l=T.getInnerMostAxes(l.length,r.shape.length)),T.assertAxesAreInnerMostDims("min",l,p.shape.length);let[c,d]=T.computeOutAndReduceShapes(p.shape,l),h=v.sizeFromShape(d),f=v.makeZerosTypedArray(v.sizeFromShape(c),p.dtype),m=a.data.get(p.dataId).values;for(let y=0;y<f.length;++y){let x=y*h,A=m[x];for(let b=0;b<h;++b){let k=m[x+b];(Number.isNaN(k)||k<A)&&(A=k)}f[y]=A}u!=null&&a.disposeIntermediateTensorInfo(p);let g=a.makeTensorInfo(c,p.dtype,f);if(i){let y=T.expandShapeToKeepDim(c,o),x=mt({inputs:{x:g},backend:a,attrs:{shape:y}});return a.disposeIntermediateTensorInfo(g),x}return g}var zL={kernelName:Oi,backendName:"cpu",kernelFunc:DL};function LL(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{paddings:s,mode:i}=n;Ae(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),f=v.sizeFromShape(o),m=o.length,g=v.computeStrides(o),y=v.getTypedArrayFromDType(r.dtype,f);for(let x=0;x<f;x++){let A=v.indexToLoc(x,m,g);for(let k=0;k<m;k++)A[k]<l[k]?A[k]=l[k]*2-A[k]-p:A[k]>=u[k]&&(A[k]=(u[k]-1)*2-A[k]+p);A=A.map((k,S)=>k-l[S]);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 BL={kernelName:zi,backendName:"cpu",kernelFunc:LL},WL=Lt((e,t)=>{let a=e%t;return e<0&&t<0||e>=0&&t>=0?a:(a+t)%t}),VL=Yt(Ll,WL),UL={kernelName:Ll,backendName:"cpu",kernelFunc:VL},GL=xl(Qy());function W7(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=B7({inputs:{x:r},backend:a,attrs:{reductionIndices:l,keepDims:!1}}),p=T.expandShapeToKeepDim(u.shape,l),c=mt({inputs:{x:u},backend:a,attrs:{shape:p}}),d=g3({inputs:{a:r,b:c},backend:a}),h=J4({inputs:{x:d},backend:a}),f=dp({inputs:{x:h},backend:a,attrs:{axis:l,keepDims:!1}}),m=mt({inputs:{x:f},backend:a,attrs:{shape:p}}),g=x3({inputs:{a:h,b:m},backend:a});return a.disposeIntermediateTensorInfo(u),a.disposeIntermediateTensorInfo(c),a.disposeIntermediateTensorInfo(d),a.disposeIntermediateTensorInfo(h),a.disposeIntermediateTensorInfo(f),a.disposeIntermediateTensorInfo(m),g}var HL={kernelName:oo,backendName:"cpu",kernelFunc:W7};function jL(e){let{inputs:t,backend:a,attrs:n}=e,{logits:r}=t,{numSamples:s,seed:i,normalized:o}=n;Ae(r,"multinomial");let l=o?r:W7({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 f=0;f<u;++f){let m=f*p,g=new Float32Array(p-1);g[0]=c[m];for(let A=1;A<g.length;++A)g[A]=g[A-1]+c[m+A];let y=GL.alea(i.toString()),x=f*s;for(let A=0;A<s;++A){let b=y();h[x+A]=g.length;for(let k=0;k<g.length;k++)if(b<g[k]){h[x+A]=k;break}}}return o||a.disposeIntermediateTensorInfo(l),a.makeTensorInfo(d,"int32",h)}var qL={kernelName:rh,backendName:"cpu",kernelFunc:jL},XL=Nn.nonMaxSuppressionV3Impl;function KL(e){let{inputs:t,backend:a,attrs:n}=e,{boxes:r,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l}=n;Ae(r,"NonMaxSuppression");let u=a.data.get(r.dataId).values,p=a.data.get(s.dataId).values,{selectedIndices:c}=XL(u,p,i,o,l);return a.makeTensorInfo([c.length],"int32",new Int32Array(c))}var ZL={kernelName:Wi,backendName:"cpu",kernelFunc:KL},YL=Nn.nonMaxSuppressionV4Impl;function JL(e){let{inputs:t,backend:a,attrs:n}=e,{boxes:r,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,padToMaxOutputSize:u}=n;Ae(r,"NonMaxSuppressionPadded");let p=a.data.get(r.dataId).values,c=a.data.get(s.dataId).values,{selectedIndices:d,validOutputs:h}=YL(p,c,i,o,l,u);return[a.makeTensorInfo([d.length],"int32",new Int32Array(d)),a.makeTensorInfo([],"int32",new Int32Array([h]))]}var QL={kernelName:Wl,backendName:"cpu",kernelFunc:JL},eB=Nn.nonMaxSuppressionV5Impl;function tB(e){let{inputs:t,backend:a,attrs:n}=e,{boxes:r,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,softNmsSigma:u}=n;Ae(r,"NonMaxSuppressionWithScore");let p=a.data.get(r.dataId).values,c=a.data.get(s.dataId).values,d=i,h=o,f=l,m=u,{selectedIndices:g,selectedScores:y}=eB(p,c,d,h,f,m);return[a.makeTensorInfo([g.length],"int32",new Int32Array(g)),a.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var aB={kernelName:Vi,backendName:"cpu",kernelFunc:tB};function nB(e){let{inputs:t,backend:a,attrs:n}=e,{indices:r}=t,{dtype:s,depth:i,onValue:o,offValue:l}=n;Ae(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 rB={kernelName:Ui,backendName:"cpu",kernelFunc:nB};function zc(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=Us({inputs:{input:n},backend:a}),s=zc({inputs:{x:r},backend:a}),i=ml({inputs:{input:n},backend:a}),o=zc({inputs:{x:i},backend:a}),l=Za({inputs:{real:s,imag:o},backend:a});return a.disposeIntermediateTensorInfo(r),a.disposeIntermediateTensorInfo(s),a.disposeIntermediateTensorInfo(i),a.disposeIntermediateTensorInfo(o),l}else return A3({backend:a,attrs:{shape:n.shape,value:0,dtype:n.dtype}})}var sB={kernelName:nu,backendName:"cpu",kernelFunc:zc};function V7(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=Us({inputs:{input:n},backend:a}),s=V7({inputs:{x:r},backend:a}),i=ml({inputs:{input:n},backend:a}),o=zc({inputs:{x:i},backend:a}),l=Za({inputs:{real:s,imag:o},backend:a});return a.disposeIntermediateTensorInfo(r),a.disposeIntermediateTensorInfo(s),a.disposeIntermediateTensorInfo(i),a.disposeIntermediateTensorInfo(o),l}else return A3({backend:a,attrs:{shape:n.shape,value:1,dtype:n.dtype}})}var iB={kernelName:Vl,backendName:"cpu",kernelFunc:V7};function U7(e){let{inputs:t,backend:a,attrs:n}=e,{axis:r}=n;if(t.length===1)return Dc({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=Dc({inputs:{input:p},backend:a,attrs:{dim:r}});return o.push(c),c}),u=gl({inputs:l,backend:a,attrs:{axis:r}});return o.forEach(p=>a.disposeIntermediateTensorInfo(p)),u}var oB={kernelName:Ul,backendName:"cpu",kernelFunc:U7};function lB(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{paddings:s,constantValue:i}=n;Ae(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),f=o.length,m=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,k)=>b+l[k]),A=v.locToIndex(x,f,m);g[A]=u[y]}return{dataId:a.write(g,o,r.dtype),shape:o,dtype:r.dtype}}var G7={kernelName:Gi,backendName:"cpu",kernelFunc:lB},uB=Lt((e,t)=>Math.pow(e,t)),dB=Yt(Hi,uB),pB={kernelName:Hi,backendName:"cpu",kernelFunc:dB};function cB(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,f]=m7(l,u,p,s.shape,s.dtype,c,i.shape,o),m=d.map(y=>a.makeTensorInfo([y.length],"int32",y)),g=a.makeTensorInfo(f,s.dtype,h);return m.concat([g])}var hB={kernelName:sh,backendName:"cpu",kernelFunc:cB};function fB(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]=g7(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 mB={kernelName:ih,backendName:"cpu",kernelFunc:fB};function gB(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),[f,m]=y7(u,r.shape,p,s.shape,s.dtype,c,i.shape,d,h,l);return a.makeTensorInfo(f,s.dtype,m)}var yB={kernelName:oh,backendName:"cpu",kernelFunc:gB};function xB(e){let{backend:t,attrs:a}=e,{start:n,stop:r,dtype:s,step:i}=a,o=p3(n,r,i,s);return t.makeTensorInfo([o.length],s,o)}var AB={kernelName:Gl,backendName:"cpu",kernelFunc:xB},bB=lt(Xi,e=>1/e),vB={kernelName:Xi,backendName:"cpu",kernelFunc:bB};function kB(e){let{inputs:t,backend:a,attrs:n}=e,{images:r}=t,{alignCorners:s,halfPixelCenters:i,size:o}=n;Ae(r,"resizeBilinear");let l=v.computeStrides(r.shape),[u,p]=o,[c,d,h,f]=r.shape,m=a.data.get(r.dataId).values,g=new Float32Array(v.sizeFromShape([c,u,p,f])),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],k=y[1]/x[1];for(let S=0;S<c;S++)for(let C=0;C<u;C++){let N;i?N=b*(C+.5)-.5:N=b*C;let $=Math.max(0,Math.floor(N)),M=N-$,R=Math.min(d-1,Math.ceil(N)),I=S*l[0]+$*l[1],_=S*l[0]+R*l[1];for(let D=0;D<p;D++){let W;i?W=k*(D+.5)-.5:W=k*D;let P=Math.max(0,Math.floor(W)),U=W-P,G=Math.min(h-1,Math.ceil(W)),q=I+P*l[2],H=_+P*l[2],B=I+G*l[2],Z=_+G*l[2];for(let X=0;X<f;X++){let re=m[q+X],ee=m[H+X],ce=m[B+X],ie=m[Z+X],ge=re+(ce-re)*U,Se=ee+(ie-ee)*U,Ne=ge+(Se-ge)*M;g[A++]=Ne}}}return a.makeTensorInfo([c,u,p,f],"float32",g)}var wB={kernelName:Yi,backendName:"cpu",kernelFunc:kB};function IB(e){let{inputs:t,backend:a,attrs:n}=e,{images:r,dy:s}=t,{alignCorners:i}=n;Ae([s,r],"resizeBilinearGrad");let o=v.computeStrides(r.shape),[l,u,p,c]=r.shape,[,d,h]=s.shape,f=new Float32Array(l*u*p*c),m=[i&&d>1?u-1:u,i&&h>1?p-1:p],g=[i&&d>1?d-1:d,i&&h>1?h-1:h],y=m[0]/g[0],x=m[1]/g[1],A=a.data.get(s.dataId).values,b=0;for(let k=0;k<l;k++){let S=k*o[0];for(let C=0;C<d;C++){let N=C*y,$=Math.floor(N),M=Math.min(Math.ceil(N),u-1),R=S+$*o[1],I=S+M*o[1],_=N-$,D=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,B=R+U*o[2],Z=R+G*o[2],X=I+U*o[2],re=I+G*o[2],ee=D*H,ce=D*q,ie=_*H,ge=_*q;for(let Se=0;Se<c;Se++){let Ne=A[b++];f[B+Se]+=Ne*ee,f[Z+Se]+=Ne*ce,f[X+Se]+=Ne*ie,f[re+Se]+=Ne*ge}}}}return a.makeTensorInfo([l,p,u,c],"float32",f)}var SB={kernelName:j2,backendName:"cpu",kernelFunc:IB};function TB(e){let{inputs:t,backend:a,attrs:n}=e,{images:r}=t,{alignCorners:s,halfPixelCenters:i,size:o}=n;Ae(r,"resizeNearestNeighbor");let l=v.computeStrides(r.shape),[u,p]=o,[c,d,h,f]=r.shape,m=a.data.get(r.dataId).values,g=new Float32Array(c*u*p*f),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],k=0;for(let S=0;S<c;S++){let C=S*l[0];for(let N=0;N<u;N++){let $=i?A*(N+.5):A*N,M=Math.min(d-1,s?Math.round($):Math.floor($));i&&(M=Math.max(0,M));let R=C+M*l[1];for(let I=0;I<p;I++){let _=i?b*(I+.5):b*I,D=Math.min(h-1,s?Math.round(_):Math.floor(_));i&&(D=Math.max(0,D));let W=R+D*l[2];for(let P=0;P<f;P++){let U=m[W+P];g[k++]=U}}}}return a.makeTensorInfo([c,u,p,f],r.dtype,g)}var CB={kernelName:Zi,backendName:"cpu",kernelFunc:TB};function NB(e){let{inputs:t,backend:a,attrs:n}=e,{images:r,dy:s}=t,{alignCorners:i}=n;Ae([s,r],"resizeNearestNeighborGrad");let o=v.computeStrides(r.shape),l=v.computeStrides(s.shape),[u,p,c,d]=r.shape,[,h,f]=s.shape,m=new Float32Array(u*p*c*d),g=a.data.get(s.dataId).values,y=[i&&h>1?p-1:p,i&&f>1?c-1:c],x=[i&&h>1?h-1:h,i&&f>1?f-1:f],A=y[0]/x[0],b=y[1]/x[1],k=1/A,S=1/b,C=Math.ceil(k)*2+2,N=Math.ceil(S)*2+2;for(let $=0;$<u;$++){let M=$*o[0];for(let R=0;R<p;R++){let I=M+R*o[1],_=Math.floor(R*k),D=Math.floor(_-C/2);for(let W=0;W<c;W++){let P=I+W*o[2],U=Math.floor(W*S),G=Math.floor(U-N/2);for(let q=0;q<d;q++){let H=0;for(let B=0;B<C;B++){let Z=B+D;if(Z<0||Z>=h)continue;let X=M+Z*l[1],re=Z*A,ee=Math.min(p-1,i?Math.round(re):Math.floor(re));if(R===ee)for(let ce=0;ce<N;ce++){let ie=ce+G;if(ie<0||ie>=f)continue;let ge=X+ie*l[2],Se=ie*b,Ne=Math.min(c-1,i?Math.round(Se):Math.floor(Se));W===Ne&&(H+=g[ge+q])}}m[P+q]=H}}}}return a.makeTensorInfo(r.shape,r.dtype,m)}var EB={kernelName:H2,backendName:"cpu",kernelFunc:NB};function RB(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{dims:s}=n;Ae(r,"reverse");let i=r.shape.length,o=v.parseAxisParam(s,r.shape);if(i===0)return er({inputs:{x:r},backend:a});let l=new jt(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 MB={kernelName:Qi,backendName:"cpu",kernelFunc:RB},$B={kernelName:go,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,f]=T.getImageCenter(i,p,c),m=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 k=0;k<p;k++){let S=k*(c*d);for(let C=0;C<c;C++){let N=C*d;for(let $=0;$<d;$++){let M=[u,k,C,$],R=M[2],I=M[1],_=(R-h)*y-(I-f)*g,D=(R-h)*g+(I-f)*y;_=Math.round(_+h),D=Math.round(D+f);let W=s;if(typeof s!="number"&&($===3?W=m:W=s[$]),_>=0&&_<c&&D>=0&&D<p){let U=D*(c*d),G=_*d,q=b+U+G+$;W=x[q]}let P=b+S+N+$;l[P]=W}}}}return{dataId:o.write(l,n.shape,n.dtype),shape:n.shape,dtype:n.dtype}}},_B=lt(eo,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}),PB={kernelName:eo,backendName:"cpu",kernelFunc:_B};function FB(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}=T.calculateShapes(s,r,i),d=!0,h=a.bufferSync(r),f=a.bufferSync(s),m=el(h,f,i,c,u,l,o,p,0,d);return a.makeTensorInfo(i,m.dtype,m.values)}var OB={kernelName:ao,backendName:"cpu",kernelFunc:FB};function DB(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 zB(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 LB(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"?DB(l,t[p+u]):zB(l,t[p+u])}return i}function BB(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=LB(o,l,r.shape[0],r.shape[1],s.shape[1],i);return a.makeTensorInfo(s.shape,"int32",u)}var WB={kernelName:zd,backendName:"cpu",kernelFunc:BB};function VB(e){let{inputs:t,backend:a}=e,{condition:n,t:r,e:s}=t;Ae([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=fa(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 f=0;f<o.length;f++)for(let m=0;m<h;m++)o[f]===1?c[d++]=l[f]:c[d++]=u[f];return a.makeTensorInfo(r.shape,p,c)}var UB={kernelName:jl,backendName:"cpu",kernelFunc:VB},GB=T.SELU_SCALEALPHA,HB=T.SELU_SCALE,jB=lt(ql,e=>e>=0?HB*e:GB*(Math.exp(e)-1)),qB={kernelName:ql,backendName:"cpu",kernelFunc:jB},XB=lt(Zl,e=>e<0?-1:e>0?1:0),KB={kernelName:Zl,backendName:"cpu",kernelFunc:XB},ZB=lt(no,e=>Math.sin(e)),YB={kernelName:no,backendName:"cpu",kernelFunc:ZB},JB=lt(Kl,e=>Math.sinh(e)),QB={kernelName:Kl,backendName:"cpu",kernelFunc:JB},eW=11920928955078125e-23,oy=Math.log(eW)+2,tW=lt(Yl,e=>{let t=e>-oy,a=e<oy,n=Math.exp(e),r;return a?r=n:t?r=e:r=Math.log(1+n),r}),aW={kernelName:Yl,backendName:"cpu",kernelFunc:tW};function nW(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockShape:s,paddings:i}=n;Ae([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=G7.kernelFunc({inputs:{x:r},backend:a,attrs:{paddings:l,constantValue:0}}),p=T.getReshaped(u.shape,s,o,!1),c=T.getPermuted(p.length,s.length,!1),d=T.getReshapedPermuted(u.shape,s,o,!1),h=mt({inputs:{x:u},backend:a,attrs:{shape:p}}),f=Ba({inputs:{x:h},backend:a,attrs:{perm:c}}),m=mt({inputs:{x:f},backend:a,attrs:{shape:d}});return a.disposeIntermediateTensorInfo(u),a.disposeIntermediateTensorInfo(h),a.disposeIntermediateTensorInfo(f),m}var rW={kernelName:Jl,backendName:"cpu",kernelFunc:nW};function sW(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,f,m]=b7(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([f.length],"bool",new Uint8Array(f.map(g=>Number(g)))),a.makeTensorInfo([m.length],n.dtype,new Int32Array(m))]}var iW={kernelName:Ld,backendName:"cpu",kernelFunc:sW};function oW(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]=v7(o,n.shape,n.dtype,i,l);return[a.makeTensorInfo(p,n.dtype,u),a.makeTensorInfo([c.length],s.dtype,new Int32Array(c))]}var lW={kernelName:eu,backendName:"cpu",kernelFunc:oW};function uW(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]=c3(i,n.shape,n.dtype,o,l,!0);return a.makeTensorInfo(p,n.dtype,u)}var dW={kernelName:Bd,backendName:"cpu",kernelFunc:uW};function pW(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]=c3(i,n.shape,n.dtype,o,l);return a.makeTensorInfo(p,n.dtype,u)}var cW={kernelName:Wd,backendName:"cpu",kernelFunc:pW};function hW(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}=T.calculateShapes(s,r,o),h=!1,f=a.bufferSync(r),m;switch(s.dtype){case"bool":{let g=a.bufferSync(s),y=Boolean(a.data.get(i.dataId).values[0]);m=el(f,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];m=el(f,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];m=el(f,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]);m=el(f,g,o,d,p,u,l,c,y,h);break}default:throw new Error(`Unsupported type ${s.dtype}`)}return a.makeTensorInfo(o,m.dtype,m.values)}var fW={kernelName:Vd,backendName:"cpu",kernelFunc:hW};function mW(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=T.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=Gs({inputs:{x:r},backend:a,attrs:{begin:u,size:d}});return u[o]+=c,h})}var gW={kernelName:Ql,backendName:"cpu",kernelFunc:mW},yW={kernelName:Ud,backendName:"cpu",kernelFunc:({inputs:e,backend:t})=>{let{x:a}=e,n=t;Ae(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}}},xW=lt(rs,(e,t)=>{let a=t;return isNaN(e)?NaN:e>0?1:a.alpha}),AW={kernelName:rs,backendName:"cpu",kernelFunc:xW};function bW(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;Ae(r,"stridedSlice");let{finalShapeSparse:h,finalShape:f,isIdentity:m,sliceDim0:g,isSimpleSlice:y,begin:x,end:A,strides:b}=St.sliceInfo(r.shape,s,i,o,l,u,p,c,d),k;if(m)k=mt({inputs:{x:r},backend:a,attrs:{shape:f}});else if(g||y){v.assert(r.shape.length>=1,()=>`Input must have rank at least 1, got: ${r.shape.length}`);let S=St.computeOutShape(x,A,b),C=Gs({inputs:{x:r},backend:a,attrs:{begin:x,size:S}});k=mt({inputs:{x:C},backend:a,attrs:{shape:f}}),a.disposeIntermediateTensorInfo(C)}else{let S=a.bufferSync(r),C=w7(h,S,b,x);k=a.makeTensorInfo(f,C.dtype,C.values)}return k}var vW={kernelName:uo,backendName:"cpu",kernelFunc:bW};function kW(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,[f,m]=h3(d,h,r,s,i,o,l,u);return[a.makeTensorInfo([f.length],"string",f),a.makeTensorInfo(c.shape,"int32",m)]}var wW={kernelName:tu,backendName:"cpu",kernelFunc:kW};function IW(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]=f3(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 SW={kernelName:Gd,backendName:"cpu",kernelFunc:IW};function TW(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=m3(i,r);return a.makeTensorInfo(s.shape,"int32",o)}var CW={kernelName:Hd,backendName:"cpu",kernelFunc:TW},NW=lt(co,e=>Math.tan(e)),EW={kernelName:co,backendName:"cpu",kernelFunc:NW},RW=lt(ho,e=>Math.tanh(e)),MW={kernelName:ho,backendName:"cpu",kernelFunc:RW};function $W(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{reps:s}=n;Ae(r,"tile");let i=S7(a.bufferSync(r),s);return a.makeTensorInfo(i.shape,i.dtype,i.values)}var _W={kernelName:ns,backendName:"cpu",kernelFunc:$W};function PW(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{k:s,sorted:i}=n;Ae(r,"topk");let o=a.data.get(r.dataId).values,[l,u]=C7(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 FW={kernelName:fo,backendName:"cpu",kernelFunc:PW};function OW(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,[f,m]=u!=null?u:[c,d],g=[p,f,m,h],y=v.computeStrides(r.shape),x=y[0],A=y[1],b=y[2],k=v.computeStrides(g),S=k[0],C=k[1],N=k[2],$=v.getTypedArrayFromDType(r.dtype,v.sizeFromShape(g));$.fill(l);let M=n.data.get(r.dataId).values,R=n.data.get(s.dataId).values;for(let I=0;I<p;++I){let _=s.shape[0]===1?R:R.subarray(I*8,I*8+8);for(let D=0;D<f;++D)for(let W=0;W<m;++W)for(let P=0;P<h;++P){let U,G=_[6]*W+_[7]*D+1;if(G===0)continue;let q=(_[0]*W+_[1]*D+_[2])/G,H=(_[3]*W+_[4]*D+_[5])/G,B=ly(q,d,o),Z=ly(H,c,o);switch(i){case"nearest":U=VW(M,c,d,x,A,b,I,Z,B,P,l);break;case"bilinear":U=UW(M,c,d,x,A,b,I,Z,B,P,l);break;default:throw new Error(`Error in Transform: Expect 'nearest' or 'bilinear', but got ${i}`)}let X=I*S+D*C+W*N+P;$[X]=U}return n.makeTensorInfo(g,r.dtype,$)}return{dataId:n.write($,g,r.dtype),shape:r.shape,dtype:r.dtype}}var DW={kernelName:mo,backendName:"cpu",kernelFunc:OW};function ly(e,t,a){switch(a){case"reflect":return zW(e,t);case"wrap":return LW(e,t);case"nearest":return WW(e,t);case"constant":default:return BW(e,t)}}function zW(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 LW(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 BW(e,t){return e}function WW(e,t){return v.clamp(0,e,t-1)}function Hu(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 VW(e,t,a,n,r,s,i,o,l,u,p){let c=Math.round(o),d=Math.round(l);return Hu(e,t,a,n,r,s,i,c,d,u,p)}function UW(e,t,a,n,r,s,i,o,l,u,p){let c=Math.floor(o),d=Math.floor(l),h=c+1,f=d+1,m=(f-l)*Hu(e,t,a,n,r,s,i,c,d,u,p)+(l-d)*Hu(e,t,a,n,r,s,i,c,f,u,p),g=(f-l)*Hu(e,t,a,n,r,s,i,h,d,u,p)+(l-d)*Hu(e,t,a,n,r,s,i,h,f,u,p);return(h-o)*m+(o-c)*g}function GW(e){let{inputs:t,attrs:a,backend:n}=e,{axis:r}=a,{x:s}=t;Ae(s,"unique");let i=n.data.get(s.dataId).values,{outputValues:o,outputShape:l,indices:u}=N7(i,r,s.shape,s.dtype);return[n.makeTensorInfo(l,s.dtype,o),n.makeTensorInfo([u.length],"int32",u)]}var HW={kernelName:lh,backendName:"cpu",kernelFunc:GW};function jW(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 f=Gs({inputs:{x:r},backend:a,attrs:{begin:p,size:c}});d[h]=mt({inputs:{x:f},backend:a,attrs:{shape:l}}),a.disposeIntermediateTensorInfo(f)}return d}var qW={kernelName:au,backendName:"cpu",kernelFunc:jW};function XW(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,segmentIds:s}=t,{numSegments:i}=n;Ae(r,"unsortedSegmentSum");let o=r.shape.length,l=s.shape.length,u=[],p=[],c=o-l,d=s;for(let f=0;f<c;++f){let m=Dc({inputs:{input:d},backend:a,attrs:{dim:f+1}});d=m,p.push(m)}for(let f=0;f<i;++f){let m=v.createScalarValue(f,"int32"),g=a.makeTensorInfo([],"int32",m),y=Z4({inputs:{a:g,b:d},backend:a}),x=Jr({inputs:{x:y},backend:a,attrs:{dtype:"float32"}}),A=Nh({inputs:{a:x,b:r},backend:a}),b=dp({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=U7({inputs:u,backend:a,attrs:{axis:0}});return p.forEach(f=>a.disposeIntermediateTensorInfo(f)),h}var KW={kernelName:uh,backendName:"cpu",kernelFunc:XW},ZW=[GO,RF,jO,XO,OF,ZO,JO,eD,aD,rD,iD,lD,dD,hD,mD,xD,bD,kD,ID,VO,TD,ND,RD,$D,PF,zF,PD,MF,OD,zD,LD,WD,UD,HD,qD,KD,YD,QD,tz,nz,sz,oz,uz,dz,cz,fz,gz,yz,xz,Az,kz,FO,Iz,LF,$z,BF,_z,VF,Lz,Bz,Vz,GF,Hz,qz,Kz,Yz,Qz,jF,XF,$F,tL,DD,nL,sL,oL,OO,ZF,JF,uL,eO,pL,fL,gL,AL,vL,wL,IL,aO,TL,NL,RL,$L,PL,OL,zL,rO,BL,UL,qL,iO,lO,ZL,QL,aB,dO,rB,iB,oB,G7,pB,zO,hO,hB,mB,yB,AB,_F,g2,vB,LO,BO,WO,wB,SB,CB,EB,MB,$B,PB,vO,OB,WB,UB,qB,wO,KB,YB,QB,IO,HL,aW,rW,iW,lW,dW,cW,fW,gW,CO,yW,EO,AW,vW,wW,SW,CW,_O,bz,EW,MW,_W,FW,DW,pO,HW,qW,KW,sB];for(let e of ZW)yn(e);var H7={};Ze(H7,{assertNotComplex:()=>uu,bindCanvasToFramebuffer:()=>oV,bindColorTextureToFramebuffer:()=>bc,bindTextureToProgramUniformSampler:()=>i6,bindTextureUnit:()=>n6,bindVertexBufferToProgramAttribute:()=>x2,callAndCheck:()=>ue,canBeRepresented:()=>j7,createFragmentShader:()=>K7,createFramebuffer:()=>a6,createProgram:()=>Z7,createStaticIndexBuffer:()=>Q7,createStaticVertexBuffer:()=>J7,createTexture:()=>e6,createVertexShader:()=>X7,getBatchDim:()=>Hs,getExtensionOrThrow:()=>ju,getFramebufferErrorMessage:()=>o6,getMaxTexturesInShader:()=>p6,getNumChannels:()=>sV,getProgramUniformLocation:()=>s6,getProgramUniformLocationOrThrow:()=>r6,getRowsCols:()=>js,getShapeAs3D:()=>Xu,getTextureShapeFromLogicalShape:()=>u6,getWebGLDisjointQueryTimerVersion:()=>c6,getWebGLErrorMessage:()=>q7,getWebGLMaxTextureSize:()=>d6,hasExtension:()=>fn,isCapableOfRenderingToFloatTexture:()=>h6,isDownloadFloatTextureEnabled:()=>f6,isReshapeFree:()=>gd,isWebGLFenceEnabled:()=>m6,isWebGLVersionEnabled:()=>b2,linkProgram:()=>Y7,logShaderSourceAndInfoLog:()=>v3,resetMaxTextureSize:()=>lV,resetMaxTexturesInShader:()=>uV,unbindColorTextureFromFramebuffer:()=>A2,unbindTextureUnit:()=>iV,validateFramebuffer:()=>qu,validateProgram:()=>Ac,validateTextureSize:()=>t6});var Fs={},pc={alpha:!1,antialias:!1,premultipliedAlpha:!1,preserveDrawingBuffer:!1,depth:!1,stencil:!1,failIfMajorPerformanceCaveat:!0};function Eh(e,t){Fs[e]=t}function Dn(e,t){if(!(e in Fs)||t!=null){let n=JW(e,t);if(n!==null)Fs[e]=n;else return console.log("Could not get context for WebGL version",e),null}let a=Fs[e];return a==null||a.isContextLost()?(delete Fs[e],Dn(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),Fs[e])}function YW(e){if(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 JW(e,t){if(e!==1&&e!==2)throw new Error("Cannot get WebGL rendering context, WebGL is disabled.");let a=t==null?YW(e):t;return a.addEventListener("webglcontextlost",n=>{n.preventDefault(),delete Fs[e]},!1),V().getBool("SOFTWARE_WEBGL_ENABLED")&&(pc.failIfMajorPerformanceCaveat=!1),e===1?a.getContext("webgl",pc)||a.getContext("experimental-webgl",pc):a.getContext("webgl2",pc)}var md;(function(e){e[e.DENSE=0]="DENSE",e[e.SHARED_BATCH=1]="SHARED_BATCH"})(md||(md={}));var hn;(function(e){e[e.RENDER=0]="RENDER",e[e.UPLOAD=1]="UPLOAD",e[e.PIXELS=2]="PIXELS",e[e.DOWNLOAD=3]="DOWNLOAD"})(hn||(hn={}));var ia;(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"})(ia||(ia={}));function pp(e,t){return[t,e]}function QW(e,t){return e*t}function cc(e){let t=v.sizeFromShape(e),a=Math.ceil(t/4);return v.sizeToSquarishShape(a)}function lu(e,t){return[Math.max(1,Math.ceil(t/2)),Math.max(1,Math.ceil(e/2))]}function eV(e,t){let[a,n]=lu(e,t);return a*n*4}function b3(e,t){let a=e,n,r,s,i,o,l,u,p,c,d;return V().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 ue(e,t){let a=t();return V().getBool("DEBUG")&&tV(e),a}function tV(e){let t=e.getError();if(t!==e.NO_ERROR)throw new Error("WebGL Error: "+q7(e,t))}var aV=596e-10,nV=65504;function j7(e){return!!(V().getBool("WEBGL_RENDER_FLOAT32_ENABLED")||e===0||aV<Math.abs(e)&&Math.abs(e)<nV)}function q7(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 ju(e,t){return Tr(e,()=>e.getExtension(t),'Extension "'+t+'" not supported on this browser.')}function X7(e,t){let a=Tr(e,()=>e.createShader(e.VERTEX_SHADER),"Unable to create vertex WebGLShader.");if(ue(e,()=>e.shaderSource(a,t)),ue(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 K7(e,t){let a=Tr(e,()=>e.createShader(e.FRAGMENT_SHADER),"Unable to create fragment WebGLShader.");if(ue(e,()=>e.shaderSource(a,t)),ue(e,()=>e.compileShader(a)),V().get("ENGINE_COMPILE_ONLY"))return a;if(e.getShaderParameter(a,e.COMPILE_STATUS)===!1)throw v3(t,e.getShaderInfoLog(a)),new Error("Failed to compile fragment shader.");return a}var rV=/ERROR: [0-9]+:([0-9]+):/g;function v3(e,t){let a=rV.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 ${v.rightPad(u[0],o)}`,"border:1px solid red; background-color:#e3d2d2; color:#a61717"),console.log(p.join(`
|
|
`))}function Z7(e){return Tr(e,()=>e.createProgram(),"Unable to create WebGLProgram.")}function Y7(e,t){if(ue(e,()=>e.linkProgram(t)),!V().get("ENGINE_COMPILE_ONLY")&&e.getProgramParameter(t,e.LINK_STATUS)===!1)throw console.log(e.getProgramInfoLog(t)),new Error("Failed to link vertex and fragment shaders.")}function Ac(e,t){if(ue(e,()=>e.validateProgram(t)),e.getProgramParameter(t,e.VALIDATE_STATUS)===!1)throw console.log(e.getProgramInfoLog(t)),new Error("Shader program validation failed.")}function J7(e,t){let a=Tr(e,()=>e.createBuffer(),"Unable to create WebGLBuffer");return ue(e,()=>e.bindBuffer(e.ARRAY_BUFFER,a)),ue(e,()=>e.bufferData(e.ARRAY_BUFFER,t,e.STATIC_DRAW)),a}function Q7(e,t){let a=Tr(e,()=>e.createBuffer(),"Unable to create WebGLBuffer");return ue(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,a)),ue(e,()=>e.bufferData(e.ELEMENT_ARRAY_BUFFER,t,e.STATIC_DRAW)),a}function sV(){return V().getNumber("WEBGL_VERSION")===2?1:4}function e6(e){return Tr(e,()=>e.createTexture(),"Unable to create WebGLTexture.")}function t6(e,t){let a=V().getNumber("WEBGL_MAX_TEXTURE_SIZE");if(e<=0||t<=0){let n=`[${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 a6(e){return Tr(e,()=>e.createFramebuffer(),"Unable to create WebGLFramebuffer.")}function x2(e,t,a,n,r,s,i){let o=e.getAttribLocation(t,a);return o===-1?!1:(ue(e,()=>e.bindBuffer(e.ARRAY_BUFFER,n)),ue(e,()=>e.vertexAttribPointer(o,r,e.FLOAT,!1,s,i)),ue(e,()=>e.enableVertexAttribArray(o)),!0)}function n6(e,t,a){l6(e,a),ue(e,()=>e.activeTexture(e.TEXTURE0+a)),ue(e,()=>e.bindTexture(e.TEXTURE_2D,t))}function iV(e,t){l6(e,t),ue(e,()=>e.activeTexture(e.TEXTURE0+t)),ue(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function r6(e,t,a){return Tr(e,()=>e.getUniformLocation(t,a),'uniform "'+a+'" not present in program.')}function s6(e,t,a){return e.getUniformLocation(t,a)}function i6(e,t,a,n){ue(e,()=>n6(e,t,n)),ue(e,()=>e.uniform1i(a,n))}function oV(e){ue(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),ue(e,()=>e.viewport(0,0,e.canvas.width,e.canvas.height)),ue(e,()=>e.scissor(0,0,e.canvas.width,e.canvas.height))}function bc(e,t,a){ue(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,a)),ue(e,()=>e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,t,0))}function A2(e,t){ue(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,t)),ue(e,()=>e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,null,0))}function qu(e){let t=e.checkFramebufferStatus(e.FRAMEBUFFER);if(t!==e.FRAMEBUFFER_COMPLETE)throw new Error("Error binding framebuffer: "+o6(e,t))}function o6(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 ${t}`}}function Tr(e,t,a){let n=ue(e,()=>t());if(n==null)throw new Error(a);return n}function l6(e,t){let a=e.MAX_COMBINED_TEXTURE_IMAGE_UNITS-1,n=t+e.TEXTURE0;if(n<e.TEXTURE0||n>a){let r=`[gl.TEXTURE0, gl.TEXTURE${a}]`;throw new Error(`textureUnit must be in ${r}.`)}}function Hs(e,t=2){return v.sizeFromShape(e.slice(0,e.length-t))}function js(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 Xu(e){let t=[1,1,1];return e.length===0||e.length===1&&e[0]===1||(t=[Hs(e),...js(e)]),t}function u6(e,t=!1){let a=V().getNumber("WEBGL_MAX_TEXTURE_SIZE"),n=V().getNumber("WEBGL_MAX_SIZE_FOR_NARROW_TEXTURE");n===1/0&&V().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=Hs(e),l=2,u=2;e.length&&([l,u]=js(e)),r=o*(l/2)*(u/2),s=v.sizeToSquarishShape(r).map(p=>p*2)}else s=v.sizeToSquarishShape(r);return s}function hc(e){return e%2===0}function gd(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.slice(-1)[0],n=t.slice(-1)[0];if(a===n||hc(a)&&hc(n)&&(e[0]===1||t[0]===1))return!0}return e[1]===t[1]&&hc(e[0])&&hc(t[0])}var vc,kc;function d6(e){if(vc==null){let t=Dn(e);vc=t.getParameter(t.MAX_TEXTURE_SIZE)}return vc}function lV(){vc=null}function uV(){kc=null}function p6(e){if(kc==null){let t=Dn(e);kc=t.getParameter(t.MAX_TEXTURE_IMAGE_UNITS)}return Math.min(16,kc)}function c6(e){if(e===0)return 0;let t,a=Dn(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 b2(e){try{if(Dn(e)!=null)return!0}catch(t){return console.log("Error when getting WebGL context: ",t),!1}return!1}function h6(e){if(e===0)return!1;let t=Dn(e);if(e===1){if(!fn(t,"OES_texture_float"))return!1}else if(!fn(t,"EXT_color_buffer_float"))return!1;return v2(t)}function f6(e){if(e===0)return!1;let t=Dn(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 v2(t);let a="EXT_color_buffer_half_float";if(fn(t,a)){let n=t.getExtension(a);return dV(t,n)}return!1}return v2(t)}function v2(e){let t=b3(e),a=e.createTexture();e.bindTexture(e.TEXTURE_2D,a);let n=1,r=1;e.texImage2D(e.TEXTURE_2D,0,t.internalFormatFloat,n,r,0,t.textureFormatFloat,t.textureTypeFloat,null);let s=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,s),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,a,0);let i=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(a),e.deleteFramebuffer(s),i}function dV(e,t){let a=b3(e,t),n=e.createTexture();e.bindTexture(e.TEXTURE_2D,n);let r=1,s=1;e.texImage2D(e.TEXTURE_2D,0,a.internalFormatHalfFloat,r,s,0,a.textureFormatFloat,a.textureTypeHalfFloat,null);let i=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,i),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,n,0);let o=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(n),e.deleteFramebuffer(i),o}function m6(e){return e!==2?!1:Dn(e).fenceSync!=null}function uu(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 ve=V();ve.registerFlag("HAS_WEBGL",()=>ve.getNumber("WEBGL_VERSION")>0);ve.registerFlag("WEBGL_VERSION",()=>b2(2)?2:b2(1)?1:0);ve.registerFlag("WEBGL_CHECK_NUMERICAL_PROBLEMS",()=>!1);ve.registerFlag("WEBGL_BUFFER_SUPPORTED",()=>ve.get("WEBGL_VERSION")===2);ve.registerFlag("WEBGL_CPU_FORWARD",()=>!0);ve.registerFlag("WEBGL_FORCE_F16_TEXTURES",()=>!1);ve.registerFlag("WEBGL_PACK",()=>ve.getBool("HAS_WEBGL"));ve.registerFlag("WEBGL_PACK_NORMALIZATION",()=>ve.getBool("WEBGL_PACK"));ve.registerFlag("WEBGL_PACK_CLIP",()=>ve.getBool("WEBGL_PACK"));ve.registerFlag("WEBGL_PACK_DEPTHWISECONV",()=>ve.getBool("WEBGL_PACK"));ve.registerFlag("WEBGL_PACK_BINARY_OPERATIONS",()=>ve.getBool("WEBGL_PACK"));ve.registerFlag("WEBGL_PACK_UNARY_OPERATIONS",()=>ve.getBool("WEBGL_PACK"));ve.registerFlag("WEBGL_PACK_ARRAY_OPERATIONS",()=>ve.getBool("WEBGL_PACK"));ve.registerFlag("WEBGL_PACK_IMAGE_OPERATIONS",()=>ve.getBool("WEBGL_PACK"));ve.registerFlag("WEBGL_PACK_REDUCE",()=>ve.getBool("WEBGL_PACK"));ve.registerFlag("WEBGL_LAZILY_UNPACK",()=>ve.getBool("WEBGL_PACK"));ve.registerFlag("WEBGL_CONV_IM2COL",()=>ve.getBool("WEBGL_PACK"));ve.registerFlag("WEBGL_MAX_TEXTURE_SIZE",()=>d6(ve.getNumber("WEBGL_VERSION")));ve.registerFlag("WEBGL_MAX_TEXTURES_IN_SHADER",()=>p6(ve.getNumber("WEBGL_VERSION")));ve.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION",()=>{let e=ve.getNumber("WEBGL_VERSION");return e===0?0:c6(e)});ve.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE",()=>ve.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0&&!Kd.isMobile());ve.registerFlag("WEBGL_RENDER_FLOAT32_CAPABLE",()=>h6(ve.getNumber("WEBGL_VERSION")));ve.registerFlag("WEBGL_RENDER_FLOAT32_ENABLED",()=>ve.getBool("WEBGL_FORCE_F16_TEXTURES")?!1:ve.getBool("WEBGL_RENDER_FLOAT32_CAPABLE"));ve.registerFlag("WEBGL_DOWNLOAD_FLOAT_ENABLED",()=>f6(ve.getNumber("WEBGL_VERSION")));ve.registerFlag("WEBGL_FENCE_API_ENABLED",()=>m6(ve.getNumber("WEBGL_VERSION")));ve.registerFlag("WEBGL_SIZE_UPLOAD_UNIFORM",()=>ve.getBool("WEBGL_RENDER_FLOAT32_ENABLED")?4:0);ve.registerFlag("WEBGL_DELETE_TEXTURE_THRESHOLD",()=>-1,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}.`)});ve.registerFlag("WEBGL_FLUSH_THRESHOLD",()=>Kd.isMobile()?1:-1,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}.`)});ve.registerFlag("CPU_HANDOFF_SIZE_THRESHOLD",()=>128);ve.registerFlag("WEBGL_USE_SHAPES_UNIFORMS",()=>!1);ve.registerFlag("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD",()=>1e5);ve.registerFlag("TOPK_K_CPU_HANDOFF_THRESHOLD",()=>128);ve.registerFlag("WEBGL_EXP_CONV",()=>!1);ve.registerFlag("SOFTWARE_WEBGL_ENABLED",()=>ve.getBool("IS_TEST"));ve.registerFlag("WEBGL_MAX_SIZE_FOR_NARROW_TEXTURE",()=>1/0);ve.registerFlag("WEBGL_AUTO_SQUARIFY_NARROW_TEXTURE_SHAPE",()=>!1);ve.registerFlag("WEBGL2_ISNAN_CUSTOM",()=>!1);ve.registerFlag("ENGINE_COMPILE_ONLY",()=>!1);function Na(){let e,t,a,n,r,s,i,o,l,u;return V().getNumber("WEBGL_VERSION")===2?(e="#version 300 es",t="in",a="out",n="in",r="texture",s="outputColor",i="out vec4 outputColor;",o=V().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 Ao(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 Rh(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}; ${o};`}).join("")}function pV(e,t){let a=e.length,n=e.map(s=>`${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 cV(e,t,a="index"){let n=e.map((s,i)=>i),r=pV(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 k3(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 w3(){return`
|
|
int getFlatIndex(ivec3 coords) {
|
|
return coords.x * outShapeStrides[0] + coords.y * outShapeStrides[1] + coords.z;
|
|
}
|
|
`}var g6=`
|
|
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:y6}=T;function hV(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:f}=I3(a.packedInputs,d.shapeInfo.logicalShape,d.shapeInfo.texShape);switch(f.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?`[${d.arrayIndex}]`:""};`)});let r=n.join(`
|
|
`),s=e.map(d=>fV(d,t,a.packedInputs,a.enableShapeUniforms)).join(`
|
|
`),i=t.texShape,o=Na(),l=yV(o),u,p,c=bV(o);return t.isPacked?(u=mV(t.logicalShape,i,a.enableShapeUniforms),p=AV(o)):(u=gV(t.logicalShape,i,a.enableShapeUniforms),p=xV(o)),a.packedInputs&&(c+=IV),[c,l,p,r,u,s,a.userCode].join(`
|
|
`)}function du(e,t=!1){let a=e.shapeInfo.logicalShape;switch(a.length){case 0:return OV(e,t);case 1:return zV(e,t);case 2:return BV(e,t);case 3:return VV(e,t);case 4:return GV(e,t);case 5:return HV(e);case 6:return jV(e);default:throw new Error(`${a.length}-D input sampling is not yet supported`)}}function x6(e,t){switch(e.shapeInfo.logicalShape.length){case 0:return FV(e);case 1:return DV(e,t);case 2:return LV(e,t);case 3:return WV(e,t);default:return UV(e,t)}}function fV(e,t,a=!1,n){let r="";a?r+=x6(e,n):r+=du(e,n);let s=e.shapeInfo.logicalShape,i=t.logicalShape;return s.length<=i.length&&(a?r+=qV(e,t):r+=XV(e,t)),r}function mV(e,t,a){switch(e.length){case 0:return A6();case 1:return SV(e,t,a);case 2:return _V(e,t,a);case 3:return CV(e,t,a);default:return EV(e,t,a)}}function gV(e,t,a){switch(e.length){case 0:return A6();case 1:return TV(e,t,a);case 2:return PV(e,t,a);case 3:return NV(e,t,a);case 4:return RV(e,t,a);case 5:return MV(e,t);case 6:return $V(e,t);default:throw new Error(`${e.length}-D output sampling is not yet supported`)}}function yV(e){return`
|
|
float sampleTexture(sampler2D textureSampler, vec2 uv) {
|
|
return ${e.texture2D}(textureSampler, uv).r;
|
|
}
|
|
`}function xV(e){return`
|
|
void setOutput(float val) {
|
|
${e.output} = vec4(val, 0, 0, 0);
|
|
}
|
|
`}function AV(e){return`
|
|
void setOutput(vec4 val) {
|
|
${e.output} = val;
|
|
}
|
|
`}function bV(e){return`${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);
|
|
}
|
|
|
|
${vV}
|
|
${kV}
|
|
${wV}
|
|
`}var vV=`
|
|
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);
|
|
}
|
|
`,kV=`
|
|
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);
|
|
}
|
|
`,wV=`
|
|
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);
|
|
}
|
|
`,IV=`
|
|
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 A6(){return`
|
|
int getOutputCoords() {
|
|
return 0;
|
|
}
|
|
`}function SV(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 TV(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 * ${t[1]} + resTexRC.y;
|
|
}
|
|
`}function CV(e,t,a){if(a)return`
|
|
ivec3 getOutputCoords() {
|
|
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
|
|
int texelsInLogicalRow = int(ceil(float(outShape[2]) / 2.0));
|
|
int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[1]) / 2.0));
|
|
ivec2 resTexRC = ivec2(resultUV.yx *
|
|
vec2(packedTexShape[0], packedTexShape[1]));
|
|
int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
|
|
|
|
int b = index / texelsInBatch;
|
|
index -= b * texelsInBatch;
|
|
|
|
int r = 2 * (index / texelsInLogicalRow);
|
|
int c = imod(index, texelsInLogicalRow) * 2;
|
|
|
|
return ivec3(b, r, c);
|
|
}
|
|
`;let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[2]/2),s=r*Math.ceil(e[1]/2);return`
|
|
ivec3 getOutputCoords() {
|
|
ivec2 resTexRC = ivec2(resultUV.yx *
|
|
vec2(${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 NV(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;
|
|
${Rh(["r","c","d"],e)}
|
|
return ivec3(r, c, d);
|
|
}
|
|
`;let n=Ao(["r","c","d"],e);return`
|
|
ivec3 getOutputCoords() {
|
|
ivec2 resTexRC = ivec2(resultUV.yx *
|
|
vec2(${t[0]}, ${t[1]}));
|
|
int index = resTexRC.x * ${t[1]} + resTexRC.y;
|
|
${n}
|
|
return ivec3(r, c, d);
|
|
}
|
|
`}function EV(e,t,a){if(a)return`
|
|
ivec4 getOutputCoords() {
|
|
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
|
|
ivec2 resTexRC = ivec2(resultUV.yx *
|
|
vec2(packedTexShape[0], packedTexShape[1]));
|
|
int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
|
|
|
|
int texelsInLogicalRow = int(ceil(float(outShape[3]) / 2.0));
|
|
int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[2]) / 2.0));
|
|
int texelsInBatchN = texelsInBatch * outShape[1];
|
|
|
|
int b2 = index / texelsInBatchN;
|
|
index -= b2 * texelsInBatchN;
|
|
|
|
int b = index / texelsInBatch;
|
|
index -= b * texelsInBatch;
|
|
|
|
int r = 2 * (index / texelsInLogicalRow);
|
|
int c = imod(index, texelsInLogicalRow) * 2;
|
|
|
|
return ivec4(b2, b, r, c);
|
|
}
|
|
`;let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[e.length-1]/2),s=r*Math.ceil(e[e.length-2]/2),i=s,o="",l="b, r, c";for(let u=2;u<e.length-1;u++)i*=e[e.length-u-1],o=`
|
|
int b${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 RV(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;
|
|
${Rh(["r","c","d","d2"],e)}
|
|
return ivec4(r, c, d, d2);
|
|
}
|
|
`;let n=Ao(["r","c","d","d2"],e);return`
|
|
ivec4 getOutputCoords() {
|
|
ivec2 resTexRC = ivec2(resultUV.yx *
|
|
vec2(${t[0]}, ${t[1]}));
|
|
int index = resTexRC.x * ${t[1]} + resTexRC.y;
|
|
${n}
|
|
return ivec4(r, c, d, d2);
|
|
}
|
|
`}function MV(e,t){let a=Ao(["r","c","d","d2","d3"],e);return`
|
|
ivec5 getOutputCoords() {
|
|
ivec2 resTexRC = ivec2(resultUV.yx * vec2(${t[0]},
|
|
${t[1]}));
|
|
|
|
int index = resTexRC.x * ${t[1]} + resTexRC.y;
|
|
|
|
${a}
|
|
|
|
ivec5 outShape = ivec5(r, c, d, d2, d3);
|
|
return outShape;
|
|
}
|
|
`}function $V(e,t){let a=Ao(["r","c","d","d2","d3","d4"],e);return`
|
|
ivec6 getOutputCoords() {
|
|
ivec2 resTexRC = ivec2(resultUV.yx *
|
|
vec2(${t[0]}, ${t[1]}));
|
|
int index = resTexRC.x * ${t[1]} + resTexRC.y;
|
|
|
|
${a}
|
|
|
|
ivec6 result = ivec6(r, c, d, d2, d3, d4);
|
|
return result;
|
|
}
|
|
`}function _V(e,t,a){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(v.arraysEqual(e,t))return a?`
|
|
ivec2 getOutputCoords() {
|
|
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
|
|
return 2 * ivec2(resultUV.yx * vec2(packedTexShape[0], packedTexShape[1]));
|
|
}
|
|
`:`
|
|
ivec2 getOutputCoords() {
|
|
return 2 * ivec2(resultUV.yx * vec2(${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, ${r}) * 2;
|
|
|
|
return ivec2(r, c);
|
|
}
|
|
`}function PV(e,t,a){return v.arraysEqual(e,t)?a?`
|
|
ivec2 getOutputCoords() {
|
|
return ivec2(resultUV.yx * vec2(outTexShape[0], outTexShape[1]));
|
|
}
|
|
`:`
|
|
ivec2 getOutputCoords() {
|
|
return ivec2(resultUV.yx * vec2(${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 * ${e[1]};
|
|
return ivec2(r, c);
|
|
}
|
|
`}function bo(e){return`offset${e}`}function FV(e){let t=e.name,a="get"+t.charAt(0).toUpperCase()+t.slice(1),n=Na();return`
|
|
vec4 ${a}() {
|
|
return ${n.texture2D}(${t}, halfCR);
|
|
}
|
|
`}function OV(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=bo(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 DV(e,t){let a=e.name,n="get"+a.charAt(0).toUpperCase()+a.slice(1),r=e.shapeInfo.texShape,s=Na();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 zV(e,t){let a=e.name,n="get"+a.charAt(0).toUpperCase()+a.slice(1);if(e.shapeInfo.isUniform)return`
|
|
float ${n}(int index) {
|
|
${pu(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=bo(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 LV(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=Na();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 BV(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=cu(e,l),h=["row","col"];return`
|
|
${du(d,t)}
|
|
float ${r}(int row, int col) {
|
|
return ${r}(${hu(h,o)});
|
|
}
|
|
`}if(e.shapeInfo.isUniform)return`
|
|
float ${r}(int row, int col) {
|
|
int index = round(dot(vec2(row, col), vec2(${a[1]}, 1)));
|
|
${pu(e)}
|
|
}
|
|
`;let u=s[0],p=s[1],c=bo(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 WV(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],f=cu(e,d),m=["b","row","col"];return`
|
|
${x6(f,t)}
|
|
vec4 ${r}(int b, int row, int col) {
|
|
return ${r}(${hu(m,h)});
|
|
}
|
|
`}let o=Na();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 VV(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 m=cu(e,u),g=["row","col","depth"];return`
|
|
${du(m,t)}
|
|
float ${r}(int row, int col, int depth) {
|
|
return ${r}(${hu(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)));
|
|
${pu(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 f=bo(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 + ${f};
|
|
vec2 uv = uvFromFlat(${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 + ${f};
|
|
vec2 uv = uvFromFlat(${c}, ${d}, index);
|
|
return sampleTexture(${n}, uv);
|
|
}
|
|
`}function UV(e,t){let a=e.name,n="get"+a.charAt(0).toUpperCase()+a.slice(1),r=Na();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",f=`b * ${d} + (row / 2) * ${c} + (col / 2)`;for(let m=2;m<i-1;m++)h=`int b${m}, `+h,d*=s[i-m-1],f=`b${m} * ${d} + `+f;return`
|
|
vec4 ${n}(${h}) {
|
|
int index = ${f};
|
|
int texR = index / ${p};
|
|
int texC = index - texR * ${p};
|
|
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${p}, ${u});
|
|
return ${r.texture2D}(${a}, uv);
|
|
}
|
|
`}function GV(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=cu(e,l),A=["row","col","depth","depth2"];return`
|
|
${du(x,t)}
|
|
float ${r}(int row, int col, int depth, int depth2) {
|
|
return ${r}(${hu(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)));
|
|
${pu(e)}
|
|
}
|
|
`;let p=e.shapeInfo.flatOffset,c=e.shapeInfo.texShape,d=c[0],h=c[1],f=`int stride2 = ${n}Shape[3];`,m=`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) {
|
|
${f}
|
|
${m}
|
|
float texR = float(row);
|
|
float texC =
|
|
dot(vec3(col, depth, depth2),
|
|
vec3(stride1, stride2, 1));
|
|
vec2 uv = (vec2(texC, texR) + halfCR) /
|
|
vec2(${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=bo(n);return t?`
|
|
float ${r}(int row, int col, int depth, int depth2) {
|
|
// Explicitly use integer operations as dot() only works on floats.
|
|
${f}
|
|
${m}
|
|
${g}
|
|
int index = row * stride0 + col * stride1 +
|
|
depth * stride2 + depth2;
|
|
vec2 uv = uvFromFlat(${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 HV(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 m=cu(e,l),g=["row","col","depth","depth2","depth3"];return`
|
|
${du(m)}
|
|
float ${n}(int row, int col, int depth, int depth2, int depth3) {
|
|
return ${n}(${hu(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;
|
|
${pu(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 f=bo(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 + ${f};
|
|
vec2 uv = uvFromFlat(${d}, ${h}, index);
|
|
return sampleTexture(${a}, uv);
|
|
}
|
|
`}function jV(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=cu(e,r),y=["row","col","depth","depth2","depth3","depth4"];return`
|
|
${du(g)}
|
|
float ${n}(int row, int col, int depth,
|
|
int depth2, int depth3, int depth4) {
|
|
return ${n}(${hu(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)));
|
|
${pu(e)}
|
|
}
|
|
`;let c=e.shapeInfo.flatOffset,d=e.shapeInfo.texShape,h=d[0],f=d[1];if(f===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}, ${i})) +
|
|
float(depth4);
|
|
vec2 uv = (vec2(texC, texR) + halfCR) /
|
|
vec2(${f}.0, ${h}.0);
|
|
return sampleTexture(${a}, uv);
|
|
}
|
|
`;if(f===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]},
|
|
${t[4]})) + float(depth3);
|
|
int texC = depth4;
|
|
vec2 uv = (vec2(texC, texR) + halfCR) /
|
|
vec2(${f}.0, ${h}.0);
|
|
return sampleTexture(${a}, uv);
|
|
}
|
|
`;let m=bo(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 + ${m};
|
|
vec2 uv = uvFromFlat(${h}, ${f}, index);
|
|
return sampleTexture(${a}, uv);
|
|
}
|
|
`}function pu(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 ${t}[i];
|
|
}
|
|
}
|
|
`}function qV(e,t){let a=e.name,n=a.charAt(0).toUpperCase()+a.slice(1),r="get"+n+"AtOutCoords",s=e.shapeInfo.logicalShape.length,i=t.logicalShape.length,o=y6(e.shapeInfo.logicalShape,t.logicalShape),l=gt(i),u=i-s,p,c=["x","y","z","w","u","v"];s===0?p="":i<2&&o.length>=1?p="coords = 0;":p=o.map(g=>`coords.${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;",f=v.sizeFromShape(e.shapeInfo.logicalShape)===1,m=v.sizeFromShape(t.logicalShape)===1;if(s===1&&!f&&!m)h=`
|
|
return vec4(outputValue.xy, outputValue.xy);
|
|
`;else if(f&&!m)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 XV(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=gt(l),p=y6(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(m=>`coords.${h[m+c]} = 0;`).join(`
|
|
`);let f="";return l<2&&o>0?f="coords":f=e.shapeInfo.logicalShape.map((m,g)=>`coords.${h[g+c]}`).join(", "),`
|
|
float ${r}() {
|
|
${u} coords = getOutputCoords();
|
|
${d}
|
|
return get${n}(${f});
|
|
}
|
|
`}function gt(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 ${e} is not yet supported`)}function I3(e,t,a){let{newShape:n,keptDims:r}=v.squeezeShape(t),s=t.length,i=e&&s===3&&t[0]===1,o=i?t.slice(1):n,l=!e&&s>1&&!v.arraysEqual(t,a)&&n.length<s||i;return{useSqueezeShape:l,uniformShape:l?o:t,keptDims:r}}function cu(e,t){let a=JSON.parse(JSON.stringify(e));return a.shapeInfo.logicalShape=t,a}function hu(e,t){return t.map(a=>e[a]).join(", ")}function KV(e,t,a,n){let r=a.map((p,c)=>{let d={logicalShape:p.shape,texShape:p.isUniform?null:p.texData.texShape,isUniform:p.isUniform,isPacked:p.isUniform?!1:p.texData.isPacked,flatOffset:null};return p.texData!=null&&p.texData.slice!=null&&p.texData.slice.flatOffset>0&&(d.flatOffset=p.texData.slice.flatOffset),{name:t.variableNames[c],shapeInfo:d}}),s=r.map(p=>p.shapeInfo),i={logicalShape:n.shape,texShape:n.texData.texShape,isUniform:!1,isPacked:n.texData.isPacked,flatOffset:null},o=hV(r,i,t),l=K7(e.gl,o),u=e.createProgram(l);return V().get("ENGINE_COMPILE_ONLY")?{program:t,fragmentShader:l,source:o,webGLProgram:u,inShapeInfos:s,outShapeInfo:i,uniformLocations:null,customUniformLocations:null,infLoc:null,nanLoc:null,inShapesLocations:null,inTexShapesLocations:null,outShapeLocation:null,outShapeStridesLocation:null,outTexShapeLocation:null}:Object.assign({program:t,fragmentShader:l,source:o,webGLProgram:u,inShapeInfos:s,outShapeInfo:i},b6(e,t,u))}function b6(e,t,a){let n={},r={},s={},i=[],o,l,u,p=null,c=null;c=e.getUniformLocation(a,"NAN",!1),V().getNumber("WEBGL_VERSION")===1&&(p=e.getUniformLocation(a,"INFINITY",!1));let d=!1;for(let h=0;h<t.variableNames.length;h++){let f=t.variableNames[h];n[f]=e.getUniformLocation(a,f,d),n[`offset${f}`]=e.getUniformLocation(a,`offset${f}`,d),t.enableShapeUniforms&&(r[`${f}Shape`]=e.getUniformLocation(a,`${f}Shape`,d),s[`${f}TexShape`]=e.getUniformLocation(a,`${f}TexShape`,d))}return t.enableShapeUniforms&&(o=e.getUniformLocation(a,"outShape",d),u=e.getUniformLocation(a,"outShapeStrides",d),l=e.getUniformLocation(a,"outTexShape",d)),t.customUniforms&&t.customUniforms.forEach((h,f)=>{i[f]=e.getUniformLocation(a,h.name,d)}),{uniformLocations:n,customUniformLocations:i,infLoc:p,nanLoc:c,inShapesLocations:r,inTexShapesLocations:s,outShapeLocation:o,outShapeStridesLocation:u,outTexShapeLocation:l}}function uy(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 ${l} must match`)})}function ZV(e,t,a,n,r){t.program.enableShapeUniforms||(uy(t.inShapeInfos,a),uy([t.outShapeInfo],[n]));let s=n.texData.texture,i=n.texData.texShape;n.texData.isPacked?e.setOutputPackedMatrixTexture(s.texture,i[0],i[1]):e.setOutputMatrixTexture(s.texture,i[0],i[1]),e.setProgram(t.webGLProgram),V().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&e.gl.uniform1f(t.infLoc,1/0),t.nanLoc!==null&&e.gl.uniform1f(t.nanLoc,NaN),a.forEach((l,u)=>{let p=t.program.variableNames[u],c=t.uniformLocations[p],d=t.uniformLocations[`offset${p}`],h=t.inShapesLocations[`${p}Shape`],f=t.inTexShapesLocations[`${p}TexShape`];if(h){let{uniformShape:m}=I3(t.program.packedInputs,l.shape,l.texData.texShape);switch(m.length){case 1:e.gl.uniform1iv(h,new Int32Array(m));break;case 2:e.gl.uniform2iv(h,new Int32Array(m));break;case 3:e.gl.uniform3iv(h,new Int32Array(m));break;case 4:e.gl.uniform4iv(h,new Int32Array(m));break;default:break}}if(f&&e.gl.uniform2i(f,l.texData.texShape[0],l.texData.texShape[1]),c!=null){if(l.isUniform){if(v.sizeFromShape(l.shape)<2)e.gl.uniform1f(c,l.uniformValues[0]);else{let m=l.uniformValues;m instanceof Float32Array||(m=new Float32Array(m)),e.gl.uniform1fv(c,m)}return}l.texData.slice!=null&&d!=null&&e.gl.uniform1i(d,l.texData.slice.flatOffset),e.setInputMatrixTexture(l.texData.texture.texture,c,u)}});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}}t.outTexShapeLocation&&e.gl.uniform2i(t.outTexShapeLocation,n.texData.texShape[0],n.texData.texShape[1]),t.program.customUniforms&&r&&t.program.customUniforms.forEach((l,u)=>{let p=t.customUniformLocations[u],c=r[u];if(l.type==="float")e.gl.uniform1fv(p,c);else if(l.type==="vec2")e.gl.uniform2fv(p,c);else if(l.type==="vec3")e.gl.uniform3fv(p,c);else if(l.type==="vec4")e.gl.uniform4fv(p,c);else if(l.type==="int")e.gl.uniform1iv(p,c);else if(l.type==="ivec2")e.gl.uniform2iv(p,c);else if(l.type==="ivec3")e.gl.uniform3iv(p,c);else if(l.type==="ivec4")e.gl.uniform4iv(p,c);else throw Error(`uniform type ${l.type} is not supported yet.`)}),e.executeProgram()}function YV(e,t,a){let n="";t.concat(a).forEach(i=>{let o=i.texData!=null&&i.texData.slice!=null&&i.texData.slice.flatOffset>0;if(e.enableShapeUniforms&&!i.isUniform){let l=i.texData.texShape,{useSqueezeShape:u,uniformShape:p,keptDims:c}=I3(e.packedInputs,i.shape,l),d="",h="",f="";if(p.length===1&&e.packedInputs){let k=[Math.ceil(l[0]/2),Math.ceil(l[1]/2)];d=`${k[0]>1}_${k[1]>1}`}else if(p.length===2&&!e.packedInputs)h=`${p[0]>1}_${p[1]>1}`;else if(p.length>2&&!e.packedInputs){let k=v.computeStrides(p);f=`${k[0]===l[1]}_${k[k.length-1]===l[1]}`}let m=i.shape.length,g=p.length===2&&v.arraysEqual(i.shape,l),y=v.sizeFromShape(i.shape)===1,x=T.getBroadcastDims(i.shape,a.shape),A=!e.packedInputs&&m===a.shape.length&&v.arraysEqual(l,a.texData.texShape),b=e.packedInputs||p.length>2?"":`${l[0]>1}_${l[1]>1}`;n+=`${m}_${A}_${u?c:""}_${p.length}_${y}_${x}_${g}_${d}_${h}_${f}_${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+`${V().getNumber("WEBGL_VERSION")}`,s}function Ea(e){return V().getBool("WEBGL_USE_SHAPES_UNIFORMS")&&e<=4}var JV=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=md.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let t=Na();this.outputShape=e,this.enableShapeUniforms=Ea(this.outputShape.length),this.userCode=`
|
|
ivec3 outCoordsFromFlatIndex(int index) {
|
|
${this.enableShapeUniforms?Rh(["r","c","d"],e):Ao(["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;
|
|
}
|
|
`}},QV=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=md.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let t=Na();this.outputShape=e,this.enableShapeUniforms=Ea(this.outputShape.length),this.userCode=`
|
|
ivec3 outCoordsFromFlatIndex(int index) {
|
|
${this.enableShapeUniforms?Rh(["r","c","d"],e):Ao(["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;
|
|
}
|
|
`}},eU=class{constructor(e){this.variableNames=["A"],this.outTexUsage=hn.DOWNLOAD;let t=Na();this.outputShape=e,this.userCode=`
|
|
${g6}
|
|
|
|
void main() {
|
|
float x = getAAtOutCoords();
|
|
${t.output} = encode_float(x);
|
|
}
|
|
`}},tU=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=hn.DOWNLOAD;let t=Na();this.outputShape=e,this.userCode=`
|
|
${g6}
|
|
|
|
void main() {
|
|
ivec3 coords = getOutputCoords();
|
|
float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));
|
|
${t.output} = encode_float(x);
|
|
}
|
|
`}},aU={R:0,G:1,B:2,A:3},dy=class{constructor(e,t=!1,a="RGBA"){this.variableNames=["A"],this.customUniforms=[{name:"texShape",type:"ivec2"}];let n=Na();this.outputShape=e,this.enableShapeUniforms=Ea(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 == ${i}) {
|
|
result = values[${aU[o]}];
|
|
}`}this.userCode=`
|
|
${this.enableShapeUniforms?w3():k3(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.);
|
|
}
|
|
`}},nU=class{constructor(e,t=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.customUniforms=[{name:"texShape",type:"ivec2"}];let a=Na();this.outputShape=e,this.enableShapeUniforms=Ea(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?w3():k3(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};
|
|
}
|
|
`}},v6={};Ze(v6,{bindVertexProgramAttributeStreams:()=>R6,createBufferFromOutputTexture:()=>_6,createFloat16MatrixTexture:()=>T6,createFloat16PackedMatrixTexture:()=>E6,createFloat32MatrixTexture:()=>S6,createIndexBuffer:()=>I6,createPackedMatrixTexture:()=>N6,createUnsignedBytesMatrixTexture:()=>C6,createVertexBuffer:()=>w6,createVertexShader:()=>k6,downloadByteEncodedFloatMatrixFromOutputTexture:()=>F6,downloadFloat32MatrixFromBuffer:()=>P6,downloadMatrixFromPackedOutputTexture:()=>D6,downloadPackedMatrixFromBuffer:()=>O6,getInternalFormatForFloat16MatrixTexture:()=>T3,getInternalFormatForFloat16PackedMatrixTexture:()=>E3,getInternalFormatForFloat32MatrixTexture:()=>S3,getInternalFormatForPackedMatrixTexture:()=>N3,getInternalFormatForUnsignedBytesMatrixTexture:()=>C3,uploadDenseMatrixToTexture:()=>M6,uploadPixelDataToTexture:()=>$6});function k6(e){let t=Na(),a=`${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 X7(e,a)}function w6(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 J7(e,t)}function I6(e){let t=new Uint16Array([0,1,2,2,1,3]);return Q7(e,t)}function cp(e,t,a,n,r,s){t6(t,a);let i=e6(e),o=e.TEXTURE_2D;return ue(e,()=>e.bindTexture(o,i)),ue(e,()=>e.texParameteri(o,e.TEXTURE_WRAP_S,e.CLAMP_TO_EDGE)),ue(e,()=>e.texParameteri(o,e.TEXTURE_WRAP_T,e.CLAMP_TO_EDGE)),ue(e,()=>e.texParameteri(o,e.TEXTURE_MIN_FILTER,e.NEAREST)),ue(e,()=>e.texParameteri(o,e.TEXTURE_MAG_FILTER,e.NEAREST)),V().getNumber("WEBGL_VERSION")===1?ue(e,()=>e.texImage2D(o,0,n,t,a,0,r,s,null)):ue(e,()=>e.texStorage2D(o,1,n,t,a)),ue(e,()=>e.bindTexture(e.TEXTURE_2D,null)),{texture:i,texShape:[a,t]}}function S3(e){return e.internalFormatFloat}function S6(e,t,a,n){let[r,s]=pp(t,a);return cp(e,r,s,S3(n),n.textureFormatFloat,e.FLOAT)}function T3(e){return e.internalFormatHalfFloat}function T6(e,t,a,n){let[r,s]=pp(t,a);return cp(e,r,s,T3(n),n.textureFormatFloat,n.textureTypeHalfFloat)}function C3(e){return e.downloadTextureFormat}function C6(e,t,a,n){let[r,s]=pp(t,a);return cp(e,r,s,C3(n),e.RGBA,e.UNSIGNED_BYTE)}function N3(e){return e.internalFormatPackedFloat}function N6(e,t,a,n){let[r,s]=lu(t,a);return cp(e,r,s,N3(n),e.RGBA,e.FLOAT)}function E3(e){return e.internalFormatPackedHalfFloat}function E6(e,t,a,n){let[r,s]=lu(t,a);return cp(e,r,s,E3(n),e.RGBA,n.textureTypeHalfFloat)}function R6(e,t,a){return ue(e,()=>e.bindBuffer(e.ARRAY_BUFFER,a)),x2(e,t,"clipSpacePos",a,3,20,0)&&x2(e,t,"uv",a,2,20,12)}function M6(e,t,a,n,r,s){ue(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),V().getNumber("WEBGL_VERSION")===2?ue(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,a,n,e.RGBA,o,i)):ue(e,()=>e.texImage2D(e.TEXTURE_2D,0,l,a,n,0,e.RGBA,o,i)),ue(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function $6(e,t,a){ue(e,()=>e.bindTexture(e.TEXTURE_2D,t)),a.data instanceof Uint8Array?V().getNumber("WEBGL_VERSION")===2?ue(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,a.width,a.height,e.RGBA,e.UNSIGNED_BYTE,a.data)):ue(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,a.width,a.height,0,e.RGBA,e.UNSIGNED_BYTE,a.data)):V().getNumber("WEBGL_VERSION")===2?ue(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,e.RGBA,e.UNSIGNED_BYTE,a)):ue(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,e.RGBA,e.UNSIGNED_BYTE,a)),ue(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function _6(e,t,a,n){let r=e.createBuffer();ue(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,r));let s=4*4*t*a;return ue(e,()=>e.bufferData(e.PIXEL_PACK_BUFFER,s,e.STREAM_READ)),ue(e,()=>e.readPixels(0,0,a,t,e.RGBA,e.FLOAT,0)),ue(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,null)),r}function P6(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 F6(e,t,a,n){let[r,s]=pp(t,a),i=4,o=new Uint8Array(QW(t*a,i));return ue(e,()=>e.readPixels(0,0,r,s,n.downloadTextureFormat,e.UNSIGNED_BYTE,o)),new Float32Array(o.buffer)}function O6(e,t,a,n,r,s,i,o){let l=e,u=new Float32Array(eV(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 D6(e,t,a){let n=new Float32Array(t*a*4);return ue(e,()=>e.readPixels(0,0,a,t,e.RGBA,e.FLOAT,n)),n}var sl=class{constructor(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.itemsToPoll=[];let t=V().getNumber("WEBGL_VERSION");if(e!=null?(this.gl=e,Eh(t,e)):this.gl=Dn(t),e=this.gl,V().getNumber("WEBGL_VERSION")===2){let r=e;this.createVertexArray=()=>ue(r,()=>r.createVertexArray()),this.bindVertexArray=s=>ue(r,()=>r.bindVertexArray(s)),this.deleteVertexArray=s=>ue(r,()=>r.deleteVertexArray(s)),this.getVertexArray=()=>ue(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=()=>ue(e,()=>r.createVertexArrayOES()),this.bindVertexArray=s=>ue(e,()=>r.bindVertexArrayOES(s)),this.deleteVertexArray=s=>ue(e,()=>r.deleteVertexArrayOES(s)),this.getVertexArray=()=>ue(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"),V().getNumber("WEBGL_VERSION")===1){let r="OES_texture_float",s="OES_texture_half_float";if(this.textureFloatExtension=ju(this.gl,r),fn(this.gl,s))this.textureHalfFloatExtension=ju(this.gl,s);else if(V().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=ju(this.gl,n);else if(V().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=w6(this.gl),this.indexBuffer=I6(this.gl),this.framebuffer=a6(this.gl),this.textureConfig=b3(this.gl,this.textureHalfFloatExtension)}get debug(){return V().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;ue(e,()=>e.finish()),ue(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),ue(e,()=>e.deleteFramebuffer(this.framebuffer)),ue(e,()=>e.bindBuffer(e.ARRAY_BUFFER,null)),ue(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null)),ue(e,()=>e.deleteBuffer(this.indexBuffer)),this.disposed=!0}createFloat32MatrixTexture(e,t){return this.throwIfDisposed(),S6(this.gl,e,t,this.textureConfig)}createFloat16MatrixTexture(e,t){return this.throwIfDisposed(),T6(this.gl,e,t,this.textureConfig)}createUnsignedBytesMatrixTexture(e,t){return this.throwIfDisposed(),C6(this.gl,e,t,this.textureConfig)}uploadPixelDataToTexture(e,t){this.throwIfDisposed(),$6(this.gl,e,t)}uploadDenseMatrixToTexture(e,t,a,n){this.throwIfDisposed(),M6(this.gl,e,t,a,n,this.textureConfig)}createFloat16PackedMatrixTexture(e,t){return this.throwIfDisposed(),E6(this.gl,e,t,this.textureConfig)}createPackedMatrixTexture(e,t){return this.throwIfDisposed(),N6(this.gl,e,t,this.textureConfig)}deleteMatrixTexture(e){this.throwIfDisposed(),this.outputTexture===e&&(A2(this.gl,this.framebuffer),this.outputTexture=null),ue(this.gl,()=>this.gl.deleteTexture(e))}downloadByteEncodedFloatMatrixFromOutputTexture(e,t,a){return this.downloadMatrixDriver(e,()=>F6(this.gl,t,a,this.textureConfig))}downloadPackedMatrixFromBuffer(e,t,a,n,r,s){return O6(this.gl,e,t,a,n,r,s,this.textureConfig)}downloadFloat32MatrixFromBuffer(e,t){return P6(this.gl,e,t)}createBufferFromTexture(e,t,a){this.bindTextureToFrameBuffer(e);let n=_6(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(V().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 V().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(t=this.beginQuery(),this.endQuery(),a=()=>this.isQueryAvailable(t,V().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))):a=()=>!0;return{query:t,isFencePassed:a}}downloadMatrixFromPackedTexture(e,t,a){return this.downloadMatrixDriver(e,()=>D6(this.gl,t,a))}createProgram(e){this.throwIfDisposed();let t=this.gl;this.vertexShader==null&&(this.vertexShader=k6(t));let a=Z7(t);ue(t,()=>t.attachShader(a,this.vertexShader)),ue(t,()=>t.attachShader(a,e)),Y7(t,a);let n;return n=Object.assign(a,{vao:this.createVertexArray()}),this.bindVertexArray(n.vao),ue(t,()=>t.bindBuffer(t.ELEMENT_ARRAY_BUFFER,this.indexBuffer)),console.assert(R6(t,n,this.vertexBuffer),"gpgpu_util.bindVertexProgramAttributeStreams not fully successful."),this.debug&&Ac(t,n),this.setProgram(n),n}deleteProgram(e){this.throwIfDisposed(),e===this.program&&(this.program=null),e!=null&&(ue(this.gl,()=>this.gl.deleteProgram(e)),this.deleteVertexArray(e.vao))}setProgram(e){this.throwIfDisposed(),this.program=e,this.program!=null&&(this.bindVertexArray(this.program.vao),this.debug&&Ac(this.gl,this.program)),ue(this.gl,()=>this.gl.useProgram(e))}getUniformLocation(e,t,a=!0){return this.throwIfDisposed(),a?r6(this.gl,e,t):s6(this.gl,e,t)}getAttributeLocation(e,t){return this.throwIfDisposed(),ue(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(),i6(this.gl,e,t,a)}setOutputMatrixTexture(e,t,a){this.setOutputMatrixTextureDriver(e,a,t)}setOutputPackedMatrixTexture(e,t,a){this.throwIfDisposed();let[n,r]=lu(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&&Ac(this.gl,this.program),qu(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()}ue(e,()=>e.drawElements(e.TRIANGLES,6,e.UNSIGNED_SHORT,0))}blockUntilAllProgramsCompleted(){this.throwIfDisposed(),ue(this.gl,()=>this.gl.finish())}getQueryTimerExtension(){return this.disjointQueryTimerExtension==null&&(this.disjointQueryTimerExtension=ju(this.gl,V().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(V().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(V().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,V().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))),this.getQueryTime(e,V().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=rU(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 V().platform&&(a=V().platform.setTimeoutCustom.bind(V().platform)),v.repeatedTry(()=>(this.pollItems(),this.itemsToPoll.length===0),()=>0,null,a)}bindTextureToFrameBuffer(e){this.throwIfDisposed(),bc(this.gl,e,this.framebuffer),this.debug&&qu(this.gl)}unbindTextureToFrameBuffer(){this.outputTexture!=null?(bc(this.gl,this.outputTexture,this.framebuffer),this.debug&&qu(this.gl)):A2(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;bc(n,e,this.framebuffer),this.debug&&qu(n),this.outputTexture=e,ue(n,()=>n.viewport(0,0,t,a)),ue(n,()=>n.scissor(0,0,t,a))}setOutputMatrixWriteRegionDriver(e,t,a,n){this.throwIfDisposed(),ue(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 rU(e){let t=0;for(;t<e.length&&e[t]();++t);return t-1}var{addImpl:sU,bincountImpl:z6,bincountReduceImpl:iU,castImpl:oU,ceilImpl:lU,concatImpl:uU,equalImpl:dU,expImpl:pU,expm1Impl:cU,floorImpl:hU,gatherNdImpl:fU,gatherV2Impl:mU,greaterImpl:gU,greaterEqualImpl:yU,lessImpl:xU,lessEqualImpl:AU,linSpaceImpl:bU,logImpl:vU,maxImpl:kU,maximumImpl:wU,minimumImpl:IU,multiplyImpl:SU,negImpl:TU,notEqualImpl:CU,prodImpl:NU,raggedGatherImpl:EU,raggedRangeImpl:RU,raggedTensorToTensorImpl:MU,rangeImpl:$U,rsqrtImpl:_U,scatterImpl:PU,sigmoidImpl:FU,simpleAbsImpl:L6,sliceImpl:OU,sparseFillEmptyRowsImpl:DU,sparseReshapeImpl:zU,sparseSegmentReductionImpl:B6,sqrtImpl:LU,stridedSliceImpl:BU,stringNGramsImpl:WU,stringSplitImpl:VU,stringToHashBucketFastImpl:UU,subImpl:GU,tileImpl:HU,topKImpl:jU,transposeImpl:R3,uniqueImpl:qU}=Ch;function W6(e,t){return["x","y","z","w","u","v"].slice(0,t).map(a=>`${e}.${a}`)}function ka(e,t){return t===1?[e]:W6(e,t)}function XU(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 KU=class{constructor(e){if(this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.enableShapeUniforms=Ea(this.outputShape.length),this.rank===0)this.userCode=`
|
|
void main() {
|
|
setOutput(vec4(getA(), 0., 0., 0.));
|
|
}
|
|
`;else{let t=ka("rc",this.rank),a=gt(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]})`}},V6=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"inputShape",type:"ivec3"}],this.outputShape=e,this.enableShapeUniforms=Ea(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=`
|
|
${ZU(t,this.enableShapeUniforms)}
|
|
${this.enableShapeUniforms?w3():k3(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 ZU(e,t){return`
|
|
ivec3 inputCoordsFromReshapedOutCoords(int index) {
|
|
${t?cV(["r","c","d"],"inputShape"):Ao(["r","c","d"],e)}
|
|
return ivec3(r, c, d);
|
|
}
|
|
`}var YU=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(e,t,a){let n=cy(t,a),r=hy(e,n,a);r in this.freeTextures||(this.freeTextures[r]=[]),r in this.usedTextures||(this.usedTextures[r]=[]);let s=py(e,n,this.gpgpu.gl,this.gpgpu.textureConfig,a);if(this.freeTextures[r].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=s,this.log();let o=this.freeTextures[r].shift();return this.usedTextures[r].push(o),o}let i;return n===ia.PACKED_2X2_FLOAT32?i=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):n===ia.PACKED_2X2_FLOAT16?i=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):n===ia.UNPACKED_FLOAT32?i=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):n===ia.UNPACKED_FLOAT16?i=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):n===ia.PACKED_4X1_UNSIGNED_BYTE&&(i=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[r].push(i),this.numUsedTextures++,this._numBytesAllocated+=s,this.log(),i}releaseTexture(e,t,a,n){if(this.freeTextures==null)return;let r=cy(a,n),s=hy(t,r,n);s in this.freeTextures||(this.freeTextures[s]=[]);let i=py(t,r,this.gpgpu.gl,this.gpgpu.textureConfig,n),o=V().get("WEBGL_DELETE_TEXTURE_THRESHOLD");o!==-1&&this._numBytesAllocated>o?(this.gpgpu.deleteMatrixTexture(e.texture),this._numBytesAllocated-=i):(this.freeTextures[s].push(e),this.numFreeTextures++,this._numBytesFree+=i),this.numUsedTextures--;let l=this.usedTextures[s],u=l.indexOf(e);if(u<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l.splice(u,1),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${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 JU(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 py(e,t,a,n,r){let s=QU(t,n),i;if(r){let[l,u]=lu(e[0],e[1]);i=l*u}else{let[l,u]=pp(e[0],e[1]);i=l*u}let o=JU(a,s);return i*o}function QU(e,t){switch(e){case ia.PACKED_2X2_FLOAT32:return N3(t);case ia.PACKED_2X2_FLOAT16:return E3(t);case ia.UNPACKED_FLOAT32:return S3(t);case ia.UNPACKED_FLOAT16:return T3(t);case ia.PACKED_4X1_UNSIGNED_BYTE:return C3(t);default:throw new Error(`Unknown physical texture type ${e}`)}}function eG(e){return V().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?e?ia.PACKED_2X2_FLOAT32:ia.UNPACKED_FLOAT32:e?ia.PACKED_2X2_FLOAT16:ia.UNPACKED_FLOAT16}function cy(e,t){if(e===hn.UPLOAD)return ia.PACKED_2X2_FLOAT32;if(e===hn.RENDER||e==null)return eG(t);if(e===hn.DOWNLOAD||e===hn.PIXELS)return ia.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${e}`)}function hy(e,t,a){return`${e[0]}_${e[1]}_${t}_${a}`}var qn=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.enableShapeUniforms=Ea(this.outputShape.length),this.userCode=`
|
|
float unaryOperation(float x) {
|
|
${t}
|
|
}
|
|
|
|
void main() {
|
|
float x = getAAtOutCoords();
|
|
float y = unaryOperation(x);
|
|
|
|
setOutput(y);
|
|
}
|
|
`}},En="if (isnan(x)) return x;",tG="return x;",fy="return abs(x);",aG="return (x >= 0.0) ? x : (exp(x) - 1.0);",nG=En+`
|
|
return (x < 0.0) ? 0.0 : x;
|
|
`,rG=En+`
|
|
return (x < 0.0) ? 0.0 : min(6.0, x);
|
|
`,Or="return x;",sG="return 1.0 / (1.0 + exp(-1.0 * x));",iG="return x;",oG=`
|
|
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;
|
|
`,lG=`
|
|
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;
|
|
`,uG=`
|
|
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;
|
|
`,dG="return 1.0 / (1.0 + exp(-1.0 * x));",Wr=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.enableShapeUniforms=Ea(this.outputShape.length),this.userCode=`
|
|
vec4 unaryOperation(vec4 x) {
|
|
${t}
|
|
}
|
|
|
|
void main() {
|
|
vec4 x = getAAtOutCoords();
|
|
vec4 y = unaryOperation(x);
|
|
|
|
setOutput(y);
|
|
}
|
|
`}},pG=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=e,this.enableShapeUniforms=Ea(this.outputShape.length);let t=e.length,a=ka("rc",t),n=gt(t),r=XU(t,a),s=a.slice(-2),i=t<=1?"rc":`vec2(${s.join(",")})`;this.userCode=`
|
|
void main() {
|
|
${n} rc = getOutputCoords();
|
|
vec4 packedInput = getA(${r});
|
|
|
|
setOutput(getChannel(packedInput, ${i}));
|
|
}
|
|
`}},cG=Nn.whereImpl,hG=1e-7,fG=1e-4,Fm={};function mG(e){return e in Fm||(Fm[e]={}),Fm[e]}var gG=V().getNumber("CPU_HANDOFF_SIZE_THRESHOLD"),yG=600;function xG(){return V().global.screen==null?1024:V().global.screen.height*V().global.screen.width*window.devicePixelRatio*yG/1024/1024}var fu=class extends Al{constructor(e){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,!V().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");let t;if(e!=null){if(e instanceof sl)t=e;else{let a=Dn(V().getNumber("WEBGL_VERSION"),e);t=new sl(a)}this.binaryCache={},this.gpgpuCreatedLocally=!1}else{let a=Dn(V().getNumber("WEBGL_VERSION"));t=new sl(a),this.binaryCache=mG(V().getNumber("WEBGL_VERSION")),this.gpgpuCreatedLocally=!0}this.gpgpu=t,this.canvas=this.gpgpu.gl.canvas,this.textureManager=new YU(this.gpgpu),this.numMBBeforeWarning=xG(),this.texData=new kd(this,vt())}nextDataId(){return fu.nextDataId++}numDataIds(){return this.texData.numDataIds()-this.pendingDeletes}writeTexture(e,t,a,n,r,s){let i=this.makeTensorInfo(t,a),o=this.texData.get(i.dataId);o.isPacked=!1,o.texture={texture:e,texShape:[n,r]},o.texShape=[n,r];let l=Xu(t),u=new dy(l,!1,s),p=this.runWebGLProgram(u,[i],a,[[n,r]]);return p.shape=t,o.texture=null,this.disposeIntermediateTensorInfo(i),p.dataId}write(e,t,a){if((V().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||V().getBool("DEBUG"))&&this.checkNumericalProblems(e),a==="complex64"&&e!=null)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let n={id:this.nextDataId()};return this.texData.set(n,{shape:t,dtype:a,values:e,usage:hn.UPLOAD,refCount:1}),n}refCount(e){return this.texData.has(e)?this.texData.get(e).refCount:0}incRef(e){let t=this.texData.get(e);t.refCount++}decRef(e){if(this.texData.has(e)){let t=this.texData.get(e);t.refCount--}}move(e,t,a,n,r){if(V().getBool("DEBUG")&&this.checkNumericalProblems(t),n==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(e,{shape:a,dtype:n,values:t,usage:hn.UPLOAD,refCount:r})}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}readSync(e){let t=this.texData.get(e),{values:a,dtype:n,complexTensorInfos:r,slice:s,shape:i,isPacked:o}=t;if(s!=null){let c;o?c=new Wr(i,Or):c=new qn(i,Or);let d=this.runWebGLProgram(c,[{dataId:e,shape:i,dtype:n}],n),h=this.readSync(d.dataId);return this.disposeIntermediateTensorInfo(d),h}if(a!=null)return this.convertAndCacheOnCPU(e);if(n==="string")return a;let l=this.activeTimers!=null,u;l&&(u=v.now());let p;if(n==="complex64"){let c=this.readSync(r.real.dataId),d=this.readSync(r.imag.dataId);p=T.mergeRealAndImagArrays(c,d)}else p=this.getValuesFromTexture(e);return l&&(this.downloadWaitMs+=v.now()-u),this.convertAndCacheOnCPU(e,p)}async read(e){if(this.pendingRead.has(e)){let h=this.pendingRead.get(e);return new Promise(f=>h.push(f))}let t=this.texData.get(e),{values:a,shape:n,slice:r,dtype:s,complexTensorInfos:i,isPacked:o}=t;if(r!=null){let h;o?h=new Wr(n,Or):h=new qn(n,Or);let f=this.runWebGLProgram(h,[{dataId:e,shape:n,dtype:s}],s),m=this.read(f.dataId);return this.disposeIntermediateTensorInfo(f),m}if(a!=null)return this.convertAndCacheOnCPU(e);if(V().getBool("DEBUG")&&!V().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&V().getNumber("WEBGL_VERSION")===2)throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");let l=null,u;if(s!=="complex64"&&V().get("WEBGL_BUFFER_SUPPORTED")){u=this.decode(e);let h=this.texData.get(u.dataId);l=this.gpgpu.createBufferFromTexture(h.texture.texture,...cc(n))}this.pendingRead.set(e,[]),s!=="complex64"&&await this.gpgpu.createAndWaitForFence();let p;if(s==="complex64"){let h=await Promise.all([this.read(i.real.dataId),this.read(i.imag.dataId)]),f=h[0],m=h[1];p=T.mergeRealAndImagArrays(f,m)}else if(l==null)p=this.getValuesFromTexture(e);else{let h=v.sizeFromShape(n);p=this.gpgpu.downloadFloat32MatrixFromBuffer(l,h)}if(u!=null&&this.disposeIntermediateTensorInfo(u),l!=null){let h=this.gpgpu.gl;ue(h,()=>h.deleteBuffer(l))}let c=this.convertAndCacheOnCPU(e,p),d=this.pendingRead.get(e);return this.pendingRead.delete(e),d.forEach(h=>h(c)),this.pendingDisposal.has(e)&&(this.pendingDisposal.delete(e),this.disposeData(e)&&vt().removeDataId(e,this),this.pendingDeletes--),c}readToGPU(e,t={}){let a=this.texData.get(e),{values:n,shape:r,slice:s,dtype:i,isPacked:o,texture:l}=a;if(i==="complex64")throw new Error("Does not support reading texture for complex64 dtype.");if(s!=null){let d;o?d=new Wr(r,Or):d=new qn(r,Or);let h=this.runWebGLProgram(d,[{dataId:e,shape:r,dtype:i}],i),f=this.readToGPU(h,t);return this.disposeIntermediateTensorInfo(h),f}if(l==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 u=this.decode(e,t.customTexShape),p=vt().makeTensorFromTensorInfo(u),c=this.texData.get(u.dataId);return Object.assign({tensorRef:p},c.texture)}bufferSync(e){let t=this.readSync(e.dataId);if(e.dtype==="string")try{let a=t.map(n=>v.decodeString(n));return _e(e.shape,e.dtype,a)}catch(a){throw new Error("Failed to decode encoded string bytes into utf-8")}return _e(e.shape,e.dtype,t)}checkNumericalProblems(e){if(e!=null)for(let t=0;t<e.length;t++){let a=e[t];if(!j7(a))throw V().getBool("WEBGL_RENDER_FLOAT32_CAPABLE")?Error(`The value ${a} cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`):Error(`The value ${a} cannot be represented on this device.`)}}getValuesFromTexture(e){let{shape:t,dtype:a,isPacked:n}=this.texData.get(e),r=v.sizeFromShape(t);if(V().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let c=this.decode(e),d=this.texData.get(c.dataId),h=this.gpgpu.downloadMatrixFromPackedTexture(d.texture.texture,...cc(t)).subarray(0,r);return this.disposeIntermediateTensorInfo(c),h}let s=V().getBool("WEBGL_PACK")&&n===!0,i=s?Xu(t):t,o=s?new tU(i):new eU(i),l=this.runWebGLProgram(o,[{shape:i,dtype:a,dataId:e}],"float32"),u=this.texData.get(l.dataId),p=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(u.texture.texture,u.texShape[0],u.texShape[1]).subarray(0,r);return this.disposeIntermediateTensorInfo(l),p}timerAvailable(){return V().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}time(e){let t=this.activeTimers,a=[],n=!1;this.programTimersStack==null?(this.programTimersStack=a,n=!0):this.activeTimers.push(a),this.activeTimers=a,e();let r=v.flatten(this.activeTimers.map(o=>o.query)).filter(o=>o!=null),s=v.flatten(this.activeTimers.map(o=>o.name)).filter(o=>o!=null);this.activeTimers=t,n&&(this.programTimersStack=null);let i={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};return(async()=>{if(V().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let o=await Promise.all(r);i.kernelMs=v.sum(o),i.getExtraProfileInfo=()=>o.map((l,u)=>({name:s[u],ms:l})).map(l=>`${l.name}: ${l.ms}`).join(", ")}else i.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,i})()}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return V().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:v.now(),endMs:null}}endTimer(e){return V().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=v.now(),e)}async getQueryTime(e){if(V().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)return this.gpgpu.waitForQueryAndGetTime(e);let t=e;return t.endMs-t.startMs}disposeData(e,t=!1){if(this.pendingDisposal.has(e))return!1;if(!this.texData.has(e))return!0;if(t?this.texData.get(e).refCount=0:this.texData.get(e).refCount--,!t&&this.texData.get(e).refCount>0)return!1;if(this.pendingRead.has(e))return this.pendingDisposal.add(e),this.pendingDeletes++,!1;this.releaseGPUData(e);let{complexTensorInfos:a}=this.texData.get(e);return a!=null&&(this.disposeData(a.real.dataId,t),this.disposeData(a.imag.dataId,t)),this.texData.delete(e),!0}releaseGPUData(e){let{texture:t,dtype:a,texShape:n,usage:r,isPacked:s,slice:i}=this.texData.get(e),o=i&&i.origDataId||e,l=this.dataRefCount.get(o);l>1?this.dataRefCount.set(o,l-1):(this.dataRefCount.delete(o),t!=null&&(this.numBytesInGPU-=this.computeBytes(n,a),this.textureManager.releaseTexture(t,n,r,s)));let u=this.texData.get(e);u.texture=null,u.texShape=null,u.isPacked=!1,u.slice=null}getTexture(e){return this.uploadToGPU(e),this.texData.get(e).texture.texture}getDataInfo(e){return this.texData.get(e)}shouldExecuteOnCPU(e,t=gG){return V().getBool("WEBGL_CPU_FORWARD")&&e.every(a=>this.texData.get(a.dataId).texture==null&&v.sizeFromShape(a.shape)<t)}getGPGPUContext(){return this.gpgpu}where(e){T.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let t=e.dataSync();return cG(e.shape,t)}packedUnaryOp(e,t,a){let n=new Wr(e.shape,t),r=this.compileAndRun(n,[e],a);return vt().makeTensorFromTensorInfo(r)}abs(e){if(this.shouldExecuteOnCPU([e])&&e.dtype!=="complex64"){let n=L6(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,n)}if(V().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,fy,e.dtype);let t=new qn(e.shape,fy),a=this.compileAndRun(t,[e]);return vt().makeTensorFromTensorInfo(a)}makeTensorInfo(e,t,a){let n;if(t==="string"&&a!=null&&a.length>0&&v.isString(a[0])){let r=a.map(s=>v.encodeString(s));n=this.write(r,e,t)}else n=this.write(a,e,t);return this.texData.get(n).usage=null,{dataId:n,shape:e,dtype:t}}makeOutput(e,t,a){return vt().makeTensorFromTensorInfo(this.makeTensorInfo(e,t,a),this)}unpackTensor(e){let t=new pG(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){let t=new KU(e.shape),a=!0;return this.runWebGLProgram(t,[e],e.dtype,null,a)}packedReshape(e,t){let a=[Hs(e.shape),...js(e.shape)],n={dtype:e.dtype,shape:a,dataId:e.dataId},r=[Hs(t),...js(t)],s=new V6(r,a),i=!0,o=[a],l=this.runWebGLProgram(s,[n],e.dtype,o,i);return{dataId:l.dataId,shape:t,dtype:l.dtype}}decode(e,t){let a=this.texData.get(e),{isPacked:n,shape:r,dtype:s}=a;if(t!=null){let c=v.sizeFromShape(r),d=t[0]*t[1]*4;v.assert(c<=d,()=>"customTexShape is too small. Row * Column * 4 should be equal or larger than the size of the tensor data.")}let i=Xu(r),o;n?o=new QV(i):o=new JV(i);let l=!0,u=[t!=null?t:cc(i)],p=this.runWebGLProgram(o,[{shape:i,dtype:s,dataId:e}],s,u,l,t);return{dtype:s,shape:r,dataId:p.dataId}}runWebGLProgram(e,t,a,n,r=!1,s){let i=this.makeTensorInfo(e.outputShape,a),o=this.texData.get(i.dataId);if(e.packedOutput&&(o.isPacked=!0),e.outPackingScheme===md.DENSE){let g=s!=null?s:cc(e.outputShape);o.texShape=g.map(y=>y*2)}if(e.outTexUsage!=null&&(o.usage=e.outTexUsage),v.sizeFromShape(i.shape)===0)return o.values=v.getTypedArrayFromDType(i.dtype,0),i;let l=[],u=t.map(g=>{if(g.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let y=this.texData.get(g.dataId);if(y.texture==null){if(!e.packedInputs&&v.sizeFromShape(g.shape)<=V().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:g.shape,texData:null,isUniform:!0,uniformValues:y.values};e.packedInputs&&(y.isPacked=!0,y.shape=g.shape)}if(this.uploadToGPU(g.dataId),!!y.isPacked!=!!e.packedInputs)g=y.isPacked?this.unpackTensor(g):this.packTensor(g),l.push(g),y=this.texData.get(g.dataId);else if(y.isPacked&&!gd(y.shape,g.shape)){let x=g,A=g.shape;g.shape=y.shape,g=this.packedReshape(g,A),l.push(g),y=this.texData.get(g.dataId),x.shape=A}return{shape:g.shape,texData:y,isUniform:!1}});this.uploadToGPU(i.dataId);let p={shape:i.shape,texData:o,isUniform:!1},c=YV(e,u,p),d=this.getAndSaveBinary(c,()=>KV(this.gpgpu,e,u,p)),h=this.activeTimers!=null,f;h&&(f=this.startTimer()),V().get("ENGINE_COMPILE_ONLY")||ZV(this.gpgpu,d,u,p,n),l.forEach(g=>this.disposeIntermediateTensorInfo(g)),h&&(f=this.endTimer(f),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(f)}));let m=V().get("WEBGL_FLUSH_THRESHOLD");if(m>0){let g=v.now();g-this.lastGlFlushTime>m&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=g)}if(!V().getBool("WEBGL_LAZILY_UNPACK")&&o.isPacked&&r===!1){let g=this.unpackTensor(i);return this.disposeIntermediateTensorInfo(i),g}return i}compileAndRun(e,t,a,n,r=!1){return a=a||t[0].dtype,this.runWebGLProgram(e,t,a,n,r)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(V().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(e=>{this.gpgpu.deleteProgram(this.binaryCache[e].webGLProgram),delete this.binaryCache[e]}),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=Oe(()=>{if(!V().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=V().getBool("DEBUG");V().set("DEBUG",!1);let t=this.abs(ze(1e-8)).dataSync()[0];if(V().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?hG:fG}uploadToGPU(e){let t=this.texData.get(e),{shape:a,dtype:n,values:r,texture:s,usage:i,isPacked:o}=t;if(s!=null)return;let l=this.activeTimers!=null,u;l&&(u=v.now());let p=t.texShape;if(p==null&&(p=u6(a,o),t.texShape=p),r!=null){let c=Xu(a),d,h=p[1],f=p[0],m=r instanceof Uint8Array||r instanceof Uint8ClampedArray;(o||!m)&&([h,f]=lu(p[0],p[1])),o?d=new nU(c,m):d=new dy(c,m);let g=m?[f,h]:p,y=this.makeTensorInfo(g,n),x=this.texData.get(y.dataId);m?x.usage=hn.PIXELS:x.usage=hn.UPLOAD,x.texShape=g,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(y.dataId),h,f,r);let A=[[f,h]],b=!0,k=this.runWebGLProgram(d,[y],n,A,b),S=this.texData.get(k.dataId);t.texShape=S.texShape,t.isPacked=S.isPacked,t.usage=S.usage,V().get("ENGINE_COMPILE_ONLY")?this.disposeData(k.dataId):(t.texture=S.texture,t.values=null,this.texData.delete(k.dataId)),this.disposeIntermediateTensorInfo(y),l&&(this.uploadWaitMs+=v.now()-u)}else{let c=this.acquireTexture(p,i,n,o);t.texture=c}}convertAndCacheOnCPU(e,t){let a=this.texData.get(e),{dtype:n}=a;return t!=null&&(a.values=AG(t,n)),a.values}acquireTexture(e,t,a,n){if(this.numBytesInGPU+=this.computeBytes(e,a),!this.warnedAboutMemory&&this.numBytesInGPU>this.numMBBeforeWarning*1024*1024){let r=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(`High memory usage in GPU: ${r} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(e,t,n)}computeBytes(e,t){return e[0]*e[1]*v.bytesPerElement(t)}checkCompileCompletion(){for(let[,e]of Object.entries(this.binaryCache))this.checkCompletion_(e)}async checkCompileCompletionAsync(){let e=[];if(this.gpgpu.parallelCompilationExtension){for(let[,t]of Object.entries(this.binaryCache))e.push(this.checkCompletionAsync_(t));return Promise.all(e)}else{for(let[,t]of Object.entries(this.binaryCache)){let a=new Promise(n=>{try{this.checkCompletion_(t),n(!0)}catch(r){throw r}});e.push(a)}return Promise.all(e)}}async checkCompletionAsync_(e){return this.gpgpu.gl.getProgramParameter(e.webGLProgram,this.gpgpu.parallelCompilationExtension.COMPLETION_STATUS_KHR)?this.checkCompletion_(e):(await A4(),this.checkCompletionAsync_(e))}checkCompletion_(e){if(this.gpgpu.gl.getProgramParameter(e.webGLProgram,this.gpgpu.gl.LINK_STATUS)===!1)throw console.log(this.gpgpu.gl.getProgramInfoLog(e.webGLProgram)),this.gpgpu.gl.getShaderParameter(e.fragmentShader,this.gpgpu.gl.COMPILE_STATUS)===!1?(v3(e.source,this.gpgpu.gl.getShaderInfoLog(e.fragmentShader)),new Error("Failed to compile fragment shader.")):new Error("Failed to link vertex and fragment shaders.");return!0}getUniformLocations(){for(let[,e]of Object.entries(this.binaryCache)){let{uniformLocations:t,customUniformLocations:a,infLoc:n,nanLoc:r,inShapesLocations:s,inTexShapesLocations:i,outShapeLocation:o,outShapeStridesLocation:l,outTexShapeLocation:u}=b6(this.gpgpu,e.program,e.webGLProgram);e.uniformLocations=t,e.customUniformLocations=a,e.infLoc=n,e.nanLoc=r,e.inShapesLocations=s,e.inTexShapesLocations=i,e.outShapeLocation=o,e.outShapeStridesLocation=l,e.outTexShapeLocation=u}}createTensorFromGPUData(e,t,a){e.channels=e.channels||"RGBA";let{texture:n,height:r,width:s,channels:i}=e,o=vt().backend;if(!o.gpgpu.gl.isTexture(n))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 l=o.writeTexture(n,t,a,r,s,i);return vt().makeTensorFromDataId(l,t,a,o)}};fu.nextDataId=0;function AG(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 bG="4.2.0";function U6(){V().set("WEBGL_FORCE_F16_TEXTURES",!0)}Kd.isBrowser()&&yo("webgl",()=>new fu,2);var vG={forceHalfFloat:U6},M3=`
|
|
if (isnan(a)) return a;
|
|
if (isnan(b)) return b;
|
|
`,yl=class{constructor(e,t,a){this.variableNames=["A","B"],this.outputShape=T.assertAndGetBroadcastShape(t,a),this.enableShapeUniforms=Ea(this.outputShape.length),this.userCode=`
|
|
float binaryOperation(float a, float b) {
|
|
${e}
|
|
}
|
|
|
|
void main() {
|
|
float a = getAAtOutCoords();
|
|
float b = getBAtOutCoords();
|
|
setOutput(binaryOperation(a, b));
|
|
}
|
|
`}},hp=`
|
|
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;
|
|
`,fp=class{constructor(e,t,a,n=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=T.assertAndGetBroadcastShape(t,a);let r=this.outputShape.length;this.enableShapeUniforms=Ea(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=`
|
|
${gt(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 Ja(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 kG={kernelName:wi,backendName:"webgl",kernelFunc:Ja};function ls(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=Ja({inputs:{x:n},backend:a}),l=Ja({inputs:{x:r},backend:a});return i.complexTensorInfos={real:o,imag:l},s}var wG={kernelName:Td,backendName:"webgl",kernelFunc:ls},G6="return (a < 0.) ? b * a : a;",H6=`
|
|
vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
|
|
return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
|
|
`;function IG(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{alpha:s}=n,i=a.makeTensorInfo([],"float32",v.createScalarValue(s,"float32")),o=V().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new fp(H6,r.shape,i.shape):new yl(G6,r.shape,i.shape),l=a.runWebGLProgram(o,[r,i],"float32");return a.disposeIntermediateTensorInfo(i),l}var SG={kernelName:Si,backendName:"webgl",kernelFunc:IG},j6="return (a < 0.) ? b * a : a;",q6=`
|
|
vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
|
|
return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
|
|
`;function TG(e){let{inputs:t,backend:a}=e,{x:n,alpha:r}=t,s=V().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new fp(q6,n.shape,r.shape):new yl(j6,n.shape,r.shape);return a.runWebGLProgram(s,[n,r],"float32")}var CG={kernelName:ji,backendName:"webgl",kernelFunc:TG},mu="if (isnan(x)) return x;";function Qe({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=V().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,p;return u?p=new Wr(i.shape,t):p=new qn(i.shape,e),o.runWebGLProgram(p,[i],l)}}function da({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 f=p.texData.get(l.dataId),m=p.texData.get(u.dataId),[g,y]=[[f.complexTensorInfos.real,m.complexTensorInfos.real],[f.complexTensorInfos.imag,m.complexTensorInfos.imag]].map(A=>{let[b,k]=A,S={dataId:b.dataId,dtype:b.dtype,shape:l.shape},C={dataId:k.dataId,dtype:k.dtype,shape:u.shape},N=new yl(e,l.shape,u.shape);return p.runWebGLProgram(N,[S,C],fa(b.dtype,k.dtype))}),x=ls({inputs:{real:g,imag:y},backend:p});return p.disposeIntermediateTensorInfo(g),p.disposeIntermediateTensorInfo(y),x}let c=s||fa(l.dtype,u.dtype);if((l.dtype==="string"||u.dtype==="string"||p.shouldExecuteOnCPU([l,u]))&&r!=null){let f=p.texData.get(l.dataId).values,m=p.texData.get(u.dataId).values,g=l.dtype==="string"?T.fromUint8ToStringArray(f):f,y=l.dtype==="string"?T.fromUint8ToStringArray(m):m,[x,A]=r(l.shape,u.shape,g,y,c),b=p.makeTensorInfo(A,c),k=p.texData.get(b.dataId);return k.values=x,b}let d=V().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,h;return d?h=new fp(t,l.shape,u.shape,a):h=new yl(e,l.shape,u.shape),p.runWebGLProgram(h,[l,u],c)}}function yd(e,t=!1){if(e==="linear")return t?iG:tG;if(e==="relu")return t?lG:nG;if(e==="elu")return t?oG:aG;if(e==="relu6")return t?uG:rG;if(e==="prelu")return t?q6:j6;if(e==="leakyrelu")return t?H6:G6;if(e==="sigmoid")return t?dG:sG;throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}var X6=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=Ea(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"],f=r?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],m="",g="";i&&(o?m=`vec4 activation(vec4 a) {
|
|
vec4 b = getPreluActivationWeightsAtOutCoords();
|
|
${i}
|
|
}`:l?m=`vec4 activation(vec4 a) {
|
|
vec4 b = getLeakyreluAlphaAtOutCoords();
|
|
${i}
|
|
}`:m=`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=`
|
|
${m}
|
|
// 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]} * ${f[0]});
|
|
result += (${h[1]} * ${f[1]});
|
|
}
|
|
return result;
|
|
}
|
|
|
|
void main() {
|
|
ivec3 rc = getOutputCoords();
|
|
vec4 result = dot2x2ARowBCol(rc);
|
|
|
|
${y}
|
|
|
|
${g}
|
|
|
|
setOutput(result);
|
|
}
|
|
`}},my={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},gy=class{constructor(e,t,a){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=T.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));
|
|
}
|
|
`}},yy="return a * b;";function $3(e){let{inputs:t,backend:a}=e,{a:n,b:r}=t,s=T.upcastType(n.dtype,r.dtype);if(n.dtype==="complex64"){let o=a.texData.get(n.dataId),l=a.texData.get(r.dataId),u=new gy(my.REAL,n.shape,r.shape),p=new gy(my.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"),f=ls({inputs:{real:d,imag:h},backend:a});return a.disposeIntermediateTensorInfo(d),a.disposeIntermediateTensorInfo(h),f}if(a.shouldExecuteOnCPU([n,r])){let o=a.texData.get(n.dataId),l=a.texData.get(r.dataId),[u,p]=SU(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 V().getBool("WEBGL_PACK_BINARY_OPERATIONS")?i=new fp(yy,n.shape,r.shape):i=new yl(yy,n.shape,r.shape),a.runWebGLProgram(i,[n,r],s)}var NG={kernelName:Li,backendName:"webgl",kernelFunc:$3};function EG(e,t,a){let n=[Hs(e.shape),...js(e.shape)],r={dtype:e.dtype,shape:n,dataId:e.dataId},s=[Hs(t),...js(t)],i=new V6(s,n),o=!0,l=[n],u=a.runWebGLProgram(i,[r],e.dtype,l,o);return{dataId:u.dataId,shape:t,dtype:u.dtype}}function pe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{shape:s}=n,i=a,o=v.sizeFromShape(r.shape),l=v.inferFromImplicitShape(s,o),u=v.sizeFromShape(l);v.assert(o===u,()=>`The new shape (${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&&!gd(r.shape,l)&&!(p.texture!==null&&gd(p.shape,l))?EG(r,l,i):(i.incRef(r.dataId),{dataId:r.dataId,shape:l,dtype:r.dtype})}var RG={kernelName:Hl,backendName:"webgl",kernelFunc:pe},xy=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);
|
|
|
|
${l}
|
|
}
|
|
setOutput(sumValue);
|
|
}
|
|
`}},MG=class{constructor(e,t){this.variableNames=["x"];let{windowSize:a,batchSize:n,inSize:r,outSize:s}=e;this.outputShape=[n,s];let i="0.0",o="";t==="prod"?i="1.0":t==="min"?(i="1.0 / 1e-20",o="min"):t==="max"&&(i="-1.0 / 1e-20",o="max");let l=`${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 $G(e){let t=[];for(;t.length===0||t[t.length-1].outSize!==1;){let a=t.length?t[t.length-1].outSize:e[1],n=T.computeOptimalWindowSize(a);t.push({inSize:a,windowSize:n,outSize:Math.ceil(a/n)})}return t}function vo(e,t,a,n){let r=$G(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 xy({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u},o):new xy({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u}):p=new MG({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 _G=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=gt(this.rank),r=PG(t);this.userCode=`
|
|
void main() {
|
|
${n} resRC = getOutputCoords();
|
|
setOutput(getA(${r}));
|
|
}
|
|
`}};function PG(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 FG=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 ${this.rank} is not yet supported.`);let n=gt(this.rank),r=W6("rc",this.rank),s=new Array(this.rank);for(let u=0;u<t.length;u++)s[t[u]]=r[u];let i=`vec2(${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 Mh(e,t,a){let n=V().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new FG(e.shape,t):new _G(e.shape,t);return a.runWebGLProgram(n,[e],e.dtype)}function OG(e,t,a,n){let r=t,s=e.shape.length,i=v.parseAxisParam(r,e.shape),o=i,l=T.getAxesPermutation(o,s),u=l!=null,p=e;u&&(p=Mh(e,l,n),o=T.getInnerMostAxes(o.length,s)),T.assertAxesAreInnerMostDims("sum",o,s);let[c,d]=T.computeOutAndReduceShapes(p.shape,o),h=c;a&&(h=T.expandShapeToKeepDim(c,i));let f=v.sizeFromShape(d),m=v.sizeFromShape(e.shape)/f,g=pe({inputs:{x:p},attrs:{shape:[m,f]},backend:n}),y=Xd(e.dtype),x=vo(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 $h(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;return OG(r,s,i,a)}var DG={kernelName:io,backendName:"webgl",kernelFunc:$h};function Sa(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=R3(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=Mh(r,s,i);return u}var zG={kernelName:Ar,backendName:"webgl",kernelFunc:Sa},K6=1e3;function Lc({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],f=n?t.shape[p-2]:t.shape[p-1],m=e.shape.slice(0,-2),g=t.shape.slice(0,-2),y=v.sizeFromShape(m),x=v.sizeFromShape(g),A=xo.assertAndGetBroadcastShape(e.shape.slice(0,-2),t.shape.slice(0,-2)).concat([h,f]);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=${n} must match.`);let b=a?[y,c,h]:[y,h,c],k=n?[x,f,d]:[x,d,f],S=pe({inputs:{x:e},backend:r,attrs:{shape:b}}),C=pe({inputs:{x:t},backend:r,attrs:{shape:k}}),N=[S,C],$=Math.max(y,x),M=a?S.shape[1]:S.shape[2],R=s!=null,I=i!=null,_=l==="leakyrelu",D=l!=null?yd(l,!0):null,W=R||I||_||D!=null,P;if((h===1||f===1)&&M>K6&&W===!1){let G=S,q=C;a&&(G=Sa({inputs:{x:S},backend:r,attrs:{perm:[0,2,1]}}),N.push(G)),n&&(q=Sa({inputs:{x:C},backend:r,attrs:{perm:[0,2,1]}}),N.push(q));let H=f!==1,B=f===1,Z=G;H&&(Z=pe({inputs:{x:G},backend:r,attrs:{shape:[$,M,1]}}),N.push(Z));let X=f===1?2:1,re=q;B&&(re=pe({inputs:{x:q},backend:r,attrs:{shape:[$,1,M]}}),N.push(re));let ee=$3({inputs:{a:Z,b:re},backend:r});P=$h({inputs:{x:ee},backend:r,attrs:{axis:X,keepDims:!0}}),N.push(ee)}else{let G=fa(e.dtype,t.dtype),q=new X6(b,k,[$,h,f],a,n,R,D,I,_),H=[S,C];if(s!=null&&H.push(s),I&&H.push(i),_){let B=r.makeTensorInfo([],"float32",v.createScalarValue(o,"float32"));H.push(B),N.push(B)}P=r.runWebGLProgram(q,H,G)}let U=pe({inputs:{x:P},backend:r,attrs:{shape:A}});N.push(P);for(let G of N)r.disposeIntermediateTensorInfo(G);return U}function LG(e){let{inputs:t,backend:a,attrs:n}=e,{a:r,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:u,activation:p,leakyreluAlpha:c}=n;return Lc({a:r,b:s,transposeA:l,transposeB:u,backend:a,bias:i,preluActivationWeights:o,leakyreluAlpha:c,activation:p})}var BG={kernelName:Hr,backendName:"webgl",kernelFunc:LG},Ay="return abs(x);";function WG(e){let{inputs:t,backend:a}=e,{x:n}=t;if(a.shouldExecuteOnCPU([n])&&n.dtype!=="complex64"){let s=a.texData.get(n.dataId),i=L6(s.values);return a.makeTensorInfo(n.shape,n.dtype,i)}let r;return V().getBool("WEBGL_PACK_UNARY_OPERATIONS")?r=new Wr(n.shape,Ay):r=new qn(n.shape,Ay),a.runWebGLProgram(r,[n],n.dtype)}var VG={kernelName:vl,backendName:"webgl",kernelFunc:WG},UG=En+`
|
|
if (abs(x) > 1.) {
|
|
return NAN;
|
|
}
|
|
return acos(x);
|
|
`,GG=Qe({opSnippet:UG}),HG={kernelName:kl,backendName:"webgl",kernelFunc:GG},jG=En+`
|
|
if (x < 1.0) return NAN;
|
|
return log(x + sqrt(x * x - 1.0));`,qG=Qe({opSnippet:jG}),XG={kernelName:wl,backendName:"webgl",kernelFunc:qG},by="return a + b;",KG=da({opSnippet:by,packedOpSnippet:by,supportsComplex:!0,cpuKernelImpl:sU}),ZG={kernelName:ts,backendName:"webgl",kernelFunc:KG},YG=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((r,s)=>`T${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 = ${n};
|
|
setOutput(result);
|
|
}
|
|
`}},JG=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((r,s)=>`T${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 wc(e){let{inputs:t,backend:a}=e,n=t;if(n.length===1)return Ja({inputs:{x:n[0]},backend:a});if(n.length>V().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let o=Math.floor(n.length/2),l=wc({inputs:n.slice(0,o),backend:a}),u=wc({inputs:n.slice(o),backend:a});return wc({inputs:[l,u],backend:a})}let r=n.map(o=>o.dtype).reduce((o,l)=>fa(o,l)),s=n.map(o=>o.shape),i=V().getBool("WEBGL_PACK")?new JG(n[0].shape,s):new YG(n[0].shape,s);return a.runWebGLProgram(i,n,r)}var QG={kernelName:Ks,backendName:"webgl",kernelFunc:wc};function eH(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=T.getAxesPermutation(u,o),c=r;p!=null&&(c=Sa({inputs:{x:r},backend:a,attrs:{perm:p}}),u=T.getInnerMostAxes(u.length,o)),T.assertAxesAreInnerMostDims("all",u,o);let[d,h]=T.computeOutAndReduceShapes(c.shape,u),f=v.sizeFromShape(h),m=pe({inputs:{x:c},backend:a,attrs:{shape:[-1,f]}}),g=vo(m,m.dtype,"all",a),y;if(i){let x=T.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(m),a.disposeIntermediateTensorInfo(g),p!=null&&a.disposeIntermediateTensorInfo(c),y}var tH={kernelName:Zs,backendName:"webgl",kernelFunc:eH};function aH(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=T.getAxesPermutation(u,o),c=r;p!=null&&(c=Sa({inputs:{x:r},backend:a,attrs:{perm:p}}),u=T.getInnerMostAxes(u.length,o)),T.assertAxesAreInnerMostDims("any",u,o);let[d,h]=T.computeOutAndReduceShapes(c.shape,u),f=v.sizeFromShape(h),m=pe({inputs:{x:c},backend:a,attrs:{shape:[-1,f]}}),g=vo(m,m.dtype,"any",a),y;if(i){let x=T.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(m),a.disposeIntermediateTensorInfo(g),p!=null&&a.disposeIntermediateTensorInfo(c),y}var nH={kernelName:Ys,backendName:"webgl",kernelFunc:aH},rH=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 ${i} bestValue) {
|
|
bestValue = candidate;
|
|
bestIndex = inIdx;
|
|
}
|
|
}
|
|
setOutput(float(bestIndex));
|
|
}
|
|
`}},sH=class{constructor(e,t,a,n){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,v.assert(e.length>2,()=>`Packed arg${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=gt(o),u=ka("coords",o),p,c;if(s===1){c=o+1;let C=gt(c);p=`
|
|
${C} sourceLocR = ${C}(${u.join()}, 0);
|
|
++${u[o-1]};
|
|
${C} sourceLocG = ${C}(${u.join()}, 0);
|
|
++${u[o-2]};
|
|
${C} sourceLocA = ${C}(${u.join()}, 0);
|
|
--${u[o-1]};
|
|
${C} sourceLocB = ${C}(${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],f=d.map(C=>"int "+C),m=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(${m.join()}),
|
|
getBestIndicesAChannel(${g.join()}),
|
|
getBestIndicesAChannel(${y.join()}),
|
|
getBestIndicesAChannel(${x.join()})));`,k=`vec4(
|
|
getAChannel(${m.join()}),
|
|
hasNextCol ? getAChannel(${g.join()}) : 0.,
|
|
hasNextRow ? getAChannel(${y.join()}) : 0.,
|
|
hasNextRow && hasNextCol ? getAChannel(${x.join()}) : 0.)`,S=n?"":`
|
|
float getBestIndicesAChannel(${f.join()}) {
|
|
return getChannel(getBestIndicesA(${d.join()}),
|
|
vec2(${d.slice(-2).join()}));
|
|
}`;this.userCode=`
|
|
float getAChannel(${f.join()}) {
|
|
return getChannel(getA(${d.join()}),
|
|
vec2(${d.slice(-2).join()}));
|
|
}
|
|
${S}
|
|
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 = ${k};
|
|
|
|
for (int i = 0; i < ${t}; i++) {
|
|
inIdx = srcIdx;
|
|
${b}
|
|
vec4 candidate = ${k};
|
|
bvec4 nan = isnan(candidate);
|
|
bvec4 replace = bvec4(
|
|
vec4(${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 Z6(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=T.computeOptimalWindowSize(s),o={windowSize:i,inSize:s,batchSize:r,outSize:Math.ceil(s/i)},l=new rH(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=Z6(e,t,a,p);return e.disposeIntermediateTensorInfo(p),c}function Y6(e,t,a,n=null){let r=n!=null?n.shape:t.shape,s=r[r.length-1],i=T.computeOptimalWindowSize(s),o=new sH(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=Y6(e,t,a,u);return e.disposeIntermediateTensorInfo(u),p}return u}function J6(e,t,a,n){let r=[a];if(T.assertAxesAreInnerMostDims("arg"+n.charAt(0).toUpperCase()+n.slice(1),r,t.shape.length),!V().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]=T.computeOutAndReduceShapes(l.shape,r),c=v.sizeFromShape(p),d=pe({inputs:{x:l},backend:e,attrs:{shape:[-1,c]}});s.push(d);let h=Z6(e,d,n);s.push(h);let f=pe({inputs:{x:h},backend:e,attrs:{shape:u}});return s.forEach(m=>e.disposeIntermediateTensorInfo(m)),f}return Y6(e,t,n)}function iH(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s}=n,i=v.parseAxisParam(s,r.shape),o=T.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=Sa({inputs:{x:r},backend:a,attrs:{perm:o}}),u.push(l),i=T.getInnerMostAxes(i.length,l.shape.length)),T.assertAxesAreInnerMostDims("argMax",[i[0]],l.shape.length);let p=J6(a,l,i[0],"max");return u.forEach(c=>a.disposeIntermediateTensorInfo(c)),p}var oH={kernelName:Js,backendName:"webgl",kernelFunc:iH};function lH(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s}=n,i=v.parseAxisParam(s,r.shape),o=T.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=Sa({inputs:{x:r},backend:a,attrs:{perm:o}}),u.push(l),i=T.getInnerMostAxes(i.length,l.shape.length)),T.assertAxesAreInnerMostDims("argMin",[i[0]],l.shape.length);let p=J6(a,l,i[0],"min");return u.forEach(c=>a.disposeIntermediateTensorInfo(c)),p}var uH={kernelName:Id,backendName:"webgl",kernelFunc:lH},dH=En+`
|
|
if (abs(x) > 1.) {
|
|
return NAN;
|
|
}
|
|
return asin(x);
|
|
`,pH=Qe({opSnippet:dH}),cH={kernelName:Il,backendName:"webgl",kernelFunc:pH},hH=En+"return log(x + sqrt(x * x + 1.0));",fH=Qe({opSnippet:hH}),mH={kernelName:Sl,backendName:"webgl",kernelFunc:fH},gH=En+`
|
|
return atan(x);
|
|
`,yH=Qe({opSnippet:gH}),xH={kernelName:Tl,backendName:"webgl",kernelFunc:yH},AH=M3+`
|
|
return atan(a, b);
|
|
`,bH=`
|
|
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);
|
|
`+hp+`
|
|
return result;
|
|
`,vH=da({opSnippet:AH,packedOpSnippet:bH}),kH={kernelName:Nl,backendName:"webgl",kernelFunc:vH},wH=En+`
|
|
if ((x < -1.0) || (x > 1.0)) return NAN;
|
|
return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,IH=Qe({opSnippet:wH}),SH={kernelName:Cl,backendName:"webgl",kernelFunc:IH},xd=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 f=t==="avg",m=`((batch * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,g=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,y="0.0";if(f||(y="-1.0 / 1e-20"),a){let C=">=";this.userCode=`
|
|
const ivec2 strides = ivec2(${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 ${C} currMinMaxValue) {
|
|
minMaxValue = value;
|
|
minMaxValueFound = 1.0;
|
|
minMaxPosition = ${n?r?m: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,k=s%4,S=`
|
|
if (${f}) {
|
|
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)
|
|
);
|
|
|
|
${S}
|
|
}
|
|
|
|
int xC = xCCorner + ${b};
|
|
if (${k===1}) {
|
|
vec4 values = vec4(
|
|
getValue(batch, xR, xC, d),
|
|
initializationValue,
|
|
initializationValue,
|
|
initializationValue
|
|
);
|
|
|
|
${S}
|
|
} else if (${k===2}) {
|
|
vec4 values = vec4(
|
|
getValue(batch, xR, xC, d),
|
|
getValue(batch, xR, xC + ${u}, d),
|
|
initializationValue,
|
|
initializationValue
|
|
);
|
|
|
|
${S}
|
|
} else if (${k===3}) {
|
|
vec4 values = vec4(
|
|
getValue(batch, xR, xC, d),
|
|
getValue(batch, xR, xC + ${u}, d),
|
|
getValue(batch, xR, xC + 2 * ${u}, d),
|
|
initializationValue
|
|
);
|
|
|
|
${S}
|
|
}
|
|
}
|
|
setOutput(${A});
|
|
}
|
|
`}},_3=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,f=e.effectiveFilterWidth,m=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 $=">=";this.userCode=`
|
|
const ivec3 strides =
|
|
ivec3(${i}, ${o}, ${l});
|
|
const ivec3 pads = ivec3(${m}, ${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 < ${f};
|
|
wC += ${c}) {
|
|
int xC = xCCorner + wC;
|
|
|
|
if (xC < 0 || xC >= ${e.inWidth}) {
|
|
continue;
|
|
}
|
|
|
|
float value = getX(batch, xD, xR, xC, ch);
|
|
|
|
// If a min / max value has already been found, use it. If not,
|
|
// use the current value.
|
|
float currMinMaxValue = mix(
|
|
value, minMaxValue, minMaxValueFound);
|
|
if (value ${$} currMinMaxValue) {
|
|
minMaxValue = value;
|
|
minMaxValueFound = 1.0;
|
|
minMaxPosition = ${n?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} * ${f} +
|
|
wR * ${f} + wC`};
|
|
}
|
|
}
|
|
}
|
|
}
|
|
setOutput(float(minMaxPosition));
|
|
}
|
|
`;return}let b="max",k=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(k="avgValue / max(count, 1.0)");let S=Math.floor(s/4)*4,C=s%4,N=`
|
|
if (${x}) {
|
|
avgValue += dot(values, ones);
|
|
} else {
|
|
minMaxValue = ${b}(values, minMaxValue);
|
|
}
|
|
`;this.userCode=`
|
|
const ivec3 strides =
|
|
ivec3(${i}, ${o}, ${l});
|
|
const ivec3 pads = ivec3(${m}, ${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 < ${S}; 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 + ${S};
|
|
if (${C===1}) {
|
|
vec4 values = vec4(
|
|
getValue(batch, xD, xR, xC, ch),
|
|
initializationValue,
|
|
initializationValue,
|
|
initializationValue
|
|
);
|
|
|
|
${N}
|
|
} else if (${C===2}) {
|
|
vec4 values = vec4(
|
|
getValue(batch, xD, xR, xC, ch),
|
|
getValue(batch, xD, xR, xC + ${c}, ch),
|
|
initializationValue,
|
|
initializationValue
|
|
);
|
|
|
|
${N}
|
|
} else if (${C===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
|
|
);
|
|
|
|
${N}
|
|
}
|
|
}
|
|
}
|
|
setOutput(${k});
|
|
}
|
|
`}};function TH(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t;uu(r,"avgPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=n,u=1;v.assert(T.eitherStridesOrDilationsAreOne(i,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let p=T.computePool2DInfo(r.shape,s,i,u,o,l);if(p.filterWidth===1&&p.filterHeight===1&&v.arraysEqual(p.inShape,p.outShape))return Ja({inputs:{x:r},backend:a});let c=new xd(p,"avg",!1);return a.runWebGLProgram(c,[r],"float32")}var CH={kernelName:Qs,backendName:"webgl",kernelFunc:TH};function NH(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=T.computePool3DInfo(r.shape,s,i,p,o,l,u),d=new _3(c,"avg",!1);return a.runWebGLProgram(d,[r],"float32")}var EH={kernelName:Kc,backendName:"webgl",kernelFunc:NH},RH=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 >= ${e.outWidth}.0 ||
|
|
fract(dyC) > 0.0) {
|
|
continue;
|
|
}
|
|
int idyC = int(dyC);
|
|
|
|
float dyValue = getDy(b, idyR, idyC, d);
|
|
|
|
dotProd += dyValue * avgMultiplier;
|
|
}
|
|
}
|
|
setOutput(dotProd);
|
|
}
|
|
`}},MH=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,a=e.filterHeight,n=e.filterWidth,r=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,p=e.effectiveFilterDepth,c=e.effectiveFilterHeight,d=e.effectiveFilterWidth,h=p-1-e.padInfo.front,f=c-1-e.padInfo.top,m=d-1-e.padInfo.left,g=1/(t*a*n);this.userCode=`
|
|
const ivec3 pads = ivec3(${h}, ${f}, ${m});
|
|
const float avgMultiplier = float(${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 $H(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,i=s,{filterSize:o,strides:l,pad:u,dimRoundingMode:p}=n,c=[1,1,1],d=T.computePool3DInfo(i.shape,o,l,c,u,p),h=new MH(d);return a.runWebGLProgram(h,[r],i.dtype)}var _H={kernelName:L2,backendName:"webgl",kernelFunc:$H};function PH(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,i=s;uu([r,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:u}=n,p=T.computePool2DInfo(i.shape,o,l,1,u),c=new RH(p);return a.runWebGLProgram(c,[r],i.dtype)}var FH={kernelName:Xc,backendName:"webgl",kernelFunc:PH};function OH(e){let{inputs:t,backend:a,attrs:n}=e,{a:r,b:s}=t,{transposeA:i,transposeB:o}=n;return Lc({a:r,b:s,transposeA:i,transposeB:o,backend:a})}var DH={kernelName:ei,backendName:"webgl",kernelFunc:OH},zH=class{constructor(e,t,a,n,r,s){this.outputShape=[],this.variableNames=["x","mean","variance"],T.assertAndGetBroadcastShape(e,t),T.assertAndGetBroadcastShape(e,a);let i="0.0";n!=null&&(T.assertAndGetBroadcastShape(e,n),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="1.0";r!=null&&(T.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)));
|
|
}
|
|
`}},LH=class{constructor(e,t,a,n,r,s){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],T.assertAndGetBroadcastShape(e,t),T.assertAndGetBroadcastShape(e,a);let i="vec4(0.0)";n!=null&&(T.assertAndGetBroadcastShape(e,n),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="vec4(1.0)";r!=null&&(T.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);
|
|
}
|
|
`}},BH=({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=V().getBool("WEBGL_PACK_NORMALIZATION")?new LH(n.shape,r.shape,s.shape,p,c,l):new zH(n.shape,r.shape,s.shape,p,c,l);return t.runWebGLProgram(d,u,u[0].dtype)},WH={kernelName:Ai,backendName:"webgl",kernelFunc:BH},VH=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=gt(this.rank);this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let a=UH(this.rank),n,r=e.map((s,i)=>`sourceLoc.${k2[i]} = start[${i}] + coords.${k2[i]};`);n=`
|
|
${t} sourceLoc;
|
|
${t} coords = getOutputCoords();
|
|
${r.join(`
|
|
`)}
|
|
`,this.userCode=`
|
|
void main() {
|
|
${n}
|
|
setOutput(getSource(${a}));
|
|
}
|
|
`}},k2=["x","y","z","w","u","v"];function UH(e){if(e===1)return"sourceLoc";if(e<=6)return k2.slice(0,e).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}var GH=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let t=gt(this.rank),a=ka("coords",this.rank),n=ka("sourceLoc",this.rank),r=this.rank===1?"sourceLoc":`vec2(${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 HH(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=St.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 gu(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{begin:s,size:i}=n,[o,l]=St.parseSliceParams(r,s,i);if(St.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=OU(c.values,o,l,r.shape,r.dtype);return a.makeTensorInfo(l,r.dtype,d)}let{isPacked:u}=a.texData.get(r.dataId),p=St.isSliceContinous(r.shape,o,l);if(u||!p){let c=V().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new GH(l):new VH(l),d=[o];return a.runWebGLProgram(c,[r],r.dtype,d)}return a.uploadToGPU(r.dataId),HH(r,o,l,a)}var jH={kernelName:Xl,backendName:"webgl",kernelFunc:gu},qH=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=T.getReshaped(r.shape,s,o),u=T.getPermuted(l.length,s.length),p=T.getReshapedPermuted(r.shape,s,o),c=T.getSliceBeginCoords(i,s.length),d=T.getSliceSize(p,i,s.length),h=[],f=pe({inputs:{x:r},backend:a,attrs:{shape:l}}),m=Sa({inputs:{x:f},backend:a,attrs:{perm:u}}),g=pe({inputs:{x:m},backend:a,attrs:{shape:p}}),y=gu({inputs:{x:g},backend:a,attrs:{begin:c,size:d}});return h.push(f),h.push(m),h.push(g),h.forEach(x=>a.disposeIntermediateTensorInfo(x)),y},XH={kernelName:El,backendName:"webgl",kernelFunc:qH};function KH(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=z6(o,l,s.dtype,s.shape,i);return a.makeTensorInfo([i],s.dtype,u)}var ZH={kernelName:Sd,backendName:"webgl",kernelFunc:KH};function YH(e){let{inputs:t,backend:a}=e,{s0:n,s1:r}=t,s=a.readSync(n.dataId),i=a.readSync(r.dataId),o=T.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return a.makeTensorInfo([o.length],"int32",Int32Array.from(o))}var JH={kernelName:Zc,backendName:"webgl",kernelFunc:YH},QH="return float(a != b);",Q6=da({opSnippet:QH,cpuKernelImpl:CU,dtype:"bool"}),ej={kernelName:Bi,backendName:"webgl",kernelFunc:Q6};function mp(e){let{inputs:t,backend:a}=e,{input:n}=t,r=a.texData.get(n.dataId);return Ja({inputs:{x:r.complexTensorInfos.real},backend:a})}var tj={kernelName:Dd,backendName:"webgl",kernelFunc:mp},aj="return float(int(x));";function nj(e,t){let a=new qn(e.shape,aj),n=t.runWebGLProgram(a,[e],"int32");return{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}function w2(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{dtype:s}=n;if(s==="complex64"){if(r.dtype==="complex64")return Ja({inputs:{x:r},backend:a});let i=gn(r.shape),o=w2({inputs:{x:r},backend:a,attrs:{dtype:"float32"}}),l=ls({inputs:{real:o,imag:i},backend:a});return i.dispose(),a.disposeIntermediateTensorInfo(o),l}if(r.dtype==="complex64"){let i=mp({inputs:{input:r},backend:a}),o=w2({inputs:{x:i},backend:a,attrs:{dtype:s}});return a.disposeIntermediateTensorInfo(i),o}if(!v.hasEncodingLoss(r.dtype,s)){let i=Ja({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]=oU(i,r.shape,r.dtype,s);return a.makeTensorInfo(o,l,u)}if(s==="int32")return nj(r,a);if(s==="bool"){let i=a.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),o=Q6({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 rj={kernelName:ti,backendName:"webgl",kernelFunc:w2},vy="return ceil(x);",sj=Qe({opSnippet:vy,packedOpSnippet:vy,cpuKernelImpl:lU}),ij={kernelName:ai,backendName:"webgl",kernelFunc:sj},oj=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));
|
|
}
|
|
`}},lj=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 uj(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{clipValueMin:s,clipValueMax:i}=n,o;V().getBool("WEBGL_PACK_CLIP")?o=new lj(r.shape):o=new oj(r.shape);let l=[[s],[i]];return a.runWebGLProgram(o,[r],r.dtype,l)}var dj={kernelName:as,backendName:"webgl",kernelFunc:uj},pj=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 ky(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function cj(e){let{inputs:t,backend:a}=e,{x:n}=t,r=a.texData.get(n.dataId),s=new pj(n.shape),i=[ky(n,r.complexTensorInfos.real),ky(n,r.complexTensorInfos.imag)];return a.runWebGLProgram(s,i,i[0].dtype)}var hj={kernelName:Yc,backendName:"webgl",kernelFunc:cj},fj=class{constructor(e){this.outputShape=[],this.outputShape=T.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;
|
|
|
|
${a.join(`
|
|
`)}
|
|
}
|
|
`}},mj=class{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=T.computeOutShape(e,t);let a=this.outputShape,n=a.length,r=gt(n),s=ka("coords",n),i=["x","y","z","w","u","v"].slice(0,n);this.variableNames=e.map((f,m)=>`T${m}`);let o=new Array(e.length-1);o[0]=e[0][t];for(let f=1;f<o.length;f++)o[f]=o[f-1]+e[f][t];let l=i[t],u=i.slice(-2),p=i.join(),c=`if (${l} < ${o[0]}) {
|
|
return getChannel(
|
|
getT0(${p}), vec2(${u.join()}));
|
|
}`;for(let f=1;f<o.length;f++){let m=o[f-1];c+=`
|
|
if (${l} < ${o[f]} && ${l} >= ${o[f-1]}) {
|
|
return getChannel(
|
|
getT${f}(${fc(i,l,m)}),
|
|
vec2(${fc(u,l,m)}));
|
|
}`}let d=o.length,h=o[o.length-1];c+=`
|
|
return getChannel(
|
|
getT${d}(${fc(i,l,h)}),
|
|
vec2(${fc(u,l,h)}));`,this.userCode=`
|
|
float getValue(${i.map(f=>"int "+f)}) {
|
|
${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 fc(e,t,a){let n=e.indexOf(t);return e.map((r,s)=>s===n?`${r} - ${a}`:r).join()}function _h(e){let{inputs:t,backend:a}=e,{input:n}=t,r=a.texData.get(n.dataId);return Ja({inputs:{x:r.complexTensorInfos.imag},backend:a})}var gj={kernelName:Pd,backendName:"webgl",kernelFunc:_h};function Ku(e,t,a){let n=e[0].dtype;if(n==="complex64"){let h=e.map(x=>mp({inputs:{input:x},backend:a})),f=e.map(x=>_h({inputs:{input:x},backend:a})),m=Ku(h,t,a),g=Ku(f,t,a),y=ls({inputs:{real:m,imag:g},backend:a});return h.forEach(x=>a.disposeIntermediateTensorInfo(x)),f.forEach(x=>a.disposeIntermediateTensorInfo(x)),a.disposeIntermediateTensorInfo(m),a.disposeIntermediateTensorInfo(g),y}let r=a.shouldExecuteOnCPU(e);if(n==="string"&&(r=!0),r){let h=e.map(b=>{let k=[-1,v.sizeFromShape(b.shape.slice(t))];return pe({inputs:{x:b},backend:a,attrs:{shape:k}})}),f=h.map(b=>({vals:a.readSync(b.dataId),shape:b.shape})),m=T.computeOutShape(h.map(b=>b.shape),1),g=h[0].shape[0]===1,y=uU(f,m,n,g),x=T.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=V().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&s[0].shape.length>1;if(s.length===1){let h=i?new qn(e[0].shape,Or):new Wr(e[0].shape,Or);return a.runWebGLProgram(h,e,n)}let o=V().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER");if(s.length>o){let h=[];for(let m=0;m<s.length;m+=o){let g=s.slice(m,m+o);h.push(Ku(g,t,a))}let f=Ku(h,t,a);for(let m of h)a.disposeIntermediateTensorInfo(m);return f}if(i){let h=new mj(s.map(f=>f.shape),t);return a.runWebGLProgram(h,s,n)}let{tensors2D:l,outShape:u}=yj(s,t,a),p=new fj(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 yj(e,t,a){let n=T.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 ev(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);T.assertParamsConsistent(i,s);let o=T.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?Ja({inputs:{x:l[0]},backend:a}):Ku(l,s,a)}var xj={kernelName:Rl,backendName:"webgl",kernelFunc:ev},tv=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,f=e.inChannels%4,m=e.dataFormat==="channelsLast",g=m?1:2,y=m?2:3,x=m?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 k=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 < ${h}; d1 += 4) {
|
|
vec4 wValues = vec4(
|
|
getW(wR, wC, d1, d2),
|
|
getW(wR, wC, d1 + 1, d2),
|
|
getW(wR, wC, d1 + 2, d2),
|
|
getW(wR, wC, d1 + 3, d2)
|
|
);
|
|
|
|
if (${m}) {
|
|
vec4 xValues = vec4(
|
|
getX(batch, xR, xC, d1),
|
|
getX(batch, xR, xC, d1 + 1),
|
|
getX(batch, xR, xC, d1 + 2),
|
|
getX(batch, xR, xC, d1 + 3)
|
|
);
|
|
dotProd += dot(xValues, wValues);
|
|
} else {
|
|
vec4 xValues = vec4(
|
|
getX(batch, d1, xR, xC),
|
|
getX(batch, d1 + 1, xR, xC),
|
|
getX(batch, d1 + 2, xR, xC),
|
|
getX(batch, d1 + 3, xR, xC)
|
|
);
|
|
dotProd += dot(xValues, wValues);
|
|
}
|
|
}
|
|
|
|
if (${f===1}) {
|
|
|
|
if (${m}) {
|
|
dotProd +=
|
|
getX(batch, xR, xC, ${h}) *
|
|
getW(wR, wC, ${h}, d2);
|
|
} else {
|
|
dotProd +=
|
|
getX(batch, ${h}, xR, xC) *
|
|
getW(wR, wC, ${h}, d2);
|
|
}
|
|
|
|
} else if (${f===2}) {
|
|
vec2 wValues = vec2(
|
|
getW(wR, wC, ${h}, d2),
|
|
getW(wR, wC, ${h} + 1, d2)
|
|
);
|
|
|
|
if (${m}) {
|
|
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, ${h} + 1, xR, xC)
|
|
);
|
|
dotProd += dot(xValues, wValues);
|
|
}
|
|
|
|
} else if (${f===3}) {
|
|
vec3 wValues = vec3(
|
|
getW(wR, wC, ${h}, d2),
|
|
getW(wR, wC, ${h} + 1, d2),
|
|
getW(wR, wC, ${h} + 2, d2)
|
|
);
|
|
|
|
if (${m}) {
|
|
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;
|
|
${k}
|
|
${b}
|
|
setOutput(result);
|
|
}
|
|
`}},Aj=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,a=e.padInfo.top,n=e.padInfo.left,r=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,p=e.filterDepth,c=e.filterHeight,d=e.filterWidth,h=Math.floor(e.inChannels/4)*4,f=e.inChannels%4;this.userCode=`
|
|
const ivec3 strides = ivec3(${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 < ${h}; d1 += 4) {
|
|
vec4 xValues = vec4(
|
|
getX(batch, xF, xR, xC, d1),
|
|
getX(batch, xF, xR, xC, d1 + 1),
|
|
getX(batch, xF, xR, xC, d1 + 2),
|
|
getX(batch, xF, xR, xC, d1 + 3)
|
|
);
|
|
vec4 wValues = vec4(
|
|
getW(wF, wR, wC, d1, d2),
|
|
getW(wF, wR, wC, d1 + 1, d2),
|
|
getW(wF, wR, wC, d1 + 2, d2),
|
|
getW(wF, wR, wC, d1 + 3, d2)
|
|
);
|
|
|
|
dotProd += dot(xValues, wValues);
|
|
}
|
|
|
|
if (${f===1}) {
|
|
dotProd +=
|
|
getX(batch, xF, xR, xC, ${h}) *
|
|
getW(wF, wR, wC, ${h}, d2);
|
|
} else if (${f===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, ${h} + 1, d2)
|
|
);
|
|
dotProd += dot(xValues, wValues);
|
|
} else if (${f===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, ${h} + 2, d2)
|
|
);
|
|
dotProd += dot(xValues, wValues);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
setOutput(dotProd);
|
|
}
|
|
`}},av=class{constructor(e,t=!1,a=null,n=!1,r=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=Ea(this.outputShape.length);let s=e.padInfo.left,i=e.strideWidth,o=e.dilationWidth,l=e.filterHeight,u=e.filterWidth,p=u,c=`
|
|
int xR; int xC; int xCOffset;
|
|
vec4 wTexel; vec4 previous; vec4 final;`;for(let m=0;m<u;m++)c+=`
|
|
vec4 xTexelC${m*2};
|
|
int xTexelC${m*2}Ready;
|
|
vec4 xTexelC${m*2+1};
|
|
int xTexelC${m*2+1}Ready;
|
|
vec4 xC${m};`;c+=`
|
|
for (int r = 0; r < ${l}; r++) {
|
|
for (int d1 = 0; d1 < ${e.inChannels}; d1 += 2) {
|
|
`;for(let m=0;m<u;m++)c+=`
|
|
xTexelC${m*2} = vec4(0.0);
|
|
xTexelC${m*2}Ready = 0;
|
|
xTexelC${m*2+1} = vec4(0.0);
|
|
xTexelC${m*2+1}Ready = 0;
|
|
xC${m} = vec4(0.0);`;c+=`
|
|
xR = xRCorner + r * dilations[0];
|
|
if (xR >=0 && xR < inDims[0]) {
|
|
`;for(let m=0;m<(p+1)/2;m++){let g=m*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 f=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);
|
|
${f}
|
|
${h}
|
|
setOutput(result);
|
|
}
|
|
`}},bj=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=Ea(this.outputShape.length);let{dataFormat:a}=t,n=Na(),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 Bc(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 nv({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",f=!1,m=!1,g,y=[];if(s!=null){let x=Bc(s.shape,h);x!=null&&(s=pe({inputs:{x:s},backend:n,attrs:{shape:x}}),y.push(s))}if(r!=null){let x=Bc(r.shape,h);x!=null&&(r=pe({inputs:{x:r},backend:n,attrs:{shape:x}}),y.push(r))}if(!((c===1||d===1)&&p>K6)&&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(gd(u.shape,A.shape),()=>`packed reshape ${u.shape} to ${A.shape} isn't free`);let k=pe({inputs:{x:t},backend:n,attrs:{shape:[1,a.inChannels,a.outChannels]}});y.push(k);let S=Lc({a:A,b:k,backend:n,transposeA:f,transposeB:m,bias:r,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),C=n.texData.get(S.dataId);v.assert(C.isPacked,()=>"batchMatMul result is expected to be packed"),u.shape=b,C.shape=a.outShape,g=Ja({inputs:{x:S},backend:n}),g.shape=a.outShape,y.push(S)}else{let x=a.outHeight*a.outWidth,A=pe({inputs:{x:e},backend:n,attrs:{shape:h?[a.batchSize,x,a.inChannels]:[a.batchSize,a.inChannels,x]}}),b=pe({inputs:{x:t},backend:n,attrs:{shape:[1,a.inChannels,a.outChannels]}}),k=Lc({a:h?A:b,b:h?b:A,transposeA:!h,transposeB:m,backend:n,bias:r,activation:o,preluActivationWeights:s,leakyreluAlpha:i});g=pe({inputs:{x:k},backend:n,attrs:{shape:a.outShape}}),y.push(A),y.push(b),y.push(k)}for(let x of y)n.disposeIntermediateTensorInfo(x);return g}function rv({x:e,filter:t,convInfo:a,backend:n,bias:r=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let{filterWidth:l,filterHeight:u,inChannels:p,outWidth:c,outHeight:d,dataFormat:h}=a,f=h==="channelsLast",m=l*u*p,g=d*c,y=[a.batchSize,m,g],x=!0,A=!1,b=[];if(s!=null){let G=Bc(s.shape,f);G!=null&&(s=pe({inputs:{x:s},backend:n,attrs:{shape:G}}),b.push(s))}if(r!=null){let G=Bc(r.shape,f);G!=null&&(r=pe({inputs:{x:r},backend:n,attrs:{shape:G}}),b.push(r))}let k=pe({inputs:{x:t},backend:n,attrs:{shape:[1,m,v.sizeFromShape(t.shape)/m]}});b.push(k);let S=new bj(y,a),C=[e.shape,[a.padInfo.top,a.padInfo.left],[a.strideHeight,a.strideWidth],[a.dilationHeight,a.dilationWidth],[a.inChannels],[a.filterWidth*a.inChannels],[a.outWidth]],N=n.runWebGLProgram(S,[e],"float32",C),$=pe({inputs:{x:N},backend:n,attrs:{shape:y}});b.push(N),b.push($);let M=r!=null,R=s!=null,I=o==="leakyrelu",_=o?yd(o,!0):null,D=new X6(f?$.shape:k.shape,f?k.shape:$.shape,f?[a.batchSize,g,a.outChannels]:[a.batchSize,a.outChannels,g],x,A,M,_,R,I),W=f?[$,k]:[k,$];if(r&&W.push(r),R&&W.push(s),I){let G=n.makeTensorInfo([],"float32",v.createScalarValue(i,"float32"));W.push(G),b.push(G)}let P=n.runWebGLProgram(D,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 vj(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=T.convertConv2DDataFormat(l),d=T.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=nv({x:r,filter:s,convInfo:d,backend:a});else if(d.strideWidth<=2&&c==="channelsLast"&&V().getBool("WEBGL_EXP_CONV")){let m=new av(d),g=[[d.padInfo.top,d.padInfo.left],[d.strideHeight,d.strideWidth],[d.dilationHeight,d.dilationWidth],[d.inHeight,d.inWidth]];h=a.runWebGLProgram(m,[r,s],"float32",g)}else if(V().getBool("WEBGL_CONV_IM2COL"))h=rv({x:r,filter:s,convInfo:d,backend:a});else{let m=new tv(d);h=a.runWebGLProgram(m,[r,s],"float32")}let f=pe({inputs:{x:h},backend:a,attrs:{shape:d.outShape}});return a.disposeIntermediateTensorInfo(h),f}var kj={kernelName:ni,backendName:"webgl",kernelFunc:vj},wj=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 >= ${e.inWidth}) {
|
|
continue;
|
|
}
|
|
|
|
if (${s}) {
|
|
float dyValue = getDy(b, yR, yC, d2);
|
|
float xValue = getX(b, xR, xC, d1);
|
|
dotProd += (xValue * dyValue);
|
|
} else {
|
|
float dyValue = getDy(b, d2, yR, yC);
|
|
float xValue = getX(b, d1, xR, xC);
|
|
dotProd += (xValue * dyValue);
|
|
}
|
|
|
|
}
|
|
}
|
|
}
|
|
setOutput(dotProd);
|
|
}
|
|
`}},Ij=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);
|
|
}
|
|
`}},Sj=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 >= ${e.inWidth}) {
|
|
continue;
|
|
}
|
|
|
|
float dyValue = getDy(b, yF, yR, yC, d2);
|
|
float xValue = getX(b, xF, xR, xC, d1);
|
|
dotProd += (xValue * dyValue);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
setOutput(dotProd);
|
|
}
|
|
`}},Tj=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,a=e.filterHeight,n=e.filterWidth,r=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=t-1-e.padInfo.front,l=a-1-e.padInfo.top,u=n-1-e.padInfo.left;this.userCode=`
|
|
const ivec3 pads = ivec3(${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 Cj(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=T.convertConv2DDataFormat(l),d=T.computeConv2DInfo(r.shape,p,i,1,o,u,!1,c),h=new wj(d);return a.runWebGLProgram(h,[r,s],"float32")}var Nj={kernelName:Cd,backendName:"webgl",kernelFunc:Cj};function Ej(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=T.convertConv2DDataFormat(u),d=T.computeConv2DInfo(i,s.shape,o,1,l,p,!1,c),h=new Ij(d);return a.runWebGLProgram(h,[r,s],"float32")}var Rj={kernelName:ri,backendName:"webgl",kernelFunc:Ej};function Mj(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=n,u=T.computeConv3DInfo(r.shape,s.shape,i,l,o),p=new Aj(u);return a.runWebGLProgram(p,[r,s],"float32")}var $j={kernelName:Jc,backendName:"webgl",kernelFunc:Mj};function _j(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,dy:s}=t,{strides:i,pad:o,filterShape:l}=n,u=T.computeConv3DInfo(r.shape,l,i,1,o),p=new Sj(u);return a.runWebGLProgram(p,[r,s],"float32")}var Pj={kernelName:B2,backendName:"webgl",kernelFunc:_j};function Fj(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,filter:s}=t,{pad:i,strides:o,inputShape:l}=n,u=T.computeConv3DInfo(l,s.shape,o,1,i),p=new Tj(u);return a.runWebGLProgram(p,[r,s],"float32")}var Oj={kernelName:Qc,backendName:"webgl",kernelFunc:Fj},Dj=mu+`
|
|
return cos(x);
|
|
`,zj=Qe({opSnippet:Dj}),Lj={kernelName:si,backendName:"webgl",kernelFunc:zj},Bj=`
|
|
float e2x = exp(-x);
|
|
return (e2x + 1.0 / e2x) / 2.0;
|
|
`,Wj=Qe({opSnippet:Bj}),Vj={kernelName:ii,backendName:"webgl",kernelFunc:Wj},Uj=class{constructor(e,t,a,n,r){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[s,i,o,l]=e,[u]=t,[p,c]=a;this.outputShape=[u,p,c,l];let d=n==="bilinear"?1:0,[h,f]=[`${i-1}.0`,`${o-1}.0`],[m,g,y]=p>1?[`${(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*${f} + float(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${f}`];this.userCode=`
|
|
const float height_ratio = float(${m});
|
|
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 > ${f} ) {
|
|
setOutput(float(${r}));
|
|
return;
|
|
}
|
|
|
|
vec2 sourceFracIndexCR = vec2(in_x,in_y);
|
|
if(${d} == 1) {
|
|
// Compute the four integer indices.
|
|
ivec2 sourceFloorCR = ivec2(sourceFracIndexCR);
|
|
ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR));
|
|
|
|
float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d);
|
|
float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d);
|
|
float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);
|
|
float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);
|
|
|
|
vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);
|
|
|
|
float top = topLeft + (topRight - topLeft) * fracCR.x;
|
|
float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;
|
|
float newValue = top + (bottom - top) * fracCR.y;
|
|
setOutput(newValue);
|
|
} else {
|
|
// Compute the coordinators of nearest neighbor point.
|
|
ivec2 sourceNearestCR = ivec2(floor(
|
|
sourceFracIndexCR + vec2(0.5,0.5)));
|
|
float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);
|
|
setOutput(newValue);
|
|
}
|
|
}
|
|
`}},Gj=e=>{let{inputs:t,backend:a,attrs:n}=e,{image:r,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:u}=n,p=new Uj(r.shape,s.shape,o,l,u);return a.runWebGLProgram(p,[r,s,i],"float32")},Hj={kernelName:ui,backendName:"webgl",kernelFunc:Gj},Ad;(function(e){e.Prod="*",e.Sum="+"})(Ad||(Ad={}));var wy=class{constructor(e,t,a,n){this.op=e,this.outputShape=t,this.variableNames=["x"],this.customUniforms=[{name:"index",type:"float"}];let r=this.outputShape.length,s=this.op===Ad.Prod?"1.0":"0.0",i=a?s:`getX(${Iy(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() {
|
|
${gt(r)} coords = getOutputCoords();
|
|
int end = ${Sy(r,"coords",this.op)};
|
|
float val = ${i};
|
|
int pow2 = int(pow(2.0, index));
|
|
if (${l}) {
|
|
int idx = ${u};
|
|
${Sy(r,"coords",this.op)} = idx;
|
|
val ${this.op}= getX(${Iy(r,"coords",this.op)});
|
|
}
|
|
setOutput(val);
|
|
}
|
|
`}};function Iy(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 ${e} is not yet supported`)}function Sy(e,t,a){if(e===1)return`${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 ${e} is not yet supported`)}function sv(e,t,a,n,r,s){let i=t.shape.length,o=T.getAxesPermutation([n],i),l=t;o!=null&&(l=Sa({inputs:{x:t},backend:a,attrs:{perm:o}}));let u=T.getInnerMostAxes(1,i)[0];if(u!==i-1)throw new Error(`WebGL cumprod shader expects an inner-most axis=${t.shape.length-1} but got axis=${n}`);let p=l.shape[u],c=Ja({inputs:{x:l},backend:a});for(let d=0;d<=Math.ceil(Math.log2(p))-1;d++){let h=new wy(e,l.shape,!1,s),f=[[d]],m=c;c=a.runWebGLProgram(h,[c],c.dtype,f),a.disposeIntermediateTensorInfo(m)}if(r){let d=new wy(e,l.shape,r,s),h=c;c=a.runWebGLProgram(d,[c],c.dtype),a.disposeIntermediateTensorInfo(h)}if(o!=null){let d=T.getUndoAxesPermutation(o),h=Sa({inputs:{x:c},backend:a,attrs:{perm:d}});return a.disposeIntermediateTensorInfo(c),a.disposeIntermediateTensorInfo(l),h}return c}function jj(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=n;return sv(Ad.Prod,r,a,s,i,o)}var qj={kernelName:oi,backendName:"webgl",kernelFunc:jj};function Xj(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=n;return sv(Ad.Sum,r,a,s,i,o)}var Kj={kernelName:li,backendName:"webgl",kernelFunc:Xj};function Zj(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,weights:s}=t,{size:i,binaryOutput:o}=n;if(r.shape.length===1){let l=a.readSync(r.dataId),u=a.readSync(s.dataId),p=z6(l,u,s.dtype,s.shape,i);return a.makeTensorInfo([i],s.dtype,p)}else if(r.shape.length===2){let l=a.bufferSync(r),u=a.bufferSync(s),p=iU(l,u,i,o);return a.makeTensorInfo(p.shape,s.dtype,p.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${r.shape.length}.`)}var Yj={kernelName:Nd,backendName:"webgl",kernelFunc:Zj},Jj=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 Qj(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),f=i==="NHWC"?[o,c,d,h]:[o,h,c,d],m=new Jj(f,s,i);return a.runWebGLProgram(m,[r],r.dtype)}var eq={kernelName:di,backendName:"webgl",kernelFunc:Qj},iv=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=Ea(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}
|
|
${u}
|
|
setOutput(result);
|
|
}
|
|
`}},ov=class{constructor(e,t=!1,a=null,n=!1,r=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=Ea(this.outputShape.length);let s=e.outChannels/e.inChannels,i=e.padInfo.left,o=e.strideWidth,l=e.dilationWidth,u=e.filterHeight,p=e.filterWidth,c=p,d=`
|
|
int xR; int xC; int xCOffset;
|
|
vec4 wTexel; vec4 previous; vec4 final;`;for(let g=0;g<p;g++)d+=`
|
|
vec4 xTexelC${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="",f="";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}
|
|
}`,f="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=`
|
|
${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);
|
|
${m}
|
|
${f}
|
|
setOutput(result);
|
|
}
|
|
`}};function tq(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(T.eitherStridesOrDilationsAreOne(i,p),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${p}'`);let c=T.computeConv2DInfo(r.shape,s.shape,i,p,o,u,!0),d;V().getBool("WEBGL_PACK_DEPTHWISECONV")&&c.strideWidth<=2&&c.outChannels/c.inChannels===1?d=new ov(c):d=new iv(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 aq={kernelName:pi,backendName:"webgl",kernelFunc:tq},nq=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 >= ${e.inWidth}) {
|
|
continue;
|
|
}
|
|
|
|
float dyValue = getDy(b, yR, yC, d2);
|
|
float xValue = getX(b, xR, xC, d1);
|
|
dotProd += (xValue * dyValue);
|
|
}
|
|
}
|
|
}
|
|
setOutput(dotProd);
|
|
}
|
|
`}},rq=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,a=e.filterWidth,n=e.strideHeight,r=e.strideWidth,s=t-1-e.padInfo.top,i=a-1-e.padInfo.left,o=e.outChannels/e.inChannels;this.userCode=`
|
|
const ivec2 pads = ivec2(${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 * ${o} + dm;
|
|
float xValue = getDy(batch, idyR, idyC, d2);
|
|
float wValue = getW(wRPerm, wCPerm, d1, dm);
|
|
dotProd += xValue * wValue;
|
|
}
|
|
}
|
|
}
|
|
setOutput(dotProd);
|
|
}
|
|
`}};function sq(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,filterShape:p}=n,c=T.computeConv2DInfo(r.shape,p,i,o,l,u,!0),d=new nq(c);return a.runWebGLProgram(d,[r,s],"float32")}var iq={kernelName:eh,backendName:"webgl",kernelFunc:sq};function oq(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,inputShape:p}=n,c=T.computeConv2DInfo(p,s.shape,i,o,l,u,!0),d=new rq(c);return a.runWebGLProgram(d,[r,s],"float32")}var lq={kernelName:th,backendName:"webgl",kernelFunc:oq},uq=class{constructor(e){this.variableNames=["X"],this.outputShape=[e,e],this.userCode=`
|
|
void main() {
|
|
ivec2 coords = getOutputCoords();
|
|
float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;
|
|
setOutput(val);
|
|
}
|
|
`}};function dq(e){let{inputs:t,backend:a}=e,{x:n}=t,r=[...n.shape,...n.shape],s=v.sizeFromShape(n.shape),i=pe({inputs:{x:n},backend:a,attrs:{shape:[s]}}),o=new uq(s),l=a.runWebGLProgram(o,[i],i.dtype),u=pe({inputs:{x:l},backend:a,attrs:{shape:r}});return a.disposeIntermediateTensorInfo(i),a.disposeIntermediateTensorInfo(l),u}var pq={kernelName:Ed,backendName:"webgl",kernelFunc:dq},cq=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:a,padInfo:n,strideHeight:r,strideWidth:s,filterHeight:i,filterWidth:o,dilationHeight:l,dilationWidth:u}=e,{top:p,left:c}=n;this.userCode=`
|
|
const ivec2 strides = ivec2(${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 hq(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=n,u=T.computeDilation2DInfo(r.shape,s.shape,i,o,"NHWC",l),p,c=new cq(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 fq={kernelName:Rd,backendName:"webgl",kernelFunc:hq};function mq(e){let{inputs:t,backend:a,attrs:n}=e,{equation:r}=n,s=t,{allDims:i,summedDims:o,idDims:l}=T.decodeEinsumEquation(r,s.length);T.checkEinsumDimSizes(i.length,l,s);let{path:u,steps:p}=T.getEinsumComputePath(o,l),c=p.length,d=null,h=i.length,f=[];for(let m=0;m<c;++m){for(let g of p[m]){let{permutationIndices:y,expandDims:x}=T.getEinsumPermutation(h,l[g]),A;T.isIdentityPermutation(y)?A=s[g]:(A=Sa({inputs:{x:s[g]},backend:a,attrs:{perm:y}}),f.push(A));let b=A.shape.slice();for(let k=0;k<x.length;++k)b.splice(x[k],0,1);v.arraysEqual(A.shape,b)||(A=pe({inputs:{x:A},backend:a,attrs:{shape:b}}),f.push(A)),d===null?d=A:(d=$3({inputs:{a:A,b:d},backend:a}),f.push(d))}m<c-1&&(u[m]>=0&&(d=$h({inputs:{x:d},backend:a,attrs:{axis:u[m]-(i.length-h),keepDims:!1}}),f.push(d)),h--)}for(let m of f)m!==d&&a.disposeIntermediateTensorInfo(m);return d}var gq={kernelName:Md,backendName:"webgl",kernelFunc:mq},yq="return (x >= 0.0) ? x : (exp(x) - 1.0);",xq=`
|
|
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;
|
|
`,Aq=Qe({opSnippet:yq,packedOpSnippet:xq}),bq={kernelName:hi,backendName:"webgl",kernelFunc:Aq},vq="return (b >= 1.0) ? a : a * (b + 1.0);",kq=`
|
|
vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
|
|
return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
|
|
`,wq=e=>{let{inputs:t,backend:a}=e,{dy:n,y:r}=t,s=V().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new fp(kq,n.shape,r.shape):new yl(vq,n.shape,r.shape);return a.runWebGLProgram(s,[n,r],n.dtype)},Iq={kernelName:W2,backendName:"webgl",kernelFunc:wq},Sq=`
|
|
return vec4(equal(a, b));
|
|
`,Tq="return float(a == b);",Cq=da({opSnippet:Tq,packedOpSnippet:Sq,dtype:"bool",cpuKernelImpl:dU}),Nq={kernelName:fi,backendName:"webgl",kernelFunc:Cq},Eq=`
|
|
// Error function is calculated approximately with elementary function.
|
|
// See "Handbook of Mathematical Functions with Formulas,
|
|
// Graphs, and Mathematical Tables", Abramowitz and Stegun.
|
|
float p = ${T.ERF_P};
|
|
float a1 = ${T.ERF_A1};
|
|
float a2 = ${T.ERF_A2};
|
|
float a3 = ${T.ERF_A3};
|
|
float a4 = ${T.ERF_A4};
|
|
float a5 = ${T.ERF_A5};
|
|
|
|
float sign = sign(x);
|
|
x = abs(x);
|
|
float t = 1.0 / (1.0 + p * x);
|
|
return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));
|
|
`,Rq=Qe({opSnippet:Eq}),Mq={kernelName:Ml,backendName:"webgl",kernelFunc:Rq},$q=mu+`
|
|
return exp(x);
|
|
`,_q=`
|
|
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;
|
|
`,lv=Qe({opSnippet:$q,packedOpSnippet:_q,cpuKernelImpl:pU,dtype:"float32"}),Pq={kernelName:mi,backendName:"webgl",kernelFunc:lv};function I2(e){let{inputs:t,attrs:a,backend:n}=e,{dim:r}=a,{input:s}=t,i=s.shape.length,o=s.shape.slice(),l=r;return r<0&&(v.assert(-(i+1)<=r,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+r+1),o.splice(l,0,1),pe({inputs:{x:s},backend:n,attrs:{shape:o}})}var Fq={kernelName:$l,backendName:"webgl",kernelFunc:I2},Ty="return exp(x) - 1.0;",Oq=Qe({opSnippet:Ty,packedOpSnippet:Ty,cpuKernelImpl:cU}),Dq={kernelName:_l,backendName:"webgl",kernelFunc:Oq},Cy=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) / ${s};
|
|
}
|
|
|
|
return result;
|
|
}
|
|
|
|
void main() {
|
|
ivec2 coords = getOutputCoords();
|
|
setOutput(mulMatDFT(coords[0], coords[1]));
|
|
}
|
|
`}};function uv(e,t,a){let n=a.texData.get(e.dataId),r=v.sizeFromShape(e.shape),s=e.shape[e.shape.length-1],i=r/s,o=pe({inputs:{x:e},backend:a,attrs:{shape:[i,s]}}),l=o.shape,u=new Cy("real",l,t),p=new Cy("imag",l,t),c=[{dataId:n.complexTensorInfos.real.dataId,dtype:n.complexTensorInfos.real.dtype,shape:l},{dataId:n.complexTensorInfos.imag.dataId,dtype:n.complexTensorInfos.imag.dtype,shape:l}],d=a.runWebGLProgram(u,c,"float32"),h=a.runWebGLProgram(p,c,"float32"),f=ls({inputs:{real:d,imag:h},backend:a});a.disposeIntermediateTensorInfo(d),a.disposeIntermediateTensorInfo(h);let m=pe({inputs:{x:f},backend:a,attrs:{shape:e.shape}});return a.disposeIntermediateTensorInfo(o),a.disposeIntermediateTensorInfo(f),m}function zq(e){let{inputs:t,backend:a}=e,{input:n}=t;return uv(n,!1,a)}var Lq={kernelName:$d,backendName:"webgl",kernelFunc:zq},Bq=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 gp(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 Bq(n,r),o=[[r]];return t.runWebGLProgram(i,[],s,o)}}var Wq={kernelName:Pl,backendName:"webgl",kernelFunc:gp},Vq=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 < ${t}) {
|
|
outputValue = getImage(coords[0], coords[1], coordX, coords[3]);
|
|
} else {
|
|
outputValue = getImage(coords[0], coords[1], coords[2], coords[3]);
|
|
}
|
|
setOutput(outputValue);
|
|
}
|
|
`}},Uq={kernelName:gi,backendName:"webgl",kernelFunc:({inputs:e,backend:t})=>{let{image:a}=e,n=t,r=new Vq(a.shape);return n.runWebGLProgram(r,[a],a.dtype)}},Ny="return floor(x);",Gq=Qe({opSnippet:Ny,packedOpSnippet:Ny,cpuKernelImpl:hU}),Hq={kernelName:yi,backendName:"webgl",kernelFunc:Gq},jq=`
|
|
float s = sign(a) * sign(b);
|
|
int ia = round(a);
|
|
int ib = round(b);
|
|
if (ib != 0) {
|
|
// Windows (D3D) wants guaranteed non-zero int division at compile-time.
|
|
return float(idiv(ia, ib, s));
|
|
} else {
|
|
return NAN;
|
|
}
|
|
`,qq=`
|
|
ivec4 ia = round(a);
|
|
ivec4 ib = round(b);
|
|
bvec4 cond = notEqual(ib, ivec4(0));
|
|
ivec4 result = ivec4(0);
|
|
vec4 s = sign(a) * sign(b);
|
|
|
|
// Windows (D3D) wants guaranteed non-zero int division at compile-time.
|
|
if (cond[0]) {
|
|
result[0] = idiv(ia[0], ib[0], s[0]);
|
|
}
|
|
if (cond[1]) {
|
|
result[1] = idiv(ia[1], ib[1], s[1]);
|
|
}
|
|
if (cond[2]) {
|
|
result[2] = idiv(ia[2], ib[2], s[2]);
|
|
}
|
|
if (cond[3]) {
|
|
result[3] = idiv(ia[3], ib[3], s[3]);
|
|
}
|
|
return vec4(result);
|
|
`,Xq=da({opSnippet:jq,packedOpSnippet:qq,dtype:"int32"}),Kq={kernelName:xi,backendName:"webgl",kernelFunc:Xq},Zq=class{constructor(e){this.variableNames=["A"];let t=Na(),[a,n]=e;this.outputShape=e,this.userCode=`
|
|
void main() {
|
|
ivec3 coords = getOutputCoords();
|
|
int texR = coords[0];
|
|
int texC = coords[1];
|
|
int depth = coords[2];
|
|
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${n}.0, ${a}.0);
|
|
|
|
vec4 values = ${t.texture2D}(A, uv);
|
|
float value;
|
|
if (depth == 0) {
|
|
value = values.r;
|
|
} else if (depth == 1) {
|
|
value = values.g;
|
|
} else if (depth == 2) {
|
|
value = values.b;
|
|
} else if (depth == 3) {
|
|
value = values.a;
|
|
}
|
|
|
|
setOutput(floor(value * 255.0 + 0.5));
|
|
}
|
|
`}},Yq=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let t=Na(),[a,n]=e;this.outputShape=e,this.userCode=`
|
|
void main() {
|
|
ivec3 coords = getOutputCoords();
|
|
int texR = coords[0];
|
|
int texC = coords[1];
|
|
int depth = coords[2];
|
|
|
|
vec4 result = vec4(0.);
|
|
|
|
for(int row=0; row<=1; row++) {
|
|
for(int col=0; col<=1; col++) {
|
|
texC = coords[1] + row;
|
|
depth = coords[2] + col;
|
|
|
|
vec2 uv = (vec2(texC, texR) + halfCR) /
|
|
vec2(${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);
|
|
}
|
|
}
|
|
|
|
${t.output} = result;
|
|
}
|
|
`}},Jq={kernelName:nd,backendName:"webgl",kernelFunc:Qq},Ko,Om=V().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");function Qq(e){let{inputs:t,backend:a,attrs:n}=e,{pixels:r}=t,{numChannels:s}=n,i=typeof HTMLVideoElement!="undefined"&&r instanceof HTMLVideoElement,o=typeof HTMLImageElement!="undefined"&&r instanceof HTMLImageElement,[l,u]=i?[r.videoWidth,r.videoHeight]:[r.width,r.height],p=[u,l],c=[u,l,s];if(o||i){let m=V().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");(Ko==null||m!==Om)&&(Om=m,Ko=document.createElement("canvas").getContext("2d",{willReadFrequently:Om})),Ko.canvas.width=l,Ko.canvas.height=u,Ko.drawImage(r,0,0,l,u),r=Ko.canvas}let d=a.makeTensorInfo(p,"int32");a.texData.get(d.dataId).usage=hn.PIXELS,a.gpgpu.uploadPixelDataToTexture(a.getTexture(d.dataId),r);let h=V().getBool("WEBGL_PACK")?new Yq(c):new Zq(c),f=a.runWebGLProgram(h,[d],"int32");return a.disposeData(d.dataId),f}function eX(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dataFormat:p,dilations:c,dimRoundingMode:d,activation:h,leakyreluAlpha:f}=n,m=T.convertConv2DDataFormat(p),g=T.computeConv2DInfo(r.shape,s.shape,l,c,u,d,!1,m),y,x=[],A=i!=null,b=o!=null,k=h==="leakyrelu",S=()=>{let N=[r,s],$=(M,R)=>{if(R==="NCHW"&&M.shape.length===1&&M.shape[0]!==1){let I=pe({inputs:{x:M},backend:a,attrs:{shape:[M.shape[0],1,1]}});return x.push(I),I}return M};if(A&&N.push($(i,p)),b&&N.push($(o,p)),k){let M=a.makeTensorInfo([],"float32",v.createScalarValue(f,"float32"));N.push(M),x.push(M)}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=nv({x:r,filter:s,convInfo:g,backend:a,bias:i,activation:h,preluActivationWeights:o,leakyreluAlpha:f});else if(g.strideWidth<=2&&m==="channelsLast"&&V().getBool("WEBGL_EXP_CONV")){let N=h?yd(h,!0):null,$=new av(g,A,N,b,k),M=[[g.padInfo.top,g.padInfo.left],[g.strideHeight,g.strideWidth],[g.dilationHeight,g.dilationWidth],[g.inHeight,g.inWidth]],R=S();y=a.runWebGLProgram($,R,"float32",M)}else if(V().getBool("WEBGL_CONV_IM2COL"))y=rv({x:r,filter:s,convInfo:g,backend:a,bias:i,activation:h,preluActivationWeights:o,leakyreluAlpha:f});else{let N=h?yd(h,!1):null,$=new tv(g,A,N,b,k),M=S();y=a.runWebGLProgram($,M,"float32")}let C=pe({inputs:{x:y},backend:a,attrs:{shape:g.outShape}});return x.push(y),x.forEach(N=>a.disposeIntermediateTensorInfo(N)),C}var tX={kernelName:jr,backendName:"webgl",kernelFunc:eX};function aX(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,f=[],m=p;m==null&&(m=[1,1]),v.assert(T.eitherStridesOrDilationsAreOne(l,m),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${m}'`);let g=T.computeConv2DInfo(r.shape,s.shape,l,m,u,c,!0),y=V().getBool("WEBGL_PACK_DEPTHWISECONV")&&g.strideWidth<=2&&g.outChannels/g.inChannels===1,x=d?yd(d,y):null,A=[r,s],b=i!=null,k=o!=null,S=d==="leakyrelu";if(b&&A.push(i),k&&A.push(o),S){let M=a.makeTensorInfo([],"float32",v.createScalarValue(h,"float32"));A.push(M),f.push(M)}let C;y?C=new ov(g,b,x,k,S):C=new iv(g,b,x,k,S);let N=[[g.padInfo.top,g.padInfo.left],[g.strideHeight,g.strideWidth],[g.dilationHeight,g.dilationWidth],[g.inHeight,g.inWidth]],$=a.runWebGLProgram(C,A,"float32",N);return f.forEach(M=>a.disposeIntermediateTensorInfo(M)),$}var nX={kernelName:qr,backendName:"webgl",kernelFunc:aX},rX=class{constructor(e,t,a,n){this.sliceDim=e,this.strides=t,this.paramsShape=n,this.variableNames=["x","indices"],this.outputShape=a;let r=gt(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 sX(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]=T.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=fU(y,x,n.dtype,u,i,p,c,n.shape,o);return a.makeTensorInfo(l,n.dtype,A.values)}let f=new rX(i,c,[u,p],n.shape),m=a.runWebGLProgram(f,[h,d],h.dtype),g=pe({inputs:{x:m},backend:a,attrs:{shape:l}});return a.disposeIntermediateTensorInfo(d),a.disposeIntermediateTensorInfo(h),a.disposeIntermediateTensorInfo(m),g}var iX={kernelName:bi,backendName:"webgl",kernelFunc:sX},oX=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let a=gt(this.rank),n=lX(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 lX(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 dv(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(V().get("DEBUG")){let x=a.readSync(s.dataId),A=r.shape[l];for(let b=0;b<x.length;++b){let k=x[b];v.assert(k<=A-1&&k>=0,()=>`GatherV2: the index value ${k} is not in [0, ${A-1}]`)}}let u=T.segment_util.collectGatherOpShapeInfo(r,s,l,o),p=v.sizeFromShape(s.shape),c=[],d=pe({inputs:{x:r},backend:a,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),h=pe({inputs:{x:s},backend:a,attrs:{shape:[u.batchSize,p/u.batchSize]}});c.push(d),c.push(h);let f=[u.batchSize,u.outerSize,p/u.batchSize,u.sliceSize];if(a.shouldExecuteOnCPU([r,s])||r.dtype==="string"){let x=a.bufferSync(h),A=a.bufferSync(d),b=mU(A,x,f);return c.forEach(k=>a.disposeIntermediateTensorInfo(k)),a.makeTensorInfo(u.outputShape,b.dtype,b.values)}let m=new oX(d.shape,f),g=a.runWebGLProgram(m,[d,h],d.dtype);c.push(g);let y=pe({inputs:{x:g},backend:a,attrs:{shape:u.outputShape}});return c.forEach(x=>a.disposeIntermediateTensorInfo(x)),y}var uX={kernelName:Fl,backendName:"webgl",kernelFunc:dv},dX="return float(a > b);",pX=`
|
|
return vec4(greaterThan(a, b));
|
|
`,cX=da({opSnippet:dX,packedOpSnippet:pX,cpuKernelImpl:gU,dtype:"bool"}),hX={kernelName:vi,backendName:"webgl",kernelFunc:cX},fX="return float(a >= b);",mX=`
|
|
return vec4(greaterThanEqual(a, b));
|
|
`,gX=da({opSnippet:fX,packedOpSnippet:mX,dtype:"bool",cpuKernelImpl:yU}),yX={kernelName:ki,backendName:"webgl",kernelFunc:gX};function xX(e){let{inputs:t,backend:a}=e,{input:n}=t;return uv(n,!0,a)}var AX={kernelName:_d,backendName:"webgl",kernelFunc:xX},bX="return float(!isnan(x) && !isinf(x));",vX=Qe({opSnippet:bX,dtype:"bool"}),kX={kernelName:Ol,backendName:"webgl",kernelFunc:vX},wX="return float(isinf(x));",IX=Qe({opSnippet:wX,dtype:"bool"}),SX={kernelName:Dl,backendName:"webgl",kernelFunc:IX},TX="return float(isnan(x));",CX=Qe({opSnippet:TX,dtype:"bool"}),NX={kernelName:Ii,backendName:"webgl",kernelFunc:CX},EX="return float(a < b);",RX=`
|
|
return vec4(lessThan(a, b));
|
|
`,MX=da({opSnippet:EX,packedOpSnippet:RX,cpuKernelImpl:xU,dtype:"bool"}),$X={kernelName:Ti,backendName:"webgl",kernelFunc:MX},_X="return float(a <= b);",PX=`
|
|
return vec4(lessThanEqual(a, b));
|
|
`,FX=da({opSnippet:_X,packedOpSnippet:PX,cpuKernelImpl:AU,dtype:"bool"}),OX={kernelName:Ci,backendName:"webgl",kernelFunc:FX};function DX(e){let{backend:t,attrs:a}=e,{start:n,stop:r,num:s}=a,i=bU(n,r,s);return t.makeTensorInfo([i.length],"float32",i)}var zX={kernelName:Fd,backendName:"webgl",kernelFunc:DX},LX=mu+`
|
|
return x < 0.0 ? 0./0. : log(x);
|
|
`,BX=`
|
|
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;
|
|
`,WX=Qe({opSnippet:LX,packedOpSnippet:BX,cpuKernelImpl:vU}),VX={kernelName:Ni,backendName:"webgl",kernelFunc:WX},UX=mu+`
|
|
return log(1.0 + x);
|
|
`,GX=Qe({opSnippet:UX}),HX={kernelName:zl,backendName:"webgl",kernelFunc:GX},jX="return float(a >= 1.0 && b >= 1.0);",qX=`
|
|
return vec4(
|
|
vec4(greaterThanEqual(a, vec4(1.0))) *
|
|
vec4(greaterThanEqual(b, vec4(1.0))));
|
|
`,XX=da({opSnippet:jX,packedOpSnippet:qX,dtype:"bool"}),KX={kernelName:Ei,backendName:"webgl",kernelFunc:XX},ZX="return float(!(x >= 1.0));",YX=Qe({opSnippet:ZX}),JX={kernelName:Ri,backendName:"webgl",kernelFunc:YX},QX="return float(a >= 1.0 || b >= 1.0);",eK=`
|
|
return min(
|
|
vec4(greaterThanEqual(a, vec4(1.0))) +
|
|
vec4(greaterThanEqual(b, vec4(1.0))),
|
|
vec4(1.0));
|
|
`,tK=da({opSnippet:QX,packedOpSnippet:eK,dtype:"bool"}),aK={kernelName:Mi,backendName:"webgl",kernelFunc:tK},nK=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 * ${o};
|
|
setOutput(val);
|
|
}
|
|
`}},rK=class{constructor(e,t,a,n,r){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${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);
|
|
}
|
|
`}},sK=e=>{let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=n,u=V().getBool("WEBGL_PACK_NORMALIZATION")?new rK(r.shape,s,i,o,l):new nK(r.shape,s,i,o,l);return a.runWebGLProgram(u,[r],r.dtype)},iK={kernelName:Od,backendName:"webgl",kernelFunc:sK},oK=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 * ${r});
|
|
}
|
|
if (k == coords[3]) {
|
|
dyi *= getDy(b, r, c, d);
|
|
result += dyi;
|
|
}
|
|
}
|
|
else {
|
|
break;
|
|
}
|
|
}
|
|
}
|
|
setOutput(result);
|
|
}
|
|
`}},lK=e=>{let{inputs:t,backend:a,attrs:n}=e,{x:r,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:u,beta:p}=n,c=new oK(r.shape,o,l,u,p);return a.runWebGLProgram(c,[r,s,i],r.dtype)},uK={kernelName:V2,backendName:"webgl",kernelFunc:lK};function dK(e,t,a,n){let r=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/r,i=pe({inputs:{x:e},attrs:{shape:[s,r]},backend:n}),o=vo(i,e.dtype,"max",n),l=pe({inputs:{x:o},attrs:{shape:a},backend:n});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}function pv(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{reductionIndices:s,keepDims:i}=n,o=r.shape.length,l=v.parseAxisParam(s,r.shape),u=l,p=T.getAxesPermutation(u,o),c=p!=null,d=a.shouldExecuteOnCPU([r]),h=r;if(c){if(d){let x=a.texData.get(h.dataId).values,A=new Array(o);for(let S=0;S<A.length;S++)A[S]=r.shape[p[S]];let b=R3(x,r.shape,r.dtype,p,A);h=a.makeTensorInfo(A,r.dtype);let k=a.texData.get(h.dataId);k.values=b}else h=Mh(r,p,a);u=T.getInnerMostAxes(u.length,o)}T.assertAxesAreInnerMostDims("max",u,o);let[f,m]=T.computeOutAndReduceShapes(h.shape,u),g=f;i&&(g=T.expandShapeToKeepDim(f,l));let y;if(d){let x=a.texData.get(h.dataId).values,A=kU(x,v.sizeFromShape(m),g,r.dtype);y=a.makeTensorInfo(g,r.dtype);let b=a.texData.get(y.dataId);b.values=A}else y=dK(h,m,g,a);return c&&a.disposeIntermediateTensorInfo(h),y}var pK={kernelName:$i,backendName:"webgl",kernelFunc:pv},cK=M3+`
|
|
return max(a, b);
|
|
`,hK=`
|
|
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);
|
|
`+hp+`
|
|
return result;
|
|
`,fK=da({opSnippet:cK,packedOpSnippet:hK,cpuKernelImpl:wU}),mK={kernelName:_i,backendName:"webgl",kernelFunc:fK};function gK(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t;uu(r,"maxPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=n,u=1;v.assert(T.eitherStridesOrDilationsAreOne(i,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let p=T.computePool2DInfo(r.shape,s,i,u,o,l);if(p.filterWidth===1&&p.filterHeight===1&&v.arraysEqual(p.inShape,p.outShape))return Ja({inputs:{x:r},backend:a});let c=new xd(p,"max",!1);return a.runWebGLProgram(c,[r],r.dtype)}var yK={kernelName:Pi,backendName:"webgl",kernelFunc:gK};function xK(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=T.computePool3DInfo(r.shape,s,i,p,o,u,l),d=new _3(c,"max",!1);return a.runWebGLProgram(d,[r],r.dtype)}var AK={kernelName:ah,backendName:"webgl",kernelFunc:xK},bK=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 * ${s} + wC;
|
|
float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);
|
|
|
|
dotProd += dyValue * mask;
|
|
}
|
|
}
|
|
setOutput(dotProd);
|
|
}
|
|
`}},vK=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,a=e.strideHeight,n=e.strideWidth,r=e.dilationDepth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterDepth,l=e.effectiveFilterHeight,u=e.effectiveFilterWidth,p=o-1-e.padInfo.front,c=l-1-e.padInfo.top,d=u-1-e.padInfo.left,h=o*l*u-1;this.userCode=`
|
|
const ivec3 pads = ivec3(${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 kK(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=T.computePool3DInfo(i.shape,o,l,c,u,p),h=new _3(d,"max",!0),f=a.runWebGLProgram(h,[i],i.dtype),m=new vK(d),g=a.runWebGLProgram(m,[r,f],i.dtype);return a.disposeIntermediateTensorInfo(f),g}var wK={kernelName:G2,backendName:"webgl",kernelFunc:kK};function IK(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s,output:i}=t,o=s;uu([s,i],"maxPoolGrad");let{filterSize:l,strides:u,pad:p,dimRoundingMode:c}=n,d=T.computePool2DInfo(o.shape,l,u,1,p,c),h=!0,f=new xd(d,"max",h),m=a.runWebGLProgram(f,[o],o.dtype),g=new bK(d),y=a.runWebGLProgram(g,[r,m],o.dtype);return a.disposeIntermediateTensorInfo(m),y}var SK={kernelName:U2,backendName:"webgl",kernelFunc:IK};function TK(e,t,a,n){let r=new xd(a,"max",!1),s=n.runWebGLProgram(r,[e],"float32");r=new xd(a,"max",!0,!0,t);let i=n.runWebGLProgram(r,[e],"float32");return[s,i]}var CK={kernelName:nh,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(T.eitherStridesOrDilationsAreOne(s,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${u}'`);let p=T.computePool2DInfo(n.shape,r,s,u,i),[c,d]=TK(n,o,p,l);return[c,d]}};function NK(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=vo(i,"float32","mean",n),l=pe({inputs:{x:o},attrs:{shape:a},backend:n});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}var EK={kernelName:Fi,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=T.getAxesPermutation(u,o),c=p!=null,d=i.shouldExecuteOnCPU([n]),h=[],f=n;if(c){if(d){let A=i.texData.get(f.dataId).values,b=new Array(o);for(let C=0;C<b.length;C++)b[C]=n.shape[p[C]];let k=R3(A,n.shape,n.dtype,p,b);f=i.makeTensorInfo(b,n.dtype);let S=i.texData.get(f.dataId);S.values=k}else f=Mh(n,p,i);h.push(f),u=T.getInnerMostAxes(u.length,o)}T.assertAxesAreInnerMostDims("sum",u,o);let[m,g]=T.computeOutAndReduceShapes(f.shape,u),y=m;r&&(y=T.expandShapeToKeepDim(m,l));let x=NK(f,g,y,i);for(let A of h)i.disposeIntermediateTensorInfo(A);return x}};function RK(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=T.getAxesPermutation(u,o),c=r;p!=null&&(c=Sa({inputs:{x:r},backend:a,attrs:{perm:p}}),u=T.getInnerMostAxes(u.length,r.shape.length)),T.assertAxesAreInnerMostDims("min",u,o);let[d,h]=T.computeOutAndReduceShapes(c.shape,u),f=v.sizeFromShape(h),m=pe({inputs:{x:c},backend:a,attrs:{shape:[-1,f]}}),g=vo(m,m.dtype,"min",a),y;if(i){let x=T.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(m),a.disposeIntermediateTensorInfo(g),p!=null&&a.disposeIntermediateTensorInfo(c),y}var MK={kernelName:Oi,backendName:"webgl",kernelFunc:RK},$K=M3+`
|
|
return min(a, b);
|
|
`,_K=`
|
|
vec4 result = vec4(min(a, b));
|
|
bvec4 isNaNA = isnan(a);
|
|
bvec4 isNaNB = isnan(b);
|
|
bvec4 isNaN = bvec4(isNaNA.x || isNaNB.x, isNaNA.y || isNaNB.y, isNaNA.z || isNaNB.z, isNaNA.w || isNaNB.w);
|
|
`+hp+`
|
|
return result;
|
|
`,PK=da({opSnippet:$K,packedOpSnippet:_K,cpuKernelImpl:IU}),FK={kernelName:Di,backendName:"webgl",kernelFunc:PK},OK=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=gt(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}));
|
|
}
|
|
`}},DK=class{constructor(e,t,a){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((h,f)=>h[0]+e[f]+h[1]);let n=e.length,r=gt(n),s=t.map(h=>h[0]).join(","),i=t.map((h,f)=>h[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=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);
|
|
}
|
|
`}},zK=({inputs:e,backend:t,attrs:a})=>{let{x:n}=e,{paddings:r,mode:s}=a,i=V().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new DK(n.shape,r,s):new OK(n.shape,r,s);return t.runWebGLProgram(i,[n],n.dtype)},LK={kernelName:zi,backendName:"webgl",kernelFunc:zK},BK=`if (b == 0.0) return NAN;
|
|
return mod(a, b);`,WK=`
|
|
vec4 result = mod(a, b);
|
|
bvec4 isNaN = equal(b, vec4(0.0));
|
|
`+hp+`
|
|
return result;
|
|
`,VK=da({opSnippet:BK,packedOpSnippet:WK}),UK={kernelName:Ll,backendName:"webgl",kernelFunc:VK},GK=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}));
|
|
}
|
|
`}},HK=`
|
|
if (a == b) {
|
|
return 1.0;
|
|
};
|
|
return a / b;`,jK=`
|
|
// 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;
|
|
`,cv=da({opSnippet:HK,packedOpSnippet:jK,checkOutOfBounds:!0}),qK={kernelName:ci,backendName:"webgl",kernelFunc:cv},Ey="return a - b;",hv=da({opSnippet:Ey,packedOpSnippet:Ey,supportsComplex:!0,cpuKernelImpl:GU}),XK={kernelName:po,backendName:"webgl",kernelFunc:hv};function fv(e){let{inputs:t,backend:a,attrs:n}=e,{logits:r}=t,{dim:s}=n,i=v.parseAxisParam([s],r.shape),o=pv({inputs:{x:r},backend:a,attrs:{reductionIndices:i,keepDims:!1}}),l=T.expandShapeToKeepDim(o.shape,i),u=pe({inputs:{x:o},backend:a,attrs:{shape:l}}),p=hv({inputs:{a:r,b:u},backend:a}),c=lv({inputs:{x:p},backend:a}),d=$h({inputs:{x:c},backend:a,attrs:{axis:i,keepDims:!1}}),h=pe({inputs:{x:d},backend:a,attrs:{shape:l}}),f=cv({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),f}var KK={kernelName:oo,backendName:"webgl",kernelFunc:fv};function ZK(e){let{inputs:t,backend:a,attrs:n}=e,{logits:r}=t,{numSamples:s,seed:i,normalized:o}=n,l=o?r:fv({inputs:{logits:r},backend:a,attrs:{dim:r.shape.length-1}}),u=l.shape[0],p=l.shape[1],c=new GK(u,p,s),d=[[i]],h=a.runWebGLProgram(c,[l],"int32",d);return o||a.disposeIntermediateTensorInfo(l),h}var YK={kernelName:rh,backendName:"webgl",kernelFunc:ZK},JK=En+`
|
|
return -x;
|
|
`,QK=`
|
|
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 eZ(e){let{inputs:t,backend:a}=e,{x:n}=t;if(a.shouldExecuteOnCPU([n])){let s=a.texData.get(n.dataId),[i,o]=TU(s.values,n.shape,n.dtype);return a.makeTensorInfo(o,n.dtype,i)}let r;return V().getBool("WEBGL_PACK_UNARY_OPERATIONS")?r=new Wr(n.shape,QK):r=new qn(n.shape,JK),a.runWebGLProgram(r,[n],n.dtype)}var tZ={kernelName:Bl,backendName:"webgl",kernelFunc:eZ},aZ=Nn.nonMaxSuppressionV3Impl;function nZ(e){T.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}=aZ(u,p,i,o,l);return a.makeTensorInfo([c.length],"int32",new Int32Array(c))}var rZ={kernelName:Wi,backendName:"webgl",kernelFunc:nZ},sZ=Nn.nonMaxSuppressionV4Impl;function iZ(e){T.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}=sZ(p,c,i,o,l,u);return[a.makeTensorInfo([d.length],"int32",new Int32Array(d)),a.makeTensorInfo([],"int32",new Int32Array([h]))]}var oZ={kernelName:Wl,backendName:"webgl",kernelFunc:iZ},lZ=Nn.nonMaxSuppressionV5Impl;function uZ(e){T.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,f=l,m=u,{selectedIndices:g,selectedScores:y}=lZ(p,c,d,h,f,m);return[a.makeTensorInfo([g.length],"int32",new Int32Array(g)),a.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var dZ={kernelName:Vi,backendName:"webgl",kernelFunc:uZ},pZ=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)));
|
|
}
|
|
`}},cZ=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 pZ(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],f=pe({inputs:{x:d},backend:a,attrs:{shape:h}});return a.disposeIntermediateTensorInfo(d),f},hZ={kernelName:Ui,backendName:"webgl",kernelFunc:cZ};function Wc(e){let{inputs:t,backend:a}=e,{x:n}=t;if(n.dtype==="complex64"){let r=mp({inputs:{input:n},backend:a}),s=Wc({inputs:{x:r},backend:a}),i=_h({inputs:{input:n},backend:a}),o=Wc({inputs:{x:i},backend:a}),l=ls({inputs:{real:s,imag:o},backend:a});return a.disposeIntermediateTensorInfo(r),a.disposeIntermediateTensorInfo(s),a.disposeIntermediateTensorInfo(i),a.disposeIntermediateTensorInfo(o),l}else return gp({attrs:{shape:n.shape,dtype:n.dtype,value:n.dtype==="string"?"":0},backend:a})}var fZ={kernelName:nu,backendName:"webgl",kernelFunc:Wc};function mv(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=mp({inputs:{input:n},backend:a}),s=mv({inputs:{x:r},backend:a}),i=_h({inputs:{input:n},backend:a}),o=Wc({inputs:{x:i},backend:a}),l=ls({inputs:{real:s,imag:o},backend:a});return a.disposeIntermediateTensorInfo(r),a.disposeIntermediateTensorInfo(s),a.disposeIntermediateTensorInfo(i),a.disposeIntermediateTensorInfo(o),l}else return gp({attrs:{shape:n.shape,dtype:n.dtype,value:1},backend:a})}var mZ={kernelName:Vl,backendName:"webgl",kernelFunc:mv};function gZ(e){let{inputs:t,backend:a,attrs:n}=e,{axis:r}=n;if(t.length===1)return I2({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=I2({inputs:{input:p},backend:a,attrs:{dim:r}});return o.push(c),c}),u=ev({inputs:l,backend:a,attrs:{axis:r}});return o.forEach(p=>a.disposeIntermediateTensorInfo(p)),u}var yZ={kernelName:Ul,backendName:"webgl",kernelFunc:gZ},xZ=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=gt(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}));
|
|
}
|
|
}
|
|
`}},AZ=class{constructor(e,t,a){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"value",type:"float"}],this.outputShape=t.map((f,m)=>f[0]+e[m]+f[1]);let n=e.length,r=gt(n),s=t.map(f=>f[0]).join(","),i=t.map((f,m)=>f[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=[`${r} rc = outputLoc;`,`${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 f=0,m=n===1?2:4;f<m;f++)h+=`
|
|
${c[f]}
|
|
if (${d}) {
|
|
result[${f}] = float(value);
|
|
} else {
|
|
${r} source = rc - start;
|
|
result[${f}] = 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);
|
|
}
|
|
`}},gv=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 gp({backend:a,attrs:{shape:u,value:i,dtype:r.dtype}})}let o=V().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new AZ(r.shape,s,i):new xZ(r.shape,s,i),l=[[i]];return a.runWebGLProgram(o,[r],r.dtype,l)},bZ={kernelName:Gi,backendName:"webgl",kernelFunc:gv},vZ=`
|
|
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);
|
|
`,kZ=`
|
|
// 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);
|
|
`+hp+`
|
|
return result;
|
|
`,wZ=da({opSnippet:vZ,packedOpSnippet:kZ}),IZ={kernelName:Hi,backendName:"webgl",kernelFunc:wZ};function SZ(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=T.getAxesPermutation(p,o),d=r;c!=null&&(d=Sa({inputs:{x:r},backend:a,attrs:{perm:c}}),p=T.getInnerMostAxes(p.length,o),l.push(d)),T.assertAxesAreInnerMostDims("prod",p,o);let h;if(a.shouldExecuteOnCPU([d])){let f=a.texData.get(d.dataId).values,{outVals:m,outShape:g,outDtype:y}=NU(d.shape,d.dtype,f,p);h=a.makeTensorInfo(g,y,m)}else{let[f,m]=T.computeOutAndReduceShapes(d.shape,p),g=v.sizeFromShape(m),y=pe({inputs:{x:d},backend:a,attrs:{shape:[-1,g]}}),x=Xd(r.dtype),A=vo(y,x,"prod",a);h=pe({inputs:{x:A},backend:a,attrs:{shape:f}}),l.push(y),l.push(A)}if(i){l.push(h);let f=T.expandShapeToKeepDim(h.shape,u);h=pe({inputs:{x:h},backend:a,attrs:{shape:f}})}return l.forEach(f=>a.disposeIntermediateTensorInfo(f)),h}var TZ={kernelName:qi,backendName:"webgl",kernelFunc:SZ};function CZ(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,f]=EU(l,u,p,s.shape,s.dtype,c,i.shape,o),m=d.map(y=>a.makeTensorInfo([y.length],"int32",y)),g=a.makeTensorInfo(f,s.dtype,h);return m.concat([g])}var NZ={kernelName:sh,backendName:"webgl",kernelFunc:CZ};function EZ(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]=RU(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 RZ={kernelName:ih,backendName:"webgl",kernelFunc:EZ};function MZ(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),[f,m]=MU(u,r.shape,p,s.shape,s.dtype,c,i.shape,d,h,l);return a.makeTensorInfo(f,s.dtype,m)}var $Z={kernelName:oh,backendName:"webgl",kernelFunc:MZ},yv=e=>{let{backend:t,attrs:a}=e,{start:n,stop:r,step:s,dtype:i}=a,o=$U(n,r,s,i);return t.makeTensorInfo([o.length],i,o)},_Z={kernelName:Gl,backendName:"webgl",kernelFunc:yv},PZ="return 1.0 / x;",FZ=Qe({opSnippet:PZ}),OZ={kernelName:Xi,backendName:"webgl",kernelFunc:FZ},DZ=En+`
|
|
return (x < 0.0) ? 0.0 : x;
|
|
`,zZ=`
|
|
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;
|
|
`,LZ=Qe({opSnippet:DZ,packedOpSnippet:zZ}),BZ={kernelName:Ki,backendName:"webgl",kernelFunc:LZ},WZ=En+`
|
|
return (x < 0.0) ? 0.0 : min(6.0, x);
|
|
`,VZ=`
|
|
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;
|
|
`,UZ=Qe({opSnippet:WZ,packedOpSnippet:VZ}),GZ={kernelName:Ji,backendName:"webgl",kernelFunc:UZ},HZ=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);
|
|
}
|
|
`}},jZ=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 qZ(e){let{inputs:t,backend:a,attrs:n}=e,{images:r}=t,{alignCorners:s,halfPixelCenters:i,size:o}=n,[l,u]=o,p=V().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new jZ(r.shape,l,u,s,i):new HZ(r.shape,l,u,s,i);return a.runWebGLProgram(p,[r],"float32")}var XZ={kernelName:Yi,backendName:"webgl",kernelFunc:qZ},KZ=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,f=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(${f});
|
|
|
|
// 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 ZZ(e){let{inputs:t,backend:a,attrs:n}=e,{images:r,dy:s}=t,{alignCorners:i}=n,o=new KZ(s.shape,r.shape,i);return a.runWebGLProgram(o,[s],s.dtype)}var YZ={kernelName:j2,backendName:"webgl",kernelFunc:ZZ},JZ=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);
|
|
}
|
|
`}},QZ=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 < ${a-1};
|
|
|
|
vec4 newValue = vec4(
|
|
getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d),
|
|
hasNextCol ? getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d + 1)
|
|
: 0.0,
|
|
hasNextRow ? getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d)
|
|
: 0.0,
|
|
(hasNextRow && hasNextCol) ?
|
|
getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d + 1) : 0.0);
|
|
|
|
setOutput(newValue);
|
|
}
|
|
`}};function eY(e){let{inputs:t,backend:a,attrs:n}=e,{images:r}=t,{alignCorners:s,halfPixelCenters:i,size:o}=n,[l,u]=o,p=V().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new QZ(r.shape,l,u,s,i):new JZ(r.shape,l,u,s,i);return a.runWebGLProgram(p,[r],r.dtype)}var tY={kernelName:Zi,backendName:"webgl",kernelFunc:eY},aY=class{constructor(e,t,a){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,n,r]=t,[,s,i]=e,o=[a&&s>1?n-1:n,a&&i>1?r-1:r],l=[a&&s>1?s-1:s,a&&i>1?i-1:i],u=o[0]/l[0],p=o[1]/l[1],c=1/u,d=1/p,h=Math.ceil(c)*2+2,f=Math.ceil(d)*2+2;this.userCode=`
|
|
void main() {
|
|
ivec4 coords = getOutputCoords();
|
|
int b = coords[0];
|
|
int d = coords[3];
|
|
int r = coords[1];
|
|
int c = coords[2];
|
|
|
|
float accumulator = 0.0;
|
|
|
|
const float heightScale = float(${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(${f});
|
|
|
|
// 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),
|
|
${a} ? float(round(sourceFracCol)) :
|
|
float(floor(sourceFracCol))));
|
|
|
|
if (r == sourceNearestRow && c == sourceNearestCol) {
|
|
accumulator += getDy(b, dyR, dyC, d);
|
|
}
|
|
}
|
|
}
|
|
// End loop over dy
|
|
|
|
setOutput(accumulator);
|
|
}
|
|
`}};function nY(e){let{inputs:t,backend:a,attrs:n}=e,{images:r,dy:s}=t,{alignCorners:i}=n,o=new aY(s.shape,r.shape,i);return a.runWebGLProgram(o,[s],s.dtype)}var rY={kernelName:H2,backendName:"webgl",kernelFunc:nY},sY=class{constructor(e,t){this.variableNames=["x"];let a=e.length;if(a>4)throw new Error(`WebGL backend: Reverse of rank-${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=gt(a);this.userCode=`
|
|
void main() {
|
|
${s} coords = getOutputCoords();
|
|
setOutput(getX(${r}));
|
|
}
|
|
`}},iY=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 < ${this.outputShape[a-2]}`,i=gt(a);a===1?this.userCode=`
|
|
void main(){
|
|
int rc = getOutputCoords();
|
|
vec4 result = vec4(0.);
|
|
result.r = getChannel(getX(${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 = ${p(n.slice())};
|
|
}
|
|
}
|
|
setOutput(result);
|
|
}
|
|
`;function o(h){return c(h)}function l(h){return h[a-1]="("+h[a-1]+" + 1)",c(h)}function u(h){return h[a-2]="("+h[a-2]+" + 1)",c(h)}function p(h){return h[a-1]="("+h[a-1]+" + 1)",h[a-2]="("+h[a-2]+" + 1)",c(h)}function c(h){let f=e.map((y,x)=>d(x,h)),m=f.join(","),g=f.slice(-2).join(",");return`getChannel(getX(${m}), vec2(${g}))`}function d(h,f){return t.indexOf(h)!==-1&&e[h]!==1?`${e[h]} - ${f[h]} - 1`:`${f[h]}`}}};function oY(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 Ja({inputs:{x:r},backend:a});let l=V().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new iY(r.shape,o):new sY(r.shape,o);return a.runWebGLProgram(l,[r],r.dtype)}var lY={kernelName:Qi,backendName:"webgl",kernelFunc:oY},uY=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 < ${a}) {
|
|
outputValue = getImage(coords[0], coordY, coordX, coords[3]);
|
|
}
|
|
setOutput(outputValue);
|
|
}
|
|
`}},dY={kernelName:go,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:a})=>{let{image:n}=e,{radians:r,fillValue:s,center:i}=t,o=a,l=new uY(n.shape,s),[u,p]=T.getImageCenter(i,n.shape[1],n.shape[2]),c=[[u,p,Math.sin(r),Math.cos(r)]];return o.runWebGLProgram(l,[n],n.dtype,c)}},pY=`
|
|
// OpenGL ES does not support round function.
|
|
// The algorithm is based on banker's rounding.
|
|
float base = floor(x);
|
|
if ((x - base) < 0.5) {
|
|
return floor(x);
|
|
} else if ((x - base) > 0.5) {
|
|
return ceil(x);
|
|
} else {
|
|
if (mod(base, 2.0) == 0.0) {
|
|
return base;
|
|
} else {
|
|
return base + 1.0;
|
|
}
|
|
}
|
|
`,cY=Qe({opSnippet:pY}),hY={kernelName:eo,backendName:"webgl",kernelFunc:cY},fY="return inversesqrt(x);",mY=Qe({opSnippet:fY,cpuKernelImpl:_U}),gY={kernelName:to,backendName:"webgl",kernelFunc:mY},xv=class{constructor(e,t,a,n,r,s,i=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=s;let o=gt(r.length),l=gt(s.length),u="";a===1?u="i":a===2&&(u="i, j");let p=`getIndices(${u})`,c="";n===1?c="i":n===2&&(c="i, coords[1]");let d=`getUpdates(${c})`,h=t>1?"strides[j]":"strides";this.userCode=`
|
|
${o} strides = ${o}(${r});
|
|
|
|
void main() {
|
|
${l} coords = getOutputCoords();
|
|
float sum = 0.0;
|
|
bool found = false;
|
|
for (int i = 0; i < ${e}; i++) {
|
|
int flattenedIndex = 0;
|
|
for (int j = 0; j < ${t}; j++) {
|
|
int index = round(${p});
|
|
flattenedIndex += index * ${h};
|
|
}
|
|
if (flattenedIndex == coords[0]) {
|
|
sum += ${d};
|
|
found = true;
|
|
}
|
|
}
|
|
setOutput(mix(getDefaultValue(), sum, float(found)));
|
|
}
|
|
`}};function yY(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}=T.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]}}),f=pe({inputs:{x:s},backend:a,attrs:{shape:[l,u]}}),m=a.makeTensorInfo([],"float32",new Float32Array([0])),g=new xv(l,o,h.shape.length,f.shape.length,p,d),y=a.runWebGLProgram(g,[f,h,m],f.dtype),x=pe({inputs:{x:y},backend:a,attrs:{shape:i}});return a.disposeIntermediateTensorInfo(h),a.disposeIntermediateTensorInfo(f),a.disposeIntermediateTensorInfo(y),a.disposeIntermediateTensorInfo(m),x}var xY={kernelName:ao,backendName:"webgl",kernelFunc:yY},AY=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=V().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 bY(e){let{inputs:t,backend:a,attrs:n}=e,{sortedSequence:r,values:s}=t,{side:i}=n,o=new AY(r.shape[0],r.shape[1],s.shape[1],i),l=[[r.shape[1]]];return a.runWebGLProgram(o,[r,s],"int32",l)}var vY={kernelName:zd,backendName:"webgl",kernelFunc:bY},kY=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=gt(a);this.userCode=`
|
|
void main() {
|
|
${s} resRC = getOutputCoords();
|
|
float cVal = getC(${n});
|
|
if (cVal >= 1.0) {
|
|
setOutput(getA(${r}));
|
|
} else {
|
|
setOutput(getB(${r}));
|
|
}
|
|
}
|
|
`}};function wY(e){let{inputs:t,backend:a}=e,{condition:n,t:r,e:s}=t,i=new kY(n.shape.length,r.shape,r.shape.length);return a.runWebGLProgram(i,[n,r,s],fa(r.dtype,s.dtype))}var IY={kernelName:jl,backendName:"webgl",kernelFunc:wY},SY=`
|
|
// Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
|
|
// see: https://arxiv.org/abs/1706.02515
|
|
float scaleAlpha = ${T.SELU_SCALEALPHA};
|
|
float scale = ${T.SELU_SCALE};
|
|
return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
|
|
`,TY=Qe({opSnippet:SY}),CY={kernelName:ql,backendName:"webgl",kernelFunc:TY},NY=mu+`
|
|
return 1.0 / (1.0 + exp(-1.0 * x));
|
|
`,EY=`
|
|
vec4 result = 1.0 / (1.0 + exp(-1.0 * x));
|
|
bvec4 isNaN = isnan(x);
|
|
|
|
result.r = isNaN.r ? x.r : result.r;
|
|
result.g = isNaN.g ? x.g : result.g;
|
|
result.b = isNaN.b ? x.b : result.b;
|
|
result.a = isNaN.a ? x.a : result.a;
|
|
|
|
return result;
|
|
`,RY=Qe({opSnippet:NY,packedOpSnippet:EY,cpuKernelImpl:FU}),MY={kernelName:ro,backendName:"webgl",kernelFunc:RY},$Y=`
|
|
if (isnan(x)) { return 0.0; }
|
|
return sign(x);
|
|
`,_Y=Qe({opSnippet:$Y}),PY={kernelName:Zl,backendName:"webgl",kernelFunc:_Y},FY=mu+`
|
|
return sin(x);
|
|
`,OY=Qe({opSnippet:FY}),DY={kernelName:no,backendName:"webgl",kernelFunc:OY},zY=`
|
|
float e2x = exp(x);
|
|
return (e2x - 1.0 / e2x) / 2.0;
|
|
`,LY=Qe({opSnippet:zY}),BY={kernelName:Kl,backendName:"webgl",kernelFunc:LY},WY=`
|
|
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;
|
|
`,VY=Qe({opSnippet:WY}),UY={kernelName:Yl,backendName:"webgl",kernelFunc:VY},GY=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=gv({inputs:{x:r},backend:a,attrs:{paddings:l,constantValue:0}}),c=T.getReshaped(p.shape,s,o,!1),d=T.getPermuted(c.length,s.length,!1),h=T.getReshapedPermuted(p.shape,s,o,!1),f=pe({inputs:{x:p},backend:a,attrs:{shape:c}}),m=Sa({inputs:{x:f},backend:a,attrs:{perm:d}}),g=pe({inputs:{x:m},backend:a,attrs:{shape:h}});return u.push(p),u.push(f),u.push(m),u.forEach(y=>a.disposeIntermediateTensorInfo(y)),g},HY={kernelName:Jl,backendName:"webgl",kernelFunc:GY};function jY(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,f,m]=DU(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([f.length],"bool",new Uint8Array(f.map(g=>Number(g)))),a.makeTensorInfo([m.length],n.dtype,new Int32Array(m))]}var qY={kernelName:Ld,backendName:"webgl",kernelFunc:jY};function XY(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]=zU(o,n.shape,n.dtype,i,l);return[a.makeTensorInfo(p,n.dtype,u),a.makeTensorInfo([c.length],s.dtype,new Int32Array(c))]}var KY={kernelName:eu,backendName:"webgl",kernelFunc:XY};function ZY(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]=B6(i,n.shape,n.dtype,o,l,!0);return a.makeTensorInfo(p,n.dtype,u)}var YY={kernelName:Bd,backendName:"webgl",kernelFunc:ZY};function JY(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
|
|
${s.shape}`);let i=a.readSync(n.dataId),o=a.readSync(r.dataId),l=a.readSync(s.dataId),[u,p]=B6(i,n.shape,n.dtype,o,l);return a.makeTensorInfo(p,n.dtype,u)}var QY={kernelName:Wd,backendName:"webgl",kernelFunc:JY};function eJ(e){let{inputs:t,backend:a,attrs:n}=e,{sparseIndices:r,sparseValues:s,defaultValue:i}=t,{outputShape:o}=n,{sliceRank:l,numUpdates:u,sliceSize:p,strides:c,outputSize:d}=T.calculateShapes(s,r,o),h=!1;if(s.dtype==="string"){let y=a.bufferSync(r),x=a.bufferSync(s),A=v.decodeString(a.readSync(i.dataId)[0]),b=PU(y,x,o,d,p,u,l,c,A,h);return a.makeTensorInfo(o,b.dtype,b.values)}let f=new xv(u,l,r.shape.length,s.shape.length,c,[d,1],h),m=a.runWebGLProgram(f,[s,r,i],s.dtype),g=pe({inputs:{x:m},backend:a,attrs:{shape:o}});return a.disposeIntermediateTensorInfo(m),g}var tJ={kernelName:Vd,backendName:"webgl",kernelFunc:eJ};function aJ(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{numOrSizeSplits:s,axis:i}=n,o=v.parseAxisParam(i,r.shape)[0],l=T.prepareSplitSize(r,s,o),u=r.shape.length,p=new Array(u).fill(0),c=r.shape.slice();return l.map(d=>{let h=[...c];h[o]=d;let f=gu({inputs:{x:r},backend:a,attrs:{begin:p,size:h}});return p[o]+=d,f})}var nJ={kernelName:Ql,backendName:"webgl",kernelFunc:aJ},Ry="return sqrt(x);",rJ=Qe({opSnippet:Ry,packedOpSnippet:Ry,cpuKernelImpl:LU}),sJ={kernelName:so,backendName:"webgl",kernelFunc:rJ},iJ="return x * x;",oJ=Qe({opSnippet:iJ}),lJ={kernelName:Ud,backendName:"webgl",kernelFunc:oJ},My="return (a - b) * (a - b);",uJ=da({opSnippet:My,packedOpSnippet:My}),dJ={kernelName:lo,backendName:"webgl",kernelFunc:uJ};function pJ({inputs:e,attrs:t,backend:a}){let{x:n}=e,r=En+`
|
|
return x > 0.0 ? 1.0 : float(${t.alpha});
|
|
`,s=new qn(n.shape,r);return a.runWebGLProgram(s,[n],n.dtype)}var cJ={kernelName:rs,backendName:"webgl",kernelFunc:pJ},hJ=class{constructor(e,t,a){this.variableNames=["x"],this.outputShape=a;let n=a.length,r=gt(a.length),s=gt(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 fJ(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:f,isIdentity:m,sliceDim0:g,isSimpleSlice:y,begin:x,end:A,strides:b}=St.sliceInfo(r.shape,s,i,o,l,u,p,c,d),k;if(m)k=pe({inputs:{x:r},backend:a,attrs:{shape:f}});else if(g||y){v.assert(r.shape.length>=1,()=>`Input must have rank at least 1, got: ${r.shape.length}`);let C=St.computeOutShape(x,A,b),N=gu({inputs:{x:r},backend:a,attrs:{begin:x,size:C}});k=pe({inputs:{x:N},backend:a,attrs:{shape:f}}),a.disposeIntermediateTensorInfo(N)}else if(a.shouldExecuteOnCPU([r])){let C=a.readSync(r.dataId),N=_e(r.shape,r.dtype,C),$=BU(h,N,b,x);k=a.makeTensorInfo(f,r.dtype,$.values)}else{let C=new hJ(x,b,h);k=a.runWebGLProgram(C,[r],r.dtype)}let S=pe({inputs:{x:k},backend:a,attrs:{shape:f}});return a.disposeIntermediateTensorInfo(k),S}var mJ={kernelName:uo,backendName:"webgl",kernelFunc:fJ};function gJ(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),[f,m]=WU(d,h,r,s,i,o,l,u);return[a.makeTensorInfo([f.length],"string",f),a.makeTensorInfo(c.shape,"int32",m)]}var yJ={kernelName:tu,backendName:"webgl",kernelFunc:gJ};function xJ(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]=VU(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 AJ={kernelName:Gd,backendName:"webgl",kernelFunc:xJ};function bJ(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=UU(i,r);return a.makeTensorInfo(s.shape,"int32",o)}var vJ={kernelName:Hd,backendName:"webgl",kernelFunc:bJ},kJ="return tan(x);",wJ=Qe({opSnippet:kJ}),IJ={kernelName:co,backendName:"webgl",kernelFunc:wJ},SJ=`
|
|
float e2x = exp(-2.0 * abs(x));
|
|
return sign(x) * (1.0 - e2x) / (1.0 + e2x);
|
|
`,TJ=Qe({opSnippet:SJ}),CJ={kernelName:ho,backendName:"webgl",kernelFunc:TJ},NJ=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=gt(this.rank),r=EJ(e);this.userCode=`
|
|
void main() {
|
|
${n} resRC = getOutputCoords();
|
|
setOutput(getA(${r}));
|
|
}
|
|
`}};function EJ(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 Av(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=HU(u,s);return a.makeTensorInfo(p.shape,p.dtype,p.values)}let i=new NJ(r.shape,s);return a.runWebGLProgram(i,[r],r.dtype)}var RJ={kernelName:ns,backendName:"webgl",kernelFunc:Av},MJ=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));
|
|
}
|
|
}
|
|
`}},$J=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 Rs(e,t){t!==null&&e.disposeIntermediateTensorInfo(t)}function $y(e){let t=1;for(;t<e;)t*=2;return t}function _J(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{k:s,sorted:i}=n,o=V().getNumber("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD"),l=V().getNumber("TOPK_K_CPU_HANDOFF_THRESHOLD"),u=r.shape,p=u[u.length-1];if(a.shouldExecuteOnCPU([r])||p<o||s>l){let $=a.readSync(r.dataId),[M,R]=jU($,u,r.dtype,s,i);return[a.makeTensorInfo(M.shape,M.dtype,M.values),a.makeTensorInfo(R.shape,R.dtype,R.values)]}if(s===0)return u[u.length-1]=0,[a.makeTensorInfo(u,r.dtype,[]),a.makeTensorInfo(u,"int32",[])];if(p===1)return[r,gp({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,f=v.sizeFromShape(u)/p,m=pe({inputs:{x:h},attrs:{shape:[f,p]},backend:a});d&&Rs(a,h);let g=$y(s),y=$y(p),x=null,A=()=>x===null?[m,m]:[m,x],b=($,M,R)=>{let I=A(),_=new MJ(R),D=[[p],[x===null?1:0],[Number.NEGATIVE_INFINITY],[$],[M]],W=x;x=a.runWebGLProgram(_,I,"int32",D),Rs(a,W)};for(let $=1;$<g;$*=2){let M=$*2;for(let R=$;R>=1;R/=2)b(M,R,[f,y])}for(let $=y;$>g;$/=2){let M=A(),R=new $J([f,$/2]),I=[[p],[x===null?1:0],[g]],_=x;x=a.runWebGLProgram(R,M,"int32",I),Rs(a,_);let D=g/2,W=D*2;for(let P=D;P>=1;P/=2)b(W,P,x.shape)}let k=x;x=gu({inputs:{x},backend:a,attrs:{begin:0,size:[f,s]}}),Rs(a,k);let S=dv({inputs:{x:m,indices:x},backend:a,attrs:{axis:1,batchDims:1}});Rs(a,m);let C=u.slice(0,-1);C.push(s),k=x,x=pe({inputs:{x},attrs:{shape:C},backend:a}),Rs(a,k);let N=S;return S=pe({inputs:{x:S},attrs:{shape:C},backend:a}),Rs(a,N),[S,x]}var PJ={kernelName:fo,backendName:"webgl",kernelFunc:_J},FJ=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 OJ(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,[f,m]=u!=null?u:[c,d],g=[p,f,m,h],y=new FJ(c,d,i,o,l,g);return a.runWebGLProgram(y,[r,s],"float32")}var DJ={kernelName:mo,backendName:"webgl",kernelFunc:OJ};function zJ(e){let{inputs:t,attrs:a,backend:n}=e,{axis:r}=a,{x:s}=t;uu(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}=qU(i,r,s.shape,s.dtype);return[n.makeTensorInfo(l,s.dtype,o),n.makeTensorInfo([u.length],"int32",u)]}var LJ={kernelName:lh,backendName:"webgl",kernelFunc:zJ};function BJ(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 m=0;m<o;m++)m!==s&&(u[p++]=i.shape[m]);let c=[],d=new Array(o).fill(0),h=i.shape.slice();h[s]=1;let f=new Array(l);for(let m=0;m<f.length;m++){d[s]=m;let g=gu({inputs:{x:i},backend:a,attrs:{begin:d,size:h}}),y=pe({inputs:{x:g},backend:a,attrs:{shape:u}});f[m]=y,c.push(g)}return c.forEach(m=>a.disposeIntermediateTensorInfo(m)),f}var WJ={kernelName:au,backendName:"webgl",kernelFunc:BJ},VJ=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 UJ(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=T.getAxesPermutation([u],o),c=r;p!=null&&(c=Sa({inputs:{x:r},backend:a,attrs:{perm:p}}),l.push(c),u=T.getInnerMostAxes(1,o)[0]);let d=T.segment_util.computeOutShape(c.shape,u,i),h=v.sizeFromShape([c.shape[u]]),f=pe({inputs:{x:c},backend:a,attrs:{shape:[-1,h]}});l.push(f);let m=Xd(r.dtype),g=(b,k,S,C,N)=>{let $=b.shape[0],M=b.shape[1],R=T.segment_util.segOpComputeOptimalWindowSize(M,N),I={windowSize:R,inSize:M,batchSize:$,numSegments:N},_=new VJ(I,k),D=a.compileAndRun(_,[b,S],C);if(l.push(D),D.shape[1]===N)return D;let W=yv({backend:a,attrs:{start:0,stop:N,step:1,dtype:"float32"}}),P=Av({inputs:{x:W},backend:a,attrs:{reps:[M/R]}});return l.push(W),l.push(P),g(D,k,P,C,N)},y=g(f,"unsortedSegmentSum",s,m,i),x=pe({inputs:{x:y},backend:a,attrs:{shape:d}}),A=x;if(p!=null){l.push(x);let b=T.getUndoAxesPermutation(p);A=Sa({inputs:{x:A},backend:a,attrs:{perm:b}})}return l.forEach(b=>a.disposeIntermediateTensorInfo(b)),A}var GJ={kernelName:uh,backendName:"webgl",kernelFunc:UJ},HJ=[BG,VG,HG,XG,ZG,QG,tH,nH,oH,uH,cH,mH,xH,kH,SH,CH,EH,_H,FH,DH,WH,XH,ZH,JH,rj,ij,dj,wG,hj,xj,kj,Nj,Rj,$j,Pj,Oj,Lj,Vj,Hj,qj,Kj,Yj,eq,aq,iq,lq,pq,fq,gq,bq,Iq,Nq,Mq,Pq,Fq,Dq,Lq,Wq,Uq,Hq,Kq,Jq,tX,nX,iX,uX,hX,yX,kG,AX,gj,kX,SX,NX,SG,$X,OX,zX,VX,HX,KX,JX,aK,iK,uK,pK,mK,yK,AK,wK,SK,CK,EK,MK,FK,LK,UK,YK,NG,tZ,rZ,oZ,dZ,ej,hZ,mZ,yZ,bZ,IZ,CG,TZ,NZ,RZ,$Z,_Z,tj,qK,OZ,BZ,GZ,RG,XZ,YZ,tY,rY,lY,dY,hY,gY,xY,vY,IY,CY,MY,PY,DY,BY,jH,KK,UY,HY,qY,KY,YY,QY,tJ,nJ,sJ,lJ,dJ,cJ,mJ,yJ,AJ,vJ,XK,DG,IJ,CJ,RJ,PJ,DJ,zG,LJ,WJ,GJ,fZ];for(let e of HJ)yn(e);var Ct;(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"})(Ct||(Ct={}));var bd;(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"})(bd||(bd={}));var bv;function jJ(e){bv=e.wasm.cwrap(Hr,null,["number","array","number","number","array","number","number","number","number","number","number","number","number"])}function qJ(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,f=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 ${N.shape.length}.`);f=N.id}let m=o==null?0:a.dataIdMap.get(o.dataId).id,g=bd[p];if(g==null)throw new Error(`${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=xo.assertAndGetBroadcastShape(r.shape.slice(0,-2),s.shape.slice(0,-2)),b=a.makeOutput([...A,y,x],r.dtype),k=a.dataIdMap.get(b.dataId).id,S=new Uint8Array(new Int32Array(r.shape).buffer),C=new Uint8Array(new Int32Array(s.shape).buffer);return bv(d,S,r.shape.length,h,C,s.shape.length,l,u,g,f,m,c||0,k),b}var XJ={kernelName:Hr,backendName:"wasm",setupFunc:jJ,kernelFunc:qJ};function Bt(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,Ct[o.dtype],p),u}return{kernelName:e,backendName:"wasm",setupFunc:n,kernelFunc:r}}var KJ=Bt(vl);function pa(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,f=T.assertAndGetBroadcastShape(u.shape,p.shape),m=o.makeOutput(f,h);if(v.sizeFromShape(f)===0)return m;let g=new Uint8Array(new Int32Array(u.shape).buffer),y=new Uint8Array(new Int32Array(p.shape).buffer),x=o.dataIdMap.get(m.dataId).id;return n(c,g,u.shape.length,d,y,p.shape.length,Ct[u.dtype],x),m}return{kernelName:e,backendName:"wasm",setupFunc:r,kernelFunc:s}}var ZJ=!0,YJ=pa(ts,ZJ),vv;function JJ(e){vv=e.wasm.cwrap(Ks,null,["array","number","number","number"])}function QJ(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 vv(s,r.length,Ct[n.dtype],i),n}var eQ={kernelName:Ks,backendName:"wasm",setupFunc:JJ,kernelFunc:QJ};function Ph(e){let{inputs:{x:t},backend:a}=e;if(t.dtype==="string")return Ue(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 tQ={kernelName:wi,backendName:"wasm",kernelFunc:Ph},kv;function aQ(e){kv=e.wasm.cwrap(Ar,null,["number","array","number","number","number","array","number"])}function Qr(e){let{inputs:t,backend:a,attrs:n}=e,[r,s]=rQ(t.x.shape,n.perm),i=!0;for(let f=0;f<s.length;f++)s[f]!==f&&(i=!1);let o=nQ(t.x.shape,n.perm),l={dataId:t.x.dataId,shape:r,dtype:t.x.dtype};if(i){let f=Ph({inputs:t,backend:a});return f.shape=o,f}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 kv(p,h,l.shape.length,Ct[l.dtype],c,d,s.length),u}function nQ(e,t){let a=new Array(e.length);for(let n=0;n<a.length;n++)a[n]=e[t[n]];return a}function rQ(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 sQ={kernelName:Ar,backendName:"wasm",kernelFunc:Qr,setupFunc:aQ};function us(e,t,a){let n=e.shape,r=e.shape.length,s=v.parseAxisParam(t,n),i=s,o=T.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=T.getInnerMostAxes(i.length,r),l=Qr({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 wv;function iQ(e){wv=e.wasm.cwrap(Zs,null,["number, number, number"])}function oQ(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}=us(i,r,t);if(d){let x=t.dataIdMap.get(u.dataId).id;l=u,o=x}let h=l.shape.length;T.assertAxesAreInnerMostDims("all",p,h);let[f,m]=T.computeOutAndReduceShapes(l.shape,p),g=v.sizeFromShape(m),y=t.makeOutput(f,i.dtype);if(v.sizeFromShape(l.shape)!==0){let x=t.dataIdMap.get(y.dataId).id;wv(o,g,x)}if(d&&t.disposeData(u.dataId),s){let x=T.expandShapeToKeepDim(y.shape,c);y.shape=x}return y}var lQ={kernelName:Zs,backendName:"wasm",setupFunc:iQ,kernelFunc:oQ},Iv;function uQ(e){Iv=e.wasm.cwrap(Ys,null,["number, number, number"])}function dQ(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}=us(i,r,t);if(d){let x=t.dataIdMap.get(u.dataId).id;l=u,o=x}let h=l.shape.length;T.assertAxesAreInnerMostDims("any",p,h);let[f,m]=T.computeOutAndReduceShapes(l.shape,p),g=v.sizeFromShape(m),y=t.makeOutput(f,i.dtype);if(v.sizeFromShape(l.shape)!==0){let x=t.dataIdMap.get(y.dataId).id;Iv(o,g,x)}if(d&&t.disposeData(u.dataId),s){let x=T.expandShapeToKeepDim(y.shape,c);y.shape=x}return y}var pQ={kernelName:Ys,backendName:"wasm",setupFunc:uQ,kernelFunc:dQ},Sv;function cQ(e){Sv=e.wasm.cwrap(Js,null,["number","number","number","number","number"])}function hQ(e){let{backend:t,inputs:a,attrs:n}=e,{axis:r}=n,{x:s}=a,i=t.dataIdMap.get(s.dataId).id,o=i,l=s,{transposed:u,axes:p,inputWasTransposed:c}=us(s,r,t);if(c){let y=t.dataIdMap.get(u.dataId).id;y!==i&&(l=u,o=y)}let d=l.shape.slice(0,-1),h=t.makeOutput(d,"int32"),f=t.dataIdMap.get(h.dataId).id,m=v.sizeFromShape(h.shape),g=l.shape[p[0]];return Sv(o,Ct[l.dtype],m,g,f),c&&t.disposeData(u.dataId),h}var fQ={kernelName:Js,backendName:"wasm",kernelFunc:hQ,setupFunc:cQ},Tv;function mQ(e){Tv=e.wasm.cwrap(Qs,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function gQ(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=T.computePool2DInfo(r.shape,i,o,1,l,u),c=p.filterHeight,d=p.filterWidth,h=p.padInfo.top,f=p.padInfo.right,m=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"),k=n.dataIdMap.get(b.dataId).id;return Tv(s,r.shape[0],r.shape[1],r.shape[2],c,d,h,f,m,g,y,x,A,k),b}var yQ={kernelName:Qs,backendName:"wasm",setupFunc:mQ,kernelFunc:gQ};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: ${n.shape}. New shape and old shape must have the same number of elements.`),e.backend.incRef(n.dataId),{dataId:n.dataId,shape:i,dtype:n.dtype}}var xQ={kernelName:Hl,backendName:"wasm",kernelFunc:La},Cv;function AQ(e){Cv=e.wasm.cwrap(ei,null,["number","array","number","number","array","number","number","number","number"])}function bQ(e){let{inputs:t,backend:a,attrs:n}=e,{a:r,b:s}=t,{transposeA:i,transposeB:o}=n;if(r.dtype!=="float32"||s.dtype!=="float32")throw new Error("BatchMatMul for non non-float32 tensors not yet supported.");let l=r.shape.length,u=s.shape.length,p=i?r.shape[l-2]:r.shape[l-1],c=o?s.shape[u-1]:s.shape[u-2],d=i?r.shape[l-1]:r.shape[l-2],h=o?s.shape[u-2]:s.shape[u-1],f=r.shape.slice(0,-2),m=s.shape.slice(0,-2),g=v.sizeFromShape(f),y=v.sizeFromShape(m),x=xo.assertAndGetBroadcastShape(r.shape.slice(0,-2),s.shape.slice(0,-2)).concat([d,h]);v.assert(p===c,()=>`Error in matMul: inner shapes (${p}) and (${c}) of Tensors with shapes ${r.shape} and ${s.shape} and transposeA=${i} and transposeB=${o} must match.`);let A=i?[g,p,d]:[g,d,p],b=o?[y,h,c]:[y,c,h],k=La({inputs:{x:r},backend:a,attrs:{shape:A}}),S=La({inputs:{x:s},backend:a,attrs:{shape:b}}),C=a.dataIdMap.get(k.dataId).id,N=a.dataIdMap.get(S.dataId).id,$=i?k.shape[2]:k.shape[1],M=o?S.shape[1]:S.shape[2],R=Math.max(g,y),I=a.makeOutput([R,$,M],k.dtype),_=a.dataIdMap.get(I.dataId).id,D=new Uint8Array(new Int32Array(k.shape).buffer),W=new Uint8Array(new Int32Array(S.shape).buffer);return Cv(C,D,k.shape.length,N,W,S.shape.length,i,o,_),a.disposeData(k.dataId),a.disposeData(S.dataId),I.shape=x,I}var vQ={kernelName:ei,backendName:"wasm",setupFunc:AQ,kernelFunc:bQ};function qs(e){let{inputs:{x:t},attrs:{begin:a,size:n},backend:r}=e,[s,i]=St.parseSliceParams(t,a,n),o=St.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 f=St.computeFlatOffset(s,p);return t.dtype==="string"?c.stringBytes=l.slice(f,f+v.sizeFromShape(i)):r.typedArrayFromHeap(u).set(l.subarray(f,f+v.sizeFromShape(i))),u}if(t.dtype==="string"){let f=Fc(l,s,i,t.shape,t.dtype);return c.stringBytes=f,u}let d=r.typedArrayFromHeap(u),h=t.shape.length;if(h===2)kQ(l,p[0],d,s,i);else if(h===3)wQ(l,p[0],p[1],d,s,i);else if(h===4)IQ(l,p[0],p[1],p[2],d,s,i);else{let f=Fc(l,s,i,t.shape,t.dtype);d.set(f)}return u}function kQ(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 wQ(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 f=d*t+h*a+u;n.set(e.subarray(f,f+s[2]),i),i+=s[2]}}function IQ(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],f=s[3];for(let m=l;m<c;m++)for(let g=u;g<d;g++)for(let y=p;y<h;y++){let x=m*t+g*a+y*n+f;r.set(e.subarray(x,x+i[3]),o),o+=i[3]}}var SQ={kernelName:Xl,backendName:"wasm",kernelFunc:qs};function TQ(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=T.getReshaped(r.shape,s,o),u=T.getPermuted(l.length,s.length),p=T.getReshapedPermuted(r.shape,s,o),c=T.getSliceBeginCoords(i,s.length),d=T.getSliceSize(p,i,s.length),h=La({inputs:{x:r},backend:a,attrs:{shape:l}}),f=Qr({inputs:{x:h},backend:a,attrs:{perm:u}}),m=La({inputs:{x:f},backend:a,attrs:{shape:p}}),g=qs({inputs:{x:m},backend:a,attrs:{begin:c,size:d}});return a.disposeData(h.dataId),a.disposeData(f.dataId),a.disposeData(h.dataId),g}var CQ={kernelName:El,backendName:"wasm",kernelFunc:TQ};function yu(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 NQ={kernelName:ti,backendName:"wasm",kernelFunc:yu},EQ=Bt(ai),Nv;function RQ(e){Nv=e.wasm.cwrap(as,null,["number","number","number","number"])}function MQ(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 Nv(o,s,i,u),l}var $Q={kernelName:as,backendName:"wasm",setupFunc:RQ,kernelFunc:MQ};function Ev(e){let{inputs:t,backend:a}=e,n=v.parseAxisParam(e.attrs.axis,t[0].shape)[0],r=t.map(h=>h.shape);T.assertParamsConsistent(r,n);let s=T.computeOutShape(t.map(h=>h.shape),n),i=t.filter(h=>v.sizeFromShape(h.shape)>0);if(i.length===1)return Ph({inputs:{x:i[0]},backend:a});let o=a.makeOutput(s,t[0].dtype);if(v.sizeFromShape(s)===0)return o;if(i[0].dtype==="string"){let h=i.map(A=>{let b=[-1,v.sizeFromShape(A.shape.slice(n))];return La({inputs:{x:A},backend:a,attrs:{shape:b}})}),f=h.map(A=>({vals:a.readSync(A.dataId),shape:A.shape}));s=T.computeOutShape(h.map(A=>A.shape),1);let m=h[0].shape[0]===1,g=l3(f,s,t[0].dtype,m),y=T.computeOutShape(i.map(A=>A.shape),n);o.shape=y;let x=a.dataIdMap.get(o.dataId);return x.stringBytes=T.fromStringArrayToUint8(g),h.forEach(A=>a.disposeData(A.dataId)),o}let l=v.sizeFromShape(i[0].shape.slice(0,n)),u=0,p=i.map(h=>{let f=v.sizeFromShape(h.shape.slice(n));return u+=f,f}),c=i.map(h=>a.typedArrayFromHeap(h)),d=a.typedArrayFromHeap(o);for(let h=0;h<l;h++){let f=h*u;for(let m=0;m<c.length;m++){let g=p[m],y=h*g,x=c[m].subarray(y,y+g);d.set(x,f),f+=g}}return o}var _Q={kernelName:Rl,backendName:"wasm",kernelFunc:Ev},Rv;function PQ(e){Rv=e.wasm.cwrap(ni,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function FQ(e){let{inputs:t,attrs:a,backend:n}=e,{x:r,filter:s}=t,i=n.dataIdMap.get(r.dataId).id,o=n.dataIdMap.get(s.dataId).id,{strides:l,dilations:u,pad:p,dimRoundingMode:c,dataFormat:d}=a,h=T.convertConv2DDataFormat(d),f=T.computeConv2DInfo(r.shape,s.shape,l,u,p,c,!1,h),m=f.filterHeight,g=f.filterWidth,y=f.padInfo.top,x=f.padInfo.right,A=f.padInfo.bottom,b=f.padInfo.left,k=f.dilationHeight,S=f.dilationWidth,C=f.strideHeight,N=f.strideWidth,$=f.inChannels,M=f.outChannels,R=f.padInfo.type==="SAME"?1:0;if(f.dataFormat!=="channelsLast")throw new Error(`wasm backend Conv2D does not support dataFormat:'${f.dataFormat}'. Please use 'channelsLast'.`);let I=n.makeOutput(f.outShape,"float32"),_=n.dataIdMap.get(I.dataId).id;return Rv(i,r.shape[0],r.shape[1],r.shape[2],o,m,g,y,x,A,b,R,k,S,C,N,$,M,_),I}var OQ={kernelName:ni,backendName:"wasm",setupFunc:PQ,kernelFunc:FQ},Mv;function DQ(e){Mv=e.wasm.cwrap(ri,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 zQ(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=T.convertConv2DDataFormat(l),h=T.computeConv2DInfo(p,s.shape,i,c,o,u,!1,d),{batchSize:f,filterHeight:m,filterWidth:g,inChannels:y,inHeight:x,inWidth:A,outChannels:b,outHeight:k,outWidth:S,strideHeight:C,strideWidth:N}=h,$=m-1-h.padInfo.top,M=g-1-h.padInfo.left,R=h.dataFormat==="channelsLast",I=v.computeStrides(h.inShape),_=v.computeStrides(r.shape),[D,W,P]=v.computeStrides(s.shape),U=I[0],G=R?I[1]:I[2],q=R?I[2]:1,H=R?1:I[1],B=_[0],Z=R?_[1]:_[2],X=R?_[2]:1,re=R?1:_[1],ee=t.makeOutput(h.inShape,"float32"),ce=t.dataIdMap.get(ee.dataId).id,ie=t.dataIdMap.get(r.dataId).id,ge=t.dataIdMap.get(s.dataId).id;return Mv(ie,ge,f,m,g,x,A,y,k,S,b,C,N,$,M,D,W,P,U,G,q,H,B,Z,X,re,ce),ee}var LQ={kernelName:ri,backendName:"wasm",setupFunc:DQ,kernelFunc:zQ},BQ=Bt(si),WQ=Bt(ii),S2;(function(e){e[e.bilinear=0]="bilinear",e[e.nearest=1]="nearest"})(S2||(S2={}));var $v;function VQ(e){$v=e.wasm.cwrap(ui,null,["number","number","number","number","array","number","number","number","number","number"])}function UQ(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]],f=t.dataIdMap.get(o.dataId),m;o.dtype!=="float32"&&(m=yu({backend:t,inputs:{x:o},attrs:{dtype:"float32"}}),f=t.dataIdMap.get(m.dataId));let g=f.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,k=new Uint8Array(new Int32Array(o.shape).buffer);return $v(g,y,x,p,k,c,d,S2[r],s,b),m!=null&&t.disposeData(m.dataId),A}var GQ={kernelName:ui,backendName:"wasm",setupFunc:VQ,kernelFunc:UQ},_v;function HQ(e){_v=e.wasm.cwrap(oi,null,["number","number","number","number","number","number"])}function jQ(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=T.getAxesPermutation([s],l),p=r;u!==null&&(p=Qr({inputs:{x:r},attrs:{perm:u},backend:a}));let c=T.getInnerMostAxes(1,l)[0];T.assertAxesAreInnerMostDims("cumprod",[c],l);let d=a.makeOutput(p.shape,p.dtype),h=p.shape[c],f=a.dataIdMap.get(p.dataId).id,m=a.dataIdMap.get(d.dataId).id;_v(f,i?1:0,o?1:0,h,m,Ct[r.dtype]);let g=d;if(u!==null){let y=T.getUndoAxesPermutation(u);g=Qr({inputs:{x:d},attrs:{perm:y},backend:a}),a.disposeData(p.dataId),a.disposeData(d.dataId)}return g}var qQ={kernelName:oi,backendName:"wasm",setupFunc:HQ,kernelFunc:jQ},Pv;function XQ(e){Pv=e.wasm.cwrap(li,null,["number","number","number","number","number","number"])}function KQ(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=T.getAxesPermutation([s],l),p=r;u!==null&&(p=Qr({inputs:{x:r},attrs:{perm:u},backend:a}));let c=T.getInnerMostAxes(1,l)[0];T.assertAxesAreInnerMostDims("cumsum",[c],l);let d=a.makeOutput(p.shape,p.dtype),h=p.shape[c],f=a.dataIdMap.get(p.dataId).id,m=a.dataIdMap.get(d.dataId).id;Pv(f,i?1:0,o?1:0,h,m,Ct[r.dtype]);let g=d;if(u!==null){let y=T.getUndoAxesPermutation(u);g=Qr({inputs:{x:d},attrs:{perm:y},backend:a}),a.disposeData(p.dataId),a.disposeData(d.dataId)}return g}var ZQ={kernelName:li,backendName:"wasm",setupFunc:XQ,kernelFunc:KQ},Fv;function YQ(e){Fv=e.wasm.cwrap(di,null,["number","number","number","array","number","array","array","number","number"])}function JQ(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),f=i==="NHWC"?[o,c,d,h]:[o,h,c,d],m=t.makeOutput(f,"float32"),g=t.dataIdMap.get(r.dataId).id,y=new Uint8Array(new Int32Array(v.computeStrides(r.shape)).buffer),x=new Uint8Array(new Int32Array(f).buffer),A=new Uint8Array(new Int32Array(v.computeStrides(f)).buffer),b=t.dataIdMap.get(m.dataId).id;return Fv(g,s,i==="NHWC"?1:0,y,r.shape.length-1,x,A,f.length,b),m}var QQ={kernelName:di,backendName:"wasm",setupFunc:YQ,kernelFunc:JQ},Ov;function eee(e){Ov=e.wasm.cwrap(pi,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function tee(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=T.computeConv2DInfo(r.shape,s.shape,l,d,p,c,!0),f=h.filterHeight,m=h.filterWidth,g=h.padInfo.top,y=h.padInfo.right,x=h.padInfo.bottom,A=h.padInfo.left,b=h.dilationHeight,k=h.dilationWidth,S=h.strideHeight,C=h.strideWidth,N=h.inChannels,$=h.outChannels,M=h.padInfo.type==="SAME"?1:0;if(h.dataFormat!=="channelsLast")throw new Error(`wasm backend DepthwiseConv2dNative does not support dataFormat:'${h.dataFormat}'. Please use 'channelsLast'.`);let R=n.makeOutput(h.outShape,"float32"),I=n.dataIdMap.get(R.dataId).id;return Ov(i,r.shape[0],r.shape[1],r.shape[2],o,f,m,g,y,x,A,M,b,k,S,C,N,$,I),R}var aee={kernelName:pi,backendName:"wasm",setupFunc:eee,kernelFunc:tee},nee=Bt(hi),ree=!1,see=pa(fi,ree,"bool"),iee=Bt(mi,"float32");function T2(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)}, ${i}]`),l=i+s+1),o.splice(l,0,1),La({inputs:{x:r},backend:n,attrs:{shape:o}})}var oee={kernelName:$l,backendName:"wasm",kernelFunc:T2};function Dv(e){let{attrs:{shape:t,value:a,dtype:n},backend:r}=e,s=r.makeOutput(t,n);return r.typedArrayFromHeap(s).fill(a),s}var lee={kernelName:Pl,backendName:"wasm",kernelFunc:Dv},zv;function uee(e){zv=e.wasm.cwrap(gi,null,["number","number","number","number","number","number"])}function dee(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 zv(s,o,l,u,p,i),r}var pee={kernelName:gi,backendName:"wasm",kernelFunc:dee,setupFunc:uee},cee=Bt(yi),hee=!1,fee=pa(xi,hee),Lv;function mee(e){Lv=e.wasm.cwrap(Ai,null,["number","number","number","number","number","number","number"])}function gee(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,f=u!=null?t.dataIdMap.get(u.dataId).id:0,m=t.makeOutput(s.shape,s.dtype);if(v.sizeFromShape(s.shape)===0)return m;let g=t.dataIdMap.get(m.dataId).id;return Lv(p,c,d,h,f,r,g),m}var yee={kernelName:Ai,backendName:"wasm",setupFunc:mee,kernelFunc:gee},Bv;function xee(e){Bv=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 Aee(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:f}=a,m=T.computeConv2DInfo(r.shape,s.shape,l,p,u,d),g=bd[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=m.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 (${A})`);b=X.id}let k=m.filterHeight,S=m.filterWidth,C=m.padInfo.top,N=m.padInfo.right,$=m.padInfo.bottom,M=m.padInfo.left,R=m.dilationHeight,I=m.dilationWidth,_=m.strideHeight,D=m.strideWidth,W=m.inChannels,P=m.padInfo.type==="SAME"?1:0,U=m.batchSize,G=m.inHeight,q=m.inWidth;if(c!=="NHWC")throw new Error(`wasm backend FusedConv2D does not support dataFormat:'${c}'. Please use 'NHWC'.`);let H=n.makeOutput(m.outShape,"float32"),B=n.dataIdMap.get(H.dataId).id,Z=o==null?0:n.dataIdMap.get(o.dataId).id;return Bv(y,U,G,q,x,k,S,b,C,N,$,M,P,R,I,_,D,W,A,g,Z,f||0,B),H}var bee={kernelName:jr,backendName:"wasm",setupFunc:xee,kernelFunc:Aee},Wv;function vee(e){Wv=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 kee(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:f}=a,m=T.computeConv2DInfo(r.shape,s.shape,l,p,u,d,!0),g=bd[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=m.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 (${A})`);b=X.id}let k=m.filterHeight,S=m.filterWidth,C=m.padInfo.top,N=m.padInfo.right,$=m.padInfo.bottom,M=m.padInfo.left,R=m.dilationHeight,I=m.dilationWidth,_=m.strideHeight,D=m.strideWidth,W=m.inChannels,P=m.padInfo.type==="SAME"?1:0,U=m.batchSize,G=m.inHeight,q=m.inWidth;if(c!=="NHWC")throw new Error(`wasm backend FusedDepthwiseConv2D does not support dataFormat:'${c}'. Please use 'NHWC'.`);let H=n.makeOutput(m.outShape,"float32"),B=n.dataIdMap.get(H.dataId).id,Z=o==null?0:n.dataIdMap.get(o.dataId).id;return Wv(y,U,G,q,x,k,S,b,C,N,$,M,P,R,I,_,D,W,A,g,Z,f||0,B),H}var wee={kernelName:qr,backendName:"wasm",setupFunc:vee,kernelFunc:kee},Vv;function Iee(e){Vv=e.wasm.cwrap(bi,null,["number","number","number","number","number","number","array","number"])}function See(e){let{backend:t,inputs:a}=e,{params:n,indices:r}=a,[s,i,o,l]=e3.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,f=new Uint8Array(new Int32Array(l).buffer),m=t.dataIdMap.get(u.dataId).id;return Vv(d,Ct[n.dtype],h,i,c,o,f,m),u}var Tee={kernelName:bi,backendName:"wasm",setupFunc:Iee,kernelFunc:See},Uv;function Cee(e){Uv=e.wasm.cwrap("Gather",null,["number","number","array","number","number","number","array","number"])}function Nee(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 C=0;C<u.length;++C){let N=u[C];v.assert(N<=p-1&&N>=0,()=>`GatherV2: the index value ${N} is not in [0, ${p-1}]`)}let c=T.segment_util.collectGatherOpShapeInfo(r,s,l,o),d=La({inputs:{x:r},attrs:{shape:[c.batchSize,c.outerSize,c.dimSize,c.sliceSize]},backend:t}),h=v.sizeFromShape(s.shape),f=La({inputs:{x:s},attrs:{shape:[c.batchSize,h/c.batchSize]},backend:t}),m=[c.batchSize,c.outerSize,h/c.batchSize,c.sliceSize],g=t.makeOutput(m,r.dtype);if(v.sizeFromShape(r.shape)===0)return g;let y=d.shape.length-1,x=t.dataIdMap.get(d.dataId).id,A=t.dataIdMap.get(f.dataId).id,b=t.dataIdMap.get(g.dataId).id,k=new Uint8Array(new Int32Array(v.computeStrides(d.shape)).buffer),S=new Uint8Array(new Int32Array(v.computeStrides(m)).buffer);return Uv(x,Ct[r.dtype],k,y,A,c.batchSize,S,b),t.disposeData(d.dataId),t.disposeData(f.dataId),g.shape=c.outputShape,g}var Eee={kernelName:Fl,backendName:"wasm",setupFunc:Cee,kernelFunc:Nee},Ree=!1,Mee=pa(vi,Ree,"bool"),$ee=!1,_ee=pa(ki,$ee,"bool"),Pee=Bt(Ii,"bool"),Gv;function Fee(e){Gv=e.wasm.cwrap(Si,null,["number","number","number","number"])}function Oee(e){let{inputs:{x:t},attrs:{alpha:a},backend:n}=e,r=n.dataIdMap.get(t.dataId).id,s=n.makeOutput(t.shape,"float32");if(v.sizeFromShape(t.shape)!==0){let i=n.dataIdMap.get(s.dataId).id;Gv(r,Ct[t.dtype],a,i)}return s}var Dee={kernelName:Si,backendName:"wasm",setupFunc:Fee,kernelFunc:Oee},zee=!1,Lee=pa(Ti,zee,"bool"),Bee=!1,Wee=pa(Ci,Bee,"bool"),Vee=Bt(Ni),Uee=!1,Gee=pa(Ei,Uee,"bool"),Hee=Bt(Ri),jee=!1,qee=pa(Mi,jee,"bool"),Xee=!1,Kee=pa(fx,Xee,"bool"),Hv;function Zee(e){Hv=e.wasm.cwrap($i,null,["number","number","number","number"])}function Yee(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}=us(i,r,t);if(d){let x=t.dataIdMap.get(u.dataId).id;l=u,o=x}let h=l.shape.length;T.assertAxesAreInnerMostDims("max",p,h);let[f,m]=T.computeOutAndReduceShapes(l.shape,p),g=v.sizeFromShape(m),y=t.makeOutput(f,i.dtype);if(v.sizeFromShape(l.shape)!==0){let x=t.dataIdMap.get(y.dataId).id;Hv(o,Ct[i.dtype],g,x)}if(d&&t.disposeData(u.dataId),s){let x=T.expandShapeToKeepDim(y.shape,c);y.shape=x}return y}var Jee={kernelName:$i,backendName:"wasm",setupFunc:Zee,kernelFunc:Yee},Qee=!1,ete=pa(_i,Qee),jv;function tte(e){jv=e.wasm.cwrap(Pi,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function ate(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 ${r.dtype}.`);let{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=a,p=T.computePool2DInfo(r.shape,i,o,1,l,u),c=p.filterHeight,d=p.filterWidth,h=p.padInfo.top,f=p.padInfo.right,m=p.padInfo.bottom,g=p.padInfo.left,y=p.dilationHeight,x=p.dilationWidth,A=p.strideHeight,b=p.strideWidth,k=p.inChannels,S=p.outChannels;if(p.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${p.dataFormat}'. Please use 'channelsLast'.`);let C=n.makeOutput(p.outShape,"float32"),N=n.dataIdMap.get(C.dataId).id;return jv(s,r.shape[0],r.shape[1],r.shape[2],c,d,h,f,m,g,y,x,A,b,k,S,N),C}var nte={kernelName:Pi,backendName:"wasm",setupFunc:tte,kernelFunc:ate},qv;function rte(e){qv=e.wasm.cwrap(Fi,null,["number, number, number"])}function ste(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}=us(i,r,t),f=c;if(h){let b=t.dataIdMap.get(p.dataId).id;b!==o&&(u=p,l=b,f=T.getInnerMostAxes(f.length,u.shape.length))}T.assertAxesAreInnerMostDims("mean",f,u.shape.length);let[m,g]=T.computeOutAndReduceShapes(u.shape,f),y=v.sizeFromShape(g),x=u;u.dtype!=="float32"&&(x=yu({backend:t,inputs:{x:u},attrs:{dtype:"float32"}}),l=t.dataIdMap.get(x.dataId).id);let A=t.makeOutput(m,"float32");if(v.sizeFromShape(u.shape)!==0){let b=t.dataIdMap.get(A.dataId).id;qv(l,y,b)}if(h&&t.disposeData(p.dataId),s){let b=T.expandShapeToKeepDim(A.shape,d);A.shape=b}return u.dtype!=="float32"&&t.disposeData(x.dataId),A}var ite={kernelName:Fi,backendName:"wasm",setupFunc:rte,kernelFunc:ste},Xv;function ote(e){Xv=e.wasm.cwrap(Oi,null,["number","number","number","number"])}function lte(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}=us(i,r,t);if(h){let A=t.dataIdMap.get(p.dataId).id;A!==o&&(u=p,l=A)}let f=u.shape.length;T.assertAxesAreInnerMostDims("min",c,f);let[m,g]=T.computeOutAndReduceShapes(u.shape,c),y=v.sizeFromShape(g),x=t.makeOutput(m,u.dtype);if(v.sizeFromShape(u.shape)!==0){let A=t.dataIdMap.get(x.dataId).id;Xv(l,Ct[i.dtype],y,A)}if(h&&t.disposeData(p.dataId),s){let A=T.expandShapeToKeepDim(x.shape,d);x.shape=A}return x}var ute={kernelName:Oi,backendName:"wasm",setupFunc:ote,kernelFunc:lte},dte=!1,pte=pa(Di,dte),C2;(function(e){e[e.reflect=0]="reflect",e[e.symmetric=1]="symmetric"})(C2||(C2={}));var Kv;function cte(e){Kv=e.wasm.cwrap(zi,null,["number","array","number","number","array","array","number","number"])}function hte(e){let{inputs:{x:t},backend:a,attrs:{paddings:n,mode:r}}=e,s=n.map((f,m)=>f[0]+t.shape[m]+f[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(f=>f[0]),c=n.map(f=>f[1]),d=new Uint8Array(new Int32Array(p).buffer),h=new Uint8Array(new Int32Array(c).buffer);return Kv(i,u,t.shape.length,Ct[t.dtype],d,h,C2[r],l),o}var fte={kernelName:zi,backendName:"wasm",kernelFunc:hte,setupFunc:cte},mte=!0,gte=pa(Li,mte),yte=Bt(Bl);function P3(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 Zv;function xte(e){Zv=e.wasm.cwrap(Wi,"number",["number","number","number","number","number"])}function Ate(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=Zv(u,p,s,r,i),{pSelectedIndices:d,selectedSize:h,pSelectedScores:f,pValidOutputs:m}=P3(t,c);return t.wasm._free(f),t.wasm._free(m),t.makeOutput([h],"int32",d)}var bte={kernelName:Wi,backendName:"wasm",setupFunc:xte,kernelFunc:Ate},Yv;function vte(e){Yv=e.wasm.cwrap(Wl,"number",["number","number","number","number","number","bool"])}function kte(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=Yv(p,c,s,r,i,o),{pSelectedIndices:h,selectedSize:f,pSelectedScores:m,pValidOutputs:g}=P3(t,d);t.wasm._free(m);let y=t.makeOutput([f],"int32",h),x=t.makeOutput([],"int32",g);return[y,x]}var wte={kernelName:Wl,backendName:"wasm",setupFunc:vte,kernelFunc:kte},Jv;function Ite(e){Jv=e.wasm.cwrap(Vi,"number",["number","number","number","number","number","number"])}function Ste(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=Jv(p,c,s,r,i,o),{pSelectedIndices:h,selectedSize:f,pSelectedScores:m,pValidOutputs:g}=P3(t,d);t.wasm._free(g);let y=t.makeOutput([f],"int32",h),x=t.makeOutput([f],"float32",m);return[y,x]}var Tte={kernelName:Vi,backendName:"wasm",setupFunc:Ite,kernelFunc:Ste},Cte=!1,Nte=pa(Bi,Cte,"bool"),Qv;function Ete(e){Qv=e.wasm.cwrap(Ui,null,["number","number","number","number","number"])}function Rte(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 Qv(c,i,o,l,p),u}var Mte={kernelName:Ui,backendName:"wasm",setupFunc:Ete,kernelFunc:Rte};function $te(e){let{inputs:{x:t},backend:a}=e,n=a.makeOutput(t.shape,t.dtype);return a.typedArrayFromHeap(n).fill(1),n}var _te={kernelName:Vl,backendName:"wasm",kernelFunc:$te};function Pte(e){let{inputs:t,backend:a,attrs:n}=e,{axis:r}=n;if(t.length===1)return T2({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=T2({inputs:{input:p},backend:a,attrs:{dim:r}});return o.push(c),c}),u=Ev({inputs:l,backend:a,attrs:{axis:r}});return o.forEach(p=>a.disposeData(p.dataId)),u}var Fte={kernelName:Ul,backendName:"wasm",kernelFunc:Pte},e8;function Ote(e){e8=e.wasm.cwrap(Gi,null,["number","array","number","number","array","array","number","number"])}function Dte(e){let{inputs:{x:t},backend:a,attrs:{paddings:n,constantValue:r}}=e,s=n.map((f,m)=>f[0]+t.shape[m]+f[1]);if(v.sizeFromShape(t.shape)===0)return Dv({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(f=>f[0]),c=n.map(f=>f[1]),d=new Uint8Array(new Int32Array(p).buffer),h=new Uint8Array(new Int32Array(c).buffer);return e8(i,u,t.shape.length,Ct[t.dtype],d,h,r,l),o}var t8={kernelName:Gi,backendName:"wasm",kernelFunc:Dte,setupFunc:Ote},zte=!1,Lte=pa(Hi,zte),a8;function Bte(e){a8=e.wasm.cwrap(ji,null,["number","number","number"])}function Wte(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=yu({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 a8(o,i,c),l.dtype!=="float32"&&a.disposeData(u.dataId),p}var Vte={kernelName:ji,backendName:"wasm",setupFunc:Bte,kernelFunc:Wte},n8;function Ute(e){n8=e.wasm.cwrap(qi,null,["number","number","number","number"])}function Gte(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}=us(i,r,t),f=c;if(h){let A=t.dataIdMap.get(p.dataId).id;A!==o&&(u=p,l=A,f=T.getInnerMostAxes(f.length,u.shape.length))}T.assertAxesAreInnerMostDims("prod",f,u.shape.length);let[m,g]=T.computeOutAndReduceShapes(u.shape,f),y=v.sizeFromShape(g),x=t.makeOutput(m,u.dtype);if(v.sizeFromShape(u.shape)!==0){let A=t.dataIdMap.get(x.dataId).id;n8(l,y,Ct[x.dtype],A)}if(h&&t.disposeData(p.dataId),s){let A=T.expandShapeToKeepDim(x.shape,d);x.shape=A}return x}var Hte={kernelName:qi,backendName:"wasm",setupFunc:Ute,kernelFunc:Gte},jte=e=>{let{backend:t,attrs:a}=e,{start:n,stop:r,step:s,dtype:i}=a,o=p3(n,r,s,i),l=t.makeOutput([o.length],i);return t.typedArrayFromHeap(l).set(o),l},qte={kernelName:Gl,backendName:"wasm",kernelFunc:jte},Xte=!0,Kte=pa(ci,Xte),Zte=Bt(Xi),Yte=Bt(Ki),Jte=Bt(Ji),r8;function Qte(e){r8=e.wasm.cwrap(Yi,null,["number","number","number","number","number","number","number","number","number","number"])}function eae(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,f=[p,l,u,h],m=t.dataIdMap.get(r.dataId),g;m.dtype!=="float32"&&(g=yu({backend:t,inputs:{x:r},attrs:{dtype:"float32"}}),m=t.dataIdMap.get(g.dataId));let y=m.id,x=t.makeOutput(f,"float32");if(v.sizeFromShape(r.shape)===0)return x;let A=t.dataIdMap.get(x.dataId).id;return r8(y,p,c,d,h,l,u,s?1:0,i?1:0,A),g!=null&&t.disposeData(g.dataId),x}var tae={kernelName:Yi,backendName:"wasm",setupFunc:Qte,kernelFunc:eae},s8;function aae(e){s8=e.wasm.cwrap(Zi,null,["number","number","number","number","number","number","number","number","number","number"])}function nae(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,f=[p,l,u,h],m=t.makeOutput(f,"float32");if(v.sizeFromShape(r.shape)===0)return m;let g=t.dataIdMap.get(r.dataId),y;g.dtype!=="float32"&&(y=yu({backend:t,inputs:{x:r},attrs:{dtype:"float32"}}),g=t.dataIdMap.get(y.dataId));let x=g.id,A=t.dataIdMap.get(m.dataId).id;return s8(x,p,c,d,h,l,u,s?1:0,i?1:0,A),y!=null&&t.disposeData(y.dataId),m}var rae={kernelName:Zi,backendName:"wasm",setupFunc:aae,kernelFunc:nae},i8;function sae(e){i8=e.wasm.cwrap(Qi,null,["number","array","number","array","number","number"])}function iae(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 Ph({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);i8(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 oae={kernelName:Qi,backendName:"wasm",kernelFunc:iae,setupFunc:sae},o8;function lae(e){o8=e.wasm.cwrap(go,null,["number","number","number","number","number","number","number","number","array","number","number"])}function uae(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,f]=r.shape,[m,g]=T.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 o8(u,c,d,h,f,s,m,g,b,A.length,p),l}var dae={kernelName:go,backendName:"wasm",kernelFunc:uae,setupFunc:lae},pae=Bt(eo),cae=Bt(to),l8;function hae(e){l8=e.wasm.cwrap(ao,null,["number","number","number","number","number","number","array","number","number"])}function fae(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}=B1.calculateShapes(s,r,i),h=t.dataIdMap.get(r.dataId).id,f=t.dataIdMap.get(s.dataId).id,m=new Uint8Array(new Int32Array(c).buffer),g=t.dataIdMap.get(o.dataId).id;return l8(h,f,Ct[s.dtype],l,u,p,m,d,g),o}var mae={kernelName:ao,backendName:"wasm",setupFunc:hae,kernelFunc:fae},u8;function gae(e){u8=e.wasm.cwrap("SelectV2",null,["number","number","number","number","number"])}function yae(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 u8(i,o,l,h,p),u}var xae={kernelName:jl,backendName:"wasm",kernelFunc:yae,setupFunc:gae},d8;function Aae(e){d8=e.wasm.cwrap(ro,null,["number","number"])}function bae(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||d8(n,s),r}var vae={kernelName:"Sigmoid",backendName:"wasm",setupFunc:Aae,kernelFunc:bae},kae=Bt(no),p8;function wae(e){p8=e.wasm.cwrap(oo,null,["number","number","number","number"])}function Iae(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||p8(r,i,o,l),s}var Sae={kernelName:oo,backendName:"wasm",setupFunc:wae,kernelFunc:Iae};function Tae(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=t8.kernelFunc({inputs:{x:r},backend:a,attrs:{paddings:l,constantValue:0}}),p=T.getReshaped(u.shape,s,o,!1),c=T.getPermuted(p.length,s.length,!1),d=T.getReshapedPermuted(u.shape,s,o,!1),h=La({inputs:{x:u},backend:a,attrs:{shape:p}}),f=Qr({inputs:{x:h},backend:a,attrs:{perm:c}}),m=La({inputs:{x:f},backend:a,attrs:{shape:d}});return a.disposeData(u.dataId),a.disposeData(h.dataId),a.disposeData(f.dataId),m}var Cae={kernelName:Jl,backendName:"wasm",kernelFunc:Tae},c8;function Nae(e){c8=e.wasm.cwrap("SparseFillEmptyRows","number",["number","number","number","number","number","number","number","number","number","number","number","number"])}function Eae(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,f=t.makeOutput(p,n.dtype),m=t.dataIdMap.get(f.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),k=t.dataIdMap.get(b.dataId).id,S=t.makeOutput([4],"int32"),C=t.dataIdMap.get(S.dataId).id,N=c8(c,d,Ct[r.dtype],o,u,l,h,m,y,A,k,C),$=t.readSync(S.dataId),M;switch($[0]){case 1:{M=T.getSparseFillEmptyRowsIndicesDenseShapeMismatch($[1]);break}case 2:{M=T.getSparseFillEmptyRowsNegativeIndexErrorMessage($[1],$[2]);break}case 3:M=T.getSparseFillEmptyRowsOutOfRangeIndexErrorMessage($[1],$[2],$[3]);break;default:M=""}if(t.disposeData(S.dataId),M)throw t.disposeData(f.dataId),t.disposeData(g.dataId),t.disposeData(x.dataId),t.disposeData(b.dataId),new Error(M);let R=f,I=g;return N!==p[0]&&(R=qs({inputs:{x:f},attrs:{begin:0,size:[N,l]},backend:t}),I=qs({inputs:{x:g},attrs:{begin:0,size:N},backend:t}),t.disposeData(f.dataId),t.disposeData(g.dataId)),[R,I,x,b]}var Rae={kernelName:Ld,backendName:"wasm",setupFunc:Nae,kernelFunc:Eae},h8;function Mae(e){h8=e.wasm.cwrap(eu,null,["number","number","number","number","number","number","number"])}function $ae(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 ${s.shape}`);let i=t.dataIdMap.get(n.dataId).id,o=t.dataIdMap.get(r.dataId).id,l=t.dataIdMap.get(s.dataId).id,u=n.shape[0],p=v.sizeFromShape(s.shape),c=t.makeOutput([u,p],n.dtype),d=t.dataIdMap.get(c.dataId).id,h=t.makeOutput([p],s.dtype),f=t.dataIdMap.get(h.dataId).id,m=t.makeOutput([3],"int32"),g=t.dataIdMap.get(m.dataId).id;h8(i,o,l,u,d,f,g);let y=t.readSync(m.dataId),x;switch(y[0]){case 0:{x=T.getSparseReshapeMultipleNegativeOneOutputDimErrorMessage(y[1],y[2]);break}case 1:{x=T.getSparseReshapeNegativeOutputDimErrorMessage(y[1],y[2]);break}case 2:x=T.getSparseReshapeEmptyTensorZeroOutputDimErrorMessage();break;case 3:{let A=Array.from(t.readSync(r.dataId)),b=Array.from(t.readSync(h.dataId));x=T.getSparseReshapeInputOutputMultipleErrorMessage(A,b);break}case 4:{let A=Array.from(t.readSync(r.dataId)),b=Array.from(t.readSync(h.dataId));x=T.getSparseReshapeInputOutputMismatchErrorMessage(A,b);break}default:x=""}if(t.disposeData(m.dataId),x)throw t.disposeData(c.dataId),t.disposeData(h.dataId),new Error(x);return[c,h]}var _ae={kernelName:eu,backendName:"wasm",setupFunc:Mae,kernelFunc:$ae},f8;function m8(e){f8=e.wasm.cwrap("SparseSegmentReduction",null,["number","number","number","number","number","number","number","number","number"])}function g8(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(T.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,f=a.makeOutput(p,r.dtype),m=a.dataIdMap.get(f.dataId).id,g=a.makeOutput([4],"int32"),y=a.dataIdMap.get(g.dataId).id;f8(c,Ct[r.dtype],r.shape[0],d,h,m,y,t,0);let x=a.readSync(g.dataId),A;switch(x[0]){case 0:{A=T.getSparseSegmentReductionNegativeSegmentIdsErrorMessage();break}case 1:{A=T.getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage();break}case 2:A=T.getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage(x[1],x[2]);break;case 3:A=T.getSparseSegmentReductionIndicesOutOfRangeErrorMessage(x[1],x[2],x[3]);break;default:A=""}if(a.disposeData(g.dataId),A)throw a.disposeData(f.dataId),new Error(A);return f}function Pae(e){return g8(e,!0)}var Fae={kernelName:Bd,backendName:"wasm",setupFunc:m8,kernelFunc:Pae};function Oae(e){return g8(e,!1)}var Dae={kernelName:Wd,backendName:"wasm",setupFunc:m8,kernelFunc:Oae};function zae(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=T.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=qs({inputs:{x:r},attrs:{begin:u,size:d},backend:n});return u[o]+=c,h})}var Lae={kernelName:Ql,backendName:"wasm",kernelFunc:zae},Bae=Bt(so),Wae=Bt(Ud),Vae=!0,Uae=pa(lo,Vae),y8;function Gae(e){y8=e.wasm.cwrap(rs,null,["number","number","number","number"])}function Hae(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 y8(i,r,Ct[s.dtype],l),o}var jae={kernelName:rs,backendName:"wasm",setupFunc:Gae,kernelFunc:Hae},x8;function qae(e){x8=e.wasm.cwrap(uo,null,["number","array","number","array","array","array","array","array","number","number"])}function Xae(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:f,isIdentity:m,sliceDim0:g,isSimpleSlice:y,begin:x,end:A,strides:b}=St.sliceInfo(r.shape,s,i,o,l,u,p,c,d),k;if(m)k=La({inputs:{x:r},backend:t,attrs:{shape:f}});else if(g||y){v.assert(r.shape.length>=1,()=>`Input must have rank at least 1, got: ${r.shape.length}`);let S=St.computeOutShape(x,A,b),C=qs({inputs:{x:r},backend:t,attrs:{begin:x,size:S}});k=La({inputs:{x:C},backend:t,attrs:{shape:f}}),t.disposeData(C.dataId)}else{let S=t.makeOutput(h,"float32"),C=t.dataIdMap.get(r.dataId).id,N=new Uint8Array(new Int32Array(v.computeStrides(r.shape)).buffer),$=new Uint8Array(new Int32Array(x).buffer),M=new Uint8Array(new Int32Array(A).buffer),R=new Uint8Array(new Int32Array(b).buffer),I=new Uint8Array(new Int32Array(h).buffer),_=new Uint8Array(new Int32Array(v.computeStrides(h)).buffer),D=t.dataIdMap.get(S.dataId).id;x8(C,N,r.shape.length,$,M,R,I,_,h.length,D),k=La({inputs:{x:S},backend:t,attrs:{shape:f}}),t.disposeData(S.dataId)}return k}var Kae={kernelName:uo,backendName:"wasm",setupFunc:qae,kernelFunc:Xae};function Zae(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),[f,m]=h3(d,h,i,o,l,u,p,c),g=t.makeOutput([f.length],"string"),y=t.dataIdMap.get(g.dataId);y.stringBytes=f;let x=t.makeOutput(s.shape,"int32");return t.typedArrayFromHeap(x).set(m),[g,x]}var Yae={kernelName:tu,backendName:"wasm",kernelFunc:Zae};function Jae(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]=f3(o,l[0],i),d=p.length,h=t.makeOutput([d,2],"int32");t.typedArrayFromHeap(h).set(u);let f=t.makeOutput([d],"string"),m=t.dataIdMap.get(f.dataId);m.stringBytes=p;let g=t.makeOutput([2],"int32");return t.typedArrayFromHeap(g).set(c),[h,f,g]}var Qae={kernelName:Gd,backendName:"wasm",kernelFunc:Jae};function ene(e){let{backend:t,inputs:a,attrs:n}=e,{input:r}=a,{numBuckets:s}=n,i=t.readSync(r.dataId),o=m3(i,s),l=t.makeOutput(r.shape,"int32");return t.typedArrayFromHeap(l).set(o),l}var tne={kernelName:Hd,backendName:"wasm",kernelFunc:ene},ane=!0,nne=pa(po,ane),A8;function rne(e){A8=e.wasm.cwrap(io,null,["number","number","number","number"])}function sne(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}=us(i,r,t),f=c;if(h){let A=t.dataIdMap.get(p.dataId).id;A!==o&&(u=p,l=A,f=T.getInnerMostAxes(f.length,u.shape.length))}T.assertAxesAreInnerMostDims("sum",f,u.shape.length);let[m,g]=T.computeOutAndReduceShapes(u.shape,f),y=v.sizeFromShape(g),x=t.makeOutput(m,u.dtype);if(v.sizeFromShape(u.shape)!==0){let A=t.dataIdMap.get(x.dataId).id;A8(l,y,Ct[x.dtype],A)}if(h&&t.disposeData(p.dataId),s){let A=T.expandShapeToKeepDim(x.shape,d);x.shape=A}return x}var ine={kernelName:io,backendName:"wasm",setupFunc:rne,kernelFunc:sne},one=Bt(co),lne=Bt(ho),b8;function une(e){b8=e.wasm.cwrap(ns,null,["number","array","number","array","number","number"])}function dne(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 b8(s,l,r.shape.length,u,o.length,Ct[p.dtype],c),p}var pne={kernelName:ns,backendName:"wasm",setupFunc:une,kernelFunc:dne},v8;function cne(e){v8=e.wasm.cwrap(fo,null,["number","array","number","number","number","bool","number","number"])}var hne=({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 v8(i,o,n.shape.length,Ct[n.dtype],r,s,p,d),[u,c]},fne={kernelName:fo,backendName:"wasm",setupFunc:cne,kernelFunc:hne},k8;function mne(e){k8=e.wasm.cwrap(mo,null,["number","number","bool","number","number","number","number","number","number","array","number","array","number","number","number","number","number"])}function gne(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,[f,m]=u!=null?u:[c,d],g=[p,f,m,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,k=t.dataIdMap.get(r.dataId).id,S=t.dataIdMap.get(s.dataId).id,C=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 k8(k,S,s.shape[0]>1,p,f,m,h,d,c,y,r.shape.length-1,x,g.length-1,C,N,l,b),A}var yne={kernelName:mo,backendName:"wasm",setupFunc:mne,kernelFunc:gne};function xne(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]=qs({inputs:{x:r},attrs:{begin:c,size:d},backend:a});return p.map(({dataId:h,dtype:f})=>({dataId:h,dtype:f,shape:l}))}var Ane={kernelName:au,backendName:"wasm",kernelFunc:xne};function bne(e){let{inputs:{x:t},backend:a}=e,n=a.makeOutput(t.shape,t.dtype);return a.typedArrayFromHeap(n).fill(0),n}var vne={kernelName:nu,backendName:"wasm",kernelFunc:bne},kne=[XJ,KJ,YJ,eQ,lQ,pQ,fQ,yQ,vQ,CQ,NQ,EQ,$Q,_Q,OQ,LQ,BQ,WQ,GQ,qQ,ZQ,QQ,aee,nee,see,iee,oee,lee,pee,cee,fee,yee,bee,wee,Tee,Eee,Mee,_ee,tQ,Pee,Dee,Lee,Wee,Vee,Gee,Hee,qee,Kee,Jee,ete,nte,ite,ute,pte,fte,gte,yte,bte,wte,Tte,Nte,Mte,_te,Fte,t8,Lte,Vte,Hte,qte,Kte,Zte,Yte,Jte,xQ,tae,rae,oae,dae,pae,cae,mae,xae,vae,kae,SQ,Sae,Cae,Rae,_ae,Fae,Dae,Lae,Bae,Wae,Uae,jae,Kae,Yae,Qae,tne,nne,ine,one,lne,pne,fne,yne,sQ,Ane,vne];for(let e of kne)yn(e);var N2=V();N2.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}});N2.registerFlag("WASM_HAS_MULTITHREAD_SUPPORT",async()=>{if(N2.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 _y=xl(aS()),wne=xl(nS()),Py=xl(rS()),Fy=_y.default||_y,Ine=Py.default||Py,w8=class extends Al{constructor(e){super(),this.wasm=e,this.dataIdNextNumber=1,this.wasm.tfjs.initWithThreadsCount(I8),E2=this.wasm.tfjs.getThreadsCount(),this.dataIdMap=new kd(this,vt())}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);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 Cne(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){let n;if(a==null)n=this.write(null,e,t);else{let r=this.dataIdNextNumber++;n={id:r},this.dataIdMap.set(n,{id:r,memoryOffset:a,shape:e,dtype:t,refCount:1});let s=v.sizeFromShape(e);this.wasm.tfjs.registerTensor(r,s,a)}return{dataId:n,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 ${t}`)}}};function Sne(e){return(t,a)=>(v.fetch(e,{credentials:"same-origin"}).then(n=>{n.ok||t.env.a(`failed to load wasm binary file at '${e}'`),n.arrayBuffer().then(r=>{WebAssembly.instantiate(r,t).then(s=>{a(s.instance,s.module)})})}),{})}function Oy(e,t,a){if(Vc!=null)return Vc;let n="tfjs-backend-wasm.wasm";return e&&t?n="tfjs-backend-wasm-threaded-simd.wasm":e&&(n="tfjs-backend-wasm-simd.wasm"),Qu!=null&&Qu[n]!=null?Qu[n]:a+n}async function Tne(){let[e,t]=await Promise.all([V().getAsync("WASM_HAS_SIMD_SUPPORT"),V().getAsync("WASM_HAS_MULTITHREAD_SUPPORT")]);return new Promise((a,n)=>{let r={};r.locateFile=(o,l)=>{if(o.endsWith(".worker.js")){let u=wne.wasmWorkerContents.replace(/\n/g,"\\n"),p=new Blob([u],{type:"application/javascript"});return URL.createObjectURL(p)}return o.endsWith(".wasm")?Oy(e,t,Zu!=null?Zu:l):l+o},F3&&(r.instantiateWasm=Sne(Oy(e,t,Zu!=null?Zu:"")));let s=!1;r.onAbort=()=>{s||ed||(ed=!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&&Vc==null?(r.mainScriptUrlOrBlob=new Blob(["var WasmBackendModuleThreadedSimd = "+Fy.toString()],{type:"text/javascript"}),i=Fy(r)):i=Ine(r),i.then(o=>{s=!0,ed=!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 Cne(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 Nne=["tfjs-backend-wasm.wasm","tfjs-backend-wasm-simd.wasm","tfjs-backend-wasm-threaded-simd.wasm"],Vc=null,Zu=null,Qu={},ed=!1,F3=!1;function Ene(e,t=!1){if(t1("setWasmPath has been deprecated in favor of setWasmPaths and will be removed in a future release."),ed)throw new Error("The WASM backend was already initialized. Make sure you call `setWasmPath()` before you call `tf.setBackend()` or `tf.ready()`");Vc=e,F3=t}function Fh(e,t=!1){if(ed)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")Zu=e;else{Qu=e;let a=Nne.filter(n=>Qu[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.`)}F3=t}var I8=-1,E2=-1;function Rne(e){I8=e}function Mne(){if(E2===-1)throw new Error("WASM backend not initialized.");return E2}var $ne="4.2.0",_ne=2;yo("wasm",async()=>{let{wasm:e}=await Tne();return new w8(e)},_ne);var zn=V();zn.registerFlag("WEBGPU_DEFERRED_SUBMIT_BATCH_SIZE",()=>15);zn.registerFlag("WEBGPU_CPU_FORWARD",()=>!0);zn.registerFlag("WEBGPU_MATMUL_PROGRAM_TYPE",()=>-1);zn.registerFlag("WEBGPU_USE_NAIVE_CONV2D_TRANSPOSE",()=>!1);zn.registerFlag("WEBGPU_USE_LOW_POWER_GPU",()=>!1);zn.registerFlag("WEBGPU_CPU_HANDOFF_SIZE_THRESHOLD",()=>1e3);zn.registerFlag("WEBGPU_USE_PROFILE_TOOL",()=>!1);zn.registerFlag("WEBGPU_IMPORT_EXTERNAL_TEXTURE",()=>!0);zn.registerFlag("WEBGPU_USE_NAIVE_CONV2D_DEBUG",()=>!1);zn.registerFlag("WEBGPU_THRESHOLD_TO_INCREASE_WORKGROUPS_FOR_MATMUL",()=>0);zn.registerFlag("WEBGPU_CONV_SEPARATE_IM2COL_SHADER",()=>!1);var Pne=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"}},Fne=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}acquireUploadBuffer(e,t){return this.acquireBuffer(e,t,!0)}acquireBuffer(e,t,a=!1){let n=Dy(e,t);if(this.freeBuffers.has(n)||this.freeBuffers.set(n,[]),this.usedBuffers.has(n)||this.usedBuffers.set(n,[]),this.numBytesUsed+=e,this.numUsedBuffers++,this.freeBuffers.get(n).length>0){this.numFreeBuffers--;let s=this.freeBuffers.get(n).shift();return this.usedBuffers.get(n).push(s),s}this.numBytesAllocated+=e;let r=this.device.createBuffer({size:e,usage:t,mappedAtCreation:a});return this.usedBuffers.get(n).push(r),r}releaseBuffer(e,t,a){if(this.freeBuffers.size===0)return;let n=Dy(t,a);this.freeBuffers.has(n)||this.freeBuffers.set(n,[]),this.freeBuffers.get(n).push(e),this.numFreeBuffers++,this.numUsedBuffers--;let r=this.usedBuffers.get(n),s=r.indexOf(e);if(s<0)throw new Error("Cannot release a buffer that was never provided by this buffer manager");r.splice(s,1),this.numBytesUsed-=t}releaseUploadBuffer(e,t,a){e.mapAsync(GPUMapMode.WRITE).then(()=>{this.releaseBuffer(e,t,a)},n=>{})}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 Dy(e,t){return`${e}_${t}`}var One=class{constructor(e){this.device=e,this.numUsedTextures=0,this.numFreeTextures=0,this.freeTextures=new Map,this.usedTextures=new Map,this.numBytesUsed=0,this.numBytesAllocated=0}acquireTexture(e,t,a,n){let r=Ly(a),s=e*t*r,i=zy(e,t,a,n);if(this.freeTextures.has(i)||this.freeTextures.set(i,[]),this.usedTextures.has(i)||this.usedTextures.set(i,[]),this.numBytesUsed+=s,this.numUsedTextures++,this.freeTextures.get(i).length>0){this.numFreeTextures--;let l=this.freeTextures.get(i).shift();return this.usedTextures.get(i).push(l),l}this.numBytesAllocated+=s;let o=this.device.createTexture({size:[e,t],format:a,usage:n});return this.usedTextures.get(i).push(o),o}releaseTexture(e,t,a,n,r){if(this.freeTextures.size===0)return;let s=zy(t,a,n,r);this.freeTextures.has(s)||this.freeTextures.set(s,[]),this.freeTextures.get(s).push(e),this.numFreeTextures++,this.numUsedTextures--;let i=this.usedTextures.get(s),o=i.indexOf(e);if(o<0)throw new Error("Cannot release a texture that was never provided by this texture manager");i.splice(o,1);let l=Ly(n),u=t*a*l;this.numBytesUsed-=u}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){this.freeTextures.forEach((e,t)=>{e.forEach(a=>{a.destroy()})}),this.usedTextures.forEach((e,t)=>{e.forEach(a=>{a.destroy()})}),this.freeTextures=new Map,this.usedTextures=new Map,this.numUsedTextures=0,this.numFreeTextures=0,this.numBytesUsed=0,this.numBytesAllocated=0}};function zy(e,t,a,n){return`${e}_${t}_${a}_${n}`}function Ly(e){if(e==="rgba8unorm")return 16;throw new Error(`${e} is not supported!`)}function Dne(e,t){if(Math.max(...e)>3)throw new Error("Cannot symbolically compute strides for rank > 4 tensor.");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]} * ${n[s+1]})`;return r}var O3=(e,t,a)=>a==="int32"?`atomicAdd(${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;
|
|
}
|
|
}`,zne=(e,t,a,n)=>{let r={dtype:n.dtype,shape:n.shape},s=Bne(a,r,t),i=e.createShaderModule({code:s,label:t.constructor.name});return e.createComputePipeline({compute:{module:i,entryPoint:"_start"},label:t.constructor.name,layout:"auto"})};function oa(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 br(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 ${e} is not yet supported`)}function ke(...e){let t;switch(e.length){case 0:t=`
|
|
fn main()
|
|
`;break;case 1:t=`
|
|
fn main(${e[0]} : i32)
|
|
`;break;default:throw Error("Unreachable")}return t}function By(e,t){let a;return a=`
|
|
${Lne(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;
|
|
${e?"main(getGlobalIndex());":"main();"};
|
|
}
|
|
`,a}function Lne(e){return`
|
|
@compute @workgroup_size(${e.workgroupSize[0]}, ${e.workgroupSize[1]}, ${e.workgroupSize[2]})
|
|
`}function Bne(e,t,a){let n=[],r=a.workgroupSize[0]*a.workgroupSize[1]*a.workgroupSize[2];if(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 {
|
|
${S8(a)?" return i32(globalId.x);":` return i32((workgroupId.z * numWorkgroups.x * numWorkgroups.y +
|
|
workgroupId.y * numWorkgroups.x + workgroupId.x) * ${r}u +
|
|
localIndex);
|
|
`}
|
|
}
|
|
`),a.isFromPixels){n.push(`
|
|
struct Uniform {
|
|
size : i32,
|
|
numChannels : i32,
|
|
outShapeStrides : vec2<i32>,
|
|
};
|
|
|
|
@group(0) @binding(0) var<storage, read_write> result: array<${td(t.dtype,a.isVec4)}>;
|
|
@group(0) @binding(2) var<uniform> uniforms: Uniform;
|
|
`);let h=Uy(a);return[Wy,n.join(`
|
|
`),Vy(t.shape),a.getUserCode(),By(h,a)].join(`
|
|
`)}let s="struct Uniforms { NAN : f32, INFINITY : f32, ";a.variableNames.forEach((h,f)=>{let m=oa(e[f].shape.length);s+=`${h.charAt(0).toLowerCase()+h.slice(1)}Shape : ${m}, `});let i=oa(t.shape.length);s+=`outShape : ${i}, `;let o=t.shape.length-1,l=oa(o);s+=`
|
|
outShapeStrides: ${l}, `,a.size&&(s+="size : i32, "),a.uniforms&&(s+=a.uniforms),s+="};",s=Kne(s),n.push(s),a.atomic?n.push(`
|
|
@group(0) @binding(0) var<storage, read_write> result: array<atomic<i32>>;
|
|
`):n.push(`
|
|
@group(0) @binding(0) var<storage, read_write> result: array<${td(t.dtype,a.isVec4)}>;
|
|
`),a.variableNames.forEach((h,f)=>{n.push(`
|
|
@group(0) @binding(${1+f}) var<storage, read> ${h}: array<${a.variableTypes?a.variableTypes[f]:td(e[f].dtype,a.isVec4)}>;
|
|
`)}),s!==""&&n.push(`
|
|
@group(0) @binding(${1+a.variableNames.length}) var<uniform> uniforms: Uniforms;
|
|
`);let u=jne(t.shape,a.dispatchLayout),p=[Wy,n.join(`
|
|
`)+Vne,Vy(t.shape),u,qne(t.shape.length)];a.atomic||p.push(Xne(t.shape,t.dtype,a.isVec4));let c=e.map((h,f)=>Hne(h,t.shape,a.variableTypes?a.variableTypes[f]==="vec4<f32>":a.isVec4,a.dispatchLayout.x.length===t.shape.length)).join(`
|
|
`);p.push(c),p.push(a.getUserCode());let d=Uy(a);return p.push(By(d,a)),p.join(`
|
|
`)}function Wne(e,t,a,n){let r=e.shaderKey;if(e.isFromPixels)return r;let s=a.map(p=>p.dtype).concat(n.dtype),i=a.map(p=>T.getBroadcastDims(p.shape,n.shape)),o=a.map(p=>v.arraysEqual(p.shape,n.shape)).join("_"),l=i.map(p=>p.join("_")).join(";"),u=S8(e)?"flatDispatch":"";return r+="_"+(e.workgroupSize?e.workgroupSize.join(","):"")+t.map(p=>p.length).join(",")+s.join(",")+e.variableNames.join(",")+l+o+u,r}var Wy=`
|
|
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;
|
|
}
|
|
|
|
fn idiv(a: i32, b: i32, sign: f32) -> i32 {
|
|
var res: i32 = a / b;
|
|
let modulo: i32 = a % b;
|
|
if (sign < 0. && modulo != 0) {
|
|
res = res - 1;
|
|
}
|
|
return res;
|
|
}
|
|
|
|
// 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);
|
|
}
|
|
`,Vne=`
|
|
fn isinf(val: f32) -> bool {
|
|
return abs(val) == uniforms.INFINITY;
|
|
}
|
|
`;function Vy(e){let t=e.length;if(t<=1)return"fn getCoordsFromIndex(index : i32) -> i32 { return index; }";let a=v.computeStrides(e),n=oa(t),r=[];for(let i=0;i<t;i++)r.push(`d${i}`);if(a.length===1)return` fn getCoordsFromIndex(index : i32) -> vec2<i32> {
|
|
let d0 = index / uniforms.outShapeStrides; let d1 = index - d0 * uniforms.outShapeStrides;
|
|
return vec2<i32>(d0, d1);
|
|
}`;let s;return s="var index2 = index;"+a.map((i,o)=>{let l=`let ${r[o]} = index2 / uniforms.outShapeStrides.${br(o)}`,u=o===a.length-1?`let ${r[o+1]} = index2 - ${r[o]} * uniforms.outShapeStrides.${br(o)}`:`index2 = index2 - ${r[o]} * uniforms.outShapeStrides.${br(o)}`;return`${l}; ${u};`}).join(""),`
|
|
fn getCoordsFromIndex(index : i32) -> ${n} {
|
|
${s}
|
|
return ${n}(${r.join(",")});
|
|
}
|
|
`}function Une(e,t){let a=e.name,n=e.shape.length,r=oa(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 t?`
|
|
fn ${s}() -> vec4<f32> {
|
|
return vec4<f32>(${a}[0]);
|
|
}
|
|
`:`
|
|
fn ${s}() ->f32 {
|
|
return f32(${a}[0]);
|
|
}
|
|
`;let l=`uniforms.${a.charAt(0).toLowerCase()+a.slice(1)}Shape`,u=`${n}D`;return n===0&&(u="1D"),t?`
|
|
fn ${s}(${o}) -> vec4<f32> {
|
|
return vec4<f32>(${a}[getIndexFromCoords${u}(${r}(${i.join(",")}),
|
|
${l}) / 4]);
|
|
}
|
|
`:`
|
|
fn ${s}(${o}) -> f32 {
|
|
return f32(${a}[getIndexFromCoords${u}(${r}(${i.join(",")}),
|
|
${l})]);
|
|
}
|
|
`}function Gne(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=oa(l);if(v.arraysEqual(e.shape,t)&&n)return a?`
|
|
fn ${i}Index(globalIndex : i32) -> vec4<f32> {
|
|
return vec4<f32>(${r}[globalIndex]);
|
|
}
|
|
|
|
fn ${i}Coords(coords : ${u}) -> vec4<f32> {
|
|
return vec4<f32>(${r}[${l>1?"getOutputIndexFromCoords(coords)":"coords"} / 4]);
|
|
}
|
|
`:`
|
|
fn ${i}Index(globalIndex : i32) -> f32 {
|
|
return f32(${r}[globalIndex]);
|
|
}
|
|
|
|
fn ${i}Coords(coords : ${u}) -> f32 {
|
|
return f32(${r}[${l>1?"getOutputIndexFromCoords(coords)":"coords"}]);
|
|
}
|
|
`;let p=T.getBroadcastDims(e.shape,t),c=l-o,d="";if(o===0)return a?`
|
|
fn ${i}Index(globalIndex : i32) -> vec4<f32> {
|
|
return get${s}();
|
|
}
|
|
|
|
fn ${i}Coords(coords : ${u}) -> vec4<f32> {
|
|
return get${s}();
|
|
}
|
|
`:`
|
|
fn ${i}Index(globalIndex : i32) -> f32{
|
|
return get${s}();
|
|
}
|
|
|
|
fn ${i}Coords(coords : ${u}) -> f32{
|
|
return get${s}();
|
|
}
|
|
`;l<2&&p.length>=1?d="coords = 0;":d=p.map(g=>`coords.${br(g+c)} = 0;`).join(`
|
|
`);let h="";if(l<2&&o>0)h="coords";else if(l>1){let g=oa(o),y=e.shape.map((x,A)=>`coords.${br(A+c)}`).join(", ");h=`${g}(${y})`}else h="coords";let f=`uniforms.${r.charAt(0).toLowerCase()+r.slice(1)}Shape`,m=`${o}D`;return a?`
|
|
fn ${i}Index(globalIndex : i32) -> vec4<f32> {
|
|
var coords = getCoordsFromIndex(globalIndex);
|
|
${d}
|
|
return ${r}[getIndexFromCoords${m}(${h}, ${f}) / 4];
|
|
}
|
|
|
|
fn ${i}Coords(coordsIn : ${u}) -> vec4<f32> {
|
|
var coords = coordsIn;
|
|
${d}
|
|
return ${r}[getIndexFromCoords${m}(${h}, ${f}) / 4];
|
|
}
|
|
`:`
|
|
fn ${i}Index(globalIndex : i32) -> f32 {
|
|
var coords = getCoordsFromIndex(globalIndex);
|
|
${d}
|
|
return f32(${r}[getIndexFromCoords${m}(${h}, ${f})]);
|
|
}
|
|
|
|
fn ${i}Coords(coordsIn : ${u}) -> f32 {
|
|
var coords = coordsIn;
|
|
${d}
|
|
return f32(${r}[getIndexFromCoords${m}(${h}, ${f})]);
|
|
}
|
|
`}function Hne(e,t,a,n){let r=Une(e,a);return e.shape.length<=t.length&&(r+=Gne(e,t,a,n)),r}function jne(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() -> ${oa(s)}{
|
|
let globalIndex = getGlobalIndex();
|
|
return getCoordsFromIndex(globalIndex);
|
|
}
|
|
`;let o="",l=[a,n,r];for(let d=0;d<l.length;d++){let h=l[d];if(h.length!==0)if(h.length===1)o+=`let d${h[0]} = i32(globalId[${d}]);`;else{let f=Dne(h,"uniforms.outShape");o+=`var index${d} = i32(globalId[${d}]);`;for(let m=0;m<f.length;m++)o+=`let d${h[m]} = index${d} / ${f[m]};`,m===f.length-1?o+=`let d${h[m+1]} = index${d} - d${h[m]} * ${f[m]};`:o+=`index${d} = index${d} - d${h[m]} * ${f[m]};`}}let u=[];for(let d=0;d<i;d++)u.push(`d${d}`);let p=oa(i),c=`fn getOutputCoords() -> ${p} {
|
|
${o}
|
|
`;return u.length===0?c+=`return ${p}(0); }`:c+=`return ${p}(${u.join(",")}); }`,c}function qne(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 S8(e){return e.dispatch[1]===1&&e.dispatch[2]===1}function td(e,t){return e==="float32"?t?"vec4<f32>":"f32":e==="int32"||e==="bool"?t?"vec4<i32>":"i32":e}function Xne(e,t,a){let n=e.length,r=td(t,a),s;if(a?s=`fn setOutputAtIndex(flatIndex : i32, value : vec4<f32>) {
|
|
result[flatIndex] = ${r}(value);
|
|
}
|
|
fn setOutputAtIndexI32(flatIndex : i32, value : vec4<i32>) {
|
|
result[flatIndex] = ${r}(value);
|
|
}`:s=`fn setOutputAtIndex(flatIndex : i32, value : f32) {
|
|
result[flatIndex] = ${r}(value);
|
|
}
|
|
fn setOutputAtIndexI32(flatIndex : i32, value : i32) {
|
|
result[flatIndex] = ${r}(value);
|
|
}`,n>=2){let i=["d0","d1","d2","d3","d4","d5"].slice(0,n),o=oa(n);a?s+=`
|
|
fn setOutputAtCoords(${i.map(l=>`${l} : i32`).join(", ")}, value : vec4<f32>) {
|
|
let flatIndex = getOutputIndexFromCoords(${o}(${i.join(", ")}));
|
|
setOutputAtIndex(flatIndex / 4, value);
|
|
}
|
|
fn setOutputAtCoordsI32(${i.map(l=>`${l} : i32`).join(", ")}, value : vec4<i32>) {
|
|
let flatIndex = getOutputIndexFromCoords(${o}(${i.join(", ")}));
|
|
setOutputAtIndexI32(flatIndex / 4, value);
|
|
}
|
|
`:s+=`
|
|
fn setOutputAtCoords(${i.map(l=>`${l} : i32`).join(", ")}, value : f32) {
|
|
let flatIndex = getOutputIndexFromCoords(${o}(${i.join(", ")}));
|
|
setOutputAtIndex(flatIndex, value);
|
|
}
|
|
fn setOutputAtCoordsI32(${i.map(l=>`${l} : i32`).join(", ")}, value : i32) {
|
|
let flatIndex = getOutputIndexFromCoords(${o}(${i.join(", ")}));
|
|
setOutputAtIndexI32(flatIndex, value);
|
|
}
|
|
`}return s}function Kne(e){let t=/(\w+)\s*:\s*vec(5|6)/g;e=e.replace(t,n=>"@align(16) "+n);let a=/vec(5|6)\s*,\s*(\w+)/g;return e=e.replace(a,(n,r,s)=>`vec${r}, @align(16) ${s}`),e}function Uy(e){return!(e.dispatchLayout.hasOwnProperty("y")&&e.dispatchLayout.y.length!==0||e.dispatchLayout.hasOwnProperty("z")&&e.dispatchLayout.z.length!==0)}var T8={};Ze(T8,{GPUBytesPerElement:()=>R2,MatMulProgramType:()=>Pn,assertNotComplex:()=>N8,computeDispatch:()=>we,computeWorkPerThreadForConv2d:()=>z3,computeWorkgroupInfoForMatMul:()=>C8,computeWorkgroupSizeForConv2d:()=>D3,flatDispatchLayout:()=>$e,isWebGPUSupported:()=>L3,tilesFitEvenlyIntoShape:()=>Zne});var Ds=e=>{let t=1;for(let a=0;a<e.length;a++)t*=e[a];return t};function Zne(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 we(e,t,a=[1,1,1],n=[1,1,1]){let[r,s,i]=[Math.ceil(Ds(e.x.map(o=>t[o]))/(a[0]*n[0])),e.y?Math.ceil(Ds(e.y.map(o=>t[o]))/(a[1]*n[1])):1,e.z?Math.ceil(Ds(e.z.map(o=>t[o]))/(a[2]*n[2])):1];return[r,s,i]}function C8(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 D3(e,t,a=!1){if(a)return[8,8,1];let n=Ds(e.x.map(s=>t[s])),r=Ds(e.y.map(s=>t[s]));return n<=4?[4,16,1]:r<=4?[16,4,1]:[16,16,1]}function z3(e,t,a=!1){if(a)return[4,4,1];let n=Ds(e.x.map(s=>t[s])),r=Ds(e.y.map(s=>t[s]));return n<=4?[1,2,1]:r<=4?[2,1,1]:[2,2,1]}function $e(e){return{x:e.map((t,a)=>a)}}function R2(e){if(e==="float32"||e==="int32"||e==="bool"||e==="string")return 4;if(e==="complex64")return 8;throw new Error(`Unknown dtype ${e}`)}function L3(){return(typeof window!="undefined"||typeof WorkerGlobalScope!="undefined")&&!!navigator.gpu}function N8(e,t){Array.isArray(e)||(e=[e]),e.forEach(a=>{a!=null&&v.assert(a.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the WebGPU backend.`)})}var Pn;(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"})(Pn||(Pn={}));var Yne=V().getNumber("WEBGPU_CPU_HANDOFF_SIZE_THRESHOLD"),Jne=(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]},Oh=class extends Al{constructor(e,t){if(super(),this.commandQueueOwnedIds=new WeakSet,this.dispatchNumberInEncoder=0,this.disposed=!1,this.downloadWaitMs=0,this.tensorDataPendingDisposal=[],this.stagingPendingDisposal=[],this.uniformPendingDisposal=[],this.uploadWaitMs=0,!L3())throw new Error("WebGPU is not supported on this device");this.pipelineCache={},this.device=e,this.queue=e.queue,this.currentCommandEncoder=null,this.currentComputePass=null,this.supportTimeQuery=e.features.has("timestamp-query-inside-passes"),this.adapterInfo=new Pne(t),this.thresholdToIncreaseWorkgroups=this.adapterInfo.intelGPUGeneration>=12?16:8,this.bufferManager=new Fne(this.device),this.textureManager=new One(this.device),this.tensorMap=new kd(this,vt()),this.supportTimeQuery&&(this.querySet=this.device.createQuerySet({type:"timestamp",count:2})),V().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:e,format:"bgra8unorm"}),document.body.appendChild(this.dummyCanvas))}nextDataId(){return Oh.nextDataId++}floatPrecision(){return 32}defaultGpuBufferUsage(){return GPUBufferUsage.STORAGE|GPUBufferUsage.COPY_SRC|GPUBufferUsage.COPY_DST}disposeData(e,t=!1){if(this.tensorDataPendingDisposal.indexOf(e)>=0)return!1;if(!this.tensorMap.has(e))return!0;let a=this.tensorMap.get(e);if(this.decRef(e),!t&&a.refCount>0)return!1;if(this.commandQueueOwnedIds.has(e))return this.tensorDataPendingDisposal.push(e),!1;let{complexTensorInfos:n}=this.tensorMap.get(e);return n!=null&&(this.disposeData(n.real.dataId,t),this.disposeData(n.imag.dataId,t)),this.releaseResource(e),this.tensorMap.delete(e),!0}memory(){return{numBytesInGPU:this.bufferManager.numBytesUsed,numBytesAllocatedInGPU:this.bufferManager.numBytesAllocated,unreliable:!1}}releaseResource(e){let t=this.tensorMap.get(e);if(!(!t||!t.resourceInfo)){if(t.external){t.resourceInfo=null;return}if("texture"in t.resourceInfo){let a=t.resourceInfo;a.texture instanceof GPUTexture&&this.textureManager.releaseTexture(a.texture,a.width,a.height,a.format,a.usage),a.texture=null}else{let a=t.resourceInfo;this.bufferManager.releaseBuffer(a.buffer,a.size,a.usage),a.buffer=null}t.resourceInfo=null}}refCount(e){return this.tensorMap.has(e)?this.tensorMap.get(e).refCount:0}incRef(e){let t=this.tensorMap.get(e);t.refCount++}decRef(e){if(this.tensorMap.has(e)){let t=this.tensorMap.get(e);t.refCount--}}write(e,t,a){if(a==="complex64"&&e!=null)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let n={id:this.nextDataId()};return this.tensorMap.set(n,{dtype:a,shape:t,values:e,refCount:1}),n}move(e,t,a,n,r){if(n==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.tensorMap.set(e,{dtype:n,shape:a,values:t,refCount:r})}submitQueue(){this.ensureComputePassEnded(),this.queue.submit([this.currentCommandEncoder.finish()]),this.currentCommandEncoder=null,this.dispatchNumberInEncoder=0,this.commandQueueOwnedIds=new WeakSet,this.tensorDataPendingDisposal.forEach(e=>{this.releaseResource(e),this.tensorMap.delete(e)}),this.uniformPendingDisposal.forEach(e=>this.bufferManager.releaseBuffer(e.buffer,e.size,e.usage)),this.stagingPendingDisposal.forEach(e=>this.bufferManager.releaseUploadBuffer(e.buffer,e.size,e.usage)),this.tensorDataPendingDisposal=[],this.uniformPendingDisposal=[],this.stagingPendingDisposal=[]}ensureCommandEncoderReady(){this.currentCommandEncoder||(this.currentCommandEncoder=this.device.createCommandEncoder())}ensureComputePassEnded(){this.currentComputePass&&(this.currentComputePass.end(),this.currentComputePass=null)}getComputePass(){return this.currentComputePass||(this.currentComputePass=this.currentCommandEncoder.beginComputePass()),this.currentComputePass}async getBufferData(e,t){let a=this.bufferManager.acquireBuffer(t,GPUBufferUsage.COPY_DST|GPUBufferUsage.MAP_READ);this.ensureCommandEncoderReady(),this.ensureComputePassEnded(),this.currentCommandEncoder.copyBufferToBuffer(e,0,a,0,t),this.submitQueue(),await a.mapAsync(GPUMapMode.READ);let n=a.getMappedRange().slice(0);return a.unmap(),a!=null&&this.bufferManager.releaseBuffer(a,t,GPUBufferUsage.COPY_DST|GPUBufferUsage.MAP_READ),V().getBool("WEBGPU_USE_PROFILE_TOOL")&&(v.assert(this.dummyContext!==void 0,()=>"Fail to get context for profiling tool"),this.dummyContext.getCurrentTexture()),n}convertAndCacheOnCPU(e,t){let a=this.tensorMap.get(e);return this.releaseResource(e),a.values=t,a.values}readSync(e){let t=this.tensorMap.get(e),{values:a}=t;if(a==null)throw new Error("WebGPU readSync is only available for CPU-resident tensors.");return a}async read(e){if(!this.tensorMap.has(e))throw new Error(`Tensor ${e} was not registered!`);let t=this.tensorMap.get(e),{values:a}=t;if(a!=null)return this.convertAndCacheOnCPU(e,a);let n;if(t.dtype==="complex64"){let r=await Promise.all([this.read(t.complexTensorInfos.real.dataId),this.read(t.complexTensorInfos.imag.dataId)]),s=r[0],i=r[1];n=T.mergeRealAndImagArrays(s,i)}else{let r=t.resourceInfo,s=await this.getBufferData(r.buffer,r.size);n=v.convertBackendValuesAndArrayBuffer(s,t.dtype)}return this.convertAndCacheOnCPU(e,n),n}copyBuffer(e,t,a){let n=this.bufferManager.acquireBuffer(t,a);return this.ensureCommandEncoderReady(),this.ensureComputePassEnded(),this.currentCommandEncoder.copyBufferToBuffer(e,0,n,0,t),this.submitQueue(),n}createTensorFromGPUData(e,t,a){let n=e.buffer;if(a==="complex64")throw new Error("Cannot write to a complex64 dtype. ");let r={id:this.nextDataId()};this.tensorMap.set(r,{dtype:a,shape:t,values:null,refCount:1,external:e.zeroCopy});let s=this.tensorMap.get(r),i=R2(s.dtype)*v.sizeFromShape(s.shape);if(e.buffer.size<i)throw new Error(`GPUBuffer size(${e.buffer.size}) is smaller than tensor size(${i})!`);if((e.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 e.zeroCopy!==!0&&(n=this.copyBuffer(n,i,n.usage)),s.resourceInfo={size:n.size,usage:n.usage,buffer:n},vt().makeTensorFromDataId(r,t,a,this)}readToGPU(e){let t=this.tensorMap.get(e),{values:a,dtype:n,shape:r,resourceInfo:s}=t;if(n==="complex64")throw new Error("Does not support reading buffer for complex64 dtype.");if(s==null)throw a!=null?new Error("Data is not on GPU but on CPU."):new Error("There is no data on GPU or CPU.");let i=s.size,o=this.bufferManager.acquireBuffer(i,s.usage);this.ensureCommandEncoderReady(),this.ensureComputePassEnded(),this.currentCommandEncoder.copyBufferToBuffer(s.buffer,0,o,0,i),this.submitQueue();let l=this.makeTensorInfo(r,n),u=vt().makeTensorFromTensorInfo(l),p=this.tensorMap.get(l.dataId);return p.resourceInfo={size:i,usage:this.defaultGpuBufferUsage(),buffer:o},{tensorRef:u,buffer:o,bufSize:i}}bufferSync(e){let t=this.readSync(e.dataId);if(e.dtype==="string")try{let a=t.map(n=>v.decodeString(n));return _e(e.shape,e.dtype,a)}catch(a){throw new Error("Failed to decode encoded string bytes into utf-8")}return _e(e.shape,e.dtype,t)}async time(e){this.supportTimeQuery||console.warn("This device doesn't support timestamp-query-inside-passes extension. Start Chrome browser with flag --disable-dawn-features=disallow_unsafe_apis then try again. Otherwise, zero will be shown for the kernel time when profiling mode is enabled. Using performance.now is not workable for webgpu since it doesn't support synchronous data read from GPU.");let t=this.activeTimers,a=[],n=!1;this.programTimersStack==null?(this.programTimersStack=a,n=!0):this.activeTimers.push(a),this.activeTimers=a,e();let r=v.flatten(this.activeTimers.map(l=>l.query)).filter(l=>l!=null),s=v.flatten(this.activeTimers.map(l=>l.name)).filter(l=>l!=null);this.activeTimers=t,n&&(this.programTimersStack=null);let i={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null},o=await Promise.all(r);return i.kernelMs=v.sum(o),i.getExtraProfileInfo=()=>o.map((l,u)=>({name:s[u],ms:l})).map(l=>`${l.name}: ${l.ms}`).join(", "),this.uploadWaitMs=0,this.downloadWaitMs=0,i}makeTensorInfo(e,t,a){return t==="string"&&a!=null&&a.length>0&&v.isString(a[0])&&(a=a.map(n=>v.encodeString(n))),{dataId:this.write(a,e,t),shape:e,dtype:t}}tensorToBinding(e){if(!e)return null;let t=this.tensorMap.get(e.dataId);if("texture"in t.resourceInfo){let n=t.resourceInfo;return n.texture instanceof GPUExternalTexture?n.texture:n.texture.createView()}let a=t.resourceInfo;return{offset:0,size:a.size,buffer:a.buffer}}async getQueryTime(e){return this.supportTimeQuery?this.getTimeFromQuerySet(e):0}uploadToGPU(e){let t=this.tensorMap.get(e);if(t.resourceInfo)return;let a=R2(t.dtype)*v.sizeFromShape(t.shape),n=this.bufferManager.acquireBuffer(a,this.defaultGpuBufferUsage());if(t.resourceInfo={size:a,usage:this.defaultGpuBufferUsage(),buffer:n},t.values){let r=this.bufferManager.acquireUploadBuffer(a,GPUBufferUsage.MAP_WRITE|GPUBufferUsage.COPY_SRC),s=r.getMappedRange();t.dtype==="int32"||t.dtype==="bool"?new Int32Array(s).set(t.values):new Float32Array(s).set(t.values),r.unmap(),this.ensureCommandEncoderReady(),this.ensureComputePassEnded(),this.currentCommandEncoder.copyBufferToBuffer(r,0,n,0,a);let i={size:a,usage:GPUBufferUsage.MAP_WRITE|GPUBufferUsage.COPY_SRC,buffer:r};this.stagingPendingDisposal.push(i)}}makeUniforms(e){let t=0,a=0,n=[],r=1;e.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`)}(a===5||a===6)&&(u=16),u>r&&(r=u),t=Math.ceil(t/u)*u,a=l.data.length,n.push(t),t+=l.data.length*4}),t=Math.ceil(t/r)*r;let s=new ArrayBuffer(t);e.forEach((l,u)=>{let p=n[u];l.type==="int32"?new Int32Array(s,p,l.data.length).set(l.data):l.type==="uint32"?new Uint32Array(s,p,l.data.length).set(l.data):new Float32Array(s,p,l.data.length).set(l.data)});let i=this.bufferManager.acquireBuffer(t,GPUBufferUsage.COPY_DST|GPUBufferUsage.UNIFORM);this.queue.writeBuffer(i,0,s,0,t);let o={size:t,usage:GPUBufferUsage.COPY_DST|GPUBufferUsage.UNIFORM,buffer:i};return this.uniformPendingDisposal.push(o),{offset:0,size:t,buffer:i}}runWebGPUProgram(e,t,a,n,r){if(r||(r=this.makeTensorInfo(e.outputShape,a)),v.sizeFromShape(r.shape)===0)return this.tensorMap.get(r.dataId).values=v.getTypedArrayFromDType(r.dtype,0),r;this.uploadToGPU(r.dataId),e.dispatch=Jne(this.device,e);let s=[],i=[];if(!e.isFromPixels){s.push({type:"float32",data:[NaN]},{type:"float32",data:[1/0]}),i=t.concat(r).map(g=>g.shape);let f="int32";i.map(g=>{s.push({type:f,data:g})});let m=v.computeStrides(r.shape);if(s.push({type:f,data:m}),e.size){let g=v.sizeFromShape(e.outputShape);s.push({type:f,data:[e.isVec4?g/4:g]})}}let o=t.map((f,m)=>{if(f.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(f.dataId),{dtype:this.tensorMap.get(f.dataId).dtype,shape:f.shape,name:e.variableNames[m]}}),l=Wne(e,i,o,r),u;l in this.pipelineCache?u=this.pipelineCache[l]:(u=zne(this.device,e,o,r),this.pipelineCache[l]=u),n&&(s=[...s,...n]);let p=[this.tensorToBinding(r),...t.map(f=>this.tensorToBinding(f)),this.makeUniforms(s)],c=this.device.createBindGroup({layout:u.getBindGroupLayout(0),entries:p.map((f,m)=>({binding:m,resource:f}))});this.ensureCommandEncoderReady();let d=this.getComputePass(),h=this.activeTimers!=null;return h&&this.supportTimeQuery&&d.writeTimestamp(this.querySet,0),d.setPipeline(u),d.setBindGroup(0,c),d.dispatchWorkgroups(e.dispatch[0],e.dispatch[1],e.dispatch[2]),h&&this.supportTimeQuery&&d.writeTimestamp(this.querySet,1),this.dispatchNumberInEncoder++,t.forEach(f=>{this.commandQueueOwnedIds.add(f.dataId)}),this.commandQueueOwnedIds.add(r.dataId),V().get("WEBGPU_DEFERRED_SUBMIT_BATCH_SIZE")<=this.dispatchNumberInEncoder&&this.submitQueue(),h&&this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(this.querySet)}),r}async getTimeFromQuerySet(e){let t=this.bufferManager.acquireBuffer(16,GPUBufferUsage.COPY_SRC|GPUBufferUsage.QUERY_RESOLVE),a=this.bufferManager.acquireBuffer(16,GPUBufferUsage.MAP_READ|GPUBufferUsage.COPY_DST);this.ensureCommandEncoderReady(),this.ensureComputePassEnded(),this.currentCommandEncoder.resolveQuerySet(e,0,2,t,0),this.currentCommandEncoder.copyBufferToBuffer(t,0,a,0,16),this.submitQueue(),await a.mapAsync(GPUMapMode.READ);let n=new BigUint64Array(a.getMappedRange()),r=Number(n[1]-n[0]);return a.unmap(),this.bufferManager.releaseBuffer(a,16,GPUBufferUsage.MAP_READ|GPUBufferUsage.COPY_DST),this.bufferManager.releaseBuffer(t,16,GPUBufferUsage.COPY_SRC|GPUBufferUsage.QUERY_RESOLVE),r/1e6}shouldExecuteOnCPU(e,t=Yne){return V().getBool("WEBGPU_CPU_FORWARD")&&e.every(a=>this.tensorMap.get(a.dataId).resourceInfo==null&&v.sizeFromShape(a.shape)<t)}numDataIds(){return this.tensorMap.numDataIds()-this.tensorDataPendingDisposal.length}dispose(){this.disposed||(this.bufferManager.dispose(),this.textureManager.dispose(),this.disposed=!0)}};Oh.nextDataId=0;L3()&&yo("webgpu",async()=>{V().set("CHECK_COMPUTATION_FOR_ERRORS",!1);let e={powerPreference:V().get("WEBGPU_USE_LOW_POWER_GPU")?"low-power":"high-performance"},t=await navigator.gpu.requestAdapter(e),a={};t.features.has("timestamp-query-inside-passes")&&(a.requiredFeatures=["timestamp-query-inside-passes"]);let n=t.limits;a.requiredLimits={maxComputeWorkgroupStorageSize:n.maxComputeWorkgroupStorageSize,maxComputeWorkgroupsPerDimension:n.maxComputeWorkgroupsPerDimension,maxStorageBufferBindingSize:n.maxStorageBufferBindingSize};let r=await t.requestDevice(a),s=await t.requestAdapterInfo();return new Oh(r,s)},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.EQUAL=5]="EQUAL",e[e.GREATER=6]="GREATER",e[e.GREATER_EQUAL=7]="GREATER_EQUAL",e[e.INT_DIV=8]="INT_DIV",e[e.LESS=9]="LESS",e[e.LESS_EQUAL=10]="LESS_EQUAL",e[e.LOGICAL_AND=11]="LOGICAL_AND",e[e.LOGICAL_OR=12]="LOGICAL_OR",e[e.MAX=13]="MAX",e[e.MIN=14]="MIN",e[e.MOD=15]="MOD",e[e.MUL=16]="MUL",e[e.NOT_EQUAL=17]="NOT_EQUAL",e[e.POW=18]="POW",e[e.PRELU=19]="PRELU",e[e.SQUARED_DIFFERENCE=20]="SQUARED_DIFFERENCE",e[e.SUB=21]="SUB"})(Pe||(Pe={}));var E8=`
|
|
if (isnan(a)) { return a; }
|
|
if (isnan(b)) { return b; }
|
|
`,Dh=`
|
|
resultTemp = select(
|
|
resultTemp, vec4<f32>(valueForNaN),
|
|
vec4<bool>(isNaN) | isnanVec4(a) | isnanVec4(b));
|
|
`,Qne="return a + b;",ere="return areal * breal - aimag * bimag;",tre="return areal * bimag + aimag * breal;",are="return a / b;",nre="return f32(a == b);",rre="return vec4<f32>(a == b);",sre="return f32(a > b);",ire="return vec4<f32>(a > b);",ore="return f32(a >= b);",lre="return vec4<f32>(a >= b);",ure=`
|
|
let s = sign(a) * sign(b);
|
|
let ia = i32(round(a));
|
|
let ib = i32(round(b));
|
|
return f32(idiv(ia, ib, s));
|
|
`,dre=`
|
|
let ia = vec4<i32>(round(a));
|
|
let ib = vec4<i32>(round(b));
|
|
let cond = ib != vec4<i32>(0);
|
|
var resultTemp = vec4<i32>(0);
|
|
let s = sign(a) * sign(b);
|
|
|
|
// Windows (D3D) wants guaranteed non-zero int division at compile-time.
|
|
if (cond[0]) {
|
|
resultTemp[0] = idiv(ia[0], ib[0], s[0]);
|
|
}
|
|
if (cond[1]) {
|
|
resultTemp[1] = idiv(ia[1], ib[1], s[1]);
|
|
}
|
|
if (cond[2]) {
|
|
resultTemp[2] = idiv(ia[2], ib[2], s[2]);
|
|
}
|
|
if (cond[3]) {
|
|
resultTemp[3] = idiv(ia[3], ib[3], s[3]);
|
|
}
|
|
return vec4<f32>(resultTemp);
|
|
`,pre="return f32(a < b);",cre="return vec4<f32>(a < b);",hre="return f32(a <= b);",fre="return vec4<f32>(a <= b);",mre="return f32(a >= 1.0 && b >= 1.0);",gre=`return (vec4<f32>(a >= vec4<f32>(1.0)) *
|
|
vec4<f32>(b >= vec4<f32>(1.0)));`,yre="return f32(a >= 1.0 || b >= 1.0);",xre=`return min(vec4<f32>(a >= vec4<f32>(1.0)) +
|
|
vec4<f32>(b >= vec4<f32>(1.0)), vec4<f32>(1.0));`,Are=`
|
|
${E8}
|
|
if (b == 0.) {
|
|
return uniforms.NAN;
|
|
}
|
|
var resultTemp = a % b;
|
|
if ((a < 0. && b < 0.) || (a >= 0. && b > 0.)) {
|
|
return resultTemp;
|
|
} else {
|
|
return (resultTemp + b) % b;
|
|
}
|
|
`,bre=`
|
|
let isNaN = !vec4<bool>(b);
|
|
let valueForNaN = uniforms.NAN;
|
|
var resultTemp = vec4<f32>(a % b);
|
|
${Dh}
|
|
|
|
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];
|
|
}
|
|
|
|
return resultTemp;
|
|
`,vre="return a * b;",kre=`
|
|
if (isnan(a) || isnan(b)) {
|
|
return 1.0;
|
|
}
|
|
return f32(a != b);
|
|
`,wre=`
|
|
var resultTemp = vec4<f32>(a != b);
|
|
let valueForNaN = 1.0;
|
|
${Dh}
|
|
|
|
return resultTemp;
|
|
`,Ire=`
|
|
if(a < 0.0 && floor(b) < b) {
|
|
return uniforms.NAN;
|
|
}
|
|
if (b == 0.0) {
|
|
return 1.0;
|
|
}
|
|
if (round(abs(b) % 2.0) != 1.0) {
|
|
return pow(abs(a), b);
|
|
}
|
|
return sign(a) * pow(abs(a), b);
|
|
`,Sre=`
|
|
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);
|
|
let valueForNaN = uniforms.NAN;
|
|
${Dh}
|
|
return resultTemp;
|
|
`,Tre="if (a < 0.0) { return b * a; } return a;",Cre=`
|
|
let aLessThanZero = vec4<f32>(a < vec4<f32>(0.0));
|
|
return (aLessThanZero * (b * a)) + ((vec4<f32>(1.0) - aLessThanZero) * a);
|
|
`,Nre="return (a - b) * (a - b);",Ere="return a - b;";function Dm(e,t,a="uniforms.NAN"){let n=t?Dh:E8;return t?`
|
|
let valueForNaN = ${a};
|
|
var resultTemp = vec4<f32>(${e}(a, b));
|
|
`+n+`
|
|
return resultTemp;
|
|
`:n+`
|
|
return ${e}(a, b);
|
|
`}function B3(e,t){switch(e){case Pe.ADD:return Qne;case Pe.ATAN2:return Dm("atan2",t);case Pe.COMPLEX_MULTIPLY_IMAG:return tre;case Pe.COMPLEX_MULTIPLY_REAL:return ere;case Pe.DIV:return are;case Pe.EQUAL:return t?rre:nre;case Pe.GREATER:return t?ire:sre;case Pe.GREATER_EQUAL:return t?lre:ore;case Pe.INT_DIV:return t?dre:ure;case Pe.LESS:return t?cre:pre;case Pe.LESS_EQUAL:return t?fre:hre;case Pe.LOGICAL_AND:return t?gre:mre;case Pe.LOGICAL_OR:return t?xre:yre;case Pe.MAX:return Dm("max",t);case Pe.MIN:return Dm("min",t);case Pe.MOD:return t?bre:Are;case Pe.MUL:return vre;case Pe.NOT_EQUAL:return t?wre:kre;case Pe.POW:return t?Sre:Ire;case Pe.PRELU:return t?Cre:Tre;case Pe.SQUARED_DIFFERENCE:return Nre;case Pe.SUB:return Ere;default:throw new Error(`BinaryType ${e} is not implemented!`)}}var le;(function(e){e[e.ABS=0]="ABS",e[e.ACOS=1]="ACOS",e[e.ACOSH=2]="ACOSH",e[e.ASIN=3]="ASIN",e[e.ASINH=4]="ASINH",e[e.ATAN=5]="ATAN",e[e.ATANH=6]="ATANH",e[e.CEIL=7]="CEIL",e[e.COS=8]="COS",e[e.COSH=9]="COSH",e[e.ELU=10]="ELU",e[e.ERF=11]="ERF",e[e.EXP=12]="EXP",e[e.EXPM1=13]="EXPM1",e[e.FLOOR=14]="FLOOR",e[e.IS_FINITE=15]="IS_FINITE",e[e.IS_INF=16]="IS_INF",e[e.IS_NAN=17]="IS_NAN",e[e.LINEAR=18]="LINEAR",e[e.LOG=19]="LOG",e[e.LOG1P=20]="LOG1P",e[e.LOGICAL_NOT=21]="LOGICAL_NOT",e[e.NEG=22]="NEG",e[e.RELU=23]="RELU",e[e.RELU6=24]="RELU6",e[e.LEAKYRELU=25]="LEAKYRELU",e[e.RECIPROCAL=26]="RECIPROCAL",e[e.ROUND=27]="ROUND",e[e.RSQRT=28]="RSQRT",e[e.SELU=29]="SELU",e[e.SIGMOID=30]="SIGMOID",e[e.SIGN=31]="SIGN",e[e.SIN=32]="SIN",e[e.SINH=33]="SINH",e[e.SOFTPLUS=34]="SOFTPLUS",e[e.SQRT=35]="SQRT",e[e.SQUARE=36]="SQUARE",e[e.STEP=37]="STEP",e[e.TAN=38]="TAN",e[e.TANH=39]="TANH",e[e.TO_INT=40]="TO_INT"})(le||(le={}));var Rre="return abs(a);",Mre=`
|
|
if (abs(a) > 1.) {
|
|
return uniforms.NAN;
|
|
}
|
|
return acos(a);
|
|
`,$re=`
|
|
if (a < 1.) {
|
|
return uniforms.NAN;
|
|
}
|
|
return acosh(a);
|
|
`,_re=`
|
|
if (abs(a) > 1.) {
|
|
return uniforms.NAN;
|
|
}
|
|
return asin(a);
|
|
`,Pre="return asinh(a);",Fre=`
|
|
if (isnan(a)) {
|
|
return uniforms.NAN;
|
|
}
|
|
return atan(a);
|
|
`,Ore=`
|
|
if (abs(a) > 1.) {
|
|
return uniforms.NAN;
|
|
}
|
|
if (a == 1.) {
|
|
return uniforms.INFINITY;
|
|
}
|
|
if (a == -1.) {
|
|
return -uniforms.INFINITY;
|
|
}
|
|
return atanh(a);
|
|
`,Dre="return ceil(a);",zre="return cos(a);",Lre=`
|
|
let e2x = exp(-a);
|
|
return (e2x + 1.0 / e2x) / 2.0;
|
|
`,Bre="return exp(a) - 1.0;",Wre="if (a >= 0.0) { return a; } return (exp(a) - 1.0);",Vre=`
|
|
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;
|
|
`,Ure=`
|
|
// Error function is calculated approximately with elementary function.
|
|
// See "Handbook of Mathematical Functions with Formulas,
|
|
// Graphs, and Mathematical Tables", Abramowitz and Stegun.
|
|
let p = ${T.ERF_P};
|
|
let a1 = ${T.ERF_A1};
|
|
let a2 = ${T.ERF_A2};
|
|
let a3 = ${T.ERF_A3};
|
|
let a4 = ${T.ERF_A4};
|
|
let a5 = ${T.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));
|
|
`,Gre="return exp(a);",Hre="return floor(a);",jre="return f32(!isnan(a) && !isinf(a));",qre="return f32(isinf(a));",Xre="return f32(isnan(a));",Kre="return a;",Zre=`if (a < 0.0) { return uniforms.NAN; }
|
|
return log(a);`,Yre=`
|
|
if (isnan(a)) { return a; }
|
|
return log(1.0 + a);
|
|
`,Jre="return f32(!(a >= 1.0));",Qre="return -a;",ese="if (a < 0.0) { return uniforms.alpha * a; } return a;",tse=`
|
|
let aLessThanZero = vec4<f32>(a < vec4<f32>(0.0));
|
|
return (aLessThanZero * (uniforms.alpha * a)) + ((vec4<f32>(1.0) - aLessThanZero) * a);
|
|
`,ase="return 1.0 / a;",nse="return select(a, 0.0, a < 0.0);",rse="return clamp(a, 0.0, 6.0);",sse="return clamp(a, vec4<f32>(0.0, 0.0, 0.0, 0.0), vec4<f32>(6.0, 6.0, 6.0, 6.0));",ise=`
|
|
return select(a, vec4<f32>(0.0), a < vec4<f32>(0.0));
|
|
`,ose="return round(a);",lse="return inverseSqrt(a);",use=`
|
|
if (a >= 0.0) {
|
|
return ${T.SELU_SCALE} * a;
|
|
} else {
|
|
return ${T.SELU_SCALEALPHA} * (exp(a) - 1.0);
|
|
}
|
|
`,dse="return 1.0 / (1.0 + exp(-1.0 * a));",pse="return sign(a);",cse="return sin(a);",hse=`
|
|
let e2x = exp(a);
|
|
return (e2x - 1.0 / e2x) / 2.0;
|
|
`,fse=`
|
|
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);
|
|
}
|
|
`,mse="return sqrt(a);",gse="return a * a;",yse=`
|
|
if (isnan(a)) {
|
|
return a;
|
|
}
|
|
|
|
return select(uniforms.stepAlpha, 1.0, a > 0.0);
|
|
`,xse="return tan(a);",Ase=`
|
|
let e2x = exp(-2.0 * abs(a));
|
|
return sign(a) * (1.0 - e2x) / (1.0 + e2x);
|
|
`,bse="return f32(i32((a)));";function $s(e,t){switch(e){case le.ABS:return Rre;case le.ACOS:return Mre;case le.ACOSH:return $re;case le.ASIN:return _re;case le.ASINH:return Pre;case le.ATAN:return Fre;case le.ATANH:return Ore;case le.COS:return zre;case le.COSH:return Lre;case le.CEIL:return Dre;case le.ELU:return t?Vre:Wre;case le.ERF:return Ure;case le.EXP:return Gre;case le.EXPM1:return Bre;case le.FLOOR:return Hre;case le.IS_FINITE:return jre;case le.IS_INF:return qre;case le.IS_NAN:return Xre;case le.LINEAR:return Kre;case le.LOG:return Zre;case le.LOG1P:return Yre;case le.LOGICAL_NOT:return Jre;case le.NEG:return Qre;case le.LEAKYRELU:return t?tse:ese;case le.RECIPROCAL:return ase;case le.RELU:return t?ise:nse;case le.RELU6:return t?sse:rse;case le.ROUND:return ose;case le.RSQRT:return lse;case le.SELU:return use;case le.SIGMOID:return dse;case le.SIGN:return pse;case le.SIN:return cse;case le.SINH:return hse;case le.SOFTPLUS:return fse;case le.SQRT:return mse;case le.SQUARE:return gse;case le.STEP:return yse;case le.TAN:return xse;case le.TANH:return Ase;case le.TO_INT:return bse;default:throw new Error(`BinaryType ${e} is not implemented!`)}}var $t=e=>{switch(e){case 1:return"f32";case 2:return"vec2<f32>";case 3:return"vec3<f32>";case 4:return"vec4<f32>";default:throw new Error(`${e}-component is not supported.`)}};function Cr(e,t=!1,a=!1,n=3){if(e===null)return"";let r="";if(e==="linear")r=$s(le.LINEAR);else if(e==="relu")r=$s(le.RELU,a);else if(e==="elu")r=$s(le.ELU,a);else if(e==="relu6")r=$s(le.RELU6,a);else if(e==="prelu")r=B3(Pe.PRELU,a);else if(e==="sigmoid")r=$s(le.SIGMOID,a);else if(e==="leakyrelu")r=$s(le.LEAKYRELU,a);else throw new Error(`Activation ${e} has not been implemented for the WebGPU backend.`);let s=$t(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 ko(e,t){return`
|
|
${e?"value = value + getBiasByOutputCoords(coords);":""}
|
|
${t?"value = activation(value, coords);":""}
|
|
`}function R8(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, colIn: i32) -> ${$t(s)} {
|
|
var value = ${$t(s)}(0.0);
|
|
let col = colIn * ${s};
|
|
${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, colIn: i32) -> ${$t(s)} {
|
|
let col = colIn * ${s};
|
|
var value = ${$t(s)}(0.0);
|
|
${o}
|
|
return value;
|
|
}
|
|
`}function W3(e,t,a,n,r=!1,s=!1,i=!1,o=1){return`
|
|
${R8(a,n,r,s,i,o)}
|
|
fn mm_write(batch: i32, row: i32, colIn: i32, valueIn: ${$t(o)}) {
|
|
let col = colIn * ${o};
|
|
${r&&s?"":"if (row < uniforms.dimAOuter && col < uniforms.dimBOuter)"}
|
|
{
|
|
var value = valueIn;
|
|
let coords = vec3<i32>(batch, row, col);
|
|
${ko(e,t)}
|
|
setOutputAtCoords(coords[0], coords[1], coords[2], value);
|
|
}
|
|
}
|
|
`}var vse=(e,t)=>e?`
|
|
mm_Asub[inputRow][inputCol] = mm_readA(batchA,
|
|
kStart + inputRow,
|
|
globalRowStart / ${t} + inputCol);
|
|
`:`
|
|
mm_Asub[inputRow][inputCol] = mm_readA(batchA,
|
|
globalRow + innerRow,
|
|
kStart / ${t} + inputCol);
|
|
`,kse=(e,t,a)=>e?`
|
|
let ACached0 = mm_Asub[k * ${t}][localRow];
|
|
let ACached1 = mm_Asub[k * ${t} + 1][localRow];
|
|
let ACached2 = mm_Asub[k * ${t} + 2][localRow];
|
|
${t===3?"":`let ACached3 = mm_Asub[k * ${t} + 3][localRow];`}
|
|
for (var i = 0; i < ${a}; i++) {
|
|
acc[i] = BCached0 * ACached0[i] + acc[i];
|
|
acc[i] = BCached1 * ACached1[i] + acc[i];
|
|
acc[i] = BCached2 * ACached2[i] + acc[i];
|
|
${t===3?"":"acc[i] = BCached3 * ACached3[i] + acc[i];"}
|
|
}`:`
|
|
for (var i = 0; i < ${a}; i++) {
|
|
let ACached = mm_Asub[tileRow + i][k];
|
|
acc[i] = BCached0 * ACached.x + acc[i];
|
|
acc[i] = BCached1 * ACached.y + acc[i];
|
|
acc[i] = BCached2 * ACached.z + acc[i];
|
|
${t===3?"":"acc[i] = BCached3 * ACached.w + acc[i];"}
|
|
}`;function zh(e,t,a=!1,n=32,r=!1,s=32,i=!1,o=!1){let l=t[1]*e[1],u=t[0]*e[0],p=a?l:n,c=a?n:l,d=p/t[0],h=n/t[1],f=e[1];return v.assert((a&&d===4&&e[1]===4||!a&&(d===3||d===4))&&p%t[0]===0&&n%t[1]===0&&e[0]===4,()=>`If transposeA ${a} is true, innerElementSize ${d} and workPerThread[1] ${e[1]} must be 4.
|
|
Otherwise, innerElementSize ${d} must be 3 or 4.
|
|
tileAWidth ${p} must be divisible by workgroupSize[0]${t[0]}. tileInner ${n} must be divisible by workgroupSize[1] ${t[1]}. colPerThread ${e[0]} must be 4.`),`
|
|
var<workgroup> mm_Asub : array<array<vec${d}<f32>, ${p/d}>, ${c}>;
|
|
var<workgroup> mm_Bsub : array<array<vec4<f32>, ${u/e[0]}>, ${n}>;
|
|
|
|
${ke()} {
|
|
let localRow = i32(localId.y);
|
|
let tileRow = ${i?"0":`localRow * ${f}`};
|
|
let tileCol = i32(localId.x);
|
|
|
|
let globalRow = ${i?"0":`i32(globalId.y) * ${f}`};
|
|
let globalCol = i32(globalId.x);
|
|
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 globalRowStart = i32(workgroupId.y) * ${l};
|
|
|
|
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>, ${f}>;
|
|
|
|
// Loop over shared dimension.
|
|
let tileRowB = localRow * ${h};
|
|
for (var t = 0; t < numTiles; t++) {
|
|
// Load one tile of A into local memory.
|
|
for (var innerRow = 0; innerRow < ${f}; innerRow++) {
|
|
let inputRow = tileRow + innerRow;
|
|
let inputCol = tileCol;
|
|
${vse(a,d)}
|
|
}
|
|
|
|
// Load one tile of B into local memory.
|
|
for (var innerRow = 0; innerRow < ${h}; 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.
|
|
for (var k = 0; k < ${n/d}; k++) {
|
|
let BCached0 = mm_Bsub[k * ${d}][tileCol];
|
|
let BCached1 = mm_Bsub[k * ${d} + 1][tileCol];
|
|
let BCached2 = mm_Bsub[k * ${d} + 2][tileCol];
|
|
${d===3?"":`let BCached3 = mm_Bsub[k * ${d} + 3][tileCol];`}
|
|
|
|
${kse(a,d,f)}
|
|
}
|
|
|
|
workgroupBarrier();
|
|
}
|
|
|
|
for (var innerRow = 0; innerRow < ${f}; innerRow++) {
|
|
mm_write(batch, globalRow + innerRow, globalCol, acc[innerRow]);
|
|
}
|
|
}`}var Gy=e=>e?`
|
|
mm_Asub[inputRow][inputCol] = mm_readA(batchA,
|
|
kStart + inputRow,
|
|
globalRowStart + inputCol);
|
|
`:`
|
|
mm_Asub[inputRow][inputCol] = mm_readA(batchA,
|
|
globalRowStart + inputRow,
|
|
kStart + inputCol);
|
|
`,wse=e=>e?"let ACached = mm_Asub[k][tileRow + innerRow];":"let ACached = mm_Asub[tileRow + innerRow][k];";function Lh(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],f=n/t[1],m=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]}) {
|
|
${Gy(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 < ${m}; 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] = acc[innerRow][innerCol] +
|
|
ACached * BCached[innerCol];
|
|
}
|
|
}
|
|
}
|
|
workgroupBarrier();
|
|
}
|
|
for (var innerRow = 0; innerRow < ${m}; 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) * ${m};
|
|
let tileCol = i32(localId.x) * ${g};
|
|
|
|
let globalRow = i32(globalId.y) * ${m};
|
|
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) * ${f};
|
|
// 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;
|
|
${Gy(a)}
|
|
}
|
|
}
|
|
|
|
// Load one tile of B into local memory.
|
|
for (var innerRow = 0; innerRow < ${f}; 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 < ${m}; innerRow++) {
|
|
${wse(a)}
|
|
for (var innerCol = 0; innerCol < ${g}; innerCol++) {
|
|
acc[innerRow][innerCol] = acc[innerRow][innerCol] + ACached * BCached[innerCol];
|
|
}
|
|
}
|
|
}
|
|
|
|
workgroupBarrier();
|
|
}
|
|
|
|
for (var innerRow = 0; innerRow < ${m}; 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}>;
|
|
|
|
${ke()} {
|
|
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}>, ${m}>;
|
|
|
|
// Without this initialization strange values show up in acc.
|
|
for (var innerRow = 0; innerRow < ${m}; innerRow++) {
|
|
for (var innerCol = 0; innerCol < ${g}; innerCol++) {
|
|
acc[innerRow][innerCol] = 0.0;
|
|
}
|
|
}
|
|
${y}
|
|
}
|
|
`}var Ise=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 Sse(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]}>;
|
|
|
|
${ke()} {
|
|
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 * ${a} + tileCol * 4;
|
|
mm_Asub[tileCol] = vec4<f32>(${Ise(t)});
|
|
workgroupBarrier();
|
|
|
|
// Compute acc values for a single thread.
|
|
for (var k = 0; k < ${a/4}; k++) {
|
|
let rowB = t * ${a} + k * 4;
|
|
let BCached = vec4<f32>(mm_readB(batchB, rowB, globalCol),
|
|
mm_readB(batchB, rowB + 1, globalCol),
|
|
mm_readB(batchB, rowB + 2, globalCol),
|
|
mm_readB(batchB, rowB + 3, globalCol));
|
|
|
|
let ACached = mm_Asub[k];
|
|
acc = acc + dot(ACached, BCached);
|
|
}
|
|
|
|
workgroupBarrier();
|
|
}
|
|
|
|
mm_write(batch, globalRow, globalCol, acc);
|
|
}
|
|
`}var Tse=class{constructor(e,t,a=!1,n=!1,r=null,s=null,i=null,o=!1){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.outputShape=t,this.dispatchLayout={x:[2],y:[1],z:[0]};let l=a?e[1]:e[2];if(this.isVec4=(l%4===0&&!a||t[1]%4===0&&a)&&t[2]%4===0&&!n,this.isVectorA=t[1]===1&&!a,!this.isVec4&&this.isVectorA)this.elementsPerThread=[1,1,1],this.workgroupSize=[32,1,1];else{let c=C8(t[1],l,t[2],a);this.workgroupSize=c.workgroupSize,this.elementsPerThread=c.elementsPerThread}this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize,this.elementsPerThread);let u=r!=null,p=i!=null;u&&this.variableNames.push("bias"),p&&this.variableNames.push("preluActivationWeights"),this.sequentialAccessByThreads=o,this.transposeA=a,this.transposeB=n,this.addBias=u,this.activation=s,this.hasPreluActivationWeights=p,[this.fitAOuter,this.fitBOuter,this.fitInner]=this.getShapeFit(t[1],t[2],l),this.shaderKey=`matMulPacked_${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`
|
|
${Cr(this.activation,this.hasPreluActivationWeights,this.isVec4)}
|
|
${W3(this.addBias,this.activation,!1,this.transposeB,this.fitAOuter,this.fitBOuter,this.fitInner,this.isVec4?4:1)}
|
|
${this.isVec4?zh(this.elementsPerThread,this.workgroupSize,this.transposeA,this.tileInner,!1,null,this.isVectorA,!0):this.isVectorA?Sse(this.workgroupSize,this.transposeA):Lh(this.elementsPerThread,this.workgroupSize,this.transposeA,this.tileInner,!1,null,this.sequentialAccessByThreads,!0)}
|
|
`}};function Cse(e){return`
|
|
var<workgroup> sumValues : array<f32, ${e}>;
|
|
${ke()} {
|
|
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 = ${e/2}u; currentSize > 1u;
|
|
currentSize = currentSize / 2u) {
|
|
if (localId.x < currentSize)
|
|
{
|
|
sumValues[localId.x] = sumValues[localId.x] + sumValues[localId.x + currentSize];
|
|
}
|
|
workgroupBarrier();
|
|
}
|
|
|
|
if (localId.x == 0u) {
|
|
sum = sumValues[0] + sumValues[1];
|
|
mm_write(batch, row, col, sum);
|
|
}
|
|
}
|
|
`}var Nse=class{constructor(e,t=!1,a=!1,n=null,r=null,s=null){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workgroupSize=[256,1,1],this.outputShape=e,this.dispatchLayout={x:[],y:[1,2],z:[0]},this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize);let i=n!=null,o=s!=null;i&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),this.transposeA=t,this.transposeB=a,this.addBias=i,this.activation=r,this.hasPreluActivationWeights=o,this.shaderKey=`matMulReduce_${this.activation}_${t}_${a}`}getUserCode(){return`
|
|
${Cr(this.activation,this.hasPreluActivationWeights)}
|
|
${W3(this.addBias,this.activation,this.transposeA,this.transposeB)}
|
|
${Cse(this.workgroupSize[0])}
|
|
`}};function Ese(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.
|
|
${ke()} {
|
|
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 < ${n}; k = k + 1) {
|
|
acc = acc + mm_Asub[tileRow][k] * mm_Bsub[k][tileCol];
|
|
}
|
|
workgroupBarrier();
|
|
}
|
|
|
|
mm_write(batch, globalRow, globalCol, acc);
|
|
}
|
|
`}var Rse=class{constructor(e,t,a,n=!1,r=!1,s=null,i=null,o=null){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workgroupSize=[16,8,1],this.outputShape=a,this.dispatchLayout={x:[2],y:[1],z:[0]},this.dispatch=[Math.ceil(a[2]/this.workgroupSize[0]),Math.ceil(a[1]/this.workgroupSize[1]),a[0]];let l=s!=null;l&&this.variableNames.push("bias");let u=o!=null;u&&this.variableNames.push("preluActivationWeights"),this.transposeA=n,this.transposeB=r,this.addBias=l,this.activation=i,this.hasPreluActivationWeights=u,this.shaderKey=`matMulSmallOutputSize_${this.activation}_${n}_${r}`}getUserCode(){return`
|
|
${Cr(this.activation,this.hasPreluActivationWeights)}
|
|
${W3(this.addBias,this.activation,this.transposeA,this.transposeB)}
|
|
${Ese(this.workgroupSize)}
|
|
`}},Mse=class{constructor(e,t,a=!1,n=!1){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workgroupSize=[8,8,1],this.atomic=!0,this.isVec4=!1,this.splitedDimInner=128,v.assert(e[0]===1,()=>"MatMulSplitKProgram only supports batch = 1."),this.outputShape=e,this.dispatchLayout={x:[2],y:[1],z:[0,3]},this.isVec4=(a&&this.outputShape[1]%4===0||!a&&t%4===0)&&this.outputShape[2]%4===0,this.elementsPerThread=[4,4,this.splitedDimInner],this.isVec4||(this.outputShape[1]<16&&(this.elementsPerThread[1]=1),this.outputShape[2]<16&&(this.elementsPerThread[0]=1)),this.dispatch=we(this.dispatchLayout,[this.outputShape[0],this.outputShape[1],this.outputShape[2],t],this.workgroupSize,this.elementsPerThread),this.transposeA=a,this.transposeB=n,this.shaderKey=`matMulSplitK_${a}_${n}_${this.elementsPerThread}_${this.isVec4}`}getUserCode(){let e=this.isVec4?4:1;return`
|
|
${R8(!1,this.transposeB,!1,!1,!1,e)}
|
|
fn mm_write(batch: i32, row : i32, colIn : i32, value : ${$t(e)}) {
|
|
let col = colIn * ${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) {
|
|
${O3("&result[flatIndex + i]",`${e>1?"value[i]":"value"}`,"float32")}
|
|
}
|
|
}
|
|
}
|
|
${this.isVec4?zh(this.elementsPerThread,this.workgroupSize,this.transposeA,32,!0,this.splitedDimInner):Lh(this.elementsPerThread,this.workgroupSize,this.transposeA,32,!0,this.splitedDimInner)}
|
|
`}},$se=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=$e(this.outputShape),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize),this.addBias=t!=null,this.hasPreluActivationWeights=n!=null,this.activation=a,this.addBias&&this.variableNames.push("bias"),this.hasPreluActivationWeights&&this.variableNames.push("preluActivationWeights"),this.shaderKey=`biasActivation_${a}`}getUserCode(){return`
|
|
${Cr(this.activation,this.hasPreluActivationWeights)}
|
|
${ke("index")} {
|
|
if (index < uniforms.size) {
|
|
let coords = getCoordsFromIndex(index);
|
|
var value = getXByOutputIndex(index);
|
|
${ko(this.addBias,this.activation)}
|
|
setOutputAtIndex(index, value);
|
|
}
|
|
}
|
|
`}},_se=class{constructor(e){this.variableNames=[],this.outputShape=[],this.uniforms="value : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=$e(this.outputShape),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="fill"}getUserCode(){return`
|
|
${ke("index")} {
|
|
if (index < uniforms.size) {
|
|
setOutputAtIndex(index, uniforms.value);
|
|
}
|
|
}
|
|
`}};function Nr(e){let{backend:t,attrs:a}=e,{shape:n,value:r}=a,{dtype:s}=a;if(s=s||v.inferDtype(r),s==="string"){let i=v.getArrayFromDType(s,v.sizeFromShape(n));return i.fill(r),t.makeTensorInfo(n,s,i)}else{let i=new _se(n),o=[{type:"float32",data:[r]}];return t.runWebGPUProgram(i,[],s,o)}}var Pse={kernelName:Pl,backendName:"webgpu",kernelFunc:Nr};function Ie(e){let{inputs:t,attrs:a}=e,{x:n}=t,{shape:r}=a,s=v.sizeFromShape(n.shape),i=v.inferFromImplicitShape(r,s),o=v.sizeFromShape(i);return v.assert(s===o,()=>`The new shape (${i}) has ${o} elements and the old shape (${n.shape}) has ${s} elements. The new shape and old shape must have the same number of elements.`),e.backend.incRef(n.dataId),{dataId:n.dataId,shape:i,dtype:n.dtype}}var Fse={kernelName:Hl,backendName:"webgpu",kernelFunc:Ie};function Bh({a:e,b:t,transposeA:a,transposeB:n,backend:r,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:o=0,activation:l=null}){let u=e.shape.length,p=t.shape.length,c=a?e.shape[u-2]:e.shape[u-1],d=n?t.shape[p-1]:t.shape[p-2],h=a?e.shape[u-1]:e.shape[u-2],f=n?t.shape[p-2]:t.shape[p-1],m=e.shape.slice(0,-2),g=t.shape.slice(0,-2),y=v.sizeFromShape(m),x=v.sizeFromShape(g),A=xo.assertAndGetBroadcastShape(e.shape.slice(0,-2),t.shape.slice(0,-2)).concat([h,f]);v.assert(c===d,()=>`Error in matMul: inner shapes (${c}) and (${d}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${a} and transposeB=${n} must match.`);let b=a?[y,c,h]:[y,h,c],k=n?[x,f,d]:[x,d,f],S=Ie({inputs:{x:e},backend:r,attrs:{shape:b}}),C=Ie({inputs:{x:t},backend:r,attrs:{shape:k}}),N=[S,C],$=Math.max(y,x),M=[S,C],R=[{type:"int32",data:[h]},{type:"int32",data:[f]},{type:"int32",data:[c]}],I,_,D=[$,h,f],W=V().get("WEBGPU_MATMUL_PROGRAM_TYPE");if(W<0){let U=V().getNumber("WEBGPU_THRESHOLD_TO_INCREASE_WORKGROUPS_FOR_MATMUL"),G=U>0?U:r.thresholdToIncreaseWorkgroups,q=$*Math.ceil(h/32)*Math.ceil(f/32);q<=G||h<=8&&q<=G*2?$*h*f<=128?W=Pn.MatMulReduceProgram:$===1&&d>=2e3?W=Pn.MatMulSplitKProgram:W=Pn.MatMulSmallOutputSizeProgram:W=Pn.MatMulPackedProgram}switch(W){case Pn.MatMulReduceProgram:I=new Nse(D,a,n,s,l,i);break;case Pn.MatMulSplitKProgram:{if(_=Nr({backend:r,attrs:{shape:D,value:0,dtype:e.dtype}}),I=new Mse(D,d,a,n),s||l){_=r.runWebGPUProgram(I,M,e.dtype,R,_);let G=new $se(_.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 B=r.runWebGPUProgram(G,H,_.dtype,q);N.push(_);let Z=Ie({inputs:{x:B},backend:r,attrs:{shape:A}});N.push(B);for(let X of N)r.disposeData(X.dataId);return Z}break}case Pn.MatMulSmallOutputSizeProgram:I=new Rse(b,k,D,a,n,s,l,i);break;case Pn.MatMulPackedProgram:let U=r.adapterInfo.isIntel();I=new Tse(b,D,a,n,s,l,i,U);break;default:throw new Error(`Unsupported MatMulProgramType ${W}.`)}s&&M.push(s),i&&M.push(i),l==="leakyrelu"&&(R.push({type:"float32",data:[o]}),I.uniforms+=" alpha : f32,"),_=r.runWebGPUProgram(I,M,e.dtype,R,_);let P=Ie({inputs:{x:_},backend:r,attrs:{shape:A}});N.push(_);for(let U of N)r.disposeData(U.dataId);return P}function Ose(e){let{inputs:t,backend:a,attrs:n}=e,{a:r,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:u,activation:p,leakyreluAlpha:c}=n;return Bh({a:r,b:s,transposeA:l,transposeB:u,backend:a,bias:i,preluActivationWeights:o,leakyreluAlpha:c,activation:p})}var Dse={kernelName:Hr,backendName:"webgpu",kernelFunc:Ose},Hy=class{constructor(e,t,a){this.variableNames=["AReal","AImag","BReal","BImag"],this.workgroupSize=[128,1,1],this.size=!0,this.outputShape=T.assertAndGetBroadcastShape(t,a),this.dispatchLayout=$e(this.outputShape),this.dispatch=we(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 {
|
|
${B3(this.op,!1)}
|
|
}
|
|
|
|
${ke("index")} {
|
|
if(index < uniforms.size) {
|
|
let areal = getARealByOutputIndex(index);
|
|
let aimag = getAImagByOutputIndex(index);
|
|
let breal = getBRealByOutputIndex(index);
|
|
let bimag = getBImagByOutputIndex(index);
|
|
setOutputAtIndex(index, binaryOpComplex(areal, aimag, breal, bimag));
|
|
}
|
|
}
|
|
`}},M2=class{constructor(e,t,a){this.size=!0,this.variableNames=["A","B"],this.outputShape=T.assertAndGetBroadcastShape(t,a),this.dispatchLayout=$e(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.isVec4=!1,this.lastDimensionSize=this.useSharedMemoryWithB?a[0]:t[0],this.shaderKey=`binary_${this.type}_${e}_${this.lastDimensionSize}_${this.useSharedMemoryWithB}`,this.type="shared",this.workgroupSize=[256,1,1],this.workPerThread=1):(v.arraysEqual(t,a)&&v.sizeFromShape(t)%4===0?(this.isVec4=!0,this.type="vec4",this.workPerThread=4):(this.isVec4=!1,this.type="plain",this.workPerThread=1),this.shaderKey=`binary_${this.type}_${e}`,this.workgroupSize=[128,1,1]),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1])}getUserCode(){let e,t=this.isVec4?"vec4<f32>":"f32",a=`
|
|
fn binaryOperation(a : ${t}, b : ${t}) -> ${t} {
|
|
let isNaN = false;
|
|
{
|
|
${B3(this.op,this.isVec4)}
|
|
}
|
|
};
|
|
`;if(this.type==="shared"){let n=this.lastDimensionSize>1?`coords[${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}>;
|
|
${ke("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}
|
|
${ke("index")} {
|
|
if (index < uniforms.size) {
|
|
let a = getAByOutputIndex(index);
|
|
let b = getBByOutputIndex(index);
|
|
setOutputAtIndex(index, binaryOperation(a, b));
|
|
}
|
|
}
|
|
`;return e}};function Qa(e){let{inputs:t}=e,{x:a}=t;return e.backend.incRef(a.dataId),{dataId:a.dataId,shape:a.shape,dtype:a.dtype}}var zse={kernelName:wi,backendName:"webgpu",kernelFunc:Qa};function wo(e){let{inputs:t,backend:a}=e,{real:n,imag:r}=t,s=a.makeTensorInfo(n.shape,"complex64"),i=a.tensorMap.get(s.dataId),o=Qa({inputs:{x:n},backend:a}),l=Qa({inputs:{x:r},backend:a});return i.complexTensorInfos={real:o,imag:l},s}var Lse={kernelName:Td,backendName:"webgpu",kernelFunc:wo},xu=class{constructor(e,t,a=""){this.variableNames=["A"],this.size=!0;let n=128;this.workgroupSize=[n,1,1],this.outputShape=e,this.dispatchLayout=$e(this.outputShape),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize),this.op=t,a!==""&&(this.uniforms=a),this.shaderKey=`unary_${t}`}getUserCode(){return`
|
|
fn unaryOperation(a : f32) -> f32 {
|
|
${$s(this.op,!1)}
|
|
}
|
|
${ke("index")} {
|
|
if (index < uniforms.size) {
|
|
let a = getAByOutputIndex(index);
|
|
setOutputAtIndex(index, unaryOperation(a));
|
|
}
|
|
}
|
|
`}};function et({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 xu(s.shape,e);return i.runWebGPUProgram(l,[s],o)}}function Jt({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,f;if(e!==Pe.MUL)[h,f]=[[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},k=new M2(e,i.shape,o.shape);return l.runWebGPUProgram(k,[A,b],fa(y.dtype,x.dtype))});else{let g=new Hy(Pe.COMPLEX_MULTIPLY_REAL,i.shape,o.shape),y=new Hy(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"),f=l.runWebGPUProgram(y,x,"float32")}let m=wo({inputs:{real:h,imag:f},backend:l});return l.disposeData(h.dataId),l.disposeData(f.dataId),m}let u=n||fa(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"?T.fromUint8ToStringArray(c):c,f=i.dtype==="string"?T.fromUint8ToStringArray(d):d,[m,g]=t(i.shape,o.shape,h,f,u);return l.makeTensorInfo(g,u,m)}let p=new M2(e,i.shape,o.shape);return l.runWebGPUProgram(p,[i,o],u)}}var{addImpl:Bse,castImpl:Wse,ceilImpl:Vse,concatImpl:Use,equalImpl:Gse,expImpl:Hse,expm1Impl:jse,floorImpl:qse,gatherNdImpl:Xse,gatherV2Impl:Kse,greaterEqualImpl:Zse,greaterImpl:Yse,lessEqualImpl:Jse,lessImpl:Qse,logImpl:eie,maxImpl:tie,maximumImpl:aie,minimumImpl:nie,multiplyImpl:rie,negImpl:sie,notEqualImpl:iie,prodImpl:oie,rangeImpl:lie,rsqrtImpl:uie,scatterImpl:die,simpleAbsImpl:pie,sliceImpl:cie,stridedSliceImpl:hie,stringNGramsImpl:fie,subImpl:mie,tileImpl:gie,topKImpl:yie,transposeImpl:xie,uniqueImpl:cfe}=Ch,Aie=et({opType:le.ABS,cpuKernelImpl:pie}),bie={kernelName:vl,backendName:"webgpu",kernelFunc:Aie},vie=et({opType:le.ACOS}),kie={kernelName:kl,backendName:"webgpu",kernelFunc:vie},wie=et({opType:le.ACOSH}),Iie={kernelName:wl,backendName:"webgpu",kernelFunc:wie},Sie=Jt({opType:Pe.ADD,cpuKernelImpl:Bse,supportsComplex:!0}),Tie={kernelName:ts,backendName:"webgpu",kernelFunc:Sie},Cie=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=$e(this.outputShape),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1]),this.shaderKey="addN"}getUserCode(){let e=[];this.variableNames.forEach(a=>{e.push(`let v${a} = get${a}ByOutputCoords(coords);`)});let t=this.variableNames.map(a=>`v${a}`).join(" + ");return`
|
|
${ke("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 Nie(e){let{inputs:t,backend:a}=e,n=t;if(n.length===1)return Qa({inputs:{x:n[0]},backend:a});let r=n.map(o=>o.dtype).reduce((o,l)=>fa(o,l)),s=n.map(o=>o.shape),i=new Cie(s);return a.runWebGPUProgram(i,n,r)}var Eie={kernelName:Ks,backendName:"webgpu",kernelFunc:Nie},Rie=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=we(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]}>;
|
|
${ke()} {
|
|
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) * ${e} + i32(localId.y);
|
|
if (x < height && y < width) {
|
|
setOutputAtIndex((y * height + x), tile[localId.x]
|
|
[localId.y]);
|
|
}
|
|
}
|
|
`}},Mie=class{constructor(e,t){this.variableNames=["A"],this.workPerThread=1,this.workgroupSize=[64,1,1],this.size=!0;let a=new Array(e.length);for(let n=0;n<a.length;n++)a[n]=e[t[n]];this.outputShape=a,this.dispatchLayout=$e(this.outputShape),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1]),this.newDim=t,this.shaderKey=`transpose_${t}`}getUserCode(){let e=oa(this.outputShape.length),t=$ie(this.newDim);return`
|
|
${ke("index")} {
|
|
for(var i = 0; i < ${this.workPerThread}; i = i + 1) {
|
|
let flatIndex = index * ${this.workPerThread} + i;
|
|
if(flatIndex < uniforms.size) {
|
|
let resRC = getCoordsFromIndex(flatIndex);
|
|
setOutputAtIndex(flatIndex, A[getIndexFromCoords${this.outputShape.length}D(
|
|
${e}(${t}), uniforms.aShape)]);
|
|
}
|
|
}
|
|
}
|
|
`}};function $ie(e){let t=e.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let a=new Array(t);for(let n=0;n<e.length;n++)a[e[n]]=`resRC.${br(n)}`;return a.join()}function kr(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=xie(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 Rie(r.shape,s);return i.runWebGPUProgram(p,[r],r.dtype)}let u=new Mie(r.shape,s);return i.runWebGPUProgram(u,[r],r.dtype)}var _ie={kernelName:Ar,backendName:"webgpu",kernelFunc:kr},Pie=class{constructor(e,t){this.workgroupSize=[64,1,1],this.variableNames=["x"],this.uniforms="reduceSize : i32,",this.size=!0,this.inputShape=[e.batchSize,e.inSize];let[a]=T.computeOutAndReduceShapes(this.inputShape,[1]);this.outputShape=a.length===0?[1]:a,this.dispatchLayout=$e(this.outputShape),this.dispatch=we(this.dispatchLayout,this.outputShape,[1,1,1]),this.reduceType=t,this.shaderKey=`reduce_${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;
|
|
}
|
|
${ke("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) {
|
|
${n}
|
|
}
|
|
}
|
|
`}};function Io(e,t,a,n,r){let s=e.shape.length,i=[],o=v.parseAxisParam(t,e.shape),l=o,u=T.getAxesPermutation(l,s),p=e;u!=null&&(p=kr({inputs:{x:e},attrs:{perm:u},backend:r}),l=T.getInnerMostAxes(l.length,s),i.push(p)),T.assertAxesAreInnerMostDims(n,l,s);let[c,d]=T.computeOutAndReduceShapes(p.shape,l),h=c;a&&(h=T.expandShapeToKeepDim(c,o));let f;if((n==="max"||n==="prod")&&r.shouldExecuteOnCPU([p])){let m=r.tensorMap.get(p.dataId).values;switch(n){case"max":let g=tie(m,v.sizeFromShape(d),h,e.dtype);f=r.makeTensorInfo(h,e.dtype,g);break;case"prod":let{outVals:y,outShape:x,outDtype:A}=oie(p.shape,p.dtype,m,l);f=r.makeTensorInfo(x,A,y);break;default:throw new Error(`${n} CPU implementation is not yet supported.`)}}else{let m=v.sizeFromShape(d),g=v.sizeFromShape(p.shape)/m,y={windowSize:m,inSize:m,batchSize:g,outSize:1},x=n==="mean"?"float32":Xd(e.dtype),A=[{type:"int32",data:[m]}],b=new Pie(y,n),k=r.runWebGPUProgram(b,[p],x,A);i.push(k),f=Ie({inputs:{x:k},attrs:{shape:h},backend:r})}return i.forEach(m=>r.disposeData(m.dataId)),f}function Fie(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{keepDims:s,axis:i}=n;return Io(r,i,s,"all",a)}var Oie={kernelName:Zs,backendName:"webgpu",kernelFunc:Fie};function Die(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{keepDims:s,axis:i}=n;return Io(r,i,s,"any",a)}var zie={kernelName:Ys,backendName:"webgpu",kernelFunc:Die},M8=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]=T.computeOutAndReduceShapes(e,n);this.outputShape=r.length===0?[1]:r,this.dispatchLayout=$e(this.outputShape),v.sizeFromShape(s)<32||v.sizeFromShape(r)>1e3?(this.type="plain",this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize)):(this.type="shared",this.dispatch=we(this.dispatchLayout,this.outputShape,[1,1,1])),this.inputShape=e,this.shaderKey=`argMinMax_${this.op}_${this.type}`}getUserCode(){let e=this.workgroupSize[0],t=()=>this.inputShape.length===1?"uniforms.xShape":`uniforms.xShape.${br(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.${br(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}>;
|
|
`}
|
|
|
|
${ke("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]);
|
|
}
|
|
}
|
|
`:`
|
|
${ke("index")} {
|
|
if (index < uniforms.size) {
|
|
let outputCoords = getCoordsFromIndex(index);
|
|
var bestIndex = 0;
|
|
var bestValue = getX(${a()} 0);
|
|
let reduceLength = ${t()};
|
|
for (var i = 1; i < reduceLength; i++) {
|
|
let candidate = getX(${a()} i);
|
|
if (candidate ${this.op} bestValue) {
|
|
bestValue = candidate;
|
|
bestIndex = i;
|
|
}
|
|
}
|
|
setOutputAtIndexI32(index, bestIndex);
|
|
}
|
|
}
|
|
`}};function Lie(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s}=n,i=v.parseAxisParam(s,r.shape),o=T.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=kr({inputs:{x:r},backend:a,attrs:{perm:o}}),u.push(l),i=T.getInnerMostAxes(i.length,l.shape.length)),T.assertAxesAreInnerMostDims("argMax",[i[0]],l.shape.length);let p=new M8(l.shape,i[0],"max"),c=[{type:"float32",data:[Number.NEGATIVE_INFINITY]}],d=a.runWebGPUProgram(p,[l],"int32",c);return u.forEach(h=>a.disposeData(h.dataId)),d}var Bie={kernelName:Js,backendName:"webgpu",kernelFunc:Lie};function Wie(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s}=n,i=v.parseAxisParam(s,r.shape),o=T.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=kr({inputs:{x:r},backend:a,attrs:{perm:o}}),u.push(l),i=T.getInnerMostAxes(i.length,l.shape.length)),T.assertAxesAreInnerMostDims("argMin",[i[0]],l.shape.length);let p=new M8(l.shape,i[0],"min"),c=[{type:"float32",data:[Number.POSITIVE_INFINITY]}],d=a.runWebGPUProgram(p,[l],"int32",c);return u.forEach(h=>a.disposeData(h.dataId)),d}var Vie={kernelName:Id,backendName:"webgpu",kernelFunc:Wie},Uie=et({opType:le.ASIN}),Gie={kernelName:Il,backendName:"webgpu",kernelFunc:Uie},Hie=et({opType:le.ASINH}),jie={kernelName:Sl,backendName:"webgpu",kernelFunc:Hie},qie=et({opType:le.ATAN}),Xie={kernelName:Tl,backendName:"webgpu",kernelFunc:qie},Kie=Jt({opType:Pe.ATAN2}),Zie={kernelName:Nl,backendName:"webgpu",kernelFunc:Kie},Yie=et({opType:le.ATANH}),Jie={kernelName:Cl,backendName:"webgpu",kernelFunc:Yie},jy=class{constructor(e,t){this.variableNames=["x"],this.uniforms="stride : vec2<i32>, pad : vec2<i32>, dilation : vec2<i32>, convDims : vec2<i32>, filterDims : vec2<i32>,",this.workgroupSize=[128,1,1],this.size=!0,this.outputShape=e.outShape,this.dispatchLayout=$e(this.outputShape),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey=`pool2D_${t}`,this.poolType=t}getUserCode(){let e="resultValue = max(value, resultValue);";this.poolType==="avg"&&(e="resultValue = resultValue + value; count = count + 1.0;");let t="resultValue";return this.poolType==="avg"&&(t="resultValue / max(count, 1.0)"),`
|
|
${ke("index")} {
|
|
if (index < uniforms.size) {
|
|
let coords = getCoordsFromIndex(index);
|
|
let batch = coords[0];
|
|
let xRCCorner = vec2<i32>(coords.yz) * uniforms.stride - uniforms.pad;
|
|
let xRCorner = xRCCorner.x;
|
|
let xCCorner = xRCCorner.y;
|
|
|
|
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.dilation.x) {
|
|
let xR = xRCorner + wR;
|
|
|
|
if (xR < 0 || xR >= uniforms.convDims.x) {
|
|
continue;
|
|
}
|
|
|
|
for (var wC = 0; wC < uniforms.filterDims.y; wC = wC + uniforms.dilation.y) {
|
|
let xC = xCCorner + wC;
|
|
if (xC < 0 || xC >= uniforms.convDims.y) {
|
|
continue;
|
|
}
|
|
|
|
let value = getX(batch, xR, xC, coords[3]);
|
|
${e}
|
|
}
|
|
}
|
|
|
|
setOutputAtIndex(index, ${t});
|
|
}
|
|
}
|
|
`}},Qie=class{constructor(e){this.variableNames=["x"],this.uniforms="stride : vec2<i32>,",this.workgroupSize=[256,1,1],this.size=!0,this.outputShape=e.outShape,this.dispatchLayout=$e(this.outputShape),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="poolWithFilterSizeEqualsOne"}getUserCode(){return`
|
|
${ke("index")} {
|
|
if (index < uniforms.size) {
|
|
let coords = getCoordsFromIndex(index);
|
|
let batch = coords[0];
|
|
let d = coords[3];
|
|
|
|
let xRCCorner = coords.yz * uniforms.stride;
|
|
let xRCorner = xRCCorner.x;
|
|
let xCCorner = xRCCorner.y;
|
|
|
|
let value = getX(batch, xRCorner, xCCorner, d);
|
|
setOutputAtIndex(index, value);
|
|
}
|
|
}
|
|
`}};function V3(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{reductionIndices:s,keepDims:i}=n;return Io(r,s,i,"max",a)}var eoe={kernelName:$i,backendName:"webgpu",kernelFunc:V3};function $8(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{keepDims:s,axis:i}=n;return Io(r,i,s,"mean",a)}var toe={kernelName:Fi,backendName:"webgpu",kernelFunc:$8};function _8(e,t,a,n){if(t.filterWidth===1&&t.filterHeight===1&&v.arraysEqual(t.inShape,t.outShape))return Qa({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=Ie({inputs:{x:e},backend:n,attrs:{shape:[e.shape[i-3]*e.shape[i-2],e.shape[i-1]]}}),l;a==="avg"?l=$8({inputs:{x:o},backend:n,attrs:{axis:0,keepDims:!1}}):(v.assert(a==="max",()=>`Invalid pool type ${a}`),l=V3({inputs:{x:o},backend:n,attrs:{reductionIndices:0,keepDims:!1}}));let u=Ie({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 Qie(t):(a==="avg"?r=new jy(t,"avg"):(v.assert(a==="max",()=>`Invalid pool type ${a}`),r=new jy(t,"max")),s.push({type:"int32",data:[t.padInfo.top,t.padInfo.left]},{type:"int32",data:[t.dilationHeight,t.dilationWidth]},{type:"int32",data:[t.inHeight,t.inWidth]},{type:"int32",data:[t.effectiveFilterHeight,t.effectiveFilterWidth]})),n.runWebGPUProgram(r,[e],e.dtype,s)}function aoe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=n,u=1,p=T.computePool2DInfo(r.shape,s,i,u,o,l);return _8(r,p,"avg",a)}var noe={kernelName:Qs,backendName:"webgpu",kernelFunc:aoe},roe=class{constructor(e){this.variableNames=["dy"],this.uniforms=`stride : vec2<i32>, pads : vec2<i32>, dilation : vec2<i32>, filterDims : vec2<i32>,
|
|
outHeight : i32, outWidth : i32, avgMultiplier : f32,`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.inShape,this.dispatchLayout=$e(this.outputShape),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="avg_pool2d_backprop"}getUserCode(){return`
|
|
${ke("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.dilation[0]) {
|
|
let dyR = f32(dyRCorner + wR) / f32(uniforms.stride[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.dilation[1]) {
|
|
let dyC = f32(dyCCorner + wC) / f32(uniforms.stride[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);
|
|
}
|
|
}
|
|
`}};function soe(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,i=s;N8([r,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:u}=n,p=T.computePool2DInfo(i.shape,o,l,1,u),c=new roe(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 ioe={kernelName:Xc,backendName:"webgpu",kernelFunc:soe};function ooe(e){let{inputs:t,backend:a,attrs:n}=e,{a:r,b:s}=t,{transposeA:i,transposeB:o}=n;return Bh({a:r,b:s,transposeA:i,transposeB:o,backend:a})}var loe={kernelName:ei,backendName:"webgpu",kernelFunc:ooe},uoe=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=$e(this.outputShape),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1]),this.start=e,this.uniforms=`start : ${oa(e.length)}, `,this.shaderKey="slice"}getUserCode(){let e=oa(this.rank),t=doe(this.rank),a;return this.start.length===1?a=this.outputShape.map((n,r)=>"sourceLoc = uniforms.start + coords;"):a=this.outputShape.map((n,r)=>`sourceLoc.${$2[r]} = uniforms.start.${br(r)} + coords.${$2[r]};`),`
|
|
${ke("index")} {
|
|
if (index < uniforms.size) {
|
|
var sourceLoc : ${e};
|
|
let coords = getCoordsFromIndex(index);
|
|
${a.join(`
|
|
`)}
|
|
setOutputAtIndex(index, getSource(${t}));
|
|
}
|
|
}
|
|
`}},$2=["x","y","z","w","u","v"];function doe(e){if(e===1)return"sourceLoc";if(e<=6)return $2.slice(0,e).map(t=>`sourceLoc.${t}`).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}function Au(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{begin:s,size:i}=n,[o,l]=St.parseSliceParams(r,s,i);if(St.assertParamsValid(r,o,l),a.shouldExecuteOnCPU([r])||r.dtype==="string"){let c=a.tensorMap.get(r.dataId),d=cie(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 uoe(o,l),p=[{type:"int32",data:o}];return a.runWebGPUProgram(u,[r],r.dtype,p)}var poe={kernelName:Xl,backendName:"webgpu",kernelFunc:Au},coe=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=T.getReshaped(r.shape,s,o),u=T.getPermuted(l.length,s.length),p=T.getReshapedPermuted(r.shape,s,o),c=T.getSliceBeginCoords(i,s.length),d=T.getSliceSize(p,i,s.length),h=[],f=Ie({inputs:{x:r},backend:a,attrs:{shape:l}}),m=kr({inputs:{x:f},backend:a,attrs:{perm:u}}),g=Ie({inputs:{x:m},backend:a,attrs:{shape:p}}),y=Au({inputs:{x:g},backend:a,attrs:{begin:c,size:d}});return h.push(f),h.push(m),h.push(g),h.forEach(x=>a.disposeData(x.dataId)),y},hoe={kernelName:El,backendName:"webgpu",kernelFunc:coe},foe=`
|
|
fn bincount_write(index: i32, value: f32) {
|
|
${O3("&result[index]","value","float32")}
|
|
}
|
|
`,moe=`
|
|
fn bincount_write(index: i32, value: f32) {
|
|
atomicStore(&result[index], bitcast<i32>(value));
|
|
}
|
|
`,P8=class{constructor(e,t,a=!1){this.outputShape=[],this.variableNames=["x"],this.uniforms="binCountSize : i32,",this.workgroupSize=[64,1,1],this.atomic=!0,this.hasWeights=!0,this.binaryOutput=!1,this.outputShape=e,this.rank=e.length,this.dispatchLayout=$e(this.outputShape),this.dispatch=we(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?moe:foe}
|
|
${ke("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 goe(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=Nr({backend:a,attrs:{shape:u,value:0,dtype:p}}),d=new P8([o],l),h=[{type:"int32",data:[i]}],f=l?[r,s]:[r];return a.runWebGPUProgram(d,f,p,h,c)}var yoe={kernelName:Sd,backendName:"webgpu",kernelFunc:goe},F8=Jt({opType:Pe.NOT_EQUAL,dtype:"bool",cpuKernelImpl:iie}),xoe={kernelName:Bi,backendName:"webgpu",kernelFunc:F8};function yp(e){let{inputs:t,backend:a}=e,{input:n}=t,r=a.tensorMap.get(n.dataId);return Qa({inputs:{x:r.complexTensorInfos.real},backend:a})}var Aoe={kernelName:Dd,backendName:"webgpu",kernelFunc:yp};function boe(e,t){let a=new xu(e.shape,le.TO_INT),n=t.runWebGPUProgram(a,[e],"int32");return{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}function _2(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{dtype:s}=n;if(s==="complex64"){if(r.dtype==="complex64")return Qa({inputs:{x:r},backend:a});let i=gn(r.shape),o=_2({inputs:{x:r},backend:a,attrs:{dtype:"float32"}}),l=wo({inputs:{real:o,imag:i},backend:a});return i.dispose(),a.disposeData(o.dataId),l}if(r.dtype==="complex64"){let i=yp({inputs:{input:r},backend:a}),o=_2({inputs:{x:i},backend:a,attrs:{dtype:s}});return a.disposeData(i.dataId),o}if(!v.hasEncodingLoss(r.dtype,s)){let i=Qa({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]=Wse(i,r.shape,r.dtype,s);return a.makeTensorInfo(o,l,u)}if(s==="int32")return boe(r,a);if(s==="bool"){let i=a.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),o=F8({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 ${s}`)}var voe={kernelName:ti,backendName:"webgpu",kernelFunc:_2},koe=et({opType:le.CEIL,cpuKernelImpl:Vse}),woe={kernelName:ai,backendName:"webgpu",kernelFunc:koe},Ioe=class{constructor(e){this.variableNames=["A"],this.uniforms="minVal : f32, maxVal : f32,",this.workPerThread=4,this.workgroupSize=[64,1,1],this.isVec4=!0,this.size=!0,this.outputShape=e,this.dispatchLayout=$e(this.outputShape),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1]),this.shaderKey="clipVec4"}getUserCode(){return`
|
|
${ke("index")} {
|
|
if(index < uniforms.size) {
|
|
let value = getAByOutputIndex(index);
|
|
var clampedValue = clamp(
|
|
value, vec4<f32>(uniforms.minVal), vec4<f32>(uniforms.maxVal));
|
|
clampedValue = select(clampedValue, value, isnanVec4(value));
|
|
setOutputAtIndex(index, clampedValue);
|
|
}
|
|
}
|
|
`}},Soe=class{constructor(e){this.variableNames=["A"],this.uniforms="minVal : f32, maxVal : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=$e(this.outputShape),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="clip"}getUserCode(){return`
|
|
${ke("index")} {
|
|
if(index < uniforms.size) {
|
|
let value = getAByOutputIndex(index);
|
|
if (isnan(value)) {
|
|
setOutputAtIndex(index, value);
|
|
return;
|
|
}
|
|
setOutputAtIndex(index, clamp(value, uniforms.minVal, uniforms.maxVal));
|
|
}
|
|
}
|
|
`}};function Toe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{clipValueMin:s,clipValueMax:i}=n,o,l=[{type:"float32",data:[s]},{type:"float32",data:[i]}];return v.sizeFromShape(r.shape)%4===0?o=new Ioe(r.shape):o=new Soe(r.shape),a.runWebGPUProgram(o,[r],r.dtype,l)}var Coe={kernelName:as,backendName:"webgpu",kernelFunc:Toe},Noe=class{constructor(e){this.uniforms="",this.workPerThread=1,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=T.computeOutShape(e,1),this.variableNames=e.map((t,a)=>`T${a}`),this.dispatchLayout=$e(this.outputShape),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1]),this.offsetLength=e.length-1;for(let t=0;t<this.offsetLength;t++)this.uniforms+=`offset${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`
|
|
${ke("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 Wh(e){let{inputs:t,backend:a}=e,{input:n}=t,r=a.tensorMap.get(n.dataId);return Qa({inputs:{x:r.complexTensorInfos.imag},backend:a})}var Eoe={kernelName:Pd,backendName:"webgpu",kernelFunc:Wh};function Yu(e,t,a){let n=e[0].dtype;if(n==="complex64"){let f=e.map(A=>yp({inputs:{input:A},backend:a})),m=e.map(A=>Wh({inputs:{input:A},backend:a})),g=Yu(f,t,a),y=Yu(m,t,a),x=wo({inputs:{real:g,imag:y},backend:a});return f.forEach(A=>a.disposeData(A.dataId)),m.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 f=e.map(k=>{let S=[-1,v.sizeFromShape(k.shape.slice(t))];return Ie({inputs:{x:k},backend:a,attrs:{shape:S}})}),m=f.map(k=>({vals:a.readSync(k.dataId),shape:k.shape})),g=T.computeOutShape(f.map(k=>k.shape),1),y=f[0].shape[0]===1,x=Use(m,g,n,y),A=T.computeOutShape(e.map(k=>k.shape),t),b=a.makeTensorInfo(A,n,x);return f.forEach(k=>a.disposeData(k.dataId)),b}let s=a.device.limits.maxStorageBuffersPerShaderStage-1;if(e.length>s){let f=[];for(let g=0;g<e.length;g+=s){let y=e.slice(g,g+s);f.push(Yu(y,t,a))}let m=Yu(f,t,a);for(let g of f)a.disposeData(g.dataId);return m}let{tensors2D:i,outShape:o}=Roe(e,t,a),l=i.map(f=>f.shape),u=new Noe(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 f=1;f<c.length;f++)c[f]=c[f-1]+l[f][1],p.push({type:"int32",data:[c[f]]})}let d=a.runWebGPUProgram(u,i,i[0].dtype,p);i.forEach(f=>a.disposeData(f.dataId));let h=Ie({inputs:{x:d},backend:a,attrs:{shape:o}});return a.disposeData(d.dataId),h}function Roe(e,t,a){let n=T.computeOutShape(e.map(r=>r.shape),t);return{tensors2D:e.map(r=>Ie({inputs:{x:r},backend:a,attrs:{shape:[v.sizeFromShape(r.shape.slice(0,t)),v.sizeFromShape(r.shape.slice(t))]}})),outShape:n}}function O8(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);T.assertParamsConsistent(i,s);let o=T.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?Qa({inputs:{x:l[0]},backend:a}):Yu(l,s,a)}var Moe={kernelName:Rl,backendName:"webgpu",kernelFunc:O8};function $oe(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 = x[xIndex];";case 3:return"resData = vec3<f32>(x[xIndex], x[xIndex + 1], x[xIndex + 2]);";case 4:return"resData = x[xIndex / 4];";default:throw new Error(`innerElementSize ${N} is not supported.`)}},c=N=>{switch(N){case 1:return"return W[row * uniforms.wShape[3] + colIn];";case 4:return"return W[row * uniforms.wShape[3] / 4 + colIn];";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);
|
|
`,f=e?"uniforms.xShape[1]":"uniforms.xShape[2]",m=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.stride[0] + uniforms.dilation[0] * WRow - uniforms.pad[0];
|
|
let xCol = outCol * uniforms.stride[1] + uniforms.dilation[1] * WCol - uniforms.pad[1];
|
|
let xCh = ${y} % inChannels;
|
|
var resData = ${$t(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 < ${f} && xCol >= 0 && xCol < ${m}) {
|
|
${d}
|
|
let xIndex = getIndexFromCoords4D(coord, uniforms.xShape);
|
|
${p(o)}
|
|
}
|
|
return resData;`,A=e?t&&n?`
|
|
let col = colIn * ${o};
|
|
${x}`:`
|
|
let col = colIn * ${o};
|
|
if (row < uniforms.dimAOuter && col < uniforms.dimInner) {
|
|
${x}
|
|
}
|
|
return ${$t(o)}(0.0);`:n&&a?`
|
|
let col = colIn * ${o};
|
|
${x}`:`
|
|
let col = colIn * ${o};
|
|
if (row < uniforms.dimInner && col < uniforms.dimBOuter) {
|
|
${x}
|
|
}
|
|
return ${$t(o)}(0.0);`,b=`${c(l)}`,k=$t(u),S=$t(e?o:l),C=$t(e?l:o);return`
|
|
${Cr(s,i,u===4,4)}
|
|
fn mm_readA(batch: i32, row : i32, colIn : i32) -> ${S} {
|
|
${e?A:b}
|
|
}
|
|
|
|
fn mm_readB(batch: i32, row : i32, colIn : i32) -> ${C} {
|
|
${e?b:A}
|
|
}
|
|
|
|
fn mm_write(batch: i32, row : i32, colIn : i32, valueIn : ${k}) {
|
|
let col = colIn * ${u};
|
|
if (row < uniforms.dimAOuter && col < uniforms.dimBOuter)
|
|
{
|
|
var value = valueIn;
|
|
let outWidth = ${e?"uniforms.outShape[2]":"uniforms.outShape[3]"};
|
|
${h}
|
|
${ko(r,s)}
|
|
setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
|
|
}
|
|
}`}var _oe=class{constructor(e,t,a,n,r=!1,s=null,i=!1,o=!1){this.variableNames=["x","W"],this.uniforms="filterDims : vec2<i32>, pad : vec2<i32>, stride : vec2<i32>, dilation : vec2<i32>, dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.outputShape=e.outShape,this.isChannelsLast=e.dataFormat==="channelsLast",this.isVec4=((e.inChannels%4===0||e.inChannels%3===0)&&this.isChannelsLast||e.outWidth%4===0&&!this.isChannelsLast)&&e.outChannels%4===0,this.dispatchLayout=this.isChannelsLast?{x:[3],y:[1,2],z:[0]}:{x:[2,3],y:[1],z:[0]},this.workgroupSize=D3(this.dispatchLayout,this.outputShape,this.isVec4),this.elementsPerThread=z3(this.dispatchLayout,this.outputShape,this.isVec4),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize,this.elementsPerThread),this.isVec4?(this.isChannelsLast&&e.inChannels%4!==0?(this.innerElementSize=3,this.variableTypes=["f32","vec4<f32>"]):(this.innerElementSize=4,this.variableTypes=["vec4<f32>","vec4<f32>"]),r&&(this.variableNames.push("bias"),this.variableTypes.push("vec4<f32>")),i&&(this.variableNames.push("preluActivationWeights"),this.variableTypes.push("vec4<f32>"))):(this.innerElementSize=this.elementsPerThread[0],r&&this.variableNames.push("bias"),i&&this.variableNames.push("preluActivationWeights")),this.sequentialAccessByThreads=o,this.addBias=r,this.activation=s,this.hasPreluActivationWeights=i,this.tileAOuter=this.workgroupSize[1]*this.elementsPerThread[1],this.tileBOuter=this.workgroupSize[0]*this.elementsPerThread[0],this.tileInner=Math.max(this.workgroupSize[0]*this.innerElementSize,this.workgroupSize[1]),this.fitAOuter=t%this.tileAOuter===0,this.fitBOuter=a%this.tileBOuter===0,this.fitInner=n%this.tileInner===0,this.shaderKey=`conv2DMM_${this.elementsPerThread}_${this.activation}}_${this.fitAOuter}_${this.fitBOuter}_${this.fitInner}_${this.isVec4}_${this.innerElementSize}_${this.isChannelsLast}_${this.sequentialAccessByThreads}`}getUserCode(){let e=this.isVec4?zh(this.elementsPerThread,this.workgroupSize,!this.isChannelsLast,this.tileInner):Lh(this.elementsPerThread,this.workgroupSize,!this.isChannelsLast,this.tileInner,!1,null,this.sequentialAccessByThreads),t=this.isVec4?[this.innerElementSize,4,4]:[1,1,1];return`
|
|
${$oe(this.isChannelsLast,this.fitAOuter,this.fitBOuter,this.fitInner,this.addBias,this.activation,this.hasPreluActivationWeights,t[0],t[1],t[2])}
|
|
${e}
|
|
`}},Poe=class{constructor(e,t=!1,a=null,n=!1){this.variableNames=["x","W"],this.uniforms="filterDims: vec2<i32>, pad: vec2<i32>, stride: vec2<i32>, dilation: vec2<i32>,",this.workgroupSize=[4,4,8],this.outputShape=e.outShape,this.isChannelsLast=e.dataFormat==="channelsLast",this.dispatchLayout=this.isChannelsLast?{x:[2],y:[1],z:[0,3]}:{x:[3],y:[2],z:[0,1]},this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize),this.addBias=t,this.activation=a,this.hasPreluActivationWeights=n,t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),this.shaderKey=`conv2dnaive_${this.activation}_${this.isChannelsLast}`}getUserCode(){return`
|
|
${Cr(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;
|
|
${ko(this.addBias,this.activation)}
|
|
setOutputAtCoords(coords.x, coords.y, coords.z, coords.w, value);
|
|
}
|
|
}
|
|
${ke("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.stride[0] + uniforms.dilation[0] * row - uniforms.pad[0];
|
|
let xCol = outCol * uniforms.stride[1] + uniforms.dilation[1] * col - uniforms.pad[1];
|
|
for (var xChannel = 0; xChannel < ${this.isChannelsLast?"uniforms.xShape[3];":"uniforms.xShape[1];"} xChannel = xChannel + 1) {
|
|
${this.isChannelsLast?"let v = readInp(batch, xRow, xCol, xChannel);":"let v = readInp(batch, xChannel, xRow, xCol);"}
|
|
let f = readFilt(row, col, xChannel, outChannel);
|
|
acc = acc + v * f;
|
|
}
|
|
}
|
|
}
|
|
writeResult(batch, outRow, outCol, outChannel, acc);
|
|
}
|
|
`}},Foe=class{constructor(e,t){this.variableNames=["x"],this.uniforms=`pad : vec2<i32>, stride : vec2<i32>, dilation : vec2<i32>, outWidth : i32, itemsPerBlockRow : i32,
|
|
inChannels : i32,`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=$e(this.outputShape),this.dispatch=we(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`
|
|
${ke("index")} {
|
|
let coords = getCoordsFromIndex(index);
|
|
if(index < uniforms.size) {
|
|
let batch = coords[0];
|
|
let row = ${a};
|
|
let col = ${n};
|
|
let offsetY = (row / uniforms.outWidth) * uniforms.stride[0] - uniforms.pad[0];
|
|
let xRow = offsetY + uniforms.dilation[0] * (col / uniforms.itemsPerBlockRow);
|
|
var value = 0.0;
|
|
if(xRow < uniforms.xShape[${e}] && xRow >= 0) {
|
|
let offsetX = (row % uniforms.outWidth) * uniforms.stride[1] -
|
|
uniforms.pad[1];
|
|
let xCol = offsetX + uniforms.dilation[1] * ((col %
|
|
uniforms.itemsPerBlockRow) / uniforms.inChannels);
|
|
let ch = col % uniforms.inChannels;
|
|
if(xCol < uniforms.xShape[${t}] && xCol >= 0) {
|
|
value = ${r};
|
|
}
|
|
}
|
|
setOutputAtIndex(index, value);
|
|
}
|
|
}
|
|
`}};function Uc(e,t){let a=e.length;return a>=3?t?[...e.slice(0,-3),e[a-3]*e[a-2],e[a-1]]:[...e.slice(0,-3),e[a-3],e[a-2]*e[a-1]]:!t&&a===1&&e[0]>1?[e[0],1]:null}function Ooe({x:e,filter:t,convInfo:a,backend:n,bias:r=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let l=a.dataFormat==="channelsLast",u=!l,p=!1,c=l&&a.filterHeight===a.inHeight&&a.filterWidth===a.inWidth&&a.padInfo.type==="VALID",d=[],h,f;if(c){let y=a.inHeight*a.inWidth*a.inChannels;h=Ie({inputs:{x:e},backend:n,attrs:{shape:[1,a.batchSize,y]}}),f=Ie({inputs:{x:t},backend:n,attrs:{shape:[1,y,a.outChannels]}})}else h=Ie({inputs:{x:e},backend:n,attrs:{shape:l?[a.batchSize,a.inHeight*a.inWidth,a.inChannels]:[a.batchSize,a.inChannels,a.inHeight*a.inWidth]}}),f=Ie({inputs:{x:t},backend:n,attrs:{shape:[1,a.inChannels,a.outChannels]}});if(d.push(h),d.push(f),s!=null){let y=Uc(s.shape,l);y!=null&&(s=Ie({inputs:{x:s},backend:n,attrs:{shape:y}}),d.push(s))}if(r!=null){let y=Uc(r.shape,l);y!=null&&(r=Ie({inputs:{x:r},backend:n,attrs:{shape:y}}),d.push(r))}let m=Bh({a:l?h:f,b:l?f:h,transposeA:u,transposeB:p,backend:n,bias:r,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),g=Ie({inputs:{x:m},backend:n,attrs:{shape:a.outShape}});d.push(m);for(let y of d)n.disposeData(y.dataId);return g}function Doe({x:e,filter:t,convInfo:a,backend:n,bias:r=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let{filterWidth:l,filterHeight:u,inChannels:p,strideWidth:c,strideHeight:d,padInfo:h,outWidth:f,outHeight:m,dilationWidth:g,dilationHeight:y,dataFormat:x}=a,A=x==="channelsLast",b=l*u*p,k=m*f,S=A?[a.batchSize,k,b]:[a.batchSize,b,k],C=new Foe(S,A),N=[{type:"int32",data:[h.top,h.left]},{type:"int32",data:[d,c]},{type:"int32",data:[y,g]},{type:"int32",data:[f]},{type:"int32",data:[p*l]},{type:"int32",data:[p]}],$=n.runWebGPUProgram(C,[e],e.dtype,N),M=[];M.push($);let R=Ie({inputs:{x:t},backend:n,attrs:{shape:[1,b,-1]}});if(M.push(R),s!=null){let D=Uc(s.shape,A);D!=null&&(s=Ie({inputs:{x:s},backend:n,attrs:{shape:D}}),M.push(s))}if(r!=null){let D=Uc(r.shape,A);D!=null&&(r=Ie({inputs:{x:r},backend:n,attrs:{shape:D}}),M.push(r))}let I=Bh({a:A?$:R,b:A?R:$,transposeA:!A,transposeB:!1,backend:n,bias:r,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),_=Ie({inputs:{x:I},backend:n,attrs:{shape:a.outShape}});M.push(I);for(let D of M)n.disposeData(D.dataId);return _}function D8({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=V().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 Ooe({x:e,filter:t,convInfo:a,backend:n,bias:r,activation:o,preluActivationWeights:s,leakyreluAlpha:i});let h=V().getNumber("WEBGPU_THRESHOLD_TO_INCREASE_WORKGROUPS_FOR_MATMUL"),f=h>0?h:n.thresholdToIncreaseWorkgroups,m=a.batchSize*Math.ceil(a.outHeight*a.outWidth/32)*Math.ceil(a.outChannels/32);if(V().getBool("WEBGPU_CONV_SEPARATE_IM2COL_SHADER")||m<=f)return Doe({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 Poe(a,l,o,u);else{let S=p?a.outHeight*a.outWidth:a.outChannels,C=p?a.outChannels:a.outHeight*a.outWidth,N=a.filterHeight*a.filterWidth*a.inChannels;x.push({type:"int32",data:[S]},{type:"int32",data:[C]},{type:"int32",data:[N]});let $=n.adapterInfo.isIntel();g=new _oe(a,S,C,N,l,o,u,$)}let A=[],b=[e,t];l&&(!p&&r.shape.length===1&&(r=Ie({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=Ie({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 k=n.runWebGPUProgram(g,b,e.dtype,x);for(let S of A)n.disposeData(S.dataId);return k}function zoe(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=T.convertConv2DDataFormat(l),d=T.computeConv2DInfo(r.shape,s.shape,i,u,o,p,!1,c);return D8({x:r,filter:s,convInfo:d,backend:n})}var Loe={kernelName:ni,backendName:"webgpu",kernelFunc:zoe},Boe=class{constructor(e){this.variableNames=["dy","W"],this.uniforms="filterDims : vec2<i32>, pads : vec2<i32>, stride : vec2<i32>, outBackprop : vec4<i32>,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.inShape,this.dispatchLayout=$e(this.outputShape),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize),this.isChannelsLast=e.dataFormat==="channelsLast",this.shaderKey=`conv2DDerInput_${this.isChannelsLast}`}getUserCode(){let e=this.isChannelsLast?1:2,t=this.isChannelsLast?2:3,a=this.isChannelsLast?3:1;return`
|
|
${ke("index")} {
|
|
if(index < uniforms.size) {
|
|
let coords = getCoordsFromIndex(index);
|
|
let batch = coords[0];
|
|
let d1 = coords[${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.stride.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.stride.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) {
|
|
if (${this.isChannelsLast}) {
|
|
let xValue = getDy(batch, idyR, idyC, d2);
|
|
let wValue = getW(wRPerm, wCPerm, d1, d2);
|
|
dotProd = dotProd + xValue * wValue;
|
|
} else {
|
|
let xValue = getDy(batch, d2, idyR, idyC);
|
|
let wValue = getW(wRPerm, wCPerm, d1, d2);
|
|
dotProd = dotProd + xValue * wValue;
|
|
}
|
|
|
|
}
|
|
}
|
|
}
|
|
setOutputAtIndex(index, dotProd);
|
|
}
|
|
}
|
|
`}},Woe=class{constructor(e){this.variableNames=["x","dy"],this.uniforms="pad : vec2<i32>, stride : vec2<i32>, batchSize : i32, outHeight : i32, outWidth : i32, inHeight : i32, inWidth : i32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.filterShape,this.dispatchLayout=$e(this.outputShape),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize),this.isChannelsLast=e.dataFormat==="channelsLast",this.shaderKey=`conv2DDerFilter_${this.isChannelsLast}`}getUserCode(){return`
|
|
${ke("index")} {
|
|
if(index < uniforms.size) {
|
|
let coords = getCoordsFromIndex(index);
|
|
let wR = coords[0];
|
|
let wC = coords[1];
|
|
let d1 = coords[2];
|
|
let d2 = coords[3];
|
|
|
|
// Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2).
|
|
// ? = to be determined. : = across all values in that axis.
|
|
var dotProd = 0.0;
|
|
for (var b = 0; b < uniforms.batchSize; b = b + 1) {
|
|
for (var yR = 0; yR < uniforms.outHeight; yR = yR + 1) {
|
|
let xR = wR + yR * uniforms.stride[0] - uniforms.pad[0];
|
|
if (xR < 0 || xR >= uniforms.inHeight) {
|
|
continue;
|
|
}
|
|
|
|
for (var yC = 0; yC < uniforms.outWidth; yC = yC + 1) {
|
|
let xC = wC + yC * uniforms.stride[1] - uniforms.pad[1];
|
|
|
|
if (xC < 0 || xC >= uniforms.inWidth) {
|
|
continue;
|
|
}
|
|
|
|
if (${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);
|
|
}
|
|
}
|
|
`}};function Voe(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=T.convertConv2DDataFormat(l),d=T.computeConv2DInfo(r.shape,p,i,1,o,u,!1,c),h=new Woe(d),f=[{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,f)}var Uoe={kernelName:Cd,backendName:"webgpu",kernelFunc:Voe};function Goe(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.stride[0]);
|
|
let xC = f32(outCol - uniforms.pads[1] + WCol) / f32(uniforms.stride[1]);
|
|
if (xR < 0.0 || xR >= f32(uniforms.outBackprop[1]) || fract(xR) > 0.0) {
|
|
return ${$t(e)}(0.0);
|
|
}
|
|
if (xC < 0.0 || xC >= f32(uniforms.outBackprop[2]) || fract(xC) > 0.0) {
|
|
return ${$t(e)}(0.0);
|
|
}
|
|
let coord = vec4<i32>(
|
|
batch,
|
|
i32(xR),
|
|
i32(xC),
|
|
col % uniforms.outBackprop[3]);
|
|
return x[getIndexFromCoords4D(coord, uniforms.xShape)/${e}];`}
|
|
}
|
|
return ${$t(e)}(0.0);`;return`
|
|
fn mm_readA(batch: i32, row : i32, colIn : i32) -> ${$t(e)} {
|
|
let col = colIn * ${e};
|
|
${a}
|
|
}
|
|
|
|
fn mm_readB(batch: i32, row : i32, colIn : i32) -> ${$t(e)} {
|
|
let col = colIn * ${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 ${$t(e)}(0.0);
|
|
}
|
|
|
|
fn mm_write(batch: i32, row : i32, colIn : i32, valueInput : ${$t(e)}) {
|
|
let col = colIn * ${e};
|
|
if (row < uniforms.dimAOuter && (col + ${e-1}) < uniforms.dimBOuter) {
|
|
var value = valueInput;
|
|
let outCoord = vec4<i32>(
|
|
batch,
|
|
row / uniforms.outShape[2],
|
|
row % uniforms.outShape[2],
|
|
col);
|
|
result[getIndexFromCoords4D(outCoord, uniforms.outShape)/${e}] = value;
|
|
}
|
|
}`}var Hoe=class{constructor(e){this.variableNames=["x","W"],this.uniforms="filterDims : vec2<i32>, pads : vec2<i32>, stride : 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=D3(this.dispatchLayout,this.outputShape,this.isVec4),this.elementsPerThread=z3(this.dispatchLayout,this.outputShape,this.isVec4),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize,this.elementsPerThread),this.isVec4&&(this.variableTypes=["vec4<f32>","f32"]),this.shaderKey=`conv2DDerInputMM_${this.isVec4}_${this.elementsPerThread}`}getUserCode(){let e=this.isVec4?zh(this.elementsPerThread,this.workgroupSize):Lh(this.elementsPerThread,this.workgroupSize);return`
|
|
${Goe(this.isVec4?4:1)}
|
|
${e}
|
|
`}};function joe(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:u,dimRoundingMode:p}=n,c=T.convertConv2DDataFormat(u),d=T.computeConv2DInfo(i,s.shape,o,1,l,p,!1,c),h=[{type:"int32",data:[d.filterHeight,d.filterWidth]},{type:"int32",data:[d.filterHeight-1-d.padInfo.top,d.filterWidth-1-d.padInfo.left]},{type:"int32",data:[d.strideHeight,d.strideWidth]},{type:"int32",data:[d.batchSize,d.outHeight,d.outWidth,d.outChannels]}],f;if(V().getBool("WEBGPU_USE_NAIVE_CONV2D_TRANSPOSE")||d.filterHeight<=2&&d.filterWidth<=2&&d.outChannels<=16&&d.inChannels===1)f=new Boe(d);else{f=new Hoe(d);let m=d.inHeight*d.inWidth,g=d.inChannels,y=d.filterHeight*d.filterWidth*d.outChannels;h.push({type:"uint32",data:[m]},{type:"uint32",data:[g]},{type:"uint32",data:[y]})}return a.runWebGPUProgram(f,[r,s],"float32",h)}var qoe={kernelName:ri,backendName:"webgpu",kernelFunc:joe},Xoe=et({opType:le.COS}),Koe={kernelName:si,backendName:"webgpu",kernelFunc:Xoe},Zoe=et({opType:le.COSH}),Yoe={kernelName:ii,backendName:"webgpu",kernelFunc:Zoe},Joe=class{constructor(e,t,a,n){this.variableNames=["Image","Boxes","BoxInd"],this.uniforms="extrapolationValue : f32,",this.workgroupSize=[64,1,1],this.size=!0;let[r]=t;this.outputShape=[r,a[0],a[1],e],this.dispatchLayout=$e(this.outputShape),this.dispatch=we(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`
|
|
${ke("index")} {
|
|
if (index < uniforms.size) {
|
|
let coords = getCoordsFromIndex(index);
|
|
let height_ratio = f32(${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);
|
|
}
|
|
}
|
|
}
|
|
`}},Qoe=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 Joe(r.shape[3],s.shape,o,l),c=[{type:"float32",data:[u]}];return a.runWebGPUProgram(p,[r,s,i],"float32",c)},ele={kernelName:ui,backendName:"webgpu",kernelFunc:Qoe},vd;(function(e){e.Prod="*",e.Sum="+"})(vd||(vd={}));var qy=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=$e(this.outputShape),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize),this.exclusive=a,this.reverse=n,this.op=e,this.shaderKey=`cum_${this.op}_${this.exclusive}_${this.reverse}`}getUserCode(){let e=this.outputShape.length,t=this.op===vd.Prod?"1.0":"0.0",a=this.exclusive?t:`getX(${Xy(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"),`
|
|
${ke("index")} {
|
|
if (index < uniforms.size) {
|
|
var coords = getCoordsFromIndex(index);
|
|
|
|
let end = ${Ky(e,"coords",this.op)};
|
|
var val = ${a};
|
|
let pow2 = i32(pow(2.0, uniforms.index));
|
|
if (${r}) {
|
|
let idx = ${s};
|
|
${Ky(e,"coords",this.op)} = idx;
|
|
val ${this.op}= getX(${Xy(e,"coords",this.op)});
|
|
}
|
|
setOutputAtIndex(index, val);
|
|
}
|
|
}
|
|
`}};function Xy(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 ${e} is not yet supported`)}function Ky(e,t,a){if(e===1)return`${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 ${e} is not yet supported`)}function z8(e,t,a,n,r,s){let i=t.shape.length,o=T.getAxesPermutation([n],i),l=t;o!=null&&(l=kr({inputs:{x:t},backend:a,attrs:{perm:o}}));let u=T.getInnerMostAxes(1,i)[0];if(u!==i-1)throw new Error(`WebGPU cumprod shader expects an inner-most axis=${t.shape.length-1} but got axis=${n}`);let p=l.shape[u],c=Qa({inputs:{x:l},backend:a});for(let d=0;d<=Math.ceil(Math.log2(p))-1;d++){let h=new qy(e,l.shape,!1,s),f=c,m=[{type:"float32",data:[d]}];c=a.runWebGPUProgram(h,[c],c.dtype,m),a.disposeData(f.dataId)}if(r){let d=new qy(e,l.shape,r,s),h=c,f=[{type:"float32",data:[0]}];c=a.runWebGPUProgram(d,[c],c.dtype,f),a.disposeData(h.dataId)}if(o!=null){let d=T.getUndoAxesPermutation(o),h=kr({inputs:{x:c},backend:a,attrs:{perm:d}});return a.disposeData(c.dataId),a.disposeData(l.dataId),h}return c}function tle(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=n;return z8(vd.Prod,r,a,s,i,o)}var ale={kernelName:oi,backendName:"webgpu",kernelFunc:tle};function nle(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=n;return z8(vd.Sum,r,a,s,i,o)}var rle={kernelName:li,backendName:"webgpu",kernelFunc:nle};function sle(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,weights:s}=t,{size:i,binaryOutput:o}=n,l=r.shape.length===1,u=v.sizeFromShape(s.shape)>0,p=s.dtype,c=l?[r.shape[0]]:[r.shape[0],r.shape[1]],d=l?[i]:[r.shape[0],i],h=Nr({backend:a,attrs:{shape:d,value:0,dtype:p}}),f=new P8(c,u,o),m=[{type:"int32",data:[i]}],g=u?[r,s]:[r];return a.runWebGPUProgram(f,g,p,m,h)}var ile={kernelName:Nd,backendName:"webgpu",kernelFunc:sle},ole=class{constructor(e,t){this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.uniforms="blockSize : i32,",this.outputShape=e,this.dispatchLayout=$e(this.outputShape),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey=`depthToSpace_${t}`,this.dataFormat=t}getUserCode(){return`
|
|
${ke("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 = ${this.getInputSamplingString()};
|
|
setOutputAtIndex(index, rlt);
|
|
}
|
|
}`}getHeightCoordString(){return this.dataFormat==="NHWC"?"coords[1]":"coords[2]"}getWidthCoordString(){return this.dataFormat==="NHWC"?"coords[2]":"coords[3]"}getDepthCoordString(){return this.dataFormat==="NHWC"?"coords[3]":"coords[1]"}getOutputDepthSize(){return this.dataFormat==="NHWC"?"uniforms.outShape[3]":"uniforms.outShape[1]"}getInputSamplingString(){return this.dataFormat==="NHWC"?"getX(b, in_h, in_w, in_d)":"getX(b, in_d, in_h, in_w)"}};function lle(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockSize:s,dataFormat:i}=n,o=r.shape[0],l=i==="NHWC"?r.shape[1]:r.shape[2],u=i==="NHWC"?r.shape[2]:r.shape[3],p=i==="NHWC"?r.shape[3]:r.shape[1],c=l*s,d=u*s,h=p/(s*s),f=i==="NHWC"?[o,c,d,h]:[o,h,c,d],m=[{type:"int32",data:[s]}],g=new ole(f,i);return a.runWebGPUProgram(g,[r],r.dtype,m)}var ule={kernelName:di,backendName:"webgpu",kernelFunc:lle},dle=class{constructor(e,t,a,n=!1,r=null,s=!1){this.variableNames=["x","W"],this.uniforms="pad : vec2<i32>, inDims : vec2<i32>,",this.workgroupSize=[16,16,1],this.outputShape=e,this.dispatchLayout={x:[3],y:[2],z:[0,1]},this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize),n&&this.variableNames.push("bias"),s&&this.variableNames.push("preluActivationWeights"),this.addBias=n,this.activation=r,this.hasPreluActivation=s,this.filterHeight=t,this.filterWidth=a,this.shaderKey=`depthwiseNCHW_${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`
|
|
${Cr(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;
|
|
}
|
|
|
|
${ke()} {
|
|
let coords = getOutputCoords();
|
|
let batch = coords[0];
|
|
let xRCCorner = vec2<i32>(coords.zw) - uniforms.pad;
|
|
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);
|
|
}
|
|
}
|
|
${ko(this.addBias,this.activation)}
|
|
if (coordsInBounds4D(coords, uniforms.outShape)) {
|
|
setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
|
|
}
|
|
}
|
|
`}},L8=class{constructor(e,t=!1,a=null,n=!1){this.variableNames=["x","W"],this.uniforms="pad : vec2<i32>, inDims : vec2<i32>,",this.workgroupSize=[4,4,4],this.workPerThread=4,this.isVec4=!0,this.outputShape=e.outShape,this.dispatchLayout={x:[3],y:[2],z:[0,1]},this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize,[4,this.workPerThread,1]),v.assert(e.dataFormat==="channelsLast",()=>"TODO: NCHW is unimplemented"),t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),this.convInfo=e,this.addBias=t,this.activation=a,this.hasPreluActivation=n,this.shaderKey=`depthwiseVec4_${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`
|
|
${Cr(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;
|
|
}
|
|
|
|
${ke()} {
|
|
let batch = i32(globalId.z) / uniforms.outShape[1];
|
|
let r = i32(globalId.z) % uniforms.outShape[1];
|
|
let c = i32(globalId.y) * ${this.workPerThread};
|
|
let d1 = i32(globalId.x) * 4;
|
|
let xRCCorner = vec2<i32>(r, c) * vec2<i32>(${t}, ${a}) - uniforms.pad;
|
|
|
|
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];
|
|
${ko(this.addBias,this.activation)}
|
|
setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
|
|
}
|
|
}
|
|
}
|
|
`}},B8=class{constructor(e,t=!1,a=null,n=!1){this.variableNames=["x","W"],this.uniforms=`pad : vec2<i32>, inDims : vec2<i32>, filterHeight : i32,
|
|
filterWidth : i32, stride : vec2<i32>, dilation : vec2<i32>,`,this.workgroupSize=[256,1,1],this.size=!0,this.outputShape=e.outShape,this.dispatchLayout=$e(this.outputShape),this.dispatch=we(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`
|
|
${Cr(this.activation,this.hasPreluActivation,!1,4)}
|
|
|
|
${ke("index")} {
|
|
if (index < uniforms.size) {
|
|
let coords = getOutputCoords();
|
|
let batch = coords[0];
|
|
let xRCCorner = vec2<i32>(coords.${this.isChannelsLast?"yz":"zw"}) * uniforms.stride - uniforms.pad;
|
|
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.dilation[0];
|
|
let inputColEnd = inputColStart + uniforms.filterWidth *
|
|
uniforms.dilation[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.dilation[0];
|
|
|
|
for (var wC = 0; wC < uniforms.filterWidth; wC = wC + 1) {
|
|
let xC = inputColStart + wC * uniforms.dilation[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.dilation[0];
|
|
|
|
if (xR < 0 || xR >= uniforms.inDims[0]) {
|
|
continue;
|
|
}
|
|
|
|
for (var wC = 0; wC < uniforms.filterWidth; wC = wC + 1) {
|
|
let xC = inputColStart + wC * uniforms.dilation[1];
|
|
|
|
if (xC < 0 || xC >= uniforms.inDims[1]) {
|
|
continue;
|
|
}
|
|
|
|
let xVal = ${e};
|
|
let wVal = getW(wR, wC, d1, q);
|
|
value = value + xVal * wVal;
|
|
}
|
|
}
|
|
}
|
|
${ko(this.addBias,this.activation)}
|
|
setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
|
|
}
|
|
}
|
|
`}};function ple(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:u,dimRoundingMode:p}=n,c=T.convertConv2DDataFormat(l),d=u;d==null&&(d=[1,1]);let h=T.computeConv2DInfo(r.shape,s.shape,i,d,o,p,!0,c),f=[{type:"int32",data:[h.padInfo.top,h.padInfo.left]},{type:"int32",data:[h.inHeight,h.inWidth]}],m=h.dataFormat==="channelsLast",g;return!m&&h.inHeight>16&&h.inWidth>16&&h.strideHeight===1&&h.strideWidth===1&&h.dilationWidth===1&&h.dilationHeight===1&&h.inChannels===h.outChannels?g=new dle(h.outShape,h.filterHeight,h.filterWidth):m&&h.outHeight>4&&h.outWidth>4&&h.strideWidth<=2&&h.inChannels===h.outChannels&&h.dilationHeight===1&&h.dilationWidth===1&&h.inChannels%4===0?g=new L8(h):(g=new B8(h),f.push({type:"int32",data:[h.filterHeight]},{type:"int32",data:[h.filterWidth]},{type:"int32",data:[h.strideHeight,h.strideWidth]},{type:"int32",data:[h.dilationHeight,h.dilationWidth]})),a.runWebGPUProgram(g,[r,s],r.dtype,f)}var cle={kernelName:pi,backendName:"webgpu",kernelFunc:ple},hle=class{constructor(e){this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=[e,e],this.dispatchLayout=$e(this.outputShape),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="diag"}getUserCode(){return`
|
|
${ke("index")} {
|
|
if (index < uniforms.size) {
|
|
let coords = getOutputCoords();
|
|
let value = select(0.0, getX(coords[0]), coords[0] == coords[1]);
|
|
setOutputAtIndex(index, value);
|
|
}
|
|
}
|
|
`}};function fle(e){let{inputs:t,backend:a}=e,{x:n}=t,r=[...n.shape,...n.shape],s=v.sizeFromShape(n.shape),i=Ie({inputs:{x:n},backend:a,attrs:{shape:[s]}}),o=new hle(s),l=a.runWebGPUProgram(o,[i],i.dtype),u=Ie({inputs:{x:l},backend:a,attrs:{shape:r}});return a.disposeData(i.dataId),a.disposeData(l.dataId),u}var mle={kernelName:Ed,backendName:"webgpu",kernelFunc:fle},gle=class{constructor(e){this.variableNames=["x","w"],this.uniforms="filterDims: vec2<i32>, pad: vec2<i32>, stride: vec2<i32>, dilation: vec2<i32>",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.outShape,this.dispatchLayout=$e(this.outputShape),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="dilation2d"}getUserCode(){return`
|
|
${ke("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.stride - uniforms.pad;
|
|
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.dilation[0];
|
|
|
|
if (hIn >= 0 && hIn < uniforms.xShape[1]) {
|
|
for (var w = 0; w < uniforms.filterDims[1]; w = w + 1) {
|
|
let wIn = wBeg + w * uniforms.dilation[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 yle(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=n,u=T.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 gle(u);return a.runWebGPUProgram(d,[r,s],r.dtype,c)}var xle={kernelName:Rd,backendName:"webgpu",kernelFunc:yle},W8=Jt({opType:Pe.MUL,cpuKernelImpl:rie,supportsComplex:!0}),Ale={kernelName:Li,backendName:"webgpu",kernelFunc:W8};function U3(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;return Io(r,s,i,"sum",a)}var ble={kernelName:io,backendName:"webgpu",kernelFunc:U3};function vle(e){let{inputs:t,backend:a,attrs:n}=e,{equation:r}=n,s=t,{allDims:i,summedDims:o,idDims:l}=T.decodeEinsumEquation(r,s.length);T.checkEinsumDimSizes(i.length,l,s);let{path:u,steps:p}=T.getEinsumComputePath(o,l),c=p.length,d=null,h=i.length,f=[];for(let m=0;m<c;++m){for(let g of p[m]){let{permutationIndices:y,expandDims:x}=T.getEinsumPermutation(h,l[g]),A;T.isIdentityPermutation(y)?A=s[g]:(A=kr({inputs:{x:s[g]},backend:a,attrs:{perm:y}}),f.push(A));let b=A.shape.slice();for(let k=0;k<x.length;++k)b.splice(x[k],0,1);v.arraysEqual(A.shape,b)||(A=Ie({inputs:{x:A},backend:a,attrs:{shape:b}}),f.push(A)),d===null?d=A:(d=W8({inputs:{a:A,b:d},backend:a}),f.push(d))}m<c-1&&(u[m]>=0&&(d=U3({inputs:{x:d},backend:a,attrs:{axis:u[m]-(i.length-h),keepDims:!1}}),f.push(d)),h--)}for(let m of f)m!==d&&a.disposeData(m.dataId);return d}var kle={kernelName:Md,backendName:"webgpu",kernelFunc:vle},wle=et({opType:le.ELU}),Ile={kernelName:hi,backendName:"webgpu",kernelFunc:wle},Sle=Jt({opType:Pe.EQUAL,dtype:"bool",cpuKernelImpl:Gse}),Tle={kernelName:fi,backendName:"webgpu",kernelFunc:Sle},Cle=et({opType:le.ERF}),Nle={kernelName:Ml,backendName:"webgpu",kernelFunc:Cle},V8=et({opType:le.EXP,cpuKernelImpl:Hse,dtype:"float32"}),Ele={kernelName:mi,backendName:"webgpu",kernelFunc:V8};function P2(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)}, ${i}]`),l=i+r+1),o.splice(l,0,1),Ie({inputs:{x:s},backend:n,attrs:{shape:o}})}var Rle={kernelName:$l,backendName:"webgpu",kernelFunc:P2},Mle=et({opType:le.EXPM1,cpuKernelImpl:jse}),$le={kernelName:_l,backendName:"webgpu",kernelFunc:Mle},Zy=class{constructor(e,t){this.variableNames=["real","imag"],this.outputShape=[],this.uniforms="exponentMultiplier : f32, denominator: f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.dispatchLayout=$e(this.outputShape),this.dispatch=we(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;
|
|
}
|
|
|
|
${ke("index")} {
|
|
if (index < uniforms.size) {
|
|
let coords = getOutputCoords();
|
|
setOutputAtIndex(index, mulMatDFT(coords[0], coords[1]));
|
|
}
|
|
}
|
|
`}};function U8(e,t,a){let n=a.tensorMap.get(e.dataId),r=v.sizeFromShape(e.shape),s=e.shape[e.shape.length-1],i=r/s,o=[],l=Ie({inputs:{x:e},backend:a,attrs:{shape:[i,s]}});o.push(l);let u=l.shape,p=new Zy("real",u),c=new Zy("imag",u),d=[{dataId:n.complexTensorInfos.real.dataId,dtype:n.complexTensorInfos.real.dtype,shape:u},{dataId:n.complexTensorInfos.imag.dataId,dtype:n.complexTensorInfos.imag.dtype,shape:u}],h=t?2*Math.PI:-2*Math.PI,f=t?u[1]:1,m=[{type:"float32",data:[h]},{type:"float32",data:[f]}],g=a.runWebGPUProgram(p,d,"float32",m);o.push(g);let y=a.runWebGPUProgram(c,d,"float32",m);o.push(y);let x=wo({inputs:{real:g,imag:y},backend:a});o.push(x);let A=Ie({inputs:{x},backend:a,attrs:{shape:e.shape}});return o.forEach(b=>a.disposeData(b.dataId)),A}function _le(e){let{inputs:t,backend:a}=e,{input:n}=t;return U8(n,!1,a)}var Ple={kernelName:$d,backendName:"webgpu",kernelFunc:_le},Fle=class{constructor(e){this.outputShape=[],this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=$e(this.outputShape),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="flipLeftRight"}getUserCode(){return`
|
|
${ke("index")} {
|
|
if (index < uniforms.size) {
|
|
let coords = getCoordsFromIndex(index);
|
|
let coordX = uniforms.xShape[2] - coords[2] - 1;
|
|
let outputValue = getX(coords[0], coords[1], coordX, coords[3]);
|
|
setOutputAtIndex(index, outputValue);
|
|
}
|
|
}
|
|
`}},Ole={kernelName:gi,backendName:"webgpu",kernelFunc:({inputs:e,backend:t})=>{let{image:a}=e,n=t,r=new Fle(a.shape);return n.runWebGPUProgram(r,[a],a.dtype)}},Dle=et({opType:le.FLOOR,cpuKernelImpl:qse}),zle={kernelName:yi,backendName:"webgpu",kernelFunc:Dle},Lle=Jt({opType:Pe.INT_DIV,dtype:"int32"}),Ble={kernelName:xi,backendName:"webgpu",kernelFunc:Lle},Wle=class{constructor(e,t,a=!1){this.isFromPixels=!0,this.outputShape=[0],this.variableNames=[],this.workgroupSize=[256,1,1],this.outputShape=e,this.dispatchLayout=$e(this.outputShape),this.dispatch=we(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>"};
|
|
${ke("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]));
|
|
}
|
|
}
|
|
}
|
|
`}},Vle={kernelName:nd,backendName:"webgpu",kernelFunc:Ule},Zo,zm=V().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU"),mc=new Map;function Ule(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=!1,f=i||o;if(u||l||f){let x;if(h){let M=r;if(!mc.has(M)||mc.get(M).expired){let R={source:M};mc.set(M,a.device.importExternalTexture(R))}x={width:p,height:c,format:null,usage:null,texture:mc.get(M)}}else{if(f){let _=V().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");(Zo==null||_!==zm)&&(zm=_,Zo=document.createElement("canvas").getContext("2d",{willReadFrequently:zm})),Zo.canvas.width=p,Zo.canvas.height=c,Zo.drawImage(r,0,0,p,c),r=Zo.canvas}let M=GPUTextureUsage.COPY_DST|GPUTextureUsage.RENDER_ATTACHMENT|GPUTextureUsage.TEXTURE_BINDING,R="rgba8unorm",I=a.textureManager.acquireTexture(d[1],d[0],R,M);a.queue.copyExternalImageToTexture({source:r},{texture:I},[d[1],d[0]]),x={width:p,height:c,format:R,usage:M,texture:I}}let A=v.sizeFromShape(d),b=v.computeStrides(d),k=new Wle(d,s,h),S=[{type:"uint32",data:[A]},{type:"uint32",data:[s]},{type:"uint32",data:[...b]}],C=a.makeTensorInfo([c,p],"int32"),N=a.tensorMap.get(C.dataId);N.resourceInfo=x;let $=a.runWebGPUProgram(k,[C],"int32",S);return a.disposeData(C.dataId),$}let m=r.data,g=m;if(s!=null&&s!==4){g=new Uint8Array(r.width*r.height*s);let x=m.length,A=0;for(let b=0;b<x;b++)b%4<s&&(g[A++]=m[b])}let y=a.makeTensorInfo(d,"int32",new Int32Array(g));return a.uploadToGPU(y.dataId),y}var Gle=class{constructor(e,t,a,n,r){this.uniforms="varianceEpsilon : f32,",this.workgroupSize=[128,1,1],this.size=!0,this.variableNames=["x","mean","variance"],T.assertAndGetBroadcastShape(e,t),T.assertAndGetBroadcastShape(e,a),this.outputShape=e,this.dispatchLayout=$e(this.outputShape),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize),n!=null&&(T.assertAndGetBroadcastShape(e,n),this.variableNames.push("offset")),r!=null&&(T.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)"),`
|
|
${ke("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)));
|
|
}
|
|
}
|
|
`}},Hle={kernelName:Ai,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 Gle(n.shape,i.shape,o.shape,c,d),f=[{type:"float32",data:[l]}];return u.runWebGPUProgram(h,p,n.dtype,f)}};function jle(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:f}=n,m=T.convertConv2DDataFormat(p),g=T.computeConv2DInfo(r.shape,s.shape,l,c,u,d,!1,m);return D8({x:r,filter:s,convInfo:g,backend:a,bias:i,preluActivationWeights:o,leakyreluAlpha:f,activation:h})}var qle={kernelName:jr,backendName:"webgpu",kernelFunc:jle};function Xle(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,f=p;f==null&&(f=[1,1]),v.assert(T.eitherStridesOrDilationsAreOne(l,f),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${f}'`);let m=T.computeConv2DInfo(r.shape,s.shape,l,f,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:[m.padInfo.top,m.padInfo.left]},{type:"int32",data:[m.inHeight,m.inWidth]}],b;return m.outHeight>4&&m.outWidth>4&&m.strideWidth<=2&&m.inChannels===m.outChannels&&m.dilationHeight===1&&m.dilationWidth===1&&m.inChannels%4===0?b=new L8(m,y,d,x):(b=new B8(m,y,d,x),A.push({type:"int32",data:[m.filterHeight]},{type:"int32",data:[m.filterWidth]},{type:"int32",data:[m.strideHeight,m.strideWidth]},{type:"int32",data:[m.dilationHeight,m.dilationWidth]})),d==="leakyrelu"&&(A.push({type:"float32",data:[h]}),b.uniforms+=" alpha : f32,"),a.runWebGPUProgram(b,g,"float32",A)}var Kle={kernelName:qr,backendName:"webgpu",kernelFunc:Xle},Zle=class{constructor(e,t){this.variableNames=["A","indices"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.dispatchLayout=$e(this.outputShape),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey=`gathernd_${e}`,this.sliceDim=e,this.uniforms=`sliceDim : i32, strides : ${oa(e)},`}getUserCode(){let e;return this.sliceDim>1?e="uniforms.strides[j]":e="uniforms.strides",`
|
|
${ke("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 = ${e};
|
|
flattenIndex = flattenIndex + indexTemp * strideNum;
|
|
}
|
|
|
|
setOutputAtIndex(index, getA(flattenIndex, coords[1]));
|
|
}
|
|
}
|
|
`}};function Yle(e){let{inputs:t,backend:a}=e,{params:n,indices:r}=t,s=r.shape,i=s[s.length-1],o=v.sizeFromShape(n.shape),[l,u,p,c]=T.prepareAndValidate(n,r),d=Ie({inputs:{x:r},backend:a,attrs:{shape:[u,i]}}),h=Ie({inputs:{x:n},backend:a,attrs:{shape:[v.sizeFromShape(n.shape)/p,p]}});if(a.shouldExecuteOnCPU([n,r])||n.dtype==="string"){let x=a.readSync(r.dataId),A=a.bufferSync(n),b=Xse(x,A,n.dtype,u,i,p,c,n.shape,o);return a.makeTensorInfo(l,n.dtype,b.values)}let f=new Zle(i,[u,p]),m=[{type:"int32",data:[i]},{type:"int32",data:c}],g=a.runWebGPUProgram(f,[h,d],h.dtype,m),y=Ie({inputs:{x:g},backend:a,attrs:{shape:l}});return a.disposeData(d.dataId),a.disposeData(h.dataId),a.disposeData(g.dataId),y}var Jle={kernelName:bi,backendName:"webgpu",kernelFunc:Yle},Qle=class{constructor(e,t){this.variableNames=["A","indices"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.slice(),this.aShape=e,this.outputShape=t,this.dispatchLayout=$e(this.outputShape),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="gather"}getUserCode(){let e=eue(this.aShape);return`
|
|
${ke("index")} {
|
|
if (index < uniforms.size) {
|
|
let resRC = getCoordsFromIndex(index);
|
|
let indexZ = i32(getIndices(resRC.x, resRC.z));
|
|
let inBounds = select(0.0, 1.0, indexZ >= 0 && indexZ < uniforms.aShape[2]);
|
|
setOutputAtIndex(index, inBounds * getA(${e}));
|
|
}
|
|
}
|
|
`}};function eue(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 G8(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=T.segment_util.collectGatherOpShapeInfo(r,s,l,o),p=v.sizeFromShape(s.shape),c=[],d=Ie({inputs:{x:r},backend:a,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),h=Ie({inputs:{x:s},backend:a,attrs:{shape:[u.batchSize,p/u.batchSize]}});c.push(d),c.push(h);let f=[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,k=_e(d.shape,d.dtype,b),S=Kse(k,A,f);return c.forEach(C=>a.disposeData(C.dataId)),a.makeTensorInfo(u.outputShape,S.dtype,S.values)}let m=new Qle(d.shape,f),g=a.runWebGPUProgram(m,[d,h],d.dtype);c.push(g);let y=Ie({inputs:{x:g},backend:a,attrs:{shape:u.outputShape}});return c.forEach(x=>a.disposeData(x.dataId)),y}var tue={kernelName:Fl,backendName:"webgpu",kernelFunc:G8},aue=Jt({opType:Pe.GREATER,cpuKernelImpl:Yse,dtype:"bool"}),nue={kernelName:vi,backendName:"webgpu",kernelFunc:aue},rue=Jt({opType:Pe.GREATER_EQUAL,dtype:"bool",cpuKernelImpl:Zse}),sue={kernelName:ki,backendName:"webgpu",kernelFunc:rue};function iue(e){let{inputs:t,backend:a}=e,{input:n}=t;return U8(n,!0,a)}var oue={kernelName:_d,backendName:"webgpu",kernelFunc:iue},lue=et({opType:le.IS_FINITE,dtype:"bool"}),uue={kernelName:Ol,backendName:"webgpu",kernelFunc:lue},due=et({opType:le.IS_INF,dtype:"bool"}),pue={kernelName:Dl,backendName:"webgpu",kernelFunc:due},cue=et({opType:le.IS_NAN,dtype:"bool"}),hue={kernelName:Ii,backendName:"webgpu",kernelFunc:cue};function fue(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{alpha:s}=n,i=[{type:"float32",data:[s]}],o=new xu(r.shape,le.LEAKYRELU,"alpha : f32,");return a.runWebGPUProgram(o,[r],"float32",i)}var mue={kernelName:Si,backendName:"webgpu",kernelFunc:fue},gue=Jt({opType:Pe.LESS,dtype:"bool",cpuKernelImpl:Qse}),yue={kernelName:Ti,backendName:"webgpu",kernelFunc:gue},xue=Jt({opType:Pe.LESS_EQUAL,dtype:"bool",cpuKernelImpl:Jse}),Aue={kernelName:Ci,backendName:"webgpu",kernelFunc:xue},bue=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=$e(this.outputShape),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="linSpace"}getUserCode(){return`
|
|
${ke("index")} {
|
|
if (index < uniforms.size) {
|
|
setOutputAtIndex(index, uniforms.start + f32(index) * uniforms.step);
|
|
}
|
|
}
|
|
`}};function vue(e){let{backend:t,attrs:a}=e,{start:n,stop:r,num:s}=a,i=(r-n)/(s-1),o=new bue(s),l=[{type:"float32",data:[n]},{type:"float32",data:[i]}];return t.runWebGPUProgram(o,[],"float32",l)}var kue={kernelName:Fd,backendName:"webgpu",kernelFunc:vue},wue=et({opType:le.LOG,cpuKernelImpl:eie}),Iue={kernelName:Ni,backendName:"webgpu",kernelFunc:wue},Sue=et({opType:le.LOG1P}),Tue={kernelName:zl,backendName:"webgpu",kernelFunc:Sue},Cue=Jt({opType:Pe.LOGICAL_AND,dtype:"bool"}),Nue={kernelName:Ei,backendName:"webgpu",kernelFunc:Cue},Eue=et({opType:le.LOGICAL_NOT}),Rue={kernelName:Ri,backendName:"webgpu",kernelFunc:Eue},Mue=Jt({opType:Pe.LOGICAL_OR}),$ue={kernelName:Mi,backendName:"webgpu",kernelFunc:Mue},H8=`
|
|
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));
|
|
}
|
|
`,_ue=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=$e(this.outputShape),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="lrn"}getUserCode(){return`
|
|
${ke("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;
|
|
}
|
|
}
|
|
${H8}
|
|
|
|
setOutputAtIndex(index, x * powValue);
|
|
}
|
|
}
|
|
`}},Pue=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=we(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};
|
|
|
|
${ke()} {
|
|
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;
|
|
}
|
|
${H8}
|
|
|
|
setOutputAtCoords(b, r, c, d, lrnSub[index] * powValue);
|
|
}
|
|
} `}};function Fue(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=n,u;s>16?u=new _ue(r.shape):u=new Pue(r.shape,s);let p=[{type:"int32",data:[s]},{type:"float32",data:[i]},{type:"float32",data:[o]},{type:"float32",data:[l]}];return a.runWebGPUProgram(u,[r],r.dtype,p)}var Oue={kernelName:Od,backendName:"webgpu",kernelFunc:Fue},Due=Jt({opType:Pe.MAX,cpuKernelImpl:aie}),zue={kernelName:_i,backendName:"webgpu",kernelFunc:Due};function Lue(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=n,u=1,p=T.computePool2DInfo(r.shape,s,i,u,o,l);return _8(r,p,"max",a)}var Bue={kernelName:Pi,backendName:"webgpu",kernelFunc:Lue};function Wue(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;return Io(r,s,i,"min",a)}var Vue={kernelName:Oi,backendName:"webgpu",kernelFunc:Wue},Uue=Jt({opType:Pe.MIN,cpuKernelImpl:nie}),Gue={kernelName:Di,backendName:"webgpu",kernelFunc:Uue},Hue=class{constructor(e,t,a){this.uniforms="",this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=t.map((n,r)=>n[0]+e[r]+n[1]),this.dispatchLayout=$e(this.outputShape),this.dispatch=we(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=oa(e),o=e>1?["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,e):"coords";return`
|
|
${ke("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}));
|
|
}
|
|
}
|
|
`}},jue={kernelName:zi,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 Hue(n.shape,r,s);return i.runWebGPUProgram(l,[n],n.dtype,o)}},que=Jt({opType:Pe.MOD}),Xue={kernelName:Ll,backendName:"webgpu",kernelFunc:que};function Kue(e){let{inputs:t,backend:a}=e,{x:n}=t;if(a.shouldExecuteOnCPU([n])){let s=a.tensorMap.get(n.dataId),[i,o]=sie(s.values,n.shape,n.dtype);return a.makeTensorInfo(o,n.dtype,i)}let r=new xu(n.shape,le.NEG);return a.runWebGPUProgram(r,[n],n.dtype)}var Zue={kernelName:Bl,backendName:"webgpu",kernelFunc:Kue};function Yue(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}=Nn.nonMaxSuppressionV3Impl(u,p,i,o,l);return a.makeTensorInfo([c.length],"int32",new Int32Array(c))}var Jue={kernelName:Wi,backendName:"webgpu",kernelFunc:Yue};function Que(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,f=l,m=u,{selectedIndices:g,selectedScores:y}=Nn.nonMaxSuppressionV5Impl(p,c,d,h,f,m);return[a.makeTensorInfo([g.length],"int32",new Int32Array(g)),a.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var ede={kernelName:Vi,backendName:"webgpu",kernelFunc:Que},tde=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=$e(this.outputShape),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="onehot"}getUserCode(){return`
|
|
${ke("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 ade(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 tde(u,i),c=Ie({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 f=[...r.shape,i],m=Ie({inputs:{x:h},backend:a,attrs:{shape:f}});return a.disposeData(h.dataId),m}var nde={kernelName:Ui,backendName:"webgpu",kernelFunc:ade};function Gc(e){let{inputs:t,backend:a}=e,{x:n}=t;if(n.dtype==="complex64"){let r=yp({inputs:{input:n},backend:a}),s=Gc({inputs:{x:r},backend:a}),i=Wh({inputs:{input:n},backend:a}),o=Gc({inputs:{x:i},backend:a}),l=wo({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 Nr({attrs:{shape:n.shape,dtype:n.dtype,value:n.dtype==="string"?"":0},backend:a})}var rde={kernelName:nu,backendName:"webgpu",kernelFunc:Gc};function j8(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=yp({inputs:{input:n},backend:a}),s=j8({inputs:{x:r},backend:a}),i=Wh({inputs:{input:n},backend:a}),o=Gc({inputs:{x:i},backend:a}),l=wo({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 Nr({attrs:{shape:n.shape,dtype:n.dtype,value:1},backend:a})}var sde={kernelName:Vl,backendName:"webgpu",kernelFunc:j8};function ide(e){let{inputs:t,backend:a,attrs:n}=e,{axis:r}=n;if(t.length===1)return P2({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=P2({inputs:{input:p},backend:a,attrs:{dim:r}});return o.push(c),c}),u=O8({inputs:l,backend:a,attrs:{axis:r}});return o.forEach(p=>a.disposeData(p.dataId)),u}var ode={kernelName:Ul,backendName:"webgpu",kernelFunc:ide},lde=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=$e(this.outputShape),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize),t.map((a,n)=>{this.uniforms+=` pad${n} : vec2<i32>,`}),this.xShape=e,this.shaderKey="pad"}getUserCode(){let e=this.xShape.length,t=oa(e),a=this.xShape.map((u,p)=>`uniforms.pad${p}[0]`).join(","),n=this.xShape.map((u,p)=>`uniforms.pad${p}[0] + uniforms.xShape${e>1?`[${p}]`:""}`).join(","),r=e>1?`${t}(${a})`:`${a}`,s=e>1?`${t}(${n})`:`${n}`,i=e>1?"any(outC < start)":"outC < start",o=e>1?"any(outC >= end)":"outC >= end",l=e>1?["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,e):"coords";return`
|
|
${ke("index")} {
|
|
if (index < uniforms.size) {
|
|
let start = ${r};
|
|
let end = ${s};
|
|
let outC = getCoordsFromIndex(index);
|
|
|
|
if (${i} || ${o}) {
|
|
setOutputAtIndex(index, uniforms.constantValue);
|
|
} else {
|
|
let coords = outC - start;
|
|
setOutputAtIndex(index, getX(${l}));
|
|
}
|
|
}
|
|
}
|
|
`}},q8=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 Qa({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 Nr({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 lde(r.shape,s);return a.runWebGPUProgram(l,[r],r.dtype,o)},ude={kernelName:Gi,backendName:"webgpu",kernelFunc:q8},dde=Jt({opType:Pe.POW}),pde={kernelName:Hi,backendName:"webgpu",kernelFunc:dde};function cde(e){let{inputs:t,backend:a}=e,{x:n,alpha:r}=t,s=new M2(Pe.PRELU,n.shape,r.shape);return a.runWebGPUProgram(s,[n,r],"float32")}var hde={kernelName:ji,backendName:"webgpu",kernelFunc:cde};function fde(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;return Io(r,s,i,"prod",a)}var mde={kernelName:qi,backendName:"webgpu",kernelFunc:fde},gde=e=>{let{backend:t,attrs:a}=e,{start:n,stop:r,step:s,dtype:i}=a,o=lie(n,r,s,i);return t.makeTensorInfo([o.length],i,o)},yde={kernelName:Gl,backendName:"webgpu",kernelFunc:gde},X8=Jt({opType:Pe.DIV}),xde={kernelName:ci,backendName:"webgpu",kernelFunc:X8},Ade=et({opType:le.RECIPROCAL}),bde={kernelName:Xi,backendName:"webgpu",kernelFunc:Ade},vde=et({opType:le.RELU}),kde={kernelName:Ki,backendName:"webgpu",kernelFunc:vde},wde=et({opType:le.RELU6}),Ide={kernelName:Ji,backendName:"webgpu",kernelFunc:wde},Sde=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=$e(this.outputShape),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="resizeBilinear"}getUserCode(){return`
|
|
${ke("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 Tde(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 Sde(r.shape,l,u);return a.runWebGPUProgram(h,[r],"float32",d)}var Cde={kernelName:Yi,backendName:"webgpu",kernelFunc:Tde},Nde=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=$e(this.outputShape),this.dispatch=we(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",`
|
|
${ke("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 = ${e};
|
|
|
|
// Compute the coordinators of nearest neighbor point.
|
|
let inputShapeRC = vec2<f32>(f32(uniforms.xShape.y), f32(uniforms.xShape.z));
|
|
let sourceNearestRC = vec2<i32>(
|
|
min(inputShapeRC - 1.0, floor(sourceFracIndexRC + uniforms.roundBase)));
|
|
let newValue = getX(b, sourceNearestRC.x, sourceNearestRC.y, d);
|
|
|
|
setOutputAtIndex(index, newValue);
|
|
}
|
|
}
|
|
`}};function Ede(e){let{inputs:t,backend:a,attrs:n}=e,{images:r}=t,{alignCorners:s,halfPixelCenters:i,size:o}=n,[l,u]=o,p=s&&l>1?1:0,c=s&&u>1?1:0,d=[{type:"float32",data:[p,c]},{type:"float32",data:[s?.5:0]}],h=new Nde(r.shape,l,u,i);return a.runWebGPUProgram(h,[r],r.dtype,d)}var Rde={kernelName:Zi,backendName:"webgpu",kernelFunc:Ede},Mde=class{constructor(e){this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=$e(this.outputShape),this.dispatch=we(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;
|
|
}
|
|
|
|
${ke("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 $de(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{dims:s}=n,i=r.shape.length;if(i===0)return Qa({inputs:{x:r},backend:a});let o=r.shape,l=[1,1,1,1];o.forEach((g,y)=>{let x=y+4-i;l[x]=g});let u=v.parseAxisParam(s,r.shape),p=[0,0,0,0];u.forEach(g=>{let y=g+4-i;p[y]=1});let c=[{type:"int32",data:p}],d=Ie({inputs:{x:r},backend:a,attrs:{shape:l}}),h=new Mde(l),f=a.runWebGPUProgram(h,[d],d.dtype,c);a.disposeData(d.dataId);let m=Ie({inputs:{x:f},backend:a,attrs:{shape:o}});return a.disposeData(f.dataId),m}var _de={kernelName:Qi,backendName:"webgpu",kernelFunc:$de},Pde=class{constructor(e,t){this.outputShape=[],this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=$e(this.outputShape),this.dispatch=we(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`
|
|
${ke("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));
|
|
${this.fillSnippet}
|
|
if(coordX >= 0 && coordX < uniforms.xShape[2] && coordY >= 0 &&
|
|
coordY < uniforms.xShape[1]) {
|
|
outputValue = getX(coords[0], coordY, coordX, coords[3]);
|
|
}
|
|
setOutputAtIndex(index, outputValue);
|
|
}
|
|
}
|
|
`}},Fde={kernelName:go,backendName:"webgpu",kernelFunc:({inputs:e,attrs:t,backend:a})=>{let{image:n}=e,{radians:r,fillValue:s,center:i}=t,o=a,l=new Pde(n.shape,s),[u,p]=T.getImageCenter(i,n.shape[1],n.shape[2]),c=[{type:"float32",data:[u]},{type:"float32",data:[p]},{type:"float32",data:[Math.sin(r)]},{type:"float32",data:[Math.cos(r)]}];return typeof s=="number"?c.push({type:"float32",data:[Number.parseFloat(s.toFixed(2))]}):c.push({type:"float32",data:s}),o.runWebGPUProgram(l,[n],n.dtype,c)}},Ode=et({opType:le.ROUND}),Dde={kernelName:eo,backendName:"webgpu",kernelFunc:Ode},zde=et({opType:le.RSQRT,cpuKernelImpl:uie}),Lde={kernelName:to,backendName:"webgpu",kernelFunc:zde},Ic=class{constructor(e,t,a,n,r,s,i,o=!0){this.variableNames=["updates","indices"],this.workgroupSize=[64,1,1],this.atomic=!0,this.outputShape=s,this.type=i,this.sumDupeIndices=o,this.dispatchLayout=$e(e),this.dispatch=we(this.dispatchLayout,e,this.workgroupSize),this.sliceDimGreaterThanOne=t>1,this.shaderKey=`scatter_${a}_${n}_${this.sliceDimGreaterThanOne}_${i}_${o}`;let l=oa(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}
|
|
${ke("index")} {
|
|
if (index < uniforms.updatesSize) {
|
|
let coords = getUpdatesCoordsFromFlatIndex(index);
|
|
var flattenedIndex = 0;
|
|
for (var j = 0; j < uniforms.sliceDim; j = j + 1) {
|
|
let indexInside = i32(round(${t}));
|
|
flattenedIndex = flattenedIndex + indexInside * ${a};
|
|
}
|
|
let updateValue =
|
|
${td(this.type,!1)}(${s});
|
|
let flatIndex = getOutputIndexFromCoords(${n});
|
|
|
|
${this.sumDupeIndices?O3("&result[flatIndex]","updateValue",this.type):"atomicStore(&result[flatIndex], bitcast<i32>(updateValue));"}
|
|
}
|
|
}`}};function Bde(e){let{inputs:t,backend:a,attrs:n}=e,{indices:r,updates:s}=t,{shape:i}=n,{sliceRank:o,numUpdates:l,sliceSize:u,strides:p,outputSize:c}=T.calculateShapes(s,r,i),d=[c/u,u];if(c===0)return a.makeTensorInfo(i,r.dtype);let h=Ie({inputs:{x:r},backend:a,attrs:{shape:[l,o]}}),f=Ie({inputs:{x:s},backend:a,attrs:{shape:[l,u]}}),m=f.dtype,g=Nr({backend:a,attrs:{shape:d,value:0,dtype:m}}),y=v.sizeFromShape(f.shape),x=[{type:"int32",data:[o]},{type:"int32",data:p},{type:"int32",data:[y]}],A=new Ic(f.shape,o,h.shape.length,f.shape.length,p,d,m),b=a.runWebGPUProgram(A,[f,h],m,x,g),k=Ie({inputs:{x:b},backend:a,attrs:{shape:i}});return a.disposeData(h.dataId),a.disposeData(f.dataId),a.disposeData(b.dataId),k}var Wde={kernelName:ao,backendName:"webgpu",kernelFunc:Bde},Vde=class{constructor(e,t){this.outputShape=[],this.variableNames=["sortedSequence","values"],this.uniforms="numInputs : i32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=$e(this.outputShape),this.dispatch=we(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;
|
|
}
|
|
|
|
${ke("index")} {
|
|
if (index < uniforms.size) {
|
|
let coords = getCoordsFromIndex(index);
|
|
let value = getValuesByOutputIndex(index);
|
|
setOutputAtIndexI32(index, findBound(coords[0], value));
|
|
}
|
|
}
|
|
`}};function Ude(e){let{inputs:t,backend:a,attrs:n}=e,{sortedSequence:r,values:s}=t,{side:i}=n,o=new Vde([s.shape[0],s.shape[1]],i),l=[{type:"int32",data:[r.shape[1]]}];return a.runWebGPUProgram(o,[r,s],"int32",l)}var Gde={kernelName:zd,backendName:"webgpu",kernelFunc:Ude},Hde=class{constructor(e,t,a){this.variableNames=["c","a","b"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.dispatchLayout=$e(this.outputShape),this.dispatch=we(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`
|
|
${ke("index")} {
|
|
if (index < uniforms.size) {
|
|
let resRC = getCoordsFromIndex(index);
|
|
let cVal = getC(${e});
|
|
if (cVal >= 1.0) {
|
|
setOutputAtIndex(index, getA(${t}));
|
|
} else {
|
|
setOutputAtIndex(index, getB(${t}));
|
|
}
|
|
}
|
|
}
|
|
`}};function jde(e){let{inputs:t,backend:a}=e,{condition:n,t:r,e:s}=t,i=new Hde(n.shape.length,r.shape,r.shape.length);return a.runWebGPUProgram(i,[n,r,s],fa(r.dtype,s.dtype))}var qde={kernelName:jl,backendName:"webgpu",kernelFunc:jde},Xde=et({opType:le.SELU}),Kde={kernelName:ql,backendName:"webgpu",kernelFunc:Xde},Zde=et({opType:le.SIGMOID}),Yde={kernelName:ro,backendName:"webgpu",kernelFunc:Zde},Jde=et({opType:le.SIGN}),Qde={kernelName:Zl,backendName:"webgpu",kernelFunc:Jde},epe=et({opType:le.SIN}),tpe={kernelName:no,backendName:"webgpu",kernelFunc:epe},ape=et({opType:le.SINH}),npe={kernelName:Kl,backendName:"webgpu",kernelFunc:ape},K8=Jt({opType:Pe.SUB,cpuKernelImpl:mie,supportsComplex:!0}),rpe={kernelName:po,backendName:"webgpu",kernelFunc:K8};function spe(e){let{inputs:t,backend:a,attrs:n}=e,{logits:r}=t,{dim:s}=n,i=v.parseAxisParam([s],r.shape),o=V3({inputs:{x:r},backend:a,attrs:{reductionIndices:i,keepDims:!1}}),l=T.expandShapeToKeepDim(o.shape,i),u=Ie({inputs:{x:o},backend:a,attrs:{shape:l}}),p=K8({inputs:{a:r,b:u},backend:a}),c=V8({inputs:{x:p},backend:a}),d=U3({inputs:{x:c},backend:a,attrs:{axis:i,keepDims:!1}}),h=Ie({inputs:{x:d},backend:a,attrs:{shape:l}}),f=X8({inputs:{a:c,b:h},backend:a});return a.disposeData(o.dataId),a.disposeData(u.dataId),a.disposeData(p.dataId),a.disposeData(c.dataId),a.disposeData(d.dataId),a.disposeData(h.dataId),f}var ipe={kernelName:oo,backendName:"webgpu",kernelFunc:spe},ope=et({opType:le.SOFTPLUS}),lpe={kernelName:Yl,backendName:"webgpu",kernelFunc:ope},upe=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((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=q8({inputs:{x:r},backend:a,attrs:{paddings:l,constantValue:0}}),c=T.getReshaped(p.shape,s,o,!1),d=T.getPermuted(c.length,s.length,!1),h=T.getReshapedPermuted(p.shape,s,o,!1),f=Ie({inputs:{x:p},backend:a,attrs:{shape:c}}),m=kr({inputs:{x:f},backend:a,attrs:{perm:d}}),g=Ie({inputs:{x:m},backend:a,attrs:{shape:h}});return u.push(p),u.push(f),u.push(m),u.forEach(y=>a.disposeData(y.dataId)),g},dpe={kernelName:Jl,backendName:"webgpu",kernelFunc:upe},ppe=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=$e(this.outputShape),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize),this.rank=this.outputShape.length,this.shaderKey="tile"}getUserCode(){let e=cpe(this.rank,"uniforms.");return`
|
|
${ke("index")} {
|
|
if (index < uniforms.size) {
|
|
let resRC = getCoordsFromIndex(index);
|
|
setOutputAtIndex(index, getA(${e}));
|
|
}
|
|
}
|
|
`}};function cpe(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 Z8(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=gie(u,s);return a.makeTensorInfo(p.shape,p.dtype,p.values)}let i=new ppe(r.shape,s);return a.runWebGPUProgram(i,[r],r.dtype)}var hpe={kernelName:ns,backendName:"webgpu",kernelFunc:Z8};function fpe(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}=T.calculateShapes(s,r,o),h=!1;if(s.dtype==="string"){let N=a.bufferSync(r),$=a.bufferSync(s),M=v.decodeString(a.readSync(i.dataId)[0]),R=die(N,$,o,d,p,u,l,c,M,h);return a.makeTensorInfo(o,R.dtype,R.values)}let f=[d/p,p],m=Ie({inputs:{x:r},backend:a,attrs:{shape:[u,l]}}),g=s.shape.length?Ie({inputs:{x:s},backend:a,attrs:{shape:[u,p]}}):Qa({inputs:{x:s},backend:a}),y=g.dtype,x=a.makeTensorInfo([],y,v.makeZerosTypedArray(1,y)),A=Ie({inputs:{x:i},backend:a,attrs:{shape:Array(f.length).fill(1)}}),b=Z8({inputs:{x:A},backend:a,attrs:{reps:f}}),k=v.sizeFromShape([u,p]),S=[{type:"int32",data:[l]},{type:"int32",data:c},{type:"int32",data:[k]}];switch(u){case 0:break;case 1:{let N=new Ic([u,p],l,m.shape.length,g.shape.length,c,f,y,h);a.runWebGPUProgram(N,[g,m],y,S,b)}break;default:{let N=new Ic([u,p],l,m.shape.length,x.shape.length,c,f,y,h);a.runWebGPUProgram(N,[x,m],y,S,b)}{let N=new Ic([u,p],l,m.shape.length,g.shape.length,c,f,y);a.runWebGPUProgram(N,[g,m],y,S,b)}}let C=Ie({inputs:{x:b},backend:a,attrs:{shape:o}});return a.disposeData(m.dataId),a.disposeData(g.dataId),a.disposeData(A.dataId),a.disposeData(x.dataId),a.disposeData(b.dataId),C}var mpe={kernelName:Vd,backendName:"webgpu",kernelFunc:fpe};function gpe(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=T.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 f=Au({inputs:{x:r},backend:a,attrs:{begin:p,size:h}});return p[o]+=d,f})}var ype={kernelName:Ql,backendName:"webgpu",kernelFunc:gpe},xpe=et({opType:le.SQRT}),Ape={kernelName:so,backendName:"webgpu",kernelFunc:xpe},bpe={kernelName:Ud,backendName:"webgpu",kernelFunc:({inputs:e,backend:t})=>{let{x:a}=e,n=t,r=new xu(a.shape,le.SQUARE);return n.runWebGPUProgram(r,[a],a.dtype)}},vpe=Jt({opType:Pe.SQUARED_DIFFERENCE}),kpe={kernelName:lo,backendName:"webgpu",kernelFunc:vpe};function wpe({inputs:e,attrs:t,backend:a}){let{x:n}=e,r=new xu(n.shape,le.STEP,"stepAlpha : f32,"),s=[{type:"float32",data:[t.alpha]}];return a.runWebGPUProgram(r,[n],n.dtype,s)}var Ipe={kernelName:rs,backendName:"webgpu",kernelFunc:wpe},Spe=class{constructor(e){this.variableNames=["x"],this.workPerThread=1,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=$e(this.outputShape),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1]);let t=oa(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`
|
|
${ke("index")} {
|
|
if (index < uniforms.size) {
|
|
let coords = getCoordsFromIndex(index);
|
|
setOutputAtIndex(index, getX(${t}));
|
|
}
|
|
}
|
|
`}};function Tpe(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:f,isIdentity:m,sliceDim0:g,isSimpleSlice:y,begin:x,end:A,strides:b}=St.sliceInfo(r.shape,s,i,o,l,u,p,c,d),k;if(m)k=Ie({inputs:{x:r},backend:a,attrs:{shape:f}});else if(g||y){v.assert(r.shape.length>=1,()=>`Input must have rank at least 1, got: ${r.shape.length}`);let S=St.computeOutShape(x,A,b),C=Au({inputs:{x:r},backend:a,attrs:{begin:x,size:S}});k=Ie({inputs:{x:C},backend:a,attrs:{shape:f}}),a.disposeData(C.dataId)}else if(a.shouldExecuteOnCPU([r])){let S=a.readSync(r.dataId),C=_e(r.shape,r.dtype,S),N=hie(h,C,b,x);k=a.makeTensorInfo(f,r.dtype,N.values)}else{let S=new Spe(h),C=[{type:"int32",data:x},{type:"int32",data:b}],N=a.runWebGPUProgram(S,[r],r.dtype,C);k=Ie({inputs:{x:N},backend:a,attrs:{shape:f}}),a.disposeData(N.dataId)}return k}var Cpe={kernelName:uo,backendName:"webgpu",kernelFunc:Tpe};function Npe(e){let{inputs:t,backend:a,attrs:n}=e,{separator:r,nGramWidths:s,leftPad:i,rightPad:o,padWidth:l,preserveShortSequences:u}=n,{data:p,dataSplits:c}=t,d=a.readSync(p.dataId),h=a.readSync(c.dataId),[f,m]=fie(d,h,r,s,i,o,l,u);return[a.makeTensorInfo([f.length],"string",f),a.makeTensorInfo(c.shape,"int32",m)]}var Epe={kernelName:tu,backendName:"webgpu",kernelFunc:Npe},Rpe=et({opType:le.TAN}),Mpe={kernelName:co,backendName:"webgpu",kernelFunc:Rpe},$pe=et({opType:le.TANH}),_pe={kernelName:ho,backendName:"webgpu",kernelFunc:$pe},Ppe=class{constructor(e){this.variableNames=["x","indices"],this.workgroupSize=[256,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=$e(this.outputShape),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize),this.uniforms=`inputSize : i32, firstPass : i32, negativeInf : f32,
|
|
dir : i32, inc : i32,`,this.shaderKey="swap"}getUserCode(){return`
|
|
${ke("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));
|
|
}
|
|
}
|
|
}
|
|
`}},Fpe=class{constructor(e){this.variableNames=["x","indices"],this.workgroupSize=[256,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=$e(this.outputShape),this.dispatch=we(this.dispatchLayout,this.outputShape,this.workgroupSize),this.uniforms="inputSize : i32, firstPass : i32, k : i32,",this.shaderKey="merge"}getUserCode(){return`
|
|
${ke("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 Yo(e,t){t!==null&&e.disposeData(t.dataId)}function Yy(e){let t=1;for(;t<e;)t*=2;return t}function Ope(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),[k,S]=yie(b,o,r.dtype,s,i);return[a.makeTensorInfo(k.shape,k.dtype,k.values),a.makeTensorInfo(S.shape,S.dtype,S.values)]}if(s===0)return o[o.length-1]=0,[a.makeTensorInfo(o,r.dtype,[]),a.makeTensorInfo(o,"int32",[])];if(l===1)return[r,Nr({attrs:{shape:o,dtype:"int32",value:0},backend:a})];let u=v.sizeFromShape(o)/l,p=Ie({inputs:{x:r},attrs:{shape:[u,l]},backend:a}),c=Yy(s),d=Yy(l),h=null,f=()=>h===null?[p,p]:[p,h],m=(b,k,S)=>{let C=f(),N=new Ppe(S),$=[{type:"int32",data:[l]},{type:"int32",data:[h===null?1:0]},{type:"float32",data:[Number.NEGATIVE_INFINITY]},{type:"int32",data:[b]},{type:"int32",data:[k]}],M=h;h=a.runWebGPUProgram(N,C,"int32",$),Yo(a,M)};for(let b=1;b<c;b*=2){let k=b*2;for(let S=b;S>=1;S/=2)m(k,S,[u,d])}for(let b=d;b>c;b/=2){let k=f(),S=new Fpe([u,b/2]),C=[{type:"int32",data:[l]},{type:"int32",data:[h===null?1:0]},{type:"int32",data:[c]}],N=h;h=a.runWebGPUProgram(S,k,"int32",C),Yo(a,N);let $=c/2,M=$*2;for(let R=$;R>=1;R/=2)m(M,R,h.shape)}let g=h;h=Au({inputs:{x:h},backend:a,attrs:{begin:0,size:[u,s]}}),Yo(a,g);let y=G8({inputs:{x:p,indices:h},backend:a,attrs:{axis:1,batchDims:1}});Yo(a,p);let x=o.slice(0,-1);x.push(s),g=h,h=Ie({inputs:{x:h},attrs:{shape:x},backend:a}),Yo(a,g);let A=y;return y=Ie({inputs:{x:y},attrs:{shape:x},backend:a}),Yo(a,A),[y,h]}var Dpe={kernelName:fo,backendName:"webgpu",kernelFunc:Ope},zpe=class{constructor(e){this.variableNames=["Image","Transforms"],this.uniforms="interpolationModeId : i32, fillModeId : i32, fillValue : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=$e(this.outputShape),this.dispatch=we(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;
|
|
}
|
|
|
|
${ke("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 Lpe(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,[f,m]=u!=null?u:[c,d],g=[p,f,m,h],y=new zpe(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 Bpe={kernelName:mo,backendName:"webgpu",kernelFunc:Lpe};function Wpe(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 m=0;m<o;m++)m!==s&&(u[p++]=i.shape[m]);let c=[],d=new Array(o).fill(0),h=i.shape.slice();h[s]=1;let f=new Array(l);for(let m=0;m<f.length;m++){d[s]=m;let g=Au({inputs:{x:i},backend:a,attrs:{begin:d,size:h}}),y=Ie({inputs:{x:g},backend:a,attrs:{shape:u}});f[m]=y,c.push(g)}return c.forEach(m=>a.disposeData(m.dataId)),f}var Vpe={kernelName:au,backendName:"webgpu",kernelFunc:Wpe},Upe=[Dse,bie,kie,Iie,Tie,Eie,Oie,zie,Bie,Vie,Gie,jie,Xie,Zie,Jie,noe,ioe,loe,hoe,yoe,voe,woe,Coe,Lse,Moe,Loe,Uoe,qoe,Koe,Yoe,ele,ale,rle,ile,ule,cle,mle,xle,kle,Ile,Tle,Nle,Ele,Rle,$le,Ple,Pse,Ole,Vle,zle,Ble,Hle,qle,Kle,Jle,tue,nue,sue,zse,oue,Eoe,uue,pue,hue,mue,yue,Aue,kue,Tue,Iue,Nue,Rue,$ue,Oue,eoe,zue,Bue,toe,Vue,Gue,jue,Xue,Ale,Zue,Jue,ede,xoe,nde,sde,ode,ude,pde,hde,mde,yde,Aoe,xde,bde,kde,Ide,Fse,Cde,Rde,_de,Fde,Dde,Lde,Wde,Gde,qde,Kde,Yde,Qde,tpe,npe,poe,Ipe,Cpe,Epe,ipe,lpe,dpe,mpe,ype,Ape,bpe,kpe,rpe,ble,Mpe,_pe,hpe,Dpe,Bpe,_ie,Vpe,rde];for(let e of Upe)yn(e);var Jy="4.2.0",Gpe="4.2.0",Hpe="4.2.0",jpe="4.2.0",qpe="4.2.0",Xpe="0.0.1-alpha.17",xp={tfjs:Jy,"tfjs-core":Jy,"tfjs-converter":Gpe,"tfjs-backend-cpu":Hpe,"tfjs-backend-webgl":jpe,"tfjs-backend-wasm":qpe,"tfjs-backend-webgpu":Xpe};function K(...e){let t=new Date,a=`${t.getHours().toString().padStart(2,"0")}:${t.getMinutes().toString().padStart(2,"0")}:${t.getSeconds().toString().padStart(2,"0")}.${t.getMilliseconds().toString().padStart(3,"0")}`;e&&console.log(a,"Human:",...e)}function Y8(e,t){let a=e.endsWith("/")?"":"/",r=t.startsWith(".")||t.startsWith("/")||t.startsWith("http:")||t.startsWith("https:")||t.startsWith("file:")?`${t}`:`${e}${a}${t}`;if(!r.toLocaleLowerCase().includes(".json"))throw new Error(`modelpath error: expecting json file: ${r}`);return r}var ae=()=>typeof performance!="undefined"?performance.now():parseInt((Number(process.hrtime.bigint())/1e3/1e3).toString());function G3(e,t,a="config",n=[]){for(let r of Object.keys(t))if(typeof t[r]=="object")G3(e[r],t[r],r,n);else{let s=e&&typeof e[r]!="undefined";s||n.push({reason:"unknown property",where:`${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 Nt(...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]=Nt(s,i):a[r]=i}),a),{})}var So={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,mask:!1,return:!1},mesh:{enabled:!0,modelPath:"facemesh.json",keepInvalid:!1},attention:{enabled:!1,modelPath:"facemesh-attention.json"},iris:{enabled:!0,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 J8=`
|
|
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 Q8=`
|
|
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];
|
|
}
|
|
`,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[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;
|
|
}
|
|
`,t9=`
|
|
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);
|
|
}
|
|
`,a9=`
|
|
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;
|
|
}
|
|
`,n9=`
|
|
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 H3=(e,t,a)=>{let n=new RegExp("\\b"+t+" \\w+ (\\w+)","ig");e.replace(n,(r,s)=>(a[s]=0,r))},j3=class{constructor(t,a,n){de(this,"uniform",{});de(this,"attribute",{});de(this,"gl");de(this,"id");de(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),H3(a,"attribute",this.attribute);for(let i in this.attribute)this.attribute[i]=this.gl.getAttribLocation(this.id,i);H3(a,"uniform",this.uniform),H3(n,"uniform",this.uniform);for(let i in this.uniform)this.uniform[i]=this.gl.getUniformLocation(this.id,i)}}};function r9(){let e=0,t=null,a=!1,n=-1,r=[null,null],s=[],i=null,o=null,l=Rn(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 k=c.createRenderbuffer();c.bindRenderbuffer(c.RENDERBUFFER,k);let S=c.createTexture();return c.bindTexture(c.TEXTURE_2D,S),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,S,0),c.bindTexture(c.TEXTURE_2D,null),c.bindFramebuffer(c.FRAMEBUFFER,null),{fbo:b,texture:S}}function f(x){return r[x]=r[x]||h(l.width,l.height),r[x]}function m(x=0){if(!o)return;let A=null,b=null,k=!1;e===0?A=t:A=f(n).texture||null,e++,a&&!(x&p.INTERMEDIATE)?(b=null,k=e%2===0):(n=(n+1)%2,b=f(n).fbo||null),c.bindTexture(c.TEXTURE_2D,A),c.bindFramebuffer(c.FRAMEBUFFER,b),c.uniform1f(o.uniform.flipY,k?-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 j3(c,J8,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?e9:Q8,k=g(b);k&&(c.uniform1fv(k.uniform.m,A),m())},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),k=.213,S=.715,C=.072;y.colorMatrix([k+A*(1-k)+b*-k,S+A*-S+b*-S,C+A*-C+b*(1-C),0,0,k+A*-k+b*.143,S+A*(1-S)+b*.14,C+A*-C+b*-.283,0,0,k+A*-k+b*-(1-k),S+A*-S+b*S,C+A*(1-C)+b*C,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,k=1/l.height,S=g(n9);S&&(c.uniform1fv(S.uniform.m,A),c.uniform2f(S.uniform.px,b,k),m())},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,k=g(a9);k&&(c.uniform2f(k.uniform.px,0,b),m(p.INTERMEDIATE),c.uniform2f(k.uniform.px,A,0),m())},pixelate:x=>{let A=x/l.width,b=x/l.height,k=g(t9);k&&(c.uniform2f(k.uniform.size,A,b),m())}};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 Vh(e){let t=e.shape.length===4?De(e):e,a=Ia(t,3,2),n=[Kr(a[0]),Kr(a[1]),Kr(a[2])],r=[ha(a[0]),ha(a[1]),ha(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=[fe(a[0],n[0]),fe(a[1],n[1]),fe(a[2],n[2])],c=[fe(r[0],n[0]),fe(r[1],n[1]),fe(r[2],n[2])],d=[te(p[0],l),te(p[1],l),te(p[2],l)],h=la([d[0],d[1],d[2]],2);u=Q(h,[1,t.shape[0]||0,t.shape[1]||0,3]),J([...p,...c,...d])}else u=Gt(t,0);return J([...a,...n,...r,a,t,e]),u}var Uh=3840,Qt=null,ea=null,bu=null,yt,xn={inputSum:0,cacheDiff:1,sumMethod:0,inputTensor:void 0};function q3(){xn.inputSum=0,xn.cacheDiff=1,xn.sumMethod=0,xn.inputTensor=void 0}function Rn(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 Gh(e,t){let a=t||Rn(e.width,e.height);return a.getContext("2d").drawImage(e,0,0),a}async function Hh(e,t,a=!0){var d,h,f;if(!e)return t.debug&&K("input error: input is missing"),{tensor:null,canvas:null};if(!(e instanceof pt)&&!(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 pt){let m=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)m=Gt(e,0);else if(e.shape[2]===4){let g=lp(e,[0,0,0],[-1,-1,3]);m=Gt(g,0),J(g)}}else e.shape.length===4&&(e.shape[3]===3?m=wa(e):e.shape[3]===4&&(m=gh(e,[0,0,0,0],[-1,-1,-1,3])));if(m==null||m.shape.length!==4||m.shape[0]!==1||m.shape[3]!==3)throw new Error(`input error: attempted to use tensor with unrecognized shape: ${e.shape.toString()}`);if(m.dtype==="int32"){let g=Xe(m,"float32");J(m),m=g}return{tensor:m,canvas:t.filter.return?ea:null}}if(typeof e.readyState!="undefined"&&e.readyState<=2)return t.debug&&K("input stream is not ready"),{tensor:null,canvas:Qt};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:Qt};let s=n,i=r;if(s>Uh&&(s=Uh,i=Math.trunc(s*r/n)),i>Uh&&(i=Uh,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");(!Qt||Qt.width!==s||Qt.height!==i)&&(Qt=Rn(s,i));let o=Qt.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,Qt.width,Qt.height),o.setTransform(1,0,0,1,0,0)):o.drawImage(e,0,0,n,r,0,0,Qt.width,Qt.height),(!ea||Qt.width!==ea.width||Qt.height!==ea.height)&&(ea=Rn(Qt.width,Qt.height)),t.filter.enabled&&ne.webgl.supported?(yt||(yt=ne.browser?new r9:null),ne.filter=!!yt,yt!=null&&yt.add?(yt.reset(),t.filter.brightness!==0&&yt.add("brightness",t.filter.brightness),t.filter.contrast!==0&&yt.add("contrast",t.filter.contrast),t.filter.sharpness!==0&&yt.add("sharpen",t.filter.sharpness),t.filter.blur!==0&&yt.add("blur",t.filter.blur),t.filter.saturation!==0&&yt.add("saturation",t.filter.saturation),t.filter.hue!==0&&yt.add("hue",t.filter.hue),t.filter.negative&&yt.add("negative"),t.filter.sepia&&yt.add("sepia"),t.filter.vintage&&yt.add("brownie"),t.filter.sepia&&yt.add("sepia"),t.filter.kodachrome&&yt.add("kodachrome"),t.filter.technicolor&&yt.add("technicolor"),t.filter.polaroid&&yt.add("polaroid"),t.filter.pixelate!==0&&yt.add("pixelate",t.filter.pixelate),((f=yt.get())==null?void 0:f.length)>1?ea=yt.apply(Qt):ea=yt.draw(Qt)):(t.debug&&K("input process error: cannot initialize filters"),ne.webgl.supported=!1,t.filter.enabled=!1,Gh(Qt,ea))):(Gh(Qt,ea),yt&&(yt=null),ne.filter=!!yt),!a)return{tensor:null,canvas:ea};if(!ea)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&&Sr)l=Sr?Sr.fromPixels(e):null;else{u=e.data.length/e.height/e.width;let m=new Uint8Array(e.data.buffer);l=Ue(m,[e.height,e.width,u],"int32")}else if((!bu||ea.width!==bu.width||ea.height!==bu.height)&&(bu=Rn(ea.width,ea.height)),Sr&&ne.browser)t.backend==="webgl"||t.backend==="humangl"||t.backend==="webgpu"?l=Sr.fromPixels(ea):(bu=Gh(ea),l=Sr.fromPixels(bu));else{let y=Gh(ea).getContext("2d").getImageData(0,0,s,i);u=y.data.length/s/i;let x=new Uint8Array(y.data.buffer);l=Ue(x,[s,i,u])}if(u===4){let m=lp(l,[0,0,0],[-1,-1,3]);J(l),l=m}if(!l)throw new Error("input error: cannot create tensor");let p=Xe(l,"float32"),c=t.filter.equalization?await Vh(p):Gt(p,0);if(J([l,p]),t.filter.autoBrightness){let m=ha(c),g=await m.data();t.filter.brightness=g[0]>1?1-g[0]/255:1-g[0],J(m)}return{tensor:c,canvas:t.filter.return?ea:null}}async function s9(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(!xn.inputTensor)xn.inputTensor=wa(t);else if(xn.inputTensor.shape[1]!==t.shape[1]||xn.inputTensor.shape[2]!==t.shape[2])J(xn.inputTensor),xn.inputTensor=wa(t);else{let n={};n.diff=fe(t,xn.inputTensor),n.squared=te(n.diff,n.diff),n.sum=rt(n.squared);let s=(await n.sum.data())[0]/(t.shape[1]||1)/(t.shape[2]||1)/255/3;J([xn.inputTensor,n.diff,n.squared,n.sum]),xn.inputTensor=wa(t),a=s<=(e.cacheSensitivity||0)}return a}async function i9(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=wa(t),n.input2=t.shape[1]!==a.shape[1]||t.shape[2]!==a.shape[2]?ye.resizeBilinear(a,[t.shape[1],t.shape[2]]):wa(a),n.diff=fe(n.input1,n.input2),n.squared=te(n.diff,n.diff),n.sum=rt(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 bp,vp,kp,Ap=class{constructor(){de(this,"browser");de(this,"node");de(this,"worker");de(this,"platform","");de(this,"agent","");de(this,"backends",[]);de(this,"initial");de(this,"filter");de(this,"tfjs");de(this,"offscreen");de(this,"perfadd",!1);de(this,"tensorflow",{version:void 0,gpu:void 0});de(this,"wasm",{supported:void 0,backend:void 0,simd:void 0,multithread:void 0});de(this,"webgl",{supported:void 0,backend:void 0,version:void 0,renderer:void 0,shader:void 0,vendor:void 0});de(this,"webgpu",{supported:void 0,backend:void 0,adapter:void 0});de(this,"cpu",{model:void 0,flags:[]});de(this,"kernels",[]);Gn(this,bp,void 0);Gn(this,vp,void 0);Gn(this,kp,void 0);if(this.browser=typeof navigator!="undefined",this.node=typeof process!="undefined"&&typeof process.versions!="undefined"&&typeof process.versions.node!="undefined",this.tfjs={version:xp["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 ja(this,bp)}set Canvas(t){mr(this,bp,t),globalThis.Canvas=t}get Image(){return ja(this,vp)}set Image(t){mr(this,vp,t),globalThis.Image=t}get ImageData(){return ja(this,kp)}set ImageData(t){mr(this,kp,t),globalThis.ImageData=t}async updateBackend(){this.backends=Object.keys(vt().registryFactory);try{this.tensorflow={version:tr().binding?tr().binding.TF_Version:void 0,gpu:tr().binding?tr().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 V().getAsync("WASM_HAS_SIMD_SUPPORT"),this.wasm.multithread=await V().getAsync("WASM_HAS_MULTITHREAD_SUPPORT"));let t=Rn(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();this.webgpu.adapter=await(n==null?void 0:n.requestAdapterInfo())}}catch(n){this.webgpu.supported=!1}try{this.kernels=Zn(ua()).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})}};bp=new WeakMap,vp=new WeakMap,kp=new WeakMap;var ne=new Ap;var qh=class{constructor(){de(this,"config");de(this,"element");de(this,"stream");de(this,"devices",[]);de(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});de(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{this.config.debug&&K("webcam","cannot get dom element",t.element);return}}else if(t.element instanceof HTMLVideoElement)this.element=t.element;else{this.config.debug&&K("webcam","unknown dom element",t.element);return}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)){this.config.debug&&K("webcam","no devices");return}try{this.stream=await navigator.mediaDevices.getUserMedia(a)}catch(i){K("webcam",i);return}if(!this.stream){this.config.debug&&K("webcam","no stream");return}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})});de(this,"pause",()=>{this.element&&this.element.pause()});de(this,"play",async()=>{this.element&&await this.element.play()});de(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 X3={};fr(X3,{"affectnet-mobilenet":()=>dce,age:()=>pce,"anti-spoofing":()=>Uce,antispoof:()=>Jpe,blazeface:()=>Qpe,"blazeface-back":()=>cce,"blazeface-front":()=>hce,"blazepose-detector":()=>fce,"blazepose-full":()=>mce,"blazepose-heavy":()=>gce,"blazepose-lite":()=>yce,centernet:()=>ece,default:()=>ahe,efficientpose:()=>xce,"efficientpose-i-lite":()=>Gce,"efficientpose-ii-lite":()=>Hce,"efficientpose-iv":()=>jce,emotion:()=>tce,faceboxes:()=>Ace,facemesh:()=>ace,"facemesh-attention":()=>vce,"facemesh-attention-pinto":()=>bce,"facemesh-detection-full":()=>kce,"facemesh-detection-short":()=>wce,faceres:()=>nce,"faceres-deep":()=>Ice,gear:()=>Cce,"gear-e1":()=>Sce,"gear-e2":()=>Tce,gender:()=>Ece,"gender-ssrnet-imdb":()=>Nce,handdetect:()=>Rce,"handlandmark-full":()=>Mce,"handlandmark-lite":()=>rce,"handlandmark-sparse":()=>$ce,handskeleton:()=>_ce,handtrack:()=>sce,"insightface-efficientnet-b0":()=>qce,"insightface-ghostnet-strides1":()=>Xce,"insightface-ghostnet-strides2":()=>Kce,"insightface-mobilenet-emore":()=>Zce,"insightface-mobilenet-swish":()=>Yce,iris:()=>ice,liveness:()=>oce,meet:()=>Pce,mobileface:()=>Fce,mobilefacenet:()=>Oce,models:()=>lce,"movenet-lightning":()=>uce,"movenet-multipose":()=>Dce,"movenet-thunder":()=>zce,nanodet:()=>Lce,"nanodet-e":()=>Jce,"nanodet-g":()=>Qce,"nanodet-m":()=>ehe,"nanodet-t":()=>the,posenet:()=>Bce,rvm:()=>Wce,selfie:()=>Vce});var Jpe=853098,Qpe=538928,ece=4030290,tce=820516,ace=1477958,nce=6978814,rce=2023432,sce=2964837,ice=2599092,oce=592976,lce=0,uce=4650216,dce=6920630,pce=161240,cce=538928,hce=402048,fce=5928856,mce=6339202,gce=27502466,yce=2726402,xce=5651240,Ace=2013002,bce=2387598,vce=2382414,kce=1026192,wce=201268,Ice=13957620,Sce=112438,Tce=112438,Cce=1498916,Nce=161236,Ece=201808,Rce=3515612,Mce=5431368,$ce=5286322,_ce=5502280,Pce=372228,Fce=2183192,Oce=5171976,Dce=9448838,zce=12477112,Lce=7574558,Bce=5032780,Wce=3739355,Vce=212886,Uce=853098,Gce=2269064,Hce=5651240,jce=25643252,qce=13013224,Xce=8093408,Kce=8049584,Zce=6938536,Yce=12168584,Jce=12319156,Qce=7574558,ehe=1887474,the=5294216,ahe={antispoof:Jpe,blazeface:Qpe,centernet:ece,emotion:tce,facemesh:ace,faceres:nce,"handlandmark-lite":rce,handtrack:sce,iris:ice,liveness:oce,models:lce,"movenet-lightning":uce,"affectnet-mobilenet":dce,age:pce,"blazeface-back":cce,"blazeface-front":hce,"blazepose-detector":fce,"blazepose-full":mce,"blazepose-heavy":gce,"blazepose-lite":yce,efficientpose:xce,faceboxes:Ace,"facemesh-attention-pinto":bce,"facemesh-attention":vce,"facemesh-detection-full":kce,"facemesh-detection-short":wce,"faceres-deep":Ice,"gear-e1":Sce,"gear-e2":Tce,gear:Cce,"gender-ssrnet-imdb":Nce,gender:Ece,handdetect:Rce,"handlandmark-full":Mce,"handlandmark-sparse":$ce,handskeleton:_ce,meet:Pce,mobileface:Fce,mobilefacenet:Oce,"movenet-multipose":Dce,"movenet-thunder":zce,nanodet:Lce,posenet:Bce,rvm:Wce,selfie:Vce,"anti-spoofing":Uce,"efficientpose-i-lite":Gce,"efficientpose-ii-lite":Hce,"efficientpose-iv":jce,"insightface-efficientnet-b0":qce,"insightface-ghostnet-strides1":Xce,"insightface-ghostnet-strides2":Kce,"insightface-mobilenet-emore":Zce,"insightface-mobilenet-swish":Yce,"nanodet-e":Jce,"nanodet-g":Qce,"nanodet-m":ehe,"nanodet-t":the};var Ra={cacheModels:!0,cacheSupported:!0,verbose:!0,debug:!1,modelBasePath:""},ma={};async function nhe(e,t){return Ra.debug&&K("load model fetch:",e,t),fetch(e,t)}function o9(e){Ra.cacheModels=e.cacheModels,Ra.verbose=e.debug,Ra.modelBasePath=e.modelBasePath}async function Me(e){var u,p,c,d;let t=Y8(Ra.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;ma[n]={name:n,sizeFromManifest:0,sizeLoadedWeights:0,sizeDesired:X3[n],inCache:!1,url:""},Ra.cacheSupported=typeof indexedDB!="undefined";let s={};try{s=Ra.cacheSupported&&Ra.cacheModels?await jn.listModels():{}}catch(h){Ra.cacheSupported=!1}ma[n].inCache=Ra.cacheSupported&&Ra.cacheModels&&Object.keys(s).includes(r),ma[n].url=ma[n].inCache?r:t;let i=typeof fetch=="undefined"?{}:{fetchFunc:(h,f)=>nhe(h,f)},o=new up(ma[n].url,i),l=!1;try{o.findIOHandler(),Ra.debug&&K("model load handler:",o.handler)}catch(h){K("error finding model i/o handler:",t,h)}try{let h=await((u=o.handler)==null?void 0:u.load())||null;ma[n].sizeFromManifest=((p=h==null?void 0:h.weightData)==null?void 0:p.byteLength)||0,h?o.loadSync(h):o=await s3(ma[n].inCache?r:t,i),ma[n].sizeLoadedWeights=((d=(c=o.artifacts)==null?void 0:c.weightData)==null?void 0:d.byteLength)||0,Ra.verbose&&K("load:",{model:n,url:o.modelUrl,bytes:ma[n].sizeLoadedWeights}),l=!0}catch(h){K("error loading model:",t,h)}if(l&&Ra.cacheModels&&Ra.cacheSupported&&!ma[n].inCache)try{let h=await o.save(r);Ra.debug&&K("model saved:",r,h)}catch(h){K("error saving model:",t,h)}return o}var K3="3.0.5";var kt={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 ihe(){let e=kt.gl;e&&(kt.extensions=e.getSupportedExtensions())}function l9(e){var t;if(e.config.backend==="humangl"&&(kt.name in vt().registry&&!((t=kt==null?void 0:kt.gl)!=null&&t.getParameter(kt.gl.VERSION))&&(K("humangl error: backend invalid context"),e.models.reset()),!a1(kt.name))){try{kt.canvas=Rn(100,100)}catch(r){K("humangl error: cannot create canvas:",r);return}try{if(kt.gl=kt.canvas.getContext("webgl2",kt.webGLattr),!kt.gl){K("humangl error: cannot get webgl context");return}if(!kt.gl.getParameter(kt.gl.VERSION).includes("2.0")){K("backend override: using fallback webgl backend as webgl 2.0 is not detected"),e.config.backend="webgl";return}kt.canvas&&(kt.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")}),kt.canvas.addEventListener("webglcontextrestored",s=>{K("humangl error: context restored:",s)}),kt.canvas.addEventListener("webglcontextcreationerror",s=>{K("humangl error: context create:",s)}))}catch(r){K("humangl error: cannot get webgl context:",r);return}try{Eh(2,kt.gl)}catch(r){K("humangl error: cannot set webgl context:",r);return}try{let r=new sl(kt.gl);yo(kt.name,()=>new fu(r),kt.priority)}catch(r){K("humangl error: cannot register webgl backend:",r);return}try{Zn("webgl").forEach(s=>{let i={...s,backendName:kt.name};yn(i)})}catch(r){K("humangl error: cannot update webgl backend registration:",r);return}try{V().flagRegistry.WEBGL_VERSION&&V().set("WEBGL_VERSION",2)}catch(r){K("humangl error: cannot set WebGL backend flags:",r);return}ihe();let a=tr(),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,kt.gl)}}var Le={tf255:255,tf1:1,tf2:2,tf05:.5,tf127:127.5,rgb:[.2989,.587,.114]};function u9(){Le.tf255=ze(255,"float32"),Le.tf1=ze(1,"float32"),Le.tf2=ze(2,"float32"),Le.tf05=ze(.5,"float32"),Le.tf127=ze(127.5,"float32"),Le.rgb=Ht([.2989,.587,.114],"float32")}async function uhe(){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 dhe(e){let t=[];if(!ne.kernels.includes("mod")){let a={kernelName:"Mod",backendName:ua(),kernelFunc:n=>Oe(()=>fe(n.inputs.a,te(xe(n.inputs.a,n.inputs.b),n.inputs.b)))};yn(a),ne.kernels.push("mod"),t.push("mod")}if(!ne.kernels.includes("floormod")){let a={kernelName:"FloorMod",backendName:ua(),kernelFunc:n=>Oe(()=>be(te(Qd(n.inputs.a,n.inputs.b),n.inputs.b),su(n.inputs.a,n.inputs.b)))};yn(a),ne.kernels.push("floormod"),t.push("floormod")}if(!ne.kernels.includes("rotatewithoffset")&&e.softwareKernels){let a={kernelName:"RotateWithOffset",backendName:ua(),kernelFunc:n=>Oe(()=>{let r=ua();Yd("cpu");let s=ye.rotateWithOffset(n.inputs.image,n.attrs.radians,n.attrs.fillValue,n.attrs.center);return Yd(r),s})};yn(a),ne.kernels.push("rotatewithoffset"),t.push("rotatewithoffset")}t.length>0&&e.debug&&K("registered kernels:",t)}var d9={};async function wp(e,t=!1){var a,n;if(e.state="backend",((a=e.config.backend)==null?void 0:a.length)===0&&(e.config.backend=await uhe()),t||ne.initial||e.config.backend&&e.config.backend.length>0&&ua()!==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(vt().registryFactory);if(e.config.backend==="humangl"&&!s.includes("humangl")&&(l9(e),s=Object.keys(vt().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?await i.requestAdapterInfo():void 0;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(V().flagRegistry.CANVAS2D_WILL_READ_FREQUENTLY&&V().set("CANVAS2D_WILL_READ_FREQUENTLY",!0),e.config.debug&&K("wasm path:",e.config.wasmPath),typeof Fh!="undefined")Fh(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 V().getAsync("WASM_HAS_MULTITHREAD_SUPPORT"),o=await V().getAsync("WASM_HAS_SIMD_SUPPORT"),e.config.debug&&K(`wasm execution: ${o?"simd":"no simd"} ${i?"multithreaded":"singlethreaded"}`),e.config.debug&&!o&&K("warning: wasm simd support is not enabled")}catch(l){K("wasm detection failed")}}try{await Yd(e.config.backend),await Jd()}catch(i){return K("error: cannot set backend:",e.config.backend,i),!1}e.config.debug&&(d9=JSON.parse(JSON.stringify(V().flags)))}if((ua()==="humangl"||ua()==="webgl")&&(V().flagRegistry.WEBGL_USE_SHAPES_UNIFORMS&&V().set("WEBGL_USE_SHAPES_UNIFORMS",!0),V().flagRegistry.WEBGL_EXP_CONV&&V().set("WEBGL_EXP_CONV",!0),e.config.debug&&typeof e.config.deallocate!="undefined"&&e.config.deallocate&&(K("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",!0),V().set("WEBGL_DELETE_TEXTURE_THRESHOLD",0))),ua(),e.config.debug){let s=V().flags,i={};for(let o of Object.keys(s))d9[o]!==s[o]&&(i[o]=s[o]);e.config.debug&&Object.keys(i).length>0&&K("backend:",ua(),"flags:",i)}if(e.config.flags&&Object.keys(e.config.flags).length>0){e.config.debug&&K("flags:",e.config.flags);for(let[s,i]of Object.entries(e.config.flags))V().set(s,i)}e1(),u9(),e.performance.initBackend=Math.trunc(ae()-r),e.config.backend=ua(),await ne.updateBackend(),dhe(e.config)}return!0}function Xh(e,t){for(let a of e){let n={kernelName:a,backendName:t.backend,kernelFunc:r=>{var s;return t.debug&&K("kernelFunc",a,t.backend,r),(s=r==null?void 0:r.inputs)==null?void 0:s.info}};yn(n)}ne.kernels=Zn(ua()).map(a=>a.kernelName.toLowerCase())}var e0={};fr(e0,{all:()=>Whe,body:()=>Zh,canvas:()=>Bhe,face:()=>Kh,gesture:()=>Qh,hand:()=>Yh,init:()=>ag,object:()=>Jh,options:()=>_t,person:()=>Lhe});var An=e=>{if(!e)K("draw error: invalid canvas");else if(!e.getContext)K("draw error: canvas context not defined");else{let t=e.getContext("2d");if(!t)K("draw error: cannot get canvas context");else return t}return null},To=e=>Math.round(e*180/Math.PI),ct=(e,t,a)=>e.replace(t,typeof a=="number"?a.toFixed(1):a),Co=(e,t)=>{if(!t.useDepth||typeof e=="undefined")return t.color;let a=Uint8ClampedArray.from([127+2*e,127-2*e,255]);return`rgba(${a[0]}, ${a[1]}, ${a[2]}, ${t.alpha})`};function bn(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 sr(e,t,a,n,r){e.fillStyle=Co(n,r),e.beginPath(),e.arc(t,a,r.pointSize,0,2*Math.PI),e.fill()}function ir(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 Z3(e,t,a){if(!(t.length<2)){e.beginPath(),e.moveTo(t[0][0],t[0][1]);for(let n of t)e.strokeStyle=Co(n[2]||0,a),e.lineTo(Math.trunc(n[0]),Math.trunc(n[1]));e.stroke(),a.fillPolygons&&(e.closePath(),e.fill())}}function c9(e,t,a){if(!(t.length<2)){if(e.lineWidth=a.lineWidth,!a.useCurves||t.length<=2){Z3(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 Y3(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 _t={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 Mn={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]},J3={count:468,mouth:13,symmetryLine:[13,Mn.midwayBetweenEyes[0]]},No={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},Q3=[{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]}],Ip=[[.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]],Eo=[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 phe=[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],che=[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],hhe=[33,133,362,263,1,78,308],I3e=phe.map(e=>Ip[e]),S3e=che.map(e=>Ip[e]),T3e=hhe.map(e=>Ip[e]);function ds(e){let t=e.map(a=>a[0]);return t.push(e[e.length-1][1]),t}var fhe=[[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]],mhe=[[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]],ghe=[[276,283],[283,282],[282,295],[295,285],[300,293],[293,334],[334,296],[296,336]],yhe=[[474,475],[475,476],[476,477],[477,474]],xhe=[[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]],Ahe=[[46,53],[53,52],[52,65],[65,55],[70,63],[63,105],[105,66],[66,107]],bhe=[[469,470],[470,471],[471,472],[472,469]],vhe=[[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]],C3e={lips:ds(fhe),leftEye:ds(mhe),leftEyebrow:ds(ghe),leftIris:ds(yhe),rightEye:ds(xhe),rightEyebrow:ds(Ahe),rightIris:ds(bhe),faceOval:ds(vhe)};var khe=[[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]],whe=[[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]],Ihe=[[276,283],[283,282],[282,295],[295,285],[300,293],[293,334],[334,296],[296,336]],She=[[474,475],[475,476],[476,477],[477,474]],The=[[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]],Che=[[46,53],[53,52],[52,65],[65,55],[70,63],[63,105],[105,66],[66,107]],Nhe=[[469,470],[470,471],[471,472],[472,469]],Ehe=[[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 ps(e){let t=e.map(a=>a[0]);return t.push(e[e.length-1][1]),t}var Rhe={lips:ps(khe),leftEye:ps(whe),leftEyebrow:ps(Ihe),leftIris:ps(She),rightEye:ps(The),rightEyebrow:ps(Che),rightIris:ps(Nhe),faceOval:ps(Ehe)},Mhe=Object.entries(Rhe).map(([e,t])=>t.map(a=>[a,e])).flat(),N3e=new Map(Mhe),Sp=[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],Ro=[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],Mo=[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 tt;function $he(e,t){var n,r,s,i,o,l,u,p,c;if(!tt.drawLabels||((n=tt.faceLabels)==null?void 0:n.length)===0)return;let a=tt.faceLabels.slice();if(e.score&&(a=ct(a,"[score]",100*e.score)),e.gender&&(a=ct(a,"[gender]",e.gender)),e.genderScore&&(a=ct(a,"[genderScore]",100*e.genderScore)),e.age&&(a=ct(a,"[age]",e.age)),e.distance&&(a=ct(a,"[distance]",100*e.distance)),e.real&&(a=ct(a,"[real]",100*e.real)),e.live&&(a=ct(a,"[live]",100*e.live)),e.emotion&&e.emotion.length>0){let d=e.emotion.map(h=>`${Math.trunc(100*h.score)}% ${h.emotion}`);d.length>3&&(d.length=3),a=ct(a,"[emotions]",d.join(" "))}(s=(r=e.rotation)==null?void 0:r.angle)!=null&&s.roll&&(a=ct(a,"[roll]",To(e.rotation.angle.roll))),(o=(i=e.rotation)==null?void 0:i.angle)!=null&&o.yaw&&(a=ct(a,"[yaw]",To(e.rotation.angle.yaw))),(u=(l=e.rotation)==null?void 0:l.angle)!=null&&u.pitch&&(a=ct(a,"[pitch]",To(e.rotation.angle.pitch))),(c=(p=e.rotation)==null?void 0:p.gaze)!=null&&c.bearing&&(a=ct(a,"[gaze]",To(e.rotation.gaze.bearing))),bn(t,a,e.box[0],e.box[1],tt)}function _he(e,t){var a,n,r,s;if((a=e.annotations)!=null&&a.leftEyeIris&&((n=e.annotations)!=null&&n.leftEyeIris[0])){t.strokeStyle=tt.useDepth?"rgba(255, 200, 255, 0.3)":tt.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(),tt.fillPolygons&&(t.fillStyle=tt.useDepth?"rgba(255, 255, 200, 0.3)":tt.color,t.fill())}if((r=e.annotations)!=null&&r.rightEyeIris&&((s=e.annotations)!=null&&s.rightEyeIris[0])){t.strokeStyle=tt.useDepth?"rgba(255, 200, 255, 0.3)":tt.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(),tt.fillPolygons&&(t.fillStyle=tt.useDepth?"rgba(255, 255, 200, 0.3)":tt.color,t.fill())}}function Phe(e,t){var a;if(tt.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]*To(e.rotation.angle.yaw)/90,r=e.box[1]+e.box[3]/2+e.box[2]*To(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]} ${e.box[1]+e.box[3]/2}
|
|
`);t.stroke(i),t.stroke(s)}}function Fhe(e,t){var a;if(tt.drawGaze&&((a=e.rotation)!=null&&a.gaze.strength)&&e.rotation.gaze.bearing&&e.annotations.leftEyeIris&&e.annotations.rightEyeIris&&e.annotations.leftEyeIris[0]&&e.annotations.rightEyeIris[0]){t.strokeStyle="pink",t.fillStyle="pink";let n=[e.annotations.leftEyeIris[0][0]+Math.sin(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[3],e.annotations.leftEyeIris[0][1]+Math.cos(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[2]];Y3(t,[e.annotations.leftEyeIris[0][0],e.annotations.leftEyeIris[0][1]],[n[0],n[1]],4);let r=[e.annotations.rightEyeIris[0][0]+Math.sin(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[3],e.annotations.rightEyeIris[0][1]+Math.cos(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[2]];Y3(t,[e.annotations.rightEyeIris[0][0],e.annotations.rightEyeIris[0][1]],[r[0],r[1]],4)}}function Ohe(e,t){if(tt.drawPolygons&&e.mesh.length>=468){t.lineWidth=1;for(let a=0;a<Eo.length/3;a++){let n=[Eo[a*3+0],Eo[a*3+1],Eo[a*3+2]].map(r=>e.mesh[r]);Z3(t,n,tt)}_he(e,t)}}function Dhe(e,t){if(tt.drawPoints)if((e==null?void 0:e.mesh.length)>=468)for(let a=0;a<e.mesh.length;a++)sr(t,e.mesh[a][0],e.mesh[a][1],e.mesh[a][2],tt),tt.drawAttention&&(Sp.includes(a)&&sr(t,e.mesh[a][0],e.mesh[a][1],e.mesh[a][2]+127,tt),Ro.includes(a)&&sr(t,e.mesh[a][0],e.mesh[a][1],e.mesh[a][2]-127,tt),Mo.includes(a)&&sr(t,e.mesh[a][0],e.mesh[a][1],e.mesh[a][2]-127,tt));else for(let[a,n]of Object.entries((e==null?void 0:e.annotations)||{})){if(!(n!=null&&n[0]))continue;let r=n[0];sr(t,r[0],r[1],0,tt),tt.drawLabels&&bn(t,a,r[0],r[1],tt)}}function zhe(e,t){tt.drawBoxes&&ir(t,e.box[0],e.box[1],e.box[2],e.box[3],tt)}function Kh(e,t,a){if(tt=Nt(_t,a),!t||!e)return;let n=An(e);if(n){n.font=tt.font,n.strokeStyle=tt.color,n.fillStyle=tt.color;for(let r of t)zhe(r,n),$he(r,n),r.mesh&&r.mesh.length>0&&(Dhe(r,n),Ohe(r,n),Phe(r,n),Fhe(r,n))}}function Zh(e,t,a){var s,i;let n=Nt(_t,a);if(!t||!e)return;let r=An(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&&(ir(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=ct(l,"[score]",100*t[o].score),bn(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=Co(t[o].keypoints[l].position[2],n),sr(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=ct(u,"[label]",l.part),u=ct(u,"[score]",100*l.score),bn(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)c9(r,u,n)}}}function Yh(e,t,a){var s,i;let n=Nt(_t,a);if(!t||!e)return;let r=An(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,ir(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=ct(l,"[label]",o.label),l=ct(l,"[score]",100*o.score),bn(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=Co(l[2],n),sr(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=ct(p,"[label]",l),bn(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=Co(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 Jh(e,t,a){var s;let n=Nt(_t,a);if(!t||!e)return;let r=An(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,ir(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=ct(o,"[label]",i.label),o=ct(o,"[score]",100*i.score),bn(r,o,i.box[0],i.box[1],n)}r.stroke()}}}function Qh(e,t,a){var r;let n=Nt(_t,a);if(!(!t||!e)&&n.drawGestures&&((r=n.gestureLabels)==null?void 0:r.length)>0){let s=An(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?`#${l[1]}`:"",c=n.gestureLabels.slice();c=ct(c,"[where]",l[0]),c=ct(c,"[who]",p),c=ct(c,"[what]",u[1]),bn(s,c,8,2+i*n.lineHeight,n),i+=1}}}}var cs={face:`face
|
|
confidence: [score]%
|
|
[gender] [genderScore]%
|
|
age: [age] years
|
|
distance: [distance]cm
|
|
real: [real]%
|
|
live: [live]%
|
|
[emotions]
|
|
roll: [roll]\xB0 yaw:[yaw]\xB0 pitch:[pitch]\xB0
|
|
gaze: [gaze]\xB0`,body:"body [score]%",bodyPart:"[label] [score]%",object:"[label] [score]%",hand:"[label] [score]%",finger:"[label]",gesture:"[where] [who]: [what]"};var tg=0;function Lhe(e,t,a){let n=Nt(_t,a);if(!t||!e)return;let r=An(e);if(r){r.lineJoin="round",r.font=n.font;for(let s=0;s<t.length;s++)if(n.drawBoxes){if(r.strokeStyle=n.color,r.fillStyle=n.color,ir(r,t[s].box[0],t[s].box[1],t[s].box[2],t[s].box[3],n),n.drawLabels){let i=`person #${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 Bhe(e,t){if(!e||!t)return;let a=An(t);a&&a.drawImage(e,0,0)}async function Whe(e,t,a){if(!(t!=null&&t.performance)||!e)return null;let n=ae(),r=Nt(_t,a),s=Promise.all([Kh(e,t.face,r),Zh(e,t.body,r),Yh(e,t.hand,r),Jh(e,t.object,r),Qh(e,t.gesture,r)]);return tg=ne.perfadd?tg+Math.round(ae()-n):Math.round(ae()-n),t.performance.draw=tg,s}function ag(){_t.faceLabels=cs.face,_t.bodyLabels=cs.body,_t.bodyPartLabels=cs.bodyPart,_t.handLabels=cs.hand,_t.fingerLabels=cs.finger,_t.objectLabels=cs.object,_t.gestureLabels=cs.gesture}var t0={};fr(t0,{connected:()=>rg,kpt:()=>ng});var ng=["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"],rg={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 vn,$o=224,m9,Vhe=5,a0=[8,16,32,32,32];function Uhe(){let e=[],t=0;for(;t<Vhe;){let a=0,n=t;for(;n<a0.length&&a0[n]===a0[t];)a+=2,n++;let r=a0[t],s=Math.ceil($o/r),i=Math.ceil($o/r);for(let o=0;o<s;++o)for(let l=0;l<i;++l)for(let u=0;u<a;++u)e.push({x:(l+.5)/i,y:(o+.5)/s});t=n}m9={x:Ht(e.map(a=>a.x)),y:Ht(e.map(a=>a.y))}}async function g9(e){if(ne.initial&&(vn=null),!vn&&e.body.detector&&e.body.detector.modelPath){vn=await Me(e.body.detector.modelPath);let t=vn!=null&&vn.executor?Object.values(vn.modelSignature.inputs):void 0;$o=Array.isArray(t)?parseInt(t[0].tensorShape.dim[1].size):0}else e.debug&&vn&&K("cached model:",vn.modelUrl);return Uhe(),vn}var f9=[5,5];function Ghe(e,t){return Oe(()=>{let a=Ia(e,12,1),n=De(a[0]),r=De(a[1]),s=De(a[2]),i=De(a[3]);n=be(xe(n,$o),t.x),r=be(xe(r,$o),t.y),s=te(xe(s,$o),f9[0]),i=te(xe(i,$o),f9[1]);let o=fe(n,xe(s,2)),l=fe(r,xe(i,2)),u=be(o,s),p=be(l,i);return la([o,l,u,p],1)})}async function Hhe(e,t,a,n){var u,p;let r=[],s={};s.boxes=Ghe(e,m9),s.scores=za(t),s.nms=await ye.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],f=[Math.round(h[0]*n[0]),Math.round(h[1]*n[1]),Math.round(h[2]*n[0]),Math.round(h[3]*n[1])],m={score:d,boxRaw:h,box:f};r.push(m)}return Object.keys(s).forEach(c=>J(s[c])),r}async function y9(e,t,a){let n={};n.res=vn==null?void 0:vn.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=De(n.logitsRaw),n.boxes=De(n.boxesRaw);let r=await Hhe(n.boxes,n.logits,t,a);return Object.keys(n).forEach(s=>J(n[s])),r}function hs(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 x9(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 n0(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 Wa,ig=256,sg=Number.MAX_SAFE_INTEGER,jhe={landmarks:["ld_3d","activation_segmentation","activation_heatmap","world_3d","output_poseflag"],detector:[]},s0=[],fs=[[0,0],[0,0],[0,0],[0,0]],A9=0,b9=e=>1-1/(1+Math.exp(e)),k9=e=>g9(e);async function w9(e){if(ne.initial&&(Wa=null),Wa)e.debug&&K("cached model:",Wa.modelUrl);else{Wa=await Me(e.body.modelPath);let t=Wa!=null&&Wa.executor?Object.values(Wa.modelSignature.inputs):void 0;ig=Array.isArray(t)?parseInt(t[0].tensorShape.dim[1].size):0}return Wa}function v9(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=ye.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];fs=[[0,0],o,l,[0,0]],n.pad=rr(n.cropped||e,fs),n.resize=ye.resizeBilinear(n.pad,[t,t]),r=xe(n.resize,Le.tf255)}else e.shape[1]!==t?(n.resize=ye.resizeBilinear(n.cropped||e,[t,t]),r=xe(n.resize,Le.tf255)):r=xe(n.cropped||e,Le.tf255);return Object.keys(n).forEach(o=>J(n[o])),r}function qhe(e,t,a){for(let n of e)n.position=[Math.trunc(n.position[0]*(t[0]+fs[2][0]+fs[2][1])/t[0]-fs[2][0]),Math.trunc(n.position[1]*(t[1]+fs[1][0]+fs[1][1])/t[1]-fs[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 Xhe(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 Khe(e,t,a){if(!(Wa!=null&&Wa.executor))return null;let n={};[n.ld,n.segmentation,n.heatmap,n.world,n.poseflag]=Wa==null?void 0:Wa.execute(e,jhe.landmarks);let r=(await n.poseflag.data())[0],s=await n.ld.data(),i=await n.world.data();Object.keys(n).forEach(f=>J(n[f]));let o=[],l=5;for(let f=0;f<s.length/l;f++){let m=b9(s[l*f+3]),g=b9(s[l*f+4]),y=Math.trunc(100*m*g*r)/100,x=[s[l*f+0]/ig,s[l*f+1]/ig,s[l*f+2]+0],A=[Math.trunc(a[0]*x[0]),Math.trunc(a[1]*x[1]),x[2]],b=[i[l*f+0],i[l*f+1],i[l*f+2]+0];o.push({part:ng[f],positionRaw:x,position:A,distance:b,score:y})}if(r<(t.body.minConfidence||0))return null;Xhe(o);let u=qhe(o,a),p=u.map(f=>f.position),c=hs(p,[a[0],a[1]]),d={};for(let[f,m]of Object.entries(rg)){let g=[];for(let y=0;y<m.length-1;y++){let x=u.find(b=>b.part===m[y]),A=u.find(b=>b.part===m[y+1]);x&&A&&g.push([x.position,A.position])}d[f]=g}return{id:0,score:Math.trunc(100*r)/100,box:c.box,boxRaw:c.boxRaw,keypoints:u,annotations:d}}async function og(e,t){var s,i,o;let a=[e.shape[2]||0,e.shape[1]||0],n=(t.body.skipTime||0)>ae()-A9,r=sg<(t.body.skipFrames||0);if(t.skipAllowed&&n&&r&&s0!==null)sg++;else{let l=[];if((i=(s=t.body)==null?void 0:s.detector)!=null&&i.enabled){let u=v9(e,224);l=await y9(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=v9(e,256,(o=l[u])==null?void 0:o.boxRaw);s0.length=0;let c=await Khe(p,t,a);J(p),c&&(c.id=u,s0.push(c))}A9=ae(),sg=0}return s0}var vu=[{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 Va,_o=0,lg=[],S9=0,ug=Number.MAX_SAFE_INTEGER;async function T9(e){if(ne.initial&&(Va=null),Va)e.debug&&K("cached model:",Va.modelUrl);else{Va=await Me(e.object.modelPath);let t=Va!=null&&Va.executor?Object.values(Va.modelSignature.inputs):void 0;_o=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}return Va}async function Zhe(e,t,a){if(!e)return[];let n={},r=[],s=await e.array();n.squeeze=De(e);let i=Ia(n.squeeze,6,1);n.stack=la([i[1],i[0],i[3],i[2]],1),n.boxes=De(n.stack),n.scores=De(i[4]),n.classes=De(i[5]),J([e,...i]),n.nms=await ye.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=vu[c].label,[h,f]=[s[0][u][0]/_o,s[0][u][1]/_o],m=[h,f,s[0][u][2]/_o-h,s[0][u][3]/_o-f],g=[Math.trunc(m[0]*t[0]),Math.trunc(m[1]*t[1]),Math.trunc(m[2]*t[0]),Math.trunc(m[3]*t[1])];r.push({id:l++,score:p,class:c,label:d,box:g,boxRaw:m})}return Object.keys(n).forEach(u=>J(n[u])),r}async function dg(e,t){if(!(Va!=null&&Va.executor))return[];let a=(t.object.skipTime||0)>ae()-S9,n=ug<(t.object.skipFrames||0);return t.skipAllowed&&a&&n&&lg.length>0?(ug++,lg):(ug=0,new Promise(async r=>{let s=[e.shape[2]||0,e.shape[1]||0],i=ye.resizeBilinear(e,[_o,_o]),o=t.object.enabled?Va==null?void 0:Va.execute(i,["tower_0/detections"]):null;S9=ae(),J(i);let l=await Zhe(o,s,t);lg=l,r(l)}))}var i0={};fr(i0,{connected:()=>cg,kpt:()=>pg});var pg=["head","neck","rightShoulder","rightElbow","rightWrist","chest","leftShoulder","leftElbow","leftWrist","bodyCenter","rightHip","rightKnee","rightAnkle","leftHip","leftKnee","leftAnkle"],cg={leftLeg:["leftHip","leftKnee","leftAnkle"],rightLeg:["rightHip","rightKnee","rightAnkle"],torso:["leftShoulder","rightShoulder","rightHip","leftHip","leftShoulder"],leftArm:["leftShoulder","leftElbow","leftWrist"],rightArm:["rightShoulder","rightElbow","rightWrist"],head:[]};var Et,N9=0,Ma={id:0,keypoints:[],box:[0,0,0,0],boxRaw:[0,0,0,0],score:0,annotations:{}},hg=Number.MAX_SAFE_INTEGER;async function E9(e){return ne.initial&&(Et=null),Et?e.debug&&K("cached model:",Et.modelUrl):Et=await Me(e.body.modelPath),Et}async function Yhe(e,t){let[a,n]=e.shape,r=Q(e,[n*a]),s=ha(r,0),i=(await s.data())[0];if(i>t){let o=ar(r,0),l=su(o,a),u=(await l.data())[0],p=xe(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 fg(e,t){if(!(Et!=null&&Et.executor)||!(Et!=null&&Et.inputs[0].shape))return[];let a=(t.body.skipTime||0)>ae()-N9,n=hg<(t.body.skipFrames||0);return t.skipAllowed&&a&&n&&Object.keys(Ma.keypoints).length>0?(hg++,[Ma]):(hg=0,new Promise(async r=>{let s=Oe(()=>{var f,m;let c=ye.resizeBilinear(e,[((f=Et==null?void 0:Et.inputs[0].shape)==null?void 0:f[2])||0,((m=Et==null?void 0:Et.inputs[0].shape)==null?void 0:m[1])||0],!1),d=te(c,Le.tf2);return fe(d,Le.tf1)}),i;if(t.body.enabled&&(i=Et==null?void 0:Et.execute(s)),N9=ae(),J(s),i){Ma.keypoints.length=0;let c=De(i);J(i);let d=Ca(c,2);J(c);for(let h=0;h<d.length;h++){let[f,m,g]=await Yhe(d[h],t.body.minConfidence);g>(t.body.minConfidence||0)&&Ma.keypoints.push({score:Math.round(100*g)/100,part:pg[h],positionRaw:[f/Et.inputs[0].shape[2],m/Et.inputs[0].shape[1]],position:[Math.round(e.shape[2]*f/Et.inputs[0].shape[2]),Math.round(e.shape[1]*m/Et.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(cg)){let h=[];for(let f=0;f<d.length-1;f++){let m=Ma.keypoints.find(y=>y.part===d[f]),g=Ma.keypoints.find(y=>y.part===d[f+1]);m&&g&&m.score>(t.body.minConfidence||0)&&g.score>(t.body.minConfidence||0)&&h.push([m.position,g.position])}Ma.annotations[c]=h}r([Ma])}))}var ku=e=>[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])],o0=e=>[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2,1],l0=(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],u0=(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}},mg=(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=ye.cropAndResize(t,[s],[0],a),o=xe(i,Le.tf255);return J(i),o},d0=(e,t)=>{let a=o0(e),n=ku(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}},p0=e=>{let t=o0(e),a=ku(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])]}},P9=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}},gg=[[1,0,0],[0,1,0],[0,0,1]],Jhe=e=>e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI)),Qhe=(e,t)=>Jhe(Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]));var M9=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]],Po=(e,t)=>{let a=0;for(let n=0;n<e.length;n++)a+=e[n]*t[n];return a},e0e=(e,t)=>{let a=[];for(let n=0;n<e.length;n++)a.push(e[n][t]);return a},$9=(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(Po(e[r],e0e(t,s)))}return a},F9=(e,t)=>{let a=Math.cos(e),n=Math.sin(e),r=[[a,-n,0],[n,a,0],[0,0,1]],s=M9(t[0],t[1]),i=$9(s,r),o=M9(-t[0],-t[1]);return $9(i,o)},t0e=e=>{let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],a=[e[0][2],e[1][2]],n=[-Po(t[0],a),-Po(t[1],a)];return[t[0].concat(n[0]),t[1].concat(n[1]),[0,0,1]]},a0e=(e,t)=>[Po(e,t[0]),Po(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 D9(e,t,a,n,r){let s=ku(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?F9(a,[0,0]):gg,u=o?i.map(h=>[...a0e(h,l),h[2]]):i,p=o?t0e(n):gg,c=o0(t),d=[Po(c,p[0]),Po(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 z9(e,t,a,n){let r=t.landmarks.length>=J3.count?J3.symmetryLine:No.symmetryLine,s=0,i=gg,o;if(e&&ne.kernels.includes("rotatewithoffset"))if(s=Qhe(t.landmarks[r[0]],t.landmarks[r[1]]),s&&s!==0&&Math.abs(s)>.2){let u=o0(t),p=[u[0]/a.shape[2],u[1]/a.shape[1]],c=ye.rotateWithOffset(a,s,0,[p[0],p[1]]);i=F9(-s,u),o=mg(t,c,[n,n]),J(c)}else o=mg(t,a,[n,n]);else o=mg(t,a,[n,n]);return[s,i,o]}var n0e=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]},L9=(e,t)=>{let a=n0e(e),n=ku(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,r0e=1.4,Ln,c0=null,ms=0,wu=null,W9=()=>ms;async function V9(e){var t;return ne.initial&&(Ln=null),Ln?e.debug&&K("cached model:",Ln.modelUrl):Ln=await Me((t=e.face.detector)==null?void 0:t.modelPath),ms=Ln.executor&&Ln.inputs[0].shape?Ln.inputs[0].shape[2]:256,wu=ze(ms,"int32"),c0=Kn(O9(ms)),Ln}function s0e(e){if(!c0||!wu)return gn([0,0]);let t={};t.boxStarts=Fe(e,[0,1],[-1,2]),t.centers=be(t.boxStarts,c0),t.boxSizes=Fe(e,[0,3],[-1,2]),t.boxSizesNormalized=xe(t.boxSizes,wu),t.centersNormalized=xe(t.centers,wu),t.halfBoxSize=xe(t.boxSizesNormalized,Le.tf2),t.starts=fe(t.centersNormalized,t.halfBoxSize),t.ends=be(t.centersNormalized,t.halfBoxSize),t.startNormalized=te(t.starts,wu),t.endNormalized=te(t.ends,wu);let a=ru([t.startNormalized,t.endNormalized],1);return Object.keys(t).forEach(n=>J(t[n])),a}async function U9(e,t){var o,l,u,p,c,d;if(!e||e.isDisposedInternal||e.shape.length!==4||e.shape[1]<1||e.shape[2]<1)return[];let a={};a.resized=ye.resizeBilinear(e,[ms,ms]),a.div=xe(a.resized,Le.tf127),a.normalized=fe(a.div,Le.tf05);let n=Ln==null?void 0:Ln.execute(a.normalized);if(Array.isArray(n)&&n.length>2){let h=n.sort((f,m)=>f.size-m.size);a.concat384=st([h[0],h[2]],2),a.concat512=st([h[1],h[3]],2),a.concat=st([a.concat512,a.concat384],1),a.batch=De(a.concat,[0])}else Array.isArray(n)?a.batch=De(n[0]):a.batch=De(n);J(n),a.boxes=s0e(a.batch),a.logits=Fe(a.batch,[0,0],[-1,1]),a.sigmoid=za(a.logits),a.scores=De(a.sigmoid),a.nms=await ye.nonMaxSuppressionAsync(a.boxes,a.scores,((o=t.face.detector)==null?void 0:o.maxDetected)||0,((l=t.face.detector)==null?void 0:l.iouThreshold)||0,((u=t.face.detector)==null?void 0:u.minConfidence)||0);let r=await a.nms.array(),s=[],i=await a.scores.data();for(let h=0;h<r.length;h++){let f=i[r[h]];if(f>(((p=t.face.detector)==null?void 0:p.minConfidence)||0)){let m={};m.bbox=Fe(a.boxes,[r[h],0],[1,-1]),m.slice=Fe(a.batch,[r[h],B9-1],[1,-1]),m.squeeze=De(m.slice),m.landmarks=Q(m.squeeze,[B9,-1]);let g=await m.bbox.data(),y={startPoint:[g[0],g[1]],endPoint:[g[2],g[3]],landmarks:await m.landmarks.array(),confidence:f};m.anchor=Fe(c0,[r[h],0],[1,2]);let x=await m.anchor.data(),A=_9(y,[(e.shape[2]||0)/ms,(e.shape[1]||0)/ms],x),b=d0(A,t.face.scale||r0e),k=p0(b);k.size[0]>(((c=t.face.detector)==null?void 0:c.minSize)||0)&&k.size[1]>(((d=t.face.detector)==null?void 0:d.minSize)||0)&&s.push(k),Object.keys(m).forEach(S=>J(m[S]))}}return Object.keys(a).forEach(h=>J(a[h])),s}var tn,gs=0,i0e=2.3,xg=Mn.leftEyeLower0,Ag=Mn.rightEyeLower0,Iu={leftBounds:[xg[0],xg[xg.length-1]],rightBounds:[Ag[0],Ag[Ag.length-1]]},Su={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};async function X9(e){var t,a;return ne.initial&&(tn=null),tn?e.debug&&K("cached model:",tn.modelUrl):tn=await Me((t=e.face.iris)==null?void 0:t.modelPath),gs=tn!=null&&tn.executor&&((a=tn.inputs)!=null&&a[0].shape)?tn.inputs[0].shape[2]:0,gs===-1&&(gs=64),tn}function h0(e,t,a,n){for(let r=0;r<Q3.length;r++){let{key:s,indices:i}=Q3[r],o=Mn[`${a}${s}`];if(!n||n.includes(s))for(let l=0;l<i.length;l++){let u=i[l];e[o[l]]=[t[u][0],t[u][1],(t[u][2]+e[o[l]][2])/2]}}}var o0e=e=>{let t=e[Iu.leftBounds[0]][2],a=e[Iu.rightBounds[0]][2];return t-a},H9=(e,t,a,n,r,s=!1)=>{let i=p0(d0(P9([e[a],e[n]]),i0e)),o=ku(i),l=ye.cropAndResize(t,[[i.startPoint[1]/r,i.startPoint[0]/r,i.endPoint[1]/r,i.endPoint[0]/r]],[0],[gs,gs]);if(s&&ne.kernels.includes("flipleftright")){let u=ye.flipLeftRight(l);J(l),l=u}return{box:i,boxSize:o,crop:l}},j9=(e,t,a,n=!1)=>{let r=[];for(let s=0;s<Su.numCoordinates;s++){let i=e[s*3],o=e[s*3+1],l=e[s*3+2];r.push([(n?1-i/gs:i/gs)*a[0]+t.startPoint[0],o/gs*a[1]+t.startPoint[1],l])}return{rawCoords:r,iris:r.slice(Su.index)}},q9=(e,t,a)=>{let n=e[Mn[`${a}EyeUpper0`][Su.upperCenter]][2],r=e[Mn[`${a}EyeLower0`][Su.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 K9(e,t,a){if(!(tn!=null&&tn.executor))return e;let{box:n,boxSize:r,crop:s}=H9(e,t,Iu.leftBounds[0],Iu.leftBounds[1],a,!0),{box:i,boxSize:o,crop:l}=H9(e,t,Iu.rightBounds[0],Iu.rightBounds[1],a,!0),u=st([s,l]);J(s),J(l);let p=tn.execute(u);J(u);let c=await p.data();J(p);let d=c.slice(0,Su.numCoordinates*3),{rawCoords:h,iris:f}=j9(d,n,r,!0),m=c.slice(Su.numCoordinates*3),{rawCoords:g,iris:y}=j9(m,i,o,!1),x=o0e(e);Math.abs(x)<30?(h0(e,h,"left",null),h0(e,g,"right",null)):x<1?h0(e,h,"left",["EyeUpper0","EyeLower0"]):h0(e,g,"right",["EyeUpper0","EyeLower0"]);let A=q9(e,f,"left"),b=q9(e,y,"right");return e.concat(A).concat(b)}async function Y9(e,t){var s,i,o,l,u,p,c,d,h,f;let a={lips:await((i=(s=t.filter(m=>m.size===160))==null?void 0:s[0])==null?void 0:i.data()),irisL:await((l=(o=t.filter(m=>m.size===10))==null?void 0:o[0])==null?void 0:l.data()),eyeL:await((p=(u=t.filter(m=>m.size===142))==null?void 0:u[0])==null?void 0:p.data()),irisR:await((d=(c=t.filter(m=>m.size===10))==null?void 0:c[1])==null?void 0:d.data()),eyeR:await((f=(h=t.filter(m=>m.size===142))==null?void 0:h[1])==null?void 0:f.data())};for(let m of Object.values(a))if(!m)return e;let n=Ro.reduce((m,g)=>m+=e[g][2],0)/Ro.length;for(let m=0;m<a.irisL.length/2;m++)e.push([a.irisL[2*m+0],a.irisL[2*m+1],n]);let r=Mo.reduce((m,g)=>m+=e[g][2],0)/Mo.length;for(let m=0;m<a.irisR.length/2;m++)e.push([a.irisR[2*m+0],a.irisR[2*m+1],r]);for(let m=0;m<a.eyeL.length/2;m++)e[Ro[m]]=[a.eyeL[2*m+0],a.eyeL[2*m+1],e[Ro[m]][2]];for(let m=0;m<a.eyeR.length/2;m++)e[Mo[m]]=[a.eyeR[2*m+0],a.eyeR[2*m+1],e[Mo[m]][2]];for(let m=0;m<a.lips.length/2;m++)e[Sp[m]]=[a.lips[2*m+0],a.lips[2*m+1],e[Sp[m]][2]];return e}var or={boxes:[],skipped:Number.MAX_SAFE_INTEGER,timestamp:0},wt=null,Tp=0;async function J9(e,t){var l,u,p,c,d,h,f,m,g,y;let a=(((l=t.face.detector)==null?void 0:l.skipTime)||0)>ae()-or.timestamp,n=or.skipped<(((u=t.face.detector)==null?void 0:u.skipFrames)||0);!t.skipAllowed||!a||!n||or.boxes.length===0?(or.boxes=await U9(e,t),or.timestamp=ae(),or.skipped=0):or.skipped++;let r=[],s=[],i=0,o=Tp;for(let x=0;x<or.boxes.length;x++){let A=or.boxes[x],b=0,k,S={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,k,S.tensor]=z9((p=t.face.detector)==null?void 0:p.rotation,A,e,(c=t.face.mesh)!=null&&c.enabled?Tp:W9()),t.filter.equalization){let C=S.tensor?await Vh(S.tensor):void 0;J(S.tensor),C&&(S.tensor=C)}if(S.boxScore=Math.round(100*A.confidence)/100,!((d=t.face.mesh)!=null&&d.enabled)||!(wt!=null&&wt.executor)){S.box=l0(A,e),S.boxRaw=u0(A,e),S.score=S.boxScore,S.size=A.size,S.mesh=A.landmarks,S.meshRaw=S.mesh.map(C=>[C[0]/(e.shape[2]||0),C[1]/(e.shape[1]||0),(C[2]||0)/o]);for(let C of Object.keys(No))S.annotations[C]=[S.mesh[No[C]]]}else if(!wt)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(S.tensor),r;let C=wt.execute(S.tensor),$=await C.find(M=>M.shape[M.shape.length-1]===1).data();if(S.faceScore=Math.round(100*$[0])/100,S.faceScore<(((f=t.face.detector)==null?void 0:f.minConfidence)||1)){if(A.confidence=S.faceScore,t.face.mesh.keepInvalid){S.box=l0(A,e),S.boxRaw=u0(A,e),S.score=S.boxScore,S.mesh=A.landmarks,S.meshRaw=S.mesh.map(M=>[M[0]/(e.shape[2]||1),M[1]/(e.shape[1]||1),(M[2]||0)/o]);for(let M of Object.keys(No))S.annotations[M]=[S.mesh[No[M]]]}}else{let M=C.find(D=>D.shape[D.shape.length-1]===1404),R=Q(M,[-1,3]),I=await R.array();J(R),(m=t.face.attention)!=null&&m.enabled?I=await Y9(I,C):(g=t.face.iris)!=null&&g.enabled&&(I=await K9(I,S.tensor,Tp)),S.mesh=D9(I,A,b,k,Tp),S.meshRaw=S.mesh.map(D=>[D[0]/(e.shape[2]||0),D[1]/(e.shape[1]||0),(D[2]||0)/o]);for(let D of Object.keys(Mn))S.annotations[D]=Mn[D].map(W=>S.mesh[W]);S.score=S.faceScore;let _={...L9(S.mesh,A),confidence:A.confidence,landmarks:A.landmarks,size:A.size};S.box=l0(_,e),S.boxRaw=u0(_,e),s.push(_)}J(C)}S.score>(((y=t.face.detector)==null?void 0:y.minConfidence)||1)?r.push(S):J(S.tensor)}return or.boxes=s,r}async function Q9(e){var t,a,n,r,s,i;return ne.initial&&(wt=null),(t=e.face.attention)!=null&&t.enabled&&(wt!=null&&wt.signature)&&Object.keys(((a=wt==null?void 0:wt.signature)==null?void 0:a.outputs)||{}).length<6&&(wt=null),wt?e.debug&&K("cached model:",wt.modelUrl):(n=e.face.attention)!=null&&n.enabled?wt=await Me(e.face.attention.modelPath):wt=await Me((r=e.face.mesh)==null?void 0:r.modelPath),Tp=wt.executor&&((s=wt==null?void 0:wt.inputs)!=null&&s[0].shape)?(i=wt==null?void 0:wt.inputs)==null?void 0:i[0].shape[2]:256,wt}var ek=Eo,tk=Ip;var kg=[],ta,f0=[],ak=0,nk=0,vg=Number.MAX_SAFE_INTEGER,wg=!1;async function rk(e){var t,a,n;return ne.initial&&(ta=null),ta?e.debug&&K("cached model:",ta.modelUrl):(ta=await Me((t=e.face.emotion)==null?void 0:t.modelPath),wg=((n=(a=ta==null?void 0:ta.inputs)==null?void 0:a[0].shape)==null?void 0:n[3])===3,wg?kg=["angry","disgust","fear","happy","neutral","sad","surprise"]:kg=["angry","disgust","fear","happy","sad","surprise","neutral"]),ta}async function Ig(e,t,a,n){var i,o;if(!ta)return[];let r=vg<(((i=t.face.emotion)==null?void 0:i.skipFrames)||0),s=(((o=t.face.emotion)==null?void 0:o.skipTime)||0)>ae()-nk;return t.skipAllowed&&s&&r&&ak===n&&f0[a]&&f0[a].length>0?(vg++,f0[a]):(vg=0,new Promise(async l=>{var p;let u=[];if((p=t.face.emotion)!=null&&p.enabled){let c={},d=ta!=null&&ta.inputs[0].shape?ta.inputs[0].shape[2]:0;if(t.face.emotion.crop>0){let f=t.face.emotion.crop,m=[[f,f,1-f,1-f]];c.resize=ye.cropAndResize(e,m,[0],[d,d])}else c.resize=ye.resizeBilinear(e,[d,d],!1);wg?(c.mul=te(c.resize,255),c.normalize=fe(c.mul,[103.939,116.779,123.68]),c.emotion=ta==null?void 0:ta.execute(c.normalize)):(c.channels=te(c.resize,Le.rgb),c.grayscale=rt(c.channels,3,!0),c.grayscaleSub=fe(c.grayscale,Le.tf05),c.grayscaleMul=te(c.grayscaleSub,Le.tf2),c.emotion=ta==null?void 0:ta.execute(c.grayscaleMul)),nk=ae();let h=await c.emotion.data();for(let f=0;f<h.length;f++)h[f]>(t.face.emotion.minConfidence||0)&&u.push({score:Math.min(.99,Math.trunc(100*h[f])/100),emotion:kg[f]});u.sort((f,m)=>m.score-f.score),Object.keys(c).forEach(f=>J(c[f]))}f0[a]=u,ak=n,l(u)}))}var ga,ys=[],ik=0,ok=0,Sg=Number.MAX_SAFE_INTEGER;async function lk(e){var t;return ne.initial&&(ga=null),ga?e.debug&&K("cached model:",ga.modelUrl):ga=await Me((t=e.face.description)==null?void 0:t.modelPath),ga}function u0e(e){let t=e.image||e.tensor||e;if(!(ga!=null&&ga.inputs[0].shape))return t;let a=ye.resizeBilinear(t,[ga.inputs[0].shape[2],ga.inputs[0].shape[1]],!1),n=te(a,Le.tf255);return J(a),n}async function Tg(e,t,a,n){var o,l,u,p;let r={age:0,gender:"unknown",genderScore:0,descriptor:[]};if(!(ga!=null&&ga.executor))return r;let s=Sg<(((o=t.face.description)==null?void 0:o.skipFrames)||0),i=(((l=t.face.description)==null?void 0:l.skipTime)||0)>ae()-ik;return t.skipAllowed&&s&&i&&ok===n&&((u=ys==null?void 0:ys[a])==null?void 0:u.age)>0&&((p=ys==null?void 0:ys[a])==null?void 0:p.genderScore)>0?(Sg++,ys[a]):(Sg=0,new Promise(async c=>{var d;if((d=t.face.description)!=null&&d.enabled){let h=u0e(e),f=ga==null?void 0:ga.execute(h);ik=ae(),J(h);let g=await f.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=ar(f.find(N=>N.shape[1]===100),1),A=(await x.data())[0];J(x);let k=await f.find(N=>N.shape[1]===100).data();r.age=Math.round(k[A-1]>k[A+1]?10*A-100*k[A-1]:10*A+100*k[A+1])/10,(Number.isNaN(g[0])||Number.isNaN(k[0]))&&K("faceres error:",{model:ga,result:f});let S=f.find(N=>N.shape[1]===1024),C=S?await S.data():[];r.descriptor=Array.from(C),f.forEach(N=>J(N))}ys[a]=r,ok=n,c(r)}))}var Tu=.1,Cg=.5;function d0e(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 dk(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 Mn.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]});Tu&&Tu>0&&(r=r.map(i=>({x:i.x>.5?i.x+Tu:i.x-Tu,y:i.y>.5?i.y+Tu:i.y-Tu})));for(let i=0;i<t;i++)for(let o=0;o<a;o++)d0e(i/t,o/t,r)||(n.set(Cg*n.get(0,o,i,0),0,o,i,0),n.set(Cg*n.get(0,o,i,1),0,o,i,1),n.set(Cg*n.get(0,o,i,2),0,o,i,2));return n.toTensor()}var aa,m0=[],Ng=Number.MAX_SAFE_INTEGER,pk=0,ck=0;async function hk(e){var t;return ne.initial&&(aa=null),aa?e.debug&&K("cached model:",aa.modelUrl):aa=await Me((t=e.face.antispoof)==null?void 0:t.modelPath),aa}async function Eg(e,t,a,n){var i,o;if(!(aa!=null&&aa.executor))return 0;let r=(((i=t.face.antispoof)==null?void 0:i.skipTime)||0)>ae()-ck,s=Ng<(((o=t.face.antispoof)==null?void 0:o.skipFrames)||0);return t.skipAllowed&&r&&s&&pk===n&&m0[a]?(Ng++,m0[a]):(Ng=0,new Promise(async l=>{let u=ye.resizeBilinear(e,[aa!=null&&aa.inputs[0].shape?aa.inputs[0].shape[2]:0,aa!=null&&aa.inputs[0].shape?aa.inputs[0].shape[1]:0],!1),p=aa==null?void 0:aa.execute(u),c=(await p.data())[0];m0[a]=Math.round(100*c)/100,pk=n,ck=ae(),J([u,p]),l(m0[a])}))}var na,g0=[],Rg=Number.MAX_SAFE_INTEGER,mk=0,gk=0;async function yk(e){var t;return ne.initial&&(na=null),na?e.debug&&K("cached model:",na.modelUrl):na=await Me((t=e.face.liveness)==null?void 0:t.modelPath),na}async function Mg(e,t,a,n){var i,o;if(!(na!=null&&na.executor))return 0;let r=(((i=t.face.liveness)==null?void 0:i.skipTime)||0)>ae()-gk,s=Rg<(((o=t.face.liveness)==null?void 0:o.skipFrames)||0);return t.skipAllowed&&r&&s&&mk===n&&g0[a]?(Rg++,g0[a]):(Rg=0,new Promise(async l=>{let u=ye.resizeBilinear(e,[na!=null&&na.inputs[0].shape?na.inputs[0].shape[2]:0,na!=null&&na.inputs[0].shape?na.inputs[0].shape[1]:0],!1),p=na==null?void 0:na.execute(u),c=(await p.data())[0];g0[a]=Math.round(100*c)/100,mk=n,gk=ae(),J([u,p]),l(g0[a])}))}var $n,$g=[],c0e=["white","black","asian","indian","other"],h0e=[15,23,28,35.5,45.5,55.5,65],Ak=0,bk=0,_g=Number.MAX_SAFE_INTEGER;async function vk(e){var t;return ne.initial&&($n=null),$n?e.debug&&K("cached model:",$n.modelUrl):$n=await Me((t=e.face.gear)==null?void 0:t.modelPath),$n}async function Pg(e,t,a,n){var i,o;if(!$n)return{age:0,gender:"unknown",genderScore:0,race:[]};let r=_g<(((i=t.face.gear)==null?void 0:i.skipFrames)||0),s=(((o=t.face.gear)==null?void 0:o.skipTime)||0)>ae()-bk;return t.skipAllowed&&s&&r&&Ak===n&&$g[a]?(_g++,$g[a]):(_g=0,new Promise(async l=>{var y,x;if(!($n!=null&&$n.inputs[0].shape))return;let u={},p=[[0,.1,.9,.9]];u.resize=ye.cropAndResize(e,p,[0],[$n.inputs[0].shape[2],$n.inputs[0].shape[1]]);let c={age:0,gender:"unknown",genderScore:0,race:[]};(y=t.face.gear)!=null&&y.enabled&&([u.age,u.gender,u.race]=$n.execute(u.resize,["age_output","gender_output","race_output"]));let d=await u.gender.data();c.gender=d[0]>d[1]?"male":"female",c.genderScore=Math.round(100*(d[0]>d[1]?d[0]:d[1]))/100;let h=await u.race.data();for(let A=0;A<h.length;A++)h[A]>(((x=t.face.gear)==null?void 0:x.minConfidence)||.2)&&c.race.push({score:Math.round(100*h[A])/100,race:c0e[A]});c.race.sort((A,b)=>b.score-A.score);let m=Array.from(await u.age.data()).map((A,b)=>[h0e[b],A]).sort((A,b)=>b[1]-A[1]),g=m[0][0];for(let A=1;A<m.length;A++)g+=m[A][1]*(m[A][0]-g);c.age=Math.round(10*g)/10,Object.keys(u).forEach(A=>J(u[A])),$g[a]=c,Ak=n,bk=ae(),l(c)}))}var an,y0=[],wk=0,Ik=0,Fg=Number.MAX_SAFE_INTEGER;async function Sk(e){return ne.initial&&(an=null),an?e.debug&&K("cached model:",an.modelUrl):an=await Me(e.face.ssrnet.modelPathAge),an}async function Og(e,t,a,n){var i,o,l,u;if(!an)return{age:0};let r=Fg<(((i=t.face.ssrnet)==null?void 0:i.skipFrames)||0),s=(((o=t.face.ssrnet)==null?void 0:o.skipTime)||0)>ae()-Ik;return t.skipAllowed&&r&&s&&wk===n&&((l=y0[a])!=null&&l.age)&&((u=y0[a])==null?void 0:u.age)>0?(Fg++,y0[a]):(Fg=0,new Promise(async p=>{var h;if(!(an!=null&&an.inputs)||!an.inputs[0]||!an.inputs[0].shape)return;let c={};c.resize=ye.resizeBilinear(e,[an.inputs[0].shape[2],an.inputs[0].shape[1]],!1),c.enhance=te(c.resize,Le.tf255);let d={age:0};if((h=t.face.ssrnet)!=null&&h.enabled&&(c.age=an.execute(c.enhance)),c.age){let f=await c.age.data();d.age=Math.trunc(10*f[0])/10}Object.keys(c).forEach(f=>J(c[f])),y0[a]=d,wk=n,Ik=ae(),p(d)}))}var Ua,x0=[],Ck=0,Nk=0,Dg=Number.MAX_SAFE_INTEGER,zg=[.2989,.587,.114];async function Ek(e){var t;return ne.initial&&(Ua=null),Ua?e.debug&&K("cached model:",Ua.modelUrl):Ua=await Me((t=e.face.ssrnet)==null?void 0:t.modelPathGender),Ua}async function Lg(e,t,a,n){var i,o,l,u;if(!Ua)return{gender:"unknown",genderScore:0};let r=Dg<(((i=t.face.ssrnet)==null?void 0:i.skipFrames)||0),s=(((o=t.face.ssrnet)==null?void 0:o.skipTime)||0)>ae()-Nk;return t.skipAllowed&&r&&s&&Ck===n&&((l=x0[a])!=null&&l.gender)&&((u=x0[a])==null?void 0:u.genderScore)>0?(Dg++,x0[a]):(Dg=0,new Promise(async p=>{var f;if(!(Ua!=null&&Ua.inputs[0].shape))return;let c={};c.resize=ye.resizeBilinear(e,[Ua.inputs[0].shape[2],Ua.inputs[0].shape[1]],!1),c.enhance=Oe(()=>{var g,y;let m;if(((y=(g=Ua==null?void 0:Ua.inputs)==null?void 0:g[0].shape)==null?void 0:y[3])===1){let[x,A,b]=Ia(c.resize,3,3),k=te(x,zg[0]),S=te(A,zg[1]),C=te(b,zg[2]),N=ph([k,S,C]);m=te(fe(N,Le.tf05),2)}else m=te(fe(c.resize,Le.tf05),2);return m});let d={gender:"unknown",genderScore:0};(f=t.face.ssrnet)!=null&&f.enabled&&(c.gender=Ua.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(m=>J(c[m])),x0[a]=d,Ck=n,Nk=ae(),p(d)}))}var nn,Bg=[],Mk=0,$k=0,_k=Number.MAX_SAFE_INTEGER;async function Pk(e){var t;return ne.initial&&(nn=null),nn?e.debug&&K("cached model:",nn.modelUrl):nn=await Me((t=e.face.mobilefacenet)==null?void 0:t.modelPath),nn}async function Wg(e,t,a,n){var i,o;if(!(nn!=null&&nn.executor))return[];let r=_k<(((i=t.face.mobilefacenet)==null?void 0:i.skipFrames)||0),s=(((o=t.face.mobilefacenet)==null?void 0:o.skipTime)||0)>ae()-$k;return t.skipAllowed&&s&&r&&Mk===n&&Bg[a]?(_k++,Bg[a]):new Promise(async l=>{var p;let u=[];if((p=t.face.mobilefacenet)!=null&&p.enabled&&(nn!=null&&nn.inputs[0].shape)){let c={};c.crop=ye.resizeBilinear(e,[nn.inputs[0].shape[2],nn.inputs[0].shape[1]],!1),c.data=nn.execute(c.crop);let d=await c.data.data();u=Array.from(d),Object.keys(c).forEach(h=>J(c[h]))}Bg[a]=u,Mk=n,$k=ae(),l(u)})}var rn,Vg=[],Ok=0,Dk=0,zk=Number.MAX_SAFE_INTEGER;async function Lk(e){return ne.initial&&(rn=null),rn?e.debug&&K("cached model:",rn.modelUrl):rn=await Me(e.face.insightface.modelPath),rn}async function Ug(e,t,a,n){var i,o;if(!(rn!=null&&rn.executor))return[];let r=zk<(((i=t.face.insightface)==null?void 0:i.skipFrames)||0),s=(((o=t.face.insightface)==null?void 0:o.skipTime)||0)>ae()-Dk;return t.skipAllowed&&s&&r&&Ok===n&&Vg[a]?(zk++,Vg[a]):new Promise(async l=>{var p;let u=[];if((p=t.face.insightface)!=null&&p.enabled&&(rn!=null&&rn.inputs[0].shape)){let c={};c.crop=ye.resizeBilinear(e,[rn.inputs[0].shape[2],rn.inputs[0].shape[1]],!1),c.data=rn.execute(c.crop);let d=await c.data.data();u=Array.from(d),Object.keys(c).forEach(h=>J(c[h]))}Vg[a]=u,Ok=n,Dk=ae(),l(u)})}var f0e=e=>{let t=(c,d)=>Math.atan2(c[1]-d[1],c[0]-d[0]);if(!e.annotations.rightEyeIris||!e.annotations.leftEyeIris)return{bearing:0,strength:0};let a=[0,-.1],n=1,r=(e.mesh[33][2]||0)>(e.mesh[263][2]||0),s=r?e.mesh[473]:e.mesh[468],i=r?[(e.mesh[133][0]+e.mesh[33][0])/2,(e.mesh[133][1]+e.mesh[33][1])/2]:[(e.mesh[263][0]+e.mesh[362][0])/2,(e.mesh[263][1]+e.mesh[362][1])/2],o=r?[e.mesh[133][0]-e.mesh[33][0],e.mesh[23][1]-e.mesh[27][1]]:[e.mesh[263][0]-e.mesh[362][0],e.mesh[253][1]-e.mesh[257][1]],l=[(i[0]-s[0])/o[0]-a[0],n*(s[1]-i[1])/o[1]-a[1]],u=Math.sqrt(l[0]*l[0]+l[1]*l[1]);return u=Math.min(u,e.boxRaw[2]/2,e.boxRaw[3]/2),{bearing:(t([0,0],l)+Math.PI/2)%Math.PI,strength:u}},Wk=(e,t)=>{let a=m=>{let g=Math.sqrt(m[0]*m[0]+m[1]*m[1]+m[2]*m[2]);return m[0]/=g,m[1]/=g,m[2]/=g,m},n=(m,g)=>{let y=m[0]-g[0],x=m[1]-g[1],A=m[2]-g[2];return[y,x,A]},r=(m,g)=>{let y=m[1]*g[2]-m[2]*g[1],x=m[2]*g[0]-m[0]*g[2],A=m[0]*g[1]-m[1]*g[0];return[y,x,A]},s=m=>{let[g,y,x,A,b,k,S,C,N]=m,$,M,R;return A<1?A>-1?(R=Math.asin(A),M=Math.atan2(-S,g),$=Math.atan2(-k,b)):(R=-Math.PI/2,M=-Math.atan2(C,N),$=0):(R=Math.PI/2,M=Math.atan2(C,N),$=0),Number.isNaN($)&&($=0),Number.isNaN(M)&&(M=0),Number.isNaN(R)&&(R=0),{pitch:2*-$,yaw:2*-M,roll:2*-R}},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(m=>[m[0]*t[0]/o,m[1]*t[1]/o,m[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),f=i.length===478?f0e(e):{bearing:0,strength:0};return{angle:h,matrix:d,gaze:f}};function Vk(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 Gg=async(e,t)=>{var f,m,g,y,x,A,b,k,S,C,N,$,M,R,I,_,D,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 J9(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 B=0;B<h.length;B++){if(e.analyze("Get Face"),!h[B].tensor||h[B].tensor.isDisposedInternal){K("Face object is disposed:",h[B].tensor);continue}if((f=e.config.face.detector)!=null&&f.mask){let ce=await dk(h[B]);J(h[B].tensor),ce&&(h[B].tensor=ce)}let Z=h[B].mesh&&h[B].mesh.length>200?Wk(h[B],[t.shape[2],t.shape[1]]):null;e.analyze("Start Emotion:"),e.config.async?i=(m=e.config.face.emotion)!=null&&m.enabled?Ig(h[B].tensor||Ue([]),e.config,B,h.length):[]:(e.state="run:emotion",a=ae(),i=(g=e.config.face.emotion)!=null&&g.enabled?await Ig(h[B].tensor||Ue([]),e.config,B,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?Eg(h[B].tensor||Ue([]),e.config,B,h.length):0:(e.state="run:antispoof",a=ae(),u=(x=e.config.face.antispoof)!=null&&x.enabled?await Eg(h[B].tensor||Ue([]),e.config,B,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?Mg(h[B].tensor||Ue([]),e.config,B,h.length):0:(e.state="run:liveness",a=ae(),p=(b=e.config.face.liveness)!=null&&b.enabled?await Mg(h[B].tensor||Ue([]),e.config,B,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=(k=e.config.face.gear)!=null&&k.enabled?Pg(h[B].tensor||Ue([]),e.config,B,h.length):null:(e.state="run:gear",a=ae(),r=(S=e.config.face.gear)!=null&&S.enabled?await Pg(h[B].tensor||Ue([]),e.config,B,h.length):null,e.performance.gear=Math.trunc(ae()-a)),e.analyze("End GEAR:"),e.analyze("Start SSRNet:"),e.config.async?(n=(C=e.config.face.ssrnet)!=null&&C.enabled?Og(h[B].tensor||Ue([]),e.config,B,h.length):null,s=(N=e.config.face.ssrnet)!=null&&N.enabled?Lg(h[B].tensor||Ue([]),e.config,B,h.length):null):(e.state="run:ssrnet",a=ae(),n=($=e.config.face.ssrnet)!=null&&$.enabled?await Og(h[B].tensor||Ue([]),e.config,B,h.length):null,s=(M=e.config.face.ssrnet)!=null&&M.enabled?await Lg(h[B].tensor||Ue([]),e.config,B,h.length):null,e.performance.ssrnet=Math.trunc(ae()-a)),e.analyze("End SSRNet:"),e.analyze("Start MobileFaceNet:"),e.config.async?o=(R=e.config.face.mobilefacenet)!=null&&R.enabled?Wg(h[B].tensor||Ue([]),e.config,B,h.length):null:(e.state="run:mobilefacenet",a=ae(),o=(I=e.config.face.mobilefacenet)!=null&&I.enabled?await Wg(h[B].tensor||Ue([]),e.config,B,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?Ug(h[B].tensor||Ue([]),e.config,B,h.length):null:(e.state="run:mobilefacenet",a=ae(),l=(D=e.config.face.insightface)!=null&&D.enabled?await Ug(h[B].tensor||Ue([]),e.config,B,h.length):null,e.performance.mobilefacenet=Math.trunc(ae()-a)),e.analyze("End InsightFace:"),e.analyze("Start Description:"),e.config.async?c=Tg(h[B].tensor||Ue([]),e.config,B,h.length):(e.state="run:description",a=ae(),c=await Tg(h[B].tensor||Ue([]),e.config,B,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?Vk(h[B],t.shape[2]):0,re=(H=e.config.face.detector)!=null&&H.return?De(h[B].tensor):null;J(h[B].tensor),h[B].tensor&&delete h[B].tensor;let ee={...h[B],id:B};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 $a={thumb:0,index:1,middle:2,ring:3,pinky:4,all:[0,1,2,3,4],nameMapping:{0:"thumb",1:"index",2:"middle",3:"ring",4:"pinky"},pointsMapping:{0:[[0,1],[1,2],[2,3],[3,4]],1:[[0,5],[5,6],[6,7],[7,8]],2:[[0,9],[9,10],[10,11],[11,12]],3:[[0,13],[13,14],[14,15],[15,16]],4:[[0,17],[17,18],[18,19],[19,20]]},getName:e=>$a.nameMapping[e],getPoints:e=>$a.pointsMapping[e]},As={none:0,half:1,full:2,nameMapping:{0:"none",1:"half",2:"full"},getName:e=>As.nameMapping[e]},Rt={verticalUp:0,verticalDown:1,horizontalLeft:2,horizontalRight:3,diagonalUpRight:4,diagonalUpLeft:5,diagonalDownRight:6,diagonalDownLeft:7,nameMapping:{0:"verticalUp",1:"verticalDown",2:"horizontalLeft",3:"horizontalRight",4:"diagonalUpRight",5:"diagonalUpLeft",6:"diagonalDownRight",7:"diagonalDownLeft"},getName:e=>Rt.nameMapping[e]},xs=class{constructor(t){de(this,"name");de(this,"curls");de(this,"directions");de(this,"weights");de(this,"weightsRelative");this.name=t,this.curls={},this.directions={},this.weights=[1,1,1,1,1],this.weightsRelative=[1,1,1,1,1]}curl(t,a,n){typeof this.curls[t]=="undefined"&&(this.curls[t]=[]),this.curls[t].push([a,n])}direction(t,a,n){this.directions[t]||(this.directions[t]=[]),this.directions[t].push([a,n])}weight(t,a){this.weights[t]=a;let n=this.weights.reduce((r,s)=>r+s,0);this.weightsRelative=this.weights.map(r=>r*5/n)}matchAgainst(t,a){let n=0;for(let r in t){let s=t[r],i=this.curls[r];if(typeof i=="undefined"){n+=this.weightsRelative[r];continue}for(let[o,l]of i)if(s===o){n+=l*this.weightsRelative[r];break}}for(let r in a){let s=a[r],i=this.directions[r];if(typeof i=="undefined"){n+=this.weightsRelative[r];continue}for(let[o,l]of i)if(s===o){n+=l*this.weightsRelative[r];break}}return n/10}};var{thumb:Bn,index:Er,middle:Rr,ring:Fo,pinky:Oo}=$a,{none:Wn,half:g0e,full:Vn}=As,{verticalUp:Cu,verticalDown:$5e,horizontalLeft:Hg,horizontalRight:y0e,diagonalUpRight:x0e,diagonalUpLeft:Nu,diagonalDownRight:_5e,diagonalDownLeft:P5e}=Rt,bs=new xs("thumbs up");bs.curl(Bn,Wn,1);bs.direction(Bn,Cu,1);bs.direction(Bn,Nu,.25);bs.direction(Bn,x0e,.25);for(let e of[$a.index,$a.middle,$a.ring,$a.pinky])bs.curl(e,Vn,1),bs.direction(e,Hg,1),bs.direction(e,y0e,1);var Wt=new xs("victory");Wt.curl(Bn,g0e,.5);Wt.curl(Bn,Wn,.5);Wt.direction(Bn,Cu,1);Wt.direction(Bn,Nu,1);Wt.curl(Er,Wn,1);Wt.direction(Er,Cu,.75);Wt.direction(Er,Nu,1);Wt.curl(Rr,Wn,1);Wt.direction(Rr,Cu,1);Wt.direction(Rr,Nu,.75);Wt.curl(Fo,Vn,1);Wt.direction(Fo,Cu,.2);Wt.direction(Fo,Nu,1);Wt.direction(Fo,Hg,.2);Wt.curl(Oo,Vn,1);Wt.direction(Oo,Cu,.2);Wt.direction(Oo,Nu,1);Wt.direction(Oo,Hg,.2);Wt.weight(Er,2);Wt.weight(Rr,2);var vs=new xs("point");vs.curl(Bn,Vn,1);vs.curl(Er,Wn,.5);vs.curl(Rr,Vn,.5);vs.curl(Fo,Vn,.5);vs.curl(Oo,Vn,.5);vs.weight(Er,2);vs.weight(Rr,2);var ks=new xs("middle finger");ks.curl(Bn,Wn,1);ks.curl(Er,Vn,.5);ks.curl(Rr,Vn,.5);ks.curl(Fo,Vn,.5);ks.curl(Oo,Vn,.5);ks.weight(Er,2);ks.weight(Rr,2);var Eu=new xs("open palm");Eu.curl(Bn,Wn,.75);Eu.curl(Er,Wn,.75);Eu.curl(Rr,Wn,.75);Eu.curl(Fo,Wn,.75);Eu.curl(Oo,Wn,.75);var Uk=[bs,Wt,vs,ks,Eu];var A0e=.7,Do={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 Gk(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 jk(e,t){if(!e||!t)return[0,0];let a=Gk(e[0],e[1],t[0],t[1]);if(e.length===2)return a;let n=Gk(e[1],e[2],t[1],t[2]);return[a,n]}function Hk(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 b0e(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),f=Math.sqrt(s*s+l*l+c*c),m=(f*f+d*d-h*h)/(2*f*d);m>1?m=1:m<-1&&(m=-1);let g=Math.acos(m);g=57.2958*g%180;let y;return g>Do.NO_CURL_START_LIMIT?y=As.none:g>Do.HALF_CURL_START_LIMIT?y=As.half:y=As.full,y}function qk(e,t,a,n){let r;return n===Math.abs(e)?e>0?r=Rt.horizontalLeft:r=Rt.horizontalRight:n===Math.abs(t)?t>0?r=Rt.horizontalLeft:r=Rt.horizontalRight:a>0?r=Rt.horizontalLeft:r=Rt.horizontalRight,r}function Xk(e,t,a,n){let r;return n===Math.abs(e)?e<0?r=Rt.verticalDown:r=Rt.verticalUp:n===Math.abs(t)?t<0?r=Rt.verticalDown:r=Rt.verticalUp:a<0?r=Rt.verticalDown:r=Rt.verticalUp,r}function v0e(e,t,a,n,r,s,i,o){let l,u=Xk(e,t,a,n),p=qk(r,s,i,o);return u===Rt.verticalUp?p===Rt.horizontalLeft?l=Rt.diagonalUpLeft:l=Rt.diagonalUpRight:p===Rt.horizontalLeft?l=Rt.diagonalDownLeft:l=Rt.diagonalDownRight,l}function k0e(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,f=0,m=c/(p+1e-5);m>1.5?d+=Do.DISTANCE_VOTE_POWER:m>.66?h+=Do.DISTANCE_VOTE_POWER:f+=Do.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],k=e[1],S=a[0],C=a[1];A===g?(S=a[0],C=a[1]):A===x&&(b=t[0],k=t[1]);let M=jk([b,k],[S,C]),R=Hk(M,Do.TOTAL_ANGLE_VOTE_POWER);d+=R[0],h+=R[1],f+=R[2];for(let _ of n){let D=Hk(_,Do.SINGLE_ANGLE_VOTE_POWER);d+=D[0],h+=D[1],f+=D[2]}let I;return d===Math.max(d,h,f)?I=Xk(l,o,u,c):f===Math.max(h,f)?I=qk(s,r,i,p):I=v0e(l,o,u,c,s,r,i,p),I}function Kk(e){let t=[],a=[],n=[],r=[];if(!e)return{curls:n,directions:r};for(let s of $a.all){let i=$a.getPoints(s),o=[],l=[];for(let u of i){let p=e[u[0]],c=e[u[1]],d=jk(p,c),h=d[0],f=d[1];o.push(h),l.push(f)}t.push(o),a.push(l)}for(let s of $a.all){let i=s===$a.thumb?1:0,o=$a.getPoints(s),l=e[o[i][0]],u=e[o[i+1][1]],p=e[o[3][1]],c=b0e(l,u,p),d=k0e(l,u,p,t[s].slice(i));n[s]=c,r[s]=d}return{curls:n,directions:r}}function A0(e){if(!e||e.length===0)return null;let t=Kk(e),a={};for(let n of $a.all)a[$a.getName(n)]={curl:As.getName(t.curls[n]),direction:Rt.getName(t.directions[n])};return a}function Zk(e){let t=[];if(!e||e.length===0)return t;let a=Kk(e);for(let n of Uk){let r=n.matchAgainst(a.curls,a.directions);r>=A0e&&t.push({name:n.name,confidence:r})}return t}var Yk=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},Jk=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 ${l<0?"up":"down"}`})}return t},Qk=e=>{var a,n,r,s;if(!e)return[];let t=[];for(let i=0;i<e.length;i++){if(!((n=(a=e[i].annotations)==null?void 0:a.leftEyeIris)!=null&&n[0])||!((s=(r=e[i].annotations)==null?void 0:r.rightEyeIris)!=null&&s[0]))continue;let o=e[i].annotations.leftEyeIris[3][0]-e[i].annotations.leftEyeIris[1][0],l=e[i].annotations.leftEyeIris[4][1]-e[i].annotations.leftEyeIris[2][1],u=Math.abs(o*l),p=e[i].annotations.rightEyeIris[3][0]-e[i].annotations.rightEyeIris[1][0],c=e[i].annotations.rightEyeIris[4][1]-e[i].annotations.rightEyeIris[2][1],d=Math.abs(p*c),h=!1;Math.abs(u-d)/Math.max(u,d)<.25&&(h=!0,t.push({iris:i,gesture:"facing center"}));let m=Math.abs(e[i].mesh[263][0]-e[i].annotations.leftEyeIris[0][0])/e[i].box[2],g=Math.abs(e[i].mesh[33][0]-e[i].annotations.rightEyeIris[0][0])/e[i].box[2];(m>.06||g>.06)&&(h=!1),m>g?m>.05&&t.push({iris:i,gesture:"looking right"}):g>.05&&t.push({iris:i,gesture:"looking left"});let y=Math.abs(e[i].mesh[145][1]-e[i].annotations.rightEyeIris[0][1])/e[i].box[3],x=Math.abs(e[i].mesh[374][1]-e[i].annotations.leftEyeIris[0][1])/e[i].box[3];(x<.01||y<.01||x>.022||y>.022)&&(h=!1),(x<.01||y<.01)&&t.push({iris:i,gesture:"looking down"}),(x>.022||y>.022)&&t.push({iris:i,gesture:"looking up"}),h&&t.push({iris:i,gesture:"looking center"})}return t},ew=e=>{if(!e)return[];let t=[];for(let a=0;a<e.length;a++){let n=[];if(e[a].annotations)for(let[r,s]of Object.entries(e[a].annotations))r!=="palmBase"&&Array.isArray(s)&&s[0]&&n.push({name:r.toLowerCase(),position:s[0]});if(n&&n.length>0){let r=n.reduce((i,o)=>(i.position[2]||0)<(o.position[2]||0)?i:o);t.push({hand:a,gesture:`${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=Zk(e[a].keypoints);for(let s of r)t.push({hand:a,gesture:s.name})}}return t};function b0(e){return[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])]}function Cp(e){return[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2]}function nw(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 ye.cropAndResize(t,s,[0],a)}function rw(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 v0(e,t=1.5){let a=Cp(e),n=b0(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 k0(e){let t=Cp(e),a=b0(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 I0e(e){return e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI))}function sw(e,t){let a=Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]);return I0e(a)}var tw=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]];function ws(e,t){let a=0;for(let n=0;n<e.length;n++)a+=e[n]*t[n];return a}function S0e(e,t){let a=[];for(let n=0;n<e.length;n++)a.push(e[n][t]);return a}function aw(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(ws(e[r],S0e(t,s)))}return a}function qg(e,t){let a=Math.cos(e),n=Math.sin(e),r=[[a,-n,0],[n,a,0],[0,0,1]],s=tw(t[0],t[1]),i=aw(s,r),o=tw(-t[0],-t[1]);return aw(i,o)}function iw(e){let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],a=[e[0][2],e[1][2]],n=[-ws(t[0],a),-ws(t[1],a)];return[t[0].concat(n[0]),t[1].concat(n[1]),[0,0,1]]}function Xg(e,t){return[ws(e,t[0]),ws(e,t[1])]}var lw=[{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 w0=class{constructor(t){de(this,"model");de(this,"anchors");de(this,"anchorsTensor");de(this,"inputSize");de(this,"inputSizeTensor");de(this,"doubleInputSizeTensor");var a,n,r,s;this.model=t,this.anchors=lw.map(i=>[i.x,i.y]),this.anchorsTensor=Kn(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=Ht([this.inputSize,this.inputSize]),this.doubleInputSizeTensor=Ht([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=xe(a.boxOffsets,this.inputSizeTensor),a.boxCenterPoints=be(a.div,this.anchorsTensor),a.halfBoxSizes=xe(a.boxSizes,this.doubleInputSizeTensor),a.sub=fe(a.boxCenterPoints,a.halfBoxSizes),a.startPoints=te(a.sub,this.inputSizeTensor),a.add=be(a.boxCenterPoints,a.halfBoxSizes),a.endPoints=te(a.add,this.inputSizeTensor);let n=ru([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=xe(n.reshape,this.inputSizeTensor),n.landmarks=be(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=ye.resizeBilinear(t,[this.inputSize,this.inputSize]),n.div=xe(n.resize,Le.tf127),n.image=fe(n.div,Le.tf1),n.batched=this.model.execute(n.image),n.predictions=De(n.batched),n.slice=Fe(n.predictions,[0,0],[-1,1]),n.sigmoid=za(n.slice),n.scores=De(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 ye.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(),f={startPoint:c,endPoint:d,palmLandmarks:h,confidence:r[l]},m=rw(f,[(t.shape[2]||1)/this.inputSize,(t.shape[1]||0)/this.inputSize]);i.push(m),Object.keys(u).forEach(g=>J(u[g]))}return Object.keys(n).forEach(l=>J(n[l])),i}};var N0e=5,uw=1.65,dw=[0,5,9,13,17,1,2],E0e=0,R0e=2,pw=0,I0=class{constructor(t,a){de(this,"handDetector");de(this,"handPoseModel");de(this,"inputSize");de(this,"storedBoxes");de(this,"skipped");de(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=>Xg([...s,1],a)),r=this.calculateLandmarksBoundingBox(n);return v0(k0(r),N0e)}getBoxForHandLandmarks(t){let a=this.calculateLandmarksBoundingBox(t),n=v0(k0(a),uw);n.palmLandmarks=[];for(let r=0;r<dw.length;r++)n.palmLandmarks.push(t[dw[r]].slice(0,2));return n}transformRawCoords(t,a,n,r){let s=b0(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=qg(n,[0,0]),u=o.map(h=>[...Xg(h,l),h[2]]),p=iw(r),c=[...Cp(a),1],d=[ws(c,p[0]),ws(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()-pw,i=this.skipped<(a.hand.skipFrames||0);a.skipAllowed&&s&&i&&(r=await this.handDetector.predict(t,a),this.skipped=0),a.skipAllowed&&this.skipped++,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?sw(u.palmLandmarks[E0e],u.palmLandmarks[R0e]):0,c=Cp(u),d=[c[0]/t.shape[2],c[1]/t.shape[1]],h=a.hand.rotation&&ne.kernels.includes("rotatewithoffset")?ye.rotateWithOffset(t,p,0,d):t.clone(),f=qg(-p,c),m=n?this.getBoxForPalmLandmarks(u.palmLandmarks,f):u,g=nw(m,h,[this.inputSize,this.inputSize]),y=xe(g,Le.tf255);J(g),J(h);let[x,A]=this.handPoseModel.execute(y);pw=ae(),J(y);let b=(await x.data())[0];if(J(x),b>=a.hand.minConfidence/4){let k=Q(A,[-1,3]),S=await k.array();J(A),J(k);let C=this.transformRawCoords(S,m,p,f),N=this.getBoxForHandLandmarks(C);this.storedBoxes[l]={...N,confidence:b};let $={landmarks:C,confidence:b,boxConfidence:u.confidence,fingerConfidence:b,box:{topLeft:N.startPoint,bottomRight:N.endPoint}};o.push($)}else this.storedBoxes[l]=null;J(A)}else{let p=v0(k0(u),uw),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 cw={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]},zo,Lo,hw;async function Kg(e,t){let a=await hw.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(cw))s[p]=cw[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=A0(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 fw(e){var a,n;ne.initial&&(zo=null,Lo=null),!zo||!Lo?[zo,Lo]=await Promise.all([e.hand.enabled?Me((a=e.hand.detector)==null?void 0:a.modelPath):null,e.hand.landmarks?Me((n=e.hand.skeleton)==null?void 0:n.modelPath):null]):(e.debug&&K("cached model:",zo.modelUrl),e.debug&&K("cached model:",Lo.modelUrl));let t=zo?new w0(zo):void 0;return t&&Lo&&(hw=new I0(t,Lo)),[zo,Lo]}var Ft=[null,null],$0e=["StatefulPartitionedCall/Postprocessor/Slice","StatefulPartitionedCall/Postprocessor/ExpandDims_1"],Is=[[0,0],[0,0]],_0e=["hand","fist","pinch","point","face","tip","pinchtip"],gw=4,yw=1.6,P0e=512,F0e=1.4,S0=Number.MAX_SAFE_INTEGER,Zg=0,Mr=[0,0],Pt={boxes:[],hands:[]},xw={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 Aw(e){var t;if(ne.initial&&(Ft[0]=null),Ft[0])e.debug&&K("cached model:",Ft[0].modelUrl);else{Xh(["tensorlistreserve","enter","tensorlistfromtensor","merge","loopcond","switch","exit","tensorliststack","nextiteration","tensorlistsetitem","tensorlistgetitem","reciprocal","shape","split","where"],e),Ft[0]=await Me((t=e.hand.detector)==null?void 0:t.modelPath);let a=Ft[0].executor?Object.values(Ft[0].modelSignature.inputs):void 0;Is[0][0]=Array.isArray(a)?parseInt(a[0].tensorShape.dim[1].size):0,Is[0][1]=Array.isArray(a)?parseInt(a[0].tensorShape.dim[2].size):0}return Ft[0]}async function bw(e){var t;if(ne.initial&&(Ft[1]=null),Ft[1])e.debug&&K("cached model:",Ft[1].modelUrl);else{Ft[1]=await Me((t=e.hand.skeleton)==null?void 0:t.modelPath);let a=Ft[1].executor?Object.values(Ft[1].modelSignature.inputs):void 0;Is[1][0]=Array.isArray(a)?parseInt(a[0].tensorShape.dim[1].size):0,Is[1][1]=Array.isArray(a)?parseInt(a[0].tensorShape.dim[2].size):0}return Ft[1]}async function O0e(e,t){let a=[];if(!e||!Ft[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,P0e),i=Math.round(s*r/8)*8;n.resize=ye.resizeBilinear(e,[s,i]),n.cast=Xe(n.resize,"int32"),[n.rawScores,n.rawBoxes]=await Ft[0].executeAsync(n.cast,$0e),n.boxes=De(n.rawBoxes,[0,2]),n.scores=De(n.rawScores,[0]);let o=Ca(n.scores,1);J(o[gw]),o.splice(gw,1),n.filtered=la(o,1),J(o),n.max=ha(n.filtered,1),n.argmax=ar(n.filtered,1);let l=0;n.nms=await ye.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),f=await h.data();J(h);let m=[f[1],f[0],f[3]-f[1],f[2]-f[0]],g=n0(m,F0e),y=[Math.trunc(m[0]*Mr[0]),Math.trunc(m[1]*Mr[1]),Math.trunc(m[2]*Mr[0]),Math.trunc(m[3]*Mr[1])],x=p[d],A=_0e[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 Yg(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&&Ft[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=ye.cropAndResize(e,[s],[0],[Is[1][0],Is[1][1]],"bilinear"),r.div=xe(r.crop,Le.tf255),[r.score,r.keypoints]=Ft[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]/Is[1][1],c[1]/Is[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=>[Mr[0]*(c[0]+t.boxRaw[0]),Mr[1]*(c[1]+t.boxRaw[1]),c[2]||0]),n.landmarks=A0(n.keypoints);for(let c of Object.keys(xw))n.annotations[c]=xw[c].map(d=>n.landmarks&&n.keypoints[d]?n.keypoints[d]:null)}Object.keys(r).forEach(l=>J(r[l]))}return n}async function Jg(e,t){var r,s;if(!((r=Ft[0])!=null&&r.executor)||!((s=Ft[1])!=null&&s.executor)||!Ft[0].inputs[0].shape||!Ft[1].inputs[0].shape)return[];Mr=[e.shape[2]||0,e.shape[1]||0],S0++;let a=(t.hand.skipTime||0)>ae()-Zg,n=S0<(t.hand.skipFrames||0);return t.skipAllowed&&a&&n?Pt.hands:new Promise(async i=>{let o=3*(t.hand.skipTime||0)>ae()-Zg,l=S0<3*(t.hand.skipFrames||0);t.skipAllowed&&Pt.hands.length===t.hand.maxDetected?Pt.hands=await Promise.all(Pt.boxes.map(p=>Yg(e,p,t))):t.skipAllowed&&o&&l&&Pt.hands.length>0?Pt.hands=await Promise.all(Pt.boxes.map(p=>Yg(e,p,t))):(Pt.boxes=await O0e(e,t),Zg=ae(),Pt.hands=await Promise.all(Pt.boxes.map(p=>Yg(e,p,t))),S0=0);let u=[...Pt.boxes];if(Pt.boxes.length=0,t.cacheSensitivity>0)for(let p=0;p<Pt.hands.length;p++){let c=x9(Pt.hands[p].keypoints,Mr);if(c.box[2]/(e.shape[2]||1)>.05&&c.box[3]/(e.shape[1]||1)>.05&&Pt.hands[p].fingerScore&&Pt.hands[p].fingerScore>(t.hand.minConfidence||0)){let d=n0(c.box,yw),h=n0(c.boxRaw,yw);Pt.boxes.push({...u[p],box:d,boxRaw:h})}}for(let p=0;p<Pt.hands.length;p++){let c=hs(Pt.hands[p].keypoints,Mr);Pt.hands[p].box=c.box,Pt.hands[p].boxRaw=c.boxRaw}i(Pt.hands)})}var lr=(e=null)=>({face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0,width:0,height:0,error:e});var Np={};fr(Np,{connected:()=>C0,horizontal:()=>Qg,kpt:()=>T0,relative:()=>t5,vertical:()=>e5});var T0=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],Qg=[["leftEye","rightEye"],["leftEar","rightEar"],["leftShoulder","rightShoulder"],["leftElbow","rightElbow"],["leftWrist","rightWrist"],["leftHip","rightHip"],["leftKnee","rightKnee"],["leftAnkle","rightAnkle"]],e5=[["leftKnee","leftShoulder"],["rightKnee","rightShoulder"],["leftAnkle","leftKnee"],["rightAnkle","rightKnee"]],t5=[[["leftHip","rightHip"],["leftShoulder","rightShoulder"]],[["leftElbow","rightElbow"],["leftShoulder","rightShoulder"]]],C0={leftLeg:["leftHip","leftKnee","leftAnkle"],rightLeg:["rightHip","rightKnee","rightAnkle"],torso:["leftShoulder","rightShoulder","rightHip","leftHip","leftShoulder"],leftArm:["leftShoulder","leftElbow","leftWrist"],rightArm:["rightShoulder","rightElbow","rightWrist"],head:[]};var me=lr(),a5=0;function kw(e,t){var i,o,l,u,p,c,d,h,f,m,g,y,x,A,b,k,S,C,N,$,M,R,I,_,D,W;let a=ae();if(!e)return lr();let n=Date.now()-e.timestamp,r=n<1e3?8-Math.log(n+1):1;if(e.canvas&&(me.canvas=e.canvas),e.error&&(me.error=e.error),!me.body||e.body.length!==me.body.length)me.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)*me.body[P].box[X]+Z)/r),G=e.body[P].boxRaw.map((Z,X)=>((r-1)*me.body[P].boxRaw[X]+Z)/r),q=e.body[P].keypoints.map((Z,X)=>{var re,ee,ce,ie,ge,Se,Ne,Be,qe;return{score:Z.score,part:Z.part,position:[me.body[P].keypoints[X]?((r-1)*(me.body[P].keypoints[X].position[0]||0)+(Z.position[0]||0))/r:Z.position[0],me.body[P].keypoints[X]?((r-1)*(me.body[P].keypoints[X].position[1]||0)+(Z.position[1]||0))/r:Z.position[1],me.body[P].keypoints[X]?((r-1)*(me.body[P].keypoints[X].position[2]||0)+(Z.position[2]||0))/r:Z.position[2]],positionRaw:[me.body[P].keypoints[X]?((r-1)*(me.body[P].keypoints[X].positionRaw[0]||0)+(Z.positionRaw[0]||0))/r:Z.positionRaw[0],me.body[P].keypoints[X]?((r-1)*(me.body[P].keypoints[X].positionRaw[1]||0)+(Z.positionRaw[1]||0))/r:Z.positionRaw[1],me.body[P].keypoints[X]?((r-1)*(me.body[P].keypoints[X].positionRaw[2]||0)+(Z.positionRaw[2]||0))/r:Z.positionRaw[2]],distance:[me.body[P].keypoints[X]?((r-1)*(((re=me.body[P].keypoints[X].distance)==null?void 0:re[0])||0)+(((ee=Z.distance)==null?void 0:ee[0])||0))/r:(ce=Z.distance)==null?void 0:ce[0],me.body[P].keypoints[X]?((r-1)*(((ie=me.body[P].keypoints[X].distance)==null?void 0:ie[1])||0)+(((ge=Z.distance)==null?void 0:ge[1])||0))/r:(Se=Z.distance)==null?void 0:Se[1],me.body[P].keypoints[X]?((r-1)*(((Ne=me.body[P].keypoints[X].distance)==null?void 0:Ne[2])||0)+(((Be=Z.distance)==null?void 0:Be[2])||0))/r:(qe=Z.distance)==null?void 0:qe[2]]}}),H={},B={connected:{}};(i=t.body.modelPath)!=null&&i.includes("efficientpose")?B=i0:(o=t.body.modelPath)!=null&&o.includes("blazepose")?B=t0:(l=t.body.modelPath)!=null&&l.includes("movenet")&&(B=Np);for(let[Z,X]of Object.entries(B.connected)){let re=[];for(let ee=0;ee<X.length-1;ee++){let ce=q.find(ge=>ge.part===X[ee]),ie=q.find(ge=>ge.part===X[ee+1]);ce&&ie&&re.push([ce.position,ie.position])}H[Z]=re}me.body[P]={...e.body[P],box:U,boxRaw:G,keypoints:q,annotations:H}}if(!me.hand||e.hand.length!==me.hand.length)me.hand=JSON.parse(JSON.stringify(e.hand));else for(let P=0;P<e.hand.length;P++){let U=e.hand[P].box.map((B,Z)=>((r-1)*me.hand[P].box[Z]+B)/r),G=e.hand[P].boxRaw.map((B,Z)=>((r-1)*me.hand[P].boxRaw[Z]+B)/r);me.hand[P].keypoints.length!==e.hand[P].keypoints.length&&(me.hand[P].keypoints=e.hand[P].keypoints);let q=e.hand[P].keypoints&&e.hand[P].keypoints.length>0?e.hand[P].keypoints.map((B,Z)=>B.map((X,re)=>((r-1)*(me.hand[P].keypoints[Z][re]||1)+(X||0))/r)):[],H={};if(Object.keys(me.hand[P].annotations).length!==Object.keys(e.hand[P].annotations).length)me.hand[P].annotations=e.hand[P].annotations,H=me.hand[P].annotations;else if(e.hand[P].annotations)for(let B of Object.keys(e.hand[P].annotations))H[B]=(c=(p=(u=e.hand[P])==null?void 0:u.annotations)==null?void 0:p[B])!=null&&c[0]?e.hand[P].annotations[B].map((Z,X)=>Z.map((re,ee)=>((r-1)*me.hand[P].annotations[B][X][ee]+re)/r)):null;me.hand[P]={...e.hand[P],box:U,boxRaw:G,keypoints:q,annotations:H}}if(!me.face||e.face.length!==me.face.length)me.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,B)=>((r-1)*me.face[P].box[B]+H)/r),G=e.face[P].boxRaw.map((H,B)=>((r-1)*me.face[P].boxRaw[B]+H)/r),q=e.face[P].annotations;if(Object.keys(me.face[P].annotations).length!==Object.keys(e.face[P].annotations).length)me.face[P].annotations=e.face[P].annotations,q=me.face[P].annotations;else if(e.face[P].annotations)for(let H of Object.keys(e.face[P].annotations))q[H]=(f=(h=(d=e.face[P])==null?void 0:d.annotations)==null?void 0:h[H])!=null&&f[0]?e.face[P].annotations[H].map((B,Z)=>B.map((X,re)=>((r-1)*me.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=(m=e.face[P].rotation)==null?void 0:m.matrix,H.angle={roll:((r-1)*(((y=(g=me.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)*(((k=(b=me.face[P].rotation)==null?void 0:b.angle)==null?void 0:k.yaw)||0)+(((C=(S=e.face[P].rotation)==null?void 0:S.angle)==null?void 0:C.yaw)||0))/r,pitch:((r-1)*((($=(N=me.face[P].rotation)==null?void 0:N.angle)==null?void 0:$.pitch)||0)+(((R=(M=e.face[P].rotation)==null?void 0:M.angle)==null?void 0:R.pitch)||0))/r},H.gaze={bearing:((r-1)*(((I=me.face[P].rotation)==null?void 0:I.gaze.bearing)||0)+(((_=e.face[P].rotation)==null?void 0:_.gaze.bearing)||0))/r,strength:((r-1)*(((D=me.face[P].rotation)==null?void 0:D.gaze.strength)||0)+(((W=e.face[P].rotation)==null?void 0:W.gaze.strength)||0))/r},me.face[P]={...e.face[P],rotation:H,box:U,boxRaw:G,annotations:q}}else me.face[P]={...e.face[P],box:U,boxRaw:G,annotations:q}}if(!me.object||e.object.length!==me.object.length)me.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)*me.object[P].box[H]+q)/r),G=e.object[P].boxRaw.map((q,H)=>((r-1)*me.object[P].boxRaw[H]+q)/r);me.object[P]={...e.object[P],box:U,boxRaw:G}}if(e.persons){let P=e.persons;if(!me.persons||P.length!==me.persons.length)me.persons=JSON.parse(JSON.stringify(P));else for(let U=0;U<P.length;U++)me.persons[U].box=P[U].box.map((G,q)=>((r-1)*me.persons[U].box[q]+G)/r)}e.gesture&&(me.gesture=e.gesture),me.width=e.width,me.height=e.height;let s=ae();return a5=ne.perfadd?a5+Math.round(s-a):Math.round(s-a),e.performance&&(me.performance={...e.performance,interpolate:a5}),me}var ya;async function n5(e){return!ya||ne.initial?ya=await Me(e.segmentation.modelPath):e.debug&&K("cached model:",ya.modelUrl),ya}async function ww(e,t){var r;if(ya||(ya=await n5(t)),!(ya!=null&&ya.executor)||!((r=ya==null?void 0:ya.inputs)!=null&&r[0].shape))return null;let a={};a.resize=ye.resizeBilinear(e,[ya.inputs[0].shape?ya.inputs[0].shape[1]:0,ya.inputs[0].shape?ya.inputs[0].shape[2]:0],!1),a.norm=xe(a.resize,Le.tf255),a.res=ya.execute(a.norm),a.squeeze=De(a.res,[0]),[a.bgRaw,a.fgRaw]=Ca(a.squeeze,2),a.fg=yh(a.fgRaw),a.mul=te(a.fg,Le.tf255),a.expand=Gt(a.mul,2),a.output=ye.resizeBilinear(a.expand,[e.shape[1]||0,e.shape[2]||0]);let n;switch(t.segmentation.mode||"default"){case"default":a.input=De(e),a.concat=st([a.input,a.output],-1),n=Xe(a.concat,"int32");break;case"alpha":n=Xe(a.output,"int32");break;default:n=Ue(0)}return Object.keys(a).forEach(s=>J(a[s])),n}var N0={};fr(N0,{distance:()=>r5,find:()=>L0e,similarity:()=>z0e});function r5(e,t,a={order:2,multiplier:25}){if(!e||!e)return Number.MAX_SAFE_INTEGER;let n=0;for(let r=0;r<e.length;r++){let s=!a.order||a.order===2?e[r]-t[r]:Math.abs(e[r]-t[r]);n+=!a.order||a.order===2?s*s:s**a.order}return(a.multiplier||20)*n}var Sw=(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.max(Math.min(s,1),0)};function z0e(e,t,a={order:2,multiplier:25,min:.2,max:.8}){let n=r5(e,t,a);return Sw(n,a.order||2,a.min||0,a.max||1)}function L0e(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?r5(e,t[i],a):Number.MAX_SAFE_INTEGER;if(o<n&&(n=o,r=i),n<(a.threshold||0))break}let s=Sw(n,a.order||2,a.min||0,a.max||1);return{index:r,distance:n,similarity:s}}var A5={};fr(A5,{Models:()=>Mp,validateModel:()=>F0});var Tw=.005,sn={keypoints:[],padding:[[0,0],[0,0],[0,0],[0,0]]};function s5(e){for(let t of Qg){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 e5){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 t5){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 Cw(e){for(let t=0;t<e.length;t++)if(e[t]&&sn.keypoints[t]){let a=[Math.abs(e[t].positionRaw[0]-sn.keypoints[t].positionRaw[0]),Math.abs(e[t].positionRaw[1]-sn.keypoints[t].positionRaw[1])];a[0]<Tw&&a[1]<Tw?e[t]=sn.keypoints[t]:sn.keypoints[t]=e[t]}else sn.keypoints[t]=e[t];return e}function Nw(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;sn.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=rr(e,sn.padding),a.resize=ye.resizeBilinear(a.pad,[t,t]);let n=Xe(a.resize,"int32");return Object.keys(a).forEach(i=>J(a[i])),n}function Ew(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]+sn.padding[2][0]+sn.padding[2][1])/t[0]-sn.padding[2][0],n.position[1]*(t[1]+sn.padding[1][0]+sn.padding[1][1])/t[1]-sn.padding[1][0]],n.positionRaw=[n.position[0]/t[0],n.position[1]/t[1]];let a=hs(e.keypoints.map(n=>n.position),t);return e.box=a.box,e.boxRaw=a.boxRaw,e}var Vt,E0=0,i5=Number.MAX_SAFE_INTEGER,Bo={boxes:[],bodies:[],last:0};async function Rw(e){var t;return ne.initial&&(Vt=null),Vt?e.debug&&K("cached model:",Vt.modelUrl):(Xh(["size"],e),Vt=await Me(e.body.modelPath)),E0=Vt!=null&&Vt.executor&&((t=Vt==null?void 0:Vt.inputs)!=null&&t[0].shape)?Vt.inputs[0].shape[2]:0,E0<64&&(E0=256),V().flagRegistry.WEBGL_USE_SHAPES_UNIFORMS&&V().set("WEBGL_USE_SHAPES_UNIFORMS",!1),Vt}function W0e(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:T0[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=hs(r.map(p=>p.position),[a.shape[2],a.shape[1]]),l={};for(let[p,c]of Object.entries(C0)){let d=[];for(let h=0;h<c.length-1;h++){let f=r.find(g=>g.part===c[h]),m=r.find(g=>g.part===c[h+1]);f&&m&&f.score>(t.body.minConfidence||0)&&m.score>(t.body.minConfidence||0)&&d.push([f.position,m.position])}l[p]=d}let u={id:0,score:s,box:o.box,boxRaw:o.boxRaw,keypoints:r,annotations:l};return s5(u),i.push(u),i}function V0e(e,t,a){let n=[];for(let r=0;r<e[0].length;r++){let s=e[0][r],i=Math.round(100*s[51+4])/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 f=[s[3*d+1],s[3*d+0]];o.push({part:T0[d],score:Math.round(100*h)/100,positionRaw:f,position:[Math.round((a.shape[2]||0)*f[0]),Math.round((a.shape[1]||0)*f[1])]})}}let l=[s[51+1],s[51+0],s[51+3]-s[51+1],s[51+2]-s[51+0]],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(C0)){let f=[];for(let m=0;m<h.length-1;m++){let g=o.find(x=>x.part===h[m]),y=o.find(x=>x.part===h[m+1]);g&&y&&g.score>(t.body.minConfidence||0)&&y.score>(t.body.minConfidence||0)&&f.push([g.position,y.position])}p[d]=f}let c={id:r,score:i,box:u,boxRaw:l,keypoints:[...o],annotations:p};s5(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 o5(e,t){var r;if(!(Vt!=null&&Vt.executor)||!((r=Vt==null?void 0:Vt.inputs)!=null&&r[0].shape))return[];t.skipAllowed||(Bo.boxes.length=0),i5++;let a=(t.body.skipTime||0)>ae()-Bo.last,n=i5<(t.body.skipFrames||0);return t.skipAllowed&&a&&n?Bo.bodies:new Promise(async s=>{let i={};i5=0,i.input=Nw(e,E0),i.res=Vt==null?void 0:Vt.execute(i.input),Bo.last=ae();let o=await i.res.array();Bo.bodies=i.res.shape[2]===17?W0e(o,t,e):V0e(o,t,e);for(let l of Bo.bodies)Ew(l,[e.shape[2]||1,e.shape[1]||1]),Cw(l.keypoints);Object.keys(i).forEach(l=>J(i[l])),s(Bo.bodies)})}var _n,R0=[],$w=0,l5=Number.MAX_SAFE_INTEGER,$0=0,M0=2.5;async function _w(e){if(!_n||ne.initial){_n=await Me(e.object.modelPath);let t=_n!=null&&_n.executor?Object.values(_n.modelSignature.inputs):void 0;$0=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):416}else e.debug&&K("cached model:",_n.modelUrl);return _n}async function U0e(e,t,a){var u,p;let n=0,r=[],s=$0;for(let c of[1,2,4]){let d=c*13,h=De(e.find(A=>A.shape[1]===d**2&&(A.shape[2]||0)===vu.length)),f=await h.array(),m=De(e.find(A=>A.shape[1]===d**2&&(A.shape[2]||0)<vu.length)),g=Q(m,[-1,4,(((u=m.shape)==null?void 0:u[1])||0)/4]),y=ar(g,2),x=await y.array();for(let A=0;A<h.shape[0];A++)for(let b=0;b<(((p=h.shape)==null?void 0:p[1])||0);b++){let k=f[A][b];if(k>(a.object.minConfidence||0)&&b!==61){let S=(.5+Math.trunc(A%d))/d,C=(.5+Math.trunc(A/d))/d,N=x[A].map(P=>P*(d/c/s)),[$,M]=[S-M0/c*N[0],C-M0/c*N[1]],[R,I]=[S+M0/c*N[2]-$,C+M0/c*N[3]-M],_=[$,M,R,I];_=_.map(P=>Math.max(0,Math.min(P,1)));let D=[_[0]*t[0],_[1]*t[1],_[2]*t[0],_[3]*t[1]],W={id:n++,score:Math.round(100*k)/100,class:b+1,label:vu[b].label,box:D.map(P=>Math.trunc(P)),boxRaw:_};r.push(W)}}J([h,m,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 ye.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 u5(e,t){if(!(_n!=null&&_n.executor))return[];let a=(t.object.skipTime||0)>ae()-$w,n=l5<(t.object.skipFrames||0);return t.skipAllowed&&a&&n&&R0.length>0?(l5++,R0):(l5=0,!ne.kernels.includes("mod")||!ne.kernels.includes("sparsetodense")?R0:new Promise(async r=>{let s=[e.shape[2]||0,e.shape[1]||0],i=ye.resizeBilinear(e,[$0,$0],!1),o=xe(i,Le.tf255),l=Vs(o,[0,3,1,2]),u;t.object.enabled&&(u=_n.execute(l)),$w=ae();let p=await U0e(u,s,t);R0=p,J([i,o,l,...u]),r(p)}))}var Rp=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],G0e=Rp.length,Ep=Rp.reduce((e,t,a)=>(e[t]=a,e),{}),H0e=[["leftHip","leftShoulder"],["leftElbow","leftShoulder"],["leftElbow","leftWrist"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["rightHip","rightShoulder"],["rightElbow","rightShoulder"],["rightElbow","rightWrist"],["rightHip","rightKnee"],["rightKnee","rightAnkle"],["leftShoulder","rightShoulder"],["leftHip","rightHip"]],Tye=H0e.map(([e,t])=>[Ep[e],Ep[t]]),Fw=[["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 Ow(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 Dw(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 _0=class{constructor(t,a){de(this,"priorityQueue");de(this,"numberOfElements");de(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 d5(e,t,a,n){return{y:n.get(e,t,a),x:n.get(e,t,a+G0e)}}function p5(e,t,a){let{heatmapY:n,heatmapX:r,id:s}=e,{y:i,x:o}=d5(n,r,s,a);return{x:e.heatmapX*t+o,y:e.heatmapY*t+i}}function c5(e,t,a){return e<t?t:e>a?a:e}function zw(e,t,a,n){let r=a-e,s=n-t;return r*r+s*s}function h5(e,t){return{x:e.x+t.x,y:e.y+t.y}}var on,q0e=["MobilenetV1/offset_2/BiasAdd","MobilenetV1/heatmap_2/BiasAdd","MobilenetV1/displacement_fwd_2/BiasAdd","MobilenetV1/displacement_bwd_2/BiasAdd"],P0=1,Ru=16,X0e=50**2;function Lw(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:c5(Math.round(y.y/Ru),0,x-1),x:c5(Math.round(y.x/Ru),0,A-1)}),[u,p]=n.shape,c=l(t.position,u,p),d=o(c),f=h5(t.position,d);for(let y=0;y<i;y++){let x=l(f,u,p),A=d5(x.y,x.x,a,r);f=h5({x:x.x*Ru,y:x.y*Ru},{x:A.x,y:A.y})}let m=l(f,u,p),g=n.get(m.y,m.x,a);return{position:f,part:Rp[a],score:g}}function K0e(e,t,a,n,r){let s=Fw.map(([d,h])=>[Ep[d],Ep[h]]),i=s.map(([,d])=>d),o=s.map(([d])=>d),l=t.shape[2],u=i.length,p=new Array(l),c=p5(e.part,Ru,a);p[e.part.id]={score:e.score,part:Rp[e.part.id],position:c};for(let d=u-1;d>=0;--d){let h=i[d],f=o[d];p[h]&&!p[f]&&(p[f]=Lw(d,p[h],f,t,a,r))}for(let d=0;d<u;++d){let h=o[d],f=i[d];p[h]&&!p[f]&&(p[f]=Lw(d,p[h],f,t,a,n))}return p}function Z0e(e,t,a,n,r){let[s,i]=r.shape,o=!0,l=Math.max(a-P0,0),u=Math.min(a+P0+1,s);for(let p=l;p<u;++p){let c=Math.max(n-P0,0),d=Math.min(n+P0+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 Y0e(e,t){let[a,n,r]=t.shape,s=new _0(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||Z0e(l,u,i,o,t)&&s.enqueue({score:u,part:{heatmapY:i,heatmapX:o,id:l}})}return s}function Bw(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?zw(a,t,s.y,s.x)<=X0e:!1})}function J0e(e,t){return t.reduce((n,{position:r,score:s},i)=>(Bw(e,r,i)||(n+=s),n),0)/t.length}function Q0e(e,t,a,n,r,s){let i=[],o=Y0e(s,t);for(;i.length<r&&!o.empty();){let l=o.dequeue(),u=p5(l.part,Ru,e);if(Bw(i,u,l.part.id))continue;let p=K0e(l,t,e,a,n);p=p.filter(h=>h.score>s);let c=J0e(i,p),d=Ow(p);c>s&&i.push({keypoints:p,box:d,score:Math.round(100*c)/100})}return i}async function f5(e,t){if(!(on!=null&&on.executor))return[];let a=Oe(()=>{if(!on.inputs[0].shape)return[];let i=ye.resizeBilinear(e,[on.inputs[0].shape[2],on.inputs[0].shape[1]]),o=fe(xe(Xe(i,"float32"),127.5),1),u=on.execute(o,q0e).map(p=>De(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=Q0e(n[0],n[1],n[2],n[3],t.body.maxDetected,t.body.minConfidence);return on.inputs[0].shape?Dw(r,[e.shape[1],e.shape[2]],[on.inputs[0].shape[2],on.inputs[0].shape[1]]):[]}async function Ww(e){return!on||ne.initial?on=await Me(e.body.modelPath):e.debug&&K("cached model:",on.modelUrl),on}var ur,efe=["fgr","pha","r1o","r2o","r3o","r4o"],Ut={},g5=0;function Gw(e){J([Ut.r1i,Ut.r2i,Ut.r3i,Ut.r4i,Ut.downsample_ratio]),Ut.r1i=Ue(0),Ut.r2i=Ue(0),Ut.r3i=Ue(0),Ut.r4i=Ue(0),g5=e.segmentation.ratio||.5,Ut.downsample_ratio=Ue(g5)}async function y5(e){return!ur||ne.initial?ur=await Me(e.segmentation.modelPath):e.debug&&K("cached model:",ur.modelUrl),Gw(e),ur}var Uw=e=>Oe(()=>{let t=De(e,[0]),a=te(t,Le.tf255);return Xe(a,"int32")});function m5(e,t){let a=e?Uw(e):nr([t.shape[1]||0,t.shape[2]||0,3],255,"int32"),n=t?Uw(t):nr([e.shape[1]||0,e.shape[2]||0,1],255,"int32"),r=st([a,n],-1);return J([a,n]),r}function tfe(e){return Oe(()=>{let t={};return t.unstack=Ca(e,-1),t.concat=st(t.unstack,1),t.split=Ia(t.concat,4,1),t.stack=st(t.split,2),t.squeeze=De(t.stack,[0]),t.expand=Gt(t.squeeze,-1),t.add=be(t.expand,1),t.mul=te(t.add,127.5),t.cast=Xe(t.mul,"int32"),t.tile=Ur(t.cast,[1,1,3]),t.alpha=nr([t.tile.shape[0]||0,t.tile.shape[1]||0,1],255,"int32"),st([t.tile,t.alpha],-1)})}async function Hw(e,t){if(ur||(ur=await y5(t)),!(ur!=null&&ur.executor))return null;Ut.src=xe(e,255),g5!==t.segmentation.ratio&&Gw(t);let[a,n,r,s,i,o]=await ur.executeAsync(Ut,efe),l;switch(t.segmentation.mode||"default"){case"default":l=m5(a,n);break;case"alpha":l=m5(null,n);break;case"foreground":l=m5(a,null);break;case"state":l=tfe(r);break;default:l=Ue(0)}return J([Ut.src,a,n,Ut.r1i,Ut.r2i,Ut.r3i,Ut.r4i]),[Ut.r1i,Ut.r2i,Ut.r3i,Ut.r4i]=[r,s,i,o],l}var xa;async function x5(e){return!xa||ne.initial?xa=await Me(e.segmentation.modelPath):e.debug&&K("cached model:",xa.modelUrl),xa}async function qw(e,t){var r;if(xa||(xa=await x5(t)),!(xa!=null&&xa.executor)||!((r=xa==null?void 0:xa.inputs)!=null&&r[0].shape))return null;let a={};a.resize=ye.resizeBilinear(e,[xa.inputs[0].shape?xa.inputs[0].shape[1]:0,xa.inputs[0].shape?xa.inputs[0].shape[2]:0],!1),a.norm=xe(a.resize,Le.tf255),a.res=xa.execute(a.norm),a.squeeze=De(a.res,[0]),a.alpha=ye.resizeBilinear(a.squeeze,[e.shape[1]||0,e.shape[2]||0]),a.mul=te(a.alpha,Le.tf255);let n;switch(t.segmentation.mode||"default"){case"default":a.input=De(e),a.concat=st([a.input,a.mul],-1),n=Xe(a.concat,"int32");break;case"alpha":n=Xe(a.mul,"int32");break;default:n=Ue(0)}return Object.keys(a).forEach(s=>J(a[s])),n}function F0(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 Mp=class{constructor(t){de(this,"instance");de(this,"models",{});this.models={},this.instance=t}stats(){let t=0,a=0,n=0;for(let s of Object.values(ma))t+=s.sizeFromManifest,a+=s.sizeLoadedWeights,n+=s.sizeDesired;let r=n>0?a/n:0;return{numLoadedModels:Object.values(ma).length,numDefinedModels:Object.keys(this.models).length,percentageLoaded:r,totalSizeFromManifest:t,totalSizeWeights:a,totalSizeLoading:n,modelStats:Object.values(ma)}}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,f,m,g,y,x,A,b,k,S,C,N,$,M,R,I,_;ne.initial&&this.reset(),t&&(this.instance=t);let a={};a.blazeface=this.instance.config.face.enabled&&!this.models.blazeface?V9(this.instance.config):null,a.antispoof=this.instance.config.face.enabled&&((n=this.instance.config.face.antispoof)!=null&&n.enabled)&&!this.models.antispoof?hk(this.instance.config):null,a.liveness=this.instance.config.face.enabled&&((r=this.instance.config.face.liveness)!=null&&r.enabled)&&!this.models.liveness?yk(this.instance.config):null,a.faceres=this.instance.config.face.enabled&&((s=this.instance.config.face.description)!=null&&s.enabled)&&!this.models.faceres?lk(this.instance.config):null,a.emotion=this.instance.config.face.enabled&&((i=this.instance.config.face.emotion)!=null&&i.enabled)&&!this.models.emotion?rk(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?X9(this.instance.config):null,a.facemesh=this.instance.config.face.enabled&&((u=this.instance.config.face.mesh)!=null&&u.enabled)&&!this.models.facemesh?Q9(this.instance.config):null,a.gear=this.instance.config.face.enabled&&((p=this.instance.config.face.gear)!=null&&p.enabled)&&!this.models.gear?vk(this.instance.config):null,a.ssrnetage=this.instance.config.face.enabled&&((c=this.instance.config.face.ssrnet)!=null&&c.enabled)&&!this.models.ssrnetage?Sk(this.instance.config):null,a.ssrnetgender=this.instance.config.face.enabled&&((d=this.instance.config.face.ssrnet)!=null&&d.enabled)&&!this.models.ssrnetgender?Ek(this.instance.config):null,a.mobilefacenet=this.instance.config.face.enabled&&((h=this.instance.config.face.mobilefacenet)!=null&&h.enabled)&&!this.models.mobilefacenet?Pk(this.instance.config):null,a.insightface=this.instance.config.face.enabled&&((f=this.instance.config.face.insightface)!=null&&f.enabled)&&!this.models.insightface?Lk(this.instance.config):null,a.blazepose=this.instance.config.body.enabled&&!this.models.blazepose&&((m=this.instance.config.body.modelPath)!=null&&m.includes("blazepose"))?w9(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"))?Rw(this.instance.config):null,a.posenet=this.instance.config.body.enabled&&!this.models.posenet&&((x=this.instance.config.body.modelPath)!=null&&x.includes("posenet"))?Ww(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"))?Aw(this.instance.config):null,a.handskeleton=this.instance.config.hand.enabled&&this.instance.config.hand.landmarks&&!this.models.handskeleton&&((S=(k=this.instance.config.hand.detector)==null?void 0:k.modelPath)!=null&&S.includes("handtrack"))?bw(this.instance.config):null,(N=(C=this.instance.config.hand.detector)==null?void 0:C.modelPath)!=null&&N.includes("handdetect")&&([a.handpose,a.handskeleton]=this.models.handpose?[null,null]:await fw(this.instance.config)),a.centernet=this.instance.config.object.enabled&&!this.models.centernet&&(($=this.instance.config.object.modelPath)!=null&&$.includes("centernet"))?T9(this.instance.config):null,a.nanodet=this.instance.config.object.enabled&&!this.models.nanodet&&((M=this.instance.config.object.modelPath)!=null&&M.includes("nanodet"))?_w(this.instance.config):null,a.selfie=this.instance.config.segmentation.enabled&&!this.models.selfie&&((R=this.instance.config.segmentation.modelPath)!=null&&R.includes("selfie"))?x5(this.instance.config):null,a.meet=this.instance.config.segmentation.enabled&&!this.models.meet&&((I=this.instance.config.segmentation.modelPath)!=null&&I.includes("meet"))?n5(this.instance.config):null,a.rvm=this.instance.config.segmentation.enabled&&!this.models.rvm&&((_=this.instance.config.segmentation.modelPath)!=null&&_.includes("rvm"))?y5(this.instance.config):null;for(let[D,W]of Object.entries(a))W!=null&&W.then&&W.then(P=>this.models[D]=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(ma).find(r=>r.startsWith(a.name));n&&(a.size=ma[n].sizeLoadedWeights,a.url=ma[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=F0(this.instance,n,a);r&&t.push(r)}return t}};function Kw(e,t,a,n,r){var o,l,u,p,c,d;let s=0,i=[];for(let h of e){let f={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]&&(f.body=b);if(f.body)for(let b of a)b.box[0]+b.box[2]>f.body.box[0]&&b.box[0]+b.box[2]<f.body.box[0]+f.body.box[2]&&b.box[1]+b.box[3]>f.body.box[1]&&b.box[1]+b.box[3]<f.body.box[1]+f.body.box[3]&&f.hands&&(f.hands.left=b),b.box[0]<f.body.box[0]+f.body.box[2]&&b.box[0]>f.body.box[0]&&b.box[1]+b.box[3]>f.body.box[1]&&b.box[1]+b.box[3]<f.body.box[1]+f.body.box[3]&&f.hands&&(f.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=f.body)==null?void 0:o.id)||b.hand!==void 0&&b.hand===((l=f.hands.left)==null?void 0:l.id)||b.hand!==void 0&&b.hand===((u=f.hands.right)==null?void 0:u.id))&&f.gestures.push(b);let m=[],g=[],y=b=>{b&&b.length===4&&(m.push(b[0],b[0]+b[2]),g.push(b[1],b[1]+b[3]))};y(f.face.box),y((p=f.body)==null?void 0:p.box),y((c=f.hands.left)==null?void 0:c.box),y((d=f.hands.right)==null?void 0:d.box);let x=Math.min(...m),A=Math.min(...g);f.box=[x,A,Math.max(...m)-x,Math.max(...g)-A],r!=null&&r[1]&&(r!=null&&r[2])&&(f.boxRaw=[f.box[0]/r[2],f.box[1]/r[1],f.box[2]/r[2],f.box[3]/r[1]]),i.push(f)}return i}var O0=`
|
|
/9j/4AAQSkZJRgABAQEAYABgAAD/4QBoRXhpZgAATU0AKgAAAAgABAEaAAUAAAABAAAAPgEbAAUA
|
|
AAABAAAARgEoAAMAAAABAAIAAAExAAIAAAARAAAATgAAAAAAAABgAAAAAQAAAGAAAAABcGFpbnQu
|
|
bmV0IDQuMi4xMwAA/9sAQwAGBAUGBQQGBgUGBwcGCAoQCgoJCQoUDg8MEBcUGBgXFBYWGh0lHxob
|
|
IxwWFiAsICMmJykqKRkfLTAtKDAlKCko/9sAQwEHBwcKCAoTCgoTKBoWGigoKCgoKCgoKCgoKCgo
|
|
KCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgo/8AAEQgBAAEAAwEhAAIRAQMRAf/E
|
|
AB8AAAEFAQEBAQEBAAAAAAAAAAABAgMEBQYHCAkKC//EALUQAAIBAwMCBAMFBQQEAAABfQECAwAE
|
|
EQUSITFBBhNRYQcicRQygZGhCCNCscEVUtHwJDNicoIJChYXGBkaJSYnKCkqNDU2Nzg5OkNERUZH
|
|
SElKU1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6g4SFhoeIiYqSk5SVlpeYmZqio6Slpqeoqaqys7S1
|
|
tre4ubrCw8TFxsfIycrS09TV1tfY2drh4uPk5ebn6Onq8fLz9PX29/j5+v/EAB8BAAMBAQEBAQEB
|
|
AQEAAAAAAAABAgMEBQYHCAkKC//EALURAAIBAgQEAwQHBQQEAAECdwABAgMRBAUhMQYSQVEHYXET
|
|
IjKBCBRCkaGxwQkjM1LwFWJy0QoWJDThJfEXGBkaJicoKSo1Njc4OTpDREVGR0hJSlNUVVZXWFla
|
|
Y2RlZmdoaWpzdHV2d3h5eoKDhIWGh4iJipKTlJWWl5iZmqKjpKWmp6ipqrKztLW2t7i5usLDxMXG
|
|
x8jJytLT1NXW19jZ2uLj5OXm5+jp6vLz9PX29/j5+v/aAAwDAQACEQMRAD8A+qaKACigApGOKAML
|
|
Xp8xlF5A7V4X8RtYs7PzfNImnx8sa8Kp9z3q2tEgp6angWs62ZZ5CTGoJ6DArGNz5p+UrID6EUrF
|
|
PUlW1EuN0XNW7PQ2L5j3JnoKXN0KijqNP0eYoqXBdgPuuo+ZPeupisWn2Jd4+0r924XgsQOCff3/
|
|
AJ1FzRKxDqGii6m3siiQ8F1XGfXI6YNWLfRbiRQMkcZI9fpTDluT2/h6Qy8gDPbtmtG38JeY480Z
|
|
5zSLUTZg8M28YwYxjAArXtdPt402qgHbpSaLWhma3o0Uqk7Nx9DWLaaVblgPs6qRyds2M/gRSQp9
|
|
zZOni2iWS2hlQ+kjYz9OMGrdjq89vIPPVhj+8M/lQyDq9P1WOYBlMZz1AOD+VdDaTiReOKulK0jO
|
|
tHmi0WDTlr0TyxRVhT8tJjIX+9SUxHXUV553BRQAVBcPhSBTSuxPY86+IGti0s5I7dsORy9fM3i6
|
|
8e8mfDO5P90ZrWWiJicNPpZZtxV/xrW0jQt4DOv6Vk2dEEdTY6BHuB25rpbPSo0QARjP0qTRI17W
|
|
wA/hFaMWmoQMgflQXYsDS142rU9tpqqenfNA7GgtihxkdKuRW6qMY/GkDZY8sY4Ap4hXbyB+VArk
|
|
EtuH4wPyrk/EGkOm+a3jw3suRQLc5i38SX9hJ9nnY+XnBUdPyNdFY6pa3KkkAE9l6f8AfJ/pSJT6
|
|
GhDmI+Zb4ZRycdv6ium0nUhKFydrelTsNnS2829RnrVgV6NKXNG55lWPLIM81Op+WrZkRMfmNNzT
|
|
A7GivPO4KKAEY4XNYWt3vkwPg4OK0giJdjw/xrqhm87Zs8tc7pX5A+leSajf6aHYJ50kn4AZpTep
|
|
rBWRm2Vobm4BXfyehPFdnpmnBFUY5rI2SN63tlToK0YI+KZpFF+3QdavwoKTLtoW0Toaswpk5pCb
|
|
LCxipAhoIuP2dKevHXoaYDylRyxhlwRQI4nxVoCXWZI1GfpXGtbSWjYPGP73+NIGupt6TqMsLruZ
|
|
ih4xnP5V09mQ+JLd8gn0xSYJnVaVdkook69K34zuUGunDS3Rx4qOzHVIp4rrOMY3NJQI7GivPO8K
|
|
KAILt9kZrz3xlebYiu8KCCWb0XvW0NFch6ysfO3jLVjfXLIn+pQkKorl7WxNxIPl71g2dUUdpo+l
|
|
pBGvHPet23iC8ihFosrxirkHQUFo0IF4FXI1O726CpKLacCrMJoJLYHAPpTwucHpSRJJ5e4AZI9x
|
|
UqpxzVpCuOC8cUpQUMRnXttuB4rjNdsYyeVwfXpmpGmcvcQyafMCFJjPY10eg34BUg4DcZP8jUO4
|
|
HaRq3lLNF+IHet7R7jz7c56rwa2wz9+xhiVeFy/T1PFegeaNPWigDsc0ZrzzvDNIaAM7VpNqdegr
|
|
xL4l6kywyRhseZ19lrdfAZL4jxYg3Fw20d63tJsdrDI5rm3Z3R0R0Mce1eKnQYAplIkWrMJ45oZS
|
|
NO3PHbNXIyfpSGWowSOasxLUiZdjFSqtNEMkUemKlAGKsRJjAppFAiORMjmsTVrNZEO4cfSoZSOD
|
|
1eJ7WXBUzQZ+7nkfSo7e2Ei+ZaMzxntjBX2NSU1Y6/wxqojiEFzkA8KTXYaUoWRyv3W5rSjpNHPX
|
|
+BmpSg8V6J5gUUAdhRXnneFFAGHrTfu5PpXzj8S70/aZtxzztXFbv4DKHxHI+H4GZiz9zxXXW8G3
|
|
GBXMjvLRXAx0oPGPSmMVeOnWrMTYpFI0bcg1fh54xmgovRcD3qxETSIZcRvzp+/BpEkqsBUqsM9K
|
|
q4Em4Gkxk0yRGXrVW6i8yFhkg+tJjRxGsWrxllkUMh9eK5uMz6bcebbnfG33kPcVkay2OntPKuo0
|
|
nhXI67c8qa7Lw3c+adjcEDGK1paSRhVV4s6A0or0jyRRQ1AHX0V553hRQBz+vNtt5z3xXzX8Qbdm
|
|
uic5YnOMdK3l8JnTXvlbwpYl+WySOgrp5YfLOOB9O1c62O7qQkc+9RsKChFPWp4DluOlSykaNruH
|
|
ArUgHShFNF2NT1qxGO3NBmyxGcE1N2560CFzjrUysO9JAPDDjFOVuKoQuSRTWouBkazbCa3cd8cV
|
|
wF7IISQccHBzUSWpV9C3o1x5b5GAjdQD1rs9DjC3kckbEhqKfxIzn8LOupRXqnkPccBSkUAzraK8
|
|
87wooA5rxMSI3HqK8B8bQl9Q8sffY5b/AAraXwkUviNrw9pH2W1ViMMRTdRjw4HpWNtDti9TPc4P
|
|
FQs2M5qdyyMHLcfjV63HTAoBGtap0wK0YxigpsuRDtVhVYd6GQydVwwIqdRnqKCR23I5pCMUW6gD
|
|
YNKuetAEise9KTxQBWuFyhrznxNZkXjFeN3I+tTIZg2OqmzmxNF0PO3vXp/g2+hukVl4zyPanTXv
|
|
JmVR+60dpThXpnlPceopWFAbnV0V553hSGgRynjC5FujOey14Ssp1HxNmTnc+a3kvcIpv37HoEYQ
|
|
QmMdVHSsnVbYJF5jVk0dsNzlruVIsl2wKxbjWrVHILjg1CRbZJb+ILHPzyhfStODWLQgFJFYd+el
|
|
UJM27HUIXxhga1Y5lLVLKLkMnoauxnPPrSEx7ShF+Y/n2qrc6xBbhizDAqkK1zJuvG9nbg8ZA681
|
|
ly/Ei052RO3uKAsZlx8QGd8xxvt9Aa1NH8dK7AXMcip64zigdkdrZX8F7EJLdwwNXMkrz1qRMRly
|
|
CK4TxmpidWI49felPYSOMmi80NIoOV6qRzXYeA5SskYPfirpfEjGr8LPWVHyD6U4CvQPL3ZItOYc
|
|
UDOoNFeed4Uhpks4H4iE/Z5MeleMeGULeLgjds10S+BGdL+Jc9OSBU2Huc5Nc74yvUtrcDBrJnZF
|
|
63PJdXvLy/lKWw46bvQVz82jXhkLO5Y+9ZlsYthcRnbIjY9R3q3awTRkEM3WmJI6C0ea3dGRsr1x
|
|
XY6TqW9FLHnjrUs0izpLK5DDjofSta3ckH09KRUkZuuTvFGdvPauE1Y3U6Mqbssf/rUxHPTaJPK2
|
|
ZmJPbBqzY6DCZh5xJC9s9aBJHU6dpemJjfEmfetJtI0+VPkUr/unFOxdiextHs33W07YHQHk11mk
|
|
Xb3KbZ1xIvcd6LEyWho4Nct41sTPYb16ipexCPPZN+wYGCvH1rrPAEJmvkPoc1VL4kZVvgZ6yFwK
|
|
cBXoHkkqinFaVyzo80GuE7WJRQSziPiGdthK5HQV4x4J/wBI8WPIewNdEvgRNL42emO/yj1UHNef
|
|
eNpRczbC+I17DvWT2OqJxc0sMK4TCisy41q0hfEkqj8aixdwTXNOlwvmqD9anS9tXH7uVG+hosO4
|
|
/wC0oOhrR0+6G4YNIEzsNEuCxAPNdjZruA4xxUmjINSjURksOlcbqFykbnjFA1sYGoassaknCqO5
|
|
rl7rxhGm7yBnBxuJq0rkSlYpw+NLlsfd5P8AerVsvHEqSBHwPVgcgVpyMyVXU3rXxcHYETAk+hru
|
|
/DWti6ZSTyOKzZqndHaxvvUGq2rQ+dYyqR24qWI8dvbr7LqDxyDAzXpvw6FvIxePGSM06Xxoyr/A
|
|
zviKFHNegeX1J41zUhXioGbuaSuM6wpCaBHG/EcA6HN/exxXjXw2jL67cv8A3Qa6H8CFR+NnoWpO
|
|
I4XI44rxLxrqjQzSEsQM1gdSPM9U1uR1YbmWIdXHf2rmpIb67YS28UrRlsLI3c/jW0VZGUpO5pW1
|
|
jfLNOjahawzwReYI5cjzMkDavHJ5/SrVv9uhtPtVxCPLBwzxnlT9KGghLU3tKvvPjHzbl7EGuisJ
|
|
GRxWLOg7nRXJEbDjmvSNK+aFSfSoZr0KutRkphc4NcRrdkVjL9aVio7Hk3iqS8ubhrWzUlsZY9kG
|
|
cZNc5D4aee5MclzJIFTzHAO0MfatqSOWu7bFS1srDUZEis0vIZoUxPvfcC+4/dx2xjr712XiTwXb
|
|
WmlQ6hol3cRhoFd4rlg3zY5wR0GelavQwjq7GD4etdVvSnk2wAB+9v8A8mvcfA2kXiRo0/UdcDis
|
|
ZnTTulqeoWqbUAJqWUb42X1FZlnjfjSwlGrr5S/eNdD4RkvLAAQ4yRyaUZcruVKl7TQ9I0G+mnzH
|
|
ckFwM8VuIK7ac3KF2eXiKapz5UWYxipNtMyNejNch0jSar3cjR27uoyQCRVRWom9DxTx54gu5fMi
|
|
lbKdMVjfCZPNlv5v9rFbVHpYqjGzbOn8SzFI9o715L4u0r7arYzk+lYdTqSujy7U/C0u4vHk+WwO
|
|
xuh9q3J9dgvbdVukMV1EwbDDgn04rZMwlHoZ+orZ6hfQ3RWVnQYCgZAq+8U0ln5NtBsV2yxYcfgK
|
|
JtW0CnB31LlroVwJ1nQLGDjeP7w+lb0dsFxjrWB0tHS6NuWPJ6A16ToUm63T3Gallr4S7cxiTjrX
|
|
PaxaF7dlVeSMUhxZ5jd+H7qCa4eF3DSE5x3zXN3Wk6jbyeaiFWUY6ZyPStYS5SalPmVipFbX0E4c
|
|
W0alvmPHJrag0rVvEE6LdljGpG2NRtQD+tW5XMI0uU9M8NeFo9PiQhecDIIrtrOMIoG3H4VlJm9t
|
|
C6CB06VPGM1IHLeItGS6uw+ORT7e3jsbQvj7gzUNam0JaWE+HN7NqOqX80n3FO1RXo8YzXdS+BHk
|
|
4z+KyzGPapcU2YIv7qQtiuaxvcaWqG4O6FwfSrS1JbPnrxoxkv7qIfejcitj4V2f2exumI+8+aKn
|
|
xHTT+G5d8Txlm4rjLxMsQwzWT3OiK0Mm6sEkVsAcjFc1d+FEmlGwEDPQVopaEuOpr6f4ZWNAu3tW
|
|
vHpAj5ZQcUFIWaDjGMVUMQ3cVDBmvbhY7QAV2nh+T/R1yeKhlrY31+b61FcQK6nIoJMi401WblRi
|
|
qr6PCw5UYq9y+YgOgWzNkRrx3xWjp+nx2v3FQcelAbmko9anQ4GBUNisPHWr1qMrQhS2K11HvmYV
|
|
hamcxSRZ5xRIqluS/DKAQQXZxyXrvo2FdlL4EeZjH+/ZbjNSZpswLNBrE1Gt7VE4ODVIlnh/j61F
|
|
j4lmeTGyUbq6LwdEqWbeX0YbhSqfEddP4Bddj4JIrhL5d8h7VjI6oLQqKNzelWre3yc4/ClFjaL6
|
|
wqBxxUUxwCKu5BmXRA6c+9ZjP83FSBoQuPs4BrsNBlUW659KmRrDY6G1lyQtW3Hy0lqQ1qVJnAbm
|
|
oy3b9KYJCqRj3o4zRctIlhjLHmpSuOBRbQOpLGpPFaES7UqkZzKN1KsEc87/AHUUmvPLTVGv72aQ
|
|
k7WJwKmRrQ3ud74Ltilgz4++2a6iNDXdS0gjyMU71my7GpqTbxSbMki3SViajTTHqkSeR/GeyZmg
|
|
nQHkEE1S+F+oPPavBL96I4/Cia1udVF+4dVrkW+Fq8+v4tjMDWUkdVJ6WM0cNV+F+MVmjUcZgqnP
|
|
1qpNNnkcVRLiZtxIS1UzzIF7mghlxUZpVQdq6nTVdAoAOKzkbQWhvwM6gMM1twOJYx3NOJE11Kt1
|
|
H1/pVVlwBkk+9NocXoOQ45FPj+fkUJFF2NSB700v/hTEty5ZpkjvVyUgcCq6GM9zC14/8Se6GcZQ
|
|
1574Xs5WkI2HBPHFQ1dm1KSSZ7Rotn9l0+KPHIHNacae1dy0Vjxaj5ptlhVp+2s2CJ9ppCKzuWNx
|
|
zSFc1SYrHNeNdIGpaYw25ZeRXmvheyk0jVpEdcLJ0q3ZxNKTa0O3vQHg/DNcHrsJDmsmjspnNzNt
|
|
fFIJ24GazOhC+azDmgZIOOKBsp3J2qSaZodubq58yQ4QAnmhGT3NO18pb7BORmu205LfYpyKVkWp
|
|
Oxr5gKYWoIZWgfGfloFq1qTPLubnGO1RPtxg4P0oBAkY/hBz6VNDDkZ6AU0W2WSdqkdKr9ZOaGSj
|
|
VtcLHmnOcgmmYvcz7mBLy3MbdD1q9ouiRK6bUAVeelOC1InPlidSsWMDFOCEdq3uefykqrinYqGy
|
|
rFvApMVka2DAowKAsMkRXQqwyDXn/iWyitNQ3qPl6itIvRoF8RXinW4tQ6HI6GuW8SIVBPalc6qe
|
|
5x9x97r3qruwTjrWZ0ksZ9TUmcDNAmZ9/wAoao63rR0+w22MLPtAzt6mghmfofiB76LdJBJBIp5D
|
|
d/oa7bSdWLIPnpDi9TM8TeKdas51XTbIyxd3J/pXS+E/EFxqNoFu7do5OmD60maHWrnZyDRkn/69
|
|
MlEyOR0xntVoNx+FUgYjPxg4FLCuWDZyKQr2RoRnP0qO+nEFpJITgAUzLqZnhu6+0rknOTXpOmwJ
|
|
Fbrt5yMmnHYyr6Oxb2ijaKLnPYMClwKQWK3n0hn+lachHOJ9pNNN0apQFzsY10a4v4hXQh0xpieQ
|
|
MA1XLZNjhK80cT8OdV+3Wl3A7ZZJCw+hrR1qLcjZ/CsbnfHRnFXseHJArOYYbrUs1uPhYbuatqFP
|
|
ByfSkMq3UIINYkto+87Tx6GkSxfsDbflGD7CtTw/pk4nzITtPIFMFudsukh4Rxz71paTpKwP5jcn
|
|
0qTRy0NORMDgVCqewoJTJgAoxjntTiTu7fWmFxAcnn1q3EPl+X8KZMi4gKqB1Peob/Tv7Us5bfeU
|
|
yOoq4R5nYxqT5I8xieH9J1DTbvyJELRg8ODwa9Ms5mSFV9BWiptbnNVrKdmif7Q1KLg96XIZc5Is
|
|
pNL5pqeUrmMtZs0jzV08phchaY00zH1p2ZNxjS1g+LdJOt6U9ssmxjyGp2urDjLlaZzng/wUPDqz
|
|
TSTmWeTrjpVjVk3Rvjr2rnqQ5dDvo1XUd2cTqSNk9OKxXGCeKxZ1DAxHTr2q5C/y8GokUhsz54qu
|
|
uCxzSQjQ0+FZblR2ro4bZYiMVQ0dBb7Qi5x0qzuG5QOh71LYErDufpSeWrHnimIXbjkUjLkH1Hem
|
|
gGxryc+tXI19KYmWegq9YLiLJ7mtqS945cS7QsWehqxA9dEjz4krPSxyZqbFFhGxUm6smjRM55Lk
|
|
HvSvNxXTY57kLT+9MNwKdhXGm5FIbkU7Bca1wMEVhaiuQcVhXWiZ14R6tHGanGBI2OtYkqEHjgVy
|
|
s9ErEeo6UBsHipKEZs5qpPdRxcbhx70NCSuybTNWihc5brW9Fq6vjMnFSdEIdDRi8RRKygZbHFbu
|
|
m6nb3RA3gMegNJhOm0jbXGOoxTuCc1Rz3FyoGKawz9KaAVcZqeMgCmIkB4FaUTbYwB6V00Fuzixb
|
|
0SFMuDU8Mlbs4UPeXHeiOXkUrDuXYnyKk3cVk0ap6HMxxketSMhrcwRC0dMMZFMQ3yzSeVQAeUaz
|
|
9Vj8uPd271nVV4m+GdpnHX67pCeKyLtBtNcR6xlk9RVeWTb3qRnO6trgttyIfm71z7ai8j7/AJmN
|
|
DNqUVa5Yi1AnjynHuBV+11YJhWWXcP8AZNSzqgmaEerSsf3NtIQP4mGKtRavdRgMIpVI9KjU0a7n
|
|
R6T43uYQI7qN2Tpkqciu503VVuQGAYZHQjFVc4alPlZrpKGAznpTwxOc9+lWjIlUACnM4XApiLNk
|
|
nmvnsK0NvpXZRVonmYqV52GsmanhXitTmFkSiJTSAvwrxUxXIrJ7miOfjf1pzNWxkRlqYWpgJupu
|
|
6gQbuahvIxPA6eo4pNXVioS5WmefakGhndH4INZs5DJXA10PaTurmLO21uKpSZqGMoXGnRzBiyjd
|
|
9Kx5rcQS428fSkjanLoaOliHGZFB56VswW+mtPufcBsGOAfmxz+tFkd8HpoaUx09FAtFY8DO71qb
|
|
Sms/Nb7RbecG6AEjFLS5c78t+p0djpVs9wsyQiJAdyr1rW+zqjErzSe559Sbk9S3C+MA1bjbgE1S
|
|
MSXzMVG0vNUI2tPKrAuCMnrVzNd0PhR49W/O2xrHmp4TxVMzQshpIzzQBehqesnuaI5VGzT2bitz
|
|
FEbNTC1ADS1JupgG6l3UAc14s04yR/aYRll+8BXCtLncDXFWjys9TCz5oW7GddH5qqNzWDOgQnC8
|
|
VSuo1kHzAGkPYopEY2+RWxV23Vzj5G/Kg3jWaNazhZuqNXS6TaKhB2c0jR1nJWOlhOxRxU4YkCgx
|
|
Y0OQatQyDbyaaFYe8uF4NY3iC9ltbVGj43NTIL3h7WzMihjzXVQXYYDdW9Cf2WcOJpfaRZ3g9KsQ
|
|
mupnCLIabGeaAL0LcVY3cVmzRHIxtUhetzEjZqjLUAIWpN1ArhupwagAfDKQ3Q1594v0c2bm6tx+
|
|
5Y8j+6ayrR5onThp8s7dzkZjuqAAmuBnqC7c0iwgtzSA0rWzjfGRW3ZadDu4AoNYo2rfS4v7orSh
|
|
05UA2r0pDbsTm29KRottBNyJ0wpJ9KhD7f6U0ikNWffIFBz60zVUW52ow4UcUN6EPcx44WsbgOmd
|
|
ua7TT5Bd24KHnFKnLlZFSN4koluLdueRWvp14swweG9DXoxldHlTjYtzGoo25qzEvwtUxas2jRPQ
|
|
5CNqkLVsYoYzUzdQA3dSFqBBmnqaBhuqhriCXTpVIzxUz+Fl03aSPI9QTypW2/dz0qKNw3SvOPZR
|
|
Mqin8VLKRcs3O4Cuk0w/MDjt1NBtHY6O2IIHY1pxgFaETIRwMkjtVSUEk4570MlFW5bap6dKzWm8
|
|
1tqH8aY+hp2FvGoGayNevVt7/ap4xzUvYjqTLtvLPcvJxSaVcyWsxTnFZlnT2t15xHmCtOBYwQy4
|
|
B9q7cPO+jPPxFO2qLEj5HWo42+aus4HpoX4W4FTF+KlotbHII9SFuK0MUNZqiLUDE3UbqBBupwag
|
|
Bc1DefPbyD/ZND2KjujyPWlKzuPesRZjHJXms9lMuw3StjnmphKDSLTJ7OfE3JrpbO4GQc9qlnRA
|
|
3LO82k5NbFvdADkjBoCSHyXIIIzgVQvdRigT7wzjgUzO1jHknlvG7qnp61etYFQDIpCZoqVijzXn
|
|
3iC8EmsOuaCGb/heR/s0ijkVv6fbxy3QMg5xmsnuX0Ldzut3+UYTPWk+2GJSe+M1pFtamcldalmx
|
|
1eO4XaThhWnC+TXqR2PHqL3maUJ4qRjxSEjj42qXdxVmaGs1MJoATfSbqBAG5p6mgAzTJTmNvpQU
|
|
tzzHXY83D/U1zF5FhjgV5r3Pa6FMsV5HWnLe7RhqBRdmTwagN2d2K2rPU1C5LAnPrUs6Iysbdrq6
|
|
f3gK0BrUKj/WClY05iM6xLOcQAj3NT29uznfKSzHuadzNu7NSBFjHNSm5VO9IRnajqoWMhTzXFtA
|
|
bvUfMduSeg702Qz0rS7FbTToQFwzjJqaGTFyfK5PQViyzUuFmuIdgGABya5u/vTaN5cnUHFUmLoZ
|
|
zyskwlgJweSK6zQdUEwVJeGr0aUrxPLxEfe0OrhPAqVjxWhznGRtUwatDK4jNxURbmkAm6jNABup
|
|
6tQAFqhupNtu59qUnZFwV5JHnWsHdIx96w5lz15rzT2uhRmt85xWbcxMnUGmZlB0bdxmrNvFIcfM
|
|
350mWjbs7YkDJY/jW5ZWW4jikWkdNp9mqYJFaJdEHHakUULu/VB1rLn1Ld/FgetMGYd/qWSQmSa0
|
|
/AemS32pfa7piLeLkg9z6UmQtz0W7uQ2cZx0A9BVzR7cAea6j2rPqX0L99KRat5A6Dk1wOoKZ52a
|
|
YfMORTYRLujiGWEq6/NWza2yKQVHNdOHerRy4laJo6TTnbbtb8KuM3Fdh5z3OJjbmpt3FaMxAtUZ
|
|
agBN1GaQBzTwaAAms3VbjERUGsa07RsdeFpuUuY4jUjljWTKK4j02RE4IpJYFk6imQkVl0xWarsO
|
|
mAEcUi0bNnZBR0rWtoguMCkUi21wI161mXuocEKaYXMS4u+pY/hVCSWSY4HT0pEmlouiSahdpEBl
|
|
mOceleiwWcNjClvHgJH97Hc1EmVFFi3Czy7mwIl/WtJbjP7uLgd/apQ2VNVvtsBhiPzdK5S4nAuR
|
|
nqOCaTGi9pcytPlU+XpmumtWII44rah8ZjiNIXRuWeNvvViQ/LXpJWPJbu7nCRvVkNxVsxBmqJmo
|
|
EPiXca0YLMuOlJsuKuPlsSi5IrNuG8s4HWs5VEkbwoOTKsk+FJY4rC1K53k1xTk5O7PSpwVNWRzt
|
|
4cms+WpKICtSLTETQj5q0YeBSGiys23pUguGxQMq3E59ayrm4x3yaAKiRtO2WPHcmhruKFxFajzZ
|
|
ScA44qRHoXhuMaLpxaUg6hcDLMf4F9KlhuDeXGASIl+8azZslYma68y48m1+7nFW5rtbRNhb5z1p
|
|
iMKbUg0zuW4A4rPgb7VdKXOMmpA7HRbMS7nUYiUda0lkQOBngVrS+JGdbWLRt2bAx5BqeQ/LXpnj
|
|
PQ4GJ+ashuK0MhWaoWcA0AaOmASMK7jRNPWYBmHyiuepO2x10qfcv6vYxCzYqoGK4HVYVTJrmb5l
|
|
c6oaM5TUJ8EgGsG4kLNUHT0M64OaqMMikSRsuKbnFMRLG3zVehOaGNE445NNlnVFpDMu6uie9Vo1
|
|
8z5mOAOST2pDK91cNN+5tsrH3PrW54a06KxT7fdrlh/q1Pc+tJ6IUdZGvHPLezMcnBOWbsPap5r3
|
|
ylFtbdT1xUWNWzU0/Zbwlgfmx8zGsHWtRHmMqE59aAMyNifvHPc1f0gtPdqkY5JosJHeNci2tktY
|
|
euPnNY+oXWZEVJNrZ9aun8SIq/CzodHuriIokhDIR1ronbKZr0o6o8ipoz//2Q==`,D0=`
|
|
/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAsICAoIBwsKCQoNDAsNERwSEQ8PESIZGhQcKSQrKigk
|
|
JyctMkA3LTA9MCcnOEw5PUNFSElIKzZPVU5GVEBHSEX/2wBDAQwNDREPESESEiFFLicuRUVFRUVF
|
|
RUVFRUVFRUVFRUVFRUVFRUVFRUVFRUVFRUVFRUVFRUVFRUVFRUVFRUVFRUX/wAARCASwBLADASIA
|
|
AhEBAxEB/8QAGwABAAIDAQEAAAAAAAAAAAAAAAEDAgQFBgf/xABDEAEAAgECBAMECQIDBgUFAQAA
|
|
AQIDBBEFEiExE0FRBiJhcRQjMkJSgZGhsWLBJDNyFSVTY3OSNEPR4fAHFjWCokT/xAAYAQEAAwEA
|
|
AAAAAAAAAAAAAAAAAQIDBP/EACARAQEBAQADAQEBAQEBAAAAAAABAhEDITFBEjJRIhP/2gAMAwEA
|
|
AhEDEQA/APqYAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAKNTq8OkxzfNkisQC8eb1XtRNbzXT4q7eU2nu0MntRq/D8StMccvW29ZmdvgjsTyvZjxOLj
|
|
+s8WLxn8TFPXs6Oj9oct7c14rkxz22nrB2I49KOdTjelmszfmpMeUxv/AA28OqwZ4icWWtt/SUi4
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAmdo3nsPNe0Pt
|
|
Fh09Z0+DNWL7+9O/7A3eJcZppsV5raI27esvH6jX5ddM25p79Ilo59VbUZOe2Tm/PeGvfPfT2iKR
|
|
PLv1+DO678XmW/a97U6TtOyzTbTF538/T9WjTNecm9a7126tqk3rSYxY5ta1plRZqZNXGjyZcPXl
|
|
mZmsx+qjBrsuO16xM7eXRt04JrdTltk5OWJnfaWf0a2lty5MdZnfzSn+WOHiOutFpjHa9e8bQ2fp
|
|
+alYy462pk7zXbuxjPesbRS0f6ZZV1ET1tErzXFLHo+A+1ddZf6NrI8PJHa1vN6iJi0bxMTHwfOa
|
|
zhzd61v1846utwniM6DUdb3nBaNrVmd9vjC/ZVePYirBqMWppz4rxaPgtEAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAItaK1m09ojcHnvarjM8P0vh49+a/eY8ng9D
|
|
h1fGM1rxjtGPfvbzdbjuTJxHX48cTPNltM/KsS9Dw7S49Jp6UpHaGe2vjz1y9J7LYK13vHWe7bj2
|
|
ex1tvM80ekuxW3RnW3Vm6P5jRx8H0+OYmMcb+bapo8GKPdpC6bQwtdHU8JpWkdJ/JweL6e23iU67
|
|
d4dubSqyVi9Zi0bwIs68XGp36TtEq7ZJmZmevzdbifCKWtbJinkt6eTgZPFw32t+sRurbWVzxs1y
|
|
Rv6T8V1NZNPtfq0seTm+Kevr+SZuxXjvaPiV8N4viycto9HseG6+uu08W6Rkj7UPmFck1tE1nlmP
|
|
Ld3eA8V8HVVi1pjq6Ma/pnqce/ERMTETHaUrKgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAADW19+TQ5p/p2bLS4v04Zmt5VjeQeJ4bjnLqsupv+Ka1+ERLv4reTmcNxcuC
|
|
vy3l0qdI2hlr66sT02ot0ZV7qqrInruzrVZLGSZ37JjqgYTG0K5lbaFVhDT1Ub456RPweY4hixWi
|
|
eSdpjvD1eWejz3FNHWYtkpvFo9EIseb3tS3SerOms22rfpPqZKzvvHSYUz70TExG6Gdbs2rljeJ/
|
|
Mx5L0vEzPaelnOi98c9J2bFNTFpit47+a+PVUvx9T9nOIfT+GV5p3yY/ds67wvsXqpxau+G09Lx+
|
|
r3TqrEAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADV4ljnLw3U0jvO
|
|
O0fs2lWqyUw6XLkyfYrWZkHldBEV09eveG3Fq1mI3jd4vPrOIaid8G9MP3Y38k6fNrt/rMk9Ou8s
|
|
tfXXn49rGWInuy8SO/k5Gl1E3rG/fzbOe94wTy99mbRvTrMOOvNfJWsesywniukrG/jU6fF43WYN
|
|
TmtEeJtEQ06aSmK2+bNtEd+qfSO17unF9Hmvy1y13XWyVmN4tExLxVK8PmNq5NrT58zawam+m/yc
|
|
0Xj8NpRYSvQZ7xEOdqI3rPozxayNRXe0ct/ON03jmrKB5nV4q1yTO20Obmv4c+cx8HoeI6WZpNoj
|
|
q83niYmYscU0r8aJ6T1n49zeJ+Meqm1drb9J+Kd5p136StGVem9l9TbHxLDFp7W7+sS+q1nesT6w
|
|
+PcAzVjiGHftzQ+v4f8AJpv6On8jH9ZgIAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAABp8VrW/C9TW0ztOO3b5Nxp8VmI4bn37TWYB8f1HFtTfUfR9FWJmsdZ9I7MtJxDX5s
|
|
d8ta1y0xzteaR2277rcuhycP12SceLxMeWNpjttHwlu8I0mfQ1y+D7k5YmJmY36T36Ka43z/AF1t
|
|
cI1ds+qxVj7/AEej19PCw9HJ4NoK4OIU5Y35YmZdzVTGebVZabx5jJS+Tmns81rNLm1Wrzc9rVw4
|
|
Yibbem72mXTTS0w0M3BvEta1bWrM95ie5EanY87wXgNOL6XPfxraXLhra/W28bR/dzYzarBqJxRe
|
|
bzE7Rt5vWU9n8mPHOGmS0Ypnea1naJb+k9ncNLR7u2y/WcxXO4TOoyUrN6zD0FaW5Y3hu49FiwUi
|
|
KxCvLMR0hlW0jn6ukWw3iXjOJzbDlneOj3GaN6zDzfFOH+LE7SRGo83XNSZ2lbG2/WfdlvaT2cy6
|
|
rNFInlrv1mfJ37cK4PwTTxOoidRm2+/2/KFuyMp47XB4LivXiunrH2b2iH2qn2K/J8x4fGDNxTSZ
|
|
9Nh8OviRvTyfT6xtWI+DeXs9MNZubypASqAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAOZx6/LoOWPvWiHTcf2hiZ0e8fc2mf1E5+vP/AEeuSd7RC2uKtI6QjHfeINTfwtPf
|
|
Jvty9WPfbt/lucP03gxfJf7d/wBoReYpm97zaNeLb4Ims9Nt94auDjem1Wo5PFi1onylS+1o7l8V
|
|
bxvtupjDMdNkYtXS1+Stt+m63xImEJ4xjHER2ZxMUjeUTO3VRmydBbjLJqPi08mbeVOXJPq1sl5Q
|
|
Vbkz9+rRy35rxHqzmZlVEe/Ez5LRlW5iyfR6zffaIjq1OSNZps2a21rZInafSPJhxGMl9LStLRWM
|
|
lorM/A4dkrWbYfLZC2W/7K6eubX6b4RzT+W76K8b7G6X62cu3Sten59nsm3j+OXz3/0ANGIAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA0OIYfpOHPijvNNo+fdvtXJO18k/
|
|
/OwPFYbz2ls3jx8VqW6xMdWPEdP9D4lkx/dt79flLLHbkxTPwY6nt2512ORTRzE2x4/dpE7cvkme
|
|
E4IrW3hRMxO8THRtU1FKWtvtvK2upx22rzRCtXkqzh2jtF7ZbT122b01ndnpuWuP3Z3+Ky20qDVv
|
|
fauzVy3mejZzNK8dVjqi87KLRLYtXruqvXzkQp7Qoid88R6rcl+WGlW0/Sa22mfhCZOq2x082ix6
|
|
jkm822pO8VrPdr4dNObVeDo8XW3uzMbzK+mvxT7szE27cvnu9j7PcNjSaXx8mOIzZevbrEeic5tN
|
|
+SZnpt8J4fHD9HXHO3PPW0x/DeBtJxx29vaAJQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAKNRim9Z5e89Nl4DzXtVh5babURHrSf7f3ec1+qnDorWrvvt5Pccb0n0zhmWk
|
|
Rvevv1+cPE2rGTFNZU26PFfxwa5dVkjelI2772nZnX6bbrEUq3o0d678u8wmuDL2ittvVjXdneeK
|
|
cGv4jpJ6U56+kS7+j118+GLXpakzHaWlp9NNY3tv+bbiYiNoQy1y30uyZJlrWmZnuym6q1iIJnop
|
|
yW2Te8bdWnnypQqzZOadokiIpSZntWN5lrxki19vNRxrUeBwnNNd+fJEY6/OejXLn3Xe/wDp9wyn
|
|
E8uo4lqqxblv7lJ26T6vpD5X7G8QycKzeBMbzMRM1/FH/wA/h9QwZ6ajDXLitvWzRgsAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAeL45w+dDrZvWv1OWd4+E+j2jX
|
|
12jx67TWw5Y6T2nzifU+rZ1y9eHwzDYxxEy18+DJodXfT5o96vafWPVbjyxDn1OOzHudbM0rt2UW
|
|
iI69mVtRXZq5tREb9VUoy2iIlRbJ0UX1VZ6btTLrI7V6yk62M2oisT1c7JmtkttVMUyZp6x0beDS
|
|
RWOvdKijDimvWd3G9pNRMfRcNfvZOb9Hpb0itJeP47k/3hgjaZnbaP1XxWW3T0movbNS0W645nbf
|
|
0nrMPpXs3xamoxdJiLbe/X1n8Uf3fKsOTw4jbaXo+EarJhtGTHMxeJ6xH7Sti9Zaj6x3HM4NxXFx
|
|
DS1mtoi8dJrv2l011QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AGjxLhODieOIye7kr9m8d4eM4to9RwjPXFa0ZIvG9bR0fQXmPbDFvTTZPOJmEWS/V8bs9R43NxLL
|
|
G8eFbePg1bajU5/s0l1ceKLx1hbjwRE9mOpx0y2uRTSZsm3PMw2aaKtIjo6kYo9EXpET0hVLXxYK
|
|
xC6MZvyx1lFs0RHfaPiCnU12pLyHGNDbUajBekWma2npWN3p8+opa20e9LSyZLxExTlpM+vdOdcZ
|
|
a9tPS8MyUvFrzWlI6727u1pYxYrbVmb7x+TQx6au3Nqcl7/0rcmW9axGnwZJj1novmxnZXV0fFp4
|
|
ZxLBPgTGK8xzXr5fOH0bFlpmxVyY7Rato3iYfNuG2x56Wrqa8s2jz+7Lu8O12bS6jkwzN6THNNI6
|
|
tvrN68Y4rxlx1vHa0bskAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAA4XtTTm0OKfTJ/aXdcL2pyRGjwU362yb7fkJz9eTxxyZJjyltRXzUZK7TFtl9Lbwy06YzrHwa+
|
|
fJFd/wCVt8m0bQ0eS2qzcm+1K/an+zNZFL5M1pjFXeI72ky48eGnPkvNp27+TPU6nHpMfLXaIjpE
|
|
erk5dRMxOfN1mPeisfshW1ne1a1577Y6x5R3U0zze31FOWI6ze0byU098kRlzbxM9qrMlPDpyRMR
|
|
Md5Vt/Ihp5898mWZm1pjftE91uCt7fCI7dWeHDEW3t723l6rslqxWZnasR+SYhFbzhnfxJ2jyeq9
|
|
lcGXWZcmW0zWKxHLaI7794eJx5fpfEKabT8t8l5isddo3l9S4VjrwrRUwzSJt3tav3pdOL6Y6dXD
|
|
j8HFWm+/KsU4NRXPvtWazHquWVAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAa+fXYNP9u8b+kdZBsDkZOO135cWOZn4y5Wu4xqctbe9y19Kp4njt6vi+PDm8DFMWybbzPlV
|
|
5PiGtz67UxbNbeKTtWIjaIXYpnwuaftT5tXJT3vmi1pMsrU5qIrG1V1a+5DCa7b9GFbRr5J6Wnbt
|
|
Cu+Wmk0m8956z8ZWZNorbfzcbX5rZslazPux3hUt41NTntktObJ13+zX1bek01r4/HzVm0bxPXy/
|
|
+bNfDgjVa2uOY92kdfg6ufJOKvLXtttVVSqbcta2vM7zXtHpLQy5ZtMd+vWd+7Zy3mdJHXra3f0c
|
|
vUarw7zFY5rT2hH1Lavnrgx81p3U49Pk4nE5L35MO/StfNRXR5tXnrS8W67WvfyiPSPi7uLHFK1p
|
|
jrtSsbR5Lc4RzsXBaYreP4l45esRD2HD9fnw6evvWvO3Tfr0aGk0U55ra0TFInv6uzgrXFXlx0i0
|
|
77RPlC83Yj+JW7oddqr6vHzTTw9/f6dod+L1t9m0T8pcbFSmPHER3892W0zPuz+jSbVvidkcqmfP
|
|
Sel7bekrI4n4dZnPWIrHeYnZee2Wpy8dEaml4npNZblw5qzb8M9JbYgAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAABEzFYmZnaI7yCXL1XGa0jJXT0571nbee27DiXEprp8nhbxG20W8
|
|
5cbD0ikfnKO+urTPvjoZdXqctdsmTaPSvRpWmsdZ6yztfaGplvv3lWW1tyRlz1x0vkn7Vo5atTNe
|
|
Y0+1o79V2KsZsvX7Ne5mwxnyTNvsx2iGneM/rCdRSuOsTasTt5kRFtpjqmOH4t4nk7estiMNa97R
|
|
Hwhna0iuKTEdmGWa4672nZtRele1N59Zlq6vLOSsYorEc07qcW65euzRvtXvPZy52naZ7ujr6fXV
|
|
rWdukREK8+njHgmZmPc67bq6ivVWhxxgxZLztNrT1mZ/SP4VZs0zaOvfp84WUtNsXLvtv3699+rU
|
|
z7+Jtt5qURqMnPpctaR1rMSw4ZoK57eNk6xHaJRh97Ltt7lo5Z+L1HAPZvVauZ2nFTSzMTzeJEz8
|
|
to6xPfvsZntPZ9rXxabmxzefdrv0j1dXh/BcmstW1qxTHHasR3+b0GPhGl+kWmd64dNEVjf73T7X
|
|
y8vy+Ddx6O3iRakxTH5RXrMw1/lX+3Itw2MFIraN48qRHdZi0cUjmmPen9noox1iO0fNzdXEYrTt
|
|
stcmd9aX0bJ+HePmiKTitO8TMLZ1cVjrMfqpz6ys4pjfrPRWZ9rXXptUit6zO+23VyaRHEc05L1/
|
|
w9J9ys/en1ljqdVbwYw452tlnl3jyjzbmmiMeKtYjpEbLeTXPUU8ee/+qjJpsV5rbkrFqzE1tEbT
|
|
DpYNbW21Mnu29fKWna0KbqTdjXXjld0cvQ63ltGHNPSfs2n+HUbS9c2s2UASqAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAOVxPWe99HpP8ArmP4b+r1EabT3yT3iOkesvMVtN7za07zad5l
|
|
XV5GmM9vVfEstvDx0jtaVVMlq+UJ18b5cMRvPeSuK87bUt+i2Z3PtG7zXpjkzXt6R+TXyTMzvM7t
|
|
ydHqZ+zhv1+Cv/ZuqvPTHMfOYaTMil1a1K2vHSLTELq2v+KWzThGo84rH5rq8JzedqR+ZeI7WnOS
|
|
34pYTafWXR/2Pln/AMyrKOCWnvmiPyR6O1y9585lhWJvl557Q6eo4T4dYiMvW3b3UanhldHpJtGX
|
|
e09unmjsT7eb1l4trI2t0hsZfrdNO0bzy+nzU20/+NmkzO9esz+TZxWis9dttvPv+Tn21jjaW8zn
|
|
26bTG3mp1M/Wzv3t0jyWXiKZJmsTERaZhXXDbNl8WaztWenxZLstPp5pau8frDtVrNMM5cfTfpMf
|
|
3aunxxbes9d/R09Dp8ebJi09ptFr3jtt2WyrW9wy1Jx132mK+Xq9PotT0iIU19ntLtExa3T47T+q
|
|
6nBaYvsZstZ+cT/LeMnUi0TXffo1s2m8Ws2/OIMWk5Jib5L328rS2t94Sh5TV4ppklpW6PT6rh+P
|
|
NbebTHyas8E081mZy5P2W6OFhjxNTE/hr/LoRO0Kvo9dPqctKzMxEx1la5t3tdnjnMs4noievcrO
|
|
yZjeFF1OSnNV0OG62cn1GWffj7Mz5w05joovzY7xes7TE7w0xrjPeex6Ua+j1UarBFu1o6Wj0lsN
|
|
3JfQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACrU5o0+nvlt92P3BxuM6nxNRGCs+7Tv8
|
|
2hToxm1r3m9utrTvMsonqyt7XTmcja0u3O6FMfi5t/u0/lzdJM81p9O3zdvHTwsUR5+bfPqOfX1h
|
|
dqV+3O7bs1+T31oqmI3TEM4rvCdkDGIIhlFd2daboS0NXG2bD6bufxXU1vlmu/u4us/N0+L1tTSx
|
|
kr9qk7w89j1FNZMV3jxLzvaJ8mer+LSOZqK2xZotbvljfr/89U453rXt9lse081xZtNjx7TGKu0t
|
|
DHlrevSevaN5Y6+tJ8c7VRNMt63n3ub+6/R54rERMztDYy4a5omclYmfxKcenrjtHLvtPrCnVmdb
|
|
eFe3JXmjy6eS/DrMuLVYsta9Mdt++6qLxO+0dEc8UmInr18iUfReHcXrqccb9Z27Q61Lb13eJ9nc
|
|
1Z35rTvE9avY4bTkpG8xEfB05vYxqybc07R281naGMREdoT5JQqy9mply7Q3bV3iXG1eXw7TWSka
|
|
c258t7+tpT5/BjT7MfHqndz12Z+M4lMMKyziUJJiN1WSu9fku23RaOgKNJqbaTU1t9yelo+D0cTE
|
|
xEx1iXmM1Nt3W4PqvFweDaffx9vjDbGvxz+TP66QDRiAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAOJxzU73rp6z296zsZMkYsdr2naKxvLyObNOfNfJbvad1dXkaeOdpvsc2yuZVzfbfqybutwu
|
|
s5s8R92J3dvJb3tnO4HSMegtmt3nfZvYp8SZl0z45NfSK7onH1bNcfRFqnUKJr0Y7dVtq7prjEsK
|
|
0XVpEM6028mW20IHK41aPo3J6zs4ODhdcvPnvExFevNXpMOrxi/PlrTee7PLX6Pwa09uaNlKtHg9
|
|
dM3z5d7ReOu02nu0JzZMfblrv5R5uvrcdImZ26T1mYhxs1Os7RH93PZ7axuafNfLitvbaYU3yZYt
|
|
PXs9NwHhui1HBa5LVicsb81onrEuVqNNSuS8Y67dZ6xPZa59Il9uX41vEitImZme3q2Kxbxora0T
|
|
Md/ROSa4Ztkj7c9OafL5LuGYubmyX3iu/TfbdSfVnpvZLT/XZK233+Mbbva1xRXyiPk8pwbH4N6T
|
|
adq5a71n0tD1WDL4tPe6Xr0tDpz8YVnJHWEXYxbqlBedoef4tW0XraO09HdyztSZcbUz43C+ee9b
|
|
SVMaeOfqq7+jGckQ1Yz7+7v2RN/WXPXZPjci2+2yyJaVMuy+uSJlA2d+pNoVRbeDcSxyTE+TDDlt
|
|
pdRXLTynrHrDOyiyZeVFnY9TjvXJjres71tG8MnJ4Nqt4tp7T1jrV1nRL1x2cvABKAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAHJ49qfD09cNZ97JPX5PPw2uI6j6Vrsl/ux7tfk1mWr7dOM8iLdm
|
|
vfebREefRsWldw7SxqNbWbR7lPesrn3Vteo7dYjDpMGCvfbeXQ0uLlxRLRxROfUc34p6fCHYrXlr
|
|
EejqrjY8uzCYW7MZjdVKqK9VlaxCYrsnYExBMRMJRPZA8/xPHtmpP9W2xx76vhWOInvt/C7ike7N
|
|
vwzE9kcapGfhlevTaFbFo8RqJ5vy8/RoW09ek0msxHfp3dzNoLzp4zUmZpMbT8HJyYJi20X2n0lh
|
|
ZY1li/RaidBF4w2mK3jrHaFGp1lN+tptPp5IjBkid5mIp16TKu0abBPv33vPlM7z+iPdFNcWXU5I
|
|
tkrNce/b1W5db1nTaf3ax9q0fxDW1ebNk2phty1mOu09VOm8W19orEz23j1TwfSeERFuEYMddptW
|
|
d43dvBn21eKJ75KbW+cf/JcTgMxXTb3nbljz+TpcPmc2uyZO1KRtVtGVdi0bx07qJnllsRO6rNTe
|
|
N4XVamsy8mnvPwc3R2jPwe8TPbdlxXNOPSZfhWWpwO85OFzv57qrODkzeHntSe8Sn6Rv0a3EZ218
|
|
8nXekfr1a0ZLVnqx19dWb6demXybOO7lYMvNMdW9S/VVLo0us7tPHdtUtEwJiZU3jq2Jhham8CVG
|
|
PNODNTJXvWd3qcWSubFXJWd4tG8PK3pPd1OB6veLaa89Y61/u2xfxh5c/rsgNHOAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAANLimq+i6O0xPv392rdeZ4rq/pOqnlnelOkIt5F8Z7Wj27I2I6sb25YY
|
|
V1ImY3dbQ08LRc23vZp2j5OJG+XJWle9p2h6HHtbJXFT7OOIpX+7TxT31j5rycdTh+Dpz+XaG/sw
|
|
w18PHWseULN2trBE9UcrJKBhFU7JAQi0dEomegNDUYovM7x3jb5tO1ZvpbaTLtzRExWfWPJ08kbT
|
|
Ex5NXWYYyV5omYtHWJieyeDzuizfRs19Jn6TM7Ru1uMcJxZqTkw+5f4ebqa7SV1MR4tdrx2vEfy1
|
|
axqsNOTLjnLXytVXi3Xj8+nmsxTLM16d5npPyUzpekTtSK+U7vS6vQ/SYmK1vWPS1HOn2dvvvvE/
|
|
tDO5XlcO+LbfHSd/W3o6/BdDOXPTnj3Kz38rS6Wm4FNrRyRzTH3p6RH/AKvR8L4dXSzE3jmtHn5I
|
|
mbfqLV+m4dbLSsZInHjr3iI6zLpYaxS01rHuxHRHiT9mv6s67Vj1aqL6326MrWiYa+/Q54BxPaGe
|
|
XRZpj8MquB4+Xg8zPnB7SX30to379GxpK1xcHiKz5IS8xr8PLPixH2bftLTy05o6dHYyVjLhy0t1
|
|
izjZa3pMVv3iO/qz1G2L+NbSajbNyW7xLsY8kTDz+fJXFqKZN4iZnafi6WHL0iYlStI7OO+7axW2
|
|
crFl7dW9jvE9ULN+J3ZbdFGOy+AYWpEqN7afNXLj+1Wd23KrJVMvCzseh0+auow1yU7WhY4fCdV4
|
|
OadPefcvPuz6S7jol649Tl4AJVAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAV581NPhtkvO0R+4NPi2
|
|
r8DB4dJ9+/7Q83Po2NTqLanNbLfvPaPSFDHV66sZ5ET0hRknyW2lTtMyouz0c8usx2n7s7vScKwx
|
|
zc1vu/y85p+maJh6Th+SOWeveXR4/wDLm8v+nX5mUWa9bbrInolmu5jdTNkxYFk2Isr3TuCzeGMz
|
|
+THdEyDDJO9Ja823rt2XWnya946pGvktDXta0ztWu/ybvLE9dkcoOf4GbJPWK1j49VmLh9JtE33v
|
|
Mevb9G7WsW8l1ccREISophiJ2jpDYpijbaOjOuOJ8ujOdqxsgVcsUjaETYvbaFFrgu5lVsm0yUtu
|
|
ryg43H5m+GIj1XcJzePoL4pnrWGtxmfchr8JvfHS1622if3QljzTTLes+qrNjrkiYtCzPMxnm095
|
|
YZJ6boS5teB49Tqscza97VtvWvlv8V/FOF34RrIxTM2xXjelp/eHoeA6XnzReY3ivX/0dfivDcfE
|
|
9HbDbaLx1pb0lOs+jO7K8Lis3cN+0NKcd9PmthzV5clJ2mF9J9GHHVL108dm1SznYr/Ft0tuhLb8
|
|
mNohFbMhLWy0mJ3rPXvDvcO1karBG8/WV6Wj+7kWrvDDBlvpdRGSnbzj1hpjX4z8mOx6UYYstc2O
|
|
uSk71tG7Ns5AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACZ2jeXneJ62dVl5KT9VTt8Z9W9xbWclPo+O
|
|
fft9qfSHEU1pv48ftYST23ZTDC/p0YtlVuvVjMbM5+LCZjYGWGdrTPxiHY4ffaf3cjTxz1v6xMS6
|
|
Olty2iXVj/Dk8n+ndrkhnGRo1v8AFdW3RCrZ5uiYsqrboncSu508yjmZRYQt50TfowYTbYGVrKrT
|
|
uTZjvukQnYhMIGVY2ZxPVWyrHVCWzXpVXkt3TE7Va+W4K7X3jv1auTNy3jdba0RZpamfroQN7Hk3
|
|
6wr1GTaN2OOJiu6Mu98NvgDi8Wy74d/yZ8PiPAiO2zU4nb6qIn1bugjfFE/ASp1ke9u15mbbRDZ1
|
|
Mb823kx0Ontn1OOkedoJCvT8I03gaKsz9q/WW+isRWsVjtHRKyrhe0XCfpWL6Vgr9fjjrEfeh5fF
|
|
feH0V5Dj3DPoOo+k4a/U5J6xH3ZZ7z3228evytOk7NvFbo0cdols47bSybt7HbddHVqUs2aW3Qnq
|
|
xVeu8LILR3SlZw3V/R8nhXn6u0/pLuPMXjeHT4Zruf6jLPvR9mZ8/g1xrvpz+TH7HUAaMAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAABRq9VXSYJyW79qx6yvmdo3l5viGs+maqYrO+OnSvx+KLeLZz2te1rZL2v
|
|
ed7WneZYWnZl5K72YV1xEyxmeqJljzIEWlVkszvbZp5soN3h2SJz3pP3odCnuWmPRxuERfJrZmtZ
|
|
mtY96fR28kbX3dXj/wAuTyf6bmK+9YX1s0cNtm3Sd4LFY2K23W1s16StiUJW7bp22RW3RluBuruz
|
|
mWEgrmCGWyNkoExKE1QlPmsqRDKeyBjaejWy2W3ttDUyz1QKslvehVqKTNosyyTvELabXptIJpaP
|
|
B39Ia2mz+JGpr51jdZefDx2hzuHZObNq58poJaGtjxJ2+LoaKP8ADRPo5+T3skx5OhpOmC0fBNQ0
|
|
5yTbn+bt8A0u9raiY6RHLVwY62mI6zMvaaHBGn0mPHt1iN5+aYVsACBXqMFNTgviyxvW0bSsAeE1
|
|
mkvw7V2w5Ote9besJx2er4rw2nEdNNekZa9aW9JeQjnxZLYskTW9Z2mJY7zz26fHrrdpbZsY7NGt
|
|
mxjvso1b9NmUwpx33XRO4K7VUTE1nmrvEx1bVo2VWiJE/XY4frY1WPlt0y17x6/FuPM0m+HJGTHO
|
|
1qu9pNVXVYt46Xj7VfRtnXXL5MfzexsALsgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAHM4jxOMFJphmJv529Dq
|
|
ZLfjDjPEIx450+K3v2+1MeUOHSOWFc3nJkmZnf4yujpVlqunOeFpV2nctLCZUXRM7MJtsWlRkv3Q
|
|
ky5NmpWt9RnrixVm17TtEQnJabXisRMzPSIew9n+CRoccajURvqLx5/chfOest642OGcIpoOG2w7
|
|
ROW9d72+LQvXevyejcPUU5M+SvpLeOataraw2a0dLbLqTtK1G3Es4lVWWUSoldFtmcXUbpidgXzK
|
|
GEW3TuCUSncnsDFMMLSms9EC6J6FpVzbZE5ALy0809ZbFr9GtfrEoFMzuuwz0Ueey3HbaBLDXe7i
|
|
tMOfwWnP9I+NZbuttvhs1uBRtXPb4SDm3iIvf57N7Dbl0VrS5+XrltEd+Z1Jx7cNms9N4TURRw3T
|
|
+PrcO3WszEvZOD7P6aYiMlvu16S7y1QAIAABxOPcLnUY/pWCv1tI96I+9DtgmXl68Biy7/NtUu3+
|
|
O8HnFa2s0tfd75KR5fFyMWTdhrPHVnX9R0cd21S3Rzsdm1iuqs256wrmGcT0RYSx5d047X02SMmO
|
|
esd49YRE9WcdSXhZ2O1p89NRji9J+cei1xMc3wXi+KZj1j1dTTaqmor06WjvWW+ddcu8XK8BZmAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAMMmWmKu952UZ9XFZmuP3revlDTtzWnmvO8q3XGmfHb9ZanV3yxtWeWn7y4es
|
|
vPNtDqZJ6Ts5mppvdl/XXRMyfGvSNlu/RVvtOzLfoipLT1VTKbSpvfogRkvtDVyZOhkyvQcA4Dzz
|
|
XV6yvTvTHMfvK+c9U3rkW+zvA/D21urr789cdZ8vi9KDb45rejl8Rry6iJ/FV1HP4vXbBTJEfYt1
|
|
+UpiHM295bXsqrO9l8QkZ0lZEqqLeyBZHZLGvZkhIndADKJ3TMoqWQMZ6pjsxll2jsCLSrmU2lFY
|
|
36gieyu0LJk3jbsga0wdqzK20QpyztQGprL/AFMrOE05NLkt6qdVWZxNrSe5o9vWBLiUjnzXn0vL
|
|
q555dHt8HOwV928/1z/LpzXxbYccRvzTB+jucOwxh0dI22mY3ltIrHLWIjyjZKyoAAAAACJiJjaY
|
|
3iXleM8InR5J1GniZw2n3oj7s/8Ao9Wi9a3rNbRE1mNpifNFnVs65XhcWTdt47bnFuF24dm8TFEz
|
|
p7T0/pn0a+HJux1OOrOux08d1ndqY7tillVkzExLOk7yd4YxGwluViJhE45raL0na0dtlWO0+bZr
|
|
1TKi+2zptZGTamT3b/tLacvJjiY3XaTWdYxZZ6/dtPm1zrv1z78fPcbwC7EAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABhkyV
|
|
xUm152iAZWtFazNp2iGhm1Vss8uP3aevnKrNntqLdelI7VRHRnrX/HRjx/tZREVjZXeybW6KbWZt
|
|
pCZ6S08tN7Nmbb7zCrJtyoS5145bSx5mWafelr3tsKmS/o08uXyhlly7RPV2+AcBnPNdZrK+53pS
|
|
fP4ytnPVda4y4BwHxOXV6uvu96Unz+MvVxG0bQRG0bR2G0nHLb2gCUDX12LxtFmpHeazt82wT1gH
|
|
mMN4tWs+rcr2aEV8DU5sM/cvO3yb+O0csLUTSdrLphRE8tlkZI7Atr2ZMazDJVKTYSCawi7Ksq7z
|
|
1QERvLK3ZGPrKbyCrbdnMcsbeaa18/RhvvM7oGEwTG0JmYYTIML22a2e28xELM19oURPNO4lOem+
|
|
n3ZY5+prVnMc2GYU4/L4A0a15cNf6rz/AC6fC6+NxCPOuOu/5tHJTbHj+F5/l1+BYumXJMd9o3/d
|
|
MRXYASgAAAAAAABhlxUz4rY8lYtS0bTEvH8R4ffhmo6bzhtPu29Pg9mq1Gnx6rDbFmrzVsizq2df
|
|
zXkMWTeIbNL7tbXaHLwzUctvexWn3bmPL8WFnHVL326VZ91MfFVjvvVlz79kLrcf2m7j7bNHH3bl
|
|
J2SirLQoy4t1++7G0dBC/RanxI8PJPv18/WG241+alovSdrV6w6mDNGfFF4/OPSW2b1zeTPL1aAs
|
|
zAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAVZ9RXBTe3WZ7R6iZOpzZq4ac1p+UermZMl89+a/byj0Ra9815ted59PQ32hlrXXRjH
|
|
DpCLX6ML5NlNsm/ZRqstfdXzbsZt06sLZNvNB1Za8RDWyZdo7q8udq5Mu/mIMt4md2lmy7JzZuWJ
|
|
dHgfBL8RvGo1MTXTxPSPx/8AstJ1XWpIs4BwSdbeNVqq/URPu0n73/s9hEREbRG0QUpWlYrWIisR
|
|
tER5JbSccur2gCUAAAAPM8Sry8Uyz67fwuxbzVPGsE49XGbvF42V4M0TEL33ERnktsxpk3sumK2j
|
|
admFdPFZ33VS2Mdui2J3UU6LYlFSsN2O5NkCyJ6K7T1TEsbAsxdpReerKkTFGMxvYEz0rsqtbbpC
|
|
b2VT1QEzuwtbaGUxspuJU3neWdKoiu8rq12gCI92YatLcublnzbEz1aOptyZqTuDHLfxN6R0+t5X
|
|
qdJhjBp6UiPLeXl9NSMnEKxHa1+bb8nrlvxUAAAAAAAAAAABTqtNj1eC2LLXeto/R43VabJw/VTh
|
|
ydY+7b1h7ho8V4dXiGlmvbJXrS3xRZ1fGv5rzeHN02bEW3cys3xZJx5ImtqztMS3MeTeGFjqlb2O
|
|
8btql3NpbZtYsnSBLeiWfdTjtutid+ghherHS5p0+f3vsX6T8Fkw181d4lMvEWdnHaGnw/UeNh5L
|
|
T7+PpPxbjdyWcvAAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAo1Oprgr63ntAmTqdRqK4K9etp7Q5d7Wy2m953lNrWyWm953mVd77R0
|
|
Za1104xxlN9lV8qnJl2a9s3xUXX2ybsJyRDWtl3YWydEC+2VRkzeW6q+T4tbJm+KRdfK1cmWZnlr
|
|
vNp7RC/R6HU8SycmCk7ed57Q9ZwvgOn4fEXtHi5/O9o7fJaZ6z1uRyOEezVstq6jiEbV71xevzer
|
|
rWtKxWsRFY6REeSRrJxz22gCUAAAAAANbX6aNVpL0npMRvWfSXlKamsRMVvXm+EvZXjmpaPWHzfL
|
|
oNRjzXicfWJ8phfPxFejx72x7xMzK+sXiNoiXlq+Pi6fWV/VfTNqfLJl/WTg9Pji8R70LqvMV1Gq
|
|
j/zcv6yz+lanzzZP1lWpelTET6S81Gp1P/Gyf90s412rjtnyfqql6asREdWM9+jz9eJ6yP8Az7uh
|
|
odZqMt458tpB1JvEViI3/RhzRt13/R1MNaziiZiJn5K9ZNceKZiIiQcu/WekT+iYrWI3lzdTrs+8
|
|
8uW0fJzcur1Np/zsn6g79phVaIeetqNR/wAXJ/3SwnUaj/i5P+6UD0ldonum161h5mNRqP8Ai5P1
|
|
lNtRqJjacuT9Qd22WN5aGeZyZd/KHJy59RHbLf8AVq31Gp/4uT9ZEvS8Lr/vSs2npzRtL1z53wK+
|
|
oza/HW2XJNd99pmX0Rb8VAAAAAAAAAAAAAAcHj/C5yV+l4I9+v24jzj1cLFk8nu5jeNpeW41wmdL
|
|
knU6ev1Vp96sfdn/ANFdTrXG+eq1q5F2LLtbZoY8m8d11bbSydErsYsm+zZrO/zcnBm226uhiyRK
|
|
EtrvCrJDOJTeu8A1MWX6Lqq5N/dnpb5O5ExMbx2cPNTeJb/DM/iYPDtPvY+nzhri/jDy5/W6AuwA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAa2p1UYo5adbz+xbxMlvqJ1OqjDHLXree0ejmzNrWm953tPmTPWbWneZ7yoy5YhjrXXTjH8s75N
|
|
mtkyxt0VZM2/m175N1V03yTKubMLXVXybeYLLX2VXy7eam+b0bOg4VquJW+rry4/O9uyZOq3UjVm
|
|
9r25axMzPaIdvhns1kzbZddM0p5Y47z8/R2+HcF03Doi1a8+Xzvbv+TotJnjDXkt+K8ODHp8cY8N
|
|
IpSO0RCwF2YAAAAAAAAACvUZYw6fJkntWN3k8dfHz2vLucdz8mkjFE9bz1+UOZosX1UzPm0nqI/W
|
|
MYo9FlcPNklfFGeH/NshLGun+Cz6PtHZtVZWlRLS+jxPkRpIn7rdoupHTdA5s6SI+7H6Mfo+32Y2
|
|
+To3neSIiZ7A0IjPXpXLePlMotGW3272t85datKzHZjbTVnsDj+FG/2Y/RlGP4R+jo20u7H6N1Ql
|
|
o+H8I/REY957R+jpfReiK6eOYHLtj2tttH6KrY/6Y/R2c+kjeJiFVtLG24hxpw7/AHY/RRkw9O37
|
|
O99Hrt1YX0tfOBLjcGp4XF8c+u8fs9c4dcVcGemSI61nd3IneN1orQAAAAAAAAAAAAABFqxes1tE
|
|
TE9JiUgPKcX4RbRXnNgiZwWnrH4XPi28PdXpW9JraImsxtMS8pxXhF9DecuGJtgmf+1TWW2N/la1
|
|
L7N7T5e3Vy6W3hsYcvLbqzbO9jvvCzvDR0+XeO7crO6FmGSvRThy/RtVXJ92elvk2rRvDUzU7pl4
|
|
izsd2J3jeBpcNz+Lg5LT7+Pp+Xk3W7js5eAAgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADs0NTrN96Yp6edkW8Wzm6+LNTq4pvTHO9vOfRoWtt
|
|
1mes95YWvs1s2fZldddOczLPLn2ju0MmebT3YZc2/mpm3qqllN1drsbZIhr3yzvtHf4AsvlYYseb
|
|
V5Yx4KTe0+UQ6nDvZ3UazbJqd8OKeu33peq0eh0+hxcmnxxWPOfOfm0mP+steT/ji8N9mKY9suum
|
|
L37+HHaPm9DSlaVitKxWsdohI0Y22gAgAAAAAAAAAABXnyRhw3yT92Nwef4xm8bVzET0rPJH5d12
|
|
CvLhho3rN9RWs9Z23n5y6O21YhrVYbdGOCfrrLPJRpv863zVS6FS09SvZj3lVZZRdPSqmnSWdrIE
|
|
ebOkK4ldTsgW1WKqd1oMZhEVZyRAImOjGI6rJ7IiATNd46qL02bHkiaxaoNGY2n4ImPgtyV2n0Vo
|
|
Gvlx7x2beiyTk08RPevSVUxux00+Fn2n7N+n5rRFb4AAAAAAAAAAAAAAACLVres1tETWekxKQHlu
|
|
L8InR2nPp43wz3j8P/s5dLveWrFqzW0bxPeJeV4xwmdFec+CJnDM9Y/CrY1xv8qvTZ+WYdbDk5oh
|
|
5zHk283U0eo3jaZZ2N5XYjrCnLSJhOK+8d1kxvCqzSwZvousrb7k9LfJ3nB1OLeJdLhufx9LEWn3
|
|
6e7LXN9Ofy5/W4AuxAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAETaKxMzO0Qi9646Ta07RDmZ9VbPbaOlI7Qi3i+c3TPUaqcu9adKfy0722ZXvFa9
|
|
XO1OrjrESxt66ZJmcjPUanlidmhkzTZVfLN5VWvsC2b7R3U3yqrZZtO1esz2h2+F+zWTUcuXXTNM
|
|
feKR3n5+iZLVbqRzNJo9TxHLyaekz62ntD1fDOA6fQbZL7Zc/wCKY6R8odLBgxabFGPDSKUjyiFj
|
|
SZkYa3aALKAAAAAAAAAAAAAADQ4pl2pTFH3p3n5Q33E12Tn1eSfKscsLZ+orS00eJqbW+Lfnu1tF
|
|
XaJnZsz3WpCfsyp00fWSvmPdVYOmSUDd8kR3InoQosy7JmUX7MdwZ17ro7KKT1XRPRAsrO0rYndr
|
|
79V1ZBaQiJ6JgCSIJASwrO07MpV2nqBlrv1a1o2bf2qtfLXaQUTO0sb05o3jv3ZXhjS20xEphW5h
|
|
yeJjjf7UdJWNKLziyRePsz0lux1SgAQAAAAAAAAAAAAAADG9K5KTS8Rato2mJZAPIcU4ZbQZuekT
|
|
OC3afT4NXFkmlntc2GmoxWx5K71tG0vHa/RX0GpmlutJ61t6wrY2xr8dXS5uesN+tt4ef0eaa223
|
|
2dnHk3juyreM81OaFGiy/RtZET9jJ7s/2bdutd2jqKeic3iNTsd8a2h1H0jTVtP2o6W+bZbOO+gA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABje9cdJt
|
|
adohGTLXFTmvO0fy52bJfU23t0pHaqLeL5xdK9Rnvqb+cUjtCi94xxvK3JetKuHrdZvaa1ljb10y
|
|
cnIs1Wt3naJc++TmVWvMz1YWybfMGdsm3eWek0mo4jm8PT0mfW3lDf4V7P5tdMZdRviwfvZ6/TaX
|
|
DpMMYsFIpWPTzXmf+steT8jn8L4Dp+HxF77Zc/4pjpHydYGjC3oAAAAAAAAAAAAAAAAADG9opS1p
|
|
7RG7zszN6WtPe0zLua+3Joss/wBOzhzG2OsL5+IrY09dsSyYRijbHEMvOChb7KjF0yS2LQ169Mso
|
|
S24noyrPVXWejNVKbTuw3T3REdQWU6LYlVvsyiUDPfqupPRr79VuOQX1lZEqoZxIMksd0gT2VT0l
|
|
bPZVbuCaW8i8bwr32WxbcGnkjaZa9p2ndv5qbw5+aNugLItF6TEtvTX5sMb969HMpfazc0d9stqe
|
|
vVZDdAQAAAAAAAAAAAAAAAADV1+iprtPOO/2u9bektoB4TJTJpNRbHkja1Z6uto8viVht+0HDvpG
|
|
H6Tjj6zHHvbecONw7Ltfkmeqmo6Ma69DXbbZTkr1mGWO3RneOaGbZRoM30fVzSelMnT83aef1FZ7
|
|
x3h1tBqfpGnjmn369LNc3sc3kzy9bQCzIAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAa+q1dNNXr7157VhGp1Xh70x+9f9ocy283m1p5rz3mVbrjXHjt91lz
|
|
5c9+fJ1nyjyhdM8lZlOOIiqrUXikd+kMreunnI5XEdX4dZiZcG+XmtNl/F83PeeWWHDOGanieSKY
|
|
q+5H2rz2hMzWd1Iqx1yajJXHhrNrW6REeb1nCPZumn2z62Ivl7xTyr/6uhwzhGn4Zj2xxzZJ+1kn
|
|
vLoNJnjHW7TbbsAszAAAAAAAAAAAAAAAAAAAAaPFrbaSK/itEOXt0rDf4xb/ACa/GZacRvaF58Q2
|
|
IjasQnzPIhCU92tMbZGzHmotG10C6nZkwpPRmipIllEbMIZIE7solgmJBnCyk9VMM6z1BtVllEqK
|
|
z0WRILYlluriWcSDJVbusV27gwInaSWM9ECyZ3hqamnSWxFmOSOaqRx725bNnSZNs9J+OynVY+WZ
|
|
YYr7TE+nVaIr0Ais81Yn1hKAAAAAAAAAAAAAAAAAABExvG09peU4nov9n66L0j6q/WPg9Y1OJaON
|
|
ZpL0+9HWs/EWzeVz9PbmrEtnyc3h9reHy26TWdnSr2YX6657ijLXpLX0+onSamL/AHJ6W+Tbv2aW
|
|
ekTv16JzeI1Ox6KJiYiY7Slz+E6jxdN4dp3vj6fl5Og2clnKACAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACZ2jeQRMxEbzO0Q08uqtkma4ulfO3r8lefUePMxWf
|
|
cjy9WvlzVxV6T1Z61/x0Y8f7Wc7Ur1lqVy+LqOWJ2hp6rXddon5rOF1tfmz5OkT0qzb8dWbxjp1c
|
|
biuuilJ5Z6r+IcQrixzEy8zl1E6rNt1tMztFY81sztU1eRucN4ffi2p5esRM72n0h7rS6XFo8FcO
|
|
CkVpX082nwXh3+z9FWLxHi36328vg6TZyW9ABAAAAAAAAAAAAAAAAAAAAAADj8Unm1tK/hqppHvw
|
|
y1k8/EMk+m0GOPeafiFpCZYwolnXspvHvLa9mF46gmnZmwozRUiUCBKYYsoBLOFbKAX0llEqqyzi
|
|
QXRLOJVRLOOwLIljZMEgrlhKyYYTAK5nZPN0RZjugUanHzVlz6xtLq361c+9eXItPpXX0dubTU+E
|
|
bL2lw2++O1fSW6m/VYAISAAAAAAAAAAAAAAAAAp1GbwcfTreelYEydcuMcRrM/L9nnlsV6wqpi2r
|
|
tv133mfWVkRyRtEdGFva7MzkYZNoamWN4bV4mYa9qztKIujhVppxGI8r1mJegeZpknBqKZY+7L0t
|
|
LRekWrO8TG8Ns/HJ5ZypAWZAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAADS12fp4VJ6z9qVuq1HgUiI+3bpDl589cOKZmevqprXPTbx477rDJlrhr1nq4+s182tMRP
|
|
RqaziXiZJrWekNG17ZbxWJ336M5LXRbI3dLTJrs07RMY6fan1dHLrowY+X7MVjt6N3R6Kul0EbWm
|
|
s7bz8Z+LnabQX43r7Y53php/mXj+Dnv0f1JO1x/8ZxbUzj02O15mfLtD13AvZqnDds+pmMmo26el
|
|
XX0Wh0/D8EYtNjilY7+s/NstpOOTW7QBKgAAAAAAAAAAAAAAAAAAAAAADG88tLW9I3BwJtz6nNf1
|
|
vK/DHVqYJ3pzT5y3MPZeojOWMQylEKpTVjZnDCwkqzYQyRRICATCITAJZQxhMAshnEq4ZQC2srKq
|
|
qrIBZCWNZZgwswmFloVyCu0dFcx1WyrtCBhv5NTPHXds2U5o3hIz4ffbPt+KHUcTSW5c9Jme0u2v
|
|
VYAKpAAAAAAAAAAAAAAAAYZctcVOa35R6tLrltN795/YvknNqrfhpPLH92V5isd9mWq6fHjk6rn0
|
|
ZxG8KK5Jm/wbVZiYZtqrmkqL023bkxvCiY3lJHNyRG81mHS4Rn5sNsNp64+3yaWaNrzOzHBl+i6q
|
|
mT7s9J+S+ay8mex6EIneN47SNXKAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAImYiJme0JafEs3h6fkidrZOn5eaLeJk7eOdm1Hi2vmtPTry/CHmOJcUvmvOPF1n09Pm
|
|
6HF9ZGm01qxO3R5vSY7XwzmzTy47zzTEd7en5Mfvt2/PURWdo3tvPrPlKymbktFqTtMTvHzbOLDG
|
|
f63JXbFX7FdnoODcDprZpq9TjiMMTvSn4vj8l5fxnrk91saPSa7i2hpOfbTVt5x1m0fLydzR6PDo
|
|
dPGHBXasd585n1lsRERG0dIF5OOe6tAEqgAAAAAAAAAAAAAAAAAAAAAAADX11+TRZrf0y2Gjxe22
|
|
gtH4piP3TPpXKwxtjhuYo9xq442iIblI2pC1RET2ILd9kxCqRjZmwlCSEohIJAQAAJZISDKGUd2M
|
|
MoBnVbVVCyAWVWeSuqyOwIlXZZKue4MJV2WWYT2QKbKL9YlfdRdIo35b7/Hd3KTzUrPrDh27uxpb
|
|
c2mpPwX/ABX9XAKpAAAAAAAAAAAAAACekTIp1eTwtJmv+GkyJn1oafeazbfpMzLR4jq/o8b823zX
|
|
6XNF8ERCvTcNpxLV5LauvPhx9Irv3lhztdtv8TtaWLicXrt03jzjzb2k1nid56ty3s/w+a7Uwzjn
|
|
1raejlarhmbhl/FpbxMO/fzj5p/ixSeXOvTtRfeI280ZI26tfDm3pWe63LaZx7qtGvniJ6tPLvOK
|
|
fOa9WzbJvTbza02jl3n5SSljscK1MajSxWZ96nSW88xw/VfQ9XMT9nfa3yemid43jtLeXsce88qQ
|
|
EqAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADia3UTm1l4j7OP3Y/u
|
|
7Vp2rM+kPJW1PhYcmS0+9MzKm/jbwz31weMzbV8UppazPL9q0/BF4rk1GLDSNqxPWPhCnHmnNrtT
|
|
qPKteWPm6U6OdHaZvO+SaRNvhv12Ub/q3FhtrNVj0uKOt56z6R5y9zix1w4qY6RtWsREOJ7L6OKa
|
|
S2rvX6zNM7T6Vh3mmZyOfya7eACzIAAAAAAAAAAAAAAAAAAAAAAAAAAczjVvqMVfW/8AZ03I41bf
|
|
Lp6/OVs/UVrY47NyOzUxd4bUJpEbb3Z7IiOrKIVSjZhMLJYyhKIgmGUQSDESIEbJEgQmCITEAmGU
|
|
IiGUAyhZVhDOoM4Wx2VQtqBKuyyWEgqlhKyyuyBVaGtkbNmvk7A15l1eH2300R6TMORPSXT4ZO+O
|
|
8fFefEX63gEAAAAAAAAAAAAAAAq1WPxdLlp+Kkx+y1Fvsz8gjhaDauGK8sx07y3OE3m1tT6RaP4c
|
|
vU6yMNKUx73zT0ilY3l2eF6a+m0kRl/zbzz3+Ez5M8z26fJruW6wzYq5sV8d43raNpZjRzPPaTmx
|
|
5b6bJ9rHO3zb2WJ8GWPEscY9bgzxH2t62n19GWW0eHOzHU5XbjXZ1x8WTnz2iZ7S2M1IjH2+LX0V
|
|
KTqs8zO9ot0j8nUthi1J3UaOFMTfLFo6xMbS9BwHWTqdHOO8+/hnln5eTjYMFo1WTH5VnePzXcIm
|
|
2k4zlpPSmXy/hfF5eMfJns69OA2cgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAADG/2LfJ874rW845mubliY7bPoto5qzHrDz0+yePNF41OotaJ7RWNtpV1OtfHqZ715fhu
|
|
j8adNpcVfeyzE2/vLuanhOu1nEctIxTTFa/+ZPbZ3eHcF0vDbTfFE2yzG03t32+DokynXl9+leDB
|
|
TTYKYccbUpWIhYCzEAAAAAAAAAAAAAAAAAAAAAAAAAAAAcXjE/4zDH9M/wAu04XF5/3jj/0f3Wz9
|
|
RUYmzDWxS2I7FSyjuzY1ZKpRKEygEwiWUIkGIk2QJNhKQhMIhkCYZQxhlAMoZwwZwgWQshVCyATL
|
|
CWc9ldpBhZXLOVdpQK7NfJPRdaWvknoDVvPvOnwuel4+TlXn3nS4VPvXj4QtEV0wAAAAAAAAAAAA
|
|
AAAAAVV02CmTxK4qRf8AFFeq0AAAanEsfPpZmO9Ji0NDLfkwdOsulrumiyzHlVzJrz4Ovoy26vB8
|
|
cTBa9NffLtMY77Rv8Yegx5ImkKdJoY1HC81Y+3OSbVn0mGGkmbY45u6tnrrTOu2xGO0RxCd+nNVj
|
|
qKxTV1vH2pjaGtnyzXXYdo96ZmGXEMk15b7/AGZiVerWPTYckZcNbx5wzc7hGbnxXxzPWk7x8pdF
|
|
0S9jh1OXgAlUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAcPjEf4/FP9H93ccXjMf4vDP9Mx+62fqKrx+S+GvibEFSsqyYwlVK
|
|
ZYsmIMoRKYJQIPIEiQ2ATCUQygCGUIhMAyhnDCGUIFkLIV1ZxIMpVWWSrsCuyqyyyq09ECq8tfJK
|
|
66jJ2Bp5J6upwn7dv9Lk5J951uE/av8AJaIrqAAAAAAAAAAAAAAAAAAAAAAq1Mc2myxPnWf4cmtu
|
|
XT9fR0tffk0WSe28bfq5Wbamm3326MtunwfK6PCv/AxPraZ/dz9PO97/AOqf5dHhdZrw7Dv3mOb9
|
|
XOxRFM+avpe38mvkPHf/AFWlrKba7Tzt99ZxKkfR7euyNXMTrtPHfa0z+zPiM/UR8Zj+Wbdu8HpN
|
|
M2bfzrV13M4dO2pyR61dNvj44/J/oAWZgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADj8bj63BPzdhyeNx0wz8ZWz9RWri7Nmv
|
|
VrYu0NmqaRZHZlDGGSiwxZSgCEkCBCQSCQBMJRCYgEsoYx3Z17AlMIhlCBnDOGEM4AlhZZKq4KrK
|
|
7LLKrIFN2vdfZReAaObu6/CO9vk5OePR1uEd7fJeIrqAIAAAAAAAAAAAAAAAAAAAAGtxCk5NFliI
|
|
3mI32+XVyNTyZOHTee946PQKPoeDffw4777eW/yVs60xv+ZxOnr4Okx1t05KRv8Ao41Z5q3yed5m
|
|
XY1szXRZ5jvFJ/hxItP0aOSN9q7yrtr4f2tHFM5+KT16Yq/vK/iGSbXw4vO14UcPx5MGfNbPG18m
|
|
1oj4THRsTw7VanPXVYpi3gzMcnrvCnG11JOupwuN8+a3pEQ6jT4divjxWnJExa09pbjbM5HHu90A
|
|
JUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAHM41H1GOf6nTc/jEf4Ws+lls/UX45uGekNujTwdm5RNIthKIZKLDFlsiQIShIC
|
|
EgCUJ7AmGTGO7IDzZQhMSDJMMYZQgZwzhhDOATuqssmVdgVWVWWyqtCBTeVF19lF+wNLNG7q8I+9
|
|
8nLyupwnt+S8RXUAQAAAAAAAAAAAAAAAAAAAAAAItWL1mto3iY2lyrcLyUxzix2ia2nvPeK+jrCL
|
|
OrTVnxpanhuPPemSs8l6RtE7dJj0ldpNP9GwRSZ3neZmV4cR/Vs4AJQAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAANHi1d9H
|
|
M+kt5ra+vPoskfDdOfqK4mn7Q3aNHBPZu0W0RdDOGFWcKLCJZeTGQQlCQSgASBsCYZQxhlAJTAmA
|
|
TsmAgGcM4YQyjsgRLC3VnaVcgwsrt3Z2V2QK7tbJ1bN5a9waeWO7p8Knt8nNyebpcK8vkvlFdQBA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAK9RXmwZI+ErEWjesx6wQeZwejeo0cccuW8
|
|
elpblJaaRGxVnCuss4ZrMvJEgCAASISCQIBlCYYpieoM0wx8k7gzIRueYM4Z79FcSy3QEsLJmWFp
|
|
BjaVVpZWlXMoGNmvkXXlr3kGtknu6XCf7OXkl1OEdl8orqgIAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAHmskcmtzV/rls0U62OXiWX4zErcc9GmkRfWVkSqqziWayxCPIANwBIhIJSxS
|
|
CRG6dwZwlhEs4BluMdzfqgZxLLdXuy3AmVdpZTKuZBjaVVpWWV2QlhZRdfZRcGpl7urwfrzfJy8r
|
|
rcH61vPyWitdMAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAHA4nHLxKZ9awnH2ZcY
|
|
jbW459aq8fZpfiI2IZwrqzhmsz3Ebm4JN0AMhCQSIASndiAziWUSriWcAyRujc80DM3RCfIETLCW
|
|
UsZEsJYSslXZAwlTddPZTkBp5e7r8Gj6rJPxhx8k9Xa4PG2C8/FaK10QAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAcfjcbZMFvnDWx9m5x2PqcNvS+zSxT7sNPxH62YZQwqzhRZO6UCB
|
|
KUAJTux3SDIRuAncQAmJZRLBMSgZ7iIAZRKd2DICUSlAljLCYWMLIFVukNfI2bNbIDTyT7zu8Ijb
|
|
Sz/qcG/2nf4T/wCE/wD2WnxWt4AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAHL9oL
|
|
+Hw2cm28VvEuPptfgyVj6yIn0no7/FtJfW8NzYMe3PaPd39d3iMug1WktNc2C9dvPbeP1aZ9xF+v
|
|
T471tHu2iflK2HkqWmvaZj5Surqc9Ps5bx+alTHqYHm68S1Vf/NmfnC2vGNTXvyT84Ql6A3cSvHM
|
|
sfaxVn5Ssrxyv3sM/lKB1xza8bwT3pePyWV4tpZ+/MfOEjfGrXiGlt2zV/PotrqcN/s5aT/+wLRj
|
|
FontMSlAlKEgndO6IAZQljDIEgeQljLCzOVdkCu/SGrkbF56NPNeKxMzMRHxENe0+89DwuNtHHzl
|
|
5PJr8NcnLW3Pbf7r1nCZm2gpae8zMrz4i/W6AgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAETETG0xukB4HVaeMHEtRi26RedvkyjBSfX9W77QYvC4xz7dMlYlrU7M929dWJLFc6aPK0q
|
|
7YLxPS0S22FlP6q38Zac0yR92s/KVc3tHfFf8tpbcsLRvB/dR/8ALLVnU0r9uL1+dZI1mnmdvGpv
|
|
6TOy6ym+Oto2tWJ+cJ/tW+KLK5KW+zes/KU7tG+h01p64qx8Y6NXNo6Y+uPJlp8rLf0rfG7MXtHa
|
|
0x8pZxqs9e2a8f8A7Oj7HaTHn0+f6RWM23LETfr6vRW4PoL99NT8ui7F4+vEdXXtnt+fVbXjGsr/
|
|
AOZE/OsPS29nuH27YrV+VpeV9pdPXhOtw49NG9Mld55+vXcTPd42I47qo7xSfyWV9oM8d8VJ/VxM
|
|
d8l46xWF9cV7en6o/qLfxp2I9ob+eCv/AHMo9op89P8A/wBORGmyT5R+qfo2X8P7n9Q/jTsx7RR5
|
|
6ef+4/8AuHftg/8A6cWcOSO9J/WEbWr3pY7Efzp2Lcfv5YK/9zWy8d1E/ZpSv5Oba1/+Hb9lc+LP
|
|
bFt87I7E/wAabWbiurvEx4nL/pjZzc2bJkn372t85ZXx55/BX85lucC0vPxnTxlnnjm32mOiZqUu
|
|
LJ2p4TwnVavNWaYbRTfre0bQ99pcH0bT0xb78vmtiIiNojaErMwAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAHnfarF7umzRHaZrLjYrdIen9ocPi8JyTt1xzF4eUw23rCm3R4r6bMy
|
|
wt6kdTaWLdjswmNoZontsCm0K5XWjopnuDC0dGpqG5bs08/daKV672MjbSaif6oh6Z5f2LtvptRX
|
|
0tEvUN3Jfo8f7cYve0eX4zV7B5z20xc/C8eSPuZIRficfXlcPaG7ino08HWIbePpLF2NuiyOyrHK
|
|
3fZFSwuovHVfaVF4QK5YWTM9UT0EKry6Ps1Tn4zjn8NZn9nOtLseydObiWW34cf918fWfk+PYANn
|
|
KAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAq1WKM+ly4p+/WYeBxTNd6zG0xO0
|
|
vobw3FcP0bi2em20Tbmj5Srr418V9sa2Z7qKyzi07MXUylhaU7yjqhLCeiq3ddaFNxFYW7NLNG8t
|
|
zya+WO6Va9J7FW66mvwidnrXiPY3Ny8RyUn71Jj9Ht3RPjk19HK9pMHj8D1ER3rHN+jqqtTjjNps
|
|
uOe16zAifXzfTz7kNyndpYazS9qT0mszDdoxrsi6m8LazMq6zDOsq1ZEyrt1WWlXaUCqyq0rbKbi
|
|
Fdp6PReyFd8uqv8ACsfy83aXrPZHHto89/xX2/SP/dpj6y8vx6EBq5gAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAB5n2q03LfDqqx39y39npmlxbS/TOG5se29tuavzgWzeV4mtui2
|
|
O3RRSY2hdVhqO2MvI36iu9lUsrSrvDHn6spnmSiq5jooyV6tq1VV69RC32byTh43h8otMx+r6I+Z
|
|
aK/g8TwX7bXh9Mid4iW+fjl8n1ICWb57xLBOm4zqse20Tbmj8+qKdnS9q8PhcTw5tumSm0/OHMxz
|
|
0Za+uzx3sX1t0Zxurr1ZxvspWiZYWZbsbT0QK7KLrZVZJFaqt5vbezNOTg9J/FaZeJns93wCvLwb
|
|
T/GJn92uGHldIBowAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADuAPA67F9H4l
|
|
qMW20VvO3yRWW97T4fC4rXJHSMtI/WGhVlue3b473K2KzMML4+62tujG9pnozXaOSOVFMnVbmq1t
|
|
trJRW5E7wwvUxTvCyY6CHOt7moxz6Wh9PxTzYaT61h8x1MbZK/OH0zTf+Fxf6I/htj45vL9WgLMn
|
|
mvbPFvocGWO9L7fq85p5maw9d7VYvE4JkmPu2if3eW0+PasdFNOnxfF1Y2hlykRsmY+LJ0MZjZXa
|
|
eq2eyi8oQTO0KLdZWzPRjWu6VaqtHR73g0bcI0sf0Q8Nkq93wqNuFaWP+XDTDDytwBowAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAef9q8HNpcGaI60vtPyl56k9Iew49j8ThGe
|
|
PwxFv0l4zH2U26fDfTYiyJljvsjf4sm6vJ1hrXjq2MkqLdZEVbgbMx0auGdmzNt6iHN1Ub5af6of
|
|
TdPG2nxx6Vj+HzaaTm1+nx/iyVj930ysbViPRrj45vL9SAuyc7j1efguqj+jd4/T33rD3HEcPj8O
|
|
1GP8WOY/Z4TTT7sKadHhbcsZnaCJ3TPZk6VdrKbTutmP0U2nqgrGOsr8deiuI2X09EqKM1dt3uuG
|
|
f/jdN/06/wAPE546S9rwud+Gaaf+XH8NMMPK2wGjAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAABrcRp4nDtRWPPHP8PCYusPoWSvNjtX1iYfPuWaXtX8MzCuvjfw32siu8ptXoxi
|
|
0wy5t4YulReqmazu2skbquURWFInddM7VYRGyL291KFnCcfj8e0le/Lbmn8n0N4b2Ur4nHLWmPsY
|
|
5e5a5+OXyXugBZmiY3iY9Xz7NjnTa3Ph/BeYj5PoTxftFg8Hjk2iOmWkW/Psrr418V5WrWd2faFc
|
|
V2jdnEMXWxntupmN7NiYU27iWML6dVMVnddjgVqMsdHr+CW5uE6f4Rt+7yuSsTDv+zWXn0WTHP3L
|
|
/tK+GHl+O0A1c4AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA8Dn93W56/wDM
|
|
t/L3z59qp24jn+OS38lnpr4r7ZxHQ2TEstt3PXUrt27K57rr1VT0BjKnJPRbMqMs7QlV2fYvHvrd
|
|
VknyrEfu9m8f7FZI8fVU85iJewbT45NfQBKo817W4eulzxHaZrL0rje09ItwqbfhtBVs3leai8RD
|
|
KLw1sduesL606dWFdsZT1jdhNeq6K9DlhCVUU6s4jZnt1YzAhnM71dH2bycmszY/K1d/0c6OzY4R
|
|
fwuK4p8rTstn6z8k7HrwGzkAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAHz3
|
|
Vxvr80/8y38voTwGpj/F5/8AqT/JfjTx/WVeyY6FPspc9dZPVXaOq2WEwIUTVRmjo2rNfLHRI3vZ
|
|
DJycXtX8dZh7t879nsnhcbwz23tt+r6I2nxyb+gCVBzuPY/E4PqI9K7ui19fTxNBnp60n+Aj5/pJ
|
|
3jZu1aOnnltMNussdfXbm+l3ZM9URHREdZVXTuT1Nk7boQiOkJw28PU47/htEp5eivJPLMTCZ9Vv
|
|
x7mJ3iJ9UqNHk8XR4b+tIXuhxAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAD
|
|
weqjbWZ4/wCZP8vePCaz/wDIaiP+Zb+UX408f0r9lOxWOifJhXWjfyYWllPRXYQxnrCrJHRd3YZI
|
|
6A1NJecHEsN/S0T+76bE7xE+r5dk93LW3pL6ZpMni6PDf8VIn9m2fjm8s9rgFmQxvHNS0esbMiew
|
|
PnHLyai9fS0w2aNfUTtrs3+uf5bGPqy068fF227KtSsdFlKqNGMV6myyY6sbdIQI8tlOWOi6Jhhk
|
|
j3RD0vA8nicMx9etZmHRcT2Zyb6XNT8N9/2dt0T449T2AJVAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAHhdfG3E9TH9cvdPEcXjk4zqI/q3L8aeP6xr2TsxpLOekMK6mFo6qpXSrm
|
|
OqBixvHSVmzC4OfqK7S9/wAByeLwbTW9K7fo8Fqo6Paeyl+fglI/Da0NcMPK7QC7AAB8313TiOf/
|
|
AKk/y2MHWrX4jG3E9R/1Lfyv0/aFNOrHxuU7LI7MMayGTVlHWUXhNe6Z6wIUsb9d1m20q7dkDpez
|
|
N9tRqKT5xEvRvKez9+Xis1/FSYerb5+OTyf6AFlAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAB43j9eXjN/jWJ/Z7J5L2mry8Upb8VIF8f6aGOey2eynHvOy7bowrrYSxZSwQJ2YXZ
|
|
92N4BoanrEvVexmTm4blr+HJ/aHltRHSXofYm/1Wrp5RaJaYY+X49WA0c4AD51xONuKan/qW/lbp
|
|
+0MOLRtxbU/9SU4J7KadWPjep2WQrr2WRPRk1TvsndXMpiRCb9FNu0rbTuqvKBscCjfi9PhWZeue
|
|
V9n434rafTHL1TfPxy+T/QAszAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAHmv
|
|
avHtfTZfnV6VxPajHzcNrf8ABeJFs/XnMcr4no18c+6vr2YadkY2YM57sEDLyY37Mo7MMnYGlqO0
|
|
vQ+xNfqNVb1tEfs87qZ2rL0/sVX/AHdnt65P7Q0wx8vx6UBo5wAHz/jUbcX1PT78qtO2vaCnJxjP
|
|
8Zif2amnnspp04+OjWejKJ6MKdmcMmyJn4m5ZHzEVPMwtJv0VZLbQDqezcb8RzT6Y/7vUPM+ytZt
|
|
n1OTyiIh6Ztn45N/6AFlAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABocbxeLw
|
|
nUR5xXm/Rvq8+OMuDJjntaswEeBxT0bNZ6NatZpNqz3rO0rqsdO3PxlaWEMpY+aqWXkryT0ZT2V3
|
|
7A0dVPuy9f7G124NM/iyT/Z4zWT7sw957MYfB4Fp4/FE2/WWmGHldcBowAAeM9qKcvFeb8VIly9P
|
|
0nq7ntbTbVYL+tJj93CwT76unR4/jo0nozhhTsy3Y1sWljM9Ce7HyQIm3RRlttVbaWrnt0Sh6n2U
|
|
x8vD8mSfv3/h3XN4Bi8Lg2nj8Uc36y6TeOPXugCUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAPD8RxeBxXUU26Tbmj8+quro+02Lw+I4ssdslNvzhzazvDPbq8d7GW7Dfqz2VzG
|
|
0s2qd+iu/Zn5Ksk9BVztX1mI8930zh2LwOHabH+HHWP2fNYp4+vwYvxXiP3fUqxtWIjyjZtj45/L
|
|
faQFmQADzftfj3w6fJ6WmHmsP23rvaqnNwqLfhvEvIYZ+sV038bo0noy36MK9oZQxrdMyrlnMbMZ
|
|
QKrS1M07zEestq/RRjr4utwY/wAV4j91p9V18fQdJj8LR4ccfdpEfsuREbREJbuMAAAAAAAAAAAA
|
|
BAJAAAAEAJEAJQAJQAJEAJQAJQAJEACUJAQlAJEAJQAJQJAAAEAJEAJBAAAJAABAJEJAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABwvanDzaPFmjvjv8A
|
|
tLztJ3h7HjGHx+FainnFeaPnHV4vFbeIU038VbHeGF+kso7Mb9mTdhKnLK3dRm7SIrHhGPxeP6Sv
|
|
9cT/AHfSnz72Zx+J7Q45/BWZ/Z9BbZ+OXyfQBZQABzeP4/E4NqI9Ii36S8Ng/wAx9C4jTxOH6ivr
|
|
jn+Hz3B/mQi/GvjdCnWNlsdI2V07LIlg6USrt2ZzZXMoFV+zPhGLxeOaavpbm/RVltEN72Yx+Jxm
|
|
b7dKUmf7L5+s9/HtRA2cqRACRACRACRACUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAACQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQCQQCRACRACRCQBCQBCQB
|
|
ACRACRACRACRACL1i9LVntMbPATTwdRkxT3pea/u+gPE8Xx+DxrPHlaYt+qNfGvjvtXXsi0dOrKk
|
|
dEXjZg6VMtbP2bMtXUdpEV0/Y2nNxbNf8OP+727xvsXH+N1U/wBEfy9k3nxyb+gCVQAGOWvNivX1
|
|
rMPnGGOXNNfOJ2fSZ6w+dZKeHxDPX8N7R+6L8a+L63KdoZ7q6zvEMpnowdKJ6ywmWUyqvIKM0vQ+
|
|
x+D6rU55+9aKx+TzWa36vbezmDwODYenW+95/Nphj5L6dQBo5wAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACAEiAAAEoA
|
|
AAAAAAAAAAAAAEAkEAkRuAkQbgkQAkQAkQAkQAl5T2nx8nEMOT8dNv0l6pwfarHvpcGWPu32/WCr
|
|
YvK4mOem6b9mGKd4Z3idmFdka0y1c892zfpMtLPaNpEV6D2Kj/Eauf6YeweQ9ieuTVz8K/3evbT4
|
|
5NfQBKoAA8FxCvJxrUx/XMvevD8Zry8fz/Haf2RfjTx/6RSOnRMyypHu9kXjowrqVSrvPRnZVl6V
|
|
kK0775MsUjvadn0nT4ow6bFijtSsVfPuFYvpPGtNTy54mfy6vorXDm8l9pEC7JIgBIgBIgBIgBIg
|
|
BIgBIhIAgBIhIAgBIgBIIBIAAhIAhIAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAJAAAAAAAAAAAAAAA
|
|
AAAAAAAAABAJQkAEAAAAAAAAAAjc3BIjdG4Mkbo5kcwMjdhzHMDPc3V8xzAs3N1fMjmBZubq+Y5g
|
|
Wbm6vmOYFm5ur5jmBZubq+Y5gWbm6vmOYFm5ur5jmBZubq+Y5gWbm6vmTzAz3N2HMnmBlu5ftFTx
|
|
OEZJ/DMW/d0t2rxKni8N1FPWkiZ9eS08e7Cy8dGGn6UhZaJljXZGnmc3UT3dPP2cnUT78xCIV6j2
|
|
H/8A9c/6f7vXPI+w8bU1U+vL/d63du5NfUiDcVSIAS8b7RV5eOb/AIqRL2TyXtNX/e2KfXH/AHlF
|
|
+NPH/pr4+2xcxx0hFpY11K7R16KM32ZWz3UaidqSgrc9kcPicWyZJjfw6T+727y3sXh2xarN+K0V
|
|
h6lvPjj3e0ASqAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAJQAAAAAkQAkQAkAAAAAAAAAAAAAAA
|
|
EgAAAAAAAAAAAAAAAAAAAAAgAAABKDcAN0bgkY8xzAyRux5kcwM9zdXNkTcFm6OZXzMeYFvMibKu
|
|
ZHMC2bo51U2RuC2bom6rc3BZzom6sBZzI52ADPnOdggFnMc6skFnMc6rc3BbznOp3RzAv50c6nml
|
|
HMC/nOf4qOY5wX85zqOc5wbHOc7X5znBsc6edr85zg2ec52vzpi4NjmY5bROG+/bllVzsNTk5dLl
|
|
n0pP8BHmMHWNmzt0aum8obm08vVjfrtnxztR0mXHzTvaZdjVRMTLkZo6yiFen9iZ2pqY/wBP93rN
|
|
3kPY+/LfPX1rE/u9XzN3HfqzdO6vmTuIZ7m7Hc3Bnu8t7TR/vHBP9E/y9Pu837SV31umn+if5Rfi
|
|
/j/01MMb1hjkrtKzBG0bMsmOZY11tOYamr6Und0LUc7XT7u3rJPqL8er9lcPhcFpbzyWm39v7O00
|
|
+FYvA4Zpsc94xxu227jv1IAgAAAAAAAAABKAAAASgASgBIgBIgBIgBIhIAAAAAAAAAAAAAAAAAAC
|
|
UACUJAAAAAAAAAAAABIAAAAAAAAAAAAAAAAAAAAg3AEbomQZbo3YzLGbAz3RNlc3YzcFs2YzdVN2
|
|
M2Bdzom6nmNwW86JurTAMuY3REJ2BB1ZRVMVBhsbSsiqeUFXLucq3lTygp5TlXcpygp5TlXcpygp
|
|
5TlXcqOUFXKjlXcrGYBXysdlswiYBVMdUTCyY6sZBWxlnMMZgGLGZZSwkDdHMiWO4MuY5mEyjcFn
|
|
N1OdVzHMC3nTzqeY5gX85zqOZPMC+Lqdbk20eb/RKOZr8QybaK/XvtH7iZ9aGlp2luzT3fg19NHS
|
|
OjbmPcYX67XH1XSZ9XIzRvMuzrK7zLkZYmYnciunb9lZ5dTk+OP+71cXeP8AZnJ/ip2nf3J/l6iL
|
|
/Fu5L9bMWZczXi6YuIbEWTzKIuyiwLt3nuO25uI4a/hx7/rLuczg8TicvFLbfdpEK6+NPH/phhjo
|
|
stLGkctUWnoxrrU3j1cnWTzZq1jzl1clo5Zcu8c+txR63iP3Tn6pv4+g4o5cVI9IiGe7CJ2iE7t3
|
|
GyN2O6dwSINwSISAlAAlACRAAlAAlACRACRCQAAAAAAAAAASgASISAAAAAAAAAAAAACQAAAAAAAA
|
|
AAAAAASAAAAAAAAAAAAAAAAIAAAQCAJljuljsCJlhMs9mOwMJYys5TkBVsjZdyHICrZPKt5E8oK4
|
|
qmKrOVOwMIqyirPY2Bjyp2ZbAI2NmSARsbMgEbI2ZAMdjZICNkbMkSCNmOzJEgx2YyzljMAwlhKy
|
|
WEwCuWErJhhMArlhLOWEgxljMpljIImWMyTKJA3N0IBO5vux3NwZbnMx3NwZczT4jf3MdPW27a3a
|
|
fJOq1XNP2KdIRfi+J2trSYfcjeF+Wm1OicVeWIiN9kai8xjY12ORqultnI1Ecsujq79XP1FovWYI
|
|
rTgeq+j8QrWZ+3Mx+r2UXeC0WG2Ti2kiN5mL807eUREvbzbaejefHJv62Iv8WUXa0WTFhVtRdlF2
|
|
rz9WUXBtc7jR9dqc2T1ttHyhvZMvJitb0jdq6XHNcNenWVN3028U99WRj6Kb02be3Tq18/SN2Lpc
|
|
3UdN9nOmZrqKX/DaJ/d0svvTLRzV3jomK6+Pd1vvWJj0ZczT0mXxNJht60hfFnQ4qu3N1cWTEgs3
|
|
Tur5k7gz3N2O5uDM3Y7m4MtxBuCQASIASIASAAAAAAACRCQAAAAAAAAEoSAAAAAAAAAAAlAAlCQA
|
|
AAAAAAAAAAASAAAAAAAAAAAAIASgAAAEJAQJQCNkbMgGOyOVnsAw5TlZ7GwMOVPKy2NgY7GzIBGx
|
|
skA2AAAAAAAAAAQkBAEghEskAxYzDPZGwK5hjMLJhjMAqmGEwumrCagomFcw2JqqtUFEsLLrV82F
|
|
o7gqljKyYYTGwMZRKUSCAQAboJnaN5Bjkneu0d5W4ccViIiOzHFWbTzNumP1Zarr8eeRMbxDW1Mx
|
|
NO67NbkhzNVnmInqzaOZrL93JyZeV0M1++7S02jvxDWxhxx033tPpC8Z6rrezWjmZyazJG2/u03h
|
|
2vFibTHoqvamiwVwY+nLGzV0+SZ1Mx8G0/45tOhzJ5lXMc3UVXRdlF1HP+iYsDPLPPy49/tz1+Te
|
|
pSIr0ho6ak5Ms5J8o2q6NImOrHV7XX488ypzTtHXo0s9t6zG7c1G1qz6ubeZiZ3UatXJG3yauSO7
|
|
cvMTEx5tPLb3prPRMVr0HB8vicNxf0+7+kt+LOJwTJyY/Bnz3tH93X36N58cWvq6LSyiyndMSlC7
|
|
mZcymLJiwLosmJVRLKLAtiU7q4lMSCzc3YxJuDMRuAlKAEgAAAlAkAAAAAABKAEgAAAAAJAAAAAA
|
|
AAAAAAAEgAAAAAAAAAAAAAkAAAAAAAAEAAAAAAAAAAAAAAAAAAAAAhIAAACAAAASgAAAAAAEAAAA
|
|
hGzJAImGMwzQDDZjNVuyNgUTVhNGxysZqDVmiu1G5NN2M4waM0+DCaN2cbGcQNGaMZq3JxMJxA1J
|
|
qx2bU4kU09slorWNwa20z02RXHbJbl26QvtFovbHWkxEdJt5y2MOHlr2U1W3jx+1hiw8vSO63lmI
|
|
XRTaEWmtY6snRHO1VpmJ+DjavpSZl2s8b7y4HFcnh0n0gha5ebJN55KRM2mdoiPN6fh+kpwXh0Wy
|
|
RHj5Otp/s5Ps1p62y31+em9aTMYt/OfVfxTiPjZ52naI7fBrI5t66xz5+a1rW7yx0eSL6iZjtEOX
|
|
qNbSletom3lENjh2fbHzbbWt3iVozruc+5ztWubf4M4ybpQ2Oboyrva0Vjza8WdDR4OkXt3n9ldX
|
|
kaePP9VtYqctYhdvt5oivTeCZ2YOxXk6ubqMfV0b9mrljfqlFcq88k7z2U5axeItDa1OPessuC8P
|
|
ya7XRWYnwqdbT/ZMilvIu4dpslNdixXja8Y5tt85djZdbDWnGOesRtXFtuw6T27No5Kx2OrKYQlC
|
|
ExKJgBnEpiyvdlEgsizKLKollFgWxLKJVRLKJBbEp3VxLKJBnuMWQJEbpBIAAAJAAAABIAAAAAAA
|
|
lAJAAAAAAAAAAAAAASAAAAAAAAAAAAAJAAAABAJABAlAAAAAAAAAAAAAAAAAAAAAAAAIAAAAAAAA
|
|
AAABAJQAAAAgAABAAI2EoBGyJhkgGPKxmqxAKpownHC+YRMdN5BrTj67R3bOn01o7p01Iv71u89o
|
|
b9a7LfBTfS1vWI2jf12VfQPSW8KX2mas+NC2iv6xMNfJpMnLtEbuuxtMRCtzF55NR5rPps1N/ctP
|
|
y6uHreE6nXZ4pak48X3rT06fB7fNeI33cbX6mI32R/MWu7XF116aDSRhxbRERs8f499bkyZeeKae
|
|
kzE2mdon81/tfxDLGOunwbzlzbx08oaHBvZHJlx48mrvaa94pu04y617576rNGLRRM0397JEd/lu
|
|
9Dw/S3x4qxffo6mm4NjwUiKY4iI9Ib1dHFY6QIaNabbrYrLfrpJtaK1rMzPZb/s+05IpP59OyLeJ
|
|
k7eNfRaOc1ue32I7fGXYpi5Y77M8OGMeOKxHSFsU3Y29deZMzirl6dlVvhLatCjJHeYQv1rXnps1
|
|
8k9/VsW6qLVmZIi1rzitlvFKRvaZ2h6TSaenC9FFY+3brM+sqeG8Prp4+kZ+lvuxPkr1mqm95nfp
|
|
DXM459676a2q1dsV7XietvNno78+CJn1cjX6mOeIm0bR33dfRU5NJjidt9t5afjG/V6JZ7I2QMNh
|
|
nyo2BhsMuVG3wAhMSbbQRAMolnE+iuGUSCyJZRKuGUSCyJZK4llEgyZMYTuCUsYSCQASISAAAlCQ
|
|
AAAAAAEoASCASAAAAAAAAAAAAlACRACQAAAAAAAAAEgCEoASCAAAAAAAAAAAAAAAAAAAAAAABAAA
|
|
AAAAAAAISAIAAAAAAQAAACASgAAAQJAQAAhIDHZhln3do7z0WS18mWsajHjmes7pg3dNi5aRMNqO
|
|
yvDHTpPRaigHZhN4hHRlaVN59JY3zRENLUavaO+yq0iNVlitJ6vNcR1MVi0zO0era1/Ea0rPvbz5
|
|
PM5MWp45qvo2GZrhmfrsnpHpHzTCseEcM/2vrr8Q1Eb4qzy44nziPN63HpYiIiI7LNHoqabBTFii
|
|
IpSNohuVxrKtWMEejPwY9G1FFmHB4mWJn7MdfnIM9JpIx15to5pbUaas/a6rqViI7MxPxqX0UT1r
|
|
O3wVzpbR2hviP5i03Y5s6a879FNtHljydhExCv8AMTPJXBnRZbz0iG5ptFjwe/l96zctMVamTJtE
|
|
yTMibu1VrdTzRMR0j0ed4lr64MVpm0RERvMz5NvX62uOJ69XhOKX1HH9bHDtFvNYnfJeOy0Z2ojX
|
|
6jjnEq6fRUmccTvN/J9H0eKcOnx45neaxEbubwHgOHg+milI3vP2resu3Wu0JQmITsmISDHZHKz2
|
|
JgFc1RMLJhGwK9iIZ7MZgEdgmAEwyiWCdwWRLKJVxKYsC2JTuriWUSDNlEsIlMAySx3SCRCQSIAS
|
|
AAACRACQAAAAAAASIASAAAAAAAAAAAAAAACRACRACQASIAAAAAAAAAAAAAAAAAAAAAAAAQCUAAAA
|
|
AAAAAAIAAAAAAAAQAAAAAACBICBICAAEJAQJQCJcLjuS2ny6fPG/LWdpd1o8T0X07SXx/e7wCdJx
|
|
Wa0jmneHQpxPDMdZmJfNtZm49weZrh0/j4o7VtSZ2+Uw0/8A7o49k92vBLc/ntFohFW9PqGXimOI
|
|
6Tu1L8T3eCx6r2t1O3JwvHjifO99v7t/Bwf2l1PXU6rS6eJ8qUm8x+so5TsekzcSjbvs4mt4rzW5
|
|
K2mbT0itesy2cHsvbvqtbmyz5xERWP2jd1tJwrTaONsOKtZ8585+cnDrzmn4Rq+IZObUROHD32n7
|
|
Vv8A0ej0uhxaXFGPFSK1j0bkY4jyZRVZVXFGUVWbGwKsk8mObekNrSW3pWf1a2aYjHbm7bNnQ1id
|
|
PW0TvuDdhJEbQABMsLW2R0ZTMQrvfbz2YWzVhpanUxEd0dWkW5c8R5uXxDX1w4pnfr5Q19XxKuOJ
|
|
2neXltVqtVxbV/RdJ715+1bypANfiOu1HENV9C0MTfNeesx2rD1PAeBYuE6aKx72W3W9/WVnBuB4
|
|
eF4dqRzZbdb5J72l160WVK02ZxCYhOwI23TsnY2BGxsnYBjsiYZsZBjMMZZSgGEolMsQDdG6NwZ7
|
|
piVe6YkFsSziVMWZRILolMSriWUSCyJTuwhMSDMRCQSI3SAlACRCQAAEoAEoASAAAAAAAAACUACR
|
|
ACQAAAAAAAAAAAAASAAAAAAAAAAAAAAAAAAACAAAAAAAAAAAAAABAAAAAAAAAAAAACBKAAAAAAAQ
|
|
JQAAAhICEbJAYTWJ7wx8KvpC0BV4ceieWGewDHlNmWwCNjZICNhIDmcZredBecdpiY69FXCOLW+i
|
|
UiZidukulmxxlx2paN4mNng+K4+I8Hy2yaTfl37TXetoCPfRxfp1qi3F48ofKMvtvxak8s6LDv61
|
|
rZji9rPaLUf5PC+bfttS0q8q3p9W/wBrRMdpUZuKdN99nzvFqPbTVz7nD8OKs+do2/mW3h4D7Xaq
|
|
ZnPrtNpqz35aRaYOHY9Zk4pNt9rR+rl6zi+OnS+WN57Rv1lXp/YrNaYtruL6zNPnGO3hxP6O5w/2
|
|
f0HDuun09Yv55Le9afznqcOvO4tBreMTHu30unnva0bWt8on+70nDuE4OHYYx4Kbesz3tPrMuhGO
|
|
IjpDOKrK9YVpsyiGUQnYGOyUgI2SlAIEmwMWMs9kTAMJYzDOYRMArmGErZhhMArlHmzmGMwDE3Ts
|
|
bAbs4swj5pgFkSziVcM4BZEsolXDKAZwyhjCYBkACQhIAAAAAAAJAAAAAAAAAAAAAAAAAAAShIAA
|
|
AAAAAAJAAAAAAAAAAAAAABAJEAAAAAAAAAAAAAAAIEoBKAAAAAAAAAAAAAAABAlAAAAAAAIAAAAA
|
|
BAkBAkBAkBAlACEgMZjdjbFW8bWrEx8YWANb6Fp+bfwab+vLDKMFK9qxH5L0bAr8OPRPKz2AY7J2
|
|
SbAjYZAI2E7AIEgIEgIEgMdkSy2NgY7MdlmyNoBXsxmFuyNgVTVjNV3KjlBRNTlXTVHKCrlIqt5T
|
|
lBhEMohlFerLlBjEMohMVTEARDKCITsAk2AEgAAAkAAAAAAAAAAAAAAAAAAAAAAAASAAAAAAAAD/
|
|
2Q==`;async function rfe(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(O0);break;case"body":case"full":a=await t(D0);break;default:a=null}if(a){let r=await createImageBitmap(a);n=await e.detect(r,e.config),r.close()}return n}async function sfe(e){return new Promise(t=>{let a;switch(e.config.warmup){case"face":a="data:image/jpeg;base64,"+O0;break;case"full":case"body":a="data:image/jpeg;base64,"+D0;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=Rn(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 ife(e){let t=r=>Buffer.from(r,"base64"),a;e.config.warmup==="face"?a=t(O0):a=t(D0);let n;if("node"in je&&ua()==="tensorflow"){let r=(void 0).decodeJpeg(a),s=Gt(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 ofe(e){let t;return typeof createImageBitmap=="function"?t=await rfe(e):typeof Image!="undefined"||ne.Canvas!==void 0?t=await sfe(e):t=await ife(e),t}async function lfe(e){var o,l,u,p;if(!V().flagRegistry.ENGINE_COMPILE_ONLY)return;let t=ua(),a=tr();if(t!=="webgl"&&t!=="humangl"||!(a!=null&&a.checkCompileCompletion))return;V().set("ENGINE_COMPILE_ONLY",!0);let n=vt().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],f=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 m=gn(h,f);try{let g=d.execute(m);r.push(c),Array.isArray(g)?g.forEach(y=>J(y)):J(g)}catch(g){e.config.debug&&K("compile fail model:",c)}J(m)}let s=await a.checkCompileCompletionAsync();a.getUniformLocations(),e.config.debug&&K("compile pass:",{models:r,kernels:s.length}),V().set("ENGINE_COMPILE_ONLY",!1);let i=vt().state.numTensors;i-n>0&&K("tensor leak:",i-n)}async function Zw(e,t){await wp(e,!1);let a=ae();return e.state="warmup",t&&(e.config=Nt(e.config,t)),!e.config.warmup||e.config.warmup.length===0||e.config.warmup==="none"?lr():new Promise(async n=>{await e.models.load(),await lfe(e);let r=await ofe(e),s=ae();e.config.debug&&K("warmup",e.config.warmup,Math.round(s-a),"ms"),e.emit("warmup"),n(r)})}var Mu,$p,_p,z0,Ss,b5=class{constructor(t){de(this,"version");de(this,"config");de(this,"result");de(this,"state");de(this,"process");de(this,"tf");de(this,"env",ne);de(this,"draw",e0);de(this,"match",N0);de(this,"models");de(this,"events");de(this,"faceTriangulation");de(this,"faceUVMap");de(this,"performance");Gn(this,Mu,void 0);Gn(this,$p,void 0);Gn(this,_p,void 0);de(this,"analyze",(...t)=>{if(!ja(this,$p))return;let a=this.tf.engine().state.numTensors,n=ja(this,Mu);mr(this,Mu,a);let r=a-n;r!==0&&K(...t,r)});Gn(this,z0,t=>{if(!ja(this,_p))return null;if(!t)return"input is not defined";if(this.env.node&&!(t instanceof pt))return"input must be a tensor";try{this.tf.getBackend()}catch(a){return"backend not loaded"}return null});de(this,"webcam",new qh);de(this,"emit",t=>{var a;(a=this.events)!=null&&a.dispatchEvent&&this.events.dispatchEvent(new Event(t))});Gn(this,Ss,{});let a=(xp.tfjs||t3).replace(/-(.*)/,"");So.wasmPath=`https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@${a}/dist/`,So.modelBasePath=ne.browser?"../models/":"file://models/",this.version=K3,Object.defineProperty(this,"version",{value:K3}),this.config=JSON.parse(JSON.stringify(So)),Object.seal(this.config),this.config.cacheModels=typeof indexedDB!="undefined",t&&(this.config=Nt(this.config,t)),o9(this.config),this.tf=je,this.state="idle",mr(this,Mu,0),mr(this,$p,!1),mr(this,_p,!1),this.performance={},this.events=typeof EventTarget!="undefined"?new EventTarget:void 0,this.models=new Mp(this),ag(),this.result=lr(),this.process={tensor:null,canvas:null},this.faceTriangulation=ek,this.faceUVMap=tk,F0(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(So)),this.config.backend=t,q3(),ne.initial=!0}validate(t){let a=G3(So,t||this.config);return a.length===0&&(this.config=Nt(this.config,t)),a}now(){return ae()}image(t,a=!1){return Hh(t,this.config,a)}async segmentation(t,a){var s,i,o;if(a&&(this.config=Nt(this.config,a)),!this.config.segmentation.enabled)return null;let n=await Hh(t,this.config);if(!n.tensor)return null;let r=null;return(s=this.config.segmentation.modelPath)!=null&&s.includes("rvm")&&(r=await Hw(n.tensor,this.config)),(i=this.config.segmentation.modelPath)!=null&&i.includes("meet")&&(r=await ww(n.tensor,this.config)),(o=this.config.segmentation.modelPath)!=null&&o.includes("selfie")&&(r=await qw(n.tensor,this.config)),J(n.tensor),r}compare(t,a){return i9(this.config,t,a)}async init(){await wp(this,!0),await this.tf.ready(),q3()}async load(t){this.state="load";let a=ae(),n=Object.values(this.models.models).filter(i=>i).length;t&&(this.config=Nt(this.config,t)),this.env.initial&&(await wp(this,!1)||K("error: backend check failed"),await Jd(),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 kw(t,this.config)}async warmup(t){let a=ae(),n=await Zw(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,k,S,C,N,$,M,R,I,_,D,W,P,U,G,q,H;this.state="config";let r;this.config=Nt(this.config,a),this.state="check";let s=ja(this,z0).call(this,t);s&&(K(s,t),this.emit("error"),n(lr(s)));let i=ae();await this.load(),r=ae(),this.state="image";let o=await Hh(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(lr("could not convert input to tensor"));return}this.emit("image"),r=ae(),this.config.skipAllowed=await s9(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?Gg(this,o.tensor):[],this.performance.face&&delete this.performance.face):(r=ae(),l=this.config.face.enabled?await Gg(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?Nt(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?f5(o.tensor,d):[]:(y=this.config.body.modelPath)!=null&&y.includes("blazepose")?u=this.config.body.enabled?og(o.tensor,d):[]:(x=this.config.body.modelPath)!=null&&x.includes("efficientpose")?u=this.config.body.enabled?fg(o.tensor,d):[]:(A=this.config.body.modelPath)!=null&&A.includes("movenet")&&(u=this.config.body.enabled?o5(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 f5(o.tensor,d):[]:(k=this.config.body.modelPath)!=null&&k.includes("blazepose")?u=this.config.body.enabled?await og(o.tensor,d):[]:(S=this.config.body.modelPath)!=null&&S.includes("efficientpose")?u=this.config.body.enabled?await fg(o.tensor,d):[]:(C=this.config.body.modelPath)!=null&&C.includes("movenet")&&(u=this.config.body.enabled?await o5(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?Nt(this.config,{hand:{maxDetected:this.config.face.enabled?2*l.length:1}}):this.config;this.config.async?(($=(N=this.config.hand.detector)==null?void 0:N.modelPath)!=null&&$.includes("handdetect")?p=this.config.hand.enabled?Kg(o.tensor,h):[]:(R=(M=this.config.hand.detector)==null?void 0:M.modelPath)!=null&&R.includes("handtrack")&&(p=this.config.hand.enabled?Jg(o.tensor,h):[]),this.performance.hand&&delete this.performance.hand):(r=ae(),(_=(I=this.config.hand.detector)==null?void 0:I.modelPath)!=null&&_.includes("handdetect")?p=this.config.hand.enabled?await Kg(o.tensor,h):[]:(W=(D=this.config.hand.detector)==null?void 0:D.modelPath)!=null&&W.includes("handtrack")&&(p=this.config.hand.enabled?await Jg(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?u5(o.tensor,this.config):[]:(U=this.config.object.modelPath)!=null&&U.includes("centernet")&&(c=this.config.object.enabled?dg(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 u5(o.tensor,this.config):[]:(q=this.config.object.modelPath)!=null&&q.includes("centernet")&&(c=this.config.object.enabled?await dg(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 f=[];this.config.gesture.enabled&&(r=ae(),f=[...Jk(l),...Yk(u),...ew(p),...Qk(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 m=((H=this.process.tensor)==null?void 0:H.shape)||[0,0,0,0];this.result={face:l,body:u,hand:p,gesture:f,object:c,performance:this.performance,canvas:this.process.canvas,timestamp:Date.now(),error:null,width:m[2],height:m[1],get persons(){return Kw(l,u,p,f,m)}},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?(ja(this,Ss)[t.id]||(this.config.debug&&K("video start",t.id),ja(this,Ss)[t.id]=!0),!t.paused&&ja(this,Ss)[t.id]&&t.readyState>=2&&await this.detect(t),n>0&&await this.sleep(n),ja(this,Ss)[t.id]&&requestAnimationFrame(()=>this.video(t,a,n))):(this.config.debug&&K("video stop",t.id),ja(this,Ss)[t.id]=!1)}};Mu=new WeakMap,$p=new WeakMap,_p=new WeakMap,z0=new WeakMap,Ss=new WeakMap;return FI(dfe);})();
|