ambiser
/
human
mirror of https://github.com/vladmandic/human
9
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity
human/dist/human.esm.js

5547 lines
1.3 MiB
Raw Blame History

/*
Human library
homepage: <https://github.com/vladmandic/human>
author: <https://github.com/vladmandic>'
*/
var c5=Object.defineProperty;var BI=e=>c5(e,"__esModule",{value:!0});var Dm=e=>{if(typeof require!="undefined")return require(e);throw new Error('Dynamic require of "'+e+'" is not supported')};var d5=(e,t)=>{BI(e);for(var n in t)c5(e,n,{get:t[n],enumerable:!0})};var h5=(e,t,n)=>{if(!t.has(e))throw TypeError("Cannot "+n)};var mn=(e,t,n)=>(h5(e,t,"read from private field"),n?n.call(e):t.get(e)),as=(e,t,n)=>{if(t.has(e))throw TypeError("Cannot add the same private member more than once");t instanceof WeakSet?t.add(e):t.set(e,n)},Ds=(e,t,n,s)=>(h5(e,t,"write to private field"),s?s.call(e,n):t.set(e,n),n);function gt(e,t){let n=e.endsWith("/")?"":"/",r=t.startsWith(".")||t.startsWith("/")||t.startsWith("http:")||t.startsWith("https:")||t.startsWith("file:")?`${t}`:`${e}${n}${t}`;if(!r.toLocaleLowerCase().includes(".json"))throw new Error(`Human: ModelPath Error: ${r} Expecting JSON file`);return r}function ue(...e){let t=new Date,n=`${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(n,"Human:",...e)}var Ye=()=>typeof performance!="undefined"?performance.now():parseInt((Number(process.hrtime.bigint())/1e3/1e3).toString());function gn(...e){let t=n=>n&&typeof n=="object";return e.reduce((n,s)=>(Object.keys(s||{}).forEach(r=>{let a=n[r],o=s[r];Array.isArray(a)&&Array.isArray(o)?n[r]=a.concat(...o):t(a)&&t(o)?n[r]=gn(a,o):n[r]=o}),n),{})}var $m={backend:"webgl",modelBasePath:"../models/",wasmPath:"",debug:!0,async:!0,warmup:"full",cacheSensitivity:.75,skipFrame:!1,filter:{enabled:!0,width:0,height:0,flip:!1,return:!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:!0,maxDetected:15,skipFrames:15,minConfidence:.2,iouThreshold:.1,return:!1},mesh:{enabled:!0,modelPath:"facemesh.json"},iris:{enabled:!0,modelPath:"iris.json"},description:{enabled:!0,modelPath:"faceres.json",skipFrames:11,minConfidence:.1},emotion:{enabled:!0,minConfidence:.1,skipFrames:17,modelPath:"emotion.json"}},body:{enabled:!0,modelPath:"movenet-lightning.json",maxDetected:1,minConfidence:.2,skipFrames:1},hand:{enabled:!0,rotation:!0,skipFrames:18,minConfidence:.1,iouThreshold:.1,maxDetected:2,landmarks:!0,detector:{modelPath:"handdetect.json"},skeleton:{modelPath:"handskeleton.json"}},object:{enabled:!1,modelPath:"mb3-centernet.json",minConfidence:.2,iouThreshold:.4,maxDetected:10,skipFrames:19},segmentation:{enabled:!1,modelPath:"selfie.json"}};function p5(){let e="",t="";if(typeof navigator!="undefined"){let n=navigator.userAgent.match(/\(([^()]+)\)/g);if(n&&n[0]){let s=n[0].match(/\(([^()]+)\)/g);e=s&&s[0]?s[0].replace(/\(|\)/g,""):"",t=navigator.userAgent.replace(n[0],""),e[1]&&(t=t.replace(n[1],"")),t=t.replace(/ /g," ")}}else typeof process!="undefined"&&(e=`${process.platform} ${process.arch}`,t=`NodeJS ${process.version}`);return{platform:e,agent:t}}var od={};d5(od,{Abs:()=>ki,Acos:()=>Ii,Acosh:()=>Si,AdadeltaOptimizer:()=>mp,AdagradOptimizer:()=>gp,AdamOptimizer:()=>Ap,AdamaxOptimizer:()=>yp,Add:()=>Vr,AddN:()=>Ta,All:()=>Ci,Any:()=>Ti,ArgMax:()=>Na,ArgMin:()=>Ou,Asin:()=>Ni,Asinh:()=>Ei,Atan:()=>Ri,Atan2:()=>Di,Atanh:()=>_i,AvgPool:()=>Ea,AvgPool3D:()=>Pu,AvgPool3DGrad:()=>Kd,AvgPoolGrad:()=>Xd,BackendWasm:()=>Bk,BatchMatMul:()=>Ra,BatchToSpaceND:()=>$i,Bincount:()=>Zd,BroadcastArgs:()=>Bm,BroadcastTo:()=>D5,Callback:()=>zv,CallbackList:()=>R3,Cast:()=>_a,Ceil:()=>Da,ClipByValue:()=>Ur,Complex:()=>Yd,ComplexAbs:()=>Mu,Concat:()=>Fi,Conv2D:()=>$a,Conv2DBackpropFilter:()=>Jd,Conv2DBackpropInput:()=>Fa,Conv3D:()=>zu,Conv3DBackpropFilterV2:()=>Qd,Conv3DBackpropInputV2:()=>eh,Cos:()=>Oa,Cosh:()=>Pa,CropAndResize:()=>Oi,Cumsum:()=>Ma,CustomCallback:()=>D3,DataStorage:()=>Ud,DenseBincount:()=>th,DepthToSpace:()=>Pi,DepthwiseConv2dNative:()=>za,DepthwiseConv2dNativeBackpropFilter:()=>nh,DepthwiseConv2dNativeBackpropInput:()=>sh,Diag:()=>rh,Dilation2D:()=>Lu,Dilation2DBackpropFilter:()=>oh,Dilation2DBackpropInput:()=>ah,ENV:()=>os,EarlyStopping:()=>Bv,Einsum:()=>ih,Elu:()=>Ba,EluGrad:()=>lh,Environment:()=>R5,Equal:()=>zi,Erf:()=>Mi,Exp:()=>Wa,ExpandDims:()=>Li,Expm1:()=>Bi,FFT:()=>uh,Fill:()=>Bu,FlipLeftRight:()=>Wi,Floor:()=>Va,FloorDiv:()=>Ua,FromPixels:()=>Rh,FusedBatchNorm:()=>Ha,FusedConv2D:()=>So,FusedDepthwiseConv2D:()=>Co,GPGPUContext:()=>vf,GatherNd:()=>Ui,GatherV2:()=>Vi,GraphModel:()=>y7,Greater:()=>Hi,GreaterEqual:()=>Ga,History:()=>_3,IFFT:()=>ch,Identity:()=>ja,Imag:()=>dh,InputSpec:()=>zt,IsFinite:()=>Gi,IsInf:()=>ji,IsNan:()=>qi,KernelBackend:()=>Du,LRN:()=>Uu,LRNGrad:()=>ph,LayerVariable:()=>S3,LayersModel:()=>Nr,LeakyRelu:()=>qa,Less:()=>Xi,LessEqual:()=>Ki,LinSpace:()=>hh,Log:()=>Xa,Log1p:()=>Zi,LogSoftmax:()=>$5,LogicalAnd:()=>Yi,LogicalNot:()=>Wu,LogicalOr:()=>Vu,MathBackendCPU:()=>af,MathBackendWebGL:()=>lu,Max:()=>Ka,MaxPool:()=>Ya,MaxPool3D:()=>Hu,MaxPool3DGrad:()=>mh,MaxPoolGrad:()=>fh,MaxPoolWithArgmax:()=>gh,Maximum:()=>Za,Mean:()=>Ja,Min:()=>Qa,Minimum:()=>eo,MirrorPad:()=>to,Mod:()=>Ji,MomentumOptimizer:()=>xp,Multinomial:()=>Ah,Multiply:()=>no,Neg:()=>Qi,NonMaxSuppressionV3:()=>tl,NonMaxSuppressionV4:()=>nl,NonMaxSuppressionV5:()=>sl,NotEqual:()=>el,OP_SCOPE_SUFFIX:()=>X5,OneHot:()=>so,OnesLike:()=>rl,Optimizer:()=>Sr,Pack:()=>al,PadV2:()=>ro,Pool:()=>HS,Pow:()=>ao,Prelu:()=>oo,Prod:()=>ol,RMSPropOptimizer:()=>bp,RNN:()=>ur,Range:()=>Gu,Rank:()=>Gm,Real:()=>yh,RealDiv:()=>La,Reciprocal:()=>il,Reduction:()=>vn,Relu:()=>io,Relu6:()=>uo,Reshape:()=>ll,ResizeBilinear:()=>lo,ResizeBilinearGrad:()=>bh,ResizeNearestNeighbor:()=>ju,ResizeNearestNeighborGrad:()=>xh,Reverse:()=>co,RotateWithOffset:()=>kl,Round:()=>ho,Rsqrt:()=>po,SGDOptimizer:()=>xc,ScatterNd:()=>ul,Select:()=>cl,Selu:()=>dl,Sequential:()=>Xl,Sigmoid:()=>mo,Sign:()=>fl,Sin:()=>fo,Sinh:()=>pl,Slice:()=>hl,Softmax:()=>yo,Softplus:()=>ml,SpaceToBatchND:()=>gl,SparseFillEmptyRows:()=>vh,SparseReshape:()=>wh,SparseSegmentMean:()=>kh,SparseSegmentSum:()=>Ih,SparseToDense:()=>Sh,SplitV:()=>Al,Sqrt:()=>go,Square:()=>qu,SquaredDifference:()=>xo,Step:()=>Gr,StridedSlice:()=>yl,StringNGrams:()=>Ch,StringSplit:()=>Th,StringToHashBucketFast:()=>Nh,Sub:()=>bo,Sum:()=>Ao,SymbolicTensor:()=>Vs,Tan:()=>vo,Tanh:()=>wo,Tensor:()=>Ge,TensorBuffer:()=>Ut,Tile:()=>Hr,TopK:()=>xl,Transform:()=>bl,Transpose:()=>ko,Unique:()=>Eh,Unpack:()=>vl,UnsortedSegmentSum:()=>Xu,Variable:()=>nc,ZerosLike:()=>wl,_FusedMatMul:()=>Io,abs:()=>Ht,acos:()=>$x,acosh:()=>Fx,add:()=>ae,addN:()=>Vh,all:()=>bg,any:()=>Uh,argMax:()=>er,argMin:()=>Ox,asin:()=>Px,asinh:()=>Mx,atan:()=>zx,atan2:()=>Lx,atanh:()=>Bx,avgPool:()=>Gh,avgPool3d:()=>kg,backend:()=>Dx,backend_util:()=>D,basicLSTMCell:()=>NT,batchNorm:()=>Fl,batchNorm2d:()=>Hx,batchNorm3d:()=>Gx,batchNorm4d:()=>jx,batchToSpaceND:()=>jh,bincount:()=>Ig,booleanMaskAsync:()=>WR,broadcastArgs:()=>qx,broadcastTo:()=>uc,browser:()=>ls,buffer:()=>We,callbacks:()=>sL,cast:()=>ce,ceil:()=>Xx,clipByValue:()=>Gn,clone:()=>Os,complex:()=>qr,concat:()=>ft,concat1d:()=>Kx,concat2d:()=>Ol,concat3d:()=>Zx,concat4d:()=>Yx,constraints:()=>r3,conv1d:()=>Sg,conv2d:()=>Jr,conv2dTranspose:()=>Tg,conv3d:()=>Ng,conv3dTranspose:()=>Qx,copyRegisteredKernels:()=>qS,cos:()=>qh,cosh:()=>Eg,cosineWindow:()=>eA,cumsum:()=>Rg,customGrad:()=>nr,data:()=>x7,denseBincount:()=>eb,deprecationWarn:()=>Ag,depthToSpace:()=>tb,depthwiseConv2d:()=>cc,deregisterOp:()=>aL,device_util:()=>rc,diag:()=>rN,dilation2d:()=>nb,disableDeprecationWarnings:()=>WC,dispose:()=>K,disposeVariables:()=>VC,div:()=>de,divNoNan:()=>sb,dot:()=>hN,dropout:()=>$b,einsum:()=>rb,elu:()=>dc,enableDebugMode:()=>BC,enableProdMode:()=>LC,enclosingPowerOfTwo:()=>Fb,engine:()=>wr,env:()=>Q,equal:()=>us,erf:()=>ab,exp:()=>cs,expandDims:()=>Ot,expm1:()=>ob,eye:()=>_g,fft:()=>ip,fill:()=>Pl,findBackend:()=>yg,findBackendFactory:()=>KC,floor:()=>hc,floorDiv:()=>xg,forceHalfFloat:()=>G6,fused:()=>ta,gather:()=>Ml,gatherND:()=>Db,gather_util:()=>cg,getBackend:()=>qC,getGradient:()=>Wm,getKernel:()=>_h,getKernelsForBackend:()=>Sl,gpgpu_util:()=>x6,grad:()=>MN,grads:()=>zN,greater:()=>jn,greaterEqual:()=>Oo,ifft:()=>gc,imag:()=>Xh,image:()=>_e,inTopKAsync:()=>JR,initializers:()=>d3,input:()=>tv,io:()=>_n,irfft:()=>Xg,isFinite:()=>TN,isInf:()=>EN,isNaN:()=>ib,keep:()=>Jt,kernel_impls:()=>rr,layers:()=>w3,leakyRelu:()=>Kh,less:()=>Dg,lessEqual:()=>Po,linalg:()=>Hb,linspace:()=>lb,loadGraphModel:()=>mt,loadLayersModel:()=>pM,localResponseNormalization:()=>ub,log:()=>ds,log1p:()=>Zh,logSigmoid:()=>HN,logSoftmax:()=>$g,logSumExp:()=>fb,logicalAnd:()=>Ps,logicalNot:()=>Jh,logicalOr:()=>Pg,logicalXor:()=>nE,losses:()=>PD,matMul:()=>Ve,math:()=>hx,max:()=>hs,maxPool:()=>Qh,maxPool3d:()=>Mg,maxPoolWithArgmax:()=>mb,maximum:()=>kr,mean:()=>_t,memory:()=>Wh,meshgrid:()=>lE,metrics:()=>Ov,min:()=>ep,minimum:()=>pc,mirrorPad:()=>gb,mod:()=>Ab,model:()=>dM,models:()=>Pv,moments:()=>tp,movingAverage:()=>HR,mul:()=>L,multiRNNCell:()=>gE,multinomial:()=>yb,neg:()=>Tt,nextFrame:()=>vp,norm:()=>Jg,notEqual:()=>Ll,oneHot:()=>ic,ones:()=>qn,onesLike:()=>ps,op:()=>W,outerProduct:()=>vE,pad:()=>Qr,pad1d:()=>IE,pad2d:()=>CE,pad3d:()=>NE,pad4d:()=>RE,pool:()=>OE,pow:()=>ea,prelu:()=>sp,print:()=>ox,prod:()=>zg,profile:()=>UC,rand:()=>BE,randomGamma:()=>HE,randomNormal:()=>xb,randomUniform:()=>Bl,range:()=>Wl,ready:()=>jC,real:()=>fc,reciprocal:()=>bb,registerBackend:()=>_l,registerCallbackConstructor:()=>fM,registerGradient:()=>F5,registerKernel:()=>To,registerOp:()=>rL,regularizers:()=>Mv,relu:()=>sr,relu6:()=>Wg,removeBackend:()=>XC,reshape:()=>U,reverse:()=>fs,reverse1d:()=>QE,reverse2d:()=>tR,reverse3d:()=>sR,reverse4d:()=>aR,rfft:()=>lp,round:()=>Vg,rsqrt:()=>Ug,scalar:()=>Ie,scatterND:()=>_b,scatter_util:()=>dg,selu:()=>Hg,separableConv2d:()=>vb,sequential:()=>hM,serialization:()=>oe,setBackend:()=>GC,setPlatform:()=>ZC,setWasmPath:()=>zie,setWasmPaths:()=>Lie,setWebGLContext:()=>hf,setdiff1dAsync:()=>wb,shared:()=>c2,sigmoid:()=>Hn,sign:()=>kb,signal:()=>OD,sin:()=>Gg,sinh:()=>jg,slice:()=>Re,slice1d:()=>rp,slice2d:()=>qg,slice3d:()=>ap,slice4d:()=>mc,slice_util:()=>xn,softmax:()=>op,softplus:()=>zl,spaceToBatchND:()=>np,sparse:()=>yc,sparseToDense:()=>Qg,spectral:()=>FD,split:()=>an,sqrt:()=>hn,square:()=>ct,squaredDifference:()=>Kg,squeeze:()=>lt,stack:()=>Dn,step:()=>Ac,stridedSlice:()=>Ib,string:()=>fp,sub:()=>ge,sum:()=>ve,sumOutType:()=>Ph,tan:()=>Sb,tanh:()=>$l,tensor:()=>dn,tensor1d:()=>Mt,tensor2d:()=>Ms,tensor3d:()=>Lh,tensor4d:()=>_R,tensor5d:()=>DR,tensor6d:()=>$R,tensor_util:()=>$s,test_util:()=>Nx,tidy:()=>H,tile:()=>Ts,time:()=>HC,topk:()=>Cb,train:()=>Lo,transpose:()=>Xe,truncatedNormal:()=>up,unique:()=>Zg,unregisterGradient:()=>jS,unregisterKernel:()=>GS,unsortedSegmentSum:()=>Tb,unstack:()=>ms,upcastType:()=>Cs,util:()=>w,valueAndGrad:()=>LN,valueAndGrads:()=>BN,variable:()=>Nb,variableGrads:()=>cb,version:()=>Vie,version_converter:()=>lB,version_core:()=>_x,version_cpu:()=>XW,version_layers:()=>OA,version_wasm:()=>Bie,version_webgl:()=>vK,webgl:()=>wK,webgl_util:()=>Uw,where:()=>bn,whereAsync:()=>Yg,zeros:()=>Pt,zerosLike:()=>Ke});var WI=Object.create,Vd=Object.defineProperty,VI=Object.getOwnPropertyDescriptor,UI=Object.getOwnPropertyNames,HI=Object.getPrototypeOf,GI=Object.prototype.hasOwnProperty,f5=e=>Vd(e,"__esModule",{value:!0}),bi=e=>{if(typeof Dm!="undefined")return Dm(e);throw new Error('Dynamic require of "'+e+'" is not supported')},vt=(e,t)=>function(){return t||(0,e[Object.keys(e)[0]])((t={exports:{}}).exports,t),t.exports},Pe=(e,t)=>{f5(e);for(var n in t)Vd(e,n,{get:t[n],enumerable:!0})},jI=(e,t,n)=>{if(t&&typeof t=="object"||typeof t=="function")for(let s of UI(t))!GI.call(e,s)&&s!=="default"&&Vd(e,s,{get:()=>t[s],enumerable:!(n=VI(t,s))||n.enumerable});return e},Ia=e=>jI(f5(Vd(e!=null?WI(HI(e)):{},"default",e&&e.__esModule&&"default"in e?{get:()=>e.default,enumerable:!0}:{value:e,enumerable:!0})),e),qI=vt({"node_modules/.pnpm/long@4.0.0/node_modules/long/src/long.js"(e,t){t.exports=s;var n=null;try{n=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(R){}function s(R,T,P){this.low=R|0,this.high=T|0,this.unsigned=!!P}s.prototype.__isLong__,Object.defineProperty(s.prototype,"__isLong__",{value:!0});function r(R){return(R&&R.__isLong__)===!0}s.isLong=r;var a={},o={};function i(R,T){var P,V,j;return T?(R>>>=0,(j=0<=R&&R<256)&&(V=o[R],V)?V:(P=u(R,(R|0)<0?-1:0,!0),j&&(o[R]=P),P)):(R|=0,(j=-128<=R&&R<128)&&(V=a[R],V)?V:(P=u(R,R<0?-1:0,!1),j&&(a[R]=P),P))}s.fromInt=i;function l(R,T){if(isNaN(R))return T?b:x;if(T){if(R<0)return b;if(R>=g)return _}else{if(R<=-A)return O;if(R+1>=A)return C}return R<0?l(-R,T).neg():u(R%m|0,R/m|0,T)}s.fromNumber=l;function u(R,T,P){return new s(R,T,P)}s.fromBits=u;var c=Math.pow;function d(R,T,P){if(R.length===0)throw Error("empty string");if(R==="NaN"||R==="Infinity"||R==="+Infinity"||R==="-Infinity")return x;if(typeof T=="number"?(P=T,T=!1):T=!!T,P=P||10,P<2||36<P)throw RangeError("radix");var V;if((V=R.indexOf("-"))>0)throw Error("interior hyphen");if(V===0)return d(R.substring(1),T,P).neg();for(var j=l(c(P,8)),q=x,X=0;X<R.length;X+=8){var ee=Math.min(8,R.length-X),te=parseInt(R.substring(X,X+ee),P);if(ee<8){var ne=l(c(P,ee));q=q.mul(ne).add(l(te))}else q=q.mul(j),q=q.add(l(te))}return q.unsigned=T,q}s.fromString=d;function h(R,T){return typeof R=="number"?l(R,T):typeof R=="string"?d(R,T):u(R.low,R.high,typeof T=="boolean"?T:R.unsigned)}s.fromValue=h;var p=1<<16,f=1<<24,m=p*p,g=m*m,A=g/2,y=i(f),x=i(0);s.ZERO=x;var b=i(0,!0);s.UZERO=b;var v=i(1);s.ONE=v;var k=i(1,!0);s.UONE=k;var S=i(-1);s.NEG_ONE=S;var C=u(4294967295|0,2147483647|0,!1);s.MAX_VALUE=C;var _=u(4294967295|0,4294967295|0,!0);s.MAX_UNSIGNED_VALUE=_;var O=u(0,2147483648|0,!1);s.MIN_VALUE=O;var E=s.prototype;E.toInt=function(){return this.unsigned?this.low>>>0:this.low},E.toNumber=function(){return this.unsigned?(this.high>>>0)*m+(this.low>>>0):this.high*m+(this.low>>>0)},E.toString=function(T){if(T=T||10,T<2||36<T)throw RangeError("radix");if(this.isZero())return"0";if(this.isNegative())if(this.eq(O)){var P=l(T),V=this.div(P),j=V.mul(P).sub(this);return V.toString(T)+j.toInt().toString(T)}else return"-"+this.neg().toString(T);for(var q=l(c(T,6),this.unsigned),X=this,ee="";;){var te=X.div(q),ne=X.sub(te.mul(q)).toInt()>>>0,se=ne.toString(T);if(X=te,X.isZero())return se+ee;for(;se.length<6;)se="0"+se;ee=""+se+ee}},E.getHighBits=function(){return this.high},E.getHighBitsUnsigned=function(){return this.high>>>0},E.getLowBits=function(){return this.low},E.getLowBitsUnsigned=function(){return this.low>>>0},E.getNumBitsAbs=function(){if(this.isNegative())return this.eq(O)?64:this.neg().getNumBitsAbs();for(var T=this.high!=0?this.high:this.low,P=31;P>0&&(T&1<<P)==0;P--);return this.high!=0?P+33:P+1},E.isZero=function(){return this.high===0&&this.low===0},E.eqz=E.isZero,E.isNegative=function(){return!this.unsigned&&this.high<0},E.isPositive=function(){return this.unsigned||this.high>=0},E.isOdd=function(){return(this.low&1)==1},E.isEven=function(){return(this.low&1)==0},E.equals=function(T){return r(T)||(T=h(T)),this.unsigned!==T.unsigned&&this.high>>>31==1&&T.high>>>31==1?!1:this.high===T.high&&this.low===T.low},E.eq=E.equals,E.notEquals=function(T){return!this.eq(T)},E.neq=E.notEquals,E.ne=E.notEquals,E.lessThan=function(T){return this.comp(T)<0},E.lt=E.lessThan,E.lessThanOrEqual=function(T){return this.comp(T)<=0},E.lte=E.lessThanOrEqual,E.le=E.lessThanOrEqual,E.greaterThan=function(T){return this.comp(T)>0},E.gt=E.greaterThan,E.greaterThanOrEqual=function(T){return this.comp(T)>=0},E.gte=E.greaterThanOrEqual,E.ge=E.greaterThanOrEqual,E.compare=function(T){if(r(T)||(T=h(T)),this.eq(T))return 0;var P=this.isNegative(),V=T.isNegative();return P&&!V?-1:!P&&V?1:this.unsigned?T.high>>>0>this.high>>>0||T.high===this.high&&T.low>>>0>this.low>>>0?-1:1:this.sub(T).isNegative()?-1:1},E.comp=E.compare,E.negate=function(){return!this.unsigned&&this.eq(O)?O:this.not().add(v)},E.neg=E.negate,E.add=function(T){r(T)||(T=h(T));var P=this.high>>>16,V=this.high&65535,j=this.low>>>16,q=this.low&65535,X=T.high>>>16,ee=T.high&65535,te=T.low>>>16,ne=T.low&65535,se=0,J=0,ie=0,le=0;return le+=q+ne,ie+=le>>>16,le&=65535,ie+=j+te,J+=ie>>>16,ie&=65535,J+=V+ee,se+=J>>>16,J&=65535,se+=P+X,se&=65535,u(ie<<16|le,se<<16|J,this.unsigned)},E.subtract=function(T){return r(T)||(T=h(T)),this.add(T.neg())},E.sub=E.subtract,E.multiply=function(T){if(this.isZero())return x;if(r(T)||(T=h(T)),n){var P=n.mul(this.low,this.high,T.low,T.high);return u(P,n.get_high(),this.unsigned)}if(T.isZero())return x;if(this.eq(O))return T.isOdd()?O:x;if(T.eq(O))return this.isOdd()?O:x;if(this.isNegative())return T.isNegative()?this.neg().mul(T.neg()):this.neg().mul(T).neg();if(T.isNegative())return this.mul(T.neg()).neg();if(this.lt(y)&&T.lt(y))return l(this.toNumber()*T.toNumber(),this.unsigned);var V=this.high>>>16,j=this.high&65535,q=this.low>>>16,X=this.low&65535,ee=T.high>>>16,te=T.high&65535,ne=T.low>>>16,se=T.low&65535,J=0,ie=0,le=0,he=0;return he+=X*se,le+=he>>>16,he&=65535,le+=q*se,ie+=le>>>16,le&=65535,le+=X*ne,ie+=le>>>16,le&=65535,ie+=j*se,J+=ie>>>16,ie&=65535,ie+=q*ne,J+=ie>>>16,ie&=65535,ie+=X*te,J+=ie>>>16,ie&=65535,J+=V*se+j*ne+q*te+X*ee,J&=65535,u(le<<16|he,J<<16|ie,this.unsigned)},E.mul=E.multiply,E.divide=function(T){if(r(T)||(T=h(T)),T.isZero())throw Error("division by zero");if(n){if(!this.unsigned&&this.high===-2147483648&&T.low===-1&&T.high===-1)return this;var P=(this.unsigned?n.div_u:n.div_s)(this.low,this.high,T.low,T.high);return u(P,n.get_high(),this.unsigned)}if(this.isZero())return this.unsigned?b:x;var V,j,q;if(this.unsigned){if(T.unsigned||(T=T.toUnsigned()),T.gt(this))return b;if(T.gt(this.shru(1)))return k;q=b}else{if(this.eq(O)){if(T.eq(v)||T.eq(S))return O;if(T.eq(O))return v;var X=this.shr(1);return V=X.div(T).shl(1),V.eq(x)?T.isNegative()?v:S:(j=this.sub(T.mul(V)),q=V.add(j.div(T)),q)}else if(T.eq(O))return this.unsigned?b:x;if(this.isNegative())return T.isNegative()?this.neg().div(T.neg()):this.neg().div(T).neg();if(T.isNegative())return this.div(T.neg()).neg();q=x}for(j=this;j.gte(T);){V=Math.max(1,Math.floor(j.toNumber()/T.toNumber()));for(var ee=Math.ceil(Math.log(V)/Math.LN2),te=ee<=48?1:c(2,ee-48),ne=l(V),se=ne.mul(T);se.isNegative()||se.gt(j);)V-=te,ne=l(V,this.unsigned),se=ne.mul(T);ne.isZero()&&(ne=v),q=q.add(ne),j=j.sub(se)}return q},E.div=E.divide,E.modulo=function(T){if(r(T)||(T=h(T)),n){var P=(this.unsigned?n.rem_u:n.rem_s)(this.low,this.high,T.low,T.high);return u(P,n.get_high(),this.unsigned)}return this.sub(this.div(T).mul(T))},E.mod=E.modulo,E.rem=E.modulo,E.not=function(){return u(~this.low,~this.high,this.unsigned)},E.and=function(T){return r(T)||(T=h(T)),u(this.low&T.low,this.high&T.high,this.unsigned)},E.or=function(T){return r(T)||(T=h(T)),u(this.low|T.low,this.high|T.high,this.unsigned)},E.xor=function(T){return r(T)||(T=h(T)),u(this.low^T.low,this.high^T.high,this.unsigned)},E.shiftLeft=function(T){return r(T)&&(T=T.toInt()),(T&=63)===0?this:T<32?u(this.low<<T,this.high<<T|this.low>>>32-T,this.unsigned):u(0,this.low<<T-32,this.unsigned)},E.shl=E.shiftLeft,E.shiftRight=function(T){return r(T)&&(T=T.toInt()),(T&=63)===0?this:T<32?u(this.low>>>T|this.high<<32-T,this.high>>T,this.unsigned):u(this.high>>T-32,this.high>=0?0:-1,this.unsigned)},E.shr=E.shiftRight,E.shiftRightUnsigned=function(T){if(r(T)&&(T=T.toInt()),T&=63,T===0)return this;var P=this.high;if(T<32){var V=this.low;return u(V>>>T|P<<32-T,P>>>T,this.unsigned)}else return T===32?u(P,0,this.unsigned):u(P>>>T-32,0,this.unsigned)},E.shru=E.shiftRightUnsigned,E.shr_u=E.shiftRightUnsigned,E.toSigned=function(){return this.unsigned?u(this.low,this.high,!1):this},E.toUnsigned=function(){return this.unsigned?this:u(this.low,this.high,!0)},E.toBytes=function(T){return T?this.toBytesLE():this.toBytesBE()},E.toBytesLE=function(){var T=this.high,P=this.low;return[P&255,P>>>8&255,P>>>16&255,P>>>24,T&255,T>>>8&255,T>>>16&255,T>>>24]},E.toBytesBE=function(){var T=this.high,P=this.low;return[T>>>24,T>>>16&255,T>>>8&255,T&255,P>>>24,P>>>16&255,P>>>8&255,P&255]},s.fromBytes=function(T,P,V){return V?s.fromBytesLE(T,P):s.fromBytesBE(T,P)},s.fromBytesLE=function(T,P){return new s(T[0]|T[1]<<8|T[2]<<16|T[3]<<24,T[4]|T[5]<<8|T[6]<<16|T[7]<<24,P)},s.fromBytesBE=function(T,P){return new s(T[4]<<24|T[5]<<16|T[6]<<8|T[7],T[0]<<24|T[1]<<16|T[2]<<8|T[3],P)}}}),XI=vt({"(disabled):node_modules/.pnpm/node-fetch@2.6.1/node_modules/node-fetch/browser.js"(){}}),KI=vt({"node_modules/.pnpm/seedrandom@2.4.3/node_modules/seedrandom/lib/alea.js"(e,t){(function(n,s,r){function a(u){var c=this,d=l();c.next=function(){var h=2091639*c.s0+c.c*23283064365386963e-26;return c.s0=c.s1,c.s1=c.s2,c.s2=h-(c.c=h|0)},c.c=1,c.s0=d(" "),c.s1=d(" "),c.s2=d(" "),c.s0-=d(u),c.s0<0&&(c.s0+=1),c.s1-=d(u),c.s1<0&&(c.s1+=1),c.s2-=d(u),c.s2<0&&(c.s2+=1),d=null}function o(u,c){return c.c=u.c,c.s0=u.s0,c.s1=u.s1,c.s2=u.s2,c}function i(u,c){var d=new a(u),h=c&&c.state,p=d.next;return p.int32=function(){return d.next()*4294967296|0},p.double=function(){return p()+(p()*2097152|0)*11102230246251565e-32},p.quick=p,h&&(typeof h=="object"&&o(h,d),p.state=function(){return o(d,{})}),p}function l(){var u=4022871197,c=function(d){d=d.toString();for(var h=0;h<d.length;h++){u+=d.charCodeAt(h);var p=.02519603282416938*u;u=p>>>0,p-=u,p*=u,u=p>>>0,p-=u,u+=p*4294967296}return(u>>>0)*23283064365386963e-26};return c}s&&s.exports?s.exports=i:r&&r.amd?r(function(){return i}):this.alea=i})(e,typeof t=="object"&&t,typeof define=="function"&&define)}}),ZI=vt({"node_modules/.pnpm/seedrandom@2.4.3/node_modules/seedrandom/lib/xor128.js"(e,t){(function(n,s,r){function a(l){var u=this,c="";u.x=0,u.y=0,u.z=0,u.w=0,u.next=function(){var h=u.x^u.x<<11;return u.x=u.y,u.y=u.z,u.z=u.w,u.w^=u.w>>>19^h^h>>>8},l===(l|0)?u.x=l:c+=l;for(var d=0;d<c.length+64;d++)u.x^=c.charCodeAt(d)|0,u.next()}function o(l,u){return u.x=l.x,u.y=l.y,u.z=l.z,u.w=l.w,u}function i(l,u){var c=new a(l),d=u&&u.state,h=function(){return(c.next()>>>0)/4294967296};return h.double=function(){do var p=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},h.int32=c.next,h.quick=h,d&&(typeof d=="object"&&o(d,c),h.state=function(){return o(c,{})}),h}s&&s.exports?s.exports=i:r&&r.amd?r(function(){return i}):this.xor128=i})(e,typeof t=="object"&&t,typeof define=="function"&&define)}}),YI=vt({"node_modules/.pnpm/seedrandom@2.4.3/node_modules/seedrandom/lib/xorwow.js"(e,t){(function(n,s,r){function a(l){var u=this,c="";u.next=function(){var h=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^(h^h<<1))|0},u.x=0,u.y=0,u.z=0,u.w=0,u.v=0,l===(l|0)?u.x=l:c+=l;for(var d=0;d<c.length+64;d++)u.x^=c.charCodeAt(d)|0,d==c.length&&(u.d=u.x<<10^u.x>>>4),u.next()}function o(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 i(l,u){var c=new a(l),d=u&&u.state,h=function(){return(c.next()>>>0)/4294967296};return h.double=function(){do var p=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},h.int32=c.next,h.quick=h,d&&(typeof d=="object"&&o(d,c),h.state=function(){return o(c,{})}),h}s&&s.exports?s.exports=i:r&&r.amd?r(function(){return i}):this.xorwow=i})(e,typeof t=="object"&&t,typeof define=="function"&&define)}}),JI=vt({"node_modules/.pnpm/seedrandom@2.4.3/node_modules/seedrandom/lib/xorshift7.js"(e,t){(function(n,s,r){function a(l){var u=this;u.next=function(){var d=u.x,h=u.i,p,f,m;return p=d[h],p^=p>>>7,f=p^p<<24,p=d[h+1&7],f^=p^p>>>10,p=d[h+3&7],f^=p^p>>>3,p=d[h+4&7],f^=p^p<<7,p=d[h+7&7],p=p^p<<13,f^=p^p<<9,d[h]=f,u.i=h+1&7,f};function c(d,h){var p,f,m=[];if(h===(h|0))f=m[0]=h;else for(h=""+h,p=0;p<h.length;++p)m[p&7]=m[p&7]<<15^h.charCodeAt(p)+m[p+1&7]<<13;for(;m.length<8;)m.push(0);for(p=0;p<8&&m[p]===0;++p);for(p==8?f=m[7]=-1:f=m[p],d.x=m,d.i=0,p=256;p>0;--p)d.next()}c(u,l)}function o(l,u){return u.x=l.x.slice(),u.i=l.i,u}function i(l,u){l==null&&(l=+new Date);var c=new a(l),d=u&&u.state,h=function(){return(c.next()>>>0)/4294967296};return h.double=function(){do var p=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},h.int32=c.next,h.quick=h,d&&(d.x&&o(d,c),h.state=function(){return o(c,{})}),h}s&&s.exports?s.exports=i:r&&r.amd?r(function(){return i}):this.xorshift7=i})(e,typeof t=="object"&&t,typeof define=="function"&&define)}}),QI=vt({"node_modules/.pnpm/seedrandom@2.4.3/node_modules/seedrandom/lib/xor4096.js"(e,t){(function(n,s,r){function a(l){var u=this;u.next=function(){var d=u.w,h=u.X,p=u.i,f,m;return u.w=d=d+1640531527|0,m=h[p+34&127],f=h[p=p+1&127],m^=m<<13,f^=f<<17,m^=m>>>15,f^=f>>>12,m=h[p]=m^f,u.i=p,m+(d^d>>>16)|0};function c(d,h){var p,f,m,g,A,y=[],x=128;for(h===(h|0)?(f=h,h=null):(h=h+"\0",f=0,x=Math.max(x,h.length)),m=0,g=-32;g<x;++g)h&&(f^=h.charCodeAt((g+32)%h.length)),g===0&&(A=f),f^=f<<10,f^=f>>>15,f^=f<<4,f^=f>>>13,g>=0&&(A=A+1640531527|0,p=y[g&127]^=f+A,m=p==0?m+1:0);for(m>=128&&(y[(h&&h.length||0)&127]=-1),m=127,g=4*128;g>0;--g)f=y[m+34&127],p=y[m=m+1&127],f^=f<<13,p^=p<<17,f^=f>>>15,p^=p>>>12,y[m]=f^p;d.w=A,d.X=y,d.i=m}c(u,l)}function o(l,u){return u.i=l.i,u.w=l.w,u.X=l.X.slice(),u}function i(l,u){l==null&&(l=+new Date);var c=new a(l),d=u&&u.state,h=function(){return(c.next()>>>0)/4294967296};return h.double=function(){do var p=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},h.int32=c.next,h.quick=h,d&&(d.X&&o(d,c),h.state=function(){return o(c,{})}),h}s&&s.exports?s.exports=i:r&&r.amd?r(function(){return i}):this.xor4096=i})(e,typeof t=="object"&&t,typeof define=="function"&&define)}}),eS=vt({"node_modules/.pnpm/seedrandom@2.4.3/node_modules/seedrandom/lib/tychei.js"(e,t){(function(n,s,r){function a(l){var u=this,c="";u.next=function(){var h=u.b,p=u.c,f=u.d,m=u.a;return h=h<<25^h>>>7^p,p=p-f|0,f=f<<24^f>>>8^m,m=m-h|0,u.b=h=h<<20^h>>>12^p,u.c=p=p-f|0,u.d=f<<16^p>>>16^m,u.a=m-h|0},u.a=0,u.b=0,u.c=2654435769|0,u.d=1367130551,l===Math.floor(l)?(u.a=l/4294967296|0,u.b=l|0):c+=l;for(var d=0;d<c.length+20;d++)u.b^=c.charCodeAt(d)|0,u.next()}function o(l,u){return u.a=l.a,u.b=l.b,u.c=l.c,u.d=l.d,u}function i(l,u){var c=new a(l),d=u&&u.state,h=function(){return(c.next()>>>0)/4294967296};return h.double=function(){do var p=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},h.int32=c.next,h.quick=h,d&&(typeof d=="object"&&o(d,c),h.state=function(){return o(c,{})}),h}s&&s.exports?s.exports=i:r&&r.amd?r(function(){return i}):this.tychei=i})(e,typeof t=="object"&&t,typeof define=="function"&&define)}}),m5=vt({"(disabled):crypto"(){}}),tS=vt({"node_modules/.pnpm/seedrandom@2.4.3/node_modules/seedrandom/seedrandom.js"(e,t){(function(n,s){var r=this,a=256,o=6,i=52,l="random",u=s.pow(a,o),c=s.pow(2,i),d=c*2,h=a-1,p;function f(v,k,S){var C=[];k=k==!0?{entropy:!0}:k||{};var _=y(A(k.entropy?[v,b(n)]:v==null?x():v,3),C),O=new m(C),E=function(){for(var R=O.g(o),T=u,P=0;R<c;)R=(R+P)*a,T*=a,P=O.g(1);for(;R>=d;)R/=2,T/=2,P>>>=1;return(R+P)/T};return E.int32=function(){return O.g(4)|0},E.quick=function(){return O.g(4)/4294967296},E.double=E,y(b(O.S),n),(k.pass||S||function(R,T,P,V){return V&&(V.S&&g(V,O),R.state=function(){return g(O,{})}),P?(s[l]=R,T):R})(E,_,"global"in k?k.global:this==s,k.state)}s["seed"+l]=f;function m(v){var k,S=v.length,C=this,_=0,O=C.i=C.j=0,E=C.S=[];for(S||(v=[S++]);_<a;)E[_]=_++;for(_=0;_<a;_++)E[_]=E[O=h&O+v[_%S]+(k=E[_])],E[O]=k;(C.g=function(R){for(var T,P=0,V=C.i,j=C.j,q=C.S;R--;)T=q[V=h&V+1],P=P*a+q[h&(q[V]=q[j=h&j+T])+(q[j]=T)];return C.i=V,C.j=j,P})(a)}function g(v,k){return k.i=v.i,k.j=v.j,k.S=v.S.slice(),k}function A(v,k){var S=[],C=typeof v,_;if(k&&C=="object")for(_ in v)try{S.push(A(v[_],k-1))}catch(O){}return S.length?S:C=="string"?v:v+"\0"}function y(v,k){for(var S=v+"",C,_=0;_<S.length;)k[h&_]=h&(C^=k[h&_]*19)+S.charCodeAt(_++);return b(k)}function x(){try{var v;return p&&(v=p.randomBytes)?v=v(a):(v=new Uint8Array(a),(r.crypto||r.msCrypto).getRandomValues(v)),b(v)}catch(C){var k=r.navigator,S=k&&k.plugins;return[+new Date,r,S,r.screen,b(n)]}}function b(v){return String.fromCharCode.apply(0,v)}if(y(s.random(),n),typeof t=="object"&&t.exports){t.exports=f;try{p=m5()}catch(v){}}else typeof define=="function"&&define.amd&&define(function(){return f})})([],Math)}}),g5=vt({"node_modules/.pnpm/seedrandom@2.4.3/node_modules/seedrandom/index.js"(e,t){var n=KI(),s=ZI(),r=YI(),a=JI(),o=QI(),i=eS(),l=tS();l.alea=n,l.xor128=s,l.xorwow=r,l.xorshift7=a,l.xor4096=o,l.tychei=i,t.exports=l}}),nS=vt({"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/alea.js"(e,t){(function(n,s,r){function a(u){var c=this,d=l();c.next=function(){var h=2091639*c.s0+c.c*23283064365386963e-26;return c.s0=c.s1,c.s1=c.s2,c.s2=h-(c.c=h|0)},c.c=1,c.s0=d(" "),c.s1=d(" "),c.s2=d(" "),c.s0-=d(u),c.s0<0&&(c.s0+=1),c.s1-=d(u),c.s1<0&&(c.s1+=1),c.s2-=d(u),c.s2<0&&(c.s2+=1),d=null}function o(u,c){return c.c=u.c,c.s0=u.s0,c.s1=u.s1,c.s2=u.s2,c}function i(u,c){var d=new a(u),h=c&&c.state,p=d.next;return p.int32=function(){return d.next()*4294967296|0},p.double=function(){return p()+(p()*2097152|0)*11102230246251565e-32},p.quick=p,h&&(typeof h=="object"&&o(h,d),p.state=function(){return o(d,{})}),p}function l(){var u=4022871197,c=function(d){d=String(d);for(var h=0;h<d.length;h++){u+=d.charCodeAt(h);var p=.02519603282416938*u;u=p>>>0,p-=u,p*=u,u=p>>>0,p-=u,u+=p*4294967296}return(u>>>0)*23283064365386963e-26};return c}s&&s.exports?s.exports=i:r&&r.amd?r(function(){return i}):this.alea=i})(e,typeof t=="object"&&t,typeof define=="function"&&define)}}),sS=vt({"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/xor128.js"(e,t){(function(n,s,r){function a(l){var u=this,c="";u.x=0,u.y=0,u.z=0,u.w=0,u.next=function(){var h=u.x^u.x<<11;return u.x=u.y,u.y=u.z,u.z=u.w,u.w^=u.w>>>19^h^h>>>8},l===(l|0)?u.x=l:c+=l;for(var d=0;d<c.length+64;d++)u.x^=c.charCodeAt(d)|0,u.next()}function o(l,u){return u.x=l.x,u.y=l.y,u.z=l.z,u.w=l.w,u}function i(l,u){var c=new a(l),d=u&&u.state,h=function(){return(c.next()>>>0)/4294967296};return h.double=function(){do var p=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},h.int32=c.next,h.quick=h,d&&(typeof d=="object"&&o(d,c),h.state=function(){return o(c,{})}),h}s&&s.exports?s.exports=i:r&&r.amd?r(function(){return i}):this.xor128=i})(e,typeof t=="object"&&t,typeof define=="function"&&define)}}),rS=vt({"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/xorwow.js"(e,t){(function(n,s,r){function a(l){var u=this,c="";u.next=function(){var h=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^(h^h<<1))|0},u.x=0,u.y=0,u.z=0,u.w=0,u.v=0,l===(l|0)?u.x=l:c+=l;for(var d=0;d<c.length+64;d++)u.x^=c.charCodeAt(d)|0,d==c.length&&(u.d=u.x<<10^u.x>>>4),u.next()}function o(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 i(l,u){var c=new a(l),d=u&&u.state,h=function(){return(c.next()>>>0)/4294967296};return h.double=function(){do var p=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},h.int32=c.next,h.quick=h,d&&(typeof d=="object"&&o(d,c),h.state=function(){return o(c,{})}),h}s&&s.exports?s.exports=i:r&&r.amd?r(function(){return i}):this.xorwow=i})(e,typeof t=="object"&&t,typeof define=="function"&&define)}}),aS=vt({"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/xorshift7.js"(e,t){(function(n,s,r){function a(l){var u=this;u.next=function(){var d=u.x,h=u.i,p,f,m;return p=d[h],p^=p>>>7,f=p^p<<24,p=d[h+1&7],f^=p^p>>>10,p=d[h+3&7],f^=p^p>>>3,p=d[h+4&7],f^=p^p<<7,p=d[h+7&7],p=p^p<<13,f^=p^p<<9,d[h]=f,u.i=h+1&7,f};function c(d,h){var p,f,m=[];if(h===(h|0))f=m[0]=h;else for(h=""+h,p=0;p<h.length;++p)m[p&7]=m[p&7]<<15^h.charCodeAt(p)+m[p+1&7]<<13;for(;m.length<8;)m.push(0);for(p=0;p<8&&m[p]===0;++p);for(p==8?f=m[7]=-1:f=m[p],d.x=m,d.i=0,p=256;p>0;--p)d.next()}c(u,l)}function o(l,u){return u.x=l.x.slice(),u.i=l.i,u}function i(l,u){l==null&&(l=+new Date);var c=new a(l),d=u&&u.state,h=function(){return(c.next()>>>0)/4294967296};return h.double=function(){do var p=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},h.int32=c.next,h.quick=h,d&&(d.x&&o(d,c),h.state=function(){return o(c,{})}),h}s&&s.exports?s.exports=i:r&&r.amd?r(function(){return i}):this.xorshift7=i})(e,typeof t=="object"&&t,typeof define=="function"&&define)}}),oS=vt({"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/xor4096.js"(e,t){(function(n,s,r){function a(l){var u=this;u.next=function(){var d=u.w,h=u.X,p=u.i,f,m;return u.w=d=d+1640531527|0,m=h[p+34&127],f=h[p=p+1&127],m^=m<<13,f^=f<<17,m^=m>>>15,f^=f>>>12,m=h[p]=m^f,u.i=p,m+(d^d>>>16)|0};function c(d,h){var p,f,m,g,A,y=[],x=128;for(h===(h|0)?(f=h,h=null):(h=h+"\0",f=0,x=Math.max(x,h.length)),m=0,g=-32;g<x;++g)h&&(f^=h.charCodeAt((g+32)%h.length)),g===0&&(A=f),f^=f<<10,f^=f>>>15,f^=f<<4,f^=f>>>13,g>=0&&(A=A+1640531527|0,p=y[g&127]^=f+A,m=p==0?m+1:0);for(m>=128&&(y[(h&&h.length||0)&127]=-1),m=127,g=4*128;g>0;--g)f=y[m+34&127],p=y[m=m+1&127],f^=f<<13,p^=p<<17,f^=f>>>15,p^=p>>>12,y[m]=f^p;d.w=A,d.X=y,d.i=m}c(u,l)}function o(l,u){return u.i=l.i,u.w=l.w,u.X=l.X.slice(),u}function i(l,u){l==null&&(l=+new Date);var c=new a(l),d=u&&u.state,h=function(){return(c.next()>>>0)/4294967296};return h.double=function(){do var p=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},h.int32=c.next,h.quick=h,d&&(d.X&&o(d,c),h.state=function(){return o(c,{})}),h}s&&s.exports?s.exports=i:r&&r.amd?r(function(){return i}):this.xor4096=i})(e,typeof t=="object"&&t,typeof define=="function"&&define)}}),iS=vt({"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/tychei.js"(e,t){(function(n,s,r){function a(l){var u=this,c="";u.next=function(){var h=u.b,p=u.c,f=u.d,m=u.a;return h=h<<25^h>>>7^p,p=p-f|0,f=f<<24^f>>>8^m,m=m-h|0,u.b=h=h<<20^h>>>12^p,u.c=p=p-f|0,u.d=f<<16^p>>>16^m,u.a=m-h|0},u.a=0,u.b=0,u.c=2654435769|0,u.d=1367130551,l===Math.floor(l)?(u.a=l/4294967296|0,u.b=l|0):c+=l;for(var d=0;d<c.length+20;d++)u.b^=c.charCodeAt(d)|0,u.next()}function o(l,u){return u.a=l.a,u.b=l.b,u.c=l.c,u.d=l.d,u}function i(l,u){var c=new a(l),d=u&&u.state,h=function(){return(c.next()>>>0)/4294967296};return h.double=function(){do var p=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},h.int32=c.next,h.quick=h,d&&(typeof d=="object"&&o(d,c),h.state=function(){return o(c,{})}),h}s&&s.exports?s.exports=i:r&&r.amd?r(function(){return i}):this.tychei=i})(e,typeof t=="object"&&t,typeof define=="function"&&define)}}),lS=vt({"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/seedrandom.js"(e,t){(function(n,s,r){var a=256,o=6,i=52,l="random",u=r.pow(a,o),c=r.pow(2,i),d=c*2,h=a-1,p;function f(v,k,S){var C=[];k=k==!0?{entropy:!0}:k||{};var _=y(A(k.entropy?[v,b(s)]:v==null?x():v,3),C),O=new m(C),E=function(){for(var R=O.g(o),T=u,P=0;R<c;)R=(R+P)*a,T*=a,P=O.g(1);for(;R>=d;)R/=2,T/=2,P>>>=1;return(R+P)/T};return E.int32=function(){return O.g(4)|0},E.quick=function(){return O.g(4)/4294967296},E.double=E,y(b(O.S),s),(k.pass||S||function(R,T,P,V){return V&&(V.S&&g(V,O),R.state=function(){return g(O,{})}),P?(r[l]=R,T):R})(E,_,"global"in k?k.global:this==r,k.state)}function m(v){var k,S=v.length,C=this,_=0,O=C.i=C.j=0,E=C.S=[];for(S||(v=[S++]);_<a;)E[_]=_++;for(_=0;_<a;_++)E[_]=E[O=h&O+v[_%S]+(k=E[_])],E[O]=k;(C.g=function(R){for(var T,P=0,V=C.i,j=C.j,q=C.S;R--;)T=q[V=h&V+1],P=P*a+q[h&(q[V]=q[j=h&j+T])+(q[j]=T)];return C.i=V,C.j=j,P})(a)}function g(v,k){return k.i=v.i,k.j=v.j,k.S=v.S.slice(),k}function A(v,k){var S=[],C=typeof v,_;if(k&&C=="object")for(_ in v)try{S.push(A(v[_],k-1))}catch(O){}return S.length?S:C=="string"?v:v+"\0"}function y(v,k){for(var S=v+"",C,_=0;_<S.length;)k[h&_]=h&(C^=k[h&_]*19)+S.charCodeAt(_++);return b(k)}function x(){try{var v;return p&&(v=p.randomBytes)?v=v(a):(v=new Uint8Array(a),(n.crypto||n.msCrypto).getRandomValues(v)),b(v)}catch(C){var k=n.navigator,S=k&&k.plugins;return[+new Date,n,S,n.screen,b(s)]}}function b(v){return String.fromCharCode.apply(0,v)}if(y(r.random(),s),typeof t=="object"&&t.exports){t.exports=f;try{p=m5()}catch(v){}}else typeof define=="function"&&define.amd?define(function(){return f}):r["seed"+l]=f})(typeof self!="undefined"?self:e,[],Math)}}),A5=vt({"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/index.js"(e,t){var n=nS(),s=sS(),r=rS(),a=aS(),o=oS(),i=iS(),l=lS();l.alea=n,l.xor128=s,l.xorwow=r,l.xorshift7=a,l.xor4096=o,l.tychei=i,t.exports=l}}),y5=vt({"(disabled):node_modules/.pnpm/string_decoder@1.1.1/node_modules/string_decoder/lib/string_decoder.js"(){}}),_u=vt({"(disabled):path"(){}}),uS=vt({"(disabled):worker_threads"(){}}),cS=vt({"(disabled):perf_hooks"(){}}),dS=vt({"node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.9.0_@tensorflow+tfjs-core@3.9.0/node_modules/@tensorflow/tfjs-backend-wasm/wasm-out/tfjs-backend-wasm-threaded-simd.js"(e,t){var n=function(){var s=typeof document!="undefined"&&document.currentScript?document.currentScript.src:void 0;return typeof __filename!="undefined"&&(s=s||__filename),function(r){r=r||{};function a(){return J.buffer!=He&&sn(J.buffer),Nn}function o(){return J.buffer!=He&&sn(J.buffer),St}function i(){return J.buffer!=He&&sn(J.buffer),ks}function l(){return J.buffer!=He&&sn(J.buffer),pn}function u(){return J.buffer!=He&&sn(J.buffer),ns}var c=typeof r!="undefined"?r:{},d,h;c.ready=new Promise(function(N,F){d=N,h=F});var p={},f;for(f in c)c.hasOwnProperty(f)&&(p[f]=c[f]);var m=[],g="./this.program",A=function(N,F){throw F},y=!1,x=!1,b=!1,v=!1;y=typeof window=="object",x=typeof importScripts=="function",b=typeof process=="object"&&typeof process.versions=="object"&&typeof process.versions.node=="string",v=!y&&!b&&!x;var k=c.ENVIRONMENT_IS_PTHREAD||!1;k&&(He=c.buffer);var S="";function C(N){return c.locateFile?c.locateFile(N,S):S+N}var _,O,E,R,T,P;if(b){x?S=_u().dirname(S)+"/":S=__dirname+"/",_=function(F,B){return T||(T=bi("fs")),P||(P=_u()),F=P.normalize(F),T.readFileSync(F,B?null:"utf8")},E=function(F){var B=_(F,!0);return B.buffer||(B=new Uint8Array(B)),Ae(B.buffer),B},process.argv.length>1&&(g=process.argv[1].replace(/\\/g,"/")),m=process.argv.slice(2),process.on("uncaughtException",function(N){if(!(N instanceof Ru))throw N}),process.on("unhandledRejection",Ar),A=function(N){process.exit(N)},c.inspect=function(){return"[Emscripten Module object]"};var V;try{V=uS()}catch(N){throw console.error('The "worker_threads" module is not supported in this node.js build - perhaps a newer version is needed?'),N}global.Worker=V.Worker}else v?(typeof read!="undefined"&&(_=function(F){return read(F)}),E=function(F){var B;return typeof readbuffer=="function"?new Uint8Array(readbuffer(F)):(B=read(F,"binary"),Ae(typeof B=="object"),B)},typeof scriptArgs!="undefined"?m=scriptArgs:typeof arguments!="undefined"&&(m=arguments),typeof quit=="function"&&(A=function(N){quit(N)}),typeof print!="undefined"&&(typeof console=="undefined"&&(console={}),console.log=print,console.warn=console.error=typeof printErr!="undefined"?printErr:print)):(y||x)&&(x?S=self.location.href:typeof document!="undefined"&&document.currentScript&&(S=document.currentScript.src),typeof s!="undefined"&&s&&(S=s),S.indexOf("blob:")!==0?S=S.substr(0,S.lastIndexOf("/")+1):S="",b?(_=function(F,B){return T||(T=bi("fs")),P||(P=_u()),F=P.normalize(F),T.readFileSync(F,B?null:"utf8")},E=function(F){var B=_(F,!0);return B.buffer||(B=new Uint8Array(B)),Ae(B.buffer),B}):(_=function(N){var F=new XMLHttpRequest;return F.open("GET",N,!1),F.send(null),F.responseText},x&&(E=function(N){var F=new XMLHttpRequest;return F.open("GET",N,!1),F.responseType="arraybuffer",F.send(null),new Uint8Array(F.response)}),O=function(N,F,B){var Z=new XMLHttpRequest;Z.open("GET",N,!0),Z.responseType="arraybuffer",Z.onload=function(){if(Z.status==200||Z.status==0&&Z.response){F(Z.response);return}B()},Z.onerror=B,Z.send(null)}),R=function(N){document.title=N});b&&typeof performance=="undefined"&&(global.performance=cS().performance);var j=c.print||console.log.bind(console),q=c.printErr||console.warn.bind(console);for(f in p)p.hasOwnProperty(f)&&(c[f]=p[f]);p=null,c.arguments&&(m=c.arguments),c.thisProgram&&(g=c.thisProgram),c.quit&&(A=c.quit);var X=Atomics.load,ee=Atomics.store,te=Atomics.compareExchange,ne;c.wasmBinary&&(ne=c.wasmBinary);var se=c.noExitRuntime||!0;typeof WebAssembly!="object"&&Ar("no native wasm support detected");var J,ie,le=!1,he;function Ae(N,F){N||Ar("Assertion failed: "+F)}function Ce(N){var F=c["_"+N];return Ae(F,"Cannot call unknown function "+N+", make sure it is exported"),F}function Te(N,F,B,Z,me){var pe={string:function(fn){var xi=0;if(fn!=null&&fn!==0){var u5=(fn.length<<2)+1;xi=gi(u5),nt(fn,xi,u5)}return xi},array:function(fn){var xi=gi(fn.length);return et(fn,xi),xi}};function fe(fn){return F==="string"?Fe(fn):F==="boolean"?Boolean(fn):fn}var we=Ce(N),rt=[],Kt=0;if(Z)for(var Vt=0;Vt<Z.length;Vt++){var Lr=pe[B[Vt]];Lr?(Kt===0&&(Kt=Eu()),rt[Vt]=Lr(Z[Vt])):rt[Vt]=Z[Vt]}var yi=we.apply(null,rt);return yi=fe(yi),Kt!==0&&mi(Kt),yi}function De(N,F,B,Z){B=B||[];var me=B.every(function(fe){return fe==="number"}),pe=F!=="string";return pe&&me&&!Z?Ce(N):function(){return Te(N,F,B,arguments,Z)}}function Me(N,F,B){for(var Z=F+B,me="";!(F>=Z);){var pe=N[F++];if(!pe)return me;if(!(pe&128)){me+=String.fromCharCode(pe);continue}var fe=N[F++]&63;if((pe&224)==192){me+=String.fromCharCode((pe&31)<<6|fe);continue}var we=N[F++]&63;if((pe&240)==224?pe=(pe&15)<<12|fe<<6|we:pe=(pe&7)<<18|fe<<12|we<<6|N[F++]&63,pe<65536)me+=String.fromCharCode(pe);else{var rt=pe-65536;me+=String.fromCharCode(55296|rt>>10,56320|rt&1023)}}return me}function Fe(N,F){return N?Me(o(),N,F):""}function ut(N,F,B,Z){if(!(Z>0))return 0;for(var me=B,pe=B+Z-1,fe=0;fe<N.length;++fe){var we=N.charCodeAt(fe);if(we>=55296&&we<=57343){var rt=N.charCodeAt(++fe);we=65536+((we&1023)<<10)|rt&1023}if(we<=127){if(B>=pe)break;F[B++]=we}else if(we<=2047){if(B+1>=pe)break;F[B++]=192|we>>6,F[B++]=128|we&63}else if(we<=65535){if(B+2>=pe)break;F[B++]=224|we>>12,F[B++]=128|we>>6&63,F[B++]=128|we&63}else{if(B+3>=pe)break;F[B++]=240|we>>18,F[B++]=128|we>>12&63,F[B++]=128|we>>6&63,F[B++]=128|we&63}}return F[B]=0,B-me}function nt(N,F,B){return ut(N,o(),F,B)}function st(N){for(var F=0,B=0;B<N.length;++B){var Z=N.charCodeAt(B);Z>=55296&&Z<=57343&&(Z=65536+((Z&1023)<<10)|N.charCodeAt(++B)&1023),Z<=127?++F:Z<=2047?F+=2:Z<=65535?F+=3:F+=4}return F}function et(N,F){a().set(N,F)}function it(N,F){return N%F>0&&(N+=F-N%F),N}var He,Nn,St,Wn,nn,ks,pn,ts,ns;function sn(N){He=N,c.HEAP8=Nn=new Int8Array(N),c.HEAP16=Wn=new Int16Array(N),c.HEAP32=ks=new Int32Array(N),c.HEAPU8=St=new Uint8Array(N),c.HEAPU16=nn=new Uint16Array(N),c.HEAPU32=pn=new Uint32Array(N),c.HEAPF32=ts=new Float32Array(N),c.HEAPF64=ns=new Float64Array(N)}var ss=c.INITIAL_MEMORY||16777216;if(k)J=c.wasmMemory,He=c.buffer;else if(c.wasmMemory)J=c.wasmMemory;else if(J=new WebAssembly.Memory({initial:ss/65536,maximum:2147483648/65536,shared:!0}),!(J.buffer instanceof SharedArrayBuffer))throw q("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"),b&&console.log("(on node you may need: --experimental-wasm-threads --experimental-wasm-bulk-memory and also use a recent version)"),Error("bad memory");J&&(He=J.buffer),ss=He.byteLength,sn(He);var rs,Vn=[],Ks=[],mr=[],Fr=[],ui=[],Zs=!1,bd=!1;k||Ks.push({func:function(){Od()}});function o0(){if(!k){if(c.preRun)for(typeof c.preRun=="function"&&(c.preRun=[c.preRun]);c.preRun.length;)wd(c.preRun.shift());di(Vn)}}function bu(){Zs=!0,!k&&di(Ks)}function i0(){k||di(mr)}function vd(){k||(bd=!0)}function En(){if(!k){if(c.postRun)for(typeof c.postRun=="function"&&(c.postRun=[c.postRun]);c.postRun.length;)l0(c.postRun.shift());di(ui)}}function wd(N){Vn.unshift(N)}function l0(N){ui.unshift(N)}var gr=0,Or=null,va=null;function u0(N){Ae(!k,"addRunDependency cannot be used in a pthread worker"),gr++,c.monitorRunDependencies&&c.monitorRunDependencies(gr)}function c0(N){if(gr--,c.monitorRunDependencies&&c.monitorRunDependencies(gr),gr==0&&(Or!==null&&(clearInterval(Or),Or=null),va)){var F=va;va=null,F()}}c.preloadedImages={},c.preloadedAudios={};function Ar(N){c.onAbort&&c.onAbort(N),k&&console.error("Pthread aborting at "+new Error().stack),N+="",q(N),le=!0,he=1,N="abort("+N+"). Build with -s ASSERTIONS=1 for more info.";var F=new WebAssembly.RuntimeError(N);throw h(F),F}function kd(N,F){return String.prototype.startsWith?N.startsWith(F):N.indexOf(F)===0}var ci="data:application/octet-stream;base64,";function Id(N){return kd(N,ci)}var d0="file://";function Sd(N){return kd(N,d0)}var Rn="tfjs-backend-wasm-threaded-simd.wasm";Id(Rn)||(Rn=C(Rn));function Cd(N){try{if(N==Rn&&ne)return new Uint8Array(ne);if(E)return E(N);throw"both async and sync fetching of the wasm failed"}catch(F){Ar(F)}}function h0(){if(!ne&&(y||x)){if(typeof fetch=="function"&&!Sd(Rn))return fetch(Rn,{credentials:"same-origin"}).then(function(N){if(!N.ok)throw"failed to load wasm binary file at '"+Rn+"'";return N.arrayBuffer()}).catch(function(){return Cd(Rn)});if(O)return new Promise(function(N,F){O(Rn,function(B){N(new Uint8Array(B))},F)})}return Promise.resolve().then(function(){return Cd(Rn)})}function p0(){var N={a:sm};function F(fe,we){var rt=fe.exports;if(c.asm=rt,rs=c.asm.F,ie=we,!k){var Kt=Se.unusedWorkers.length;Se.unusedWorkers.forEach(function(Vt){Se.loadWasmModuleToWorker(Vt,function(){--Kt||c0("wasm-instantiate")})})}}k||u0("wasm-instantiate");function B(fe){F(fe.instance,fe.module)}function Z(fe){return h0().then(function(we){return WebAssembly.instantiate(we,N)}).then(fe,function(we){q("failed to asynchronously prepare wasm: "+we),Ar(we)})}function me(){return!ne&&typeof WebAssembly.instantiateStreaming=="function"&&!Id(Rn)&&!Sd(Rn)&&typeof fetch=="function"?fetch(Rn,{credentials:"same-origin"}).then(function(fe){var we=WebAssembly.instantiateStreaming(fe,N);return we.then(B,function(rt){return q("wasm streaming compile failed: "+rt),q("falling back to ArrayBuffer instantiation"),Z(B)})}):Z(B)}if(c.instantiateWasm)try{var pe=c.instantiateWasm(N,F);return pe}catch(fe){return q("Module.instantiateWasm callback failed with error: "+fe),!1}return me().catch(h),{}}var f0={10024:function(){throw"Canceled!"},10042:function(N,F){setTimeout(function(){s5(N,F)},0)}};function Td(){Se.initRuntime()}function di(N){for(;N.length>0;){var F=N.shift();if(typeof F=="function"){F(c);continue}var B=F.func;typeof B=="number"?F.arg===void 0?rs.get(B)():rs.get(B)(F.arg):B(F.arg===void 0?null:F.arg)}}function vu(N,F){if(N<=0||N>a().length||N&!0||F<0)return-28;if(F==0)return 0;F>=2147483647&&(F=1/0);var B=Atomics.load(i(),Ai>>2),Z=0;if(B==N){var me=Atomics.compareExchange(i(),Ai>>2,B,0);if(me==B&&(--F,Z=1,F<=0))return 1}var pe=Atomics.notify(i(),N>>2,F);if(pe>=0)return pe+Z;throw"Atomics.notify returned an unexpected value "+pe}c._emscripten_futex_wake=vu;function m0(N){if(k)throw"Internal Error! killThread() can only ever be called from main application thread!";if(!N)throw"Internal Error! Null pthread_ptr in killThread!";i()[N+12>>2]=0;var F=Se.pthreads[N];F.worker.terminate(),Se.freeThreadData(F),Se.runningWorkers.splice(Se.runningWorkers.indexOf(F.worker),1),F.worker.pthread=void 0}function g0(N){if(k)throw"Internal Error! cancelThread() can only ever be called from main application thread!";if(!N)throw"Internal Error! Null pthread_ptr in cancelThread!";var F=Se.pthreads[N];F.worker.postMessage({cmd:"cancel"})}function A0(N){if(k)throw"Internal Error! cleanupThread() can only ever be called from main application thread!";if(!N)throw"Internal Error! Null pthread_ptr in cleanupThread!";var F=Se.pthreads[N];if(F){i()[N+12>>2]=0;var B=F.worker;Se.returnWorkerToPool(B)}}var Se={unusedWorkers:[],runningWorkers:[],initMainThreadBlock:function(){for(var N=Math.min(4,Math.max(1,(navigator.hardwareConcurrency||1)/2)),F=0;F<N;++F)Se.allocateUnusedWorker()},initRuntime:function(){for(var N=ka(228),F=0;F<228/4;++F)l()[N/4+F]=0;i()[N+12>>2]=N;var B=N+152;i()[B>>2]=B;for(var Z=ka(512),F=0;F<128;++F)l()[Z/4+F]=0;Atomics.store(l(),N+100>>2,Z),Atomics.store(l(),N+40>>2,N),Rm(N,!x,1),n5(N)},initWorker:function(){},pthreads:{},threadExitHandlers:[],setThreadStatus:function(){},runExitHandlers:function(){for(;Se.threadExitHandlers.length>0;)Se.threadExitHandlers.pop()();k&&fi()&&t5()},runExitHandlersAndDeinitThread:function(N,F){Atomics.store(l(),N+56>>2,1),Atomics.store(l(),N+60>>2,0),Se.runExitHandlers(),Atomics.store(l(),N+4>>2,F),Atomics.store(l(),N+0>>2,1),vu(N+0,2147483647),Rm(0,0,0)},threadExit:function(N){var F=fi();F&&(Se.runExitHandlersAndDeinitThread(F,N),k&&postMessage({cmd:"exit"}))},threadCancel:function(){Se.runExitHandlersAndDeinitThread(fi(),-1),postMessage({cmd:"cancelDone"})},terminateAllThreads:function(){for(var N in Se.pthreads){var F=Se.pthreads[N];F&&F.worker&&Se.returnWorkerToPool(F.worker)}Se.pthreads={};for(var B=0;B<Se.unusedWorkers.length;++B){var Z=Se.unusedWorkers[B];Z.terminate()}Se.unusedWorkers=[];for(var B=0;B<Se.runningWorkers.length;++B){var Z=Se.runningWorkers[B],F=Z.pthread;Se.freeThreadData(F),Z.terminate()}Se.runningWorkers=[]},freeThreadData:function(N){if(!!N){if(N.threadInfoStruct){var F=i()[N.threadInfoStruct+100>>2];i()[N.threadInfoStruct+100>>2]=0,Nu(F),Nu(N.threadInfoStruct)}N.threadInfoStruct=0,N.allocatedOwnStack&&N.stackBase&&Nu(N.stackBase),N.stackBase=0,N.worker&&(N.worker.pthread=null)}},returnWorkerToPool:function(N){Se.runWithoutMainThreadQueuedCalls(function(){delete Se.pthreads[N.pthread.threadInfoStruct],Se.unusedWorkers.push(N),Se.runningWorkers.splice(Se.runningWorkers.indexOf(N),1),Se.freeThreadData(N.pthread),N.pthread=void 0})},runWithoutMainThreadQueuedCalls:function(N){i()[l5>>2]=0;try{N()}finally{i()[l5>>2]=1}},receiveObjectTransfer:function(N){},loadWasmModuleToWorker:function(N,F){N.onmessage=function(B){var Z=B.data,me=Z.cmd;if(N.pthread&&(Se.currentProxiedOperationCallerThread=N.pthread.threadInfoStruct),Z.targetThread&&Z.targetThread!=fi()){var pe=Se.pthreads[Z.targetThread];pe?pe.worker.postMessage(B.data,Z.transferList):console.error('Internal error! Worker sent a message "'+me+'" to target pthread '+Z.targetThread+", but that thread no longer exists!"),Se.currentProxiedOperationCallerThread=void 0;return}if(me==="processQueuedMainThreadWork")Nm();else if(me==="spawnThread")$d(B.data);else if(me==="cleanupThread")A0(Z.thread);else if(me==="killThread")m0(Z.thread);else if(me==="cancelThread")g0(Z.thread);else if(me==="loaded")N.loaded=!0,F&&F(N),N.runPthread&&(N.runPthread(),delete N.runPthread);else if(me==="print")j("Thread "+Z.threadId+": "+Z.text);else if(me==="printErr")q("Thread "+Z.threadId+": "+Z.text);else if(me==="alert")alert("Thread "+Z.threadId+": "+Z.text);else if(me==="exit"){var fe=N.pthread&&Atomics.load(l(),N.pthread.threadInfoStruct+64>>2);fe&&Se.returnWorkerToPool(N)}else if(me==="exitProcess")try{LI(Z.returnCode)}catch(we){if(we instanceof Ru)return;throw we}else me==="cancelDone"?Se.returnWorkerToPool(N):me==="objectTransfer"?Se.receiveObjectTransfer(B.data):B.data.target==="setimmediate"?N.postMessage(B.data):q("worker sent an unknown command "+me);Se.currentProxiedOperationCallerThread=void 0},N.onerror=function(B){q("pthread sent an error! "+B.filename+":"+B.lineno+": "+B.message)},b&&(N.on("message",function(B){N.onmessage({data:B})}),N.on("error",function(B){N.onerror(B)}),N.on("exit",function(B){})),N.postMessage({cmd:"load",urlOrBlob:c.mainScriptUrlOrBlob||s,wasmMemory:J,wasmModule:ie})},allocateUnusedWorker:function(){var N=C("tfjs-backend-wasm-threaded-simd.worker.js");Se.unusedWorkers.push(new Worker(N))},getNewWorker:function(){return Se.unusedWorkers.length==0&&(Se.allocateUnusedWorker(),Se.loadWasmModuleToWorker(Se.unusedWorkers[0])),Se.unusedWorkers.length>0?Se.unusedWorkers.pop():null},busySpinWait:function(N){for(var F=performance.now()+N;performance.now()<F;);}};function y0(N,F){o5(N,F),mi(N)}c.establishStackSpace=y0;function x0(){return se}c.getNoExitRuntime=x0;function b0(N,F){return rs.get(N)(F)}c.invokeEntryPoint=b0;function v0(N,F,B,Z){Ar("Assertion failed: "+Fe(N)+", at: "+[F?Fe(F):"unknown filename",B,Z?Fe(Z):"unknown function"])}function w0(N,F){var B=_main(N,F)}var wa;b?wa=function(){var N=process.hrtime();return N[0]*1e3+N[1]/1e6}:k?wa=function(){return performance.now()-c.__performance_now_clock_drift}:typeof dateNow!="undefined"?wa=dateNow:wa=function(){return performance.now()};function k0(N){return i()[Qy()>>2]=N,N}function I0(N,F){if(k)return Pr(1,1,N,F)}function S0(N,F){if(N==F)postMessage({cmd:"processQueuedMainThreadWork"});else if(k)postMessage({targetThread:N,cmd:"processThreadQueue"});else{var B=Se.pthreads[N],Z=B&&B.worker;if(!Z)return;Z.postMessage({cmd:"processThreadQueue"})}return 1}function C0(){Ar()}function T0(N,F,B){var Z=D0(F,B);return f0[N].apply(null,Z)}function N0(N,F){}function E0(N,F,B){if(N<=0||N>a().length||N&!0)return-28;if(y){if(Atomics.load(i(),N>>2)!=F)return-6;for(var me=performance.now(),pe=me+B,fe=Atomics.exchange(i(),Ai>>2,N);;){if(me=performance.now(),me>pe)return fe=Atomics.exchange(i(),Ai>>2,0),-73;if(fe=Atomics.exchange(i(),Ai>>2,0),fe==0)break;if(Nm(),Atomics.load(i(),N>>2)!=F)return-6;fe=Atomics.exchange(i(),Ai>>2,N)}return 0}else{var Z=Atomics.wait(i(),N>>2,F,B);if(Z==="timed-out")return-73;if(Z==="not-equal")return-6;if(Z==="ok")return 0;throw"Atomics.wait returned an unexpected value "+Z}}function R0(N,F,B){o().copyWithin(N,F,F+B)}function _0(){return b?bi("os").cpus().length:navigator.hardwareConcurrency}function Pr(N,F){for(var B=arguments.length-2,Z=Eu(),me=B,pe=gi(me*8),fe=pe>>3,we=0;we<B;we++){var rt=arguments[2+we];u()[fe+we]=rt}var Kt=a5(N,me,pe,F);return mi(Z),Kt}var wu=[],ku=[];function D0(N,F){ku.length=0;var B;for(F>>=2;B=o()[N++];){var Z=B<105;Z&&F&1&&F++,ku.push(Z?u()[F++>>1]:i()[F]),++F}return ku}function $0(N,F,B){wu.length=F;for(var Z=B>>3,me=0;me<F;me++)wu[me]=u()[Z+me];var pe=N<0,fe=pe?f0[-N-1]:nm[N];return fe.apply(null,wu)}function F0(){return o().length}function O0(N){try{return J.grow(N-He.byteLength+65535>>>16),sn(J.buffer),1}catch(F){}}function P0(N){var F=F0();if(N<=F)return!1;var B=2147483648;if(N>B)return!1;for(var Z=1;Z<=4;Z*=2){var me=F*(1+.2/Z);me=Math.min(me,N+100663296);var pe=Math.min(B,it(Math.max(N,me),65536)),fe=O0(pe);if(fe)return!0}return!1}var Le={inEventHandler:0,removeAllEventListeners:function(){for(var N=Le.eventHandlers.length-1;N>=0;--N)Le._removeHandler(N);Le.eventHandlers=[],Le.deferredCalls=[]},registerRemoveEventListeners:function(){Le.removeEventListenersRegistered||(Fr.push(Le.removeAllEventListeners),Le.removeEventListenersRegistered=!0)},deferredCalls:[],deferCall:function(N,F,B){function Z(fe,we){if(fe.length!=we.length)return!1;for(var rt in fe)if(fe[rt]!=we[rt])return!1;return!0}for(var me in Le.deferredCalls){var pe=Le.deferredCalls[me];if(pe.targetFunction==N&&Z(pe.argsList,B))return}Le.deferredCalls.push({targetFunction:N,precedence:F,argsList:B}),Le.deferredCalls.sort(function(fe,we){return fe.precedence<we.precedence})},removeDeferredCalls:function(N){for(var F=0;F<Le.deferredCalls.length;++F)Le.deferredCalls[F].targetFunction==N&&(Le.deferredCalls.splice(F,1),--F)},canPerformEventHandlerRequests:function(){return Le.inEventHandler&&Le.currentEventHandler.allowsDeferredCalls},runDeferredCalls:function(){if(!!Le.canPerformEventHandlerRequests())for(var N=0;N<Le.deferredCalls.length;++N){var F=Le.deferredCalls[N];Le.deferredCalls.splice(N,1),--N,F.targetFunction.apply(null,F.argsList)}},eventHandlers:[],removeAllHandlersOnTarget:function(N,F){for(var B=0;B<Le.eventHandlers.length;++B)Le.eventHandlers[B].target==N&&(!F||F==Le.eventHandlers[B].eventTypeString)&&Le._removeHandler(B--)},_removeHandler:function(N){var F=Le.eventHandlers[N];F.target.removeEventListener(F.eventTypeString,F.eventListenerFunc,F.useCapture),Le.eventHandlers.splice(N,1)},registerOrRemoveHandler:function(N){var F=function(me){++Le.inEventHandler,Le.currentEventHandler=N,Le.runDeferredCalls(),N.handlerFunc(me),Le.runDeferredCalls(),--Le.inEventHandler};if(N.callbackfunc)N.eventListenerFunc=F,N.target.addEventListener(N.eventTypeString,F,N.useCapture),Le.eventHandlers.push(N),Le.registerRemoveEventListeners();else for(var B=0;B<Le.eventHandlers.length;++B)Le.eventHandlers[B].target==N.target&&Le.eventHandlers[B].eventTypeString==N.eventTypeString&&Le._removeHandler(B--)},queueEventHandlerOnThread_iiii:function(N,F,B,Z,me){var pe=Eu(),fe=gi(12);i()[fe>>2]=B,i()[fe+4>>2]=Z,i()[fe+8>>2]=me,Em(0,N,637534208,F,Z,fe),mi(pe)},getTargetThreadForEventCallback:function(N){switch(N){case 1:return 0;case 2:return Se.currentProxiedOperationCallerThread;default:return N}},getNodeNameForTarget:function(N){return N?N==window?"#window":N==screen?"#screen":N&&N.nodeName?N.nodeName:"":""},fullscreenEnabled:function(){return document.fullscreenEnabled||document.webkitFullscreenEnabled}};function M0(N){var F=st(N)+1,B=ka(F);return nt(N,B,F),B}function z0(N,F,B,Z){var me=Eu(),pe=gi(12),fe=0;F&&(fe=M0(F)),i()[pe>>2]=fe,i()[pe+4>>2]=B,i()[pe+8>>2]=Z,Em(0,N,657457152,0,fe,pe),mi(me)}function L0(N,F,B,Z){F=F?Fe(F):"",z0(N,F,B,Z)}function B0(N){return N>2?Fe(N):N}var W0=[0,typeof document!="undefined"?document:0,typeof window!="undefined"?window:0];function V0(N){N=B0(N);var F=W0[N]||(typeof document!="undefined"?document.querySelector(N):void 0);return F}function Iu(N){return V0(N)}function Nd(N,F,B){var Z=Iu(N);if(!Z)return-4;if(Z.canvasSharedPtr&&(i()[Z.canvasSharedPtr>>2]=F,i()[Z.canvasSharedPtr+4>>2]=B),Z.offscreenCanvas||!Z.controlTransferredOffscreen){Z.offscreenCanvas&&(Z=Z.offscreenCanvas);var me=!1;if(Z.GLctxObject&&Z.GLctxObject.GLctx){var pe=Z.GLctxObject.GLctx.getParameter(2978);me=pe[0]===0&&pe[1]===0&&pe[2]===Z.width&&pe[3]===Z.height}Z.width=F,Z.height=B,me&&Z.GLctxObject.GLctx.viewport(0,0,F,B)}else if(Z.canvasSharedPtr){var fe=i()[Z.canvasSharedPtr+8>>2];return L0(fe,N,F,B),1}else return-4;return 0}function Ed(N,F,B){return k?Pr(2,1,N,F,B):Nd(N,F,B)}function U0(N,F,B){var Z=Iu(N);return Z?Nd(N,F,B):Ed(N,F,B)}function H0(N){}function G0(N,F){}function j0(N){var F=N.getExtension("ANGLE_instanced_arrays");if(F)return N.vertexAttribDivisor=function(B,Z){F.vertexAttribDivisorANGLE(B,Z)},N.drawArraysInstanced=function(B,Z,me,pe){F.drawArraysInstancedANGLE(B,Z,me,pe)},N.drawElementsInstanced=function(B,Z,me,pe,fe){F.drawElementsInstancedANGLE(B,Z,me,pe,fe)},1}function q0(N){var F=N.getExtension("OES_vertex_array_object");if(F)return N.createVertexArray=function(){return F.createVertexArrayOES()},N.deleteVertexArray=function(B){F.deleteVertexArrayOES(B)},N.bindVertexArray=function(B){F.bindVertexArrayOES(B)},N.isVertexArray=function(B){return F.isVertexArrayOES(B)},1}function X0(N){var F=N.getExtension("WEBGL_draw_buffers");if(F)return N.drawBuffers=function(B,Z){F.drawBuffersWEBGL(B,Z)},1}function K0(N){return!!(N.multiDrawWebgl=N.getExtension("WEBGL_multi_draw"))}var tt={counter:1,buffers:[],programs:[],framebuffers:[],renderbuffers:[],textures:[],uniforms:[],shaders:[],vaos:[],contexts:{},offscreenCanvases:{},timerQueriesEXT:[],programInfos:{},stringCache:{},unpackAlignment:4,recordError:function(F){tt.lastError||(tt.lastError=F)},getNewId:function(N){for(var F=tt.counter++,B=N.length;B<F;B++)N[B]=null;return F},getSource:function(N,F,B,Z){for(var me="",pe=0;pe<F;++pe){var fe=Z?i()[Z+pe*4>>2]:-1;me+=Fe(i()[B+pe*4>>2],fe<0?void 0:fe)}return me},createContext:function(N,F){var B=N.getContext("webgl",F);if(!B)return 0;var Z=tt.registerContext(B,F);return Z},registerContext:function(N,F){var B=ka(8);i()[B+4>>2]=fi();var Z={handle:B,attributes:F,version:F.majorVersion,GLctx:N};return N.canvas&&(N.canvas.GLctxObject=Z),tt.contexts[B]=Z,(typeof F.enableExtensionsByDefault=="undefined"||F.enableExtensionsByDefault)&&tt.initExtensions(Z),B},makeContextCurrent:function(N){return tt.currentContext=tt.contexts[N],c.ctx=Mr=tt.currentContext&&tt.currentContext.GLctx,!(N&&!Mr)},getContext:function(N){return tt.contexts[N]},deleteContext:function(N){tt.currentContext===tt.contexts[N]&&(tt.currentContext=null),typeof Le=="object"&&Le.removeAllHandlersOnTarget(tt.contexts[N].GLctx.canvas),tt.contexts[N]&&tt.contexts[N].GLctx.canvas&&(tt.contexts[N].GLctx.canvas.GLctxObject=void 0),Nu(tt.contexts[N].handle),tt.contexts[N]=null},initExtensions:function(N){if(N||(N=tt.currentContext),!N.initExtensionsDone){N.initExtensionsDone=!0;var F=N.GLctx;j0(F),q0(F),X0(F),F.disjointTimerQueryExt=F.getExtension("EXT_disjoint_timer_query"),K0(F);var B=F.getSupportedExtensions()||[];B.forEach(function(Z){Z.indexOf("lose_context")<0&&Z.indexOf("debug")<0&&F.getExtension(Z)})}},populateUniformTable:function(N){for(var F=tt.programs[N],B=tt.programInfos[N]={uniforms:{},maxUniformLength:0,maxAttributeLength:-1,maxUniformBlockNameLength:-1},Z=B.uniforms,me=Mr.getProgramParameter(F,35718),pe=0;pe<me;++pe){var fe=Mr.getActiveUniform(F,pe),we=fe.name;B.maxUniformLength=Math.max(B.maxUniformLength,we.length+1),we.slice(-1)=="]"&&(we=we.slice(0,we.lastIndexOf("[")));var rt=Mr.getUniformLocation(F,we);if(rt){var Kt=tt.getNewId(tt.uniforms);Z[we]=[fe.size,Kt],tt.uniforms[Kt]=rt;for(var Vt=1;Vt<fe.size;++Vt){var Lr=we+"["+Vt+"]";rt=Mr.getUniformLocation(F,Lr),Kt=tt.getNewId(tt.uniforms),tt.uniforms[Kt]=rt}}}}},Z0=["default","low-power","high-performance"];function Y0(N,F){var B=F>>2,Z=i()[B+(24>>2)],me={alpha:!!i()[B+(0>>2)],depth:!!i()[B+(4>>2)],stencil:!!i()[B+(8>>2)],antialias:!!i()[B+(12>>2)],premultipliedAlpha:!!i()[B+(16>>2)],preserveDrawingBuffer:!!i()[B+(20>>2)],powerPreference:Z0[Z],failIfMajorPerformanceCaveat:!!i()[B+(28>>2)],majorVersion:i()[B+(32>>2)],minorVersion:i()[B+(36>>2)],enableExtensionsByDefault:i()[B+(40>>2)],explicitSwapControl:i()[B+(44>>2)],proxyContextToMainThread:i()[B+(48>>2)],renderViaOffscreenBackBuffer:i()[B+(52>>2)]},pe=Iu(N);if(!pe||me.explicitSwapControl)return 0;var fe=tt.createContext(pe,me);return fe}function J0(N,F){return Y0(N,F)}var hi={mappings:{},buffers:[null,[],[]],printChar:function(N,F){var B=hi.buffers[N];F===0||F===10?((N===1?j:q)(Me(B,0)),B.length=0):B.push(F)},varargs:void 0,get:function(){hi.varargs+=4;var N=i()[hi.varargs-4>>2];return N},getStr:function(N){var F=Fe(N);return F},get64:function(N,F){return N}};function Rd(N){return k?Pr(3,1,N):0}function _d(N,F,B,Z,me){if(k)return Pr(4,1,N,F,B,Z,me)}function Dd(N,F,B,Z){if(k)return Pr(5,1,N,F,B,Z);for(var me=0,pe=0;pe<B;pe++){for(var fe=i()[F+pe*8>>2],we=i()[F+(pe*8+4)>>2],rt=0;rt<we;rt++)hi.printChar(N,o()[fe+rt]);me+=we}return i()[Z>>2]=me,0}function Q0(N){var F=Se.threadExitHandlers.pop();N&&F()}function em(N,F){Se.threadExitHandlers.push(function(){rs.get(N)(F)})}function $d(N){if(k)throw"Internal Error! spawnThread() can only ever be called from main application thread!";var F=Se.getNewWorker();if(F.pthread!==void 0)throw"Internal error!";if(!N.pthread_ptr)throw"Internal error, no pthread ptr!";Se.runningWorkers.push(F);for(var B=ka(128*4),Z=0;Z<128;++Z)i()[B+Z*4>>2]=0;var me=N.stackBase+N.stackSize,pe=Se.pthreads[N.pthread_ptr]={worker:F,stackBase:N.stackBase,stackSize:N.stackSize,allocatedOwnStack:N.allocatedOwnStack,threadInfoStruct:N.pthread_ptr},fe=pe.threadInfoStruct>>2;Atomics.store(l(),fe+(64>>2),N.detached),Atomics.store(l(),fe+(100>>2),B),Atomics.store(l(),fe+(40>>2),pe.threadInfoStruct),Atomics.store(l(),fe+(80>>2),N.stackSize),Atomics.store(l(),fe+(76>>2),me),Atomics.store(l(),fe+(104>>2),N.stackSize),Atomics.store(l(),fe+(104+8>>2),me),Atomics.store(l(),fe+(104+12>>2),N.detached);var we=e5(),rt=we+40;Atomics.store(l(),fe+(172>>2),rt),F.pthread=pe;var Kt={cmd:"run",start_routine:N.startRoutine,arg:N.arg,threadInfoStruct:N.pthread_ptr,stackBase:N.stackBase,stackSize:N.stackSize};F.runPthread=function(){Kt.time=performance.now(),F.postMessage(Kt,N.transferList)},F.loaded&&(F.runPthread(),delete F.runPthread)}function tm(N,F,B,Z){if(typeof SharedArrayBuffer=="undefined")return q("Current environment does not support SharedArrayBuffer, pthreads are not available!"),6;if(!N)return q("pthread_create called with a null thread pointer!"),28;var me=[],pe=0;if(k&&(me.length===0||pe))return r5(687865856,N,F,B,Z);if(pe)return pe;var fe=0,we=0,rt=0;F&&F!=-1?(fe=i()[F>>2],fe+=81920,we=i()[F+8>>2],rt=i()[F+12>>2]!==0):fe=2097152;var Kt=we==0;Kt?we=i5(16,fe):(we-=fe,Ae(we>0));for(var Vt=ka(228),Lr=0;Lr<228>>2;++Lr)l()[(Vt>>2)+Lr]=0;i()[N>>2]=Vt,i()[Vt+12>>2]=Vt;var yi=Vt+152;i()[yi>>2]=yi;var fn={stackBase:we,stackSize:fe,allocatedOwnStack:Kt,detached:rt,startRoutine:B,pthread_ptr:Vt,arg:Z,transferList:me};return k?(fn.cmd="spawnThread",postMessage(fn,me)):$d(fn),0}function Fd(N){if(k)return Pr(6,1,N);switch(N){case 30:return 16384;case 85:var F=2147483648;return F/16384;case 132:case 133:case 12:case 137:case 138:case 15:case 235:case 16:case 17:case 18:case 19:case 20:case 149:case 13:case 10:case 236:case 153:case 9:case 21:case 22:case 159:case 154:case 14:case 77:case 78:case 139:case 82:case 68:case 67:case 164:case 11:case 29:case 47:case 48:case 95:case 52:case 51:case 46:return 200809;case 27:case 246:case 127:case 128:case 23:case 24:case 160:case 161:case 181:case 182:case 242:case 183:case 184:case 243:case 244:case 245:case 165:case 178:case 179:case 49:case 50:case 168:case 169:case 175:case 170:case 171:case 172:case 97:case 76:case 32:case 173:case 35:case 80:case 81:case 79:return-1;case 176:case 177:case 7:case 155:case 8:case 157:case 125:case 126:case 92:case 93:case 129:case 130:case 131:case 94:case 91:return 1;case 74:case 60:case 69:case 70:case 4:return 1024;case 31:case 42:case 72:return 32;case 87:case 26:case 33:return 2147483647;case 34:case 1:return 47839;case 38:case 36:return 99;case 43:case 37:return 2048;case 0:return 2097152;case 3:return 65536;case 28:return 32768;case 44:return 32767;case 75:return 16384;case 39:return 1e3;case 89:return 700;case 71:return 256;case 40:return 255;case 2:return 100;case 180:return 64;case 25:return 20;case 5:return 16;case 6:return 6;case 73:return 4;case 84:return typeof navigator=="object"&&navigator.hardwareConcurrency||1}return k0(28),-1}k||Se.initMainThreadBlock();var Mr,nm=[null,I0,Ed,Rd,_d,Dd,Fd],sm={e:v0,r:w0,x:S0,b:C0,y:T0,j:N0,c:E0,d:vu,f:wa,p:R0,z:_0,u:$0,q:P0,v:U0,i:H0,t:G0,w:J0,m:Rd,n:_d,g:Dd,o:Td,a:J||c.wasmMemory,k:Q0,l:em,h:tm,s:Fd},Jy=p0(),Od=c.___wasm_call_ctors=function(){return(Od=c.___wasm_call_ctors=c.asm.A).apply(null,arguments)},rm=c._init=function(){return(rm=c._init=c.asm.B).apply(null,arguments)},am=c._register_tensor=function(){return(am=c._register_tensor=c.asm.C).apply(null,arguments)},om=c._dispose_data=function(){return(om=c._dispose_data=c.asm.D).apply(null,arguments)},im=c._dispose=function(){return(im=c._dispose=c.asm.E).apply(null,arguments)},lm=c._Abs=function(){return(lm=c._Abs=c.asm.G).apply(null,arguments)},um=c._Add=function(){return(um=c._Add=c.asm.H).apply(null,arguments)},cm=c._AddN=function(){return(cm=c._AddN=c.asm.I).apply(null,arguments)},dm=c._All=function(){return(dm=c._All=c.asm.J).apply(null,arguments)},hm=c._Any=function(){return(hm=c._Any=c.asm.K).apply(null,arguments)},pm=c._ArgMax=function(){return(pm=c._ArgMax=c.asm.L).apply(null,arguments)},fm=c._AvgPool=function(){return(fm=c._AvgPool=c.asm.M).apply(null,arguments)},mm=c._BatchMatMul=function(){return(mm=c._BatchMatMul=c.asm.N).apply(null,arguments)},gm=c._Ceil=function(){return(gm=c._Ceil=c.asm.O).apply(null,arguments)},Am=c._ClipByValue=function(){return(Am=c._ClipByValue=c.asm.P).apply(null,arguments)},ym=c._Conv2D=function(){return(ym=c._Conv2D=c.asm.Q).apply(null,arguments)},xm=c._Conv2DBackpropInput=function(){return(xm=c._Conv2DBackpropInput=c.asm.R).apply(null,arguments)},bm=c._Cos=function(){return(bm=c._Cos=c.asm.S).apply(null,arguments)},vm=c._Cosh=function(){return(vm=c._Cosh=c.asm.T).apply(null,arguments)},wm=c._CropAndResize=function(){return(wm=c._CropAndResize=c.asm.U).apply(null,arguments)},km=c._Cumsum=function(){return(km=c._Cumsum=c.asm.V).apply(null,arguments)},Im=c._DepthToSpace=function(){return(Im=c._DepthToSpace=c.asm.W).apply(null,arguments)},Sm=c._DepthwiseConv2dNative=function(){return(Sm=c._DepthwiseConv2dNative=c.asm.X).apply(null,arguments)},Cm=c._Elu=function(){return(Cm=c._Elu=c.asm.Y).apply(null,arguments)},Pd=c._Equal=function(){return(Pd=c._Equal=c.asm.Z).apply(null,arguments)},Md=c._Exp=function(){return(Md=c._Exp=c.asm._).apply(null,arguments)},zd=c._FlipLeftRight=function(){return(zd=c._FlipLeftRight=c.asm.$).apply(null,arguments)},Su=c._Floor=function(){return(Su=c._Floor=c.asm.aa).apply(null,arguments)},pi=c._FloorDiv=function(){return(pi=c._FloorDiv=c.asm.ba).apply(null,arguments)},Tm=c._FusedBatchNorm=function(){return(Tm=c._FusedBatchNorm=c.asm.ca).apply(null,arguments)},Cu=c._FusedConv2D=function(){return(Cu=c._FusedConv2D=c.asm.da).apply(null,arguments)},Y=c._FusedDepthwiseConv2D=function(){return(Y=c._FusedDepthwiseConv2D=c.asm.ea).apply(null,arguments)},re=c._Gather=function(){return(re=c._Gather=c.asm.fa).apply(null,arguments)},xe=c._GatherNd=function(){return(xe=c._GatherNd=c.asm.ga).apply(null,arguments)},Qe=c._Greater=function(){return(Qe=c._Greater=c.asm.ha).apply(null,arguments)},Et=c._GreaterEqual=function(){return(Et=c._GreaterEqual=c.asm.ia).apply(null,arguments)},bt=c._LeakyRelu=function(){return(bt=c._LeakyRelu=c.asm.ja).apply(null,arguments)},je=c._Less=function(){return(je=c._Less=c.asm.ka).apply(null,arguments)},qe=c._LessEqual=function(){return(qe=c._LessEqual=c.asm.la).apply(null,arguments)},rn=c._Log=function(){return(rn=c._Log=c.asm.ma).apply(null,arguments)},yr=c._LogicalAnd=function(){return(yr=c._LogicalAnd=c.asm.na).apply(null,arguments)},xr=c._Max=function(){return(xr=c._Max=c.asm.oa).apply(null,arguments)},Ld=c._MaxPool=function(){return(Ld=c._MaxPool=c.asm.pa).apply(null,arguments)},Tu=c._Maximum=function(){return(Tu=c._Maximum=c.asm.qa).apply(null,arguments)},Un=c._Mean=function(){return(Un=c._Mean=c.asm.ra).apply(null,arguments)},zr=c._Min=function(){return(zr=c._Min=c.asm.sa).apply(null,arguments)},Bd=c._Minimum=function(){return(Bd=c._Minimum=c.asm.ta).apply(null,arguments)},J8=c._MirrorPad=function(){return(J8=c._MirrorPad=c.asm.ua).apply(null,arguments)},Q8=c._Multiply=function(){return(Q8=c._Multiply=c.asm.va).apply(null,arguments)},eI=c._Neg=function(){return(eI=c._Neg=c.asm.wa).apply(null,arguments)},tI=c._NonMaxSuppressionV3=function(){return(tI=c._NonMaxSuppressionV3=c.asm.xa).apply(null,arguments)},nI=c._NonMaxSuppressionV4=function(){return(nI=c._NonMaxSuppressionV4=c.asm.ya).apply(null,arguments)},sI=c._NonMaxSuppressionV5=function(){return(sI=c._NonMaxSuppressionV5=c.asm.za).apply(null,arguments)},rI=c._NotEqual=function(){return(rI=c._NotEqual=c.asm.Aa).apply(null,arguments)},aI=c._OneHot=function(){return(aI=c._OneHot=c.asm.Ba).apply(null,arguments)},oI=c._PadV2=function(){return(oI=c._PadV2=c.asm.Ca).apply(null,arguments)},iI=c._Pow=function(){return(iI=c._Pow=c.asm.Da).apply(null,arguments)},lI=c._Prelu=function(){return(lI=c._Prelu=c.asm.Ea).apply(null,arguments)},uI=c._Prod=function(){return(uI=c._Prod=c.asm.Fa).apply(null,arguments)},cI=c._RealDiv=function(){return(cI=c._RealDiv=c.asm.Ga).apply(null,arguments)},dI=c._Relu=function(){return(dI=c._Relu=c.asm.Ha).apply(null,arguments)},hI=c._Relu6=function(){return(hI=c._Relu6=c.asm.Ia).apply(null,arguments)},pI=c._ResizeBilinear=function(){return(pI=c._ResizeBilinear=c.asm.Ja).apply(null,arguments)},fI=c._Reverse=function(){return(fI=c._Reverse=c.asm.Ka).apply(null,arguments)},mI=c._RotateWithOffset=function(){return(mI=c._RotateWithOffset=c.asm.La).apply(null,arguments)},gI=c._Round=function(){return(gI=c._Round=c.asm.Ma).apply(null,arguments)},AI=c._Rsqrt=function(){return(AI=c._Rsqrt=c.asm.Na).apply(null,arguments)},yI=c._ScatterNd=function(){return(yI=c._ScatterNd=c.asm.Oa).apply(null,arguments)},xI=c._SelectV2=function(){return(xI=c._SelectV2=c.asm.Pa).apply(null,arguments)},bI=c._Sigmoid=function(){return(bI=c._Sigmoid=c.asm.Qa).apply(null,arguments)},vI=c._Sin=function(){return(vI=c._Sin=c.asm.Ra).apply(null,arguments)},wI=c._Softmax=function(){return(wI=c._Softmax=c.asm.Sa).apply(null,arguments)},kI=c._Sqrt=function(){return(kI=c._Sqrt=c.asm.Ta).apply(null,arguments)},II=c._Square=function(){return(II=c._Square=c.asm.Ua).apply(null,arguments)},SI=c._SquaredDifference=function(){return(SI=c._SquaredDifference=c.asm.Va).apply(null,arguments)},CI=c._Step=function(){return(CI=c._Step=c.asm.Wa).apply(null,arguments)},TI=c._StridedSlice=function(){return(TI=c._StridedSlice=c.asm.Xa).apply(null,arguments)},NI=c._Sub=function(){return(NI=c._Sub=c.asm.Ya).apply(null,arguments)},EI=c._Sum=function(){return(EI=c._Sum=c.asm.Za).apply(null,arguments)},RI=c._Tan=function(){return(RI=c._Tan=c.asm._a).apply(null,arguments)},_I=c._Tanh=function(){return(_I=c._Tanh=c.asm.$a).apply(null,arguments)},DI=c._Tile=function(){return(DI=c._Tile=c.asm.ab).apply(null,arguments)},$I=c._TopK=function(){return($I=c._TopK=c.asm.bb).apply(null,arguments)},FI=c._Transform=function(){return(FI=c._Transform=c.asm.cb).apply(null,arguments)},OI=c._Transpose=function(){return(OI=c._Transpose=c.asm.db).apply(null,arguments)},PI=c.__FusedMatMul=function(){return(PI=c.__FusedMatMul=c.asm.eb).apply(null,arguments)},ka=c._malloc=function(){return(ka=c._malloc=c.asm.fb).apply(null,arguments)},Nu=c._free=function(){return(Nu=c._free=c.asm.gb).apply(null,arguments)},Qy=c.___errno_location=function(){return(Qy=c.___errno_location=c.asm.hb).apply(null,arguments)},e5=c._emscripten_get_global_libc=function(){return(e5=c._emscripten_get_global_libc=c.asm.ib).apply(null,arguments)},fi=c._pthread_self=function(){return(fi=c._pthread_self=c.asm.jb).apply(null,arguments)},t5=c.___pthread_tsd_run_dtors=function(){return(t5=c.___pthread_tsd_run_dtors=c.asm.kb).apply(null,arguments)},Nm=c._emscripten_main_thread_process_queued_calls=function(){return(Nm=c._emscripten_main_thread_process_queued_calls=c.asm.lb).apply(null,arguments)},MI=c._emscripten_current_thread_process_queued_calls=function(){return(MI=c._emscripten_current_thread_process_queued_calls=c.asm.mb).apply(null,arguments)},n5=c._emscripten_register_main_browser_thread_id=function(){return(n5=c._emscripten_register_main_browser_thread_id=c.asm.nb).apply(null,arguments)},s5=c.__emscripten_do_dispatch_to_thread=function(){return(s5=c.__emscripten_do_dispatch_to_thread=c.asm.ob).apply(null,arguments)},r5=c._emscripten_sync_run_in_main_thread_4=function(){return(r5=c._emscripten_sync_run_in_main_thread_4=c.asm.pb).apply(null,arguments)},a5=c._emscripten_run_in_main_runtime_thread_js=function(){return(a5=c._emscripten_run_in_main_runtime_thread_js=c.asm.qb).apply(null,arguments)},Em=c.__emscripten_call_on_thread=function(){return(Em=c.__emscripten_call_on_thread=c.asm.rb).apply(null,arguments)},zI=c._emscripten_tls_init=function(){return(zI=c._emscripten_tls_init=c.asm.sb).apply(null,arguments)},Rm=c.__emscripten_thread_init=function(){return(Rm=c.__emscripten_thread_init=c.asm.tb).apply(null,arguments)},Eu=c.stackSave=function(){return(Eu=c.stackSave=c.asm.ub).apply(null,arguments)},mi=c.stackRestore=function(){return(mi=c.stackRestore=c.asm.vb).apply(null,arguments)},gi=c.stackAlloc=function(){return(gi=c.stackAlloc=c.asm.wb).apply(null,arguments)},o5=c._emscripten_stack_set_limits=function(){return(o5=c._emscripten_stack_set_limits=c.asm.xb).apply(null,arguments)},i5=c._memalign=function(){return(i5=c._memalign=c.asm.yb).apply(null,arguments)},l5=c.__emscripten_allow_main_runtime_queued_calls=10016,Ai=c.__emscripten_main_thread_futex=11652;c.cwrap=De,c.PThread=Se,c.PThread=Se,c.wasmMemory=J,c.ExitStatus=Ru;var Wd;function Ru(N){this.name="ExitStatus",this.message="Program terminated with exit("+N+")",this.status=N}va=function N(){Wd||_m(),Wd||(va=N)};function _m(N){if(N=N||m,gr>0)return;if(k){d(c),bu(),postMessage({cmd:"loaded"});return}if(o0(),gr>0)return;function F(){Wd||(Wd=!0,c.calledRun=!0,!le&&(bu(),i0(),d(c),c.onRuntimeInitialized&&c.onRuntimeInitialized(),En()))}c.setStatus?(c.setStatus("Running..."),setTimeout(function(){setTimeout(function(){c.setStatus("")},1),F()},1)):F()}c.run=_m;function LI(N,F){if(!(F&&se&&N===0)){if(!F&&k)throw postMessage({cmd:"exitProcess",returnCode:N}),new Ru(N);se||(Se.terminateAllThreads(),he=N,vd(),c.onExit&&c.onExit(N),le=!0),A(N,new Ru(N))}}if(c.preInit)for(typeof c.preInit=="function"&&(c.preInit=[c.preInit]);c.preInit.length>0;)c.preInit.pop()();return k&&(se=!1,Se.initWorker()),_m(),r.ready}}();typeof e=="object"&&typeof t=="object"?t.exports=n:typeof define=="function"&&define.amd?define([],function(){return n}):typeof e=="object"&&(e.WasmBackendModuleThreadedSimd=n)}}),hS=vt({"node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.9.0_@tensorflow+tfjs-core@3.9.0/node_modules/@tensorflow/tfjs-backend-wasm/wasm-out/tfjs-backend-wasm.js"(e,t){var n=function(){var s=typeof document!="undefined"&&document.currentScript?document.currentScript.src:void 0;return typeof __filename!="undefined"&&(s=s||__filename),function(r){r=r||{};var a=typeof r!="undefined"?r:{},o,i;a.ready=new Promise(function(Y,re){o=Y,i=re});var l={},u;for(u in a)a.hasOwnProperty(u)&&(l[u]=a[u]);var c=[],d="./this.program",h=function(Y,re){throw re},p=!1,f=!1,m=!1,g=!1;p=typeof window=="object",f=typeof importScripts=="function",m=typeof process=="object"&&typeof process.versions=="object"&&typeof process.versions.node=="string",g=!p&&!m&&!f;var A="";function y(Y){return a.locateFile?a.locateFile(Y,A):A+Y}var x,b,v,k,S,C;m?(f?A=_u().dirname(A)+"/":A=__dirname+"/",x=function(re,xe){return S||(S=bi("fs")),C||(C=_u()),re=C.normalize(re),S.readFileSync(re,xe?null:"utf8")},v=function(re){var xe=x(re,!0);return xe.buffer||(xe=new Uint8Array(xe)),j(xe.buffer),xe},process.argv.length>1&&(d=process.argv[1].replace(/\\/g,"/")),c=process.argv.slice(2),process.on("uncaughtException",function(Y){if(!(Y instanceof Tm))throw Y}),process.on("unhandledRejection",Zs),h=function(Y){process.exit(Y)},a.inspect=function(){return"[Emscripten Module object]"}):g?(typeof read!="undefined"&&(x=function(re){return read(re)}),v=function(re){var xe;return typeof readbuffer=="function"?new Uint8Array(readbuffer(re)):(xe=read(re,"binary"),j(typeof xe=="object"),xe)},typeof scriptArgs!="undefined"?c=scriptArgs:typeof arguments!="undefined"&&(c=arguments),typeof quit=="function"&&(h=function(Y){quit(Y)}),typeof print!="undefined"&&(typeof console=="undefined"&&(console={}),console.log=print,console.warn=console.error=typeof printErr!="undefined"?printErr:print)):(p||f)&&(f?A=self.location.href:typeof document!="undefined"&&document.currentScript&&(A=document.currentScript.src),s&&(A=s),A.indexOf("blob:")!==0?A=A.substr(0,A.lastIndexOf("/")+1):A="",x=function(Y){var re=new XMLHttpRequest;return re.open("GET",Y,!1),re.send(null),re.responseText},f&&(v=function(Y){var re=new XMLHttpRequest;return re.open("GET",Y,!1),re.responseType="arraybuffer",re.send(null),new Uint8Array(re.response)}),b=function(Y,re,xe){var Qe=new XMLHttpRequest;Qe.open("GET",Y,!0),Qe.responseType="arraybuffer",Qe.onload=function(){if(Qe.status==200||Qe.status==0&&Qe.response){re(Qe.response);return}xe()},Qe.onerror=xe,Qe.send(null)},k=function(Y){document.title=Y});var _=a.print||console.log.bind(console),O=a.printErr||console.warn.bind(console);for(u in l)l.hasOwnProperty(u)&&(a[u]=l[u]);l=null,a.arguments&&(c=a.arguments),a.thisProgram&&(d=a.thisProgram),a.quit&&(h=a.quit);var E;a.wasmBinary&&(E=a.wasmBinary);var R=a.noExitRuntime||!0;typeof WebAssembly!="object"&&Zs("no native wasm support detected");var T,P=!1,V;function j(Y,re){Y||Zs("Assertion failed: "+re)}function q(Y){var re=a["_"+Y];return j(re,"Cannot call unknown function "+Y+", make sure it is exported"),re}function X(Y,re,xe,Qe,Et){var bt={string:function(Un){var zr=0;if(Un!=null&&Un!==0){var Bd=(Un.length<<2)+1;zr=Su(Bd),ie(Un,zr,Bd)}return zr},array:function(Un){var zr=Su(Un.length);return le(Un,zr),zr}};function je(Un){return re==="string"?se(Un):re==="boolean"?Boolean(Un):Un}var qe=q(Y),rn=[],yr=0;if(Qe)for(var xr=0;xr<Qe.length;xr++){var Ld=bt[xe[xr]];Ld?(yr===0&&(yr=Md()),rn[xr]=Ld(Qe[xr])):rn[xr]=Qe[xr]}var Tu=qe.apply(null,rn);return Tu=je(Tu),yr!==0&&zd(yr),Tu}function ee(Y,re,xe,Qe){xe=xe||[];var Et=xe.every(function(je){return je==="number"}),bt=re!=="string";return bt&&Et&&!Qe?q(Y):function(){return X(Y,re,xe,arguments,Qe)}}var te=typeof TextDecoder!="undefined"?new TextDecoder("utf8"):void 0;function ne(Y,re,xe){for(var Qe=re+xe,Et=re;Y[Et]&&!(Et>=Qe);)++Et;if(Et-re>16&&Y.subarray&&te)return te.decode(Y.subarray(re,Et));for(var bt="";re<Et;){var je=Y[re++];if(!(je&128)){bt+=String.fromCharCode(je);continue}var qe=Y[re++]&63;if((je&224)==192){bt+=String.fromCharCode((je&31)<<6|qe);continue}var rn=Y[re++]&63;if((je&240)==224?je=(je&15)<<12|qe<<6|rn:je=(je&7)<<18|qe<<12|rn<<6|Y[re++]&63,je<65536)bt+=String.fromCharCode(je);else{var yr=je-65536;bt+=String.fromCharCode(55296|yr>>10,56320|yr&1023)}}return bt}function se(Y,re){return Y?ne(Te,Y,re):""}function J(Y,re,xe,Qe){if(!(Qe>0))return 0;for(var Et=xe,bt=xe+Qe-1,je=0;je<Y.length;++je){var qe=Y.charCodeAt(je);if(qe>=55296&&qe<=57343){var rn=Y.charCodeAt(++je);qe=65536+((qe&1023)<<10)|rn&1023}if(qe<=127){if(xe>=bt)break;re[xe++]=qe}else if(qe<=2047){if(xe+1>=bt)break;re[xe++]=192|qe>>6,re[xe++]=128|qe&63}else if(qe<=65535){if(xe+2>=bt)break;re[xe++]=224|qe>>12,re[xe++]=128|qe>>6&63,re[xe++]=128|qe&63}else{if(xe+3>=bt)break;re[xe++]=240|qe>>18,re[xe++]=128|qe>>12&63,re[xe++]=128|qe>>6&63,re[xe++]=128|qe&63}}return re[xe]=0,xe-Et}function ie(Y,re,xe){return J(Y,Te,re,xe)}function le(Y,re){Ce.set(Y,re)}function he(Y,re){return Y%re>0&&(Y+=re-Y%re),Y}var Ae,Ce,Te,De,Me,Fe,ut,nt,st;function et(Y){Ae=Y,a.HEAP8=Ce=new Int8Array(Y),a.HEAP16=De=new Int16Array(Y),a.HEAP32=Fe=new Int32Array(Y),a.HEAPU8=Te=new Uint8Array(Y),a.HEAPU16=Me=new Uint16Array(Y),a.HEAPU32=ut=new Uint32Array(Y),a.HEAPF32=nt=new Float32Array(Y),a.HEAPF64=st=new Float64Array(Y)}var it=a.INITIAL_MEMORY||16777216,He,Nn=[],St=[],Wn=[],nn=[],ks=!1;St.push({func:function(){Td()}});function pn(){if(a.preRun)for(typeof a.preRun=="function"&&(a.preRun=[a.preRun]);a.preRun.length;)ss(a.preRun.shift());Or(Nn)}function ts(){ks=!0,Or(St)}function ns(){Or(Wn)}function sn(){if(a.postRun)for(typeof a.postRun=="function"&&(a.postRun=[a.postRun]);a.postRun.length;)rs(a.postRun.shift());Or(nn)}function ss(Y){Nn.unshift(Y)}function rs(Y){nn.unshift(Y)}var Vn=0,Ks=null,mr=null;function Fr(Y){Vn++,a.monitorRunDependencies&&a.monitorRunDependencies(Vn)}function ui(Y){if(Vn--,a.monitorRunDependencies&&a.monitorRunDependencies(Vn),Vn==0&&(Ks!==null&&(clearInterval(Ks),Ks=null),mr)){var re=mr;mr=null,re()}}a.preloadedImages={},a.preloadedAudios={};function Zs(Y){a.onAbort&&a.onAbort(Y),Y+="",O(Y),P=!0,V=1,Y="abort("+Y+"). Build with -s ASSERTIONS=1 for more info.";var re=new WebAssembly.RuntimeError(Y);throw i(re),re}function bd(Y,re){return String.prototype.startsWith?Y.startsWith(re):Y.indexOf(re)===0}var o0="data:application/octet-stream;base64,";function bu(Y){return bd(Y,o0)}var i0="file://";function vd(Y){return bd(Y,i0)}var En="tfjs-backend-wasm.wasm";bu(En)||(En=y(En));function wd(Y){try{if(Y==En&&E)return new Uint8Array(E);if(v)return v(Y);throw"both async and sync fetching of the wasm failed"}catch(re){Zs(re)}}function l0(){if(!E&&(p||f)){if(typeof fetch=="function"&&!vd(En))return fetch(En,{credentials:"same-origin"}).then(function(Y){if(!Y.ok)throw"failed to load wasm binary file at '"+En+"'";return Y.arrayBuffer()}).catch(function(){return wd(En)});if(b)return new Promise(function(Y,re){b(En,function(xe){Y(new Uint8Array(xe))},re)})}return Promise.resolve().then(function(){return wd(En)})}function gr(){var Y={a:p0};function re(je,qe){var rn=je.exports;a.asm=rn,T=a.asm.i,et(T.buffer),He=a.asm.o,ui("wasm-instantiate")}Fr("wasm-instantiate");function xe(je){re(je.instance)}function Qe(je){return l0().then(function(qe){return WebAssembly.instantiate(qe,Y)}).then(je,function(qe){O("failed to asynchronously prepare wasm: "+qe),Zs(qe)})}function Et(){return!E&&typeof WebAssembly.instantiateStreaming=="function"&&!bu(En)&&!vd(En)&&typeof fetch=="function"?fetch(En,{credentials:"same-origin"}).then(function(je){var qe=WebAssembly.instantiateStreaming(je,Y);return qe.then(xe,function(rn){return O("wasm streaming compile failed: "+rn),O("falling back to ArrayBuffer instantiation"),Qe(xe)})}):Qe(xe)}if(a.instantiateWasm)try{var bt=a.instantiateWasm(Y,re);return bt}catch(je){return O("Module.instantiateWasm callback failed with error: "+je),!1}return Et().catch(i),{}}function Or(Y){for(;Y.length>0;){var re=Y.shift();if(typeof re=="function"){re(a);continue}var xe=re.func;typeof xe=="number"?re.arg===void 0?He.get(xe)():He.get(xe)(re.arg):xe(re.arg===void 0?null:re.arg)}}function va(){Zs()}function u0(Y,re,xe){Te.copyWithin(Y,re,re+xe)}function c0(){return Te.length}function Ar(Y){try{return T.grow(Y-Ae.byteLength+65535>>>16),et(T.buffer),1}catch(re){}}function kd(Y){var re=c0(),xe=2147483648;if(Y>xe)return!1;for(var Qe=1;Qe<=4;Qe*=2){var Et=re*(1+.2/Qe);Et=Math.min(Et,Y+100663296);var bt=Math.min(xe,he(Math.max(Y,Et),65536)),je=Ar(bt);if(je)return!0}return!1}var ci={mappings:{},buffers:[null,[],[]],printChar:function(Y,re){var xe=ci.buffers[Y];re===0||re===10?((Y===1?_:O)(ne(xe,0)),xe.length=0):xe.push(re)},varargs:void 0,get:function(){ci.varargs+=4;var Y=Fe[ci.varargs-4>>2];return Y},getStr:function(Y){var re=se(Y);return re},get64:function(Y,re){return Y}};function Id(Y){return 0}function d0(Y,re,xe,Qe,Et){}function Sd(Y,re,xe,Qe){for(var Et=0,bt=0;bt<xe;bt++){for(var je=Fe[re+bt*8>>2],qe=Fe[re+(bt*8+4)>>2],rn=0;rn<qe;rn++)ci.printChar(Y,Te[je+rn]);Et+=qe}return Fe[Qe>>2]=Et,0}function Rn(){return 6}function Cd(Y){return Fe[Pd()>>2]=Y,Y}function h0(Y){switch(Y){case 30:return 16384;case 85:var re=2147483648;return re/16384;case 132:case 133:case 12:case 137:case 138:case 15:case 235:case 16:case 17:case 18:case 19:case 20:case 149:case 13:case 10:case 236:case 153:case 9:case 21:case 22:case 159:case 154:case 14:case 77:case 78:case 139:case 82:case 68:case 67:case 164:case 11:case 29:case 47:case 48:case 95:case 52:case 51:case 46:return 200809;case 27:case 246:case 127:case 128:case 23:case 24:case 160:case 161:case 181:case 182:case 242:case 183:case 184:case 243:case 244:case 245:case 165:case 178:case 179:case 49:case 50:case 168:case 169:case 175:case 170:case 171:case 172:case 97:case 76:case 32:case 173:case 35:case 80:case 81:case 79:return-1;case 176:case 177:case 7:case 155:case 8:case 157:case 125:case 126:case 92:case 93:case 129:case 130:case 131:case 94:case 91:return 1;case 74:case 60:case 69:case 70:case 4:return 1024;case 31:case 42:case 72:return 32;case 87:case 26:case 33:return 2147483647;case 34:case 1:return 47839;case 38:case 36:return 99;case 43:case 37:return 2048;case 0:return 2097152;case 3:return 65536;case 28:return 32768;case 44:return 32767;case 75:return 16384;case 39:return 1e3;case 89:return 700;case 71:return 256;case 40:return 255;case 2:return 100;case 180:return 64;case 25:return 20;case 5:return 16;case 6:return 6;case 73:return 4;case 84:return typeof navigator=="object"&&navigator.hardwareConcurrency||1}return Cd(28),-1}var p0={a:va,d:u0,e:kd,f:Id,c:d0,b:Sd,g:Rn,h:h0},f0=gr(),Td=a.___wasm_call_ctors=function(){return(Td=a.___wasm_call_ctors=a.asm.j).apply(null,arguments)},di=a._init=function(){return(di=a._init=a.asm.k).apply(null,arguments)},vu=a._register_tensor=function(){return(vu=a._register_tensor=a.asm.l).apply(null,arguments)},m0=a._dispose_data=function(){return(m0=a._dispose_data=a.asm.m).apply(null,arguments)},g0=a._dispose=function(){return(g0=a._dispose=a.asm.n).apply(null,arguments)},A0=a._Abs=function(){return(A0=a._Abs=a.asm.p).apply(null,arguments)},Se=a._Add=function(){return(Se=a._Add=a.asm.q).apply(null,arguments)},y0=a._AddN=function(){return(y0=a._AddN=a.asm.r).apply(null,arguments)},x0=a._All=function(){return(x0=a._All=a.asm.s).apply(null,arguments)},b0=a._Any=function(){return(b0=a._Any=a.asm.t).apply(null,arguments)},v0=a._ArgMax=function(){return(v0=a._ArgMax=a.asm.u).apply(null,arguments)},w0=a._AvgPool=function(){return(w0=a._AvgPool=a.asm.v).apply(null,arguments)},wa=a._BatchMatMul=function(){return(wa=a._BatchMatMul=a.asm.w).apply(null,arguments)},k0=a._Ceil=function(){return(k0=a._Ceil=a.asm.x).apply(null,arguments)},I0=a._ClipByValue=function(){return(I0=a._ClipByValue=a.asm.y).apply(null,arguments)},S0=a._Conv2D=function(){return(S0=a._Conv2D=a.asm.z).apply(null,arguments)},C0=a._Conv2DBackpropInput=function(){return(C0=a._Conv2DBackpropInput=a.asm.A).apply(null,arguments)},T0=a._Cos=function(){return(T0=a._Cos=a.asm.B).apply(null,arguments)},N0=a._Cosh=function(){return(N0=a._Cosh=a.asm.C).apply(null,arguments)},E0=a._CropAndResize=function(){return(E0=a._CropAndResize=a.asm.D).apply(null,arguments)},R0=a._Cumsum=function(){return(R0=a._Cumsum=a.asm.E).apply(null,arguments)},_0=a._DepthToSpace=function(){return(_0=a._DepthToSpace=a.asm.F).apply(null,arguments)},Pr=a._DepthwiseConv2dNative=function(){return(Pr=a._DepthwiseConv2dNative=a.asm.G).apply(null,arguments)},wu=a._Elu=function(){return(wu=a._Elu=a.asm.H).apply(null,arguments)},ku=a._Equal=function(){return(ku=a._Equal=a.asm.I).apply(null,arguments)},D0=a._Exp=function(){return(D0=a._Exp=a.asm.J).apply(null,arguments)},$0=a._FlipLeftRight=function(){return($0=a._FlipLeftRight=a.asm.K).apply(null,arguments)},F0=a._Floor=function(){return(F0=a._Floor=a.asm.L).apply(null,arguments)},O0=a._FloorDiv=function(){return(O0=a._FloorDiv=a.asm.M).apply(null,arguments)},P0=a._FusedBatchNorm=function(){return(P0=a._FusedBatchNorm=a.asm.N).apply(null,arguments)},Le=a._FusedConv2D=function(){return(Le=a._FusedConv2D=a.asm.O).apply(null,arguments)},M0=a._FusedDepthwiseConv2D=function(){return(M0=a._FusedDepthwiseConv2D=a.asm.P).apply(null,arguments)},z0=a._Gather=function(){return(z0=a._Gather=a.asm.Q).apply(null,arguments)},L0=a._GatherNd=function(){return(L0=a._GatherNd=a.asm.R).apply(null,arguments)},B0=a._Greater=function(){return(B0=a._Greater=a.asm.S).apply(null,arguments)},W0=a._GreaterEqual=function(){return(W0=a._GreaterEqual=a.asm.T).apply(null,arguments)},V0=a._LeakyRelu=function(){return(V0=a._LeakyRelu=a.asm.U).apply(null,arguments)},Iu=a._Less=function(){return(Iu=a._Less=a.asm.V).apply(null,arguments)},Nd=a._LessEqual=function(){return(Nd=a._LessEqual=a.asm.W).apply(null,arguments)},Ed=a._Log=function(){return(Ed=a._Log=a.asm.X).apply(null,arguments)},U0=a._LogicalAnd=function(){return(U0=a._LogicalAnd=a.asm.Y).apply(null,arguments)},H0=a._Max=function(){return(H0=a._Max=a.asm.Z).apply(null,arguments)},G0=a._MaxPool=function(){return(G0=a._MaxPool=a.asm._).apply(null,arguments)},j0=a._Maximum=function(){return(j0=a._Maximum=a.asm.$).apply(null,arguments)},q0=a._Mean=function(){return(q0=a._Mean=a.asm.aa).apply(null,arguments)},X0=a._Min=function(){return(X0=a._Min=a.asm.ba).apply(null,arguments)},K0=a._Minimum=function(){return(K0=a._Minimum=a.asm.ca).apply(null,arguments)},tt=a._MirrorPad=function(){return(tt=a._MirrorPad=a.asm.da).apply(null,arguments)},Z0=a._Multiply=function(){return(Z0=a._Multiply=a.asm.ea).apply(null,arguments)},Y0=a._Neg=function(){return(Y0=a._Neg=a.asm.fa).apply(null,arguments)},J0=a._NonMaxSuppressionV3=function(){return(J0=a._NonMaxSuppressionV3=a.asm.ga).apply(null,arguments)},hi=a._NonMaxSuppressionV4=function(){return(hi=a._NonMaxSuppressionV4=a.asm.ha).apply(null,arguments)},Rd=a._NonMaxSuppressionV5=function(){return(Rd=a._NonMaxSuppressionV5=a.asm.ia).apply(null,arguments)},_d=a._NotEqual=function(){return(_d=a._NotEqual=a.asm.ja).apply(null,arguments)},Dd=a._OneHot=function(){return(Dd=a._OneHot=a.asm.ka).apply(null,arguments)},Q0=a._PadV2=function(){return(Q0=a._PadV2=a.asm.la).apply(null,arguments)},em=a._Pow=function(){return(em=a._Pow=a.asm.ma).apply(null,arguments)},$d=a._Prelu=function(){return($d=a._Prelu=a.asm.na).apply(null,arguments)},tm=a._Prod=function(){return(tm=a._Prod=a.asm.oa).apply(null,arguments)},Fd=a._RealDiv=function(){return(Fd=a._RealDiv=a.asm.pa).apply(null,arguments)},Mr=a._Relu=function(){return(Mr=a._Relu=a.asm.qa).apply(null,arguments)},nm=a._Relu6=function(){return(nm=a._Relu6=a.asm.ra).apply(null,arguments)},sm=a._ResizeBilinear=function(){return(sm=a._ResizeBilinear=a.asm.sa).apply(null,arguments)},Jy=a._Reverse=function(){return(Jy=a._Reverse=a.asm.ta).apply(null,arguments)},Od=a._RotateWithOffset=function(){return(Od=a._RotateWithOffset=a.asm.ua).apply(null,arguments)},rm=a._Round=function(){return(rm=a._Round=a.asm.va).apply(null,arguments)},am=a._Rsqrt=function(){return(am=a._Rsqrt=a.asm.wa).apply(null,arguments)},om=a._ScatterNd=function(){return(om=a._ScatterNd=a.asm.xa).apply(null,arguments)},im=a._SelectV2=function(){return(im=a._SelectV2=a.asm.ya).apply(null,arguments)},lm=a._Sigmoid=function(){return(lm=a._Sigmoid=a.asm.za).apply(null,arguments)},um=a._Sin=function(){return(um=a._Sin=a.asm.Aa).apply(null,arguments)},cm=a._Softmax=function(){return(cm=a._Softmax=a.asm.Ba).apply(null,arguments)},dm=a._Sqrt=function(){return(dm=a._Sqrt=a.asm.Ca).apply(null,arguments)},hm=a._Square=function(){return(hm=a._Square=a.asm.Da).apply(null,arguments)},pm=a._SquaredDifference=function(){return(pm=a._SquaredDifference=a.asm.Ea).apply(null,arguments)},fm=a._Step=function(){return(fm=a._Step=a.asm.Fa).apply(null,arguments)},mm=a._StridedSlice=function(){return(mm=a._StridedSlice=a.asm.Ga).apply(null,arguments)},gm=a._Sub=function(){return(gm=a._Sub=a.asm.Ha).apply(null,arguments)},Am=a._Sum=function(){return(Am=a._Sum=a.asm.Ia).apply(null,arguments)},ym=a._Tan=function(){return(ym=a._Tan=a.asm.Ja).apply(null,arguments)},xm=a._Tanh=function(){return(xm=a._Tanh=a.asm.Ka).apply(null,arguments)},bm=a._Tile=function(){return(bm=a._Tile=a.asm.La).apply(null,arguments)},vm=a._TopK=function(){return(vm=a._TopK=a.asm.Ma).apply(null,arguments)},wm=a._Transform=function(){return(wm=a._Transform=a.asm.Na).apply(null,arguments)},km=a._Transpose=function(){return(km=a._Transpose=a.asm.Oa).apply(null,arguments)},Im=a.__FusedMatMul=function(){return(Im=a.__FusedMatMul=a.asm.Pa).apply(null,arguments)},Sm=a._malloc=function(){return(Sm=a._malloc=a.asm.Qa).apply(null,arguments)},Cm=a._free=function(){return(Cm=a._free=a.asm.Ra).apply(null,arguments)},Pd=a.___errno_location=function(){return(Pd=a.___errno_location=a.asm.Sa).apply(null,arguments)},Md=a.stackSave=function(){return(Md=a.stackSave=a.asm.Ta).apply(null,arguments)},zd=a.stackRestore=function(){return(zd=a.stackRestore=a.asm.Ua).apply(null,arguments)},Su=a.stackAlloc=function(){return(Su=a.stackAlloc=a.asm.Va).apply(null,arguments)};a.cwrap=ee;var pi;function Tm(Y){this.name="ExitStatus",this.message="Program terminated with exit("+Y+")",this.status=Y}mr=function Y(){pi||Cu(),pi||(mr=Y)};function Cu(Y){if(Y=Y||c,Vn>0||(pn(),Vn>0))return;function re(){pi||(pi=!0,a.calledRun=!0,!P&&(ts(),ns(),o(a),a.onRuntimeInitialized&&a.onRuntimeInitialized(),sn()))}a.setStatus?(a.setStatus("Running..."),setTimeout(function(){setTimeout(function(){a.setStatus("")},1),re()},1)):re()}if(a.run=Cu,a.preInit)for(typeof a.preInit=="function"&&(a.preInit=[a.preInit]);a.preInit.length>0;)a.preInit.pop()();return Cu(),r.ready}}();typeof e=="object"&&typeof t=="object"?t.exports=n:typeof define=="function"&&define.amd?define([],function(){return n}):typeof e=="object"&&(e.WasmBackendModule=n)}}),pS="3.9.0",fS="3.9.0",mS="3.9.0",gS="3.9.0",AS="3.9.0",yS="3.9.0",xS="3.9.0",bS="3.9.0",vS=1e-7,wS=1e-4,Ud=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}},Du=class{refCount(e){return Is("refCount")}incRef(e){return Is("incRef")}timerAvailable(){return!0}time(e){return Is("time")}read(e){return Is("read")}readSync(e){return Is("readSync")}numDataIds(){return Is("numDataIds")}disposeData(e,t){return Is("disposeData")}write(e,t,n){return Is("write")}move(e,t,n,s,r){return Is("move")}memory(){return Is("memory")}floatPrecision(){return Is("floatPrecision")}epsilon(){return this.floatPrecision()===32?vS:wS}dispose(){return Is("dispose")}};function Is(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 x5(e){let t=e.length,n=0;for(;t>0;)n=Math.random()*t|0,t--,Hd(e,t,n)}function kS(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 n=e.length,s=0;for(;n>0;)s=Math.random()*n|0,n--,Hd(e,n,s),Hd(t,n,s)}function $u(e,t,n){return Math.max(e,Math.min(t,n))}function IS(e){return e%2==0?e:e+1}function Hd(e,t,n){let s=e[t];e[t]=e[n],e[n]=s}function SS(e){let t=0;for(let n=0;n<e.length;n++)t+=e[n];return t}function CS(e,t){let n=Math.random();return t*n+(1-n)*e}function TS(e,t){let n=0;for(let s=0;s<e.length;s++){let r=Number(e[s])-Number(t[s]);n+=r*r}return n}function M(e,t){if(!e)throw new Error(typeof t=="string"?t:t())}function An(e,t,n=""){M(br(e,t),()=>n+` Shapes ${e} and ${t} must match`)}function Sa(e){M(e!=null,()=>"The input to the tensor constructor must be a non-null value.")}function Ca(e,t=[],n=!1){if(t==null&&(t=[]),Array.isArray(e)||cn(e)&&!n)for(let s=0;s<e.length;++s)Ca(e[s],t,n);else t.push(e);return t}function $t(e){if(e.length===0)return 1;let t=e[0];for(let n=1;n<e.length;n++)t*=e[n];return t}function NS(e){return e.length===0}function br(e,t){if(e===t)return!0;if(e==null||t==null||e.length!==t.length)return!1;for(let n=0;n<e.length;n++)if(e[n]!==t[n])return!1;return!0}function Zt(e){return e%1==0}function ES(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 RS(e){let t=Math.ceil(Math.sqrt(e));return[t,Math.ceil(e/t)]}function _S(e){let t=new Uint32Array(e);for(let n=0;n<e;++n)t[n]=n;return x5(t),t}function Fu(e,t){return t<=e.length?e:e+" ".repeat(t-e.length)}function DS(e,t=s=>0,n){return new Promise((s,r)=>{let a=0,o=()=>{if(e()){s();return}a++;let i=t(a);if(n!=null&&a>=n){r();return}setTimeout(o,i)};o()})}function $S(e,t){let n=1,s=-1;for(let a=0;a<e.length;++a)if(e[a]>=0)n*=e[a];else if(e[a]===-1){if(s!==-1)throw Error(`Shapes can only have 1 implicit size. Found -1 at dim ${s} and dim ${a}`);s=a}else if(e[a]<0)throw Error(`Shapes can not be < 0. Found ${e[a]} at dim ${a}`);if(s===-1){if(t>0&&t!==n)throw Error(`Size(${t}) must match the product of shape ${e}`);return e}if(n===0)throw Error(`Cannot infer the missing size in [${e}] when there are 0 elements`);if(t%n!=0)throw Error(`The implicit shape can't be a fractional number. Got ${t} / ${n}`);let r=e.slice();return r[s]=t/n,r}function Ss(e,t){let n=t.length;return e=e==null?t.map((s,r)=>r):[].concat(e),M(e.every(s=>s>=-n&&s<n),()=>`All values in axis param must be in range [-${n}, ${n}) but got axis ${e}`),M(e.every(s=>Zt(s)),()=>`All values in axis param must be integers but got axis ${e}`),e.map(s=>s<0?n+s:s)}function b5(e,t){let n=[],s=[],r=t!=null&&Array.isArray(t)&&t.length===0,a=t==null||r?null:Ss(t,e).sort(),o=0;for(let i=0;i<e.length;++i){if(a!=null){if(a[o]===i&&e[i]!==1)throw new Error(`Can't squeeze axis ${i} since its dim '${e[i]}' is not 1`);(a[o]==null||a[o]>i)&&e[i]===1&&(n.push(e[i]),s.push(i)),a[o]<=i&&o++}e[i]!==1&&(n.push(e[i]),s.push(i))}return{newShape:n,keptDims:s}}function v5(e,t){let n=null;if(e==null||e==="float32")n=new Float32Array(t);else if(e==="int32")n=new Int32Array(t);else if(e==="bool")n=new Uint8Array(t);else throw new Error(`Unknown data type ${e}`);return n}function w5(e,t){let n=null;if(e==null||e==="float32")n=new Float32Array(t);else if(e==="int32")n=new Int32Array(t);else if(e==="bool")n=new Uint8Array(t);else if(e==="string")n=new Array(t);else throw new Error(`Unknown data type ${e}`);return n}function k5(e,t){for(let n=0;n<e.length;n++){let s=e[n];if(isNaN(s)||!isFinite(s))throw Error(`A tensor of type ${t} being uploaded contains ${s}.`)}}function I5(e){return e==="bool"||e==="complex64"||e==="float32"||e==="int32"||e==="string"}function FS(e,t){return!(t==="complex64"||t==="float32"&&e!=="complex64"||t==="int32"&&e!=="float32"&&e!=="complex64"||t==="bool"&&e==="bool")}function cn(e){return e instanceof Float32Array||e instanceof Int32Array||e instanceof Uint8Array}function Fm(e){if(e==="float32"||e==="int32")return 4;if(e==="complex64")return 8;if(e==="bool")return 1;throw new Error(`Unknown dtype ${e}`)}function S5(e){if(e==null)return 0;let t=0;return e.forEach(n=>t+=n.length),t}function Br(e){return typeof e=="string"||e instanceof String}function C5(e){return typeof e=="boolean"}function T5(e){return typeof e=="number"}function Gd(e){return Array.isArray(e)?Gd(e[0]):e instanceof Float32Array?"float32":e instanceof Int32Array||e instanceof Uint8Array?"int32":T5(e)?"float32":Br(e)?"string":C5(e)?"bool":"float32"}function Wr(e){return!!(e&&e.constructor&&e.call&&e.apply)}function jd(e,t){for(let n=t;n<e;++n)if(e%n==0)return n;return e}function vi(e){let t=e.length;if(t<2)return[];let n=new Array(t-1);n[t-2]=e[t-1];for(let s=t-3;s>=0;--s)n[s]=n[s+1]*e[s+1];return n}function N5(e,t,n,s=!1){let r=new Array;if(t.length===1){let a=t[0]*(s?2:1);for(let o=0;o<a;o++)r[o]=n[e+o]}else{let a=t[0],o=t.slice(1),i=o.reduce((l,u)=>l*u)*(s?2:1);for(let l=0;l<a;l++)r[l]=N5(e+l*i,o,n,s)}return r}function wi(e,t,n=!1){if(e.length===0)return t[0];let s=e.reduce((r,a)=>r*a)*(n?2:1);if(s===0)return[];if(s!==t.length)throw new Error(`[${e}] does not match the input size ${t.length}${n?" for a complex tensor":""}.`);return N5(0,e,t,n)}function Om(e,t){let n=qd(e,t);for(let s=0;s<n.length;s++)n[s]=1;return n}function qd(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 OS(e,t){let n=e.reduce((s,r)=>s*r,1);if(t==null||t==="float32")return wi(e,new Float32Array(n));if(t==="int32")return wi(e,new Int32Array(n));if(t==="bool")return wi(e,new Uint8Array(n));throw new Error(`Unknown data type ${t}`)}function Pm(e){e.forEach(t=>{M(Number.isInteger(t)&&t>=0,()=>`Tensor must have a shape comprised of positive integers but got shape [${e}].`)})}function PS(e,t,n){if(t===0)return 0;if(t===1)return e[0];let s=e[e.length-1];for(let r=0;r<e.length-1;++r)s+=n[r]*e[r];return s}function MS(e,t,n){if(t===0)return[];if(t===1)return[e];let s=new Array(t);for(let r=0;r<s.length-1;++r)s[r]=Math.floor(e/n[r]),e-=s[r]*n[r];return s[s.length-1]=e,s}function Mm(e){return e&&e.then&&typeof e.then=="function"}function Ys(...e){Q().getBool("IS_TEST")||Q().getBool("PROD")||console.warn(...e)}function zS(...e){Q().getBool("IS_TEST")||Q().getBool("PROD")||console.log(...e)}var E5="tfjsflags",R5=class{constructor(e){this.global=e,this.flags={},this.flagRegistry={},this.urlFlags={},this.getQueryParams=LS,this.populateURLFlags()}setPlatform(e,t){this.platform!=null&&Ys(`Platform ${this.platformName} has already been set. Overwriting the platform with ${t}.`),this.platformName=e,this.platform=t}registerFlag(e,t,n){if(this.flagRegistry[e]={evaluationFn:t,setHook:n},this.urlFlags[e]!=null){let s=this.urlFlags[e];Ys(`Setting feature override from URL ${e}: ${s}.`),this.set(e,s)}}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(Mm(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);E5 in e&&e[E5].split(",").forEach(n=>{let[s,r]=n.split(":");this.urlFlags[s]=WS(s,r)})}};function LS(e){let t={};return e.replace(/[?&]([^=?&]+)(?:=([^&]*))?/g,(n,...s)=>(BS(t,s[0],s[1]),s.join("="))),t}function BS(e,t,n){e[decodeURIComponent(t)]=decodeURIComponent(n||"")}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 ${e}.`)}function Q(){return os}var os=null;function VS(e){os=e}var zm;function _5(){if(zm==null){let e;if(typeof window!="undefined")e=window;else if(typeof global!="undefined")e=global;else if(typeof process!="undefined")e=process;else if(typeof self!="undefined")e=self;else throw new Error("Could not find a global object");zm=e}return zm}function US(){let e=_5();return e._tfGlobals==null&&(e._tfGlobals=new Map),e._tfGlobals}function Lm(e,t){let n=US();if(n.has(e))return n.get(e);{let s=t();return n.set(e,s),n.get(e)}}var ki="Abs",Ii="Acos",Si="Acosh",Vr="Add",Ta="AddN",Ci="All",Ti="Any",Na="ArgMax",Ou="ArgMin",Ni="Asin",Ei="Asinh",Ri="Atan",_i="Atanh",Di="Atan2",Ea="AvgPool",Xd="AvgPoolGrad",Pu="AvgPool3D",Kd="AvgPool3DGrad",Ra="BatchMatMul",$i="BatchToSpaceND",Zd="Bincount",D5="BroadcastTo",Bm="BroadcastArgs",_a="Cast",Da="Ceil",Ur="ClipByValue",Yd="Complex",Mu="ComplexAbs",Fi="Concat",$a="Conv2D",Jd="Conv2DBackpropFilter",Fa="Conv2DBackpropInput",zu="Conv3D",Qd="Conv3DBackpropFilterV2",eh="Conv3DBackpropInputV2",Oa="Cos",Pa="Cosh",Ma="Cumsum",Oi="CropAndResize",th="DenseBincount",Pi="DepthToSpace",za="DepthwiseConv2dNative",nh="DepthwiseConv2dNativeBackpropFilter",sh="DepthwiseConv2dNativeBackpropInput",rh="Diag",Lu="Dilation2D",ah="Dilation2DBackpropInput",oh="Dilation2DBackpropFilter",La="RealDiv",ih="Einsum",Ba="Elu",lh="EluGrad",Mi="Erf",zi="Equal",Wa="Exp",Li="ExpandDims",Bi="Expm1",uh="FFT",Bu="Fill",Wi="FlipLeftRight",Va="Floor",Ua="FloorDiv",Ha="FusedBatchNorm",Vi="GatherV2",Ui="GatherNd",Hi="Greater",Ga="GreaterEqual",ja="Identity",ch="IFFT",dh="Imag",Gi="IsFinite",ji="IsInf",qi="IsNan",qa="LeakyRelu",Xi="Less",Ki="LessEqual",hh="LinSpace",Xa="Log",Zi="Log1p",Yi="LogicalAnd",Wu="LogicalNot",Vu="LogicalOr",$5="LogSoftmax",Uu="LRN",ph="LRNGrad",Ka="Max",Za="Maximum",Ya="MaxPool",fh="MaxPoolGrad",Hu="MaxPool3D",mh="MaxPool3DGrad",gh="MaxPoolWithArgmax",Ja="Mean",Qa="Min",eo="Minimum",to="MirrorPad",Ji="Mod",Ah="Multinomial",no="Multiply",Qi="Neg",el="NotEqual",tl="NonMaxSuppressionV3",nl="NonMaxSuppressionV4",sl="NonMaxSuppressionV5",rl="OnesLike",so="OneHot",al="Pack",ro="PadV2",HS="Pool",ao="Pow",oo="Prelu",ol="Prod",Gu="Range",yh="Real",il="Reciprocal",io="Relu",ll="Reshape",ju="ResizeNearestNeighbor",xh="ResizeNearestNeighborGrad",lo="ResizeBilinear",bh="ResizeBilinearGrad",uo="Relu6",co="Reverse",ho="Round",po="Rsqrt",ul="ScatterNd",cl="Select",dl="Selu",hl="Slice",fo="Sin",pl="Sinh",fl="Sign",mo="Sigmoid",ml="Softplus",go="Sqrt",Ao="Sum",gl="SpaceToBatchND",Al="SplitV",yo="Softmax",vh="SparseFillEmptyRows",wh="SparseReshape",kh="SparseSegmentMean",Ih="SparseSegmentSum",Sh="SparseToDense",xo="SquaredDifference",qu="Square",yl="StridedSlice",Ch="StringNGrams",Th="StringSplit",Nh="StringToHashBucketFast",bo="Sub",vo="Tan",wo="Tanh",Hr="Tile",xl="TopK",bl="Transform",ko="Transpose",Eh="Unique",vl="Unpack",Xu="UnsortedSegmentSum",wl="ZerosLike",Gr="Step",Rh="FromPixels",kl="RotateWithOffset",Io="_FusedMatMul",So="FusedConv2D",Co="FusedDepthwiseConv2D",Il=Lm("kernelRegistry",()=>new Map),Ku=Lm("gradRegistry",()=>new Map);function _h(e,t){let n=Vm(e,t);return Il.get(n)}function Wm(e){return Ku.get(e)}function Sl(e){let t=Il.entries(),n=[];for(;;){let{done:s,value:r}=t.next();if(s)break;let[a,o]=r,[i]=a.split("_");i===e&&n.push(o)}return n}function To(e){let{kernelName:t,backendName:n}=e,s=Vm(t,n);Il.has(s)&&Ys(`The kernel '${t}' for backend '${n}' is already registered`),Il.set(s,e)}function F5(e){let{kernelName:t}=e;Ku.has(t)&&Q().getBool("DEBUG")&&Ys(`Overriding the gradient for '${t}'`),Ku.set(t,e)}function GS(e,t){let n=Vm(e,t);if(!Il.has(n))throw new Error(`The kernel '${e}' for backend '${t}' is not registered`);Il.delete(n)}function jS(e){if(!Ku.has(e))throw new Error(`The gradient '${e}' for backend is not registered`);Ku.delete(e)}function qS(e,t){Sl(e).forEach(s=>{let r=Object.assign({},s,{backendName:t});To(r)})}function Vm(e,t){return`${t}_${e}`}var w={};Pe(w,{arraysEqual:()=>br,assert:()=>M,assertNonNegativeIntegerDimensions:()=>Pm,assertNonNull:()=>Sa,assertShapesMatch:()=>An,bytesFromStringArray:()=>S5,bytesPerElement:()=>Fm,checkConversionForErrors:()=>k5,clamp:()=>$u,computeStrides:()=>vi,createScalarValue:()=>QS,createShuffledIndices:()=>_S,decodeString:()=>Fh,distSquared:()=>TS,encodeString:()=>Ju,fetch:()=>t9,fingerPrint64:()=>JS,flatten:()=>Ca,getArrayFromDType:()=>w5,getTypedArrayFromDType:()=>v5,hasEncodingLoss:()=>FS,hexToLong:()=>Zu,indexToLoc:()=>MS,inferDtype:()=>Gd,inferFromImplicitShape:()=>$S,isBoolean:()=>C5,isFunction:()=>Wr,isInt:()=>Zt,isNumber:()=>T5,isPromise:()=>Mm,isScalarShape:()=>NS,isString:()=>Br,isTypedArray:()=>cn,isValidDtype:()=>I5,locToIndex:()=>PS,makeOnesTypedArray:()=>Om,makeZerosNestedTypedArray:()=>OS,makeZerosTypedArray:()=>qd,nearestDivisor:()=>jd,nearestLargerEven:()=>IS,now:()=>Yu,parseAxisParam:()=>Ss,randUniform:()=>CS,repeatedTry:()=>DS,rightPad:()=>Fu,shuffle:()=>x5,shuffleCombo:()=>kS,sizeFromShape:()=>$t,sizeToSquarishShape:()=>RS,squeezeShape:()=>b5,sum:()=>SS,swap:()=>Hd,tanh:()=>ES,toNestedArray:()=>wi,toTypedArray:()=>$h});var O5=Ia(qI()),No=O5.default||O5;function Zu(e){return No.fromString(e,!0,16)}var P5=Zu("c3a5c85c97cb3127"),Eo=Zu("b492b66fbe98f273"),yn=Zu("9ae16a3b2f90404f");function Um(e){return e.xor(e.shru(47))}function M5(e,t,n){let s=e.slice(t,t+n);return No.fromBytes(Array.from(s),!0,!0)}function pt(e,t){return M5(e,t,8)}function z5(e,t){return M5(e,t,4)}function Yt(e,t){return t===0?e:e.shru(t).or(e.shl(64-t))}function jr(e,t,n=Zu("9ddfea08eb382d69")){let s=e.xor(t).mul(n);s=s.xor(s.shru(47));let r=t.xor(s).mul(n);return r=r.xor(r.shru(47)),r=r.mul(n),r}function XS(e,t,n,s,r,a){r=r.add(e),a=Yt(a.add(r).add(s),21);let o=r;return r=r.add(t),r=r.add(n),a=a.add(Yt(r,44)),[r.add(s),a.add(o)]}function Dh(e,t,n,s){return XS(pt(e,t),pt(e,t+8),pt(e,t+16),pt(e,t+24),n,s)}function KS(e,t=e.length){if(t>=8){let n=yn.add(t*2),s=pt(e,0).add(yn),r=pt(e,t-8),a=Yt(r,37).mul(n).add(s),o=Yt(s,25).add(r).mul(n);return jr(a,o,n)}if(t>=4){let n=yn.add(t*2),s=z5(e,0);return jr(s.shl(3).add(t),z5(e,t-4),n)}if(t>0){let n=e[0],s=e[t>>1],r=e[t-1],a=n+(s<<8),o=t+(r<<2);return Um(yn.mul(a).xor(P5.mul(o))).mul(yn)}return yn}function ZS(e,t=e.length){let n=yn.add(t*2),s=pt(e,0).mul(Eo),r=pt(e,8),a=pt(e,t-8).mul(n),o=pt(e,t-16).mul(yn);return jr(Yt(s.add(r),43).add(Yt(a,30)).add(o),s.add(Yt(r.add(yn),18)).add(a),n)}function YS(e,t=e.length){let n=yn.add(t*2),s=pt(e,0).mul(yn),r=pt(e,8),a=pt(e,t-8).mul(n),o=pt(e,t-16).mul(yn),i=Yt(s.add(r),43).add(Yt(a,30)).add(o),l=jr(i,s.add(Yt(r.add(yn),18)).add(a),n),u=pt(e,16).mul(n),c=pt(e,24),d=i.add(pt(e,t-32)).mul(n),h=l.add(pt(e,t-24)).mul(n);return jr(Yt(u.add(c),43).add(Yt(d,30)).add(h),u.add(Yt(c.add(s),18)).add(d),n)}function JS(e,t=e.length){let n=No.fromNumber(81,!0);if(t<=32)return t<=16?KS(e,t):ZS(e,t);if(t<=64)return YS(e,t);let s=n,r=n.mul(Eo).add(113),a=Um(r.mul(yn).add(113)).mul(yn),o=[No.UZERO,No.UZERO],i=[No.UZERO,No.UZERO];s=s.mul(yn).add(pt(e,0));let l=0,u=(t-1>>6)*64,c=u+(t-1&63)-63;do s=Yt(s.add(r).add(o[0]).add(pt(e,l+8)),37).mul(Eo),r=Yt(r.add(o[1]).add(pt(e,l+48)),42).mul(Eo),s=s.xor(i[1]),r=r.add(o[0]).add(pt(e,l+40)),a=Yt(a.add(i[0]),33).mul(Eo),o=Dh(e,l,o[1].mul(Eo),s.add(i[0])),i=Dh(e,l+32,a.add(i[1]),r.add(pt(e,l+16))),[a,s]=[s,a],l+=64;while(l!==u);let d=Eo.add(a.and(255).shl(1));return l=c,i[0]=i[0].add(t-1&63),o[0]=o[0].add(i[0]),i[0]=i[0].add(o[0]),s=Yt(s.add(r).add(o[0]).add(pt(e,l+8)),37).mul(d),r=Yt(r.add(o[1]).add(pt(e,l+48)),42).mul(d),s=s.xor(i[1].mul(9)),r=r.add(o[0].mul(9).add(pt(e,l+40))),a=Yt(a.add(i[0]),33).mul(d),o=Dh(e,l,o[1].mul(d),s.add(i[0])),i=Dh(e,l+32,a.add(i[1]),r.add(pt(e,l+16))),[a,s]=[s,a],jr(jr(o[0],i[0],d).add(Um(r).mul(P5)).add(a),jr(o[1],i[1],d).add(s),d)}function QS(e,t){return t==="string"?Ju(e):$h([e],t)}function e9(e,t){return e instanceof Float32Array&&t==="float32"||e instanceof Int32Array&&t==="int32"||e instanceof Uint8Array&&t==="bool"}function $h(e,t){if(t==="string")throw new Error("Cannot convert a string[] to a TypedArray");if(Array.isArray(e)&&(e=Ca(e)),Q().getBool("DEBUG")&&k5(e,t),e9(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 n=new Uint8Array(e.length);for(let s=0;s<n.length;++s)Math.round(e[s])!==0&&(n[s]=1);return n}else throw new Error(`Unknown data type ${t}`)}function Yu(){return Q().platform.now()}function t9(e,t){return Q().platform.fetch(e,t)}function Ju(e,t="utf-8"){return t=t||"utf-8",Q().platform.encode(e,t)}function Fh(e,t="utf-8"){return t=t||"utf-8",Q().platform.decode(e,t)}var n9=class{constructor(e,t){this.backendTimer=e,this.logger=t,t==null&&(this.logger=new r9)}profileKernel(e,t,n){let s,r=()=>{s=n()},a,o=Yu();if(this.backendTimer.timerAvailable())a=this.backendTimer.time(r);else{r();for(let l of s)l.dataSync();a=Promise.resolve({kernelMs:Yu()-o})}if(Q().getBool("CHECK_COMPUTATION_FOR_ERRORS"))for(let l=0;l<s.length;l++){let u=s[l];u.data().then(c=>{s9(c,u.dtype,e)})}return{kernelName:e,outputs:s,inputs:t,timeMs:a.then(l=>l.kernelMs),extraInfo:a.then(l=>l.getExtraProfileInfo!=null?l.getExtraProfileInfo():"")}}logKernelProfile(e){let{kernelName:t,outputs:n,timeMs:s,inputs:r,extraInfo:a}=e;n.forEach(o=>{Promise.all([o.data(),s,a]).then(i=>{this.logger.logKernelProfile(t,o,i[0],i[1],r,i[2])})})}};function s9(e,t,n){if(t!=="float32")return!1;for(let s=0;s<e.length;s++){let r=e[s];if(isNaN(r)||!isFinite(r))return console.warn(`Found ${r} in the result of '${n}'`),!0}return!1}var r9=class{logKernelProfile(e,t,n,s,r,a){let o=typeof s=="number"?Fu(`${s}ms`,9):s.error,i=Fu(e,25),l=t.rank,u=t.size,c=Fu(t.shape.toString(),14),d="";for(let h in r){let p=r[h];if(p!=null){let f=p.shape||t.shape,m=f.length;d+=`${h}: ${m}D ${m>0?f:""} `}}console.log(`%c${i} %c${o} %c${l}D ${c} %c${u} %c${d} %c${a}`,"font-weight:bold","color:red","color:blue","color: orange","color: green","color: steelblue")}};function a9(e,t,n){let s={},r={};for(let l=0;l<t.length;l++)s[t[l].id]=!0;for(let l=0;l<e.length;l++){let u=e[l],c=u.inputs;for(let d in c){let h=c[d],p=!1;for(let f=0;f<t.length;f++)if(s[h.id]){u.outputs.forEach(m=>s[m.id]=!0),p=!0,r[u.id]=!0;break}if(p)break}}let a={};a[n.id]=!0;let o={};for(let l=e.length-1;l>=0;l--){let u=e[l],c=u.inputs;for(let d=0;d<u.outputs.length;d++)if(a[u.outputs[d].id]){for(let h in c)a[c[h].id]=!0,o[u.id]=!0;break}}let i=[];for(let l=0;l<e.length;l++){let u=e[l];if(r[u.id]&&o[u.id]){let c={};for(let h in u.inputs){let p=u.inputs[h];s[p.id]&&(c[h]=p)}let d=Object.assign({},u);d.inputs=c,d.outputs=u.outputs,i.push(d)}}return i}function o9(e,t,n,s){for(let r=t.length-1;r>=0;r--){let a=t[r],o=[];if(a.outputs.forEach(l=>{let u=e[l.id];u!=null?o.push(u):o.push(null)}),a.gradient==null)throw new Error(`Cannot compute gradient: gradient function not found for ${a.kernelName}.`);let i=a.gradient(o);for(let l in a.inputs){if(!(l in i))throw new Error(`Cannot backprop through input ${l}. Available gradients found: ${Object.keys(i)}.`);let u=n(()=>i[l]());if(u.dtype!=="float32")throw new Error(`Error in gradient for op ${a.kernelName}. The gradient of input ${l} must have 'float32' dtype, but has '${u.dtype}'`);let c=a.inputs[l];if(!br(u.shape,c.shape))throw new Error(`Error in gradient for op ${a.kernelName}. The gradient of input '${l}' has shape '${u.shape}', which does not match the shape of the input '${c.shape}'`);if(e[c.id]==null)e[c.id]=u;else{let d=e[c.id];e[c.id]=s(d,u),d.dispose()}}}}var L5=20,Qu=3,Hm=7;function i9(e,t,n,s){let r=vi(t),a=l9(e,t,n,r),o=t.length,i=Oh(e,t,n,r,a),l=["Tensor"];return s&&(l.push(` dtype: ${n}`),l.push(` rank: ${o}`),l.push(` shape: [${t}]`),l.push(" values:")),l.push(i.map(u=>" "+u).join(`
`)),l.join(`
`)}function l9(e,t,n,s){let r=$t(t),a=s[s.length-1],o=new Array(a).fill(0),i=t.length,l=n==="complex64"?tc(e):e;if(i>1)for(let u=0;u<r/a;u++){let c=u*a;for(let d=0;d<a;d++)o[d]=Math.max(o[d],ec(l[c+d],0,n).length)}return o}function ec(e,t,n){let s;return Array.isArray(e)?s=`${parseFloat(e[0].toFixed(Hm))} + ${parseFloat(e[1].toFixed(Hm))}j`:Br(e)?s=`'${e}'`:n==="bool"?s=B5(e):s=parseFloat(e.toFixed(Hm)).toString(),Fu(s,t)}function B5(e){return e===0?"false":"true"}function Oh(e,t,n,s,r,a=!0){let o=n==="complex64"?2:1,i=t[0],l=t.length;if(l===0){if(n==="complex64"){let m=tc(e);return[ec(m[0],0,n)]}return n==="bool"?[B5(e[0])]:[e[0].toString()]}if(l===1){if(i>L5){let g=Qu*o,A=Array.from(e.slice(0,g)),y=Array.from(e.slice((i-Qu)*o,i*o));return n==="complex64"&&(A=tc(A),y=tc(y)),["["+A.map((x,b)=>ec(x,r[b],n)).join(", ")+", ..., "+y.map((x,b)=>ec(x,r[i-Qu+b],n)).join(", ")+"]"]}let m=n==="complex64"?tc(e):Array.from(e);return["["+m.map((g,A)=>ec(g,r[A],n)).join(", ")+"]"]}let u=t.slice(1),c=s.slice(1),d=s[0]*o,h=[];if(i>L5){for(let m=0;m<Qu;m++){let g=m*d,A=g+d;h.push(...Oh(e.slice(g,A),u,n,c,r,!1))}h.push("...");for(let m=i-Qu;m<i;m++){let g=m*d,A=g+d;h.push(...Oh(e.slice(g,A),u,n,c,r,m===i-1))}}else for(let m=0;m<i;m++){let g=m*d,A=g+d;h.push(...Oh(e.slice(g,A),u,n,c,r,m===i-1))}let p=l===2?",":"";h[0]="["+h[0]+p;for(let m=1;m<h.length-1;m++)h[m]=" "+h[m]+p;let f=`,
`;for(let m=2;m<l;m++)f+=`
`;return h[h.length-1]=" "+h[h.length-1]+"]"+(a?"":f),h}function tc(e){let t=[];for(let n=0;n<e.length;n+=2)t.push([e[n],e[n+1]]);return t}var Ut=class{constructor(e,t,n){if(this.dtype=t,this.shape=e.slice(),this.size=$t(e),n!=null){let s=n.length;M(s===this.size,()=>`Length of values '${s}' does not match the size inferred by the shape '${this.size}'.`)}if(t==="complex64")throw new Error("complex64 dtype TensorBuffers are not supported. Please create a TensorBuffer for the real and imaginary parts separately and call tf.complex(real, imag).");this.values=n||w5(t,this.size),this.strides=vi(e)}set(e,...t){t.length===0&&(t=[0]),M(t.length===this.rank,()=>`The number of provided coordinates (${t.length}) must match the rank (${this.rank})`);let n=this.locToIndex(t);this.values[n]=e}get(...e){e.length===0&&(e=[0]);let t=0;for(let s of e){if(s<0||s>=this.shape[t]){let r=`Requested out of range element at ${e}. Buffer shape=${this.shape}`;throw new Error(r)}t++}let n=e[e.length-1];for(let s=0;s<e.length-1;++s)n+=this.strides[s]*e[s];return this.values[n]}locToIndex(e){if(this.rank===0)return 0;if(this.rank===1)return e[0];let t=e[e.length-1];for(let n=0;n<e.length-1;++n)t+=this.strides[n]*e[n];return t}indexToLoc(e){if(this.rank===0)return[];if(this.rank===1)return[e];let t=new Array(this.shape.length);for(let n=0;n<t.length-1;++n)t[n]=Math.floor(e/this.strides[n]),e-=t[n]*this.strides[n];return t[t.length-1]=e,t}get rank(){return this.shape.length}toTensor(){return Js().makeTensor(this.values,this.shape,this.dtype)}},Js=null,Cl=null,u9=null;function c9(e){Js=e}function d9(e){Cl=e}function h9(e){u9=e}var Ge=class{constructor(e,t,n,s){this.kept=!1,this.isDisposedInternal=!1,this.shape=e.slice(),this.dtype=t||"float32",this.size=$t(e),this.strides=vi(e),this.dataId=n,this.id=s,this.rankType=this.rank<5?this.rank.toString():"higher"}get rank(){return this.shape.length}async buffer(){let e=await this.data();return Cl.buffer(this.shape,this.dtype,e)}bufferSync(){return Cl.buffer(this.shape,this.dtype,this.dataSync())}async array(){let e=await this.data();return wi(this.shape,e,this.dtype==="complex64")}arraySync(){return wi(this.shape,this.dataSync(),this.dtype==="complex64")}async data(){this.throwIfDisposed();let e=Js().read(this.dataId);if(this.dtype==="string"){let t=await e;try{return t.map(n=>Fh(n))}catch(n){throw new Error("Failed to decode the string bytes into utf-8. To get the original bytes, call tensor.bytes().")}}return e}dataSync(){this.throwIfDisposed();let e=Js().readSync(this.dataId);if(this.dtype==="string")try{return e.map(t=>Fh(t))}catch(t){throw new Error("Failed to decode the string bytes into utf-8. To get the original bytes, call tensor.bytes().")}return e}async bytes(){this.throwIfDisposed();let e=await Js().read(this.dataId);return this.dtype==="string"?e:new Uint8Array(e.buffer)}dispose(){this.isDisposed||(Js().disposeTensor(this),this.isDisposedInternal=!0)}get isDisposed(){return this.isDisposedInternal}throwIfDisposed(){if(this.isDisposed)throw new Error("Tensor is disposed.")}print(e=!1){return Cl.print(this,e)}clone(){return this.throwIfDisposed(),Cl.clone(this)}toString(e=!1){let t=this.dataSync();return i9(t,this.shape,this.dtype,e)}cast(e){return this.throwIfDisposed(),Cl.cast(this,e)}variable(e=!0,t,n){return this.throwIfDisposed(),Js().makeVariable(this,e,t,n)}};Object.defineProperty(Ge,Symbol.hasInstance,{value:e=>!!e&&e.data!=null&&e.dataSync!=null&&e.throwIfDisposed!=null});function p9(){return Lm("Tensor",()=>Ge)}p9();var nc=class extends Ge{constructor(e,t,n,s){super(e.shape,e.dtype,e.dataId,s);this.trainable=t,this.name=n}assign(e){if(e.dtype!==this.dtype)throw new Error(`dtype of the new value (${e.dtype}) and previous value (${this.dtype}) must match`);if(!br(e.shape,this.shape))throw new Error(`shape of the new value (${e.shape}) and previous value (${this.shape}) must match`);Js().disposeTensor(this),this.dataId=e.dataId,Js().incRef(this,null)}dispose(){Js().disposeVariable(this),this.isDisposedInternal=!0}};Object.defineProperty(nc,Symbol.hasInstance,{value:e=>e instanceof Ge&&e.assign!=null&&e.assign instanceof Function});var $s={};Pe($s,{assertTypesMatch:()=>W5,getTensorsInContainer:()=>Zm,isTensorInList:()=>m9,makeTypesMatch:()=>Ct});var Gm;(function(e){e.R0="R0",e.R1="R1",e.R2="R2",e.R3="R3",e.R4="R4",e.R5="R5",e.R6="R6"})(Gm||(Gm={}));var jm;(function(e){e.float32="float32",e.int32="int32",e.bool="int32",e.complex64="complex64"})(jm||(jm={}));var qm;(function(e){e.float32="float32",e.int32="int32",e.bool="bool",e.complex64="complex64"})(qm||(qm={}));var Xm;(function(e){e.float32="float32",e.int32="float32",e.bool="float32",e.complex64="complex64"})(Xm||(Xm={}));var Km;(function(e){e.float32="complex64",e.int32="complex64",e.bool="complex64",e.complex64="complex64"})(Km||(Km={}));var f9={float32:Xm,int32:jm,bool:qm,complex64:Km};function Cs(e,t){if(e==="string"||t==="string"){if(e==="string"&&t==="string")return"string";throw new Error(`Can not upcast ${e} with ${t}`)}return f9[e][t]}function Ph(e){return Cs(e,"int32")}function Ct(e,t){if(e.dtype===t.dtype)return[e,t];let n=Cs(e.dtype,t.dtype);return[e.cast(n),t.cast(n)]}function W5(e,t){M(e.dtype===t.dtype,()=>`The dtypes of the first(${e.dtype}) and second(${t.dtype}) input must match`)}function m9(e,t){return t.some(n=>n.id===e.id)}function Zm(e){let t=[],n=new Set;return V5(e,t,n),t}function V5(e,t,n){if(e==null)return;if(e instanceof Ge){t.push(e);return}if(!g9(e))return;let s=e;for(let r in s){let a=s[r];n.has(a)||(n.add(a),V5(a,t,n))}}function g9(e){return Array.isArray(e)||typeof e=="object"}function Ym(e){return e.kernelName!=null}var U5=class{constructor(){this.registeredVariables={},this.nextTapeNodeId=0,this.numBytes=0,this.numTensors=0,this.numStringTensors=0,this.numDataBuffers=0,this.gradientDepth=0,this.kernelDepth=0,this.scopeStack=[],this.numDataMovesStack=[],this.nextScopeId=0,this.tensorInfo=new WeakMap,this.profiling=!1,this.activeProfile={newBytes:0,newTensors:0,peakBytes:0,kernels:[],result:null,get kernelNames(){return Array.from(new Set(this.kernels.map(e=>e.name)))}}}dispose(){for(let e in this.registeredVariables)this.registeredVariables[e].dispose()}},sc=class{constructor(e){this.ENV=e,this.registry={},this.registryFactory={},this.pendingBackendInitId=0,this.state=new U5}async ready(){if(this.pendingBackendInit!=null)return this.pendingBackendInit.then(()=>{});if(this.backendInstance!=null)return;let e=this.getSortedBackends();for(let t=0;t<e.length;t++){let n=e[t];if(await this.initializeBackend(n).success){await this.setBackend(n);return}}throw new Error("Could not initialize any backends, all backend initializations failed.")}get backend(){if(this.pendingBackendInit!=null)throw new Error(`Backend '${this.backendName}' has not yet been initialized. Make sure to await tf.ready() or await tf.setBackend() before calling other methods`);if(this.backendInstance==null){let{name:e,asyncInit:t}=this.initializeBackendsAndReturnBest();if(t)throw new Error(`The highest priority backend '${e}' has not yet been initialized. Make sure to await tf.ready() or await tf.setBackend() before calling other methods`);this.setBackend(e)}return this.backendInstance}backendNames(){return Object.keys(this.registryFactory)}findBackend(e){if(!(e in this.registry))if(e in this.registryFactory){let{asyncInit:t}=this.initializeBackend(e);if(t)return null}else return null;return this.registry[e]}findBackendFactory(e){return e in this.registryFactory?this.registryFactory[e].factory:null}registerBackend(e,t,n=1){return e in this.registryFactory?(Ys(`${e} backend was already registered. Reusing existing backend factory.`),!1):(this.registryFactory[e]={factory:t,priority:n},!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:n}=this.initializeBackend(e);if(!(n?await t:t))return!1}return this.backendInstance=this.registry[e],this.setupRegisteredKernels(),this.profiler=new n9(this.backendInstance),!0}setupRegisteredKernels(){Sl(this.backendName).forEach(t=>{t.setupFunc!=null&&t.setupFunc(this.backendInstance)})}disposeRegisteredKernels(e){Sl(e).forEach(n=>{n.disposeFunc!=null&&n.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 n=t.factory();if(n&&!(n instanceof Du)&&typeof n.then=="function"){let s=++this.pendingBackendInitId,r=n.then(a=>s<this.pendingBackendInitId?!1:(this.registry[e]=a,this.pendingBackendInit=null,!0)).catch(a=>(s<this.pendingBackendInitId||(this.pendingBackendInit=null,Ys(`Initialization of backend ${e} failed`),Ys(a.stack||a.message)),!1));return this.pendingBackendInit=r,{success:r,asyncInit:!0}}else return this.registry[e]=n,{success:!0,asyncInit:!1}}catch(n){return Ys(`Initialization of backend ${e} failed`),Ys(n.stack||n.message),{success:!1,asyncInit:!1}}}removeBackend(e){if(!(e in this.registryFactory))throw new Error(`${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 n=e[t],{success:s,asyncInit:r}=this.initializeBackend(n);if(r||s)return{name:n,asyncInit:r}}throw new Error("Could not initialize any backends, all backend initializations failed.")}moveData(e,t){let n=this.state.tensorInfo.get(t),s=n.backend,r=this.readSync(t),a=s.refCount(t);s.disposeData(t,!0),n.backend=e,e.move(t,r,n.shape,n.dtype,a),this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack[this.state.numDataMovesStack.length-1]++}tidy(e,t){let n=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");n=e}let s;return this.scopedRun(()=>this.startScope(n),()=>this.endScope(s),()=>(s=t(),s instanceof Promise&&console.error("Cannot return a Promise inside of tidy."),s))}scopedRun(e,t,n){e();try{let s=n();return t(),s}catch(s){throw t(),s}}nextTensorId(){return sc.nextTensorId++}nextVariableId(){return sc.nextVariableId++}clone(e){let t=z.runKernel(ja,{x:e}),n={x:e},s=a=>({x:()=>{let o="float32",i={x:a},l={dtype:o};return z.runKernel(_a,i,l)}}),r=[];return this.addTapeNode(this.state.activeScope.name,n,[t],s,r,{}),t}runKernel(e,t,n){if(this.backendName==null&&this.backend,!(_h(e,this.backendName)!=null))throw new Error(`Kernel '${e}' not registered for backend '${this.backendName}'`);return this.runKernelFunc({kernelName:e,inputs:t,attrs:n})}shouldCheckForMemLeaks(){return this.ENV.getBool("IS_TEST")}checkKernelForMemLeak(e,t,n){let s=this.backend.numDataIds(),r=0;n.forEach(i=>{r+=i.dtype==="complex64"?3:1});let a=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],o=s-t-r-a;if(o>0)throw new Error(`Backend '${this.backendName}' has an internal memory leak (${o} data ids) after running '${e}'`)}runKernelFunc(e){let t,n=[],s=this.isTapeOn(),r=this.state.numBytes,a=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);let o;this.backendName==null&&this.backend;let i,l=Ym(e)?e.kernelName:this.state.activeScope!=null?this.state.activeScope.name:"";if(Ym(e)){let{kernelName:p,inputs:f,attrs:m}=e;this.backendName==null&&this.backend;let g=_h(p,this.backendName);M(g!=null,()=>`Cannot find registered kernel '${p}' for backend '${this.backendName}'`),o=()=>{let A=this.backend.numDataIds();i=g.kernelFunc({inputs:f,attrs:m,backend:this.backend});let y=Array.isArray(i)?i:[i];this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(p,A,y);let x=y.map(b=>{if(b.rank!=null)return b;let{dataId:v,shape:k,dtype:S}=b;return this.makeTensorFromDataId(v,k,S)});if(s){let b=this.getTensorsForGradient(p,f,x);n=this.saveTensorsForBackwardMode(b)}return x}}else{let{forwardFunc:p}=e,f=m=>{!s||(n=m.map(g=>this.keep(this.clone(g))))};o=()=>{let m=this.backend.numDataIds();i=this.tidy(()=>p(this.backend,f));let g=Array.isArray(i)?i:[i];return this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(l,m,g),g}}let{inputs:u,attrs:c}=e,d=Ym(e)?null:e.backwardsFunc,h;return this.scopedRun(()=>this.state.kernelDepth++,()=>this.state.kernelDepth--,()=>{!this.ENV.getBool("DEBUG")&&!this.state.profiling?t=o():(h=this.profiler.profileKernel(l,u,()=>o()),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(h),t=h.outputs)}),s&&this.addTapeNode(l,u,t,d,n,c),this.state.profiling&&this.state.activeProfile.kernels.push({name:l,bytesAdded:this.state.numBytes-r,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-a,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(u).map(p=>u[p]!=null?u[p].shape:null),outputShapes:t.map(p=>p.shape),kernelTimeMs:h.timeMs,extraInfo:h.extraInfo}),Array.isArray(i)?t:t[0]}saveTensorsForBackwardMode(e){return e.map(n=>this.keep(this.clone(n)))}getTensorsForGradient(e,t,n){let s=Wm(e);if(s!=null){let r=s.inputsToSave||[],a=s.outputsToSave||[],o;s.saveAllInputs?(M(Array.isArray(t),()=>"saveAllInputs is true, expected inputs to be an array."),o=Object.keys(t).map(l=>t[l])):o=r.map(l=>t[l]);let i=n.filter((l,u)=>a[u]);return o.concat(i)}return[]}makeTensor(e,t,n,s){if(e==null)throw new Error("Values passed to engine.makeTensor() are null");n=n||"float32",s=s||this.backend;let r=e;n==="string"&&Br(e[0])&&(r=e.map(i=>Ju(i)));let a=s.write(r,t,n),o=new Ge(t,n,a,this.nextTensorId());if(this.trackTensor(o,s),n==="string"){let i=this.state.tensorInfo.get(a),l=S5(r);this.state.numBytes+=l-i.bytes,i.bytes=l}return o}makeTensorFromDataId(e,t,n,s){n=n||"float32";let r=new Ge(t,n,e,this.nextTensorId());return this.trackTensor(r,s),r}makeVariable(e,t=!0,n,s){n=n||this.nextVariableId().toString(),s!=null&&s!==e.dtype&&(e=e.cast(s));let r=new nc(e,t,n,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 n=0;e.dtype!=="complex64"&&e.dtype!=="string"&&(n=e.size*Fm(e.dtype)),this.state.numBytes+=n,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:n})),e instanceof nc||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 n=e.size*Fm(e.dtype);this.state.numBytes-=n}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,n=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(s=>s.totalBytesSnapshot)),this.state.activeProfile.newBytes=this.state.numBytes-t,this.state.activeProfile.newTensors=this.state.numTensors-n;for(let s of this.state.activeProfile.kernels)s.kernelTimeMs=await s.kernelTimeMs,s.extraInfo=await s.extraInfo;return this.state.activeProfile}isTapeOn(){return this.state.gradientDepth>0&&this.state.kernelDepth===0}addTapeNode(e,t,n,s,r,a){let o={id:this.state.nextTapeNodeId++,kernelName:e,inputs:t,outputs:n,saved:r},i=Wm(e);i!=null&&(s=i.gradFunc),s!=null&&(o.gradient=l=>(l=l.map((u,c)=>{if(u==null){let d=n[c],h=qd(d.size,d.dtype);return this.makeTensor(h,d.shape,d.dtype)}return u}),s(l.length>1?l:l[0],r,a))),this.state.activeTape.push(o)}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=Zm(e),n=new Set(t.map(r=>r.id));for(let r=0;r<this.state.activeScope.track.length;r++){let a=this.state.activeScope.track[r];!a.kept&&!n.has(a.id)&&a.dispose()}let s=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===s.id&&this.track(r)})}gradients(e,t,n,s=!1){if(M(t.length>0,()=>"gradients() received an empty list of xs."),n!=null&&n.dtype!=="float32")throw new Error(`dy must have 'float32' dtype, but has '${n.dtype}'`);let r=this.scopedRun(()=>this.startTape(),()=>this.endTape(),()=>this.tidy("forward",e));M(r instanceof Ge,()=>"The result y returned by f() must be a tensor.");let a=a9(this.state.activeTape,t,r);if(!s&&a.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 o={};o[r.id]=n==null?A9(r.shape):n,o9(o,a,l=>this.tidy(l),y9);let i=t.map(l=>o[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:i}})}customGrad(e){return M(Wr(e),()=>"The f passed in customGrad(f) must be a function."),(...t)=>{M(t.every(o=>o instanceof Ge),()=>"The args passed in customGrad(f)(x1, x2,...) must all be tensors");let n,s={};t.forEach((o,i)=>{s[i]=o});let r=(o,i)=>(n=e(...t,i),M(n.value instanceof Ge,()=>"The function f passed in customGrad(f) must return an object where `obj.value` is a tensor"),M(Wr(n.gradFunc),()=>"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function."),n.value),a=(o,i)=>{let l=n.gradFunc(o,i),u=Array.isArray(l)?l:[l];M(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(...)."),M(u.every(d=>d instanceof Ge),()=>"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns a list of only tensors.");let c={};return u.forEach((d,h)=>{c[h]=()=>d}),c};return this.runKernelFunc({forwardFunc:r,backwardsFunc:a,inputs:s})}}readSync(e){return this.state.tensorInfo.get(e).backend.readSync(e)}read(e){return this.state.tensorInfo.get(e).backend.read(e)}async time(e){let t=Yu(),n=await this.backend.time(e);return n.wallMs=Yu()-t,n}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 U5;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}};sc.nextTensorId=0;sc.nextVariableId=0;function A9(e){let t=Om($t(e),"float32");return z.makeTensor(t,e,"float32")}function H5(){let e=_5();if(e._tfengine==null){let t=new R5(e);e._tfengine=new sc(t)}return VS(e._tfengine.ENV),c9(()=>e._tfengine),e._tfengine}var z=H5();function y9(e,t){let n={a:e,b:t};return z.runKernel(Vr,n)}var rc={};Pe(rc,{isBrowser:()=>G5,isMobile:()=>b9});function x9(){return typeof navigator!="undefined"&&navigator!=null}function b9(e){if(e||x9()){if(e||(e=navigator),e.product==="ReactNative")return!0;let t=e.userAgent||e.vendor||(typeof window!="undefined"?window.opera:"");if(!t){let n=e;return n.userAgentData&&n.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 G5(){return typeof window!="undefined"&&window.document!=null||typeof WorkerGlobalScope!="undefined"}var Fs=Q();Fs.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.")});Fs.registerFlag("IS_BROWSER",()=>G5());Fs.registerFlag("IS_NODE",()=>typeof process!="undefined"&&typeof process.versions!="undefined"&&typeof process.versions.node!="undefined");Fs.registerFlag("IS_CHROME",()=>typeof navigator!="undefined"&&navigator!=null&&navigator.userAgent!=null&&/Chrome/.test(navigator.userAgent)&&/Google Inc/.test(navigator.vendor));Fs.registerFlag("PROD",()=>!1);Fs.registerFlag("TENSORLIKE_CHECK_SHAPE_CONSISTENCY",()=>Fs.getBool("DEBUG"));Fs.registerFlag("DEPRECATION_WARNINGS_ENABLED",()=>!0);Fs.registerFlag("IS_TEST",()=>!1);Fs.registerFlag("CHECK_COMPUTATION_FOR_ERRORS",()=>!0);Fs.registerFlag("WRAP_TO_IMAGEBITMAP",()=>!1);function Qs(e,t){let n=e;if(cn(e))return t==="string"?[]:[e.length];if(!Array.isArray(e))return[];let s=[];for(;Array.isArray(n)||cn(n)&&t!=="string";)s.push(n.length),n=n[0];return Array.isArray(e)&&Q().getBool("TENSORLIKE_CHECK_SHAPE_CONSISTENCY")&&j5(e,s,[]),s}function j5(e,t,n){if(n=n||[],!Array.isArray(e)&&!cn(e)){M(t.length===0,()=>`Element arr[${n.join("][")}] is a primitive, but should be an array/TypedArray of ${t[0]} elements`);return}M(t.length>0,()=>`Element arr[${n.join("][")}] should be a primitive, but is an array of ${e.length} elements`),M(e.length===t[0],()=>`Element arr[${n.join("][")}] should have ${t[0]} elements, but has ${e.length} elements`);let s=t.slice(1);for(let r=0;r<e.length;++r)j5(e[r],s,n.concat(r))}function q5(e,t,n,s){if(e!=="string_or_numeric"){if(e==null)throw new Error("Expected dtype cannot be null.");if(e!=="numeric"&&e!==t||e==="numeric"&&t==="string")throw new Error(`Argument '${n}' passed to '${s}' must be ${e} tensor, but got ${t} tensor`)}}function $(e,t,n,s="numeric"){if(e instanceof Ge)return q5(s,e.dtype,t,n),e;let r=Gd(e);if(r!=="string"&&["bool","int32","float32"].indexOf(s)>=0&&(r=s),q5(s,r,t,n),e==null||!cn(e)&&!Array.isArray(e)&&typeof e!="number"&&typeof e!="boolean"&&typeof e!="string"){let l=e==null?"null":e.constructor.name;throw new Error(`Argument '${t}' passed to '${n}' must be a Tensor or TensorLike, but got '${l}'`)}let a=Qs(e,r);!cn(e)&&!Array.isArray(e)&&(e=[e]);let i=r!=="string"?$h(e,r):Ca(e,[],!0);return z.makeTensor(i,a,r)}function ac(e,t,n,s="numeric"){if(!Array.isArray(e))throw new Error(`Argument ${t} passed to ${n} must be a \`Tensor[]\` or \`TensorLike[]\``);return e.map((a,o)=>$(a,`${t}[${o}]`,n,s))}var X5="__op";function W(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 ${t.length} keys.`);let n=t[0],s=e[n];n.endsWith("_")&&(n=n.substring(0,n.length-1)),n=n+X5;let r=(...a)=>{z.startScope(n);try{let o=s(...a);return Mm(o)&&console.error("Cannot return a Promise inside of tidy."),z.endScope(o),o}catch(o){throw z.endScope(null),o}};return Object.defineProperty(r,"name",{value:n,configurable:!0}),r}function v9(e,t){let n=$(e,"real","complex"),s=$(t,"imag","complex");An(n.shape,s.shape,`real and imag shapes, ${n.shape} and ${s.shape}, must match in call to tf.complex().`);let r={real:n,imag:s};return z.runKernel(Yd,r)}var qr=W({complex_:v9});function Xr(e,t,n,s){if(s==null&&(s=Gd(e)),s==="complex64")throw new Error("Cannot construct a complex64 tensor directly. Please use tf.complex(real, imag).");if(!cn(e)&&!Array.isArray(e)&&typeof e!="number"&&typeof e!="boolean"&&typeof e!="string")throw new Error("values passed to tensor(values) must be a number/boolean/string or an array of numbers/booleans/strings, or a TypedArray");if(t!=null){Pm(t);let r=$t(t),a=$t(n);M(r===a,()=>`Based on the provided shape, [${t}], the tensor should have ${r} values but has ${a}`);for(let o=0;o<n.length;++o){let i=n[o],l=o===n.length-1?i!==$t(t.slice(o)):!0;M(n[o]===t[o]||!l,()=>`Error creating a new Tensor. Inferred shape (${n}) does not match the provided shape (${t}). `)}}return!cn(e)&&!Array.isArray(e)&&(e=[e]),t=t||n,e=s!=="string"?$h(e,s):Ca(e,[],!0),z.makeTensor(e,t,s)}function dn(e,t,n){let s=Qs(e,n);return Xr(e,t,s,n)}var Jm={float32:4,float16:2,int32:4,uint16:2,uint8:1,bool:1,complex64:8},Mh=4;async function w9(e,t){let n=[],s=[],r=Array.isArray(e)?e.map(o=>o.name):Object.keys(e);for(let o=0;o<r.length;++o){let i=r[o],l=Array.isArray(e)?e[o].tensor:e[i];if(l.dtype!=="float32"&&l.dtype!=="int32"&&l.dtype!=="bool"&&l.dtype!=="string"&&l.dtype!=="complex64")throw new Error(`Unsupported dtype in weight '${i}': ${l.dtype}`);let u={name:i,shape:l.shape,dtype:l.dtype};if(l.dtype==="string"){let c=new Promise(async d=>{let h=await l.bytes(),p=h.reduce((g,A)=>g+A.length,0)+Mh*h.length,f=new Uint8Array(p),m=0;for(let g=0;g<h.length;g++){let A=h[g],y=new Uint8Array(new Uint32Array([A.length]).buffer);f.set(y,m),m+=Mh,f.set(A,m),m+=A.length}d(f)});s.push(c)}else s.push(l.data());t!=null&&(u.group=t),n.push(u)}let a=await Promise.all(s);return{data:k9(a),specs:n}}function K5(e,t){let n={},s,r=0;for(let a of t){let o=a.name,i=a.dtype,l=a.shape,u=$t(l),c;if("quantization"in a){let d=a.quantization;if(d.dtype==="uint8"||d.dtype==="uint16"){if(!("min"in d&&"scale"in d))throw new Error(`Weight ${a.name} with quantization ${d.dtype} doesn't have corresponding metadata min and scale.`)}else if(d.dtype==="float16"){if(i!=="float32")throw new Error(`Weight ${a.name} is quantized with ${d.dtype} which only supports weights of type float32 not ${i}.`)}else throw new Error(`Weight ${a.name} has unknown quantization dtype ${d.dtype}. Supported quantization dtypes are: 'uint8', 'uint16', and 'float16'.`);let h=Jm[d.dtype],p=e.slice(r,r+u*h),f=d.dtype==="uint8"?new Uint8Array(p):new Uint16Array(p);if(i==="float32")if(d.dtype==="uint8"||d.dtype==="uint16"){c=new Float32Array(f.length);for(let m=0;m<f.length;m++){let g=f[m];c[m]=g*d.scale+d.min}}else if(d.dtype==="float16")s===void 0&&(s=E9()),c=s(f);else throw new Error(`Unsupported quantization type ${d.dtype} for weight type float32.`);else if(i==="int32"){if(d.dtype!=="uint8"&&d.dtype!=="uint16")throw new Error(`Unsupported quantization type ${d.dtype} for weight type int32.`);c=new Int32Array(f.length);for(let m=0;m<f.length;m++){let g=f[m];c[m]=Math.round(g*d.scale+d.min)}}else throw new Error(`Unsupported dtype in weight '${o}': ${i}`);r+=u*h}else if(i==="string"){let d=$t(a.shape);c=[];for(let h=0;h<d;h++){let p=new Uint32Array(e.slice(r,r+Mh))[0];r+=Mh;let f=new Uint8Array(e.slice(r,r+p));c.push(f),r+=p}}else{let d=Jm[i],h=e.slice(r,r+u*d);if(i==="float32")c=new Float32Array(h);else if(i==="int32")c=new Int32Array(h);else if(i==="bool")c=new Uint8Array(h);else if(i==="complex64"){c=new Float32Array(h);let p=new Float32Array(c.length/2),f=new Float32Array(c.length/2);for(let A=0;A<p.length;A++)p[A]=c[A*2],f[A]=c[A*2+1];let m=dn(p,l,"float32"),g=dn(f,l,"float32");n[o]=qr(m,g),m.dispose(),g.dispose()}else throw new Error(`Unsupported dtype in weight '${o}': ${i}`);r+=u*d}i!=="complex64"&&(n[o]=dn(c,l,i))}return n}function k9(e){if(e===null)throw new Error(`Invalid input value: ${JSON.stringify(e)}`);let t=0,n=[];e.forEach(a=>{if(t+=a.byteLength,n.push(a.byteLength===a.buffer.byteLength?a:new a.constructor(a)),!(a instanceof Float32Array||a instanceof Int32Array||a instanceof Uint8Array))throw new Error(`Unsupported TypedArray subtype: ${a.constructor.name}`)});let s=new Uint8Array(t),r=0;return n.forEach(a=>{s.set(new Uint8Array(a.buffer),r),r+=a.byteLength}),s.buffer}var Qm=typeof Buffer!="undefined"&&(typeof Blob=="undefined"||typeof atob=="undefined"||typeof btoa=="undefined");function Z5(e){return Qm?Buffer.byteLength(e):new Blob([e]).size}function I9(e){if(Qm)return Buffer.from(e).toString("base64");let t=new Uint8Array(e),n="";for(let s=0,r=t.length;s<r;s++)n+=String.fromCharCode(t[s]);return btoa(n)}function S9(e){if(Qm){let s=Buffer.from(e,"base64");return s.buffer.slice(s.byteOffset,s.byteOffset+s.byteLength)}let t=atob(e),n=new Uint8Array(t.length);for(let s=0;s<t.length;++s)n.set([t.charCodeAt(s)],s);return n.buffer}function eg(e){if(e.length===1)return e[0];let t=0;e.forEach(r=>{t+=r.byteLength});let n=new Uint8Array(t),s=0;return e.forEach(r=>{n.set(new Uint8Array(r),s),s+=r.byteLength}),n.buffer}function Y5(e){let t="/";for(e=e.trim();e.endsWith(t);)e=e.slice(0,e.length-1);let n=e.split(t);return n[n.length-1]}function J5(e,t){let n={modelTopology:e.modelTopology,format:e.format,generatedBy:e.generatedBy,convertedBy:e.convertedBy,weightsManifest:t};return e.signature!=null&&(n.signature=e.signature),e.userDefinedMetadata!=null&&(n.userDefinedMetadata=e.userDefinedMetadata),e.modelInitializer!=null&&(n.modelInitializer=e.modelInitializer),e.trainingConfig!=null&&(n.trainingConfig=e.trainingConfig),n}async function tg(e,t){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){let[s,r]=await t(e.weightsManifest);n.weightSpecs=s,n.weightData=r}return e.signature!=null&&(n.signature=e.signature),e.userDefinedMetadata!=null&&(n.userDefinedMetadata=e.userDefinedMetadata),e.modelInitializer!=null&&(n.modelInitializer=e.modelInitializer),n}function oc(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:Z5(JSON.stringify(e.modelTopology)),weightSpecsBytes:e.weightSpecs==null?0:Z5(JSON.stringify(e.weightSpecs)),weightDataBytes:e.weightData==null?0:e.weightData.byteLength}}function C9(){let e=n=>{let s=n<<13,r=0;for(;(s&8388608)==0;)r-=8388608,s<<=1;return s&=~8388608,r+=947912704,s|r},t=new Uint32Array(2048);t[0]=0;for(let n=1;n<1024;n++)t[n]=e(n);for(let n=1024;n<2048;n++)t[n]=939524096+(n-1024<<13);return t}function T9(){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 N9(){let e=new Uint32Array(64);for(let t=0;t<64;t++)e[t]=1024;return e[0]=e[32]=0,e}function E9(){let e=C9(),t=T9(),n=N9();return s=>{let r=new ArrayBuffer(4*s.length),a=new Uint32Array(r);for(let o=0;o<s.length;o++){let i=s[o],l=e[n[i>>10]+(i&1023)]+t[i>>10];a[o]=l}return new Float32Array(r)}}var Rt=class{constructor(){this.saveRouters=[],this.loadRouters=[]}static getInstance(){return Rt.instance==null&&(Rt.instance=new Rt),Rt.instance}static registerSaveRouter(e){Rt.getInstance().saveRouters.push(e)}static registerLoadRouter(e){Rt.getInstance().loadRouters.push(e)}static getSaveHandlers(e){return Rt.getHandlers(e,"save")}static getLoadHandlers(e,t){return Rt.getHandlers(e,"load",t)}static getHandlers(e,t,n){let s=[];return(t==="load"?Rt.getInstance().loadRouters:Rt.getInstance().saveRouters).forEach(a=>{let o=a(e,n);o!==null&&s.push(o)}),s}},R9=e=>Rt.registerSaveRouter(e),_9=e=>Rt.registerLoadRouter(e),D9=e=>Rt.getSaveHandlers(e),$9=(e,t)=>Rt.getLoadHandlers(e,t),ng="tensorflowjs",sg=1,Ro="models_store",Kr="model_info_store";function Q5(){if(!Q().getBool("IS_BROWSER"))throw new Error("Failed to obtain IndexedDB factory because the current environmentis not a web browser.");let e=typeof window=="undefined"?self:window,t=e.indexedDB||e.mozIndexedDB||e.webkitIndexedDB||e.msIndexedDB||e.shimIndexedDB;if(t==null)throw new Error("The current browser does not appear to support IndexedDB.");return t}function rg(e){let t=e.result;t.createObjectStore(Ro,{keyPath:"modelPath"}),t.createObjectStore(Kr,{keyPath:"modelPath"})}var _o=class{constructor(e){if(this.indexedDB=Q5(),e==null||!e)throw new Error("For IndexedDB, modelPath must not be null, undefined or empty.");this.modelPath=e}async save(e){if(e.modelTopology instanceof ArrayBuffer)throw new Error("BrowserLocalStorage.save() does not support saving model topology in binary formats yet.");return this.databaseAction(this.modelPath,e)}async load(){return this.databaseAction(this.modelPath)}databaseAction(e,t){return new Promise((n,s)=>{let r=this.indexedDB.open(ng,sg);r.onupgradeneeded=()=>rg(r),r.onsuccess=()=>{let a=r.result;if(t==null){let o=a.transaction(Ro,"readonly"),l=o.objectStore(Ro).get(this.modelPath);l.onsuccess=()=>{if(l.result==null)return a.close(),s(new Error(`Cannot find model with path '${this.modelPath}' in IndexedDB.`));n(l.result.modelArtifacts)},l.onerror=u=>(a.close(),s(l.error)),o.oncomplete=()=>a.close()}else{let o=oc(t),i=a.transaction(Kr,"readwrite"),l=i.objectStore(Kr),u=l.put({modelPath:this.modelPath,modelArtifactsInfo:o}),c;u.onsuccess=()=>{c=a.transaction(Ro,"readwrite");let h=c.objectStore(Ro).put({modelPath:this.modelPath,modelArtifacts:t,modelArtifactsInfo:o});h.onsuccess=()=>n({modelArtifactsInfo:o}),h.onerror=p=>{l=i.objectStore(Kr);let f=l.delete(this.modelPath);f.onsuccess=()=>(a.close(),s(h.error)),f.onerror=m=>(a.close(),s(h.error))}},u.onerror=d=>(a.close(),s(u.error)),i.oncomplete=()=>{c==null?a.close():c.oncomplete=()=>a.close()}}},r.onerror=a=>s(r.error)})}};_o.URL_SCHEME="indexeddb://";var ex=e=>Q().getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(_o.URL_SCHEME)?F9(e.slice(_o.URL_SCHEME.length)):null;Rt.registerSaveRouter(ex);Rt.registerLoadRouter(ex);function F9(e){return new _o(e)}function O9(e){return e.startsWith(_o.URL_SCHEME)?e.slice(_o.URL_SCHEME.length):e}var P9=class{constructor(){this.indexedDB=Q5()}async listModels(){return new Promise((e,t)=>{let n=this.indexedDB.open(ng,sg);n.onupgradeneeded=()=>rg(n),n.onsuccess=()=>{let s=n.result,r=s.transaction(Kr,"readonly"),o=r.objectStore(Kr).getAll();o.onsuccess=()=>{let i={};for(let l of o.result)i[l.modelPath]=l.modelArtifactsInfo;e(i)},o.onerror=i=>(s.close(),t(o.error)),r.oncomplete=()=>s.close()},n.onerror=s=>t(n.error)})}async removeModel(e){return e=O9(e),new Promise((t,n)=>{let s=this.indexedDB.open(ng,sg);s.onupgradeneeded=()=>rg(s),s.onsuccess=()=>{let r=s.result,a=r.transaction(Kr,"readwrite"),o=a.objectStore(Kr),i=o.get(e),l;i.onsuccess=()=>{if(i.result==null)return r.close(),n(new Error(`Cannot find model with path '${e}' in IndexedDB.`));{let u=o.delete(e),c=()=>{l=r.transaction(Ro,"readwrite");let h=l.objectStore(Ro).delete(e);h.onsuccess=()=>t(i.result.modelArtifactsInfo),h.onerror=p=>n(i.error)};u.onsuccess=c,u.onerror=d=>(c(),r.close(),n(i.error))}},i.onerror=u=>(r.close(),n(i.error)),a.oncomplete=()=>{l==null?r.close():l.oncomplete=()=>r.close()}},s.onerror=r=>n(s.error)})}},vr="/",Tl="tensorflowjs_models",tx="info",M9="model_topology",z9="weight_specs",L9="weight_data",B9="model_metadata";function nx(e){return{info:[Tl,e,tx].join(vr),topology:[Tl,e,M9].join(vr),weightSpecs:[Tl,e,z9].join(vr),weightData:[Tl,e,L9].join(vr),modelMetadata:[Tl,e,B9].join(vr)}}function sx(e){for(let t of Object.values(e))window.localStorage.removeItem(t)}function W9(e){let t=e.split(vr);if(t.length<3)throw new Error(`Invalid key format: ${e}`);return t.slice(1,t.length-1).join(vr)}function V9(e){return e.startsWith(Do.URL_SCHEME)?e.slice(Do.URL_SCHEME.length):e}var Do=class{constructor(e){if(!Q().getBool("IS_BROWSER")||typeof window=="undefined"||typeof window.localStorage=="undefined")throw new Error("The current environment does not support local storage.");if(this.LS=window.localStorage,e==null||!e)throw new Error("For local storage, modelPath must not be null, undefined or empty.");this.modelPath=e,this.keys=nx(this.modelPath)}async save(e){if(e.modelTopology instanceof ArrayBuffer)throw new Error("BrowserLocalStorage.save() does not support saving model topology in binary formats yet.");{let t=JSON.stringify(e.modelTopology),n=JSON.stringify(e.weightSpecs),s=oc(e);try{this.LS.setItem(this.keys.info,JSON.stringify(s)),this.LS.setItem(this.keys.topology,t),this.LS.setItem(this.keys.weightSpecs,n),this.LS.setItem(this.keys.weightData,I9(e.weightData));let r={format:e.format,generatedBy:e.generatedBy,convertedBy:e.convertedBy,signature:e.signature!=null?e.signature:void 0,userDefinedMetadata:e.userDefinedMetadata!=null?e.userDefinedMetadata:void 0,modelInitializer:e.modelInitializer!=null?e.modelInitializer:void 0,trainingConfig:e.trainingConfig!=null?e.trainingConfig:void 0};return this.LS.setItem(this.keys.modelMetadata,JSON.stringify(r)),{modelArtifactsInfo:s}}catch(r){throw sx(this.keys),new Error(`Failed to save model '${this.modelPath}' to local storage: size quota being exceeded is a possible cause of this failure: modelTopologyBytes=${s.modelTopologyBytes}, weightSpecsBytes=${s.weightSpecsBytes}, weightDataBytes=${s.weightDataBytes}.`)}}}async load(){let e=JSON.parse(this.LS.getItem(this.keys.info));if(e==null)throw new Error(`In local storage, there is no model with name '${this.modelPath}'`);if(e.modelTopologyType!=="JSON")throw new Error("BrowserLocalStorage does not support loading non-JSON model topology yet.");let t={},n=JSON.parse(this.LS.getItem(this.keys.topology));if(n==null)throw new Error(`In local storage, the topology of model '${this.modelPath}' is missing.`);t.modelTopology=n;let s=JSON.parse(this.LS.getItem(this.keys.weightSpecs));if(s==null)throw new Error(`In local storage, the weight specs of model '${this.modelPath}' are missing.`);t.weightSpecs=s;let r=this.LS.getItem(this.keys.modelMetadata);if(r!=null){let o=JSON.parse(r);t.format=o.format,t.generatedBy=o.generatedBy,t.convertedBy=o.convertedBy,o.signature!=null&&(t.signature=o.signature),o.userDefinedMetadata!=null&&(t.userDefinedMetadata=o.userDefinedMetadata),o.modelInitializer!=null&&(t.modelInitializer=o.modelInitializer),o.trainingConfig!=null&&(t.trainingConfig=o.trainingConfig)}let a=this.LS.getItem(this.keys.weightData);if(a==null)throw new Error(`In local storage, the binary weight values of model '${this.modelPath}' are missing.`);return t.weightData=S9(a),t}};Do.URL_SCHEME="localstorage://";var rx=e=>Q().getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(Do.URL_SCHEME)?U9(e.slice(Do.URL_SCHEME.length)):null;Rt.registerSaveRouter(rx);Rt.registerLoadRouter(rx);function U9(e){return new Do(e)}var H9=class{constructor(){M(Q().getBool("IS_BROWSER"),()=>"Current environment is not a web browser"),M(typeof window=="undefined"||typeof window.localStorage!="undefined",()=>"Current browser does not appear to support localStorage"),this.LS=window.localStorage}async listModels(){let e={},t=Tl+vr,n=vr+tx;for(let s=0;s<this.LS.length;++s){let r=this.LS.key(s);if(r.startsWith(t)&&r.endsWith(n)){let a=W9(r);e[a]=JSON.parse(this.LS.getItem(r))}}return e}async removeModel(e){e=V9(e);let t=nx(e);if(this.LS.getItem(t.info)==null)throw new Error(`Cannot find model at path '${e}'`);let n=JSON.parse(this.LS.getItem(t.info));return sx(t),n}},Nl="://",is=class{constructor(){this.managers={}}static getInstance(){return is.instance==null&&(is.instance=new is),is.instance}static registerManager(e,t){M(e!=null,()=>"scheme must not be undefined or null."),e.endsWith(Nl)&&(e=e.slice(0,e.indexOf(Nl))),M(e.length>0,()=>"scheme must not be an empty string.");let n=is.getInstance();M(n.managers[e]==null,()=>`A model store manager is already registered for scheme '${e}'.`),n.managers[e]=t}static getManager(e){let t=this.getInstance().managers[e];if(t==null)throw new Error(`Cannot find model manager for scheme '${e}'`);return t}static getSchemes(){return Object.keys(this.getInstance().managers)}};function zh(e){if(e.indexOf(Nl)===-1)throw new Error(`The url string provided does not contain a scheme. Supported schemes are: ${is.getSchemes().join(",")}`);return{scheme:e.split(Nl)[0],path:e.split(Nl)[1]}}async function ax(e,t,n=!1){M(e!==t,()=>`Old path and new path are the same: '${e}'`);let s=Rt.getLoadHandlers(e);M(s.length>0,()=>`Copying failed because no load handler is found for source URL ${e}.`),M(s.length<2,()=>`Copying failed because more than one (${s.length}) load handlers for source URL ${e}.`);let r=s[0],a=Rt.getSaveHandlers(t);M(a.length>0,()=>`Copying failed because no save handler is found for destination URL ${t}.`),M(a.length<2,()=>`Copying failed because more than one (${s.length}) save handlers for destination URL ${t}.`);let o=a[0],i=zh(e).scheme,l=zh(e).path,u=i===zh(e).scheme,c=await r.load();n&&u&&await is.getManager(i).removeModel(l);let d=await o.save(c);return n&&!u&&await is.getManager(i).removeModel(l),d.modelArtifactsInfo}async function G9(){let e=is.getSchemes(),t={};for(let n of e){let s=await is.getManager(n).listModels();for(let r in s){let a=n+Nl+r;t[a]=s[r]}}return t}async function j9(e){let t=zh(e);return is.getManager(t.scheme).removeModel(t.path)}async function q9(e,t){return ax(e,t,!1)}async function X9(e,t){return ax(e,t,!0)}var K9=class{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)}};if(Q().get("IS_BROWSER")){Q().setPlatform("browser",new K9);try{is.registerManager(Do.URL_SCHEME,new H9)}catch(e){}try{is.registerManager(_o.URL_SCHEME,new P9)}catch(e){}}var Z9={importFetch:()=>XI()},ag,Y9=class{constructor(){this.util=bi("util"),this.textEncoder=new this.util.TextEncoder}fetch(e,t){return Q().global.fetch!=null?Q().global.fetch(e,t):(ag==null&&(ag=Z9.importFetch()),ag(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 ${t}`);return this.textEncoder.encode(e)}decode(e,t){return e.length===0?"":new this.util.TextDecoder(t).decode(e)}};Q().get("IS_NODE")&&Q().setPlatform("node",new Y9);function We(e,t="float32",n){return t=t||"float32",Pm(e),new Ut(e,t,n)}function J9(e,t){let n=$(e,"x","cast");if(!I5(t))throw new Error(`Failed to cast to unknown dtype ${t}`);if(t==="string"&&n.dtype!=="string"||t!=="string"&&n.dtype==="string")throw new Error("Only strings can be casted to strings");let s={x:n},r={dtype:t};return z.runKernel(_a,s,r)}var ce=W({cast_:J9});function Q9(e){let n={x:$(e,"x","clone","string_or_numeric")};return z.runKernel(ja,n)}var Os=W({clone_:Q9});function ox(e,t=!1){console.log(e.toString(t))}H5();var eC={buffer:We,cast:ce,clone:Os,print:ox};d9(eC);var _n={};Pe(_n,{browserFiles:()=>iC,browserHTTPRequest:()=>hC,concatenateArrayBuffers:()=>eg,copyModel:()=>q9,decodeWeights:()=>K5,encodeWeights:()=>w9,fromMemory:()=>fC,getLoadHandlers:()=>$9,getModelArtifactsForJSON:()=>tg,getModelArtifactsInfoForJSON:()=>oc,getSaveHandlers:()=>D9,http:()=>lg,isHTTPScheme:()=>ig,listModels:()=>G9,loadWeights:()=>lC,moveModel:()=>X9,registerLoadRouter:()=>_9,registerSaveRouter:()=>R9,removeModel:()=>j9,weightsLoaderFactory:()=>cx,withSaveHandler:()=>mC});var tC="model",nC=".json",sC=".weights.bin";function ix(e){return new Promise(t=>setTimeout(t)).then(e)}var El=class{constructor(e){if(!Q().getBool("IS_BROWSER"))throw new Error("browserDownloads() cannot proceed because the current environment is not a browser.");e.startsWith(El.URL_SCHEME)&&(e=e.slice(El.URL_SCHEME.length)),(e==null||e.length===0)&&(e=tC),this.modelJsonFileName=e+nC,this.weightDataFileName=e+sC}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 n=[{paths:["./"+this.weightDataFileName],weights:e.weightSpecs}],s=J5(e,n),r=window.URL.createObjectURL(new Blob([JSON.stringify(s)],{type:"application/json"})),a=this.modelJsonAnchor==null?document.createElement("a"):this.modelJsonAnchor;if(a.download=this.modelJsonFileName,a.href=r,await ix(()=>a.dispatchEvent(new MouseEvent("click"))),e.weightData!=null){let o=this.weightDataAnchor==null?document.createElement("a"):this.weightDataAnchor;o.download=this.weightDataFileName,o.href=t,await ix(()=>o.dispatchEvent(new MouseEvent("click")))}return{modelArtifactsInfo:oc(e)}}}};El.URL_SCHEME="downloads://";var rC=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 n=new FileReader;n.onload=s=>{let r=JSON.parse(s.target.result),a=r.modelTopology;if(a==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 ${this.jsonFile.name}`));return}if(this.weightsFiles.length===0){e({modelTopology:a});return}let i=tg(r,l=>this.loadWeights(l));e(i)},n.onerror=s=>t(`Failed to read model topology and weights manifest JSON from file '${this.jsonFile.name}'. BrowserFiles supports loading Keras-style tf.Model artifacts only.`),n.readAsText(this.jsonFile)})}loadWeights(e){let t=[],n=[];for(let a of e)t.push(...a.weights),n.push(...a.paths);let s=this.checkManifestAndWeightFiles(e),r=n.map(a=>this.loadWeightsFile(a,s[a]));return Promise.all(r).then(a=>[t,eg(a)])}loadWeightsFile(e,t){return new Promise((n,s)=>{let r=new FileReader;r.onload=a=>{let o=a.target.result;n(o)},r.onerror=a=>s(`Failed to weights data from file of path '${e}'.`),r.readAsArrayBuffer(t)})}checkManifestAndWeightFiles(e){let t=[],n=this.weightsFiles.map(r=>Y5(r.name)),s={};for(let r of e)r.paths.forEach(a=>{let o=Y5(a);if(t.indexOf(o)!==-1)throw new Error(`Duplicate file basename found in weights manifest: '${o}'`);if(t.push(o),n.indexOf(o)===-1)throw new Error(`Weight file with basename '${o}' is not provided.`);s[a]=this.weightsFiles[n.indexOf(o)]});if(t.length!==this.weightsFiles.length)throw new Error(`Mismatch in the number of files in weights manifest (${t.length}) and the number of weight files provided (${this.weightsFiles.length}).`);return s}},aC=e=>Q().getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(El.URL_SCHEME)?oC(e.slice(El.URL_SCHEME.length)):null;Rt.registerSaveRouter(aC);function oC(e="model"){return new El(e)}function iC(e){return new rC(e)}function lx(e,t,n,s){o(e),n=n==null?0:n,s=s==null?1:s,i(n,s);let r=0,a=l=>(l.then(u=>{let c=n+ ++r/e.length*(s-n);return t(c),u}),l);function o(l){M(l!=null&&Array.isArray(l)&&l.length>0,()=>"promises must be a none empty array")}function i(l,u){M(l>=0&&l<=1,()=>`Progress fraction must be in range [0, 1], but got startFraction ${l}`),M(u>=0&&u<=1,()=>`Progress fraction must be in range [0, 1], but got endFraction ${u}`),M(u>=l,()=>`startFraction must be no more than endFraction, but got startFraction ${l} and endFraction ${u}`)}return Promise.all(e.map(a))}async function ux(e,t){t==null&&(t={});let n=t.fetchFunc==null?Q().platform.fetch:t.fetchFunc,s=e.map(d=>n(d,t.requestInit,{isBinary:!0})),r=0,a=.5,i=(t.onProgress==null?await Promise.all(s):await lx(s,t.onProgress,r,a)).map(d=>d.arrayBuffer()),l=.5,u=1;return t.onProgress==null?await Promise.all(i):await lx(i,t.onProgress,l,u)}async function lC(e,t="",n,s){return cx(o=>ux(o,{requestInit:s}))(e,t,n)}function cx(e){return async(t,n="",s)=>{let r=t.map(()=>!1),a={},o=s!=null?s.map(()=>!1):[],i=[];if(t.forEach((p,f)=>{let m=0;p.weights.forEach(g=>{let A="quantization"in g?g.quantization.dtype:g.dtype,y=Jm[A]*$t(g.shape),x=()=>{r[f]=!0,a[f]==null&&(a[f]=[]),a[f].push({manifestEntry:g,groupOffset:m,sizeBytes:y})};s!=null?s.forEach((b,v)=>{b===g.name&&(x(),o[v]=!0)}):x(),i.push(g.name),m+=y})}),!o.every(p=>p)){let p=s.filter((f,m)=>!o[m]);throw new Error(`Could not find weights in manifest with names: ${p.join(", ")}.
Manifest JSON has weights with names: ${i.join(", ")}.`)}let l=r.reduce((p,f,m)=>(f&&p.push(m),p),[]),u=[];l.forEach(p=>{t[p].paths.forEach(f=>{let m=n+(n.endsWith("/")?"":"/")+f;u.push(m)})});let c=await e(u),d={},h=0;return l.forEach(p=>{let f=t[p].paths.length,m=0;for(let b=0;b<f;b++)m+=c[h+b].byteLength;let g=new ArrayBuffer(m),A=new Uint8Array(g),y=0;for(let b=0;b<f;b++){let v=new Uint8Array(c[h+b]);A.set(v,y),y+=v.byteLength}a[p].forEach(b=>{let v=g.slice(b.groupOffset,b.groupOffset+b.sizeBytes),k=K5(v,[b.manifestEntry]);for(let S in k)d[S]=k[S]}),h+=f}),d}}var uC="application/octet-stream",cC="application/json",og=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?(M(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=Q().platform.fetch,M(e!=null&&e.length>0,()=>"URL path for http must not be null, undefined or empty."),Array.isArray(e)&&M(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 n=[{paths:["./model.weights.bin"],weights:e.weightSpecs}],s=J5(e,n);t.body.append("model.json",new Blob([JSON.stringify(s)],{type:cC}),"model.json"),e.weightData!=null&&t.body.append("model.weights.bin",new Blob([e.weightData],{type:uC}),"model.weights.bin");let r=await this.fetch(this.path,t);if(r.ok)return{modelArtifactsInfo:oc(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 a=`Failed to parse model JSON of response from ${this.path}.`;throw this.path.endsWith(".pb")?a+=" 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.":a+=" Please make sure the server is serving valid JSON for this request.",new Error(a)}let n=t.modelTopology,s=t.weightsManifest;if(n==null&&s==null)throw new Error(`The JSON from HTTP path ${this.path} contains neither model topology or manifest for weights.`);return tg(t,r=>this.loadWeights(r))}async loadWeights(e){let t=Array.isArray(this.path)?this.path[1]:this.path,[n,s]=dC(t),r=this.weightPathPrefix||n,a=[];for(let u of e)a.push(...u.weights);let o=[],i=[];for(let u of e)for(let c of u.paths)this.weightUrlConverter!=null?i.push(this.weightUrlConverter(c)):o.push(r+c+s);this.weightUrlConverter&&o.push(...await Promise.all(i));let l=await ux(o,{requestInit:this.requestInit,fetchFunc:this.fetch,onProgress:this.onProgress});return[a,eg(l)]}};og.URL_SCHEME_REGEX=/^https?:\/\//;function dC(e){let t=e.lastIndexOf("/"),n=e.lastIndexOf("?"),s=e.substring(0,t),r=n>t?e.substring(n):"";return[s+"/",r]}function ig(e){return e.match(og.URL_SCHEME_REGEX)!=null}var dx=(e,t)=>{if(typeof fetch=="undefined"&&(t==null||t.fetchFunc==null))return null;{let n=!0;if(Array.isArray(e)?n=e.every(s=>ig(s)):n=ig(e),n)return lg(e,t)}return null};Rt.registerSaveRouter(dx);Rt.registerLoadRouter(dx);function lg(e,t){return new og(e,t)}function hC(e,t){return lg(e,t)}var ug=class{constructor(e){this.modelArtifacts=e}async load(){return this.modelArtifacts}},pC=class{constructor(e){this.saveHandler=e}async save(e){return this.saveHandler(e)}};function fC(e,t,n,s){return arguments.length===1?e.modelTopology!=null||e.weightSpecs!=null?new ug(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 ug({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 ug({modelTopology:e,weightSpecs:t,weightData:n,trainingConfig:s}))}function mC(e){return new pC(e)}var hx={};Pe(hx,{confusionMatrix:()=>bC});function gC(e,t,n=!1,s=!1){let r=$(e,"a","matMul"),a=$(t,"b","matMul");[r,a]=Ct(r,a);let o={a:r,b:a},i={transposeA:n,transposeB:s};return z.runKernel(Ra,o,i)}var Ve=W({matMul_:gC});function AC(e,t,n=1,s=0){if(t<2)throw new Error(`Error in oneHot: depth must be >=2, but it is ${t}`);let a={indices:$(e,"indices","oneHot","int32")},o={depth:t,onValue:n,offValue:s};return z.runKernel(so,a,o)}var ic=W({oneHot_:AC});function yC(e,t){let n=$(e,"x","transpose");if(t==null&&(t=n.shape.map((a,o)=>o).reverse()),M(n.rank===t.length,()=>`Error in transpose: rank of input ${n.rank} must match length of perm ${t}.`),t.forEach(a=>{M(a>=0&&a<n.rank,()=>`All entries in 'perm' must be between 0 and ${n.rank-1} but got ${t}`)}),n.rank<=1)return n.clone();let s={x:n},r={perm:t};return z.runKernel(ko,s,r)}var Xe=W({transpose_:yC});function xC(e,t,n){let s=$(e,"labels","confusionMatrix"),r=$(t,"predictions","confusionMatrix");M(n==null||n>0&&Number.isInteger(n),()=>`If provided, numClasses must be a positive integer, but got ${n}`),M(s.rank===1,()=>`Expected the rank of labels to be 1, but got ${s.rank}`),M(r.rank===1,()=>`Expected the rank of predictions to be 1, but got ${r.rank}`),M(s.shape[0]===r.shape[0],()=>`Mismatch in the number of examples: ${s.shape[0]} vs. ${r.shape[0]}. Labels and predictions should have the same number of elements.`),M(n>0&&Number.isInteger(n),()=>`numClasses is required to be a positive integer, but got ${n}`);let a=ic(ce(s,"int32"),n),o=ic(ce(r,"int32"),n),i=Xe(a),l=Ve(i,o);return ce(l,"int32")}var bC=W({confusionMatrix_:xC}),ls={};Pe(ls,{fromPixels:()=>TC,fromPixelsAsync:()=>SC,toPixels:()=>CC});function Lh(e,t,n){if(Sa(e),t!=null&&t.length!==3)throw new Error("tensor3d() requires shape to have three numbers");let s=Qs(e,n);if(s.length!==3&&s.length!==1)throw new Error("tensor3d() requires values to be number[][][] or flat/TypedArray");if(s.length===1&&t==null)throw new Error("tensor3d() requires shape to be provided when `values` are a flat array");return Xr(e,t,s,n)}var Rl;function px(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 n=!1,s=!1,r=!1,a=!1,o=!1,i=!1;if(e.data instanceof Uint8Array)n=!0;else if(typeof ImageData!="undefined"&&e instanceof ImageData)s=!0;else if(typeof HTMLVideoElement!="undefined"&&e instanceof HTMLVideoElement)r=!0;else if(typeof HTMLImageElement!="undefined"&&e instanceof HTMLImageElement)a=!0;else if(e.getContext!=null)o=!0;else if(typeof ImageBitmap!="undefined"&&e instanceof ImageBitmap)i=!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 ${e.constructor.name}`);if(r){let f=2;if(r&&e.readyState<f)throw new Error("The video element has not loaded data yet. Please wait for `loadeddata` event on the <video> element.")}if(_h(Rh,z.backendName)!=null){let f={pixels:e},m={numChannels:t};return z.runKernel(Rh,f,m)}let[u,c]=r?[e.videoWidth,e.videoHeight]:[e.width,e.height],d;o?d=e.getContext("2d").getImageData(0,0,u,c).data:s||n?d=e.data:(a||r||i)&&(Rl==null&&(Rl=document.createElement("canvas").getContext("2d")),Rl.canvas.width=u,Rl.canvas.height=c,Rl.drawImage(e,0,0,u,c),d=Rl.getImageData(0,0,u,c).data);let h;if(t===4)h=new Int32Array(d);else{let f=u*c;h=new Int32Array(f*t);for(let m=0;m<f;m++)for(let g=0;g<t;++g)h[m*t+g]=d[m*4+g]}return Lh(h,[c,u,t],"int32")}function vC(e){return e!=null&&e.data instanceof Uint8Array}function wC(){return typeof window!="undefined"&&typeof ImageBitmap!="undefined"&&window.hasOwnProperty("createImageBitmap")}function kC(e){return e!=null&&e.width!==0&&e.height!==0}function IC(e){return wC()&&!(e instanceof ImageBitmap)&&kC(e)&&!vC(e)}async function SC(e,t=3){let n=null;if(Q().getBool("WRAP_TO_IMAGEBITMAP")&&IC(e)){let s;try{s=await createImageBitmap(e,{premultiplyAlpha:"none"})}catch(r){s=null}s!=null&&s.width===e.width&&s.height===e.height?n=s:n=e}else n=e;return px(n,t)}async function CC(e,t){let n=$(e,"img","toPixels");if(!(e instanceof Ge)){let u=n;n=ce(u,"int32"),u.dispose()}if(n.rank!==2&&n.rank!==3)throw new Error(`toPixels only supports rank 2 or 3 tensors, got rank ${n.rank}.`);let[s,r]=n.shape.slice(0,2),a=n.rank===2?1:n.shape[2];if(a>4||a===2)throw new Error(`toPixels only supports depth of size 1, 3 or 4 but got ${a}`);if(n.dtype!=="float32"&&n.dtype!=="int32")throw new Error(`Unsupported type for toPixels: ${n.dtype}. Please use float32 or int32 tensors.`);let o=await n.data(),i=n.dtype==="float32"?255:1,l=new Uint8ClampedArray(r*s*4);for(let u=0;u<s*r;++u){let c=[0,0,0,255];for(let h=0;h<a;h++){let p=o[u*a+h];if(n.dtype==="float32"){if(p<0||p>1)throw new Error(`Tensor values for a float32 Tensor must be in the range [0 - 1] but encountered ${p}.`)}else if(n.dtype==="int32"&&(p<0||p>255))throw new Error(`Tensor values for a int32 Tensor must be in the range [0 - 255] but encountered ${p}.`);a===1?(c[0]=p*i,c[1]=p*i,c[2]=p*i):c[h]=p*i}let d=u*4;l[d+0]=Math.round(c[0]),l[d+1]=Math.round(c[1]),l[d+2]=Math.round(c[2]),l[d+3]=Math.round(c[3])}if(t!=null){t.width=r,t.height=s;let u=t.getContext("2d"),c=new ImageData(l,r,s);u.putImageData(c,0,0)}return n!==e&&n.dispose(),l}var TC=W({fromPixels_:px}),cg={};Pe(cg,{prepareAndValidate:()=>fx});function fx(e,t){let n=e.shape.length,s=t.shape.length;if(n<1)throw new Error(`tf.gatherND() expects the input to be rank 1 or higher, but the rank was ${n}.`);if(s<1)throw new Error(`tf.gatherND() expects the indices to be rank 1 or higher, but the rank was ${s}.`);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[s-1]>n)throw new Error(`index innermost dimension length must be <= tensor rank; saw: ${t.shape[s-1]} vs. ${n}`);if($t(e.shape)===0)throw new Error(`Requested more than 0 entries, but input is empty. Input shape: ${e.shape}.`);let r=t.shape,a=r[r.length-1],o=1;for(let d=0;d<r.length-1;++d)o*=r[d];let i=e.shape,l=r.slice();l.pop();let u=1;for(let d=a;d<n;++d)u*=i[d],l.push(i[d]);let c=[...vi(e.shape).map(d=>d/u),1].slice(0,a);return[l,o,u,c]}var dg={};Pe(dg,{calculateShapes:()=>mx,validateInput:()=>pg,validateUpdateShape:()=>hg});function hg(e,t,n){let s=t.rank>1?t.shape[t.rank-1]:1,r=t.rank>1?t.rank-1:1,a=`Must have updates.shape = indices.shape[:batchDim] + shape[sliceDim:], got updates.shape: ${n.shape}, indices.shape: ${t.shape}, shape: ${e}, sliceDim: ${s}, and batchDim: ${r}.`;if(n.rank<r)throw new Error(a+` update.rank < ${r}. `);if(e.length<s+(n.rank-r))throw new Error(a+` Output shape length < ${s+(n.rank-r)}`);if(n.rank!==r+e.length-s)throw new Error(a+` update.rank != ${r+e.length-s}`);for(let o=0;o<r;++o)if(n.shape[o]!==t.shape[o])throw new Error(a+` updates.shape[${o}] (${n.shape[o]}) != indices.shape[${o}] (${t.shape[o]}).`);for(let o=0;o<n.rank-r;++o)if(n.shape[o+r]!==e[o+s])throw new Error(a+` updates.shape[${o+r}] (${n.shape[o+r]}) != shape[${o+r}] (${e[o+r]})`)}function pg(e,t,n){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(n.length<1)throw new Error(`Output rank must be greater or equal to 1, but got shape: ${n}`);if(n.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: ${e.shape}`)}hg(n,t,e)}function mx(e,t,n){let s=t.shape.length,r=s>1?t.shape[s-1]:1,a=n.length,o=1;for(let d=r;d<a;++d)o*=n[d];let i=r<1?1:r,l=$t(t.shape)/i,u=[...vi(n.slice(0,r)),1],c=$t(n);return{sliceRank:r,numUpdates:l,sliceSize:o,strides:u,outputSize:c}}var xn={};Pe(xn,{assertParamsValid:()=>NC,computeFlatOffset:()=>RC,computeOutShape:()=>gx,getNormalizedAxes:()=>bx,isSliceContinous:()=>EC,maskToAxes:()=>Bh,parseSliceParams:()=>Cx,sliceInfo:()=>_C,startForAxis:()=>Ix,startIndicesWithElidedDims:()=>vx,stopForAxis:()=>Sx,stopIndicesWithElidedDims:()=>wx,stridesForAxis:()=>kx,stridesWithElidedDims:()=>Ax});function NC(e,t,n){let s=e.shape.length;M(s===t.length,()=>`Error in slice${s}D: Length of begin ${t} must match the rank of the array (${s}).`),M(s===n.length,()=>`Error in slice${s}D: Length of size ${n} must match the rank of the array (${s}).`);for(let r=0;r<s;++r)M(t[r]+n[r]<=e.shape[r],()=>`Error in slice${s}D: begin[${r}] + size[${r}] (${t[r]+n[r]}) would overflow input.shape[${r}] (${e.shape[r]})`)}function Bh(e){let t=[],n=0;for(;e>0;)e&1&&t.push(n),e/=2,n++;return t}function gx(e,t,n){let s=[];for(let r=0;r<e.length;r++)s[r]=Math.ceil((t[r]-e[r])/n[r]);return s}function Ax(e,t,n,s){let r=[...e];for(let a=r.length;a<s.length;a++)r.push(1);for(let a=0;a<n;a++)a===0?r[t]=1:(r.splice(t,0,1),r.pop());return r}function yx(e,t,n){return n<=e?n:n-(t-1)}function xx(e,t){let n=[];for(let s=0;s<e;s++)n.push(t+s);return n}function bx(e,t,n,s,r,a,o,i,l){let u=e.length,c=new Array(u),d=new Array(u),h=new Array(u);if(t.length&&n>0){let p=t[0],f=n+1;c=vx(o,p,f,s,e),d=wx(i,p,f,r,e),h=Ax(a,p,f,e)}else for(let p=0;p<u;p++)c[p]=Ix(o,s,a,e,p,l),d[p]=Sx(i,r,a,e,p,l),h[p]=kx(a,p,l);return{begin:c,end:d,strides:h}}function vx(e,t,n,s,r){let a=[...r],o=xx(n,t);for(let i=0;i<a.length;i++)if(o.indexOf(i)>-1)a[i]=0;else{let l=yx(t,n,i),u=s[l];e&1<<l&&(u=0),a[i]=u}return a}function wx(e,t,n,s,r){let a=[...r],o=xx(n,t);for(let i=0;i<a.length;i++)if(o.indexOf(i)>-1)a[i]=Number.MAX_SAFE_INTEGER;else{let l=yx(t,n,i),u=s[l];e&1<<l&&(u=Number.MAX_SAFE_INTEGER),a[i]=u}for(let i=0;i<a.length;i++){let l=r[i];a[i]<0&&(a[i]+=l),a[i]=$u(0,a[i],r[i])}return a}function kx(e,t,n){let s=e[t];return(n&1<<t||s==null)&&(s=1),s}function Ix(e,t,n,s,r,a){let o=t[r],i=n[r]||1;(e&1<<r||a&1<<r||o==null)&&(i>0?o=Number.MIN_SAFE_INTEGER:o=Number.MAX_SAFE_INTEGER);let l=s[r];return o<0&&(o+=l),o=$u(0,o,l-1),o}function Sx(e,t,n,s,r,a){let o=t[r],i=n[r]||1;(e&1<<r||a&1<<r||o==null)&&(i>0?o=Number.MAX_SAFE_INTEGER:o=Number.MIN_SAFE_INTEGER);let l=s[r];return o<0&&(o+=l),i>0?o=$u(0,o,l):o=$u(-1,o,l-1),o}function EC(e,t,n){let s=n.length;for(let r=0;r<n.length;r++)if(n[r]>1){s=r;break}for(let r=s+1;r<n.length;r++)if(t[r]>0||n[r]!==e[r])return!1;return!0}function RC(e,t){let n=e.length>0?e[e.length-1]:1;for(let s=0;s<e.length-1;s++)n+=e[s]*t[s];return n}function Cx(e,t,n){let s,r=e.shape.length;typeof t=="number"?s=[t,...new Array(r-1).fill(0)]:t.length<r?s=t.concat(new Array(r-t.length).fill(0)):s=t.slice(),s.forEach(o=>{M(o!==-1,()=>"slice() does not support negative begin indexing.")});let a;return n==null?a=new Array(r).fill(-1):typeof n=="number"?a=[n,...new Array(r-1).fill(-1)]:n.length<r?a=n.concat(new Array(r-n.length).fill(-1)):a=n,a=a.map((o,i)=>o>=0?o:(M(o===-1,()=>`Negative size values should be exactly -1 but got ${o} for the slice() size at index ${i}.`),e.shape[i]-s[i])),[s,a]}function _C(e,t,n,s,r,a,o,i,l){let u=t.slice(),c=n.slice(),d=s;s==null&&(d=new Array(u.length));let h=Bh(o);if(h.length>1)throw new Error("Multiple ellipses in slice is not allowed.");if(o!==0&&i!==0)throw new Error("Using both ellipsisMask and newAxisMask is not yet supported.");if(o!==0&&l!==0)throw new Error("Using both ellipsisMask and shrinkAxisMask is not yet supported.");let p=e.length-u.length,f=Bh(i),m=e.slice();f.forEach(S=>{u[S]=0,c[S]=1,m.splice(S,0,1)});let{begin:g,end:A,strides:y}=bx(m,h,p,u,c,d,r,a,o);u=g,c=A,d=y;let x=Bh(l);x.forEach(S=>{c[S]=u[S]+1,d[S]=1});let b=gx(u,c,d),v=b.filter((S,C)=>x.indexOf(C)===-1);return{nonStrided:d.every(S=>S===1),$begin:u,$end:c,$strides:d,size:b,newShape:m,outShape:v}}var oe={};Pe(oe,{Serializable:()=>Tx,SerializationMap:()=>$o,registerClass:()=>Zr});var Tx=class{getClassName(){return this.constructor.className}static fromConfig(e,t){return new e(t)}},$o=class{constructor(){this.classNameMap={}}static getMap(){return $o.instance==null&&($o.instance=new $o),$o.instance}static register(e){$o.getMap().classNameMap[e.className]=[e,e.fromConfig]}};function Zr(e){M(e.className!=null,()=>"Class being registered does not have the static className property defined."),M(typeof e.className=="string",()=>"className is required to be a string, but got type "+typeof e.className),M(e.className.length>0,()=>"Class being registered has an empty-string as its className, which is disallowed."),$o.register(e)}var Nx={};Pe(Nx,{TEST_EPSILON_FLOAT16:()=>Ex,encodeStrings:()=>Rx,expectArrayBuffersEqual:()=>zC,expectArraysClose:()=>$C,expectArraysEqual:()=>OC,expectNumbersClose:()=>PC,expectPromiseToFail:()=>FC,expectValuesInRange:()=>MC,testEpsilon:()=>fg});var DC=.001,Ex=.1;function $C(e,t,n){return n==null&&(n=fg()),mg(e,t,(s,r)=>gg(s,r,n))}function fg(){return z.backend.floatPrecision()===32?DC:Ex}function mg(e,t,n){let s=!0;if((cn(e)||cn(t))&&(s=!1),cn(e)&&cn(t)&&(s=!0),s){let o=e.constructor.name,i=t.constructor.name;if(o!==i)throw new Error(`Arrays are of different type. Actual: ${o}. Expected: ${i}`)}if(Array.isArray(e)&&Array.isArray(t)){let o=Qs(e),i=Qs(t);if(!br(o,i))throw new Error(`Arrays have different shapes. Actual: [${o}]. Expected: [${i}]`)}let r=cn(e)?e:Ca(e),a=cn(t)?t:Ca(t);if(r.length!==a.length)throw new Error(`Arrays have different lengths actual: ${r.length} vs expected: ${a.length}.
Actual: ${r}.
Expected: ${a}.`);for(let o=0;o<a.length;++o){let i=r[o],l=a[o];if(!n(i,l))throw new Error(`Arrays differ: actual[${o}] = ${i}, expected[${o}] = ${l}.
Actual: ${r}.
Expected: ${a}.`)}}function FC(e,t){e().then(()=>t.fail(),()=>t())}function OC(e,t){let n=typeof t=="string"||typeof t=="number"||typeof t=="boolean"?[t]:t;return Br(e)||Br(e[0])||Br(t)||Br(t[0])?mg(e,n,(s,r)=>s==r):mg(e,t,(s,r)=>gg(s,r,0))}function PC(e,t,n){if(n==null&&(n=fg()),!gg(e,t,n))throw new Error(`Numbers differ: actual === ${e}, expected === ${t}`)}function gg(e,t,n){return!isFinite(e)&&!isFinite(t)?!0:!(isNaN(e)||isNaN(t)||Math.abs(e-t)>n)}function MC(e,t,n){for(let s=0;s<e.length;s++)if(e[s]<t||e[s]>n)throw new Error(`Value out of range:${e[s]} low: ${t}, high: ${n}`)}function zC(e,t){expect(new Float32Array(e)).toEqual(new Float32Array(t))}function Rx(e){for(let t=0;t<e.length;t++){let n=e[t];Array.isArray(n)?Rx(n):e[t]=Ju(n)}return e}var _x="3.9.0";function LC(){Q().set("PROD",!0)}function BC(){Q().set("DEBUG",!0)}function WC(){Q().set("DEPRECATION_WARNINGS_ENABLED",!1),console.warn("TensorFlow.js deprecation warnings have been disabled.")}function Ag(e){Q().getBool("DEPRECATION_WARNINGS_ENABLED")&&console.warn(e+" You can disable deprecation warnings with tf.disableDeprecationWarnings().")}h9(Ag);function VC(){z.disposeVariables()}function wr(){return z}function Wh(){return z.memory()}function UC(e){return z.profile(e)}function H(e,t){return z.tidy(e,t)}function K(e){Zm(e).forEach(n=>n.dispose())}function Jt(e){return z.keep(e)}function HC(e){return z.time(e)}function GC(e){return z.setBackend(e)}function jC(){return z.ready()}function qC(){return z.backendName}function XC(e){z.removeBackend(e)}function yg(e){return z.findBackend(e)}function KC(e){return z.findBackendFactory(e)}function _l(e,t,n=1){return z.registerBackend(e,t,n)}function Dx(){return z.backend}function ZC(e,t){Q().setPlatform(e,t)}function YC(e,t){let n=$(e,"a","add"),s=$(t,"b","add");[n,s]=Ct(n,s);let r={a:n,b:s};return z.runKernel(Vr,r)}var ae=W({add_:YC});function JC(e,t){let n=$(e,"a","floorDiv"),s=$(t,"b","floorDiv");[n,s]=Ct(n,s);let r={a:n,b:s};return z.runKernel(Ua,r)}var xg=W({floorDiv_:JC});function QC(e,t){let n=$(e,"a","div"),s=$(t,"b","div");if([n,s]=Ct(n,s),n.dtype==="int32"&&s.dtype==="int32")return xg(n,s);let r={a:n,b:s},a={};return z.runKernel(La,r,a)}var de=W({div_:QC});function eT(e,t){let n=$(e,"a","mul"),s=$(t,"b","mul");[n,s]=Ct(n,s);let r={a:n,b:s};return z.runKernel(no,r)}var L=W({mul_:eT});function tT(e){let t=$(e,"x","abs");if(t.dtype==="complex64"){let n={x:t};return z.runKernel(Mu,n)}else{let n={x:t};return z.runKernel(ki,n)}}var Ht=W({abs_:tT});function nT(e){let n={x:$(e,"x","acos")};return z.runKernel(Ii,n)}var $x=W({acos_:nT});function sT(e){let n={x:$(e,"x","acosh")};return z.runKernel(Si,n)}var Fx=W({acosh_:sT});function rT(e){M(Array.isArray(e),()=>"The argument passed to tf.addN() must be a list of tensors"),M(e.length>=1,()=>`Must pass at least one tensor to tf.addN(), but got ${e.length}`);let t=e.map((r,a)=>$(r,`tensors${a}`,"addN")),n=t[0];t.forEach(r=>{if(r.dtype!==n.dtype)throw new Error("All tensors passed to tf.addN() must have the same dtype")}),t.forEach(r=>{if(!br(r.shape,n.shape))throw new Error("All tensors passed to tf.addN() must have the same shape")});let s=t;return z.runKernel(Ta,s)}var Vh=W({addN_:rT});function aT(e,t=null,n=!1){let r={x:$(e,"x","all","bool")},a={axis:t,keepDims:n};return z.runKernel(Ci,r,a)}var bg=W({all_:aT});function oT(e,t=null,n=!1){let r={x:$(e,"x","any","bool")},a={axis:t,keepDims:n};return z.runKernel(Ti,r,a)}var Uh=W({any_:oT});function iT(e,t=0){let s={x:$(e,"x","argMax")},r={axis:t};return z.runKernel(Na,s,r)}var er=W({argMax_:iT});function lT(e,t=0){let s={x:$(e,"x","argMin")},r={axis:t};return z.runKernel(Ou,s,r)}var Ox=W({argMin_:lT});function uT(e){let n={x:$(e,"x","asin")};return z.runKernel(Ni,n)}var Px=W({asin_:uT});function cT(e){let n={x:$(e,"x","asinh")};return z.runKernel(Ei,n)}var Mx=W({asinh_:cT});function dT(e){let n={x:$(e,"x","atan")};return z.runKernel(Ri,n)}var zx=W({atan_:dT});function hT(e,t){let n=$(e,"a","atan2"),s=$(t,"b","atan2");[n,s]=Ct(n,s);let r={a:n,b:s};return z.runKernel(Di,r)}var Lx=W({atan2_:hT});function pT(e){let n={x:$(e,"x","atanh")};return z.runKernel(_i,n)}var Bx=W({atanh_:pT});function fT(e,t,n,s,r="NHWC",a){let o=e[3],i=[...t,o],l=Ux(r);return lc(e,i,n,a,s,null,null,l)}function Wx(e,t,n,s,r,a,o="channelsLast"){let[i,l]=Hh(t),u;if(o==="channelsLast")u=[i,l,e[3],e[3]];else if(o==="channelsFirst")u=[i,l,e[1],e[1]];else throw new Error(`Unknown dataFormat ${o}`);return lc(e,u,n,s,r,a,!1,o)}function mT(e,t,n,s,r,a,o="NDHWC"){let[i,l,u]=wg(t),c,d;if(o==="NDHWC")d="channelsLast",c=[i,l,u,e[4],e[4]];else if(o==="NCDHW")d="channelsFirst",c=[i,l,u,e[1],e[1]];else throw new Error(`Unknown dataFormat ${o}`);return Vx(e,c,n,s,r,!1,d,a)}function lc(e,t,n,s,r,a,o=!1,i="channelsLast"){let[l,u,c,d]=[-1,-1,-1,-1];if(i==="channelsLast")[l,u,c,d]=e;else if(i==="channelsFirst")[l,d,u,c]=e;else throw new Error(`Unknown dataFormat ${i}`);let[h,p,,f]=t,[m,g]=Hh(n),[A,y]=Hh(s),x=Dl(h,A),b=Dl(p,y),{padInfo:v,outHeight:k,outWidth:S}=yT(r,u,c,m,g,x,b,a,i),C=o?f*d:f,_;return i==="channelsFirst"?_=[l,C,k,S]:i==="channelsLast"&&(_=[l,k,S,C]),{batchSize:l,dataFormat:i,inHeight:u,inWidth:c,inChannels:d,outHeight:k,outWidth:S,outChannels:C,padInfo:v,strideHeight:m,strideWidth:g,filterHeight:h,filterWidth:p,effectiveFilterHeight:x,effectiveFilterWidth:b,dilationHeight:A,dilationWidth:y,inShape:e,outShape:_,filterShape:t}}function Vx(e,t,n,s,r,a=!1,o="channelsLast",i){let[l,u,c,d,h]=[-1,-1,-1,-1,-1];if(o==="channelsLast")[l,u,c,d,h]=e;else if(o==="channelsFirst")[l,h,u,c,d]=e;else throw new Error(`Unknown dataFormat ${o}`);let[p,f,m,,g]=t,[A,y,x]=wg(n),[b,v,k]=wg(s),S=Dl(p,b),C=Dl(f,v),_=Dl(m,k),{padInfo:O,outDepth:E,outHeight:R,outWidth:T}=xT(r,u,c,d,A,y,x,S,C,_,i),P=a?g*h:g,V;return o==="channelsFirst"?V=[l,P,E,R,T]:o==="channelsLast"&&(V=[l,E,R,T,P]),{batchSize:l,dataFormat:o,inDepth:u,inHeight:c,inWidth:d,inChannels:h,outDepth:E,outHeight:R,outWidth:T,outChannels:P,padInfo:O,strideDepth:A,strideHeight:y,strideWidth:x,filterDepth:p,filterHeight:f,filterWidth:m,effectiveFilterDepth:S,effectiveFilterHeight:C,effectiveFilterWidth:_,dilationDepth:b,dilationHeight:v,dilationWidth:k,inShape:e,outShape:V,filterShape:t}}function gT(e,t,n,s,r){s==null&&(s=vg(e,t,n));let a=e[0],o=e[1],i=Fo((a-t+2*s)/n+1,r),l=Fo((o-t+2*s)/n+1,r);return[i,l]}function AT(e,t,n,s,r,a){r==null&&(r=vg(e,t,s));let o=e[0],i=e[1],l=e[2],u=Fo((o-t+2*r)/s+1,a),c=Fo((i-t+2*r)/s+1,a),d=Fo((l-t+2*r)/s+1,a);return[u,c,d,n]}function vg(e,t,n,s=1){let r=Dl(t,s);return Math.floor((e[0]*(n-1)-n+r)/2)}function Hh(e){return typeof e=="number"?[e,e,e]:e.length===2?[e[0],e[1],1]:e}function wg(e){return typeof e=="number"?[e,e,e]:e}function Dl(e,t){return t<=1?e:e+(e-1)*(t-1)}function yT(e,t,n,s,r,a,o,i,l){let u,c,d;if(typeof e=="number"){u={top:e,bottom:e,left:e,right:e,type:e===0?"VALID":"NUMBER"};let p=gT([t,n],a,s,e,i);c=p[0],d=p[1]}else if(e==="same"){c=Math.ceil(t/s),d=Math.ceil(n/r);let h=Math.max(0,(c-1)*s+a-t),p=Math.max(0,(d-1)*r+o-n),f=Math.floor(h/2),m=h-f,g=Math.floor(p/2),A=p-g;u={top:f,bottom:m,left:g,right:A,type:"SAME"}}else if(e==="valid")u={top:0,bottom:0,left:0,right:0,type:"VALID"},c=Math.ceil((t-a+1)/s),d=Math.ceil((n-o+1)/r);else if(typeof e=="object"){let h=l==="channelsLast"?e[1][0]:e[2][0],p=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:h,bottom:p,left:f,right:m,type:h===0&&p===0&&f===0&&m===0?"VALID":"EXPLICIT"},c=Fo((t-a+h+p)/s+1,i),d=Fo((n-o+f+m)/r+1,i)}else throw Error(`Unknown padding parameter: ${e}`);return{padInfo:u,outHeight:c,outWidth:d}}function xT(e,t,n,s,r,a,o,i,l,u,c){let d,h,p,f;if(typeof e=="number"){d={top:e,bottom:e,left:e,right:e,front:e,back:e,type:e===0?"VALID":"NUMBER"};let g=AT([t,n,s,1],i,1,r,e,c);h=g[0],p=g[1],f=g[2]}else if(e==="same"){h=Math.ceil(t/r),p=Math.ceil(n/a),f=Math.ceil(s/o);let m=(h-1)*r+i-t,g=(p-1)*a+l-n,A=(f-1)*o+u-s,y=Math.floor(m/2),x=m-y,b=Math.floor(g/2),v=g-b,k=Math.floor(A/2),S=A-k;d={top:b,bottom:v,left:k,right:S,front:y,back:x,type:"SAME"}}else if(e==="valid")d={top:0,bottom:0,left:0,right:0,front:0,back:0,type:"VALID"},h=Math.ceil((t-i+1)/r),p=Math.ceil((n-l+1)/a),f=Math.ceil((s-u+1)/o);else throw Error(`Unknown padding parameter: ${e}`);return{padInfo:d,outDepth:h,outHeight:p,outWidth:f}}function Fo(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 Yr(e){let[t,n,s]=Hh(e);return t===1&&n===1&&s===1}function tr(e,t){return Yr(e)||Yr(t)}function Ux(e){if(e==="NHWC")return"channelsLast";if(e==="NCHW")return"channelsFirst";throw new Error(`Unknown dataFormat ${e}`)}function bT(e,t){let s={x:$(e,"x","reshape","string_or_numeric")},r={shape:t};return z.runKernel(ll,s,r)}var U=W({reshape_:bT});function vT(e,t,n,s,r){let a=$(e,"x","avgPool","float32"),o=1;M(tr(n,o),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${n} and dilations '${o}'`);let i=a,l=!1;a.rank===3&&(l=!0,i=U(a,[1,a.shape[0],a.shape[1],a.shape[2]])),M(i.rank===4,()=>`Error in avgPool: x must be rank 4 but got rank ${i.rank}.`),r!=null&&M(Zt(s),()=>`Error in avgPool: pad must be an integer when using, dimRoundingMode ${r} but got pad ${s}.`);let u={x:i},c={filterSize:t,strides:n,pad:s,dimRoundingMode:r},d=z.runKernel(Ea,u,c);return d=ce(d,a.dtype),l?U(d,[d.shape[1],d.shape[2],d.shape[3]]):d}var Gh=W({avgPool_:vT});function wT(e,t,n,s,r,a="NDHWC"){let o=$(e,"x","avgPool3d","float32"),i=o,l=!1;o.rank===4&&(l=!0,i=U(o,[1,o.shape[0],o.shape[1],o.shape[2],o.shape[3]])),M(i.rank===5,()=>`Error in avgPool3d: x must be rank 5 but got rank ${i.rank}.`),M(a==="NDHWC",()=>`Error in avgPool3d: Only NDHWC is currently supported, but got dataFormat of ${a}`),r!=null&&M(Zt(s),()=>`Error in avgPool3d: pad must be an integer when using, dimRoundingMode ${r} but got pad ${s}.`);let u={x:i},c={filterSize:t,strides:n,pad:s,dimRoundingMode:r,dataFormat:a},d=z.runKernel(Pu,u,c);return d=ce(d,i.dtype),l?U(d,[d.shape[1],d.shape[2],d.shape[3],d.shape[4]]):d}var kg=W({avgPool3d_:wT});function kT(e,t=0){M(e.length>=1,()=>"Pass at least one tensor to concat");let n=ac(e,"tensors","concat","string_or_numeric");if(n[0].dtype==="complex64"&&n.forEach(a=>{if(a.dtype!=="complex64")throw new Error(`Cannot concatenate complex64 tensors with a tensor
with dtype ${a.dtype}. `)}),n.length===1)return Os(n[0]);let s=n,r={axis:t};return z.runKernel(Fi,s,r)}var ft=W({concat_:kT});function IT(e){let n={x:$(e,"x","sigmoid")};return z.runKernel(mo,n)}var Hn=W({sigmoid_:IT});function ST(e,t,n){let s=$(e,"x","slice","string_or_numeric");if(s.rank===0)throw new Error("Slicing scalar is not possible");let r={x:s},a={begin:t,size:n};return z.runKernel(hl,r,a)}var Re=W({slice_:ST});function CT(e){let n={x:$(e,"x","tanh")};return z.runKernel(wo,n)}var $l=W({tanh_:CT});function TT(e,t,n,s,r,a){let o=$(e,"forgetBias","basicLSTMCell"),i=$(t,"lstmKernel","basicLSTMCell"),l=$(n,"lstmBias","basicLSTMCell"),u=$(s,"data","basicLSTMCell"),c=$(r,"c","basicLSTMCell"),d=$(a,"h","basicLSTMCell"),h=ft([u,d],1),p=Ve(h,i),f=ae(p,l),m=f.shape[0],g=f.shape[1]/4,A=[m,g],y=Re(f,[0,0],A),x=Re(f,[0,g],A),b=Re(f,[0,g*2],A),v=Re(f,[0,g*3],A),k=ae(L(Hn(y),$l(x)),L(c,Hn(ae(o,b)))),S=L($l(k),Hn(v));return[k,S]}var NT=W({basicLSTMCell_:TT});function ET(e,t,n){let s=$(e,"x","batchToSpaceND"),r=t.reduce((i,l)=>i*l);M(s.rank>=1+t.length,()=>`input rank is ${s.rank} but should be > than blockShape.length ${t.length}`),M(n.length===t.length,()=>`crops.length is ${n.length} but should be equal to blockShape.length ${t.length}`),M(s.shape[0]%r==0,()=>`input tensor batch is ${s.shape[0]} but is not divisible by the product of the elements of blockShape ${t.join(" * ")} === ${r}`);let a={x:s},o={blockShape:t,crops:n};return z.runKernel($i,a,o)}var jh=W({batchToSpaceND_:ET});function RT(e){let t;return e.rank===0||e.rank===1?t=U(e,[1,1,1,e.size]):e.rank===2?t=U(e,[1,1,e.shape[0],e.shape[1]]):e.rank===3?t=U(e,[1,e.shape[0],e.shape[1],e.shape[2]]):t=e,t}function _T(e,t,n,s,r,a){a==null&&(a=.001);let o=$(e,"x","batchNorm"),i=$(t,"mean","batchNorm"),l=$(n,"variance","batchNorm"),u;r!=null&&(u=$(r,"scale","batchNorm"));let c;s!=null&&(c=$(s,"offset","batchNorm")),M(i.rank===l.rank,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),M(c==null||i.rank===c.rank,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),M(u==null||i.rank===u.rank,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let h={x:RT(o),scale:u,offset:c,mean:i,variance:l},p={varianceEpsilon:a},f=z.runKernel(Ha,h,p);return U(f,o.shape)}var Fl=W({batchNorm_:_T});function DT(e,t,n,s,r,a){let o=$(e,"x","batchNorm"),i=$(t,"mean","batchNorm"),l=$(n,"variance","batchNorm"),u;r!=null&&(u=$(r,"scale","batchNorm"));let c;return s!=null&&(c=$(s,"offset","batchNorm")),M(o.rank===2,()=>`Error in batchNorm2D: x must be rank 2 but got rank ${o.rank}.`),M(i.rank===2||i.rank===1,()=>`Error in batchNorm2D: mean must be rank 2 or rank 1 but got rank ${i.rank}.`),M(l.rank===2||l.rank===1,()=>`Error in batchNorm2D: variance must be rank 2 or rank 1 but got rank ${l.rank}.`),u!=null&&M(u.rank===2||u.rank===1,()=>`Error in batchNorm2D: scale must be rank 2 or rank 1 but got rank ${u.rank}.`),c!=null&&M(c.rank===2||c.rank===1,()=>`Error in batchNorm2D: offset must be rank 2 or rank 1 but got rank ${c.rank}.`),Fl(o,i,l,c,u,a)}var Hx=W({batchNorm2d_:DT});function $T(e,t,n,s,r,a){let o=$(e,"x","batchNorm"),i=$(t,"mean","batchNorm"),l=$(n,"variance","batchNorm"),u;r!=null&&(u=$(r,"scale","batchNorm"));let c;return s!=null&&(c=$(s,"offset","batchNorm")),M(o.rank===3,()=>`Error in batchNorm3D: x must be rank 3 but got rank ${o.rank}.`),M(i.rank===3||i.rank===1,()=>`Error in batchNorm3D: mean must be rank 3 or rank 1 but got rank ${i.rank}.`),M(l.rank===3||l.rank===1,()=>`Error in batchNorm3D: variance must be rank 3 or rank 1 but got rank ${l.rank}.`),u!=null&&M(u.rank===3||u.rank===1,()=>`Error in batchNorm3D: scale must be rank 3 or rank 1 but got rank ${u.rank}.`),c!=null&&M(c.rank===3||c.rank===1,()=>`Error in batchNorm3D: offset must be rank 3 or rank 1 but got rank ${c.rank}.`),Fl(o,i,l,c,u,a)}var Gx=W({batchNorm3d_:$T});function FT(e,t,n,s,r,a){let o=$(e,"x","batchNorm"),i=$(t,"mean","batchNorm"),l=$(n,"variance","batchNorm"),u;r!=null&&(u=$(r,"scale","batchNorm"));let c;return s!=null&&(c=$(s,"offset","batchNorm")),M(o.rank===4,()=>`Error in batchNorm4D: x must be rank 4 but got rank ${o.rank}.`),M(i.rank===4||i.rank===1,()=>`Error in batchNorm4D: mean must be rank 4 or rank 1 but got rank ${i.rank}.`),M(l.rank===4||l.rank===1,()=>`Error in batchNorm4D: variance must be rank 4 or rank 1 but got rank ${l.rank}.`),u!=null&&M(u.rank===4||u.rank===1,()=>`Error in batchNorm4D: scale must be rank 4 or rank 1 but got rank ${u.rank}.`),c!=null&&M(c.rank===4||c.rank===1,()=>`Error in batchNorm4D: offset must be rank 4 or rank 1 but got rank ${c.rank}.`),Fl(o,i,l,c,u,a)}var jx=W({batchNorm4d_:FT});function OT(e,t,n){let s=$(e,"x","bincount"),r=$(t,"weights","bincount");M(s.dtype==="int32",()=>`Error in bincount: input dtype must be int32, but got ${s.dtype}`),M(n>=0,()=>`size must be non-negative, but got ${n}.`),M(r.size===s.size||r.size===0,()=>`Error in bincount: weights must have the same size as input or0-length, but got input shape: ${s.shape}, weights shape: ${r.shape}.`);let a={x:s,weights:r},o={size:n};return z.runKernel(Zd,a,o)}var Ig=W({bincount_:OT});function PT(e,t){let n=$(e,"s0","broadcastArgs","int32"),s=$(t,"s1","broadcastArgs","int32");if(n.rank!==1)throw new Error(`broadcastArgs(): first input must be a vector (rank=1). Has rank ${n.rank}`);if(s.rank!==1)throw new Error(`broadcastArgs(): second input must be a vector (rank=1). Has rank ${s.rank}`);let r={s0:n,s1:s};return z.runKernel(Bm,r)}var qx=W({broadcastArgs_:PT});function MT(e,t){let n=$(e,"broadcastTo","x"),s=n.shape;if(t.some(u=>!(u>0)||u%1!=0))throw new Error(`broadcastTo(): Invalid broadcast shape [${t}].`);if(t.length<n.rank)throw new Error(`broadcastTo(): shape.length=${t.length} < input.rank=${n.rank}.`);if(t.length>n.rank){let u=n.shape.slice();for(;u.length<t.length;)u.unshift(1);n=U(n,u)}let r=n.shape,a=Array.from(t);for(let u=t.length-1;u>=0;u--)if(r[u]===t[u])a[u]=1;else if(n.shape[u]!==1)throw new Error(`broadcastTo(): [${s}] cannot be broadcast to [${t}].`);if(a.map((u,c)=>u>1?c:-1).filter(u=>u>=0).length===0)return Os(n);let i={x:n},l={reps:a};return z.runKernel(Hr,i,l)}var uc=W({broadcastTo_:MT});function zT(e){let n={x:$(e,"x","ceil")};return z.runKernel(Da,n)}var Xx=W({ceil_:zT});function LT(e,t,n){let s=$(e,"x","clipByValue");M(t<=n,()=>`Error in clip: min (${t}) must be less than or equal to max (${n}).`);let r={x:s},a={clipValueMin:t,clipValueMax:n};return z.runKernel(Ur,r,a)}var Gn=W({clipByValue_:LT});function BT(e){return ft(e,0)}var Kx=W({concat1d_:BT});function WT(e,t){return ft(e,t)}var Ol=W({concat2d_:WT});function VT(e,t){return ft(e,t)}var Zx=W({concat3d_:VT});function UT(e,t){return ft(e,t)}var Yx=W({concat4d_:UT});function HT(e,t,n,s,r="NHWC",a=[1,1],o){let i=$(e,"x","conv2d"),l=$(t,"filter","conv2d"),u=i,c=!1;i.rank===3&&(c=!0,u=U(i,[1,i.shape[0],i.shape[1],i.shape[2]])),M(u.rank===4,()=>`Error in conv2d: input must be rank 4, but got rank ${u.rank}.`),M(l.rank===4,()=>`Error in conv2d: filter must be rank 4, but got rank ${l.rank}.`),o!=null&&M(Zt(s),()=>`Error in conv2d: pad must be an integer when using, dimRoundingMode ${o} but got pad ${s}.`);let d=r==="NHWC"?u.shape[3]:u.shape[1];M(d===l.shape[2],()=>`Error in conv2d: depth of input (${d}) must match input depth for filter ${l.shape[2]}.`),M(tr(n,a),()=>`Error in conv2D: Either strides or dilations must be 1. Got strides ${n} and dilations '${a}'`);let h={x:u,filter:l},p={strides:n,pad:s,dataFormat:r,dilations:a,dimRoundingMode:o},f=z.runKernel($a,h,p);return c?U(f,[f.shape[1],f.shape[2],f.shape[3]]):f}var Jr=W({conv2d_:HT});function GT(e,t,n,s,r="NWC",a=1,o){let i=$(e,"x","conv1d"),l=$(t,"filter","conv1d"),u=i,c=!1;i.rank===2&&(c=!0,u=U(i,[1,i.shape[0],i.shape[1]])),M(u.rank===3,()=>`Error in conv1d: input must be rank 3, but got rank ${u.rank}.`),M(l.rank===3,()=>`Error in conv1d: filter must be rank 3, but got rank ${l.rank}.`),o!=null&&M(Zt(s),()=>`Error in conv1d: pad must be an integer when using, dimRoundingMode ${o} but got pad ${s}.`),M(u.shape[2]===l.shape[1],()=>`Error in conv1d: depth of input (${u.shape[2]}) must match input depth for filter ${l.shape[1]}.`),M(tr(n,a),()=>`Error in conv1D: Either stride or dilation must be 1. Got stride ${n} and dilation '${a}'`),M(r==="NWC",()=>`Error in conv1d: got dataFormat of ${r} but only NWC is currently supported.`);let d=U(l,[1,l.shape[0],l.shape[1],l.shape[2]]),h=U(u,[u.shape[0],1,u.shape[1],u.shape[2]]),g=Jr(h,d,[1,n],s,"NHWC",[1,a],o);return c?U(g,[g.shape[2],g.shape[3]]):U(g,[g.shape[0],g.shape[2],g.shape[3]])}var Sg=W({conv1d_:GT});function jT(e,t,n,s,r,a="NHWC",o){M(e.length===t.rank,()=>`Length of inShape (${e.length}) and rank of dy (${t.rank}) must match`);let i=e,l=t,u=!1;t.rank===3&&(u=!0,l=U(t,[1,t.shape[0],t.shape[1],t.shape[2]]),i=[1,e[0],e[1],e[2]]),M(i.length===4,()=>`Error in conv2dDerInput: inShape must be length 4, but got length ${i.length}.`),M(l.rank===4,()=>`Error in conv2dDerInput: dy must be rank 4, but got rank ${l.rank}`),M(n.rank===4,()=>`Error in conv2dDerInput: filter must be rank 4, but got rank ${n.rank}`);let c=a==="NHWC"?i[3]:i[1],d=a==="NHWC"?l.shape[3]:l.shape[1];M(c===n.shape[2],()=>`Error in conv2dDerInput: depth of input (${c}) must match input depth for filter ${n.shape[2]}.`),M(d===n.shape[3],()=>`Error in conv2dDerInput: depth of output (${d}) must match output depth for filter ${n.shape[3]}.`),o!=null&&M(Zt(r),()=>`Error in conv2dDerInput: pad must be an integer when using, dimRoundingMode ${o} but got pad ${r}.`);let h={dy:l,filter:n},p={strides:s,pad:r,dataFormat:a,dimRoundingMode:o,inputShape:i},f=z.runKernel(Fa,h,p);return u?U(f,[f.shape[1],f.shape[2],f.shape[3]]):f}var Cg=W({conv2DBackpropInput_:jT});function qT(e,t,n,s,r,a){let o=$(e,"x","conv2dTranspose"),i=$(t,"filter","conv2dTranspose");return Cg(n,o,i,s,r,"NHWC",a)}var Tg=W({conv2dTranspose_:qT});function XT(e,t,n,s,r="NDHWC",a=[1,1,1]){let o=$(e,"x","conv3d"),i=$(t,"filter","conv3d"),l=o,u=!1;o.rank===4&&(u=!0,l=U(o,[1,o.shape[0],o.shape[1],o.shape[2],o.shape[3]])),M(l.rank===5,()=>`Error in conv3d: input must be rank 5, but got rank ${l.rank}.`),M(i.rank===5,()=>`Error in conv3d: filter must be rank 5, but got rank ${i.rank}.`),M(l.shape[4]===i.shape[3],()=>`Error in conv3d: depth of input (${l.shape[4]}) must match input depth for filter ${i.shape[3]}.`),M(tr(n,a),()=>`Error in conv3D: Either strides or dilations must be 1. Got strides ${n} and dilations '${a}'`),M(r==="NDHWC",()=>`Error in conv3d: got dataFormat of ${r} but only NDHWC is currently supported.`);let c={x:l,filter:i},d={strides:n,pad:s,dataFormat:r,dilations:a},h=z.runKernel(zu,c,d);return u?U(h,[h.shape[1],h.shape[2],h.shape[3],h.shape[4]]):h}var Ng=W({conv3d_:XT});function KT(e,t,n,s,r){M(e.length===t.rank,()=>`Length of inShape (${e.length}) and rank of dy (${t.rank}) must match`);let a=e,o=t,i=!1;t.rank===4&&(i=!0,o=U(t,[1,t.shape[0],t.shape[1],t.shape[2],t.shape[3]]),a=[1,e[0],e[1],e[2],e[3]]);let l=a[4],u=o.shape[4];M(a.length===5,()=>`Error in conv3dDerInput: inShape must be length 5, but got length ${a.length}.`),M(o.rank===5,()=>`Error in conv3dDerInput: dy must be rank 5, but got rank ${o.rank}`),M(n.rank===5,()=>`Error in conv3dDerInput: filter must be rank 5, but got rank ${n.rank}`),M(l===n.shape[3],()=>`Error in conv3dDerInput: depth of input (${l}) must match input depth for filter ${n.shape[3]}.`),M(u===n.shape[4],()=>`Error in conv3dDerInput: depth of output (${u}) must match output depth for filter ${n.shape[4]}.`);let c={dy:o,filter:n},d={pad:r,strides:s,inputShape:a},h=z.runKernel(eh,c,d);return i?U(h,[h.shape[1],h.shape[2],h.shape[3],h.shape[4]]):h}var Jx=W({conv3DBackpropInput_:KT});function ZT(e,t,n,s,r){let a=$(e,"x","conv3dTranspose"),o=$(t,"filter","conv3dTranspose");return Jx(n,a,o,s,r)}var Qx=W({conv3dTranspose_:ZT});function YT(e){let n={x:$(e,"x","cos")};return z.runKernel(Oa,n)}var qh=W({cos_:YT});function JT(e){let n={x:$(e,"x","cosh")};return z.runKernel(Pa,n)}var Eg=W({cosh_:JT});function QT(e,t=0,n=!1,s=!1){let a={x:$(e,"x","cumsum")},o={axis:t,exclusive:n,reverse:s};return z.runKernel(Ma,a,o)}var Rg=W({cumsum_:QT});function eN(e,t,n,s=!1){let r=$(e,"x","denseBincount"),a=$(t,"weights","denseBincount");M(r.dtype==="int32",()=>`Error in denseBincount: input dtype must be int32, but got ${r.dtype}`),M(r.rank<=2,()=>`Error in denseBincount: input must be at most rank 2, but got rank ${r.rank}.`),M(n>=0,()=>`size must be non-negative, but got ${n}.`),M(a.size===r.size||a.size===0,()=>`Error in denseBincount: weights must have the same shape as x or 0-length, but got x shape: ${r.shape}, weights shape: ${a.shape}.`);let o={x:r,weights:a},i={size:n,binaryOutput:s};return z.runKernel(th,o,i)}var eb=W({denseBincount_:eN});function tN(e,t,n="NHWC"){let s=$(e,"x","depthToSpace"),r=n==="NHWC"?s.shape[1]:s.shape[2],a=n==="NHWC"?s.shape[2]:s.shape[3],o=n==="NHWC"?s.shape[3]:s.shape[1];M(r*t>=0,()=>`Negative dimension size caused by overflow when multiplying
${r} and ${t} for depthToSpace with input shape
${s.shape}`),M(a*t>=0,()=>`Negative dimension size caused by overflow when multiplying
${a} and ${t} for depthToSpace with input shape
${s.shape}`),M(o%(t*t)==0,()=>`Dimension size must be evenly divisible by ${t*t} but is ${o} for depthToSpace with input shape ${s.shape}`);let i={x:s},l={blockSize:t,dataFormat:n};return z.runKernel(Pi,i,l)}var tb=W({depthToSpace_:tN});function nN(e,t,n,s,r="NHWC",a=[1,1],o){let i=$(e,"x","depthwiseConv2d"),l=$(t,"filter","depthwiseConv2d"),u=i,c=!1;i.rank===3&&(c=!0,u=U(i,[1,i.shape[0],i.shape[1],i.shape[2]])),M(u.rank===4,()=>`Error in depthwiseConv2d: input must be rank 4, but got rank ${u.rank}.`),M(l.rank===4,()=>`Error in depthwiseConv2d: filter must be rank 4, but got rank ${l.rank}.`),M(u.shape[3]===l.shape[2],()=>`Error in depthwiseConv2d: number of input channels (${u.shape[3]}) must match the inChannels dimension in filter ${l.shape[2]}.`),o!=null&&M(Zt(s),()=>`Error in depthwiseConv2d: pad must be an integer when using, dimRoundingMode ${o} but got pad ${s}.`);let d={x:u,filter:l},h={strides:n,pad:s,dataFormat:r,dilations:a,dimRoundingMode:o},p=z.runKernel(za,d,h);return c?U(p,[p.shape[1],p.shape[2],p.shape[3]]):p}var cc=W({depthwiseConv2d_:nN});function sN(e){let n={x:$(e,"x","diag")};return z.runKernel(rh,n)}var rN=W({diag_:sN});function aN(e,t,n,s,r=[1,1],a="NHWC"){let o=$(e,"x","dilation2d"),i=$(t,"filter","dilation2d");M(o.rank===3||o.rank===4,()=>`Error in dilation2d: input must be rank 3 or 4, but got rank ${o.rank}.`),M(i.rank===3,()=>`Error in dilation2d: filter must be rank 3, but got rank ${i.rank}.`),M(a==="NHWC",()=>`Error in dilation2d: Only NHWC is currently supported, but got dataFormat of ${a}`);let l=o,u=!1;o.rank===3&&(l=U(o,[1,o.shape[0],o.shape[1],o.shape[2]]),u=!0);let c={x:l,filter:i},d={strides:n,pad:s,dilations:r},h=z.runKernel(Lu,c,d);return u?U(h,[h.shape[1],h.shape[2],h.shape[3]]):h}var nb=W({dilation2d_:aN});function oN(e,t){let n=e.length,s=[];for(let r=0;r<n;r++){let a=n-1-r,o=e[a]||1;(t[t.length-1-r]||1)>1&&o===1&&s.unshift(a)}return s}function Gt(e,t){let n=[];for(let s=0;s<t.length;s++){let r=e[e.length-s-1],a=t.length-s-1,o=t[a];(r==null||r===1&&o>1)&&n.unshift(a)}return n}function At(e,t){let n=[],s=Math.max(e.length,t.length);for(let r=0;r<s;r++){let a=e[e.length-r-1];a==null&&(a=1);let o=t[t.length-r-1];if(o==null&&(o=1),a===1)n.unshift(o);else if(o===1)n.unshift(a);else if(a!==o){let i=`Operands could not be broadcast together with shapes ${e} and ${t}.`;throw Error(i)}else n.unshift(a)}return n}function iN(e,t){let n=$(e,"a","equal","string_or_numeric"),s=$(t,"b","equal","string_or_numeric");[n,s]=Ct(n,s),At(n.shape,s.shape);let r={a:n,b:s};return z.runKernel(zi,r)}var us=W({equal_:iN});function lN(e,t,n){let s=$(t,"a","where"),r=$(n,"b","where"),a=$(e,"condition","where","bool"),o=At(At(a.shape,s.shape),r.shape),i=uc(a,o),l=uc(s,o),u=uc(r,o),c={condition:i,t:l,e:u};return z.runKernel(cl,c)}var bn=W({where_:lN});function uN(e){let n={x:$(e,"x","zerosLike")};return z.runKernel(wl,n)}var Ke=W({zerosLike_:uN});function cN(e,t){let n=$(e,"a","div"),s=$(t,"b","div");[n,s]=Ct(n,s);let r=de(n,s),a=Ke(r),o=us(s,a);return bn(o,a,r)}var sb=W({divNoNan_:cN});function dN(e,t){let n=$(e,"t1","dot"),s=$(t,"t2","dot");M((n.rank===1||n.rank===2)&&(s.rank===1||s.rank===2),()=>`Error in dot: inputs must all be rank 1 or 2, but got ranks ${n.rank} and ${s.rank}.`);let r=n.rank===1?n.size:n.shape[1],a=s.rank===1?s.size:s.shape[0];if(M(r===a,()=>`Error in dot: inner dimensions of inputs must match, but got ${r} and ${a}.`),n.rank===1&&s.rank===1){let o=U(n,[1,-1]),i=U(s,[-1,1]),l=Ve(o,i);return U(l,[])}else if(n.rank===1&&s.rank===2){let o=U(n,[1,-1]),i=U(s,[s.shape[0],s.shape[1]]),l=Ve(o,i);return U(l,[l.size])}else if(n.rank===2&&s.rank===1){let o=U(s,[-1,1]),i=Ve(n,o);return U(i,[i.size])}else{let o=U(s,[s.shape[0],s.shape[1]]);return Ve(n,o)}}var hN=W({dot_:dN});function pN(e,...t){let n=t.map((r,a)=>$(r,`tensors${a}`,"einsum")),s={equation:e};return z.runKernel(ih,n,s)}var rb=W({einsum_:pN});function fN(e){let n={x:$(e,"x","elu")};return z.runKernel(Ba,n)}var dc=W({elu_:fN});function mN(e){let t=$(e,"x","erf");M(t.dtype==="int32"||t.dtype==="float32",()=>"Input dtype must be `int32` or `float32`."),t.dtype==="int32"&&(t=ce(t,"float32"));let n={x:t};return z.runKernel(Mi,n)}var ab=W({erf_:mN});function gN(e){let n={x:$(e,"x","exp")};return z.runKernel(Wa,n)}var cs=W({exp_:gN});function AN(e,t=0){let n=$(e,"x","expandDims","string_or_numeric");M(t<=n.rank,()=>"Axis must be <= rank of the tensor");let s={input:n},r={dim:t};return z.runKernel(Li,s,r)}var Ot=W({expandDims_:AN});function yN(e){let n={x:$(e,"x","expm1")};return z.runKernel(Bi,n)}var ob=W({expm1_:yN});function xN(e,t){let n=$(e,"x","tile","string_or_numeric");M(n.rank===t.length,()=>`Error in transpose: rank of input ${n.rank} must match length of reps ${t}.`);let s={x:n},r={reps:t};return z.runKernel(Hr,s,r)}var Ts=W({tile_:xN});function bN(e,t,n,s="float32"){t==null&&(t=e);let r=We([e,t],s),a=e<=t?e:t;for(let i=0;i<a;++i)r.set(1,i,i);let o=U(r.toTensor(),[e,t]);if(n==null)return o;if(n.length===1)return Ts(Ot(o,0),[n[0],1,1]);if(n.length===2)return Ts(Ot(Ot(o,0),0),[n[0],n[1],1,1]);if(n.length===3)return Ts(Ot(Ot(Ot(o,0),0),0),[n[0],n[1],n[2],1,1]);throw new Error(`eye() currently supports only 1D and 2D batchShapes, but received ${n.length}D.`)}var _g=W({eye_:bN});function Pl(e,t,n){let s={shape:e,value:t,dtype:n};return z.runKernel(Bu,{},s)}function vN(e){let n={x:$(e,"x","floor")};return z.runKernel(Va,n)}var hc=W({floor_:vN});function wN(e,t,n=0,s=0){let r=$(e,"x","gather"),a=$(t,"indices","gather","int32"),o={x:r,indices:a},i={axis:n,batchDims:s};return z.runKernel(Vi,o,i)}var Ml=W({gather_:wN});function kN(e,t){let n=$(e,"a","greater","string_or_numeric"),s=$(t,"b","greater","string_or_numeric");[n,s]=Ct(n,s),At(n.shape,s.shape);let r={a:n,b:s};return z.runKernel(Hi,r)}var jn=W({greater_:kN});function IN(e,t){let n=$(e,"a","greaterEqual","string_or_numeric"),s=$(t,"b","greaterEqual","string_or_numeric");[n,s]=Ct(n,s),At(n.shape,s.shape);let r={a:n,b:s};return z.runKernel(Ga,r)}var Oo=W({greaterEqual_:IN});function SN(e){let n={input:$(e,"input","imag")};return z.runKernel(dh,n)}var Xh=W({imag_:SN});function CN(e){let n={x:$(e,"x","isFinite")};return z.runKernel(Gi,n)}var TN=W({isFinite_:CN});function NN(e){let n={x:$(e,"x","isInf")};return z.runKernel(ji,n)}var EN=W({isInf_:NN});function RN(e){let n={x:$(e,"x","isNaN")};return z.runKernel(qi,n)}var ib=W({isNaN_:RN});function _N(e,t=.2){let s={x:$(e,"x","leakyRelu")},r={alpha:t};return z.runKernel(qa,s,r)}var Kh=W({leakyRelu_:_N});function DN(e,t){let n=$(e,"a","less","string_or_numeric"),s=$(t,"b","less","string_or_numeric");[n,s]=Ct(n,s),At(n.shape,s.shape);let r={a:n,b:s};return z.runKernel(Xi,r)}var Dg=W({less_:DN});function $N(e,t){let n=$(e,"a","lessEqual","string_or_numeric"),s=$(t,"b","lessEqual","string_or_numeric");[n,s]=Ct(n,s),At(n.shape,s.shape);let r={a:n,b:s};return z.runKernel(Ki,r)}var Po=W({lessEqual_:$N});function lb(e,t,n){if(n<=0)throw new Error("The number of values should be positive.");let s={start:e,stop:t,num:n};return z.runKernel(hh,{},s)}function FN(e,t=5,n=1,s=1,r=.5){let a=$(e,"x","localResponseNormalization");M(a.rank===4||a.rank===3,()=>`Error in localResponseNormalization: x must be rank 3 or 4 but got
rank ${a.rank}.`),M(Zt(t),()=>`Error in localResponseNormalization: depthRadius must be an integer but got depthRadius ${t}.`);let o=a,i=!1;a.rank===3&&(i=!0,o=U(a,[1,a.shape[0],a.shape[1],a.shape[2]]));let l={x:o},u={depthRadius:t,bias:n,alpha:s,beta:r},c=z.runKernel(Uu,l,u);return i?U(c,[c.shape[1],c.shape[2],c.shape[3]]):c}var ub=W({localResponseNormalization_:FN});function ON(e){let n={x:$(e,"x","log")};return z.runKernel(Xa,n)}var ds=W({log_:ON});function PN(e){let n={x:$(e,"x","log1p")};return z.runKernel(Zi,n)}var Zh=W({log1p_:PN});function MN(e){return M(Wr(e),()=>"The f passed in grad(f) must be a function"),(t,n)=>{let s=$(t,"x","tf.grad","string_or_numeric"),r=n!=null?$(n,"dy","tf.grad"):null;return z.tidy(()=>{let{value:a,grads:o}=z.gradients(()=>e(s),[s],r);return r!=null&&An(a.shape,r.shape,"The shape of dy passed in grad(f)(x, dy) must match the shape returned by f(x)"),Yh(o),o[0]})}}function zN(e){return M(Wr(e),()=>"The f passed in grads(f) must be a function"),(t,n)=>{M(Array.isArray(t),()=>"The args passed in grads(f)(args) must be an array of `Tensor`s or `TensorLike`s");let s=ac(t,"args","tf.grads","string_or_numeric"),r=n!=null?$(n,"dy","tf.grads"):null;return z.tidy(()=>{let{value:a,grads:o}=z.gradients(()=>e(...s),s,r);return r!=null&&An(a.shape,r.shape,"The shape of dy passed in grads(f)([x1,...], dy) must match the shape returned by f([x1,...])"),Yh(o),o})}}function LN(e){return M(Wr(e),()=>"The f passed in valueAndGrad(f) must be a function"),(t,n)=>{M(t instanceof Ge,()=>"The x passed in valueAndGrad(f)(x) must be a tensor"),M(n==null||n instanceof Ge,()=>"The dy passed in valueAndGrad(f)(x, dy) must be a tensor");let{grads:s,value:r}=z.gradients(()=>e(t),[t],n);return Yh(s),{grad:s[0],value:r}}}function BN(e){return M(Wr(e),()=>"The f passed in valueAndGrads(f) must be a function"),(t,n)=>{M(Array.isArray(t)&&t.every(r=>r instanceof Ge),()=>"The args passed in valueAndGrads(f)(args) must be array of tensors"),M(n==null||n instanceof Ge,()=>"The dy passed in valueAndGrads(f)(args, dy) must be a tensor");let s=z.gradients(()=>e(...t),t,n);return n!=null&&An(s.value.shape,n.shape,"The shape of dy passed in valueAndGrads(f)([x1,...], dy) must match the shape returned by f([x1,...])"),Yh(s.grads),s}}function cb(e,t){M(Wr(e),()=>"The f passed in variableGrads(f) must be a function"),M(t==null||Array.isArray(t)&&t.every(u=>u instanceof nc),()=>"The varList passed in variableGrads(f, varList) must be an array of variables");let n=t!=null;if(!n){t=[];for(let u in z.registeredVariables)t.push(z.registeredVariables[u])}let s=n?t.filter(u=>!u.trainable):null,r=t.length;t=t.filter(u=>u.trainable),M(t.length>0,()=>`variableGrads() expects at least one of the input variables to be trainable, but none of the ${r} variables is trainable.`);let a=!0,{value:o,grads:i}=z.gradients(e,t,null,a);M(i.some(u=>u!=null),()=>"Cannot find a connection between any variable and the result of the loss function y=f(x). Please make sure the operations that use variables are inside the function f passed to minimize()."),M(o.rank===0,()=>`The f passed in variableGrads(f) must return a scalar, but it returned a rank-${o.rank} tensor`);let l={};return t.forEach((u,c)=>{i[c]!=null&&(l[u.name]=i[c])}),s!=null&&s.forEach(u=>l[u.name]=null),{value:o,grads:l}}function nr(e){return z.customGrad(e)}function Yh(e){if(e.filter(n=>n==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 WN(e){let n={x:$(e,"x","neg")};return z.runKernel(Qi,n)}var Tt=W({neg_:WN});function VN(e){let n={x:$(e,"x","softplus")};return z.runKernel(ml,n)}var zl=W({softplus_:VN});function UN(e){let t=$(e,"x","logSigmoid");return nr(s=>({value:Tt(zl(Tt(s))),gradFunc:o=>L(o,Hn(Tt(s)))}))(t)}var HN=W({logSigmoid_:UN});function GN(e,t=null,n=!1){let r={x:$(e,"x","max")},a={reductionIndices:t,keepDims:n};return z.runKernel(Ka,r,a)}var hs=W({max_:GN});function jN(e,t){let n=$(e,"a","sub"),s=$(t,"b","sub");[n,s]=Ct(n,s);let r={a:n,b:s};return z.runKernel(bo,r)}var ge=W({sub_:jN});function qN(e,t=null,n=!1){let s=$(e,"x","sum");s.dtype==="bool"&&(s=ce(s,"int32"));let r={x:s},a={axis:t,keepDims:n};return z.runKernel(Ao,r,a)}var ve=W({sum_:qN});function XN(e,t=-1){let n=$(e,"logits","logSoftmax");if(t===-1&&(t=n.rank-1),t!==n.rank-1)throw Error(`Log Softmax along a non-last dimension is not yet supported. Logits was rank ${n.rank} and axis was ${t}`);return nr((r,a)=>{let o=!0,i=hs(r,t,!0),l=ge(r,i),u=ge(ce(l,"float32"),ds(ve(cs(l),t,o)));return a([u]),{value:u,gradFunc:(d,h)=>{let[p]=h,f=!0,m=cs(p);return ge(d,L(ve(d,t,f),m))}}})(n)}var $g=W({logSoftmax_:XN});function Fg(e,t){for(let n=0;n<e.length;++n)if(e[e.length-n-1]!==t-1-n)return!1;return!0}function db(e,t,n){let s=e.length+t.length,r=[],a=0,o=0;for(let i=0;i<s;i++)n.indexOf(i)===-1?r.push(e[a++]):r.push(t[o++]);return r}function hb(e,t){let n=[],s=e.length;for(let a=0;a<s;a++)t.indexOf(a)===-1&&n.push(e[a]);let r=t.map(a=>e[a]);return[n,r]}function Mo(e,t){let n=t.map(s=>1);return db(e,n,t)}function KN(e,t,n){M(Fg(t,n),()=>`${e} supports only inner-most axes for now. Got axes ${t} and rank-${n} input.`)}function pb(e,t){if(Fg(e,t))return null;let n=[];for(let s=0;s<t;++s)e.indexOf(s)===-1&&n.push(s);return e.forEach(s=>n.push(s)),n}function Og(e){return e.map((t,n)=>[n,t]).sort((t,n)=>t[1]-n[1]).map(t=>t[0])}function ZN(e,t){let n=[];for(let s=t-e;s<t;++s)n.push(s);return n}function YN(e,t=null,n=!1){let s=$(e,"x","logSumExp"),r=Ss(t,s.shape),a=hs(s,r,!0),o=ge(s,a),i=cs(o),l=ve(i,r),u=ds(l),c=ae(U(a,u.shape),u);if(n){let d=Mo(c.shape,r);return U(c,d)}return c}var fb=W({logSumExp_:YN});function JN(e,t){let n=$(e,"a","logicalAnd","bool"),s=$(t,"b","logicalAnd","bool");At(n.shape,s.shape);let r={a:n,b:s};return z.runKernel(Yi,r)}var Ps=W({logicalAnd_:JN});function QN(e){let n={x:$(e,"x","logicalNot","bool")};return z.runKernel(Wu,n)}var Jh=W({logicalNot_:QN});function eE(e,t){let n=$(e,"a","logicalOr","bool"),s=$(t,"b","logicalOr","bool");At(n.shape,s.shape);let r={a:n,b:s};return z.runKernel(Vu,r)}var Pg=W({logicalOr_:eE});function tE(e,t){let n=$(e,"a","logicalXor","bool"),s=$(t,"b","logicalXor","bool");return At(n.shape,s.shape),Ps(Pg(e,t),Jh(Ps(e,t)))}var nE=W({logicalXor_:tE});function sE(e,t,n,s,r){let a=$(e,"x","maxPool"),o=1,i=a,l=!1;a.rank===3&&(l=!0,i=U(a,[1,a.shape[0],a.shape[1],a.shape[2]])),M(i.rank===4,()=>`Error in maxPool: input must be rank 4 but got rank ${i.rank}.`),M(tr(n,o),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${n} and dilations '${o}'`),r!=null&&M(Zt(s),()=>`Error in maxPool: pad must be an integer when using, dimRoundingMode ${r} but got pad ${s}.`);let u={x:i},c={filterSize:t,strides:n,pad:s,dimRoundingMode:r},d=z.runKernel(Ya,u,c);return l?U(d,[d.shape[1],d.shape[2],d.shape[3]]):d}var Qh=W({maxPool_:sE});function rE(e,t=[1,1,1],n,s,r,a="NDHWC"){let o=$(e,"x","maxPool3d"),i=o,l=!1;o.rank===4&&(l=!0,i=U(o,[1,o.shape[0],o.shape[1],o.shape[2],o.shape[3]])),M(i.rank===5,()=>`Error in maxPool3d: x must be rank 5 but got rank ${i.rank}.`),M(a==="NDHWC",()=>`Error in maxPool3d: Only NDHWC is currently supported, but got dataFormat of ${a}`),r!=null&&M(Zt(s),()=>`Error in maxPool3d: pad must be an integer when using, dimRoundingMode ${r} but got pad ${s}.`);let u={x:i},c={filterSize:t,strides:n,pad:s,dimRoundingMode:r,dataFormat:a},d=z.runKernel(Hu,u,c);return l?U(d,[d.shape[1],d.shape[2],d.shape[3],d.shape[4]]):d}var Mg=W({maxPool3d_:rE});function aE(e,t,n,s,r=!1){let o={x:$(e,"x","maxPoolWithArgmax")},i={filterSize:t,strides:n,pad:s,includeBatchInIndex:r},l=z.runKernel(gh,o,i);return{result:l[0],indexes:l[1]}}var mb=W({maxPoolWithArgmax_:aE});function oE(e,t){let n=$(e,"a","maximum"),s=$(t,"b","maximum");[n,s]=Ct(n,s),n.dtype==="bool"&&(n=ce(n,"int32"),s=ce(s,"int32")),At(n.shape,s.shape);let r={a:n,b:s};return z.runKernel(Za,r)}var kr=W({maximum_:oE});function iE(e,t=null,n=!1){let r={x:$(e,"x","mean")},a={axis:t,keepDims:n};return z.runKernel(Ja,r,a)}var _t=W({mean_:iE});function Pt(e,t="float32"){if(t==="complex64"){let s=Pt(e,"float32"),r=Pt(e,"float32");return qr(s,r)}let n=qd($t(e),t);return z.makeTensor(n,e,t)}function qn(e,t="float32"){if(t==="complex64"){let s=qn(e,"float32"),r=Pt(e,"float32");return qr(s,r)}let n=Om($t(e),t);return z.makeTensor(n,e,t)}function lE(e,t,{indexing:n="xy"}={}){if(n!=="xy"&&n!=="ij")throw new TypeError(`${n} is not a valid third argument to meshgrid`);if(e===void 0)return[];let s=$(e,"x","meshgrid",e instanceof Ge?e.dtype:"float32");if(t===void 0)return[s];let r=$(t,"y","meshgrid",t instanceof Ge?t.dtype:"float32"),a=$t(s.shape),o=$t(r.shape);return n==="xy"?(s=U(s,[1,-1]),r=U(r,[-1,1]),[Ve(qn([o,1],s.dtype),s),Ve(r,qn([1,a],r.dtype))]):(s=U(s,[-1,1]),r=U(r,[1,-1]),[Ve(s,qn([1,o],s.dtype)),Ve(qn([a,1],r.dtype),r)])}function uE(e,t=null,n=!1){let r={x:$(e,"x","min")},a={axis:t,keepDims:n};return z.runKernel(Qa,r,a)}var ep=W({min_:uE});function cE(e,t){let n=$(e,"a","minimum"),s=$(t,"b","minimum");[n,s]=Ct(n,s),n.dtype==="bool"&&(n=ce(n,"int32"),s=ce(s,"int32")),At(n.shape,s.shape);let r={a:n,b:s};return z.runKernel(eo,r)}var pc=W({minimum_:cE});function dE(e,t,n){M(n==="reflect"||n==="symmetric",()=>`Invalid mode. Mode must be either reflect or symmetric. Got ${n}.`);let s=$(e,"x","mirrorPad");if(s.rank===0)throw new Error("mirrorPad(scalar) is not defined. Pass non-scalar to mirrorPad");M(t.length===s.rank,()=>`Padding doesn't match input. Must be ${s.rank}. Got ${t.length}.`);let r=n==="reflect"?1:0;for(let i=0;i<s.rank;i++)M(t[i].length===2,()=>"Invalid number of paddings. Must be length of 2 each."),M(t[i][0]>=0&&t[i][0]<=s.shape[i]-r&&t[i][1]>=0&&t[i][1]<=s.shape[i]-r,()=>`Padding in dimension ${i} cannot be greater than or equal to ${s.shape[i]-r} or less than 0 for input of shape ${s.shape}`);let a={paddings:t,mode:n},o={x:s};return z.runKernel(to,o,a)}var gb=W({mirrorPad_:dE});function hE(e,t){let n=$(e,"a","mod"),s=$(t,"b","mod");[n,s]=Ct(n,s);let r={a:n,b:s};return z.runKernel(Ji,r)}var Ab=W({mod_:hE});function pE(e){let t=$(e,"x","square"),n={};return z.runKernel("Square",{x:t},n)}var ct=W({square_:pE});function fE(e,t=null,n=!1){e=$(e,"x","moments");let s=Ss(t,e.shape),r=_t(e,s,n),a=r.shape;n||(a=Mo(r.shape,s));let o=ct(ge(ce(e,"float32"),U(r,a))),i=_t(o,s,n);return{mean:r,variance:i}}var tp=W({moments_:fE});function mE(e,t,n,s){let r=$(t,"data","multiRNNCell"),a=ac(n,"c","multiRNNCell"),o=ac(s,"h","multiRNNCell"),i=r,l=[];for(let d=0;d<e.length;d++){let h=e[d](i,a[d],o[d]);l.push(h[0]),l.push(h[1]),i=h[1]}let u=[],c=[];for(let d=0;d<l.length;d+=2)u.push(l[d]),c.push(l[d+1]);return[u,c]}var gE=W({multiRNNCell_:mE});function AE(e,t,n,s=!1){let r=$(e,"logits","multinomial"),a=r.size,o=r.rank;if(a<2)throw new Error(`Error in multinomial: you need at least 2 outcomes, but got ${a}.`);if(o>2)throw new Error(`Rank of probabilities must be 1 or 2, but is ${o}`);n=n||Math.random();let l={logits:o===1?U(r,[1,-1]):r},u={numSamples:t,seed:n,normalized:s},c=z.runKernel(Ah,l,u);return o===1?U(c,[c.size]):c}var yb=W({multinomial_:AE});function yE(e,t){let n=$(e,"a","notEqual","string_or_numeric"),s=$(t,"b","notEqual","string_or_numeric");[n,s]=Ct(n,s),At(n.shape,s.shape);let r={a:n,b:s};return z.runKernel(el,r)}var Ll=W({notEqual_:yE});function xE(e){let n={x:$(e,"x","onesLike")};return z.runKernel(rl,n)}var ps=W({onesLike_:xE});function bE(e,t){let n=$(e,"v1","outerProduct"),s=$(t,"v2","outerProduct");M(n.rank===1&&s.rank===1,()=>`Error in outerProduct: inputs must be rank 1, but got ranks ${n.rank} and ${s.rank}.`);let r=U(n,[-1,1]),a=U(s,[1,-1]);return Ve(r,a)}var vE=W({outerProduct_:bE});function wE(e,t,n=0){let s=$(e,"x","pad");if(s.rank===0)throw new Error("pad(scalar) is not defined. Pass non-scalar to pad");let r={paddings:t,constantValue:n},a={x:s};return z.runKernel(ro,a,r)}var Qr=W({pad_:wE});function kE(e,t,n=0){return M(t.length===2,()=>"Invalid number of paddings. Must be length of 2."),Qr(e,[t],n)}var IE=W({pad1d_:kE});function SE(e,t,n=0){return M(t.length===2&&t[0].length===2&&t[1].length===2,()=>"Invalid number of paddings. Must be length of 2 each."),Qr(e,t,n)}var CE=W({pad2d_:SE});function TE(e,t,n=0){return M(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."),Qr(e,t,n)}var NE=W({pad3d_:TE});function EE(e,t,n=0){return M(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."),Qr(e,t,n)}var RE=W({pad4d_:EE});function _E(e,t,n){let s=$(e,"x","spaceToBatchND");M(s.rank>=1+t.length,()=>`input rank ${s.rank} should be > than [blockShape] ${t.length}`),M(n.length===t.length,()=>`paddings.shape[0] ${n.length} must be equal to [blockShape] ${t.length}`),M(s.shape.reduce((o,i,l)=>l>0&&l<=t.length?o&&(i+n[l-1][0]+n[l-1][1])%t[l-1]==0:o,!0),()=>`input spatial dimensions ${s.shape.slice(1)} with paddings ${n.toString()} must be divisible by blockShapes ${t.toString()}`);let r={x:s},a={blockShape:t,paddings:n};return z.runKernel(gl,r,a)}var np=W({spaceToBatchND_:_E});function DE(e,t,n,s,r,a){r==null&&(r=[1,1]),a==null&&(a=1),s===0&&(s="valid");let o=$(e,"x","maxPool"),i=o,l=!1;o.rank===3&&(l=!0,i=U(o,[1,o.shape[0],o.shape[1],o.shape[2]])),M(tr(a,r),()=>`Error in pool: Either strides or dilations must be 1. Got strides ${a} and dilations '${r}'`);let u=Wx(i.shape,t,a,r,s),c=[u.dilationHeight,u.dilationWidth],d;s==="same"?d=FE([u.filterHeight,u.filterWidth],c):d=[[0,0],[0,0]];let h=c[0]===1&&c[1]===1,[p,f]=$E([u.inHeight,u.inWidth],c,d),m=h?s:"valid",g=h?i:np(i,c,p),y=(n==="avg"?()=>Gh(g,t,a,m):()=>Qh(g,t,a,m))(),x=h?y:jh(y,c,f);return l?U(x,[x.shape[1],x.shape[2],x.shape[3]]):x}function $E(e,t,n){let s=n.map(c=>c[0]),r=n.map(c=>c[1]),a=e.concat(s,r),o=t.map((c,d)=>(c-a[d]%c)%c),i=r.map((c,d)=>c+o[d]),l=t.map((c,d)=>[s[d],i[d]]),u=t.map((c,d)=>[0,o[d]]);return[l,u]}function FE(e,t){let s=e.map((o,i)=>o+(o-1)*(t[i]-1)).map(o=>o-1),r=s.map(o=>Math.floor(o/2)),a=s.map((o,i)=>o-r[i]);return s.map((o,i)=>[r[i],a[i]])}var OE=W({pool_:DE});function PE(e,t){let n=$(e,"base","pow"),s=$(t,"exp","pow");[n,s]=Ct(n,s);let r={a:n,b:s};return z.runKernel(ao,r)}var ea=W({pow_:PE});function ME(e,t){let n=$(e,"x","prelu"),s=$(t,"alpha","prelu"),r={x:n,alpha:s};return z.runKernel(oo,r)}var sp=W({prelu_:ME});function zE(e,t=null,n=!1){let s=$(e,"x","prod");s.dtype==="bool"&&(s=ce(s,"int32"));let r={x:s},a={axis:t,keepDims:n};return z.runKernel(ol,r,a)}var zg=W({prod_:zE});function LE(e,t,n){let s=$t(e),r=null;if(n==null||n==="float32")r=new Float32Array(s);else if(n==="int32")r=new Int32Array(s);else if(n==="bool")r=new Uint8Array(s);else throw new Error(`Unknown data type ${n}`);for(let a=0;a<s;a++)r[a]=t();return z.makeTensor(r,e,n)}var BE=W({rand_:LE}),Lg=Ia(g5()),Bg=class{constructor(e,t,n,s,r){this.mean=e,this.stdDev=t,this.dtype=n,this.nextVal=NaN,this.truncated=s,this.truncated&&(this.upper=this.mean+this.stdDev*2,this.lower=this.mean-this.stdDev*2);let a=r||Math.random();this.random=Lg.alea(a.toString())}nextValue(){if(!isNaN(this.nextVal)){let s=this.nextVal;return this.nextVal=NaN,s}let e,t,n=!1;for(;!n;){let s,r,a;do s=2*this.random()-1,r=2*this.random()-1,a=s*s+r*r;while(a>=1||a===0);let o=Math.sqrt(-2*Math.log(a)/a);e=this.mean+this.stdDev*s*o,t=this.mean+this.stdDev*r*o,(!this.truncated||this.isValidTruncated(e))&&(n=!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}},WE=class{constructor(e,t,n,s){this.alpha=e,this.beta=1/t,this.dtype=n;let r=s||Math.random();this.randu=Lg.alea(r.toString()),this.randn=new Bg(0,1,n,!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,n,s,r,a;for(;;){do s=this.randn.nextValue(),a=1+this.c*s;while(a<=0);if(a*=a*a,e=s*s,t=1-.331*e*e,n=.5*e+this.d*(1-a+Math.log(a)),r=this.randu(),r<t||Math.log(r)<n)break}return a=1/this.beta*this.d*a,this.alpha<1&&(a*=Math.pow(this.randu(),1/this.alpha)),this.convertValue(a)}convertValue(e){return this.dtype==="float32"?e:Math.round(e)}},VE=class{constructor(e=0,t=1,n,s){if(this.canReturnFloat=()=>this.dtype==null||this.dtype==="float32",this.min=e,this.range=t-e,this.dtype=n,s==null&&(s=Math.random()),typeof s=="number"&&(s=s.toString()),!this.canReturnFloat()&&this.range<=1)throw new Error(`The difference between ${e} - ${t} <= 1 and dtype is not float`);this.random=Lg.alea(s)}convertValue(e){return this.canReturnFloat()?e:Math.round(e)}nextValue(){return this.convertValue(this.min+this.range*this.random())}};function UE(e,t,n=1,s="float32",r){if(n==null&&(n=1),s==null&&(s="float32"),s!=="float32"&&s!=="int32")throw new Error(`Unsupported data type ${s}`);let a=new WE(t,n,s,r),o=We(e,s);for(let i=0;i<o.values.length;i++)o.values[i]=a.nextValue();return o.toTensor()}var HE=W({randomGamma_:UE});function GE(e,t=0,n=1,s,r){if(s!=null&&s==="bool")throw new Error(`Unsupported data type ${s}`);let a=new Bg(t,n,s,!1,r),o=We(e,s);for(let i=0;i<o.values.length;i++)o.values[i]=a.nextValue();return o.toTensor()}var xb=W({randomNormal_:GE});function jE(e,t=0,n=1,s="float32",r){let a=We(e,s),o=new VE(t,n,null,r);for(let i=0;i<a.values.length;i++)a.values[i]=o.nextValue();return a.toTensor()}var Bl=W({randomUniform_:jE});function Wl(e,t,n=1,s="float32"){if(n===0)throw new Error("Cannot have a step of zero");let r={start:e,stop:t,step:n,dtype:s};return z.runKernel(Gu,{},r)}function qE(e){let n={input:$(e,"input","real")};return z.runKernel(yh,n)}var fc=W({real_:qE});function XE(e){let n={x:$(e,"x","reciprocal")};return z.runKernel(il,n)}var bb=W({reciprocal_:XE});function KE(e){let n={x:$(e,"x","relu")};return z.runKernel(io,n)}var sr=W({relu_:KE});function ZE(e){let n={x:$(e,"x","relu6")};return z.runKernel(uo,n)}var Wg=W({relu6_:ZE});function YE(e,t){let s={x:$(e,"x","reverse")},r={dims:t};return z.runKernel(co,s,r)}var fs=W({reverse_:YE});function JE(e){let t=$(e,"x","reverse");return M(t.rank===1,()=>`Error in reverse1D: x must be rank 1 but got rank ${t.rank}.`),fs(t,0)}var QE=W({reverse1d_:JE});function eR(e,t){let n=$(e,"x","reverse");return M(n.rank===2,()=>`Error in reverse2D: x must be rank 2 but got rank ${n.rank}.`),fs(n,t)}var tR=W({reverse2d_:eR});function nR(e,t){let n=$(e,"x","reverse");return M(n.rank===3,()=>`Error in reverse3D: x must be rank 3 but got rank ${n.rank}.`),fs(n,t)}var sR=W({reverse3d_:nR});function rR(e,t){let n=$(e,"x","reverse");return M(n.rank===4,()=>`Error in reverse4D: x must be rank 4 but got rank ${n.rank}.`),fs(n,t)}var aR=W({reverse4d_:rR});function oR(e){let n={x:$(e,"x","round")};return z.runKernel(ho,n)}var Vg=W({round_:oR});function iR(e){let n={x:$(e,"x","rsqrt")};return z.runKernel(po,n)}var Ug=W({rsqrt_:iR});function Ie(e,t){if((cn(e)&&t!=="string"||Array.isArray(e))&&t!=="complex64")throw new Error("Error creating a new Scalar: value must be a primitive (number|boolean|string)");if(t==="string"&&cn(e)&&!(e instanceof Uint8Array))throw new Error("When making a scalar from encoded string, the value must be `Uint8Array`.");return Xr(e,[],[],t)}function lR(e){let n={x:$(e,"x","selu")};return z.runKernel(dl,n)}var Hg=W({selu_:lR});function uR(e,t,n,s,r,a=[1,1],o="NHWC"){let i=$(e,"x","separableConv2d"),l=$(t,"depthwiseFilter","separableConv2d"),u=$(n,"pointwiseFilter","separableConv2d"),c=i,d=!1;if(i.rank===3&&(d=!0,c=U(i,[1,i.shape[0],i.shape[1],i.shape[2]])),o==="NCHW")throw new Error("separableConv2d currently does not support dataFormat NCHW; only NHWC is supported");M(c.rank===4,()=>`Error in separableConv2d: input must be rank 4, but got rank ${c.rank}.`),M(l.rank===4,()=>`Error in separableConv2d: depthwise filter must be rank 4, but got rank ${l.rank}.`),M(u.rank===4,()=>`Error in separableConv2d: pointwise filter must be rank 4, but got rank ${l.rank}.`),M(u.shape[0]===1,()=>`Error in separableConv2d: the first dimension of pointwise filter must be 1, but got ${u.shape[0]}.`),M(u.shape[1]===1,()=>`Error in separableConv2d: the second dimension of pointwise filter must be 1, but got ${u.shape[1]}.`);let h=l.shape[2],p=l.shape[3];M(u.shape[2]===h*p,()=>`Error in separableConv2d: the third dimension of pointwise filter must be ${h*p}, but got ${u.shape[2]}.`);let f=cc(c,l,s,r,o,a),g=Jr(f,u,1,"valid",o);return d?U(g,[g.shape[1],g.shape[2],g.shape[3]]):g}var vb=W({separableConv2d_:uR});async function cR(e,t){let n=$(e,"x","setdiff1d"),s=$(t,"y","setdiff1d");M(n.dtype===s.dtype,()=>`x and y should have the same dtype, but got x (${n.dtype}) and y (${s.dtype}).`),M(n.rank===1,()=>`x should be 1D tensor, but got x (${n.shape}).`),M(s.rank===1,()=>`y should be 1D tensor, but got y (${s.shape}).`);let r=await n.data(),a=await s.data(),o=new Set(a),i=0;for(let c=0;c<r.length;c++)o.has(r[c])||i++;let l=new Ut([i],n.dtype),u=new Ut([i],"int32");for(let c=0,d=0;c<r.length;c++)o.has(r[c])||(l.values[d]=r[c],u.values[d]=c,d++);return[l.toTensor(),u.toTensor()]}var wb=cR;function dR(e){let n={x:$(e,"x","sign")};return z.runKernel(fl,n)}var kb=W({sign_:dR});function hR(e){let n={x:$(e,"x","sin")};return z.runKernel(fo,n)}var Gg=W({sin_:hR});function pR(e){let n={x:$(e,"x","sinh")};return z.runKernel(pl,n)}var jg=W({sinh_:pR});function fR(e,t,n){let s=$(e,"x","slice1d");return M(s.rank===1,()=>`slice1d expects a rank-1 tensor, but got a rank-${s.rank} tensor`),Re(s,[t],[n])}var rp=W({slice1d_:fR});function mR(e,t,n){let s=$(e,"x","slice2d");return M(s.rank===2,()=>`slice2d expects a rank-2 tensor, but got a rank-${s.rank} tensor`),Re(s,t,n)}var qg=W({slice2d_:mR});function gR(e,t,n){let s=$(e,"x","slice3d");return M(s.rank===3,()=>`slice3d expects a rank-3 tensor, but got a rank-${s.rank} tensor`),Re(s,t,n)}var ap=W({slice3d_:gR});function AR(e,t,n){let s=$(e,"x","slice4d");return M(s.rank===4,()=>`slice4d expects a rank-4 tensor, but got a rank-${s.rank} tensor`),Re(s,t,n)}var mc=W({slice4d_:AR});function yR(e,t=-1){let n=$(e,"logits","softmax","float32");if(t===-1&&(t=n.rank-1),t!==n.rank-1)throw Error(`Softmax along a non-last dimension is not yet supported. Logits was rank ${n.rank} and dim was ${t}`);let s={logits:n},r={dim:t};return z.runKernel(yo,s,r)}var op=W({softmax_:yR});function xR(e){M(e.dtype==="complex64",()=>`The dtype for tf.spectral.fft() must be complex64 but got ${e.dtype}.`);let t={input:e};return z.runKernel(uh,t)}var ip=W({fft_:xR});function bR(e){M(e.dtype==="complex64",()=>`The dtype for tf.spectral.ifft() must be complex64 but got ${e.dtype}.`);let t={input:e};return z.runKernel(ch,t)}var gc=W({ifft_:bR});function vR(e){let t=e.shape[e.shape.length-1],n=e.size/t,s;if(t<=2){let r=U(e,[n,t]);s=gc(r)}else{let r=[n,2*(t-1)],a=U(fc(e),[n,t]),o=U(Xh(e),[n,t]),i=fs(Re(a,[0,1],[n,t-2]),1),l=L(fs(Re(o,[0,1],[n,t-2]),1),Ie(-1)),u=ft([a,i],1),c=ft([o,l],1),d=U(qr(u,c),[r[0],r[1]]);s=gc(d)}if(s=fc(s),e.rank===3&&e.shape[0]!==0){let r=s,a=e.shape[0];s=U(s,[a,s.shape[0]/a,s.shape[1]]),r.dispose()}return s}var Xg=W({irfft_:vR});function wR(e,t,n=0){let r={x:$(e,"x","split")},a={numOrSizeSplits:t,axis:n};return z.runKernel(Al,r,a)}var an=W({split_:wR});function kR(e,t){M(e.dtype==="float32",()=>`The dtype for rfft() must be real value but got ${e.dtype}`);let n=e.shape[e.shape.length-1],s=e.size/n,r;if(t!=null&&t<n){let f=e.shape.map(g=>0),m=e.shape.map(g=>g);m[e.shape.length-1]=t,r=Re(e,f,m),n=t}else if(t!=null&&t>n){let f=e.shape.map(m=>m);f[e.shape.length-1]=t-n,r=ft([e,Pt(f)],e.shape.length-1),n=t}else r=e;let a=Ke(r),o=U(qr(r,a),[s,n]),i=ip(o),l=Math.floor(n/2)+1,u=fc(i),c=Xh(i),d=an(u,[l,n-l],u.shape.length-1),h=an(c,[l,n-l],c.shape.length-1),p=r.shape.slice();return p[r.shape.length-1]=l,U(qr(d[0],h[0]),p)}var lp=W({rfft_:kR});function IR(e){let n={x:$(e,"x","sqrt")};return z.runKernel(go,n)}var hn=W({sqrt_:IR});function SR(e,t){let n=$(e,"a","squaredDifference"),s=$(t,"b","squaredDifference");[n,s]=Ct(n,s),At(n.shape,s.shape);let r={a:n,b:s},a={};return z.runKernel(xo,r,a)}var Kg=W({squaredDifference_:SR});function CR(e,t){let n=$(e,"x","squeeze");return U(n,b5(n.shape,t).newShape)}var lt=W({squeeze_:CR});function TR(e,t=0){let n=ac(e,"tensors","stack","string_or_numeric");M(n.length>=1,()=>"Pass at least one tensor to tf.stack"),n.length>0&&M(t<=n[0].rank,()=>"Axis must be <= rank of the tensor");let s=n,r={axis:t};return z.runKernel(al,s,r)}var Dn=W({stack_:TR});function NR(e,t=0){let s={x:$(e,"x","step")},r={alpha:t};return z.runKernel(Gr,s,r)}var Ac=W({step_:NR});function ER(e,t,n,s,r=0,a=0,o=0,i=0,l=0){let c={x:$(e,"x","stridedSlice","string_or_numeric")},d={begin:t,end:n,strides:s,beginMask:r,endMask:a,ellipsisMask:o,newAxisMask:i,shrinkAxisMask:l};return z.runKernel(yl,c,d)}var Ib=W({stridedSlice_:ER});function RR(e){let n={x:$(e,"x","tan")};return z.runKernel(vo,n)}var Sb=W({tan_:RR});function Mt(e,t){Sa(e);let n=Qs(e,t);if(n.length!==1)throw new Error("tensor1d() requires values to be a flat/TypedArray");return Xr(e,null,n,t)}function Ms(e,t,n){if(Sa(e),t!=null&&t.length!==2)throw new Error("tensor2d() requires shape to have two numbers");let s=Qs(e,n);if(s.length!==2&&s.length!==1)throw new Error("tensor2d() requires values to be number[][] or flat/TypedArray");if(s.length===1&&t==null)throw new Error("tensor2d() requires shape to be provided when `values` are a flat/TypedArray");return Xr(e,t,s,n)}function _R(e,t,n){if(Sa(e),t!=null&&t.length!==4)throw new Error("tensor4d() requires shape to have four numbers");let s=Qs(e,n);if(s.length!==4&&s.length!==1)throw new Error("tensor4d() requires values to be number[][][][] or flat/TypedArray");if(s.length===1&&t==null)throw new Error("tensor4d() requires shape to be provided when `values` are a flat array");return Xr(e,t,s,n)}function DR(e,t,n){if(Sa(e),t!=null&&t.length!==5)throw new Error("tensor5d() requires shape to have five numbers");let s=Qs(e,n);if(s.length!==5&&s.length!==1)throw new Error("tensor5d() requires values to be number[][][][][] or flat/TypedArray");if(s.length===1&&t==null)throw new Error("tensor5d() requires shape to be provided when `values` are a flat array");return Xr(e,t,s,n)}function $R(e,t,n){if(Sa(e),t!=null&&t.length!==6)throw new Error("tensor6d() requires shape to have six numbers");let s=Qs(e,n);if(s.length!==6&&s.length!==1)throw new Error("tensor6d() requires values to be number[][][][][][] or flat/TypedArray");if(s.length===1&&t==null)throw new Error("tensor6d() requires shape to be provided when `values` are a flat array");return t=t||s,Xr(e,t,s,n)}function FR(e,t=1,n=!0){let s=$(e,"x","topk");if(s.rank===0)throw new Error("topk() expects the input to be of rank 1 or higher");let r=s.shape[s.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 a={x:s},o={k:t,sorted:n},[i,l]=z.runKernel(xl,a,o);return{values:i,indices:l}}var Cb=W({topk_:FR});function OR(e,t=0,n=1,s,r){if(s!=null&&s==="bool")throw new Error("Unsupported data type $ { dtype }");let a=new Bg(t,n,s,!0,r),o=We(e,s);for(let i=0;i<o.values.length;i++)o.values[i]=a.nextValue();return o.toTensor()}var up=W({truncatedNormal_:OR});function PR(e,t=0){let n=$(e,"x","unique","string_or_numeric");M(n.rank>0,()=>"The input tensor must be at least 1D");let s={x:n},r={axis:t},[a,o]=z.runKernel(Eh,s,r);return{values:a,indices:o}}var Zg=W({unique_:PR});function MR(e,t,n){let s=$(e,"x","unsortedSegmentSum"),r=$(t,"segmentIds","unsortedSegmentSum","int32");M(Zt(n),()=>"numSegments must be of dtype int");let a={x:s,segmentIds:r},o={numSegments:n};return z.runKernel(Xu,a,o)}var Tb=W({unsortedSegmentSum_:MR});function zR(e,t=0){let n=$(e,"x","unstack","string_or_numeric");M(t>=-n.shape.length&&t<n.shape.length,()=>`Axis = ${t} is not in [-${n.shape.length}, ${n.shape.length})`);let s={value:n},r={axis:t};return z.runKernel(vl,s,r)}var ms=W({unstack_:zR});function Nb(e,t=!0,n,s){return z.makeVariable(e,t,n,s)}function Eb(e,t){let n=[];for(let a=0;a<t.length;a++)t[a]&&n.push(a);let s=We(e,"int32"),r=We([n.length,e.length],"int32");for(let a=0;a<n.length;a++){let o=s.indexToLoc(n[a]),i=a*e.length;r.values.set(o,i)}return r.toTensor()}async function LR(e){let t=$(e,"condition","whereAsync","bool"),n=await t.data(),s=Eb(t.shape,n);return e!==t&&t.dispose(),s}var Yg=LR;async function BR(e,t,n){let s=$(e,"tensor","boolMask"),r=$(t,"mask","boolMask","bool"),a=n==null?0:n,o=r.rank,i=s.shape;M(o>0,()=>"mask cannot be scalar"),An(i.slice(a,a+o),r.shape,"mask's shape must match the first K dimensions of tensor's shape,");let l=1;for(let m=a;m<a+o;m++)l*=i[m];let u=i.slice(0,a).concat([l],i.slice(a+o)),c=U(s,u),d=U(r,[-1]),h=await Yg(d),p=lt(h,[1]),f=Ml(c,p,a);return e!==s&&s.dispose(),t!==r&&r.dispose(),p.dispose(),c.dispose(),d.dispose(),h.dispose(),f}var WR=BR;function VR(e,t="euclidean",n=null,s=!1){e=$(e,"x","norm");let r=Rb(e,t,n),a=r.shape;if(s){let o=Ss(n,e.shape);a=Mo(r.shape,o)}return U(r,a)}function Rb(e,t,n=null){if(e.rank===0)return Ht(e);if(e.rank!==1&&n===null)return Rb(U(e,[-1]),t,n);if(e.rank===1||typeof n=="number"||Array.isArray(n)&&n.length===1){if(t===1)return ve(Ht(e),n);if(t===1/0)return hs(Ht(e),n);if(t===-1/0)return ep(Ht(e),n);if(t==="euclidean"||t===2)return hn(ve(ea(Ht(e),Ie(2,"int32")),n));throw new Error(`Error in norm: invalid ord value: ${t}`)}if(Array.isArray(n)&&n.length===2){if(t===1)return hs(ve(Ht(e),n[0]),n[1]-1);if(t===1/0)return hs(ve(Ht(e),n[1]),n[0]);if(t===-1/0)return ep(ve(Ht(e),n[1]),n[0]);if(t==="fro"||t==="euclidean")return hn(ve(ct(e),n));throw new Error(`Error in norm: invalid ord value: ${t}`)}throw new Error(`Error in norm: invalid axis: ${n}`)}var Jg=W({norm_:VR});function UR(e,t,n,s,r=!0){let a=$(e,"v","movingAverage"),o=$(t,"x","movingAverage"),i=$(n,"decay","movingAverage");W5(a,o),M(br(a.shape,o.shape),()=>"Shape mismatch in v and x");let l=Ie(1),u=ge(l,i),c=L(ge(o,a),u);if(r){M(s!=null,()=>"When using zeroDebias: true, step is required.");let d=$(s,"step","movingAverage");c=de(c,ge(l,ea(i,d)))}return ae(a,c)}var HR=W({movingAverage_:UR});function GR(e,t,n){let s=$(e,"indices","scatterND","int32"),r=$(t,"updates","scatterND");pg(r,s,n);let a={indices:s,updates:r},o={shape:n};return z.runKernel(ul,a,o)}var _b=W({scatterND_:GR});function jR(e,t,n,s){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,a=e.rank>1?e.shape[1]:1;if(n.length!==a)throw new Error(`outputShape has incorrect number of elements:, ${n.length}, should be: ${a}.`);let o=t.size;if(!(t.rank===0||t.rank===1&&o===r))throw new Error(`sparseValues has incorrect shape ${t.shape}, should be [] or [${r}]`);if(t.dtype!==s.dtype)throw new Error("sparseValues.dtype must match defaultValues.dtype")}function qR(e,t,n,s=0){let r=$(e,"sparseIndices","sparseToDense","int32"),a=$(t,"sparseValues","sparseToDense"),o=$(s,"defaultValue","sparseToDense",a.dtype);jR(r,a,n,o);let i={sparseIndices:r,sparseValues:a,defaultValue:o},l={outputShape:n};return z.runKernel(Sh,i,l)}var Qg=W({sparseToDense_:qR});function XR(e,t){let n=$(t,"indices","gatherND","int32"),r={params:$(e,"x","gatherND","string_or_numeric"),indices:n};return z.runKernel(Ui,r)}var Db=W({gatherND_:XR});function KR(e,t){if(t==null)return e.shape.slice();if(br(e.shape,t))return t;if(e.shape.length===t.length){let n=[];for(let s=0;s<e.shape.length;s++)t[s]==null&&e.shape[s]!=null?n.push(e.shape[s]):n.push(t[s]);return n}return t}function ZR(e,t,n,s){let r=$(e,"x","dropout");if(M(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.`),M(t>=0&&t<1,()=>`rate must be a float in the range [0, 1), but got ${t}.`),t===0)return e instanceof Ge?r.clone():r;let a=KR(r,n),o=1-t,i=de(hc(ae(Bl(a,0,1,"float32",s),o)),o);return L(r,i)}var $b=W({dropout_:ZR});function Fb(e){return Math.floor(Math.pow(2,Math.ceil(Math.log(e)/Math.log(2))))}function eA(e,t,n){let s=1-e%2,r=new Float32Array(e);for(let a=0;a<e;++a){let o=2*Math.PI*a/(e+s-1);r[a]=t-n*Math.cos(o)}return Mt(r,"float32")}async function YR(e,t,n=1){let s=$(e,"predictions","inTopK"),r=$(t,"targets","inTopK");M(s.rank>1,()=>`inTopK() expects the predictions to be of rank 2 or higher, but got ${s.rank}`),M(s.rank-1===r.rank,()=>`predictions rank should be 1 larger than targets rank, but got predictions rank ${s.rank} and targets rank ${r.rank}`),An(s.shape.slice(0,s.shape.length-1),r.shape,"predictions's shape should be align with the targets' shape, except the last dimension.");let a=s.shape[s.shape.length-1];M(n>0&&n<=a,()=>`'k' passed to inTopK() must be > 0 && <= the predictions last dimension (${a}), but got ${n}`);let o=await s.data(),i=await r.data(),[l,u]=[o.length/a,a],c=v5("bool",l);for(let d=0;d<l;d++){let h=d*u,p=o.subarray(h,h+u),f=[];for(let m=0;m<p.length;m++)f.push({value:p[m],index:m});f.sort((m,g)=>g.value-m.value),c[d]=0;for(let m=0;m<n;m++)if(f[m].index===i[d]){c[d]=1;break}}return e!==s&&s.dispose(),t!==r&&r.dispose(),dn(c,r.shape,"bool")}var JR=YR,ta={};Pe(ta,{conv2d:()=>t_,depthwiseConv2d:()=>a_,matMul:()=>i_});function QR(e,t,n,s,r,a="NHWC",o){let i=e;e.rank===3&&(i=U(e,[1,e.shape[0],e.shape[1],e.shape[2]]));let l=t;l.rank===3&&(l=U(t,[1,t.shape[0],t.shape[1],t.shape[2]])),M(i.rank===4,()=>`Error in conv2dDerFilter: input must be rank 4, but got shape ${i.shape}.`),M(l.rank===4,()=>`Error in conv2dDerFilter: dy must be rank 4, but got shape ${l.shape}.`),M(n.length===4,()=>`Error in conv2dDerFilter: filterShape must be length 4, but got ${n}.`);let u=a==="NHWC"?i.shape[3]:i.shape[1],c=a==="NHWC"?l.shape[3]:l.shape[1];M(u===n[2],()=>`Error in conv2dDerFilter: depth of input ${u}) must match input depth in filter (${n[2]}.`),M(c===n[3],()=>`Error in conv2dDerFilter: depth of dy (${c}) must match output depth for filter (${n[3]}).`),o!=null&&M(Zt(r),()=>`Error in conv2dDerFilter: pad must be an integer when using, dimRoundingMode ${o} but got pad ${r}.`);let d={x:i,dy:l},h={strides:s,pad:r,dataFormat:a,dimRoundingMode:o,filterShape:n};return z.runKernel(Jd,d,h)}var tA=W({conv2DBackpropFilter_:QR});function cp(e,t,n){if(n==null||n==="linear")return e;if(n==="relu")return L(e,Ac(t));throw new Error(`Cannot compute gradient for fused activation ${n}.`)}function dp(e,t){let n=t,s=Gt(e.shape,t.shape);return s.length>0&&(n=ve(n,s)),U(n,e.shape)}function hp(e,t,n,s){if(t==="linear")return e;if(t==="relu")return sr(e);if(t==="elu")return dc(e);if(t==="relu6")return Wg(e);if(t==="prelu")return sp(e,n);if(t==="leakyrelu")return Kh(e,s);if(t==="sigmoid")return Hn(e);throw new Error(`Unknown fused activation ${t}.`)}var pp=(e,t)=>!(e>0)||t==="linear";function e_({x:e,filter:t,strides:n,pad:s,dataFormat:r="NHWC",dilations:a=[1,1],dimRoundingMode:o,bias:i,activation:l="linear",preluActivationWeights:u,leakyreluAlpha:c}){if(l=l||"linear",pp(z.state.gradientDepth,l)===!1){let v=Jr(e,t,n,s,r,a,o);return i!=null&&(v=ae(v,i)),hp(v,l,u,c)}let d=$(e,"x","conv2d"),h=$(t,"filter","conv2d"),p=d,f=!1;d.rank===3&&(f=!0,p=U(d,[1,d.shape[0],d.shape[1],d.shape[2]])),M(p.rank===4,()=>`Error in fused conv2d: input must be rank 4, but got rank ${p.rank}.`),M(h.rank===4,()=>`Error in fused conv2d: filter must be rank 4, but got rank ${h.rank}.`),o!=null&&M(Zt(s),()=>`Error in fused conv2d: pad must be an integer when using, dimRoundingMode ${o} but got pad ${s}.`),M(p.shape[3]===h.shape[2],()=>`Error in conv2d: depth of input (${p.shape[3]}) must match input depth for filter ${h.shape[2]}.`),M(tr(n,a),()=>`Error in conv2D: Either strides or dilations must be 1. Got strides ${n} and dilations '${a}'`),M(r==="NHWC",()=>`Error in conv2d: got dataFormat of ${r} but only NHWC is currently supported.`);let m=lc(p.shape,h.shape,n,a,s,o),g;i!=null&&(g=$(i,"bias","fused conv2d"),[g]=Ct(g,d),At(m.outShape,g.shape));let A;u!=null&&(A=$(u,"prelu weights","fused conv2d"));let y=(v,k)=>{let[S,C,_,O]=k,E=cp(v,_,l);M(Yr(a),()=>`Error in gradient of fused conv2D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '${a}'`);let R=Cg(C.shape,E,S,n,s),T=tA(C,E,S.shape,n,s),P=[R,T];if(O!=null){let V=dp(O,E);P.push(V)}return P},x={x:p,filter:h,bias:g,preluActivationWeights:A},b={strides:n,pad:s,dataFormat:r,dilations:a,dimRoundingMode:o,activation:l,leakyreluAlpha:c};return i==null?nr((k,S,C)=>{let _=z.runKernel(So,x,b);return C([S,k,_]),f&&(_=U(_,[_.shape[1],_.shape[2],_.shape[3]])),{value:_,gradFunc:y}})(p,h):nr((k,S,C,_)=>{let O=z.runKernel(So,x,b);return _([S,k,O,C]),f&&(O=U(O,[O.shape[1],O.shape[2],O.shape[3]])),{value:O,gradFunc:y}})(p,h,g)}var t_=W({fusedConv2d_:e_});function n_(e,t,n,s,r,a=[1,1],o){let i=e;e.rank===3&&(i=U(e,[1,e.shape[0],e.shape[1],e.shape[2]]));let l=t;l.rank===3&&(l=U(t,[1,t.shape[0],t.shape[1],t.shape[2]]));let u={x:i,dy:l},c={strides:s,pad:r,dimRoundingMode:o,dilations:a,filterShape:n};return z.runKernel(nh,u,c)}var Ob=W({depthwiseConv2dNativeBackpropFilter_:n_});function s_(e,t,n,s,r,a=[1,1],o){let i=t,l=!1;t.rank===3&&(l=!0,i=U(t,[1,t.shape[0],t.shape[1],t.shape[2]]));let u={dy:i,filter:n},c={strides:s,pad:r,dimRoundingMode:o,dilations:a,inputShape:e},d=z.runKernel(sh,u,c);return l?U(d,[d.shape[1],d.shape[2],d.shape[3]]):d}var Pb=W({depthwiseConv2dNativeBackpropInput_:s_});function r_({x:e,filter:t,strides:n,pad:s,dataFormat:r="NHWC",dilations:a=[1,1],dimRoundingMode:o,bias:i,activation:l="linear",preluActivationWeights:u,leakyreluAlpha:c}){if(pp(z.state.gradientDepth,l)===!1){let v=cc(e,t,n,s,r,a,o);return i!=null&&(v=ae(v,i)),hp(v,l,u,c)}let d=$(e,"x","depthwiseConv2d"),h=$(t,"filter","depthwiseConv2d"),p=d,f=!1;d.rank===3&&(f=!0,p=U(d,[1,d.shape[0],d.shape[1],d.shape[2]])),M(p.rank===4,()=>`Error in fused depthwiseConv2d: input must be rank 4, but got rank ${p.rank}.`),M(h.rank===4,()=>`Error in fused depthwiseConv2d: filter must be rank 4, but got rank ${h.rank}.`),M(p.shape[3]===h.shape[2],()=>`Error in fused depthwiseConv2d: number of input channels (${p.shape[3]}) must match the inChannels dimension in filter ${h.shape[2]}.`),a==null&&(a=[1,1]),M(tr(n,a),()=>`Error in fused depthwiseConv2d: Either strides or dilations must be 1. Got strides ${n} and dilations '${a}'`),o!=null&&M(Zt(s),()=>`Error in fused depthwiseConv2d: pad must be an integer when using dimRoundingMode ${o} but got pad ${s}.`);let m=lc(p.shape,h.shape,n,a,s,o,!0),g;i!=null&&(g=$(i,"bias","fused conv2d"),[g]=Ct(g,d),At(m.outShape,g.shape));let A;u!=null&&(A=$(u,"prelu weights","fused depthwiseConv2d"));let y=(v,k)=>{M(Yr(a),()=>`Error in gradient of fused depthwiseConv2d: dilation rates greater than 1 are not yet supported. Got dilations '${a}'`);let[S,C,_,O]=k,E=cp(v,_,l),R=Pb(C.shape,E,S,n,s,a,o),T=Ob(C,E,S.shape,n,s,a,o);if(O!=null){let P=dp(g,E);return[R,T,P]}return[R,T]},x={x:p,filter:h,bias:g,preluActivationWeights:A},b={strides:n,pad:s,dataFormat:r,dilations:a,dimRoundingMode:o,activation:l,leakyreluAlpha:c};return i==null?nr((k,S,C)=>{let _=z.runKernel(Co,x,b);return C([S,k,_]),f&&(_=U(_,[_.shape[1],_.shape[2],_.shape[3]])),{value:_,gradFunc:y}})(p,h):nr((k,S,C,_)=>{let O=z.runKernel(Co,x,b);return _([S,k,O,C]),f&&(O=U(O,[O.shape[1],O.shape[2],O.shape[3]])),{value:O,gradFunc:y}})(p,h,g)}var a_=W({fusedDepthwiseConv2d_:r_});function o_({a:e,b:t,transposeA:n=!1,transposeB:s=!1,bias:r,activation:a="linear",preluActivationWeights:o,leakyreluAlpha:i}){if(pp(z.state.gradientDepth,a)===!1){let O=Ve(e,t,n,s);return r!=null&&(O=ae(O,r)),hp(O,a,o,i)}let l=$(e,"a","fused matMul"),u=$(t,"b","fused matMul");[l,u]=Ct(l,u);let c=n?l.shape[l.rank-2]:l.shape[l.rank-1],d=s?u.shape[u.rank-1]:u.shape[u.rank-2],h=n?l.shape[l.rank-1]:l.shape[l.rank-2],p=s?u.shape[u.rank-2]:u.shape[u.rank-1],f=l.shape.slice(0,-2),m=u.shape.slice(0,-2),g=$t(f),A=$t(m);M(l.rank>=2&&u.rank>=2&&l.rank===u.rank,()=>`Error in fused matMul: inputs must have the same rank of at least 2, got ranks ${l.rank} and ${u.rank}.`),M(br(f,m),()=>`Error in fused matMul: outer dimensions (${f}) and (${m}) of Tensors with shapes ${l.shape} and ${u.shape} must match.`),M(c===d,()=>`Error in fused matMul: inner shapes (${c}) and (${d}) of Tensors with shapes ${l.shape} and ${u.shape} and transposeA=${n} and transposeB=${s} must match.`);let y=l.shape.slice(0,-2).concat([h,p]),x=n?U(l,[g,c,h]):U(l,[g,h,c]),b=s?U(u,[A,p,d]):U(u,[A,d,p]),v;r!=null&&(v=$(r,"bias","fused matMul"),[v]=Ct(v,l),At(y,v.shape));let k;o!=null&&(k=$(o,"prelu weights","fused matMul"));let S=(O,E)=>{let[R,T,P,V]=E,j=cp(U(O,P.shape),P,a),q,X;if(!n&&!s?(q=Ve(j,T,!1,!0),X=Ve(R,j,!0,!1)):!n&&s?(q=Ve(j,T,!1,!1),X=Ve(j,R,!0,!1)):n&&!s?(q=Ve(T,j,!1,!0),X=Ve(R,j,!1,!1)):(q=Ve(T,j,!0,!0),X=Ve(j,R,!0,!0)),r!=null){let ee=dp(V,j);return[q,X,ee]}else return[q,X]},C={a:x,b,bias:v,preluActivationWeights:k},_={transposeA:n,transposeB:s,activation:a,leakyreluAlpha:i};return r==null?nr((E,R,T)=>{let P=z.runKernel(Io,C,_);return T([E,R,P]),{value:U(P,y),gradFunc:S}})(x,b):nr((E,R,T,P)=>{let V=z.runKernel(Io,C,_);return P([E,R,V,T]),{value:U(V,y),gradFunc:S}})(x,b,v)}var i_=W({fusedMatMul_:o_});function l_(e){return eA(e,.54,.46)}var u_=W({hammingWindow_:l_});function c_(e){return eA(e,.5,.5)}var Mb=W({hannWindow_:c_});function d_(e,t,n,s=!1,r=0){let a=0,o=[];for(;a+t<=e.size;)o.push(Re(e,a,t)),a+=n;if(s)for(;a<e.size;){let i=a+t-e.size,l=ft([Re(e,a,t-i),Pl([i],r)]);o.push(l),a+=n}return o.length===0?Ms([],[0,t]):U(ft(o),[o.length,t])}var zb=W({frame_:d_});function h_(e,t,n,s,r=Mb){s==null&&(s=Fb(t));let a=zb(e,t,n),o=L(a,r(t));return lp(o,s)}var p_=W({stft_:h_});function f_(e,t,n,s,r="bilinear",a=0){let o=$(e,"image","cropAndResize"),i=$(t,"boxes","cropAndResize","float32"),l=$(n,"boxInd","cropAndResize","int32"),u=i.shape[0];M(o.rank===4,()=>`Error in cropAndResize: image must be rank 4,but got rank ${o.rank}.`),M(i.rank===2&&i.shape[1]===4,()=>`Error in cropAndResize: boxes must be have size [${u},4] but had shape ${i.shape}.`),M(l.rank===1&&l.shape[0]===u,()=>`Error in cropAndResize: boxInd must be have size [${u}] but had shape ${i.shape}.`),M(s.length===2,()=>`Error in cropAndResize: cropSize must be of length 2, but got length ${s.length}.`),M(s[0]>=1&&s[1]>=1,()=>`cropSize must be atleast [1,1], but was ${s}`),M(r==="bilinear"||r==="nearest",()=>`method must be bilinear or nearest, but was ${r}`);let c={image:o,boxes:i,boxInd:l},d={method:r,extrapolationValue:a,cropSize:s};return z.runKernel(Oi,c,d)}var m_=W({cropAndResize_:f_});function g_(e){let t=$(e,"image","flipLeftRight","float32");M(t.rank===4,()=>`Error in flipLeftRight: image must be rank 4,but got rank ${t.rank}.`);let n={image:t};return z.runKernel(Wi,n,{})}var A_=W({flipLeftRight_:g_});function y_(e){let t=$(e,"image","grayscaleToRGB"),n=t.rank-1,s=t.shape[n];M(t.rank>=2,()=>`Error in grayscaleToRGB: images must be at least rank 2, but got rank ${t.rank}.`),M(s===1,()=>`Error in grayscaleToRGB: last dimension of a grayscale image should be size 1, but got size ${s}.`);let r=new Array(t.rank);return r.fill(1,0,n),r[n]=3,Ts(t,r)}var x_=W({grayscaleToRGB_:y_});function b_(e,t,n=0,s=.5){let r=$(e,"image","rotateWithOffset","float32");M(r.rank===4,()=>`Error in rotateWithOffset: image must be rank 4,but got rank ${r.rank}.`);let a={image:r},o={radians:t,fillValue:n,center:s};return z.runKernel(kl,a,o)}var v_=W({rotateWithOffset_:b_});function Vl(e,t,n,s,r,a){s==null&&(s=.5),r==null&&(r=Number.NEGATIVE_INFINITY),a==null&&(a=0);let o=e.shape[0];return n=Math.min(n,o),M(0<=s&&s<=1,()=>`iouThreshold must be in [0, 1], but was '${s}'`),M(e.rank===2,()=>`boxes must be a 2D tensor, but was of rank '${e.rank}'`),M(e.shape[1]===4,()=>`boxes must have 4 columns, but 2nd dimension was ${e.shape[1]}`),M(t.rank===1,()=>"scores must be a 1D tensor"),M(t.shape[0]===o,()=>`scores has incompatible shape with boxes. Expected ${o}, but was ${t.shape[0]}`),M(0<=a&&a<=1,()=>`softNmsSigma must be in [0, 1], but was '${a}'`),{maxOutputSize:n,iouThreshold:s,scoreThreshold:r,softNmsSigma:a}}function w_(e,t,n,s=.5,r=Number.NEGATIVE_INFINITY){let a=$(e,"boxes","nonMaxSuppression"),o=$(t,"scores","nonMaxSuppression"),i=Vl(a,o,n,s,r);n=i.maxOutputSize,s=i.iouThreshold,r=i.scoreThreshold;let l={maxOutputSize:n,iouThreshold:s,scoreThreshold:r};return z.runKernel(tl,{boxes:a,scores:o},l)}var k_=W({nonMaxSuppression_:w_});function I_(e,t,n){let s=S_(e,t,n),r=s<0?-(s+1):s;e.splice(r,0,t)}function S_(e,t,n){return T_(e,t,n||C_)}function C_(e,t){return e>t?1:e<t?-1:0}function T_(e,t,n){let s=0,r=e.length,a=0,o=!1;for(;s<r;){a=s+(r-s>>>1);let i=n(t,e[a]);i>0?s=a+1:(r=a,o=!i)}return o?s:-s-1}function Lb(e,t,n,s,r){return nA(e,t,n,s,r,0)}function Bb(e,t,n,s,r,a){return nA(e,t,n,s,r,0,!1,a,!0)}function Wb(e,t,n,s,r,a){return nA(e,t,n,s,r,a,!0)}function nA(e,t,n,s,r,a,o=!1,i=!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(Vb);let c=a>0?-.5/a:0,d=[],h=[];for(;d.length<n&&u.length>0;){let g=u.pop(),{score:A,boxIndex:y,suppressBeginIndex:x}=g;if(A<r)break;let b=!1;for(let v=d.length-1;v>=x;--v){let k=N_(e,y,d[v]);if(k>=s){b=!0;break}if(g.score=g.score*E_(s,c,k),g.score<=r)break}g.suppressBeginIndex=d.length,b||(g.score===A?(d.push(y),h.push(g.score)):g.score>r&&I_(u,g,Vb))}let p=d.length,f=n-p;i&&f>0&&(d.push(...new Array(f).fill(0)),h.push(...new Array(f).fill(0)));let m={selectedIndices:d};return o&&(m.selectedScores=h),l&&(m.validOutputs=p),m}function N_(e,t,n){let s=e.subarray(t*4,t*4+4),r=e.subarray(n*4,n*4+4),a=Math.min(s[0],s[2]),o=Math.min(s[1],s[3]),i=Math.max(s[0],s[2]),l=Math.max(s[1],s[3]),u=Math.min(r[0],r[2]),c=Math.min(r[1],r[3]),d=Math.max(r[0],r[2]),h=Math.max(r[1],r[3]),p=(i-a)*(l-o),f=(d-u)*(h-c);if(p<=0||f<=0)return 0;let m=Math.max(a,u),g=Math.max(o,c),A=Math.min(i,d),y=Math.min(l,h),x=Math.max(A-m,0)*Math.max(y-g,0);return x/(p+f-x)}function E_(e,t,n){let s=Math.exp(t*n*n);return n<=e?s:0}function Vb(e,t){return e.score-t.score||e.score===t.score&&t.boxIndex-e.boxIndex}async function R_(e,t,n,s=.5,r=Number.NEGATIVE_INFINITY){let a=$(e,"boxes","nonMaxSuppressionAsync"),o=$(t,"scores","nonMaxSuppressionAsync"),i=Vl(a,o,n,s,r);n=i.maxOutputSize,s=i.iouThreshold,r=i.scoreThreshold;let l=await Promise.all([a.data(),o.data()]),u=l[0],c=l[1],{selectedIndices:d}=Lb(u,c,n,s,r);return a!==e&&a.dispose(),o!==t&&o.dispose(),Mt(d,"int32")}var __=R_;function D_(e,t,n,s=.5,r=Number.NEGATIVE_INFINITY,a=0){let o=$(e,"boxes","nonMaxSuppression"),i=$(t,"scores","nonMaxSuppression"),l=Vl(o,i,n,s,r,a);n=l.maxOutputSize,s=l.iouThreshold,r=l.scoreThreshold,a=l.softNmsSigma;let u={boxes:o,scores:i},c={maxOutputSize:n,iouThreshold:s,scoreThreshold:r,softNmsSigma:a},d=z.runKernel(sl,u,c);return{selectedIndices:d[0],selectedScores:d[1]}}var $_=W({nonMaxSuppressionWithScore_:D_});async function F_(e,t,n,s=.5,r=Number.NEGATIVE_INFINITY,a=0){let o=$(e,"boxes","nonMaxSuppressionAsync"),i=$(t,"scores","nonMaxSuppressionAsync"),l=Vl(o,i,n,s,r,a);n=l.maxOutputSize,s=l.iouThreshold,r=l.scoreThreshold,a=l.softNmsSigma;let u=await Promise.all([o.data(),i.data()]),c=u[0],d=u[1],{selectedIndices:h,selectedScores:p}=Wb(c,d,n,s,r,a);return o!==e&&o.dispose(),i!==t&&i.dispose(),{selectedIndices:Mt(h,"int32"),selectedScores:Mt(p)}}var O_=F_;function P_(e,t,n,s=.5,r=Number.NEGATIVE_INFINITY,a=!1){let o=$(e,"boxes","nonMaxSuppression"),i=$(t,"scores","nonMaxSuppression"),l=Vl(o,i,n,s,r,null),u=l.maxOutputSize,c=l.iouThreshold,d=l.scoreThreshold,h={boxes:o,scores:i},p={maxOutputSize:u,iouThreshold:c,scoreThreshold:d,padToMaxOutputSize:a},f=z.runKernel(nl,h,p);return{selectedIndices:f[0],validOutputs:f[1]}}var M_=W({nonMaxSuppressionPadded_:P_});async function z_(e,t,n,s=.5,r=Number.NEGATIVE_INFINITY,a=!1){let o=$(e,"boxes","nonMaxSuppressionAsync"),i=$(t,"scores","nonMaxSuppressionAsync"),l=Vl(o,i,n,s,r,null),u=l.maxOutputSize,c=l.iouThreshold,d=l.scoreThreshold,[h,p]=await Promise.all([o.data(),i.data()]),{selectedIndices:f,validOutputs:m}=Bb(h,p,u,c,d,a);return o!==e&&o.dispose(),i!==t&&i.dispose(),{selectedIndices:Mt(f,"int32"),validOutputs:Ie(m,"int32")}}var L_=z_;function B_(e,t,n=!1,s=!1){let r=$(e,"images","resizeBilinear");M(r.rank===3||r.rank===4,()=>`Error in resizeBilinear: x must be rank 3 or 4, but got rank ${r.rank}.`),M(t.length===2,()=>`Error in resizeBilinear: new shape must 2D, but got shape ${t}.`),M(s===!1||n===!1,()=>"Error in resizeBilinear: If halfPixelCenters is true, alignCorners must be false.");let a=r,o=!1;r.rank===3&&(o=!0,a=U(r,[1,r.shape[0],r.shape[1],r.shape[2]]));let[]=t,i={images:a},l={alignCorners:n,halfPixelCenters:s,size:t},u=z.runKernel(lo,i,l);return o?U(u,[u.shape[1],u.shape[2],u.shape[3]]):u}var W_=W({resizeBilinear_:B_});function V_(e,t,n=!1,s=!1){let r=$(e,"images","resizeNearestNeighbor");M(r.rank===3||r.rank===4,()=>`Error in resizeNearestNeighbor: x must be rank 3 or 4, but got rank ${r.rank}.`),M(t.length===2,()=>`Error in resizeNearestNeighbor: new shape must 2D, but got shape ${t}.`),M(r.dtype==="float32"||r.dtype==="int32",()=>"`images` must have `int32` or `float32` as dtype"),M(s===!1||n===!1,()=>"Error in resizeNearestNeighbor: If halfPixelCenters is true, alignCorners must be false.");let a=r,o=!1;r.rank===3&&(o=!0,a=U(r,[1,r.shape[0],r.shape[1],r.shape[2]]));let[]=t,i={images:a},l={alignCorners:n,halfPixelCenters:s,size:t},u=z.runKernel(ju,i,l);return o?U(u,[u.shape[1],u.shape[2],u.shape[3]]):u}var U_=W({resizeNearestNeighbor_:V_});function H_(e,t="binary",n=!1,s=.5){let r=$(e,"image","threshold"),a=.2989,o=.587,i=.114,l=r.shape[0]*r.shape[1],u=L(Mt([s]),255),c,d,h,p;if(M(r.rank===3,()=>`Error in threshold: image must be rank 3,but got rank ${r.rank}.`),M(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]}.`),M(r.dtype==="int32"||r.dtype==="float32",()=>`Error in dtype: image dtype must be int32 or float32,but got dtype ${r.dtype}.`),M(t==="otsu"||t==="binary",()=>`Method must be binary or otsu, but was ${t}`),r.shape[2]===3){[c,d,h]=an(r,[1,1,1],-1);let g=L(c,a),A=L(d,o),y=L(h,i);p=ae(ae(g,A),y)}else p=e;if(t==="otsu"){let g=Ig(ce(Vg(p),"int32"),dn([]),256);u=G_(g,l)}let f=n?Po(p,u):jn(p,u);return ce(L(f,255),"int32")}function G_(e,t){let n=Mt([-1]),s=Mt([0]),r=Mt([0]),a,o,i,l,u,c;for(let d=0;d<e.size-1;d++){a=Re(e,0,d+1),o=Re(e,d+1),u=de(ve(a),t),c=de(ve(o),t);let h=ve(L(a,Wl(0,a.size)));i=de(h,ve(a));let p=Pl(o.shape,a.size),f=ae(Wl(0,o.size),p),m=L(o,f);l=de(ve(m),ve(o));let g=ge(i,l),A=ge(i,l),y=L(u,c);r=L(L(y,g),A);let x=jn(r,s);s=bn(x,r,s),n=bn(x,Mt([d]),n)}return n}var j_=W({threshold_:H_});function q_(e,t,n="nearest",s="constant",r=0,a){let o=$(e,"image","transform","float32"),i=$(t,"transforms","transform","float32");M(o.rank===4,()=>`Error in transform: image must be rank 4,but got rank ${o.rank}.`),M(i.rank===2&&(i.shape[0]===o.shape[0]||i.shape[0]===1)&&i.shape[1]===8,()=>"Error in transform: Input transform should be batch x 8 or 1 x 8"),M(a==null||a.length===2,()=>`Error in transform: outputShape must be [height, width] or null, but got ${a}.`);let l={image:o,transforms:i},u={interpolation:n,fillMode:s,fillValue:r,outputShape:a};return z.runKernel(bl,l,u)}var X_=W({transform_:q_});function K_(e,t,n){M(t%1==0,()=>`bandPart(): numLower must be an integer, got ${t}.`),M(n%1==0,()=>`bandPart(): numUpper must be an integer, got ${n}.`);let s=$(e,"a","bandPart");M(s.rank>=2,()=>`bandPart(): Rank must be at least 2, got ${s.rank}.`);let r=s.shape,[a,o]=s.shape.slice(-2);if(!(t<=a))throw new Error(`bandPart(): numLower (${t}) must not be greater than the number of rows (${a}).`);if(!(n<=o))throw new Error(`bandPart(): numUpper (${n}) must not be greater than the number of columns (${o}).`);t<0&&(t=a),n<0&&(n=o);let i=U(Wl(0,a,1,"int32"),[-1,1]),l=Wl(0,o,1,"int32"),u=ge(i,l),c=Ps(Po(u,Ie(+t,"int32")),Oo(u,Ie(-n,"int32"))),d=Pt([a,o],s.dtype);return U(Dn(ms(U(s,[-1,a,o])).map(h=>bn(c,h,d))),r)}var Z_=W({bandPart_:K_});function Y_(e){let t;if(Array.isArray(e)){t=!1,M(e!=null&&e.length>0,()=>"Gram-Schmidt process: input must not be null, undefined, or empty");let r=e[0].shape[0];for(let a=1;a<e.length;++a)M(e[a].shape[0]===r,()=>`Gram-Schmidt: Non-unique lengths found in the input vectors: (${e[a].shape[0]} vs. ${r})`)}else t=!0,e=an(e,e.shape[0],0).map(r=>lt(r,[0]));M(e.length<=e[0].shape[0],()=>`Gram-Schmidt: Number of vectors (${e.length}) exceeds number of dimensions (${e[0].shape[0]}).`);let n=[],s=e;for(let r=0;r<e.length;++r)n.push(z.tidy(()=>{let a=s[r];if(r>0)for(let o=0;o<r;++o){let i=L(ve(L(n[o],a)),n[o]);a=ge(a,i)}return de(a,Jg(a,"euclidean"))}));return t?Dn(n,0):n}var J_=W({gramSchmidt_:Y_});function Q_(e,t=!1){if(M(e.rank>=2,()=>`qr() requires input tensor to have a rank >= 2, but got rank ${e.rank}`),e.rank===2)return Ub(e,t);{let n=e.shape.slice(0,e.shape.length-2).reduce((l,u)=>l*u),s=ms(U(e,[n,e.shape[e.shape.length-2],e.shape[e.shape.length-1]]),0),r=[],a=[];s.forEach(l=>{let[u,c]=Ub(l,t);r.push(u),a.push(c)});let o=U(Dn(r,0),e.shape),i=U(Dn(a,0),e.shape);return[o,i]}}function Ub(e,t=!1){return z.tidy(()=>{M(e.shape.length===2,()=>`qr2d() requires a 2D Tensor, but got a ${e.shape.length}D Tensor.`);let n=e.shape[0],s=e.shape[1],r=_g(n),a=Os(e),o=Ms([[1]],[1,1]),i=Os(o),l=n>=s?s:n;for(let u=0;u<l;++u){let c=a,d=i,h=r;[i,a,r]=z.tidy(()=>{let p=Re(a,[u,u],[n-u,1]),f=Jg(p),m=Re(a,[u,u],[1,1]),g=bn(jn(m,0),Ms([[-1]]),Ms([[1]])),A=ge(m,L(g,f)),y=de(p,A);y.shape[0]===1?i=Os(o):i=ft([o,Re(y,[1,0],[y.shape[0]-1,y.shape[1]])],0);let x=Tt(de(Ve(g,A),f)),b=Re(a,[u,0],[n-u,s]),v=L(x,i),k=Xe(i);if(u===0)a=ge(b,Ve(v,Ve(k,b)));else{let _=ge(b,Ve(v,Ve(k,b)));a=ft([Re(a,[0,0],[u,s]),_],0)}let S=Xe(v),C=Re(r,[0,u],[n,r.shape[1]-u]);if(u===0)r=ge(C,Ve(Ve(C,i),S));else{let _=ge(C,Ve(Ve(C,i),S));r=ft([Re(r,[0,0],[n,u]),_],1)}return[i,a,r]}),K([c,d,h])}return!t&&n>s&&(r=Re(r,[0,0],[n,s]),a=Re(a,[0,0],[s,s])),[r,a]})}var eD=W({qr_:Q_}),vn;(function(e){e[e.NONE=0]="NONE",e[e.MEAN=1]="MEAN",e[e.SUM=2]="SUM",e[e.SUM_BY_NONZERO_WEIGHTS=3]="SUM_BY_NONZERO_WEIGHTS"})(vn||(vn={}));function tD(e,t,n=vn.SUM_BY_NONZERO_WEIGHTS){let s=$(e,"losses","computeWeightedLoss"),r=null;t!=null&&(r=$(t,"weights","computeWeightedLoss"));let a=r==null?s:L(s,r);if(n===vn.NONE)return a;if(n===vn.SUM)return ve(a);if(n===vn.MEAN){if(r==null)return _t(a);{let o=s.size/r.size,i=de(ve(a),ve(r));return o>1?de(i,Ie(o)):i}}if(n===vn.SUM_BY_NONZERO_WEIGHTS){if(r==null)return de(ve(a),Ie(s.size));{let o=L(r,qn(s.shape)),i=ce(ve(Ll(o,Ie(0))),"float32");return de(ve(a),i)}}throw Error(`Unknown reduction: ${n}`)}var Ir=W({computeWeightedLoss_:tD});function nD(e,t,n,s=vn.SUM_BY_NONZERO_WEIGHTS){let r=$(e,"labels","absoluteDifference"),a=$(t,"predictions","absoluteDifference"),o=null;n!=null&&(o=$(n,"weights","absoluteDifference")),An(r.shape,a.shape,"Error in absoluteDifference: ");let i=Ht(ge(r,a));return Ir(i,o,s)}var sD=W({absoluteDifference_:nD});function rD(e,t,n,s,r=vn.SUM_BY_NONZERO_WEIGHTS){let a=$(e,"labels","cosineDistance"),o=$(t,"predictions","cosineDistance"),i=null;s!=null&&(i=$(s,"weights","cosineDistance")),An(a.shape,o.shape,"Error in cosineDistance: ");let l=Ie(1),u=ge(l,ve(L(a,o),n,!0));return Ir(u,i,r)}var aD=W({cosineDistance_:rD});function oD(e,t,n,s=vn.SUM_BY_NONZERO_WEIGHTS){let r=$(e,"labels","hingeLoss"),a=$(t,"predictions","hingeLoss"),o=null;n!=null&&(o=$(n,"weights","hingeLoss")),An(r.shape,a.shape,"Error in hingeLoss: ");let i=Ie(1);r=ge(L(Ie(2),r),i);let l=sr(ge(i,L(r,a)));return Ir(l,o,s)}var iD=W({hingeLoss_:oD});function lD(e,t,n,s=1,r=vn.SUM_BY_NONZERO_WEIGHTS){let a=$(e,"labels","huberLoss"),o=$(t,"predictions","huberLoss"),i=null;n!=null&&(i=$(n,"weights","huberLoss")),An(a.shape,o.shape,"Error in huberLoss: ");let l=Ie(s),u=Ht(ge(o,a)),c=pc(u,l),d=ge(u,c),h=ae(L(Ie(.5),ct(c)),L(l,d));return Ir(h,i,r)}var uD=W({huberLoss_:lD});function cD(e,t,n,s=1e-7,r=vn.SUM_BY_NONZERO_WEIGHTS){let a=$(e,"labels","logLoss"),o=$(t,"predictions","logLoss"),i=null;n!=null&&(i=$(n,"weights","logLoss")),An(a.shape,o.shape,"Error in logLoss: ");let l=Ie(1),u=Ie(s),c=Tt(L(a,ds(ae(o,u)))),d=L(ge(l,a),ds(ae(ge(l,o),u))),h=ge(c,d);return Ir(h,i,r)}var dD=W({logLoss_:cD});function hD(e,t,n,s=vn.SUM_BY_NONZERO_WEIGHTS){let r=$(e,"labels","meanSquaredError"),a=$(t,"predictions","meanSquaredError"),o=null;n!=null&&(o=$(n,"weights","meanSquaredError")),An(r.shape,a.shape,"Error in meanSquaredError: ");let i=Kg(r,a);return Ir(i,o,s)}var pD=W({meanSquaredError_:hD});function fD(e,t){let n=$(e,"labels","sigmoidCrossEntropyWithLogits"),s=$(t,"logits","sigmoidCrossEntropyWithLogits");An(n.shape,s.shape,"Error in sigmoidCrossEntropyWithLogits: ");let r=sr(s),a=L(s,n),o=Zh(cs(Tt(Ht(s))));return ae(ge(r,a),o)}function mD(e,t,n,s=0,r=vn.SUM_BY_NONZERO_WEIGHTS){let a=$(e,"multiClassLabels","sigmoidCrossEntropy"),o=$(t,"logits","sigmoidCrossEntropy"),i=null;if(n!=null&&(i=$(n,"weights","sigmoidCrossEntropy")),An(a.shape,o.shape,"Error in sigmoidCrossEntropy: "),s>0){let u=Ie(s),c=Ie(1),d=Ie(.5);a=ae(L(a,ge(c,u)),L(d,u))}let l=fD(a,o);return Ir(l,i,r)}var gD=W({sigmoidCrossEntropy_:mD});function AD(e,t,n=-1){if(n===-1&&(n=t.rank-1),n!==t.rank-1)throw Error(`Softmax cross entropy along a non-last dimension is not yet supported. Labels / logits was rank ${t.rank} and dim was ${n}`);return nr((r,a,o)=>{let l=fb(a,[n],!0),u=ge(ce(a,"float32"),l);o([r,u]);let c=Tt(L(u,r));return{value:ve(c,[n]),gradFunc:(p,f)=>{let[m,g]=f,A=Mo(p.shape,[n]);return[L(U(p,A),ge(ce(m,"float32"),cs(g))),L(U(p,A),ge(cs(g),ce(m,"float32")))]}}})(e,t)}function yD(e,t,n,s=0,r=vn.SUM_BY_NONZERO_WEIGHTS){let a=$(e,"onehotLabels","softmaxCrossEntropy"),o=$(t,"logits","softmaxCrossEntropy"),i=null;if(n!=null&&(i=$(n,"weights","softmaxCrossEntropy")),An(a.shape,o.shape,"Error in softmaxCrossEntropy: "),s>0){let u=Ie(s),c=Ie(1),d=Ie(a.shape[1]);a=ae(L(a,ge(c,u)),de(u,d))}let l=AD(a,o);return Ir(l,i,r)}var xD=W({softmaxCrossEntropy_:yD});function bD(e,t,n,s){let r=$(e,"indices","sparseFillEmptyRows"),a=$(t,"values","sparseFillEmptyRows"),o=$(n,"denseShape","sparseFillEmptyRows"),i=$(s,"defaultValue","sparseFillEmptyRows",a.dtype);if(r.rank!==2)throw new Error(`Indices should be Tensor2D but received shape
${r.shape}`);if(a.rank!==1)throw new Error(`Values should be Tensor1D but received shape ${a.shape}`);if(o.rank!==1)throw new Error(`Dense shape should be Tensor1D but received shape ${o.shape}`);if(i.rank!==0)throw new Error(`Default value should be a scalar but received shape ${i.shape}`);let l={indices:r,values:a,denseShape:o,defaultValue:i},u=z.runKernel(vh,l);return{outputIndices:u[0],outputValues:u[1],emptyRowIndicator:u[2],reverseIndexMap:u[3]}}var vD=W({sparseFillEmptyRows_:bD});function wD(e,t,n){let s=$(e,"inputIndices","sparseReshape"),r=$(t,"inputShape","sparseReshape"),a=$(n,"newShape","sparseReshape");if(s.rank!==2)throw new Error(`Input indices should be Tensor2D but received shape
${s.shape}`);if(r.rank!==1)throw new Error(`Input shape should be Tensor1D but received shape ${r.shape}`);if(a.rank!==1)throw new Error(`New shape should be Tensor1D but received shape ${a.shape}`);let o={inputIndices:s,inputShape:r,newShape:a},i=z.runKernel(wh,o);return{outputIndices:i[0],outputShape:i[1]}}var kD=W({sparseReshape_:wD});function ID(e,t,n){let s=$(e,"data","sparseSegmentMean"),r=$(t,"indices","sparseSegmentMean"),a=$(n,"segmentIds","sparseSegmentMean");if(s.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(a.rank!==1)throw new Error(`Segment ids should be Tensor1D but received shape
${a.shape}`);let o={data:s,indices:r,segmentIds:a};return z.runKernel(kh,o)}var SD=W({sparseSegmentMean_:ID});function CD(e,t,n){let s=$(e,"data","sparseSegmentSum"),r=$(t,"indices","sparseSegmentSum"),a=$(n,"segmentIds","sparseSegmentSum");if(s.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(a.rank!==1)throw new Error(`Segment ids should be Tensor1D but received shape
${a.shape}`);let o={data:s,indices:r,segmentIds:a};return z.runKernel(Ih,o)}var TD=W({sparseSegmentSum_:CD});function ND(e,t,n,s,r,a,o,i){let l=$(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: ${l.shape}`);let u=$(t,"dataSplits","stringNGrams");if(u.dtype!=="int32")throw new Error("Data splits must be of datatype int32");let c={separator:n,nGramWidths:s,leftPad:r,rightPad:a,padWidth:o,preserveShortSequences:i},d={data:l,dataSplits:u},h=z.runKernel(Ch,d,c);return{nGrams:h[0],nGramsSplits:h[1]}}var ED=W({stringNGrams_:ND});function RD(e,t,n=!0){let s=$(e,"input","stringSplit","string"),r=$(t,"delimiter","stringSplit","string");if(s.rank!==1)throw new Error(`Input should be Tensor1D but received shape ${s.shape}`);if(r.rank!==0)throw new Error(`Delimiter should be a scalar but received shape ${r.shape}`);let a={skipEmpty:n},o={input:s,delimiter:r},i=z.runKernel(Th,o,a);return{indices:i[0],values:i[1],shape:i[2]}}var _D=W({stringSplit_:RD});function DD(e,t){let n=$(e,"input","stringToHashBucketFast","string"),s={numBuckets:t};if(t<=0)throw new Error("Number of buckets must be at least 1");let r={input:n};return z.runKernel(Nh,r,s)}var $D=W({stringToHashBucketFast_:DD}),FD={fft:ip,ifft:gc,rfft:lp,irfft:Xg},OD={hammingWindow:u_,hannWindow:Mb,frame:zb,stft:p_},_e={flipLeftRight:A_,grayscaleToRGB:x_,resizeNearestNeighbor:U_,resizeBilinear:W_,rotateWithOffset:v_,cropAndResize:m_,nonMaxSuppression:k_,nonMaxSuppressionAsync:__,nonMaxSuppressionWithScore:$_,nonMaxSuppressionWithScoreAsync:O_,nonMaxSuppressionPadded:M_,nonMaxSuppressionPaddedAsync:L_,threshold:j_,transform:X_},Hb={bandPart:Z_,gramSchmidt:J_,qr:eD},PD={absoluteDifference:sD,computeWeightedLoss:Ir,cosineDistance:aD,hingeLoss:iD,huberLoss:uD,logLoss:dD,meanSquaredError:pD,sigmoidCrossEntropy:gD,softmaxCrossEntropy:xD},yc={sparseFillEmptyRows:vD,sparseReshape:kD,sparseSegmentMean:SD,sparseSegmentSum:TD},fp={stringNGrams:ED,stringSplit:_D,stringToHashBucketFast:$D},Sr=class extends Tx{minimize(e,t=!1,n){let{value:s,grads:r}=this.computeGradients(e,n);if(n!=null){let a=n.map(o=>({name:o.name,tensor:r[o.name]}));this.applyGradients(a)}else this.applyGradients(r);return K(r),t?s:(s.dispose(),null)}get iterations(){return this.iterations_==null&&(this.iterations_=0),this.iterations_}incrementIterations(){this.iterations_=this.iterations+1}computeGradients(e,t){return cb(e,t)}dispose(){this.iterations_!=null&&K(this.iterations_)}async saveIterations(){return this.iterations_==null&&(this.iterations_=0),{name:"iter",tensor:Ie(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 ${this.getClassName()}`)}async extractIterations(e){return this.iterations_=(await e[0].tensor.data())[0],e.slice(1)}};Object.defineProperty(Sr,Symbol.hasInstance,{value:e=>e.minimize!=null&&e.computeGradients!=null&&e.applyGradients!=null});var mp=class extends Sr{constructor(e,t,n=null){super();this.learningRate=e,this.rho=t,this.epsilon=n,this.accumulatedGrads=[],this.accumulatedUpdates=[],n==null&&(this.epsilon=z.backend.epsilon())}applyGradients(e){(Array.isArray(e)?e.map(n=>n.name):Object.keys(e)).forEach((n,s)=>{let r=z.registeredVariables[n],a=!1;this.accumulatedGrads[s]==null&&(this.accumulatedGrads[s]={originalName:`${n}/accum_grad`,variable:H(()=>Ke(r).variable(a))}),this.accumulatedUpdates[s]==null&&(this.accumulatedUpdates[s]={originalName:`${n}/accum_var`,variable:H(()=>Ke(r).variable(a))});let o=Array.isArray(e)?e[s].tensor:e[n];if(o==null)return;let i=this.accumulatedGrads[s].variable,l=this.accumulatedUpdates[s].variable;H(()=>{let u=ae(L(i,this.rho),L(ct(o),1-this.rho)),c=L(de(hn(ae(l,this.epsilon)),hn(ae(i,this.epsilon))),o),d=ae(L(l,this.rho),L(ct(c),1-this.rho));i.assign(u),l.assign(d);let h=ae(L(c,-this.learningRate),r);r.assign(h)})}),this.incrementIterations()}dispose(){this.accumulatedUpdates!=null&&(K(this.accumulatedGrads.map(e=>e.variable)),K(this.accumulatedUpdates.map(e=>e.variable)))}async getWeights(){let e=[...this.accumulatedGrads,...this.accumulatedUpdates];return[await this.saveIterations()].concat(e.map(t=>({name:t.originalName,tensor:t.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=e.length/2,n=!1;this.accumulatedGrads=e.slice(0,t).map(s=>({originalName:s.name,variable:s.tensor.variable(n)})),this.accumulatedUpdates=e.slice(t,t*2).map(s=>({originalName:s.name,variable:s.tensor.variable(n)}))}getConfig(){return{learningRate:this.learningRate,rho:this.rho,epsilon:this.epsilon}}static fromConfig(e,t){return new e(t.learningRate,t.rho,t.epsilon)}};mp.className="Adadelta";Zr(mp);var gp=class extends Sr{constructor(e,t=.1){super();this.learningRate=e,this.initialAccumulatorValue=t,this.accumulatedGrads=[]}applyGradients(e){(Array.isArray(e)?e.map(n=>n.name):Object.keys(e)).forEach((n,s)=>{let r=z.registeredVariables[n];if(this.accumulatedGrads[s]==null){let i=!1;this.accumulatedGrads[s]={originalName:`${n}/accumulator`,variable:H(()=>Pl(r.shape,this.initialAccumulatorValue).variable(i))}}let a=Array.isArray(e)?e[s].tensor:e[n];if(a==null)return;let o=this.accumulatedGrads[s].variable;H(()=>{let i=ae(o,ct(a));o.assign(i);let l=ae(L(de(a,hn(ae(i,z.backend.epsilon()))),-this.learningRate),r);r.assign(l)})}),this.incrementIterations()}dispose(){this.accumulatedGrads!=null&&K(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(n=>({originalName:n.name,variable:n.tensor.variable(t)}))}getConfig(){return{learningRate:this.learningRate,initialAccumulatorValue:this.initialAccumulatorValue}}static fromConfig(e,t){return new e(t.learningRate,t.initialAccumulatorValue)}};gp.className="Adagrad";Zr(gp);var Ap=class extends Sr{constructor(e,t,n,s=null){super();this.learningRate=e,this.beta1=t,this.beta2=n,this.epsilon=s,this.accumulatedFirstMoment=[],this.accumulatedSecondMoment=[],H(()=>{this.accBeta1=Ie(t).variable(),this.accBeta2=Ie(n).variable()}),s==null&&(this.epsilon=z.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(n=>n.name):Object.keys(e);H(()=>{let n=ge(1,this.accBeta1),s=ge(1,this.accBeta2);t.forEach((r,a)=>{let o=z.registeredVariables[r],i=!1;this.accumulatedFirstMoment[a]==null&&(this.accumulatedFirstMoment[a]={originalName:`${r}/m`,variable:H(()=>Ke(o).variable(i))}),this.accumulatedSecondMoment[a]==null&&(this.accumulatedSecondMoment[a]={originalName:`${r}/v`,variable:H(()=>Ke(o).variable(i))});let l=Array.isArray(e)?e[a].tensor:e[r];if(l==null)return;let u=this.accumulatedFirstMoment[a].variable,c=this.accumulatedSecondMoment[a].variable,d=ae(L(u,this.beta1),L(l,1-this.beta1)),h=ae(L(c,this.beta2),L(ct(l),1-this.beta2)),p=de(d,n),f=de(h,s);u.assign(d),c.assign(h);let m=ae(L(de(p,ae(hn(f),this.epsilon)),-this.learningRate),o);o.assign(m)}),this.accBeta1.assign(L(this.accBeta1,this.beta1)),this.accBeta2.assign(L(this.accBeta2,this.beta2))}),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.accBeta2.dispose(),this.accumulatedFirstMoment!=null&&K(this.accumulatedFirstMoment.map(e=>e.variable)),this.accumulatedSecondMoment!=null&&K(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),H(()=>{this.accBeta1.assign(ea(this.beta1,this.iterations_+1)),this.accBeta2.assign(ea(this.beta2,this.iterations_+1))});let t=e.length/2,n=!1;this.accumulatedFirstMoment=e.slice(0,t).map(s=>({originalName:s.name,variable:s.tensor.variable(n)})),this.accumulatedSecondMoment=e.slice(t,t*2).map(s=>({originalName:s.name,variable:s.tensor.variable(n)}))}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)}};Ap.className="Adam";Zr(Ap);var yp=class extends Sr{constructor(e,t,n,s=null,r=0){super();this.learningRate=e,this.beta1=t,this.beta2=n,this.epsilon=s,this.decay=r,this.accumulatedFirstMoment=[],this.accumulatedWeightedInfNorm=[],H(()=>{this.iteration=Ie(0).variable(),this.accBeta1=Ie(t).variable()}),s==null&&(this.epsilon=z.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(n=>n.name):Object.keys(e);H(()=>{let n=ge(1,this.accBeta1),s=de(-this.learningRate,ae(L(this.iteration,this.decay),1));t.forEach((r,a)=>{let o=z.registeredVariables[r],i=!1;this.accumulatedFirstMoment[a]==null&&(this.accumulatedFirstMoment[a]={originalName:`${r}/m`,variable:Ke(o).variable(i)}),this.accumulatedWeightedInfNorm[a]==null&&(this.accumulatedWeightedInfNorm[a]={originalName:`${r}/v`,variable:Ke(o).variable(i)});let l=Array.isArray(e)?e[a].tensor:e[r];if(l==null)return;let u=this.accumulatedFirstMoment[a].variable,c=this.accumulatedWeightedInfNorm[a].variable,d=ae(L(u,this.beta1),L(l,1-this.beta1)),h=L(c,this.beta2),p=Ht(l),f=kr(h,p);u.assign(d),c.assign(f);let m=ae(L(de(s,n),de(d,ae(f,this.epsilon))),o);o.assign(m)}),this.iteration.assign(ae(this.iteration,1)),this.accBeta1.assign(L(this.accBeta1,this.beta1))}),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.iteration.dispose(),this.accumulatedFirstMoment!=null&&K(this.accumulatedFirstMoment.map(e=>e.variable)),this.accumulatedWeightedInfNorm!=null&&K(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)}};yp.className="Adamax";Zr(yp);var xc=class extends Sr{constructor(e){super();this.learningRate=e,this.setLearningRate(e)}applyGradients(e){(Array.isArray(e)?e.map(n=>n.name):Object.keys(e)).forEach((n,s)=>{let r=Array.isArray(e)?e[s].tensor:e[n];if(r==null)return;let a=z.registeredVariables[n];H(()=>{let o=ae(L(this.c,r),a);a.assign(o)})}),this.incrementIterations()}setLearningRate(e){this.learningRate=e,this.c!=null&&this.c.dispose(),this.c=Jt(Ie(-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)}};xc.className="SGD";Zr(xc);var xp=class extends xc{constructor(e,t,n=!1){super(e);this.learningRate=e,this.momentum=t,this.useNesterov=n,this.accumulations=[],this.m=Ie(this.momentum)}applyGradients(e){(Array.isArray(e)?e.map(n=>n.name):Object.keys(e)).forEach((n,s)=>{let r=z.registeredVariables[n];if(this.accumulations[s]==null){let i=!1;this.accumulations[s]={originalName:`${n}/momentum`,variable:H(()=>Ke(r).variable(i))}}let a=this.accumulations[s].variable,o=Array.isArray(e)?e[s].tensor:e[n];o!=null&&H(()=>{let i,l=ae(L(this.m,a),o);this.useNesterov?i=ae(L(this.c,ae(o,L(l,this.m))),r):i=ae(L(this.c,l),r),a.assign(l),r.assign(i)})}),this.incrementIterations()}dispose(){this.m.dispose(),this.accumulations!=null&&K(this.accumulations.map(e=>e.variable))}setMomentum(e){this.momentum=e}async getWeights(){return[await this.saveIterations()].concat(this.accumulations.map(e=>({name:e.originalName,tensor:e.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=!1;this.accumulations=e.map(n=>({originalName:n.name,variable:n.tensor.variable(t)}))}getConfig(){return{learningRate:this.learningRate,momentum:this.momentum,useNesterov:this.useNesterov}}static fromConfig(e,t){return new e(t.learningRate,t.momentum,t.useNesterov)}};xp.className="Momentum";Zr(xp);var bp=class extends Sr{constructor(e,t=.9,n=0,s=null,r=!1){super();if(this.learningRate=e,this.decay=t,this.momentum=n,this.epsilon=s,this.accumulatedMeanSquares=[],this.accumulatedMoments=[],this.accumulatedMeanGrads=[],this.centered=r,s==null&&(this.epsilon=z.backend.epsilon()),e==null)throw new Error("learningRate for RMSPropOptimizer must be defined.")}applyGradients(e){(Array.isArray(e)?e.map(n=>n.name):Object.keys(e)).forEach((n,s)=>{let r=z.registeredVariables[n],a=!1;this.accumulatedMeanSquares[s]==null&&(this.accumulatedMeanSquares[s]={originalName:`${n}/rms`,variable:H(()=>Ke(r).variable(a))}),this.accumulatedMoments[s]==null&&(this.accumulatedMoments[s]={originalName:`${n}/momentum`,variable:H(()=>Ke(r).variable(a))}),this.accumulatedMeanGrads[s]==null&&this.centered&&(this.accumulatedMeanGrads[s]={originalName:`${n}/mg`,variable:H(()=>Ke(r).variable(a))});let o=Array.isArray(e)?e[s].tensor:e[n];if(o==null)return;let i=this.accumulatedMeanSquares[s].variable,l=this.accumulatedMoments[s].variable;H(()=>{let u=ae(L(i,this.decay),L(ct(o),1-this.decay));if(this.centered){let c=this.accumulatedMeanGrads[s].variable,d=ae(L(c,this.decay),L(o,1-this.decay)),h=de(L(o,this.learningRate),hn(ge(u,ae(ct(d),this.epsilon)))),p=ae(L(l,this.momentum),h);i.assign(u),c.assign(d),l.assign(p);let f=ge(r,p);r.assign(f)}else{let c=ae(L(i,this.decay),L(ct(o),1-this.decay)),d=ae(L(l,this.momentum),de(L(o,this.learningRate),hn(ae(c,this.epsilon))));i.assign(c),l.assign(d);let h=ge(r,d);r.assign(h)}})}),this.incrementIterations()}dispose(){this.accumulatedMeanSquares!=null&&K(this.accumulatedMeanSquares.map(e=>e.variable)),this.accumulatedMeanGrads!=null&&this.centered&&K(this.accumulatedMeanGrads.map(e=>e.variable)),this.accumulatedMoments!=null&&K(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,n=!1;this.accumulatedMeanSquares=e.slice(0,t).map(s=>({originalName:s.name,variable:s.tensor.variable(n)})),this.accumulatedMoments=e.slice(t,t*2).map(s=>({originalName:s.name,variable:s.tensor.variable(n)})),this.centered&&(this.accumulatedMeanGrads=e.slice(t*2,t*3).map(s=>({originalName:s.name,variable:s.tensor.variable(n)})))}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)}};bp.className="RMSProp";Zr(bp);var zo=class{static sgd(e){return new xc(e)}static momentum(e,t,n=!1){return new xp(e,t,n)}static rmsprop(e,t=.9,n=0,s=null,r=!1){return new bp(e,t,n,s,r)}static adam(e=.001,t=.9,n=.999,s=null){return new Ap(e,t,n,s)}static adadelta(e=.001,t=.95,n=null){return new mp(e,t,n)}static adamax(e=.002,t=.9,n=.999,s=null,r=0){return new yp(e,t,n,s,r)}static adagrad(e,t=.1){return new gp(e,t)}},Lo={sgd:zo.sgd,momentum:zo.momentum,adadelta:zo.adadelta,adagrad:zo.adagrad,rmsprop:zo.rmsprop,adamax:zo.adamax,adam:zo.adam},MD=(()=>typeof requestAnimationFrame!="undefined"?requestAnimationFrame:typeof setImmediate!="undefined"?setImmediate:e=>e())();function vp(){return new Promise(e=>MD(()=>e()))}var D={};Pe(D,{ERF_A1:()=>XD,ERF_A2:()=>KD,ERF_A3:()=>ZD,ERF_A4:()=>YD,ERF_A5:()=>JD,ERF_P:()=>qD,PARALLELIZE_THRESHOLD:()=>sA,SELU_SCALE:()=>jb,SELU_SCALEALPHA:()=>Gb,applyActivation:()=>hp,assertAndGetBroadcastShape:()=>At,assertAxesAreInnerMostDims:()=>KN,assertParamsConsistent:()=>zD,assignToTypedArray:()=>r$,axesAreInnerMostDims:()=>Fg,calculateShapes:()=>mx,checkEinsumDimSizes:()=>c$,combineLocations:()=>db,complexWithEvenIndex:()=>t$,complexWithOddIndex:()=>n$,computeConv2DInfo:()=>lc,computeConv3DInfo:()=>Vx,computeDefaultPad:()=>vg,computeDilation2DInfo:()=>fT,computeOptimalWindowSize:()=>BD,computeOutAndReduceShapes:()=>hb,computeOutShape:()=>LD,computePool2DInfo:()=>Wx,computePool3DInfo:()=>mT,convertConv2DDataFormat:()=>Ux,decodeEinsumEquation:()=>l$,eitherStridesOrDilationsAreOne:()=>tr,expandShapeToKeepDim:()=>Mo,exponent:()=>o$,exponents:()=>a$,fromStringArrayToUint8:()=>x$,fromUint8ToStringArray:()=>y$,getAxesPermutation:()=>pb,getBroadcastDims:()=>oN,getComplexWithIndex:()=>s$,getEinsumComputePath:()=>d$,getEinsumPermutation:()=>u$,getFusedBiasGradient:()=>dp,getFusedDyActivation:()=>cp,getImageCenter:()=>WD,getInnerMostAxes:()=>ZN,getPermuted:()=>UD,getReductionAxes:()=>Gt,getReshaped:()=>VD,getReshapedPermuted:()=>HD,getSliceBeginCoords:()=>GD,getSliceSize:()=>jD,getUndoAxesPermutation:()=>Og,isIdentityPermutation:()=>h$,log:()=>zS,mergeRealAndImagArrays:()=>QD,prepareAndValidate:()=>fx,prepareSplitSize:()=>f$,segment_util:()=>Kb,shouldFuse:()=>pp,slice_util:()=>xn,splitRealAndImagArrays:()=>e$,tupleValuesAreOne:()=>Yr,upcastType:()=>Cs,validateInput:()=>pg,validateUpdateShape:()=>hg,warn:()=>Ys});function zD(e,t){let n=e[0].length;e.forEach((r,a)=>{M(r.length===n,()=>`Error in concat${n}D: rank of tensors[${a}] must be the same as the rank of the rest (${n})`)}),M(t>=0&&t<n,()=>`Error in concat${n}D: axis must be between 0 and ${n-1}.`);let s=e[0];e.forEach((r,a)=>{for(let o=0;o<n;o++)M(o===t||r[o]===s[o],()=>`Error in concat${n}D: Shape of tensors[${a}] (${r}) does not match the shape of the rest (${s}) along the non-concatenated axis ${a}.`)})}function LD(e,t){let n=e[0].slice();for(let s=1;s<e.length;s++)n[t]+=e[s][t];return n}var sA=30;function BD(e){return e<=sA?e:jd(e,Math.floor(Math.sqrt(e)))}function WD(e,t,n){let s=n*(typeof e=="number"?e:e[0]),r=t*(typeof e=="number"?e:e[1]);return[s,r]}function VD(e,t,n,s=!0){let r=[];if(s)r=r.concat(t.slice(0)),r.push(e[0]/n),r=r.concat(e.slice(1));else{r=r.concat(e[0]);let a=t.length;for(let o=0;o<a;++o)r=r.concat([e[o+1]/t[o],t[o]]);r=r.concat(e.slice(a+1))}return r}function UD(e,t,n=!0){let s=[];if(n){s.push(t);for(let r=t+1;r<e;++r)r<=2*t?(s.push(r),s.push(r-(t+1))):s.push(r)}else{let r=[],a=[];for(let o=1;o<e;++o)o>=t*2+1||o%2==1?a.push(o):r.push(o);s.push(...r),s.push(0),s.push(...a)}return s}function HD(e,t,n,s=!0){let r=[];s?r.push(e[0]/n):r.push(e[0]*n);for(let a=1;a<e.length;++a)a<=t.length?s?r.push(t[a-1]*e[a]):r.push(e[a]/t[a-1]):r.push(e[a]);return r}function GD(e,t){let n=[0];for(let s=0;s<t;++s)n.push(e[s][0]);return n}function jD(e,t,n){let s=e.slice(0,1);for(let r=0;r<n;++r)s.push(e[r+1]-t[r][0]-t[r][1]);return s}var Gb=1.7580993408473768,jb=1.0507009873554805,qD=.3275911,XD=.254829592,KD=-.284496736,ZD=1.421413741,YD=-1.453152027,JD=1.061405429;function QD(e,t){if(e.length!==t.length)throw new Error(`Cannot merge real and imag arrays of different lengths. real:${e.length}, imag: ${t.length}.`);let n=new Float32Array(e.length*2);for(let s=0;s<n.length;s+=2)n[s]=e[s/2],n[s+1]=t[s/2];return n}function e$(e){let t=new Float32Array(e.length/2),n=new Float32Array(e.length/2);for(let s=0;s<e.length;s+=2)t[s/2]=e[s],n[s/2]=e[s+1];return{real:t,imag:n}}function t$(e){let t=Math.ceil(e.length/4),n=new Float32Array(t),s=new Float32Array(t);for(let r=0;r<e.length;r+=4)n[Math.floor(r/4)]=e[r],s[Math.floor(r/4)]=e[r+1];return{real:n,imag:s}}function n$(e){let t=Math.floor(e.length/4),n=new Float32Array(t),s=new Float32Array(t);for(let r=2;r<e.length;r+=4)n[Math.floor(r/4)]=e[r],s[Math.floor(r/4)]=e[r+1];return{real:n,imag:s}}function s$(e,t){let n=e[t*2],s=e[t*2+1];return{real:n,imag:s}}function r$(e,t,n,s){e[s*2]=t,e[s*2+1]=n}function a$(e,t){let n=new Float32Array(e/2),s=new Float32Array(e/2);for(let r=0;r<Math.ceil(e/2);r++){let a=(t?2:-2)*Math.PI*(r/e);n[r]=Math.cos(a),s[r]=Math.sin(a)}return{real:n,imag:s}}function o$(e,t,n){let s=(n?2:-2)*Math.PI*(e/t),r=Math.cos(s),a=Math.sin(s);return{real:r,imag:a}}var rA="->",i$=/->/g,qb=",",Xb="...";function l$(e,t){e=e.replace(/\s/g,"");let n=(e.length-e.replace(i$,"").length)/rA.length;if(n<1)throw new Error("Equations without an arrow are not supported.");if(n>1)throw new Error(`Equation must contain exactly one arrow ("${rA}").`);let[s,r]=e.split(rA);M(s.indexOf(Xb)===-1,()=>`The ellipsis notation ("${Xb}") is not supported yet.`);let a=s.split(qb),o=a.length;if(t!==o)throw new Error(`Expected ${o} input tensors, received ${t}`);if(o>2)throw new Error("Support for more than 2 input tensors is not implemented yet.");let i=[];for(let h=0;h<r.length;++h){let p=r[h];if(!a.some(f=>f.indexOf(p)!==-1))throw new Error(`Output subscripts contain the label ${p} not present in the input subscripts.`);i.indexOf(p)===-1&&i.push(p)}for(let h=0;h<s.length;++h){let p=s[h];i.indexOf(p)===-1&&p!==qb&&i.push(p)}let l=new Array(a.length);for(let h=0;h<o;++h){if(new Set(a[h].split("")).size!==a[h].length)throw new Error(`Found duplicate axes in input component ${a[h]}. Support for duplicate axes in input is not implemented yet.`);l[h]=[];for(let p=0;p<a[h].length;++p)l[h].push(i.indexOf(a[h][p]))}let u=i.length,c=r.length,d=[];for(let h=c;h<u;++h)d.push(h);return{allDims:i,summedDims:d,idDims:l}}function u$(e,t){let n=new Array(e);n.fill(-1);for(let r=0;r<t.length;++r)n[t[r]]=r;let s=[];for(let r=0;r<e;++r)n[r]===-1&&s.push(r);return n=n.filter(r=>r!==-1),{permutationIndices:n,expandDims:s}}function c$(e,t,n){let s=new Array(e);for(let r=0;r<n.length;++r){let a=n[r].shape;for(let o=0;o<t[r].length;++o)s[t[r][o]]===void 0?s[t[r][o]]=a[o]:M(s[t[r][o]]===a[o],()=>`Expected dimension ${s[t[r][o]]} at axis ${o} of input shaped ${JSON.stringify(a)}, but got dimension ${a[o]}`)}}function d$(e,t){let n=e,s=[],r=0;e.length===0&&n.push(-1),r=e.length+1;for(let o=0;o<r;++o)s.push([]);let a=[];for(let o=0;o<n.length;++o){let i=n[o],l=p$(t,i);for(let u of l)a.indexOf(u)===-1&&(s[o].push(u),a.push(u))}return{path:n,steps:s}}function h$(e){return e.every((t,n)=>t===n)}function p$(e,t){let n=[];for(let s=0;s<e.length;++s)(e[s].length===0||e[s].indexOf(t)!==-1||t===-1)&&n.push(s);return n}function f$(e,t,n=0){let s=[];if(typeof t=="number")M(e.shape[n]%t==0,()=>"Number of splits must evenly divide the axis."),s=new Array(t).fill(e.shape[n]/t);else{let r=t.reduce((o,i)=>(i===-1&&(o+=1),o),0);M(r<=1,()=>"There should be only one negative value in split array.");let a=t.indexOf(-1);if(a!==-1){let o=t.reduce((i,l)=>l>0?i+l:i);t[a]=e.shape[n]-o}M(e.shape[n]===t.reduce((o,i)=>o+i),()=>"The sum of sizes must match the size of the axis dimension."),s=t}return s}var Kb={};Pe(Kb,{collectGatherOpShapeInfo:()=>A$,computeOutShape:()=>g$,segOpComputeOptimalWindowSize:()=>m$});function m$(e,t){let n=!1,s;for(e<=sA?(s=e,n=!0):s=jd(e,Math.floor(Math.sqrt(e)));!n;)s>t||s===e?n=!0:s=jd(e,s+1);return s}function g$(e,t,n){let s=[],r=e.length;for(let a=0;a<r;a++)a!==t?s.push(e[a]):s.push(n);return s}function A$(e,t,n,s){let r=t.shape.length,a=e.shape.length;if(s!==0&&(s<-r||s>r))throw new Error(`Expect batchDims in the range of [-${r}, ${r}], but got ${s}`);if(s<0&&(s+=r),s>a)throw new Error(`batchDims (${s}) must be less than rank(x) (
${a}).`);if(n<s)throw new Error(`batchDims (${s}) must be less than or equal to axis (${n}).`);for(let d=0;d<s;++d)if(e.shape[d]!==t.shape[d])throw new Error(`x.shape[${d}]: ${e.shape[d]} should be equal to indices.shape[${d}]: ${t.shape[d]}.`);let o=e.shape[n],i=[],l=1,u=1,c=1;for(let d=0;d<s;++d)i.push(e.shape[d]),l*=e.shape[d];for(let d=s;d<n;d++)i.push(e.shape[d]),u*=e.shape[d];for(let d=s;d<r;d++)i.push(t.shape[d]);for(let d=n+1;d<a;d++)i.push(e.shape[d]),c*=e.shape[d];return{batchSize:l,sliceSize:c,outerSize:u,dimSize:o,outputShape:i}}function y$(e){try{return e.map(t=>Fh(t))}catch(t){throw new Error(`Failed to decode encoded string bytes into utf-8, error: ${t}`)}}function x$(e){return e.map(t=>Ju(t))}var rr={};Pe(rr,{nonMaxSuppressionV3Impl:()=>Lb,nonMaxSuppressionV4Impl:()=>Bb,nonMaxSuppressionV5Impl:()=>Wb,whereImpl:()=>Eb});var Zb={kernelName:ki,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(e,Ac(ce(n,"float32"),-1))}}},b$={kernelName:Ii,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>{let s=ct(ce(n,"float32")),r=hn(ge(Ie(1),s));return Tt(de(e,r))}}}},v$={kernelName:Si,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>{let s=hn(ge(ct(ce(n,"float32")),1));return de(e,s)}}}},w$={kernelName:Vr,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t,r=At(n.shape,s.shape);return{a:()=>{let i=e,l=Gt(n.shape,r);return l.length>0&&(i=ve(i,l)),U(i,n.shape)},b:()=>{let i=e,l=Gt(s.shape,r);return l.length>0&&(i=ve(i,l)),U(i,s.shape)}}}},k$={kernelName:Ta,saveAllInputs:!0,gradFunc:(e,t)=>{let n={};return t.forEach((s,r)=>{n[r]=()=>e.clone()}),n}},I$={kernelName:Na,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>Ke(n)}}},S$={kernelName:Ou,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>Ke(n)}}},C$={kernelName:Ni,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>de(e,hn(ge(Ie(1),ct(ce(n,"float32")))))}}},T$={kernelName:Ei,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>{let s=hn(ae(Ie(1),ct(ce(n,"float32"))));return de(e,s)}}}},N$={kernelName:Di,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t,r=At(n.shape,s.shape);return{a:()=>{let i=ae(ct(n),ct(s)),l=L(e,de(s,i)),u=Gt(n.shape,r);return u.length>0&&(l=ve(l,u)),U(l,n.shape)},b:()=>{let i=ae(ct(n),ct(s)),l=Tt(L(e,de(n,i))),u=Gt(s.shape,r);return u.length>0&&(l=ve(l,u)),U(l,s.shape)}}}},E$={kernelName:Ri,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>de(e,ae(ct(ce(n,"float32")),1))}}},R$={kernelName:_i,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>de(e,ge(Ie(1),ct(ce(n,"float32"))))}}};function _$(e,t,n,s,r,a){let o=$(e,"dy","avgPool3dGrad"),i=$(t,"input","avgPool3dGrad"),l=o,u=i,c=!1;i.rank===4&&(c=!0,l=U(o,[1,o.shape[0],o.shape[1],o.shape[2],o.shape[3]]),u=U(i,[1,i.shape[0],i.shape[1],i.shape[2],i.shape[3]])),M(l.rank===5,()=>`Error in avgPool3dGrad: dy must be rank 5 but got rank ${l.rank}.`),M(u.rank===5,()=>`Error in avgPool3dGrad: input must be rank 5 but got rank ${u.rank}.`),a!=null&&M(Zt(r),()=>`Error in avgPool3dGrad: pad must be an integer when using, dimRoundingMode ${a} but got pad ${r}.`);let d={dy:l,input:u},h={filterSize:n,strides:s,pad:r,dimRoundingMode:a},p=z.runKernel(Kd,d,h);return c?U(p,[p.shape[1],p.shape[2],p.shape[3],p.shape[4]]):p}var D$=W({avgPool3dGrad_:_$}),$$={kernelName:Pu,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[s]=t,{filterSize:r,strides:a,pad:o,dimRoundingMode:i}=n;return{x:()=>D$(e,s,r,a,o,i)}}};function F$(e,t,n,s,r){let a=$(e,"dy","avgPoolGrad"),o=$(t,"input","avgPoolGrad");M(o.rank===a.rank,()=>`Rank of input (${o.rank}) does not match rank of dy (${a.rank})`);let i=o,l=a,u=!1;o.rank===3&&(u=!0,i=U(o,[1,o.shape[0],o.shape[1],o.shape[2]]),l=U(a,[1,a.shape[0],a.shape[1],a.shape[2]])),M(l.rank===4,()=>`Error in avgPoolGrad: dy must be rank 4 but got rank ${l.rank}.`),M(i.rank===4,()=>`Error in avgPoolGrad: input must be rank 4 but got rank ${i.rank}.`);let c={dy:l,input:i},d={filterSize:n,strides:s,pad:r},h=z.runKernel(Xd,c,d);return u?U(h,[h.shape[1],h.shape[2],h.shape[3]]):h}var O$=W({avgPoolGrad_:F$}),P$={kernelName:Ea,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[s]=t,{filterSize:r,strides:a,pad:o}=n;return{x:()=>O$(e,s,r,a,o)}}},M$={kernelName:Ra,inputsToSave:["a","b"],gradFunc:(e,t,n)=>{let[s,r]=t,{transposeA:a,transposeB:o}=n;return!a&&!o?{a:()=>Ve(e,r,!1,!0),b:()=>Ve(s,e,!0,!1)}:!a&&o?{a:()=>Ve(e,r,!1,!1),b:()=>Ve(e,s,!0,!1)}:a&&!o?{a:()=>Ve(r,e,!1,!0),b:()=>Ve(s,e,!1,!1)}:{a:()=>Ve(r,e,!0,!0),b:()=>Ve(e,s,!0,!0)}}},z$={kernelName:$i,gradFunc:(e,t,n)=>{let{blockShape:s,crops:r}=n;return{x:()=>np(e,s,r)}}},L$={kernelName:D5,gradFunc:(e,t,n)=>{let s=n,r=s.inputShape,a=s.shape,o=Array.from(a);for(let l=r.length-1;l>=0;l--)if(r[l]===a[l])o[l]=1;else if(r[l]!==1)throw new Error(`broadcastTo(): [${r}] cannot be broadcast to [${a}].`);let i=[];for(let l=0;l<o.length;l++)o[l]>1&&i.push(l);return{x:()=>ve(e,i,!0)}}},B$={kernelName:_a,gradFunc:e=>({x:()=>e.clone()})},W$={kernelName:Da,gradFunc:e=>({x:()=>Ke(e)})},V$={kernelName:Ur,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[s]=t,{clipValueMin:r,clipValueMax:a}=n;return{x:()=>bn(Ps(Oo(s,r),Po(s,a)),e,Ke(e))}}},U$={kernelName:Mu,inputsToSave:["x"],gradFunc:Zb.gradFunc},H$={kernelName:Fi,saveAllInputs:!0,gradFunc:(e,t,n)=>{let s=t.map(l=>l.shape),{axis:r}=n,a=Ss(r,t[0].shape)[0],o=s.map(l=>l[a]);return an(e,o,a).map(l=>()=>l)}},G$={kernelName:$a,inputsToSave:["x","filter"],gradFunc:(e,t,n)=>{let[s,r]=t,{dilations:a,strides:o,pad:i,dataFormat:l}=n;return M(Yr(a),()=>`Error in gradient of conv2D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '${a}'`),{x:()=>Cg(s.shape,e,r,o,i,l),filter:()=>tA(s,e,r.shape,o,i,l)}}},j$={kernelName:Fa,inputsToSave:["dy","filter"],gradFunc:(e,t,n)=>{let[s,r]=t,{strides:a,pad:o,dataFormat:i,dimRoundingMode:l}=n;return{dy:()=>Jr(e,r,a,o,i,1,l),filter:()=>tA(e,s,r.shape,a,o,i,l)}}};function q$(e,t,n,s,r){let a=e;e.rank===4&&(a=U(e,[1,e.shape[0],e.shape[1],e.shape[2],e.shape[3]]));let o=t;o.rank===4&&(o=U(t,[1,t.shape[0],t.shape[1],t.shape[2],t.shape[3]])),M(a.rank===5,()=>`Error in conv3dDerFilter: input must be rank 5, but got shape ${a.shape}.`),M(o.rank===5,()=>`Error in conv3dDerFilter: dy must be rank 5, but got shape ${o.shape}.`),M(n.length===5,()=>`Error in conv3dDerFilter: filterShape must be length 5, but got ${n}.`),M(a.shape[4]===n[3],()=>`Error in conv3dDerFilter: depth of input ${a.shape[4]}) must match input depth in filter (${n[3]}.`),M(o.shape[4]===n[4],()=>`Error in conv3dDerFilter: depth of dy (${o.shape[4]}) must match output depth for filter (${n[4]}).`);let i={x:a,dy:o},l={strides:s,pad:r,filterShape:n};return z.runKernel(Qd,i,l)}var X$=W({conv3DBackpropFilter_:q$}),K$={kernelName:zu,inputsToSave:["x","filter"],gradFunc:(e,t,n)=>{let{dilations:s,strides:r,pad:a}=n;M(Yr(s),()=>`Error in gradient of conv3D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '${s}'`);let[o,i]=t;return{x:()=>Jx(o.shape,e,i,r,a),filter:()=>X$(o,e,i.shape,r,a)}}},Z$={kernelName:Oa,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(Tt(Gg(ce(n,"float32"))),e)}}},Y$={kernelName:Pa,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(jg(ce(n,"float32")),e)}}},J$={kernelName:Ma,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[s]=t,{axis:r,exclusive:a,reverse:o}=n;return{x:()=>{let i=pb([r],s.rank),l=Rg(e,r,a,!o);return i!=null&&(l=Xe(l,i)),l}}}},Q$={kernelName:za,inputsToSave:["x","filter"],gradFunc:(e,t,n)=>{let{dilations:s,strides:r,pad:a,dimRoundingMode:o}=n,i=s==null?[1,1]:s;M(Yr(i),()=>`Error in gradient of depthwiseConv2dNative: dilation rates greater than 1 are not yet supported. Got dilations '${i}'`);let[l,u]=t;return M(l.rank===4,()=>`Error in gradient of depthwiseConv2dNative: input must be rank 4, but got rank ${l.rank}.`),M(u.rank===4,()=>`Error in gradient of depthwiseConv2dNative: filter must be rank 4, but got rank ${u.rank}.`),M(l.shape[3]===u.shape[2],()=>`Error in gradient of depthwiseConv2d: number of input channels (${l.shape[3]}) must match the inChannels dimension in filter ${u.shape[2]}.`),M(tr(r,i),()=>`Error in gradient of depthwiseConv2d: Either strides or dilations must be 1. Got strides ${r} and dilations '${i}'.`),o!=null&&M(Zt(a),()=>`Error in depthwiseConv2d: pad must be an integer when using, dimRoundingMode ${o} but got pad ${a}.`),{x:()=>Pb(l.shape,e,u,r,a,i,o),filter:()=>Ob(l,e,u.shape,r,a,i,o)}}},eF={kernelName:Lu,inputsToSave:["x","filter"],gradFunc:(e,t,n)=>{let[s,r]=t,a={x:s,filter:r,dy:e},o={x:s,filter:r,dy:e};return{x:()=>z.runKernel(ah,a,n),filter:()=>z.runKernel(oh,o,n)}}},tF={kernelName:Ba,outputsToSave:[!0],gradFunc:(e,t)=>{let[n]=t,s={dy:e,y:n};return{x:()=>z.runKernel(lh,s)}}},nF={kernelName:Mi,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t,s=L(cs(Tt(ct(n))),2/Math.sqrt(Math.PI));return{x:()=>L(e,s)}}},sF={kernelName:Wa,outputsToSave:[!0],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(e,n)}}},rF={kernelName:Li,inputsToSave:["input"],gradFunc:(e,t)=>{let[n]=t;return{input:()=>U(e,n.shape)}}},aF={kernelName:Bi,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(e,cs(n))}}},oF={kernelName:Va,gradFunc:e=>({x:()=>Ke(e)})},iF={kernelName:Ua,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t,r=At(n.shape,s.shape);return{a:()=>{let i=de(e,ce(s,"float32")),l=Gt(n.shape,r);return l.length>0?U(ve(i,l),n.shape):i},b:()=>{let i=L(e,ce(n,"float32")),l=Gt(s.shape,r);l.length>0&&(i=U(ve(i,l),s.shape));let u=ct(s);return Tt(de(i,ce(u,"float32")))}}}},lF={kernelName:Ha,inputsToSave:["x","mean","variance","scale"],gradFunc:(e,t,n)=>{let{varianceEpsilon:s}=n,[r,a,o,i]=t,l=i==null?Ie(1):i,u=Gt(a.shape,r.shape),c=[];if(a.rank===1){for(let b=0;b<r.shape.length-1;++b)c.push(r.shape[b]);c.push(1)}let d=ge(r,a),h=L(e,l),p=Ug(ae(o,Ie(s))),f=L(L(L(p,p),p),Ie(-.5));return{x:()=>a.rank===1?U(L(L(e,Ts(U(p,[1,1,1,a.shape[0]]),c)),l),r.shape):U(L(L(e,p),l),r.shape),mean:()=>{let b=L(L(p,Ie(-1)),h);return a.rank===1&&(b=ve(b,u)),U(b,a.shape)},variance:()=>{let b=L(L(f,d),h);return a.rank===1&&(b=ve(b,u)),U(b,a.shape)},scale:()=>{let b=L(d,p),v=L(e,b);return a.rank===1&&(v=ve(v,u)),U(v,a.shape)},offset:()=>{let b=e;return a.rank===1&&(b=ve(b,u)),U(b,a.shape)}}}},uF={kernelName:Vi,inputsToSave:["x","indices"],gradFunc:(e,t,n)=>{let[s,r]=t,{axis:a}=n,o=Ss(a,s.shape)[0];return{x:()=>{let l=s.shape,u=r.size,c=l.slice(0,o),d=c.length,h=l.slice(a,l.length).slice(1),p=h.length,f=Yb(0,d),m=Yb(d+1,d+1+p),g=Jb([c,[u],h]),A=U(e,g),y=U(r,[u]),x=Jb([[d],f,m]),b=Xe(A,x),v=Tb(b,y,s.shape[o]),k=Og(x);return v=Xe(v,k),v},indices:()=>r}}};function Yb(e,t){let n=[];for(let s=e;s<t;++s)n.push(s);return n}function Jb(e){let t=[];for(let n=0;n<e.length;++n)for(let s=0;s<e[n].length;++s)t.push(e[n][s]);return t}var cF={kernelName:Ga,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t;return{a:()=>Ke(n),b:()=>Ke(s)}}},dF={kernelName:ja,gradFunc:e=>({x:()=>ce(e,"float32")})},hF={kernelName:Gi,gradFunc:e=>({x:()=>Ke(e)})},pF={kernelName:ji,gradFunc:e=>({x:()=>Ke(e)})},fF={kernelName:qi,gradFunc:e=>({x:()=>Ke(e)})},mF={kernelName:qa,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[s]=t,{alpha:r}=n,a=jn(s,0);return{x:()=>bn(a,e,L(e,r))}}},gF={kernelName:Zi,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>de(e,ae(n,1))}}},AF={kernelName:Xa,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>de(e,ce(n,"float32"))}}},yF={kernelName:$5,inputsToSave:[],outputsToSave:[!0],gradFunc:(e,t,n)=>{let[s]=t,{axis:r}=n;return{logits:()=>{let a=!0,o=cs(s);return ge(e,L(ve(e,r,a),o))}}}};function xF(e,t,n,s=5,r=1,a=1,o=.5){let i={x:e,y:t,dy:n},l={depthRadius:s,bias:r,alpha:a,beta:o};return z.runKernel(ph,i,l)}var bF=W({localResponseNormalizationBackprop_:xF}),vF={kernelName:Uu,inputsToSave:["x"],outputsToSave:[!0],gradFunc:(e,t,n)=>{let[s,r]=t,{depthRadius:a,bias:o,alpha:i,beta:l}=n;return{x:()=>bF(s,r,e,a,o,i,l)}}};function Qb(e,t,n,s){return t.rank<n.rank&&(t=U(t,Mo(t.shape,s))),e.rank<n.rank&&(e=U(e,Mo(e.shape,s))),{x:()=>L(e,ce(us(n,t),e.dtype))}}var e3={kernelName:Ka,inputsToSave:["x"],outputsToSave:[!0],gradFunc:(e,t,n)=>{let s=n,{reductionIndices:r}=s,a=t[0],o=t[1],i=Ss(r,a.shape),l=Qb(e,o,a,i);return{x:()=>l.x()}}},wF={kernelName:Za,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t;return{a:()=>L(e,ce(Oo(n,s),"float32")),b:()=>L(e,ce(Dg(n,s),"float32"))}}};function kF(e,t,n,s,r,a,o){let i=$(e,"dy","maxPool3dGrad"),l=$(t,"input","maxPool3dGrad"),u=$(n,"output","maxPool3dGrad"),c=i,d=l,h=u,p=!1;l.rank===4&&(p=!0,c=U(i,[1,i.shape[0],i.shape[1],i.shape[2],i.shape[3]]),d=U(l,[1,l.shape[0],l.shape[1],l.shape[2],l.shape[3]]),h=U(u,[1,u.shape[0],u.shape[1],u.shape[2],u.shape[3]])),M(c.rank===5,()=>`Error in maxPool3dGrad: dy must be rank 5 but got rank ${c.rank}.`),M(d.rank===5,()=>`Error in maxPool3dGrad: input must be rank 5 but got rank ${d.rank}.`),M(h.rank===5,()=>`Error in maxPool3dGrad: output must be rank 5 but got rank ${h.rank}.`),o!=null&&M(Zt(a),()=>`Error in maxPool3dGrad: pad must be an integer when using, dimRoundingMode ${o} but got pad ${a}.`);let f={dy:c,input:d,output:h},m={filterSize:s,strides:r,pad:a,dimRoundingMode:o},g=z.runKernel(mh,f,m);return p?U(g,[g.shape[1],g.shape[2],g.shape[3],g.shape[4]]):g}var IF=W({maxPool3dGrad_:kF}),SF={kernelName:Hu,inputsToSave:["x"],outputsToSave:[!0],gradFunc:(e,t,n)=>{let[s,r]=t,{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=n;return{x:()=>IF(e,s,r,a,o,i,l)}}};function CF(e,t,n,s,r,a,o){let i=$(e,"dy","maxPoolGrad"),l=$(t,"input","maxPoolGrad"),u=$(n,"output","maxPoolGrad");M(l.rank===i.rank,()=>`Rank of input (${l.rank}) does not match rank of dy (${i.rank})`),M(i.rank===4,()=>`Error in maxPoolGrad: dy must be rank 4 but got rank ${i.rank}.`),M(l.rank===4,()=>`Error in maxPoolGrad: input must be rank 4 but got rank ${l.rank}.`),o!=null&&M(Zt(a),()=>`Error in maxPoolGrad: pad must be an integer when using, dimRoundingMode ${o} but got pad ${a}.`);let c={dy:i,input:l,output:u},d={filterSize:s,strides:r,pad:a,dimRoundingMode:o};return z.runKernel(fh,c,d)}var TF=W({maxPoolGrad_:CF}),NF={kernelName:Ya,inputsToSave:["x"],outputsToSave:[!0],gradFunc:(e,t,n)=>{let[s,r]=t,{filterSize:a,strides:o,pad:i}=n;return{x:()=>TF(e,s,r,a,o,i)}}},EF={kernelName:Ja,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[s]=t,{axis:r}=n,a=Ss(r,s.shape),i=hb(s.shape,a)[1],l=$t(i);return{x:()=>{let c=s.shape.slice();a.forEach(p=>{c[p]=1});let d=U(e,c);return de(L(d,qn(s.shape,"float32")),l)}}}},RF={kernelName:Qa,inputsToSave:["x"],outputsToSave:[!0],gradFunc:(e,t,n)=>{let s=n,{axis:r}=s,[a,o]=t,i=Ss(r,a.shape),l=Qb(e,o,a,i);return{x:()=>l.x()}}},_F={kernelName:eo,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t;return{a:()=>L(e,ce(Po(n,s),"float32")),b:()=>L(e,ce(jn(n,s),"float32"))}}},DF={kernelName:to,inputsToSave:["x"],gradFunc:(e,t,n)=>{let s=t[0],{paddings:r}=n,a=r.map(o=>o[0]);return{x:()=>Re(e,a,s.shape)}}},$F={kernelName:Ji,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t,r=At(n.shape,s.shape);return{a:()=>{let i=Gt(n.shape,r);return i.length>0?U(ve(e,i),n.shape):e},b:()=>{let i=L(e,Tt(hc(de(n,s)))),l=Gt(s.shape,r);return l.length>0?U(ve(i,l),s.shape):i}}}},FF={kernelName:no,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t,r=At(n.shape,s.shape);return{a:()=>{let i=L(e,ce(s,"float32")),l=Gt(n.shape,r);return l.length>0?U(ve(i,l),n.shape):i},b:()=>{let i=L(e,ce(n,"float32")),l=Gt(s.shape,r);return l.length>0?U(ve(i,l),s.shape):i}}}},OF={kernelName:Qi,gradFunc:e=>({x:()=>Tt(e)})},PF={kernelName:so,inputsToSave:["indices"],gradFunc:(e,t)=>{let n=t[0];return{indices:()=>Pt(n.shape,"float32")}}},MF={kernelName:rl,gradFunc:e=>({x:()=>Ke(e)})},zF={kernelName:al,saveAllInputs:!0,gradFunc:(e,t,n)=>{let{axis:s}=n;return ms(e,s).map(a=>()=>a)}},t3={kernelName:ro,inputsToSave:["x"],gradFunc:(e,t,n)=>{let s=t[0],{paddings:r}=n,a=r.map(o=>o[0]);return{x:()=>Re(e,a,s.shape)}}},LF={kernelName:ao,inputsToSave:["a","b"],outputsToSave:[!0],gradFunc:(e,t)=>{let[n,s,r]=t,a=n,o=s,i=At(a.shape,o.shape);return{a:()=>{let c=ce(o,"float32"),d=L(e,L(c,ea(a,ge(c,Ie(1))))),h=Gt(a.shape,i);return h.length>0&&(d=ve(d,h)),U(d,a.shape)},b:()=>{let c=jn(a,0),d=bn(c,ds(a),Ke(a)),h=L(e,L(r,d)),p=Gt(o.shape,i);return p.length>0&&(h=ve(h,p)),U(h,o.shape)}}}},BF={kernelName:oo,inputsToSave:["x","alpha"],gradFunc:(e,t)=>{let[n,s]=t,r=jn(n,0);return{x:()=>bn(r,e,L(e,s)),alpha:()=>{let a=bn(r,Ke(e),L(e,n)),o=Gt(s.shape,e.shape);return o.length>0&&(a=ve(a,o)),U(a,s.shape)}}}},WF={kernelName:La,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t,r=At(n.shape,s.shape);return{a:()=>{let i=de(e,ce(s,"float32")),l=Gt(n.shape,r);return l.length>0?U(ve(i,l),n.shape):i},b:()=>{let i=L(e,ce(n,"float32")),l=Gt(s.shape,r);l.length>0&&(i=U(ve(i,l),s.shape));let u=ct(s);return Tt(de(i,ce(u,"float32")))}}}},VF={kernelName:il,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>de(e,Tt(ct(n)))}}},UF={kernelName:uo,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t,s=L(Po(n,6),Ac(n));return{x:()=>L(e,ce(s,"float32"))}}},HF={kernelName:io,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(e,ce(Ac(n),"float32"))}}},GF={kernelName:ll,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>U(e,n.shape)}}},jF={kernelName:lo,inputsToSave:["images"],gradFunc:(e,t,n)=>{let[s]=t,r={dy:e,images:s};return{images:()=>z.runKernel(bh,r,n)}}},qF={kernelName:ju,inputsToSave:["images"],gradFunc:(e,t,n)=>{let[s]=t,r={dy:e,images:s};return{images:()=>z.runKernel(xh,r,n)}}},XF={kernelName:co,gradFunc:(e,t,n)=>{let{dims:s}=n,r=Ss(s,e.shape);return{x:()=>fs(e,r)}}},KF={kernelName:ho,gradFunc:e=>({x:()=>Ke(e)})},ZF={kernelName:po,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>Tt(de(e,L(ea(n,1.5),2)))}}},YF={kernelName:cl,inputsToSave:["condition"],gradFunc:(e,t)=>{let[n]=t;return{condition:()=>ce(Ke(n),"float32"),t:()=>L(e,ce(n,e.dtype)),e:()=>L(e,ce(Jh(n),e.dtype))}}},JF={kernelName:dl,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>{let s=jn(n,Ie(0)),r=Ie(Gb),a=Ie(jb),o=L(e,a),i=L(L(e,r),cs(ce(n,"float32")));return bn(s,o,i)}}}},QF={kernelName:mo,outputsToSave:[!0],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(e,L(n,ge(Ie(1),n)))}}},eO={kernelName:fl,gradFunc:e=>({x:()=>Ke(e)})},tO={kernelName:fo,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(qh(ce(n,"float32")),e)}}},nO={kernelName:pl,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(Eg(ce(n,"float32")),e)}}},sO={kernelName:hl,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[s]=t,{begin:r,size:a}=n,o=s.shape,[i,l]=Cx(s,r,a),u=[];for(let c=0;c<e.rank;c++)u.push([i[c],o[c]-i[c]-l[c]]);return{x:()=>Qr(e,u)}}},rO={kernelName:yo,outputsToSave:[!0],gradFunc:(e,t,n)=>{let[s]=t,{dim:r}=n,a=!0,o=L(e,s);return{logits:()=>ge(o,L(ve(o,[r],a),s))}}},aO={kernelName:ml,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(e,Hn(n))}}},n3={kernelName:gl,gradFunc:(e,t,n)=>{let{blockShape:s,paddings:r}=n;return{x:()=>jh(e,s,r)}}},s3={kernelName:Al,gradFunc:(e,t,n)=>{let{axis:s}=n;return{x:()=>ft(e,s)}}},oO={kernelName:go,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>de(e,L(hn(ce(n,"float32")),2))}}},iO={kernelName:qu,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(e,L(ce(n,"float32"),2))}}},lO={kernelName:xo,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t,r=Ie(2);return{a:()=>L(e,L(r,ge(n,s))),b:()=>L(e,L(r,ge(s,n)))}}},uO={kernelName:Gr,gradFunc:e=>({x:()=>Ke(e)})},cO={kernelName:bo,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t,r=At(n.shape,s.shape);return{a:()=>{let i=e,l=Gt(n.shape,r);return l.length>0&&(i=ve(i,l)),U(i,n.shape)},b:()=>{let i=e,l=Gt(s.shape,r);return l.length>0&&(i=ve(i,l)),U(Tt(i),s.shape)}}}},dO={kernelName:Ao,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[s]=t,r=s.shape.slice(),{axis:a}=n;Ss(a,s.shape).forEach(u=>{r[u]=1});let i=U(e,r),l=L(i,qn(s.shape,"float32"));return{x:()=>l}}},hO={kernelName:vo,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>de(e,ct(qh(n)))}}},pO={kernelName:wo,outputsToSave:[!0],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(ge(Ie(1),ct(n)),e)}}},fO={kernelName:Hr,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[s]=t,{reps:r}=n;return{x:()=>{let o=Ke(s);if(s.rank===1)for(let i=0;i<r[0];++i)o=ae(o,Re(e,[i*s.shape[0]],[s.shape[0]]));else if(s.rank===2)for(let i=0;i<r[0];++i)for(let l=0;l<r[1];++l)o=ae(o,Re(e,[i*s.shape[0],l*s.shape[1]],[s.shape[0],s.shape[1]]));else if(s.rank===3)for(let i=0;i<r[0];++i)for(let l=0;l<r[1];++l)for(let u=0;u<r[2];++u)o=ae(o,Re(e,[i*s.shape[0],l*s.shape[1],u*s.shape[2]],[s.shape[0],s.shape[1],s.shape[2]]));else if(s.rank===4)for(let i=0;i<r[0];++i)for(let l=0;l<r[1];++l)for(let u=0;u<r[2];++u)for(let c=0;c<r[3];++c)o=ae(o,Re(e,[i*s.shape[0],l*s.shape[1],u*s.shape[2],c*s.shape[3]],[s.shape[0],s.shape[1],s.shape[2],s.shape[3]]));else throw new Error(`Gradient for tile operation is not implemented for rank-${s.rank} tensors yet.`);return o}}}},mO={kernelName:ko,gradFunc:(e,t,n)=>{let s=n,{perm:r}=s,a=Og(r);return{x:()=>Xe(e,a)}}},gO={kernelName:vl,gradFunc:(e,t,n)=>{let s=n,{axis:r}=s;return{value:()=>Dn(e,r)}}},AO={kernelName:Xu,inputsToSave:["segmentIds"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>yO(e,n)}}};function yO(e,t){let n=kr(t,Ke(t)),s=Ml(e,n),r=Oo(t,Ie(0,"int32")),a=s.rank-r.rank;for(let i=0;i<a;++i)r=Ot(r,i+1);r=Ps(r,qn(s.shape,"bool"));let o=Ke(s);return bn(r,s,o)}var xO={kernelName:wl,gradFunc:e=>({x:()=>Ke(e)})},bO=[Zb,b$,v$,w$,k$,I$,S$,C$,T$,N$,E$,R$,$$,P$,M$,z$,L$,B$,W$,V$,U$,H$,j$,G$,K$,Z$,Y$,J$,Q$,eF,WF,tF,nF,sF,rF,aF,iF,oF,lF,uF,cF,dF,hF,pF,fF,mF,gF,AF,yF,vF,e3,e3,wF,SF,NF,EF,RF,_F,DF,$F,FF,OF,PF,MF,zF,t3,t3,LF,BF,VF,UF,HF,GF,jF,qF,XF,KF,ZF,YF,JF,QF,eO,tO,nO,sO,rO,aO,n3,n3,s3,s3,oO,lO,iO,uO,cO,dO,hO,pO,fO,mO,gO,AO,xO];for(let e of bO)F5(e);var r3={};Pe(r3,{maxNorm:()=>IO,minMaxNorm:()=>TO,nonNeg:()=>CO,unitNorm:()=>SO});var aA;function jt(){return aA==null&&(aA=Dx().epsilon()),aA}function zs(){return"channelsLast"}var Cr=class extends Error{constructor(e){super(e);Object.setPrototypeOf(this,Cr.prototype)}},Ls=class extends Error{constructor(e){super(e);Object.setPrototypeOf(this,Ls.prototype)}},G=class extends Error{constructor(e){super(e);Object.setPrototypeOf(this,G.prototype)}},Oe=class extends Error{constructor(e){super(e);Object.setPrototypeOf(this,Oe.prototype)}},a3=class extends Error{constructor(e){super(e);Object.setPrototypeOf(this,a3.prototype)}};function Bo(e,t){if(Array.isArray(e)){let n=[];for(let s=0;s<t;s++)n=n.concat(e);return n}else{let n=new Array(t);return n.fill(e),n}}function ar(e,t){if(!e)throw new a3(t)}function o3(e,t){let n=0;for(let s of e)s===t&&n++;return n}function $n(e){return e.length===1?e[0]:e}function yt(e){return Array.isArray(e)?e:[e]}function Tr(e){let n=e.replace(/(.)([A-Z][a-z0-9]+)/g,"$1_$2").replace(/([a-z])([A-Z])/g,"$1_$2").toLowerCase();return n[0]!=="_"?n:"private"+n}function Wo(e){return e.length<=1||e.indexOf("_")===-1?e:e.replace(/[_]+(\w|$)/g,(t,n)=>n.toUpperCase())}var Ns={};function oA(e){if(e==null)return null;let t={};return t.className=e.getClassName(),t.config=e.getConfig(),t}function iA(e){if(!(e==null||typeof e!="object"))if(Array.isArray(e))e.forEach(t=>iA(t));else{let t=Object.keys(e);for(let n of t){let s=e[n];s!=null&&typeof s=="object"&&(!Array.isArray(s)&&s.type==="ndarray"&&typeof s.value=="number"?e[n]=s.value:iA(s))}}}function bc(e,t={},n={},s="object",r=!1){if(typeof e=="string"){let a=e,o;if(a in n)o=n[a];else if(a in Ns)o=Ns[a];else if(o=t[a],o==null)throw new G(`Unknown ${s}: ${e}. This may be due to one of the following reasons:
1. The ${s} is defined in Python, in which case it needs to be ported to TensorFlow.js or your JavaScript code.
2. The custom ${s} is defined in JavaScript, but is not registered properly with tf.serialization.registerClass().`);return o}else{let a=e;if(a.className==null||a.config==null)throw new G(`${s}: Improper config format: ${JSON.stringify(a)}.
'className' and 'config' must set.`);let o=a.className,i,l;if(o in n?[i,l]=n[o]:o in Ns?[i,l]=Ns.className:o in t&&([i,l]=t[o]),i==null)throw new G(`Unknown ${s}: ${o}. This may be due to one of the following reasons:
1. The ${s} is defined in Python, in which case it needs to be ported to TensorFlow.js or your JavaScript code.
2. The custom ${s} is defined in JavaScript, but is not registered properly with tf.serialization.registerClass().`);if(l!=null){let u={};for(let p of Object.keys(Ns))u[p]=Ns[p];for(let p of Object.keys(n))u[p]=n[p];let c=a.config;c.customObjects=u;let d=Object.assign({},Ns);for(let p of Object.keys(n))Ns[p]=n[p];iA(a.config);let h=l(i,a.config,n,r);return Ns=Object.assign({},d),h}else{let u=Object.assign({},Ns);for(let d of Object.keys(n))Ns[d]=n[d];let c=new i(a.config);return Ns=Object.assign({},u),c}}}function vO(e,t){return e<t?-1:e>t?1:0}function wp(e,t){return-1*vO(e,t)}function na(e){if(e==null)return e;let t=[];for(let n of e)t.indexOf(n)===-1&&t.push(n);return t}function wO(e){if(e==null)throw new G(`Invalid value in obj: ${JSON.stringify(e)}`);for(let t in e)if(e.hasOwnProperty(t))return!1;return!0}function Vo(e,t,n){if(n!=null&&e.indexOf(n)<0)throw new G(`${n} is not a valid ${t}. Valid values are ${e} or null/undefined.`)}function lA(e,t,n=0,s=1/0){return ar(n>=0),ar(s>=n),Array.isArray(e)&&e.length>=n&&e.length<=s&&e.every(r=>typeof r===t)}function Qt(e,t){Array.isArray(e)?(w.assert(e.length>0,()=>`${t} is unexpectedly an empty array.`),e.forEach((n,s)=>Qt(n,`element ${s+1} of ${t}`))):w.assert(Number.isInteger(e)&&e>0,()=>`Expected ${t} to be a positive integer, but got ${i3(e)}.`)}function i3(e){return e===null?"null":Array.isArray(e)?"["+e.map(t=>i3(t)).join(",")+"]":typeof e=="string"?`"${e}"`:`${e}`}function kO(e,t){let n=w.now(),s;return(...a)=>{let o=w.now();return o-n<t||(n=o,s=e(...a)),s}}function l3(e){return e==="relu"?"relu":e==="linear"?"linear":e==="elu"?"elu":null}function uA(e,t){return H(()=>hn(ve(L(e,e),t,!0)))}var vc=class extends oe.Serializable{getConfig(){return{}}},cA=class extends vc{constructor(e){super();this.defaultMaxValue=2,this.defaultAxis=0,this.maxValue=e.maxValue!=null?e.maxValue:this.defaultMaxValue,this.axis=e.axis!=null?e.axis:this.defaultAxis}apply(e){return H(()=>{let t=uA(e,this.axis),n=Gn(t,0,this.maxValue);return L(e,de(n,ae(jt(),t)))})}getConfig(){return{maxValue:this.maxValue,axis:this.axis}}};cA.className="MaxNorm";oe.registerClass(cA);var dA=class extends vc{constructor(e){super();this.defaultAxis=0,this.axis=e.axis!=null?e.axis:this.defaultAxis}apply(e){return H(()=>de(e,ae(jt(),uA(e,this.axis))))}getConfig(){return{axis:this.axis}}};dA.className="UnitNorm";oe.registerClass(dA);var hA=class extends vc{apply(e){return sr(e)}};hA.className="NonNeg";oe.registerClass(hA);var pA=class extends vc{constructor(e){super();this.defaultMinValue=0,this.defaultMaxValue=1,this.defaultRate=1,this.defaultAxis=0,this.minValue=e.minValue!=null?e.minValue:this.defaultMinValue,this.maxValue=e.maxValue!=null?e.maxValue:this.defaultMaxValue,this.rate=e.rate!=null?e.rate:this.defaultRate,this.axis=e.axis!=null?e.axis:this.defaultAxis}apply(e){return H(()=>{let t=uA(e,this.axis),n=ae(L(this.rate,Gn(t,this.minValue,this.maxValue)),L(1-this.rate,t));return L(e,de(n,ae(jt(),t)))})}getConfig(){return{minValue:this.minValue,maxValue:this.maxValue,rate:this.rate,axis:this.axis}}};pA.className="MinMaxNorm";oe.registerClass(pA);var u3={maxNorm:"MaxNorm",minMaxNorm:"MinMaxNorm",nonNeg:"NonNeg",unitNorm:"UnitNorm"};function qt(e){return oA(e)}function c3(e,t={}){return bc(e,oe.SerializationMap.getMap().classNameMap,t,"constraint")}function Xt(e){if(e==null)return null;if(typeof e=="string"){let n={className:e in u3?u3[e]:e,config:{}};return c3(n)}else return e instanceof vc?e:c3(e)}function IO(e){return new cA(e)}function SO(e){return new dA(e)}function CO(){return new hA}function TO(e){return new pA(e)}var d3={};Pe(d3,{constant:()=>ZO,glorotNormal:()=>sP,glorotUniform:()=>nP,heNormal:()=>rP,heUniform:()=>aP,identity:()=>eP,leCunNormal:()=>oP,leCunUniform:()=>iP,ones:()=>KO,orthogonal:()=>lP,randomNormal:()=>JO,randomUniform:()=>YO,truncatedNormal:()=>QO,varianceScaling:()=>tP,zeros:()=>XO});var NO=["channelsFirst","channelsLast"],EO=["nearest","bilinear"],RO=["valid","same","causal"],_O=["max","avg"],DO=["sum","mul","concat","ave"],Ul=new Map;function Ft(e){Vo(NO,"DataFormat",e)}function $O(e){Vo(EO,"InterpolationFormat",e)}function gs(e){Vo(RO,"PaddingMode",e)}function h3(e){Vo(_O,"PoolMode",e)}var wc=[],p3="/";function Uo(e,t){wc.push(e);try{let n=t();return wc.pop(),n}catch(n){throw wc.pop(),n}}function FO(){return wc.length===0?"":wc.join(p3)+p3}function f3(e){if(!g3(e))throw new Error("Not a valid tensor name: '"+e+"'");return FO()+e}function m3(e){if(!g3(e))throw new Error("Not a valid tensor name: '"+e+"'");Ul.has(e)||Ul.set(e,0);let t=Ul.get(e);if(Ul.set(e,Ul.get(e)+1),t>0){let n=`${e}_${t}`;return Ul.set(n,1),n}else return e}var OO=new RegExp(/^[A-Za-z0-9][-A-Za-z0-9\._\/]*$/);function g3(e){return!!e.match(OO)}function PO(e){return e===parseInt(e.toString(),10)}function sa(e,t,n){t==null&&(t=0),n==null&&(n=e.length);let s=1;for(let r=t;r<n;++r)s*=e[r];return s}function Hl(e){if(e.length===0)return Number.NaN;let t=Number.POSITIVE_INFINITY;for(let n=0;n<e.length;n++){let s=e[n];s<t&&(t=s)}return t}function ra(e){if(e.length===0)return Number.NaN;let t=Number.NEGATIVE_INFINITY;for(let n=0;n<e.length;n++){let s=e[n];s>t&&(t=s)}return t}function Bs(e,t){if(t<e)throw new G(`end (${t}) < begin (${e}) is forbidden.`);let n=[];for(let s=e;s<t;++s)n.push(s);return n}function kp(e,t){return ce(e,t)}function kc(e,t=-1){let n=e.shape.slice();return t<0&&(t=n.length+t+1),n.splice(t,0,1),U(e,n)}function MO(e,t){return H(()=>{if(e.shape.length!==2)throw new G(`repeat() expects a rank-2 tensor, but received a rank-${e.shape.length} tensor.`);let n=kc(e,1);return gA(n,[1,t,1])})}function zO(e){let t=[sa(e.shape)];return U(e,t)}function LO(e){if(e.rank<=1)throw new G(`batchFlatten requires a minimum rank of 2. Got rank: ${e.rank}.`);let t=[e.shape[0],sa(e.shape,1)];return U(e,t)}function Ho(e,t,n){return H(()=>{switch(e.rank){case 1:return rp(e,t,n);case 2:return qg(e,[t,0],[n,e.shape[1]]);case 3:return ap(e,[t,0,0],[n,e.shape[1],e.shape[2]]);case 4:return mc(e,[t,0,0,0],[n,e.shape[1],e.shape[2],e.shape[3]]);case 5:return Re(e,[t,0,0,0,0],[n,e.shape[1],e.shape[2],e.shape[3],e.shape[4]]);case 6:return Re(e,[t,0,0,0,0,0],[n,e.shape[1],e.shape[2],e.shape[3],e.shape[4],e.shape[5]]);default:throw new G(`sliceAlongFirstAxis() received an unsupported tensor rank: ${e.rank}`)}})}function fA(e,t,n){return H(()=>{switch(e.rank){case 1:return rp(e,t,n);case 2:return qg(e,[0,t],[e.shape[0],n]);case 3:return ap(e,[0,0,t],[e.shape[0],e.shape[1],n]);case 4:return mc(e,[0,0,0,t],[e.shape[0],e.shape[1],e.shape[2],n]);default:throw new G(`sliceAlongLastAxis() received an unsupported tensor rank: ${e.rank}`)}})}function Ip(e,t,n,s){return H(()=>{switch(e.rank){case 1:return rp(e,t,n);case 2:switch(s){case 1:return Ho(e,t,n);case 2:return fA(e,t,n);default:throw new G(`The axis is not within the rank of the tensor ${s}`)}case 3:switch(s){case 1:return Ho(e,t,n);case 2:return ap(e,[0,t,0],[e.shape[0],n,e.shape[2]]);case 3:return fA(e,t,n);default:throw new G(`The axis is not within the rank of the tensor ${s}`)}case 4:switch(s){case 1:return Ho(e,t,n);case 2:return mc(e,[0,t,0,0],[e.shape[0],n,e.shape[2],e.shape[3]]);case 3:return mc(e,[0,0,t,0],[e.shape[0],e.shape[1],n,e.shape[3]]);case 4:return fA(e,t,n);default:throw new G(`The axis is not within the rank of the tensor ${s}`)}default:throw new G(`sliceAlongLastAxis() received an unsupported tensor rank: ${e.rank}`)}})}function mA(e,t=-1){let n;return t<0&&(n=e[0].rank,n!==0?t=n:t=0),t===e[0].rank&&(t=-1),ft(e,t)}function A3(e,t){switch(e.rank){case 1:return Kx([e,t]);case 2:return Ol([e,t],0);case 3:return Zx([e,t],0);case 4:return Yx([e,t],0);default:throw new G(`concatAlongFirstAxis() received an unsupported tensor rank: ${e.rank}`)}}function gA(e,t){if(Array.isArray(t)||(t=[t]),e.rank!==t.length)throw new G(`The length of input n (${t.length}) does not match the number of dimensions in input x (${e.rank})`);return Ts(e,t)}function Sp(e,t=0,n=1,s,r){return xb(e,t,n,s,r)}function or(e,t,n,s){if(e.rank<2||t.rank<2)throw new Oe(`dot requires both inputs to be rank >= 2 but got x shape = ${e.shape} and y shape = ${t.shape}`);if(t.rank>=3){let r=e.shape.slice(-1)[0],a=t.shape.slice(-2)[0];if(r!==a)throw new Oe(`If rank y >= 3, then the second last dim of y must equal the last dim of x but got x shape = ${e.shape} and y shape = ${t.shape}`)}if(e.rank===2&&t.rank===2){let r=!1,a=!1;return ta.matMul({a:e,b:t,transposeA:r,transposeB:a,bias:s?AA(e.rank,s,zs()):null,activation:n})}else{let r=e.shape.slice(),a=r.pop();e=U(e,[-1,a]);let o=t.shape.slice(),i=o.pop(),l=o.pop(),u=[...o,i],c=Array.from({length:t.rank},(f,m)=>m===0?t.rank-2:m<=t.rank-2?m-1:m);t=U(Xe(t,c),[l,-1]);let d=[...r,...u],h=!1,p=!1;return U(ta.matMul({a:e,b:t,transposeA:h,transposeB:p,bias:s?AA(e.rank,s,zs()):null,activation:n}),d)}}function y3(e,t,n){return H(()=>(Array.isArray(t)?t=Mt(t,"int32"):t=ce(t,"int32"),Ml(e,t,n)))}function Ic(e){return L(e,e)}function AA(e,t,n){let s=t.shape;if(t.rank!==1&&t.rank!==e)throw new G(`Unexpected bias dimensions: ${t.rank}; expected it to be 1 or ${e}`);if(e===5){if(n==="channelsFirst")return s.length===1?U(t,[1,s[0],1,1,1]):U(t,[1,s[3],s[0],s[1],s[2]]);if(n==="channelsLast")return s.length===1?U(t,[1,1,1,1,s[0]]):U(t,[1].concat(s))}else if(e===4){if(n==="channelsFirst")return s.length===1?U(t,[1,s[0],1,1]):U(t,[1,s[2],s[0],s[1]]);if(n==="channelsLast")return s.length===1?U(t,[1,1,1,s[0]]):U(t,[1].concat(s))}else if(e===3){if(n==="channelsFirst")return s.length===1?U(t,[1,s[0],1]):U(t,[1,s[1],s[0]]);if(n==="channelsLast")return s.length===1?U(t,[1,1,s[0]]):U(t,[1].concat(s))}else if(e<3)return t;throw new G(`Unsupported input rank by biasAdd: ${t.rank}`)}function Ws(e,t,n){return H(()=>(n==null&&(n=zs()),Ft(n),ae(e,AA(e.rank,t,n))))}function BO(e,t=1){if(t!==1)throw new Oe(`Support for alpha values other than 1 (${t}) is not implemented yet.`);return dc(e)}function WO(e){return H(()=>de(e,ae(Ht(e),1)))}function x3(e,t,n,s){return H(()=>$b(e,t,n,s))}function VO(e){return H(()=>{let t=ae(.5,L(.2,e));return Gn(t,0,1)})}function Sc(e,t,n=!1){return n?e():t()}var UO=["fanIn","fanOut","fanAvg"],HO=["normal","uniform","truncatedNormal"];function GO(e){Vo(UO,"FanMode",e)}function jO(e){Vo(HO,"Distribution",e)}var Es=class extends oe.Serializable{fromConfigUsesCustomObjects(){return!1}getConfig(){return{}}},yA=class extends Es{apply(e,t){return Pt(e,t)}};yA.className="Zeros";oe.registerClass(yA);var Cp=class extends Es{apply(e,t){return qn(e,t)}};Cp.className="Ones";oe.registerClass(Cp);var xA=class extends Es{constructor(e){super();if(typeof e!="object")throw new G(`Expected argument of type ConstantConfig but got ${e}`);if(e.value===void 0)throw new G(`config must have value set but got ${e}`);this.value=e.value}apply(e,t){return H(()=>L(Ie(this.value),qn(e,t)))}getConfig(){return{value:this.value}}};xA.className="Constant";oe.registerClass(xA);var bA=class extends Es{constructor(e){super();this.DEFAULT_MINVAL=-.05,this.DEFAULT_MAXVAL=.05,this.minval=e.minval||this.DEFAULT_MINVAL,this.maxval=e.maxval||this.DEFAULT_MAXVAL,this.seed=e.seed}apply(e,t){return Bl(e,this.minval,this.maxval,t)}getConfig(){return{minval:this.minval,maxval:this.maxval,seed:this.seed}}};bA.className="RandomUniform";oe.registerClass(bA);var vA=class extends Es{constructor(e){super();this.DEFAULT_MEAN=0,this.DEFAULT_STDDEV=.05,this.mean=e.mean||this.DEFAULT_MEAN,this.stddev=e.stddev||this.DEFAULT_STDDEV,this.seed=e.seed}apply(e,t){if(t=t||"float32",t!=="float32"&&t!=="int32")throw new Oe(`randomNormal does not support dType ${t}.`);return Sp(e,this.mean,this.stddev,t,this.seed)}getConfig(){return{mean:this.mean,stddev:this.stddev,seed:this.seed}}};vA.className="RandomNormal";oe.registerClass(vA);var wA=class extends Es{constructor(e){super();this.DEFAULT_MEAN=0,this.DEFAULT_STDDEV=.05,this.mean=e.mean||this.DEFAULT_MEAN,this.stddev=e.stddev||this.DEFAULT_STDDEV,this.seed=e.seed}apply(e,t){if(t=t||"float32",t!=="float32"&&t!=="int32")throw new Oe(`truncatedNormal does not support dType ${t}.`);return up(e,this.mean,this.stddev,t,this.seed)}getConfig(){return{mean:this.mean,stddev:this.stddev,seed:this.seed}}};wA.className="TruncatedNormal";oe.registerClass(wA);var kA=class extends Es{constructor(e){super();this.gain=e.gain!=null?e.gain:1}apply(e,t){return H(()=>{if(e.length!==2||e[0]!==e[1])throw new G("Identity matrix initializer can only be used for 2D square matrices.");return L(this.gain,_g(e[0]))})}getConfig(){return{gain:this.gain}}};kA.className="Identity";oe.registerClass(kA);function qO(e,t="channelsLast"){let n,s;if(Ft(t),e.length===2)n=e[0],s=e[1];else if([3,4,5].indexOf(e.length)!==-1){if(t==="channelsFirst"){let r=sa(e,2);n=e[1]*r,s=e[0]*r}else if(t==="channelsLast"){let r=sa(e,0,e.length-2);n=e[e.length-2]*r,s=e[e.length-1]*r}}else{let r=sa(e);n=Math.sqrt(r),s=Math.sqrt(r)}return[n,s]}var Fn=class extends Es{constructor(e){super();if(e.scale<0)throw new G(`scale must be a positive float. Got: ${e.scale}`);this.scale=e.scale==null?1:e.scale,this.mode=e.mode==null?"fanIn":e.mode,GO(this.mode),this.distribution=e.distribution==null?"normal":e.distribution,jO(this.distribution),this.seed=e.seed}apply(e,t){let n=qO(e),s=n[0],r=n[1],a=this.scale;if(this.mode==="fanIn"?a/=Math.max(1,s):this.mode==="fanOut"?a/=Math.max(1,r):a/=Math.max(1,(s+r)/2),this.distribution==="normal"){let o=Math.sqrt(a);if(t=t||"float32",t!=="float32"&&t!=="int32")throw new Oe(`${this.getClassName()} does not support dType ${t}.`);return up(e,0,o,t,this.seed)}else{let o=Math.sqrt(3*a);return Bl(e,-o,o,t)}}getConfig(){return{scale:this.scale,mode:this.mode,distribution:this.distribution,seed:this.seed}}};Fn.className="VarianceScaling";oe.registerClass(Fn);var Tp=class extends Fn{constructor(e){super({scale:1,mode:"fanAvg",distribution:"uniform",seed:e==null?null:e.seed})}getClassName(){return Fn.className}};Tp.className="GlorotUniform";oe.registerClass(Tp);var Np=class extends Fn{constructor(e){super({scale:1,mode:"fanAvg",distribution:"normal",seed:e==null?null:e.seed})}getClassName(){return Fn.className}};Np.className="GlorotNormal";oe.registerClass(Np);var Ep=class extends Fn{constructor(e){super({scale:2,mode:"fanIn",distribution:"normal",seed:e==null?null:e.seed})}getClassName(){return Fn.className}};Ep.className="HeNormal";oe.registerClass(Ep);var Rp=class extends Fn{constructor(e){super({scale:2,mode:"fanIn",distribution:"uniform",seed:e==null?null:e.seed})}getClassName(){return Fn.className}};Rp.className="HeUniform";oe.registerClass(Rp);var _p=class extends Fn{constructor(e){super({scale:1,mode:"fanIn",distribution:"normal",seed:e==null?null:e.seed})}getClassName(){return Fn.className}};_p.className="LeCunNormal";oe.registerClass(_p);var Dp=class extends Fn{constructor(e){super({scale:1,mode:"fanIn",distribution:"uniform",seed:e==null?null:e.seed})}getClassName(){return Fn.className}};Dp.className="LeCunNormal";oe.registerClass(Dp);var IA=class extends Es{constructor(e){super();if(this.DEFAULT_GAIN=1,this.gain=e.gain==null?this.DEFAULT_GAIN:e.gain,this.seed=e.seed,this.seed!=null)throw new Oe("Random seed is not implemented for Orthogonal Initializer yet.")}apply(e,t){return H(()=>{if(e.length<2)throw new Oe("Shape must be at least 2D.");e[0]*e[1]>2e3&&console.warn(`Orthogonal initializer is being called on a matrix with more than 2000 (${e[0]*e[1]}) elements: Slowness may result.`);let n=e[0]>e[1]?[e[1],e[0]]:e,s=Sp(n,0,1,"float32"),r=Hb.gramSchmidt(s);return e[0]>e[1]&&(r=Xe(r)),L(this.gain,r)})}getConfig(){return{gain:this.gain,seed:this.seed}}};IA.className="Orthogonal";oe.registerClass(IA);var b3={constant:"Constant",glorotNormal:"GlorotNormal",glorotUniform:"GlorotUniform",heNormal:"HeNormal",heUniform:"HeUniform",identity:"Identity",leCunNormal:"LeCunNormal",leCunUniform:"LeCunUniform",ones:"Ones",orthogonal:"Orthogonal",randomNormal:"RandomNormal",randomUniform:"RandomUniform",truncatedNormal:"TruncatedNormal",varianceScaling:"VarianceScaling",zeros:"Zeros"};function v3(e,t={}){return bc(e,oe.SerializationMap.getMap().classNameMap,t,"initializer")}function Nt(e){return oA(e)}function wt(e){if(typeof e=="string"){let t=e in b3?b3[e]:e;if(t==="GlorotNormal")return new Np;if(t==="GlorotUniform")return new Tp;if(t==="HeNormal")return new Ep;if(t==="HeUniform")return new Rp;if(t==="LeCunNormal")return new _p;if(t==="LeCunUniform")return new Dp;{let n={};return n.className=t,n.config={},v3(n)}}else return e instanceof Es?e:v3(e)}function XO(){return new yA}function KO(){return new Cp}function ZO(e){return new xA(e)}function YO(e){return new bA(e)}function JO(e){return new vA(e)}function QO(e){return new wA(e)}function eP(e){return new kA(e)}function tP(e){return new Fn(e)}function nP(e){return new Tp(e)}function sP(e){return new Np(e)}function rP(e){return new Ep(e)}function aP(e){return new Rp(e)}function oP(e){return new _p(e)}function iP(e){return new Dp(e)}function lP(e){return new IA(e)}var w3={};Pe(w3,{Layer:()=>Ze,RNN:()=>ur,RNNCell:()=>Fc,activation:()=>HM,add:()=>QM,alphaDropout:()=>Pz,average:()=>ez,averagePooling1d:()=>V1,averagePooling2d:()=>U1,averagePooling3d:()=>H1,avgPool1d:()=>uz,avgPool2d:()=>dz,avgPool3d:()=>pz,avgPooling1d:()=>cz,avgPooling2d:()=>hz,avgPooling3d:()=>fz,batchNormalization:()=>oz,bidirectional:()=>Nz,concatenate:()=>tz,conv1d:()=>OM,conv2d:()=>PM,conv2dTranspose:()=>MM,conv3d:()=>zM,conv3dTranspose:()=>LM,convLstm2d:()=>Iz,convLstm2dCell:()=>Sz,cropping2D:()=>WM,dense:()=>GM,depthwiseConv2d:()=>UM,dot:()=>az,dropout:()=>jM,elu:()=>EM,embedding:()=>JM,flatten:()=>XM,gaussianDropout:()=>Oz,gaussianNoise:()=>Fz,globalAveragePooling1d:()=>mz,globalAveragePooling2d:()=>gz,globalMaxPool1d:()=>Rz,globalMaxPool2d:()=>_z,globalMaxPooling1d:()=>_v,globalMaxPooling2d:()=>Dv,gru:()=>yz,gruCell:()=>xz,input:()=>tv,inputLayer:()=>NM,layerNormalization:()=>iz,leakyReLU:()=>_M,lstm:()=>bz,lstmCell:()=>vz,masking:()=>Mz,maxPool1d:()=>Dz,maxPool2d:()=>$z,maxPooling1d:()=>$v,maxPooling2d:()=>Fv,maxPooling3d:()=>Az,maximum:()=>nz,minimum:()=>sz,multiply:()=>rz,permute:()=>YM,prelu:()=>DM,reLU:()=>RM,repeatVector:()=>KM,reshape:()=>ZM,rnn:()=>Cz,separableConv2d:()=>BM,simpleRNN:()=>wz,simpleRNNCell:()=>kz,softmax:()=>$M,spatialDropout1d:()=>qM,stackedRNNCells:()=>Tz,thresholdedReLU:()=>FM,timeDistributed:()=>Ez,upSampling2d:()=>VM,zeroPadding2d:()=>lz});var uP=0;function k3(){return uP++}var $p={};function Fp(e=""){return e in $p||($p[e]=0),$p[e]+=1,e+$p[e].toString()}function SA(e){return Array.isArray(e)&&Array.isArray(e[0])}function Op(e){return e.length===0?[]:Array.isArray(e[0])?e:[e]}function ze(e){let t;if(Array.isArray(e)){if(e.length!==1)throw new G(`Expected Tensor length to be 1; got ${e.length}`);t=e[0]}else t=e;return t}function at(e){if(Array.isArray(e)&&Array.isArray(e[0])){if(e.length===1)return e=e,e[0];throw new G(`Expected exactly 1 Shape; got ${e.length}`)}else return e}function Pp(e){let t=0;for(let n of e)n.shape.length===0?t+=1:t+=n.shape.reduce((s,r)=>s*r);return t}var I3="Variable",S3=class{constructor(e,t="float32",n=I3,s=!0,r=null){this.dtype=t==null?"float32":t,this.shape=e.shape,this.id=k3(),n=n==null?I3:n,this.originalName=f3(n),this.name=m3(this.originalName),this.trainable_=s,this.constraint=r,this.val=Nb(e,this.trainable_,this.name,this.dtype)}read(){return this.assertNotDisposed(),this.val}write(e){return this.assertNotDisposed(),cP(this.val,e),this.val.id!==e.id&&(this.val.assign(e),this.constraint!=null&&this.val.assign(this.constraint.apply(this.val))),this}dispose(){this.assertNotDisposed(),this.val.dispose()}assertNotDisposed(){if(this.val.isDisposed)throw new Error(`LayersVariable ${this.name} is already disposed.`)}get trainable(){return this.trainable_}set trainable(e){this.trainable_=e,this.val.trainable=e}};function cP(e,t){if(e.shape.toString()!==t.shape.toString())throw new Error("Shape mismatch: "+JSON.stringify(e.shape)+" vs. "+JSON.stringify(t.shape))}function CA(e){return e.map(t=>t.read())}function TA(e){e.forEach(t=>{t[0].write(t[1])})}var zt=class{constructor(e){this.dtype=e.dtype,this.shape=e.shape,e.shape!=null?this.ndim=e.shape.length:this.ndim=e.ndim,this.maxNDim=e.maxNDim,this.minNDim=e.minNDim,this.axes=e.axes||{}}},Vs=class{constructor(e,t,n,s,r,a,o){this.dtype=e,this.shape=t,this.sourceLayer=n,this.inputs=s,this.callArgs=r,this.outputTensorIndex=o,this.id=k3(),a!=null&&(this.originalName=f3(a),this.name=m3(this.originalName)),this.rank=t.length}},dP=0,Mp=class{constructor(e,t){this.callArgs=t,this.id=dP++,this.outboundLayer=e.outboundLayer,this.inboundLayers=e.inboundLayers,this.nodeIndices=e.nodeIndices,this.tensorIndices=e.tensorIndices,this.inputTensors=e.inputTensors,this.outputTensors=e.outputTensors,this.inputMasks=e.inputMasks,this.outputMasks=e.outputMasks,this.inputShapes=e.inputShapes,this.outputShapes=e.outputShapes;for(let n of e.inboundLayers)n!=null&&n.outboundNodes.push(this);e.outboundLayer.inboundNodes.push(this)}getConfig(){let e=[];for(let t of this.inboundLayers)t!=null?e.push(t.name):e.push(null);return{outboundLayer:this.outboundLayer?this.outboundLayer.name:null,inboundLayers:e,nodeIndices:this.nodeIndices,tensorIndices:this.tensorIndices}}},hP=0,Ze=class extends oe.Serializable{constructor(e={}){super();this._callHook=null,this._addedWeightNames=[],this._stateful=!1,this.id=hP++,this.activityRegularizer=null,this.inputSpec=null,this.supportsMasking=!1,this._trainableWeights=[],this._nonTrainableWeights=[],this._losses=[],this._updates=[],this._built=!1,this.inboundNodes=[],this.outboundNodes=[];let t=e.name;if(!t){let n=this.getClassName();t=Tr(n)+"_"+Fp(n)}if(this.name=t,this.trainable_=e.trainable==null?!0:e.trainable,e.inputShape!=null||e.batchInputShape!=null){let n;if(e.batchInputShape!=null)n=e.batchInputShape;else if(e.inputShape!=null){let r=null;e.batchSize!=null&&(r=e.batchSize),n=[r].concat(e.inputShape)}this.batchInputShape=n;let s=e.dtype;s==null&&(s=e.inputDType),s==null&&(s="float32"),this.dtype=s}e.weights!=null?this.initialWeights=e.weights:this.initialWeights=null,this._refCount=null,this.fastWeightInitDuringBuild=!1}static nodeKey(e,t){return e.name+"_ib-"+t.toString()}getNodeAtIndex(e,t){if(this.inboundNodes.length===0)throw new Ls(`The layer has never been called and thus has no defined ${t}.`);if(this.inboundNodes.length<=e)throw new G(`Asked to get ${t} at node ${e}, but the layer has only ${this.inboundNodes.length} inbound nodes.`);return this.inboundNodes[e]}getInputAt(e){return $n(this.getNodeAtIndex(e,"input").inputTensors)}getOutputAt(e){return $n(this.getNodeAtIndex(e,"output").outputTensors)}get input(){if(this.inboundNodes.length>1)throw new Cr(`Layer ${this.name} has multiple inbound nodes, hence the notion of "layer input" is ill-defined. Use \`getInputAt(nodeIndex)\` instead.`);if(this.inboundNodes.length===0)throw new Cr(`Layer ${this.name} is not connected, no input to return.`);return $n(this.getNodeAtIndex(0,"input").inputTensors)}get output(){if(this.inboundNodes.length===0)throw new Cr(`Layer ${this.name} has no inbound nodes.`);if(this.inboundNodes.length>1)throw new Cr(`Layer ${this.name} has multiple inbound nodes, hence the notion of "layer output" is ill-defined. Use \`getOutputAt(nodeIndex)\` instead.`);return $n(this.getNodeAtIndex(0,"output").outputTensors)}get losses(){return this._losses}calculateLosses(){return this.losses.map(e=>e())}get updates(){return this._updates}get built(){return this._built}set built(e){this._built=e}get trainable(){return this.trainable_}set trainable(e){this._trainableWeights.forEach(t=>t.trainable=e),this.trainable_=e}get trainableWeights(){return this.trainable_?this._trainableWeights.filter(e=>e.trainable):[]}set trainableWeights(e){this._trainableWeights=e}get nonTrainableWeights(){return this.trainable?this._trainableWeights.filter(e=>!e.trainable).concat(this._nonTrainableWeights):this._trainableWeights.concat(this._nonTrainableWeights)}set nonTrainableWeights(e){this._nonTrainableWeights=e}get weights(){return this.trainableWeights.concat(this.nonTrainableWeights)}get stateful(){return this._stateful}resetStates(){if(!this.stateful)throw new Error("Cannot call the resetStates() method of a non-stateful Layer object.")}assertInputCompatibility(e){if(e=yt(e),this.inputSpec==null||this.inputSpec.length===0)return;let t=yt(this.inputSpec);if(e.length!==t.length)throw new G(`Layer ${this.name} expects ${t.length} inputs, but it received ${e.length} input tensors. Input received: ${e}`);for(let n=0;n<e.length;n++){let s=e[n],r=t[n];if(r==null)continue;let a=s.rank;if(r.ndim!=null&&a!==r.ndim)throw new G(`Input ${n} is incompatible with layer ${this.name}: expected ndim=${r.ndim}, found ndim=${a}`);if(r.maxNDim!=null&&a>r.maxNDim)throw new G(`Input ${n} is incompatible with layer ${this.name}: expected max_ndim=${r.maxNDim}, found ndim=${a}`);if(r.minNDim!=null&&a<r.minNDim)throw new G(`Input ${n} is incompatible with layer ${this.name}: expected min_ndim=${r.minNDim}, found ndim=${a}.`);if(r.dtype!=null&&s.dtype!==r.dtype)throw new G(`Input ${n} is incompatible with layer ${this.name} : expected dtype=${r.dtype}, found dtype=${s.dtype}.`);if(r.axes){let o=s.shape;for(let i in r.axes){let l=Number(i),u=r.axes[i],c=l>=0?o[l]:o[o.length+l];if(u!=null&&[u,null].indexOf(c)===-1)throw new G(`Input ${n} is incompatible with layer ${this.name}: expected axis ${l} of input shape to have value ${u} but got shape ${o}.`)}}if(r.shape!=null)for(let o=0;o<r.shape.length;++o){let i=r.shape[o],l=s.shape[o];if(i!=null&&l!=null&&i!==l)throw new G(`Input ${n} is incompatible with layer ${this.name}: expected shape=${r.shape}, found shape=${s.shape}.`)}}}call(e,t){return e}invokeCallHook(e,t){this._callHook!=null&&this._callHook(e,t)}setCallHook(e){this._callHook=e}clearCallHook(){this._callHook=null}apply(e,t){t=t||{},this.assertNotDisposed();let n=yt(e),s=!0;for(let a of n)if(!(a instanceof Vs)){s=!1;break}let r=!0;for(let a of n)if(a instanceof Vs){r=!1;break}if(s===r)throw new G("Arguments to apply() must be all SymbolicTensors or all Tensors");return Uo(this.name,()=>{if(!this.built){this.assertInputCompatibility(e);let a=[];for(let o of yt(e))a.push(o.shape);this.build($n(a)),this.built=!0,this.initialWeights&&this.setWeights(this.initialWeights),this._refCount===null&&r&&(this._refCount=1)}if(this.assertInputCompatibility(e),r){let a=this.call(e,t),o=yt(a),i=[];for(let l of o)n.indexOf(l)!==-1&&(l=l.clone()),i.push(l);if(a=$n(i),this.activityRegularizer!=null)throw new Oe("Layer invocation in the presence of activity regularizer(s) is not supported yet.");return a}else{let a=pP(e),o=this.computeOutputShape(a),i,l=fP(e);if(this.warnOnIncompatibleInputShape(Array.isArray(e)?a[0]:a),o!=null&&o.length>0&&Array.isArray(o[0])?i=o.map((u,c)=>new Vs(l,u,this,yt(e),t,this.name,c)):i=new Vs(l,o,this,yt(e),t,this.name),this.addInboundNode(e,i,null,null,a,o,t),this._refCount++,this.activityRegularizer!=null)throw new Oe("Layer invocation in the presence of activity regularizer(s) is not supported yet.");return i}})}warnOnIncompatibleInputShape(e){if(this.batchInputShape!=null)if(e.length!==this.batchInputShape.length)console.warn(`The rank of the input tensor provided (shape: ${JSON.stringify(e)}) does not match that of the batchInputShape (${JSON.stringify(this.batchInputShape)}) of the layer ${this.name}`);else{let t=!1;this.batchInputShape.forEach((n,s)=>{n!=null&&e[s]!=null&&e[s]!==n&&(t=!0)}),t&&console.warn(`The shape of the input tensor (${JSON.stringify(e)}) does not match the expectation of layer ${this.name}: ${JSON.stringify(this.batchInputShape)}`)}}get outputShape(){if(this.inboundNodes==null||this.inboundNodes.length===0)throw new Cr(`The layer ${this.name} has never been called and thus has no defined output shape.`);let e=[];for(let t of this.inboundNodes){let n=JSON.stringify(t.outputShapes);e.indexOf(n)===-1&&e.push(n)}if(e.length===1){let t=this.inboundNodes[0].outputShapes;return Array.isArray(t)&&Array.isArray(t[0])&&t.length===1?t[0]:t}else throw new Cr(`The layer ${this.name} has multiple inbound nodes with different output shapes. Hence the notion of "output shape" is ill-defined for the layer.`)}countParams(){if(!this.built)throw new Ls(`You tried to call countParams() on ${this.name}, but the layer is not built yet. Build it first by calling build(batchInputShape).`);return Pp(this.weights)}build(e){this.built=!0}getWeights(e=!1){return CA(e?this.trainableWeights:this.weights)}setWeights(e){H(()=>{let t=this.weights;if(t.length!==e.length)throw new G(`You called setWeights(weights) on layer "${this.name}" with a weight list of length ${e.length}, but the layer was expecting ${t.length} weights. Provided weights: ${e}...`);if(t.length===0)return;let n=[],s=CA(t);for(let r=0;r<s.length;++r){let a=s[r],o=t[r],i=e[r];if(!w.arraysEqual(a.shape,i.shape))throw new G(`Layer weight shape ${a.shape} not compatible with provided weight shape ${i.shape}`);n.push([o,i])}TA(n)})}addWeight(e,t,n,s,r,a,o){if(this._addedWeightNames.indexOf(e)!==-1)throw new G(`Duplicate weight name ${e} for layer ${this.name}`);this._addedWeightNames.push(e),n==null&&(n="float32"),this.fastWeightInitDuringBuild&&(s=wt("zeros"));let i=s.apply(t,n),l=new S3(i,n,e,a,o);return i.dispose(),r!=null&&this.addLoss(()=>r.apply(l.read())),a==null&&(a=!0),a?this._trainableWeights.push(l):this._nonTrainableWeights.push(l),l}setFastWeightInitDuringBuild(e){this.fastWeightInitDuringBuild=e}addLoss(e){e==null||Array.isArray(e)&&e.length===0||(e=yt(e),this._losses!==void 0&&this._losses!==null&&this.losses.push(...e))}computeOutputShape(e){return e}computeMask(e,t){if(!this.supportsMasking){if(t!=null)if(Array.isArray(t))t.forEach(n=>{if(n!=null)throw new TypeError(`Layer ${this.name} does not support masking, but was passed an inputMask.`)});else throw new TypeError(`Layer ${this.name} does not support masking, but was passed an inputMask.`);return null}return t}addInboundNode(e,t,n,s,r,a,o=null){let i=yt(e);t=yt(t),n=yt(n),s=yt(s),r=Op(r),a=Op(a);let l=[],u=[],c=[];for(let d of i)l.push(d.sourceLayer),u.push(d.nodeIndex),c.push(d.tensorIndex);new Mp({outboundLayer:this,inboundLayers:l,nodeIndices:u,tensorIndices:c,inputTensors:i,outputTensors:t,inputMasks:n,outputMasks:s,inputShapes:r,outputShapes:a},o);for(let d=0;d<t.length;d++)t[d].sourceLayer=this,t[d].nodeIndex=this.inboundNodes.length-1,t[d].tensorIndex=d}getConfig(){let e={name:this.name,trainable:this.trainable};return this.batchInputShape!=null&&(e.batchInputShape=this.batchInputShape),this.dtype!=null&&(e.dtype=this.dtype),e}disposeWeights(){return this.weights.forEach(e=>e.dispose()),this.weights.length}assertNotDisposed(){if(this._refCount===0)throw new Error(`Layer '${this.name}' is already disposed.`)}dispose(){if(!this.built)throw new Error(`Cannot dispose Layer ${this.name} because it has not been built yet.`);if(this._refCount===null)throw new Error(`Cannot dispose Layer ${this.name} because it has not been used yet.`);this.assertNotDisposed();let e=0;return--this._refCount==0&&(e=this.disposeWeights()),{refCountAfterDispose:this._refCount,numDisposedVariables:e}}};function pP(e){e=yt(e);let t=[];for(let n of e)t.push(n.shape);return $n(t)}function fP(e){return"float32"}function C3(e,t,n){if((t==null||n!=null&&n>0)&&(t=e.sourceLayer,n=e.nodeIndex),t.inboundNodes.length===0)return[e];{let s=t.inboundNodes[n];if(s.inboundLayers.length===0)return s.inputTensors;{let r=[];for(let a=0;a<s.inboundLayers.length;a++){let o=s.inputTensors[a],i=s.inboundLayers[a],l=s.nodeIndices[a],u=C3(o,i,l);for(let c of u)r.indexOf(c)===-1&&r.push(c)}return r}}}var Gl=class extends Ze{constructor(e){super({dtype:e.dtype,name:e.name!=null?e.name:Fp("input").toString()});if(e.batchSize==null&&(e.batchSize=null),e.sparse==null&&(e.sparse=!1),this.trainable=!1,this.built=!0,this.sparse=e.sparse,e.inputShape!=null&&e.batchInputShape!=null)throw new G("Only provide the inputShape OR batchInputShape argument to inputLayer, not both at the same time.");let t=e.batchInputShape;if(t==null){if(e.inputShape==null)throw new G("An InputLayer should be passed either a `batchInputShape` or an `inputShape`.");t=[e.batchSize].concat(e.inputShape)}else if(e.batchSize!=null)throw new G("Cannot specify batchSize if batchInputShape is specified when creating an InputLayer.");let n=e.dtype||"float32";this.batchInputShape=t,this.dtype=n,this.inputSpec=[{shape:t}];let s=new Vs(this.dtype,this.batchInputShape,this,[],{},this.name);s.nodeIndex=0,s.tensorIndex=0,new Mp({outboundLayer:this,inboundLayers:[],nodeIndices:[],tensorIndices:[],inputTensors:[s],outputTensors:[s],inputMasks:[null],outputMasks:[null],inputShapes:[t],outputShapes:[t]})}apply(e,t){throw new G(`Cannot pass any input to an InputLayer's apply() method. InputLayer name: ${this.name}`)}dispose(){return{refCountAfterDispose:this._refCount,numDisposedVariables:0}}getConfig(){return{batchInputShape:this.batchInputShape,dtype:this.dtype,sparse:this.sparse,name:this.name}}};Gl.className="InputLayer";oe.registerClass(Gl);function T3(e){if(e.batchShape==null&&e.shape==null)throw new Error("Please provide to Input either a `shape` or a `batchShape` argument. Note that `shape` does not include the batch dimension.");if(e.batchShape!=null&&e.shape!=null)throw new G("Please provide either a `shape` or `batchShape` argument to Input, but not both.");let t=e.batchShape;e.shape!=null&&t==null&&(t=[null].concat(e.shape));let n=e.dtype;return n==null&&(n="float32"),new Gl({batchInputShape:t,name:e.name,dtype:n,sparse:e.sparse}).inboundNodes[0].outputTensors[0]}async function aa(e){if(e==null)return;let t=[],n=[],s=[];for(let r in e){let a=e[r];if(typeof a!="number"){let o=a;t.push(o.data()),n.push(r),s.push(o)}}if(t.length>0){let r=await Promise.all(t);for(let a=0;a<r.length;++a)e[n[a]]=r[a][0];K(s)}}function N3(e){if(e!=null)for(let t in e){let n=e[t];typeof n!="number"&&n.dispose()}}var E3;(function(e){e[e.SILENT=0]="SILENT",e[e.VERBOSE=1]="VERBOSE"})(E3||(E3={}));var mP=125,jl=class{constructor(){this.validationData=null}setParams(e){this.params=e}async onEpochBegin(e,t){}async onEpochEnd(e,t){}async onBatchBegin(e,t){}async onBatchEnd(e,t){}async onTrainBegin(e){}async onTrainEnd(e){}setModel(e){}},R3=class{constructor(e,t=10){e==null&&(e=[]),this.callbacks=e,this.queueLength=t}append(e){this.callbacks.push(e)}setParams(e){for(let t of this.callbacks)t.setParams(e)}setModel(e){for(let t of this.callbacks)t.setModel(e)}async onEpochBegin(e,t){t==null&&(t={});for(let n of this.callbacks)await n.onEpochBegin(e,t)}async onEpochEnd(e,t){t==null&&(t={});for(let n of this.callbacks)await n.onEpochEnd(e,t)}async onBatchBegin(e,t){t==null&&(t={});for(let n of this.callbacks)await n.onBatchBegin(e,t)}async onBatchEnd(e,t){t==null&&(t={});for(let n of this.callbacks)await n.onBatchEnd(e,t)}async onTrainBegin(e){e==null&&(e={});for(let t of this.callbacks)await t.onTrainBegin(e)}async onTrainEnd(e){e==null&&(e={});for(let t of this.callbacks)await t.onTrainEnd(e)}},gP=class extends jl{constructor(){super()}async onEpochBegin(e){this.seen=0,this.totals={}}async onBatchEnd(e,t){t==null&&(t={});let n=t.size==null?0:t.size;this.seen+=n;for(let s in t){let r=t[s];if(typeof r=="number")this.totals.hasOwnProperty(s)||(this.totals[s]=0),this.totals[s]=this.totals[s]+r*n;else{let a;s in this.totals?a=this.totals[s]:this.totals[s]=0;let o=H(()=>ae(this.totals[s],L(r,n)));this.totals[s]=o,a!=null&&a.dispose()}}}async onEpochEnd(e,t){if(t!=null)for(let n of this.params.metrics)this.totals[n]!=null&&(typeof this.totals[n]=="number"?t[n]=this.totals[n]/this.seen:H(()=>{let s=L(de(1,this.seen),this.totals[n]);t[n]=s,this.totals[n].dispose(),Jt(t[n])}))}},_3=class extends jl{async onTrainBegin(e){this.epoch=[],this.history={}}async onEpochEnd(e,t){t==null&&(t={}),this.epoch.push(e);for(let n in t)this.history[n]==null&&(this.history[n]=[]),this.history[n].push(t[n])}async syncData(){let e=[],t=[],n=[];for(let r in this.history){let a=this.history[r];for(let o=0;o<a.length;++o)if(typeof a[o]!="number"){let i=a[o];e.push(i.data()),t.push(r),n.push(o)}}let s=await Promise.all(e);for(let r=0;r<s.length;++r)this.history[t[r]][n[r]].dispose(),this.history[t[r]][n[r]]=s[r][0]}},D3=class extends jl{constructor(e,t){super();if(this.currentEpoch=0,this.yieldEvery=t||"auto",this.yieldEvery==="auto"&&(this.yieldEvery=mP),this.yieldEvery==="never"&&e.onYield!=null)throw new Error("yieldEvery is `never` but you provided an `onYield` callback. Either change `yieldEvery` or remove the callback");w.isNumber(this.yieldEvery)&&(this.maybeWait=kO(this.maybeWait.bind(this),this.yieldEvery)),this.trainBegin=e.onTrainBegin,this.trainEnd=e.onTrainEnd,this.epochBegin=e.onEpochBegin,this.epochEnd=e.onEpochEnd,this.batchBegin=e.onBatchBegin,this.batchEnd=e.onBatchEnd,this.yield=e.onYield}async maybeWait(e,t,n){let s=[];this.yield!=null&&(await aa(n),s.push(this.yield(e,t,n))),s.push(vp()),await Promise.all(s)}async onEpochBegin(e,t){this.currentEpoch=e,this.epochBegin!=null&&(await aa(t),await this.epochBegin(e,t))}async onEpochEnd(e,t){let n=[];this.epochEnd!=null&&(await aa(t),n.push(this.epochEnd(e,t))),this.yieldEvery==="epoch"&&n.push(vp()),await Promise.all(n)}async onBatchBegin(e,t){this.batchBegin!=null&&(await aa(t),await this.batchBegin(e,t))}async onBatchEnd(e,t){let n=[];this.batchEnd!=null&&(await aa(t),n.push(this.batchEnd(e,t))),this.yieldEvery==="batch"?n.push(vp()):w.isNumber(this.yieldEvery)&&n.push(this.maybeWait(this.currentEpoch,e,t)),await Promise.all(n)}async onTrainBegin(e){this.trainBegin!=null&&(await aa(e),await this.trainBegin(e))}async onTrainEnd(e){this.trainEnd!=null&&(await aa(e),await this.trainEnd(e))}};function $3(e,t){return e==null&&(e={}),e instanceof jl?[e]:Array.isArray(e)&&e[0]instanceof jl?e:yt(e).map(s=>new D3(s,t))}var Rs=class{constructor(){}static registerCallbackConstructor(e,t){w.assert(e>=0&&Number.isInteger(e),()=>`Verbosity level is expected to be an integer >= 0, but got ${e}`),Rs.checkForDuplicate(t),Rs.constructors[e]==null&&(Rs.constructors[e]=[]),Rs.constructors[e].push(t)}static checkForDuplicate(e){for(let t in Rs.constructors)Rs.constructors[+t].forEach(s=>{if(s===e)throw new G("Duplicate callback constructor.")})}static clear(){Rs.constructors={}}static createCallbacks(e){let t=[];for(let n in Rs.constructors){let s=+n;e>=s&&t.push(...Rs.constructors[s])}return t.map(n=>new n)}};Rs.constructors={};function F3(e,t,n,s,r,a,o,i,l){let u=new _3,c=[new gP,...Rs.createCallbacks(t)];e!=null&&c.push(...e),c.push(u);let d=new R3(c);return d.setParams({epochs:n,initialEpoch:s,samples:r,steps:a,batchSize:o,verbose:t,doValidation:i,metrics:l}),{callbackList:d,history:u}}function Us(e,t={},n=!1){return bc(e,oe.SerializationMap.getMap().classNameMap,t,"layer",n)}function zp(e,t){return H(()=>{e.dtype!=="float32"&&(e=ce(e,"float32"));let n=ve(Ic(e),t,!0),s=Pl(n.shape,jt()),r=hn(kr(n,s));return de(e,r)})}function Go(e,t){return H(()=>_t(Ic(ge(t,e)),-1))}function Lp(e,t){return H(()=>_t(Ht(ge(t,e)),-1))}function ql(e,t){return H(()=>{let n=ge(e,t),s=Gn(Ht(e),jt(),Number.MAX_VALUE),r=Ht(de(n,s));return L(100,_t(r,-1))})}function AP(e,t){return H(()=>{let n=Gn(t,jt(),Number.MAX_VALUE),s=ds(ae(1,n)),r=Gn(e,jt(),Number.MAX_VALUE),a=ds(ae(1,r));return _t(Ic(ge(s,a)),-1)})}function yP(e,t){return H(()=>{let n=kr(0,ge(1,L(e,t)));return _t(Ic(n),-1)})}function xP(e,t){return H(()=>{let n=kr(0,ge(1,L(e,t)));return _t(n,-1)})}function bP(e,t){return H(()=>{let n=ve(L(e,t),-1),s=hs(L(ge(1,e),t),-1);return kr(0,ae(1,ge(s,n)))})}function vP(e,t){return H(()=>{let n=Math.log(2),s=ge(t,e),r=ge(ae(s,zl(L(-2,s))),n);return _t(r,-1)})}function Cc(e,t,n=!1){return H(()=>{if(n)t=op(t);else{let s=ve(t,t.shape.length-1,!0);t=de(t,s)}return t=Gn(t,jt(),1-jt()),Tt(ve(L(ce(e,"float32"),ds(t)),t.shape.length-1))})}function Bp(e,t,n=!1){return H(()=>{let s=ce(hc(zO(e)),"int32");t=Gn(t,jt(),1-jt());let r=t.shape,a=U(ic(s,r[r.length-1]),r);return Cc(a,t,n)})}function wP(e,t){if(!w.arraysEqual(e.shape,t.shape))throw new G(`logits and labels must have the same shape, but got shapes ${JSON.stringify(e.shape)} and ${JSON.stringify(t.shape)}`);return H(()=>{let n=sr(t),s=Tt(Ht(t));return ae(ge(n,L(t,e)),Zh(cs(s)))})}function Wp(e,t){return H(()=>{let n;return n=Gn(t,jt(),1-jt()),n=ds(de(n,ge(1,n))),_t(wP(e,n),-1)})}function kP(e,t){return H(()=>{let n=Gn(e,jt(),1),s=Gn(t,jt(),1);return ve(L(e,ds(de(n,s))),-1)})}function IP(e,t){return H(()=>{let n=ds(ae(jt(),t));return _t(ge(t,L(e,n)),-1)})}function NA(e,t){return H(()=>{let n=zp(e,-1),s=zp(t,-1),r=L(n,s);return Tt(ve(r,-1))})}var Vp={meanSquaredError:Go,meanAbsoluteError:Lp,meanAbsolutePercentageError:ql,meanSquaredLogarithmicError:AP,squaredHinge:yP,hinge:xP,categoricalHinge:bP,logcosh:vP,categoricalCrossentropy:Cc,sparseCategoricalCrossentropy:Bp,binaryCrossentropy:Wp,kullbackLeiblerDivergence:kP,poisson:IP,cosineProximity:NA};function EA(e){if(typeof e=="string"){if(e in Vp)return Vp[e];let t=`Unknown loss ${e}`;throw e.toLowerCase().includes("softmaxcrossentropy")&&(t=`Unknown loss ${e}. Use "categoricalCrossentropy" as the string name for tf.losses.softmaxCrossEntropy`),new G(t)}else return e}function RA(e,t){return H(()=>{let n=L(.5,ps(t)),s=kp(jn(t,n),e.dtype);return _t(us(e,s),-1)})}function _A(e,t){return H(()=>kp(us(er(e,-1),er(t,-1)),"float32"))}function O3(e,t){return H(()=>ce(ve(Ps(us(e,1),us(t,1))),"float32"))}function SP(e,t){return H(()=>ce(ve(Ps(us(e,1),us(t,0))),"float32"))}function CP(e,t){return H(()=>ce(ve(Ps(us(e,0),us(t,1))),"float32"))}function P3(e,t){return H(()=>{let n=O3(e,t),s=CP(e,t),r=ae(n,s);return ce(bn(jn(r,0),de(n,r),0),"float32")})}function TP(e,t){return H(()=>{let n=O3(e,t),s=SP(e,t),r=ae(n,s);return ce(bn(jn(r,0),de(n,r),0),"float32")})}function M3(e,t){return Wp(e,t)}function z3(e,t){return e.rank===t.rank&&(e=lt(e,[e.rank-1])),t=er(t,-1),t.dtype!==e.dtype&&(t=ce(t,e.dtype)),ce(us(e,t),"float32")}var NP=Go,EP=Go,RP=Lp,_P=Lp,DP=ql,$P=ql,DA=Cc,FP=NA,L3=Bp,Up={binaryAccuracy:RA,categoricalAccuracy:_A,precision:P3,categoricalCrossentropy:DA,sparseCategoricalCrossentropy:L3,mse:NP,MSE:EP,mae:RP,MAE:_P,mape:DP,MAPE:$P,cosine:FP};function OP(e){if(typeof e=="string"&&e in Up)return Up[e];if(typeof e!="string"&&e!=null)return e;throw new G(`Unknown metric ${e}`)}function Hp(e){if(ar(e!==null,`Unknown LossOrMetricFn ${e}`),typeof e=="string")return e;{let t;for(let n of Object.keys(Vp))if(Vp[n]===e){t=n;break}if(t!==void 0)return t;for(let n of Object.keys(Up))if(Up[n]===e){t=n;break}return t!==void 0?t:e.name}}function PP(e){let t={Adagrad:()=>Lo.adagrad(.01),Adadelta:()=>Lo.adadelta(1,.95,jt()),Adam:()=>Lo.adam(.001,.9,.999,jt()),Adamax:()=>Lo.adamax(.002,.9,.999,jt(),0),RMSProp:()=>Lo.rmsprop(.001,.9,0,jt()),SGD:()=>Lo.sgd(.01)};if(t.adagrad=t.Adagrad,t.adadelta=t.Adadelta,t.adam=t.Adam,t.adamax=t.Adamax,t.rmsprop=t.RMSProp,t.sgd=t.SGD,e in t)return t[e]();throw new G(`Unknown Optimizer ${e}`)}var B3=1*1024*1024;function W3(e,t,n=!1){if(e==null||typeof e!="object"||Object.getPrototypeOf(e)!==Object.prototype||!$A(e))throw new Error("User-defined metadata is expected to be a JSON object, but is not.");if(n){let s=JSON.stringify(e);s.length>B3&&console.warn(`User-defined metadata of model "${t}" is too large in size (length=${s.length} when serialized). It is not recommended to store such large objects in user-defined metadata. Please make sure its serialized length is <= ${B3}.`)}}function $A(e){if(e===null)return!0;if(typeof e=="object")if(Object.getPrototypeOf(e)===Object.prototype){let t=Object.keys(e);for(let n of t)if(typeof n!="string"||!$A(e[n]))return!1;return!0}else if(Array.isArray(e)){for(let t of e)if(!$A(t))return!1;return!0}else return!1;else{let t=typeof e;return t==="string"||t==="number"||t==="boolean"}}function MP(e,t,n,s=console.log){let r=LP(e),a=["Layer (type)","Output shape","Param #"];r?(t=t||65,n=n||[.45,.85,1]):(t=t||98,n=n||[.33,.55,.67,1]),n[n.length-1]<=1&&(n=n.map(c=>Math.floor(t*c)));let o;if(!r){a.push("Receives inputs"),o=[];for(let c in e.nodesByDepth)o.push(...e.nodesByDepth[c])}s("_".repeat(t)),Gp(a,n,s),s("=".repeat(t));let i=e.layers;for(let c=0;c<i.length;++c)r?BP(i[c],n,s):WP(i[c],n,o,s),s((c===i.length-1?"=":"_").repeat(t));e.checkTrainableWeightsConsistency();let l=zP(e),u=Pp(e.nonTrainableWeights);s(`Total params: ${l+u}`),s(`Trainable params: ${l}`),s(`Non-trainable params: ${u}`),s("_".repeat(t))}function zP(e){let t;return e.collectedTrainableWeights!=null?t=Pp(e.collectedTrainableWeights):t=Pp(e.trainableWeights),t}function LP(e){let t=!0,n=[],s=[];for(let r in e.nodesByDepth)n.push(e.nodesByDepth[r]);for(let r of n){if(r.length>1||r.length===1&&r[0].inboundLayers.length>1){t=!1;break}s.push(...r)}if(t)for(let r of e.layers){let a=!1;for(let o of r.inboundNodes)if(s.indexOf(o)!==-1)if(a){t=!1;break}else a=!0;if(!t)break}return t}function Gp(e,t,n=console.log){let s="";for(let r=0;r<e.length;++r)r>0&&(s=s.slice(0,s.length-1)+" "),s+=e[r],s=s.slice(0,t[r]),s+=" ".repeat(t[r]-s.length);n(s)}function BP(e,t,n){let s;try{s=JSON.stringify(e.outputShape)}catch(i){s="multiple"}let r=e.name,a=e.getClassName(),o=[`${r} (${a})`,s,e.countParams().toString()];Gp(o,t,n)}function WP(e,t,n,s){let r;try{r=JSON.stringify(e.outputShape)}catch(c){r="multiple"}let a=[];for(let c of e.inboundNodes)if(!(n!=null&&n.length>0&&n.indexOf(c)===-1))for(let d=0;d<c.inboundLayers.length;++d){let h=c.inboundLayers[d].name,p=c.nodeIndices[d],f=c.tensorIndices[d];a.push(`${h}[${p}][${f}]`)}let o=e.name,i=e.getClassName(),l=a.length===0?"":a[0],u=[`${o} (${i})`,r,e.countParams().toString(),l];Gp(u,t,s);for(let c=1;c<a.length;++c)Gp(["","","",a[c]],t,s)}function V3(e,t,n){return(e==="inboundNodes"||e==="outputLayers"||e==="inputLayers")&&t===0&&typeof n=="string"}function Tc(e,t){if(e===null)return null;if(typeof e=="string")return Wo(e);if(typeof e=="number"||typeof e=="boolean")return e;if(e instanceof Array){let n=[],s=e.length;for(let r=0;r<s;++r){let a=e[r];V3(t,r,a)?n.push(a):n.push(Tc(a,t))}return n}else{let n={};for(let s of Object.keys(e)){let r=e[s];if(s==="name"&&typeof r=="string")n[s]=r;else{let a=Wo(s);n[a]=Tc(r,a)}}return n}}function FA(e,t){if(e==null)return null;if(typeof e=="string")return Tr(e);if(typeof e=="number"||typeof e=="boolean")return e;if(e instanceof Array){let n=[],s=e.length;for(let r=0;r<s;++r){let a=e[r];V3(t,r,a)?n.push(a):n.push(FA(a,t))}return n}else{let n={};for(let s of Object.keys(e)){let r=e[s],a=Tr(s);(s==="name"||s==="className")&&typeof r=="string"?n[a]=r:n[a]=FA(r,s)}return n}}var OA="3.9.0";function VP(e,t){if(e.dtype==null||e.dtype===t.dtype)return t;try{return ce(t,e.dtype)}catch(n){throw new G(`The dtype of the feed (${t.dtype}) can not be cast to the dtype of the key '${e.name}' (${e.dtype}).`)}}var jo=class{constructor(e){if(this.id2Value={},this.id2Mask={},this.name2Id={},e instanceof jo)for(let t in e.id2Value)this.id2Value[t]=e.id2Value[t],t in e.id2Mask&&(this.id2Mask[t]=e.id2Mask[t]);else{if(e==null)return;for(let t of e)this.add(t.key,t.value)}}add(e,t,n){if(this.id2Value[e.id]==null)this.id2Value[e.id]=VP(e,t),this.name2Id[e.name]=e.id,n!=null&&(this.id2Mask[e.id]=n);else throw new G(`Duplicate key: name=${e.name}, id=${e.id}`);return this}addFeed(e){this.add(e.key,e.value)}hasKey(e){return this.id2Value[e.id]!=null}names(){return Object.keys(this.name2Id)}getValue(e){if(e instanceof Vs){if(this.id2Value[e.id]==null)throw new G(`Nonexistent key: ${e.name}`);return this.id2Value[e.id]}else{let t=this.name2Id[e];if(t==null)throw new G(`Feed dict has no SymbolicTensor name: ${e}`);return this.id2Value[t]}}getMask(e){if(e instanceof Vs){if(this.id2Value[e.id]==null)throw new G(`Nonexistent key: ${e.name}`);return this.id2Mask[e.id]}else{let t=this.name2Id[e];if(t==null)throw new G(`Feed dict has no SymbolicTensor name: ${e}`);return this.id2Mask[t]}}disposeMasks(){this.id2Mask!=null&&K(this.id2Mask)}},PA={},U3={};function Nc(e,t,n,s){let r=n==null?!1:n.training,a=Array.isArray(e),o=a?e:[e],i=o.map(f=>f.name),l=[],u=t.names();for(let f of i)u.indexOf(f)!==-1?l.push(t.getValue(f)):l.push(null);s!=null&&(s.maxNumTensors=-1/0,s.minNumTensors=1/0);let c=i.join(",")+"|"+t.names().join(","),d,h;if(PA[c]==null){let f=UP(o,t);d=f.sorted,h=f.recipientCounts,PA[c]=d,U3[c]=h}d=PA[c],h={},r||Object.assign(h,U3[c]);let p=new jo(t);for(let f=0;f<d.length;++f){if(s!=null){let _=Wh().numTensors;_>s.maxNumTensors&&(s.maxNumTensors=_),_<s.minNumTensors&&(s.minNumTensors=_)}let m=d[f],g=m.sourceLayer;if(g instanceof Gl)continue;let A=[],y=[],x=[],b=!1;for(let _ of m.inputs){let O=p.getValue(_),E=p.getMask(_);A.push(O),y.push(E),E!=null&&(b=!0),r||(h[_.name]--,h[_.name]===0&&!t.hasKey(_)&&i.indexOf(_.name)===-1&&!O.isDisposed&&_.sourceLayer.stateful!==!0&&x.push(O))}b&&(n=n||{},n.mask=y[0]);let v=yt(g.apply(A,n)),k=null;g.supportsMasking&&(k=g.computeMask(A,y));let S=GP(m),C=Array.isArray(S)?S:[S];for(let _=0;_<C.length;++_){p.hasKey(C[_])||p.add(C[_],v[_],Array.isArray(k)?k[0]:k);let O=i.indexOf(C[_].name);O!==-1&&(l[O]=v[_])}r||K(x)}return p.disposeMasks(),a?l:l[0]}function UP(e,t){w.assert(e!=null&&e.length>0,()=>"Expected at least one fetch, got none");let n=[],s={};if(e.length===1){let r=H3(e[0],t);n=r.sorted,s=r.recipientMap}else{let r=new Set;for(let a of e){let{sorted:o,recipientMap:i}=H3(a,t);for(let l of o)r.has(l.name)||(n.push(l),r.add(l.name));for(let l in i)s[l]==null&&(s[l]=new Set),i[l].forEach(u=>s[l].add(u))}}return{sorted:n,recipientCounts:HP(s)}}function HP(e){let t={};for(let n in e)t[n]=e[n].size;return t}function H3(e,t){let n=new Set,s=[],r={};for(let i of t.names())n.add(i);let a=[],o=[];for(a.push(e);a.length>0;){let i=a[a.length-1];if(n.has(i.name)){a.pop();continue}let l=o[o.length-1]===a.length-1;if(i.inputs.length===0||l)a.pop(),s.push(i),n.add(i.name),l&&o.pop();else{o.push(a.length-1);for(let u of i.inputs)r[u.name]==null&&(r[u.name]=new Set),r[u.name].add(i.name),!n.has(u.name)&&a.push(u)}}return{sorted:s,recipientMap:r}}function GP(e){let t;if(e.sourceLayer.inboundNodes.length===1)t=e.sourceLayer.output;else{let n=null;for(let s=0;s<e.sourceLayer.inboundNodes.length;++s)for(let r of e.sourceLayer.inboundNodes[s].outputTensors)if(r.id===e.id){n=s;break}t=e.sourceLayer.getOutputAt(n)}return t}var ir=class extends Ze{constructor(e){super({});if(this.containerNodes=new Set,this.name=e.name,this.name==null){let A=this.getClassName().toLowerCase();this.name=Fp(A)}if(this.supportsMasking=!1,this.trainable_=!0,Array.isArray(e.inputs)?this.inputs=e.inputs.slice():this.inputs=[e.inputs],Array.isArray(e.outputs)?this.outputs=e.outputs.slice():this.outputs=[e.outputs],na(this.inputs).length!==this.inputs.length)throw new G(`The list of inputs passed to the model is redundant. All inputs should only appear once. Found: ${this.inputs.map(A=>A.name)}`);na(this.outputs).length!==this.outputs.length&&console.warn(`The list of outputs passed to the model is redundant. All outputs should only appear once. Found: ${this.outputs.map(A=>A.name)}`),this.inputLayers=[],this.inputLayersNodeIndices=[],this.inputLayersTensorIndices=[],this.outputLayers=[],this.outputLayersNodeIndices=[],this.outputLayersTensorIndices=[],this.layers=[],this.internalContainerRefs=[];for(let A of this.outputs){let y=A.sourceLayer,x=A.nodeIndex,b=A.tensorIndex;this.outputLayers.push(y),this.outputLayersNodeIndices.push(x),this.outputLayersTensorIndices.push(b)}for(let A of this.inputs){let y=A.sourceLayer,x=A.nodeIndex,b=A.tensorIndex;ar(x===0,"input layer has >1 nodes"),ar(b===0,"input layer has >1 tensors"),this.inputLayers.push(y),this.inputLayersNodeIndices.push(x),this.inputLayersTensorIndices.push(b)}this.inputNames=[],this.outputNames=[],this.feedInputShapes=[],this.feedInputNames=[],this.feedOutputNames=[];for(let A=0;A<this.inputLayers.length;A++){let y=this.inputLayers[A];if(!(y instanceof Gl))throw new TypeError(`Input layers to a LayersModel must be InputLayer objects. Received inputs: ${e.inputs}. Input ${A} (0-based) originates from layer type ${y.getClassName()}.`);this.inputNames.push(y.name),this.feedInputShapes.push(y.batchInputShape),this.feedInputNames.push(y.name)}for(let A of this.outputLayers)this.outputNames.push(A.name);this.internalInputShapes=this.inputs.map(A=>A.shape),this.internalOutputShapes=this.outputs.map(A=>A.shape);let t={},n={},s={},r={},a={},o=[],i=(A,y,x,b,v,k)=>{(b==null||v==null||k==null)&&(b=A.sourceLayer,v=A.nodeIndex,k=A.tensorIndex);let S=b.inboundNodes[v];if(x.indexOf(S)!==-1)throw new Ls(`The tensor ${A.name} at layer "${b.name}" is part of a cycle.`);if(y.indexOf(S)!==-1)return;this.containerNodes.add(ir.nodeKey(b,v)),b.id in a||(a[b.id]=Object.keys(a).length),x.indexOf(S)===-1&&x.push(S);let C=S.inboundLayers.length;for(let _=0;_<C;_++){let O=S.inputTensors[_],E=S.inboundLayers[_],R=S.nodeIndices[_],T=S.tensorIndices[_];i(O,y,x,E,R,T)}for(y.push(S);x.indexOf(S)>=0;)x.splice(x.indexOf(S),1);o.push(S)},l=[],u=[];for(let A of this.outputs)i(A,l,u);let c=o.slice().reverse();for(let A of c){n[A.id]=A,A.id in t||(t[A.id]=0);let y=t[A.id],x=s[A.outboundLayer.id]==null?0:s[A.outboundLayer.id];y=Math.max(y,x),s[A.outboundLayer.id]=y,r[A.outboundLayer.id]=A.outboundLayer,t[A.id]=y;for(let b=0;b<A.inboundLayers.length;b++){let v=A.inboundLayers[b],k=A.nodeIndices[b],S=v.inboundNodes[k],C=t[S.id]==null?0:t[S.id];t[S.id]=Math.max(y+1,C),n[S.id]=S}}let d={};for(let A in t){let y=t[A];y in d||(d[y]=[]),d[y].push(n[A])}let h={};for(let A in s){let y=s[A];y in h||(h[y]=[]),h[y].push(r[A])}let p=Object.keys(h).map(A=>parseInt(A,10)).sort(wp);this.layers=[];for(let A of p){let y=h[A];y.sort((x,b)=>{let v=a[x.id],k=a[b.id];return v<k?-1:v>k?1:0});for(let x of y)x instanceof ir&&this.internalContainerRefs.push(x),this.layers.push(x)}this.layersByDepth=h,p=Object.keys(d).map(A=>parseInt(A,10)).sort(wp);let f=this.inputs.slice(),m=[];for(let A of p)for(let y of d[A]){let x=y.outboundLayer;if(x!=null){for(let b of y.inputTensors)if(f.indexOf(b)===-1)throw new Ls(`Graph disconnected: cannot obtain value for tensor ${b} at layer "${x.name}". The following previous layers were accessed without issue: ${m}`);for(let b of y.outputTensors)f.push(b);m.push(x.name)}}this.nodesByDepth=d;let g=this.layers.map(A=>A.name);for(let A of g){let y=g.filter(x=>x===A).length;if(y!==1)throw new Ls(`The name "${A}" is used ${y} times in the model. All layer names should be unique. Layer names: `+JSON.stringify(g))}this.outboundNodes=[],this.inboundNodes=[],new Mp({outboundLayer:this,inboundLayers:[],nodeIndices:[],tensorIndices:[],inputTensors:this.inputs,outputTensors:this.outputs,inputMasks:this.inputs.map(A=>null),outputMasks:this.outputs.map(A=>null),inputShapes:this.inputs.map(A=>A.shape),outputShapes:this.outputs.map(A=>A.shape)}),this.built=!0,this._refCount=1}assertNotDisposed(){if(this._refCount===0)throw new Error(`Container '${this.name}' is already disposed.`)}dispose(){this.assertNotDisposed();let e={refCountAfterDispose:null,numDisposedVariables:0};if(--this._refCount==0){for(let t of this.layers)e.numDisposedVariables+=t.dispose().numDisposedVariables;for(let t of this.internalContainerRefs)e.numDisposedVariables+=t.dispose().numDisposedVariables}return e.refCountAfterDispose=this._refCount,e}get trainable(){return this.trainable_}set trainable(e){this.layers.forEach(t=>{t._trainableWeights.forEach(n=>n.trainable=e)}),this.trainable_=e}get trainableWeights(){if(this._trainableWeights.length>0)throw new G("Container instance unexpectedly contains _trainableWeights.The trainable weights of a Container are a union of the trainable weights of its consituent Layers. Its own _trainableWeights must remain an empty Array.");if(!this.trainable)return[];let e=[];for(let t of this.layers)e=e.concat(t.trainableWeights);return e}get nonTrainableWeights(){let e=[];for(let t of this.layers)e.push(...t.nonTrainableWeights);if(!this.trainable){let t=[];for(let n of this.layers)t.push(...n.trainableWeights);return t.concat(e)}return e}get weights(){return this.trainableWeights.concat(this.nonTrainableWeights)}loadWeights(e,t=!0){let n={},s=0;for(let a of this.layers)for(let o of a.weights){if(n[o.originalName]!=null)throw new G(`Duplicate weight name: ${o.originalName}`);n[o.originalName]=o,s++}let r=[];for(let a in e){let o=a;if(n[a]==null){let i=a.split("/");o=i.slice(0,-2).concat([i[i.length-1]]).join("/")}if(n[o]!=null)r.push([n[o],e[a]]);else if(t)throw new G(`Provided weight data has no target variable: ${a}`);delete n[o]}if(t){let a=[];for(let o in n)a.push(o);if(a.length>0)throw new G(`${a.length} of ${s} weights are not set: ${a}`)}TA(r)}updatedConfig(){let e=this.getConfig(),t={};return t.className=this.getClassName(),t.config=e,t.kerasVersion=`tfjs-layers ${OA}`,t.backend="TensorFlow.js",t}toJSON(e,t=!0){let n=FA(this.updatedConfig());return t?JSON.stringify(n):n}call(e,t){return H(()=>{e=yt(e);let n=new jo;for(let s=0;s<this.inputs.length;++s)n.add(this.inputs[s],e[s]);return Nc(this.outputs,n,t)})}computeMask(e,t){return H(()=>{e=yt(e);let n;return t==null?n=Bo(null,e.length):n=yt(t),this.runInternalGraph(e,n)[1]})}computeOutputShape(e){let t=Op(e);if(t.length!==this.inputLayers.length)throw new G(`Invalid inputShape argument ${e}: model has ${this.inputLayers.length} tensor inputs.`);let n={};for(let o=0;o<t.length;o++){let i=this.inputLayers[o],l=t[o],u=i.name+"_0_0";n[u]=l}let s=Object.keys(this.nodesByDepth).map(o=>parseInt(o,10)).sort(wp);if(s.length>1)for(let o of s){let i=this.nodesByDepth[o];for(let l of i){let u=l.outboundLayer;if(this.inputLayers.map(f=>f.id).indexOf(u.id)!==-1)continue;let c=[];for(let f=0;f<l.inboundLayers.length;f++){let m=l.inboundLayers[f],g=l.nodeIndices[f],A=l.tensorIndices[f],y=`${m.name}_${g}_${A}`,x=n[y];c.push(x)}let d=u.computeOutputShape($n(c)),h=Op(d),p=u.inboundNodes.indexOf(l);for(let f=0;f<h.length;f++){let m=`${u.name}_${p}_${f}`;n[m]=h[f]}}}let r=[],a=[];for(let o=0;o<this.outputLayers.length;o++){let i=this.outputLayers[o],l=this.outputLayersNodeIndices[o],u=this.outputLayersTensorIndices[o],c=`${i.name}_${l}_${u}`;a.push(c)}for(let o=0;o<a.length;o++){let i=a[o];ar(i in n),r.push(n[i])}return $n(r)}runInternalGraph(e,t){t==null&&(t=Bo(null,e.length));let n={};for(let i=0;i<this.inputs.length;++i){let l=this.inputs[i],u=e[i],c=t[i];n[l.id]=[u,c]}let s=Object.keys(this.nodesByDepth).map(i=>parseInt(i,10)).sort(wp);for(let i of s){let l=this.nodesByDepth[i];for(let u of l){let c=u.outboundLayer,d=u.inputTensors,h=u.outputTensors,p=new Array;for(let f of d)f.id in n&&p.push(n[f.id]);if(p.length===d.length){let f={},m,g,A,y;if(u.callArgs!=null&&(f=u.callArgs),p.length===1){let[x,b]=p[0];f.mask==null&&(f.mask=b),A=yt(c.call(x,f)),y=yt(c.computeMask(x,b)),m=[x],g=[b]}else m=p.map(x=>x[0]),g=p.map(x=>x[1]),f.mask==null&&(f.mask=g),A=yt(c.call(m,f)),y=yt(c.computeMask(m,g));if(c.activityRegularizer)throw new Oe("LayersModel invocation with concrete Tensor value(s) in the presence of activity regularizer(s) is not supported yet.");for(let x=0;x<h.length;++x){let b=h[x],v=A[x],k=y[x];n[b.id]=[v,k]}}}}let r=[],a=[],o=[];for(let i of this.outputs){ar(i.id in n,`Could not compute output ${i.name} : ${i.id}`);let[l,u]=n[i.id];o.push(l.shape),r.push(l),a.push(u)}return[r,a,o]}buildNodeConversionMap(e){let t={},n;for(let s of this.layers){n=s instanceof ir?1:0;for(let r=0;r<s.inboundNodes.length;r++){let a=ir.nodeKey(s,r);this.containerNodes.has(a)&&(t[a]=n,n+=1)}}return t}getLayer(e,t){if(t!=null){if(this.layers.length<=t)throw new G(`Was asked to retrieve layer at index ${t}, but model only has ${this.layers.length} layer(s).`);return this.layers[t]}else if(e==null)throw new G("Provide either a layer name or layer index");for(let n of this.layers)if(n.name===e)return n;throw new G(`No such layer: ${e}`)}calculateLosses(){return H(()=>{let e=[];for(let t of this.layers)for(let n=0;n<t.inboundNodes.length;++n){let s=ir.nodeKey(t,n);this.containerNodes.has(s)&&e.push(...t.calculateLosses())}return e})}getConfig(){let e={name:this.name},t=this.buildNodeConversionMap(this.layers),n=[];for(let a of this.layers){let o=a.getClassName(),i=a.getConfig(),l=[];for(let c=0;c<a.inboundNodes.length;c++){let d=a.inboundNodes[c],h=ir.nodeKey(a,c),p={};if(this.containerNodes.has(h)){if(d.callArgs)try{JSON.stringify(d.callArgs),p=d.callArgs}catch(f){console.warn(`Layer ${a.name} was passed non-serializable keyword arguments: ${d.callArgs}. They will not be included in the serialized model (and thus will be missing at deserialization time).`),p={}}if(d.inboundLayers.length>0){let f=[];for(let m=0;m<d.inboundLayers.length;m++){let g=d.inboundLayers[m],A=d.nodeIndices[m],y=d.tensorIndices[m],x=ir.nodeKey(g,A),b=t[x];b==null&&(b=0),f.push([g.name,b,y,p])}l.push(f)}}}let u={};u.name=a.name,u.className=o,u.config=i,u.inboundNodes=l,n.push(u)}e.layers=n;let s=[];for(let a=0;a<this.inputLayers.length;a++){let o=this.inputLayers[a],i=this.inputLayersNodeIndices[a],l=ir.nodeKey(o,i);if(!this.containerNodes.has(l))continue;let u=t[l];u==null&&(u=0);let c=this.inputLayersTensorIndices[a];s.push([o.name,u,c])}e.inputLayers=s;let r=[];for(let a=0;a<this.outputLayers.length;a++){let o=this.outputLayers[a],i=this.outputLayersNodeIndices[a],l=ir.nodeKey(o,i);if(!this.containerNodes.has(l))continue;let u=t[l];u==null&&(u=0);let c=this.outputLayersTensorIndices[a];r.push([o.name,u,c])}return e.outputLayers=r,e}static fromConfig(e,t,n={},s=!1){let r={},a={};function o(m,g){m.name in a?a[m.name].push(g):a[m.name]=[g]}function i(m,g){let A=[],y;for(let x of g){let b=x[0],v=x[1],k=x[2];if(y=x[3]==null?{}:x[3],!(b in r)){o(m,g);return}let S=r[b];if(S.inboundNodes.length<=v){o(m,g);return}let C=S.inboundNodes[v];A.push(C.outputTensors[k])}A.length>0&&m.apply($n(A),y)}function l(m){let g=m.name,A=Us(m,t.customObjects!=null?t.customObjects:{});A.setFastWeightInitDuringBuild(s),r[g]=A,m.inboundNodes.forEach(x=>{if(!(x instanceof Array))throw new G(`Corrupted configuration, expected array for nodeData: ${x}`);o(A,x)})}let u=t.name,c=t.layers;for(let m of c)l(m);for(;!wO(a);)for(let m of c){let g=r[m.name];if(g.name in a){let A=a[g.name];delete a[g.name];for(let y of A)i(g,y)}}let d=[],h=[],p=t.inputLayers;for(let m of p){let g=m[0],A=m[1],y=m[2];ar(g in r);let b=r[g].inboundNodes[A].outputTensors;d.push(b[y])}let f=t.outputLayers;for(let m of f){let g=m[0],A=m[1],y=m[2];ar(g in r);let b=r[g].inboundNodes[A].outputTensors;h.push(b[y])}return new e({inputs:d,outputs:h,name:u})}get stateful(){if(this._stateful)throw new G("Container instance unexpectedly has _stateful = true. The statefulness of a Container is determined by the Layers it contains. Its _stateful property must remain the default false.");for(let e of this.layers)if(e.stateful)return!0;return!1}resetStates(){H(()=>{this.layers.forEach(e=>{e.stateful&&e.resetStates()})})}};function jP(e,t,n){let s=t.length;if(e==null||Array.isArray(e)&&e.length===0)return t.map(r=>null);if(s===1)return Array.isArray(e)&&e.length===1?e:typeof e=="object"&&t[0]in e?[e[t[0]]]:[e];if(Array.isArray(e)){if(e.length!==s)throw new Error(`Provided ${n} is an array of ${e.length} element(s), but the model has ${s} outputs. Make sure a set of weights is provided for each model output.`);return e}else if(typeof e=="object"&&Object.keys(e).length>0&&typeof e[Object.keys(e)[0]]=="object"){let r=[];return t.forEach(a=>{a in e?r.push(e[a]):r.push(null)}),r}else throw new Error(`The model has multiple (${s}) outputs, so ${n} must be either an array with ${s} elements or an object with ${t} keys. Provided ${n} not understood: ${JSON.stringify(e)}`)}function G3(e,t){return jP(e,t,"classWeight")}async function j3(e,t,n,s){if(t!=null||s!=null)throw new Error("Support sampleWeight is not implemented yet");if(n!=null){let r=H(()=>{if(e.shape.length===1)return Os(e);if(e.shape.length===2){if(e.shape[1]>1)return er(e,1);if(e.shape[1]===1)return U(e,[e.shape[0]]);throw new Error(`Encountered unexpected last-dimension size (${e.shape[1]}) during handling of class weights. The size is expected to be >= 1.`)}else throw new Error(`Unexpected rank of target (y) tensor (${e.rank}) during handling of class weights. The rank is expected to be 1 or 2.`)}),a=Array.from(await r.data());K(r);let o=[];return a.forEach(i=>{if(n[i]==null)throw new Error(`classWeight must contain all classes in the training data. The class ${i} exists in the data but not in classWeight`);o.push(n[i])}),Mt(o,"float32")}else return null}function qP(e,t){return L(e,t)}var XP=32;function q3(e,t){let n,s,r=t;n=r.xs,s=r.ys,w.assert(n!=null&&s!=null,()=>`A Dataset iterator for fitDataset() is expected to generate objects of the form \`{xs: xVal, ys: yVal}\`, where the two values may be \`tf.Tensor\`, an array of Tensors, or a map of string to Tensor. The provided Dataset instead generates ${t}`);let a=X3("input",e.inputNames,n),o=X3("output",e.outputNames,s),i=a[0].shape[0];w.assert(a.length===e.inputs.length,()=>`LayersModel has ${e.inputs.length} inputs, but the dataset provides ${a.length} inputs. (Expected input keys: ${JSON.stringify(e.inputNames)})`),w.assert(o.length===e.outputs.length,()=>`LayersModel has ${e.outputs.length} outputs, but the dataset provides ${o.length} outputs. (Expected output keys: ${JSON.stringify(e.outputNames)})`);for(let l=0;l<a.length;l++)w.assert(a[l].shape[0]===i,()=>`Batch size mismatch: input ${e.inputNames[l]} has ${a[l].shape[0]}; expected ${i} based on input ${e.inputNames[0]}.`);for(let l=0;l<o.length;l++)w.assert(o[l].shape[0]===i,()=>`Batch size mismatch: output ${e.outputNames[l]} has ${o[l].shape[0]}; expected ${i} based on input ${e.inputNames[0]}.`);return{xs:a,ys:o}}function X3(e,t,n){if(n instanceof Ge)return[n];if(Array.isArray(n))return w.assert(n.length===t.length,()=>`Received an array of ${n.length} Tensors, but expected ${t.length} to match the ${e} keys ${t}.`),n;{let s=[];for(let r of t){if(n[r]==null)throw new G(`The feature data generated by the dataset lacks the required ${e} key '${r}'.`);s.push(n[r])}return s}}function KP(e){if(e.length===3)throw new Oe("Validation with sample weights is not implemented yet.");return{xs:e[0],ys:e[1]}}async function ZP(e,t,n){let s=n.batchesPerEpoch!=null;if(w.assert(e.optimizer!=null,()=>"You must compile a model before training/testing. Use LayersModel.compile(modelCompileConfig)."),w.assert(n!=null,()=>"For fitDataset(), the 2nd argument (config) is required, but it is not provided in this call."),w.assert(n.epochs!=null&&n.epochs>0&&Number.isInteger(n.epochs),()=>`For fitDataset(), config.epochs is expected to be a positive integer, but got ${n.epochs}`),w.assert(!s||n.batchesPerEpoch>0&&Number.isInteger(n.batchesPerEpoch),()=>`For fitDataset(), config.batchesPerEpoch is expected to be a positive integer if specified, but got ${n.batchesPerEpoch}`),w.assert(n.validationSplit==null,()=>"`validationSplit` is not supported by `fitDataset()`. Use validationData instead."),e.isTraining)throw new Error("Cannot start training because another fit() call is ongoing.");e.isTraining=!0;try{let r=n.validationData!=null,a,o;if(r)if(K3(n.validationData))w.assert(n.validationBatches==null||n.validationBatches>0&&Number.isInteger(n.validationBatches),()=>`For fitDataset() with dataset-based validation, config.validationBatches is expected not to be provided, or to be a positive integer, but got ${n.validationBatches}`);else{let g=KP(n.validationData);a=g.xs,o=g.ys}let i=e.makeTrainFunction(),l=e.getDedupedMetricsNames(),u;r?u=l.slice().concat(l.map(g=>"val_"+g)):u=l.slice();let c=$3(n.callbacks,n.yieldEvery),d=n.verbose==null?1:n.verbose,{callbackList:h,history:p}=F3(c,d,n.epochs,null,null,YP(t,n),null,r,u);h.setModel(e),e.history=p,await h.onTrainBegin(),e.stopTraining_=!1;let f=n.initialEpoch==null?0:n.initialEpoch,m=await t.iterator();for(;f<n.epochs;){let g={};await h.onEpochBegin(f);let A=0,y=0;for(s||(m=await t.iterator());s?A<n.batchesPerEpoch:!0;){let x=await m.next();if(s&&x.done){console.warn(`You provided \`batchesPerEpoch\` as ${n.batchesPerEpoch}, but your dataset iterator ran out of data after ${A} batches; interrupting training. Make sure that your dataset can generate at least \`batchesPerEpoch * epochs\` batches (in this case, ${n.batchesPerEpoch*n.epochs} batches). You may need to use the repeat() function when building your dataset.`);break}if(x.value!=null){let{xs:b,ys:v}=q3(e,x.value),k={};k.batch=y,k.size=b[0].shape[0],await h.onBatchBegin(y,k);let S=[];if(n.classWeight!=null){let O=G3(n.classWeight,e.outputNames);for(let E=0;E<O.length;++E)S.push(await j3(v[E],null,O[E]))}let C=b.concat(v).concat(S),_=i(C);K(C);for(let O=0;O<l.length;++O){let E=l[O],R=_[O];k[E]=R,Jt(R)}await h.onBatchEnd(y,k),N3(k),y++,A++}if(s?A>=n.batchesPerEpoch:x.done){if(r){let b;K3(n.validationData)?b=yt(await e.evaluateDataset(n.validationData,{batches:n.validationBatches})):b=yt(e.evaluate(a,o,{batchSize:n.validationBatchSize==null?XP:n.validationBatchSize,verbose:0}));for(let v=0;v<e.metricsNames.length;++v)g[`val_${e.metricsNames[v]}`]=b[v]}break}if(e.stopTraining_)break}if(await h.onEpochEnd(f,g),f++,e.stopTraining_)break}return await h.onTrainEnd(),await e.history.syncData(),e.history}finally{e.isTraining=!1}}function YP(e,t){let n=null;return t.batchesPerEpoch!=null?n=t.batchesPerEpoch:Number.isFinite(e.size)&&(n=e.size),n}function K3(e){return typeof e.iterator=="function"}function JP(e){return typeof e.next=="function"}async function QP(e,t,n){n=n||{};let s=n.batches!=null,r=e.testFunction,a=[];if(n.verbose>0)throw new Oe("Verbose mode is not implemented yet.");w.assert(!s||n.batches>0&&Number.isInteger(n.batches),()=>`Test loop expects \`batches\` to be a positive integer, but received ${JSON.stringify(n.batches)}`);let o=JP(t)?t:await t.iterator(),i=0,l=0;for(;s?l<n.batches:!0;){let u=await o.next();if(a=H(()=>{if(u.value){let{xs:c,ys:d}=q3(e,u.value),h=c.concat(d),p=H(()=>r(h));if(K(h),l===0)for(let m=0;m<p.length;++m)a.push(Ie(0));let f=h[0].shape[0];for(let m=0;m<p.length;++m){let g=p[m],A=a[m];a[m]=H(()=>ae(a[m],L(f,g))),l>0&&K(A)}K(p),i+=f,++l}return a}),u.done){s&&console.warn(`Your dataset iterator ran out of data during evaluateDataset(). Interrupting evalution. Make sure that your dataset can generate at least \`batches\` batches (in this case, ${n.batches} batches). You may need to use the repeat() function when building your dataset.`);break}}for(let u=0;u<a.length;++u){let c=a[u];a[u]=de(a[u],i),K(c)}return $n(a)}function MA(e){w.assert(e>0&&Number.isInteger(e),()=>`batchSize is required to be a positive integer, but got ${e}`)}function Ec(e,t,n){return e==null?[null]:Array.isArray(e)?e.map(s=>Ho(s,t,n-t)):Ho(e,t,n-t)}function zA(e,t){return H(()=>e==null?null:Array.isArray(e)?e.map(n=>zA(n,t)):y3(e,t.dtype==="int32"?t:ce(t,"int32")))}function LA(e,t){let n=[],s=0,r=null;for(;s<e;)r=s+t,r>=e&&(r=e),n.push([s,r]),s=r;return n}async function eM(e,t,n,s,r,a,o,i,l,u,c,d,h,p,f){r==null&&(r=32),a==null&&(a=1),c==null&&(c=!0),h==null&&(h=0);let m=!1;if(l!=null&&u!=null&&(m=!0),f!=null&&(m=!0,p==null))throw new G("Can only use `validationSteps` when doing step-wise training, i.e., `stepsPerEpoch` must be set.");let g=e.checkNumSamples(n,r,p,"steps_per_epoch"),A;g!=null&&(A=Bs(0,g)),o==null&&(o=1);let{callbackList:y,history:x}=F3(i,o,a,h,g,p,r,m,d);y.setModel(e),e.history=x,await y.onTrainBegin(),e.stopTraining_=!1;for(let b=h;b<a;++b){await y.onEpochBegin(b);let v={};if(p!=null)throw new Oe("stepsPerEpoch mode is not implemented yet.");{if(c==="batch")throw new Oe("batch shuffling is not implemneted yet");c&&w.shuffle(A);let k=Mt(A),S=LA(g,r);for(let C=0;C<S.length;++C){let _={};if(await y.onBatchBegin(C,_),H(()=>{let O=S[C][0],E=S[C][1],R=Ho(k,O,E-O);_.batch=C,_.size=E-O;let T=zA(n,R),P=t(T);for(let V=0;V<s.length;++V){let j=s[V],q=P[V];_[j]=q,Jt(q)}if(C===S.length-1&&m){let V=e.testLoop(l,u,r);for(let j=0;j<s.length;++j){let q=s[j],X=V[j];Jt(X),v["val_"+q]=X}}}),await y.onBatchEnd(C,_),N3(_),e.stopTraining_)break}k.dispose()}if(await y.onEpochEnd(b,v),e.stopTraining_)break}return await y.onTrainEnd(),await e.history.syncData(),e.history}async function tM(e,t,n,s={}){if(e.isTraining)throw new Error("Cannot start training because another fit() call is ongoing.");e.isTraining=!0;let r,a,o,i,l,u,c;try{let d=s.batchSize==null?32:s.batchSize;MA(d);let h=!1,p=await e.standardizeUserData(t,n,s.sampleWeight,s.classWeight,h,d);r=p[0],a=p[1],c=p[2];let f=!1,m;if(s.validationData!=null&&s.validationData.length>0){if(f=!0,s.validationData.length===2)o=s.validationData[0],i=s.validationData[1];else throw s.validationData.length===3?new Oe("validationData including sample weights is not supported yet."):new G(`When passing validation data, it must contain 2 (valX, valY) or 3 (valX, valY, valSampleWeight) items; ${s.validationData} is invalid.`);let S=!0,C=await e.standardizeUserData(o,i,null,null,S,d);l=C[0],u=C[1],m=l.concat(u)}else if(s.validationSplit!=null&&s.validationSplit>0&&s.validationSplit<1){f=!0;let S=Math.floor(r[0].shape[0]*(1-s.validationSplit)),C=r[0].shape[0];l=Ec(r,S,C),r=Ec(r,0,S),u=Ec(a,S,C),a=Ec(a,0,S),m=l.concat(u)}else s.validationSteps!=null&&(f=!0);let g=r.concat(a).concat(c);e.checkTrainableWeightsConsistency();let A=e.makeTrainFunction(),y=e.getDedupedMetricsNames(),x,b;f?(e.makeTestFunction(),x=e.testFunction,b=y.slice().concat(y.map(S=>"val_"+S))):(x=null,m=[],b=y.slice());let v=$3(s.callbacks,s.yieldEvery);return await eM(e,A,g,y,d,s.epochs,s.verbose,v,x,m,s.shuffle,b,s.initialEpoch,null,null)}finally{e.isTraining=!1,qo(r,t),qo(a,n),qo(l,o),qo(u,i),c!=null&&K(c)}}function Z3(e){let t=[];e instanceof Ge&&(e=[e]);for(let n=0;n<e.length;++n){let s=e[n];if(s.rank===1)t.push(kc(s,1));else{if(s.rank===0)throw new Error("Expected tensor to be at least 1D, but received a 0D tensor (scalar).");t.push(s)}}return t}function qo(e,t){if(e==null)return;let n=[];if(t instanceof Ge)n.push(t.id);else if(Array.isArray(t))t.forEach(r=>n.push(r.id));else if(t!=null)for(let r in t){let a=t[r];n.push(a.id)}let s=[];if(e instanceof Ge)n.indexOf(e.id)===-1&&s.push(e);else if(Array.isArray(e))e.forEach(r=>{n.indexOf(r.id)===-1&&s.push(r)});else if(e!=null)for(let r in e){let a=e[r];n.indexOf(a.id)===-1&&s.push(a)}s.forEach(r=>{r.isDisposed||r.dispose()})}function nM(e){return e instanceof Ge}function BA(e){return Array.isArray(e)}function Y3(e){return!nM(e)&&!BA(e)}function J3(e,t,n,s=!0,r=""){if(t==null||t.length===0){if(e!=null){let o=!1;if(BA(e)&&e.length>0)o=!0;else if(Y3(e)){for(let i in e)if(e.hasOwnProperty(i)){o=!0;break}}else o=!0;if(o)throw new G(`Error when checking model ${r} expected no data, but got ${e}`)}return[]}if(e==null)return t.map(o=>null);let a;if(Y3(e)){e=e,a=[];for(let o of t){if(e[o]==null)throw new G(`No data provided for "${o}". Need data for each key in: ${t}`);a.push(e[o])}}else if(BA(e)){if(e=e,e.length!==t.length)throw new G(`Error when checking model ${r}: the Array of Tensors that you are passing to your model is not the size the model expected. Expected to see ${t.length} Tensor(s), but instead got the following list of Tensor(s): ${e}`);a=e}else{if(e=e,t.length>1)throw new G(`The model ${r} expects ${t.length} Tensor(s), but only received one Tensor. Found: Tensor with shape ${e.shape}`);a=[e]}if(a=Z3(a),n!=null)for(let o=0;o<t.length;++o){if(n[o]==null)continue;let i=a[o];if(i.shape.length!==n[o].length)throw new G(`Error when checking ${r}: expected ${t[o]} to have ${n[o].length} dimension(s). but got array with shape ${i.shape}`);for(let l=0;l<n[o].length;++l){if(l===0&&!s)continue;let u=i.shape[l],c=n[o][l];if(c!=null&&c>=0&&u!==c)throw new G(`${r} expected a batch of elements where each example has shape [${n[o].slice(1,n[o].length)}] (i.e.,tensor shape [*,${n[o].slice(1,n[o].length)}]) but the ${r} received an input with ${i.shape[0]} examples, each with shape [${i.shape.slice(1,i.shape.length)}] (tensor shape [${i.shape}])`)}}return a}function sM(e,t,n){let s=na(e.map(a=>a.shape[0]));s.sort();let r=na(t.map(a=>a.shape[0]));if(r.sort(),s.length>1)throw new G(`All input Tensors (x) should have the same number of samples. Got array shapes: ${JSON.stringify(e.map(a=>a.shape))}`);if(r.length>1)throw new G(`All target Tensors (y) should have the same number of samples. Got array shapes: ${JSON.stringify(t.map(a=>a.shape))}`);if(s.length>0&&r.length>0&&!w.arraysEqual(s,r))throw new G(`Input Tensors should have the same number of samples as target Tensors. Found ${s[0]} input sample(s) and ${r[0]} target sample(s).`)}function rM(e,t,n){let s=[Go,Wp,Cc];for(let r=0;r<e.length;++r){let a=e[r],o=t[r],i=n[r];if(o!=null){if(o===Cc&&a.shape[a.shape.length-1]===1)throw new G(`You are passing a target array of shape ${a.shape} while using a loss 'categorical_crossentropy'. 'categorical_crossentropy'expects targets to be binary matrices (1s and 0s) of shape [samples, classes].`);if(s.indexOf(o)!==-1){let l=a.shape.slice(1),u=i.slice(1);for(let c=0;c<l.length;++c){let d=l[c],h=u[c];if(h!=null&&d!==h)throw new G(`A target Tensor with shape ${a.shape} was passed for an output of shape ${i}, while using a loss function that expects targets to have the same shape as the output.`)}}}}}function Q3(e,t,n,s=!0,r=""){let a;if(Array.isArray(e)){if(e.length!==t.length)throw new G(`Error when checking model ${r}: the Array of Tensors that you are passing to your model is not the size the the model expected. Expected to see ${t.length} Tensor(s), but instead got ${e.length} Tensors(s).`);a=e}else{if(t.length>1)throw new G(`The model expects ${t.length} ${r} Tensors, but only received one Tensor. Found: array with shape ${JSON.stringify(e.shape)}.`);a=[e]}if(n!=null)for(let o=0;o<t.length;++o){if(n[o]==null)continue;let i=a[o];if(i.shape.length!==n[o].length)throw new G(`Error when checking ${r}: expected ${t[o]} to have ${n[o].length} dimension(s), but got array with shape ${JSON.stringify(i.shape)}`);for(let l=0;l<n[o].length;++l){if(l===0&&!s)continue;let u=i.shape[l],c=n[o][l];if(c!=null&&c!==u)throw new G(`Error when checking ${r}: expected ${t[o]} to have shape ${JSON.stringify(n[o])} but got array with shape ${JSON.stringify(i.shape)}.`)}}}function aM(e,t){if(e==null||Array.isArray(e)&&e.length===0)return t.map(s=>[]);let n;if(typeof e=="string"||typeof e=="function")n=[e];else if(Array.isArray(e)||typeof e=="object")n=e;else throw new TypeError(`Type of metrics argument not understood. Expected an string,function, Array, or Object, found: ${e}`);if(Array.isArray(n))return t.map(s=>n);{let s=[];for(let r of t){let a=n.hasOwnProperty(r)?n[r]:[];Array.isArray(a)||(a=[a]),s.push(a)}return s}}var oM="layers-model",Nr=class extends ir{constructor(e){super(e);this.isTraining=!1}summary(e,t,n=console.log){if(!this.built)throw new G("This model has never been called, thus its weights have not been created yet. So no summary can be displayed. Build the model first (e.g., by calling it on some test data).");MP(this,e,t,n)}compile(e){if(e.loss==null&&(e.loss=[]),this.loss=e.loss,typeof e.optimizer=="string")this.optimizer_=PP(e.optimizer),this.isOptimizerOwned=!0;else{if(!(e.optimizer instanceof Sr))throw new G("User-defined optimizer must be an instance of tf.Optimizer.");this.optimizer_=e.optimizer,this.isOptimizerOwned=!1}let t=[];if(!Array.isArray(e.loss)&&typeof e.loss!="string"&&typeof e.loss!="function"){e.loss=e.loss;for(let a in e.loss)if(this.outputNames.indexOf(a)===-1)throw new G(`Unknown entry in loss dictionary: "${a}". Only expected the following keys: ${this.outputNames}`);for(let a of this.outputNames)e.loss[a]==null&&console.warn(`Output "${a}" is missing from loss dictionary. We assume this was done on purpose, and we will not be expecting data to be passed to ${a} during training`),t.push(EA(e.loss[a]))}else if(Array.isArray(e.loss)){if(e.loss.length!==this.outputs.length)throw new G(`When passing an Array as loss, it should have one entry per model output. The model has ${this.outputs.length} output(s), but you passed loss=${e.loss}.`);t=e.loss.map(o=>EA(o))}else{let a=EA(e.loss);this.outputs.forEach(o=>{t.push(a)})}this.lossFunctions=t,this.feedOutputNames=[],this.feedOutputShapes=[],this.feedLossFns=[];for(let a=0;a<this.outputs.length;++a){let o=this.internalOutputShapes[a],i=this.outputNames[a];this.feedOutputNames.push(i),this.feedOutputShapes.push(o),this.feedLossFns.push(this.lossFunctions[a])}let n=[];this.metrics=e.metrics,this.metricsNames=["loss"],this.metricsTensors=[],Uo("loss",()=>{for(let a=0;a<this.outputs.length;++a){if(n.indexOf(a)!==-1)continue;let o=this.lossFunctions[a];this.outputs.length>1&&(this.metricsTensors.push([o,a]),this.metricsNames.push(this.outputNames[a]+"_loss"))}});let s=aM(e.metrics,this.outputNames),r=(a,o,i)=>{this.outputNames.length>1&&(o=this.outputNames[a]+"_"+o),this.metricsNames.push(o),this.metricsTensors.push([i,a])};Uo("metric",()=>{for(let a=0;a<this.outputs.length;++a){if(n.indexOf(a)!==-1)continue;let o=s[a];(l=>{let u="",c,d,h;for(let p of l){if(typeof p=="string"&&["accuracy","acc","crossentropy","ce"].indexOf(p)!==-1){let m=this.internalOutputShapes[a];m[m.length-1]===1||this.lossFunctions[a]===Wp?["accuracy","acc"].indexOf(p)!==-1?d=RA:["crossentropy","ce"].indexOf(p)!==-1&&(d=M3):this.lossFunctions[a]===Bp?["accuracy","acc"].indexOf(p)!==-1?d=z3:["crossentropy","ce"].indexOf(p)!==-1&&(d=L3):["accuracy","acc"].indexOf(p)!==-1?d=_A:["crossentropy","ce"].indexOf(p)!==-1&&(d=DA);let g;["accuracy","acc"].indexOf(p)!==-1?g="acc":["crossentropy","ce"].indexOf(p)!==-1&&(g="ce"),h=d,c=u+g}else h=OP(p),c=u+Hp(p);let f;Uo(c,()=>{f=h}),r(a,c,f)}})(o)}}),this.collectedTrainableWeights=this.trainableWeights}checkTrainableWeightsConsistency(){this.collectedTrainableWeights!=null&&this.trainableWeights.length!==this.collectedTrainableWeights.length&&console.warn("Discrepancy between trainableweights and collected trainable weights. Did you set `model.trainable` without calling `model.compile()` afterwards?")}evaluate(e,t,n={}){let s=n.batchSize==null?32:n.batchSize;MA(s);let r=!0,a=this.standardizeUserDataXY(e,t,r,s);try{let o=a[0].concat(a[1]);this.makeTestFunction();let i=this.testFunction,l=this.testLoop(i,o,s,n.verbose,n.steps);return $n(l)}finally{qo(a[0],e),qo(a[1],t)}}async evaluateDataset(e,t){return this.makeTestFunction(),QP(this,e,t)}checkNumSamples(e,t,n,s="steps"){let r;if(n!=null){if(r=null,t!=null)throw new G(`If ${s} is set, batchSize must be null or undefined.Got batchSize = ${t}`)}else if(e!=null)Array.isArray(e)?r=e[0].shape[0]:r=e.shape[0];else throw new G(`Either the input data should have a defined shape, or ${s} shoud be specified.`);return r}execute(e,t){if(Array.isArray(t)&&t.length===0)throw new G("`outputs` is an empty Array, which is not allowed.");let n=Array.isArray(t),s=n?t:[t],r=this.retrieveSymbolicTensors(s),a=new jo;if(e instanceof Ge&&(e=[e]),Array.isArray(e)){if(e.length!==this.inputs.length)throw new G(`The number of inputs provided (${e.length}) does not match the number of inputs of this model (${this.inputs.length}).`);for(let i=0;i<this.inputs.length;++i)a.add(this.inputs[i],e[i])}else for(let i of this.inputs){let l=e[i.name];if(l==null)throw new G(`No value is provided for the model's input ${i.name}`);a.add(i,l)}let o=Nc(r,a);return n?o:o[0]}retrieveSymbolicTensors(e){let t=Bo(null,e.length),n=e.length;for(let s of this.layers){let r=Array.isArray(s.output)?s.output:[s.output],a=r.map(o=>o.name);for(let o=0;o<e.length;++o){let i=a.indexOf(e[o]);if(i!==-1&&(t[o]=r[i],n--),n===0)break}if(n===0)break}if(n>0){let s=[];throw t.forEach((r,a)=>{r==null&&s.push(e[a])}),new G(`Cannot find SymbolicTensors for output name(s): ${JSON.stringify(s)}`)}return t}predictLoop(e,t=32,n=!1){return H(()=>{let s=this.checkNumSamples(e);if(n)throw new Oe("Verbose predictLoop() is not implemented yet.");let r=LA(s,t),a=this.outputs.map(o=>[]);for(let o=0;o<r.length;++o)H(()=>{let l=r[o][0],u=r[o][1],c=Ec(e,l,u),d=[];if(Array.isArray(c))for(let p=0;p<c.length;++p)d.push({key:this.inputs[p],value:c[p]});else d.push({key:this.inputs[0],value:c});let h=new jo(d);return Nc(this.outputs,h)}).forEach((l,u)=>a[u].push(l));return $n(a.map(o=>ft(o,0)))})}predict(e,t={}){let n=Z3(e);Q3(n,this.inputNames,this.feedInputShapes,!1);try{let s=t.batchSize==null?32:t.batchSize;return MA(s),this.predictLoop(n,s)}finally{qo(n,e)}}predictOnBatch(e){Q3(e,this.inputNames,this.feedInputShapes,!0);let t=(Array.isArray(e)?e[0]:e).shape[0];return this.predictLoop(e,t)}standardizeUserDataXY(e,t,n=!0,s){if(this.optimizer_==null)throw new Ls("You must compile a model before training/testing. Use LayersModel.compile(modelCompileArgs).");let r=[];for(let a=0;a<this.feedOutputShapes.length;++a){let o=this.feedOutputShapes[a];this.feedLossFns[a]===Bp?r.push(o.slice(0,o.length-1).concat([1])):r.push(o)}if(e=J3(e,this.feedInputNames,this.feedInputShapes,!1,"input"),t=J3(t,this.feedOutputNames,r,!1,"target"),sM(e,t,null),rM(t,this.feedLossFns,this.feedOutputShapes),this.stateful&&s!=null&&s>0&&e[0].shape[0]%s!=0)throw new G(`In a stateful network, you should only pass inputs with a number of samples that is divisible by the batch size ${s}. Found: ${e[0].shape[0]} sample(s).`);return[e,t]}async standardizeUserData(e,t,n,s,r=!0,a){let[o,i]=this.standardizeUserDataXY(e,t,r,a);if(n!=null)throw new Error("sample weight is not supported yet.");let l=null;if(s!=null){let u=G3(s,this.outputNames);l=[];for(let c=0;c<u.length;++c)l.push(await j3(i[c],null,u[c]))}return[o,i,l]}testLoop(e,t,n,s=0,r){return H(()=>{let a=this.checkNumSamples(t,n,r,"steps"),o=[];if(s>0)throw new Oe("Verbose mode is not implemented yet.");if(r!=null)throw new Oe("steps mode in testLoop() is not implemented yet");{let i=LA(a,n),l=Mt(Bs(0,a));for(let u=0;u<i.length;++u){let c=i[u][0],d=i[u][1],h=Ho(l,c,d-c),p=zA(t,h),f=e(p);if(u===0)for(let m=0;m<f.length;++m)o.push(Ie(0));for(let m=0;m<f.length;++m){let g=f[m];o[m]=ae(o[m],L(d-c,g))}}for(let u=0;u<o.length;++u)o[u]=de(o[u],a)}return o})}getDedupedMetricsNames(){let e=this.metricsNames,t=[];for(let n=0;n<e.length;++n){let s=e[n],r=s;o3(e,s)>1&&(r+=`_${o3(e.slice(0,n),s)}`),t.push(r)}return t}makeTrainFunction(){return e=>{let t=[],n=e.slice(0,this.inputs.length),s=e.slice(this.inputs.length,this.inputs.length+this.outputs.length),r=e.slice(this.inputs.length+this.outputs.length,this.inputs.length+this.outputs.length*2),a=[],o=()=>{let c=[];for(let f=0;f<this.inputs.length;++f)c.push({key:this.inputs[f],value:n[f]});let d=new jo(c),h=Nc(this.outputs,d,{training:!0}),p;for(let f=0;f<this.lossFunctions.length;++f){let g=this.lossFunctions[f](s[f],h[f]);r[f]!=null&&(g=qP(g,r[f]));let A=_t(g);t.push(A),f===0?p=g:p=ae(p,g)}for(let f=0;f<this.metricsTensors.length;++f){let m;if(this.outputs.length>1&&f<this.outputs.length)m=t[f];else{let g=this.metricsTensors[f][0],A=this.metricsTensors[f][1];m=_t(g(s[A],h[A]))}Jt(m),a.push(m)}return p=_t(p),this.calculateLosses().forEach(f=>{p=ae(p,f)}),p},i=this.collectedTrainableWeights.map(c=>c.read()),l=!0;return[this.optimizer_.minimize(o,l,i)].concat(a)}}makeTestFunction(){this.testFunction=e=>H(()=>{let t=[],n,s=e.slice(0,this.inputs.length),r=e.slice(this.inputs.length,this.inputs.length+this.outputs.length),a=[];for(let l=0;l<this.inputs.length;++l)a.push({key:this.inputs[l],value:s[l]});let o=new jo(a),i=Nc(this.outputs,o);for(let l=0;l<this.lossFunctions.length;++l){let u=this.lossFunctions[l],c=_t(u(r[l],i[l]));l===0?n=c:n=ae(n,c),t.push(n)}for(let l=0;l<this.metricsTensors.length;++l){let u=this.metricsTensors[l][0],c=this.metricsTensors[l][1],d=_t(u(r[c],i[c]));t.push(d)}return t})}async fit(e,t,n={}){return tM(this,e,t,n)}async fitDataset(e,t){return ZP(this,e,t)}async trainOnBatch(e,t){let n=await this.standardizeUserData(e,t),s=n[0],r=n[1],o=this.makeTrainFunction()(s.concat(r)),i=[];for(let l of o){let u=await l.data();i.push(u[0])}return K(o),$n(i)}getNamedWeights(e){let t=[],n=e!=null&&e.trainableOnly,s=n?this.trainableWeights:this.weights,r=this.getWeights(n);for(let a=0;a<s.length;++a)n&&!s[a].trainable||t.push({name:s[a].originalName,tensor:r[a]});return t}set stopTraining(e){this.stopTraining_=e}get stopTraining(){return this.stopTraining_}get optimizer(){return this.optimizer_}set optimizer(e){this.optimizer_!==e&&(this.optimizer_=e,this.isOptimizerOwned=!1)}dispose(){let e=super.dispose();if(e.refCountAfterDispose===0&&this.optimizer!=null&&this.isOptimizerOwned){let t=Wh().numTensors;this.optimizer_.dispose(),e.numDisposedVariables+=t-Wh().numTensors}return e}getLossIdentifiers(){let e;if(typeof this.loss=="string")e=Tr(this.loss);else if(Array.isArray(this.loss)){for(let t of this.loss)if(typeof t!="string")throw new Error("Serialization of non-string loss is not supported.");e=this.loss.map(t=>Tr(t))}else{let t=Object.keys(this.loss);e={};let n=this.loss;for(let s of t)if(typeof n[s]=="string")e[s]=Tr(n[s]);else throw new Error("Serialization of non-string loss is not supported.")}return e}getMetricIdentifiers(){if(typeof this.metrics=="string"||typeof this.metrics=="function")return[Tr(Hp(this.metrics))];if(Array.isArray(this.metrics))return this.metrics.map(e=>Tr(Hp(e)));{let e={};for(let t in this.metrics)e[t]=Tr(Hp(this.metrics[t]));return e}}getTrainingConfig(){return{loss:this.getLossIdentifiers(),metrics:this.getMetricIdentifiers(),optimizer_config:{class_name:this.optimizer.getClassName(),config:this.optimizer.getConfig()}}}loadTrainingConfig(e){if(e.weighted_metrics!=null)throw new Error("Loading weight_metrics is not supported yet.");if(e.loss_weights!=null)throw new Error("Loading loss_weights is not supported yet.");if(e.sample_weight_mode!=null)throw new Error("Loading sample_weight_mode is not supported yet.");let t=Tc(e.optimizer_config),n=Us(t),s;if(typeof e.loss=="string")s=Wo(e.loss);else if(Array.isArray(e.loss))s=e.loss.map(a=>Wo(a));else if(e.loss!=null){s={};for(let a in e.loss)s[a]=Wo(e.loss[a])}let r;if(Array.isArray(e.metrics))r=e.metrics.map(a=>Wo(a));else if(e.metrics!=null){r={};for(let a in e.metrics)r[a]=Wo(e.metrics[a])}this.compile({loss:s,metrics:r,optimizer:n})}async save(e,t){if(typeof e=="string"){let l=_n.getSaveHandlers(e);if(l.length===0)throw new G(`Cannot find any save handlers for URL '${e}'`);if(l.length>1)throw new G(`Found more than one (${l.length}) save handlers for URL '${e}'`);e=l[0]}if(e.save==null)throw new G("LayersModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");let n=await _n.encodeWeights(this.getNamedWeights(t)),s=!1,r=null,o={modelTopology:this.toJSON(r,s),format:oM,generatedBy:`TensorFlow.js tfjs-layers v${OA}`,convertedBy:null};if((t==null?!1:t.includeOptimizer)&&this.optimizer!=null){o.trainingConfig=this.getTrainingConfig();let l="optimizer",{data:u,specs:c}=await _n.encodeWeights(await this.optimizer.getWeights(),l);n.specs.push(...c),n.data=_n.concatenateArrayBuffers([n.data,u])}if(this.userDefinedMetadata!=null){let l=!0;W3(this.userDefinedMetadata,this.name,l),o.userDefinedMetadata=this.userDefinedMetadata}return o.weightData=n.data,o.weightSpecs=n.specs,e.save(o)}setUserDefinedMetadata(e){W3(e,this.name),this.userDefinedMetadata=e}getUserDefinedMetadata(){return this.userDefinedMetadata}};Nr.className="Model";oe.registerClass(Nr);var ev=class extends Nr{};ev.className="Functional";oe.registerClass(ev);async function iM(e,t){"modelTopology"in e||(e={modelTopology:e}),e=e;let n=e.modelTopology;n.model_config!=null&&(n=n.model_config);let s=Tc(n),r=Us(s,t);if(e.weightsManifest!=null){let a=await _n.loadWeights(e.weightsManifest,e.pathPrefix,r.weights.map(i=>i.originalName)),o={};for(let i of r.weights)o[i.originalName]=a[i.originalName];r.loadWeights(o),K(a)}return r}async function lM(e,t){if(t==null&&(t={}),typeof e=="string"){let n=_n.getLoadHandlers(e,t);if(n.length===0)n.push(_n.browserHTTPRequest(e,t));else if(n.length>1)throw new G(`Found more than one (${n.length}) load handlers for URL '${e}'`);e=n[0]}return uM(e,void 0,t)}async function uM(e,t,n){if(n==null&&(n={}),e.load==null)throw new G("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");let s=await e.load(),r=s.modelTopology;r.model_config!=null&&(r=r.model_config);let a=n.strict==null?!0:n.strict,o=s.weightData!=null&&s.weightSpecs!=null&&a,i=Us(Tc(r),t,o),l=s.trainingConfig;if(l!=null&&i.loadTrainingConfig(l),s.userDefinedMetadata!=null&&i.setUserDefinedMetadata(s.userDefinedMetadata),s.weightData!=null){if(s.weightSpecs==null)throw new G("LayersModel artifacts contains weight data, but not weight specs. Therefore loading of weights cannot proceed.");let{modelWeights:u,optimizerWeights:c}=cM(s.weightData,s.weightSpecs);i.loadWeights(u,a),i.optimizer!=null&&c.length>0&&await i.optimizer.setWeights(c),K(u),K(c.map(d=>d.tensor))}return i}function cM(e,t){let n=_n.decodeWeights(e,t),s={},r=[];return t.forEach(a=>{a.group==="optimizer"?r.push({name:a.name,tensor:n[a.name]}):s[a.name]=n[a.name]}),{modelWeights:s,optimizerWeights:r}}var Xl=class extends Nr{constructor(e){super({inputs:[],outputs:[]});if(e=e||{},this.trainable=!0,this.built=!1,this.name=e.name!=null?e.name:Fp("sequential_"),e.layers!=null)for(let t of e.layers)this.add(t)}checkShape(e){if(e.inboundNodes[0].outputTensors[0].shape.some(n=>n<0))throw new G(`Negative dimension size caused by adding layer ${e.name} with input shape [${e.inboundNodes[0].inputTensors[0].shape}]`)}add(e){let t=e instanceof Xl||e instanceof Nr,n;if(t){if(n=e,n.outputs.length!==1)throw new G("All layers in a Sequential model should have a single output tensor. For multi-output layers, use the functional API.");if(n.inputs.length!==1)throw new G("All layers in a Sequential model should have a single input tensor. For multi-input layers, use the functional API.")}if(this.outputs.length===0){if(e.inboundNodes.length===0){if(e.batchInputShape==null)throw new G("The first layer in a Sequential model must get an `inputShape` or `batchInputShape` argument.");let s=T3({batchShape:e.batchInputShape,dtype:e.dtype,name:e.name+"_input"});e.apply(s)}if(t)this.outputs=n.outputs,this.inputs=n.inputs;else{if(e.inboundNodes.length!==1)throw new G(`A layer added to a Sequential model must not already be connected somewhere else. LayersModel received layer ${e.name} which has ${e.inboundNodes.length} pre-existing inbound connections.`);if(e.inboundNodes[0].outputTensors.length!==1)throw new G("All layers in a Sequential model should have a single output tensor. For multi-output layers, use the functional API.");this.checkShape(e),this.outputs=[e.inboundNodes[0].outputTensors[0]],this.inputs=C3(this.outputs[0])}this.inboundNodes=[],new Mp({outboundLayer:this,inboundLayers:[],nodeIndices:[],tensorIndices:[],inputTensors:this.inputs,outputTensors:this.outputs,inputMasks:Bo(null,this.inputs.length),outputMasks:[null],inputShapes:this.inputs.map(s=>s.shape),outputShapes:this.outputs[0].shape})}else{let s=e.apply(this.outputs[0]);if(Array.isArray(s))throw new TypeError("All layers in a Sequential model should have a single output tensor. For multi-output layers, use the functional API.");this.checkShape(e),this.outputs=[s],this.inboundNodes[0].outputTensors=this.outputs,this.inboundNodes[0].outputShapes=[this.outputs[0].shape]}this.layers.push(e),this.built=!1}pop(){if(this.layers.length===0)throw new TypeError("There are no layers in the model.");if(this.layers.pop(),this.layers.length===0)this.outputs=[],this.inboundNodes=[],this.outboundNodes=[];else{let e=this.layers.length-1;this.layers[e].outboundNodes=[],this.outputs=[this.layers[e].output],this.inboundNodes[0].outputTensors=this.outputs,this.inboundNodes[0].outputShapes=[this.outputs[0].shape]}}call(e,t){return this.model==null&&this.build(),this.model.call(e,t)}build(e){if(at(e),this.inputs.length===0||this.outputs.length===0)throw new TypeError("Sequential model cannot be built: model is empty. Add some layers first.");this.model=new Nr({inputs:this.inputs,outputs:this.outputs[0],name:this.name+"_model"}),this.model.trainable=this.trainable,this.supportsMasking=this.model.supportsMasking,this.inputLayers=this.model.inputLayers,this.inputLayersNodeIndices=this.model.inputLayersNodeIndices,this.inputLayersTensorIndices=this.model.inputLayersTensorIndices,this.outputLayers=this.model.outputLayers,this.outputLayersNodeIndices=this.model.outputLayersNodeIndices,this.outputLayersTensorIndices=this.model.outputLayersTensorIndices,this.nodesByDepth=this.model.nodesByDepth,this.containerNodes=this.model.containerNodes,this.outputNames=this.model.outputNames,this.inputNames=this.model.inputNames,this.built=!0}countParams(){return this.built||this.build(),super.countParams()}summary(e,t,n=console.log){this.built||this.build(),super.summary(e,t,n)}setWeights(e){this.model==null&&this.build(),this.model.setWeights(e)}evaluate(e,t,n={}){if(!this.built)throw new Ls("The model needs to be compiled before being used.");return this.model.evaluate(e,t,n)}async evaluateDataset(e,t){if(!this.built)throw new Ls("The model needs to be compiled before being used.");return this.model.evaluateDataset(e,t)}predict(e,t={}){return this.model==null&&this.build(),this.model.predict(e,t)}predictOnBatch(e){return this.model==null&&this.build(),this.model.predictOnBatch(e)}compile(e){this.build(),this.model.compile(e),this.optimizer_=this.model.optimizer,this.isOptimizerOwned=this.model.isOptimizerOwned,this.loss=this.model.loss,this.metrics=this.model.metrics,this.metricsTensors=this.model.metricsTensors,this.metricsNames=this.model.metricsNames}get optimizer(){return this.model==null?void 0:this.model.optimizer}set optimizer(e){this.model.optimizer=e}async fit(e,t,n={}){if(!this.built)throw new Ls("The model needs to be compiled before being used.");return this.model.fit(e,t,n)}async fitDataset(e,t){if(!this.built)throw new Ls("The model needs to be compiled before being used.");return this.model.fitDataset(e,t)}async trainOnBatch(e,t){return this.model.trainOnBatch(e,t)}static fromConfig(e,t,n={},s=!1){let r,a={};if(t instanceof Array){if(t[0].className==null||t[0].className==="Merge")throw new G("Legacy serialization format not supported yet.");r=t}else w.assert(t.layers!=null,()=>"When the config data for a Sequential model is not an Array, it must be an Object that contains the 'layers' field."),r=t.layers,delete t.layers,a=t;let o=new e(a);if(!(o instanceof Xl))throw new Oe(`Sequential.fromConfig called on non-Sequential input: ${o}`);for(let i of r){let u=Us(i,void 0,s);s&&u.setFastWeightInitDuringBuild(!0),o.add(u)}return o}set stopTraining(e){if(this.model==null)throw new G("Cannot set the stopTraining property of a sequential model before it is compiled.");this.model.stopTraining=e}get stopTraining(){if(this.model==null)throw new G("Cannot get the stopTraining property of a sequential model before it is compiled.");return this.model.stopTraining}getConfig(){let e=[];for(let t of this.layers){let n={};n.className=t.getClassName(),n.config=t.getConfig(),e.push(n)}return{name:this.name,layers:e}}};Xl.className="Sequential";oe.registerClass(Xl);function dM(e){return new Nr(e)}function hM(e){return new Xl(e)}function pM(e,t){return t==null&&(t={}),lM(e,t)}function tv(e){return T3(e)}function fM(e,t){Rs.registerCallbackConstructor(e,t)}var On=class extends oe.Serializable{getConfig(){return{}}},nv=class extends On{apply(e,t=1){return BO(e,t)}};nv.className="elu";oe.registerClass(nv);var sv=class extends On{apply(e){return Hg(e)}};sv.className="selu";oe.registerClass(sv);var rv=class extends On{apply(e){return sr(e)}};rv.className="relu";oe.registerClass(rv);var av=class extends On{apply(e){return H(()=>pc(6,sr(e)))}};av.className="relu6";oe.registerClass(av);var ov=class extends On{apply(e){return e}};ov.className="linear";oe.registerClass(ov);var iv=class extends On{apply(e){return Hn(e)}};iv.className="sigmoid";oe.registerClass(iv);var lv=class extends On{apply(e){return VO(e)}};lv.className="hardSigmoid";oe.registerClass(lv);var uv=class extends On{apply(e){return zl(e)}};uv.className="softplus";oe.registerClass(uv);var cv=class extends On{apply(e){return WO(e)}};cv.className="softsign";oe.registerClass(cv);var dv=class extends On{apply(e){return $l(e)}};dv.className="tanh";oe.registerClass(dv);var WA=class extends On{apply(e,t=-1){return op(e,t)}};WA.className="softmax";oe.registerClass(WA);var hv=class extends On{apply(e,t=-1){return $g(e,t)}};hv.className="logSoftmax";oe.registerClass(hv);var pv=class extends On{apply(e,t=1){return H(()=>L(Hn(L(e,t)),e))}};pv.className="swish";oe.registerClass(pv);var fv=class extends On{apply(e){return H(()=>L(e,$l(zl(e))))}};fv.className="mish";oe.registerClass(fv);function oa(e){return e.getClassName()}function VA(e,t={}){return bc(e,oe.SerializationMap.getMap().classNameMap,t,"activation")}function ia(e){if(e==null){let t={};return t.className="linear",t.config={},VA(t)}if(typeof e=="string"){let t={};return t.className=e,t.config={},VA(t)}else return e instanceof On?e:VA(e)}function UA(e){if(e!=null&&typeof e!="object")throw new Error(`Argument to L1L2 regularizer's constructor is expected to be an object, but received: ${e}`)}var mv=class extends oe.Serializable{},Rc=class extends mv{constructor(e){super();UA(e),this.l1=e==null||e.l1==null?.01:e.l1,this.l2=e==null||e.l2==null?.01:e.l2,this.hasL1=this.l1!==0,this.hasL2=this.l2!==0}apply(e){return H(()=>{let t=Pt([1]);return this.hasL1&&(t=ae(t,ve(L(this.l1,Ht(e))))),this.hasL2&&(t=ae(t,ve(L(this.l2,Ic(e))))),U(t,[])})}getConfig(){return{l1:this.l1,l2:this.l2}}static fromConfig(e,t){return new e({l1:t.l1,l2:t.l2})}};Rc.className="L1L2";oe.registerClass(Rc);function mM(e){return UA(e),new Rc({l1:e!=null?e.l1:null,l2:0})}function gM(e){return UA(e),new Rc({l2:e!=null?e.l2:null,l1:0})}var gv={l1l2:"L1L2"};function dt(e){return oA(e)}function Av(e,t={}){return bc(e,oe.SerializationMap.getMap().classNameMap,t,"regularizer")}function kt(e){if(e==null)return null;if(typeof e=="string"){let n={className:e in gv?gv[e]:e,config:{}};return Av(n)}else return e instanceof mv?e:Av(e)}var HA=class extends Ze{constructor(e){super(e==null?{}:e);this.supportsMasking=!0,e!=null&&(this.maxValue=e.maxValue)}call(e,t){e=ze(e);let n=sr(e);return this.maxValue!=null&&(n=Gn(n,0,this.maxValue)),n}computeOutputShape(e){return e}getConfig(){let e={maxValue:this.maxValue},t=super.getConfig();return Object.assign(e,t),e}};HA.className="ReLU";oe.registerClass(HA);var GA=class extends Ze{constructor(e){super(e==null?{}:e);this.DEFAULT_ALPHA=.3,e==null&&(e={}),this.alpha=e.alpha==null?this.DEFAULT_ALPHA:e.alpha}call(e,t){let n=ze(e);return Kh(n,this.alpha)}computeOutputShape(e){return e}getConfig(){let e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}};GA.className="LeakyReLU";oe.registerClass(GA);var jA=class extends Ze{constructor(e){super(e==null?{}:e);if(this.DEFAULT_ALPHA_INITIALIZER="zeros",e==null&&(e={}),this.supportsMasking=!0,this.alphaInitializer=wt(e.alphaInitializer||this.DEFAULT_ALPHA_INITIALIZER),this.alphaRegularizer=kt(e.alphaRegularizer),this.alphaConstraint=Xt(e.alphaConstraint),e.sharedAxes==null)this.sharedAxes=null;else if(Array.isArray(e.sharedAxes))this.sharedAxes=e.sharedAxes;else if(typeof e.sharedAxes=="number")this.sharedAxes=[e.sharedAxes];else throw new G(`Expected sharedAxes to be a number or an array of numbers, but got ${e.sharedAxes}`)}build(e){e=at(e);let t=e.slice(1);if(this.sharedAxes!=null)for(let s of this.sharedAxes)t[s-1]=1;this.alpha=this.addWeight("alpha",t,"float32",this.alphaInitializer,this.alphaRegularizer,!0,this.alphaConstraint);let n={};if(this.sharedAxes!=null)for(let s=1;s<e.length;++s)n[s]=e[s];this.inputSpec=[new zt({ndim:e.length,axes:n})],this.built=!0}call(e,t){return e=ze(e),sp(e,this.alpha.read())}getConfig(){let e={alphaInitializer:Nt(this.alphaInitializer),alphaRegularizer:dt(this.alphaRegularizer),alphaConstraint:qt(this.alphaConstraint),sharedAxes:this.sharedAxes},t=super.getConfig();return Object.assign(e,t),e}};jA.className="PReLU";oe.registerClass(jA);var qA=class extends Ze{constructor(e){super(e==null?{}:e);if(this.DEFAULT_ALPHA=1,e==null&&(e={}),e.alpha!=null&&e.alpha!==this.DEFAULT_ALPHA)throw new Oe(`Non-default alpha value (${e.alpha}) is not supported by the ELU layer yet.`);this.alpha=e.alpha==null?this.DEFAULT_ALPHA:e.alpha}call(e,t){let n=ze(e);return dc(n)}computeOutputShape(e){return e}getConfig(){let e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}};qA.className="ELU";oe.registerClass(qA);var XA=class extends Ze{constructor(e){super(e==null?{}:e);this.DEFAULT_THETA=1,e==null&&(e={}),this.theta=e.theta==null?this.DEFAULT_THETA:e.theta}call(e,t){let n=ze(e);return L(n,ce(jn(n,this.theta),"float32"))}computeOutputShape(e){return e}getConfig(){let e={theta:this.theta},t=super.getConfig();return Object.assign(e,t),e}};XA.className="ThresholdedReLU";oe.registerClass(XA);var KA=class extends Ze{constructor(e){super(e==null?{}:e);this.DEFAULT_AXIS=1,e==null&&(e={}),this.softmax=new WA().apply,this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis}call(e,t){let n=ze(e);return this.softmax(n,this.axis)}computeOutputShape(e){return e}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};KA.className="Softmax";oe.registerClass(KA);function Kl(e,t,n){if(typeof e=="number")return Bo(e,t);if(e.length!==t)throw new G(`The ${n} argument must be an integer or tuple of ${t} integers. Received: ${e.length} elements.`);for(let s=0;s<t;++s){let r=e[s];if(!PO(r))throw new G(`The ${n} argument must be an integer or tuple of ${t} integers. Received: ${JSON.stringify(e)} including a non-integer number ${r}`)}return e}function Hs(e,t,n,s,r=1){if(e==null)return e;let a=t+(t-1)*(r-1),o;return n==="same"?o=e:o=e-a+1,Math.floor((o+s-1)/s)}function lr(e,t,n,s){if(e==null)return null;if(s==="valid")e=e*t+ra([n-t,0]);else if(s==="same")e=e*t;else throw new G(`Unsupport padding mode: ${s}.`);return e}function ZA(e,t){return H(()=>(Ft(t),t==="channelsFirst"?Xe(e,[0,2,3,1]):e))}function yv(e,t){return H(()=>(Ft(t),t==="channelsFirst"?Xe(e,[0,2,3,4,1]):e))}function AM(e,t,n,s=1,r="valid",a,o=1){return H(()=>{if(a==null&&(a=zs()),Ft(a),e.shape.length!==3)throw new G(`The input of a conv1dWithBias operation should be 3, but is ${e.shape.length} instead.`);if(t.shape.length!==3)throw new G(`The kernel for a conv1dWithBias operation should be 3, but is ${t.shape.length} instead`);if(n!=null&&n.shape.length!==1)throw new G(`The bias for a conv1dWithBias operation should be 1, but is ${t.shape.length} instead`);if(a==="channelsFirst"&&(e=Xe(e,[0,2,1])),r==="causal")throw new Oe("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");let i=Sg(e,t,s,r==="same"?"same":"valid","NWC",o);return n!=null&&(i=Ws(i,n)),i})}function xv(e,t,n,s=[1,1],r="valid",a,o,i=null){return H(()=>{if(a==null&&(a=zs()),Ft(a),e.rank!==3&&e.rank!==4)throw new G(`conv2dWithBiasActivation expects input to be of rank 3 or 4, but received ${e.rank}.`);if(t.rank!==3&&t.rank!==4)throw new G(`conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received ${e.rank}.`);let l=ZA(e,a);if(r==="causal")throw new Oe("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return l=ta.conv2d({x:l,filter:t,strides:s,pad:r==="same"?"same":"valid",dilations:o,dataFormat:"NHWC",bias:n,activation:i}),a==="channelsFirst"&&(l=Xe(l,[0,3,1,2])),l})}function yM(e,t,n,s=[1,1,1],r="valid",a,o){return H(()=>{if(a==null&&(a=zs()),Ft(a),e.rank!==4&&e.rank!==5)throw new G(`conv3dWithBias expects input to be of rank 4 or 5, but received ${e.rank}.`);if(t.rank!==4&&t.rank!==5)throw new G(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${e.rank}.`);let i=yv(e,a);if(r==="causal")throw new Oe("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return i=Ng(i,t,s,r==="same"?"same":"valid","NDHWC",o),n!=null&&(i=Ws(i,n)),a==="channelsFirst"&&(i=Xe(i,[0,4,1,2,3])),i})}var YA=class extends Ze{constructor(e,t){super(t);if(this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",YA.verifyArgs(t),this.rank=e,Qt(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new Oe(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=Kl(t.kernelSize,e,"kernelSize"),this.strides=Kl(t.strides==null?1:t.strides,e,"strides"),this.padding=t.padding==null?"valid":t.padding,gs(this.padding),this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Ft(this.dataFormat),this.activation=ia(t.activation),this.useBias=t.useBias==null?!0:t.useBias,this.biasInitializer=wt(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=Xt(t.biasConstraint),this.biasRegularizer=kt(t.biasRegularizer),this.activityRegularizer=kt(t.activityRegularizer),this.dilationRate=Kl(t.dilationRate==null?1:t.dilationRate,e,"dilationRate"),this.rank===1&&Array.isArray(this.dilationRate)&&this.dilationRate.length!==1)throw new G(`dilationRate must be a number or an array of a single number for 1D convolution, but received ${JSON.stringify(this.dilationRate)}`);if(this.rank===2){if(typeof this.dilationRate=="number")this.dilationRate=[this.dilationRate,this.dilationRate];else if(this.dilationRate.length!==2)throw new G(`dilationRate must be a number or array of two numbers for 2D convolution, but received ${JSON.stringify(this.dilationRate)}`)}else if(this.rank===3){if(typeof this.dilationRate=="number")this.dilationRate=[this.dilationRate,this.dilationRate,this.dilationRate];else if(this.dilationRate.length!==3)throw new G(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(e){if(ar("kernelSize"in e,"required key 'kernelSize' not in config"),typeof e.kernelSize!="number"&&!lA(e.kernelSize,"number",1,3))throw new G(`BaseConv expects config.kernelSize to be number or number[] with length 1, 2, or 3, but received ${JSON.stringify(e.kernelSize)}.`)}getConfig(){let e={kernelSize:this.kernelSize,strides:this.strides,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,activation:oa(this.activation),useBias:this.useBias,biasInitializer:Nt(this.biasInitializer),biasRegularizer:dt(this.biasRegularizer),activityRegularizer:dt(this.activityRegularizer),biasConstraint:qt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}},_c=class extends YA{constructor(e,t){super(e,t);this.kernel=null,_c.verifyArgs(t),this.filters=t.filters,Qt(this.filters,"filters"),this.kernelInitializer=wt(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=Xt(t.kernelConstraint),this.kernelRegularizer=kt(t.kernelRegularizer)}build(e){e=at(e);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new G(`The channel dimension of the input should be defined. Found ${e[t]}`);let n=e[t],s=this.kernelSize.concat([n,this.filters]);this.kernel=this.addWeight("kernel",s,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[{ndim:this.rank+2,axes:{[t]:n}}],this.built=!0}call(e,t){return H(()=>{e=ze(e);let n,s=this.bias==null?null:this.bias.read(),r=l3(this.activation.getClassName());if(r!=null&&this.rank===2)n=xv(e,this.kernel.read(),s,this.strides,this.padding,this.dataFormat,this.dilationRate,r);else{if(this.rank===1)n=AM(e,this.kernel.read(),s,this.strides[0],this.padding,this.dataFormat,this.dilationRate[0]);else if(this.rank===2)n=xv(e,this.kernel.read(),s,this.strides,this.padding,this.dataFormat,this.dilationRate);else if(this.rank===3)n=yM(e,this.kernel.read(),s,this.strides,this.padding,this.dataFormat,this.dilationRate);else throw new Oe("convolutions greater than 3D are not implemented yet.");this.activation!=null&&(n=this.activation.apply(n))}return n})}computeOutputShape(e){e=at(e);let t=[],n=this.dataFormat==="channelsLast"?e.slice(1,e.length-1):e.slice(2);for(let r=0;r<n.length;++r){let a=Hs(n[r],this.kernelSize[r],this.padding,this.strides[r],typeof this.dilationRate=="number"?this.dilationRate:this.dilationRate[r]);t.push(a)}let s=[e[0]];return this.dataFormat==="channelsLast"?(s=s.concat(t),s.push(this.filters)):(s.push(this.filters),s=s.concat(t)),s}getConfig(){let e={filters:this.filters,kernelInitializer:Nt(this.kernelInitializer),kernelRegularizer:dt(this.kernelRegularizer),kernelConstraint:qt(this.kernelConstraint)},t=super.getConfig();return Object.assign(e,t),e}static verifyArgs(e){if(!("filters"in e)||typeof e.filters!="number"||e.filters<1)throw new G(`Convolution layer expected config.filters to be a 'number' > 0 but got ${JSON.stringify(e.filters)}`)}},Dc=class extends _c{constructor(e){super(2,e);Dc.verifyArgs(e)}getConfig(){let e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!lA(e.kernelSize,"number",1,2))throw new G(`Conv2D expects config.kernelSize to be number or number[] with length 1 or 2, but received ${JSON.stringify(e.kernelSize)}.`)}};Dc.className="Conv2D";oe.registerClass(Dc);var $c=class extends _c{constructor(e){super(3,e);$c.verifyArgs(e)}getConfig(){let e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!(Array.isArray(e.kernelSize)&&(e.kernelSize.length===1||e.kernelSize.length===3)))throw new G(`Conv3D expects config.kernelSize to be number or [number, number, number], but received ${JSON.stringify(e.kernelSize)}.`)}};$c.className="Conv3D";oe.registerClass($c);var JA=class extends Dc{constructor(e){super(e);if(this.inputSpec=[new zt({ndim:4})],this.padding!=="same"&&this.padding!=="valid")throw new G(`Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=at(e),e.length!==4)throw new G("Input should have rank 4; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new G("The channel dimension of the inputs should be defined. Found `None`.");let n=e[t],s=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",s,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new zt({ndim:4,axes:{[t]:n}})],this.built=!0}call(e,t){return H(()=>{let n=ze(e);if(n.shape.length!==4)throw new G(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let s=n.shape,r=s[0],a,o;this.dataFormat==="channelsFirst"?(a=2,o=3):(a=1,o=2);let i=s[a],l=s[o],u=this.kernelSize[0],c=this.kernelSize[1],d=this.strides[0],h=this.strides[1],p=lr(i,d,u,this.padding),f=lr(l,h,c,this.padding),m=[r,p,f,this.filters];this.dataFormat!=="channelsLast"&&(n=Xe(n,[0,2,3,1]));let g=Tg(n,this.kernel.read(),m,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(g=Xe(g,[0,3,1,2])),this.bias!=null&&(g=Ws(g,this.bias.read(),this.dataFormat)),this.activation!=null&&(g=this.activation.apply(g)),g})}computeOutputShape(e){e=at(e);let t=e.slice(),n,s,r;this.dataFormat==="channelsFirst"?(n=1,s=2,r=3):(n=3,s=1,r=2);let a=this.kernelSize[0],o=this.kernelSize[1],i=this.strides[0],l=this.strides[1];return t[n]=this.filters,t[s]=lr(t[s],i,a,this.padding),t[r]=lr(t[r],l,o,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};JA.className="Conv2DTranspose";oe.registerClass(JA);var QA=class extends $c{constructor(e){super(e);if(this.inputSpec=[new zt({ndim:5})],this.padding!=="same"&&this.padding!=="valid")throw new G(`Conv3DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=at(e),e.length!==5)throw new G("Input should have rank 5; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new G("The channel dimension of the inputs should be defined. Found `None`.");let n=e[t],s=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",s,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new zt({ndim:5,axes:{[t]:n}})],this.built=!0}call(e,t){return H(()=>{let n=ze(e);if(n.shape.length!==5)throw new G(`Conv3DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let s=n.shape,r=s[0],a,o,i;this.dataFormat==="channelsFirst"?(i=2,a=3,o=4):(i=1,a=2,o=3);let l=s[i],u=s[a],c=s[o],d=this.kernelSize[0],h=this.kernelSize[1],p=this.kernelSize[2],f=this.strides[0],m=this.strides[1],g=this.strides[2],A=lr(l,f,d,this.padding),y=lr(u,m,h,this.padding),x=lr(c,g,p,this.padding),b=[r,A,y,x,this.filters];this.dataFormat!=="channelsLast"&&(n=Xe(n,[0,2,3,4,1]));let v=Qx(n,this.kernel.read(),b,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(v=Xe(v,[0,4,1,2,3])),this.bias!==null&&(v=Ws(v,this.bias.read(),this.dataFormat)),this.activation!==null&&(v=this.activation.apply(v)),v})}computeOutputShape(e){e=at(e);let t=e.slice(),n,s,r,a;this.dataFormat==="channelsFirst"?(n=1,s=2,r=3,a=4):(n=4,s=1,r=2,a=3);let o=this.kernelSize[0],i=this.kernelSize[1],l=this.kernelSize[2],u=this.strides[0],c=this.strides[1],d=this.strides[2];return t[n]=this.filters,t[s]=lr(t[s],u,o,this.padding),t[r]=lr(t[r],c,i,this.padding),t[a]=lr(t[a],d,l,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};QA.className="Conv3DTranspose";oe.registerClass(QA);var bv=class extends _c{constructor(e,t){super(e,t);if(this.DEFAULT_DEPTHWISE_INITIALIZER="glorotUniform",this.DEFAULT_POINTWISE_INITIALIZER="glorotUniform",this.depthwiseKernel=null,this.pointwiseKernel=null,t.filters==null)throw new G("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(t.kernelInitializer!=null||t.kernelRegularizer!=null||t.kernelConstraint!=null)throw new G("Fields kernelInitializer, kernelRegularizer and kernelConstraint are invalid for SeparableConv2D. Use depthwiseInitializer, depthwiseRegularizer, depthwiseConstraint, pointwiseInitializer, pointwiseRegularizer and pointwiseConstraint instead.");if(t.padding!=null&&t.padding!=="same"&&t.padding!=="valid")throw new G(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(t.padding)}`);this.depthMultiplier=t.depthMultiplier==null?1:t.depthMultiplier,this.depthwiseInitializer=wt(t.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=kt(t.depthwiseRegularizer),this.depthwiseConstraint=Xt(t.depthwiseConstraint),this.pointwiseInitializer=wt(t.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=kt(t.pointwiseRegularizer),this.pointwiseConstraint=Xt(t.pointwiseConstraint)}build(e){if(e=at(e),e.length<this.rank+2)throw new G(`Inputs to SeparableConv${this.rank}D should have rank ${this.rank+2}, but received input shape: ${JSON.stringify(e)}`);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null||e[t]<0)throw new G(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(e[t])}`);let n=e[t],s=this.kernelSize.concat([n,this.depthMultiplier]),r=[];for(let o=0;o<this.rank;++o)r.push(1);r.push(n*this.depthMultiplier,this.filters);let a=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",s,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,a,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",r,"float32",this.pointwiseInitializer,this.pointwiseRegularizer,a,this.pointwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,a,this.biasConstraint):this.bias=null,this.inputSpec=[new zt({ndim:this.rank+2,axes:{[t]:n}})],this.built=!0}call(e,t){return H(()=>{e=ze(e);let n;if(this.rank===1)throw new Oe("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(e=Xe(e,[0,2,3,1])),n=vb(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(n=Ws(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),this.dataFormat==="channelsFirst"&&(n=Xe(n,[0,3,1,2])),n})}getConfig(){let e=super.getConfig();return delete e.rank,delete e.kernelInitializer,delete e.kernelRegularizer,delete e.kernelConstraint,e.depthwiseInitializer=Nt(this.depthwiseInitializer),e.pointwiseInitializer=Nt(this.pointwiseInitializer),e.depthwiseRegularizer=dt(this.depthwiseRegularizer),e.pointwiseRegularizer=dt(this.pointwiseRegularizer),e.depthwiseConstraint=qt(this.depthwiseConstraint),e.pointwiseConstraint=qt(this.pointwiseConstraint),e}};bv.className="SeparableConv";var e1=class extends bv{constructor(e){super(2,e)}};e1.className="SeparableConv2D";oe.registerClass(e1);var jp=class extends _c{constructor(e){super(1,e);jp.verifyArgs(e),this.inputSpec=[{ndim:3}]}getConfig(){let e=super.getConfig();return delete e.rank,delete e.dataFormat,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!lA(e.kernelSize,"number",1,1))throw new G(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(e.kernelSize)}.`)}};jp.className="Conv1D";oe.registerClass(jp);var t1=class extends Ze{constructor(e){super(e);typeof e.cropping=="number"?this.cropping=[[e.cropping,e.cropping],[e.cropping,e.cropping]]:typeof e.cropping[0]=="number"?this.cropping=[[e.cropping[0],e.cropping[0]],[e.cropping[1],e.cropping[1]]]:this.cropping=e.cropping,this.dataFormat=e.dataFormat===void 0?"channelsLast":e.dataFormat,this.inputSpec=[{ndim:4}]}computeOutputShape(e){return this.dataFormat==="channelsFirst"?[e[0],e[1],e[2]-this.cropping[0][0]-this.cropping[0][1],e[3]-this.cropping[1][0]-this.cropping[1][1]]:[e[0],e[1]-this.cropping[0][0]-this.cropping[0][1],e[2]-this.cropping[1][0]-this.cropping[1][1],e[3]]}call(e,t){return H(()=>{if(e=ze(e),this.dataFormat==="channelsLast"){let n=Ip(e,this.cropping[0][0],e.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return Ip(n,this.cropping[1][0],e.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let n=Ip(e,this.cropping[0][0],e.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return Ip(n,this.cropping[1][0],e.shape[3]-this.cropping[1][1]-this.cropping[1][0],4)}})}getConfig(){let e={cropping:this.cropping,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};t1.className="Cropping2D";oe.registerClass(t1);var n1=class extends Ze{constructor(e){super(e);this.DEFAULT_SIZE=[2,2],this.inputSpec=[{ndim:4}],this.size=e.size==null?this.DEFAULT_SIZE:e.size,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Ft(this.dataFormat),this.interpolation=e.interpolation==null?"nearest":e.interpolation,$O(this.interpolation)}computeOutputShape(e){if(this.dataFormat==="channelsFirst"){let t=e[2]==null?null:this.size[0]*e[2],n=e[3]==null?null:this.size[1]*e[3];return[e[0],e[1],t,n]}else{let t=e[1]==null?null:this.size[0]*e[1],n=e[2]==null?null:this.size[1]*e[2];return[e[0],t,n,e[3]]}}call(e,t){return H(()=>{let n=ze(e),s=n.shape;if(this.dataFormat==="channelsFirst"){n=Xe(n,[0,2,3,1]);let r=this.size[0]*s[2],a=this.size[1]*s[3],o=this.interpolation==="nearest"?_e.resizeNearestNeighbor(n,[r,a]):_e.resizeBilinear(n,[r,a]);return Xe(o,[0,3,1,2])}else{let r=this.size[0]*s[1],a=this.size[1]*s[2];return this.interpolation==="nearest"?_e.resizeNearestNeighbor(n,[r,a]):_e.resizeBilinear(n,[r,a])}})}getConfig(){let e={size:this.size,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};n1.className="UpSampling2D";oe.registerClass(n1);function xM(e,t,n=[1,1],s="valid",r,a){return H(()=>{r==null&&(r=zs()),Ft(r);let o=ZA(e,r);if(e.rank!==4)throw new G(`Input for depthwiseConv2d is required to be 4-D, but is instead ${e.rank}-D`);if(t.rank!==4)throw new G(`depthwiseKernel is required to be 4-D, but is instead ${t.rank}-D`);return o=cc(o,t,n,s==="same"?"same":"valid","NHWC",a),r==="channelsFirst"&&(o=Xe(o,[0,3,1,2])),o})}var s1=class extends YA{constructor(e){super(2,e);this.depthwiseKernel=null,this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=wt(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=Xt(e.depthwiseConstraint),this.depthwiseRegularizer=kt(e.depthwiseRegularizer)}build(e){if(e=at(e),e.length<4)throw new G(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(e)}.`);let t=this.dataFormat==="channelsFirst"?1:3;if(e[t]==null||e[t]<0)throw new G(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${e[t]}).`);let n=e[t],s=[this.kernelSize[0],this.kernelSize[1],n,this.depthMultiplier];this.depthwiseKernel=this.addWeight("depthwise_kernel",s,null,this.depthwiseInitializer,this.depthwiseRegularizer,!0,this.depthwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[n*this.depthMultiplier],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return H(()=>{e=ze(e);let n=xM(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(n=Ws(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),n})}computeOutputShape(e){e=at(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],s=this.dataFormat==="channelsFirst"?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,r=Hs(t,this.kernelSize[0],this.padding,this.strides[0]),a=Hs(n,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[e[0],s,r,a]:[e[0],r,a,s]}getConfig(){let e=super.getConfig();return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=Nt(this.depthwiseInitializer),e.depthwiseRegularizer=dt(this.depthwiseRegularizer),e.depthwiseConstraint=qt(this.depthwiseRegularizer),e}};s1.className="DepthwiseConv2D";oe.registerClass(s1);function vv(e,t,n,s){if(Array.isArray(e)){if(t!=null||n!=null)throw new G("When inputs is an array, neither initialState or constants should be provided");s!=null&&(n=e.slice(e.length-s,e.length),e=e.slice(0,e.length-s)),e.length>1&&(t=e.slice(1,e.length)),e=e[0]}function r(a){return a==null||Array.isArray(a)?a:[a]}return t=r(t),n=r(n),{inputs:e,initialState:t,constants:n}}function wv(e,t,n,s=!1,r,a,o=!1,i=!1){return H(()=>{let l=t.shape.length;if(l<3)throw new G(`Input should be at least 3D, but is ${l}D.`);let u=[1,0].concat(Bs(2,l));if(t=Xe(t,u),a!=null)throw new Oe("The rnn() functoin of the deeplearn.js backend does not support constants yet.");o&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),r!=null&&(r=ce(ce(r,"bool"),"float32"),r.rank===l-1&&(r=Ot(r,-1)),r=Xe(r,u)),s&&(t=fs(t,0),r!=null&&(r=fs(r,0)));let c=[],d,h=n,p=t.shape[0],f=ms(t),m;r!=null&&(m=ms(r));for(let A=0;A<p;++A){let y=f[A],x=H(()=>e(y,h));if(r==null)d=x[0],h=x[1];else{let b=H(()=>{let v=m[A],k=ge(ps(v),v),S=ae(L(x[0],v),L(h[0],k)),C=h.map((_,O)=>ae(L(x[1][O],v),L(_,k)));return{output:S,newStates:C}});d=b.output,h=b.newStates}i&&c.push(d)}let g;return i&&(g=Dn(c,1)),[d,g,h]})}var ur=class extends Ze{constructor(e){super(e);let t;if(e.cell==null)throw new G("cell property is missing for the constructor of RNN.");if(Array.isArray(e.cell)?t=new Kp({cells:e.cell}):t=e.cell,t.stateSize==null)throw new G("The RNN cell should have an attribute `stateSize` (tuple of integers, one integer per RNN state).");this.cell=t,this.returnSequences=e.returnSequences==null?!1:e.returnSequences,this.returnState=e.returnState==null?!1:e.returnState,this.goBackwards=e.goBackwards==null?!1:e.goBackwards,this._stateful=e.stateful==null?!1:e.stateful,this.unroll=e.unroll==null?!1:e.unroll,this.supportsMasking=!0,this.inputSpec=[new zt({ndim:3})],this.stateSpec=null,this.states_=null,this.numConstants=null,this.keptStates=[]}getStates(){if(this.states_==null){let e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;return Bs(0,e).map(t=>null)}else return this.states_}setStates(e){this.states_=e}computeOutputShape(e){SA(e)&&(e=e[0]),e=e;let t=this.cell.stateSize;Array.isArray(t)||(t=[t]);let n=t[0],s;if(this.returnSequences?s=[e[0],e[1],n]:s=[e[0],n],this.returnState){let r=[];for(let a of t)r.push([e[0],a]);return[s].concat(r)}else return s}computeMask(e,t){return H(()=>{Array.isArray(t)&&(t=t[0]);let n=this.returnSequences?t:null;if(this.returnState){let s=this.states.map(r=>null);return[n].concat(s)}else return n})}get states(){if(this.states_==null){let e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1,t=[];for(let n=0;n<e;++n)t.push(null);return t}else return this.states_}set states(e){this.states_=e}build(e){let t=null;if(this.numConstants!=null)throw new Oe("Constants support is not implemented in RNN yet.");SA(e)&&(e=e[0]),e=e;let n=this.stateful?e[0]:null,s=e.slice(2);this.inputSpec[0]=new zt({shape:[n,null,...s]});let r=[e[0]].concat(e.slice(2));if(t!=null)throw new Oe("Constants support is not implemented in RNN yet.");this.cell.build(r);let a;if(Array.isArray(this.cell.stateSize)?a=this.cell.stateSize:a=[this.cell.stateSize],this.stateSpec!=null){if(!w.arraysEqual(this.stateSpec.map(o=>o.shape[o.shape.length-1]),a))throw new G(`An initialState was passed that is not compatible with cell.stateSize. Received stateSpec=${this.stateSpec}; However cell.stateSize is ${this.cell.stateSize}`)}else this.stateSpec=a.map(o=>new zt({shape:[null,o]}));this.stateful&&this.resetStates()}resetStates(e,t=!1){H(()=>{if(!this.stateful)throw new Cr("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape[0];if(n==null)throw new G("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(this.states_==null)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(s=>Pt([n,s])):this.states_=[Pt([n,this.cell.stateSize])];else if(e==null)K(this.states_),this.keptStates!=null&&(K(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(s=>Pt([n,s])):this.states_[0]=Pt([n,this.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new G(`Layer ${this.name} expects ${this.states_.length} state(s), but it received ${e.length} state value(s). Input received: ${e}`);t===!0?this.keptStates.push(this.states_.slice()):K(this.states_);for(let s=0;s<this.states_.length;++s){let r=e[s],a=Array.isArray(this.cell.stateSize)?this.cell.stateSize[s]:this.cell.stateSize,o=[n,a];if(!w.arraysEqual(r.shape,o))throw new G(`State ${s} is incompatible with layer ${this.name}: expected shape=${o}, received shape=${r.shape}`);this.states_[s]=r}}this.states_=this.states_.map(s=>Jt(s.clone()))})}apply(e,t){let n=t==null?null:t.initialState,s=t==null?null:t.constants;t==null&&(t={});let r=vv(e,n,s,this.numConstants);e=r.inputs,n=r.initialState,s=r.constants;let a=[],o=[];if(n!=null){t.initialState=n,a=a.concat(n),this.stateSpec=[];for(let l of n)this.stateSpec.push(new zt({shape:l.shape}));o=o.concat(this.stateSpec)}if(s!=null&&(t.constants=s,a=a.concat(s),this.numConstants=s.length),a[0]instanceof Vs){let l=[e].concat(a),u=this.inputSpec.concat(o),c=this.inputSpec;this.inputSpec=u;let d=super.apply(l,t);return this.inputSpec=c,d}else return super.apply(e,t)}call(e,t){return H(()=>{let n=t==null?null:t.mask,s=t==null?null:t.training,r=t==null?null:t.initialState;e=ze(e),r==null&&(this.stateful?r=this.states_:r=this.getInitialState(e));let a=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;if(r.length!==a)throw new G(`RNN Layer has ${a} state(s) but was passed ${r.length} initial state(s).`);this.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");let o={training:s},l=wv((p,f)=>{let m=this.cell.call([p].concat(f),o);return[m[0],m.slice(1)]},e,r,this.goBackwards,n,null,this.unroll,this.returnSequences),u=l[0],c=l[1],d=l[2];this.stateful&&this.resetStates(d,s);let h=this.returnSequences?c:u;return this.returnState?[h].concat(d):h})}getInitialState(e){return H(()=>{let t=Pt(e.shape);return t=ve(t,[1,2]),t=kc(t),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(n=>n>1?gA(t,[1,n]):t):this.cell.stateSize>1?[gA(t,[1,this.cell.stateSize])]:[t]})}get trainableWeights(){return this.trainable?this.cell.trainableWeights:[]}get nonTrainableWeights(){return this.trainable?this.cell.nonTrainableWeights:this.cell.weights}setFastWeightInitDuringBuild(e){super.setFastWeightInitDuringBuild(e),this.cell!=null&&this.cell.setFastWeightInitDuringBuild(e)}getConfig(){let e=super.getConfig(),t={returnSequences:this.returnSequences,returnState:this.returnState,goBackwards:this.goBackwards,stateful:this.stateful,unroll:this.unroll};this.numConstants!=null&&(t.numConstants=this.numConstants);let n=this.cell.getConfig();return this.getClassName()===ur.className&&(t.cell={className:this.cell.getClassName(),config:n}),Object.assign({},n,e,t)}static fromConfig(e,t,n={}){let s=t.cell,r=Us(s,n);return new e(Object.assign(t,{cell:r}))}};ur.className="RNN";oe.registerClass(ur);var Fc=class extends Ze{},qp=class extends Fc{constructor(e){super(e);this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=e.units,Qt(this.units,"units"),this.activation=ia(e.activation==null?this.DEFAULT_ACTIVATION:e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=wt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=wt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=wt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=kt(e.kernelRegularizer),this.recurrentRegularizer=kt(e.recurrentRegularizer),this.biasRegularizer=kt(e.biasRegularizer),this.kernelConstraint=Xt(e.kernelConstraint),this.recurrentConstraint=Xt(e.recurrentConstraint),this.biasConstraint=Xt(e.biasConstraint),this.dropout=Hl([1,ra([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Hl([1,ra([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=at(e),this.kernel=this.addWeight("kernel",[e[e.length-1],this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias?this.bias=this.addWeight("bias",[this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return H(()=>{if(e=e,e.length!==2)throw new G(`SimpleRNNCell expects 2 input Tensors, got ${e.length}.`);let n=e[1];e=e[0];let s=t.training==null?!1:t.training;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=la({ones:()=>ps(e),rate:this.dropout,training:s})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=la({ones:()=>ps(n),rate:this.recurrentDropout,training:s}));let r,a=this.dropoutMask,o=this.recurrentDropoutMask;a!=null?r=or(L(e,a),this.kernel.read()):r=or(e,this.kernel.read()),this.bias!=null&&(r=Ws(r,this.bias.read())),o!=null&&(n=L(n,o));let i=ae(r,or(n,this.recurrentKernel.read()));return this.activation!=null&&(i=this.activation.apply(i)),[i,i]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:oa(this.activation),useBias:this.useBias,kernelInitializer:Nt(this.kernelInitializer),recurrentInitializer:Nt(this.recurrentInitializer),biasInitializer:Nt(this.biasInitializer),kernelRegularizer:dt(this.kernelRegularizer),recurrentRegularizer:dt(this.recurrentRegularizer),biasRegularizer:dt(this.biasRegularizer),activityRegularizer:dt(this.activityRegularizer),kernelConstraint:qt(this.kernelConstraint),recurrentConstraint:qt(this.recurrentConstraint),biasConstraint:qt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign({},e,t)}};qp.className="SimpleRNNCell";oe.registerClass(qp);var r1=class extends ur{constructor(e){e.cell=new qp(e);super(e)}call(e,t){return H(()=>{this.cell.dropoutMask!=null&&(K(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(K(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,s=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:s,initialState:r})})}static fromConfig(e,t){return new e(t)}};r1.className="SimpleRNN";oe.registerClass(r1);var Xp=class extends Fc{constructor(e){super(e);if(this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",e.resetAfter)throw new G("GRUCell does not support reset_after parameter set to true.");this.units=e.units,Qt(this.units,"units"),this.activation=ia(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=ia(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=wt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=wt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=wt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=kt(e.kernelRegularizer),this.recurrentRegularizer=kt(e.recurrentRegularizer),this.biasRegularizer=kt(e.biasRegularizer),this.kernelConstraint=Xt(e.kernelConstraint),this.recurrentConstraint=Xt(e.recurrentConstraint),this.biasConstraint=Xt(e.biasConstraint),this.dropout=Hl([1,ra([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Hl([1,ra([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=at(e);let t=e[e.length-1];this.kernel=this.addWeight("kernel",[t,this.units*3],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units*3],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias?this.bias=this.addWeight("bias",[this.units*3],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return H(()=>{if(e=e,e.length!==2)throw new G(`GRUCell expects 2 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training==null?!1:t.training,s=e[1];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=la({ones:()=>ps(e),rate:this.dropout,training:n,count:3})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=la({ones:()=>ps(s),rate:this.recurrentDropout,training:n,count:3}));let r=this.dropoutMask,a=this.recurrentDropoutMask,o,i,l;0<this.dropout&&this.dropout<1&&(e=L(e,r[0]));let u=or(e,this.kernel.read());this.useBias&&(u=Ws(u,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(s=L(s,a[0]));let c=this.recurrentKernel.read(),[d,h]=an(c,[2*this.units,this.units],c.rank-1),p=or(s,d),[f,m,g]=an(u,3,u.rank-1),[A,y]=an(p,2,p.rank-1);o=this.recurrentActivation.apply(ae(f,A)),i=this.recurrentActivation.apply(ae(m,y));let x=or(L(i,s),h);l=this.activation.apply(ae(g,x));let b=ae(L(o,s),L(ae(1,Tt(o)),l));return[b,b]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:oa(this.activation),recurrentActivation:oa(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Nt(this.kernelInitializer),recurrentInitializer:Nt(this.recurrentInitializer),biasInitializer:Nt(this.biasInitializer),kernelRegularizer:dt(this.kernelRegularizer),recurrentRegularizer:dt(this.recurrentRegularizer),biasRegularizer:dt(this.biasRegularizer),activityRegularizer:dt(this.activityRegularizer),kernelConstraint:qt(this.kernelConstraint),recurrentConstraint:qt(this.recurrentConstraint),biasConstraint:qt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign({},e,t)}};Xp.className="GRUCell";oe.registerClass(Xp);var a1=class extends ur{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new Xp(e);super(e)}call(e,t){return H(()=>{this.cell.dropoutMask!=null&&(K(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(K(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,s=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:s,initialState:r})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};a1.className="GRU";oe.registerClass(a1);var Oc=class extends Fc{constructor(e){super(e);this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=e.units,Qt(this.units,"units"),this.activation=ia(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=ia(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=wt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=wt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=wt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.unitForgetBias=e.unitForgetBias,this.kernelRegularizer=kt(e.kernelRegularizer),this.recurrentRegularizer=kt(e.recurrentRegularizer),this.biasRegularizer=kt(e.biasRegularizer),this.kernelConstraint=Xt(e.kernelConstraint),this.recurrentConstraint=Xt(e.recurrentConstraint),this.biasConstraint=Xt(e.biasConstraint),this.dropout=Hl([1,ra([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Hl([1,ra([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=[this.units,this.units],this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){var t;e=at(e);let n=e[e.length-1];this.kernel=this.addWeight("kernel",[n,this.units*4],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units*4],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint);let s;if(this.useBias){if(this.unitForgetBias){let r=this.biasInitializer,a=this.units;s=new(t=class extends Es{apply(i,l){let u=r.apply([a]),c=new Cp().apply([a]),d=r.apply([a*2]);return A3(A3(u,c),d)}},t.className="CustomInit",t)}else s=this.biasInitializer;this.bias=this.addWeight("bias",[this.units*4],null,s,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0}call(e,t){return H(()=>{let n=t.training==null?!1:t.training;if(e=e,e.length!==3)throw new G(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let s=e[1],r=e[2];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=la({ones:()=>ps(e),rate:this.dropout,training:n,count:4})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=la({ones:()=>ps(s),rate:this.recurrentDropout,training:n,count:4}));let a=this.dropoutMask,o=this.recurrentDropoutMask,i,l,u,c;0<this.dropout&&this.dropout<1&&(e=L(e,a[0]));let d=or(e,this.kernel.read());0<this.recurrentDropout&&this.recurrentDropout<1&&(s=L(s,o[0])),d=ae(d,or(s,this.recurrentKernel.read())),this.useBias&&(d=Ws(d,this.bias.read()));let[h,p,f,m]=an(d,4,d.rank-1);i=this.recurrentActivation.apply(h),l=this.recurrentActivation.apply(p),u=ae(L(l,r),L(i,this.activation.apply(f))),c=this.recurrentActivation.apply(m);let g=L(c,this.activation.apply(u));return[g,g,u]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:oa(this.activation),recurrentActivation:oa(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Nt(this.kernelInitializer),recurrentInitializer:Nt(this.recurrentInitializer),biasInitializer:Nt(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:dt(this.kernelRegularizer),recurrentRegularizer:dt(this.recurrentRegularizer),biasRegularizer:dt(this.biasRegularizer),activityRegularizer:dt(this.activityRegularizer),kernelConstraint:qt(this.kernelConstraint),recurrentConstraint:qt(this.recurrentConstraint),biasConstraint:qt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return Object.assign({},e,t)}};Oc.className="LSTMCell";oe.registerClass(Oc);var o1=class extends ur{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new Oc(e);super(e)}call(e,t){return H(()=>{this.cell.dropoutMask!=null&&(K(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(K(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,s=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:s,initialState:r})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};o1.className="LSTM";oe.registerClass(o1);var Kp=class extends Fc{constructor(e){super(e);this.cells=e.cells}get stateSize(){let e=[];for(let t of this.cells.slice().reverse())Array.isArray(t.stateSize)?e.push(...t.stateSize):e.push(t.stateSize);return e}call(e,t){return H(()=>{e=e;let n=e.slice(1),s=[];for(let o of this.cells.slice().reverse())Array.isArray(o.stateSize)?s.push(n.splice(0,o.stateSize.length)):s.push(n.splice(0,1));s.reverse();let r=[],a;for(let o=0;o<this.cells.length;++o){let i=this.cells[o];n=s[o],o===0?a=[e[0]].concat(n):a=[a[0]].concat(n),a=i.call(a,t),r.push(a.slice(1))}n=[];for(let o of r.slice().reverse())n.push(...o);return[a[0]].concat(n)})}build(e){SA(e)&&(e=e[0]),e=e;let t;this.cells.forEach((n,s)=>{Uo(`RNNCell_${s}`,()=>{n.build(e),Array.isArray(n.stateSize)?t=n.stateSize[0]:t=n.stateSize,e=[e[0],t]})}),this.built=!0}getConfig(){let e=super.getConfig(),t=r=>({className:r.getClassName(),config:r.getConfig()}),s={cells:this.cells.map(t)};return Object.assign({},e,s)}static fromConfig(e,t,n={}){let s=[];for(let r of t.cells)s.push(Us(r,n));return new e({cells:s})}get trainableWeights(){if(!this.trainable)return[];let e=[];for(let t of this.cells)e.push(...t.trainableWeights);return e}get nonTrainableWeights(){let e=[];for(let t of this.cells)e.push(...t.nonTrainableWeights);if(!this.trainable){let t=[];for(let n of this.cells)t.push(...n.trainableWeights);return t.concat(e)}return e}getWeights(){let e=[];for(let t of this.cells)e.push(...t.weights);return CA(e)}setWeights(e){let t=[];for(let n of this.cells){let s=n.weights.length,r=e.splice(s);for(let a=0;a<n.weights.length;++a)t.push([n.weights[a],r[a]])}TA(t)}};Kp.className="StackedRNNCells";oe.registerClass(Kp);function la(e){let{ones:t,rate:n,training:s=!1,count:r=1}=e,a=()=>x3(t(),n),o=()=>Sc(a,t,s);return!r||r<=1?Jt(o().clone()):Array(r).fill(void 0).map(o).map(l=>Jt(l.clone()))}var bM=function(e,t){var n={};for(var s in e)Object.prototype.hasOwnProperty.call(e,s)&&t.indexOf(s)<0&&(n[s]=e[s]);if(e!=null&&typeof Object.getOwnPropertySymbols=="function")for(var r=0,s=Object.getOwnPropertySymbols(e);r<s.length;r++)t.indexOf(s[r])<0&&Object.prototype.propertyIsEnumerable.call(e,s[r])&&(n[s[r]]=e[s[r]]);return n},kv=class extends ur{constructor(e){if(e.unroll)throw new Oe("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(e.cell))throw new Oe("It is not possible at the moment to stack convolutional cells.");super(e);this.inputSpec=[new zt({ndim:5})]}call(e,t){return H(()=>{if(this.cell.dropoutMask!=null&&(K(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(K(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),t&&t.constants)throw new G("ConvRNN2D cell does not support constants");let n=t==null?null:t.mask,s=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:s,initialState:r})})}computeOutputShape(e){let t=this.computeSingleOutputShape(e);return this.returnSequences||(t=[t[0],...t.slice(2)]),this.returnState&&(t=[t,...Array(2).fill([e[0],...t.slice(-3)])]),t}getInitialState(e){return H(()=>{let{stateSize:t}=this.cell,n=e.shape,s=this.computeSingleOutputShape(n),r=[s[0],...s.slice(2)],a=Pt(r);return Array.isArray(t)?Array(t.length).fill(a):[a]})}resetStates(e,t=!1){H(()=>{if(!this.stateful)throw new Cr("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape,s=this.computeSingleOutputShape(n),r=[s[0],...s.slice(2)];if(n[0]==null)throw new G("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(this.getStates()==null)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Pt(r)):this.states_=[Pt(r)];else if(e==null)K(this.states_),this.keptStates!=null&&(K(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Pt(r)):this.states_[0]=Pt(r);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new G(`Layer ${this.name} expects ${this.states_.length} state(s), but it received ${e.length} state value(s). Input received: ${e}`);t?this.keptStates.push(this.states_.slice()):K(this.states_);for(let o=0;o<this.states_.length;++o){let i=e[o],l=r;if(!w.arraysEqual(i.shape,l))throw new G(`State ${o} is incompatible with layer ${this.name}: expected shape=${l}, received shape=${i.shape}`);this.states_[o]=i}}this.states_=this.states_.map(o=>Jt(o.clone()))})}computeSingleOutputShape(e){let{dataFormat:t,filters:n,kernelSize:s,padding:r,strides:a,dilationRate:o}=this.cell,i=t==="channelsFirst",l=e[i?3:2],u=e[i?4:3],c=Hs(l,s[0],r,a[0],o[0]),d=Hs(u,s[1],r,a[1],o[1]);return[...e.slice(0,2),...i?[n,c,d]:[c,d,n]]}};kv.className="ConvRNN2D";var Zp=class extends Oc{constructor(e){let{filters:t,kernelSize:n,strides:s,padding:r,dataFormat:a,dilationRate:o}=e;super(Object.assign({},e,{units:t}));this.filters=t,Qt(this.filters,"filters"),this.kernelSize=Kl(n,2,"kernelSize"),this.kernelSize.forEach(i=>Qt(i,"kernelSize")),this.strides=Kl(s||1,2,"strides"),this.strides.forEach(i=>Qt(i,"strides")),this.padding=r||"valid",gs(this.padding),this.dataFormat=a||"channelsLast",Ft(this.dataFormat),this.dilationRate=Kl(o||1,2,"dilationRate"),this.dilationRate.forEach(i=>Qt(i,"dilationRate"))}build(e){var t;e=at(e);let n=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[n]==null)throw new G(`The channel dimension of the input should be defined. Found ${e[n]}`);let s=e[n],r=4,a=this.kernelSize.concat([s,this.filters*r]);this.kernel=this.addWeight("kernel",a,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);let o=this.kernelSize.concat([this.filters,this.filters*r]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",o,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){let i;if(this.unitForgetBias){let l=this.biasInitializer,u=this.filters;i=new(t=class extends Es{apply(d,h){let p=l.apply([u]),f=qn([u]),m=l.apply([u*2]);return mA([p,f,m])}},t.className="CustomInit",t)}else i=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*r],null,i,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(e,t){return H(()=>{if(e.length!==3)throw new G(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training||!1,s=e[0],r=e[1],a=e[2],o=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=la({ones:()=>ps(s),rate:this.dropout,training:n,count:o}));let i=this.dropoutMask,l=(ee,te,ne)=>!te||!te[ne]?ee:L(te[ne],ee),u=l(s,i,0),c=l(s,i,1),d=l(s,i,2),h=l(s,i,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=la({ones:()=>ps(r),rate:this.recurrentDropout,training:n,count:o}));let p=this.recurrentDropoutMask,f=l(r,p,0),m=l(r,p,1),g=l(r,p,2),A=l(r,p,3),y=3,[x,b,v,k]=an(this.kernel.read(),o,y),[S,C,_,O]=this.useBias?an(this.bias.read(),o):[null,null,null,null];u=this.inputConv(u,x,S,this.padding),c=this.inputConv(c,b,C,this.padding),d=this.inputConv(d,v,_,this.padding),h=this.inputConv(h,k,O,this.padding);let[E,R,T,P]=an(this.recurrentKernel.read(),o,y);f=this.recurrentConv(f,E),m=this.recurrentConv(m,R),g=this.recurrentConv(g,T),A=this.recurrentConv(A,P);let V=this.recurrentActivation.apply(ae(u,f)),j=this.recurrentActivation.apply(ae(c,m)),q=ae(L(j,a),L(V,this.activation.apply(ae(d,g)))),X=L(this.recurrentActivation.apply(ae(h,A)),this.activation.apply(q));return[X,X,q]})}getConfig(){let e=super.getConfig(),{units:t}=e,n=bM(e,["units"]),s={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign({},n,s)}inputConv(e,t,n,s){let r=Jr(e,t,this.strides,s||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return n?Ws(r,n,this.dataFormat):r}recurrentConv(e,t){return Jr(e,t,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};Zp.className="ConvLSTM2DCell";oe.registerClass(Zp);var i1=class extends kv{constructor(e){let t=new Zp(e);super(Object.assign({},e,{cell:t}))}static fromConfig(e,t){return new e(t)}};i1.className="ConvLSTM2D";oe.registerClass(i1);var Yp=class extends Ze{constructor(e){super(e);this.rate=Math.max(Math.min(e.rate,1),0),this.noiseShape=e.noiseShape,this.seed=e.seed,this.supportsMasking=!0}getNoiseShape(e){if(this.noiseShape==null)return this.noiseShape;let t=e.shape,n=[];for(let s=0;s<this.noiseShape.length;++s)n.push(this.noiseShape[s]==null?t[s]:this.noiseShape[s]);return n}call(e,t){return H(()=>{this.invokeCallHook(e,t);let n=ze(e);if(0<this.rate&&this.rate<1){let s=t.training==null?!1:t.training,r=this.getNoiseShape(n);return Sc(()=>x3(n,this.rate,r,this.seed),()=>n,s)}return e})}getConfig(){let e={rate:this.rate,noiseShape:this.noiseShape,seed:this.seed},t=super.getConfig();return Object.assign(e,t),e}dispose(){return super.dispose()}};Yp.className="Dropout";oe.registerClass(Yp);var l1=class extends Yp{constructor(e){super(e);this.inputSpec=[{ndim:3}]}getNoiseShape(e){let t=e.shape;return[t[0],1,t[2]]}};l1.className="SpatialDropout1D";oe.registerClass(l1);var u1=class extends Ze{constructor(e){super(e);if(this.activation=null,this.useBias=!0,this.kernel=null,this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",e.batchInputShape==null&&e.inputShape==null&&e.inputDim!=null){let t=null;e.batchSize!=null&&(t=e.batchSize),this.batchInputShape=[t,e.inputDim]}this.units=e.units,Qt(this.units,"units"),this.activation=ia(e.activation),e.useBias!=null&&(this.useBias=e.useBias),this.kernelInitializer=wt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=wt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=Xt(e.kernelConstraint),this.biasConstraint=Xt(e.biasConstraint),this.kernelRegularizer=kt(e.kernelRegularizer),this.biasRegularizer=kt(e.biasRegularizer),this.activityRegularizer=kt(e.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(e){e=at(e);let t=e[e.length-1];this.kernel==null&&(this.kernel=this.addWeight("kernel",[t,this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint))),this.inputSpec=[{minNDim:2,axes:{[-1]:t}}],this.built=!0}computeOutputShape(e){e=at(e);let t=e.slice();return t[t.length-1]=this.units,t}call(e,t){return H(()=>{this.invokeCallHook(e,t);let n=ze(e),s=l3(this.activation.getClassName()),r;return s!=null?r=or(n,this.kernel.read(),s,this.bias?this.bias.read():null):(r=or(n,this.kernel.read()),this.bias!=null&&(r=Ws(r,this.bias.read())),this.activation!=null&&(r=this.activation.apply(r))),r})}getConfig(){let e={units:this.units,activation:oa(this.activation),useBias:this.useBias,kernelInitializer:Nt(this.kernelInitializer),biasInitializer:Nt(this.biasInitializer),kernelRegularizer:dt(this.kernelRegularizer),biasRegularizer:dt(this.biasRegularizer),activityRegularizer:dt(this.activityRegularizer),kernelConstraint:qt(this.kernelConstraint),biasConstraint:qt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}};u1.className="Dense";oe.registerClass(u1);var c1=class extends Ze{constructor(e){e=e||{};super(e);this.inputSpec=[{minNDim:3}],this.dataFormat=e.dataFormat}computeOutputShape(e){e=at(e);for(let t of e.slice(1))if(t==null)throw new G(`The shape of the input to "Flatten" is not fully defined (got ${e.slice(1)}). Make sure to pass a complete "input_shape" or "batch_input_shape" argument to the first layer in your model.`);return[e[0],sa(e,1)]}call(e,t){return H(()=>{this.invokeCallHook(e,t);let n=ze(e);if(this.dataFormat==="channelsFirst"&&n.rank>1){let s=[0];for(let r=2;r<n.rank;++r)s.push(r);s.push(1),n=Xe(n,s)}return LO(n)})}getConfig(){let e={};this.dataFormat!=null&&(e.dataFormat=this.dataFormat);let t=super.getConfig();return Object.assign(e,t),e}};c1.className="Flatten";oe.registerClass(c1);var d1=class extends Ze{constructor(e){super(e);this.supportsMasking=!0,this.activation=ia(e.activation)}call(e,t){return H(()=>{this.invokeCallHook(e,t);let n=ze(e);return this.activation.apply(n)})}getConfig(){let e={activation:oa(this.activation)},t=super.getConfig();return Object.assign(e,t),e}};d1.className="Activation";oe.registerClass(d1);var h1=class extends Ze{constructor(e){super(e);this.n=e.n,this.inputSpec=[{ndim:2}]}computeOutputShape(e){return[e[0],this.n,e[1]]}call(e,t){return H(()=>(e=ze(e),MO(e,this.n)))}getConfig(){let e={n:this.n},t=super.getConfig();return Object.assign(e,t),e}};h1.className="RepeatVector";oe.registerClass(h1);var p1=class extends Ze{constructor(e){super(e);this.targetShape=e.targetShape;for(let t=0;t<this.targetShape.length;++t)this.isUnknown(this.targetShape[t])&&(this.targetShape[t]=null)}isUnknown(e){return e<0||e==null}fixUnknownDimension(e,t){let n="Total size of new array must be unchanged.",s=t.slice(),r=1,a=null;for(let i=0;i<s.length;++i){let l=s[i];if(this.isUnknown(l))if(a===null)a=i;else throw new G("Can only specifiy one unknown dimension.");else r*=l}let o=sa(e);if(a!==null){if(r===0||o%r!=0)throw new G(n);s[a]=o/r}else if(o!==r)throw new G(n);return s}computeOutputShape(e){let t=!1;for(let n=0;n<e.length;++n)if(this.isUnknown(e[n])){t=!0;break}return t?e.slice(0,1).concat(this.targetShape):e.slice(0,1).concat(this.fixUnknownDimension(e.slice(1),this.targetShape))}call(e,t){return H(()=>{this.invokeCallHook(e,t);let n=ze(e),s=n.shape,r=s.slice(0,1).concat(this.fixUnknownDimension(s.slice(1),this.targetShape));return U(n,r)})}getConfig(){let e={targetShape:this.targetShape},t=super.getConfig();return Object.assign(e,t),e}};p1.className="Reshape";oe.registerClass(p1);var f1=class extends Ze{constructor(e){super(e);if(e.dims==null)throw new Error("Required configuration field `dims` is missing during Permute constructor call.");if(!Array.isArray(e.dims))throw new Error(`Permute constructor requires \`dims\` to be an Array, but received ${e.dims} instead.`);let t=Bs(1,e.dims.length+1);if(!w.arraysEqual(e.dims.slice().sort(),t))throw new Error("Invalid permutation `dims`: "+JSON.stringify(e.dims)+" `dims` must contain consecutive integers starting from 1.");this.dims=e.dims,this.dimsIncludingBatch=[0].concat(this.dims),this.inputSpec=[new zt({ndim:this.dims.length+1})]}computeOutputShape(e){e=at(e);let t=e.slice();return this.dims.forEach((n,s)=>{t[s+1]=e[n]}),t}call(e,t){return Xe(ze(e),this.dimsIncludingBatch)}getConfig(){let e={dims:this.dims},t=super.getConfig();return Object.assign(e,t),e}};f1.className="Permute";oe.registerClass(f1);var m1=class extends Ze{constructor(e){super(e==null?{}:e);this.supportsMasking=!0,e!=null?this.maskValue=e.maskValue==null?0:e.maskValue:this.maskValue=0}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={maskValue:this.maskValue};return Object.assign(t,e),t}computeMask(e,t){let n=ze(e),s=-1;return Uh(Ll(n,this.maskValue),s)}call(e,t){return H(()=>{this.invokeCallHook(e,t);let n=ze(e),s=-1,r=!0,a=Uh(Ll(n,this.maskValue),s,r);return L(n,ce(a,n.dtype))})}};m1.className="Masking";oe.registerClass(m1);var g1=class extends Ze{constructor(e){super(e);if(this.embeddings=null,this.DEFAULT_EMBEDDINGS_INITIALIZER="randomUniform",e.batchInputShape==null&&e.inputShape==null){let t=null;e.batchSize!=null&&(t=e.batchSize),e.inputLength==null?this.batchInputShape=[t,null]:this.batchInputShape=[t].concat(yt(e.inputLength))}this.inputDim=e.inputDim,Qt(this.inputDim,"inputDim"),this.outputDim=e.outputDim,Qt(this.outputDim,"outputDim"),this.embeddingsInitializer=wt(e.embeddingsInitializer||this.DEFAULT_EMBEDDINGS_INITIALIZER),this.embeddingsRegularizer=kt(e.embeddingsRegularizer),this.activityRegularizer=kt(e.activityRegularizer),this.embeddingsConstraint=Xt(e.embeddingsConstraint),this.maskZero=e.maskZero,this.supportsMasking=e.maskZero,this.inputLength=e.inputLength}build(e){this.embeddings=this.addWeight("embeddings",[this.inputDim,this.outputDim],this.dtype,this.embeddingsInitializer,this.embeddingsRegularizer,!0,this.embeddingsConstraint),this.built=!0}warnOnIncompatibleInputShape(e){}computeMask(e,t){return H(()=>this.maskZero?(e=ze(e),Ll(e,Ke(e))):null)}computeOutputShape(e){if(e=at(e),this.inputLength==null)return[...e,this.outputDim];let t=yt(this.inputLength);if(t.length!==e.length-1)throw new G(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);{let n=0;for(let s=0;s<t.length;++s){let r=t[s],a=e[s+1];if(r!=null&&a!=null&&r!==a)throw new G(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);r==null&&(t[n]=a),n++}}return[e[0],...t,this.outputDim]}call(e,t){return H(()=>{this.invokeCallHook(e,t);let n=ze(e);n.dtype!=="int32"&&(n=kp(n,"int32"));let s=y3(this.embeddings.read(),U(n,[n.size]));return U(s,at(this.computeOutputShape(n.shape)))})}getConfig(){let e={inputDim:this.inputDim,outputDim:this.outputDim,embeddingsInitializer:Nt(this.embeddingsInitializer),embeddingsRegularizer:dt(this.embeddingsRegularizer),activityRegularizer:dt(this.activityRegularizer),embeddingsConstraint:qt(this.embeddingsConstraint),maskZero:this.maskZero,inputLength:this.inputLength},t=super.getConfig();return Object.assign(e,t),e}};g1.className="Embedding";oe.registerClass(g1);var Xo=class extends Ze{constructor(e){super(e||{});this.supportsMasking=!0}mergeFunction(e){throw new Oe}computeElementwiseOpOutputShape(e,t){if(e==null||t==null)return null;if(e.length<t.length)return this.computeElementwiseOpOutputShape(t,e);if(t.length===0)return e;let n=e.slice(0,e.length-t.length);for(let s=0;s<t.length;++s){let r=e[e.length-t.length+s],a=t[s];if(r==null||a==null||r<0||a<0)n.push(null);else if(r===1)n.push(a);else if(a===1)n.push(r);else{if(r!==a)throw new G("Operands could not be broadcast together with shapes "+JSON.stringify(e)+" "+JSON.stringify(t));n.push(r)}}return n}build(e){if(Array.isArray(e)&&!Array.isArray(e[0])&&(e=[at(e)]),e=e,e.length<2)throw new G(`A merge layer should be called on an Array of at least 2 inputs. Got ${e.length} input(s).`);let t=[];for(let r of e)r!=null&&r[0]!==null&&t.push(r[0]);if(t=na(t),t.length>1)throw new G(`Can not merge tensors with different batch sizes. Got tensors with shapes: ${JSON.stringify(e)}.`);let n=e[0]==null?null:e[0].slice(1);for(let r=1;r<e.length;++r){let a=e[r]==null?null:e[r].slice(1);n=this.computeElementwiseOpOutputShape(n,a)}let s=e.map(r=>r.length);e.indexOf(null)===-1&&na(s).length===1?this.reshapeRequired=!1:this.reshapeRequired=!0}call(e,t){return H(()=>{if(e=e,this.reshapeRequired){let n=[],s=e.map(r=>r.rank);if(s.indexOf(null)===-1){let r=ra(s);for(let a of e){let o=a.rank;for(let i=0;i<r-o;++i)a=kc(a,1);n.push(a)}return this.mergeFunction(n)}else{let r=!1;for(let i of e){let l=i.rank;if(l==null){let u=i.shape,c=u[0],d=u.slice(1).concat([c]),h=U(i,[c].concat(sa(u.slice(1))));h=Xe(h,[1,0]),h=U(h,d),n.push(h),r=!0}else if(l>1){let u=Bs(1,l).concat([0]);n.push(Xe(i,u)),r=!0}else n.push(i)}let a=this.mergeFunction(n),o=a.rank;if(r){if(o==null){let i=a.shape,l=i.length,u=i[l-1],c=[u].concat(i.slice(0,i.length-1));a=U(Xe(U(a,[-1,u]),[1,0]),c)}else if(o>1){let i=[o-1].concat(Bs(0,o-1));a=Xe(a,i)}}return a}}else return this.mergeFunction(e)})}computeOutputShape(e){e=e;let t;e[0]==null?t=null:t=e[0].slice(1);for(let s=1;s<e.length;++s){let r=e[s]==null?null:e[s].slice(1);t=this.computeElementwiseOpOutputShape(t,r)}let n=[];for(let s of e)s!=null&&s[0]!==null&&n.push(s[0]);return n=na(n),n.length===1?t=n.concat(t):t=[null].concat(t),t}computeMask(e,t){return H(()=>{if(t==null)return null;if(!Array.isArray(t))throw new G("`mask` should be an Array");if(!Array.isArray(e))throw new G("`inputs` should be an Array");if(t.length!==e.length)throw new G(`The Array 'inputs' and 'mask' are expected to have the same length, but have different lengths (${e.length} vs ${t.length})`);if(t.every(s=>s==null))return null;t=t.map(s=>s==null?s:Ot(s,0));let n=t[0];for(let s=1;s<t.length-1;++s)n=Ps(n,t[s]);return n})}},A1=class extends Xo{constructor(e){super(e)}mergeFunction(e){return H(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=ae(t,e[n]);return t})}};A1.className="Add";oe.registerClass(A1);var y1=class extends Xo{constructor(e){super(e)}mergeFunction(e){return H(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=L(t,e[n]);return t})}};y1.className="Multiply";oe.registerClass(y1);var x1=class extends Xo{constructor(e){super(e)}mergeFunction(e){return H(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=ae(t,e[n]);return L(1/e.length,t)})}};x1.className="Average";oe.registerClass(x1);var b1=class extends Xo{constructor(e){super(e)}mergeFunction(e){return H(()=>{let t=e[0];for(let n=1;n<e.length;++n)t=kr(t,e[n]);return t})}};b1.className="Maximum";oe.registerClass(b1);var v1=class extends Xo{constructor(e){super(e)}mergeFunction(e){return H(()=>{let t=e[0];for(let n=1;n<e.length;++n)t=pc(t,e[n]);return t})}};v1.className="Minimum";oe.registerClass(v1);var w1=class extends Xo{constructor(e){super(e);this.DEFAULT_AXIS=-1,e==null&&(e={}),this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){if(!(Array.isArray(e)&&Array.isArray(e[0]))||e.length===1)throw new G("A `Concatenate` layer should be called on a list of at least 2 inputs");e=e;let t=!0;for(let s of e)if(s!=null){t=!1;break}if(t)return;let n=[];for(let s=0;s<e.length;++s){let r=e[s].slice();r.splice(this.axis,1);let a=!1;for(let o of n)if(w.arraysEqual(o,r)){a=!0;break}a||n.push(r)}if(n.length>1)throw new G("A `Concatenate` layer requires inputs with matching shapes except for the concat axis. Got input shapes: "+JSON.stringify(e))}mergeFunction(e){return H(()=>mA(e,this.axis))}computeOutputShape(e){if(!(Array.isArray(e)&&Array.isArray(e[0])))throw new G("A `Concatenate` layer should be called on a list of inputs.");let t=e,n=t[0].slice(),s=this.axis<0?n.length+this.axis:this.axis;for(let r of t.slice(1)){if(n[s]==null||r[s]==null){n[s]=null;break}n[s]+=r[s]}return n}computeMask(e,t){if(t==null)return null;if(!Array.isArray(t))throw new G("`mask` should be an array for Concatenate");if(!Array.isArray(e))throw new G("`inputs` should be an array for Concatenate");if(t.length!==e.length)throw new G(`Mismatch in the length of mask (${t.length}) and the legnth of inputs (${e.length})`);return H(()=>{let n=!0;if(t.forEach(a=>{if(a!=null){n=!1;return}}),n)return null;let s=[];for(let a=0;a<e.length;++a)t[a]==null?s.push(ce(ps(e[a]),"bool")):t[a].rank<e[a].rank?s.push(Ot(t[a],-1)):s.push(t[a]);let r=ft(s,this.axis);return bg(r,-1,!1)})}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};w1.className="Concatenate";oe.registerClass(w1);function Pc(e,t){for(;e<0;)e+=t;return e}function vM(e,t,n){if(e.shape.length>3||t.shape.length>3)throw new Oe("batchDot is not implemented for tensors of 4D or higher rank yet");if(w.assert(e.shape.length>=2,()=>`batchDot requires the rank of x to be >= 2, but got ${e.shape.length}`),w.assert(e.shape.length>=2,()=>`batchDot requires the rank of y to be >= 2, but got ${t.shape.length}`),typeof n=="number"&&(n=[n,n]),e.dtype==="complex64"||t.dtype==="complex64")throw new Oe("batchDot is not implemented for complex64-type Tensors yet.");let s=e.shape.length,r=t.shape.length;n==null&&(n=[s-1,r-2]);let a=n;return H(()=>{let o;if(s>r){o=s-r;let l=[];for(let u=0;u<o;++u)l.push(1);t=U(t,t.shape.concat(l))}else if(r>s){o=r-s;let l=[];for(let u=0;u<o;++u)l.push(1);e=U(e,e.shape.concat(l))}else o=0;let i;if(e.shape.length===2&&t.shape.length===2)a[0]===a[1]?i=ve(L(e,t),a[0]):i=ve(L(Xe(e,[1,0]),t),a[1]);else{let l=a[0]!==e.shape.length-1,u=a[1]===t.shape.length-1;i=Ve(e,t,l,u)}if(o>0){let l;s>r?l=s+r-3:l=s-1;let u=[];for(let c=l;c<l+o;++c)u.push(c);i=lt(i,u)}return i.shape.length===1&&(i=Ot(i,1)),i})}var k1=class extends Xo{constructor(e){super(e);this.axes=e.axes,this.normalize=e.normalize==null?!1:e.normalize,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){w.assert(Array.isArray(e)&&e.length===2&&Array.isArray(e[0])&&Array.isArray(e[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let t=e[0],n=e[1];if(t.length>3||n.length>3)throw new Oe("Dot layer does not support tensors of 4D or higher rank yet.");let s=this.interpretAxes(t,n);if(t[s[0]]!==n[s[1]])throw new G(`Dimension incompatibility: ${t[s[0]]} !== ${n[s[1]]}`)}mergeFunction(e){if(e.length!==2)throw new G(`A \`Dot\` layer must be called on exactly 2 inputs, but received ${e.length} input(s).`);let t=e[0],n=e[1],s;return Array.isArray(this.axes)?s=this.axes.map((r,a)=>Pc(r,e[a].shape.length)):s=[Pc(this.axes,t.shape.length),Pc(this.axes,n.shape.length)],this.normalize&&(t=zp(t,s[0]),n=zp(n,s[1])),vM(t,n,s)}interpretAxes(e,t){let n;return Array.isArray(this.axes)?n=this.axes:n=[Pc(this.axes,e.length),Pc(this.axes,t.length)],n}computeOutputShape(e){w.assert(Array.isArray(e)&&e.length===2&&Array.isArray(e[0])&&Array.isArray(e[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let t=e[0].slice(),n=e[1].slice();if(t.length>3||n.length>3)throw new Oe("Dot layer does not support tensors of 4D or higher rank yet.");let s=this.interpretAxes(t,n);t.splice(s[0],1),n.splice(s[1],1),n.splice(0,1);let r=t.concat(n);return r.length===1&&r.push(1),r}computeMask(e,t){return null}getConfig(){let e={axes:this.axes,normalize:this.normalize},t=super.getConfig();return Object.assign(e,t),e}};k1.className="Dot";oe.registerClass(k1);var I1=class extends Ze{constructor(e){super(e);this.supportsMasking=!0,this.stddev=e.stddev}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={stddev:this.stddev};return Object.assign(t,e),t}call(e,t){return H(()=>{this.invokeCallHook(e,t);let n=ze(e);return Sc(()=>ae(Sp(n.shape,0,this.stddev),n),()=>n,t.training||!1)})}};I1.className="GaussianNoise";oe.registerClass(I1);var S1=class extends Ze{constructor(e){super(e);this.supportsMasking=!0,this.rate=e.rate}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={rate:this.rate};return Object.assign(t,e),t}call(e,t){return H(()=>{this.invokeCallHook(e,t);let n=ze(e);return this.rate>0&&this.rate<1?Sc(()=>{let r=Math.sqrt(this.rate/(1-this.rate));return L(n,Sp(n.shape,1,r))},()=>n,t.training||!1):n})}};S1.className="GaussianDropout";oe.registerClass(S1);var C1=class extends Ze{constructor(e){super(e);this.supportsMasking=!0,this.rate=e.rate,this.noiseShape=e.noiseShape}_getNoiseShape(e){return this.noiseShape||ze(e).shape}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={rate:this.rate};return Object.assign(t,e),t}call(e,t){return H(()=>{if(this.rate<1&&this.rate>0){let n=this._getNoiseShape(e);return Sc(()=>{let r=ze(e),a=1.6732632423543772,o=1.0507009873554805,i=-a*o,l=Oo(Bl(n),this.rate);l=kp(l,"float32");let u=((1-this.rate)*(1+this.rate*i**2))**-.5,c=-u*i*this.rate,d=ae(L(r,l),L(ae(l,-1),i));return ae(L(d,u),c)},()=>ze(e),t.training||!1)}return e})}};C1.className="AlphaDropout";oe.registerClass(C1);function Mc(e,t,n,s,r,a=.001){let o;if(e.rank===2)o=Hx(e,t,n,s,r,a);else if(e.rank===3)o=Gx(e,t,n,s,r,a);else if(e.rank===4)o=jx(e,t,n,s,r,a);else throw new Oe(`batchNormalization is not implemented for array of rank ${e.rank} yet`);return o}function wM(e,t,n,s,r=.001){return H(()=>{let a=tp(e,s),o=a.mean,i=a.variance;return[Mc(e,o,i,n,t,r),o,i]})}function kM(e,t,n,s,r=.001){return H(()=>{let a=tp(e,s),o=a.mean,i=a.variance,l=[];for(let f of Bs(0,e.rank))s.indexOf(f)!==-1?l.push(1):l.push(e.shape[f]);let u=U(o,l),c=U(i,l),d=t==null?null:U(t,l),h=n==null?null:U(n,l);return[Mc(e,u,c,h,d,r),o,i]})}function IM(e,t,n,s,r=.001){return w.arraysEqual(s.slice().sort(),Bs(0,e.rank-1))?wM(e,t,n,s,r):kM(e,t,n,s,r)}var T1=class extends Ze{constructor(e){e==null&&(e={});super(e);this.supportsMasking=!0,this.axis=e.axis==null?-1:e.axis,this.momentum=e.momentum==null?.99:e.momentum,this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=wt(e.betaInitializer||"zeros"),this.gammaInitializer=wt(e.gammaInitializer||"ones"),this.movingMeanInitializer=wt(e.movingMeanInitializer||"zeros"),this.movingVarianceInitializer=wt(e.movingVarianceInitializer||"ones"),this.betaConstraint=Xt(e.betaConstraint),this.gammaConstraint=Xt(e.gammaConstraint),this.betaRegularizer=kt(e.betaRegularizer),this.gammaRegularizer=kt(e.gammaRegularizer)}build(e){e=at(e);let t=this.axis>=0?this.axis:this.axis+e.length,n=e[t];if(n==null)throw new G(`Axis ${t} of input tensor should have a defined dimension but the layer received an input with shape ${JSON.stringify(e)}.`);this.inputSpec=[new zt({ndim:e.length,axes:{[t]:n}})];let s=[n];this.scale&&(this.gamma=this.addWeight("gamma",s,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",s,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",s,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",s,null,this.movingVarianceInitializer,null,!1),this.built=!0}call(e,t){return H(()=>{let n=t.training==null?!1:t.training,s=ze(e),r=s.shape,a=r.length,o=Bs(0,a),i=this.axis>=0?this.axis:this.axis+a;o.splice(i,1);let l=Bo(1,a);l[i]=r[i];let u=o.slice();u.sort();let c=!w.arraysEqual(u,Bs(0,a).slice(0,a-1)),d=()=>{if(c){let A=U(this.movingMean.read(),l),y=U(this.movingVariance.read(),l),x=this.center?U(this.beta.read(),l):null,b=this.scale?U(this.gamma.read(),l):null;return Mc(s,A,y,x,b,this.epsilon)}else return Mc(s,this.movingMean.read(),this.movingVariance.read(),this.beta==null?null:this.beta.read(),this.gamma==null?null:this.gamma.read(),this.epsilon)};if(!n)return d();let[h,p,f]=IM(s,this.gamma.read(),this.beta.read(),o,this.epsilon),m=(A,y,x)=>{H(()=>{let b=1-x,v=A.read(),k=L(ge(v,y),b);A.write(ge(v,k))})};return(()=>{m(this.movingMean,p,this.momentum),m(this.movingVariance,f,this.momentum)})(),h})}getConfig(){let e={axis:this.axis,momentum:this.momentum,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:Nt(this.betaInitializer),gammaInitializer:Nt(this.gammaInitializer),movingMeanInitializer:Nt(this.movingMeanInitializer),movingVarianceInitializer:Nt(this.movingVarianceInitializer),betaRegularizer:dt(this.betaRegularizer),gammaRegularizer:dt(this.gammaRegularizer),betaConstraint:qt(this.betaConstraint),gammaConstraint:qt(this.gammaConstraint)},t=super.getConfig();return Object.assign(e,t),e}};T1.className="BatchNormalization";oe.registerClass(T1);var N1=class extends Ze{constructor(e){e==null&&(e={});super(e);if(this.axis=e.axis==null?-1:e.axis,typeof this.axis=="number"){if(!Number.isInteger(this.axis))throw new Error(`Expected axis to be an integer, but received ${this.axis}`)}else if(Array.isArray(this.axis)){for(let t of this.axis)if(!Number.isInteger(t))throw new Error(`Expected axis to be an array of integers, but received ${JSON.stringify(this.axis)}`)}else throw new Error(`Expected axis to be an integer or an array of integers, but received ${JSON.stringify(this.axis)}`);this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=wt(e.betaInitializer||"zeros"),this.gammaInitializer=wt(e.gammaInitializer||"ones"),this.betaRegularizer=kt(e.betaRegularizer),this.gammaRegularizer=kt(e.gammaRegularizer),this.supportsMasking=!0}build(e){e=at(e);let t=e.length;typeof this.axis=="number"&&(this.axis=[this.axis]);for(let r=0;r<this.axis.length;++r)this.axis[r]<0&&(this.axis[r]+=t);for(let r of this.axis)if(r<0||r>=t)throw new Error(`Invalid axis: ${r}`);if(this.axis.length!==na(this.axis).length)throw new Error(`Found duplicate axes in: ${this.axis}`);let n=this.axis.map(r=>e[r]),s=!0;this.scale?this.gamma=this.addWeight("gamma",n,"float32",this.gammaInitializer,this.gammaRegularizer,s):this.gamma=null,this.center?this.beta=this.addWeight("beta",n,"float32",this.betaInitializer,this.betaRegularizer,s):this.beta=null,this.built=!0}call(e,t){let n=ze(e),s=n.shape,r=s.length;return H(()=>{let a=!0,{mean:o,variance:i}=tp(n,this.axis,a),l=Bo(1,r);for(let f of this.axis)l[f]=s[f];let u=f=>f!=null&&f.shape.length!==r&&this.axis!==[r-1]?U(f,l):f,c=u(this.gamma.read()),d=u(this.beta.read()),h=[],p=[];for(let f=0;f<r;++f)this.axis.indexOf(f)!==-1?(h.push(s[f]),p.push(1)):(h.push(1),p.push(s[f]));return o=Ts(o,h),i=Ts(i,h),c=Ts(c,p),d=Ts(d,p),Mc(n,o,i,d,c,this.epsilon)})}getConfig(){let e={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:Nt(this.betaInitializer),gammaInitializer:Nt(this.gammaInitializer),betaRegularizer:dt(this.betaRegularizer),gammaRegularizer:dt(this.gammaRegularizer)},t=super.getConfig();return Object.assign(e,t),e}};N1.className="LayerNormalization";oe.registerClass(N1);function SM(e,t,n){return H(()=>{if(e.rank!==4)throw new G(`temporalPadding expects input tensor to be 4-D, but received a ${e.rank}-D tensor.`);if(t==null&&(t=[[1,1],[1,1]]),t.length!==2||t[0].length!==2||t[1].length!==2)throw new G("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(n==null&&(n=zs()),n!=="channelsLast"&&n!=="channelsFirst")throw new G(`Unknown data format: ${n}. Supported data formats are 'channelsLast' and 'channelsFirst.`);let s;return n==="channelsFirst"?s=[[0,0],[0,0],t[0],t[1]]:s=[[0,0],t[0],t[1],[0,0]],Qr(e,s)})}var E1=class extends Ze{constructor(e){e==null&&(e={});super(e);if(this.dataFormat=e.dataFormat==null?zs():e.dataFormat,e.padding==null)this.padding=[[1,1],[1,1]];else if(typeof e.padding=="number")this.padding=[[e.padding,e.padding],[e.padding,e.padding]];else{if(e.padding=e.padding,e.padding.length!==2)throw new G(`ZeroPadding2D expects padding to be a length-2 array, but received a length-${e.padding.length} array.`);let t,n;if(typeof e.padding[0]=="number")t=[e.padding[0],e.padding[0]],n=[e.padding[1],e.padding[1]];else{if(e.padding=e.padding,e.padding[0].length!==2)throw new G(`ZeroPadding2D expects height padding to be a length-2 array, but received a length-${e.padding[0].length} array.`);if(t=e.padding[0],e.padding[1].length!==2)throw new G(`ZeroPadding2D expects width padding to be a length-2 array, but received a length-${e.padding[1].length} array.`);n=e.padding[1]}this.padding=[t,n]}this.inputSpec=[new zt({ndim:4})]}computeOutputShape(e){e=at(e);let t,n;return this.dataFormat==="channelsFirst"?(e[2]!=null&&e[2]>=0?t=e[2]+this.padding[0][0]+this.padding[0][1]:t=null,e[3]!=null&&e[3]>=0?n=e[3]+this.padding[1][0]+this.padding[1][1]:n=null,[e[0],e[1],t,n]):(e[1]!=null&&e[1]>=0?t=e[1]+this.padding[0][0]+this.padding[0][1]:t=null,e[2]!=null&&e[2]>=0?n=e[2]+this.padding[1][0]+this.padding[1][1]:n=null,[e[0],t,n,e[3]])}call(e,t){return H(()=>SM(ze(e),this.padding,this.dataFormat))}getConfig(){let e={padding:this.padding,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};E1.className="ZeroPadding2D";oe.registerClass(E1);function Jp(e,t,n,s,r,a){return H(()=>{Ft(r),h3(a),gs(s),n==null&&(n=[1,1]),s==null&&(s="valid"),r==null&&(r=zs()),a==null&&(a="max"),e=ZA(e,r);let o,i=s==="same"?"same":"valid";return a==="max"?o=Qh(e,t,n,i):o=Gh(e,t,n,i),r==="channelsFirst"&&(o=Xe(o,[0,3,1,2])),o})}function Iv(e,t,n,s,r,a){return H(()=>{Ft(r),h3(a),gs(s),n==null&&(n=[1,1,1]),s==null&&(s="valid"),r==null&&(r=zs()),a==null&&(a="max"),e=yv(e,r);let o,i=s==="same"?"same":"valid";return a==="max"?o=Mg(e,t,n,i):o=kg(e,t,n,i),r==="channelsFirst"&&(o=Xe(o,[0,4,1,2,3])),o})}var Sv=class extends Ze{constructor(e){e.poolSize==null&&(e.poolSize=2);super(e);if(typeof e.poolSize=="number")this.poolSize=[e.poolSize];else if(Array.isArray(e.poolSize)&&e.poolSize.length===1&&typeof e.poolSize[0]=="number")this.poolSize=e.poolSize;else throw new G(`poolSize for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.poolSize)}`);if(Qt(this.poolSize,"poolSize"),e.strides==null)this.strides=this.poolSize;else if(typeof e.strides=="number")this.strides=[e.strides];else if(Array.isArray(e.strides)&&e.strides.length===1&&typeof e.strides[0]=="number")this.strides=e.strides;else throw new G(`strides for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.strides)}`);Qt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,gs(this.padding),this.inputSpec=[new zt({ndim:3})]}computeOutputShape(e){e=at(e);let t=Hs(e[1],this.poolSize[0],this.padding,this.strides[0]);return[e[0],t,e[2]]}call(e,t){return H(()=>{this.invokeCallHook(e,t),e=kc(ze(e),2);let n=this.poolingFunction(ze(e),[this.poolSize[0],1],[this.strides[0],1],this.padding,"channelsLast");return lt(n,[2])})}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides},t=super.getConfig();return Object.assign(e,t),e}},R1=class extends Sv{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return Ft(r),gs(s),Jp(e,t,n,s,r,"max")}};R1.className="MaxPooling1D";oe.registerClass(R1);var _1=class extends Sv{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return Ft(r),gs(s),Jp(e,t,n,s,r,"avg")}};_1.className="AveragePooling1D";oe.registerClass(_1);var Cv=class extends Ze{constructor(e){e.poolSize==null&&(e.poolSize=[2,2]);super(e);if(this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==2)throw new G(`If the strides property of a 2D pooling layer is an Array, it is expected to have a length of 2, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides];Qt(this.poolSize,"poolSize"),Qt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Ft(this.dataFormat),gs(this.padding),this.inputSpec=[new zt({ndim:4})]}computeOutputShape(e){e=at(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2];return t=Hs(t,this.poolSize[0],this.padding,this.strides[0]),n=Hs(n,this.poolSize[1],this.padding,this.strides[1]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n]:[e[0],t,n,e[3]]}call(e,t){return H(()=>(this.invokeCallHook(e,t),this.poolingFunction(ze(e),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},D1=class extends Cv{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return Ft(r),gs(s),Jp(e,t,n,s,r,"max")}};D1.className="MaxPooling2D";oe.registerClass(D1);var $1=class extends Cv{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return Ft(r),gs(s),Jp(e,t,n,s,r,"avg")}};$1.className="AveragePooling2D";oe.registerClass($1);var Tv=class extends Ze{constructor(e){e.poolSize==null&&(e.poolSize=[2,2,2]);super(e);if(this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==3)throw new G(`If the strides property of a 3D pooling layer is an Array, it is expected to have a length of 3, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides,e.strides];Qt(this.poolSize,"poolSize"),Qt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Ft(this.dataFormat),gs(this.padding),this.inputSpec=[new zt({ndim:5})]}computeOutputShape(e){e=at(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],s=this.dataFormat==="channelsFirst"?e[4]:e[3];return t=Hs(t,this.poolSize[0],this.padding,this.strides[0]),n=Hs(n,this.poolSize[1],this.padding,this.strides[1]),s=Hs(s,this.poolSize[2],this.padding,this.strides[2]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n,s]:[e[0],t,n,s,e[4]]}call(e,t){return H(()=>(this.invokeCallHook(e,t),this.poolingFunction(ze(e),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},F1=class extends Tv{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return Ft(r),gs(s),Iv(e,t,n,s,r,"max")}};F1.className="MaxPooling3D";oe.registerClass(F1);var O1=class extends Tv{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return Ft(r),gs(s),Iv(e,t,n,s,r,"avg")}};O1.className="AveragePooling3D";oe.registerClass(O1);var Nv=class extends Ze{constructor(e){super(e);this.inputSpec=[new zt({ndim:3})]}computeOutputShape(e){return[e[0],e[2]]}call(e,t){throw new Oe}},P1=class extends Nv{constructor(e){super(e||{})}call(e,t){return H(()=>{let n=ze(e);return _t(n,1)})}};P1.className="GlobalAveragePooling1D";oe.registerClass(P1);var M1=class extends Nv{constructor(e){super(e||{})}call(e,t){return H(()=>{let n=ze(e);return hs(n,1)})}};M1.className="GlobalMaxPooling1D";oe.registerClass(M1);var Ev=class extends Ze{constructor(e){super(e);this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Ft(this.dataFormat),this.inputSpec=[new zt({ndim:4})]}computeOutputShape(e){return e=e,this.dataFormat==="channelsLast"?[e[0],e[3]]:[e[0],e[1]]}call(e,t){throw new Oe}getConfig(){let e={dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},z1=class extends Ev{call(e,t){return H(()=>{let n=ze(e);return this.dataFormat==="channelsLast"?_t(n,[1,2]):_t(n,[2,3])})}};z1.className="GlobalAveragePooling2D";oe.registerClass(z1);var L1=class extends Ev{call(e,t){return H(()=>{let n=ze(e);return this.dataFormat==="channelsLast"?hs(n,[1,2]):hs(n,[2,3])})}};L1.className="GlobalMaxPooling2D";oe.registerClass(L1);var Rv=class extends Ze{constructor(e){super(e);this.layer=e.layer}build(e){this.built=!0}get trainable(){return this.layer!=null?this.layer.trainable:!1}set trainable(e){this.layer!=null&&(this.layer.trainable=e)}get trainableWeights(){return this.layer.trainableWeights}get nonTrainableWeights(){return this.layer.nonTrainableWeights}get updates(){return this.layer._updates}get losses(){return this.layer.losses}getWeights(){return this.layer.getWeights()}setWeights(e){this.layer.setWeights(e)}getConfig(){let e={layer:{className:this.layer.getClassName(),config:this.layer.getConfig()}},t=super.getConfig();return Object.assign(e,t),e}setFastWeightInitDuringBuild(e){super.setFastWeightInitDuringBuild(e),this.layer!=null&&this.layer.setFastWeightInitDuringBuild(e)}static fromConfig(e,t,n={}){let s=t.layer,r=Us(s,n);delete t.layer;let a={layer:r};return Object.assign(a,t),new e(a)}},B1=class extends Rv{constructor(e){super(e);this.supportsMasking=!0}build(e){if(e=at(e),e.length<3)throw new G(`TimeDistributed layer expects an input shape >= 3D, but received input shape ${JSON.stringify(e)}`);this.inputSpec=[{shape:e}];let t=[e[0]].concat(e.slice(2));this.layer.built||(this.layer.build(t),this.layer.built=!0),super.build(e)}computeOutputShape(e){e=at(e);let t=[e[0]].concat(e.slice(2)),n=this.layer.computeOutputShape(t),s=e[1];return[n[0],s].concat(n.slice(1))}call(e,t){return H(()=>(e=ze(e),wv((a,o)=>[ze(this.layer.call(a,t)),[]],e,[],!1,null,null,!1,!0)[1]))}};B1.className="TimeDistributed";oe.registerClass(B1);function CM(e){Vo(DO,"BidirectionalMergeMode",e)}var TM="concat",W1=class extends Rv{constructor(e){super(e);let t=e.layer.getConfig(),n={};n.className=e.layer.getClassName(),n.config=t,this.forwardLayer=Us(n),t.goBackwards=t.goBackwards!==!0;let s={};if(s.className=e.layer.getClassName(),s.config=t,this.backwardLayer=Us(s),this.forwardLayer.name="forward_"+this.forwardLayer.name,this.backwardLayer.name="backward_"+this.backwardLayer.name,this.mergeMode=e.mergeMode===void 0?TM:e.mergeMode,CM(this.mergeMode),e.weights)throw new Oe("weights support is not implemented for Bidirectional layer yet.");this._stateful=e.layer.stateful,this.returnSequences=e.layer.returnSequences,this.returnState=e.layer.returnState,this.supportsMasking=!0,this._trainable=!0,this.inputSpec=e.layer.inputSpec,this.numConstants=null}get trainable(){return this._trainable}set trainable(e){this._trainable=e,this.forwardLayer!=null&&(this.forwardLayer.trainable=e),this.backwardLayer!=null&&(this.backwardLayer.trainable=e)}getWeights(){return this.forwardLayer.getWeights().concat(this.backwardLayer.getWeights())}setWeights(e){let t=e.length,n=Math.floor(t/2);this.forwardLayer.setWeights(e.slice(0,n)),this.backwardLayer.setWeights(e.slice(n))}computeOutputShape(e){let t=this.forwardLayer.computeOutputShape(e);Array.isArray(t)&&Array.isArray(t[0])||(t=[t]),t=t;let n,s,r;return this.returnState&&(r=t.slice(1)),n=t[0],n=n,this.mergeMode==="concat"?(n[n.length-1]*=2,s=[n]):this.mergeMode==null?s=[n,n.slice()]:s=[n],this.returnState?this.mergeMode==null?s.concat(r).concat(r.slice()):[n].concat(r).concat(r.slice()):$n(s)}apply(e,t){let n=t==null?null:t.initialState,s=t==null?null:t.constants;t==null&&(t={});let r=vv(e,n,s,this.numConstants);if(e=r.inputs,n=r.initialState,s=r.constants,Array.isArray(e)&&(n=e.slice(1),e=e[0]),(n==null||n.length===0)&&s==null)return super.apply(e,t);let a=[],o=[];if(n!=null){let l=n.length;if(l%2>0)throw new G("When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.");t.initialState=n,a.push(...n);let u=n.map(c=>new zt({shape:c.shape}));this.forwardLayer.stateSpec=u.slice(0,l/2),this.backwardLayer.stateSpec=u.slice(l/2),o.push(...u)}if(s!=null)throw new Oe("Support for constants in Bidirectional layers is not implemented yet.");let i=a[0]instanceof Vs;for(let l of a)if(l instanceof Vs!==i)throw new G("The initial state of a Bidirectional layer cannot be specified as a mix of symbolic and non-symbolic tensors");if(i){let l=[e].concat(a),u=this.inputSpec.concat(o),c=this.inputSpec;this.inputSpec=u;let d=super.apply(l,t);return this.inputSpec=c,d}else return super.apply(e,t)}call(e,t){return H(()=>{let n=t.initialState,s,r;if(n==null)s=this.forwardLayer.call(e,t),r=this.backwardLayer.call(e,t);else{let i=n.slice(0,n.length/2),l=n.slice(n.length/2);s=this.forwardLayer.call(e,Object.assign(t,{initialState:i})),r=this.backwardLayer.call(e,Object.assign(t,{initialState:l}))}let a;this.returnState&&(Array.isArray(s)&&(a=s.slice(1).concat(r.slice(1))),s=s[0],r=r[0]),this.returnSequences&&(r=fs(r,1));let o;return this.mergeMode==="concat"?o=mA([s,r]):this.mergeMode==="sum"?o=ae(s,r):this.mergeMode==="ave"?o=L(.5,ae(s,r)):this.mergeMode==="mul"?o=L(s,r):this.mergeMode==null&&(o=[s,r]),this.returnState?this.mergeMode==null?o.concat(a):[o].concat(a):o})}resetStates(e){this.forwardLayer.resetStates(),this.backwardLayer.resetStates()}build(e){Uo(this.forwardLayer.name,()=>{this.forwardLayer.build(e)}),Uo(this.backwardLayer.name,()=>{this.backwardLayer.build(e)}),this.built=!0}computeMask(e,t){Array.isArray(t)&&(t=t[0]);let n;if(this.returnSequences?this.mergeMode==null?n=[t,t]:n=t:this.mergeMode==null?n=[null,null]:n=null,this.returnState){let r=this.forwardLayer.states.map(a=>null);return Array.isArray(n)?n.concat(r).concat(r):[n].concat(r).concat(r)}else return n}get trainableWeights(){return this.forwardLayer.trainableWeights.concat(this.backwardLayer.trainableWeights)}get nonTrainableWeights(){return this.forwardLayer.nonTrainableWeights.concat(this.backwardLayer.nonTrainableWeights)}setFastWeightInitDuringBuild(e){super.setFastWeightInitDuringBuild(e),this.forwardLayer!=null&&this.forwardLayer.setFastWeightInitDuringBuild(e),this.backwardLayer!=null&&this.backwardLayer.setFastWeightInitDuringBuild(e)}getConfig(){let e={mergeMode:this.mergeMode},t=super.getConfig();return Object.assign(e,t),e}static fromConfig(e,t){let n=Us(t.layer);if(delete t.layer,t.numConstants!=null)throw new Oe("Deserialization of a Bidirectional layer with numConstants present is not supported yet.");let s=t;return s.layer=n,new e(s)}};W1.className="Bidirectional";oe.registerClass(W1);function NM(e){return new Gl(e)}function EM(e){return new qA(e)}function RM(e){return new HA(e)}function _M(e){return new GA(e)}function DM(e){return new jA(e)}function $M(e){return new KA(e)}function FM(e){return new XA(e)}function OM(e){return new jp(e)}function PM(e){return new Dc(e)}function MM(e){return new JA(e)}function zM(e){return new $c(e)}function LM(e){return new QA(e)}function BM(e){return new e1(e)}function WM(e){return new t1(e)}function VM(e){return new n1(e)}function UM(e){return new s1(e)}function HM(e){return new d1(e)}function GM(e){return new u1(e)}function jM(e){return new Yp(e)}function qM(e){return new l1(e)}function XM(e){return new c1(e)}function KM(e){return new h1(e)}function ZM(e){return new p1(e)}function YM(e){return new f1(e)}function JM(e){return new g1(e)}function QM(e){return new A1(e)}function ez(e){return new x1(e)}function tz(e){return new w1(e)}function nz(e){return new b1(e)}function sz(e){return new v1(e)}function rz(e){return new y1(e)}function az(e){return new k1(e)}function oz(e){return new T1(e)}function iz(e){return new N1(e)}function lz(e){return new E1(e)}function V1(e){return new _1(e)}function uz(e){return V1(e)}function cz(e){return V1(e)}function U1(e){return new $1(e)}function dz(e){return U1(e)}function hz(e){return U1(e)}function H1(e){return new O1(e)}function pz(e){return H1(e)}function fz(e){return H1(e)}function mz(e){return new P1(e)}function gz(e){return new z1(e)}function _v(e){return new M1(e)}function Dv(e){return new L1(e)}function $v(e){return new R1(e)}function Fv(e){return new D1(e)}function Az(e){return new F1(e)}function yz(e){return new a1(e)}function xz(e){return new Xp(e)}function bz(e){return new o1(e)}function vz(e){return new Oc(e)}function wz(e){return new r1(e)}function kz(e){return new qp(e)}function Iz(e){return new i1(e)}function Sz(e){return new Zp(e)}function Cz(e){return new ur(e)}function Tz(e){return new Kp(e)}function Nz(e){return new W1(e)}function Ez(e){return new B1(e)}var Rz=_v,_z=Dv,Dz=$v,$z=Fv;function Fz(e){return new I1(e)}function Oz(e){return new S1(e)}function Pz(e){return new C1(e)}function Mz(e){return new m1(e)}var Ov={};Pe(Ov,{MAPE:()=>Xz,MSE:()=>Yz,binaryAccuracy:()=>zz,binaryCrossentropy:()=>Lz,categoricalAccuracy:()=>Wz,categoricalCrossentropy:()=>Vz,cosineProximity:()=>Gz,mape:()=>Kz,meanAbsoluteError:()=>jz,meanAbsolutePercentageError:()=>qz,meanSquaredError:()=>Zz,mse:()=>Jz,precision:()=>Uz,recall:()=>Hz,sparseCategoricalAccuracy:()=>Bz});function zz(e,t){return RA(e,t)}function Lz(e,t){return M3(e,t)}function Bz(e,t){return z3(e,t)}function Wz(e,t){return _A(e,t)}function Vz(e,t){return DA(e,t)}function Uz(e,t){return P3(e,t)}function Hz(e,t){return TP(e,t)}function Gz(e,t){return NA(e,t)}function jz(e,t){return Lp(e,t)}function qz(e,t){return ql(e,t)}function Xz(e,t){return ql(e,t)}function Kz(e,t){return ql(e,t)}function Zz(e,t){return Go(e,t)}function Yz(e,t){return Go(e,t)}function Jz(e,t){return Go(e,t)}var Pv={};Pe(Pv,{modelFromJSON:()=>iM});var Mv={};Pe(Mv,{l1:()=>eL,l1l2:()=>Qz,l2:()=>tL});function Qz(e){return new Rc(e)}function eL(e){return mM(e)}function tL(e){return gM(e)}var zv=class extends jl{constructor(){super(...arguments);this.model=null}setModel(e){if(!(e instanceof Nr))throw new Error("model must be a LayersModel, not some other Container");this.model=e}};function Qp(e,t){return e<t}function Lv(e,t){return e>t}var Bv=class extends zv{constructor(e){super();if(e==null&&(e={}),e.restoreBestWeights)throw new Oe("restoreBestWeights = True is not implemented in EarlyStopping yet.");this.monitor=e.monitor||"val_loss",this.minDelta=Math.abs(e.minDelta||0),this.patience=e.patience||0,this.verbose=e.verbose||0,this.mode=e.mode||"auto",this.baseline=e.baseline,["auto","min","max"].indexOf(this.mode)===-1&&(console.warn(`EarlyStopping mode '${this.mode}' is invalid. Falling back to mode 'auto'.`),this.mode="auto"),this.mode==="min"?this.monitorFunc=Qp:this.mode==="max"?this.monitorFunc=Lv:this.monitor.indexOf("acc")!==-1?this.monitorFunc=Lv:this.monitorFunc=Qp,this.monitorFunc===Qp&&(this.minDelta*=-1)}async onTrainBegin(e){this.wait=0,this.stoppedEpoch=0,this.baseline!=null?this.best=this.baseline:this.best=this.monitorFunc===Qp?1/0:-1/0}async onEpochEnd(e,t){await aa(t);let n=this.getMonitorValue(t);n!=null&&(this.monitorFunc(n-this.minDelta,this.best)?(this.best=n,this.wait=0):(this.wait++,this.wait>=this.patience&&(this.stoppedEpoch=e,this.model.stopTraining=!0)))}async onTrainEnd(e){this.stoppedEpoch>0&&this.verbose&&console.log(`Epoch ${this.stoppedEpoch}: early stopping.`)}getMonitorValue(e){e==null&&(e={});let t=e[this.monitor];return t==null&&console.warn(`Metric for EarlyStopping ${this.monitor} is not available. Available metrics are: ${Object.keys(e)}`),t}};function nL(e){return new Bv(e)}var sL={earlyStopping:nL},Gs;(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_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"})(Gs||(Gs={}));var Wv;(function(e){let t;(function(n){n[n.LEGACY=0]="LEGACY",n[n.V1=1]="V1",n[n.V2=2]="V2"})(t=e.CheckpointFormatVersion||(e.CheckpointFormatVersion={}))})(Wv||(Wv={}));var G1={};function rL(e,t){let n={tfOpName:e,category:"custom",inputs:[],attrs:[],customExecutor:t};G1[e]=n}function Vv(e){return G1[e]}function aL(e){delete G1[e]}function I(e,t,n,s,r){let a=t.inputParams[e];if(a&&a.inputIndexStart!==void 0){let i=a.inputIndexStart,l=a.inputIndexEnd===0?void 0:a.inputIndexEnd===void 0?i+1:a.inputIndexEnd;if(a.type==="tensor")return wn(t.inputNames[a.inputIndexStart],n,s,r);if(a.type==="tensors")return t.inputNames.slice(i,l).map(h=>wn(h,n,s,r));let u=wn(t.inputNames.slice(i)[0],n,s,r),c=u.dataSync();return a.type==="number"?c[0]:w.toNestedArray(u.shape,c)}let o=t.attrParams[e];return o&&o.value}function wn(e,t,n,s){let[r,a]=Xn(e);if(s!=null){let i=s.getHashTableHandleByName(r);if(i!=null)return i}let o=n.currentContextIds.find(i=>!!t[ef(r,i)]);return o!==void 0?t[ef(r,o)][a]:void 0}function oL(e,t,n){return t[ef(e,n.currentContextId)]}function Er(e,t){let[n,s,r]=Xn(e);return[ef(n,t&&t.currentContextId),s,r]}function ef(e,t){return t?`${e}-${t}`:e}function Xn(e){let t=e.split(":");if(t.length===1)return[e,0,void 0];let n=t[0],s=t.length===3?t[1]:void 0,r=Number(t[t.length-1]);return[n,r,s]}function tf(e,t,n){let s=I("pad",e,t,n);if(s==="explicit"){s=I("explicitPaddings",e,t,n);let r=[[0,0],[0,0],[0,0],[0,0]];for(let a=0;a<4;a++)r[a][0]=s[a*2],r[a][1]=s[a*2+1];return r}return s}function Rr(e){return e.kept?e:Os(e)}var Uv={};Pe(Uv,{json:()=>iL});var iL=[{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}]}],Hv={};Pe(Hv,{json:()=>lL});var lL=[{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}]}],Gv={};Pe(Gv,{json:()=>uL});var uL=[{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:"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"}]}],jv={};Pe(jv,{json:()=>cL});var cL=[{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"}]},{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"}]}],qv={};Pe(qv,{json:()=>dL});var dL=[{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",notSupported:!0}]},{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:"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"}]}],Xv={};Pe(Xv,{json:()=>hL});var hL=[{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}]}],Kv={};Pe(Kv,{json:()=>pL});var pL=[{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:"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"}]}],Zv={};Pe(Zv,{json:()=>fL});var fL=[{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"}]}],Yv={};Pe(Yv,{json:()=>mL});var mL=[{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"}]}],Jv={};Pe(Jv,{json:()=>gL});var gL=[{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"}]}],Qv={};Pe(Qv,{json:()=>AL});var AL=[{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}]}],e7={};Pe(e7,{json:()=>yL});var yL=[{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:"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"}]}],t7={};Pe(t7,{json:()=>xL});var xL=[{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}]}],n7={};Pe(n7,{json:()=>bL});var bL=[{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:"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"}]}],s7={};Pe(s7,{json:()=>vL});var vL=[{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}]}],r7={};Pe(r7,{json:()=>wL});var wL=[{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"}]}],a7={};Pe(a7,{json:()=>kL});var kL=[{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}]}],o7={};Pe(o7,{json:()=>IL});var IL=[{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"}]}],i7={};Pe(i7,{json:()=>SL});var SL=[{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:[]}],l7=class{static get Instance(){return this._instance||(this._instance=new this)}constructor(){let e=[Uv,Hv,Gv,jv,qv,Xv,Kv,Zv,Yv,Jv,Qv,e7,t7,n7,s7,r7,a7,o7,i7],t=[].concat(...e.map(n=>n.json));this.opMappers=t.reduce((n,s)=>(n[s.tfOpName]=s,n),{})}transformGraph(e,t={}){let n=e.node,s=[],r=[],a=[],o=n.reduce((f,m)=>(f[m.name]=this.mapNode(m),m.op.startsWith("Placeholder")?s.push(f[m.name]):m.op==="Const"?r.push(f[m.name]):(m.input==null||m.input.length===0)&&a.push(f[m.name]),f),{}),i=[],l=[],u={},c={};t!=null&&(u=this.mapSignatureEntries(t.inputs),c=this.mapSignatureEntries(t.outputs));let d=Object.keys(o);d.forEach(f=>{let m=o[f];m.inputNames.forEach((g,A)=>{let[y,,x]=Er(g),b=o[y];if(b.outputs!=null){let v=b.outputs.indexOf(x);if(v!==-1){let k=`${y}:${v}`;m.inputNames[A]=k}}m.inputs.push(b),b.children.push(m)})}),Object.keys(c).length===0?d.forEach(f=>{let m=o[f];m.children.length===0&&l.push(m)}):Object.keys(c).forEach(f=>{let[m]=Er(f),g=o[m];g!=null&&(g.signatureKey=c[f],l.push(g))}),Object.keys(u).length>0?Object.keys(u).forEach(f=>{let[m]=Er(f),g=o[m];g&&(g.signatureKey=u[f],i.push(g))}):i=s;let h={};e.library!=null&&e.library.function!=null&&(h=e.library.function.reduce((f,m)=>(f[m.signature.name]=this.mapFunction(m),f),{}));let p={nodes:o,inputs:i,outputs:l,weights:r,placeholders:s,signature:t,functions:h};return a.length>0&&(p.initNodes=a),p}mapSignatureEntries(e){return Object.keys(e||{}).reduce((t,n)=>(t[e[n].name]=n,t),{})}mapNode(e){let t=Vv(e.op)||this.opMappers[e.op]||{};e.attr==null&&(e.attr={});let n={name:e.name,op:e.op,category:t.category,inputNames:(e.input||[]).map(s=>s.startsWith("^")?s.substr(1):s),inputs:[],children:[],inputParams:{},attrParams:{},rawAttrs:e.attr,outputs:t.outputs};return t.inputs!=null&&(n.inputParams=t.inputs.reduce((s,r)=>(s[r.name]={type:r.type,inputIndexStart:r.start,inputIndexEnd:r.end},s),{})),t.attrs!=null&&(n.attrParams=t.attrs.reduce((s,r)=>{let a=r.type,o;switch(r.type){case"string":o=j1(e.attr,r.tfName,r.defaultValue),o===void 0&&!!r.tfDeprecatedName&&(o=j1(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"string[]":o=e2(e.attr,r.tfName,r.defaultValue),o===void 0&&!!r.tfDeprecatedName&&(o=e2(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"number":o=X1(e.attr,r.tfName,r.defaultValue||0),o===void 0&&!!r.tfDeprecatedName&&(o=X1(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"number[]":o=Q1(e.attr,r.tfName,r.defaultValue),o===void 0&&!!r.tfDeprecatedName&&(o=Q1(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"bool":o=q1(e.attr,r.tfName,r.defaultValue),o===void 0&&!!r.tfDeprecatedName&&(o=q1(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"bool[]":o=n2(e.attr,r.tfName,r.defaultValue),o===void 0&&!!r.tfDeprecatedName&&(o=n2(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"shape":o=J1(e.attr,r.tfName,r.defaultValue),o===void 0&&!!r.tfDeprecatedName&&(o=J1(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"shape[]":o=t2(e.attr,r.tfName,r.defaultValue),o===void 0&&!!r.tfDeprecatedName&&(o=t2(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"dtype":o=Z1(e.attr,r.tfName,r.defaultValue),o===void 0&&!!r.tfDeprecatedName&&(o=Z1(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"dtype[]":o=Y1(e.attr,r.tfName,r.defaultValue),o===void 0&&!!r.tfDeprecatedName&&(o=Y1(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"func":o=c7(e.attr,r.tfName,r.defaultValue),o===void 0&&!!r.tfDeprecatedName&&(o=c7(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"tensor":case"tensors":break;default:throw new Error(`Unsupported param type: ${r.type} for op: ${e.op}`)}return s[r.name]={value:o,type:a},s},{})),n}mapFunction(e){let t=e.nodeDef,n=[],s=[],r={};t!=null&&(r=t.reduce((c,d)=>(c[d.name]=this.mapNode(d),d.op==="Const"&&s.push(c[d.name]),c),{}));let a=[],o=[];e.signature.inputArg.forEach(c=>{let[d]=Er(c.name),h={name:d,op:"Placeholder",inputs:[],inputNames:[],category:"graph",inputParams:{},attrParams:{dtype:{value:K1(c.type),type:"dtype"}},children:[]};h.signatureKey=c.name,a.push(h),r[d]=h}),Object.keys(r).forEach(c=>{let d=r[c];d.inputNames.forEach((h,p)=>{let[f,,m]=Er(h),g=r[f];if(g.outputs!=null){let A=g.outputs.indexOf(m);if(A!==-1){let y=`${f}:${A}`;d.inputNames[p]=y}}d.inputs.push(g),g.children.push(d)})});let l=e.ret;e.signature.outputArg.forEach(c=>{let[d,h]=Er(l[c.name]),p=r[d];p!=null&&(p.defaultOutput=h,o.push(p))});let u=this.mapArgsToSignature(e);return{nodes:r,inputs:a,outputs:o,weights:s,placeholders:n,signature:u}}mapArgsToSignature(e){return{methodName:e.signature.name,inputs:e.signature.inputArg.reduce((t,n)=>(t[n.name]=this.mapArgToTensorInfo(n),t),{}),outputs:e.signature.outputArg.reduce((t,n)=>(t[n.name]=this.mapArgToTensorInfo(n,e.ret),t),{})}}mapArgToTensorInfo(e,t){let n=e.name;return t!=null&&(n=t[n]),{name:n,dtype:e.type}}};function CL(e){let t=Q().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 u7(e,t){let n=Array.isArray(e)?String.fromCharCode.apply(null,e):CL(e);return t?n:n.toLowerCase()}function j1(e,t,n,s=!1){let r=e[t];return r!=null?u7(r.s,s):n}function q1(e,t,n){let s=e[t];return s?s.b:n}function X1(e,t,n){let s=e[t]||{},r=s.i!=null?s.i:s.f!=null?s.f:n;return typeof r=="number"?r:parseInt(r,10)}function K1(e){switch(typeof e=="string"&&(e=Gs[e]),e){case Gs.DT_FLOAT:return"float32";case Gs.DT_INT32:case Gs.DT_INT64:case Gs.DT_INT8:case Gs.DT_UINT8:return"int32";case Gs.DT_BOOL:return"bool";case Gs.DT_DOUBLE:return"float32";case Gs.DT_STRING:return"string";default:return null}}function c7(e,t,n){let s=e[t];return s&&s.func?s.func.name:n}function Z1(e,t,n){let s=e[t];return s&&s.type?K1(s.type):n}function Y1(e,t,n){let s=e[t];return s&&s.list&&s.list.type?s.list.type.map(r=>K1(r)):n}function d7(e){if(!e.unknownRank)return e.dim!=null?e.dim.map(t=>typeof t.size=="number"?t.size:parseInt(t.size,10)):[]}function J1(e,t,n){let s=e[t];return s&&s.shape?d7(s.shape):n}function Q1(e,t,n){let s=e[t];return s?((s.list.f&&s.list.f.length?s.list.f:s.list.i)||[]).map(r=>typeof r=="number"?r:parseInt(r,10)):n}function e2(e,t,n,s=!1){let r=e[t];return r&&r.list&&r.list.s?r.list.s.map(a=>u7(a,s)):n}function t2(e,t,n){let s=e[t];return s&&s.list&&s.list.shape?s.list.shape.map(r=>d7(r)):n}function n2(e,t,n){let s=e[t];return s&&s.list&&s.list.b?s.list.b:n}var TL=class{constructor(e,t,n){this.node=e,this.tensorMap=t,this.context=n,this.inputs=[],this.attrs={},this.inputs=e.inputNames.map(s=>this.getInput(s)),e.rawAttrs!=null&&(this.attrs=Object.keys(e.rawAttrs).reduce((s,r)=>(s[r]=this.getAttr(r),s),{}))}getInput(e){return wn(e,this.tensorMap,this.context)}getAttr(e,t){let n=this.node.rawAttrs[e];if(n.tensor!=null)return wn(e,this.tensorMap,this.context);if(n.i!=null||n.f!=null)return X1(this.node.rawAttrs,e,t);if(n.s!=null)return j1(this.node.rawAttrs,e,t);if(n.b!=null)return q1(this.node.rawAttrs,e,t);if(n.shape!=null)return J1(this.node.rawAttrs,e,t);if(n.type!=null)return Z1(this.node.rawAttrs,e,t);if(n.list!=null){if(n.list.i!=null||n.list.f!=null)return Q1(this.node.rawAttrs,e,t);if(n.list.s!=null)return e2(this.node.rawAttrs,e,t);if(n.list.shape!=null)return t2(this.node.rawAttrs,e,t);if(n.list.b!=null)return n2(this.node.rawAttrs,e,t);if(n.list.type!=null)return Y1(this.node.rawAttrs,e,t)}return t}},NL=(e,t,n)=>{switch(e.op){case"BiasAdd":case"AddV2":case"Add":return[ae(I("a",e,t,n),I("b",e,t,n))];case"AddN":return[Vh(I("tensors",e,t,n))];case"FloorMod":case"Mod":return[Ab(I("a",e,t,n),I("b",e,t,n))];case"Mul":return[L(I("a",e,t,n),I("b",e,t,n))];case"RealDiv":case"Div":return[de(I("a",e,t,n),I("b",e,t,n))];case"DivNoNan":return[sb(I("a",e,t,n),I("b",e,t,n))];case"FloorDiv":return[xg(I("a",e,t,n),I("b",e,t,n))];case"Sub":return[ge(I("a",e,t,n),I("b",e,t,n))];case"Minimum":return[pc(I("a",e,t,n),I("b",e,t,n))];case"Maximum":return[kr(I("a",e,t,n),I("b",e,t,n))];case"Pow":return[ea(I("a",e,t,n),I("b",e,t,n))];case"SquaredDifference":return[Kg(I("a",e,t,n),I("b",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},EL=(e,t,n)=>{switch(e.op){case"Abs":case"ComplexAbs":return[Ht(I("x",e,t,n))];case"Acos":return[$x(I("x",e,t,n))];case"Acosh":return[Fx(I("x",e,t,n))];case"Asin":return[Px(I("x",e,t,n))];case"Asinh":return[Mx(I("x",e,t,n))];case"Atan":return[zx(I("x",e,t,n))];case"Atan2":return[Lx(I("x",e,t,n),I("y",e,t,n))];case"Atanh":return[Bx(I("x",e,t,n))];case"Ceil":return[Xx(I("x",e,t,n))];case"Complex":return[qr(I("real",e,t,n),I("imag",e,t,n))];case"Cos":return[qh(I("x",e,t,n))];case"Cosh":return[Eg(I("x",e,t,n))];case"Elu":return[dc(I("x",e,t,n))];case"Erf":return[ab(I("x",e,t,n))];case"Exp":return[cs(I("x",e,t,n))];case"Expm1":return[ob(I("x",e,t,n))];case"Floor":return[hc(I("x",e,t,n))];case"Log":return[ds(I("x",e,t,n))];case"Log1p":return[Zh(I("x",e,t,n))];case"Imag":return[Xh(I("x",e,t,n))];case"Neg":return[Tt(I("x",e,t,n))];case"Reciprocal":return[bb(I("x",e,t,n))];case"Real":return[fc(I("x",e,t,n))];case"Relu":return[sr(I("x",e,t,n))];case"Round":return[Vg(I("x",e,t,n))];case"Selu":return[Hg(I("x",e,t,n))];case"Sigmoid":return[Hn(I("x",e,t,n))];case"Sin":return[Gg(I("x",e,t,n))];case"Sign":return[kb(I("x",e,t,n))];case"Sinh":return[jg(I("x",e,t,n))];case"Softplus":return[zl(I("x",e,t,n))];case"Sqrt":return[hn(I("x",e,t,n))];case"Square":return[ct(I("x",e,t,n))];case"Tanh":return[$l(I("x",e,t,n))];case"Tan":return[Sb(I("x",e,t,n))];case"ClipByValue":return[Gn(I("x",e,t,n),I("clipValueMin",e,t,n),I("clipValueMax",e,t,n))];case"Relu6":return[Wg(I("x",e,t,n))];case"Rsqrt":return[Ug(wn(e.inputNames[0],t,n))];case"Prod":return[zg(I("x",e,t,n),I("axes",e,t,n))];case"LeakyRelu":return[Kh(I("x",e,t,n),I("alpha",e,t,n))];case"Prelu":return[sp(I("x",e,t,n),I("alpha",e,t,n))];case"IsNan":return[ib(wn(e.inputNames[0],t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}};function _s(e,t,n=""){if(!(typeof e=="number"||typeof t=="number")){w.assert(e.length===t.length,()=>n+` Shapes ${e} and ${t} must match`);for(let s=0;s<e.length;s++){let r=e[s],a=t[s];w.assert(r<0||a<0||r===a,()=>n+` Shapes ${e} and ${t} must match`)}}}function h7(e){return!(typeof e=="number"||e.some(t=>t<0))}function zc(e,t,n){let s=s2(e,n),r=!h7(s);if(r&&t.length===0)throw new Error(`Tried to calculate elements of an empty list with non-fully-defined elementShape: ${s}`);if(r&&t.forEach(a=>{s=s2(a.shape,s)}),!h7(s))throw new Error(`Non-fully-defined elementShape: ${s}`);return s}function s2(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 n=[];for(let s=0;s<e.length;++s){let r=e[s],a=t[s];if(r>=0&&a>=0&&r!==a)throw new Error(`Incompatible shape during merge: ${e} vs. ${t}`);n[s]=r>=0?r:a}return n}var RL=class{constructor(e,t,n,s,r,a,o){this.name=e,this.dtype=t,this.maxSize=n,this.elementShape=s,this.identicalElementShapes=r,this.dynamicSize=a,this.clearAfterRead=o,this.tensors=[],this.closed_=!1,this.idTensor=Ie(0),Jt(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 n=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),_s(this.elementShape,t.shape,`TensorArray ${this.name}: Could not write to TensorArray index ${e}.`),n.read)throw new Error(`TensorArray ${this.name}: Could not write to TensorArray index ${e}, because it has already been read.`);if(n.written)throw new Error(`TensorArray ${this.name}: Could not write to TensorArray index ${e}, because it has already been written.`);n.tensor=t,Jt(t),n.written=!0,this.tensors[e]=n}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((n,s)=>this.write(n,t[s]))}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 s=0;s<this.size();s++)e.push(s)}if(e.length===0)return dn([],[0].concat(this.elementShape));let n=this.readMany(e);return _s(this.elementShape,n[0].shape,"TensorArray shape mismatch: "),Dn(n,0)}concat(e){if(!!e&&e!==this.dtype)throw new Error(`TensorArray dtype is ${this.dtype} but concat requested dtype ${e}`);if(this.size()===0)return dn([],[0].concat(this.elementShape));let t=[];for(let s=0;s<this.size();s++)t.push(s);let n=this.readMany(t);return _s(this.elementShape,n[0].shape,`TensorArray shape mismatch: tensor array shape (${this.elementShape}) vs first tensor shape (${n[0].shape})`),ft(n,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. ${t.shape[0]}`);let n=Math.max(...e);if(!this.dynamicSize&&n>=this.maxSize)throw new Error(`Max index must be < array size (${n} vs. ${this.maxSize})`);this.writeMany(e,ms(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 n=0,s=e.map(i=>(n+=i,n));if(n!==t.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: ${t.shape}`);if(!this.dynamicSize&&e.length!==this.maxSize)throw new Error(`TensorArray's size is not equal to the size of lengths (${this.maxSize} vs. ${e.length}), and the TensorArray is not marked as dynamically resizeable`);let r=n===0?0:t.size/n,a=[];H(()=>{t=U(t,[1,n,r]);for(let i=0;i<e.length;++i){let l=i===0?0:s[i-1],u=[0,l,0],c=[1,e[i],r];a[i]=U(Re(t,u,c),this.elementShape)}return a});let o=[];for(let i=0;i<e.length;i++)o[i]=i;this.writeMany(o,a)}},Lc=class{constructor(e,t,n,s=-1){this.tensors=e,this.elementShape=t,this.elementDtype=n,e!=null&&e.forEach(r=>{if(n!==r.dtype)throw new Error(`Invalid data types; op elements ${n}, but list elements ${r.dtype}`);_s(t,r.shape,"TensorList shape mismatch: "),Jt(r)}),this.idTensor=Ie(0),this.maxNumElements=s,Jt(this.idTensor)}get id(){return this.idTensor.id}copy(){return new Lc([...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,n=-1){if(t!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t}, but list elements ${this.elementDtype}`);if(n!==-1&&this.tensors.length!==n)throw new Error(`Operation expected a list with ${n} elements but got a list with ${this.tensors.length} elements.`);_s(e,this.elementShape,"TensorList shape mismatch: ");let s=zc(this.elementShape,this.tensors,e);return H(()=>{let r=this.tensors.map(a=>U(a,s));return Dn(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 n=zc(this.elementShape,this.tensors,e),s=this.tensors.pop();return _s(s.shape,e,"TensorList shape mismatch: "),U(s,n)}pushBack(e){if(e.dtype!==this.elementDtype)throw new Error(`Invalid data types; op elements ${e.dtype}, but list elements ${this.elementDtype}`);if(_s(e.shape,this.elementShape,"TensorList shape mismatch: "),this.maxNumElements===this.size())throw new Error("Trying to push element into a full list.");Jt(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}.`);this.tensors.length=e}getItem(e,t,n){if(n!==this.elementDtype)throw new Error(`Invalid data types; op elements ${n}, 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.`);_s(this.tensors[e].shape,t,"TensorList shape mismatch: ");let s=zc(this.elementShape,this.tensors,t);return U(this.tensors[e],s)}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.`);_s(this.elementShape,t.shape,"TensorList shape mismatch: "),Jt(t),this.tensors[e]=t}gather(e,t,n){if(t!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t}, but list elements ${this.elementDtype}`);_s(this.elementShape,n,"TensorList shape mismatch: "),e=e.slice(0,this.size());let s=zc(this.elementShape,this.tensors,n);return e.length===0?dn([],[0].concat(s)):H(()=>{let r=e.map(a=>U(this.tensors[a],s));return Dn(r,0)})}concat(e,t){if(!!e&&e!==this.elementDtype)throw new Error(`TensorList dtype is ${this.elementDtype} but concat requested dtype ${e}`);_s(this.elementShape,t,"TensorList shape mismatch: ");let n=zc(this.elementShape,this.tensors,t);return this.size()===0?dn([],[0].concat(n)):H(()=>{let s=this.tensors.map(r=>U(r,n));return ft(s,0)})}};function _L(e,t,n){let s=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!==n)throw new Error(`Invalid data types; op elements ${e.dtype}, but list elements ${n}`);let r=e.shape.slice(1);_s(r,t,"TensorList shape mismatch: ");let a=ms(e);return new Lc(a,t,s)}function DL(e,t,n){return new Lc([],e,t,n)}function $L(e,t,n,s){if(t.length!==e.shape[0])throw new Error(`Expected len(indices) == tensor.shape[0], but saw: ${t.length} vs. ${e.shape[0]}`);let r=Math.max(...t);if(s!=null&&s!==-1&&r>=s)throw new Error(`Max index must be < array size (${r} vs. ${s})`);let a=new Lc([],n,e.dtype,s),o=ms(e,0);return t.forEach((i,l)=>{a.setItem(i,o[l])}),a}function FL(e,t,n){let s=0,r=t.map(c=>(s+=c,s));if(s!==e.shape[0])throw new Error(`Expected sum of lengths to be equal to
tensor.shape[0], but sum of lengths is
${s}, and tensor's shape is: ${e.shape}`);let a=e.shape.slice(1),o=s2(a,n),i=s===0?0:e.size/s,l=H(()=>{let c=[];e=U(e,[1,s,i]);for(let d=0;d<t.length;++d){let h=d===0?0:r[d-1],p=[0,h,0],f=[1,t[d],i];c[d]=U(Re(e,p,f),o)}return e.dispose(),c}),u=new Lc([],n,e.dtype,t.length);for(let c=0;c<l.length;c++)u.setItem(c,l[c]);return u}var OL=async(e,t,n)=>{switch(e.op){case"If":case"StatelessIf":{let s=I("thenBranch",e,t,n),r=I("elseBranch",e,t,n),a=I("cond",e,t,n),o=I("args",e,t,n);return(await a.data())[0]?n.functionMap[s].executeFunctionAsync(o,n.tensorArrayMap,n.tensorListMap):n.functionMap[r].executeFunctionAsync(o,n.tensorArrayMap,n.tensorListMap)}case"While":case"StatelessWhile":{let s=I("body",e,t,n),r=I("cond",e,t,n),a=I("args",e,t,n),o=await n.functionMap[r].executeFunctionAsync(a,n.tensorArrayMap,n.tensorListMap),i=a.map(c=>c.id),l=await o[0].data();o.forEach(c=>{!c.kept&&i.indexOf(c.id)===-1&&c.dispose()});let u=a;for(;l[0];){let c=u;u=await n.functionMap[s].executeFunctionAsync(u,n.tensorArrayMap,n.tensorListMap);let d=u.map(p=>p.id);c.forEach(p=>{!p.kept&&i.indexOf(p.id)===-1&&d.indexOf(p.id)===-1&&p.dispose()});let h=await n.functionMap[r].executeFunctionAsync(u,n.tensorArrayMap,n.tensorListMap);l=await h[0].data(),h.forEach(p=>{!p.kept&&i.indexOf(p.id)===-1&&d.indexOf(p.id)===-1&&p.dispose()})}return u}case"LoopCond":{let s=I("pred",e,t,n);return[Rr(s)]}case"Switch":{let s=I("pred",e,t,n),r=I("data",e,t,n);return r.kept||(r=Rr(r)),(await s.data())[0]?[void 0,r]:[r,void 0]}case"Merge":{let s=e.inputNames.find(r=>wn(r,t,n)!==void 0);if(s){let r=wn(s,t,n);return[Rr(r)]}return}case"Enter":{let s=I("frameName",e,t,n),r=I("tensor",e,t,n);return n.enterFrame(s),[Rr(r)]}case"Exit":{let s=I("tensor",e,t,n);return n.exitFrame(),[Rr(s)]}case"NextIteration":{let s=I("tensor",e,t,n);return n.nextIteration(),[Rr(s)]}case"TensorArrayV3":{let s=I("size",e,t,n),r=I("dtype",e,t,n),a=I("elementShape",e,t,n),o=I("dynamicSize",e,t,n),i=I("clearAfterRead",e,t,n),l=I("identicalElementShapes",e,t,n),u=I("name",e,t,n),c=new RL(u,r,s,a,l,o,i);return n.addTensorArray(c),[c.idTensor,Ie(1)]}case"TensorArrayWriteV3":{let s=I("tensorArrayId",e,t,n),r=I("index",e,t,n),a=I("tensor",e,t,n),o=n.getTensorArray(s.id);return o.write(r,a),[o.idTensor]}case"TensorArrayReadV3":{let s=I("tensorArrayId",e,t,n),r=I("index",e,t,n);return[n.getTensorArray(s.id).read(r)]}case"TensorArrayGatherV3":{let s=I("tensorArrayId",e,t,n),r=I("indices",e,t,n),a=I("dtype",e,t,n);return[n.getTensorArray(s.id).gather(r,a)]}case"TensorArrayScatterV3":{let s=I("tensorArrayId",e,t,n),r=I("indices",e,t,n),a=I("tensor",e,t,n),o=n.getTensorArray(s.id);return o.scatter(r,a),[o.idTensor]}case"TensorArrayConcatV3":{let s=I("tensorArrayId",e,t,n),r=n.getTensorArray(s.id),a=I("dtype",e,t,n);return[r.concat(a)]}case"TensorArraySplitV3":{let s=I("tensorArrayId",e,t,n),r=I("tensor",e,t,n),a=I("lengths",e,t,n),o=n.getTensorArray(s.id);return o.split(a,r),[o.idTensor]}case"TensorArraySizeV3":{let s=I("tensorArrayId",e,t,n),r=n.getTensorArray(s.id);return[Ie(r.size(),"int32")]}case"TensorArrayCloseV3":{let s=I("tensorArrayId",e,t,n),r=n.getTensorArray(s.id);return r.clearAndClose(),[r.idTensor]}case"TensorListSetItem":{let s=I("tensorListId",e,t,n),r=I("index",e,t,n),a=I("tensor",e,t,n),o=n.getTensorList(s.id);return o.setItem(r,a),[o.idTensor]}case"TensorListGetItem":{let s=I("tensorListId",e,t,n),r=I("index",e,t,n),a=I("elementShape",e,t,n),o=I("elementDType",e,t,n);return[n.getTensorList(s.id).getItem(r,a,o)]}case"TensorListScatterV2":case"TensorListScatter":{let s=I("indices",e,t,n),r=I("tensor",e,t,n),a=I("elementShape",e,t,n),o=I("numElements",e,t,n),i=$L(r,s,a,o);return n.addTensorList(i),[i.idTensor]}case"TensorListReserve":case"EmptyTensorList":{let s=I("elementShape",e,t,n),r=I("elementDType",e,t,n),a;e.op==="TensorListReserve"?a="numElements":a="maxNumElements";let o=I(a,e,t,n),i=DL(s,r,o);return n.addTensorList(i),[i.idTensor]}case"TensorListGather":{let s=I("tensorListId",e,t,n),r=I("indices",e,t,n),a=I("elementShape",e,t,n),o=I("elementDType",e,t,n);return[n.getTensorList(s.id).gather(r,o,a)]}case"TensorListStack":{let s=I("tensorListId",e,t,n),r=I("elementShape",e,t,n),a=I("elementDType",e,t,n),o=I("numElements",e,t,n);return[n.getTensorList(s.id).stack(r,a,o)]}case"TensorListFromTensor":{let s=I("tensor",e,t,n),r=I("elementShape",e,t,n),a=I("elementDType",e,t,n),o=_L(s,r,a);return n.addTensorList(o),[o.idTensor]}case"TensorListConcat":{let s=I("tensorListId",e,t,n),r=n.getTensorList(s.id),a=I("dtype",e,t,n),o=I("elementShape",e,t,n);return[r.concat(a,o)]}case"TensorListPushBack":{let s=I("tensorListId",e,t,n),r=I("tensor",e,t,n),a=n.getTensorList(s.id);return a.pushBack(r),[a.idTensor]}case"TensorListPopBack":{let s=I("tensorListId",e,t,n),r=I("elementShape",e,t,n),a=I("elementDType",e,t,n);return[n.getTensorList(s.id).popBack(r,a)]}case"TensorListSplit":{let s=I("tensor",e,t,n),r=I("elementShape",e,t,n),a=I("lengths",e,t,n),o=FL(s,a,r);return n.addTensorList(o),[o.idTensor]}default:throw TypeError(`Node type ${e.op} is not implemented`)}};function p7(e,t,n){let[s,r]=I("fusedOps",e,t,n),a=s==="biasadd",o=!a,i=r==="prelu",l=s==="fusedbatchnorm",u=I("numArgs",e,t,n);if(a){if(i&&u!==2)throw new Error("FusedConv2d and DepthwiseConv2d with BiasAdd and Prelu must have two extra arguments: bias and alpha.");if(!i&&a&&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 c=I("strides",e,t,n),d=tf(e,t,n),h=I("dataFormat",e,t,n).toUpperCase(),p=I("dilations",e,t,n),[f,m]=I("args",e,t,n);o&&(m=f,f=void 0);let g=I("leakyreluAlpha",e,t,n);return{stride:c,pad:d,dataFormat:h,dilations:p,biasArg:f,preluArg:m,activationFunc:r,leakyreluAlpha:g}}var PL=(e,t,n)=>{switch(e.op){case"Conv1D":{let s=I("stride",e,t,n),r=I("pad",e,t,n),a=I("dataFormat",e,t,n).toUpperCase(),o=I("dilation",e,t,n);return[Sg(I("x",e,t,n),I("filter",e,t,n),s,r,a,o)]}case"Conv2D":{let s=I("strides",e,t,n),r=tf(e,t,n),a=I("dataFormat",e,t,n).toUpperCase(),o=I("dilations",e,t,n);return[Jr(I("x",e,t,n),I("filter",e,t,n),[s[1],s[2]],r,a,[o[1],o[2]])]}case"_FusedConv2D":{let{stride:s,pad:r,dataFormat:a,dilations:o,biasArg:i,preluArg:l,activationFunc:u,leakyreluAlpha:c}=p7(e,t,n);return[ta.conv2d({x:I("x",e,t,n),filter:I("filter",e,t,n),strides:[s[1],s[2]],pad:r,dataFormat:a,dilations:[o[1],o[2]],bias:i,activation:u,preluActivationWeights:l,leakyreluAlpha:c})]}case"FusedDepthwiseConv2dNative":{let{stride:s,pad:r,dataFormat:a,dilations:o,biasArg:i,preluArg:l,activationFunc:u,leakyreluAlpha:c}=p7(e,t,n);return[ta.depthwiseConv2d({x:I("x",e,t,n),filter:I("filter",e,t,n),strides:[s[1],s[2]],pad:r,dataFormat:a,dilations:[o[1],o[2]],bias:i,activation:u,preluActivationWeights:l,leakyreluAlpha:c})]}case"Conv2DBackpropInput":case"Conv2dTranspose":{let s=I("outputShape",e,t,n),r=I("strides",e,t,n),a=tf(e,t,n);return[Tg(I("x",e,t,n),I("filter",e,t,n),s,[r[1],r[2]],a)]}case"DepthwiseConv2dNative":case"DepthwiseConv2d":{let s=I("strides",e,t,n),r=tf(e,t,n),a=I("dilations",e,t,n),o=I("dataFormat",e,t,n).toUpperCase();return[cc(I("input",e,t,n),I("filter",e,t,n),[s[1],s[2]],r,o,[a[1],a[2]])]}case"Conv3D":{let s=I("strides",e,t,n),r=I("pad",e,t,n),a=I("dataFormat",e,t,n).toUpperCase(),o=I("dilations",e,t,n);return[Ng(I("x",e,t,n),I("filter",e,t,n),[s[1],s[2],s[3]],r,a,[o[1],o[2],o[3]])]}case"AvgPool":{let s=I("strides",e,t,n),r=I("pad",e,t,n),a=I("kernelSize",e,t,n);return[Gh(I("x",e,t,n),[a[1],a[2]],[s[1],s[2]],r)]}case"MaxPool":{let s=I("strides",e,t,n),r=I("pad",e,t,n),a=I("kernelSize",e,t,n);return[Qh(I("x",e,t,n),[a[1],a[2]],[s[1],s[2]],r)]}case"MaxPoolWithArgmax":{let s=I("strides",e,t,n),r=I("pad",e,t,n),a=I("kernelSize",e,t,n),o=I("includeBatchInIndex",e,t,n),{result:i,indexes:l}=mb(I("x",e,t,n),[a[1],a[2]],[s[1],s[2]],r,o);return[i,l]}case"AvgPool3D":{let s=I("strides",e,t,n),r=I("pad",e,t,n),a=I("kernelSize",e,t,n);return[kg(I("x",e,t,n),[a[1],a[2],a[3]],[s[1],s[2],s[3]],r)]}case"MaxPool3D":{let s=I("strides",e,t,n),r=I("pad",e,t,n),a=I("kernelSize",e,t,n);return[Mg(I("x",e,t,n),[a[1],a[2],a[3]],[s[1],s[2],s[3]],r)]}case"Dilation2D":{let s=I("strides",e,t,n),r=I("pad",e,t,n),a=I("dilations",e,t,n),o=s[1],i=s[2],l=a[1],u=a[2];return[nb(I("x",e,t,n),I("filter",e,t,n),[o,i],r,[l,u],"NHWC")]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},ML=(e,t,n)=>{switch(e.op){case"Fill":{let s=I("shape",e,t,n),r=I("dtype",e,t,n),a=I("value",e,t,n);return[Pl(s,a,r)]}case"LinSpace":{let s=I("start",e,t,n),r=I("stop",e,t,n),a=I("num",e,t,n);return[lb(s,r,a)]}case"Multinomial":{let s=I("logits",e,t,n),r=I("numSamples",e,t,n),a=I("seed",e,t,n);return[yb(s,r,a)]}case"OneHot":{let s=I("indices",e,t,n),r=I("depth",e,t,n),a=I("onValue",e,t,n),o=I("offValue",e,t,n);return[ic(s,r,a,o)]}case"Ones":return[qn(I("shape",e,t,n),I("dtype",e,t,n))];case"OnesLike":return[ps(I("x",e,t,n))];case"RandomUniform":return[Bl(I("shape",e,t,n),I("minval",e,t,n),I("maxval",e,t,n),I("dtype",e,t,n))];case"Range":{let s=I("start",e,t,n),r=I("stop",e,t,n),a=I("step",e,t,n);return[Wl(s,r,a,I("dtype",e,t,n))]}case"TruncatedNormal":{let s=I("shape",e,t,n),r=I("mean",e,t,n),a=I("stdDev",e,t,n),o=I("seed",e,t,n);return[up(s,r,a,I("dtype",e,t,n),o)]}case"Zeros":return[Pt(I("shape",e,t,n),I("dtype",e,t,n))];case"ZerosLike":return[Ke(I("x",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}};function r2(e,t,n){let s=I("boxes",e,t,n),r=I("scores",e,t,n),a=I("maxOutputSize",e,t,n),o=I("iouThreshold",e,t,n),i=I("scoreThreshold",e,t,n),l=I("softNmsSigma",e,t,n);return{boxes:s,scores:r,maxOutputSize:a,iouThreshold:o,scoreThreshold:i,softNmsSigma:l}}var zL=async(e,t,n)=>{switch(e.op){case"NonMaxSuppressionV5":{let{boxes:s,scores:r,maxOutputSize:a,iouThreshold:o,scoreThreshold:i,softNmsSigma:l}=r2(e,t,n),u=await _e.nonMaxSuppressionWithScoreAsync(s,r,a,o,i,l);return[u.selectedIndices,u.selectedScores]}case"NonMaxSuppressionV4":{let{boxes:s,scores:r,maxOutputSize:a,iouThreshold:o,scoreThreshold:i}=r2(e,t,n),l=I("padToMaxOutputSize",e,t,n),u=await _e.nonMaxSuppressionPaddedAsync(s,r,a,o,i,l);return[u.selectedIndices,u.validOutputs]}case"NonMaxSuppressionV3":case"NonMaxSuppressionV2":{let{boxes:s,scores:r,maxOutputSize:a,iouThreshold:o,scoreThreshold:i}=r2(e,t,n);return[await _e.nonMaxSuppressionAsync(s,r,a,o,i)]}case"Where":{let s=ce(I("condition",e,t,n),"bool"),r=[await Yg(s)];return s.dispose(),r}case"ListDiff":return wb(I("x",e,t,n),I("y",e,t,n));default:throw TypeError(`Node type ${e.op} is not implemented`)}},LL=(e,t,n)=>{switch(e.op){case"TopKV2":{let s=I("x",e,t,n),r=I("k",e,t,n),a=I("sorted",e,t,n),o=Cb(s,r,a);return[o.values,o.indices]}case"Unique":{let s=I("x",e,t,n),r=Zg(s);return[r.values,r.indices]}case"UniqueV2":{let s=I("x",e,t,n),r=I("axis",e,t,n),a=Zg(s,r);return[a.values,a.indices]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},BL=(e,t,n)=>{switch(e.op){case"Const":return t[e.name];case"PlaceholderWithDefault":let s=I("default",e,t,n);return[wn(e.name,t,n)||s];case"Placeholder":return[wn(e.name,t,n)];case"Identity":case"StopGradient":case"FakeQuantWithMinMaxVars":{let u=I("x",e,t,n);return[Rr(u)]}case"IdentityN":return I("x",e,t,n).map(u=>Rr(u));case"Snapshot":let r=I("x",e,t,n);return[Rr(r)];case"Shape":return[Mt(I("x",e,t,n).shape,"int32")];case"ShapeN":return I("x",e,t,n).map(u=>Mt(u.shape));case"Size":return[Ie(I("x",e,t,n).size,"int32")];case"Rank":return[Ie(I("x",e,t,n).rank,"int32")];case"NoOp":return[Ie(1)];case"Print":let a=I("x",e,t,n),o=I("data",e,t,n),i=I("message",e,t,n),l=I("summarize",e,t,n);console.warn("The graph has a tf.print() operation,usually used for debugging, which slows down performance."),console.log(i);for(let u=0;u<o.length;u++)console.log(Array.prototype.slice.call(o[u].dataSync()).slice(0,l));return[a];default:throw TypeError(`Node type ${e.op} is not implemented`)}},WL=class{constructor(e,t){this.keyDType=e,this.valueDType=t,this.handle=Ie(0),this.tensorMap=new Map,Jt(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 Ie(this.size(),"int32")}async import(e,t){this.checkKeyAndValueTensor(e,t);let n=await e.data();return this.tensorMap.forEach(s=>s.dispose()),this.tensorMap.clear(),H(()=>{let s=ms(t),r=n.length,a=s.length;w.assert(r===a,()=>`The number of elements doesn't match, keys has ${r} elements, the values has ${a} elements.`);for(let o=0;o<r;o++){let i=n[o],l=s[o];Jt(l),this.tensorMap.set(i,l)}return this.handle})}async find(e,t){this.checkKeyAndValueTensor(e,t);let n=await e.data();return H(()=>{let s=[];for(let r=0;r<n.length;r++){let a=n[r],o=this.findWithDefault(a,t);s.push(o)}return Dn(s)})}findWithDefault(e,t){let n=this.tensorMap.get(e);return n!=null?n: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}`)}},VL=async(e,t,n,s)=>{switch(e.op){case"HashTable":case"HashTableV2":{let r=I("keyDType",e,t,n),a=I("valueDType",e,t,n),o=new WL(r,a);return s.addHashTable(e.name,o),[o.handle]}case"LookupTableImport":case"LookupTableImportV2":{let r=I("tableHandle",e,t,n,s),a=I("keys",e,t,n),o=I("values",e,t,n);return[await s.getHashTableById(r.id).import(a,o)]}case"LookupTableFind":case"LookupTableFindV2":{let r=I("tableHandle",e,t,n,s),a=I("keys",e,t,n),o=I("defaultValue",e,t,n);return[await s.getHashTableById(r.id).find(a,o)]}case"LookupTableSize":case"LookupTableSizeV2":{let r=I("tableHandle",e,t,n,s);return[s.getHashTableById(r.id).tensorSize()]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},UL=(e,t,n)=>{switch(e.op){case"ResizeBilinear":{let s=I("images",e,t,n),r=I("size",e,t,n),a=I("alignCorners",e,t,n),o=I("halfPixelCenters",e,t,n);return[_e.resizeBilinear(s,[r[0],r[1]],a,o)]}case"ResizeNearestNeighbor":{let s=I("images",e,t,n),r=I("size",e,t,n),a=I("alignCorners",e,t,n),o=I("halfPixelCenters",e,t,n);return[_e.resizeNearestNeighbor(s,[r[0],r[1]],a,o)]}case"CropAndResize":{let s=I("image",e,t,n),r=I("boxes",e,t,n),a=I("boxInd",e,t,n),o=I("cropSize",e,t,n),i=I("method",e,t,n),l=I("extrapolationValue",e,t,n);return[_e.cropAndResize(s,r,a,o,i,l)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},HL=(e,t,n)=>{switch(e.op){case"Equal":return[us(I("a",e,t,n),I("b",e,t,n))];case"NotEqual":return[Ll(I("a",e,t,n),I("b",e,t,n))];case"Greater":return[jn(I("a",e,t,n),I("b",e,t,n))];case"GreaterEqual":return[Oo(I("a",e,t,n),I("b",e,t,n))];case"Less":return[Dg(I("a",e,t,n),I("b",e,t,n))];case"LessEqual":return[Po(I("a",e,t,n),I("b",e,t,n))];case"LogicalAnd":return[Ps(I("a",e,t,n),I("b",e,t,n))];case"LogicalNot":return[Jh(I("a",e,t,n))];case"LogicalOr":return[Pg(I("a",e,t,n),I("b",e,t,n))];case"Select":case"SelectV2":return[bn(I("condition",e,t,n),I("a",e,t,n),I("b",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},GL=(e,t,n)=>{switch(e.op){case"BatchMatMul":case"BatchMatMulV2":case"MatMul":return[Ve(I("a",e,t,n),I("b",e,t,n),I("transposeA",e,t,n),I("transposeB",e,t,n))];case"Einsum":return[rb(I("equation",e,t,n),...I("tensors",e,t,n))];case"Transpose":return[Xe(I("x",e,t,n),I("perm",e,t,n))];case"_FusedMatMul":let[s,r]=I("fusedOps",e,t,n),a=s==="biasadd",o=r==="prelu",i=I("numArgs",e,t,n),l=I("leakyreluAlpha",e,t,n);if(a){if(o&&i!==2)throw new Error("Fused MatMul with BiasAdd and Prelu must have two extra arguments: bias and alpha.");if(!o&&i!==1)throw new Error("Fused MatMul with BiasAdd must have one extra argument: bias.")}let[u,c]=I("args",e,t,n);return[ta.matMul({a:I("a",e,t,n),b:I("b",e,t,n),transposeA:I("transposeA",e,t,n),transposeB:I("transposeB",e,t,n),bias:u,activation:r,preluActivationWeights:c,leakyreluAlpha:l})];default:throw TypeError(`Node type ${e.op} is not implemented`)}},jL=(e,t,n)=>{switch(e.op){case"FusedBatchNorm":case"FusedBatchNormV2":return[Fl(I("x",e,t,n),I("mean",e,t,n),I("variance",e,t,n),I("offset",e,t,n),I("scale",e,t,n),I("epsilon",e,t,n))];case"FusedBatchNormV3":return[Fl(I("x",e,t,n),I("mean",e,t,n),I("variance",e,t,n),I("offset",e,t,n),I("scale",e,t,n),I("epsilon",e,t,n))];case"LRN":return[ub(I("x",e,t,n),I("radius",e,t,n),I("bias",e,t,n),I("alpha",e,t,n),I("beta",e,t,n))];case"Softmax":return[op(I("x",e,t,n))];case"LogSoftmax":return[$g(I("x",e,t,n))];case"SparseToDense":return[Qg(I("sparseIndices",e,t,n),I("outputShape",e,t,n),I("sparseValues",e,t,n),I("defaultValue",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},qL=(e,t,n)=>{switch(e.op){case"Max":{let o=I("axis",e,t,n),i=I("keepDims",e,t,n);return[hs(I("x",e,t,n),o,i)]}case"Mean":{let o=I("axis",e,t,n),i=I("keepDims",e,t,n);return[_t(I("x",e,t,n),o,i)]}case"Min":{let o=I("axis",e,t,n),i=I("keepDims",e,t,n);return[ep(I("x",e,t,n),o,i)]}case"Sum":{let o=I("axis",e,t,n),i=I("keepDims",e,t,n);return[ve(I("x",e,t,n),o,i)]}case"All":{let o=I("axis",e,t,n),i=I("keepDims",e,t,n);return[bg(I("x",e,t,n),o,i)]}case"Any":{let o=I("axis",e,t,n),i=I("keepDims",e,t,n);return[Uh(I("x",e,t,n),o,i)]}case"ArgMax":{let o=I("axis",e,t,n);return[er(I("x",e,t,n),o)]}case"ArgMin":{let o=I("axis",e,t,n);return[Ox(I("x",e,t,n),o)]}case"Prod":{let o=I("axis",e,t,n),i=I("keepDims",e,t,n);return[zg(I("x",e,t,n),o,i)]}case"Cumsum":{let o=I("axis",e,t,n),i=I("exclusive",e,t,n),l=I("reverse",e,t,n);return[Rg(I("x",e,t,n),o,i,l)]}case"Bincount":let s=I("x",e,t,n),r=I("weights",e,t,n),a=I("size",e,t,n);return[Ig(s,r,a)];case"DenseBincount":{let o=I("x",e,t,n),i=I("weights",e,t,n),l=I("size",e,t,n),u=I("binaryOutput",e,t,n);return[eb(o,i,l,u)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},XL=(e,t,n)=>{switch(e.op){case"ConcatV2":case"Concat":{let s=I("n",e,t,n),r=I("axis",e,t,n),a=I("tensors",e,t,n);return a=a.slice(0,s),[ft(a,r)]}case"Gather":{let s=I("x",e,t,n),r=I("indices",e,t,n);return[Ml(s,ce(r,"int32"),0)]}case"GatherV2":{let s=I("axis",e,t,n),r=I("batchDims",e,t,n),a=I("x",e,t,n),o=I("indices",e,t,n);return[Ml(a,ce(o,"int32"),s,r)]}case"Reverse":{let s=I("dims",e,t,n),r=[];for(let o=0;o<s.length;o++)s[o]&&r.push(o);let a=I("x",e,t,n);return[fs(a,r)]}case"ReverseV2":{let s=I("axis",e,t,n),r=I("x",e,t,n);return[fs(r,s)]}case"Slice":{let s=I("begin",e,t,n),r=I("size",e,t,n);return[Re(I("x",e,t,n),s,r)]}case"StridedSlice":{let s=I("begin",e,t,n),r=I("end",e,t,n),a=I("strides",e,t,n),o=I("beginMask",e,t,n),i=I("endMask",e,t,n),l=I("ellipsisMask",e,t,n),u=I("newAxisMask",e,t,n),c=I("shrinkAxisMask",e,t,n),d=I("x",e,t,n);return[Ib(d,s,r,a,o,i,l,u,c)]}case"Pack":return H(()=>{let s=I("axis",e,t,n),r=I("tensors",e,t,n),a=r[0].shape,o=lt(r[0]).shape,i=r.map(l=>{let u=w.arraysEqual(l.shape,a);if(!u&&!w.arraysEqual(lt(l).shape,o))throw new Error("the input tensors shape does not match");return u?l:U(l,a)});return[Dn(i,s)]});case"Unpack":{let s=I("axis",e,t,n),r=I("tensor",e,t,n);return ms(r,s)}case"Tile":{let s=I("reps",e,t,n);return[Ts(I("x",e,t,n),s)]}case"Split":case"SplitV":{let s=I("axis",e,t,n),r=I("numOrSizeSplits",e,t,n),a=I("x",e,t,n);return an(a,r,s)}case"ScatterNd":{let s=I("indices",e,t,n),r=I("values",e,t,n),a=I("shape",e,t,n);return[_b(s,r,a)]}case"GatherNd":{let s=I("x",e,t,n),r=I("indices",e,t,n);return[Db(s,r)]}case"SparseToDense":{let s=I("sparseIndices",e,t,n),r=I("outputShape",e,t,n),a=I("sparseValues",e,t,n),o=I("defaultValue",e,t,n);return[Qg(s,a,r,a.dtype===o.dtype?o:ce(o,a.dtype))]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},KL=(e,t,n)=>{switch(e.op){case"SparseFillEmptyRows":{let{outputIndices:s,outputValues:r,emptyRowIndicator:a,reverseIndexMap:o}=yc.sparseFillEmptyRows(I("indices",e,t,n),I("values",e,t,n),I("denseShape",e,t,n),I("defaultValue",e,t,n));return[s,r,a,o]}case"SparseReshape":{let{outputIndices:s,outputShape:r}=yc.sparseReshape(I("inputIndices",e,t,n),I("inputShape",e,t,n),I("newShape",e,t,n));return[s,r]}case"SparseSegmentMean":return[yc.sparseSegmentMean(I("data",e,t,n),I("indices",e,t,n),I("segmentIds",e,t,n))];case"SparseSegmentSum":return[yc.sparseSegmentSum(I("data",e,t,n),I("indices",e,t,n),I("segmentIds",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},ZL=(e,t,n)=>{switch(e.op){case"FFT":return[ip(I("x",e,t,n))];case"IFFT":return[gc(I("x",e,t,n))];case"RFFT":return[lp(I("x",e,t,n))];case"IRFFT":return[Xg(I("x",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},YL=(e,t,n)=>{switch(e.op){case"StringNGrams":{let{nGrams:s,nGramsSplits:r}=fp.stringNGrams(I("data",e,t,n),I("dataSplits",e,t,n),I("separator",e,t,n),I("nGramWidths",e,t,n),I("leftPad",e,t,n),I("rightPad",e,t,n),I("padWidth",e,t,n),I("preserveShortSequences",e,t,n));return[s,r]}case"StringSplit":{let{indices:s,values:r,shape:a}=fp.stringSplit(I("input",e,t,n),I("delimiter",e,t,n),I("skipEmpty",e,t,n));return[s,r,a]}case"StringToHashBucketFast":return[fp.stringToHashBucketFast(I("input",e,t,n),I("numBuckets",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},JL=(e,t,n)=>{switch(e.op){case"Cast":return[ce(I("x",e,t,n),I("dtype",e,t,n))];case"ExpandDims":{let s=I("axis",e,t,n);return[Ot(I("x",e,t,n),s)]}case"Squeeze":{let s=I("axis",e,t,n);return[lt(I("x",e,t,n),s)]}case"Reshape":return[U(I("x",e,t,n),I("shape",e,t,n))];case"MirrorPad":return[gb(I("x",e,t,n),I("padding",e,t,n),I("mode",e,t,n))];case"PadV2":case"Pad":return[Qr(I("x",e,t,n),I("padding",e,t,n),I("constantValue",e,t,n))];case"SpaceToBatchND":{let s=I("blockShape",e,t,n),r=I("paddings",e,t,n);return[np(I("x",e,t,n),s,r)]}case"BatchToSpaceND":{let s=I("blockShape",e,t,n),r=I("crops",e,t,n);return[jh(I("x",e,t,n),s,r)]}case"DepthToSpace":{let s=I("blockSize",e,t,n),r=I("dataFormat",e,t,n).toUpperCase();return[tb(I("x",e,t,n),s,r)]}case"BroadcastTo":return[uc(I("x",e,t,n),I("shape",e,t,n))];case"BroadcastArgs":return[qx(I("s0",e,t,n),I("s1",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}};function f7(e,t,n,s){let r=((a,o,i)=>{switch(a.category){case"arithmetic":return H(()=>NL(a,o,i));case"basic_math":return H(()=>EL(a,o,i));case"control":return OL(a,o,i);case"convolution":return H(()=>PL(a,o,i));case"creation":return H(()=>ML(a,o,i));case"dynamic":return zL(a,o,i);case"evaluation":return H(()=>LL(a,o,i));case"image":return H(()=>UL(a,o,i));case"graph":return H(()=>BL(a,o,i));case"logical":return H(()=>HL(a,o,i));case"matrices":return H(()=>GL(a,o,i));case"normalization":return H(()=>jL(a,o,i));case"reduction":return H(()=>qL(a,o,i));case"slice_join":return H(()=>XL(a,o,i));case"sparse":return H(()=>KL(a,o,i));case"spectral":return H(()=>ZL(a,o,i));case"string":return H(()=>YL(a,o,i));case"transformation":return H(()=>JL(a,o,i));case"hash_table":return VL(a,o,i,s);case"custom":let l=Vv(a.op);if(l&&l.customExecutor)return l.customExecutor(new TL(a,o,i));throw TypeError(`Custom op ${a.op} is not registered.`);default:throw TypeError(`Unknown op '${a.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,n);return w.isPromise(r)?r.then(a=>[].concat(a)):[].concat(r)}var m7=class{constructor(e={},t={},n={},s={}){this.weightMap=e,this.tensorArrayMap=t,this.tensorListMap=n,this.functionMap=s,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 n=this.contexts.slice(0,this.contexts.length-t);e.push(this.contextIdforContexts(n))}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 g7(e,t,n,s){let r=new Set,a=[],o=null,i=null,l=new Set,u=Object.keys(e).map(h=>Xn(h)[0]),c=[];s!=null&&(c=s.map(h=>Xn(h.name)[0]));let d=[...t];for(;d.length>0;){let h=d.pop();if((A7(h)||sB(h)||rB(h))&&o==null&&(o=h,i=o.children.map(p=>p.name).filter(p=>r.has(p))),r.add(h.name),n[h.name]==null&&u.indexOf(h.name)===-1&&c.indexOf(h.name)===-1){if(h.inputs.length===0){a.push(h.name);continue}h.inputs.forEach(p=>{l.has(p.name)||(l.add(p.name),d.push(p))})}}return{inputs:e,outputs:t,usedNodes:r,missingInputs:a,dynamicNode:o,syncInputs:i}}function QL(e,t,n){let{usedNodes:s,inputs:r}=n,a=[],o=Object.keys(r).map(c=>Xn(c)[0]).map(c=>e.nodes[c]),i=e.initNodes;o.forEach(c=>{s.has(c.name)&&a.push(c)}),e.weights.forEach(c=>{s.has(c.name)&&a.push(c)}),i!=null&&i.forEach(c=>{s.has(c.name)&&a.push(c)});let l=new Set,u=[];for(;a.length>0;){let c=a.pop();l.add(c.name),t[c.name]||u.push(c),c.children.forEach(d=>{!l.has(d.name)&&s.has(d.name)&&d.inputs.every(h=>l.has(h.name))&&a.push(d)})}return u}var eB=["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"],tB=["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"],nB=["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2","LookupTableSize","LookupTableSizeV2"];function A7(e){return eB.indexOf(e.op)>=0}function sB(e){return tB.indexOf(e.op)>=0}function rB(e){return nB.indexOf(e.op)>=0}var a2=class{constructor(e,t){this.graph=e,this.parent=t,this.compiledMap=new Map,this._weightMap={},this.SEPERATOR=",",this._functions={},this._functionExecutorMap={},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(n=>{this._functionExecutorMap[n]=new a2(e.functions[n],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(n=>e[n].map(s=>s.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 n=e.map(r=>r.name).sort(),s=t.map(r=>r.name).sort();return n.join(this.SEPERATOR)+"--"+s.join(this.SEPERATOR)}compile(e,t){let n=g7(e,t,this.weightMap,this._initNodes),{missingInputs:s,dynamicNode:r,syncInputs:a}=n;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 [${a}]`);if(s.length>0){let o=t.map(l=>l.name),i=Object.keys(e);throw new Error(`Cannot compute the outputs [${o}] from the provided inputs [${i}]. Missing the following inputs: [${s}]`)}return QL(this.graph,this.weightMap,n)}execute(e,t){e=this.mapInputs(e);let n=Object.keys(e).sort();this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t);let s=n.map(c=>this.graph.nodes[Xn(c)[0]]),r=t.map(c=>Xn(c)[0]),a=r.map(c=>this.graph.nodes[c]);a.length===0&&(a=this._outputs);let o=this.getCompilationKey(s,a),i=this.compiledMap.get(o);i==null&&(i=this.compile(e,a),this.compiledMap.set(o,i));let l={},u={};return H(()=>{let c=new m7(this.weightMap,l,u,this.functionExecutorMap),d=Object.assign({},this.weightMap);Object.keys(e).forEach(f=>{let[m,g]=Xn(f),A=[];A[g]=e[f],d[m]=A});let h=this.getFrozenTensorIds(d),p={};for(let f=0;f<i.length;f++){let m=i[f];if(!d[m.name]){let g=f7(m,d,c,this._resourceManager);if(w.isPromise(g))throw new Error(`The execution of the op '${m.op}' returned a promise. Please use model.executeAsync() instead.`);d[m.name]=g,this.checkTensorForDisposal(m.name,m,d,c,h,r,p)}}return this.parent==null&&c.dispose(h),t.map(f=>wn(f,d,c))})}getFrozenTensorIds(e){let t=[].concat.apply([],Object.keys(e).map(n=>e[n]).map(n=>n.map(s=>s.id)));return new Set(t)}checkTensorForDisposal(e,t,n,s,r,a,o){t.category==="control"||a.indexOf(e)!==-1||(n[e].forEach(i=>{i!=null&&(o[i.id]=(o[i.id]||0)+t.children.length)}),t.inputs.forEach(i=>{if(i.category!=="control"){let l=oL(i.name,n,s);l!=null&&l.forEach(u=>{if(u&&!u.kept&&!r.has(u.id)){let c=o[u.id];c===1?(u.dispose(),delete o[u.id]):c!=null&&o[u.id]--}})}}))}async executeAsync(e,t){return this._executeAsync(e,t)}async _executeAsync(e,t,n=!1,s={},r={}){n||(e=this.mapInputs(e),this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t));let a=new m7(this.weightMap,s,r,this.functionExecutorMap),o=await this.executeWithControlFlow(e,a,t,n),i=t.map(d=>wn(d,o,a)),l=i.map(d=>d.id),u=Object.keys(e).map(d=>e[d].id),c=new Set([...l,...u,...this.weightIds]);return Object.keys(o).forEach(d=>{o[d].forEach(p=>{p&&!p.kept&&!p.isDisposed&&!c.has(p.id)&&p.dispose()})}),this.parent==null&&a.dispose(c),i}async executeFunctionAsync(e,t,n){let s=e.reduce((r,a,o)=>(r[this.inputs[o].name]=a,r),{});return this._executeAsync(s,this.outputNodes,!0,t,n)}async executeWithControlFlow(e,t,n,s){let r=Object.keys(e),a=r.map(y=>this.graph.nodes[Xn(y)[0]]),o=n.map(y=>Xn(y)[0]),i=o.map(y=>this.graph.nodes[y]);i.length===0&&(i=this._outputs);let{usedNodes:l,missingInputs:u,dynamicNode:c,syncInputs:d}=g7(e,i,this.weightMap,this._initNodes),h=[...a,...this.graph.weights,...this._initNodes||[]].map(y=>({node:y,contexts:t.currentContext})),p=Object.assign({},this.weightMap);Object.keys(e).forEach(y=>{let[x,b]=Xn(y),v=[];v[b]=e[y],p[x]=v});let f={},m=this.getFrozenTensorIds(p),g={};for(;h.length>0;){let y=this.processStack(a,h,t,p,g,m,o,f,l);await Promise.all(y)}c==null&&!s&&console.warn("This model execution did not contain any nodes with control flow or dynamic output shapes. You can use model.execute() instead.");let A=i.filter(y=>!A7(y)&&!wn(y.name,p,t)).map(y=>y.name);if(A.length>0){let y="";throw c!=null&&(y=`Alternatively, to avoid the dynamic ops, use model.execute() and specify the inputs [${d}]`),new Error(`Cannot compute the outputs [${A}] from the provided inputs [${r}]. Consider providing the following inputs: [${u}]. ${y}`)}return p}processStack(e,t,n,s,r,a,o,i,l){let u=[];for(;t.length>0;){let c=t.pop();n.currentContext=c.contexts;let d="";if(c.node.op==="Enter"&&I("isConstant",c.node,s,n)&&([d]=Er(c.node.name,n)),s[c.node.name]==null){let h=f7(c.node,s,n,this._resourceManager);d||([d]=Er(c.node.name,n));let p=n.currentContext;w.isPromise(h)?u.push(h.then(f=>(s[d]=f,n.currentContext=p,this.checkTensorForDisposal(d,c.node,s,n,a,o,i),this.processChildNodes(c.node,t,n,s,r,l),f))):(s[d]=h,this.checkTensorForDisposal(d,c.node,s,n,a,o,i),this.processChildNodes(c.node,t,n,s,r,l))}else this.processChildNodes(c.node,t,n,s,r,l)}return u}processChildNodes(e,t,n,s,r,a){e.children.forEach(o=>{let[i]=Er(o.name,n);r[i]||!a.has(o.name)||(o.op==="Merge"?o.inputNames.some(l=>!!wn(l,s,n))&&(r[i]=!0,t.push({contexts:n.currentContext,node:o})):o.inputNames.every(l=>!!wn(l,s,n))&&(r[i]=!0,t.push({contexts:n.currentContext,node:o})))})}dispose(){Object.keys(this.weightMap).forEach(e=>this.weightMap[e].forEach(t=>t.dispose()))}checkInputShapeAndType(e){Object.keys(e).forEach(t=>{let n=e[t],[s]=Xn(t),r=this.graph.nodes[s];if(r.attrParams.shape&&r.attrParams.shape.value){let a=r.attrParams.shape.value,o=a.length===n.shape.length&&n.shape.every((i,l)=>a[l]===-1||a[l]===i);w.assert(o,()=>`The shape of dict['${r.name}'] provided in model.execute(dict) must be [${a}], but was [${n.shape}]`)}r.attrParams.dtype&&r.attrParams.dtype.value&&w.assert(n.dtype===r.attrParams.dtype.value,()=>`The dtype of dict['${r.name}'] provided in model.execute(dict) must be ${r.attrParams.dtype.value}, but was ${n.dtype}`)})}mapInputs(e){let t={};for(let n in e)if(this._signature!=null&&this._signature.inputs!=null&&this._signature.inputs[n]!=null){let s=this._signature.inputs[n];t[s.name]=e[n]}else t[n]=e[n];return t}checkInputs(e){let t=Object.keys(e).filter(n=>{let[s]=Xn(n);return this.graph.nodes[s]==null});if(t.length>0)throw new Error(`The dict provided in model.execute(dict) has keys: [${t}] that are not part of graph`)}mapOutputs(e){return e.map(t=>this._signature!=null&&this._signature.outputs!=null&&this._signature.outputs[t]!=null?this._signature.outputs[t].name:t,{})}checkOutputs(e){e.forEach(t=>{let[n]=Xn(t);if(!this.graph.nodes[n])throw new Error(`The output '${t}' is not found in the graph`)})}},aB=class{constructor(e={},t={}){this.hashTableNameToHandle=e,this.hashTableMap=t}addHashTable(e,t){this.hashTableNameToHandle[e]=t.handle,this.hashTableMap[t.id]=t}getHashTableHandleByName(e){return this.hashTableNameToHandle[e]}getHashTableById(e){return this.hashTableMap[e]}dispose(){for(let e in this.hashTableMap)this.hashTableMap[e].clearAndClose(),delete this.hashTableMap[e];for(let e in this.hashTableNameToHandle)this.hashTableNameToHandle[e].dispose(),delete this.hashTableNameToHandle[e]}},oB="?tfjs-format=file",iB="model.json",y7=class{constructor(e,t={}){this.modelUrl=e,this.loadOptions=t,this.version="n/a",t==null&&(this.loadOptions={}),this.resourceManager=new aB}get modelVersion(){return this.version}get inputNodes(){return this.executor.inputNodes}get outputNodes(){return this.executor.outputNodes}get inputs(){return this.executor.inputs}get outputs(){return this.executor.outputs}get weights(){return this.executor.weightMap}get metadata(){return this.artifacts.userDefinedMetadata}get modelSignature(){return this.signature}findIOHandler(){let e=this.modelUrl;if(e.load!=null)this.handler=e;else if(this.loadOptions.requestInit!=null)this.handler=_n.browserHTTPRequest(e,this.loadOptions);else{let t=_n.getLoadHandlers(e,this.loadOptions);if(t.length===0)t.push(_n.browserHTTPRequest(e,this.loadOptions));else if(t.length>1)throw new Error(`Found more than one (${t.length}) load handlers for URL '${[e]}'`);this.handler=t[0]}}async load(){if(this.findIOHandler(),this.handler.load==null)throw new Error("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");let e=await this.handler.load();return this.loadSync(e)}loadSync(e){this.artifacts=e;let t=this.artifacts.modelTopology,n;this.artifacts.userDefinedMetadata!=null&&this.artifacts.userDefinedMetadata.signature!=null?n=this.artifacts.userDefinedMetadata.signature:n=this.artifacts.signature,this.signature=n,this.version=`${t.versions.producer}.${t.versions.minConsumer}`;let s=_n.decodeWeights(this.artifacts.weightData,this.artifacts.weightSpecs);if(this.executor=new a2(l7.Instance.transformGraph(t,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(s),this.executor.resourceManager=this.resourceManager,e.modelInitializer!=null&&e.modelInitializer.node!=null){let r=l7.Instance.transformGraph(e.modelInitializer);this.initializer=new a2(r),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializer.executeAsync({},[])}return!0}async save(e,t){if(typeof e=="string"){let n=_n.getSaveHandlers(e);if(n.length===0)throw new Error(`Cannot find any save handlers for URL '${e}'`);if(n.length>1)throw new Error(`Found more than one (${n.length}) save handlers for URL '${e}'`);e=n[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)}predict(e,t){return this.execute(e,this.outputNodes)}normalizeInputs(e){if(!(e instanceof Ge)&&!Array.isArray(e))return e;if(e=Array.isArray(e)?e:[e],e.length!==this.inputNodes.length)throw new Error(`Input tensor count mismatch,the graph model has ${this.inputNodes.length} placeholders, while there are ${e.length} input tensors.`);return this.inputNodes.reduce((t,n,s)=>(t[n]=e[s],t),{})}normalizeOutputs(e){return e=e||this.outputNodes,Array.isArray(e)?e:[e]}execute(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let n=this.executor.execute(e,t);return n.length>1?n:n[0]}async executeAsync(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let n=await this.executor.executeAsync(e,t);return n.length>1?n:n[0]}convertTensorMapToTensorsMap(e){return Object.keys(e).reduce((t,n)=>(t[n]=[e[n]],t),{})}dispose(){this.executor.dispose(),this.initializer&&this.initializer.dispose(),this.resourceManager.dispose()}};async function mt(e,t={}){if(e==null)throw new Error("modelUrl in loadGraphModel() cannot be null. Please provide a url or an IOHandler that loads the model");t==null&&(t={}),t.fromTFHub&&e.load==null&&(e.endsWith("/")||(e=e+"/"),e=`${e}${iB}${oB}`);let n=new y7(e,t);return await n.load(),n}var lB="3.9.0",x7={};Pe(x7,{CSVDataset:()=>_7,Dataset:()=>Yl,FileDataSource:()=>z7,TextLineDataset:()=>N7,URLDataSource:()=>L7,array:()=>_B,csv:()=>VB,func:()=>UB,generator:()=>HB,microphone:()=>jB,version_data:()=>qB,webcam:()=>GB,zip:()=>DB});var uB=Ia(A5()),cB=Ia(A5());function dB(e,t){return nf(e,t)}function nf(e,t,n=new Map,s=new Set){if(e==null)return null;if(s.has(e))throw new Error("Circular references are not supported.");if(n.has(e))return n.get(e);let r=t(e);if(r.recurse&&r.value!==null)throw new Error("A deep map function may not return both a value and recurse=true.");if(r.recurse)if(Zl(e)){let a=Array.isArray(e)?[]:{};s.add(e);for(let o in e){let i=e[o],l=nf(i,t,n,s);a[o]=l}return s.delete(e),a}else throw new Error(`Can't recurse into non-iterable type: ${e}`);else return n.set(e,r.value),r.value}function hB(e,t=v7){return b7(e,t)}function b7(e,t,n=new Set){let s=e[0];if(n.has(s))throw new Error("Circular references are not supported.");let r=t(e);if(r.recurse&&r.value!==null)throw new Error("A deep zip function may not return both a value and recurse=true.");if(r.recurse)if(Zl(s)){let a=Array.isArray(s)?[]:{};n.add(s);for(let o in s){let i=e.map(u=>u[o]),l=b7(i,t,n);a[o]=l}return n.delete(s),a}else throw new Error(`Can't recurse into non-iterable type: ${s}`);else return r.value}function v7(e){return e===null?null:Zl(e[0])?{value:null,recurse:!0}:{value:e,recurse:!1}}async function w7(e,t){let n=new Map;nf(e,t,n);for(let r of Array.from(n.keys())){let a=n.get(r);if(w.isPromise(a)){let o=await a;n.set(r,o)}}return nf(e,t,n)}function Zl(e){let t=!1;if(Q().get("IS_BROWSER"))t=e instanceof TextDecoder;else{let{StringDecoder:n}=y5();t=e instanceof n}return e!=null&&!ArrayBuffer.isView(e)&&(Array.isArray(e)||typeof e=="object"&&!(e instanceof Ge)&&!(e instanceof Promise)&&!t)}function pB(e){return e==null||fB(e)||Array.isArray(e)||typeof e=="object"&&e instanceof Ge||w.isTypedArray(e)}function fB(e){return e===null||typeof e!="object"&&typeof e!="function"}function mB(e){return dB(e,gB)}function gB(e){return e instanceof Ge?{value:e.clone(),recurse:!1}:Zl(e)?{value:null,recurse:!0}:{value:e,recurse:!1}}var k7=class{constructor(e){if(this.capacity=e,this.begin=0,this.end=0,e==null)throw new RangeError("Can't create a ring buffer of unknown capacity.");if(e<1)throw new RangeError("Can't create ring buffer of capacity < 1.");this.data=new Array(e),this.doubledCapacity=2*e}wrap(e){for(;e<0;)e+=this.doubledCapacity;return e%this.doubledCapacity}get(e){if(e<0)throw new RangeError("Can't get item at a negative index.");return this.data[e%this.capacity]}set(e,t){if(e<0)throw new RangeError("Can't set item at a negative index.");this.data[e%this.capacity]=t}length(){let e=this.end-this.begin;return e<0&&(e=this.doubledCapacity+e),e}isFull(){return this.length()===this.capacity}isEmpty(){return this.length()===0}push(e){if(this.isFull())throw new RangeError("Ring buffer is full.");this.set(this.end,e),this.end=this.wrap(this.end+1)}pushAll(e){for(let t of e)this.push(t)}pop(){if(this.isEmpty())throw new RangeError("Ring buffer is empty.");this.end=this.wrap(this.end-1);let e=this.get(this.end);return this.set(this.end,void 0),e}unshift(e){if(this.isFull())throw new RangeError("Ring buffer is full.");this.begin=this.wrap(this.begin-1),this.set(this.begin,e)}shift(){if(this.isEmpty())throw new RangeError("Ring buffer is empty.");let e=this.get(this.begin);return this.set(this.begin,void 0),this.begin=this.wrap(this.begin+1),e}shuffleExcise(e){if(this.isEmpty())throw new RangeError("Ring buffer is empty.");let t=this.wrap(this.begin+e),n=this.get(t);return this.set(t,this.pop()),n}},o2=class extends k7{constructor(){super(o2.INITIAL_CAPACITY)}isFull(){return!1}push(e){super.isFull()&&this.expand(),super.push(e)}unshift(e){super.isFull()&&this.expand(),super.unshift(e)}expand(){let e=this.capacity*2,t=new Array(e),n=this.length();for(let s=0;s<n;s++)t[s]=this.get(this.wrap(this.begin+s));this.data=t,this.capacity=e,this.doubledCapacity=2*this.capacity,this.begin=0,this.end=n}};o2.INITIAL_CAPACITY=32;function I7(e){return new xB(e)}function i2(e){return new bB(e)}function AB(e,t){return new C7(e,t)}function yB(e,t=ua.FAIL){return new EB(e,t)}var en=class{async toArray(){let e=[],t=await this.next();for(;!t.done;)e.push(t.value),t=await this.next();return e}async toArrayForTest(){let e=this.prefetch(100),t=[],n=await e.next();for(;!n.done;)t.push(n.value),n=await e.next();return t}async resolveFully(){let e=await this.next();for(;!e.done;)e=await this.next()}async resolveWhile(e){let t=await this.next(),n=e(t.value);for(;!t.done&&n;)t=await this.next(),n=e(t.value)}handleErrors(e){return new TB(this,e)}filter(e){return new SB(this,e)}map(e){return new CB(this,e)}mapAsync(e){return new S7(this,e)}serialMapAsync(e){return new S7(this,e).serial()}flatmap(e){return new NB(this,e)}async forEachAsync(e){return this.map(e).resolveFully()}async serialForEach(e){return this.serialMapAsync(e).resolveWhile(t=>t===!0)}rowMajorBatch(e,t=!0){return new IB(this,e,t)}columnMajorBatch(e,t=!0,n=v7){return this.rowMajorBatch(e,t).map(r=>hB(r,n))}concatenate(e,t){return new C7(I7([this,e]),t)}take(e){return e<0||e==null?this:new kB(this,e)}skip(e){return e<0||e==null?this:new wB(this,e)}prefetch(e){return new T7(this,e)}shuffle(e,t){return new RB(this,e,t)}serial(){return new vB(this)}},xB=class extends en{constructor(e){super();this.items=e,this.trav=0}summary(){return`Array of ${this.items.length} items`}async next(){if(this.trav>=this.items.length)return{value:null,done:!0};let e=this.items[this.trav];return this.trav++,{value:mB(e),done:!1}}},bB=class extends en{constructor(e){super();this.nextFn=e}summary(){return"Function call"}async next(){try{return this.nextFn()}catch(e){throw e.message=`Error thrown while iterating through a dataset: ${e.message}`,e}}},vB=class extends en{constructor(e){super();this.upstream=e,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Serial`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){return this.upstream.next()}},wB=class extends en{constructor(e,t){super();this.upstream=e,this.maxCount=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Skip`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;this.count++<this.maxCount;){let e=await this.upstream.next();if(e.done)return e;K(e.value)}return this.upstream.next()}},kB=class extends en{constructor(e,t){super();this.upstream=e,this.maxCount=t,this.count=0}summary(){return`${this.upstream.summary()} -> Take`}async next(){return this.count++>=this.maxCount?{value:null,done:!0}:this.upstream.next()}},IB=class extends en{constructor(e,t,n=!0){super();this.upstream=e,this.batchSize=t,this.enableSmallLastBatch=n,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> RowMajorBatch`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){let e=[];for(;e.length<this.batchSize;){let t=await this.upstream.next();if(t.done)return this.enableSmallLastBatch&&e.length>0?{value:e,done:!1}:{value:null,done:!0};e.push(t.value)}return{value:e,done:!1}}},SB=class extends en{constructor(e,t){super();this.upstream=e,this.predicate=t,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Filter`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;){let e=await this.upstream.next();if(e.done||this.predicate(e.value))return e;K(e.value)}}},CB=class extends en{constructor(e,t){super();this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Map`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=$s.getTensorsInContainer(e.value),n=this.transform(e.value),s=$s.getTensorsInContainer(n);for(let r of t)$s.isTensorInList(r,s)||r.dispose();return{value:n,done:!1}}},TB=class extends en{constructor(e,t){super();this.upstream=e,this.handler=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> handleErrors`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;)try{return await this.upstream.next()}catch(e){if(!this.handler(e))return{value:null,done:!0}}}},S7=class extends en{constructor(e,t){super();this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> AsyncMap`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=$s.getTensorsInContainer(e.value),n=await this.transform(e.value),s=$s.getTensorsInContainer(n);for(let r of t)$s.isTensorInList(r,s)||r.dispose();return{value:n,done:!1}}},l2=class extends en{constructor(){super();this.outputQueue=new o2,this.lastRead=Promise.resolve({value:null,done:!1})}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;this.outputQueue.length()===0;)if(!await this.pump())return{value:null,done:!0};return{value:this.outputQueue.shift(),done:!1}}},NB=class extends l2{constructor(e,t){super();this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Flatmap`}async pump(){let e=await this.upstream.next();if(e.done)return!1;let t=$s.getTensorsInContainer(e.value),n=this.transform(e.value),s=$s.getTensorsInContainer(n);this.outputQueue.pushAll(n);for(let r of t)$s.isTensorInList(r,s)||r.dispose();return!0}},C7=class extends en{constructor(e,t){super();this.baseErrorHandler=t,this.lastRead=null,this.iterator=null,this.moreIterators=e}summary(){return"TODO: fill in upstream of chained summaries -> Chained"}async next(){return this.lastRead=this.readFromChain(this.lastRead),this.lastRead}async readFromChain(e){if(await e,this.iterator==null){let n=await this.moreIterators.next();if(n.done)return{value:null,done:!0};this.iterator=n.value,this.baseErrorHandler!=null&&(this.iterator=this.iterator.handleErrors(this.baseErrorHandler))}let t=await this.iterator.next();return t.done?(this.iterator=null,this.readFromChain(e)):t}},ua;(function(e){e[e.FAIL=0]="FAIL",e[e.SHORTEST=1]="SHORTEST",e[e.LONGEST=2]="LONGEST"})(ua||(ua={}));var EB=class extends en{constructor(e,t=ua.FAIL){super();this.iterators=e,this.mismatchMode=t,this.count=0,this.currentPromise=null}summary(){return"{TODO: fill in upstream of zip summaries} -> Zip"}async nextState(e){await e;let t=0,n=0;function s(a){return a instanceof en?{value:a.next().then(i=>(t++,i.done&&n++,i.value)),recurse:!1}:{value:null,recurse:!0}}let r=await w7(this.iterators,s);if(t===n)return{value:null,done:!0};if(n>0)switch(this.mismatchMode){case ua.FAIL:throw new Error(`Zipped streams should have the same length. Mismatched at element ${this.count}.`);case ua.SHORTEST:return{value:null,done:!0};case ua.LONGEST:default:}return this.count++,{value:r,done:!1}}async next(){return this.currentPromise=this.nextState(this.currentPromise),this.currentPromise}},T7=class extends en{constructor(e,t){super();this.upstream=e,this.bufferSize=t,this.buffer=new k7(t)}summary(){return`${this.upstream.summary()} -> Prefetch`}refill(){for(;!this.buffer.isFull();){let e=this.upstream.next();this.buffer.push(e)}}next(){return this.refill(),this.buffer.shift()}},RB=class extends T7{constructor(e,t,n){super(e,t);this.upstream=e,this.windowSize=t,this.upstreamExhausted=!1,this.random=cB.alea(n||w.now().toString()),this.lastRead=Promise.resolve({value:null,done:!1})}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}randomInt(e){return Math.floor(this.random()*e)}chooseIndex(){return this.randomInt(this.buffer.length())}async serialNext(){for(this.upstreamExhausted||this.refill();!this.buffer.isEmpty();){let e=this.chooseIndex(),t=await this.buffer.shuffleExcise(e);if(t.done)this.upstreamExhausted=!0;else return this.refill(),t}return{value:null,done:!0}}},Yl=class{constructor(){this.size=null}batch(e,t=!0){let n=this;w.assert(e>0,()=>`batchSize needs to be positive, but it is
${e}`);let s;return this.size===1/0||this.size==null?s=this.size:t?s=Math.ceil(this.size/e):s=Math.floor(this.size/e),Kn(async()=>(await n.iterator()).columnMajorBatch(e,t,$B),s)}concatenate(e){let t=this,n;return this.size===1/0||e.size===1/0?n=1/0:this.size!=null&&e.size!=null?n=this.size+e.size:n=null,Kn(async()=>(await t.iterator()).concatenate(await e.iterator()),n)}filter(e){let t=this,n;return this.size===1/0?n=1/0:n=null,Kn(async()=>(await t.iterator()).filter(s=>H(()=>e(s))),n)}async forEachAsync(e){return(await this.iterator()).forEachAsync(e)}map(e){let t=this;return Kn(async()=>(await t.iterator()).map(n=>H(()=>e(n))),this.size)}mapAsync(e){let t=this;return Kn(async()=>(await t.iterator()).mapAsync(e),this.size)}prefetch(e){if(e==null)throw new RangeError("`Dataset.prefetch()` requires bufferSize to be specified.");let t=this;return Kn(async()=>(await t.iterator()).prefetch(e),this.size)}repeat(e){let t=this,n;return this.size!=null&&e>0?n=this.size*e:e===0?n=0:this.size!=null&&(e===void 0||e<0)?n=1/0:n=null,Kn(async()=>{let s=i2(async()=>({value:await t.iterator(),done:!1}));return AB(s.take(e))},n)}skip(e){let t=this,n;return this.size!=null&&e>=0&&this.size>=e?n=this.size-e:this.size!=null&&(this.size<e||e===void 0||e<0)?n=0:n=null,Kn(async()=>(await t.iterator()).skip(e),n)}shuffle(e,t,n=!0){if(e==null||e<0)throw this.size==null?new RangeError("`Dataset.shuffle()` requires bufferSize to be specified."):new RangeError(`\`Dataset.shuffle()\` requires bufferSize to be specified. If your data fits in main memory (for regular JS objects), and/or GPU memory (for \`tf.Tensor\`s), consider setting bufferSize to the dataset size (${this.size} elements)`);let s=this,r=uB.alea(t||w.now().toString());return Kn(async()=>{let a=r.int32();return n&&(a+=r.int32()),(await s.iterator()).shuffle(e,a.toString())},this.size)}take(e){let t=this,n;return this.size!=null&&this.size>e?n=e:this.size!=null&&this.size<=e?n=this.size:n=null,Kn(async()=>(await t.iterator()).take(e),n)}async toArray(){if(this.size===1/0)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArray()}async toArrayForTest(){if(this.size===1/0)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArrayForTest()}};Yl.MAX_BUFFER_SIZE=1e4;function Kn(e,t=null){return new class extends Yl{constructor(){super(...arguments);this.size=t}async iterator(){return e()}}}function _B(e){return Kn(async()=>I7(e),e.length)}function DB(e){if(!Zl(e))throw new Error("The argument to zip() must be an object or array.");let t;if(Array.isArray(e))for(let n=0;n<e.length;n++)t=t==null?e[n].size:Math.min(t,e[n].size);else if(e instanceof Object)for(let n in e)t=t==null?e[n].size:Math.min(t,e[n].size);return Kn(async()=>{let n=await w7(e,s=>{if(s instanceof Yl)return{value:s.iterator(),recurse:!1};if(Zl(s))return{value:null,recurse:!0};throw new Error("Leaves of the structure passed to zip() must be Datasets, not primitives.")});return yB(n,ua.SHORTEST)},t)}function $B(e){if(e===null)return null;let t=e[0];return pB(t)?{value:FB(e),recurse:!1}:{value:null,recurse:!0}}function FB(e){if(e.length===0)throw new Error("Can't make a batch of zero elements.");return e[0]instanceof Ge?Dn(e):dn(e)}var N7=class extends Yl{constructor(e){super();this.input=e}async iterator(){return(await this.input.iterator()).decodeUTF8().split(`
`).map(s=>(s.endsWith("\r")&&(s=s.slice(0,-1)),s))}},sf='"',Bc=Symbol("out"),E7=Symbol("field"),rf=Symbol("quote"),u2=Symbol("quoteafterquote"),R7=Symbol("quoteinquote"),_7=class extends Yl{constructor(e,t){super();this.input=e,this.hasHeader=!0,this.fullColumnNames=null,this.columnNamesValidated=!1,this.columnConfigs=null,this.configuredColumnsOnly=!1,this.delimiter=",",this.delimWhitespace=!1,this.base=new N7(e),t||(t={}),this.hasHeader=t.hasHeader!==!1,this.fullColumnNames=t.columnNames,this.columnConfigs=t.columnConfigs,this.configuredColumnsOnly=t.configuredColumnsOnly,t.delimWhitespace?(w.assert(t.delimiter==null,()=>"Delimiter should not be provided when delimWhitespace is true."),this.delimWhitespace=!0,this.delimiter=" "):this.delimiter=t.delimiter?t.delimiter:","}async columnNames(){return this.columnNamesValidated||await this.setColumnNames(),this.configuredColumnsOnly?Object.keys(this.columnConfigs):this.fullColumnNames}async setColumnNames(){let e=await this.maybeReadHeaderLine();if(!this.fullColumnNames&&!e)throw new Error("Column names must be provided if there is no header line.");this.fullColumnNames&&e&&w.assert(e.length===this.fullColumnNames.length,()=>"The length of provided columnNames ("+this.fullColumnNames.length.toString()+") does not match the length of the header line read from file ("+e.length.toString()+")."),this.fullColumnNames||(this.fullColumnNames=e);let t=this.fullColumnNames.reduce((s,r)=>(s[r]=s[r]+1||1,s),{}),n=Object.keys(t).filter(s=>t[s]>1);if(w.assert(n.length===0,()=>"Duplicate column names found: "+n.toString()),this.columnConfigs){for(let s of Object.keys(this.columnConfigs))if(this.fullColumnNames.indexOf(s)===-1)throw new Error('The key "'+s+'" provided in columnConfigs does not match any of the column names ('+this.fullColumnNames.toString()+").")}this.columnNamesValidated=!0}async maybeReadHeaderLine(){if(this.hasHeader){let t=await(await this.base.iterator()).next();if(t.done)throw new Error("No data was found for CSV parsing.");let n=t.value;return this.parseRow(n,!1)}else return null}async iterator(){this.columnNamesValidated||await this.setColumnNames();let e=await this.base.iterator();return this.hasHeader&&(e=e.skip(1)),e.map(t=>this.makeDataElement(t))}makeDataElement(e){let t=this.parseRow(e),n={},s={};for(let r=0;r<this.fullColumnNames.length;r++){let a=this.fullColumnNames[r],o=this.columnConfigs?this.columnConfigs[a]:null;if(!(this.configuredColumnsOnly&&!o)){let i=t[r],l=null;if(i==="")if(o&&o.default!==void 0)l=o.default;else{if(o&&(o.required||o.isLabel))throw new Error(`Required column ${a} is empty in this line: ${e}`);l=void 0}else{let u=Number(i);if(isNaN(u))o&&o.dtype==="bool"?l=this.getBoolean(i):l=i;else if(!o||!o.dtype)l=u;else switch(o.dtype){case"float32":l=u;break;case"int32":l=Math.floor(u);break;case"bool":l=this.getBoolean(i);break;default:l=u}}o&&o.isLabel?s[a]=l:n[a]=l}}return Object.keys(s).length===0?n:{xs:n,ys:s}}getBoolean(e){return e==="1"||e.toLowerCase()==="true"?1:0}parseRow(e,t=!0){let n=[],s=0,r=e.length,a=Bc;for(let o=0;o<r;o++)switch(a){case Bc:switch(e.charAt(o)){case sf:s=o+1,a=rf;break;case this.delimiter:if(s=o+1,this.delimiter===" "&&this.delimWhitespace)break;n.push(""),a=Bc;break;default:a=E7,s=o;break}break;case E7:switch(e.charAt(o)){case this.delimiter:n.push(e.substring(s,o)),a=Bc,s=o+1;break;default:}break;case rf:switch(e.charAt(o)){case sf:a=u2;break;default:}break;case u2:switch(e.charAt(o)){case this.delimiter:n.push(e.substring(s,o-1)),a=Bc,s=o+1;break;case sf:a=rf;break;default:a=R7;break}break;case R7:switch(e.charAt(o)){case sf:a=rf;break;default:}break;default:}if(a===u2?n.push(e.substring(s,r-1)):n.push(e.substring(s)),t&&n.length!==this.fullColumnNames.length)throw new Error(`Invalid row in csv file. Should have ${this.fullColumnNames.length} elements in a row, but got ${n}`);return n}},D7=class extends en{constructor(e){super();this.microphoneConfig=e,this.isClosed=!1,this.fftSize=e.fftSize||1024;let t=Math.log2(this.fftSize);if(this.fftSize<0||t<4||t>14||!Number.isInteger(t))throw new Error(`Invalid fftSize: it must be a power of 2 between 2 to 4 and 2 to 14, but got ${this.fftSize}`);if(this.numFrames=e.numFramesPerSpectrogram||43,this.sampleRateHz=e.sampleRateHz,this.columnTruncateLength=e.columnTruncateLength||this.fftSize,this.audioTrackConstraints=e.audioTrackConstraints,this.smoothingTimeConstant=e.smoothingTimeConstant||0,this.includeSpectrogram=e.includeSpectrogram!==!1,this.includeWaveform=e.includeWaveform===!0,!this.includeSpectrogram&&!this.includeWaveform)throw new Error("Both includeSpectrogram and includeWaveform are false. At least one type of data should be returned.")}summary(){return"microphone"}static async create(e={}){if(Q().get("IS_NODE"))throw new Error("microphone API is only supported in browser environment.");let t=new D7(e);return await t.start(),t}async start(){try{this.stream=await navigator.mediaDevices.getUserMedia({audio:this.audioTrackConstraints==null?!0:this.audioTrackConstraints,video:!1})}catch(n){throw new Error(`Error thrown while initializing video stream: ${n.message}`)}if(!this.stream)throw new Error("Could not obtain audio from microphone.");let e=window.AudioContext||window.webkitAudioContext;if(this.audioContext=new e,!this.sampleRateHz)this.sampleRateHz=this.audioContext.sampleRate;else if(this.audioContext.sampleRate!==this.sampleRateHz)throw new Error(`Mismatch in sampling rate: Expected: ${this.sampleRateHz}; Actual: ${this.audioContext.sampleRate}`);let t=this.audioContext.createMediaStreamSource(this.stream);this.analyser=this.audioContext.createAnalyser(),this.analyser.fftSize=this.fftSize*2,this.analyser.smoothingTimeConstant=this.smoothingTimeConstant,t.connect(this.analyser),this.freqData=new Float32Array(this.fftSize),this.timeData=new Float32Array(this.fftSize)}async next(){if(this.isClosed)return{value:null,done:!0};let e,t,n=await this.getAudioData();if(this.includeSpectrogram){let s=this.flattenQueue(n.freqDataQueue);e=this.getTensorFromAudioDataArray(s,[this.numFrames,this.columnTruncateLength,1])}if(this.includeWaveform){let s=this.flattenQueue(n.timeDataQueue);t=this.getTensorFromAudioDataArray(s,[this.numFrames*this.fftSize,1])}return{value:{spectrogram:e,waveform:t},done:!1}}async capture(){return(await this.next()).value}async getAudioData(){let e=[],t=[],n=0;return new Promise(s=>{let r=setInterval(()=>{this.includeSpectrogram&&(this.analyser.getFloatFrequencyData(this.freqData),this.freqData[0]===-1/0&&s({freqDataQueue:e,timeDataQueue:t}),e.push(this.freqData.slice(0,this.columnTruncateLength))),this.includeWaveform&&(this.analyser.getFloatTimeDomainData(this.timeData),t.push(this.timeData.slice())),++n===this.numFrames&&(clearInterval(r),s({freqDataQueue:e,timeDataQueue:t}))},this.fftSize/this.sampleRateHz*1e3)})}stop(){this.isClosed||(this.isClosed=!0,this.analyser.disconnect(),this.audioContext.close(),this.stream!=null&&this.stream.getTracks().length>0&&this.stream.getTracks()[0].stop())}toArray(){throw new Error("Can not convert infinite audio stream to array.")}getSampleRate(){return this.sampleRateHz}flattenQueue(e){let t=e[0].length,n=new Float32Array(e.length*t);return e.forEach((s,r)=>n.set(s,r*t)),n}getTensorFromAudioDataArray(e,t){let n=new Float32Array(w.sizeFromShape(t));return n.set(e,n.length-e.length),dn(n,t)}},$7=class extends en{constructor(e,t){super();if(this.webcamVideoElement=e,this.webcamConfig=t,this.isClosed=!0,this.resize=!1,this.needToResize())if(this.resize=!0,this.cropSize=[this.webcamConfig.resizeHeight,this.webcamConfig.resizeWidth],this.cropBoxInd=Mt([0],"int32"),this.webcamConfig.centerCrop){let n=this.webcamConfig.resizeWidth*1/this.webcamVideoElement.width,s=this.webcamConfig.resizeHeight*1/this.webcamVideoElement.height,r=(1-n)/2,a=(1-s)/2,o=r+n,i=s+a;this.cropBox=Ms([a,r,i,o],[1,4])}else this.cropBox=Ms([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(e,t={}){if(Q().get("IS_NODE"))throw new Error("tf.data.webcam is only supported in browser environment.");if(!e){if(e=document.createElement("video"),!t.resizeWidth||!t.resizeHeight)throw new Error("Please provide webcam video element, or resizeWidth and resizeHeight to create a hidden video element.");e.width=t.resizeWidth,e.height=t.resizeHeight}let n=new $7(e,t);return await n.start(),n}async start(){this.webcamConfig.facingMode&&w.assert(this.webcamConfig.facingMode==="user"||this.webcamConfig.facingMode==="environment",()=>`Invalid webcam facing mode: ${this.webcamConfig.facingMode}. Please provide 'user' or 'environment'`);try{this.stream=await navigator.mediaDevices.getUserMedia({video:{deviceId:this.webcamConfig.deviceId,facingMode:this.webcamConfig.facingMode?this.webcamConfig.facingMode:"user",width:this.webcamVideoElement.width,height:this.webcamVideoElement.height}})}catch(e){throw e.message=`Error thrown while initializing video stream: ${e.message}`,e}if(!this.stream)throw new Error("Could not obtain video from webcam.");try{this.webcamVideoElement.srcObject=this.stream}catch(e){console.log(e),this.webcamVideoElement.src=window.URL.createObjectURL(this.stream)}return this.webcamVideoElement.play(),this.isClosed=!1,new Promise(e=>{this.webcamVideoElement.onloadedmetadata=()=>{e()}})}async next(){if(this.isClosed)return{value:null,done:!0};let e;try{e=ls.fromPixels(this.webcamVideoElement)}catch(t){throw new Error(`Error thrown converting video to pixels: ${JSON.stringify(t)}`)}if(this.resize)try{return{value:this.cropAndResizeFrame(e),done:!1}}catch(t){throw new Error(`Error thrown cropping the video: ${t.message}`)}finally{e.dispose()}else return{value:e,done:!1}}needToResize(){return!!(this.webcamConfig.resizeWidth&&this.webcamConfig.resizeHeight&&(this.webcamVideoElement.width!==this.webcamConfig.resizeWidth||this.webcamVideoElement.height!==this.webcamConfig.resizeHeight))}cropAndResizeFrame(e){return H(()=>{let t=Ot(ce(e,"float32"),0),n;n=_e.cropAndResize(t,this.cropBox,this.cropBoxInd,this.cropSize,"bilinear");let s=n.shape;return U(n,s.slice(1))})}async capture(){return(await this.next()).value}stop(){this.stream.getTracks().forEach(t=>t.stop());try{this.webcamVideoElement.srcObject=null}catch(t){console.log(t),this.webcamVideoElement.src=null}this.isClosed=!0}toArray(){throw new Error("Can not convert infinite video stream to array.")}},F7=class{},O7=class extends en{split(e){return new OB(this,e)}},OB=class extends O7{constructor(e,t){super();this.upstream=e,this.impl=new PB(e,t)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},PB=class extends l2{constructor(e,t){super();this.upstream=e,this.separator=t,this.carryover=""}summary(){return`${this.upstream.summary()} -> Split('${this.separator}')`}async pump(){let e=await this.upstream.next();if(e.done)return this.carryover===""?!1:(this.outputQueue.push(this.carryover),this.carryover="",!0);let t=e.value.split(this.separator);t[0]=this.carryover+t[0];for(let n of t.slice(0,-1))this.outputQueue.push(n);return this.carryover=t[t.length-1],!0}},MB=class extends en{decodeUTF8(){return new zB(this)}},zB=class extends O7{constructor(e){super();this.upstream=e,this.impl=new LB(e)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},LB=class extends l2{constructor(e){super();if(this.upstream=e,Q().get("IS_BROWSER"))this.decoder=new TextDecoder("utf-8");else{let{StringDecoder:t}=y5();this.decoder=new t("utf8")}}summary(){return`${this.upstream.summary()} -> Utf8`}async pump(){let e=await this.upstream.next(),t;if(e.done)return!1;t=e.value;let n;return Q().get("IS_BROWSER")?n=this.decoder.decode(t,{stream:!0}):n=this.decoder.write(Buffer.from(t.buffer)),this.outputQueue.push(n),!0}},P7=class extends MB{constructor(e,t={}){super();this.file=e,this.options=t,w.assert(e instanceof Uint8Array||(Q().get("IS_BROWSER")?e instanceof File||e instanceof Blob:!1),()=>"FileChunkIterator only supports File, Blob and Uint8Array right now."),this.offset=t.offset||0,this.chunkSize=t.chunkSize||1024*1024}summary(){return`FileChunks ${this.file}`}async next(){return this.offset>=(this.file instanceof Uint8Array?this.file.byteLength:this.file.size)?{value:null,done:!0}:{value:await new Promise((t,n)=>{let s=this.offset+this.chunkSize;if(this.file instanceof Uint8Array)t(new Uint8Array(this.file.slice(this.offset,s)));else{let r=new FileReader;r.onload=o=>{let i=r.result;if(i instanceof ArrayBuffer&&(i=new Uint8Array(i)),!(i instanceof Uint8Array))return n(new TypeError("FileReader returned unknown type."));t(i)},r.onabort=o=>n(new Error("Aborted")),r.onerror=o=>n(new Error(o.type));let a=this.file.slice(this.offset,s);r.readAsArrayBuffer(a)}this.offset=s}),done:!1}}};async function BB(e,t={}){let n,s;typeof e=="string"?n=e:(n=e.url,s=WB(e));let r=await w.fetch(n,s);if(r.ok){let a=new Uint8Array(await r.arrayBuffer());return new P7(a,t)}else throw new Error(r.statusText)}var WB=e=>({method:e.method,headers:e.headers,body:e.body,mode:e.mode,credentials:e.credentials,cache:e.cache,redirect:e.redirect,referrer:e.referrer,integrity:e.integrity});function M7(e){return typeof e=="string"&&e.substr(0,7)==="file://"}var z7=class extends F7{constructor(e,t={}){super();this.input=e,this.options=t}async iterator(){if(M7(this.input)&&Q().get("IS_NODE")){let e=bi("fs");this.input=e.readFileSync(this.input.substr(7))}return new P7(this.input,this.options)}},L7=class extends F7{constructor(e,t={}){super();this.url=e,this.fileOptions=t}async iterator(){return M7(this.url)?new z7(this.url,this.fileOptions).iterator():BB(this.url,this.fileOptions)}};function VB(e,t={}){return new _7(new L7(e),t)}function UB(e){let t=i2(e);return Kn(async()=>t)}function HB(e){return Kn(async()=>{let t=await e();return i2(()=>t.next())})}async function GB(e,t){return $7.create(e,t)}async function jB(e){return D7.create(e)}var qB="3.9.0";function ke(e,t){Array.isArray(e)||(e=[e]),e.forEach(n=>{n!=null&&w.assert(n.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the CPU backend.`)})}var XB=rr.whereImpl,af=class extends Du{constructor(){super();this.blockSize=48,this.firstUse=!0,this.data=new Ud(this,wr())}nextDataId(){return af.nextDataId++}write(e,t,n){this.firstUse&&(this.firstUse=!1,Q().get("IS_NODE")&&D.warn(`
============================
Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To speed things up dramatically, install our node backend, which binds to TensorFlow C++, by running npm i @tensorflow/tfjs-node, or npm i @tensorflow/tfjs-node-gpu if you have CUDA. Then call require('@tensorflow/tfjs-node'); (-gpu suffix for CUDA) at the start of your program. Visit https://github.com/tensorflow/tfjs-node for more details.
============================`));let s={id:this.nextDataId()};return this.data.set(s,{values:e,dtype:n,refCount:1}),s}makeTensorInfo(e,t,n){let s;if(t==="string"&&n!=null&&n.length>0&&w.isString(n[0])){let r=n.map(a=>w.encodeString(a));s=this.write(r,e,t)}else s=this.write(n,e,t);return{dataId:s,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,n,s,r){this.data.set(e,{values:t,dtype:s,refCount:r})}numDataIds(){return this.data.numDataIds()}async read(e){return this.readSync(e)}readSync(e){let{dtype:t,complexTensorInfos:n}=this.data.get(e);if(t==="complex64"){let s=this.readSync(n.real.dataId),r=this.readSync(n.imag.dataId);return D.mergeRealAndImagArrays(s,r)}return this.data.get(e).values}bufferSync(e){let t=this.readSync(e.dataId),n=t;if(e.dtype==="string")try{n=t.map(s=>w.decodeString(s))}catch(s){throw new Error("Failed to decode encoded string bytes into utf-8")}return We(e.shape,e.dtype,n)}makeOutput(e,t,n){let s=this.write(e,t,n);return wr().makeTensorFromDataId(s,t,n,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:n}=this.data.get(e);n!=null&&(this.disposeData(n.real.dataId,!0),this.disposeData(n.imag.dataId,!0)),this.data.delete(e)}return!0}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}async time(e){let t=w.now();return e(),{kernelMs:w.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){ke([e],"where");let t=this.readSync(e.dataId);return XB(e.shape,t)}dispose(){}floatPrecision(){return 32}epsilon(){return super.epsilon()}};af.nextDataId=0;var c2={};Pe(c2,{addImpl:()=>W7,bincountImpl:()=>h2,bincountReduceImpl:()=>V7,ceilImpl:()=>U7,concatImpl:()=>p2,equalImpl:()=>H7,expImpl:()=>j7,expm1Impl:()=>X7,floorImpl:()=>K7,gatherNdImpl:()=>Z7,gatherV2Impl:()=>Y7,greaterEqualImpl:()=>Q7,greaterImpl:()=>J7,lessEqualImpl:()=>tw,lessImpl:()=>ew,linSpaceImpl:()=>nw,logImpl:()=>sw,maxImpl:()=>rw,maximumImpl:()=>aw,minimumImpl:()=>ow,multiplyImpl:()=>f2,negImpl:()=>iw,notEqualImpl:()=>lw,prodImpl:()=>uw,rangeImpl:()=>g2,rsqrtImpl:()=>cw,sigmoidImpl:()=>PW,simpleAbsImpl:()=>B7,sliceImpl:()=>uf,sparseFillEmptyRowsImpl:()=>hw,sparseReshapeImpl:()=>pw,sparseSegmentReductionImpl:()=>A2,sqrtImpl:()=>LW,squaredDifferenceImpl:()=>fw,stridedSliceImpl:()=>mw,stringNGramsImpl:()=>gw,stringSplitImpl:()=>Aw,stringToHashBucketFastImpl:()=>yw,subImpl:()=>xw,tileImpl:()=>bw,topKImpl:()=>ww,transposeImpl:()=>m2,uniqueImpl:()=>kw});function B7(e){let t=new Float32Array(e.length);for(let n=0;n<e.length;++n)t[n]=Math.abs(e[n]);return t}var KB=e=>{let{x:t}=e.inputs,n=e.backend;ke(t,"abs");let s=new Float32Array(w.sizeFromShape(t.shape)),r=n.data.get(t.dataId).values;return s=B7(r),n.makeOutput(s,t.shape,"float32")},ZB={kernelName:ki,backendName:"cpu",kernelFunc:KB};function Lt(e){return(t,n,s,r,a)=>{let o=D.assertAndGetBroadcastShape(t,n),i=o.length,l=w.computeStrides(o),u=w.sizeFromShape(o),c=w.getTypedArrayFromDType(a,u),d=t.length,h=n.length,p=w.computeStrides(t),f=w.computeStrides(n),m=D.getBroadcastDims(t,o),g=D.getBroadcastDims(n,o);if(m.length+g.length===0)for(let A=0;A<c.length;++A)c[A]=e(s[A%s.length],r[A%r.length]);else for(let A=0;A<c.length;++A){let y=w.indexToLoc(A,i,l),x=y.slice(-d);m.forEach(S=>x[S]=0);let b=w.locToIndex(x,d,p),v=y.slice(-h);g.forEach(S=>v[S]=0);let k=w.locToIndex(v,h,f);c[A]=e(s[b],r[k])}return[c,o]}}function Zn(e){let{inputs:t,backend:n}=e,{real:s,imag:r}=t,a=n.data.get(s.dataId).values,o=n.data.get(r.dataId).values,i=n.makeTensorInfo(s.shape,"complex64"),l=n.data.get(i.dataId);return l.complexTensorInfos={real:n.makeTensorInfo(s.shape,"float32",a),imag:n.makeTensorInfo(r.shape,"float32",o)},i}var YB={kernelName:Yd,backendName:"cpu",kernelFunc:Zn};function of(e,t,n="float32"){if(n==="complex64"){let r=of(e,t,"float32"),a=of(e,t,"float32");return Zn({inputs:{real:r,imag:a},backend:e})}let s=w.makeZerosTypedArray(w.sizeFromShape(t),n);return e.makeTensorInfo(t,n,s)}function cr(e){let{inputs:t,backend:n}=e,{x:s}=t;return n.incRef(s.dataId),{dataId:s.dataId,shape:s.shape,dtype:s.dtype}}var JB={kernelName:ja,backendName:"cpu",kernelFunc:cr};function Ko(e){let{inputs:t,backend:n}=e,{input:s}=t,r=n.data.get(s.dataId).complexTensorInfos.real,a=n.data.get(r.dataId).values;return n.makeTensorInfo(r.shape,r.dtype,a)}var QB={kernelName:yh,backendName:"cpu",kernelFunc:Ko};function ca(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{dtype:a}=s;if(a==="complex64"){if(r.dtype==="complex64")return cr({inputs:{x:r},backend:n});let o=of(n,r.shape,r.dtype),i=ca({inputs:{x:r},backend:n,attrs:{dtype:"float32"}}),l=Zn({inputs:{real:i,imag:o},backend:n});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(i),l}if(r.dtype==="complex64"){let o=Ko({inputs:{input:r},backend:n}),i=ca({inputs:{x:o},backend:n,attrs:{dtype:a}});return n.disposeIntermediateTensorInfo(o),i}if(!w.hasEncodingLoss(r.dtype,a)){let o=cr({inputs:{x:r},backend:n});return{dataId:o.dataId,shape:o.shape,dtype:a}}if(a==="int32"){let o=n.data.get(r.dataId).values,i=Int32Array.from(o);return n.makeTensorInfo(r.shape,"int32",i)}if(a==="bool"){let o=n.data.get(r.dataId).values,i=w.toTypedArray([0],r.dtype),[l,u]=Lt((c,d)=>c!==d?1:0)(r.shape,[],o,i,"bool");return n.makeTensorInfo(u,"bool",l)}throw new Error(`Error in Cast: failed to cast ${r.dtype} to ${a}`)}var eW={kernelName:_a,backendName:"cpu",kernelFunc:ca};function tn(e,t,n,s){return n==null?({inputs:r,backend:a})=>{let{a:o,b:i}=r,l=a;ke([o,i],e);let u=l.data.get(o.dataId).values,c=l.data.get(i.dataId).values,d=o.dtype==="string"?D.fromUint8ToStringArray(u):u,h=o.dtype==="string"?D.fromUint8ToStringArray(c):c,p=s||o.dtype,[f,m]=t(o.shape,i.shape,d,h,p);return l.makeTensorInfo(m,p,f)}:({inputs:r,backend:a})=>{let{a:o,b:i}=r,l=a;if(o.dtype==="complex64"||i.dtype==="complex64"){let u=ca({inputs:{x:o},backend:l,attrs:{dtype:"complex64"}}),c=l.data.get(u.dataId),d=c.complexTensorInfos.real,h=c.complexTensorInfos.imag,p=l.data.get(d.dataId).values,f=l.data.get(h.dataId).values,m=ca({inputs:{x:i},backend:l,attrs:{dtype:"complex64"}}),g=l.data.get(m.dataId),A=g.complexTensorInfos.real,y=g.complexTensorInfos.imag,x=l.data.get(A.dataId).values,b=l.data.get(y.dataId).values,[v,k,S]=n(o.shape,i.shape,p,f,x,b),C=l.makeTensorInfo(S,"float32",v),_=l.makeTensorInfo(S,"float32",k),O=Zn({inputs:{real:C,imag:_},backend:l});return l.disposeIntermediateTensorInfo(u),l.disposeIntermediateTensorInfo(m),l.disposeIntermediateTensorInfo(C),l.disposeIntermediateTensorInfo(_),O}else{let u=l.data.get(o.dataId).values,c=l.data.get(i.dataId).values,d=s||o.dtype,[h,p]=t(o.shape,i.shape,u,c,d);return l.makeTensorInfo(p,d,h)}}}function d2(e){return(t,n,s,r,a,o)=>{let i=D.assertAndGetBroadcastShape(t,n),l=w.sizeFromShape(i),u=i.length,c=w.computeStrides(i),d=w.getTypedArrayFromDType("float32",l),h=w.getTypedArrayFromDType("float32",l),p=D.getBroadcastDims(t,i),f=D.getBroadcastDims(n,i),m=D.mergeRealAndImagArrays(s,r),g=D.mergeRealAndImagArrays(a,o),A=t.length,y=w.computeStrides(t),x=n.length,b=w.computeStrides(n);if(p.length+f.length===0)for(let v=0;v<d.length;v++){let k=v%m.length,S=v%g.length,C=e(m[k*2],m[k*2+1],g[S*2],g[S*2+1]);d[v]=C.real,h[v]=C.imag}else for(let v=0;v<d.length;v++){let k=w.indexToLoc(v,u,c),S=k.slice(-A);p.forEach(R=>S[R]=0);let C=w.locToIndex(S,A,y),_=k.slice(-x);f.forEach(R=>_[R]=0);let O=w.locToIndex(_,x,b),E=e(m[C*2],m[C*2+1],g[O*2],g[O*2+1]);d[v]=E.real,h[v]=E.imag}return[d,h,i]}}var W7=Lt((e,t)=>e+t),tW=d2((e,t,n,s)=>({real:e+n,imag:t+s})),Wc=tn(Vr,W7,tW),nW={kernelName:Vr,backendName:"cpu",kernelFunc:Wc};function h2(e,t,n,s,r){let a=w.sizeFromShape(s),o=w.makeZerosTypedArray(r,n);for(let i=0;i<e.length;i++){let l=e[i];if(l<0)throw new Error("Input x must be non-negative!");l>=r||(a>0?o[l]+=t[i]:o[l]+=1)}return o}function V7(e,t,n,s=!1){let r=e.shape[0],a=e.shape[1],o=We([r,n],t.dtype);for(let i=0;i<r;i++)for(let l=0;l<a;l++){let u=e.get(i,l);if(u<0)throw new Error("Input x must be non-negative!");u>=n||(s?o.set(1,i,u):t.size>0?o.set(o.get(i,u)+t.get(i,l),i,u):o.set(o.get(i,u)+1,i,u))}return o}function da(e){return(t,n,s)=>{let r=w.getTypedArrayFromDType(n,t.length);for(let a=0;a<t.length;++a)r[a]=e(t[a],s);return r}}function ot(e,t,n){return({inputs:s,attrs:r,backend:a})=>{let{x:o}=s;if(ke(o,e),o.dtype==="string"||n==="string")throw new Error("unaryKernelFunc does not support string input/output");let i=a,l=i.data.get(o.dataId).values,u=w.sizeFromShape(o.shape),c=n||o.dtype,d=w.getArrayFromDType(c,u);for(let h=0;h<u;++h)d[h]=t(l[h],r);return i.makeTensorInfo(o.shape,c,d)}}function Jl(e,t,n){return({inputs:s,attrs:r,backend:a})=>{let{x:o}=s;if(ke(o,e),o.dtype==="string"||n==="string")throw new Error("unaryKernelFunc does not support string input/output");let i=a,l=i.data.get(o.dataId).values,u=n||o.dtype,c=t(l,u,r);return i.makeTensorInfo(o.shape,u,c)}}var U7=da(e=>Math.ceil(e)),sW=Jl(Da,U7),rW={kernelName:Da,backendName:"cpu",kernelFunc:sW};function p2(e,t,n,s){let r=w.getArrayFromDType(n,w.sizeFromShape(t));if(s&&n!=="string"){let a=0;e.forEach(o=>{let i=w.sizeFromShape(o.shape);r.set(o.vals,a),a+=i})}else{let a=0;e.forEach(o=>{let i=n==="string"?D.fromUint8ToStringArray(o.vals):o.vals,l=0;for(let u=0;u<o.shape[0];++u){let c=u*t[1]+a;for(let d=0;d<o.shape[1];++d)r[c+d]=i[l++]}a+=o.shape[1]})}return r}var H7=Lt((e,t)=>e===t?1:0),G7=tn(zi,H7,null,"bool"),aW={kernelName:zi,backendName:"cpu",kernelFunc:G7},j7=da(e=>Math.exp(e)),q7=Jl(Wa,j7),oW={kernelName:Wa,backendName:"cpu",kernelFunc:q7},X7=da(e=>Math.expm1(e)),iW=Jl(Bi,X7),lW={kernelName:Bi,backendName:"cpu",kernelFunc:iW},K7=da(e=>Math.floor(e)),uW=Jl(Va,K7),cW={kernelName:Va,backendName:"cpu",kernelFunc:uW};function Z7(e,t,n,s,r,a,o,i,l){let u=We([s,a],n);for(let c=0;c<s;c++){let d=[],h=0;for(let p=0;p<r;p++){let f=e[c*r+p];h+=f*o[p],d.push(f)}if(h<0||h>=l/a)throw new Error(`Invalid indices: ${d} does not index into ${i}`);for(let p=0;p<a;p++)u.values[c*a+p]=t.get(...t.indexToLoc(h*a+p))}return u}function Y7(e,t,n){let s=We(n,e.dtype);for(let r=0;r<s.size;++r){let o=s.indexToLoc(r).slice(),i=o[0],l=o[2],u=t.locToIndex([i,l]);o[2]=t.values[u];let c=e.locToIndex(o);s.values[r]=e.values[c]}return s}var J7=Lt((e,t)=>e>t?1:0),dW=tn(Hi,J7,null,"bool"),hW={kernelName:Hi,backendName:"cpu",kernelFunc:dW},Q7=Lt((e,t)=>e>=t?1:0),pW=tn(Ga,Q7,null,"bool"),fW={kernelName:Ga,backendName:"cpu",kernelFunc:pW},ew=Lt((e,t)=>e<t?1:0),mW=tn(Xi,ew,null,"bool"),gW={kernelName:Xi,backendName:"cpu",kernelFunc:mW},tw=Lt((e,t)=>e<=t?1:0),AW=tn(Ki,tw,null,"bool"),yW={kernelName:Ki,backendName:"cpu",kernelFunc:AW};function nw(e,t,n){let s=(t-e)/(n-1),r=w.makeZerosTypedArray(n,"float32");r[0]=e;for(let a=1;a<r.length;a++)r[a]=r[a-1]+s;return r}var sw=da(e=>Math.log(e)),xW=Jl(Xa,sw),bW={kernelName:Xa,backendName:"cpu",kernelFunc:xW};function rw(e,t,n,s){let r=w.getTypedArrayFromDType(s,w.sizeFromShape(n));for(let a=0;a<r.length;++a){let o=a*t,i=e[o];for(let l=0;l<t;++l){let u=e[o+l];(Number.isNaN(u)||u>i)&&(i=u)}r[a]=i}return r}var aw=Lt((e,t)=>Math.max(e,t)),vW=tn(Za,aw),wW={kernelName:Za,backendName:"cpu",kernelFunc:vW},ow=Lt((e,t)=>Math.min(e,t)),kW=tn(eo,ow),IW={kernelName:eo,backendName:"cpu",kernelFunc:kW},f2=Lt((e,t)=>e*t),SW=d2((e,t,n,s)=>({real:e*n-t*s,imag:e*s+t*n})),lf=tn(no,f2,SW),CW={kernelName:no,backendName:"cpu",kernelFunc:lf};function iw(e,t,n){let s=w.createScalarValue(-1,n);return f2([],t,s,e,n)}function TW(e){let{inputs:t,backend:n}=e,{x:s}=t;ke(s,"neg");let r=n.data.get(s.dataId).values,[a,o]=iw(r,s.shape,s.dtype);return n.makeTensorInfo(o,s.dtype,a)}var NW={kernelName:Qi,backendName:"cpu",kernelFunc:TW},lw=Lt((e,t)=>e!==t?1:0),EW=tn(el,lw,null,"bool"),RW={kernelName:el,backendName:"cpu",kernelFunc:EW};function m2(e,t,n,s,r){let a=t.length,o=w.sizeFromShape(t),i=w.computeStrides(t),l=w.computeStrides(r),u=w.getTypedArrayFromDType(n,w.sizeFromShape(r));for(let c=0;c<o;++c){let d=w.indexToLoc(c,a,i),h=new Array(d.length);for(let f=0;f<h.length;f++)h[f]=d[s[f]];let p=w.locToIndex(h,a,l);u[p]=e[c]}return u}function As(e){let{inputs:t,attrs:n,backend:s}=e,{x:r}=t,{perm:a}=n;ke(r,"transpose");let o=r.shape.length,i=new Array(o);for(let d=0;d<i.length;d++)i[d]=r.shape[a[d]];let l=s.data.get(r.dataId).values,u=m2(l,r.shape,r.dtype,a,i);return{dataId:s.write(u,i,r.dtype),shape:i,dtype:r.dtype}}var _W={kernelName:ko,backendName:"cpu",kernelFunc:As};function uw(e,t,n,s){let[r,a]=D.computeOutAndReduceShapes(e,s),o=Cs(t,"int32"),i=w.makeZerosTypedArray(w.sizeFromShape(r),o),l=w.sizeFromShape(a);for(let u=0;u<i.length;++u){let c=u*l,d=1;for(let h=0;h<l;++h)d*=n[c+h];i[u]=d}return{outVals:i,outShape:r,outDtype:o}}function DW(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;ke(r,"prod");let i=r.shape.length,l=w.parseAxisParam(a,r.shape),u=D.getAxesPermutation(l,i),c=l,d=r,h=[];u!=null&&(d=As({inputs:{x:r},backend:n,attrs:{perm:u}}),h.push(d),c=D.getInnerMostAxes(c.length,i));let p=n.data.get(d.dataId).values,{outVals:f,outShape:m,outDtype:g}=uw(d.shape,d.dtype,p,c),A=m;return o&&(A=D.expandShapeToKeepDim(m,l)),h.forEach(y=>n.disposeIntermediateTensorInfo(y)),n.makeTensorInfo(A,g,f)}var $W={kernelName:ol,backendName:"cpu",kernelFunc:DW};function g2(e,t,n,s){let r=e===t,a=e<t&&n<0,o=t<e&&n>1;if(r||a||o)return w.makeZerosTypedArray(0,s);let i=Math.abs(Math.ceil((t-e)/n)),l=w.makeZerosTypedArray(i,s);t<e&&n===1&&(n=-1),l[0]=e;for(let u=1;u<l.length;u++)l[u]=l[u-1]+n;return l}var cw=da(e=>1/Math.sqrt(e)),FW=Jl(po,cw),OW={kernelName:po,backendName:"cpu",kernelFunc:FW},PW=da(e=>1/(1+Math.exp(-e))),dw=ot(mo,e=>1/(1+Math.exp(-e))),MW={kernelName:mo,backendName:"cpu",kernelFunc:dw};function uf(e,t,n,s,r){let a=xn.isSliceContinous(s,t,n),o=w.sizeFromShape(n),i=w.computeStrides(s);if(a){let d=xn.computeFlatOffset(t,i);return r==="string"?e.slice(d,d+o):e.subarray(d,d+o)}let l=r==="string"?D.fromUint8ToStringArray(e):e,u=We(s,r,l),c=We(n,r);for(let d=0;d<c.size;++d){let h=c.indexToLoc(d),p=h.map((f,m)=>f+t[m]);c.set(u.get(...p),...h)}return r==="string"?D.fromStringArrayToUint8(c.values):c.values}function Zo(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{begin:a,size:o}=s;ke(r,"slice");let[i,l]=xn.parseSliceParams(r,a,o);xn.assertParamsValid(r,i,l);let u=n.data.get(r.dataId).values,c=uf(u,i,l,r.shape,r.dtype);return n.makeTensorInfo(l,r.dtype,c)}var zW={kernelName:hl,backendName:"cpu",kernelFunc:Zo};function hw(e,t,n,s,r,a,o){let i=t[0],l=a[0],u=new Array(l),c=new Array(i),d=t[1];if(l===0){if(i!==0)throw new Error(`Received SparseTensor with denseShape[0] = 0 but
indices.shape[0] = ${i}`);let g=w.getArrayFromDType(n,0),A=w.getArrayFromDType(r,0);return[g,[0,d],A,u,c]}let h=!0,p=0,f=new Array(l).fill(0);for(let g=0;g<i;++g){let A=e[g*d];if(A<0)throw new Error(`indices(${g}, 0) is invalid: ${A} < 0`);if(A>=l)throw new Error(`indices(${g}, 0) is invalid: ${A} >= ${l}`);++f[A],h=h&&A>=p,p=A}let m=!0;for(let g=0;g<l;++g){let A=f[g]===0;u[g]=A,m=m&&!A,f[g]=Math.max(f[g],1),g>0&&(f[g]+=f[g-1])}if(m&&h){let g=e,A=s;for(let y=0;y<i;++y)c[y]=y;return[g,[i,d],A,u,c]}else{let g=f[l-1],A=w.getArrayFromDType(n,g*d),y=w.getArrayFromDType(r,g),x=new Array(l).fill(0);for(let b=0;b<i;++b){let v=e[b*d],k=x[v],S=(v===0?0:f[v-1])+k;x[v]++;for(let C=0;C<d;++C)A[S*d+C]=e[b*d+C];y[S]=s[b],c[b]=S}for(let b=0;b<l;++b)if(x[b]===0){let k=b===0?0:f[b-1];A[k*d+0]=b;for(let S=1;S<d;++S)A[k*d+S]=0;y[k]=o}return[A,[g,d],y,u,c]}}function pw(e,t,n,s,r){let a=w.sizeFromShape(s),o=t[0],i=r.length,l=[],u=1,c=-1;for(let g=0;g<i;++g){let A=r[g];if(A===-1){if(c!==-1)throw new Error(`only one output dimension may be -1, not both ${c} and ${g}`);c=g,l.push(1)}else{if(A<0)throw new Error(`size ${g} must be non-negative, not ${A}`);u*=A,l.push(A)}}if(c!==-1){if(u<=0)throw new Error("reshape cannot infer the missing input size for an empty tensor unless all specified input sizes are non-zero");let g=Math.trunc(a/u);if(u*g!==a)throw new Error(`Input to reshape is a SparseTensor with ${a}
dense values, but the requested shape requires a multiple of ${u}. inputShape=${s} outputShape= ${l}`);l[c]=g}let d=w.sizeFromShape(l);if(d!==a)throw new Error(`Input to reshape is a tensor with ${a} dense values, but the requested shape has ${d}. inputShape=${s} outputShape=${l}`);let h=s.length,p=[];if(h>0){p[h-1]=1;for(let g=h-2;g>=0;--g)p[g]=p[g+1]*s[g+1]}let f=[];if(i>0){f[i-1]=1;for(let g=i-2;g>=0;--g)f[g]=f[g+1]*l[g+1]}let m=w.getArrayFromDType(n,o*i);for(let g=0;g<o;++g){let A=0;for(let y=0;y<h;++y)A+=e[g*h+y]*p[y];for(let y=0;y<i;++y)m[g*i+y]=Math.trunc(A/f[y]),A%=f[y]}return[m,[o,i],l]}function A2(e,t,n,s,r,a=!1,o=0){let i=s.length;if(i!==r.length)throw new Error("segmentIds and indices should have same size.");let l=[t[0],e.length/t[0]],u=l[1],d=i>0?r[i-1]+1:0;if(d<0)throw new Error("segment ids must be >= 0");let h=t.slice();h[0]=d;let p=h.reduce((x,b)=>x*b,1),f=w.getArrayFromDType(n,p);if(i===0)return d>0&&f.fill(o),[f,h];if(d<=0)throw new Error("segment ids must be >= 0");let m=0,g=1,A=0,y=r[m];for(;;){let x=0;if(g<i){if(x=r[g],y===x){++g;continue}if(y>=x)throw new Error("segment ids are not increasing")}if(y<0||y>=d)throw new Error(`Segment id ${y} out of range [0, ${d}), possibly because segmentIds input is not sorted.`);y>A&&f.fill(o,A*u,y*u);for(let b=m;b<g;++b){let v=s[b];if(v<0||v>=l[0])throw new Error(`Bad: indices[${b}] == ${s[b]} out of range [0, ${l[0]})`);for(let k=0;k<u;k++)f[y*u+k]+=e[v*u+k]}if(a)for(let b=0;b<u;b++)f[y*u+b]/=g-m;if(m=g,++g,A=y+1,y=x,g>i)break}return A<d&&f.fill(o,A*u,d*u),[f,h]}var LW=da(e=>Math.sqrt(e)),BW=ot(go,e=>Math.sqrt(e)),WW={kernelName:go,backendName:"cpu",kernelFunc:BW},fw=Lt((e,t)=>{let n=e-t;return n*n}),VW=tn(xo,fw),UW={kernelName:xo,backendName:"cpu",kernelFunc:VW};function mw(e,t,n,s){let r=We(e,t.dtype);for(let a=0;a<r.size;a++){let o=r.indexToLoc(a),i=new Array(o.length);for(let l=0;l<i.length;l++)i[l]=o[l]*n[l]+s[l];r.set(t.get(...i),...o)}return r}var HW=class{constructor(e,t,n,s,r,a){this.separator=w.encodeString(e),this.nGramWidths=t,this.leftPad=w.encodeString(n),this.rightPad=w.encodeString(s),this.padWidth=r,this.preserveShort=a}getPadWidth(e){return Math.min(this.padWidth<0?e-1:this.padWidth,e-1)}getNumNGrams(e,t){let n=this.getPadWidth(t);return Math.max(0,e+2*n-t+1)}createNGrams(e,t,n,s,r,a){for(let o=0;o<r;++o){let i=this.getPadWidth(a),l=Math.max(0,i-o),u=Math.max(0,i-(r-(o+1))),c=a-(l+u),d=t+(l>0?0:o-i),h=0;h+=l*this.leftPad.length;for(let A=0;A<c;++A)h+=e[d+A].length;h+=u*this.rightPad.length,h+=(l+u+c-1)*this.separator.length,n[s+o]=new Uint8Array(h);let f=n[s+o],m=0,g=A=>A.forEach(y=>f[m++]=y);for(let A=0;A<l;++A)g(this.leftPad),g(this.separator);for(let A=0;A<c-1;++A)g(e[d+A]),g(this.separator);if(c>0){g(e[d+c-1]);for(let A=0;A<u;++A)g(this.separator),g(this.rightPad)}else{for(let A=0;A<u-1;++A)g(this.rightPad),g(this.separator);g(this.rightPad)}}}compute(e,t){let n=e.length,s=t.length;if(s>0){let i=t[0];if(i!==0)throw new Error(`First split value must be 0, got ${i}`);for(let l=1;l<s;++l){let u=t[l]>=i;if(u=u&&t[l]<=n,!u)throw new Error(`Invalid split value ${t[l]}, must be in [${i}, ${n}]`);i=t[l]}if(i!==n)throw new Error(`Last split value must be data size. Expected ${n}, got ${i}`)}let r=s-1,a=w.getArrayFromDType("int32",s);if(n===0||s===0){let i=new Array(n);for(let l=0;l<=r;++l)a[l]=0;return[i,a]}a[0]=0;for(let i=1;i<=r;++i){let l=t[i]-t[i-1],u=0;this.nGramWidths.forEach(c=>{u+=this.getNumNGrams(l,c)}),this.preserveShort&&l>0&&u===0&&(u=1),a[i]=a[i-1]+u}let o=new Array(a[r]);for(let i=0;i<r;++i){let l=t[i],u=a[i];if(this.nGramWidths.forEach(c=>{let d=t[i+1]-t[i],h=this.getNumNGrams(d,c);this.createNGrams(e,l,o,u,h,c),u+=h}),this.preserveShort&&u===a[i]){let c=t[i+1]-t[i];if(c===0)continue;let d=c+2*this.padWidth,h=1;this.createNGrams(e,l,o,u,h,d)}}return[o,a]}};function gw(e,t,n,s,r,a,o,i){return new HW(n,s,r,a,o,i).compute(e,t)}function GW(e,t,n,s){if(!e.length)return;if(t.length===0){for(let a=0;a<e.length;++a)s.push(e.subarray(a,a+1));return}if(t.length===1){let a=t[0],o=e.indexOf(a);for(;o!==-1;){let i=e.subarray(0,o);(!n||i.length!==0)&&s.push(i),e=e.subarray(o+1),o=e.indexOf(a)}(!n||e.length!==0)&&s.push(e);return}let r=0;for(let a=0;a<e.length+1;a++)if(a===e.length||t.indexOf(e[a])!==-1){let o=e.subarray(r,a);(!n||o.length!==0)&&s.push(o),r=a+1}}function Aw(e,t,n){let s=e.length,r=[],a=0,o=0,i=new Array(s);for(let h=0;h<s;++h){let p=r.length;GW(e[h],t,n,r);let f=r.length-p;i[h]=f,a+=f,o=Math.max(o,f)}let l=w.getArrayFromDType("int32",a*2),u=new Array(a),c=[s,o],d=0;for(let h=0;h<s;++h)for(let p=0;p<i[h];++p)l[d*2]=h,l[d*2+1]=p,u[d]=r[d],++d;return[l,u,c]}function yw(e,t){let n=w.getArrayFromDType("int32",e.length);for(let s=0;s<e.length;++s)n[s]=w.fingerPrint64(e[s]).modulo(t).getLowBitsUnsigned();return n}var xw=Lt((e,t)=>e-t),jW=d2((e,t,n,s)=>({real:e-n,imag:t-s})),y2=tn(bo,xw,jW),qW={kernelName:bo,backendName:"cpu",kernelFunc:y2};function bw(e,t){let n=new Array(e.rank);for(let r=0;r<n.length;r++)n[r]=e.shape[r]*t[r];let s=We(n,e.dtype);for(let r=0;r<s.values.length;++r){let a=s.indexToLoc(r),o=new Array(e.rank);for(let l=0;l<o.length;l++)o[l]=a[l]%e.shape[l];let i=e.locToIndex(o);s.values[r]=e.values[i]}return s}var Vc=(e,t)=>{let n=t.value-e.value;return n===0?e.index-t.index:n};function vw(e,t,n=0,s=e.length-1){for(;s>n;){if(s-n>600){let i=s-n+1,l=t-n+1,u=Math.log(i),c=.5*Math.exp(2*u/3),d=.5*Math.sqrt(u*c*(i-c)/i)*Math.sign(l-i/2),h=Math.max(n,Math.floor(t-l*c/i+d)),p=Math.min(s,Math.floor(t+(i-l)*c/i+d));vw(e,t,h,p)}let r=e[t],a=n,o=s;for(w.swap(e,n,t),Vc(e[s],r)>0&&w.swap(e,n,s);a<o;){for(w.swap(e,a,o),a++,o--;Vc(e[a],r)<0;)a=a+1;for(;Vc(e[o],r)>0;)o=o-1}Vc(e[n],r)===0?w.swap(e,n,o):(o=o+1,w.swap(e,o,s)),o<=t&&(n=o+1),t<=o&&(s=o-1)}}function ww(e,t,n,s,r){let a=t[t.length-1],[o,i]=[e.length/a,a],l=w.getTypedArrayFromDType(n,o*s),u=w.getTypedArrayFromDType("int32",o*s);for(let d=0;d<o;d++){let h=d*i,p=e.subarray(h,h+i),f=new Array(p.length);p.forEach((y,x)=>f[x]={value:y,index:x}),s<f.length&&(vw(f,s),f=f.slice(0,s)),r&&f.sort(Vc);let m=d*s,g=l.subarray(m,m+s),A=u.subarray(m,m+s);for(let y=0;y<s;y++)g[y]=f[y].value,A[y]=f[y].index}let c=t.slice();return c[c.length-1]=s,[We(c,n,l),We(c,"int32",u)]}function kw(e,t,n,s){let r=w.parseAxisParam(t,n)[0],a=[1,n[0],1];for(let f=0;f<r;f++)a[0]*=n[f];a[1]=n[r];for(let f=r+1;f<n.length;f++)a[2]*=n[f];let o={},i=new Int32Array(n[r]),l=new Ut(a,s,e),u=[],c=a[0]===1&&a[2]===1;for(let f=0;f<n[r];f++){let m;if(c)m=e[f].toString();else{let g=[];for(let A=0;A<a[0];A++)for(let y=0;y<a[2];y++)g.push(l.get(A,f,y));m=g.join(",")}if(o[m]!==void 0)i[f]=o[m];else{let g=Object.keys(o).length;o[m]=g,i[f]=g,u.push(f)}}let d=a.slice();d[1]=Object.keys(o).length;let h=new Ut(d,s);u.forEach((f,m)=>{for(let g=0;g<a[0];g++)for(let A=0;A<a[2];A++)h.set(l.get(g,f,A),g,m,A)});let p=n.slice();return p[r]=d[1],{outputValues:h.values,outputShape:p,indices:i}}var XW="3.9.0";_l("cpu",()=>new af,1);var Iw=ot(Ba,e=>e>=0?e:Math.exp(e)-1),KW={kernelName:Ba,backendName:"cpu",kernelFunc:Iw};function Sw(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{alpha:a}=s;ke([r],"leakyRelu");let o=w.sizeFromShape(r.shape),i=n.data.get(r.dataId).values,l=w.getTypedArrayFromDType("float32",o);for(let u=0;u<i.length;u++)l[u]=i[u]<0?a*i[u]:i[u];return n.makeTensorInfo(r.shape,"float32",l)}var ZW={kernelName:qa,backendName:"cpu",kernelFunc:Sw},YW=Lt((e,t)=>e<0?t*e:e);function Cw(e){let{inputs:t,backend:n}=e,{x:s,alpha:r}=t;ke([s,r],"prelu");let a=n.data.get(s.dataId).values,o=n.data.get(r.dataId).values,[i,l]=YW(s.shape,r.shape,a,o,s.dtype);return n.makeTensorInfo(l,s.dtype,i)}var JW={kernelName:oo,backendName:"cpu",kernelFunc:Cw},Tw=ot(io,e=>Math.max(0,e)),QW={kernelName:io,backendName:"cpu",kernelFunc:Tw},Nw=ot(uo,e=>Math.min(Math.max(0,e),6)),eV={kernelName:uo,backendName:"cpu",kernelFunc:Nw};function x2(e,t,n,s,r){if(n==="linear")return cr({inputs:{x:t},backend:e});if(n==="relu")return Tw({inputs:{x:t},backend:e});if(n==="elu")return Iw({inputs:{x:t},backend:e});if(n==="relu6")return Nw({inputs:{x:t},backend:e});if(n==="prelu")return Cw({inputs:{x:t,alpha:s},backend:e});if(n==="leakyrelu")return Sw({inputs:{x:t},backend:e,attrs:{alpha:r}});if(n==="sigmoid")return dw({inputs:{x:t},backend:e});throw new Error(`Activation ${n} has not been implemented for the CPU backend.`)}function xt(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{shape:a}=s,o=w.sizeFromShape(r.shape),i=w.inferFromImplicitShape(a,o),l=w.sizeFromShape(i);w.assert(o===l,()=>`The new shape (${i}) has ${l} elements and the old shape (${r.shape}) has ${o} elements. The new shape and old shape must have the same number of elements.`),n.incRef(r.dataId);let u=n.data.get(r.dataId);if(u.complexTensorInfos!=null){let c=u.complexTensorInfos.real,d=u.complexTensorInfos.imag;c.shape=i,d.shape=i}return{dataId:r.dataId,shape:i,dtype:r.dtype}}var tV={kernelName:ll,backendName:"cpu",kernelFunc:xt};function Ew(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a}=t,{transposeA:o,transposeB:i}=s;ke([r,a],"matMul");let l=r.shape.length,u=a.shape.length,c=o?r.shape[l-2]:r.shape[l-1],d=i?a.shape[u-1]:a.shape[u-2],h=o?r.shape[l-1]:r.shape[l-2],p=i?a.shape[u-2]:a.shape[u-1],f=r.shape.slice(0,-2),m=a.shape.slice(0,-2),g=w.sizeFromShape(f),A=w.sizeFromShape(m),y=g===A||g===1||A===1;w.assert(l>=2&&u>=2&&y,()=>`Error in matMul: the input batch dimensions must either be the same or at least one input batch dimension must be 1. Got input batch dimensions of (${f}) and (${m}).`);let b=(g>A?r.shape.slice(0,-2):a.shape.slice(0,-2)).concat([h,p]);w.assert(c===d,()=>`Error in matMul: inner shapes (${c}) and (${d}) of Tensors with shapes ${r.shape} and ${a.shape} and transposeA=${o} and transposeB=${i} must match.`);let v=o?[g,c,h]:[g,h,c],k=i?[A,p,d]:[A,d,p],S=xt({inputs:{x:r},backend:n,attrs:{shape:v}}),C=xt({inputs:{x:a},backend:n,attrs:{shape:k}}),_=o?S.shape[1]:S.shape[2],O=o?S.shape[2]:S.shape[1],E=i?C.shape[1]:C.shape[2],R=Math.max(g,A),T=n.data.get(S.dataId).values,P=n.data.get(C.dataId).values,V=w.computeStrides(S.shape),j=w.computeStrides(C.shape),[q,X,ee]=o?[V[0],1,V[1]]:[V[0],V[1],1],[te,ne,se]=i?[1,j[1],j[0]]:[j[1],1,j[0]],J=O*E,ie=We([R,O,E],S.dtype),le=ie.values,he=n.blockSize;for(let Ae=0;Ae<R;Ae++)for(let Ce=0;Ce<O;Ce+=he)for(let Te=0;Te<E;Te+=he)for(let De=0;De<_;De+=he){let Me=Math.min(Ce+he,O),Fe=Math.min(Te+he,E),ut=Math.min(De+he,_);for(let nt=Ce;nt<Me;nt++)for(let st=Te;st<Fe;st++){let et=0;for(let it=De;it<ut;it++){let He=Math.min(Ae,g-1)*q,Nn=Math.min(Ae,A-1)*se,St=T[He+nt*X+it*ee],Wn=P[it*te+st*ne+Nn];et+=St*Wn}le[Ae*J+(nt*E+st)]+=et}}return n.disposeIntermediateTensorInfo(S),n.disposeIntermediateTensorInfo(C),n.makeTensorInfo(b,ie.dtype,ie.values)}var nV={kernelName:Ra,backendName:"cpu",kernelFunc:Ew};function sV(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a,bias:o,preluActivationWeights:i}=t,{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:d}=s,h,p,f,m=[];h=Ew({inputs:{a:r,b:a},attrs:{transposeA:l,transposeB:u},backend:n}),o&&(p=Wc({inputs:{a:h,b:o},backend:n}),m.push(h),h=p),c&&(f=x2(n,h,c,i,d),m.push(h),h=f);for(let A of m)n.disposeIntermediateTensorInfo(A);return h}var rV={kernelName:Io,backendName:"cpu",kernelFunc:sV},aV=ot(Ii,e=>Math.acos(e)),oV={kernelName:Ii,backendName:"cpu",kernelFunc:aV},iV=ot(Si,e=>Math.acosh(e)),lV={kernelName:Si,backendName:"cpu",kernelFunc:iV};function uV(e){let{inputs:t,backend:n}=e,s=t;ke(t,"addN");let r=s.map(i=>n.data.get(i.dataId).values),a=We(s[0].shape,s[0].dtype),o=a.values;for(let i=0;i<s.length;i++){let l=r[i];for(let u=0;u<o.length;u++)o[u]+=l[u]}return n.makeTensorInfo(a.shape,a.dtype,a.values)}var cV={kernelName:Ta,backendName:"cpu",kernelFunc:uV};function dV(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;ke(r,"all");let i=w.parseAxisParam(a,r.shape),l=i,u=D.getAxesPermutation(l,r.shape.length),c=r;u!=null&&(c=As({inputs:{x:r},backend:n,attrs:{perm:u}}),l=D.getInnerMostAxes(l.length,r.shape.length)),D.assertAxesAreInnerMostDims("all",l,c.shape.length);let[d,h]=D.computeOutAndReduceShapes(c.shape,l),p=w.sizeFromShape(h),f=w.makeZerosTypedArray(w.sizeFromShape(d),c.dtype),m=n.data.get(c.dataId).values;for(let A=0;A<f.length;++A){let y=A*p,x=m[y];for(let b=0;b<p;++b){let v=m[y+b];x=x&&v}f[A]=x}u!=null&&n.disposeIntermediateTensorInfo(c);let g=n.makeTensorInfo(d,c.dtype,f);if(o){let A=D.expandShapeToKeepDim(d,i),y=xt({inputs:{x:g},backend:n,attrs:{shape:A}});return n.disposeIntermediateTensorInfo(g),y}return g}var hV={kernelName:Ci,backendName:"cpu",kernelFunc:dV};function pV(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;ke(r,"any");let i=w.parseAxisParam(a,r.shape),l=i,u=D.getAxesPermutation(l,r.shape.length),c=r;u!=null&&(c=As({inputs:{x:r},backend:n,attrs:{perm:u}}),l=D.getInnerMostAxes(l.length,r.shape.length)),D.assertAxesAreInnerMostDims("any",l,c.shape.length);let[d,h]=D.computeOutAndReduceShapes(c.shape,l),p=w.sizeFromShape(h),f=w.makeZerosTypedArray(w.sizeFromShape(d),c.dtype),m=n.data.get(c.dataId).values;for(let A=0;A<f.length;++A){let y=A*p,x=m[y];for(let b=0;b<p;++b){let v=m[y+b];x=x||v}f[A]=x}u!=null&&n.disposeIntermediateTensorInfo(c);let g=n.makeTensorInfo(d,c.dtype,f);if(o){let A=D.expandShapeToKeepDim(d,i),y=xt({inputs:{x:g},backend:n,attrs:{shape:A}});return n.disposeIntermediateTensorInfo(g),y}return g}var fV={kernelName:Ti,backendName:"cpu",kernelFunc:pV};function mV(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a}=s;ke(r,"argMax");let o=w.parseAxisParam(a,r.shape),i=D.getAxesPermutation(o,r.shape.length),l=r,u=[];i!=null&&(l=As({inputs:{x:r},backend:n,attrs:{perm:i}}),u.push(l),o=D.getInnerMostAxes(o.length,l.shape.length)),o=[o[0]],D.assertAxesAreInnerMostDims("argMax",o,l.shape.length);let[c,d]=D.computeOutAndReduceShapes(l.shape,o),h=w.sizeFromShape(c),p=w.makeZerosTypedArray(h,"int32"),f=w.sizeFromShape(d),m=n.data.get(l.dataId).values;for(let g=0;g<p.length;++g){let A=g*f,y=m[A],x=0;for(let b=0;b<f;++b){let v=m[A+b];v>y&&(y=v,x=b)}p[g]=x}return u.forEach(g=>n.disposeIntermediateTensorInfo(g)),n.makeTensorInfo(c,"int32",p)}var gV={kernelName:Na,backendName:"cpu",kernelFunc:mV};function AV(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a}=s;ke(r,"argMin");let o=w.parseAxisParam(a,r.shape),i=D.getAxesPermutation(o,r.shape.length),l=r,u=[];i!=null&&(l=As({inputs:{x:r},backend:n,attrs:{perm:i}}),u.push(l),o=D.getInnerMostAxes(o.length,l.shape.length)),o=[o[0]],D.assertAxesAreInnerMostDims("argMin",o,l.shape.length);let[c,d]=D.computeOutAndReduceShapes(l.shape,o),h=w.sizeFromShape(c),p=w.makeZerosTypedArray(h,"int32"),f=w.sizeFromShape(d),m=n.data.get(l.dataId).values;for(let g=0;g<p.length;++g){let A=g*f,y=m[A],x=0;for(let b=0;b<f;++b){let v=m[A+b];v<y&&(y=v,x=b)}p[g]=x}return u.forEach(g=>n.disposeIntermediateTensorInfo(g)),n.makeTensorInfo(c,"int32",p)}var yV={kernelName:Ou,backendName:"cpu",kernelFunc:AV},xV=ot(Ni,e=>Math.asin(e)),bV={kernelName:Ni,backendName:"cpu",kernelFunc:xV},vV=ot(Ei,e=>Math.asinh(e)),wV={kernelName:Ei,backendName:"cpu",kernelFunc:vV},kV=ot(Ri,e=>Math.atan(e)),IV={kernelName:Ri,backendName:"cpu",kernelFunc:kV},SV=Lt((e,t)=>Math.atan2(e,t)),CV=tn(Di,SV),TV={kernelName:Di,backendName:"cpu",kernelFunc:CV},NV=ot(_i,e=>Math.atanh(e)),EV={kernelName:_i,backendName:"cpu",kernelFunc:NV};function b2(e,t,n,s,r,a){let o=r.strideHeight,i=r.strideWidth,l=r.dilationHeight,u=r.dilationWidth,c=r.effectiveFilterHeight,d=r.effectiveFilterWidth,h=r.padInfo.top,p=r.padInfo.left,f=a==="max"?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,m=We(r.outShape,n),g=m.values,A=r.outShape[1]*r.outShape[2]*r.outShape[3],y=r.outShape[2]*r.outShape[3],x=r.outShape[3];for(let b=0;b<r.batchSize;++b){let v=b*A,k=b*s[0];for(let S=0;S<r.inChannels;++S)for(let C=0;C<r.outHeight;++C){let _=C*o-h,O=Math.max(0,_),E=Math.min(r.inHeight,c+_),R=v+C*y;for(let T=0;T<r.outWidth;++T){let P=T*i-p,V=Math.max(0,P),j=Math.min(r.inWidth,d+P),q=f,X=0,ee=0;for(let ne=O;ne<E;ne+=l){let se=k+ne*s[1];for(let J=V;J<j;J+=u){let ie=se+J*s[2],le=e[ie+S];a==="max"&&le>q?q=le:a==="avg"&&(X+=le,ee++)}if(isNaN(q))break}let te=R+T*x+S;g[te]=a==="avg"?X/ee:q}}}return m}function Rw(e,t,n,s,r=!1,a=!1){let o=We(s.outShape,"int32"),i=s.strideHeight,l=s.strideWidth,u=s.dilationHeight,c=s.dilationWidth,d=s.effectiveFilterHeight,h=s.effectiveFilterWidth,p=s.padInfo.top,f=s.padInfo.left,m=We(t,n,e);for(let g=0;g<s.batchSize;++g)for(let A=0;A<s.inChannels;++A)for(let y=0;y<s.outHeight;++y){let x=y*i-p,b=x;for(;b<0;)b+=u;let v=Math.min(s.inHeight,d+x);for(let k=0;k<s.outWidth;++k){let S=k*l-f,C=S;for(;C<0;)C+=c;let _=Math.min(s.inWidth,h+S),O=Number.NEGATIVE_INFINITY,E=-1;for(let R=b;R<v;R+=u){let T=R-x;for(let P=C;P<_;P+=c){let V=P-S,j=m.get(g,R,P,A);j>O&&(O=j,r?E=a?((g*s.inHeight+R)*s.inWidth+P)*s.inChannels+A:(R*s.inWidth+P)*s.inChannels+A:E=T*h+V)}}o.set(E,g,y,k,A)}}return o}function _w(e,t,n,s,r,a){let o=r.strideDepth,i=r.strideHeight,l=r.strideWidth,u=r.dilationDepth,c=r.dilationHeight,d=r.dilationWidth,h=r.effectiveFilterDepth,p=r.effectiveFilterHeight,f=r.effectiveFilterWidth,m=r.padInfo.front,g=r.padInfo.top,A=r.padInfo.left,y=a==="max"?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,x=We(r.outShape,n),b=x.values,v=r.outShape[1]*r.outShape[2]*r.outShape[3]*r.outShape[4],k=r.outShape[2]*r.outShape[3]*r.outShape[4],S=r.outShape[3]*r.outShape[4],C=r.outShape[4];for(let _=0;_<r.batchSize;++_){let O=_*v,E=_*s[0];for(let R=0;R<r.inChannels;++R)for(let T=0;T<r.outDepth;++T){let P=T*o-m,V=P;for(;V<0;)V+=u;let j=Math.min(r.inDepth,h+P),q=O+T*k;for(let X=0;X<r.outHeight;++X){let ee=X*i-g,te=ee;for(;te<0;)te+=c;let ne=Math.min(r.inHeight,p+ee),se=q+X*S;for(let J=0;J<r.outWidth;++J){let ie=J*l-A,le=ie;for(;le<0;)le+=d;let he=Math.min(r.inWidth,f+ie),Ae=se+J*C,Ce=y,Te=0,De=0;for(let Fe=V;Fe<j;Fe+=u){let ut=E+Fe*s[1];for(let nt=te;nt<ne;nt+=c){let st=ut+nt*s[2];for(let et=le;et<he;et+=d){let it=st+et*s[3],He=e[it+R];if(a==="max"&&He>Ce?Ce=He:a==="avg"&&(Te+=He,De++),isNaN(Ce))break}if(isNaN(Ce))break}if(isNaN(Ce))break}let Me=Ae+R;b[Me]=a==="avg"?Te/De:Ce}}}}return x}function RV(e,t){let n=We(t.outShape,"int32"),s=t.strideDepth,r=t.strideHeight,a=t.strideWidth,o=t.dilationDepth,i=t.dilationHeight,l=t.dilationWidth,u=t.effectiveFilterDepth,c=t.effectiveFilterHeight,d=t.effectiveFilterWidth,h=t.padInfo.front,p=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 A=0;A<t.outDepth;++A){let y=A*s-h,x=y;for(;x<0;)x+=o;let b=Math.min(t.inDepth,u+y);for(let v=0;v<t.outHeight;++v){let k=v*r-p,S=k;for(;S<0;)S+=i;let C=Math.min(t.inHeight,c+k);for(let _=0;_<t.outWidth;++_){let O=_*a-f,E=O;for(;E<0;)E+=l;let R=Math.min(t.inWidth,d+O),T=Number.NEGATIVE_INFINITY,P=-1;for(let V=x;V<b;V+=o){let j=V-y;for(let q=S;q<C;q+=i){let X=q-k;for(let ee=E;ee<R;ee+=l){let te=ee-O,ne=e.get(m,V,q,ee,g);ne>=T&&(T=ne,P=j*c*d+X*c+te)}}}n.set(P,m,A,v,_,g)}}}return n}function _V(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t;ke(r,"avgPool");let{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=s,u=1;w.assert(D.eitherStridesOrDilationsAreOne(o,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${o} and dilations '${u}'`);let c=D.computePool2DInfo(r.shape,a,o,u,i,l),d;if(c.filterWidth===1&&c.filterHeight===1&&w.arraysEqual(c.inShape,c.outShape))d=cr({inputs:{x:r},backend:n});else{let h=n.data.get(r.dataId).values,p=w.computeStrides(r.shape),f=b2(h,r.shape,r.dtype,p,c,"avg");d=n.makeTensorInfo(c.outShape,r.dtype,f.values)}return d}var DV={kernelName:Ea,backendName:"cpu",kernelFunc:_V};function $V(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{filterSize:a,strides:o,pad:i,dimRoundingMode:l,dataFormat:u}=s;ke(r,"avgPool3d");let c=D.computePool3DInfo(r.shape,a,o,1,i,l,u),d=n.data.get(r.dataId).values,h=_w(d,r.shape,r.dtype,w.computeStrides(r.shape),c,"avg");return n.makeTensorInfo(h.shape,"float32",h.values)}var FV={kernelName:Pu,backendName:"cpu",kernelFunc:$V};function OV(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a}=t,{filterSize:o,strides:i,pad:l,dimRoundingMode:u}=s;ke([r,a],"avgPool3DGrad");let c=D.computePool3DInfo(a.shape,o,i,1,l,u),d=c.strideDepth,h=c.strideHeight,p=c.strideWidth,f=c.filterDepth,m=c.filterHeight,g=c.filterWidth,A=c.dilationDepth,y=c.dilationHeight,x=c.dilationWidth,b=c.effectiveFilterDepth,v=c.effectiveFilterHeight,k=c.effectiveFilterWidth,S=b-1-c.padInfo.front,C=k-1-c.padInfo.left,_=v-1-c.padInfo.top,O=We(a.shape,"float32"),E=1/(f*m*g),R=n.bufferSync(r);for(let T=0;T<c.batchSize;++T)for(let P=0;P<c.inChannels;++P)for(let V=0;V<c.inDepth;++V)for(let j=0;j<c.inHeight;++j)for(let q=0;q<c.inWidth;++q){let X=V-S,ee=j-_,te=q-C,ne=0;for(let se=0;se<b;se+=A){let J=(X+se)/d;if(!(J<0||J>=c.outDepth||Math.floor(J)!==J))for(let ie=0;ie<v;ie+=y){let le=(ee+ie)/h;if(!(le<0||le>=c.outHeight||Math.floor(le)!==le))for(let he=0;he<k;he+=x){let Ae=(te+he)/p;if(Ae<0||Ae>=c.outWidth||Math.floor(Ae)!==Ae)continue;ne+=R.get(T,J,le,Ae,P)}}}O.set(ne*E,T,V,j,q,P)}return n.makeTensorInfo(O.shape,O.dtype,O.values)}var PV={kernelName:Kd,backendName:"cpu",kernelFunc:OV};function MV(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a}=t,o=a;ke([r,a],"avgPoolGrad");let{filterSize:i,strides:l,pad:u}=s,c=D.computePool2DInfo(o.shape,i,l,1,u),d=c.strideHeight,h=c.strideWidth,p=c.filterHeight,f=c.filterWidth,m=c.dilationHeight,g=c.dilationWidth,A=c.effectiveFilterHeight,y=c.effectiveFilterWidth,x=y-1-c.padInfo.left,b=A-1-c.padInfo.top,v=We(o.shape,"float32"),k=1/(p*f),S=n.data.get(r.dataId).values,C=We(r.shape,"float32",S);for(let _=0;_<c.batchSize;++_)for(let O=0;O<c.inChannels;++O)for(let E=0;E<c.inHeight;++E)for(let R=0;R<c.inWidth;++R){let T=E-b,P=R-x,V=0;for(let j=0;j<A;j+=m){let q=(T+j)/d;if(!(q<0||q>=c.outHeight||Math.floor(q)!==q))for(let X=0;X<y;X+=g){let ee=(P+X)/h;if(ee<0||ee>=c.outWidth||Math.floor(ee)!==ee)continue;V+=C.get(_,q,ee,O)}}v.set(V*k,_,E,R,O)}return n.makeTensorInfo(v.shape,v.dtype,v.values)}var zV={kernelName:Xd,backendName:"cpu",kernelFunc:MV};function LV(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,scale:a,offset:o,mean:i,variance:l}=t;w.assert(i.shape.length===l.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),w.assert(o==null||i.shape.length===o.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),w.assert(a==null||i.shape.length===a.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks."),ke([r,i,l,a,o],"batchNorm");let{varianceEpsilon:u}=s;u==null&&(u=.001);let c=n.data.get(r.dataId).values,d=n.data.get(i.dataId).values,h=n.data.get(l.dataId).values,p=a?n.data.get(a.dataId).values:new Float32Array([1]),f=o?n.data.get(o.dataId).values:new Float32Array([0]),m=new Float32Array(c.length),g=f.length,A=p.length,y=h.length,x=d.length,b=0,v=0,k=0,S=0;for(let C=0;C<c.length;++C)m[C]=f[b++]+(c[C]-d[v++])*p[k++]/Math.sqrt(h[S++]+u),b>=g&&(b=0),v>=x&&(v=0),k>=A&&(k=0),S>=y&&(S=0);return n.makeTensorInfo(r.shape,r.dtype,m)}var BV={kernelName:Ha,backendName:"cpu",kernelFunc:LV};function WV(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockShape:a,crops:o}=s;ke([r],"batchToSpaceND");let i=a.reduce((A,y)=>A*y),l=D.getReshaped(r.shape,a,i),u=D.getPermuted(l.length,a.length),c=D.getReshapedPermuted(r.shape,a,i),d=D.getSliceBeginCoords(o,a.length),h=D.getSliceSize(c,o,a.length),p=xt({inputs:{x:r},backend:n,attrs:{shape:l}}),f=As({inputs:{x:p},backend:n,attrs:{perm:u}}),m=xt({inputs:{x:f},backend:n,attrs:{shape:c}}),g=Zo({inputs:{x:m},backend:n,attrs:{begin:d,size:h}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(m),g}var VV={kernelName:$i,backendName:"cpu",kernelFunc:WV};function UV(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,weights:a}=t,{size:o}=s,i=n.data.get(r.dataId).values,l=n.data.get(a.dataId).values,u=h2(i,l,a.dtype,a.shape,o);return n.makeTensorInfo([o],a.dtype,u)}var HV={kernelName:Zd,backendName:"cpu",kernelFunc:UV};function GV(e){let{inputs:t,backend:n}=e,{s0:s,s1:r}=t,a=n.data.get(s.dataId).values,o=n.data.get(r.dataId).values,i=D.assertAndGetBroadcastShape(Array.from(a),Array.from(o));return n.makeTensorInfo([i.length],"int32",Int32Array.from(i))}var jV={kernelName:Bm,backendName:"cpu",kernelFunc:GV},qV=ot(Ur,(e,t)=>{let n=t;return e>n.clipValueMax?n.clipValueMax:e<n.clipValueMin?n.clipValueMin:e}),XV={kernelName:Ur,backendName:"cpu",kernelFunc:qV},KV=e=>{let{x:t}=e.inputs,n=e.backend,s=new Float32Array(w.sizeFromShape(t.shape)),r=n.data.get(t.dataId),a=r.complexTensorInfos.real,o=r.complexTensorInfos.imag,i=n.data.get(a.dataId).values,l=n.data.get(o.dataId).values;for(let u=0;u<i.length;u++){let c=i[u],d=l[u];s[u]=Math.hypot(c,d)}return n.makeOutput(s,t.shape,"float32")},ZV={kernelName:Mu,backendName:"cpu",kernelFunc:KV};function Ql(e){let{inputs:t,backend:n}=e,{input:s}=t,r=n.data.get(s.dataId).complexTensorInfos.imag,a=n.data.get(r.dataId).values;return n.makeTensorInfo(r.shape,r.dtype,a)}var YV={kernelName:dh,backendName:"cpu",kernelFunc:Ql};function eu(e){let{inputs:t,backend:n,attrs:s}=e,{axis:r}=s,a=w.parseAxisParam(r,t[0].shape)[0],o=D.computeOutShape(t.map(m=>m.shape),a);if(w.sizeFromShape(o)===0)return n.makeTensorInfo(o,t[0].dtype,[]);let i=t.filter(m=>w.sizeFromShape(m.shape)>0);if(i.length===1)return cr({inputs:{x:i[0]},backend:n});let l=i.map(m=>m.shape);if(D.assertParamsConsistent(l,a),i[0].dtype==="complex64"){let m=i.map(b=>Ko({inputs:{input:b},backend:n})),g=i.map(b=>Ql({inputs:{input:b},backend:n})),A=eu({inputs:m,backend:n,attrs:{axis:a}}),y=eu({inputs:g,backend:n,attrs:{axis:a}}),x=Zn({inputs:{real:A,imag:y},backend:n});return m.forEach(b=>n.disposeIntermediateTensorInfo(b)),g.forEach(b=>n.disposeIntermediateTensorInfo(b)),n.disposeIntermediateTensorInfo(A),n.disposeIntermediateTensorInfo(y),x}let u=i.map(m=>{let g=w.sizeFromShape(m.shape.slice(a));return xt({inputs:{x:m},backend:n,attrs:{shape:[-1,g]}})}),c=u.map(m=>({vals:n.data.get(m.dataId).values,shape:m.shape}));o=D.computeOutShape(u.map(m=>m.shape),1);let d=u[0].shape[0]===1,h=p2(c,o,t[0].dtype,d),p=D.computeOutShape(i.map(m=>m.shape),a),f=n.makeTensorInfo(p,t[0].dtype,h);return u.forEach(m=>n.disposeIntermediateTensorInfo(m)),f}var JV={kernelName:Fi,backendName:"cpu",kernelFunc:eu};function Dw(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dataFormat:l,dilations:u,dimRoundingMode:c}=s;ke([r,a],"conv2d");let d=D.convertConv2DDataFormat(l),h=D.computeConv2DInfo(r.shape,a.shape,o,u,i,c,!1,d),p=h.filterHeight,f=h.filterWidth,m=h.dilationHeight,g=h.dilationWidth,A=h.padInfo.left,y=h.padInfo.top,x=h.dataFormat==="channelsLast",b=new Ut(h.outShape,r.dtype),v=w.computeStrides(r.shape),k=w.computeStrides(a.shape),S=v[0],C=x?v[1]:v[2],_=x?v[2]:1,O=x?1:v[1],E=b.strides[0],R=x?b.strides[1]:b.strides[2],T=x?b.strides[2]:1,P=x?1:b.strides[1],V=n.data.get(r.dataId).values,j=n.data.get(a.dataId).values,q=b.values;for(let X=0;X<h.batchSize;++X){let ee=X*S,te=X*E;for(let ne=0;ne<h.outHeight;++ne){let se=te+ne*R,J=ne*h.strideHeight-y;for(let ie=0;ie<p;++ie){let le=J+ie*m;if(le<0||le>=h.inHeight)continue;let he=ie*k[0],Ae=ee+le*C;for(let Ce=0;Ce<h.outWidth;++Ce){let Te=se+Ce*T,De=Ce*h.strideWidth-A;for(let Me=0;Me<f;++Me){let Fe=De+Me*g;if(Fe<0||Fe>=h.inWidth)continue;let ut=he+Me*k[1],nt=Ae+Fe*_,st=ut;for(let et=0;et<h.inChannels;++et){let it=V[nt+et*O];for(let He=0;He<h.outChannels;++He)q[Te+He*P]+=it*j[st+He];st+=h.outChannels}}}}}}return n.makeTensorInfo(b.shape,b.dtype,q)}var QV={kernelName:$a,backendName:"cpu",kernelFunc:Dw};function eU(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,dy:a}=t,{strides:o,pad:i,dataFormat:l,dimRoundingMode:u,filterShape:c}=s;ke([r,a],"conv2dBackpropFilter");let d=D.convertConv2DDataFormat(l),h=D.computeConv2DInfo(r.shape,c,o,1,i,u,!1,d),{strideHeight:p,strideWidth:f,filterHeight:m,filterWidth:g}=h,A=h.dataFormat==="channelsLast",y=new Ut(h.filterShape,"float32"),x=h.padInfo.left,b=h.padInfo.top,v=n.data.get(r.dataId).values,k=n.data.get(a.dataId).values,S=new Ut(r.shape,r.dtype,v),C=new Ut(a.shape,a.dtype,k);for(let _=0;_<m;++_){let O=Math.max(0,Math.ceil((b-_)/p)),E=Math.min(h.outHeight,(h.inHeight+b-_)/p);for(let R=0;R<g;++R){let T=Math.max(0,Math.ceil((x-R)/f)),P=Math.min(h.outWidth,(h.inWidth+x-R)/f);for(let V=0;V<h.inChannels;++V)for(let j=0;j<h.outChannels;++j){let q=0;for(let X=0;X<h.batchSize;++X)for(let ee=O;ee<E;++ee){let te=_+ee*p-b;for(let ne=T;ne<P;++ne){let se=R+ne*f-x;A?q+=S.get(X,te,se,V)*C.get(X,ee,ne,j):q+=S.get(X,V,te,se)*C.get(X,j,ee,ne)}}y.set(q,_,R,V,j)}}}return n.makeTensorInfo(y.shape,y.dtype,y.values)}var tU={kernelName:Jd,backendName:"cpu",kernelFunc:eU};function nU(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,filter:a}=t,{inputShape:o,strides:i,pad:l,dataFormat:u,dimRoundingMode:c}=s;ke([r,a],"conv2dBackpropInput");let d=w.computeStrides(a.shape),h=w.computeStrides(r.shape),p=D.convertConv2DDataFormat(u),f=D.computeConv2DInfo(o,a.shape,i,1,l,c,!1,p),m=new Ut(f.inShape,"float32"),g=m.values,A=n.data.get(r.dataId).values,y=n.data.get(a.dataId).values,[x,b,v]=d,{batchSize:k,filterHeight:S,filterWidth:C,inChannels:_,inHeight:O,inWidth:E,outChannels:R,outHeight:T,outWidth:P,strideHeight:V,strideWidth:j}=f;p=f.dataFormat;let q=S-1-f.padInfo.top,X=C-1-f.padInfo.left,ee=p==="channelsLast",te=m.strides[0],ne=ee?m.strides[1]:m.strides[2],se=ee?m.strides[2]:1,J=ee?1:m.strides[1],ie=h[0],le=ee?h[1]:h[2],he=ee?h[2]:1,Ae=ee?1:h[1];for(let Ce=0;Ce<k;++Ce)for(let Te=0;Te<_;++Te)for(let De=0;De<O;++De){let Me=De-q,Fe=Math.max(0,Math.ceil(Me/V)),ut=Math.min(T,(S+Me)/V);for(let nt=0;nt<E;++nt){let st=nt-X,et=Math.max(0,Math.ceil(st/j)),it=Math.min(P,(C+st)/j),He=0;for(let St=Fe;St<ut;++St){let Wn=St*V-Me;for(let nn=et;nn<it;++nn){let ks=nn*j-st,pn=ie*Ce+le*St+he*nn,ts=x*(S-1-Wn)+b*(C-1-ks)+v*Te;for(let ns=0;ns<R;++ns){let sn=A[pn+Ae*ns],ss=y[ts+ns];He+=sn*ss}}}let Nn=te*Ce+ne*De+se*nt+J*Te;g[Nn]=He}}return n.makeTensorInfo(m.shape,m.dtype,m.values)}var sU={kernelName:Fa,backendName:"cpu",kernelFunc:nU};function rU(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dilations:l}=s;ke([r,a],"conv3d");let u=D.computeConv3DInfo(r.shape,a.shape,o,l,i),{filterDepth:c,filterHeight:d,filterWidth:h,dilationDepth:p,dilationHeight:f,dilationWidth:m,padInfo:g}=u,A=g.front,y=g.left,x=g.top,b=new Ut(u.outShape,r.dtype),v=n.data.get(r.dataId).values,k=n.data.get(a.dataId).values,S=b.values,C=w.computeStrides(r.shape),_=w.computeStrides(a.shape);for(let O=0;O<u.batchSize;++O){let E=O*C[0],R=O*b.strides[0];for(let T=0;T<u.outDepth;++T){let P=R+T*b.strides[1],V=T*u.strideDepth-A;for(let j=0;j<c;++j){let q=V+j*p;if(q<0||q>=u.inDepth)continue;let X=j*_[0],ee=E+q*C[1];for(let te=0;te<u.outHeight;++te){let ne=P+te*b.strides[2],se=te*u.strideHeight-x;for(let J=0;J<d;++J){let ie=se+J*f;if(ie<0||ie>=u.inHeight)continue;let le=X+J*_[1],he=ee+ie*C[2];for(let Ae=0;Ae<u.outWidth;++Ae){let Ce=ne+Ae*u.outChannels,Te=Ae*u.strideWidth-y;for(let De=0;De<h;++De){let Me=Te+De*m;if(Me<0||Me>=u.inWidth)continue;let Fe=le+De*_[2],ut=he+Me*u.inChannels,nt=Fe;for(let st=0;st<u.inChannels;++st){let et=v[ut+st];for(let it=0;it<u.outChannels;++it)S[Ce+it]+=et*k[nt+it];nt+=u.outChannels}}}}}}}}return n.makeTensorInfo(b.shape,b.dtype,b.values)}var aU={kernelName:zu,backendName:"cpu",kernelFunc:rU};function oU(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,dy:a}=t,{strides:o,pad:i,filterShape:l}=s;ke([r,a],"conv3dBackpropFilterV2");let u=w.computeStrides(r.shape),c=w.computeStrides(a.shape),d=D.computeConv3DInfo(r.shape,l,o,1,i),h=d.strideDepth,p=d.strideHeight,f=d.strideWidth,m=d.filterDepth,g=d.filterHeight,A=d.filterWidth,y=new Ut(d.filterShape,"float32"),x=y.values,[b,v,k,S]=y.strides,C=n.data.get(a.dataId).values,[_,O,E,R]=c,T=n.data.get(r.dataId).values,[P,V,j,q]=u,X=d.padInfo.front,ee=d.padInfo.left,te=d.padInfo.top;for(let ne=0;ne<m;++ne){let se=Math.max(0,Math.ceil((X-ne)/h)),J=Math.min(d.outDepth,(d.inDepth+X-ne)/h),ie=ne*b;for(let le=0;le<g;++le){let he=Math.max(0,Math.ceil((te-le)/p)),Ae=Math.min(d.outHeight,(d.inHeight+te-le)/p),Ce=le*v+ie;for(let Te=0;Te<A;++Te){let De=Math.max(0,Math.ceil((ee-Te)/f)),Me=Math.min(d.outWidth,(d.inWidth+ee-Te)/f),Fe=Te*k+Ce;for(let ut=0;ut<d.inChannels;++ut){let nt=ut*S+Fe;for(let st=0;st<d.outChannels;++st){let et=0;for(let it=0;it<d.batchSize;++it){let He=it*P,Nn=it*_;for(let St=se;St<J;++St){let nn=(ne+St*h-X)*V+He,ks=St*O+Nn;for(let pn=he;pn<Ae;++pn){let ns=(le+pn*p-te)*j+nn,sn=pn*E+ks;for(let ss=De;ss<Me;++ss){let Vn=(Te+ss*f-ee)*q+ns,Ks=ss*R+sn;et+=T[Vn+ut]*C[Ks+st]}}}}x[nt+st]=et}}}}}return n.makeTensorInfo(y.shape,y.dtype,y.values)}var iU={kernelName:Qd,backendName:"cpu",kernelFunc:oU};function lU(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,filter:a}=t,{pad:o,strides:i,inputShape:l}=s;ke([r],"conv3dBackpropInputV2");let u=w.computeStrides(r.shape),c=w.computeStrides(a.shape),d=D.computeConv3DInfo(l,a.shape,i,1,o),h=new Ut(d.inShape,"float32"),p=h.values,[f,m,g,A]=h.strides,y=n.data.get(r.dataId).values,[x,b,v,k]=u,S=n.data.get(a.dataId).values,[C,_,O,E]=c,{batchSize:R,filterDepth:T,filterHeight:P,filterWidth:V,inChannels:j,inDepth:q,inHeight:X,inWidth:ee,outChannels:te,outDepth:ne,outHeight:se,outWidth:J,strideDepth:ie,strideHeight:le,strideWidth:he}=d,Ae=T-1-d.padInfo.front,Ce=P-1-d.padInfo.top,Te=V-1-d.padInfo.left;for(let De=0;De<R;++De)for(let Me=0;Me<j;++Me)for(let Fe=0;Fe<q;++Fe){let ut=Fe-Ae,nt=Math.max(0,Math.ceil(ut/ie)),st=Math.min(ne,(T+ut)/ie);for(let et=0;et<X;++et){let it=et-Ce,He=Math.max(0,Math.ceil(it/le)),Nn=Math.min(se,(P+it)/le);for(let St=0;St<ee;++St){let Wn=St-Te,nn=Math.max(0,Math.ceil(Wn/he)),ks=Math.min(J,(V+Wn)/he),pn=0;for(let ts=nt;ts<st;++ts){let ns=ts*ie-ut;for(let sn=He;sn<Nn;++sn){let ss=sn*le-it;for(let rs=nn;rs<ks;++rs){let Vn=rs*he-Wn,Ks=x*De+b*ts+v*sn+k*rs,mr=C*(T-1-ns)+_*(P-1-ss)+O*(V-1-Vn)+E*Me;for(let Fr=0;Fr<te;++Fr){let ui=y[Ks+Fr],Zs=S[mr+Fr];pn+=ui*Zs}}}}p[f*De+m*Fe+g*et+A*St+Me]=pn}}}return n.makeTensorInfo(h.shape,h.dtype,h.values)}var uU={kernelName:eh,backendName:"cpu",kernelFunc:lU},cU=ot(Oa,e=>Math.cos(e)),dU={kernelName:Oa,backendName:"cpu",kernelFunc:cU},hU=ot(Pa,e=>Math.cosh(e)),pU={kernelName:Pa,backendName:"cpu",kernelFunc:hU};function fU(e){let{inputs:t,backend:n,attrs:s}=e,{image:r,boxes:a,boxInd:o}=t,{cropSize:i,method:l,extrapolationValue:u}=s,[c,d,h,p]=r.shape,f=a.shape[0],[m,g]=i,A=We([f,m,g,p],"float32"),y=n.data.get(a.dataId).values,x=n.data.get(o.dataId).values,b=n.data.get(r.dataId).values,v=w.computeStrides(r.shape),k=w.computeStrides(A.shape);for(let S=0;S<f;S++){let C=S*4,_=y[C],O=y[C+1],E=y[C+2],R=y[C+3],T=x[S];if(T>=c)continue;let P=m>1?(E-_)*(d-1)/(m-1):0,V=g>1?(R-O)*(h-1)/(g-1):0;for(let j=0;j<m;j++){let q=m>1?_*(d-1)+j*P:.5*(_+E)*(d-1);if(q<0||q>d-1){for(let X=0;X<g;X++)for(let ee=0;ee<p;ee++){let te=ee+X*k[2]+j*k[1]+S*k[0];A.values[te]=u}continue}if(l==="bilinear"){let X=Math.floor(q),ee=Math.ceil(q),te=q-X;for(let ne=0;ne<g;ne++){let se=g>1?O*(h-1)+ne*V:.5*(O+R)*(h-1);if(se<0||se>h-1){for(let he=0;he<p;he++){let Ae=he+ne*k[2]+j*k[1]+S*k[0];A.values[Ae]=u}continue}let J=Math.floor(se),ie=Math.ceil(se),le=se-J;for(let he=0;he<p;he++){let Ae=he+J*v[2]+X*v[1]+T*v[0],Ce=b[Ae];Ae=he+ie*v[2]+X*v[1]+T*v[0];let Te=b[Ae];Ae=he+J*v[2]+ee*v[1]+T*v[0];let De=b[Ae];Ae=he+ie*v[2]+ee*v[1]+T*v[0];let Me=b[Ae],Fe=Ce+(Te-Ce)*le,ut=De+(Me-De)*le;Ae=he+ne*k[2]+j*k[1]+S*k[0],A.values[Ae]=Fe+(ut-Fe)*te}}}else for(let X=0;X<g;++X){let ee=g>1?O*(h-1)+X*V:.5*(O+R)*(h-1);if(ee<0||ee>h-1){for(let se=0;se<p;se++){let J=se+X*k[2]+j*k[1]+S*k[0];A.values[J]=u}continue}let te=Math.round(ee),ne=Math.round(q);for(let se=0;se<p;se++){let J=se+te*v[2]+ne*v[1]+T*v[0],ie=se+X*k[2]+j*k[1]+S*k[0];A.values[ie]=b[J]}}}}return n.makeTensorInfo(A.shape,A.dtype,A.values)}var mU={kernelName:Oi,backendName:"cpu",kernelFunc:fU};function gU(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,exclusive:o,reverse:i}=s;ke(r,"cumsum");let l=D.getAxesPermutation([a],r.shape.length),u=r;l!=null&&(u=As({inputs:{x:r},backend:n,attrs:{perm:l}}));let c=D.getInnerMostAxes(1,r.shape.length)[0];if(c!==u.shape.length-1)throw new Error(`backend.cumsum in CPU expects an inner-most axis=${u.shape.length-1} but got axis=${c}`);let d=Cs(u.dtype,"int32"),h=w.makeZerosTypedArray(w.sizeFromShape(u.shape),d),p=n.data.get(u.dataId).values,f=u.shape[u.shape.length-1],m=i?(A,y)=>A+f-y-1:(A,y)=>A+y;for(let A=0;A<p.length;A+=f)for(let y=0;y<f;y++){let x=m(A,y);if(y===0)h[x]=o?0:p[x];else{let b=m(A,y-1);h[x]=o?p[b]+h[b]:p[x]+h[b]}}let g=n.makeTensorInfo(u.shape,d,h);if(l!=null){let A=D.getUndoAxesPermutation(l),y=As({inputs:{x:g},backend:n,attrs:{perm:A}});return n.disposeIntermediateTensorInfo(g),n.disposeIntermediateTensorInfo(u),y}return g}var AU={kernelName:Ma,backendName:"cpu",kernelFunc:gU};function yU(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,weights:a}=t,{size:o,binaryOutput:i}=s;if(r.shape.length===1){let l=n.data.get(r.dataId).values,u=n.data.get(a.dataId).values,c=h2(l,u,a.dtype,a.shape,o);return n.makeTensorInfo([o],a.dtype,c)}else if(r.shape.length===2){let l=n.bufferSync(r),u=n.bufferSync(a),c=V7(l,u,o,i);return n.makeTensorInfo(c.shape,a.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${r.shape.length}.`)}var xU={kernelName:th,backendName:"cpu",kernelFunc:yU};function bU(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockSize:a,dataFormat:o}=s;w.assert(o==="NHWC",()=>`Only NHWC dataFormat supported on CPU for depthToSpace. Got ${o}`),w.assert(a>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${a}`);let i=r.shape[0],l=r.shape[1],u=r.shape[2],c=r.shape[3],d=l*a,h=u*a,p=c/(a*a),f=n.data.get(r.dataId).values,m=new Float32Array(i*d*h*p),g=0;for(let A=0;A<i;++A)for(let y=0;y<d;++y){let x=Math.floor(y/a),b=y%a;for(let v=0;v<h;++v){let k=Math.floor(v/a),S=v%a,C=(b*a+S)*p;for(let _=0;_<p;++_){let E=_+C+c*(k+u*(x+l*A));m[g++]=f[E]}}}return n.makeTensorInfo([i,d,h,p],r.dtype,m)}var vU={kernelName:Pi,backendName:"cpu",kernelFunc:bU};function $w(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dilations:l,dimRoundingMode:u}=s;ke([r,a],"depthwiseConv2DNative");let c=w.computeStrides(r.shape),d=w.computeStrides(a.shape),h=l;h==null&&(h=[1,1]),w.assert(D.eitherStridesOrDilationsAreOne(o,h),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${o} and dilations '${h}'`);let p=D.computeConv2DInfo(r.shape,a.shape,o,h,i,u,!0),{filterHeight:f,filterWidth:m,dilationHeight:g,dilationWidth:A,padInfo:y}=p,x=y.left,b=y.top,v=p.outChannels/p.inChannels,k=new Ut(p.outShape,r.dtype),S=n.data.get(r.dataId).values,C=n.data.get(a.dataId).values,_=k.values;for(let O=0;O<p.batchSize;++O){let E=O*c[0],R=O*k.strides[0];for(let T=0;T<p.outHeight;++T){let P=R+T*k.strides[1],V=T*p.strideHeight-b;for(let j=0;j<f;++j){let q=V+j*g;if(q<0||q>=p.inHeight)continue;let X=j*d[0],ee=E+q*c[1];for(let te=0;te<p.outWidth;++te){let ne=P+te*k.strides[2],se=te*p.strideWidth-x;for(let J=0;J<m;++J){let ie=se+J*A;if(ie<0||ie>=p.inWidth)continue;let le=X+J*d[1],he=ee+ie*p.inChannels,Ae=ne,Ce=le;for(let Te=0;Te<p.inChannels;++Te){let De=S[he+Te];for(let Me=0;Me<v;++Me)_[Ae+Me]+=De*C[Ce+Me];Ae+=v,Ce+=v}}}}}}return n.makeTensorInfo(k.shape,k.dtype,k.values)}var wU={kernelName:za,backendName:"cpu",kernelFunc:$w};function kU(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,dy:a}=t,{strides:o,dilations:i,pad:l,dimRoundingMode:u,filterShape:c}=s;ke([r,a],"depthwiseConv2dNativeBackpropFilter");let d=D.computeConv2DInfo(r.shape,c,o,i,l,u,!0),{strideHeight:h,strideWidth:p,filterHeight:f,filterWidth:m}=d,g=new Ut(d.filterShape,"float32"),A=d.padInfo.left,y=d.padInfo.top,x=d.outChannels/d.inChannels,b=n.data.get(r.dataId).values,v=new Ut(r.shape,r.dtype,b),k=n.data.get(a.dataId).values,S=new Ut(a.shape,a.dtype,k);for(let C=0;C<f;++C){let _=Math.max(0,Math.ceil((y-C)/h)),O=Math.min(d.outHeight,(d.inHeight+y-C)/h);for(let E=0;E<m;++E){let R=Math.max(0,Math.ceil((A-E)/p)),T=Math.min(d.outWidth,(d.inWidth+A-E)/p);for(let P=0;P<d.outChannels;++P){let V=Math.trunc(P/x),j=P%x,q=0;for(let X=0;X<d.batchSize;++X)for(let ee=_;ee<O;++ee){let te=C+ee*h-y;for(let ne=R;ne<T;++ne){let se=E+ne*p-A;q+=v.get(X,te,se,V)*S.get(X,ee,ne,P)}}g.set(q,C,E,V,j)}}}return n.makeTensorInfo(g.shape,g.dtype,g.values)}var IU={kernelName:nh,backendName:"cpu",kernelFunc:kU};function SU(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,filter:a}=t,{strides:o,dilations:i,pad:l,dimRoundingMode:u,inputShape:c}=s;ke([r,a],"depthwiseConv2DNativeBackpropInput");let d=w.computeStrides(r.shape),h=w.computeStrides(a.shape),p=D.computeConv2DInfo(c,a.shape,o,i,l,u,!0),f=new Ut(p.inShape,"float32"),m=f.values,[g,A,y]=f.strides,x=n.data.get(r.dataId).values,[b,v,k]=d,S=n.data.get(a.dataId).values,[C,_,O]=h,{batchSize:E,filterHeight:R,filterWidth:T,inChannels:P,inHeight:V,inWidth:j,outChannels:q,outHeight:X,outWidth:ee,strideHeight:te,strideWidth:ne}=p,se=R-1-p.padInfo.top,J=T-1-p.padInfo.left,ie=q/P;for(let le=0;le<E;++le)for(let he=0;he<P;++he)for(let Ae=0;Ae<V;++Ae){let Ce=Ae-se,Te=Math.max(0,Math.ceil(Ce/te)),De=Math.min(X,(R+Ce)/te);for(let Me=0;Me<j;++Me){let Fe=Me-J,ut=Math.max(0,Math.ceil(Fe/ne)),nt=Math.min(ee,(T+Fe)/ne),st=0;for(let et=Te;et<De;++et){let it=et*te-Ce;for(let He=ut;He<nt;++He){let Nn=He*ne-Fe,St=b*le+v*et+k*He,Wn=C*(R-1-it)+_*(T-1-Nn)+O*he;for(let nn=0;nn<ie;++nn){let ks=he*ie+nn,pn=x[St+ks],ts=S[Wn+nn];st+=pn*ts}}}m[g*le+A*Ae+y*Me+he]=st}}return n.makeTensorInfo(f.shape,f.dtype,f.values)}var CU={kernelName:sh,backendName:"cpu",kernelFunc:SU};function TU(e){let{inputs:t,backend:n}=e,{x:s}=t,r=w.sizeFromShape(s.shape),a=n.data.get(s.dataId).values,o=We([r,r],s.dtype),i=o.values;for(let u=0;u<a.length;u++)i[u*r+u]=a[u];let l=[...s.shape,...s.shape];return n.makeTensorInfo(l,o.dtype,o.values)}var NU={kernelName:rh,backendName:"cpu",kernelFunc:TU},EU={kernelName:Lu,backendName:"cpu",kernelFunc:({inputs:e,backend:t,attrs:n})=>{let{x:s,filter:r}=e,{strides:a,pad:o,dilations:i}=n,l=t,u=l.data.get(s.dataId).values,c=s.shape.length,d=l.data.get(r.dataId).values,h=r.shape.length,{batchSize:p,inHeight:f,inWidth:m,inChannels:g,outHeight:A,outWidth:y,padInfo:x,strideHeight:b,strideWidth:v,filterHeight:k,filterWidth:S,dilationHeight:C,dilationWidth:_,outShape:O}=D.computeDilation2DInfo(s.shape,r.shape,a,o,"NHWC",i),E=w.sizeFromShape(O),R=O.length,T=w.getArrayFromDType(s.dtype,E);for(let V=0;V<p;++V)for(let j=0;j<A;++j){let q=j*b-x.top;for(let X=0;X<y;++X){let ee=X*v-x.left;for(let te=0;te<g;++te){let ne=Number.MIN_SAFE_INTEGER;for(let J=0;J<k;++J){let ie=q+J*C;if(ie>=0&&ie<f)for(let le=0;le<S;++le){let he=ee+le*_;if(he>=0&&he<m){let Ae=w.locToIndex([V,ie,he,te],c,w.computeStrides(s.shape)),Ce=w.locToIndex([J,le,te],h,w.computeStrides(r.shape)),Te=u[Ae]+d[Ce];Te>ne&&(ne=Te)}}}let se=w.locToIndex([V,j,X,te],R,w.computeStrides(O));T[se]=ne}}}return{dataId:l.write(w.toTypedArray(T,s.dtype),O,s.dtype),shape:O,dtype:s.dtype}}},RU={kernelName:oh,backendName:"cpu",kernelFunc:({inputs:e,backend:t,attrs:n})=>{let{x:s,filter:r,dy:a}=e,{strides:o,pad:i,dilations:l}=n,u=t,c=w.toNestedArray(s.shape,u.data.get(s.dataId).values),d=w.toNestedArray(r.shape,u.data.get(r.dataId).values),{batchSize:h,inHeight:p,inWidth:f,inChannels:m,outHeight:g,outWidth:A,padInfo:y,strideHeight:x,strideWidth:b,filterHeight:v,filterWidth:k,dilationHeight:S,dilationWidth:C,outShape:_}=D.computeDilation2DInfo(s.shape,r.shape,o,i,"NHWC",l);w.assert(a.rank===_.length,()=>`Error in ${oh}, dy must have the same rank as output ${_.length}, but got ${a.rank}`);let O=w.toNestedArray(_,u.data.get(a.dataId).values),E=w.makeZerosNestedTypedArray(r.shape,r.dtype);for(let T=0;T<h;++T)for(let P=0;P<g;++P){let V=P*x-y.top;for(let j=0;j<A;++j){let q=j*b-y.left;for(let X=0;X<m;++X){let ee=Number.MIN_SAFE_INTEGER,te=0,ne=0;for(let se=0;se<v;++se){let J=V+se*S;if(J>=0&&J<p)for(let ie=0;ie<k;++ie){let le=q+ie*C;if(le>=0&&le<f){let he=c[T][J][le][X]+d[se][ie][X];he>ee&&(ee=he,te=se,ne=ie)}}}E[te][ne][X]+=O[T][P][j][X]}}}return{dataId:u.write(w.toTypedArray(E,s.dtype),r.shape,r.dtype),shape:r.shape,dtype:r.dtype}}},_U={kernelName:ah,backendName:"cpu",kernelFunc:({inputs:e,backend:t,attrs:n})=>{let{x:s,filter:r,dy:a}=e,{strides:o,pad:i,dilations:l}=n,u=t,c=w.toNestedArray(s.shape,u.data.get(s.dataId).values),d=w.toNestedArray(r.shape,u.data.get(r.dataId).values),{batchSize:h,inHeight:p,inWidth:f,inChannels:m,outHeight:g,outWidth:A,padInfo:y,strideHeight:x,strideWidth:b,filterHeight:v,filterWidth:k,dilationHeight:S,dilationWidth:C,outShape:_}=D.computeDilation2DInfo(s.shape,r.shape,o,i,"NHWC",l);w.assert(a.rank===_.length,()=>`Error in ${ah}, dy must have the same rank as output ${_.length}, but got ${a.rank}`);let O=w.toNestedArray(_,u.data.get(a.dataId).values),E=w.makeZerosNestedTypedArray(s.shape,s.dtype);for(let T=0;T<h;++T)for(let P=0;P<g;++P){let V=P*x-y.top;for(let j=0;j<A;++j){let q=j*b-y.left;for(let X=0;X<m;++X){let ee=Number.MIN_SAFE_INTEGER,te=V<0?0:V,ne=q<0?0:q;for(let se=0;se<v;++se){let J=V+se*S;if(J>=0&&J<p)for(let ie=0;ie<k;++ie){let le=q+ie*C;if(le>=0&&le<f){let he=c[T][J][le][X]+d[se][ie][X];he>ee&&(ee=he,te=J,ne=le)}}}E[T][te][ne][X]+=O[T][P][j][X]}}}return{dataId:u.write(w.toTypedArray(E,s.dtype),s.shape,s.dtype),shape:s.shape,dtype:s.dtype}}};function Uc(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;ke(r,"sum");let i;r.dtype==="bool"?i=ca({inputs:{x:r},backend:n,attrs:{dtype:"int32"}}):i=cr({inputs:{x:r},backend:n});let l=i.shape.length,u=w.parseAxisParam(a,i.shape),c=D.getAxesPermutation(u,l),d=u,h=i;c!=null&&(h=As({inputs:{x:i},backend:n,attrs:{perm:c}}),d=D.getInnerMostAxes(d.length,l)),D.assertAxesAreInnerMostDims("sum",d,h.shape.length);let[p,f]=D.computeOutAndReduceShapes(h.shape,d),m=D.upcastType(h.dtype,"int32"),g=of(n,p,m),A=w.sizeFromShape(f),y=n.data.get(g.dataId).values,x=n.data.get(h.dataId).values;for(let b=0;b<y.length;++b){let v=b*A,k=0;for(let S=0;S<A;++S)k+=x[v+S];y[b]=k}if(o){let b=D.expandShapeToKeepDim(g.shape,u),v=g;g=xt({inputs:{x:g},backend:n,attrs:{shape:b}}),n.disposeIntermediateTensorInfo(v)}return n.disposeIntermediateTensorInfo(i),c!=null&&n.disposeIntermediateTensorInfo(h),g}var DU={kernelName:Ao,backendName:"cpu",kernelFunc:Uc};function $U(e){let{inputs:t,backend:n,attrs:s}=e,{equation:r}=s,a=t,{allDims:o,summedDims:i,idDims:l}=D.decodeEinsumEquation(r,a.length);D.checkEinsumDimSizes(o.length,l,a);let{path:u,steps:c}=D.getEinsumComputePath(i,l),d=c.length,h=null,p=o.length,f=[];for(let m=0;m<d;++m){for(let g of c[m]){let{permutationIndices:A,expandDims:y}=D.getEinsumPermutation(p,l[g]),x;D.isIdentityPermutation(A)?x=a[g]:(x=As({inputs:{x:a[g]},backend:n,attrs:{perm:A}}),f.push(x));let b=x.shape.slice();for(let v=0;v<y.length;++v)b.splice(y[v],0,1);w.arraysEqual(x.shape,b)||(x=xt({inputs:{x},backend:n,attrs:{shape:b}}),f.push(x)),h===null?h=x:(h=lf({inputs:{a:x,b:h},backend:n}),f.push(h))}m<d-1&&(u[m]>=0&&(h=Uc({inputs:{x:h},backend:n,attrs:{axis:u[m]-(o.length-p),keepDims:!1}}),f.push(h)),p--)}for(let m of f)m!==h&&n.disposeIntermediateTensorInfo(m);return h}var FU={kernelName:ih,backendName:"cpu",kernelFunc:$U};function OU(e){let{inputs:t,backend:n}=e,{dy:s,y:r}=t;ke([s,r],"eluGrad");let a=new Float32Array(w.sizeFromShape(r.shape)),o=n.data.get(r.dataId).values,i=n.data.get(s.dataId).values;for(let l=0;l<o.length;++l){let u=o[l];u>=1?a[l]=i[l]:a[l]=i[l]*(u+1)}return n.makeTensorInfo(r.shape,"float32",a)}var PU={kernelName:lh,backendName:"cpu",kernelFunc:OU},MU=D.ERF_P,zU=D.ERF_A1,LU=D.ERF_A2,BU=D.ERF_A3,WU=D.ERF_A4,VU=D.ERF_A5,UU=ot(Mi,e=>{let t=Math.sign(e),n=Math.abs(e),s=1/(1+MU*n);return t*(1-((((VU*s+WU)*s+BU)*s+LU)*s+zU)*s*Math.exp(-n*n))}),HU={kernelName:Mi,backendName:"cpu",kernelFunc:UU};function cf(e){let{inputs:t,backend:n,attrs:s}=e,{input:r}=t,{dim:a}=s,o=r.shape.length,i=r.shape.slice(),l=a;return a<0&&(w.assert(-(o+1)<=a,()=>`Axis must be in the interval [${-(o+1)}, ${o}]`),l=o+a+1),i.splice(l,0,1),xt({inputs:{x:r},backend:n,attrs:{shape:i}})}var GU={kernelName:Li,backendName:"cpu",kernelFunc:cf},jU=Lt((e,t)=>e/t),v2=tn(La,jU),w2={kernelName:La,backendName:"cpu",kernelFunc:v2};function Fw(e,t,n){let s=e.shape,r=s[0],a=s[1],o=n.data.get(e.dataId),i=o.complexTensorInfos.real,l=o.complexTensorInfos.imag,u=[r,a],c=w.sizeFromShape(u),d=w.getTypedArrayFromDType("float32",c),h=w.getTypedArrayFromDType("float32",c);for(let g=0;g<r;g++){let A=Zo({inputs:{x:i},backend:n,attrs:{begin:[g,0],size:[1,a]}}),y=Zo({inputs:{x:l},backend:n,attrs:{begin:[g,0],size:[1,a]}}),x=Zn({inputs:{real:A,imag:y},backend:n}),{real:b,imag:v}=qU(x,t,n),k=D.mergeRealAndImagArrays(b,v);for(let S=0;S<a;S++){let C=D.getComplexWithIndex(k,S);d[g*a+S]=C.real,h[g*a+S]=C.imag}n.disposeIntermediateTensorInfo(A),n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(x)}let p=n.makeTensorInfo(u,"float32",d),f=n.makeTensorInfo(u,"float32",h),m=Zn({inputs:{real:p,imag:f},backend:n});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),m}function qU(e,t,n){let s=w.sizeFromShape(e.shape),r=n.data.get(e.dataId),a=n.data.get(r.complexTensorInfos.real.dataId).values,o=n.data.get(r.complexTensorInfos.imag.dataId).values;if(XU(s)){let i=k2(a,o,s,t,n),l=[e.shape[0],e.shape[1]];if(t){let u=n.makeTensorInfo(l,"float32",i.real),c=n.makeTensorInfo(l,"float32",i.imag),d=n.makeTensorInfo([],"float32",w.createScalarValue(s,"float32")),h=cr({inputs:{x:d},backend:n}),p=w2.kernelFunc({inputs:{a:u,b:d},backend:n}),f=w2.kernelFunc({inputs:{a:c,b:h},backend:n}),m=n.data.get(p.dataId).values,g=n.data.get(f.dataId).values;return n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),{real:m,imag:g}}return i}else{let i=D.mergeRealAndImagArrays(a,o),l=KU(i,s,t);return D.splitRealAndImagArrays(l)}}function XU(e){return(e&e-1)==0}function k2(e,t,n,s,r){if(n===1)return{real:e,imag:t};let a=D.mergeRealAndImagArrays(e,t),o=n/2,i=D.complexWithEvenIndex(a),l=i.real,u=i.imag,c=[l.length],d=r.makeTensorInfo(c,"float32",l),h=r.makeTensorInfo(c,"float32",u),p=Zn({inputs:{real:d,imag:h},backend:r}),f=D.complexWithOddIndex(a),m=f.real,g=f.imag,A=[m.length],y=r.makeTensorInfo(A,"float32",m),x=r.makeTensorInfo(A,"float32",g),b=Zn({inputs:{real:y,imag:x},backend:r}),v=k2(l,u,o,s,r),k=v.real,S=v.imag,C=[k.length],_=r.makeTensorInfo(C,"float32",k),O=r.makeTensorInfo(C,"float32",S),E=Zn({inputs:{real:_,imag:O},backend:r}),R=k2(m,g,o,s,r),T=R.real,P=R.imag,V=[T.length],j=r.makeTensorInfo(V,"float32",T),q=r.makeTensorInfo(V,"float32",P),X=Zn({inputs:{real:j,imag:q},backend:r}),ee=D.exponents(n,s),te=[ee.real.length],ne=r.makeTensorInfo(te,"float32",ee.real),se=r.makeTensorInfo(te,"float32",ee.imag),J=Zn({inputs:{real:ne,imag:se},backend:r}),ie=lf({inputs:{a:J,b:X},backend:r}),le=Wc({inputs:{a:E,b:ie},backend:r}),he=y2({inputs:{a:E,b:ie},backend:r}),Ae=Ko({inputs:{input:le},backend:r}),Ce=Ko({inputs:{input:he},backend:r}),Te=Ql({inputs:{input:le},backend:r}),De=Ql({inputs:{input:he},backend:r}),Me=eu({inputs:[Ae,Ce],backend:r,attrs:{axis:0}}),Fe=eu({inputs:[Te,De],backend:r,attrs:{axis:0}}),ut=r.data.get(Me.dataId).values,nt=r.data.get(Fe.dataId).values;return r.disposeIntermediateTensorInfo(d),r.disposeIntermediateTensorInfo(h),r.disposeIntermediateTensorInfo(p),r.disposeIntermediateTensorInfo(y),r.disposeIntermediateTensorInfo(x),r.disposeIntermediateTensorInfo(b),r.disposeIntermediateTensorInfo(_),r.disposeIntermediateTensorInfo(O),r.disposeIntermediateTensorInfo(E),r.disposeIntermediateTensorInfo(j),r.disposeIntermediateTensorInfo(q),r.disposeIntermediateTensorInfo(X),r.disposeIntermediateTensorInfo(ne),r.disposeIntermediateTensorInfo(se),r.disposeIntermediateTensorInfo(J),r.disposeIntermediateTensorInfo(ie),r.disposeIntermediateTensorInfo(le),r.disposeIntermediateTensorInfo(he),r.disposeIntermediateTensorInfo(Ae),r.disposeIntermediateTensorInfo(Te),r.disposeIntermediateTensorInfo(Ce),r.disposeIntermediateTensorInfo(De),r.disposeIntermediateTensorInfo(Me),r.disposeIntermediateTensorInfo(Fe),{real:ut,imag:nt}}function KU(e,t,n){let s=new Float32Array(t*2);for(let r=0;r<t;r++){let a=0,o=0;for(let i=0;i<t;i++){let l=D.exponent(r*i,t,n),u=D.getComplexWithIndex(e,i);a+=u.real*l.real-u.imag*l.imag,o+=u.real*l.imag+u.imag*l.real}n&&(a/=t,o/=t),D.assignToTypedArray(s,a,o,r)}return s}function ZU(e){let{inputs:t,backend:n}=e,{input:s}=t,r=w.sizeFromShape(s.shape),a=s.shape[s.shape.length-1],o=r/a,i=xt({inputs:{x:s},backend:n,attrs:{shape:[o,a]}}),l=Fw(i,!1,n),u=xt({inputs:{x:l},backend:n,attrs:{shape:s.shape}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(l),u}var YU={kernelName:uh,backendName:"cpu",kernelFunc:ZU};function I2(e){let{backend:t,attrs:n}=e,{shape:s,value:r,dtype:a}=n,o=a||w.inferDtype(r),i=w.getArrayFromDType(o,w.sizeFromShape(s));return QU(i,r,o),t.makeTensorInfo(s,o,i)}var JU={kernelName:Bu,backendName:"cpu",kernelFunc:I2};function QU(e,t,n){e.fill(t)}var eH={kernelName:Wi,backendName:"cpu",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:s}=e,r=n,a=w.getTypedArrayFromDType(s.dtype,w.sizeFromShape(s.shape)),[o,i,l,u]=s.shape,c=r.data.get(s.dataId).values;for(let h=0;h<o;h++){let p=h*l*i*u;for(let f=0;f<i;f++){let m=f*(l*u);for(let g=0;g<l;g++){let A=g*u;for(let y=0;y<u;y++){let x=Math.round(l-g-1),b=p+m+A+y,v=c[b];if(x>=0&&x<l){let k=x*u,S=p+m+k+y;v=c[S]}a[b]=v}}}}return{dataId:r.write(a,s.shape,s.dtype),shape:s.shape,dtype:s.dtype}}},tH=Lt((e,t)=>Math.floor(e/t)),nH=tn(Ua,tH,null,"int32"),sH={kernelName:Ua,backendName:"cpu",kernelFunc:nH};function rH(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dataFormat:c,dilations:d,dimRoundingMode:h,activation:p,leakyreluAlpha:f}=s,m=Dw({inputs:{x:r,filter:a},backend:n,attrs:{strides:l,pad:u,dataFormat:c,dilations:d,dimRoundingMode:h}});if(o){let g=m;m=Wc({inputs:{a:m,b:o},backend:n}),n.disposeIntermediateTensorInfo(g)}if(p){let g=m;m=x2(n,m,p,i,f),n.disposeIntermediateTensorInfo(g)}return m}var aH={kernelName:So,backendName:"cpu",kernelFunc:rH};function oH(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dataFormat:c,dilations:d,dimRoundingMode:h,activation:p,leakyreluAlpha:f}=s,m=$w({inputs:{x:r,filter:a},backend:n,attrs:{strides:l,pad:u,dataFormat:c,dilations:d,dimRoundingMode:h}});if(o){let g=m;m=Wc({inputs:{a:m,b:o},backend:n}),n.disposeIntermediateTensorInfo(g)}if(p){let g=m;m=x2(n,m,p,i,f),n.disposeIntermediateTensorInfo(g)}return m}var iH={kernelName:Co,backendName:"cpu",kernelFunc:oH};function lH(e){let{inputs:t,backend:n}=e,{params:s,indices:r}=t,a=w.sizeFromShape(s.shape),o=r.shape,i=o[o.length-1],[l,u,c,d]=D.prepareAndValidate(s,r);if(u===0)return n.makeTensorInfo(l,s.dtype,[]);let h=n.data.get(r.dataId).values,p=n.bufferSync(s),f=Z7(h,p,s.dtype,u,i,c,d,s.shape,a);return n.makeTensorInfo(l,s.dtype,f.values)}var uH={kernelName:Ui,backendName:"cpu",kernelFunc:lH};function cH(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,indices:a}=t,{axis:o,batchDims:i}=s;ke([r,a],"gatherV2");let l=i;i==null&&(l=0);let u=w.sizeFromShape(a.shape),c=w.parseAxisParam(o,r.shape)[0],d=D.segment_util.collectGatherOpShapeInfo(r,a,c,l),h=xt({inputs:{x:r},backend:n,attrs:{shape:[d.batchSize,d.outerSize,d.dimSize,d.sliceSize]}}),p=xt({inputs:{x:a},backend:n,attrs:{shape:[d.batchSize,u/d.batchSize]}}),f=[d.batchSize,d.outerSize,u/d.batchSize,d.sliceSize],m=n.bufferSync(p),g=n.bufferSync(h),A=Y7(g,m,f);return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(p),n.makeTensorInfo(d.outputShape,A.dtype,A.values)}var dH={kernelName:Vi,backendName:"cpu",kernelFunc:cH};function hH(e){let{inputs:t,backend:n}=e,{input:s}=t,r=w.sizeFromShape(s.shape),a=s.shape[s.shape.length-1],o=r/a,i=xt({inputs:{x:s},backend:n,attrs:{shape:[o,a]}}),l=Fw(i,!0,n),u=xt({inputs:{x:l},backend:n,attrs:{shape:s.shape}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(l),u}var pH={kernelName:ch,backendName:"cpu",kernelFunc:hH},fH=ot(Gi,e=>Number.isFinite(e)?1:0,"bool"),mH={kernelName:Gi,backendName:"cpu",kernelFunc:fH},gH=ot(ji,e=>Math.abs(e)===1/0?1:0,"bool"),AH={kernelName:ji,backendName:"cpu",kernelFunc:gH},yH=ot(qi,e=>Number.isNaN(e)?1:0,"bool"),xH={kernelName:qi,backendName:"cpu",kernelFunc:yH};function bH(e){let{backend:t,attrs:n}=e,{start:s,stop:r,num:a}=n,o=nw(s,r,a);return t.makeTensorInfo([o.length],"float32",o)}var vH={kernelName:hh,backendName:"cpu",kernelFunc:bH},wH=ot(Zi,e=>Math.log1p(e)),kH={kernelName:Zi,backendName:"cpu",kernelFunc:wH},IH=Lt((e,t)=>e&&t),SH=tn(Yi,IH,null,"bool"),CH={kernelName:Yi,backendName:"cpu",kernelFunc:SH},TH=ot(Wu,e=>e?0:1,"bool"),NH={kernelName:Wu,backendName:"cpu",kernelFunc:TH},EH=Lt((e,t)=>e||t),RH=tn(Vu,EH,null,"bool"),_H={kernelName:Vu,backendName:"cpu",kernelFunc:RH};function DH(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{depthRadius:a,bias:o,alpha:i,beta:l}=s;ke(r,"LRN");let u=r.shape[3],c=u-1,d=n.data.get(r.dataId).values,h=w.sizeFromShape(r.shape),p=new Float32Array(h);function f(m){let g=m%u,A=m-g+Math.max(0,g-a),y=m-g+Math.min(g+a,c),x=0;for(;A<=y;A++){let b=d[A];x+=b*b}return x}for(let m=0;m<h;m++){let g=f(m),A=d[m]*Math.pow(o+i*g,-l);p[m]=A}return n.makeTensorInfo(r.shape,r.dtype,p)}var $H={kernelName:Uu,backendName:"cpu",kernelFunc:DH};function FH(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,y:a,dy:o}=t,{depthRadius:i,bias:l,alpha:u,beta:c}=s;ke(o,"LRNGrad");let d=w.sizeFromShape(o.shape),h=o.shape[3],p=n.data.get(o.dataId).values,f=n.data.get(r.dataId).values,m=n.data.get(a.dataId).values,g=new Float32Array(d),A=d;for(let y=0;y<A;y++){let x=y%h,b=y-x+Math.max(0,x-i),v=y-x+Math.min(h,x+i+1),k=0;for(let S=b;S<v;S++)k+=Math.pow(f[S],2);k=u*k+l;for(let S=b;S<v;S++){let C=-2*u*c*f[S]*m[y]/k;y===S&&(C+=Math.pow(k,-c)),C*=p[y],g[S]+=C}}return n.makeTensorInfo(o.shape,r.dtype,g)}var OH={kernelName:ph,backendName:"cpu",kernelFunc:FH};function Ow(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{reductionIndices:a,keepDims:o}=s,i=n,l=r.shape,u=l.length,c=w.parseAxisParam(a,l),d=c,h=D.getAxesPermutation(d,u),p=i.data.get(r.dataId).values;if(h!=null){let b=new Array(u);for(let v=0;v<b.length;v++)b[v]=l[h[v]];p=m2(p,l,r.dtype,h,b),d=D.getInnerMostAxes(d.length,u),l=b}ke(r,"max"),D.assertAxesAreInnerMostDims("max",d,u);let[f,m]=D.computeOutAndReduceShapes(l,d),g=w.sizeFromShape(m),A=rw(p,g,f,r.dtype),y=i.write(A,f,r.dtype),x=f;return o&&(x=D.expandShapeToKeepDim(f,c)),{dataId:y,shape:x,dtype:r.dtype}}var PH={kernelName:Ka,backendName:"cpu",kernelFunc:Ow};function MH(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t;ke(r,"maxPool");let{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=s,u=1;w.assert(D.eitherStridesOrDilationsAreOne(o,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${o} and dilations '${u}'`);let c=D.computePool2DInfo(r.shape,a,o,u,i,l),d;if(c.filterWidth===1&&c.filterHeight===1&&w.arraysEqual(c.inShape,c.outShape))d=cr({inputs:{x:r},backend:n});else{let h=n.data.get(r.dataId).values,p=w.computeStrides(r.shape),f=b2(h,r.shape,r.dtype,p,c,"max");d=n.makeTensorInfo(c.outShape,r.dtype,f.values)}return d}var zH={kernelName:Ya,backendName:"cpu",kernelFunc:MH};function LH(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{filterSize:a,strides:o,pad:i,dimRoundingMode:l,dataFormat:u}=s;ke(r,"maxPool3d");let c=D.computePool3DInfo(r.shape,a,o,1,i,l,u),d=n.data.get(r.dataId).values,h=_w(d,r.shape,r.dtype,w.computeStrides(r.shape),c,"max");return n.makeTensorInfo(h.shape,"float32",h.values)}var BH={kernelName:Hu,backendName:"cpu",kernelFunc:LH};function WH(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a}=t,{filterSize:o,strides:i,pad:l,dimRoundingMode:u}=s;ke([r,a],"maxPool3DGrad");let c=D.computePool3DInfo(a.shape,o,i,1,l,u),d=n.bufferSync(a),h=RV(d,c),p=c.strideDepth,f=c.strideHeight,m=c.strideWidth,g=c.dilationDepth,A=c.dilationHeight,y=c.dilationWidth,x=c.effectiveFilterDepth,b=c.effectiveFilterHeight,v=c.effectiveFilterWidth,k=x-1-c.padInfo.front,S=v-1-c.padInfo.left,C=b-1-c.padInfo.top,_=We(a.shape,"float32"),O=n.bufferSync(r);for(let E=0;E<c.batchSize;++E)for(let R=0;R<c.inChannels;++R)for(let T=0;T<c.inDepth;++T)for(let P=0;P<c.inHeight;++P)for(let V=0;V<c.inWidth;++V){let j=T-k,q=P-C,X=V-S,ee=0;for(let te=0;te<x;te+=g){let ne=(j+te)/p;if(!(ne<0||ne>=c.outDepth||Math.floor(ne)!==ne))for(let se=0;se<b;se+=A){let J=(q+se)/f;if(!(J<0||J>=c.outHeight||Math.floor(J)!==J))for(let ie=0;ie<v;ie+=y){let le=(X+ie)/m;if(le<0||le>=c.outWidth||Math.floor(le)!==le)continue;let he=x*b*v-1-h.get(E,ne,J,le,R),Ae=te*b*v+se*v+ie,Ce=he===Ae?1:0;if(Ce===0)continue;ee+=O.get(E,ne,J,le,R)*Ce}}}_.set(ee,E,T,P,V,R)}return n.makeTensorInfo(_.shape,_.dtype,_.values)}var VH={kernelName:mh,backendName:"cpu",kernelFunc:WH};function UH(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a,output:o}=t,i=a;ke([a,o],"maxPoolGrad");let{filterSize:l,strides:u,pad:c,dimRoundingMode:d}=s,h=D.computePool2DInfo(i.shape,l,u,1,c,d),p=n.data.get(i.dataId).values,f=We(h.outShape,i.dtype,Rw(p,i.shape,i.dtype,h).values),m=h.strideHeight,g=h.strideWidth,A=h.dilationHeight,y=h.dilationWidth,x=h.effectiveFilterHeight,b=h.effectiveFilterWidth,v=b-1-h.padInfo.left,k=x-1-h.padInfo.top,S=We(i.shape,"float32"),C=n.data.get(r.dataId).values,_=We(r.shape,"float32",C);for(let O=0;O<h.batchSize;++O)for(let E=0;E<h.inChannels;++E)for(let R=0;R<h.inHeight;++R)for(let T=0;T<h.inWidth;++T){let P=R-k,V=T-v,j=0;for(let q=0;q<x;q+=A){let X=(P+q)/m;if(!(X<0||X>=h.outHeight||Math.floor(X)!==X))for(let ee=0;ee<b;ee+=y){let te=(V+ee)/g;if(te<0||te>=h.outWidth||Math.floor(te)!==te)continue;let ne=x*b-1-f.get(O,X,te,E),se=q*b+ee,J=ne===se?1:0;if(J===0)continue;j+=_.get(O,X,te,E)*J}}S.set(j,O,R,T,E)}return n.makeTensorInfo(S.shape,S.dtype,S.values)}var HH={kernelName:fh,backendName:"cpu",kernelFunc:UH};function GH(e,t,n,s,r){let a=w.computeStrides(t),o=b2(e,t,n,a,r,"max"),i=Rw(e,t,n,r,!0,s);return[o.values,i.values]}var jH={kernelName:gh,backendName:"cpu",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:s}=e,{filterSize:r,strides:a,pad:o,includeBatchInIndex:i}=t,l=n;ke(s,"MaxPoolWithArgmax");let u=l.data.get(s.dataId).values,c=D.computePool2DInfo(s.shape,r,a,[1,1],o),[d,h]=GH(u,s.shape,s.dtype,i,c),p=l.write(d,c.outShape,s.dtype),f=l.write(h,c.outShape,s.dtype);return[{dataId:p,shape:c.outShape,dtype:s.dtype},{dataId:f,shape:c.outShape,dtype:"int32"}]}};function qH(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s,i=w.parseAxisParam(a,r.shape),u=D.computeOutAndReduceShapes(r.shape,i)[1],c=w.sizeFromShape(u),d=[],h=n.makeTensorInfo([],"float32",new Float32Array([c]));d.push(h);let p=ca({inputs:{x:r},backend:n,attrs:{dtype:"float32"}});d.push(p);let f=v2({inputs:{a:p,b:h},backend:n});d.push(f);let m=Uc({inputs:{x:f},backend:n,attrs:{axis:a,keepDims:o}});return d.forEach(g=>n.disposeIntermediateTensorInfo(g)),m}var XH={kernelName:Ja,backendName:"cpu",kernelFunc:qH};function KH(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;ke(r,"min");let i=w.parseAxisParam(a,r.shape),l=i,u=D.getAxesPermutation(l,r.shape.length),c=r;u!=null&&(c=As({inputs:{x:r},backend:n,attrs:{perm:u}}),l=D.getInnerMostAxes(l.length,r.shape.length)),D.assertAxesAreInnerMostDims("min",l,c.shape.length);let[d,h]=D.computeOutAndReduceShapes(c.shape,l),p=w.sizeFromShape(h),f=w.makeZerosTypedArray(w.sizeFromShape(d),c.dtype),m=n.data.get(c.dataId).values;for(let A=0;A<f.length;++A){let y=A*p,x=m[y];for(let b=0;b<p;++b){let v=m[y+b];(Number.isNaN(v)||v<x)&&(x=v)}f[A]=x}u!=null&&n.disposeIntermediateTensorInfo(c);let g=n.makeTensorInfo(d,c.dtype,f);if(o){let A=D.expandShapeToKeepDim(d,i),y=xt({inputs:{x:g},backend:n,attrs:{shape:A}});return n.disposeIntermediateTensorInfo(g),y}return g}var ZH={kernelName:Qa,backendName:"cpu",kernelFunc:KH};function YH(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{paddings:a,mode:o}=s;ke(r,"mirrorPad");let i=a.map((x,b)=>x[0]+r.shape[b]+x[1]),l=a.map(x=>x[0]),u=a.map((x,b)=>x[0]+r.shape[b]),c=o==="reflect"?0:1,d=n.data.get(r.dataId).values,h=r.shape.length,p=w.computeStrides(r.shape),f=w.sizeFromShape(i),m=i.length,g=w.computeStrides(i),A=w.getTypedArrayFromDType(r.dtype,f);for(let x=0;x<f;x++){let b=w.indexToLoc(x,m,g);for(let k=0;k<m;k++)b[k]<l[k]?b[k]=l[k]*2-b[k]-c:b[k]>=u[k]&&(b[k]=(u[k]-1)*2-b[k]+c);b=b.map((k,S)=>k-l[S]);let v=w.locToIndex(b,h,p);A[x]=d[v]}return{dataId:n.write(A,i,r.dtype),shape:i,dtype:r.dtype}}var JH={kernelName:to,backendName:"cpu",kernelFunc:YH},QH=Lt((e,t)=>{let n=e%t;return e<0&&t<0||e>=0&&t>=0?n:(n+t)%t}),eG=tn(Ji,QH),tG={kernelName:Ji,backendName:"cpu",kernelFunc:eG},nG=Ia(g5());function Pw(e){let{inputs:t,backend:n,attrs:s}=e,{logits:r}=t,{dim:a}=s,o=r.shape.length,i=a;if(i===-1&&(i=o-1),i!==o-1)throw Error(`Softmax along a non-last dimension is not yet supported. Logits was rank ${o} and dim was ${i}`);let l=w.parseAxisParam([i],r.shape),u=Ow({inputs:{x:r},backend:n,attrs:{reductionIndices:l,keepDims:!1}}),c=D.expandShapeToKeepDim(u.shape,l),d=xt({inputs:{x:u},backend:n,attrs:{shape:c}}),h=y2({inputs:{a:r,b:d},backend:n}),p=q7({inputs:{x:h},backend:n}),f=Uc({inputs:{x:p},backend:n,attrs:{axis:l,keepDims:!1}}),m=xt({inputs:{x:f},backend:n,attrs:{shape:c}}),g=v2({inputs:{a:p,b:m},backend:n});return n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(m),g}var sG={kernelName:yo,backendName:"cpu",kernelFunc:Pw};function rG(e){let{inputs:t,backend:n,attrs:s}=e,{logits:r}=t,{numSamples:a,seed:o,normalized:i}=s;ke(r,"multinomial");let l=i?r:Pw({inputs:{logits:r},backend:n,attrs:{dim:-1}}),u=l.shape[0],c=l.shape[1],d=n.data.get(l.dataId).values,h=[u,a],p=w.makeZerosTypedArray(w.sizeFromShape(h),"int32");for(let f=0;f<u;++f){let m=f*c,g=new Float32Array(c-1);g[0]=d[m];for(let x=1;x<g.length;++x)g[x]=g[x-1]+d[m+x];let A=nG.alea(o.toString()),y=f*a;for(let x=0;x<a;++x){let b=A();p[y+x]=g.length;for(let v=0;v<g.length;v++)if(b<g[v]){p[y+x]=v;break}}}return i||n.disposeIntermediateTensorInfo(l),n.makeTensorInfo(h,"int32",p)}var aG={kernelName:Ah,backendName:"cpu",kernelFunc:rG},oG=rr.nonMaxSuppressionV3Impl;function iG(e){let{inputs:t,backend:n,attrs:s}=e,{boxes:r,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l}=s;ke(r,"NonMaxSuppression");let u=n.data.get(r.dataId).values,c=n.data.get(a.dataId).values,{selectedIndices:d}=oG(u,c,o,i,l);return n.makeTensorInfo([d.length],"int32",new Int32Array(d))}var lG={kernelName:tl,backendName:"cpu",kernelFunc:iG},uG=rr.nonMaxSuppressionV4Impl;function cG(e){let{inputs:t,backend:n,attrs:s}=e,{boxes:r,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l,padToMaxOutputSize:u}=s;ke(r,"NonMaxSuppressionPadded");let c=n.data.get(r.dataId).values,d=n.data.get(a.dataId).values,{selectedIndices:h,validOutputs:p}=uG(c,d,o,i,l,u);return[n.makeTensorInfo([h.length],"int32",new Int32Array(h)),n.makeTensorInfo([],"int32",new Int32Array([p]))]}var dG={kernelName:nl,backendName:"cpu",kernelFunc:cG},hG=rr.nonMaxSuppressionV5Impl;function pG(e){let{inputs:t,backend:n,attrs:s}=e,{boxes:r,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l,softNmsSigma:u}=s;ke(r,"NonMaxSuppressionWithScore");let c=n.data.get(r.dataId).values,d=n.data.get(a.dataId).values,h=o,p=i,f=l,m=u,{selectedIndices:g,selectedScores:A}=hG(c,d,h,p,f,m);return[n.makeTensorInfo([g.length],"int32",new Int32Array(g)),n.makeTensorInfo([A.length],"float32",new Float32Array(A))]}var fG={kernelName:sl,backendName:"cpu",kernelFunc:pG};function mG(e){let{inputs:t,backend:n,attrs:s}=e,{indices:r}=t,{depth:a,onValue:o,offValue:i}=s;ke(r,"oneHot");let l=w.sizeFromShape(r.shape),u=new Float32Array(l*a);u.fill(i);let c=n.data.get(r.dataId).values;for(let d=0;d<l;++d)c[d]>=0&&c[d]<a&&(u[d*a+c[d]]=o);return n.makeTensorInfo([...r.shape,a],"int32",u)}var gG={kernelName:so,backendName:"cpu",kernelFunc:mG};function df(e){let{inputs:t,backend:n}=e,{x:s}=t;if(s.dtype==="string")throw new Error("zerosLike is not supported for string tensors");if(s.dtype==="complex64"){let r=Ko({inputs:{input:s},backend:n}),a=df({inputs:{x:r},backend:n}),o=Ql({inputs:{input:s},backend:n}),i=df({inputs:{x:o},backend:n}),l=Zn({inputs:{real:a,imag:i},backend:n});return n.disposeIntermediateTensorInfo(r),n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(i),l}else return I2({backend:n,attrs:{shape:s.shape,value:0,dtype:s.dtype}})}var AG={kernelName:wl,backendName:"cpu",kernelFunc:df};function Mw(e){let{inputs:t,backend:n}=e,{x:s}=t;if(s.dtype==="string")throw new Error("onesLike is not supported for string tensors");if(s.dtype==="complex64"){let r=Ko({inputs:{input:s},backend:n}),a=Mw({inputs:{x:r},backend:n}),o=Ql({inputs:{input:s},backend:n}),i=df({inputs:{x:o},backend:n}),l=Zn({inputs:{real:a,imag:i},backend:n});return n.disposeIntermediateTensorInfo(r),n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(i),l}else return I2({backend:n,attrs:{shape:s.shape,value:1,dtype:s.dtype}})}var yG={kernelName:rl,backendName:"cpu",kernelFunc:Mw};function zw(e){let{inputs:t,backend:n,attrs:s}=e,{axis:r}=s;if(t.length===1)return cf({inputs:{input:t[0]},backend:n,attrs:{dim:r}});let a=t[0].shape,o=t[0].dtype;t.forEach(c=>{w.assertShapesMatch(a,c.shape,"All tensors passed to stack must have matching shapes"),w.assert(o===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let i=[],l=t.map(c=>{let d=cf({inputs:{input:c},backend:n,attrs:{dim:r}});return i.push(d),d}),u=eu({inputs:l,backend:n,attrs:{axis:r}});return i.forEach(c=>n.disposeIntermediateTensorInfo(c)),u}var xG={kernelName:al,backendName:"cpu",kernelFunc:zw};function bG(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{paddings:a,constantValue:o}=s;ke(r,"pad");let i=a.map((y,x)=>y[0]+r.shape[x]+y[1]),l=a.map(y=>y[0]),u=n.data.get(r.dataId).values,c=w.sizeFromShape(r.shape),d=r.shape.length,h=w.computeStrides(r.shape),p=w.sizeFromShape(i),f=i.length,m=w.computeStrides(i),g=w.getTypedArrayFromDType(r.dtype,p);o!==0&&g.fill(o);for(let y=0;y<c;y++){let b=w.indexToLoc(y,d,h).map((k,S)=>k+l[S]),v=w.locToIndex(b,f,m);g[v]=u[y]}return{dataId:n.write(g,i,r.dtype),shape:i,dtype:r.dtype}}var Lw={kernelName:ro,backendName:"cpu",kernelFunc:bG},vG=Lt((e,t)=>Math.pow(e,t)),wG=tn(ao,vG),kG={kernelName:ao,backendName:"cpu",kernelFunc:wG};function IG(e){let{backend:t,attrs:n}=e,{start:s,stop:r,dtype:a,step:o}=n,i=g2(s,r,o,a);return t.makeTensorInfo([i.length],a,i)}var SG={kernelName:Gu,backendName:"cpu",kernelFunc:IG},CG=ot(il,e=>1/e),TG={kernelName:il,backendName:"cpu",kernelFunc:CG};function NG(e){let{inputs:t,backend:n,attrs:s}=e,{images:r}=t,{alignCorners:a,halfPixelCenters:o,size:i}=s;ke(r,"resizeBilinear");let l=w.computeStrides(r.shape),[u,c]=i,[d,h,p,f]=r.shape,m=n.data.get(r.dataId).values,g=new Float32Array(w.sizeFromShape([d,u,c,f])),A=[a&&u>1?h-1:h,a&&c>1?p-1:p],y=[a&&u>1?u-1:u,a&&c>1?c-1:c],x=0,b=A[0]/y[0],v=A[1]/y[1];for(let k=0;k<d;k++)for(let S=0;S<u;S++){let C;o?C=b*(S+.5)-.5:C=b*S;let _=Math.max(0,Math.floor(C)),O=C-_,E=Math.min(h-1,Math.ceil(C)),R=k*l[0]+_*l[1],T=k*l[0]+E*l[1];for(let P=0;P<c;P++){let V;o?V=v*(P+.5)-.5:V=v*P;let j=Math.max(0,Math.floor(V)),q=V-j,X=Math.min(p-1,Math.ceil(V)),ee=R+j*l[2],te=T+j*l[2],ne=R+X*l[2],se=T+X*l[2];for(let J=0;J<f;J++){let ie=m[ee+J],le=m[te+J],he=m[ne+J],Ae=m[se+J],Ce=ie+(he-ie)*q,Te=le+(Ae-le)*q,De=Ce+(Te-Ce)*O;g[x++]=De}}}return n.makeTensorInfo([d,u,c,f],"float32",g)}var EG={kernelName:lo,backendName:"cpu",kernelFunc:NG};function RG(e){let{inputs:t,backend:n,attrs:s}=e,{images:r,dy:a}=t,{alignCorners:o}=s;ke([a,r],"resizeBilinearGrad");let i=w.computeStrides(r.shape),[l,u,c,d]=r.shape,[,h,p]=a.shape,f=new Float32Array(l*u*c*d),m=[o&&h>1?u-1:u,o&&p>1?c-1:c],g=[o&&h>1?h-1:h,o&&p>1?p-1:p],A=m[0]/g[0],y=m[1]/g[1],x=n.data.get(a.dataId).values,b=0;for(let v=0;v<l;v++){let k=v*i[0];for(let S=0;S<h;S++){let C=S*A,_=Math.floor(C),O=Math.min(Math.ceil(C),u-1),E=k+_*i[1],R=k+O*i[1],T=C-_,P=1-T;for(let V=0;V<p;V++){let j=V*y,q=Math.floor(j),X=Math.min(Math.ceil(j),c-1),ee=j-q,te=1-ee,ne=E+q*i[2],se=E+X*i[2],J=R+q*i[2],ie=R+X*i[2],le=P*te,he=P*ee,Ae=T*te,Ce=T*ee;for(let Te=0;Te<d;Te++){let De=x[b++];f[ne+Te]+=De*le,f[se+Te]+=De*he,f[J+Te]+=De*Ae,f[ie+Te]+=De*Ce}}}}return n.makeTensorInfo([l,c,u,d],"float32",f)}var _G={kernelName:bh,backendName:"cpu",kernelFunc:RG};function DG(e){let{inputs:t,backend:n,attrs:s}=e,{images:r}=t,{alignCorners:a,halfPixelCenters:o,size:i}=s;ke(r,"resizeNearestNeighbor");let l=w.computeStrides(r.shape),[u,c]=i,[d,h,p,f]=r.shape,m=n.data.get(r.dataId).values,g=new Float32Array(d*u*c*f),A=[a&&u>1?h-1:h,a&&c>1?p-1:p],y=[a&&u>1?u-1:u,a&&c>1?c-1:c],x=A[0]/y[0],b=A[1]/y[1],v=0;for(let k=0;k<d;k++){let S=k*l[0];for(let C=0;C<u;C++){let _=o?x*(C+.5):x*C,O=Math.min(h-1,a?Math.round(_):Math.floor(_));o&&(O=Math.max(0,O));let E=S+O*l[1];for(let R=0;R<c;R++){let T=o?b*(R+.5):b*R,P=Math.min(p-1,a?Math.round(T):Math.floor(T));o&&(P=Math.max(0,P));let V=E+P*l[2];for(let j=0;j<f;j++){let q=m[V+j];g[v++]=q}}}}return n.makeTensorInfo([d,u,c,f],r.dtype,g)}var $G={kernelName:ju,backendName:"cpu",kernelFunc:DG};function FG(e){let{inputs:t,backend:n,attrs:s}=e,{images:r,dy:a}=t,{alignCorners:o}=s;ke([a,r],"resizeNearestNeighborGrad");let i=w.computeStrides(r.shape),l=w.computeStrides(a.shape),[u,c,d,h]=r.shape,[,p,f]=a.shape,m=new Float32Array(u*c*d*h),g=n.data.get(a.dataId).values,A=[o&&p>1?c-1:c,o&&f>1?d-1:d],y=[o&&p>1?p-1:p,o&&f>1?f-1:f],x=A[0]/y[0],b=A[1]/y[1],v=1/x,k=1/b,S=Math.ceil(v)*2+2,C=Math.ceil(k)*2+2;for(let _=0;_<u;_++){let O=_*i[0];for(let E=0;E<c;E++){let R=O+E*i[1],T=Math.floor(E*v),P=Math.floor(T-S/2);for(let V=0;V<d;V++){let j=R+V*i[2],q=Math.floor(V*k),X=Math.floor(q-C/2);for(let ee=0;ee<h;ee++){let te=0;for(let ne=0;ne<S;ne++){let se=ne+P;if(se<0||se>=p)continue;let J=O+se*l[1],ie=se*x,le=Math.min(c-1,o?Math.round(ie):Math.floor(ie));if(E===le)for(let he=0;he<C;he++){let Ae=he+X;if(Ae<0||Ae>=f)continue;let Ce=J+Ae*l[2],Te=Ae*b,De=Math.min(d-1,o?Math.round(Te):Math.floor(Te));V===De&&(te+=g[Ce+ee])}}m[j+ee]=te}}}}return n.makeTensorInfo(r.shape,r.dtype,m)}var OG={kernelName:xh,backendName:"cpu",kernelFunc:FG};function PG(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{dims:a}=s;ke(r,"reverse");let o=r.shape.length,i=w.parseAxisParam(a,r.shape);if(o===0)return cr({inputs:{x:r},backend:n});let l=new Ut(r.shape,r.dtype),u=n.bufferSync(r);for(let c=0;c<l.size;c++){let d=l.indexToLoc(c),h=d.slice();i.forEach(p=>h[p]=r.shape[p]-1-h[p]),l.set(u.get(...h),...d)}return n.makeTensorInfo(l.shape,l.dtype,l.values)}var MG={kernelName:co,backendName:"cpu",kernelFunc:PG},zG={kernelName:kl,backendName:"cpu",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:s}=e,{radians:r,fillValue:a,center:o}=t,i=n,l=w.getTypedArrayFromDType(s.dtype,w.sizeFromShape(s.shape)),[u,c,d,h]=s.shape,[p,f]=D.getImageCenter(o,c,d),m=255,g=Math.sin(r),A=Math.cos(r),y=i.data.get(s.dataId).values;for(let b=0;b<u;b++){let v=b*d*c*h;for(let k=0;k<c;k++){let S=k*(d*h);for(let C=0;C<d;C++){let _=C*h;for(let O=0;O<h;O++){let E=[u,k,C,O],R=E[2],T=E[1],P=(R-p)*A-(T-f)*g,V=(R-p)*g+(T-f)*A;P=Math.round(P+p),V=Math.round(V+f);let j=a;if(typeof a!="number"&&(O===3?j=m:j=a[O]),P>=0&&P<d&&V>=0&&V<c){let X=V*(d*h),ee=P*h,te=v+X+ee+O;j=y[te]}let q=v+S+_+O;l[q]=j}}}}return{dataId:i.write(l,s.shape,s.dtype),shape:s.shape,dtype:s.dtype}}},LG=ot(ho,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}),BG={kernelName:ho,backendName:"cpu",kernelFunc:LG};function Bw(e,t,n,s,r,a,o,i,l,u){let c=[s/r,r],d=e.values,h=t.values;if(s===0)return We(n,t.dtype);let p=We(c,t.dtype);p.values.fill(l);for(let f=0;f<a;f++){let m=[],g=0;for(let A=0;A<o;A++){let y=d[f*o+A];m.push(y),g+=y*i[A]}if(g<0||g>=s/r)throw new Error(`Invalid indices: ${m} does not index into ${n}`);for(let A=0;A<r;A++)u?p.values[g*r+A]+=h[f*r+A]:p.values[g*r+A]=t.rank===0?h[0]:h[f*r+A]}return p}function WG(e){let{inputs:t,backend:n,attrs:s}=e,{indices:r,updates:a}=t,{shape:o}=s,{sliceRank:i,numUpdates:l,sliceSize:u,strides:c,outputSize:d}=D.calculateShapes(a,r,o),h=!0,p=n.bufferSync(r),f=n.bufferSync(a),m=Bw(p,f,o,d,u,l,i,c,0,h);return n.makeTensorInfo(o,m.dtype,m.values)}var VG={kernelName:ul,backendName:"cpu",kernelFunc:WG};function UG(e){let{inputs:t,backend:n}=e,{condition:s,t:r,e:a}=t;ke([s,r,a],"select");let o=s.shape.length,i=n.data.get(s.dataId).values,l=n.data.get(r.dataId).values,u=n.data.get(a.dataId).values,c=Cs(r.dtype,a.dtype),d=w.makeZerosTypedArray(w.sizeFromShape(r.shape),c),h=0,p=o===0||o>1||r.shape.length===1?1:w.sizeFromShape(r.shape.slice(1));for(let f=0;f<i.length;f++)for(let m=0;m<p;m++)i[f]===1?d[h++]=l[f]:d[h++]=u[f];return n.makeTensorInfo(r.shape,c,d)}var HG={kernelName:cl,backendName:"cpu",kernelFunc:UG},GG=D.SELU_SCALEALPHA,jG=D.SELU_SCALE,qG=ot(dl,e=>e>=0?jG*e:GG*(Math.exp(e)-1)),XG={kernelName:dl,backendName:"cpu",kernelFunc:qG},KG=ot(fl,e=>e<0?-1:e>0?1:0),ZG={kernelName:fl,backendName:"cpu",kernelFunc:KG},YG=ot(fo,e=>Math.sin(e)),JG={kernelName:fo,backendName:"cpu",kernelFunc:YG},QG=ot(pl,e=>Math.sinh(e)),ej={kernelName:pl,backendName:"cpu",kernelFunc:QG},tj=11920928955078125e-23,Ww=Math.log(tj)+2,nj=ot(ml,e=>{let t=e>-Ww,n=e<Ww,s=Math.exp(e),r;return n?r=s:t?r=e:r=Math.log(1+s),r}),sj={kernelName:ml,backendName:"cpu",kernelFunc:nj};function rj(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockShape:a,paddings:o}=s;ke([r],"spaceToBatchND");let i=w.sizeFromShape(a),l=[[0,0]];l.push(...o);for(let k=1+a.length;k<r.shape.length;++k)l.push([0,0]);let u=Lw.kernelFunc({inputs:{x:r},backend:n,attrs:{paddings:l,constantValue:0}}),c=D.getReshaped(u.shape,a,i,!1),d=D.getPermuted(c.length,a.length,!1),h=D.getReshapedPermuted(u.shape,a,i,!1),m=xt({inputs:{x:u},backend:n,attrs:{shape:c}}),y=As({inputs:{x:m},backend:n,attrs:{perm:d}}),v=xt({inputs:{x:y},backend:n,attrs:{shape:h}});return n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(y),v}var aj={kernelName:gl,backendName:"cpu",kernelFunc:rj};function oj(e){let{inputs:t,backend:n}=e,{indices:s,values:r,denseShape:a,defaultValue:o}=t;if(a.shape.length!==1)throw new Error(`Dense shape must be a vector, saw:
${a.shape}`);if(s.shape.length!==2)throw new Error(`Indices must be a matrix, saw:
${s.shape}`);if(r.shape.length!==1)throw new Error(`Values must be a vector, saw:
${r.shape}`);if(o.shape.length!==0)throw new Error(`Default value must be a scalar, saw:
${o.shape}`);let i=n.data.get(s.dataId).values,l=n.data.get(r.dataId).values,u=n.data.get(a.dataId).values,c=n.data.get(o.dataId).values[0],[d,h,p,f,m]=hw(i,s.shape,s.dtype,l,r.dtype,u,c);return[n.makeTensorInfo(h,s.dtype,d),n.makeTensorInfo([h[0]],r.dtype,p),n.makeTensorInfo([f.length],"bool",new Uint8Array(f.map(g=>Number(g)))),n.makeTensorInfo([m.length],s.dtype,new Int32Array(m))]}var ij={kernelName:vh,backendName:"cpu",kernelFunc:oj};function lj(e){let{inputs:t,backend:n}=e,{inputIndices:s,inputShape:r,newShape:a}=t;if(s.shape.length!==2)throw new Error(`Input indices should be a matrix but received shape
${s.shape}`);if(r.shape.length!==1)throw new Error(`Input shape should be a vector but received shape
${r.shape}`);if(a.shape.length!==1)throw new Error(`Target shape should be a vector but received shape ${a.shape}`);let o=Array.from(n.data.get(r.dataId).values),i=n.data.get(s.dataId).values,l=Array.from(n.data.get(a.dataId).values),[u,c,d]=pw(i,s.shape,s.dtype,o,l);return[n.makeTensorInfo(c,s.dtype,u),n.makeTensorInfo([d.length],a.dtype,new Int32Array(d))]}var uj={kernelName:wh,backendName:"cpu",kernelFunc:lj};function cj(e){let{inputs:t,backend:n}=e,{data:s,indices:r,segmentIds:a}=t;if(s.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(a.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
${a.shape}`);let o=n.data.get(s.dataId).values,i=n.data.get(r.dataId).values,l=n.data.get(a.dataId).values,[u,c]=A2(o,s.shape,s.dtype,i,l,!0);return n.makeTensorInfo(c,s.dtype,u)}var dj={kernelName:kh,backendName:"cpu",kernelFunc:cj};function hj(e){let{inputs:t,backend:n}=e,{data:s,indices:r,segmentIds:a}=t;if(s.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(a.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
${a.shape}`);let o=n.data.get(s.dataId).values,i=n.data.get(r.dataId).values,l=n.data.get(a.dataId).values,[u,c]=A2(o,s.shape,s.dtype,i,l);return n.makeTensorInfo(c,s.dtype,u)}var pj={kernelName:Ih,backendName:"cpu",kernelFunc:hj};function fj(e){let{inputs:t,backend:n,attrs:s}=e,{sparseIndices:r,sparseValues:a,defaultValue:o}=t,{outputShape:i}=s,{sliceRank:l,numUpdates:u,sliceSize:c,strides:d,outputSize:h}=D.calculateShapes(a,r,i),p=!1,f=n.bufferSync(r),m=n.bufferSync(a),g=n.data.get(o.dataId).values[0],A=Bw(f,m,i,h,c,u,l,d,g,p);return n.makeTensorInfo(i,A.dtype,A.values)}var mj={kernelName:Sh,backendName:"cpu",kernelFunc:fj};function gj(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{numOrSizeSplits:a,axis:o}=s,i=w.parseAxisParam(o,r.shape)[0],l=D.prepareSplitSize(r,a,i),u=new Array(r.shape.length).fill(0),c=r.shape.slice();return l.map(d=>{let h=[...c];h[i]=d;let p=Zo({inputs:{x:r},backend:n,attrs:{begin:u,size:h}});return u[i]+=d,p})}var Aj={kernelName:Al,backendName:"cpu",kernelFunc:gj},yj={kernelName:qu,backendName:"cpu",kernelFunc:({inputs:e,backend:t})=>{let{x:n}=e,s=t;ke(n,"square");let r=s.data.get(n.dataId).values,a=new Float32Array(r.length);for(let i=0;i<r.length;++i){let l=r[i];a[i]=l*l}return{dataId:s.write(a,n.shape,n.dtype),shape:n.shape,dtype:n.dtype}}},xj=ot(Gr,(e,t)=>{let n=t;return isNaN(e)?NaN:e>0?1:n.alpha}),bj={kernelName:Gr,backendName:"cpu",kernelFunc:xj};function vj(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{begin:a,end:o,strides:i,beginMask:l,endMask:u,ellipsisMask:c,newAxisMask:d,shrinkAxisMask:h}=s;ke(r,"stridedSlice");let{nonStrided:p,$begin:f,$strides:m,size:g,newShape:A,outShape:y}=xn.sliceInfo(r.shape,a,o,i,l,u,c,d,h),x=xt({inputs:{x:r},backend:n,attrs:{shape:A}}),b;if(p){let k=Zo({inputs:{x},backend:n,attrs:{begin:f,size:g}});b=xt({inputs:{x:k},backend:n,attrs:{shape:y}}),n.disposeIntermediateTensorInfo(k)}else if(y.some(k=>k===0))b=n.makeTensorInfo(y,r.dtype,[]);else{let k=n.bufferSync(x),S=mw(y,k,m,f);b=n.makeTensorInfo(S.shape,S.dtype,S.values)}let v=xt({inputs:{x:b},backend:n,attrs:{shape:y}});return n.disposeIntermediateTensorInfo(x),n.disposeIntermediateTensorInfo(b),v}var wj={kernelName:yl,backendName:"cpu",kernelFunc:vj};function kj(e){let{inputs:t,backend:n,attrs:s}=e,{separator:r,nGramWidths:a,leftPad:o,rightPad:i,padWidth:l,preserveShortSequences:u}=s,{data:c,dataSplits:d}=t,h=n.data.get(c.dataId).values,p=n.data.get(d.dataId).values,[f,m]=gw(h,p,r,a,o,i,l,u);return[n.makeTensorInfo([f.length],"string",f),n.makeTensorInfo(d.shape,"int32",m)]}var Ij={kernelName:Ch,backendName:"cpu",kernelFunc:kj};function Sj(e){let{inputs:t,backend:n,attrs:s}=e,{skipEmpty:r}=s,{input:a,delimiter:o}=t;if(a.dtype!=="string")throw new Error("Input must be of datatype string");if(a.shape.length!==1)throw new Error(`Input must be a vector, got shape: ${a.shape}`);if(o.shape.length!==0)throw new Error(`Delimiter must be a scalar, got shape: ${o.shape}`);let i=n.data.get(a.dataId).values,l=n.data.get(o.dataId).values[0],[u,c,d]=Aw(i,l,r),h=c.length;return[n.makeTensorInfo([h,2],"int32",u),n.makeTensorInfo([h],"string",c),n.makeTensorInfo([2],"int32",new Int32Array(d))]}var Cj={kernelName:Th,backendName:"cpu",kernelFunc:Sj};function Tj(e){let{inputs:t,backend:n,attrs:s}=e,{numBuckets:r}=s,{input:a}=t;if(a.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 o=n.data.get(a.dataId).values,i=yw(o,r);return n.makeTensorInfo(a.shape,"int32",i)}var Nj={kernelName:Nh,backendName:"cpu",kernelFunc:Tj},Ej=ot(vo,e=>Math.tan(e)),Rj={kernelName:vo,backendName:"cpu",kernelFunc:Ej},_j=ot(wo,e=>Math.tanh(e)),Dj={kernelName:wo,backendName:"cpu",kernelFunc:_j};function $j(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{reps:a}=s;ke(r,"tile");let o=bw(n.bufferSync(r),a);return n.makeTensorInfo(o.shape,o.dtype,o.values)}var Fj={kernelName:Hr,backendName:"cpu",kernelFunc:$j};function Oj(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{k:a,sorted:o}=s;ke(r,"topk");let i=n.data.get(r.dataId).values,[l,u]=ww(i,r.shape,r.dtype,a,o);return[n.makeTensorInfo(l.shape,l.dtype,l.values),n.makeTensorInfo(u.shape,u.dtype,u.values)]}var Pj={kernelName:xl,backendName:"cpu",kernelFunc:Oj};function Mj(e){let{inputs:t,attrs:n,backend:s}=e,{image:r,transforms:a}=t,{interpolation:o,fillMode:i,fillValue:l,outputShape:u}=n,[c,d,h,p]=r.shape,[f,m]=u!=null?u:[d,h],g=[c,f,m,p],A=w.computeStrides(r.shape),y=A[0],x=A[1],b=A[2],v=w.getTypedArrayFromDType(r.dtype,w.sizeFromShape(g));v.fill(l);let k=s.data.get(r.dataId).values,S=s.data.get(a.dataId).values;for(let _=0;_<c;++_){let O=a.shape[0]===1?S:S.subarray(_*8,_*8+8);for(let E=0;E<f;++E)for(let R=0;R<m;++R)for(let T=0;T<p;++T){let P,V=O[6]*R+O[7]*E+1;if(V===0)continue;let j=(O[0]*R+O[1]*E+O[2])/V,q=(O[3]*R+O[4]*E+O[5])/V,X=Vw(j,h,i),ee=Vw(q,d,i);switch(o){case"nearest":P=Uj(k,d,h,y,x,b,_,ee,X,T,l);break;case"bilinear":P=Hj(k,d,h,y,x,b,_,ee,X,T,l);break;default:throw new Error(`Error in Transform: Expect 'nearest' or 'bilinear', but got ${o}`)}let te=_*y+E*x+R*b+T;v[te]=P}return s.makeTensorInfo(g,r.dtype,v)}return{dataId:s.write(v,g,r.dtype),shape:r.shape,dtype:r.dtype}}var zj={kernelName:bl,backendName:"cpu",kernelFunc:Mj};function Vw(e,t,n){switch(n){case"reflect":return Lj(e,t);case"wrap":return Bj(e,t);case"nearest":return Vj(e,t);case"constant":default:return Wj(e,t)}}function Lj(e,t){let n=e;if(n<0)if(t<=1)n=0;else{let s=2*t;n<s&&(n=s*Math.trunc(-n/s)+n),n=n<-t?n+s:-n-1}else if(n>t-1)if(t<=1)n=0;else{let s=2*t;n-=s*Math.trunc(n/s),n>=t&&(n=s-n-1)}return w.clamp(0,n,t-1)}function Bj(e,t){let n=e;if(n<0)if(t<=1)n=0;else{let s=t-1;n+=t*(Math.trunc(-n/s)+1)}else if(n>t-1)if(t<=1)n=0;else{let s=t-1;n-=t*Math.trunc(n/s)}return w.clamp(0,n,t-1)}function Wj(e,t){return e}function Vj(e,t){return w.clamp(0,e,t-1)}function Hc(e,t,n,s,r,a,o,i,l,u,c){let d=o*s+i*r+l*a+u;return 0<=i&&i<t&&0<=l&&l<n?e[d]:c}function Uj(e,t,n,s,r,a,o,i,l,u,c){let d=Math.round(i),h=Math.round(l);return Hc(e,t,n,s,r,a,o,d,h,u,c)}function Hj(e,t,n,s,r,a,o,i,l,u,c){let d=Math.floor(i),h=Math.floor(l),p=d+1,f=h+1,m=(f-l)*Hc(e,t,n,s,r,a,o,d,h,u,c)+(l-h)*Hc(e,t,n,s,r,a,o,d,f,u,c),g=(f-l)*Hc(e,t,n,s,r,a,o,p,h,u,c)+(l-h)*Hc(e,t,n,s,r,a,o,p,f,u,c);return(p-i)*m+(i-d)*g}function Gj(e){let{inputs:t,attrs:n,backend:s}=e,{axis:r}=n,{x:a}=t;ke(a,"unique");let o=s.data.get(a.dataId).values,{outputValues:i,outputShape:l,indices:u}=kw(o,r,a.shape,a.dtype);return[s.makeTensorInfo(l,a.dtype,i),s.makeTensorInfo([u.length],"int32",u)]}var jj={kernelName:Eh,backendName:"cpu",kernelFunc:Gj};function qj(e){let{inputs:t,backend:n,attrs:s}=e,{value:r}=t,{axis:a}=s;a<0&&(a+=r.shape.length);let o=r.shape.length,i=r.shape[a],l=new Array(o-1),u=0;for(let p=0;p<o;p++)p!==a&&(l[u++]=r.shape[p]);let c=new Array(o).fill(0),d=r.shape.slice();d[a]=1;let h=new Array(i);for(let p=0;p<h.length;p++){c[a]=p;let f=Zo({inputs:{x:r},backend:n,attrs:{begin:c,size:d}});h[p]=xt({inputs:{x:f},backend:n,attrs:{shape:l}}),n.disposeIntermediateTensorInfo(f)}return h}var Xj={kernelName:vl,backendName:"cpu",kernelFunc:qj};function Kj(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,segmentIds:a}=t,{numSegments:o}=s;ke(r,"unsortedSegmentSum");let i=r.shape.length,l=a.shape.length,u=[],c=[],d=i-l,h=a;for(let f=0;f<d;++f){let m=cf({inputs:{input:h},backend:n,attrs:{dim:f+1}});h=m,c.push(m)}for(let f=0;f<o;++f){let m=w.createScalarValue(f,"int32"),g=n.makeTensorInfo([],"int32",m),A=G7({inputs:{a:g,b:h},backend:n}),y=ca({inputs:{x:A},backend:n,attrs:{dtype:"float32"}}),x=lf({inputs:{a:y,b:r},backend:n}),b=Uc({inputs:{x},backend:n,attrs:{axis:0,keepDims:!1}});u.push(b),c.push(g),c.push(A),c.push(y),c.push(x),c.push(b)}let p=zw({inputs:u,backend:n,attrs:{axis:0}});return c.forEach(f=>n.disposeIntermediateTensorInfo(f)),p}var Zj={kernelName:Xu,backendName:"cpu",kernelFunc:Kj},Yj=[rV,ZB,oV,lV,nW,cV,hV,fV,gV,yV,bV,wV,IV,TV,EV,DV,FV,PV,zV,nV,BV,VV,HV,jV,eW,rW,XV,YB,ZV,JV,tU,sU,QV,iU,uU,aU,dU,pU,mU,AU,xU,vU,wU,IU,CU,NU,EU,_U,RU,w2,FU,KW,PU,aW,HU,oW,GU,lW,YU,JU,eH,cW,sH,aH,iH,uH,dH,hW,fW,JB,pH,YV,mH,AH,xH,ZW,gW,yW,vH,bW,kH,CH,NH,_H,$H,OH,wW,zH,BH,VH,HH,jH,PH,XH,ZH,IW,JH,tG,aG,CW,NW,lG,dG,fG,RW,gG,yG,xG,Lw,kG,JW,$W,SG,QB,TG,QW,eV,tV,EG,_G,$G,OG,MG,zG,BG,OW,VG,HG,XG,MW,ZG,JG,ej,zW,sG,sj,aj,ij,uj,dj,pj,mj,Aj,WW,yj,UW,bj,wj,Ij,Cj,Nj,qW,DU,Rj,Dj,Fj,Pj,_W,zj,jj,Xj,Zj,AG];for(let e of Yj)To(e);var Uw={};Pe(Uw,{assertNotComplex:()=>nu,bindCanvasToFramebuffer:()=>uq,bindColorTextureToFramebuffer:()=>mf,bindTextureToProgramUniformSampler:()=>r6,bindTextureUnit:()=>t6,bindVertexBufferToProgramAttribute:()=>T2,callAndCheck:()=>be,canBeRepresented:()=>Hw,createFragmentShader:()=>qw,createFramebuffer:()=>e6,createProgram:()=>Xw,createStaticIndexBuffer:()=>Yw,createStaticVertexBuffer:()=>Zw,createTexture:()=>Jw,createVertexShader:()=>jw,getBatchDim:()=>Jo,getExtensionOrThrow:()=>qc,getFramebufferErrorMessage:()=>a6,getMaxTexturesInShader:()=>u6,getNumChannels:()=>iq,getProgramUniformLocation:()=>s6,getProgramUniformLocationOrThrow:()=>n6,getRowsCols:()=>Qo,getShapeAs3D:()=>gf,getTextureShapeFromLogicalShape:()=>i6,getWebGLDisjointQueryTimerVersion:()=>c6,getWebGLErrorMessage:()=>Gw,getWebGLMaxTextureSize:()=>l6,hasExtension:()=>xs,isCapableOfRenderingToFloatTexture:()=>d6,isDownloadFloatTextureEnabled:()=>h6,isReshapeFree:()=>Kc,isWebGLFenceEnabled:()=>p6,isWebGLVersionEnabled:()=>E2,linkProgram:()=>Kw,resetMaxTextureSize:()=>cq,resetMaxTexturesInShader:()=>dq,unbindColorTextureFromFramebuffer:()=>N2,unbindTextureUnit:()=>lq,validateFramebuffer:()=>Xc,validateProgram:()=>ff,validateTextureSize:()=>Qw});var Yo={},S2={alpha:!1,antialias:!1,premultipliedAlpha:!1,preserveDrawingBuffer:!1,depth:!1,stencil:!1,failIfMajorPerformanceCaveat:!0};function hf(e,t){Yo[e]=t}function dr(e){if(!(e in Yo)){let n=Qj(e);if(n!==null)Yo[e]=n;else return console.log("Could not get context for WebGL version",e),null}let t=Yo[e];return t.isContextLost()?(delete Yo[e],dr(e)):(t.disable(t.DEPTH_TEST),t.disable(t.STENCIL_TEST),t.disable(t.BLEND),t.disable(t.DITHER),t.disable(t.POLYGON_OFFSET_FILL),t.disable(t.SAMPLE_COVERAGE),t.enable(t.SCISSOR_TEST),t.enable(t.CULL_FACE),t.cullFace(t.BACK),Yo[e])}function Jj(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 Qj(e){if(e!==1&&e!==2)throw new Error("Cannot get WebGL rendering context, WebGL is disabled.");let t=Jj(e);return t.addEventListener("webglcontextlost",n=>{n.preventDefault(),delete Yo[e]},!1),e===1?t.getContext("webgl",S2)||t.getContext("experimental-webgl",S2):t.getContext("webgl2",S2)}var Gc;(function(e){e[e.DENSE=0]="DENSE",e[e.SHARED_BATCH=1]="SHARED_BATCH"})(Gc||(Gc={}));var ys;(function(e){e[e.RENDER=0]="RENDER",e[e.UPLOAD=1]="UPLOAD",e[e.PIXELS=2]="PIXELS",e[e.DOWNLOAD=3]="DOWNLOAD"})(ys||(ys={}));var on;(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"})(on||(on={}));function jc(e,t){return[t,e]}function eq(e,t){return e*t}function pf(e){let t=w.sizeFromShape(e),n=Math.ceil(t/4);return w.sizeToSquarishShape(n)}function tu(e,t){return[Math.max(1,Math.ceil(t/2)),Math.max(1,Math.ceil(e/2))]}function tq(e,t){let[n,s]=tu(e,t);return n*s*4}function C2(e,t){let n=e,s,r,a,o,i,l,u,c,d,h;return Q().getNumber("WEBGL_VERSION")===2?(s=n.R32F,r=n.R16F,a=n.RGBA16F,o=n.RGBA32F,i=n.RED,u=4,c=1,d=n.HALF_FLOAT,h=n.FLOAT):(s=e.RGBA,r=e.RGBA,a=e.RGBA,o=n.RGBA,i=e.RGBA,u=4,c=4,d=t!=null?t.HALF_FLOAT_OES:null,h=e.FLOAT),l=e.RGBA,{internalFormatFloat:s,internalFormatHalfFloat:r,internalFormatPackedHalfFloat:a,internalFormatPackedFloat:o,textureFormatFloat:i,downloadTextureFormat:l,downloadUnpackNumChannels:u,defaultNumChannels:c,textureTypeHalfFloat:d,textureTypeFloat:h}}function be(e,t){let n=t();return Q().getBool("DEBUG")&&nq(e),n}function nq(e){let t=e.getError();if(t!==e.NO_ERROR)throw new Error("WebGL Error: "+Gw(e,t))}var sq=596e-10,rq=65504;function Hw(e){return!!(Q().getBool("WEBGL_RENDER_FLOAT32_ENABLED")||e===0||sq<Math.abs(e)&&Math.abs(e)<rq)}function Gw(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 qc(e,t){return _r(e,()=>e.getExtension(t),'Extension "'+t+'" not supported on this browser.')}function jw(e,t){let n=_r(e,()=>e.createShader(e.VERTEX_SHADER),"Unable to create vertex WebGLShader.");if(be(e,()=>e.shaderSource(n,t)),be(e,()=>e.compileShader(n)),e.getShaderParameter(n,e.COMPILE_STATUS)===!1)throw console.log(e.getShaderInfoLog(n)),new Error("Failed to compile vertex shader.");return n}function qw(e,t){let n=_r(e,()=>e.createShader(e.FRAGMENT_SHADER),"Unable to create fragment WebGLShader.");if(be(e,()=>e.shaderSource(n,t)),be(e,()=>e.compileShader(n)),e.getShaderParameter(n,e.COMPILE_STATUS)===!1)throw oq(t,e.getShaderInfoLog(n)),new Error("Failed to compile fragment shader.");return n}var aq=/ERROR: [0-9]+:([0-9]+):/g;function oq(e,t){let n=aq.exec(t);if(n==null){console.log(`Couldn't parse line number in error: ${t}`),console.log(e);return}let s=+n[1],r=e.split(`
`),a=r.length.toString().length+2,o=r.map((d,h)=>w.rightPad((h+1).toString(),a)+d),i=0;for(let d=0;d<o.length;d++)i=Math.max(o[d].length,i);let l=o.slice(0,s-1),u=o.slice(s-1,s),c=o.slice(s);console.log(l.join(`
`)),console.log(t.split(`
`)[0]),console.log(`%c ${w.rightPad(u[0],i)}`,"border:1px solid red; background-color:#e3d2d2; color:#a61717"),console.log(c.join(`
`))}function Xw(e){return _r(e,()=>e.createProgram(),"Unable to create WebGLProgram.")}function Kw(e,t){if(be(e,()=>e.linkProgram(t)),e.getProgramParameter(t,e.LINK_STATUS)===!1)throw console.log(e.getProgramInfoLog(t)),new Error("Failed to link vertex and fragment shaders.")}function ff(e,t){if(be(e,()=>e.validateProgram(t)),e.getProgramParameter(t,e.VALIDATE_STATUS)===!1)throw console.log(e.getProgramInfoLog(t)),new Error("Shader program validation failed.")}function Zw(e,t){let n=_r(e,()=>e.createBuffer(),"Unable to create WebGLBuffer");return be(e,()=>e.bindBuffer(e.ARRAY_BUFFER,n)),be(e,()=>e.bufferData(e.ARRAY_BUFFER,t,e.STATIC_DRAW)),n}function Yw(e,t){let n=_r(e,()=>e.createBuffer(),"Unable to create WebGLBuffer");return be(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,n)),be(e,()=>e.bufferData(e.ELEMENT_ARRAY_BUFFER,t,e.STATIC_DRAW)),n}function iq(){return Q().getNumber("WEBGL_VERSION")===2?1:4}function Jw(e){return _r(e,()=>e.createTexture(),"Unable to create WebGLTexture.")}function Qw(e,t){let n=Q().getNumber("WEBGL_MAX_TEXTURE_SIZE");if(e<=0||t<=0){let s=`[${e}x${t}]`;throw new Error("Requested texture size "+s+" is invalid.")}if(e>n||t>n){let s=`[${e}x${t}]`,r=`[${n}x${n}]`;throw new Error("Requested texture size "+s+" greater than WebGL maximum on this browser / GPU "+r+".")}}function e6(e){return _r(e,()=>e.createFramebuffer(),"Unable to create WebGLFramebuffer.")}function T2(e,t,n,s,r,a,o){let i=e.getAttribLocation(t,n);return i===-1?!1:(be(e,()=>e.bindBuffer(e.ARRAY_BUFFER,s)),be(e,()=>e.vertexAttribPointer(i,r,e.FLOAT,!1,a,o)),be(e,()=>e.enableVertexAttribArray(i)),!0)}function t6(e,t,n){o6(e,n),be(e,()=>e.activeTexture(e.TEXTURE0+n)),be(e,()=>e.bindTexture(e.TEXTURE_2D,t))}function lq(e,t){o6(e,t),be(e,()=>e.activeTexture(e.TEXTURE0+t)),be(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function n6(e,t,n){return _r(e,()=>e.getUniformLocation(t,n),'uniform "'+n+'" not present in program.')}function s6(e,t,n){return e.getUniformLocation(t,n)}function r6(e,t,n,s){be(e,()=>t6(e,t,s)),be(e,()=>e.uniform1i(n,s))}function uq(e){be(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),be(e,()=>e.viewport(0,0,e.canvas.width,e.canvas.height)),be(e,()=>e.scissor(0,0,e.canvas.width,e.canvas.height))}function mf(e,t,n){be(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,n)),be(e,()=>e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,t,0))}function N2(e,t){be(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,t)),be(e,()=>e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,null,0))}function Xc(e){let t=e.checkFramebufferStatus(e.FRAMEBUFFER);if(t!==e.FRAMEBUFFER_COMPLETE)throw new Error("Error binding framebuffer: "+a6(e,t))}function a6(e,t){switch(t){case e.FRAMEBUFFER_INCOMPLETE_ATTACHMENT:return"FRAMEBUFFER_INCOMPLETE_ATTACHMENT";case e.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT:return"FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT";case e.FRAMEBUFFER_INCOMPLETE_DIMENSIONS:return"FRAMEBUFFER_INCOMPLETE_DIMENSIONS";case e.FRAMEBUFFER_UNSUPPORTED:return"FRAMEBUFFER_UNSUPPORTED";default:return`unknown error ${t}`}}function _r(e,t,n){let s=be(e,()=>t());if(s==null)throw new Error(n);return s}function o6(e,t){let n=e.MAX_COMBINED_TEXTURE_IMAGE_UNITS-1,s=t+e.TEXTURE0;if(s<e.TEXTURE0||s>n){let r=`[gl.TEXTURE0, gl.TEXTURE${n}]`;throw new Error(`textureUnit must be in ${r}.`)}}function Jo(e,t=2){return w.sizeFromShape(e.slice(0,e.length-t))}function Qo(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 gf(e){let t=[1,1,1];return e.length===0||e.length===1&&e[0]===1||(t=[Jo(e),...Qo(e)]),t}function i6(e,t=!1){let n=Q().getNumber("WEBGL_MAX_TEXTURE_SIZE");t&&(n=n*2,e=e.map((r,a)=>a>=e.length-2?w.nearestLargerEven(e[a]):e[a]),e.length===1&&(e=[2,e[0]])),e.length!==2&&(e=w.squeezeShape(e).newShape);let s=w.sizeFromShape(e);if(e.length<=1&&s<=n)return[1,s];if(e.length===2&&e[0]<=n&&e[1]<=n)return e;if(e.length===3&&e[0]*e[1]<=n&&e[2]<=n)return[e[0]*e[1],e[2]];if(e.length===3&&e[0]<=n&&e[1]*e[2]<=n)return[e[0],e[1]*e[2]];if(e.length===4&&e[0]*e[1]*e[2]<=n&&e[3]<=n)return[e[0]*e[1]*e[2],e[3]];if(e.length===4&&e[0]<=n&&e[1]*e[2]*e[3]<=n)return[e[0],e[1]*e[2]*e[3]];if(t){let r=Jo(e),a=2,o=2;return e.length&&([a,o]=Qo(e)),s=r*(a/2)*(o/2),w.sizeToSquarishShape(s).map(i=>i*2)}return w.sizeToSquarishShape(s)}function Af(e){return e%2==0}function Kc(e,t){if(e=e.slice(-2),t=t.slice(-2),w.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 n=e.slice(-1)[0],s=t.slice(-1)[0];if(n===s||Af(n)&&Af(s)&&(e[0]===1||t[0]===1))return!0}return e[1]===t[1]&&Af(e[0])&&Af(t[0])}var yf,xf;function l6(e){if(yf==null){let t=dr(e);yf=t.getParameter(t.MAX_TEXTURE_SIZE)}return yf}function cq(){yf=null}function dq(){xf=null}function u6(e){if(xf==null){let t=dr(e);xf=t.getParameter(t.MAX_TEXTURE_IMAGE_UNITS)}return Math.min(16,xf)}function c6(e){if(e===0)return 0;let t,n=dr(e);return xs(n,"EXT_disjoint_timer_query_webgl2")&&e===2?t=2:xs(n,"EXT_disjoint_timer_query")?t=1:t=0,t}function xs(e,t){return e.getExtension(t)!=null}function E2(e){try{if(dr(e)!=null)return!0}catch(t){return console.log("Error when getting WebGL context: ",t),!1}return!1}function d6(e){if(e===0)return!1;let t=dr(e);if(e===1){if(!xs(t,"OES_texture_float"))return!1}else if(!xs(t,"EXT_color_buffer_float"))return!1;return R2(t)}function h6(e){if(e===0)return!1;let t=dr(e);if(e===1){if(!xs(t,"OES_texture_float")||!xs(t,"WEBGL_color_buffer_float"))return!1}else{if(xs(t,"EXT_color_buffer_float"))return R2(t);let s="EXT_color_buffer_half_float";if(xs(t,s)){let r=t.getExtension(s);return hq(t,r)}return!1}return R2(t)}function R2(e){let t=C2(e),n=e.createTexture();e.bindTexture(e.TEXTURE_2D,n);let s=1,r=1;e.texImage2D(e.TEXTURE_2D,0,t.internalFormatFloat,s,r,0,t.textureFormatFloat,t.textureTypeFloat,null);let a=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,a),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(a),o}function hq(e,t){let n=C2(e,t),s=e.createTexture();e.bindTexture(e.TEXTURE_2D,s);let r=1,a=1;e.texImage2D(e.TEXTURE_2D,0,n.internalFormatHalfFloat,r,a,0,n.textureFormatFloat,n.textureTypeHalfFloat,null);let o=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,o),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,s,0);let i=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(s),e.deleteFramebuffer(o),i}function p6(e){return e!==2?!1:dr(e).fenceSync!=null}function nu(e,t){Array.isArray(e)||(e=[e]),e.forEach(n=>{n!=null&&w.assert(n.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the WebGL backend.`)})}var Ne=Q();Ne.registerFlag("HAS_WEBGL",()=>Ne.getNumber("WEBGL_VERSION")>0);Ne.registerFlag("WEBGL_VERSION",()=>E2(2)?2:E2(1)?1:0);Ne.registerFlag("WEBGL_CHECK_NUMERICAL_PROBLEMS",()=>!1);Ne.registerFlag("WEBGL_BUFFER_SUPPORTED",()=>Ne.get("WEBGL_VERSION")===2);Ne.registerFlag("WEBGL_CPU_FORWARD",()=>!0);Ne.registerFlag("WEBGL_FORCE_F16_TEXTURES",()=>!1);Ne.registerFlag("WEBGL_PACK",()=>Ne.getBool("HAS_WEBGL"));Ne.registerFlag("WEBGL_PACK_NORMALIZATION",()=>Ne.getBool("WEBGL_PACK"));Ne.registerFlag("WEBGL_PACK_CLIP",()=>Ne.getBool("WEBGL_PACK"));Ne.registerFlag("WEBGL_PACK_DEPTHWISECONV",()=>Ne.getBool("WEBGL_PACK"));Ne.registerFlag("WEBGL_PACK_BINARY_OPERATIONS",()=>Ne.getBool("WEBGL_PACK"));Ne.registerFlag("WEBGL_PACK_UNARY_OPERATIONS",()=>Ne.getBool("WEBGL_PACK"));Ne.registerFlag("WEBGL_PACK_ARRAY_OPERATIONS",()=>Ne.getBool("WEBGL_PACK"));Ne.registerFlag("WEBGL_PACK_IMAGE_OPERATIONS",()=>Ne.getBool("WEBGL_PACK"));Ne.registerFlag("WEBGL_PACK_REDUCE",()=>Ne.getBool("WEBGL_PACK"));Ne.registerFlag("WEBGL_LAZILY_UNPACK",()=>Ne.getBool("WEBGL_PACK"));Ne.registerFlag("WEBGL_CONV_IM2COL",()=>Ne.getBool("WEBGL_PACK"));Ne.registerFlag("WEBGL_MAX_TEXTURE_SIZE",()=>l6(Ne.getNumber("WEBGL_VERSION")));Ne.registerFlag("WEBGL_MAX_TEXTURES_IN_SHADER",()=>u6(Ne.getNumber("WEBGL_VERSION")));Ne.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION",()=>{let e=Ne.getNumber("WEBGL_VERSION");return e===0?0:c6(e)});Ne.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE",()=>Ne.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0&&!rc.isMobile());Ne.registerFlag("WEBGL_RENDER_FLOAT32_CAPABLE",()=>d6(Ne.getNumber("WEBGL_VERSION")));Ne.registerFlag("WEBGL_RENDER_FLOAT32_ENABLED",()=>Ne.getBool("WEBGL_FORCE_F16_TEXTURES")?!1:Ne.getBool("WEBGL_RENDER_FLOAT32_CAPABLE"));Ne.registerFlag("WEBGL_DOWNLOAD_FLOAT_ENABLED",()=>h6(Ne.getNumber("WEBGL_VERSION")));Ne.registerFlag("WEBGL_FENCE_API_ENABLED",()=>p6(Ne.getNumber("WEBGL_VERSION")));Ne.registerFlag("WEBGL_SIZE_UPLOAD_UNIFORM",()=>Ne.getBool("WEBGL_RENDER_FLOAT32_ENABLED")?4:0);Ne.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}.`)});Ne.registerFlag("WEBGL_FLUSH_THRESHOLD",()=>rc.isMobile()&&Ne.getBool("IS_CHROME")?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}.`)});Ne.registerFlag("CPU_HANDOFF_SIZE_THRESHOLD",()=>128);Ne.registerFlag("WEBGL_USE_SHAPES_UNIFORMS",()=>!1);Ne.registerFlag("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD",()=>1e5);Ne.registerFlag("TOPK_K_CPU_HANDOFF_THRESHOLD",()=>128);function kn(){let e,t,n,s,r,a,o,i,l,u;return Q().getNumber("WEBGL_VERSION")===2?(e="#version 300 es",t="in",n="out",s="in",r="texture",a="outputColor",o="out vec4 outputColor;",i=`
bool isnan_custom(float val) {
return (val > 0.0 || val < 0.0) ? false : val != 0.0;
}
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",n="varying",s="varying",r="texture2D",a="gl_FragColor",o="",i=`
#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:n,varyingFs:s,texture2D:r,output:a,defineOutput:o,defineSpecialNaN:i,defineSpecialInf:l,defineRound:u}}function ei(e,t,n="index"){let s=w.computeStrides(t);return s.map((r,a)=>{let o=`int ${e[a]} = ${n} / ${r}`,i=a===s.length-1?`int ${e[a+1]} = ${n} - ${e[a]} * ${r}`:`index -= ${e[a]} * ${r}`;return`${o}; ${i};`}).join("")}function bf(e,t,n="index"){let s=w.computeStrides(t);return s.map((r,a)=>{let o=`int ${e[a]} = ${n} / outShapeStrides[${a}]`,i=a===s.length-1?`int ${e[a+1]} = ${n} - ${e[a]} * outShapeStrides[${a}]`:`index -= ${e[a]} * outShapeStrides[${a}]`;return`${o}; ${i};`}).join("")}function pq(e,t){let n=e.length,s=e.map(a=>`${t}[${a}]`),r=new Array(n-1);r[n-2]=s[n-1];for(let a=n-3;a>=0;--a)r[a]=`(${r[a+1]} * ${s[a+1]})`;return r}function fq(e,t,n="index"){let s=e.map((a,o)=>o),r=pq(s,t);return r.map((a,o)=>{let i=`int ${e[o]} = ${n} / ${r[o]}`,l=o===r.length-1?`int ${e[o+1]} = ${n} - ${e[o]} * ${r[o]}`:`index -= ${e[o]} * ${r[o]}`;return`${i}; ${l};`}).join("")}function _2(e){let t=w.computeStrides(e).map(n=>n.toString());return`
int getFlatIndex(ivec3 coords) {
return coords.x * ${t[0]} + coords.y * ${t[1]} + coords.z;
}
`}function D2(){return`
int getFlatIndex(ivec3 coords) {
return coords.x * outShapeStrides[0] + coords.y * outShapeStrides[1] + coords.z;
}
`}var f6=`
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:m6}=D;function mq(e,t,n){let s=[];if(e.forEach(p=>{let f=w.sizeFromShape(p.shapeInfo.logicalShape);if(p.shapeInfo.isUniform?s.push(`uniform float ${p.name}${f>1?`[${f}]`:""};`):(s.push(`uniform sampler2D ${p.name};`),s.push(`uniform int offset${p.name};`)),n.enableShapeUniforms){let{uniformShape:m}=$2(n.packedInputs,p.shapeInfo.logicalShape,p.shapeInfo.texShape);switch(m.length){case 1:s.push(`uniform int ${p.name}Shape;`);break;case 2:s.push(`uniform ivec2 ${p.name}Shape;`);break;case 3:s.push(`uniform ivec3 ${p.name}Shape;`);break;case 4:s.push(`uniform ivec4 ${p.name}Shape;`);break;default:break}s.push(`uniform ivec2 ${p.name}TexShape;`)}}),n.enableShapeUniforms){switch(t.logicalShape.length){case 1:s.push("uniform int outShape;");break;case 2:s.push("uniform ivec2 outShape;"),s.push("uniform int outShapeStrides;");break;case 3:s.push("uniform ivec3 outShape;"),s.push("uniform ivec2 outShapeStrides;");break;case 4:s.push("uniform ivec4 outShape;"),s.push("uniform ivec3 outShapeStrides;");break;default:break}s.push("uniform ivec2 outTexShape;")}n.customUniforms&&n.customUniforms.forEach(p=>{s.push(`uniform ${p.type} ${p.name}${p.arrayIndex?`[${p.arrayIndex}]`:""};`)});let r=s.join(`
`),a=e.map(p=>gq(p,t,n.packedInputs,n.enableShapeUniforms)).join(`
`),o=t.texShape,i=kn(),l=xq(i),u,c,d=wq(i);return t.isPacked?(u=Aq(t.logicalShape,o,n.enableShapeUniforms),c=vq(i)):(u=yq(t.logicalShape,o,n.enableShapeUniforms),c=bq(i)),n.packedInputs&&(d+=Cq),[d,l,c,r,u,a,n.userCode].join(`
`)}function su(e,t=!1){let n=e.shapeInfo.logicalShape;switch(n.length){case 0:return zq(e,t);case 1:return Bq(e,t);case 2:return Vq(e,t);case 3:return Hq(e,t);case 4:return jq(e,t);case 5:return qq(e);case 6:return Xq(e);default:throw new Error(`${n.length}-D input sampling is not yet supported`)}}function g6(e,t){switch(e.shapeInfo.logicalShape.length){case 0:return Mq(e);case 1:return Lq(e,t);case 2:return Wq(e,t);case 3:return Uq(e,t);default:return Gq(e,t)}}function gq(e,t,n=!1,s){let r="";n?r+=g6(e,s):r+=su(e,s);let a=e.shapeInfo.logicalShape,o=t.logicalShape;return a.length<=o.length&&(n?r+=Kq(e,t):r+=Zq(e,t)),r}function Aq(e,t,n){switch(e.length){case 0:return A6();case 1:return Tq(e,t,n);case 2:return Oq(e,t,n);case 3:return Eq(e,t,n);default:return _q(e,t,n)}}function yq(e,t,n){switch(e.length){case 0:return A6();case 1:return Nq(e,t,n);case 2:return Pq(e,t,n);case 3:return Rq(e,t,n);case 4:return Dq(e,t,n);case 5:return $q(e,t);case 6:return Fq(e,t);default:throw new Error(`${e.length}-D output sampling is not yet supported`)}}function xq(e){return`
float sampleTexture(sampler2D textureSampler, vec2 uv) {
return ${e.texture2D}(textureSampler, uv).r;
}
`}function bq(e){return`
void setOutput(float val) {
${e.output} = vec4(val, 0, 0, 0);
}
`}function vq(e){return`
void setOutput(vec4 val) {
${e.output} = val;
}
`}function wq(e){return`${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);
}
${kq}
${Iq}
${Sq}
`}var kq=`
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);
}
`,Iq=`
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);
}
`,Sq=`
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);
}
`,Cq=`
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 Tq(e,t,n){let s=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];return s[0]===1?n?`
int getOutputCoords() {
return 2 * int(resultUV.x * ceil(float(outTexShape[1]) / 2.0));
}
`:`
int getOutputCoords() {
return 2 * int(resultUV.x * ${s[1]}.0);
}
`:s[1]===1?n?`
int getOutputCoords() {
return 2 * int(resultUV.y * ceil(float(outTexShape[0]) / 2.0));
}
`:`
int getOutputCoords() {
return 2 * int(resultUV.y * ${s[0]}.0);
}
`:n?`
int getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(packedTexShape[0], packedTexShape[1]));
return 2 * (resTexRC.x * packedTexShape[1] + resTexRC.y);
}
`:`
int getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${s[0]}, ${s[1]}));
return 2 * (resTexRC.x * ${s[1]} + resTexRC.y);
}
`}function Nq(e,t,n){return t[0]===1?n?`
int getOutputCoords() {
return int(resultUV.x * float(outTexShape[1]));
}
`:`
int getOutputCoords() {
return int(resultUV.x * ${t[1]}.0);
}
`:t[1]===1?n?`
int getOutputCoords() {
return int(resultUV.y * float(outTexShape[0]));
}
`:`
int getOutputCoords() {
return int(resultUV.y * ${t[0]}.0);
}
`:n?`
int getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
return resTexRC.x * outTexShape[1] + resTexRC.y;
}
`:`
int getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
return resTexRC.x * ${t[1]} + resTexRC.y;
}
`}function Eq(e,t,n){if(n)return`
ivec3 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
int texelsInLogicalRow = int(ceil(float(outShape[2]) / 2.0));
int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[1]) / 2.0));
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(packedTexShape[0], packedTexShape[1]));
int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
int b = index / texelsInBatch;
index -= b * texelsInBatch;
int r = 2 * (index / texelsInLogicalRow);
int c = imod(index, texelsInLogicalRow) * 2;
return ivec3(b, r, c);
}
`;let s=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[2]/2),a=r*Math.ceil(e[1]/2);return`
ivec3 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${s[0]}, ${s[1]}));
int index = resTexRC.x * ${s[1]} + resTexRC.y;
int b = index / ${a};
index -= b * ${a};
int r = 2 * (index / ${r});
int c = imod(index, ${r}) * 2;
return ivec3(b, r, c);
}
`}function Rq(e,t,n){if(n)return`
ivec3 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
int index = resTexRC.x * outTexShape[1] + resTexRC.y;
${bf(["r","c","d"],e)}
return ivec3(r, c, d);
}
`;let s=ei(["r","c","d"],e);return`
ivec3 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${s}
return ivec3(r, c, d);
}
`}function _q(e,t,n){if(n)return`
ivec4 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(packedTexShape[0], packedTexShape[1]));
int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
int texelsInLogicalRow = int(ceil(float(outShape[3]) / 2.0));
int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[2]) / 2.0));
int texelsInBatchN = texelsInBatch * outShape[1];
int b2 = index / texelsInBatchN;
index -= b2 * texelsInBatchN;
int b = index / texelsInBatch;
index -= b * texelsInBatch;
int r = 2 * (index / texelsInLogicalRow);
int c = imod(index, texelsInLogicalRow) * 2;
return ivec4(b2, b, r, c);
}
`;let s=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[e.length-1]/2),a=r*Math.ceil(e[e.length-2]/2),o=a,i="",l="b, r, c";for(let u=2;u<e.length-1;u++)o*=e[e.length-u-1],i=`
int b${u} = index / ${o};
index -= b${u} * ${o};
`+i,l=`b${u}, `+l;return`
ivec${e.length} getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${s[0]}, ${s[1]}));
int index = resTexRC.x * ${s[1]} + resTexRC.y;
${i}
int b = index / ${a};
index -= b * ${a};
int r = 2 * (index / ${r});
int c = imod(index, ${r}) * 2;
return ivec${e.length}(${l});
}
`}function Dq(e,t,n){if(n)return`
ivec4 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
int index = resTexRC.x * outTexShape[1] + resTexRC.y;
${bf(["r","c","d","d2"],e)}
return ivec4(r, c, d, d2);
}
`;let s=ei(["r","c","d","d2"],e);return`
ivec4 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${s}
return ivec4(r, c, d, d2);
}
`}function $q(e,t){let n=ei(["r","c","d","d2","d3"],e);return`
ivec5 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx * vec2(${t[0]},
${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${n}
ivec5 outShape = ivec5(r, c, d, d2, d3);
return outShape;
}
`}function Fq(e,t){let n=ei(["r","c","d","d2","d3","d4"],e);return`
ivec6 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${n}
ivec6 result = ivec6(r, c, d, d2, d3, d4);
return result;
}
`}function Oq(e,t,n){let s=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(w.arraysEqual(e,t))return n?`
ivec2 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
return 2 * ivec2(resultUV.yx * vec2(packedTexShape[0], packedTexShape[1]));
}
`:`
ivec2 getOutputCoords() {
return 2 * ivec2(resultUV.yx * vec2(${s[0]}, ${s[1]}));
}
`;let r=Math.ceil(e[1]/2);return n?`
ivec2 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
int texelsInLogicalRow = int(ceil(float(outShape[1]) / 2.0));
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(packedTexShape[0], packedTexShape[1]));
int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
int r = 2 * (index / texelsInLogicalRow);
int c = imod(index, texelsInLogicalRow) * 2;
return ivec2(r, c);
}
`:`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${s[0]}, ${s[1]}));
int index = resTexRC.x * ${s[1]} + resTexRC.y;
int r = 2 * (index / ${r});
int c = imod(index, ${r}) * 2;
return ivec2(r, c);
}
`}function Pq(e,t,n){return w.arraysEqual(e,t)?n?`
ivec2 getOutputCoords() {
return ivec2(resultUV.yx * vec2(outTexShape[0], outTexShape[1]));
}
`:`
ivec2 getOutputCoords() {
return ivec2(resultUV.yx * vec2(${t[0]}, ${t[1]}));
}
`:e[1]===1?n?`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
int index = resTexRC.x * outTexShape[1] + resTexRC.y;
return ivec2(index, 0);
}
`:`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
return ivec2(index, 0);
}
`:e[0]===1?n?`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
int index = resTexRC.x * outTexShape[1] + resTexRC.y;
return ivec2(0, index);
}
`:`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
return ivec2(0, index);
}
`:n?`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
int index = resTexRC.x * outTexShape[1] + resTexRC.y;
int r = index / outShape[1];
int c = index - r * outShape[1];
return ivec2(r, c);
}
`:`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
int r = index / ${e[1]};
int c = index - r * ${e[1]};
return ivec2(r, c);
}
`}function ti(e){return`offset${e}`}function Mq(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),s=kn();return`
vec4 ${n}() {
return ${s.texture2D}(${t}, halfCR);
}
`}function zq(e,t){let n=e.name,s="get"+n.charAt(0).toUpperCase()+n.slice(1);if(e.shapeInfo.isUniform)return`float ${s}() {return ${n};}`;let[r,a]=e.shapeInfo.texShape;if(r===1&&a===1)return`
float ${s}() {
return sampleTexture(${n}, halfCR);
}
`;let o=ti(n);if(t)return`
float ${s}() {
vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], ${o});
return sampleTexture(${n}, uv);
}
`;let[i,l]=e.shapeInfo.texShape;return`
float ${s}() {
vec2 uv = uvFromFlat(${i}, ${l}, ${o});
return sampleTexture(${n}, uv);
}
`}function Lq(e,t){let n=e.name,s="get"+n.charAt(0).toUpperCase()+n.slice(1),r=e.shapeInfo.texShape,a=kn();if(t)return`
vec4 ${s}(int index) {
ivec2 packedTexShape = ivec2(ceil(float(${n}TexShape[0]) / 2.0), ceil(float(${n}TexShape[1]) / 2.0));
vec2 uv = packedUVfrom1D(
packedTexShape[0], packedTexShape[1], index);
return ${a.texture2D}(${n}, uv);
}
`;let o=[Math.ceil(r[0]/2),Math.ceil(r[1]/2)];return`
vec4 ${s}(int index) {
vec2 uv = packedUVfrom1D(
${o[0]}, ${o[1]}, index);
return ${a.texture2D}(${n}, uv);
}
`}function Bq(e,t){let n=e.name,s="get"+n.charAt(0).toUpperCase()+n.slice(1);if(e.shapeInfo.isUniform)return`
float ${s}(int index) {
${ru(e)}
}
`;let r=e.shapeInfo.texShape,a=r[0],o=r[1];if(o===1&&a===1)return`
float ${s}(int index) {
return sampleTexture(${n}, halfCR);
}
`;let i=ti(n);return o===1?t?`
float ${s}(int index) {
vec2 uv = vec2(0.5, (float(index + ${i}) + 0.5) / float(${n}TexShape[0]));
return sampleTexture(${n}, uv);
}
`:`
float ${s}(int index) {
vec2 uv = vec2(0.5, (float(index + ${i}) + 0.5) / ${a}.0);
return sampleTexture(${n}, uv);
}
`:a===1?t?`
float ${s}(int index) {
vec2 uv = vec2((float(index + ${i}) + 0.5) / float(${n}TexShape[1]), 0.5);
return sampleTexture(${n}, uv);
}
`:`
float ${s}(int index) {
vec2 uv = vec2((float(index + ${i}) + 0.5) / ${o}.0, 0.5);
return sampleTexture(${n}, uv);
}
`:t?`
float ${s}(int index) {
vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], index + ${i});
return sampleTexture(${n}, uv);
}
`:`
float ${s}(int index) {
vec2 uv = uvFromFlat(${a}, ${o}, index + ${i});
return sampleTexture(${n}, uv);
}
`}function Wq(e,t){let n=e.shapeInfo.logicalShape,s=e.name,r="get"+s.charAt(0).toUpperCase()+s.slice(1),a=e.shapeInfo.texShape,o=a[0],i=a[1],l=kn();if(a!=null&&w.arraysEqual(n,a))return t?`
vec4 ${r}(int row, int col) {
vec2 uv = (vec2(col, row) + halfCR) / vec2(${s}TexShape[1], ${s}TexShape[0]);
return ${l.texture2D}(${s}, uv);
}
`:`
vec4 ${r}(int row, int col) {
vec2 uv = (vec2(col, row) + halfCR) / vec2(${i}.0, ${o}.0);
return ${l.texture2D}(${s}, uv);
}
`;if(t)return`
vec4 ${r}(int row, int col) {
ivec2 packedTexShape = ivec2(ceil(float(${s}TexShape[0]) / 2.0), ceil(float(${s}TexShape[1]) / 2.0));
int valuesPerRow = int(ceil(float(${s}Shape[1]) / 2.0));
vec2 uv = packedUVfrom2D(valuesPerRow, packedTexShape[0], packedTexShape[1], row, col);
return ${l.texture2D}(${s}, uv);
}
`;let u=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)],c=Math.ceil(n[1]/2);return`
vec4 ${r}(int row, int col) {
vec2 uv = packedUVfrom2D(${c}, ${u[0]}, ${u[1]}, row, col);
return ${l.texture2D}(${s}, uv);
}
`}function Vq(e,t){let n=e.shapeInfo.logicalShape,s=e.name,r="get"+s.charAt(0).toUpperCase()+s.slice(1),a=e.shapeInfo.texShape;if(a!=null&&w.arraysEqual(n,a)){if(t)return`
float ${r}(int row, int col) {
vec2 uv = (vec2(col, row) + halfCR) / vec2(${s}TexShape[1], ${s}TexShape[0]);
return sampleTexture(${s}, uv);
}
`;let h=a[0],p=a[1];return`
float ${r}(int row, int col) {
vec2 uv = (vec2(col, row) + halfCR) / vec2(${p}.0, ${h}.0);
return sampleTexture(${s}, uv);
}
`}let{newShape:o,keptDims:i}=w.squeezeShape(n),l=o;if(l.length<n.length){let h=au(e,l),p=["row","col"];return`
${su(h,t)}
float ${r}(int row, int col) {
return ${r}(${ou(p,i)});
}
`}if(e.shapeInfo.isUniform)return`
float ${r}(int row, int col) {
int index = round(dot(vec2(row, col), vec2(${n[1]}, 1)));
${ru(e)}
}
`;let u=a[0],c=a[1],d=ti(s);return c===1?t?`
float ${r}(int row, int col) {
float index = dot(vec3(row, col, ${d}), vec3(${s}Shape[1], 1, 1));
vec2 uv = vec2(0.5, (index + 0.5) / float(${s}TexShape[0]));
return sampleTexture(${s}, uv);
}
`:`
float ${r}(int row, int col) {
float index = dot(vec3(row, col, ${d}), vec3(${n[1]}, 1, 1));
vec2 uv = vec2(0.5, (index + 0.5) / ${u}.0);
return sampleTexture(${s}, uv);
}
`:u===1?t?`
float ${r}(int row, int col) {
float index = dot(vec3(row, col, ${d}), vec3(${s}Shape[1], 1, 1));
vec2 uv = vec2((index + 0.5) / float(${s}TexShape[1]), 0.5);
return sampleTexture(${s}, uv);
}
`:`
float ${r}(int row, int col) {
float index = dot(vec3(row, col, ${d}), vec3(${n[1]}, 1, 1));
vec2 uv = vec2((index + 0.5) / ${c}.0, 0.5);
return sampleTexture(${s}, uv);
}
`:t?`
float ${r}(int row, int col) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${s}Shape[1] + col + ${d};
vec2 uv = uvFromFlat(${s}TexShape[0], ${s}TexShape[1], index);
return sampleTexture(${s}, uv);
}
`:`
float ${r}(int row, int col) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${n[1]} + col + ${d};
vec2 uv = uvFromFlat(${u}, ${c}, index);
return sampleTexture(${s}, uv);
}
`}function Uq(e,t){let n=e.shapeInfo.logicalShape,s=e.name,r="get"+s.charAt(0).toUpperCase()+s.slice(1),a=e.shapeInfo.texShape,o=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)];if(n[0]===1){let h=n.slice(1),p=[1,2],f=au(e,h),m=["b","row","col"];return`
${g6(f,t)}
vec4 ${r}(int b, int row, int col) {
return ${r}(${ou(m,p)});
}
`}let i=kn();if(t)return`
vec4 ${r}(int b, int row, int col) {
ivec2 packedTexShape = ivec2(ceil(float(${s}TexShape[0]) / 2.0), ceil(float(${s}TexShape[1]) / 2.0));
int valuesPerRow = int(ceil(float(${s}Shape[2]) / 2.0));
int texelsInBatch = valuesPerRow * int(ceil(float(${s}Shape[1]) / 2.0));
vec2 uv = packedUVfrom3D(
packedTexShape[0], packedTexShape[1], texelsInBatch, valuesPerRow, b, row, col);
return ${i.texture2D}(${s}, uv);
}
`;let l=o[0],u=o[1],c=Math.ceil(n[2]/2),d=c*Math.ceil(n[1]/2);return`
vec4 ${r}(int b, int row, int col) {
vec2 uv = packedUVfrom3D(
${l}, ${u}, ${d}, ${c}, b, row, col);
return ${i.texture2D}(${s}, uv);
}
`}function Hq(e,t){let n=e.shapeInfo.logicalShape,s=e.name,r="get"+s.charAt(0).toUpperCase()+s.slice(1),a=n[1]*n[2],o=n[2],{newShape:i,keptDims:l}=w.squeezeShape(n),u=i;if(u.length<n.length){let m=au(e,u),g=["row","col","depth"];return`
${su(m,t)}
float ${r}(int row, int col, int depth) {
return ${r}(${ou(g,l)});
}
`}if(e.shapeInfo.isUniform)return`
float ${r}(int row, int col, int depth) {
int index = round(dot(vec3(row, col, depth),
vec3(${a}, ${o}, 1)));
${ru(e)}
}
`;let c=e.shapeInfo.texShape,d=c[0],h=c[1],p=e.shapeInfo.flatOffset;if(h===a&&p==null)return t?`
float ${r}(int row, int col, int depth) {
int stride1 = ${s}Shape[2];
float texR = float(row);
float texC = dot(vec2(col, depth), vec2(stride1, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${s}TexShape[1], ${s}TexShape[0]);
return sampleTexture(${s}, uv);
}
`:`
float ${r}(int row, int col, int depth) {
float texR = float(row);
float texC = dot(vec2(col, depth), vec2(${o}, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${h}.0, ${d}.0);
return sampleTexture(${s}, uv);
}
`;if(h===o&&p==null)return t?`
float ${r}(int row, int col, int depth) {
float texR = dot(vec2(row, col), vec2(${s}Shape[1], 1));
float texC = float(depth);
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${s}TexShape[1], ${s}TexShape[0]);
return sampleTexture(${s}, uv);
}
`:`
float ${r}(int row, int col, int depth) {
float texR = dot(vec2(row, col), vec2(${n[1]}, 1));
float texC = float(depth);
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${h}.0, ${d}.0);
return sampleTexture(${s}, uv);
}
`;let f=ti(s);return t?`
float ${r}(int row, int col, int depth) {
// Explicitly use integer operations as dot() only works on floats.
int stride0 = ${s}Shape[1] * ${s}Shape[2];
int stride1 = ${s}Shape[2];
int index = row * ${a} + col * ${o} + depth + ${f};
vec2 uv = uvFromFlat(${s}TexShape[0], ${s}TexShape[1], index);
return sampleTexture(${s}, uv);
}
`:`
float ${r}(int row, int col, int depth) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${a} + col * ${o} + depth + ${f};
vec2 uv = uvFromFlat(${d}, ${h}, index);
return sampleTexture(${s}, uv);
}
`}function Gq(e,t){let n=e.name,s="get"+n.charAt(0).toUpperCase()+n.slice(1),r=kn();if(t)return`
vec4 ${s}(int b2, int b, int row, int col) {
int valuesPerRow = int(ceil(float(${n}Shape[3]) / 2.0));
int texelsInBatch = valuesPerRow * int(ceil(float(${n}Shape[2]) / 2.0));
int index = b * texelsInBatch + (row / 2) * valuesPerRow + (col / 2);
texelsInBatch *= ${n}Shape[1];
index = b2 * texelsInBatch + index;
ivec2 packedTexShape = ivec2(ceil(float(${n}TexShape[0]) / 2.0), ceil(float(${n}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 ${r.texture2D}(${n}, uv);
}
`;let a=e.shapeInfo.logicalShape,o=a.length,i=e.shapeInfo.texShape,l=[Math.ceil(i[0]/2),Math.ceil(i[1]/2)],u=l[0],c=l[1],d=Math.ceil(a[o-1]/2),h=d*Math.ceil(a[o-2]/2),p="int b, int row, int col",f=`b * ${h} + (row / 2) * ${d} + (col / 2)`;for(let m=2;m<o-1;m++)p=`int b${m}, `+p,h*=a[o-m-1],f=`b${m} * ${h} + `+f;return`
vec4 ${s}(${p}) {
int index = ${f};
int texR = index / ${c};
int texC = index - texR * ${c};
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${c}, ${u});
return ${r.texture2D}(${n}, uv);
}
`}function jq(e,t){let n=e.shapeInfo.logicalShape,s=e.name,r="get"+s.charAt(0).toUpperCase()+s.slice(1),a=n[3],o=n[2]*a,i=n[1]*o,{newShape:l,keptDims:u}=w.squeezeShape(n);if(l.length<n.length){let y=au(e,l),x=["row","col","depth","depth2"];return`
${su(y,t)}
float ${r}(int row, int col, int depth, int depth2) {
return ${r}(${ou(x,u)});
}
`}if(e.shapeInfo.isUniform)return`
float ${r}(int row, int col, int depth, int depth2) {
int index = round(dot(vec4(row, col, depth, depth2),
vec4(${i}, ${o}, ${a}, 1)));
${ru(e)}
}
`;let c=e.shapeInfo.flatOffset,d=e.shapeInfo.texShape,h=d[0],p=d[1],f=`int stride2 = ${s}Shape[3];`,m=`int stride1 = ${s}Shape[2] * stride2;`,g=`int stride0 = ${s}Shape[1] * stride1;`;if(p===i&&c==null)return t?`
float ${r}(int row, int col, int depth, int depth2) {
${f}
${m}
float texR = float(row);
float texC =
dot(vec3(col, depth, depth2),
vec3(stride1, stride2, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${s}TexShape[1], ${s}TexShape[0]);
return sampleTexture(${s}, uv);
}
`:`
float ${r}(int row, int col, int depth, int depth2) {
float texR = float(row);
float texC =
dot(vec3(col, depth, depth2),
vec3(${o}, ${a}, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${p}.0, ${h}.0);
return sampleTexture(${s}, uv);
}
`;if(p===a&&c==null)return t?`
float ${r}(int row, int col, int depth, int depth2) {
float texR = dot(vec3(row, col, depth),
vec3(${s}Shape[1] * ${s}Shape[2], ${s}Shape[2], 1));
float texC = float(depth2);
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${s}TexShape[1], ${s}TexShape[0]);
return sampleTexture(${s}, uv);
}
`:`
float ${r}(int row, int col, int depth, int depth2) {
float texR = dot(vec3(row, col, depth),
vec3(${n[1]*n[2]}, ${n[2]}, 1));
float texC = float(depth2);
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${p}.0, ${h}.0);
return sampleTexture(${s}, uv);
}
`;let A=ti(s);return t?`
float ${r}(int row, int col, int depth, int depth2) {
// Explicitly use integer operations as dot() only works on floats.
${f}
${m}
${g}
int index = row * stride0 + col * stride1 +
depth * stride2 + depth2;
vec2 uv = uvFromFlat(${s}TexShape[0], ${s}TexShape[1], index + ${A});
return sampleTexture(${s}, uv);
}
`:`
float ${r}(int row, int col, int depth, int depth2) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${i} + col * ${o} +
depth * ${a} + depth2;
vec2 uv = uvFromFlat(${h}, ${p}, index + ${A});
return sampleTexture(${s}, uv);
}
`}function qq(e){let t=e.shapeInfo.logicalShape,n=e.name,s="get"+n.charAt(0).toUpperCase()+n.slice(1),r=t[4],a=t[3]*r,o=t[2]*a,i=t[1]*o,{newShape:l,keptDims:u}=w.squeezeShape(t);if(l.length<t.length){let m=au(e,l),g=["row","col","depth","depth2","depth3"];return`
${su(m)}
float ${s}(int row, int col, int depth, int depth2, int depth3) {
return ${s}(${ou(g,u)});
}
`}if(e.shapeInfo.isUniform)return`
float ${s}(int row, int col, int depth, int depth2, int depth3) {
float index = dot(
vec4(row, col, depth, depth2),
vec4(${i}, ${o}, ${a}, ${r})) +
depth3;
${ru(e)}
}
`;let c=e.shapeInfo.flatOffset,d=e.shapeInfo.texShape,h=d[0],p=d[1];if(p===i&&c==null)return`
float ${s}(int row, int col, int depth, int depth2, int depth3) {
int texR = row;
float texC = dot(vec4(col, depth, depth2, depth3),
vec4(${o}, ${a}, ${r}, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${p}.0, ${h}.0);
return sampleTexture(${n}, uv);
}
`;if(p===r&&c==null)return`
float ${s}(int row, int col, int depth, int depth2, int depth3) {
float texR = dot(
vec4(row, col, depth, depth2),
vec4(${t[1]*t[2]*t[3]},
${t[2]*t[3]}, ${t[3]}, 1));
int texC = depth3;
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${p}.0, ${h}.0);
return sampleTexture(${n}, uv);
}
`;let f=ti(n);return`
float ${s}(int row, int col, int depth, int depth2, int depth3) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${i} + col * ${o} + depth * ${a} +
depth2 * ${r} + depth3 + ${f};
vec2 uv = uvFromFlat(${h}, ${p}, index);
return sampleTexture(${n}, uv);
}
`}function Xq(e){let t=e.shapeInfo.logicalShape,n=e.name,s="get"+n.charAt(0).toUpperCase()+n.slice(1),{newShape:r,keptDims:a}=w.squeezeShape(t);if(r.length<t.length){let g=au(e,r),A=["row","col","depth","depth2","depth3","depth4"];return`
${su(g)}
float ${s}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
return ${s}(${ou(A,a)});
}
`}let o=t[5],i=t[4]*o,l=t[3]*i,u=t[2]*l,c=t[1]*u;if(e.shapeInfo.isUniform)return`
float ${s}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
int index = round(dot(
vec4(row, col, depth, depth2),
vec4(${c}, ${u}, ${l}, ${i})) +
dot(
vec2(depth3, depth4),
vec2(${o}, 1)));
${ru(e)}
}
`;let d=e.shapeInfo.flatOffset,h=e.shapeInfo.texShape,p=h[0],f=h[1];if(f===c&&d==null)return`
float ${s}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
int texR = row;
float texC = dot(vec4(col, depth, depth2, depth3),
vec4(${u}, ${l}, ${i}, ${o})) +
float(depth4);
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${f}.0, ${p}.0);
return sampleTexture(${n}, uv);
}
`;if(f===o&&d==null)return`
float ${s}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
float texR = dot(vec4(row, col, depth, depth2),
vec4(${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, ${p}.0);
return sampleTexture(${n}, uv);
}
`;let m=ti(n);return`
float ${s}(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 * ${c} + col * ${u} + depth * ${l} +
depth2 * ${i} + depth3 * ${o} + depth4 + ${m};
vec2 uv = uvFromFlat(${p}, ${f}, index);
return sampleTexture(${n}, uv);
}
`}function ru(e){let t=e.name,n=w.sizeFromShape(e.shapeInfo.logicalShape);return n<2?`return ${t};`:`
for (int i = 0; i < ${n}; i++) {
if (i == index) {
return ${t}[i];
}
}
`}function Kq(e,t){let n=e.name,s=n.charAt(0).toUpperCase()+n.slice(1),r="get"+s+"AtOutCoords",a=e.shapeInfo.logicalShape.length,o=t.logicalShape.length,i=m6(e.shapeInfo.logicalShape,t.logicalShape),l=ht(o),u=o-a,c,d=["x","y","z","w","u","v"];a===0?c="":o<2&&i.length>=1?c="coords = 0;":c=i.map(y=>`coords.${d[y+u]} = 0;`).join(`
`);let h="";o<2&&a>0?h="coords":h=e.shapeInfo.logicalShape.map((y,x)=>`coords.${d[x+u]}`).join(", ");let p="return outputValue;",m=w.sizeFromShape(e.shapeInfo.logicalShape)===1,A=w.sizeFromShape(t.logicalShape)===1;if(a===1&&!m&&!A)p=`
return vec4(outputValue.xy, outputValue.xy);
`;else if(m&&!A)o===1?p=`
return vec4(outputValue.x, outputValue.x, 0., 0.);
`:p=`
return vec4(outputValue.x);
`;else if(i.length){let y=a-2,x=a-1;i.indexOf(y)>-1&&i.indexOf(x)>-1?p="return vec4(outputValue.x);":i.indexOf(y)>-1?p="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":i.indexOf(x)>-1&&(p="return vec4(outputValue.xx, outputValue.zz);")}return`
vec4 ${r}() {
${l} coords = getOutputCoords();
${c}
vec4 outputValue = get${s}(${h});
${p}
}
`}function Zq(e,t){let n=e.name,s=n.charAt(0).toUpperCase()+n.slice(1),r="get"+s+"AtOutCoords",a=t.texShape,o=e.shapeInfo.texShape,i=e.shapeInfo.logicalShape.length,l=t.logicalShape.length;if(!e.shapeInfo.isUniform&&i===l&&e.shapeInfo.flatOffset==null&&w.arraysEqual(o,a))return`
float ${r}() {
return sampleTexture(${n}, resultUV);
}
`;let u=ht(l),c=m6(e.shapeInfo.logicalShape,t.logicalShape),d=l-i,h,p=["x","y","z","w","u","v"];i===0?h="":l<2&&c.length>=1?h="coords = 0;":h=c.map(m=>`coords.${p[m+d]} = 0;`).join(`
`);let f="";return l<2&&i>0?f="coords":f=e.shapeInfo.logicalShape.map((m,g)=>`coords.${p[g+d]}`).join(", "),`
float ${r}() {
${u} coords = getOutputCoords();
${h}
return get${s}(${f});
}
`}function ht(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 $2(e,t,n){let{newShape:s,keptDims:r}=w.squeezeShape(t),a=t.length,o=e&&a===3&&t[0]===1,i=o?t.slice(1):s,l=!e&&a>1&&!w.arraysEqual(t,n)&&s.length<a||o;return{useSqueezeShape:l,uniformShape:l?i:t,keptDims:r}}function au(e,t){let n=JSON.parse(JSON.stringify(e));return n.shapeInfo.logicalShape=t,n}function ou(e,t){return t.map(n=>e[n]).join(", ")}function Yq(e,t,n,s){let r=n.map((x,b)=>{let v={logicalShape:x.shape,texShape:x.isUniform?null:x.texData.texShape,isUniform:x.isUniform,isPacked:x.isUniform?!1:x.texData.isPacked,flatOffset:null};return x.texData!=null&&x.texData.slice!=null&&x.texData.slice.flatOffset>0&&(v.flatOffset=x.texData.slice.flatOffset),{name:t.variableNames[b],shapeInfo:v}}),a=r.map(x=>x.shapeInfo),o={logicalShape:s.shape,texShape:s.texData.texShape,isUniform:!1,isPacked:s.texData.isPacked,flatOffset:null},i=mq(r,o,t),l=e.createProgram(i),u=null,c=e.getUniformLocation(l,"NAN",!1);Q().getNumber("WEBGL_VERSION")===1&&(u=e.getUniformLocation(l,"INFINITY",!1));let d=!1,h={},p={},f={};for(let x=0;x<t.variableNames.length;x++){let b=t.variableNames[x];h[b]=e.getUniformLocation(l,b,d),h[`offset${b}`]=e.getUniformLocation(l,`offset${b}`,d),t.enableShapeUniforms&&(p[`${b}Shape`]=e.getUniformLocation(l,`${b}Shape`,d),f[`${b}TexShape`]=e.getUniformLocation(l,`${b}TexShape`,d))}let m,g,A;t.enableShapeUniforms&&(m=e.getUniformLocation(l,"outShape",d),A=e.getUniformLocation(l,"outShapeStrides",d),g=e.getUniformLocation(l,"outTexShape",d));let y=[];return t.customUniforms&&t.customUniforms.forEach((x,b)=>{y[b]=e.getUniformLocation(l,x.name,d)}),{program:t,source:i,webGLProgram:l,uniformLocations:h,customUniformLocations:y,inShapeInfos:a,outShapeInfo:o,infLoc:u,nanLoc:c,inShapesLocations:p,inTexShapesLocations:f,outShapeLocation:m,outShapeStridesLocation:A,outTexShapeLocation:g}}function y6(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((n,s)=>{let r=n.logicalShape,a=t[s],o=a.shape;if(!w.arraysEqual(r,o))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${r} and ${o} must match`);if(n.isUniform&&a.isUniform)return;let i=n.texShape,l=a.isUniform?null:a.texData.texShape;if(!w.arraysEqual(i,l))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${i} and ${l} must match`)})}function Jq(e,t,n,s,r){t.program.enableShapeUniforms||(y6(t.inShapeInfos,n),y6([t.outShapeInfo],[s]));let a=s.texData.texture,o=s.texData.texShape;s.texData.isPacked?e.setOutputPackedMatrixTexture(a,o[0],o[1]):e.setOutputMatrixTexture(a,o[0],o[1]),e.setProgram(t.webGLProgram),Q().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&e.gl.uniform1f(t.infLoc,1/0),t.nanLoc!==null&&e.gl.uniform1f(t.nanLoc,NaN),n.forEach((l,u)=>{let c=t.program.variableNames[u],d=t.uniformLocations[c],h=t.uniformLocations[`offset${c}`],p=t.inShapesLocations[`${c}Shape`],f=t.inTexShapesLocations[`${c}TexShape`];if(p){let{uniformShape:m}=$2(t.program.packedInputs,l.shape,l.texData.texShape);switch(m.length){case 1:e.gl.uniform1iv(p,new Int32Array(m));break;case 2:e.gl.uniform2iv(p,new Int32Array(m));break;case 3:e.gl.uniform3iv(p,new Int32Array(m));break;case 4:e.gl.uniform4iv(p,new Int32Array(m));break;default:break}}if(f&&e.gl.uniform2i(f,l.texData.texShape[0],l.texData.texShape[1]),d!=null){if(l.isUniform){if(w.sizeFromShape(l.shape)<2)e.gl.uniform1f(d,l.uniformValues[0]);else{let m=l.uniformValues;m instanceof Float32Array||(m=new Float32Array(m)),e.gl.uniform1fv(d,m)}return}l.texData.slice!=null&&h!=null&&e.gl.uniform1i(h,l.texData.slice.flatOffset),e.setInputMatrixTexture(l.texData.texture,d,u)}});let i=t.outShapeLocation;if(i)switch(s.shape.length){case 1:e.gl.uniform1iv(i,new Int32Array(s.shape));break;case 2:e.gl.uniform2iv(i,new Int32Array(s.shape));break;case 3:e.gl.uniform3iv(i,new Int32Array(s.shape));break;case 4:e.gl.uniform4iv(i,new Int32Array(s.shape));break;default:break}if(t.outShapeStridesLocation){let l=w.computeStrides(s.shape);switch(s.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,s.texData.texShape[0],s.texData.texShape[1]),t.program.customUniforms&&r&&t.program.customUniforms.forEach((l,u)=>{let c=t.customUniformLocations[u],d=r[u];if(l.type==="float")e.gl.uniform1fv(c,d);else if(l.type==="vec2")e.gl.uniform2fv(c,d);else if(l.type==="vec3")e.gl.uniform3fv(c,d);else if(l.type==="vec4")e.gl.uniform4fv(c,d);else if(l.type==="int")e.gl.uniform1iv(c,d);else if(l.type==="ivec2")e.gl.uniform2iv(c,d);else if(l.type==="ivec3")e.gl.uniform3iv(c,d);else if(l.type==="ivec4")e.gl.uniform4iv(c,d);else throw Error(`uniform type ${l.type} is not supported yet.`)}),e.executeProgram()}function Qq(e,t,n){let s="";t.concat(n).forEach(o=>{let i=o.texData!=null&&o.texData.slice!=null&&o.texData.slice.flatOffset>0;if(e.enableShapeUniforms&&!o.isUniform){let l=o.texData.texShape,{useSqueezeShape:u,uniformShape:c,keptDims:d}=$2(e.packedInputs,o.shape,l),h="",p="",f="";if(c.length===1&&e.packedInputs){let v=[Math.ceil(l[0]/2),Math.ceil(l[1]/2)];h=`${v[0]>1}_${v[1]>1}`}else if(c.length===2&&!e.packedInputs)p=`${c[0]>1}_${c[1]>1}`;else if(c.length>2&&!e.packedInputs){let v=w.computeStrides(c);f=`${v[0]===l[1]}_${v[v.length-1]===l[1]}`}let m=o.shape.length,g=c.length===2&&w.arraysEqual(o.shape,l),A=w.sizeFromShape(o.shape)===1,y=D.getBroadcastDims(o.shape,n.shape),x=!e.packedInputs&&m===n.shape.length&&w.arraysEqual(l,n.texData.texShape),b=e.packedInputs||c.length>2?"":`${l[0]>1}_${l[1]>1}`;s+=`${m}_${x}_${u?d:""}_${c.length}_${A}_${y}_${g}_${h}_${p}_${f}_${b}_${i}`}else{let l=o.isUniform?"uniform":o.texData.texShape;s+=`${o.shape}_${l}_${i}`}});let r=e.userCode,a=e.constructor.name;return a+="_"+s+"_"+r+`${Q().getNumber("WEBGL_VERSION")}`,a}function bs(e){return Q().getBool("WEBGL_USE_SHAPES_UNIFORMS")&&e<=4}var eX=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=Gc.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let t=kn();this.outputShape=e,this.enableShapeUniforms=bs(this.outputShape.length),this.userCode=`
ivec3 outCoordsFromFlatIndex(int index) {
${this.enableShapeUniforms?bf(["r","c","d"],e):ei(["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;
}
`}},tX=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=Gc.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let t=kn();this.outputShape=e,this.enableShapeUniforms=bs(this.outputShape.length),this.userCode=`
ivec3 outCoordsFromFlatIndex(int index) {
${this.enableShapeUniforms?bf(["r","c","d"],e):ei(["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;
}
`}},nX=class{constructor(e){this.variableNames=["A"],this.outTexUsage=ys.DOWNLOAD;let t=kn();this.outputShape=e,this.userCode=`
${f6}
void main() {
float x = getAAtOutCoords();
${t.output} = encode_float(x);
}
`}},sX=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=ys.DOWNLOAD;let t=kn();this.outputShape=e,this.userCode=`
${f6}
void main() {
ivec3 coords = getOutputCoords();
float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));
${t.output} = encode_float(x);
}
`}},rX=class{constructor(e,t=!1){this.variableNames=["A"],this.customUniforms=[{name:"texShape",type:"ivec2"}];let n=kn();this.outputShape=e,this.enableShapeUniforms=bs(this.outputShape.length);let s="result";t&&(s="floor(result * 255. + 0.5)"),this.userCode=`
${this.enableShapeUniforms?D2():_2(e)}
void main() {
ivec3 coords = getOutputCoords();
int flatIndex = getFlatIndex(coords);
int 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]);
vec4 values = ${n.texture2D}(A, uv);
float result;
if(offset == 0) {
result = values[0];
} else if(offset == 1) {
result = values[1];
} else if(offset == 2) {
result = values[2];
} else {
result = values[3];
}
${n.output} = vec4(${s}, 0., 0., 0.);
}
`}},aX=class{constructor(e,t=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.customUniforms=[{name:"texShape",type:"ivec2"}];let n=kn();this.outputShape=e,this.enableShapeUniforms=bs(this.outputShape.length);let s="",r="result";t&&(r="floor(result * 255. + 0.5)");for(let a=0;a<=1;a++)for(let o=0;o<=1;o++){let i=a*2+o;s+=`
localCoords = coords;
if(localCoords[2] + ${o} < ${this.enableShapeUniforms?"outShape[2]":`${e[2]}`}) {
localCoords[2] += ${o};
if (localCoords[1] + ${a} < ${this.enableShapeUniforms?"outShape[1]":`${e[1]}`}) {
localCoords[1] += ${a};
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 = ${n.texture2D}(A, uv);
if (offset == 0) {
result[${i}] = values[0];
} else if (offset == 1) {
result[${i}] = values[1];
} else if (offset == 2) {
result[${i}] = values[2];
} else {
result[${i}] = values[3];
}
}
}
`}this.userCode=`
${this.enableShapeUniforms?D2():_2(e)}
void main() {
ivec3 coords = getOutputCoords();
vec4 result = vec4(0.);
int flatIndex, r, c, offset;
ivec3 localCoords;
vec2 uv;
vec4 values;
${s}
${n.output} = ${r};
}
`}},x6={};Pe(x6,{bindVertexProgramAttributeStreams:()=>N6,createBufferFromOutputTexture:()=>_6,createFloat16MatrixTexture:()=>I6,createFloat16PackedMatrixTexture:()=>T6,createFloat32MatrixTexture:()=>k6,createIndexBuffer:()=>w6,createPackedMatrixTexture:()=>C6,createUnsignedBytesMatrixTexture:()=>S6,createVertexBuffer:()=>v6,createVertexShader:()=>b6,downloadByteEncodedFloatMatrixFromOutputTexture:()=>$6,downloadFloat32MatrixFromBuffer:()=>D6,downloadMatrixFromPackedOutputTexture:()=>O6,downloadPackedMatrixFromBuffer:()=>F6,getInternalFormatForFloat16MatrixTexture:()=>O2,getInternalFormatForFloat16PackedMatrixTexture:()=>z2,getInternalFormatForFloat32MatrixTexture:()=>F2,getInternalFormatForPackedMatrixTexture:()=>M2,getInternalFormatForUnsignedBytesMatrixTexture:()=>P2,uploadDenseMatrixToTexture:()=>E6,uploadPixelDataToTexture:()=>R6});function b6(e){let t=kn(),n=`${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 jw(e,n)}function v6(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 Zw(e,t)}function w6(e){let t=new Uint16Array([0,1,2,2,1,3]);return Yw(e,t)}function Zc(e,t,n,s,r,a){Qw(t,n);let o=Jw(e),i=e.TEXTURE_2D;return be(e,()=>e.bindTexture(i,o)),be(e,()=>e.texParameteri(i,e.TEXTURE_WRAP_S,e.CLAMP_TO_EDGE)),be(e,()=>e.texParameteri(i,e.TEXTURE_WRAP_T,e.CLAMP_TO_EDGE)),be(e,()=>e.texParameteri(i,e.TEXTURE_MIN_FILTER,e.NEAREST)),be(e,()=>e.texParameteri(i,e.TEXTURE_MAG_FILTER,e.NEAREST)),be(e,()=>e.texImage2D(i,0,s,t,n,0,r,a,null)),be(e,()=>e.bindTexture(e.TEXTURE_2D,null)),o}function F2(e){return e.internalFormatFloat}function k6(e,t,n,s){let[r,a]=jc(t,n);return Zc(e,r,a,F2(s),s.textureFormatFloat,e.FLOAT)}function O2(e){return e.internalFormatHalfFloat}function I6(e,t,n,s){let[r,a]=jc(t,n);return Zc(e,r,a,O2(s),s.textureFormatFloat,s.textureTypeHalfFloat)}function P2(e){return e.downloadTextureFormat}function S6(e,t,n,s){let[r,a]=jc(t,n);return Zc(e,r,a,P2(s),e.RGBA,e.UNSIGNED_BYTE)}function M2(e){return e.internalFormatPackedFloat}function C6(e,t,n,s){let[r,a]=tu(t,n);return Zc(e,r,a,M2(s),e.RGBA,e.FLOAT)}function z2(e){return e.internalFormatPackedHalfFloat}function T6(e,t,n,s){let[r,a]=tu(t,n);return Zc(e,r,a,z2(s),e.RGBA,s.textureTypeHalfFloat)}function N6(e,t,n){let s=0,r=3*4,a=3*4+2*4;return be(e,()=>e.bindBuffer(e.ARRAY_BUFFER,n)),T2(e,t,"clipSpacePos",n,3,a,s)&&T2(e,t,"uv",n,2,a,r)}function E6(e,t,n,s,r,a){be(e,()=>e.bindTexture(e.TEXTURE_2D,t));let o,i,l;r instanceof Uint8Array?(o=new Uint8Array(n*s*4),i=e.UNSIGNED_BYTE,l=e.RGBA):(o=new Float32Array(n*s*4),i=e.FLOAT,l=a.internalFormatPackedFloat),o.set(r),be(e,()=>e.texImage2D(e.TEXTURE_2D,0,l,n,s,0,e.RGBA,i,o)),be(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function R6(e,t,n){be(e,()=>e.bindTexture(e.TEXTURE_2D,t)),n.data instanceof Uint8Array?be(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,n.width,n.height,0,e.RGBA,e.UNSIGNED_BYTE,n.data)):be(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,e.RGBA,e.UNSIGNED_BYTE,n)),be(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function _6(e,t,n,s){let r=e.createBuffer();be(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,r));let i=4*4*t*n;return be(e,()=>e.bufferData(e.PIXEL_PACK_BUFFER,i,e.STREAM_READ)),be(e,()=>e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,0)),be(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,null)),r}function D6(e,t,n){let s=e,r=new Float32Array(n);return s.bindBuffer(s.PIXEL_PACK_BUFFER,t),s.getBufferSubData(s.PIXEL_PACK_BUFFER,0,r),s.bindBuffer(s.PIXEL_PACK_BUFFER,null),r}function $6(e,t,n,s){let[r,a]=jc(t,n),o=4,i=new Uint8Array(eq(t*n,o));return be(e,()=>e.readPixels(0,0,r,a,s.downloadTextureFormat,e.UNSIGNED_BYTE,i)),new Float32Array(i.buffer)}function F6(e,t,n,s,r,a,o,i){let l=e,u=new Float32Array(tq(a,o));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 O6(e,t,n){let s=new Float32Array(t*n*4);return be(e,()=>e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,s)),s}var vf=class{constructor(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.vertexAttrsAreBound=!1,this.itemsToPoll=[];let t=Q().getNumber("WEBGL_VERSION");e!=null?(this.gl=e,hf(t,e)):this.gl=dr(t);let n="WEBGL_color_buffer_float",s="EXT_color_buffer_half_float";if(Q().getNumber("WEBGL_VERSION")===1){let r="OES_texture_float",a="OES_texture_half_float";if(this.textureFloatExtension=qc(this.gl,r),xs(this.gl,a))this.textureHalfFloatExtension=qc(this.gl,a);else if(Q().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(n),xs(this.gl,s))this.colorBufferHalfFloatExtension=qc(this.gl,s);else if(Q().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(n="EXT_color_buffer_float",xs(this.gl,n))this.colorBufferFloatExtension=this.gl.getExtension(n);else if(xs(this.gl,s))this.colorBufferHalfFloatExtension=this.gl.getExtension(s);else throw new Error("GL context does not support color renderable floats");this.vertexBuffer=v6(this.gl),this.indexBuffer=w6(this.gl),this.framebuffer=e6(this.gl),this.textureConfig=C2(this.gl,this.textureHalfFloatExtension)}get debug(){return Q().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;be(e,()=>e.finish()),be(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),be(e,()=>e.deleteFramebuffer(this.framebuffer)),be(e,()=>e.bindBuffer(e.ARRAY_BUFFER,null)),be(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null)),be(e,()=>e.deleteBuffer(this.indexBuffer)),this.disposed=!0}createFloat32MatrixTexture(e,t){return this.throwIfDisposed(),k6(this.gl,e,t,this.textureConfig)}createFloat16MatrixTexture(e,t){return this.throwIfDisposed(),I6(this.gl,e,t,this.textureConfig)}createUnsignedBytesMatrixTexture(e,t){return this.throwIfDisposed(),S6(this.gl,e,t,this.textureConfig)}uploadPixelDataToTexture(e,t){this.throwIfDisposed(),R6(this.gl,e,t)}uploadDenseMatrixToTexture(e,t,n,s){this.throwIfDisposed(),E6(this.gl,e,t,n,s,this.textureConfig)}createFloat16PackedMatrixTexture(e,t){return this.throwIfDisposed(),T6(this.gl,e,t,this.textureConfig)}createPackedMatrixTexture(e,t){return this.throwIfDisposed(),C6(this.gl,e,t,this.textureConfig)}deleteMatrixTexture(e){this.throwIfDisposed(),this.outputTexture===e&&(N2(this.gl,this.framebuffer),this.outputTexture=null),be(this.gl,()=>this.gl.deleteTexture(e))}downloadByteEncodedFloatMatrixFromOutputTexture(e,t,n){return this.downloadMatrixDriver(e,()=>$6(this.gl,t,n,this.textureConfig))}downloadPackedMatrixFromBuffer(e,t,n,s,r,a){return F6(this.gl,e,t,n,s,r,a,this.textureConfig)}downloadFloat32MatrixFromBuffer(e,t){return D6(this.gl,e,t)}createBufferFromTexture(e,t,n){this.bindTextureToFrameBuffer(e);let s=_6(this.gl,t,n,this.textureConfig);return this.unbindTextureToFrameBuffer(),s}createAndWaitForFence(){let e=this.createFence(this.gl);return this.pollFence(e)}createFence(e){let t,n;if(Q().getBool("WEBGL_FENCE_API_ENABLED")){let s=e,r=s.fenceSync(s.SYNC_GPU_COMMANDS_COMPLETE,0);e.flush(),n=()=>{let a=s.clientWaitSync(r,0,0);return a===s.ALREADY_SIGNALED||a===s.CONDITION_SATISFIED},t=r}else Q().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(t=this.beginQuery(),this.endQuery(),n=()=>this.isQueryAvailable(t,Q().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))):n=()=>!0;return{query:t,isFencePassed:n}}downloadMatrixFromPackedTexture(e,t,n){return this.downloadMatrixDriver(e,()=>O6(this.gl,t,n))}createProgram(e){this.throwIfDisposed();let t=this.gl,n=qw(t,e);this.vertexShader==null&&(this.vertexShader=b6(t));let s=Xw(t);return be(t,()=>t.attachShader(s,this.vertexShader)),be(t,()=>t.attachShader(s,n)),Kw(t,s),this.debug&&ff(t,s),this.vertexAttrsAreBound||(this.setProgram(s),this.vertexAttrsAreBound=N6(t,this.program,this.vertexBuffer)),s}deleteProgram(e){this.throwIfDisposed(),e===this.program&&(this.program=null),e!=null&&be(this.gl,()=>this.gl.deleteProgram(e))}setProgram(e){this.throwIfDisposed(),this.program=e,this.program!=null&&this.debug&&ff(this.gl,this.program),be(this.gl,()=>this.gl.useProgram(e))}getUniformLocation(e,t,n=!0){return this.throwIfDisposed(),n?n6(this.gl,e,t):s6(this.gl,e,t)}getAttributeLocation(e,t){return this.throwIfDisposed(),be(this.gl,()=>this.gl.getAttribLocation(e,t))}getUniformLocationNoThrow(e,t){return this.throwIfDisposed(),this.gl.getUniformLocation(e,t)}setInputMatrixTexture(e,t,n){this.throwIfDisposed(),this.throwIfNoProgram(),r6(this.gl,e,t,n)}setOutputMatrixTexture(e,t,n){this.setOutputMatrixTextureDriver(e,n,t)}setOutputPackedMatrixTexture(e,t,n){this.throwIfDisposed();let[s,r]=tu(t,n);this.setOutputMatrixTextureDriver(e,s,r)}setOutputMatrixWriteRegion(e,t,n,s){this.setOutputMatrixWriteRegionDriver(n,e,s,t)}setOutputPackedMatrixWriteRegion(e,t,n,s){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")}debugValidate(){this.program!=null&&ff(this.gl,this.program),Xc(this.gl)}executeProgram(){this.throwIfDisposed(),this.throwIfNoProgram();let e=this.gl;this.debug&&this.debugValidate(),be(e,()=>e.drawElements(e.TRIANGLES,6,e.UNSIGNED_SHORT,0))}blockUntilAllProgramsCompleted(){this.throwIfDisposed(),be(this.gl,()=>this.gl.finish())}getQueryTimerExtension(){return this.disjointQueryTimerExtension==null&&(this.disjointQueryTimerExtension=qc(this.gl,Q().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(Q().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let n=this.gl,s=this.getQueryTimerExtensionWebGL2(),r=n.createQuery();return n.beginQuery(s.TIME_ELAPSED_EXT,r),r}let e=this.getQueryTimerExtensionWebGL1(),t=e.createQueryEXT();return e.beginQueryEXT(e.TIME_ELAPSED_EXT,t),t}endQuery(){if(Q().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let t=this.gl,n=this.getQueryTimerExtensionWebGL2();t.endQuery(n.TIME_ELAPSED_EXT);return}let e=this.getQueryTimerExtensionWebGL1();e.endQueryEXT(e.TIME_ELAPSED_EXT)}async waitForQueryAndGetTime(e){return await w.repeatedTry(()=>this.disposed||this.isQueryAvailable(e,Q().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))),this.getQueryTime(e,Q().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))}getQueryTime(e,t){if(t===0)return null;if(t===2){let n=this.gl;return n.getQueryParameter(e,n.QUERY_RESULT)/1e6}else{let n=this.getQueryTimerExtensionWebGL1();return n.getQueryObjectEXT(e,n.QUERY_RESULT_EXT)/1e6}}isQueryAvailable(e,t){if(t===0)return!0;if(t===2){let n=this.gl,s=this.getQueryTimerExtensionWebGL2(),r=n.getQueryParameter(e,n.QUERY_RESULT_AVAILABLE);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(s.GPU_DISJOINT_EXT)),r&&!this.disjoint}else{let n=this.getQueryTimerExtensionWebGL1(),s=n.getQueryObjectEXT(e,n.QUERY_RESULT_AVAILABLE_EXT);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(n.GPU_DISJOINT_EXT)),s&&!this.disjoint}}pollFence(e){return new Promise(t=>{this.addItemToPoll(()=>e.isFencePassed(),()=>t())})}pollItems(){let e=oX(this.itemsToPoll.map(t=>t.isDoneFn));for(let t=0;t<=e;++t){let{resolveFn:n}=this.itemsToPoll[t];n()}this.itemsToPoll=this.itemsToPoll.slice(e+1)}addItemToPoll(e,t){this.itemsToPoll.push({isDoneFn:e,resolveFn:t}),!(this.itemsToPoll.length>1)&&w.repeatedTry(()=>(this.pollItems(),this.itemsToPoll.length===0))}bindTextureToFrameBuffer(e){this.throwIfDisposed(),mf(this.gl,e,this.framebuffer),this.debug&&Xc(this.gl)}unbindTextureToFrameBuffer(){this.outputTexture!=null?(mf(this.gl,this.outputTexture,this.framebuffer),this.debug&&Xc(this.gl)):N2(this.gl,this.framebuffer)}downloadMatrixDriver(e,t){this.bindTextureToFrameBuffer(e);let n=t();return this.unbindTextureToFrameBuffer(),n}setOutputMatrixTextureDriver(e,t,n){this.throwIfDisposed();let s=this.gl;mf(s,e,this.framebuffer),this.debug&&Xc(s),this.outputTexture=e,be(s,()=>s.viewport(0,0,t,n)),be(s,()=>s.scissor(0,0,t,n))}setOutputMatrixWriteRegionDriver(e,t,n,s){this.throwIfDisposed(),be(this.gl,()=>this.gl.scissor(e,t,n,s))}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 oX(e){let t=0;for(;t<e.length&&e[t]();++t);return t-1}var{addImpl:iX,bincountImpl:P6,bincountReduceImpl:lX,ceilImpl:uX,concatImpl:cX,equalImpl:dX,expImpl:hX,expm1Impl:pX,floorImpl:fX,gatherNdImpl:mX,gatherV2Impl:gX,greaterImpl:AX,greaterEqualImpl:yX,lessImpl:xX,lessEqualImpl:bX,linSpaceImpl:vX,logImpl:wX,maxImpl:kX,maximumImpl:IX,minimumImpl:SX,multiplyImpl:CX,negImpl:TX,notEqualImpl:NX,prodImpl:EX,rangeImpl:RX,rsqrtImpl:_X,sigmoidImpl:DX,simpleAbsImpl:M6,sliceImpl:$X,sparseFillEmptyRowsImpl:FX,sparseReshapeImpl:OX,sparseSegmentReductionImpl:z6,sqrtImpl:PX,stridedSliceImpl:MX,stringNGramsImpl:zX,stringSplitImpl:LX,stringToHashBucketFastImpl:BX,subImpl:WX,tileImpl:VX,topKImpl:UX,transposeImpl:L2,uniqueImpl:HX}=c2;function L6(e,t){return["x","y","z","w","u","v"].slice(0,t).map(n=>`${e}.${n}`)}function In(e,t){return t===1?[e]:L6(e,t)}function GX(e,t){if(e===1)return"rc";let n="";for(let s=0;s<e;s++)n+=t[s],s<e-1&&(n+=",");return n}var jX=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=e;let t=e.length;if(t===0)this.userCode=`
void main() {
setOutput(vec4(getA(), 0., 0., 0.));
}
`;else{let n=In("rc",t),s=ht(t),r=XX(t,e,n),a=KX(t,e[e.length-1],e[e.length-2],n),o=ZX(e,n);this.userCode=`
void main() {
${s} rc = getOutputCoords();
if(${r}) {
setOutput(vec4(0));
} else {
${a}
setOutput(vec4(${o}));
}
}
`}}};function qX(e,t){let n=[];for(let s=0;s<=1;s++)for(let r=0;r<=1;r++){let a=`${s===0?"r":"rp1"}, ${r===0?"c":"cp1"}`;for(let o=2;o<e;o++)a=`${t[t.length-1-o]},`+a;n.push(a)}return n}function XX(e,t,n){if(e===1)return`rc > ${t[0]}`;let s="";for(let r=e-2;r<e;r++)s+=`${n[r]} >= ${t[r]}`,r<e-1&&(s+="||");return s}function KX(e,t,n,s){if(e===1)return"";let r=s.slice(-2);return`
int r = ${r[0]};
int c = ${r[1]};
int rp1 = r + 1;
int cp1 = c + 1;
bool cEdge = cp1 >= ${t};
bool rEdge = rp1 >= ${n};
`}function ZX(e,t){let n=e.length,s=qX(n,t);return n===1?`getA(rc),
rc + 1 >= ${e[0]} ? 0. : getA(rc + 1),
0, 0`:`getA(${s[0]}),
cEdge ? 0. : getA(${s[1]}),
rEdge ? 0. : getA(${s[2]}),
rEdge || cEdge ? 0. : getA(${s[3]})`}var B6=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"inputShape",type:"ivec3"}],this.outputShape=e,this.enableShapeUniforms=bs(this.outputShape.length);let n="";for(let s=0;s<4;s++){let r="thisRC = rc;";s%2==1&&(r+="thisRC.z += 1;"),s>1&&(r+="thisRC.y += 1;"),n+=`
${r}
${s>0?"if(thisRC.y < rows && thisRC.z < cols){":""}
int flatIndex = getFlatIndex(thisRC);
ivec3 inputRC = inputCoordsFromReshapedOutCoords(flatIndex);
vec2 inputRCInnerDims = vec2(float(inputRC.y),float(inputRC.z));
result[${s}] =
getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);
${s>0?"}":""}
`}this.userCode=`
${YX(t,this.enableShapeUniforms)}
${this.enableShapeUniforms?D2():_2(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]};
${n}
setOutput(result);
}
`}};function YX(e,t){return`
ivec3 inputCoordsFromReshapedOutCoords(int index) {
${t?fq(["r","c","d"],"inputShape"):ei(["r","c","d"],e)}
return ivec3(r, c, d);
}
`}var JX=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(e,t,n){let s=V6(t,n),r=U6(e,s,n);r in this.freeTextures||(this.freeTextures[r]=[]),r in this.usedTextures||(this.usedTextures[r]=[]);let a=W6(e,s,this.gpgpu.gl,this.gpgpu.textureConfig,n);if(this.freeTextures[r].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=a,this.log();let i=this.freeTextures[r].shift();return this.usedTextures[r].push(i),i}let o;return s===on.PACKED_2X2_FLOAT32?o=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):s===on.PACKED_2X2_FLOAT16?o=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):s===on.UNPACKED_FLOAT32?o=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):s===on.UNPACKED_FLOAT16?o=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):s===on.PACKED_4X1_UNSIGNED_BYTE&&(o=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[r].push(o),this.numUsedTextures++,this._numBytesAllocated+=a,this.log(),o}releaseTexture(e,t,n,s){if(this.freeTextures==null)return;let r=V6(n,s),a=U6(t,r,s);a in this.freeTextures||(this.freeTextures[a]=[]);let o=W6(t,r,this.gpgpu.gl,this.gpgpu.textureConfig,s),i=Q().get("WEBGL_DELETE_TEXTURE_THRESHOLD");i!==-1&&this._numBytesAllocated>i?(this.gpgpu.deleteMatrixTexture(e),this._numBytesAllocated-=o):(this.freeTextures[a].push(e),this.numFreeTextures++,this._numBytesFree+=o),this.numUsedTextures--;let l=this.usedTextures[a],u=l.indexOf(e);if(u<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l.splice(u,1),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${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)});for(let e in this.usedTextures)this.usedTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function QX(e,t){let n=e;if(t===n.R32F)return 4;if(t===n.R16F)return 2;if(t===n.RGBA32F)return 16;if(t===e.RGBA)return 16;if(t===n.RGBA16F)return 8;throw new Error(`Unknown internal format ${t}`)}function W6(e,t,n,s,r){let a=eK(t,s),o;if(r){let[l,u]=tu(e[0],e[1]);o=l*u}else{let[l,u]=jc(e[0],e[1]);o=l*u}let i=QX(n,a);return o*i}function eK(e,t){switch(e){case on.PACKED_2X2_FLOAT32:return M2(t);case on.PACKED_2X2_FLOAT16:return z2(t);case on.UNPACKED_FLOAT32:return F2(t);case on.UNPACKED_FLOAT16:return O2(t);case on.PACKED_4X1_UNSIGNED_BYTE:return P2(t);default:throw new Error(`Unknown physical texture type ${e}`)}}function tK(e){return Q().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?e?on.PACKED_2X2_FLOAT32:on.UNPACKED_FLOAT32:e?on.PACKED_2X2_FLOAT16:on.UNPACKED_FLOAT16}function V6(e,t){if(e===ys.UPLOAD)return on.PACKED_2X2_FLOAT32;if(e===ys.RENDER||e==null)return tK(t);if(e===ys.DOWNLOAD||e===ys.PIXELS)return on.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${e}`)}function U6(e,t,n){return`${e[0]}_${e[1]}_${t}_${n}`}var ha=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.enableShapeUniforms=bs(this.outputShape.length),this.userCode=`
float unaryOperation(float x) {
${t}
}
void main() {
float x = getAAtOutCoords();
float y = unaryOperation(x);
setOutput(y);
}
`}},js="if (isnan(x)) return x;",nK="return x;",H6="return abs(x);",sK="return (x >= 0.0) ? x : (exp(x) - 1.0);",rK=js+`
return (x < 0.0) ? 0.0 : x;
`,aK=js+`
return (x < 0.0) ? 0.0 : min(6.0, x);
`,wf="return x;",oK="return 1.0 / (1.0 + exp(-1.0 * x));",iK="return x;",lK=`
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;
`,uK=`
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;
`,cK=`
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;
`,dK="return 1.0 / (1.0 + exp(-1.0 * x));",iu=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.enableShapeUniforms=bs(this.outputShape.length),this.userCode=`
vec4 unaryOperation(vec4 x) {
${t}
}
void main() {
vec4 x = getAAtOutCoords();
vec4 y = unaryOperation(x);
setOutput(y);
}
`}},hK=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=e;let t=e.length,n=In("rc",t),s=ht(t),r=GX(t,n),a=n.slice(-2),o=t<=1?"rc":`vec2(${a.join(",")})`;this.userCode=`
void main() {
${s} rc = getOutputCoords();
vec4 packedInput = getA(${r});
setOutput(getChannel(packedInput, ${o}));
}
`}},pK=rr.whereImpl,fK=1e-7,mK=1e-4,kf={};function gK(e){return e in kf||(kf[e]={}),kf[e]}var AK=Q().getNumber("CPU_HANDOFF_SIZE_THRESHOLD"),yK=600;function xK(){return Q().global.screen==null?1024:Q().global.screen.height*Q().global.screen.width*window.devicePixelRatio*yK/1024/1024}var lu=class extends Du{constructor(e){super();if(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,!Q().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");if(e==null){let t=dr(Q().getNumber("WEBGL_VERSION"));this.binaryCache=gK(Q().getNumber("WEBGL_VERSION")),this.gpgpu=new vf(t),this.canvas=t.canvas,this.gpgpuCreatedLocally=!0}else this.gpgpu=e,this.binaryCache={},this.gpgpuCreatedLocally=!1,this.canvas=e.gl.canvas;this.textureManager=new JX(this.gpgpu),this.numMBBeforeWarning=xK(),this.texData=new Ud(this,wr())}nextDataId(){return lu.nextDataId++}numDataIds(){return this.texData.numDataIds()-this.pendingDeletes}write(e,t,n){if((Q().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||Q().getBool("DEBUG"))&&this.checkNumericalProblems(e),n==="complex64"&&e!=null)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let s={id:this.nextDataId()};return this.texData.set(s,{shape:t,dtype:n,values:e,usage:ys.UPLOAD,refCount:1}),s}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,n,s,r){if(Q().getBool("DEBUG")&&this.checkNumericalProblems(t),s==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(e,{shape:n,dtype:s,values:t,usage:ys.UPLOAD,refCount:r})}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}readSync(e){let t=this.texData.get(e),{values:n,dtype:s,complexTensorInfos:r,slice:a,shape:o,isPacked:i}=t;if(a!=null){let d;i?d=new iu(o,wf):d=new ha(o,wf);let h=this.runWebGLProgram(d,[{dataId:e,shape:o,dtype:s}],s),p=this.readSync(h.dataId);return this.disposeIntermediateTensorInfo(h),p}if(n!=null)return this.convertAndCacheOnCPU(e);if(s==="string")return n;let l=this.activeTimers!=null,u;l&&(u=w.now());let c;if(s==="complex64"){let d=this.readSync(r.real.dataId),h=this.readSync(r.imag.dataId);c=D.mergeRealAndImagArrays(d,h)}else c=this.getValuesFromTexture(e);return l&&(this.downloadWaitMs+=w.now()-u),this.convertAndCacheOnCPU(e,c)}async read(e){if(this.pendingRead.has(e)){let p=this.pendingRead.get(e);return new Promise(f=>p.push(f))}let t=this.texData.get(e),{values:n,shape:s,slice:r,dtype:a,complexTensorInfos:o,isPacked:i}=t;if(r!=null){let p;i?p=new iu(s,wf):p=new ha(s,wf);let f=this.runWebGLProgram(p,[{dataId:e,shape:s,dtype:a}],a),m=this.read(f.dataId);return this.disposeIntermediateTensorInfo(f),m}if(n!=null)return this.convertAndCacheOnCPU(e);if(!Q().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&Q().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(a!=="complex64"&&Q().get("WEBGL_BUFFER_SUPPORTED")){u=this.decode(e);let p=this.texData.get(u.dataId);l=this.gpgpu.createBufferFromTexture(p.texture,...pf(s))}this.pendingRead.set(e,[]),a!=="complex64"&&await this.gpgpu.createAndWaitForFence();let c;if(a==="complex64"){let p=await Promise.all([this.read(o.real.dataId),this.read(o.imag.dataId)]),f=p[0],m=p[1];c=D.mergeRealAndImagArrays(f,m)}else if(l==null)c=this.getValuesFromTexture(e);else{let p=w.sizeFromShape(s);c=this.gpgpu.downloadFloat32MatrixFromBuffer(l,p)}if(u!=null&&this.disposeIntermediateTensorInfo(u),l!=null){let p=this.gpgpu.gl;be(p,()=>p.deleteBuffer(l))}let d=this.convertAndCacheOnCPU(e,c),h=this.pendingRead.get(e);return this.pendingRead.delete(e),h.forEach(p=>p(d)),this.pendingDisposal.has(e)&&(this.pendingDisposal.delete(e),this.disposeData(e)&&wr().removeDataId(e,this),this.pendingDeletes--),d}bufferSync(e){let t=this.readSync(e.dataId),n=t;if(e.dtype==="string")try{n=t.map(s=>w.decodeString(s))}catch(s){throw new Error("Failed to decode encoded string bytes into utf-8")}return We(e.shape,e.dtype,n)}checkNumericalProblems(e){if(e!=null)for(let t=0;t<e.length;t++){let n=e[t];if(!Hw(n))throw Q().getBool("WEBGL_RENDER_FLOAT32_CAPABLE")?Error(`The value ${n} cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`):Error(`The value ${n} cannot be represented on this device.`)}}getValuesFromTexture(e){let{shape:t,dtype:n,isPacked:s}=this.texData.get(e),r=w.sizeFromShape(t);if(Q().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let d=this.decode(e),h=this.texData.get(d.dataId),p=this.gpgpu.downloadMatrixFromPackedTexture(h.texture,...pf(t)).subarray(0,r);return this.disposeIntermediateTensorInfo(d),p}let a=Q().getBool("WEBGL_PACK")&&s===!0,o=a?gf(t):t,i=a?new sX(o):new nX(o),l=this.runWebGLProgram(i,[{shape:o,dtype:n,dataId:e}],"float32"),u=this.texData.get(l.dataId),c=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(u.texture,u.texShape[0],u.texShape[1]).subarray(0,r);return this.disposeIntermediateTensorInfo(l),c}timerAvailable(){return Q().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}async time(e){let t=this.activeTimers,n=[],s=!1;this.programTimersStack==null?(this.programTimersStack=n,s=!0):this.activeTimers.push(n),this.activeTimers=n,e();let r=w.flatten(this.activeTimers.map(i=>i.query)).filter(i=>i!=null),a=w.flatten(this.activeTimers.map(i=>i.name)).filter(i=>i!=null);this.activeTimers=t,s&&(this.programTimersStack=null);let o={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};if(Q().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let i=await Promise.all(r);o.kernelMs=w.sum(i),o.getExtraProfileInfo=()=>i.map((l,u)=>({name:a[u],ms:l})).map(l=>`${l.name}: ${l.ms}`).join(", ")}else o.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,o}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return Q().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:w.now(),endMs:null}}endTimer(e){return Q().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=w.now(),e)}async getQueryTime(e){if(Q().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:n}=this.texData.get(e);return n!=null&&(this.disposeData(n.real.dataId,t),this.disposeData(n.imag.dataId,t)),this.texData.delete(e),!0}releaseGPUData(e){let{texture:t,dtype:n,texShape:s,usage:r,isPacked:a,slice:o}=this.texData.get(e),i=o&&o.origDataId||e,l=this.dataRefCount.get(i);l>1?this.dataRefCount.set(i,l-1):(this.dataRefCount.delete(i),t!=null&&(this.numBytesInGPU-=this.computeBytes(s,n),this.textureManager.releaseTexture(t,s,r,a)));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}getDataInfo(e){return this.texData.get(e)}shouldExecuteOnCPU(e,t=AK){return Q().getBool("WEBGL_CPU_FORWARD")&&e.every(n=>this.texData.get(n.dataId).texture==null&&w.sizeFromShape(n.shape)<t)}getGPGPUContext(){return this.gpgpu}where(e){D.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let t=e.dataSync();return pK(e.shape,t)}packedUnaryOp(e,t,n){let s=new iu(e.shape,t),r=this.compileAndRun(s,[e],n);return wr().makeTensorFromDataId(r.dataId,r.shape,r.dtype)}abs(e){if(this.shouldExecuteOnCPU([e])&&e.dtype!=="complex64"){let s=M6(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,s)}if(Q().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,H6,e.dtype);let t=new ha(e.shape,H6),n=this.compileAndRun(t,[e]);return wr().makeTensorFromDataId(n.dataId,n.shape,n.dtype)}makeTensorInfo(e,t,n){let s;if(t==="string"&&n!=null&&n.length>0&&w.isString(n[0])){let r=n.map(a=>w.encodeString(a));s=this.write(r,e,t)}else s=this.write(n,e,t);return this.texData.get(s).usage=null,{dataId:s,shape:e,dtype:t}}makeOutput(e,t,n){let{dataId:s}=this.makeTensorInfo(e,t,n);return wr().makeTensorFromDataId(s,e,t,this)}unpackTensor(e){let t=new hK(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){let t=new jX(e.shape),n=!0;return this.runWebGLProgram(t,[e],e.dtype,null,n)}packedReshape(e,t){let n=[Jo(e.shape),...Qo(e.shape)],s={dtype:e.dtype,shape:n,dataId:e.dataId},r=[Jo(t),...Qo(t)],a=new B6(r,n),o=!0,i=[n],l=this.runWebGLProgram(a,[s],e.dtype,i,o);return{dataId:l.dataId,shape:t,dtype:l.dtype}}decode(e){let t=this.texData.get(e),{isPacked:n,shape:s,dtype:r}=t,a=gf(s),o,i=pf(a);n?o=new tX(a):o=new eX(a);let l=!0,u=[i],c=this.runWebGLProgram(o,[{shape:a,dtype:r,dataId:e}],r,u,l);return{dtype:r,shape:s,dataId:c.dataId}}runWebGLProgram(e,t,n,s,r=!1){let a=this.makeTensorInfo(e.outputShape,n),o=this.texData.get(a.dataId);if(e.packedOutput&&(o.isPacked=!0),e.outPackingScheme===Gc.DENSE){let m=pf(e.outputShape);o.texShape=m.map(g=>g*2)}if(e.outTexUsage!=null&&(o.usage=e.outTexUsage),w.sizeFromShape(a.shape)===0)return o.values=w.getTypedArrayFromDType(a.dtype,0),a;let i=[],l=t.map(m=>{if(m.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let g=this.texData.get(m.dataId);if(g.texture==null){if(!e.packedInputs&&w.sizeFromShape(m.shape)<=Q().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:m.shape,texData:null,isUniform:!0,uniformValues:g.values};e.packedInputs&&(g.isPacked=!0,g.shape=m.shape)}else if(!!g.isPacked!=!!e.packedInputs)m=g.isPacked?this.unpackTensor(m):this.packTensor(m),i.push(m),g=this.texData.get(m.dataId);else if(g.isPacked&&!Kc(g.shape,m.shape)){let A=m,y=m.shape;m.shape=g.shape,m=this.packedReshape(m,y),i.push(m),g=this.texData.get(m.dataId),A.shape=y}return this.uploadToGPU(m.dataId),{shape:m.shape,texData:g,isUniform:!1}});this.uploadToGPU(a.dataId);let u={shape:a.shape,texData:o,isUniform:!1},c=Qq(e,l,u),d=this.getAndSaveBinary(c,()=>Yq(this.gpgpu,e,l,u)),h=this.activeTimers!=null,p;h&&(p=this.startTimer()),Jq(this.gpgpu,d,l,u,s),i.forEach(m=>this.disposeIntermediateTensorInfo(m)),h&&(p=this.endTimer(p),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(p)}));let f=Q().get("WEBGL_FLUSH_THRESHOLD");if(f>0){let m=w.now();m-this.lastGlFlushTime>f&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=m)}if(!Q().getBool("WEBGL_LAZILY_UNPACK")&&o.isPacked&&r===!1){let m=this.unpackTensor(a);return this.disposeIntermediateTensorInfo(a),m}return a}compileAndRun(e,t,n,s,r=!1){return n=n||t[0].dtype,this.runWebGLProgram(e,t,n,s,r)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(Q().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(t=>{this.gpgpu.deleteProgram(this.binaryCache[t].webGLProgram),delete this.binaryCache[t]}),this.textureManager.dispose(),this.canvas!=null&&typeof HTMLCanvasElement!="undefined"&&this.canvas instanceof HTMLCanvasElement?this.canvas.remove():this.canvas=null,this.gpgpuCreatedLocally&&(this.gpgpu.program=null,this.gpgpu.dispose()),this.disposed=!0)}floatPrecision(){return this.floatPrecisionValue==null&&(this.floatPrecisionValue=H(()=>{if(!Q().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=Q().getBool("DEBUG");Q().set("DEBUG",!1);let t=this.abs(Ie(1e-8)).dataSync()[0];if(Q().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?fK:mK}uploadToGPU(e){let t=this.texData.get(e),{shape:n,dtype:s,values:r,texture:a,usage:o,isPacked:i}=t;if(a!=null)return;let l=this.activeTimers!=null,u;l&&(u=w.now());let c=t.texShape;if(c==null&&(c=i6(n,i),t.texShape=c),r!=null){let d=gf(n),h,p=c[1],f=c[0],m=r instanceof Uint8Array;i?([p,f]=tu(c[0],c[1]),h=new aX(d,m)):h=new rX(d,m);let g=this.makeTensorInfo([f,p],s);m?this.texData.get(g.dataId).usage=ys.PIXELS:this.texData.get(g.dataId).usage=ys.UPLOAD,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(g.dataId),p,f,r);let A=[[f,p]],y=!0,x=this.runWebGLProgram(h,[g],s,A,y),b=this.texData.get(x.dataId);t.texture=b.texture,t.texShape=b.texShape,t.isPacked=b.isPacked,t.usage=b.usage,this.disposeIntermediateTensorInfo(g),this.texData.delete(x.dataId),t.values=null,l&&(this.uploadWaitMs+=w.now()-u)}else{let d=this.acquireTexture(c,o,s,i);t.texture=d}}convertAndCacheOnCPU(e,t){let n=this.texData.get(e),{dtype:s}=n;return this.releaseGPUData(e),t!=null&&(n.values=bK(t,s)),n.values}acquireTexture(e,t,n,s){if(this.numBytesInGPU+=this.computeBytes(e,n),!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,s)}computeBytes(e,t){return e[0]*e[1]*w.bytesPerElement(t)}};lu.nextDataId=0;function bK(e,t){if(t==="float32"||t==="complex64")return e;if(t==="int32"||t==="bool"){let n=t==="int32"?new Int32Array(e.length):new Uint8Array(e.length);for(let s=0;s<n.length;++s)n[s]=Math.round(e[s]);return n}else throw new Error(`Unknown dtype ${t}`)}var vK="3.9.0";function G6(){Q().set("WEBGL_FORCE_F16_TEXTURES",!0)}rc.isBrowser()&&_l("webgl",()=>new lu,2);var wK={forceHalfFloat:G6},j6=`
if (isnan(a)) return a;
if (isnan(b)) return b;
`,uu=class{constructor(e,t,n){this.variableNames=["A","B"],this.outputShape=D.assertAndGetBroadcastShape(t,n),this.enableShapeUniforms=bs(this.outputShape.length),this.userCode=`
float binaryOperation(float a, float b) {
${e}
}
void main() {
float a = getAAtOutCoords();
float b = getBAtOutCoords();
setOutput(binaryOperation(a, b));
}
`}},If=`
result.r = isNaN.r > 0. ? NAN : result.r;
result.g = isNaN.g > 0. ? NAN : result.g;
result.b = isNaN.b > 0. ? NAN : result.b;
result.a = isNaN.a > 0. ? NAN : result.a;
`,Yc=class{constructor(e,t,n,s=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=D.assertAndGetBroadcastShape(t,n);let r=this.outputShape.length;this.enableShapeUniforms=bs(r);let a="";if(s)if(r===0||w.sizeFromShape(this.outputShape)===1)a=`
result.y = 0.;
result.z = 0.;
result.w = 0.;
`;else if(a=`
${ht(r)} coords = getOutputCoords();
`,r===1)this.enableShapeUniforms?a+=`
result.y = (coords + 1) >= outShape ? 0. : result.y;
result.z = 0.;
result.w = 0.;
`:a+=`
result.y = (coords + 1) >= ${this.outputShape[0]} ? 0. : result.y;
result.z = 0.;
result.w = 0.;
`;else{let i=In("coords",r);this.enableShapeUniforms?a+=`
bool nextRowOutOfBounds =
(${i[r-2]} + 1) >= outShape[${r} - 2];
bool nextColOutOfBounds =
(${i[r-1]} + 1) >= outShape[${r} - 1];
result.y = nextColOutOfBounds ? 0. : result.y;
result.z = nextRowOutOfBounds ? 0. : result.z;
result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;
`:a+=`
bool nextRowOutOfBounds =
(${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);
${a}
setOutput(result);
}
`}};function Yn(e){let{inputs:t,backend:n}=e,{x:s}=t;return n.incRef(s.dataId),{dataId:s.dataId,shape:s.shape,dtype:s.dtype}}var kK={kernelName:ja,backendName:"webgl",kernelFunc:Yn};function pa(e){let{inputs:t,backend:n}=e,{real:s,imag:r}=t,a=n.makeTensorInfo(s.shape,"complex64"),o=n.texData.get(a.dataId),i=Yn({inputs:{x:s},backend:n}),l=Yn({inputs:{x:r},backend:n});return o.complexTensorInfos={real:i,imag:l},a}var IK={kernelName:Yd,backendName:"webgl",kernelFunc:pa},q6="return (a < 0.) ? b * a : a;",X6=`
vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function SK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{alpha:a}=s,o=n.makeTensorInfo([],"float32",w.createScalarValue(a,"float32")),i=Q().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Yc(X6,r.shape,o.shape):new uu(q6,r.shape,o.shape),l=n.runWebGLProgram(i,[r,o],r.dtype);return n.disposeIntermediateTensorInfo(o),l}var CK={kernelName:qa,backendName:"webgl",kernelFunc:SK},K6="return (a < 0.) ? b * a : a;",Z6=`
vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function TK(e){let{inputs:t,backend:n}=e,{x:s,alpha:r}=t,a=Q().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Yc(Z6,s.shape,r.shape):new uu(K6,s.shape,r.shape);return n.runWebGLProgram(a,[s,r],s.dtype)}var NK={kernelName:oo,backendName:"webgl",kernelFunc:TK},Y6="if (isnan(x)) return x;",EK=`
if (isnan(a)) return a;
if (isnan(b)) return b;
`,RK=`
result.r = isNaN.r > 0. ? NAN : result.r;
result.g = isNaN.g > 0. ? NAN : result.g;
result.b = isNaN.b > 0. ? NAN : result.b;
result.a = isNaN.a > 0. ? NAN : result.a;
`;function Je({opSnippet:e,packedOpSnippet:t,cpuKernelImpl:n,dtype:s}){return({inputs:r,backend:a})=>{let{x:o}=r,i=a,l=s||o.dtype;if(i.shouldExecuteOnCPU([o])&&n!=null){let d=i.texData.get(o.dataId),h=n(d.values,l);return i.makeTensorInfo(o.shape,l,h)}let u=Q().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,c;return u?c=new iu(o.shape,t):c=new ha(o.shape,e),i.runWebGLProgram(c,[o],l)}}function ln({opSnippet:e,packedOpSnippet:t,checkOutOfBounds:n=!1,supportsComplex:s=!1,cpuKernelImpl:r,dtype:a}){return({inputs:o,backend:i})=>{let{a:l,b:u}=o,c=i;if(s&&l.dtype==="complex64"){let f=c.texData.get(l.dataId),m=c.texData.get(u.dataId),[g,A]=[[f.complexTensorInfos.real,m.complexTensorInfos.real],[f.complexTensorInfos.imag,m.complexTensorInfos.imag]].map(x=>{let[b,v]=x,k={dataId:b.dataId,dtype:b.dtype,shape:l.shape},S={dataId:v.dataId,dtype:v.dtype,shape:u.shape},C=new uu(e,l.shape,u.shape);return c.runWebGLProgram(C,[k,S],Cs(b.dtype,v.dtype))}),y=pa({inputs:{real:g,imag:A},backend:c});return c.disposeIntermediateTensorInfo(g),c.disposeIntermediateTensorInfo(A),y}let d=a||Cs(l.dtype,u.dtype);if((l.dtype==="string"||u.dtype==="string"||c.shouldExecuteOnCPU([l,u]))&&r!=null){let f=c.texData.get(l.dataId).values,m=c.texData.get(u.dataId).values,g=l.dtype==="string"?D.fromUint8ToStringArray(f):f,A=l.dtype==="string"?D.fromUint8ToStringArray(m):m,[y,x]=r(l.shape,u.shape,g,A,d),b=c.makeTensorInfo(x,d),v=c.texData.get(b.dataId);return v.values=y,b}let h=Q().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,p;return h?p=new Yc(t,l.shape,u.shape,n):p=new uu(e,l.shape,u.shape),c.runWebGLProgram(p,[l,u],d)}}function Sf(e,t=!1){if(e==="linear")return t?iK:nK;if(e==="relu")return t?uK:rK;if(e==="elu")return t?lK:sK;if(e==="relu6")return t?cK:aK;if(e==="prelu")return t?Z6:K6;if(e==="leakyrelu")return t?X6:q6;if(e==="sigmoid")return t?dK:oK;throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}var J6=class{constructor(e,t,n,s=!1,r=!1,a=!1,o=null,i=!1,l=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=n,this.enableShapeUniforms=bs(this.outputShape.length);let u=s?e[1]:e[2],c=Math.ceil(u/2),d=s?"i * 2, rc.y":"rc.y, i * 2",h=r?"rc.z, i * 2":"i * 2, rc.z",p=s?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],f=r?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],m="",g="";o&&(i?m=`vec4 activation(vec4 a) {
vec4 b = getPreluActivationWeightsAtOutCoords();
${o}
}`:l?m=`vec4 activation(vec4 a) {
vec4 b = getLeakyreluAlphaAtOutCoords();
${o}
}`:m=`vec4 activation(vec4 x) {
${o}
}`,g="result = activation(result);");let A=a?"result += getBiasAtOutCoords();":"";a&&this.variableNames.push("bias"),i&&this.variableNames.push("preluActivationWeights"),l&&this.variableNames.push("leakyreluAlpha");let y="rc.x",x="rc.x";e[0]<t[0]?y=`int(min(float(rc.x), ${e[0]-1}.))`:t[0]<e[0]&&(x=`int(min(float(rc.x), ${t[0]-1}.))`),this.userCode=`
${m}
// Don't use uniform for sharedDimensionPacked for performance.
const float sharedDimension = ${c}.0;
vec4 dot2x2ARowBCol(ivec3 rc) {
vec4 result = vec4(0);
for (int i = 0; i < ${c}; i++) {
int batchA = ${y};
int batchB = ${x};
vec4 a = getMatrixA(batchA, ${d});
vec4 b = getMatrixB(batchB, ${h});
// These swizzled products need to be separately added.
// See: https://github.com/tensorflow/tfjs/issues/1735
result += (${p[0]} * ${f[0]});
result += (${p[1]} * ${f[1]});
}
return result;
}
void main() {
ivec3 rc = getOutputCoords();
vec4 result = dot2x2ARowBCol(rc);
${A}
${g}
setOutput(result);
}
`}},Q6={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},e4=class{constructor(e,t,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=D.assertAndGetBroadcastShape(t,n),this.userCode=`
float binaryOpComplex(
float areal, float aimag, float breal, float bimag) {
${e}
}
void main() {
float areal = getARealAtOutCoords();
float aimag = getAImagAtOutCoords();
float breal = getBRealAtOutCoords();
float bimag = getBImagAtOutCoords();
setOutput(binaryOpComplex(areal, aimag, breal, bimag));
}
`}},t4="return a * b;";function B2(e){let{inputs:t,backend:n}=e,{a:s,b:r}=t,a=D.upcastType(s.dtype,r.dtype);if(s.dtype==="complex64"){let i=n.texData.get(s.dataId),l=n.texData.get(r.dataId),u=new e4(Q6.REAL,s.shape,r.shape),c=new e4(Q6.IMAG,s.shape,r.shape),d=[{dataId:i.complexTensorInfos.real.dataId,dtype:i.complexTensorInfos.real.dtype,shape:s.shape},{dataId:i.complexTensorInfos.imag.dataId,dtype:i.complexTensorInfos.imag.dtype,shape:s.shape},{dataId:l.complexTensorInfos.real.dataId,dtype:l.complexTensorInfos.real.dtype,shape:r.shape},{dataId:l.complexTensorInfos.imag.dataId,dtype:l.complexTensorInfos.imag.dtype,shape:r.shape}],h=n.runWebGLProgram(u,d,"float32"),p=n.runWebGLProgram(c,d,"float32"),f=pa({inputs:{real:h,imag:p},backend:n});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(p),f}if(n.shouldExecuteOnCPU([s,r])){let i=n.texData.get(s.dataId),l=n.texData.get(r.dataId),[u,c]=CX(s.shape,r.shape,i.values,l.values,a),d=n.makeTensorInfo(c,a),h=n.texData.get(d.dataId);return h.values=u,d}let o;return Q().getBool("WEBGL_PACK_BINARY_OPERATIONS")?o=new Yc(t4,s.shape,r.shape):o=new uu(t4,s.shape,r.shape),n.runWebGLProgram(o,[s,r],a)}var _K={kernelName:no,backendName:"webgl",kernelFunc:B2};function DK(e,t,n){let s=[Jo(e.shape),...Qo(e.shape)],r={dtype:e.dtype,shape:s,dataId:e.dataId},a=[Jo(t),...Qo(t)],o=new B6(a,s),i=!0,l=[s],u=n.runWebGLProgram(o,[r],e.dtype,l,i);return{dataId:u.dataId,shape:t,dtype:u.dtype}}function ye(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{shape:a}=s,o=n,i=w.sizeFromShape(r.shape),l=w.inferFromImplicitShape(a,i),u=w.sizeFromShape(l);w.assert(i===u,()=>`The new shape (${l}) has ${u} elements and the old shape (${r.shape}) has ${i} elements. The new shape and old shape must have the same number of elements.`);let c=o.texData.get(r.dataId);return c.isPacked&&!Kc(r.shape,l)&&!(c.texture!==null&&Kc(c.shape,l))?DK(r,l,o):(o.incRef(r.dataId),{dataId:r.dataId,shape:l,dtype:r.dtype})}var $K={kernelName:ll,backendName:"webgl",kernelFunc:ye},n4=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:s,inSize:r,outSize:a}=e;this.outputShape=[s,a];let o=Math.floor(n/4)*4,i=n%4,l="sumValue += dot(values, ones);";if(t!=null){let c=1/t;l=`sumValue += dot(values * ${w.isInt(c)?c.toPrecision(2):c}, ones);`}let u="";r%n>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 * ${n};
float sumValue = 0.0;
for (int i = 0; i < ${o}; 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 + ${o};
if (${i===1}) {
vec4 values = vec4(getValue(batch, inIdx), 0.0, 0.0, 0.0);
${l}
} else if (${i===2}) {
vec4 values = vec4(
getValue(batch, inIdx),
getValue(batch, inIdx + 1), 0.0, 0.0);
${l}
} else if (${i===3}) {
vec4 values = vec4(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
getValue(batch, inIdx + 2), 0.0);
${l}
}
setOutput(sumValue);
}
`}},FK=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:s,inSize:r,outSize:a}=e;this.outputShape=[s,a];let o="0.0",i="";t==="prod"?o="1.0":t==="min"?(o="1.0 / 1e-20",i="min"):t==="max"&&(o="-1.0 / 1e-20",i="max");let l=`${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(n/4)*4,c=n%4,d=`
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 = ${i}(values, minMaxValue);
if (${t==="min"} || ${t==="max"}) {
minMaxValue = ${i}(values, minMaxValue);
bvec4 isNaN = isnan(values);
if (isNaN.r || isNaN.g || isNaN.b || isNaN.a) {
minMaxValue = vec4(NAN);
}
}
}
`,h="vec4";t==="all"?(o="1.0",d=`
bool reducedAllValue = all(values);
float floatedReducedAllValue = float(reducedAllValue);
allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0);
`,h="bvec4"):t==="any"&&(o="0.0",d=`
bool reducedAnyValue = any(values);
float floatedReducedAnyValue = float(reducedAnyValue);
anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);
`,h="bvec4");let p="";r%n>0&&(p=`
if (inIdx < 0 || inIdx >= ${r}) {
return initializationValue;
}
`),this.userCode=`
const float initializationValue = ${o};
const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
float getValue(int batch, int inIdx) {
${p}
return getX(batch, inIdx);
}
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
int outIdx = coords[1];
int inOffset = outIdx * ${n};
vec4 minMaxValue = vec4(${o});
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;
${h} values = ${h}(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
getValue(batch, inIdx + 2),
getValue(batch, inIdx + 3)
);
${d}
}
int inIdx = inOffset + ${u};
if (${c===1}) {
${h} values = ${h}(
getValue(batch, inIdx),
initializationValue,
initializationValue,
initializationValue
);
${d}
} else if (${c===2}) {
${h} values = ${h}(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
initializationValue,
initializationValue
);
${d}
} else if (${c===3}) {
${h} values = ${h}(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
getValue(batch, inIdx + 2),
initializationValue
);
${d}
}
setOutput(${l});
}
`}};function OK(e){let t=[];for(;t.length===0||t[t.length-1].outSize!==1;){let n=t.length?t[t.length-1].outSize:e[1],s=D.computeOptimalWindowSize(n);t.push({inSize:n,windowSize:s,outSize:Math.ceil(n/s)})}return t}function ni(e,t,n,s){let r=OK(e.shape),a=e;for(let o=0;o<r.length;o++){let{inSize:i,windowSize:l,outSize:u}=r[o],c,d;n==="mean"?c=o===0?new n4({windowSize:l,inSize:i,batchSize:e.shape[0],outSize:u},i):new n4({windowSize:l,inSize:i,batchSize:e.shape[0],outSize:u}):c=new FK({windowSize:l,inSize:i,batchSize:e.shape[0],outSize:u},n),d=a,a=s.runWebGLProgram(c,[a],t),d.dataId!==e.dataId&&s.disposeIntermediateTensorInfo(d)}return a}var PK=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let a=0;a<n.length;a++)n[a]=e[t[a]];this.outputShape=n,this.rank=n.length;let s=ht(this.rank),r=MK(t);this.userCode=`
void main() {
${s} resRC = getOutputCoords();
setOutput(getA(${r}));
}
`}};function MK(e){let t=e.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],s=new Array(t);for(let r=0;r<e.length;r++)s[e[r]]=n[r];return s.join()}var zK=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;let n=new Array(e.length);for(let u=0;u<n.length;u++)n[u]=e[t[u]];if(this.outputShape=n,this.rank=n.length,this.rank>6)throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);let s=ht(this.rank),r=L6("rc",this.rank),a=new Array(this.rank);for(let u=0;u<t.length;u++)a[t[u]]=r[u];let o=`vec2(${a.slice(-2).join()})`,i=`++${r[this.rank-1]} < ${n[this.rank-1]}`,l=`getChannel(getA(${a.join()}), ${o})`;this.userCode=`
void main() {
${s} rc = getOutputCoords();
vec4 result = vec4(0.);
result[0] = ${l};
if(${i}) {
result[1] = ${l};
}
--${r[this.rank-1]};
if(++${r[this.rank-2]} < ${n[this.rank-2]}) {
result[2] = ${l};
if(${i}) {
result[3] = ${l};
}
}
setOutput(result);
}
`}};function Cf(e,t,n){let s=Q().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new zK(e.shape,t):new PK(e.shape,t);return n.runWebGLProgram(s,[e],e.dtype)}function LK(e,t,n,s){let r=t,a=e.shape.length,o=w.parseAxisParam(r,e.shape),i=o,l=D.getAxesPermutation(i,a),u=l!=null,c=e;u&&(c=Cf(e,l,s),i=D.getInnerMostAxes(i.length,a)),D.assertAxesAreInnerMostDims("sum",i,a);let[d,h]=D.computeOutAndReduceShapes(c.shape,i),p=d;n&&(p=D.expandShapeToKeepDim(d,o));let f=w.sizeFromShape(h),g=w.sizeFromShape(e.shape)/f,A=ye({inputs:{x:c},attrs:{shape:[g,f]},backend:s}),y=Ph(e.dtype),x=ni(A,y,"sum",s),b=ye({inputs:{x},attrs:{shape:p},backend:s});return s.disposeIntermediateTensorInfo(A),s.disposeIntermediateTensorInfo(x),u&&s.disposeIntermediateTensorInfo(c),b}function Tf(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;return LK(r,a,o,n)}var BK={kernelName:Ao,backendName:"webgl",kernelFunc:Tf};function Sn(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{perm:a}=s,o=n,i=r.shape.length,l=new Array(i);for(let c=0;c<l.length;c++)l[c]=r.shape[a[c]];let u;if(o.shouldExecuteOnCPU([r])){let d=o.texData.get(r.dataId).values,h=L2(d,r.shape,r.dtype,a,l);u=o.makeTensorInfo(l,r.dtype);let p=o.texData.get(u.dataId);p.values=h}else u=Cf(r,a,o);return u}var WK={kernelName:ko,backendName:"webgl",kernelFunc:Sn},s4=1e3;function Nf({a:e,b:t,transposeA:n,transposeB:s,backend:r,bias:a=null,preluActivationWeights:o=null,leakyreluAlpha:i=0,activation:l=null}){let u=e.shape.length,c=t.shape.length,d=n?e.shape[u-2]:e.shape[u-1],h=s?t.shape[c-1]:t.shape[c-2],p=n?e.shape[u-1]:e.shape[u-2],f=s?t.shape[c-2]:t.shape[c-1],m=e.shape.slice(0,-2),g=t.shape.slice(0,-2),A=w.sizeFromShape(m),y=w.sizeFromShape(g),x=A===y||A===1||y===1;w.assert(u>=2&&c>=2&&x,()=>`Error in matMul: the input batch dimensions must either be the same or at least one input batch dimension must be 1. Got input batch dimensions of (${m}) and (${g}).`);let v=(A>y?e.shape.slice(0,-2):t.shape.slice(0,-2)).concat([p,f]);w.assert(d===h,()=>`Error in matMul: inner shapes (${d}) and (${h}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${n} and transposeB=${s} must match.`);let k=n?[A,d,p]:[A,p,d],S=s?[y,f,h]:[y,h,f],C=ye({inputs:{x:e},backend:r,attrs:{shape:k}}),_=ye({inputs:{x:t},backend:r,attrs:{shape:S}}),O=[C,_],E=Math.max(A,y),R=n?C.shape[1]:C.shape[2],T=a!=null,P=o!=null,V=l==="leakyrelu",j=l!=null?Sf(l,!0):null,q=T||P||V||j!=null,X;if((p===1||f===1)&&R>s4&&q===!1){let te=C,ne=_;n&&(te=Sn({inputs:{x:C},backend:r,attrs:{perm:[0,2,1]}}),O.push(te)),s&&(ne=Sn({inputs:{x:_},backend:r,attrs:{perm:[0,2,1]}}),O.push(ne));let se=f!==1,J=f===1,ie=te;se&&(ie=ye({inputs:{x:te},backend:r,attrs:{shape:[E,R,1]}}),O.push(ie));let le=f===1?2:1,he=ne;J&&(he=ye({inputs:{x:ne},backend:r,attrs:{shape:[E,1,R]}}),O.push(he));let Ae=B2({inputs:{a:ie,b:he},backend:r});X=Tf({inputs:{x:Ae},backend:r,attrs:{axis:le,keepDims:!0}}),O.push(Ae)}else{let te=Cs(e.dtype,t.dtype),ne=new J6(k,S,[E,p,f],n,s,T,j,P,V),se=[C,_];if(a!=null&&se.push(a),P&&se.push(o),V){let J=r.makeTensorInfo([],"float32",w.createScalarValue(i,"float32"));se.push(J),O.push(J)}X=r.runWebGLProgram(ne,se,te)}let ee=ye({inputs:{x:X},backend:r,attrs:{shape:v}});O.push(X);for(let te of O)r.disposeIntermediateTensorInfo(te);return ee}function VK(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a,bias:o,preluActivationWeights:i}=t,{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:d}=s;return Nf({a:r,b:a,transposeA:l,transposeB:u,backend:n,bias:o,preluActivationWeights:i,leakyreluAlpha:d,activation:c})}var UK={kernelName:Io,backendName:"webgl",kernelFunc:VK},r4="return abs(x);";function HK(e){let{inputs:t,backend:n}=e,{x:s}=t;if(n.shouldExecuteOnCPU([s])&&s.dtype!=="complex64"){let a=n.texData.get(s.dataId),o=M6(a.values);return n.makeTensorInfo(s.shape,s.dtype,o)}let r;return Q().getBool("WEBGL_PACK_UNARY_OPERATIONS")?r=new iu(s.shape,r4):r=new ha(s.shape,r4),n.runWebGLProgram(r,[s],s.dtype)}var GK={kernelName:ki,backendName:"webgl",kernelFunc:HK},jK=js+`
if (abs(x) > 1.) {
return NAN;
}
return acos(x);
`,qK=Je({opSnippet:jK}),XK={kernelName:Ii,backendName:"webgl",kernelFunc:qK},KK=js+`
if (x < 1.0) return NAN;
return log(x + sqrt(x * x - 1.0));`,ZK=Je({opSnippet:KK}),YK={kernelName:Si,backendName:"webgl",kernelFunc:ZK},a4="return a + b;",JK=ln({opSnippet:a4,packedOpSnippet:a4,supportsComplex:!0,cpuKernelImpl:iX}),QK={kernelName:Vr,backendName:"webgl",kernelFunc:JK},eZ=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((r,a)=>`T${a}`);let n=[];this.variableNames.forEach(r=>{n.push(`float v${r} = get${r}AtOutCoords();`)});let s=this.variableNames.map(r=>`v${r}`).join(" + ");this.userCode=`
void main() {
${n.join(`
`)}
float result = ${s};
setOutput(result);
}
`}},tZ=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((r,a)=>`T${a}`);let n=[];this.variableNames.forEach(r=>{n.push(`vec4 v${r} = get${r}AtOutCoords();`)});let s=this.variableNames.map(r=>`v${r}`).join(" + ");this.userCode=`
void main() {
${n.join(`
`)}
vec4 result = ${s};
setOutput(result);
}
`}};function Ef(e){let{inputs:t,backend:n}=e,s=t;if(s.length===1)return Yn({inputs:{x:s[0]},backend:n});if(s.length>Q().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let l=Math.floor(s.length/2),u=Ef({inputs:s.slice(0,l),backend:n}),c=Ef({inputs:s.slice(l),backend:n});return Ef({inputs:[u,c],backend:n})}let r=s.map(l=>l.dtype).reduce((l,u)=>Cs(l,u)),a=s.map(l=>l.shape),i=Q().getBool("WEBGL_PACK")?new tZ(s[0].shape,a):new eZ(s[0].shape,a);return n.runWebGLProgram(i,s,r)}var nZ={kernelName:Ta,backendName:"webgl",kernelFunc:Ef};function sZ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s,i=r.shape.length,l=w.parseAxisParam(a,r.shape),u=l,c=D.getAxesPermutation(u,i),d=r;c!=null&&(d=Sn({inputs:{x:r},backend:n,attrs:{perm:c}}),u=D.getInnerMostAxes(u.length,i)),D.assertAxesAreInnerMostDims("all",u,i);let[h,p]=D.computeOutAndReduceShapes(d.shape,u),f=w.sizeFromShape(p),m=ye({inputs:{x:d},backend:n,attrs:{shape:[-1,f]}}),g=ni(m,m.dtype,"all",n),A;if(o){let y=D.expandShapeToKeepDim(h,l);A=ye({inputs:{x:g},backend:n,attrs:{shape:y}})}else A=ye({inputs:{x:g},backend:n,attrs:{shape:h}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(g),c!=null&&n.disposeIntermediateTensorInfo(d),A}var rZ={kernelName:Ci,backendName:"webgl",kernelFunc:sZ};function aZ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s,i=r.shape.length,l=w.parseAxisParam(a,r.shape),u=l,c=D.getAxesPermutation(u,i),d=r;c!=null&&(d=Sn({inputs:{x:r},backend:n,attrs:{perm:c}}),u=D.getInnerMostAxes(u.length,i)),D.assertAxesAreInnerMostDims("any",u,i);let[h,p]=D.computeOutAndReduceShapes(d.shape,u),f=w.sizeFromShape(p),m=ye({inputs:{x:d},backend:n,attrs:{shape:[-1,f]}}),g=ni(m,m.dtype,"any",n),A;if(o){let y=D.expandShapeToKeepDim(h,l);A=ye({inputs:{x:g},backend:n,attrs:{shape:y}})}else A=ye({inputs:{x:g},backend:n,attrs:{shape:h}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(g),c!=null&&n.disposeIntermediateTensorInfo(d),A}var oZ={kernelName:Ti,backendName:"webgl",kernelFunc:aZ},iZ=class{constructor(e,t,n){this.variableNames=["A"];let{windowSize:s,batchSize:r,outSize:a}=e;n||this.variableNames.push("bestIndicesA"),this.outputShape=[r,a];let o=t==="max"?">":"<",i=n?"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 * ${s};
int bestIndex = inOffset;
float bestValue = getA(batch, bestIndex);
for (int i = 0; i < ${s}; i++) {
int inIdx = ${i};
float candidate = getA(batch, inIdx);
if (candidate ${o} bestValue) {
bestValue = candidate;
bestIndex = inIdx;
}
}
setOutput(float(bestIndex));
}
`}},lZ=class{constructor(e,t,n,s){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,w.assert(e.length>2,()=>`Packed arg${n.charAt(0).toUpperCase()+n.slice(1)} supports only inputs with rank above 2.`);let r=e[e.length-1],a=Math.ceil(r/t);this.outputShape=e.slice(0,-1),a>1&&this.outputShape.push(a),s||this.variableNames.push("bestIndicesA");let o=this.outputShape,i=o.length,l=ht(i),u=In("coords",i),c,d;if(a===1){d=i+1;let S=ht(d);c=`
${S} sourceLocR = ${S}(${u.join()}, 0);
++${u[i-1]};
${S} sourceLocG = ${S}(${u.join()}, 0);
++${u[i-2]};
${S} sourceLocA = ${S}(${u.join()}, 0);
--${u[i-1]};
${S} sourceLocB = ${S}(${u.join()}, 0);
--${u[i-2]};`}else d=i,c=`
${l} sourceLocR = coords;
++${u[i-1]};
${l} sourceLocG = coords;
++${u[i-2]};
${l} sourceLocA = coords;
--${u[i-1]};
${l} sourceLocB = coords;
--${u[i-2]};`;let h=["x","y","z","w","u","v"].slice(0,d),p="."+h[d-1],f=h.map(S=>"int "+S),m=In("sourceLocR",d-1).concat("inIdx.r"),g=In("sourceLocG",d-1).concat("inIdx.g"),A=In("sourceLocB",d-1).concat("inIdx.b"),y=In("sourceLocA",d-1).concat("inIdx.a"),x=n==="max"?"greaterThan":"lessThan",b=s?"":`
inIdx = round(vec4(getBestIndicesAChannel(${m.join()}),
getBestIndicesAChannel(${g.join()}),
getBestIndicesAChannel(${A.join()}),
getBestIndicesAChannel(${y.join()})));`,v=`vec4(
getAChannel(${m.join()}),
hasNextCol ? getAChannel(${g.join()}) : 0.,
hasNextRow ? getAChannel(${A.join()}) : 0.,
hasNextRow && hasNextCol ? getAChannel(${y.join()}) : 0.)`,k=s?"":`
float getBestIndicesAChannel(${f.join()}) {
return getChannel(getBestIndicesA(${h.join()}),
vec2(${h.slice(-2).join()}));
}`;this.userCode=`
float getAChannel(${f.join()}) {
return getChannel(getA(${h.join()}),
vec2(${h.slice(-2).join()}));
}
${k}
void main() {
${l} coords = getOutputCoords();
bool hasNextCol = ${u[i-1]} < ${o[i-1]-1};
bool hasNextRow = ${u[i-2]} < ${o[i-2]-1};
${c}
ivec4 srcIdx = ivec4(sourceLocR${p}, sourceLocG${p},
sourceLocB${p}, sourceLocA${p}) * ${t};
ivec4 inIdx = srcIdx;
vec4 bestIndex = vec4(inIdx);
vec4 bestValue = ${v};
for (int i = 0; i < ${t}; i++) {
inIdx = srcIdx;
${b}
vec4 candidate = ${v};
bvec4 nan = isnan(candidate);
bvec4 replace = bvec4(
vec4(${x}(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 o4(e,t,n,s=null){let r=t.shape[0],a=t.shape[1];s!=null&&(r=s.shape[0],a=s.shape[1]);let o=D.computeOptimalWindowSize(a),i={windowSize:o,inSize:a,batchSize:r,outSize:Math.ceil(a/o)},l=new iZ(i,n,s==null),u=[t];s!=null&&u.push(s);let c=e.runWebGLProgram(l,u,"int32");if(c.shape[1]===1)return c;let d=o4(e,t,n,c);return e.disposeIntermediateTensorInfo(c),d}function i4(e,t,n,s=null){let r=s!=null?s.shape:t.shape,a=r[r.length-1],o=D.computeOptimalWindowSize(a),i=new lZ(r,o,n,s==null),l=s==null?[t]:[t,s],u=e.runWebGLProgram(i,l,"int32");if(u.shape.length===t.shape.length){let c=i4(e,t,n,u);return e.disposeIntermediateTensorInfo(u),c}return u}function l4(e,t,n,s){let r=[n];if(D.assertAxesAreInnerMostDims("arg"+s.charAt(0).toUpperCase()+s.slice(1),r,t.shape.length),!Q().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let a=[],o=e.texData.get(t.dataId),i=o!==null&&o.isPacked,l=t;i&&(l=e.unpackTensor(t),a.push(l));let[u,c]=D.computeOutAndReduceShapes(l.shape,r),d=w.sizeFromShape(c),h=ye({inputs:{x:l},backend:e,attrs:{shape:[-1,d]}});a.push(h);let p=o4(e,h,s);a.push(p);let f=ye({inputs:{x:p},backend:e,attrs:{shape:u}});return a.forEach(m=>e.disposeIntermediateTensorInfo(m)),f}return i4(e,t,s)}function uZ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a}=s,o=w.parseAxisParam(a,r.shape),i=D.getAxesPermutation(o,r.shape.length),l=r,u=[];i!=null&&(l=Sn({inputs:{x:r},backend:n,attrs:{perm:i}}),u.push(l),o=D.getInnerMostAxes(o.length,l.shape.length)),D.assertAxesAreInnerMostDims("argMax",[o[0]],l.shape.length);let c=l4(n,l,o[0],"max");return u.forEach(d=>n.disposeIntermediateTensorInfo(d)),c}var cZ={kernelName:Na,backendName:"webgl",kernelFunc:uZ};function dZ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a}=s,o=w.parseAxisParam(a,r.shape),i=D.getAxesPermutation(o,r.shape.length),l=r,u=[];i!=null&&(l=Sn({inputs:{x:r},backend:n,attrs:{perm:i}}),u.push(l),o=D.getInnerMostAxes(o.length,l.shape.length)),D.assertAxesAreInnerMostDims("argMin",[o[0]],l.shape.length);let c=l4(n,l,o[0],"min");return u.forEach(d=>n.disposeIntermediateTensorInfo(d)),c}var hZ={kernelName:Ou,backendName:"webgl",kernelFunc:dZ},pZ=js+`
if (abs(x) > 1.) {
return NAN;
}
return asin(x);
`,fZ=Je({opSnippet:pZ}),mZ={kernelName:Ni,backendName:"webgl",kernelFunc:fZ},gZ=js+"return log(x + sqrt(x * x + 1.0));",AZ=Je({opSnippet:gZ}),yZ={kernelName:Ei,backendName:"webgl",kernelFunc:AZ},xZ=js+`
return atan(x);
`,bZ=Je({opSnippet:xZ}),vZ={kernelName:Ri,backendName:"webgl",kernelFunc:bZ},wZ=EK+`
return atan(a, b);
`,kZ=`
vec4 result = atan(a, b);
vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
`+RK+`
return result;
`,IZ=ln({opSnippet:wZ,packedOpSnippet:kZ}),SZ={kernelName:Di,backendName:"webgl",kernelFunc:IZ},CZ=js+`
if ((x < -1.0) || (x > 1.0)) return NAN;
return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,TZ=Je({opSnippet:CZ}),NZ={kernelName:_i,backendName:"webgl",kernelFunc:TZ},Jc=class{constructor(e,t,n,s=!1,r=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let a=e.filterWidth,o=e.strideHeight,i=e.strideWidth,l=e.dilationHeight,u=e.dilationWidth,c=e.effectiveFilterHeight,d=e.effectiveFilterWidth,h=e.padInfo.top,p=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) * ${e.inChannels} + d`,A="0.0";if(f||(A="-1.0 / 1e-20"),n){let S=">=";this.userCode=`
const ivec2 strides = ivec2(${o}, ${i});
const ivec2 pads = ivec2(${h}, ${p});
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 < ${c};
wR += ${l}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${d};
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 ${S} currMinMaxValue) {
minMaxValue = value;
minMaxValueFound = 1.0;
minMaxPosition = ${s?r?m:g:`wR * ${d} + wC`};
}
}
}
setOutput(float(minMaxPosition));
}
`;return}let y="max",x=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(x="avgValue / count");let b=Math.floor(a/4)*4,v=a%4,k=`
if (${f}) {
avgValue += dot(values, ones);
} else {
minMaxValue = ${y}(values, minMaxValue);
}
`;this.userCode=`
const ivec2 strides = ivec2(${o}, ${i});
const ivec2 pads = ivec2(${h}, ${p});
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 xR, int xC, int d) {
if (xC < 0 || xC >= ${e.inWidth}) {
return initializationValue;
}
count += 1.0;
return getX(batch, xR, xC, d);
}
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d = coords[3];
ivec2 xRCCorner = coords.yz * strides - pads;
int xRCorner = xRCCorner.x;
int xCCorner = xRCCorner.y;
// max/min x(?, ?, d) to get y(yR, yC, d).
// ? = to be determined
vec4 minMaxValue = vec4(${A});
float avgValue = 0.0;
count = 0.0;
for (int wR = 0; wR < ${c};
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)
);
${k}
}
int xC = xCCorner + ${b};
if (${v===1}) {
vec4 values = vec4(
getValue(batch, xR, xC, d),
initializationValue,
initializationValue,
initializationValue
);
${k}
} else if (${v===2}) {
vec4 values = vec4(
getValue(batch, xR, xC, d),
getValue(batch, xR, xC + ${u}, d),
initializationValue,
initializationValue
);
${k}
} else if (${v===3}) {
vec4 values = vec4(
getValue(batch, xR, xC, d),
getValue(batch, xR, xC + ${u}, d),
getValue(batch, xR, xC + 2 * ${u}, d),
initializationValue
);
${k}
}
}
setOutput(${x});
}
`}},W2=class{constructor(e,t,n,s=!1,r=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let a=e.filterWidth,o=e.strideDepth,i=e.strideHeight,l=e.strideWidth,u=e.dilationDepth,c=e.dilationHeight,d=e.dilationWidth,h=e.effectiveFilterDepth,p=e.effectiveFilterHeight,f=e.effectiveFilterWidth,m=e.padInfo.front,g=e.padInfo.top,A=e.padInfo.left;this.outputShape=e.outShape;let y=t==="avg",x="0.0";if(y||(x="-1.0 / 1e-20"),n){let _=">=";this.userCode=`
const ivec3 strides =
ivec3(${o}, ${i}, ${l});
const ivec3 pads = ivec3(${m}, ${g}, ${A});
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 < ${h};
wD += ${u}) {
int xD = xDCorner + wD;
if (xD < 0 || xD >= ${e.inDepth}) {
continue;
}
for (int wR = 0; wR < ${p};
wR += ${c}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${f};
wC += ${d}) {
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 = ${s?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 * ${p} * ${f} +
wR * ${f} + wC`};
}
}
}
}
setOutput(float(minMaxPosition));
}
`;return}let b="max",v=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(v="avgValue / count");let k=Math.floor(a/4)*4,S=a%4,C=`
if (${y}) {
avgValue += dot(values, ones);
} else {
minMaxValue = ${b}(values, minMaxValue);
}
`;this.userCode=`
const ivec3 strides =
ivec3(${o}, ${i}, ${l});
const ivec3 pads = ivec3(${m}, ${g}, ${A});
const float initializationValue = ${x};
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 >= ${e.inWidth}) {
return initializationValue;
}
count += 1.0;
return getX(batch, xD, xR, xC, ch);
}
void main() {
ivec5 coords = getOutputCoords();
int batch = coords.x;
int ch = coords.u;
ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
int xDCorner = xCorner.x;
int xRCorner = xCorner.y;
int xCCorner = xCorner.z;
// max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).
// ? = to be determined
vec4 minMaxValue = vec4(${x});
float avgValue = 0.0;
count = 0.0;
for (int wD = 0; wD < ${h};
wD += ${u}) {
int xD = xDCorner + wD;
if (xD < 0 || xD >= ${e.inDepth}) {
continue;
}
for (int wR = 0; wR < ${p};
wR += ${c}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${k}; wC += 4) {
int xC = xCCorner + wC * ${d};
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
getValue(batch, xD, xR, xC + ${d}, ch),
getValue(batch, xD, xR, xC + 2 * ${d}, ch),
getValue(batch, xD, xR, xC + 3 * ${d}, ch)
);
${C}
}
int xC = xCCorner + ${k};
if (${S===1}) {
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
initializationValue,
initializationValue,
initializationValue
);
${C}
} else if (${S===2}) {
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
getValue(batch, xD, xR, xC + ${d}, ch),
initializationValue,
initializationValue
);
${C}
} else if (${S===3}) {
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
getValue(batch, xD, xR, xC + ${d}, ch),
getValue(batch, xD, xR, xC + 2 * ${d}, ch),
initializationValue
);
${C}
}
}
setOutput(${v});
}
}
`}};function EZ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t;nu(r,"avgPool");let{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=s,u=1;w.assert(D.eitherStridesOrDilationsAreOne(o,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${o} and dilations '${u}'`);let c=D.computePool2DInfo(r.shape,a,o,u,i,l);if(c.filterWidth===1&&c.filterHeight===1&&w.arraysEqual(c.inShape,c.outShape))return Yn({inputs:{x:r},backend:n});let d=new Jc(c,"avg",!1);return n.runWebGLProgram(d,[r],"float32")}var RZ={kernelName:Ea,backendName:"webgl",kernelFunc:EZ};function _Z(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{filterSize:a,strides:o,pad:i,dimRoundingMode:l,dataFormat:u}=s,c=[1,1,1],d=D.computePool3DInfo(r.shape,a,o,c,i,l,u),h=new W2(d,"avg",!1);return n.runWebGLProgram(h,[r],"float32")}var DZ={kernelName:Pu,backendName:"webgl",kernelFunc:_Z},$Z=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,s=e.strideHeight,r=e.strideWidth,a=e.dilationHeight,o=e.dilationWidth,i=e.effectiveFilterHeight,l=e.effectiveFilterWidth,u=i-1-e.padInfo.top,c=l-1-e.padInfo.left,d=1/(t*n);this.userCode=`
const ivec2 pads = ivec2(${u}, ${c});
const float avgMultiplier = float(${d});
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 < ${i};
wR += ${a}) {
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 < ${l};
wC+= ${o}) {
float dyC = float(dyCCorner + wC) / ${r}.0;
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
float dyValue = getDy(b, idyR, idyC, d);
dotProd += dyValue * avgMultiplier;
}
}
setOutput(dotProd);
}
`}},FZ=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,s=e.filterWidth,r=e.strideDepth,a=e.strideHeight,o=e.strideWidth,i=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,c=e.effectiveFilterDepth,d=e.effectiveFilterHeight,h=e.effectiveFilterWidth,p=c-1-e.padInfo.front,f=d-1-e.padInfo.top,m=h-1-e.padInfo.left,g=1/(t*n*s);this.userCode=`
const ivec3 pads = ivec3(${p}, ${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 < ${c};
wD += ${i}) {
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 < ${d};
wR += ${l}) {
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 < ${h};
wC += ${u}) {
float dyC = float(dyCCorner + wC) / ${o}.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 OZ(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a}=t,o=a,{filterSize:i,strides:l,pad:u,dimRoundingMode:c}=s,d=[1,1,1],h=D.computePool3DInfo(o.shape,i,l,d,u,c),p=new FZ(h);return n.runWebGLProgram(p,[r],o.dtype)}var PZ={kernelName:Kd,backendName:"webgl",kernelFunc:OZ};function MZ(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a}=t,o=a;nu([r,a],"avgPoolGrad");let{filterSize:i,strides:l,pad:u}=s,c=D.computePool2DInfo(o.shape,i,l,1,u),d=new $Z(c);return n.runWebGLProgram(d,[r],o.dtype)}var zZ={kernelName:Xd,backendName:"webgl",kernelFunc:MZ};function LZ(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a}=t,{transposeA:o,transposeB:i}=s;return Nf({a:r,b:a,transposeA:o,transposeB:i,backend:n})}var BZ={kernelName:Ra,backendName:"webgl",kernelFunc:LZ},WZ=class{constructor(e,t,n,s,r,a){this.outputShape=[],this.variableNames=["x","mean","variance"],D.assertAndGetBroadcastShape(e,t),D.assertAndGetBroadcastShape(e,n);let o="0.0";s!=null&&(D.assertAndGetBroadcastShape(e,s),this.variableNames.push("offset"),o="getOffsetAtOutCoords()");let i="1.0";r!=null&&(D.assertAndGetBroadcastShape(e,r),this.variableNames.push("scale"),i="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
void main() {
float x = getXAtOutCoords();
float mean = getMeanAtOutCoords();
float variance = getVarianceAtOutCoords();
float offset = ${o};
float scale = ${i};
float inv = scale * inversesqrt(variance + float(${a}));
setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));
}
`}},VZ=class{constructor(e,t,n,s,r,a){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],D.assertAndGetBroadcastShape(e,t),D.assertAndGetBroadcastShape(e,n);let o="vec4(0.0)";s!=null&&(D.assertAndGetBroadcastShape(e,s),this.variableNames.push("offset"),o="getOffsetAtOutCoords()");let i="vec4(1.0)";r!=null&&(D.assertAndGetBroadcastShape(e,r),this.variableNames.push("scale"),i="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
void main() {
vec4 offset = ${o};
vec4 scale = ${i};
vec4 x = getXAtOutCoords();
vec4 mean = getMeanAtOutCoords();
vec4 variance = getVarianceAtOutCoords();
vec4 inv = scale * inversesqrt(variance + vec4(${a}));
setOutput((x - mean) * inv + offset);
}
`}},UZ=({inputs:e,backend:t,attrs:n})=>{let{x:s,mean:r,variance:a,offset:o,scale:i}=e;w.assert(r.shape.length===a.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),w.assert(o==null||r.shape.length===o.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),w.assert(i==null||r.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:l}=n;l==null&&(l=.001);let u=[s,r,a],c=null;o!=null&&(c=o.shape,u.push(o));let d=null;i!=null&&(d=i.shape,u.push(i));let h=Q().getBool("WEBGL_PACK_NORMALIZATION")?new VZ(s.shape,r.shape,a.shape,c,d,l):new WZ(s.shape,r.shape,a.shape,c,d,l);return t.runWebGLProgram(h,u,u[0].dtype)},HZ={kernelName:Ha,backendName:"webgl",kernelFunc:UZ},GZ=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=ht(this.rank);this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let n=jZ(this.rank),s,r=e.map((a,o)=>`sourceLoc.${V2[o]} = start[${o}] + coords.${V2[o]};`);s=`
${t} sourceLoc;
${t} coords = getOutputCoords();
${r.join(`
`)}
`,this.userCode=`
void main() {
${s}
setOutput(getSource(${n}));
}
`}},V2=["x","y","z","w","u","v"];function jZ(e){if(e===1)return"sourceLoc";if(e<=6)return V2.slice(0,e).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}var qZ=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let t=ht(this.rank),n=In("coords",this.rank),s=In("sourceLoc",this.rank),r=this.rank===1?"sourceLoc":`vec2(${s.slice(-2).join()})`,a=`getChannel(getSource(${s.join()}), ${r})`,o=`
result.x = ${a};
if (++${n[this.rank-1]} < ${e[this.rank-1]}) {
++${s[this.rank-1]};
result.y = ${a};
--${s[this.rank-1]};
}
`,i=this.rank===1?"":`
--${n[this.rank-1]};
if (++${n[this.rank-2]} < ${e[this.rank-2]}) {
++${s[this.rank-2]};
result.z = ${a};
if (++${n[this.rank-1]} < ${e[this.rank-1]}) {
++${s[this.rank-1]};
result.w = ${a};
}
}
`,l=this.rank<=4?`sourceLoc = coords +
${t}(${e.map((u,c)=>`start[${c}]`).join()});`:e.map((u,c)=>`${s[c]} = ${n[c]} + start[${c}];`).join(`
`);this.userCode=`
void main() {
${t} coords = getOutputCoords();
${t} sourceLoc;
${l}
vec4 result = vec4(0.);
${o}
${i}
setOutput(result);
}
`}};function XZ(e,t,n,s){let r=s.texData.get(e.dataId),a=s.makeTensorInfo(n,e.dtype),o=s.texData.get(a.dataId);Object.assign(o,r),o.refCount=1,o.shape=n,o.dtype=e.dtype;let i=xn.computeFlatOffset(t,w.computeStrides(e.shape));r.slice&&(i+=r.slice.flatOffset),o.slice={flatOffset:i,origDataId:r.slice&&r.slice.origDataId||e.dataId};let l=s.dataRefCount.get(o.slice.origDataId)||1;return s.dataRefCount.set(o.slice.origDataId,l+1),a}function cu(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{begin:a,size:o}=s,[i,l]=xn.parseSliceParams(r,a,o);if(xn.assertParamsValid(r,i,l),w.sizeFromShape(l)===0)return n.makeTensorInfo(l,r.dtype,[]);if(n.shouldExecuteOnCPU([r])||r.dtype==="string"){let d=n.texData.get(r.dataId),h=$X(d.values,i,l,r.shape,r.dtype);return n.makeTensorInfo(l,r.dtype,h)}let{isPacked:u}=n.texData.get(r.dataId),c=xn.isSliceContinous(r.shape,i,l);if(u||!c){let d=Q().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new qZ(l):new GZ(l),h=[i];return n.runWebGLProgram(d,[r],r.dtype,h)}return n.uploadToGPU(r.dataId),XZ(r,i,l,n)}var KZ={kernelName:hl,backendName:"webgl",kernelFunc:cu},ZZ=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockShape:a,crops:o}=s;w.assert(r.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let i=a.reduce((y,x)=>y*x),l=D.getReshaped(r.shape,a,i),u=D.getPermuted(l.length,a.length),c=D.getReshapedPermuted(r.shape,a,i),d=D.getSliceBeginCoords(o,a.length),h=D.getSliceSize(c,o,a.length),p=[],f=ye({inputs:{x:r},backend:n,attrs:{shape:l}}),m=Sn({inputs:{x:f},backend:n,attrs:{perm:u}}),g=ye({inputs:{x:m},backend:n,attrs:{shape:c}}),A=cu({inputs:{x:g},backend:n,attrs:{begin:d,size:h}});return p.push(f),p.push(m),p.push(g),p.forEach(y=>n.disposeIntermediateTensorInfo(y)),A},YZ={kernelName:$i,backendName:"webgl",kernelFunc:ZZ};function JZ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,weights:a}=t,{size:o}=s,i=n.readSync(r.dataId),l=n.readSync(a.dataId),u=P6(i,l,a.dtype,a.shape,o);return n.makeTensorInfo([o],a.dtype,u)}var QZ={kernelName:Zd,backendName:"webgl",kernelFunc:JZ},eY="return float(a != b);",u4=ln({opSnippet:eY,cpuKernelImpl:NX,dtype:"bool"}),tY={kernelName:el,backendName:"webgl",kernelFunc:u4};function Qc(e){let{inputs:t,backend:n}=e,{input:s}=t,r=n.texData.get(s.dataId);return Yn({inputs:{x:r.complexTensorInfos.real},backend:n})}var nY={kernelName:yh,backendName:"webgl",kernelFunc:Qc},sY="return float(int(x));";function rY(e,t){let n=new ha(e.shape,sY),s=t.runWebGLProgram(n,[e],"int32");return{dataId:s.dataId,shape:s.shape,dtype:s.dtype}}function U2(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{dtype:a}=s;if(a==="complex64"){if(r.dtype==="complex64")return Yn({inputs:{x:r},backend:n});let o=Pt(r.shape),i=U2({inputs:{x:r},backend:n,attrs:{dtype:"float32"}}),l=pa({inputs:{real:i,imag:o},backend:n});return o.dispose(),n.disposeIntermediateTensorInfo(i),l}if(r.dtype==="complex64"){let o=Qc({inputs:{input:r},backend:n}),i=U2({inputs:{x:o},backend:n,attrs:{dtype:a}});return n.disposeIntermediateTensorInfo(o),i}if(!w.hasEncodingLoss(r.dtype,a)){let o=Yn({inputs:{x:r},backend:n});return{dataId:o.dataId,shape:o.shape,dtype:a}}if(a==="int32")return rY(r,n);if(a==="bool"){let o=n.makeTensorInfo([],"bool",w.getTypedArrayFromDType("bool",1)),l=u4({inputs:{a:r,b:o},backend:n});return n.disposeIntermediateTensorInfo(o),l}throw new Error(`Error in Cast: failed to cast ${r.dtype} to ${a}`)}var aY={kernelName:_a,backendName:"webgl",kernelFunc:U2},c4="return ceil(x);",oY=Je({opSnippet:c4,packedOpSnippet:c4,cpuKernelImpl:uX}),iY={kernelName:Da,backendName:"webgl",kernelFunc:oY},lY=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));
}
`}},uY=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 cY(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{clipValueMin:a,clipValueMax:o}=s,i;Q().getBool("WEBGL_PACK_CLIP")?i=new uY(r.shape):i=new lY(r.shape);let l=[[a],[o]];return n.runWebGLProgram(i,[r],r.dtype,l)}var dY={kernelName:Ur,backendName:"webgl",kernelFunc:cY},hY=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 d4(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function pY(e){let{inputs:t,backend:n}=e,{x:s}=t,r=n.texData.get(s.dataId),a=new hY(s.shape),o=[d4(s,r.complexTensorInfos.real),d4(s,r.complexTensorInfos.imag)];return n.runWebGLProgram(a,o,o[0].dtype)}var fY={kernelName:Mu,backendName:"webgl",kernelFunc:pY},mY=class{constructor(e){this.outputShape=[],this.outputShape=D.computeOutShape(e,1),this.variableNames=e.map((a,o)=>`T${o}`);let t=new Array(e.length-1);t[0]=e[0][1];for(let a=1;a<t.length;a++)t[a]=t[a-1]+e[a][1];let n=[`if (yC < ${t[0]}) setOutput(getT0(yR, yC));`];for(let a=1;a<t.length;a++){let o=t[a-1];n.push(`else if (yC < ${t[a]}) setOutput(getT${a}(yR, yC-${o}));`)}let s=t.length,r=t[t.length-1];n.push(`else setOutput(getT${s}(yR, yC-${r}));`),this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
int yR = coords.x;
int yC = coords.y;
${n.join(`
`)}
}
`}},gY=class{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=D.computeOutShape(e,t);let n=this.outputShape,s=n.length,r=ht(s),a=In("coords",s),o=["x","y","z","w","u","v"].slice(0,s);this.variableNames=e.map((f,m)=>`T${m}`);let i=new Array(e.length-1);i[0]=e[0][t];for(let f=1;f<i.length;f++)i[f]=i[f-1]+e[f][t];let l=o[t],u=o.slice(-2),c=o.join(),d=`if (${l} < ${i[0]}) {
return getChannel(
getT0(${c}), vec2(${u.join()}));
}`;for(let f=1;f<i.length;f++){let m=i[f-1];d+=`
if (${l} < ${i[f]} && ${l} >= ${i[f-1]}) {
return getChannel(
getT${f}(${Rf(o,l,m)}),
vec2(${Rf(u,l,m)}));
}`}let h=i.length,p=i[i.length-1];d+=`
return getChannel(
getT${h}(${Rf(o,l,p)}),
vec2(${Rf(u,l,p)}));`,this.userCode=`
float getValue(${o.map(f=>"int "+f)}) {
${d}
}
void main() {
${r} coords = getOutputCoords();
vec4 result = vec4(getValue(${a}), 0., 0., 0.);
${a[s-1]} = ${a[s-1]} + 1;
if (${a[s-1]} < ${n[s-1]}) {
result.g = getValue(${a});
}
${a[s-2]} = ${a[s-2]} + 1;
if (${a[s-2]} < ${n[s-2]}) {
result.a = getValue(${a});
}
${a[s-1]} = ${a[s-1]} - 1;
if (${a[s-2]} < ${n[s-2]} &&
${a[s-1]} < ${n[s-1]}) {
result.b = getValue(${a});
}
setOutput(result);
}
`}};function Rf(e,t,n){let s=e.indexOf(t);return e.map((a,o)=>o===s?`${a} - ${n}`:a).join()}function _f(e){let{inputs:t,backend:n}=e,{input:s}=t,r=n.texData.get(s.dataId);return Yn({inputs:{x:r.complexTensorInfos.imag},backend:n})}var AY={kernelName:dh,backendName:"webgl",kernelFunc:_f};function du(e,t,n){let s=e[0].dtype;if(s==="complex64"){let c=e.map(m=>Qc({inputs:{input:m},backend:n})),d=e.map(m=>_f({inputs:{input:m},backend:n})),h=du(c,t,n),p=du(d,t,n),f=pa({inputs:{real:h,imag:p},backend:n});return c.forEach(m=>n.disposeIntermediateTensorInfo(m)),d.forEach(m=>n.disposeIntermediateTensorInfo(m)),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(p),f}let r=n.shouldExecuteOnCPU(e);if(s==="string"&&(r=!0),r){let c=e.map(A=>{let y=w.sizeFromShape(A.shape.slice(t));return ye({inputs:{x:A},backend:n,attrs:{shape:[-1,y]}})}),d=c.map(A=>({vals:n.readSync(A.dataId),shape:A.shape})),h=D.computeOutShape(c.map(A=>A.shape),1),p=c[0].shape[0]===1,f=cX(d,h,s,p),m=D.computeOutShape(e.map(A=>A.shape),t),g=n.makeTensorInfo(m,s,f);return c.forEach(A=>n.disposeIntermediateTensorInfo(A)),g}if(e.length>Q().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){let c=Math.floor(e.length/2),d=du(e.slice(0,c),t,n),h=du(e.slice(c),t,n),p=du([d,h],t,n);return n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(h),p}if(Q().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&e[0].shape.length>1){let c=new gY(e.map(d=>d.shape),t);return n.runWebGLProgram(c,e,s)}let{tensors2D:a,outShape:o}=yY(e,t,n),i=new mY(a.map(c=>c.shape)),l=n.runWebGLProgram(i,a,s);a.forEach(c=>n.disposeIntermediateTensorInfo(c));let u=ye({inputs:{x:l},attrs:{shape:o},backend:n});return n.disposeIntermediateTensorInfo(l),u}function yY(e,t,n){let s=D.computeOutShape(e.map(a=>a.shape),t);return{tensors2D:e.map(a=>ye({inputs:{x:a},attrs:{shape:[-1,w.sizeFromShape(a.shape.slice(t))]},backend:n})),outShape:s}}function h4(e){let{inputs:t,backend:n,attrs:s}=e,{axis:r}=s,a=w.parseAxisParam(r,t[0].shape)[0],o=D.computeOutShape(t.map(u=>u.shape),a);if(w.sizeFromShape(o)===0)return n.makeTensorInfo(o,t[0].dtype,[]);let i=t.filter(u=>w.sizeFromShape(u.shape)>0);if(i.length===1)return Yn({inputs:{x:i[0]},backend:n});let l=i.map(u=>u.shape);return D.assertParamsConsistent(l,a),du(i,a,n)}var xY={kernelName:Fi,backendName:"webgl",kernelFunc:h4},p4=class{constructor(e,t=!1,n=null,s=!1,r=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let a=e.padInfo.top,o=e.padInfo.left,i=e.strideHeight,l=e.strideWidth,u=e.dilationHeight,c=e.dilationWidth,d=e.filterHeight,h=e.filterWidth,p=Math.floor(e.inChannels/4)*4,f=e.inChannels%4,m=e.dataFormat==="channelsLast",g=m?1:2,A=m?2:3,y=m?3:1,x="",b="";n&&(s?x=`float activation(float a) {
float b = getPreluActivationWeightsAtOutCoords();
${n}
}`:r?x=`float activation(float a) {
float b = getLeakyreluAlphaAtOutCoords();
${n}
}`:x=`
float activation(float x) {
${n}
}
`,b="result = activation(result);");let v=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),s&&this.variableNames.push("preluActivationWeights"),r&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
${x}
const ivec2 strides = ivec2(${i}, ${l});
const ivec2 pads = ivec2(${a}, ${o});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d2 = coords[${y}];
ivec2 xRCCorner =
ivec2(coords[${g}], coords[${A}]) * 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 < ${d}; wR++) {
int xR = xRCorner + wR * ${u};
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${h}; wC++) {
int xC = xCCorner + wC * ${c};
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
for (int d1 = 0; d1 < ${p}; d1 += 4) {
vec4 wValues = vec4(
getW(wR, wC, d1, d2),
getW(wR, wC, d1 + 1, d2),
getW(wR, wC, d1 + 2, d2),
getW(wR, wC, d1 + 3, d2)
);
if (${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, ${p}) *
getW(wR, wC, ${p}, d2);
} else {
dotProd +=
getX(batch, ${p}, xR, xC) *
getW(wR, wC, ${p}, d2);
}
} else if (${f===2}) {
vec2 wValues = vec2(
getW(wR, wC, ${p}, d2),
getW(wR, wC, ${p} + 1, d2)
);
if (${m}) {
vec2 xValues = vec2(
getX(batch, xR, xC, ${p}),
getX(batch, xR, xC, ${p} + 1)
);
dotProd += dot(xValues, wValues);
} else {
vec2 xValues = vec2(
getX(batch, ${p}, xR, xC),
getX(batch, ${p} + 1, xR, xC)
);
dotProd += dot(xValues, wValues);
}
} else if (${f===3}) {
vec3 wValues = vec3(
getW(wR, wC, ${p}, d2),
getW(wR, wC, ${p} + 1, d2),
getW(wR, wC, ${p} + 2, d2)
);
if (${m}) {
vec3 xValues = vec3(
getX(batch, xR, xC, ${p}),
getX(batch, xR, xC, ${p} + 1),
getX(batch, xR, xC, ${p} + 2)
);
dotProd += dot(xValues, wValues);
} else {
vec3 xValues = vec3(
getX(batch, ${p}, xR, xC),
getX(batch, ${p} + 1, xR, xC),
getX(batch, ${p} + 2, xR, xC)
);
dotProd += dot(xValues, wValues);
}
}
}
}
float result = dotProd;
${v}
${b}
setOutput(result);
}
`}},bY=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,n=e.padInfo.top,s=e.padInfo.left,r=e.strideDepth,a=e.strideHeight,o=e.strideWidth,i=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,c=e.filterDepth,d=e.filterHeight,h=e.filterWidth,p=Math.floor(e.inChannels/4)*4,f=e.inChannels%4;this.userCode=`
const ivec3 strides = ivec3(${r}, ${a}, ${o});
const ivec3 pads = ivec3(${t}, ${n}, ${s});
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 < ${c}; wF++) {
int xF = xFCorner + wF * ${i};
if (xF < 0 || xF >= ${e.inDepth}) {
continue;
}
for (int wR = 0; wR < ${d}; wR++) {
int xR = xRCorner + wR * ${l};
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${h}; wC++) {
int xC = xCCorner + wC * ${u};
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
for (int d1 = 0; d1 < ${p}; d1 += 4) {
vec4 xValues = vec4(
getX(batch, xF, xR, xC, d1),
getX(batch, xF, xR, xC, d1 + 1),
getX(batch, xF, xR, xC, d1 + 2),
getX(batch, xF, xR, xC, d1 + 3)
);
vec4 wValues = vec4(
getW(wF, wR, wC, d1, d2),
getW(wF, wR, wC, d1 + 1, d2),
getW(wF, wR, wC, d1 + 2, d2),
getW(wF, wR, wC, d1 + 3, d2)
);
dotProd += dot(xValues, wValues);
}
if (${f===1}) {
dotProd +=
getX(batch, xF, xR, xC, ${p}) *
getW(wF, wR, wC, ${p}, d2);
} else if (${f===2}) {
vec2 xValues = vec2(
getX(batch, xF, xR, xC, ${p}),
getX(batch, xF, xR, xC, ${p} + 1)
);
vec2 wValues = vec2(
getW(wF, wR, wC, ${p}, d2),
getW(wF, wR, wC, ${p} + 1, d2)
);
dotProd += dot(xValues, wValues);
} else if (${f===3}) {
vec3 xValues = vec3(
getX(batch, xF, xR, xC, ${p}),
getX(batch, xF, xR, xC, ${p} + 1),
getX(batch, xF, xR, xC, ${p} + 2)
);
vec3 wValues = vec3(
getW(wF, wR, wC, ${p}, d2),
getW(wF, wR, wC, ${p} + 1, d2),
getW(wF, wR, wC, ${p} + 2, d2)
);
dotProd += dot(xValues, wValues);
}
}
}
}
setOutput(dotProd);
}
`}},vY=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"inputShape",type:"ivec3"},{name:"pad",type:"ivec2"},{name:"stride",type:"ivec2"},{name:"dilation",type:"ivec2"},{name:"inChannels",type:"int"},{name:"itemsPerBlockRow",type:"int"},{name:"outWidth",type:"int"}],this.outputShape=e,this.enableShapeUniforms=bs(this.outputShape.length);let{dataFormat:n}=t,s=kn(),r=n==="channelsLast",a=r?0:1,o=r?1:2,i=this.enableShapeUniforms?"if(blockIndex < outShape[1] && pos < outShape[0]) {":`if(blockIndex < ${e[1]} && pos < ${e[0]}) {`,l="";for(let u=0;u<=1;u++)for(let c=0;c<=1;c++)l+=`
blockIndex = rc.y + ${c};
pos = rc.x + ${u};
${i}
offsetY = int(blockIndex / outWidth) * stride[0] - pad[0];
d0 = offsetY + dilation[0] * (pos / itemsPerBlockRow);
if(d0 < inputShape[${a}] && 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[${o}] && d1 >= 0) {
ch = imod(pos, inChannels);
if (${r}) {
innerDims = vec2(d1, ch);
result[${u*2+c}] = getChannel(
getA(d0, int(innerDims.x),
int(innerDims.y)), innerDims);
} else {
innerDims = vec2(d0, d1);
result[${u*2+c}] = getChannel(
getA(ch, int(innerDims.x),
int(innerDims.y)), innerDims);
}
}
}
}
`;this.userCode=`
void main() {
ivec2 rc = getOutputCoords();
vec4 result = vec4(0);
int blockIndex, pos, offsetY, d0, offsetX, d1, ch;
vec2 innerDims;
${l}
${s.output} = result;
}
`}};function f4({x:e,filter:t,convInfo:n,backend:s,bias:r=null,preluActivationWeights:a=null,leakyreluAlpha:o=0,activation:i=null}){let l=e.shape,u=s.texData.get(e.dataId),c=n.inChannels,d=l[0]*l[1]*l[2],h=n.outChannels,p=n.dataFormat==="channelsLast",f=!1,m=!1,g,A=[];if(!((d===1||h===1)&&c>s4)&&u.isPacked&&p&&u.texture!=null&&l[2]%2!=0&&w.arraysEqual(u.shape.slice(-3),l.slice(-3))){let b=l[0]*l[1]*(l[2]+1),v={dataId:e.dataId,shape:[1,b,n.inChannels],dtype:e.dtype},k=u.shape;u.shape=u.shape.slice(),u.shape[u.shape.length-2]++,w.assert(Kc(u.shape,v.shape),()=>`packed reshape ${u.shape} to ${v.shape} isn't free`);let S=ye({inputs:{x:t},backend:s,attrs:{shape:[1,n.inChannels,n.outChannels]}});A.push(S);let C=Nf({a:v,b:S,backend:s,transposeA:f,transposeB:m,bias:r,activation:i,preluActivationWeights:a,leakyreluAlpha:o}),_=s.texData.get(C.dataId);w.assert(_.isPacked,()=>"batchMatMul result is expected to be packed"),u.shape=k,_.shape=n.outShape,g=Yn({inputs:{x:C},backend:s}),g.shape=n.outShape,A.push(C)}else{let b=p?l[0]*l[1]*l[2]:l[0]*l[2]*l[3],v=ye({inputs:{x:e},backend:s,attrs:{shape:[1,b,n.inChannels]}}),k=ye({inputs:{x:t},backend:s,attrs:{shape:[1,n.inChannels,n.outChannels]}}),S=Nf({a:v,b:k,transposeA:f,transposeB:m,backend:s,bias:r,activation:i,preluActivationWeights:a,leakyreluAlpha:o});g=ye({inputs:{x:S},backend:s,attrs:{shape:n.outShape}}),A.push(v),A.push(k),A.push(S)}for(let b of A)s.disposeIntermediateTensorInfo(b);return g}function m4({x:e,filter:t,convInfo:n,backend:s,bias:r=null,preluActivationWeights:a=null,leakyreluAlpha:o=0,activation:i=null}){let{filterWidth:l,filterHeight:u,inChannels:c,outWidth:d,outHeight:h,dataFormat:p}=n,f=p==="channelsLast",m=l*u*c,g=h*d,A=[m,g],y=!0,x=!1,b=[],v=ye({inputs:{x:e},backend:s,attrs:{shape:e.shape.slice(1)}}),k=ye({inputs:{x:t},backend:s,attrs:{shape:[1,m,w.sizeFromShape(t.shape)/m]}});b.push(v),b.push(k);let S=new vY(A,n),C=[v.shape,[n.padInfo.top,n.padInfo.left],[n.strideHeight,n.strideWidth],[n.dilationHeight,n.dilationWidth],[n.inChannels],[n.filterWidth*n.inChannels],[n.outWidth]],_=s.runWebGLProgram(S,[v],"float32",C),O=ye({inputs:{x:_},backend:s,attrs:{shape:[1,A[0],A[1]]}});b.push(_),b.push(O);let E=r!=null,R=a!=null,T=i==="leakyrelu",P=i?Sf(i,!0):null,V=new J6(O.shape,k.shape,[1,g,n.outChannels],y,x,E,P,R,T),j=[O,k];if(r&&j.push(r),R&&j.push(a),T){let te=s.makeTensorInfo([],"float32",w.createScalarValue(o,"float32"));j.push(te),b.push(te)}let q=s.runWebGLProgram(V,j,"float32"),X=f?[1,h,d,n.outChannels]:[1,n.outChannels,h,d],ee=ye({inputs:{x:q},backend:s,attrs:{shape:X}});b.push(q);for(let te of b)s.disposeIntermediateTensorInfo(te);return ee}function wY(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dataFormat:l,dilations:u,dimRoundingMode:c}=s,d=D.convertConv2DDataFormat(l),h=D.computeConv2DInfo(r.shape,a.shape,o,u,i,c,!1,d),p;if(h.filterHeight===1&&h.filterWidth===1&&h.dilationHeight===1&&h.dilationWidth===1&&h.strideHeight===1&&h.strideWidth===1&&(h.padInfo.type==="SAME"||h.padInfo.type==="VALID"))p=f4({x:r,filter:a,convInfo:h,backend:n});else if(Q().getBool("WEBGL_CONV_IM2COL")&&r.shape[0]===1)p=m4({x:r,filter:a,convInfo:h,backend:n});else{let m=new p4(h);p=n.runWebGLProgram(m,[r,a],"float32")}let f=ye({inputs:{x:p},backend:n,attrs:{shape:h.outShape}});return n.disposeIntermediateTensorInfo(p),f}var kY={kernelName:$a,backendName:"webgl",kernelFunc:wY},IY=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,s=e.padInfo.top,r=e.padInfo.left,a=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} - ${s};
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int yC = 0; yC < ${e.outWidth}; yC++) {
int xC = wC + yC * ${n} - ${r};
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
if (${a}) {
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);
}
`}},SY=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,s=e.strideHeight,r=e.strideWidth,a=e.dataFormat==="channelsLast",o=t-1-e.padInfo.top,i=n-1-e.padInfo.left,l=a?1:2,u=a?2:3,c=a?3:1;this.userCode=`
const ivec2 pads = ivec2(${o}, ${i});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d1 = coords[${c}];
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) / ${s}.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 < ${n}; 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 = ${n} - 1 - wC;
for (int d2 = 0; d2 < ${e.outChannels}; d2++) {
if (${a}) {
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);
}
`}},CY=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideDepth,n=e.strideHeight,s=e.strideWidth,r=e.padInfo.front,a=e.padInfo.top,o=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 * ${n} - ${a};
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int yC = 0; yC < ${e.outWidth}; yC++) {
int xC = wC + yC * ${s} - ${o};
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
float dyValue = getDy(b, yF, yR, yC, d2);
float xValue = getX(b, xF, xR, xC, d1);
dotProd += (xValue * dyValue);
}
}
}
}
setOutput(dotProd);
}
`}},TY=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,s=e.filterWidth,r=e.strideDepth,a=e.strideHeight,o=e.strideWidth,i=t-1-e.padInfo.front,l=n-1-e.padInfo.top,u=s-1-e.padInfo.left;this.userCode=`
const ivec3 pads = ivec3(${i}, ${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 < ${n}; wR++) {
float dyR = float(dyRCorner + wR) / ${a}.0;
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 ||
fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
int wRPerm = ${n} - 1 - wR;
for (int wC = 0; wC < ${s}; wC++) {
float dyC = float(dyCCorner + wC) / ${o}.0;
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
int wCPerm = ${s} - 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 NY(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,dy:a}=t,{strides:o,pad:i,dataFormat:l,dimRoundingMode:u,filterShape:c}=s,d=D.convertConv2DDataFormat(l),h=D.computeConv2DInfo(r.shape,c,o,1,i,u,!1,d),p=new IY(h);return n.runWebGLProgram(p,[r,a],"float32")}var EY={kernelName:Jd,backendName:"webgl",kernelFunc:NY};function RY(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,filter:a}=t,{inputShape:o,strides:i,pad:l,dataFormat:u,dimRoundingMode:c}=s,d=D.convertConv2DDataFormat(u),h=D.computeConv2DInfo(o,a.shape,i,1,l,c,!1,d),p=new SY(h);return n.runWebGLProgram(p,[r,a],"float32")}var _Y={kernelName:Fa,backendName:"webgl",kernelFunc:RY};function DY(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dilations:l}=s,u=D.computeConv3DInfo(r.shape,a.shape,o,l,i),c=new bY(u);return n.runWebGLProgram(c,[r,a],"float32")}var $Y={kernelName:zu,backendName:"webgl",kernelFunc:DY};function FY(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,dy:a}=t,{strides:o,pad:i,filterShape:l}=s,u=D.computeConv3DInfo(r.shape,l,o,1,i),c=new CY(u);return n.runWebGLProgram(c,[r,a],"float32")}var OY={kernelName:Qd,backendName:"webgl",kernelFunc:FY};function PY(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,filter:a}=t,{pad:o,strides:i,inputShape:l}=s,u=D.computeConv3DInfo(l,a.shape,i,1,o),c=new TY(u);return n.runWebGLProgram(c,[r,a],"float32")}var MY={kernelName:eh,backendName:"webgl",kernelFunc:PY},zY=Y6+`
return cos(x);
`,LY=Je({opSnippet:zY}),BY={kernelName:Oa,backendName:"webgl",kernelFunc:LY},WY=`
float e2x = exp(-x);
return (e2x + 1.0 / e2x) / 2.0;
`,VY=Je({opSnippet:WY}),UY={kernelName:Pa,backendName:"webgl",kernelFunc:VY},HY=class{constructor(e,t,n,s,r){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[a,o,i,l]=e,[u]=t,[c,d]=n;this.outputShape=[u,c,d,l];let h=s==="bilinear"?1:0,[p,f]=[`${o-1}.0`,`${i-1}.0`],[m,g,A]=c>1?[`${(o-1)/(c-1)}`,"(y2-y1) * height_ratio",`y1*${p} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${p}`],[y,x,b]=d>1?[`${(i-1)/(d-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(${y});
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 >= ${a}) {
return;
}
float height_scale = ${g};
float width_scale = ${x};
float in_y = ${A};
if( in_y < 0.0 || in_y > ${p} ) {
setOutput(float(${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(${h} == 1) {
// Compute the four integer indices.
ivec2 sourceFloorCR = ivec2(sourceFracIndexCR);
ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR));
float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d);
float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d);
float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);
float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);
vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);
float top = topLeft + (topRight - topLeft) * fracCR.x;
float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;
float newValue = top + (bottom - top) * fracCR.y;
setOutput(newValue);
} else {
// Compute the coordinators of nearest neighbor point.
ivec2 sourceNearestCR = ivec2(floor(
sourceFracIndexCR + vec2(0.5,0.5)));
float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);
setOutput(newValue);
}
}
`}},GY=e=>{let{inputs:t,backend:n,attrs:s}=e,{image:r,boxes:a,boxInd:o}=t,{cropSize:i,method:l,extrapolationValue:u}=s,c=new HY(r.shape,a.shape,i,l,u);return n.runWebGLProgram(c,[r,a,o],"float32")},jY={kernelName:Oi,backendName:"webgl",kernelFunc:GY},g4=class{constructor(e,t,n){this.variableNames=["x"],this.customUniforms=[{name:"index",type:"float"}],this.outputShape=e;let s=e.length,r=t?"0.0":`getX(${A4(s,"coords")})`,a=e[e.length-1],o="",i="";t?(o=n?`end != ${a-1}`:"end != 0",i=n?"end + 1":"end - 1"):(o=n?`end + pow2 < ${a}`:"end >= pow2",i=n?"end + pow2":"end - pow2"),this.userCode=`
void main() {
${ht(s)} coords = getOutputCoords();
int end = ${y4(s,"coords")};
float val = ${r};
int pow2 = int(pow(2.0, index));
if (${o}) {
int idx = ${i};
${y4(s,"coords")} = idx;
val += getX(${A4(s,"coords")});
}
setOutput(val);
}
`}};function A4(e,t){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 sum for rank ${e} is not yet supported`)}function y4(e,t){if(e===1)return`${t}`;if(e===2)return`${t}.y`;if(e===3)return`${t}.z`;if(e===4)return`${t}.w`;throw Error(`Cumulative sum for rank ${e} is not yet supported`)}function qY(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,exclusive:o,reverse:i}=s,l=r.shape.length,u=D.getAxesPermutation([a],l),c=r;u!=null&&(c=Sn({inputs:{x:r},backend:n,attrs:{perm:u}}));let d=D.getInnerMostAxes(1,l)[0];if(d!==l-1)throw new Error(`WebGL cumsum shader expects an inner-most axis=${r.shape.length-1} but got axis=${a}`);let h=c.shape[d],p=Yn({inputs:{x:c},backend:n});for(let f=0;f<=Math.ceil(Math.log2(h))-1;f++){let m=new g4(c.shape,!1,i),g=[[f]],A=p;p=n.runWebGLProgram(m,[p],p.dtype,g),n.disposeIntermediateTensorInfo(A)}if(o){let f=new g4(c.shape,o,i),m=p;p=n.runWebGLProgram(f,[p],p.dtype),n.disposeIntermediateTensorInfo(m)}if(u!=null){let f=D.getUndoAxesPermutation(u),m=Sn({inputs:{x:p},backend:n,attrs:{perm:f}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(c),m}return p}var XY={kernelName:Ma,backendName:"webgl",kernelFunc:qY};function KY(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,weights:a}=t,{size:o,binaryOutput:i}=s;if(r.shape.length===1){let l=n.readSync(r.dataId),u=n.readSync(a.dataId),c=P6(l,u,a.dtype,a.shape,o);return n.makeTensorInfo([o],a.dtype,c)}else if(r.shape.length===2){let l=n.bufferSync(r),u=n.bufferSync(a),c=lX(l,u,o,i);return n.makeTensorInfo(c.shape,a.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${r.shape.length}.`)}var ZY={kernelName:th,backendName:"webgl",kernelFunc:KY},YY=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=[],this.outputShape=e,this.blockSize=t,this.dataFormat=n,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 JY(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockSize:a,dataFormat:o}=s;w.assert(a>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${a}`);let i=r.shape[0],l=o==="NHWC"?r.shape[1]:r.shape[2],u=o==="NHWC"?r.shape[2]:r.shape[3],c=o==="NHWC"?r.shape[3]:r.shape[1],d=l*a,h=u*a,p=c/(a*a),f=o==="NHWC"?[i,d,h,p]:[i,p,d,h],m=new YY(f,a,o);return n.runWebGLProgram(m,[r],r.dtype)}var QY={kernelName:Pi,backendName:"webgl",kernelFunc:JY},x4=class{constructor(e,t=!1,n=null,s=!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=bs(this.outputShape.length);let a=e.filterHeight,o=e.filterWidth,i=e.outChannels/e.inChannels,l="",u="";n&&(s?l=`float activation(float a) {
float b = getPreluActivationWeightsAtOutCoords();
${n}
}`:r?l=`float activation(float a) {
float b = getLeakyreluAlphaAtOutCoords();
${n}
}`:l=`
float activation(float x) {
${n}
}
`,u="result = activation(result);");let c=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),s&&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 / ${i};
int q = d2 - d1 * ${i};
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 < ${a}; wR++) {
int xR = xRCorner + wR * dilations[0];
if (xR < 0 || xR >= inDims[0]) {
continue;
}
for (int wC = 0; wC < ${o}; 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;
${c}
${u}
setOutput(result);
}
`}},b4=class{constructor(e,t=!1,n=null,s=!1,r=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=bs(this.outputShape.length);let a=e.outChannels/e.inChannels,o=e.padInfo.left,i=e.strideWidth,l=e.dilationWidth,u=e.filterHeight,c=e.filterWidth,d=c,h=`
int xR; int xC; int xCOffset;
vec4 wTexel; vec4 previous; vec4 final;`;for(let g=0;g<c;g++)h+=`
vec4 xTexelC${g*2};
int xTexelC${g*2}Ready;
vec4 xTexelC${g*2+1};
int xTexelC${g*2+1}Ready;
vec4 xC${g};`;for(let g=0;g<u;g++){for(let A=0;A<c;A++)h+=`
xTexelC${A*2} = vec4(0.0);
xTexelC${A*2}Ready = 0;
xTexelC${A*2+1} = vec4(0.0);
xTexelC${A*2+1}Ready = 0;
xC${A} = vec4(0.0);`;h+=`
xR = xRCorner + ${g} * dilations[0];
if (xR >=0 && xR < inDims[0]) {
`;for(let A=0;A<(d+1)/2;A++){let y=A*2;if(h+=`
xC = xCCorner + ${y*l};
`,i===1){if(y<c&&(o%2==1?(h+=`
xCOffset = xC + 1;
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${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${y}Ready = 1;
}
`,l===1&&y>0?h+=`
xC${y} = vec4(xTexelC${y-2}.zw, xTexelC${y}.xy);
`:h+=`
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);
}
`):h+=`
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<c)){let x=o%2==0?w.nearestLargerEven(l):l;l%2==0&&o%2==1||l%2!=0&&o%2!=1?(h+=`
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${y+1}Ready = 1;
}
`,l>1&&(h+=`
xCOffset -= 2;
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${y}Ready == 0) {
xTexelC${y} = getX(batch, xR, xCOffset, d1);
xTexelC${y}Ready = 1;
}
`),h+=`
xC${y+1} = vec4(xTexelC${y}.zw, xTexelC${y+1}.xy);
`):x===1?h+=`
xC${y+1} = xTexelC${y};
`:h+=`
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${y+1};
`}}else y<c&&(o%2==1?(h+=`
xCOffset = xC + 1 - strides[1];
if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${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<c&&(h+=`
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);
`)):(h+=`
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${y+1}.xy);
`,y+1<c&&(h+=`
xC${y+1} = vec4(xTexelC${y}.zw, xTexelC${y+1}.zw);
`)));y<c&&(h+=`
wTexel = getW(${g}, ${y}, d1, q);
dotProd += xC${y} * vec4(wTexel.xz, wTexel.xz);
`,y+1<c&&(h+=`
wTexel = getW(${g}, ${y+1}, d1, q);
dotProd += xC${y+1} * vec4(wTexel.xz, wTexel.xz);
`))}h+=`
}
`}let p="",f="";n&&(s?p=`vec4 activation(vec4 a) {
vec4 b = getPreluActivationWeightsAtOutCoords();
${n}
}`:r?p=`vec4 activation(vec4 a) {
vec4 b = getLeakyreluAlphaAtOutCoords();
${n}
}`:p=`vec4 activation(vec4 x) {
${n}
}`,f="result = activation(result);");let m=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),s&&this.variableNames.push("preluActivationWeights"),r&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
${p}
void main() {
ivec4 coords = getOutputCoords();
int batch = coords.x;
ivec2 xRCCorner = coords.yz * strides - pads;
int d2 = coords.w;
int d1 = d2 / ${a};
int q = d2 - d1 * ${a};
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);
${h}
vec4 result = dotProd - vec4(0.000000000000001);
${m}
${f}
setOutput(result);
}
`}};function eJ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dilations:l,dimRoundingMode:u}=s,c=l;c==null&&(c=[1,1]),w.assert(D.eitherStridesOrDilationsAreOne(o,c),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${o} and dilations '${c}'`);let d=D.computeConv2DInfo(r.shape,a.shape,o,c,i,u,!0),h;Q().getBool("WEBGL_PACK_DEPTHWISECONV")&&d.strideWidth<=2&&d.outChannels/d.inChannels==1?h=new b4(d):h=new x4(d);let p=[[d.padInfo.top,d.padInfo.left],[d.strideHeight,d.strideWidth],[d.dilationHeight,d.dilationWidth],[d.inHeight,d.inWidth]];return n.runWebGLProgram(h,[r,a],"float32",p)}var tJ={kernelName:za,backendName:"webgl",kernelFunc:eJ},nJ=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,s=e.padInfo.top,r=e.padInfo.left,a=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 * ${a} + 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} - ${s};
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int yC = 0; yC < ${e.outWidth}; yC++) {
int xC = wC + yC * ${n} - ${r};
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
float dyValue = getDy(b, yR, yC, d2);
float xValue = getX(b, xR, xC, d1);
dotProd += (xValue * dyValue);
}
}
}
setOutput(dotProd);
}
`}},sJ=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,s=e.strideHeight,r=e.strideWidth,a=t-1-e.padInfo.top,o=n-1-e.padInfo.left,i=e.outChannels/e.inChannels;this.userCode=`
const ivec2 pads = ivec2(${a}, ${o});
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) / ${s}.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 < ${n}; 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 = ${n} - 1 - wC;
// TO DO: Vec4 over the channelMul
for (int dm = 0; dm < ${i}; dm++) {
int d2 = d1 * ${i} + dm;
float xValue = getDy(batch, idyR, idyC, d2);
float wValue = getW(wRPerm, wCPerm, d1, dm);
dotProd += xValue * wValue;
}
}
}
setOutput(dotProd);
}
`}};function rJ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,dy:a}=t,{strides:o,dilations:i,pad:l,dimRoundingMode:u,filterShape:c}=s,d=D.computeConv2DInfo(r.shape,c,o,i,l,u,!0),h=new nJ(d);return n.runWebGLProgram(h,[r,a],"float32")}var aJ={kernelName:nh,backendName:"webgl",kernelFunc:rJ};function oJ(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,filter:a}=t,{strides:o,dilations:i,pad:l,dimRoundingMode:u,inputShape:c}=s,d=D.computeConv2DInfo(c,a.shape,o,i,l,u,!0),h=new sJ(d);return n.runWebGLProgram(h,[r,a],"float32")}var iJ={kernelName:sh,backendName:"webgl",kernelFunc:oJ},lJ=class{constructor(e){this.variableNames=["X"],this.outputShape=[e,e],this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;
setOutput(val);
}
`}};function uJ(e){let{inputs:t,backend:n}=e,{x:s}=t,r=[...s.shape,...s.shape],a=w.sizeFromShape(s.shape),o=ye({inputs:{x:s},backend:n,attrs:{shape:[a]}}),i=new lJ(a),l=n.runWebGLProgram(i,[o],o.dtype),u=ye({inputs:{x:l},backend:n,attrs:{shape:r}});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(l),u}var cJ={kernelName:rh,backendName:"webgl",kernelFunc:uJ},dJ=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:n,padInfo:s,strideHeight:r,strideWidth:a,filterHeight:o,filterWidth:i,dilationHeight:l,dilationWidth:u}=e,{top:c,left:d}=s;this.userCode=`
const ivec2 strides = ivec2(${r}, ${a});
const ivec2 pads = ivec2(${c}, ${d});
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 < ${o}; h++) {
int hIn = hBeg + h * ${l};
if (hIn >= 0 && hIn < ${t}) {
for (int w = 0; w < ${i}; w++) {
int wIn = wBeg + w * ${u};
if (wIn >= 0 && wIn < ${n}) {
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 hJ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dilations:l}=s,u=D.computeDilation2DInfo(r.shape,a.shape,o,i,"NHWC",l),c,d=new dJ(u);c=n.runWebGLProgram(d,[r,a],"float32");let h=ye({inputs:{x:c},backend:n,attrs:{shape:u.outShape}});return n.disposeIntermediateTensorInfo(c),h}var pJ={kernelName:Lu,backendName:"webgl",kernelFunc:hJ};function fJ(e){let{inputs:t,backend:n,attrs:s}=e,{equation:r}=s,a=t,{allDims:o,summedDims:i,idDims:l}=D.decodeEinsumEquation(r,a.length);D.checkEinsumDimSizes(o.length,l,a);let{path:u,steps:c}=D.getEinsumComputePath(i,l),d=c.length,h=null,p=o.length,f=[];for(let m=0;m<d;++m){for(let g of c[m]){let{permutationIndices:A,expandDims:y}=D.getEinsumPermutation(p,l[g]),x;D.isIdentityPermutation(A)?x=a[g]:(x=Sn({inputs:{x:a[g]},backend:n,attrs:{perm:A}}),f.push(x));let b=x.shape.slice();for(let v=0;v<y.length;++v)b.splice(y[v],0,1);w.arraysEqual(x.shape,b)||(x=ye({inputs:{x},backend:n,attrs:{shape:b}}),f.push(x)),h===null?h=x:(h=B2({inputs:{a:x,b:h},backend:n}),f.push(h))}m<d-1&&(u[m]>=0&&(h=Tf({inputs:{x:h},backend:n,attrs:{axis:u[m]-(o.length-p),keepDims:!1}}),f.push(h)),p--)}for(let m of f)m!==h&&n.disposeIntermediateTensorInfo(m);return h}var mJ={kernelName:ih,backendName:"webgl",kernelFunc:fJ},gJ="return (x >= 0.0) ? x : (exp(x) - 1.0);",AJ=`
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;
`,yJ=Je({opSnippet:gJ,packedOpSnippet:AJ}),xJ={kernelName:Ba,backendName:"webgl",kernelFunc:yJ},bJ="return (b >= 1.0) ? a : a * (b + 1.0);",vJ=`
vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
`,wJ=e=>{let{inputs:t,backend:n}=e,{dy:s,y:r}=t,a=Q().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Yc(vJ,s.shape,r.shape):new uu(bJ,s.shape,r.shape);return n.runWebGLProgram(a,[s,r],s.dtype)},kJ={kernelName:lh,backendName:"webgl",kernelFunc:wJ},IJ=`
return vec4(equal(a, b));
`,SJ="return float(a == b);",CJ=ln({opSnippet:SJ,packedOpSnippet:IJ,dtype:"bool",cpuKernelImpl:dX}),TJ={kernelName:zi,backendName:"webgl",kernelFunc:CJ},NJ=`
// Error function is calculated approximately with elementary function.
// See "Handbook of Mathematical Functions with Formulas,
// Graphs, and Mathematical Tables", Abramowitz and Stegun.
float p = ${D.ERF_P};
float a1 = ${D.ERF_A1};
float a2 = ${D.ERF_A2};
float a3 = ${D.ERF_A3};
float a4 = ${D.ERF_A4};
float a5 = ${D.ERF_A5};
float sign = sign(x);
x = abs(x);
float t = 1.0 / (1.0 + p * x);
return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));
`,EJ=Je({opSnippet:NJ}),RJ={kernelName:Mi,backendName:"webgl",kernelFunc:EJ},v4="return exp(x);",w4=Je({opSnippet:v4,packedOpSnippet:v4,cpuKernelImpl:hX}),_J={kernelName:Wa,backendName:"webgl",kernelFunc:w4};function H2(e){let{inputs:t,attrs:n,backend:s}=e,{dim:r}=n,{input:a}=t,o=a.shape.length,i=a.shape.slice(),l=r;return r<0&&(w.assert(-(o+1)<=r,()=>`Axis must be in the interval [${-(o+1)}, ${o}]`),l=o+r+1),i.splice(l,0,1),ye({inputs:{x:a},backend:s,attrs:{shape:i}})}var DJ={kernelName:Li,backendName:"webgl",kernelFunc:H2},k4="return exp(x) - 1.0;",$J=Je({opSnippet:k4,packedOpSnippet:k4,cpuKernelImpl:pX}),FJ={kernelName:Bi,backendName:"webgl",kernelFunc:$J},I4=class{constructor(e,t,n){this.variableNames=["real","imag"];let s=t[1];this.outputShape=t;let r=n?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,a=n?`${s}.0`:"1.0",o;if(e==="real")o="return real * expR - imag * expI;";else if(e==="imag")o="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) {
${o}
}
float mulMatDFT(int batch, int index) {
float indexRatio = float(index) / float(${s});
float exponentMultiplierTimesIndexRatio =
exponentMultiplier * indexRatio;
float result = 0.0;
for (int i = 0; i < ${s}; 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) / ${a};
}
return result;
}
void main() {
ivec2 coords = getOutputCoords();
setOutput(mulMatDFT(coords[0], coords[1]));
}
`}};function S4(e,t,n){let s=n.texData.get(e.dataId),r=w.sizeFromShape(e.shape),a=e.shape[e.shape.length-1],o=r/a,i=ye({inputs:{x:e},backend:n,attrs:{shape:[o,a]}}),l=i.shape,u=new I4("real",l,t),c=new I4("imag",l,t),d=[{dataId:s.complexTensorInfos.real.dataId,dtype:s.complexTensorInfos.real.dtype,shape:l},{dataId:s.complexTensorInfos.imag.dataId,dtype:s.complexTensorInfos.imag.dtype,shape:l}],h=n.runWebGLProgram(u,d,"float32"),p=n.runWebGLProgram(c,d,"float32"),f=pa({inputs:{real:h,imag:p},backend:n});n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(p);let m=ye({inputs:{x:f},backend:n,attrs:{shape:e.shape}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(f),m}function OJ(e){let{inputs:t,backend:n}=e,{input:s}=t;return S4(s,!1,n)}var PJ={kernelName:uh,backendName:"webgl",kernelFunc:OJ},MJ=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 ed(e){let{backend:t,attrs:n}=e,{shape:s,value:r}=n,{dtype:a}=n;if(a=a||w.inferDtype(r),a==="string"){let o=w.getArrayFromDType(a,w.sizeFromShape(s));return o.fill(r),t.makeTensorInfo(s,a,o)}else{let o=new MJ(s,r),i=[[r]];return t.runWebGLProgram(o,[],a,i)}}var zJ={kernelName:Bu,backendName:"webgl",kernelFunc:ed},LJ=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 < ${t}) {
outputValue = getImage(coords[0], coords[1], coordX, coords[3]);
} else {
outputValue = getImage(coords[0], coords[1], coords[2], coords[3]);
}
setOutput(outputValue);
}
`}},BJ={kernelName:Wi,backendName:"webgl",kernelFunc:({inputs:e,backend:t})=>{let{image:n}=e,s=t,r=new LJ(n.shape);return s.runWebGLProgram(r,[n],n.dtype)}},C4="return floor(x);",WJ=Je({opSnippet:C4,packedOpSnippet:C4,cpuKernelImpl:fX}),VJ={kernelName:Va,backendName:"webgl",kernelFunc:WJ},UJ=`
float s = sign(a) * sign(b);
int ia = round(a);
int ib = round(b);
if (ib != 0) {
// Windows (D3D) wants guaranteed non-zero int division at compile-time.
return float(idiv(ia, ib, s));
} else {
return NAN;
}
`,HJ=`
ivec4 ia = round(a);
ivec4 ib = round(b);
bvec4 cond = notEqual(ib, ivec4(0));
ivec4 result = ivec4(0);
vec4 s = sign(a) * sign(b);
// Windows (D3D) wants guaranteed non-zero int division at compile-time.
if (cond[0]) {
result[0] = idiv(ia[0], ib[0], s[0]);
}
if (cond[1]) {
result[1] = idiv(ia[1], ib[1], s[1]);
}
if (cond[2]) {
result[2] = idiv(ia[2], ib[2], s[2]);
}
if (cond[3]) {
result[3] = idiv(ia[3], ib[3], s[3]);
}
return vec4(result);
`,GJ=ln({opSnippet:UJ,packedOpSnippet:HJ,dtype:"int32"}),jJ={kernelName:Ua,backendName:"webgl",kernelFunc:GJ},qJ=class{constructor(e){this.variableNames=["A"];let t=kn(),[n,s]=e;this.outputShape=e,this.userCode=`
void main() {
ivec3 coords = getOutputCoords();
int texR = coords[0];
int texC = coords[1];
int depth = coords[2];
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${s}.0, ${n}.0);
vec4 values = ${t.texture2D}(A, uv);
float value;
if (depth == 0) {
value = values.r;
} else if (depth == 1) {
value = values.g;
} else if (depth == 2) {
value = values.b;
} else if (depth == 3) {
value = values.a;
}
setOutput(floor(value * 255.0 + 0.5));
}
`}},XJ=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let t=kn(),[n,s]=e;this.outputShape=e,this.userCode=`
void main() {
ivec3 coords = getOutputCoords();
int texR = coords[0];
int texC = coords[1];
int depth = coords[2];
vec4 result = vec4(0.);
for(int row=0; row<=1; row++) {
for(int col=0; col<=1; col++) {
texC = coords[1] + row;
depth = coords[2] + col;
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${s}.0, ${n}.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;
}
`}},KJ={kernelName:Rh,backendName:"webgl",kernelFunc:ZJ},hu;function ZJ(e){let{inputs:t,backend:n,attrs:s}=e,{pixels:r}=t,{numChannels:a}=s,o=typeof HTMLVideoElement!="undefined"&&r instanceof HTMLVideoElement,i=typeof HTMLImageElement!="undefined"&&r instanceof HTMLImageElement,[l,u]=o?[r.videoWidth,r.videoHeight]:[r.width,r.height],c=[u,l],d=[u,l,a];(i||o)&&(hu==null&&(hu=document.createElement("canvas").getContext("2d")),hu.canvas.width=l,hu.canvas.height=u,hu.drawImage(r,0,0,l,u),r=hu.canvas);let h=n.makeTensorInfo(c,"int32");n.texData.get(h.dataId).usage=ys.PIXELS,n.gpgpu.uploadPixelDataToTexture(n.getTexture(h.dataId),r);let p=Q().getBool("WEBGL_PACK")?new XJ(d):new qJ(d),f=n.runWebGLProgram(p,[h],"int32");return n.disposeData(h.dataId),f}function YJ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dataFormat:c,dilations:d,dimRoundingMode:h,activation:p,leakyreluAlpha:f}=s,m=D.convertConv2DDataFormat(c),g=D.computeConv2DInfo(r.shape,a.shape,l,d,u,h,!1,m),A,y=[];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"))A=f4({x:r,filter:a,convInfo:g,backend:n,bias:o,activation:p,preluActivationWeights:i,leakyreluAlpha:f});else if(Q().getBool("WEBGL_CONV_IM2COL")&&r.shape[0]===1)A=m4({x:r,filter:a,convInfo:g,backend:n,bias:o,activation:p,preluActivationWeights:i,leakyreluAlpha:f});else{let b=o!=null,v=i!=null,k=p==="leakyrelu",S=p?Sf(p,!1):null,C=new p4(g,b,S,v,k),_=[r,a];if(o&&_.push(o),i&&_.push(i),k){let O=n.makeTensorInfo([],"float32",w.createScalarValue(f,"float32"));_.push(O),y.push(O)}A=n.runWebGLProgram(C,_,"float32")}let x=ye({inputs:{x:A},backend:n,attrs:{shape:g.outShape}});return y.push(A),y.forEach(b=>n.disposeIntermediateTensorInfo(b)),x}var JJ={kernelName:So,backendName:"webgl",kernelFunc:YJ};function QJ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dilations:c,dimRoundingMode:d,activation:h,leakyreluAlpha:p}=s,f=[],m=c;m==null&&(m=[1,1]),w.assert(D.eitherStridesOrDilationsAreOne(l,m),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${m}'`);let g=D.computeConv2DInfo(r.shape,a.shape,l,m,u,d,!0),A=Q().getBool("WEBGL_PACK_DEPTHWISECONV")&&g.strideWidth<=2&&g.outChannels/g.inChannels==1,y=h?Sf(h,A):null,x=[r,a],b=o!=null,v=i!=null,k=h==="leakyrelu";if(b&&x.push(o),v&&x.push(i),k){let O=n.makeTensorInfo([],"float32",w.createScalarValue(p,"float32"));x.push(O),f.push(O)}let S;A?S=new b4(g,b,y,v,k):S=new x4(g,b,y,v,k);let C=[[g.padInfo.top,g.padInfo.left],[g.strideHeight,g.strideWidth],[g.dilationHeight,g.dilationWidth],[g.inHeight,g.inWidth]],_=n.runWebGLProgram(S,x,"float32",C);return f.forEach(O=>n.disposeIntermediateTensorInfo(O)),_}var eQ={kernelName:Co,backendName:"webgl",kernelFunc:QJ},tQ=class{constructor(e,t,n){this.sliceDim=e,this.strides=t,this.variableNames=["x","indices"],this.outputShape=n;let s=ht(t.length),r=ht(n.length),a=this.sliceDim>1?"strides[j]":"strides";this.userCode=`
${s} strides = ${s}(${this.strides});
void main() {
${r} coords = getOutputCoords();
int flattenIndex = 0;
for (int j = 0; j < ${this.sliceDim}; j++) {
int index = round(getIndices(coords[0], j));
flattenIndex += index * ${a};
}
setOutput(getX(flattenIndex, coords[1]));
}
`}};function nQ(e){let{inputs:t,backend:n}=e,{params:s,indices:r}=t,a=r.shape,o=a[a.length-1],i=w.sizeFromShape(s.shape),[l,u,c,d]=D.prepareAndValidate(s,r),h=ye({inputs:{x:r},backend:n,attrs:{shape:[u,o]}}),p=ye({inputs:{x:s},backend:n,attrs:{shape:[w.sizeFromShape(s.shape)/c,c]}});if(n.shouldExecuteOnCPU([s,r])||s.dtype==="string"){let A=n.readSync(r.dataId),y=n.bufferSync(s),x=mX(A,y,s.dtype,u,o,c,d,s.shape,i);return n.makeTensorInfo(l,s.dtype,x.values)}let f=new tQ(o,d,[u,c]),m=n.runWebGLProgram(f,[p,h],p.dtype),g=ye({inputs:{x:m},backend:n,attrs:{shape:l}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(m),g}var sQ={kernelName:Ui,backendName:"webgl",kernelFunc:nQ},rQ=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let n=ht(this.rank),s=aQ(e,2);this.userCode=`
void main() {
${n} resRC = getOutputCoords();
setOutput(getA(${s}));
}
`}};function aQ(e,t){let n=["resRC.x","resRC.y","resRC.z","resRC.w"],s=[];for(let r=0;r<e.length;r++)r===2?s.push("int(getIndices(resRC.x, resRC.z))"):s.push(`${n[r]}`);return s.join()}function T4(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,indices:a}=t,{axis:o,batchDims:i}=s,l=w.parseAxisParam(o,r.shape)[0],u=D.segment_util.collectGatherOpShapeInfo(r,a,l,i),c=w.sizeFromShape(a.shape),d=[],h=ye({inputs:{x:r},backend:n,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),p=ye({inputs:{x:a},backend:n,attrs:{shape:[u.batchSize,c/u.batchSize]}});d.push(h),d.push(p);let f=[u.batchSize,u.outerSize,c/u.batchSize,u.sliceSize];if(n.shouldExecuteOnCPU([r,a])||r.dtype==="string"){let y=n.bufferSync(p),x=n.bufferSync(h),b=gX(x,y,f);return d.forEach(v=>n.disposeIntermediateTensorInfo(v)),n.makeTensorInfo(u.outputShape,b.dtype,b.values)}let m=new rQ(h.shape,f),g=n.runWebGLProgram(m,[h,p],h.dtype);d.push(g);let A=ye({inputs:{x:g},backend:n,attrs:{shape:u.outputShape}});return d.forEach(y=>n.disposeIntermediateTensorInfo(y)),A}var oQ={kernelName:Vi,backendName:"webgl",kernelFunc:T4},iQ="return float(a > b);",lQ=`
return vec4(greaterThan(a, b));
`,uQ=ln({opSnippet:iQ,packedOpSnippet:lQ,cpuKernelImpl:AX,dtype:"bool"}),cQ={kernelName:Hi,backendName:"webgl",kernelFunc:uQ},dQ="return float(a >= b);",hQ=`
return vec4(greaterThanEqual(a, b));
`,pQ=ln({opSnippet:dQ,packedOpSnippet:hQ,dtype:"bool",cpuKernelImpl:yX}),fQ={kernelName:Ga,backendName:"webgl",kernelFunc:pQ};function mQ(e){let{inputs:t,backend:n}=e,{input:s}=t;return S4(s,!0,n)}var gQ={kernelName:ch,backendName:"webgl",kernelFunc:mQ},AQ="return float(!isnan(x) && !isinf(x));",yQ=Je({opSnippet:AQ,dtype:"bool"}),xQ={kernelName:Gi,backendName:"webgl",kernelFunc:yQ},bQ="return float(isinf(x));",vQ=Je({opSnippet:bQ,dtype:"bool"}),wQ={kernelName:ji,backendName:"webgl",kernelFunc:vQ},kQ="return float(isnan(x));",IQ=Je({opSnippet:kQ,dtype:"bool"}),SQ={kernelName:qi,backendName:"webgl",kernelFunc:IQ},CQ="return float(a < b);",TQ=`
return vec4(lessThan(a, b));
`,NQ=ln({opSnippet:CQ,packedOpSnippet:TQ,cpuKernelImpl:xX,dtype:"bool"}),EQ={kernelName:Xi,backendName:"webgl",kernelFunc:NQ},RQ="return float(a <= b);",_Q=`
return vec4(lessThanEqual(a, b));
`,DQ=ln({opSnippet:RQ,packedOpSnippet:_Q,cpuKernelImpl:bX,dtype:"bool"}),$Q={kernelName:Ki,backendName:"webgl",kernelFunc:DQ};function FQ(e){let{backend:t,attrs:n}=e,{start:s,stop:r,num:a}=n,o=vX(s,r,a);return t.makeTensorInfo([o.length],"float32",o)}var OQ={kernelName:hh,backendName:"webgl",kernelFunc:FQ},PQ=`if (x < 0.0) return NAN;
return log(x);`,MQ=`
vec4 result = log(x);
vec4 isNaN = vec4(lessThan(x, vec4(0.0)));
result.r = isNaN.r == 1.0 ? NAN : result.r;
result.g = isNaN.g == 1.0 ? NAN : result.g;
result.b = isNaN.b == 1.0 ? NAN : result.b;
result.a = isNaN.a == 1.0 ? NAN : result.a;
return result;
`,zQ=Je({opSnippet:PQ,packedOpSnippet:MQ,cpuKernelImpl:wX}),LQ={kernelName:Xa,backendName:"webgl",kernelFunc:zQ},BQ="return log(1.0 + x);",WQ=Je({opSnippet:BQ}),VQ={kernelName:Zi,backendName:"webgl",kernelFunc:WQ},UQ="return float(a >= 1.0 && b >= 1.0);",HQ=`
return vec4(
vec4(greaterThanEqual(a, vec4(1.0))) *
vec4(greaterThanEqual(b, vec4(1.0))));
`,GQ=ln({opSnippet:UQ,packedOpSnippet:HQ,dtype:"bool"}),jQ={kernelName:Yi,backendName:"webgl",kernelFunc:GQ},qQ="return float(!(x >= 1.0));",XQ=Je({opSnippet:qQ}),KQ={kernelName:Wu,backendName:"webgl",kernelFunc:XQ},ZQ="return float(a >= 1.0 || b >= 1.0);",YQ=`
return min(
vec4(greaterThanEqual(a, vec4(1.0))) +
vec4(greaterThanEqual(b, vec4(1.0))),
vec4(1.0));
`,JQ=ln({opSnippet:ZQ,packedOpSnippet:YQ,dtype:"bool"}),QQ={kernelName:Vu,backendName:"webgl",kernelFunc:JQ},eee=class{constructor(e,t,n,s,r){this.variableNames=["x"],this.outputShape=[];let a=t,o=e[3]-1;this.outputShape=e;let i,l=`float(${n}) + float(${s}) * sum`;r===.5?i=`inversesqrt(${l})`:r===1?i=`1.0/(${l})`:i=`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 = -${a}; j <= ${a}; j++) {
int idx = d + j;
if (idx >= 0 && idx <= ${o}) {
float z = getX(b, r, c, idx);
sum += z * z;
}
}
float val = x * ${i};
setOutput(val);
}
`}},tee=class{constructor(e,t,n,s,r){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let a=t,o=e[3]-1;this.outputShape=e;let i,l=`float(${n}) + float(${s}) * sum`;r===.5?i=`inversesqrt(${l})`:r===1?i=`1.0/(${l})`:i=`exp(log(${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 - ${a};
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 = - ${a}; j <= ${a}; j++) {
ivec2 idx = depth + j;
bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));
bvec2 belowUpperBound = lessThanEqual(idx, ivec2(${o}));
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 * ${i};
setOutput(result);
}
`}},nee=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{depthRadius:a,bias:o,alpha:i,beta:l}=s,u=Q().getBool("WEBGL_PACK_NORMALIZATION")?new tee(r.shape,a,o,i,l):new eee(r.shape,a,o,i,l);return n.runWebGLProgram(u,[r],r.dtype)},see={kernelName:Uu,backendName:"webgl",kernelFunc:nee},ree=class{constructor(e,t,n,s,r){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=n,this.alpha=s,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 = ${this.depth};
float norm = 0.0;
for (int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k) {
if (k < depthBegin){
continue;
}
else if (k >= depthBegin && k < depthEnd) {
norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k);
}
else {
break;
}
}
norm = float(${s}) * norm + float(${n});
for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){
if (k < depthBegin){
continue;
}
else if (k >= depthBegin && k < depthEnd){
float dyi = -2.0 * float(${s})
* 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);
}
`}},aee=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r,y:a,dy:o}=t,{depthRadius:i,bias:l,alpha:u,beta:c}=s,d=new ree(r.shape,i,l,u,c);return n.runWebGLProgram(d,[r,a,o],r.dtype)},oee={kernelName:ph,backendName:"webgl",kernelFunc:aee};function iee(e,t,n,s){let r=w.sizeFromShape(t),o=w.sizeFromShape(e.shape)/r,i=ye({inputs:{x:e},attrs:{shape:[o,r]},backend:s}),l=ni(i,e.dtype,"max",s),u=ye({inputs:{x:l},attrs:{shape:n},backend:s});return s.disposeIntermediateTensorInfo(i),s.disposeIntermediateTensorInfo(l),u}function N4(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{reductionIndices:a,keepDims:o}=s,i=r.shape.length,l=w.parseAxisParam(a,r.shape),u=l,c=D.getAxesPermutation(u,i),d=c!=null,h=n.shouldExecuteOnCPU([r]),p=r;if(d){if(h){let x=n.texData.get(p.dataId).values,b=new Array(i);for(let S=0;S<b.length;S++)b[S]=r.shape[c[S]];let v=L2(x,r.shape,r.dtype,c,b);p=n.makeTensorInfo(b,r.dtype);let k=n.texData.get(p.dataId);k.values=v}else p=Cf(r,c,n);u=D.getInnerMostAxes(u.length,i)}D.assertAxesAreInnerMostDims("max",u,i);let[f,m]=D.computeOutAndReduceShapes(p.shape,u),g=f;o&&(g=D.expandShapeToKeepDim(f,l));let A;if(h){let x=n.texData.get(p.dataId).values,b=kX(x,w.sizeFromShape(m),g,r.dtype);A=n.makeTensorInfo(g,r.dtype);let v=n.texData.get(A.dataId);v.values=b}else A=iee(p,m,g,n);return d&&n.disposeIntermediateTensorInfo(p),A}var lee={kernelName:Ka,backendName:"webgl",kernelFunc:N4},uee=j6+`
return max(a, b);
`,cee=`
vec4 result = vec4(max(a, b));
vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
`+If+`
return result;
`,dee=ln({opSnippet:uee,packedOpSnippet:cee,cpuKernelImpl:IX}),hee={kernelName:Za,backendName:"webgl",kernelFunc:dee};function pee(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t;nu(r,"maxPool");let{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=s,u=1;w.assert(D.eitherStridesOrDilationsAreOne(o,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${o} and dilations '${u}'`);let c=D.computePool2DInfo(r.shape,a,o,u,i,l);if(c.filterWidth===1&&c.filterHeight===1&&w.arraysEqual(c.inShape,c.outShape))return Yn({inputs:{x:r},backend:n});let d=new Jc(c,"max",!1);return n.runWebGLProgram(d,[r],r.dtype)}var fee={kernelName:Ya,backendName:"webgl",kernelFunc:pee};function mee(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{filterSize:a,strides:o,pad:i,dataFormat:l,dimRoundingMode:u}=s,c=[1,1,1],d=D.computePool3DInfo(r.shape,a,o,c,i,u,l),h=new W2(d,"max",!1);return n.runWebGLProgram(h,[r],r.dtype)}var gee={kernelName:Hu,backendName:"webgl",kernelFunc:mee},Aee=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideHeight,n=e.strideWidth,s=e.dilationHeight,r=e.effectiveFilterHeight,a=e.effectiveFilterWidth,o=r-1-e.padInfo.top,i=a-1-e.padInfo.left,l=r*a-1;this.userCode=`
const ivec2 pads = ivec2(${o}, ${i});
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 += ${s}) {
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 < ${a}; wC++) {
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(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 * ${a} + wC;
float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);
dotProd += dyValue * mask;
}
}
setOutput(dotProd);
}
`}},yee=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,n=e.strideHeight,s=e.strideWidth,r=e.dilationDepth,a=e.dilationHeight,o=e.dilationWidth,i=e.effectiveFilterDepth,l=e.effectiveFilterHeight,u=e.effectiveFilterWidth,c=i-1-e.padInfo.front,d=l-1-e.padInfo.top,h=u-1-e.padInfo.left,p=i*l*u-1;this.userCode=`
const ivec3 pads = ivec3(${c}, ${d}, ${h});
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 < ${i};
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 += ${a}) {
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 < ${u};
wC += ${o}) {
float dyC = float(dyCCorner + wC) / ${s}.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 = ${p} -
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 xee(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a}=t,o=a,{filterSize:i,strides:l,pad:u,dimRoundingMode:c}=s,d=[1,1,1],h=D.computePool3DInfo(o.shape,i,l,d,u,c),p=new W2(h,"max",!0),f=n.runWebGLProgram(p,[o],o.dtype),m=new yee(h),g=n.runWebGLProgram(m,[r,f],o.dtype);return n.disposeIntermediateTensorInfo(f),g}var bee={kernelName:mh,backendName:"webgl",kernelFunc:xee};function vee(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a,output:o}=t,i=a;nu([a,o],"maxPoolGrad");let{filterSize:l,strides:u,pad:c,dimRoundingMode:d}=s,h=D.computePool2DInfo(i.shape,l,u,1,c,d),p=!0,f=new Jc(h,"max",p),m=n.runWebGLProgram(f,[i],i.dtype),g=new Aee(h),A=n.runWebGLProgram(g,[r,m],i.dtype);return n.disposeIntermediateTensorInfo(m),A}var wee={kernelName:fh,backendName:"webgl",kernelFunc:vee};function kee(e,t,n,s){let r=new Jc(n,"max",!1),a=s.runWebGLProgram(r,[e],"float32");r=new Jc(n,"max",!0,!0,t);let o=s.runWebGLProgram(r,[e],"float32");return[a,o]}var Iee={kernelName:gh,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:s}=e,{filterSize:r,strides:a,pad:o,includeBatchInIndex:i}=t,l=n;w.assert(s.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${s.shape.length}.`);let u=[1,1];w.assert(D.eitherStridesOrDilationsAreOne(a,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${a} and dilations '${u}'`);let c=D.computePool2DInfo(s.shape,r,a,u,o),[d,h]=kee(s,i,c,l);return[d,h]}};function See(e,t,n,s){let r=w.sizeFromShape(t),o=w.sizeFromShape(e.shape)/r,i=ye({inputs:{x:e},attrs:{shape:[o,r]},backend:s}),l=ni(i,"float32","mean",s),u=ye({inputs:{x:l},attrs:{shape:n},backend:s});return s.disposeIntermediateTensorInfo(i),s.disposeIntermediateTensorInfo(l),u}var Cee={kernelName:Ja,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:s}=e,{keepDims:r,axis:a}=t,o=n,i=s.shape.length,l=w.parseAxisParam(a,s.shape),u=l,c=D.getAxesPermutation(u,i),d=c!=null,h=o.shouldExecuteOnCPU([s]),p=[],f=s;if(d){if(h){let b=o.texData.get(f.dataId).values,v=new Array(i);for(let C=0;C<v.length;C++)v[C]=s.shape[c[C]];let k=L2(b,s.shape,s.dtype,c,v);f=o.makeTensorInfo(v,s.dtype);let S=o.texData.get(f.dataId);S.values=k}else f=Cf(s,c,o);p.push(f),u=D.getInnerMostAxes(u.length,i)}D.assertAxesAreInnerMostDims("sum",u,i);let[m,g]=D.computeOutAndReduceShapes(f.shape,u),A=m;r&&(A=D.expandShapeToKeepDim(m,l));let y=See(f,g,A,o);for(let x of p)o.disposeIntermediateTensorInfo(x);return y}};function Tee(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s,i=r.shape.length,l=w.parseAxisParam(a,r.shape),u=l,c=D.getAxesPermutation(u,i),d=r;c!=null&&(d=Sn({inputs:{x:r},backend:n,attrs:{perm:c}}),u=D.getInnerMostAxes(u.length,r.shape.length)),D.assertAxesAreInnerMostDims("min",u,i);let[h,p]=D.computeOutAndReduceShapes(d.shape,u),f=w.sizeFromShape(p),m=ye({inputs:{x:d},backend:n,attrs:{shape:[-1,f]}}),g=ni(m,m.dtype,"min",n),A;if(o){let y=D.expandShapeToKeepDim(h,l);A=ye({inputs:{x:g},backend:n,attrs:{shape:y}})}else A=ye({inputs:{x:g},backend:n,attrs:{shape:h}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(g),c!=null&&n.disposeIntermediateTensorInfo(d),A}var Nee={kernelName:Qa,backendName:"webgl",kernelFunc:Tee},Eee=j6+`
return min(a, b);
`,Ree=`
vec4 result = vec4(min(a, b));
vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
`+If+`
return result;
`,_ee=ln({opSnippet:Eee,packedOpSnippet:Ree,cpuKernelImpl:SX}),Dee={kernelName:eo,backendName:"webgl",kernelFunc:_ee},$ee=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((u,c)=>u[0]+e[c]+u[1]);let s=e.length,r=ht(s),a=t.map(u=>u[0]).join(","),o=t.map((u,c)=>u[0]+e[c]).join(","),i=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,s),l=n==="reflect"?0:1;if(s===1){this.userCode=`
int start = ${a};
int end = ${o};
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 = ${r}(${a});
${r} end = ${r}(${o});
void main() {
${r} outC = getOutputCoords();
for (int i = 0; i < ${s}; 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};
}
}
${r} coords = outC - start;
setOutput(getX(${i}));
}
`}},Fee=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((p,f)=>p[0]+e[f]+p[1]);let s=e.length,r=ht(s),a=t.map(p=>p[0]).join(","),o=t.map((p,f)=>p[0]+e[f]).join(","),i=In("rc",s),l=In("source",s),u=`${i[s-1]} < ${this.outputShape[s-1]}`,c=s===1?"source":`vec2(${l.slice(-2).join()})`,d=n==="reflect"?0:1,h="";if(s===1){let p=`
${r} source = rc;
if (source < start) {
source = start * 2 - source - ${d};
} else if (source >= end) {
source = (end - 1) * 2 - source + ${d};
}
source -= start;
`;h=`
${r} rc = outputLoc;
${p}
result[0] = getChannel(getX(${l.join()}), ${c});
${i[s-1]} += 1;
if(${u}) {
${p}
result[1] = getChannel(getX(${l.join()}), ${c});
}
`}else{let p=`
${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 - ${d}) +
gte * ((end - 1) * 2 - source + ${d});
source -= start;
`;h=`
${r} rc = outputLoc;
${p}
result[0] = getChannel(getX(${l.join()}), ${c});
${i[s-1]} += 1;
if(${u}) {
${p}
result[1] = getChannel(getX(${l.join()}), ${c});
}
rc = outputLoc;
${i[s-2]} += 1;
if(${i[s-2]} < ${this.outputShape[s-2]}) {
${p}
result[2] = getChannel(getX(${l.join()}), ${c});
${i[s-1]} += 1;
if(${u}) {
${p}
result[3] = getChannel(getX(${l.join()}), ${c});
}
}
`}this.userCode=`
const ${r} start = ${r}(${a});
const ${r} end = ${r}(${o});
void main() {
${r} outputLoc = getOutputCoords();
vec4 result = vec4(0.);
${h}
setOutput(result);
}
`}},Oee=({inputs:e,backend:t,attrs:n})=>{let{x:s}=e,{paddings:r,mode:a}=n,o=Q().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Fee(s.shape,r,a):new $ee(s.shape,r,a);return t.runWebGLProgram(o,[s],s.dtype)},Pee={kernelName:to,backendName:"webgl",kernelFunc:Oee},Mee=`if (b == 0.0) return NAN;
return mod(a, b);`,zee=`
vec4 result = mod(a, b);
vec4 isNaN = vec4(equal(b, vec4(0.0)));
`+If+`
return result;
`,Lee=ln({opSnippet:Mee,packedOpSnippet:zee}),Bee={kernelName:Ji,backendName:"webgl",kernelFunc:Lee},Wee=class{constructor(e,t,n){this.variableNames=["probs"],this.customUniforms=[{name:"seed",type:"float"}],this.outputShape=[e,n],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}));
}
`}},Vee=`
if (a == b) {
return 1.0;
};
return a / b;`,Uee=`
// 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;
`,E4=ln({opSnippet:Vee,packedOpSnippet:Uee,checkOutOfBounds:!0}),Hee={kernelName:La,backendName:"webgl",kernelFunc:E4},R4="return a - b;",_4=ln({opSnippet:R4,packedOpSnippet:R4,supportsComplex:!0,cpuKernelImpl:WX}),Gee={kernelName:bo,backendName:"webgl",kernelFunc:_4};function D4(e){let{inputs:t,backend:n,attrs:s}=e,{logits:r}=t,{dim:a}=s,o=w.parseAxisParam([a],r.shape),i=N4({inputs:{x:r},backend:n,attrs:{reductionIndices:o,keepDims:!1}}),l=D.expandShapeToKeepDim(i.shape,o),u=ye({inputs:{x:i},backend:n,attrs:{shape:l}}),c=_4({inputs:{a:r,b:u},backend:n}),d=w4({inputs:{x:c},backend:n}),h=Tf({inputs:{x:d},backend:n,attrs:{axis:o,keepDims:!1}}),p=ye({inputs:{x:h},backend:n,attrs:{shape:l}}),f=E4({inputs:{a:d,b:p},backend:n});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(p),f}var jee={kernelName:yo,backendName:"webgl",kernelFunc:D4};function qee(e){let{inputs:t,backend:n,attrs:s}=e,{logits:r}=t,{numSamples:a,seed:o,normalized:i}=s,l=i?r:D4({inputs:{logits:r},backend:n,attrs:{dim:r.shape.length-1}}),u=l.shape[0],c=l.shape[1],d=new Wee(u,c,a),h=[[o]],p=n.runWebGLProgram(d,[l],"int32",h);return i||n.disposeIntermediateTensorInfo(l),p}var Xee={kernelName:Ah,backendName:"webgl",kernelFunc:qee},$4="return -x;";function Kee(e){let{inputs:t,backend:n}=e,{x:s}=t;if(n.shouldExecuteOnCPU([s])){let a=n.texData.get(s.dataId),[o,i]=TX(a.values,s.shape,s.dtype);return n.makeTensorInfo(i,s.dtype,o)}let r;return Q().getBool("WEBGL_PACK_UNARY_OPERATIONS")?r=new iu(s.shape,$4):r=new ha(s.shape,$4),n.runWebGLProgram(r,[s],s.dtype)}var Zee={kernelName:Qi,backendName:"webgl",kernelFunc:Kee},Yee=rr.nonMaxSuppressionV3Impl;function Jee(e){D.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:s}=e,{boxes:r,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l}=s,u=n.readSync(r.dataId),c=n.readSync(a.dataId),{selectedIndices:d}=Yee(u,c,o,i,l);return n.makeTensorInfo([d.length],"int32",new Int32Array(d))}var Qee={kernelName:tl,backendName:"webgl",kernelFunc:Jee},ete=rr.nonMaxSuppressionV4Impl;function tte(e){D.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:s}=e,{boxes:r,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l,padToMaxOutputSize:u}=s,c=n.readSync(r.dataId),d=n.readSync(a.dataId),{selectedIndices:h,validOutputs:p}=ete(c,d,o,i,l,u);return[n.makeTensorInfo([h.length],"int32",new Int32Array(h)),n.makeTensorInfo([],"int32",new Int32Array([p]))]}var nte={kernelName:nl,backendName:"webgl",kernelFunc:tte},ste=rr.nonMaxSuppressionV5Impl;function rte(e){D.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:s}=e,{boxes:r,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l,softNmsSigma:u}=s,c=n.readSync(r.dataId),d=n.readSync(a.dataId),h=o,p=i,f=l,m=u,{selectedIndices:g,selectedScores:A}=ste(c,d,h,p,f,m);return[n.makeTensorInfo([g.length],"int32",new Int32Array(g)),n.makeTensorInfo([A.length],"float32",new Float32Array(A))]}var ate={kernelName:sl,backendName:"webgl",kernelFunc:rte},ote=class{constructor(e,t,n,s){this.variableNames=["indices"],this.outputShape=[e,t],this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
int index = round(getIndices(coords.x));
setOutput(mix(float(${s}), float(${n}),
float(index == coords.y)));
}
`}},ite=e=>{let{inputs:t,backend:n,attrs:s}=e,{indices:r}=t,{depth:a,onValue:o,offValue:i}=s,l=w.sizeFromShape(r.shape),u=new ote(l,a,o,i),c=ye({inputs:{x:r},backend:n,attrs:{shape:[l]}}),d=n.runWebGLProgram(u,[c],r.dtype);n.disposeIntermediateTensorInfo(c);let h=[...r.shape,a],p=ye({inputs:{x:d},backend:n,attrs:{shape:h}});return n.disposeIntermediateTensorInfo(d),p},lte={kernelName:so,backendName:"webgl",kernelFunc:ite};function Df(e){let{inputs:t,backend:n}=e,{x:s}=t;if(s.dtype==="complex64"){let r=Qc({inputs:{input:s},backend:n}),a=Df({inputs:{x:r},backend:n}),o=_f({inputs:{input:s},backend:n}),i=Df({inputs:{x:o},backend:n}),l=pa({inputs:{real:a,imag:i},backend:n});return n.disposeIntermediateTensorInfo(r),n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(i),l}else return ed({attrs:{shape:s.shape,dtype:s.dtype,value:s.dtype==="string"?"":0},backend:n})}var ute={kernelName:wl,backendName:"webgl",kernelFunc:Df};function F4(e){let{inputs:t,backend:n}=e,{x:s}=t;if(s.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(s.dtype==="complex64"){let r=Qc({inputs:{input:s},backend:n}),a=F4({inputs:{x:r},backend:n}),o=_f({inputs:{input:s},backend:n}),i=Df({inputs:{x:o},backend:n}),l=pa({inputs:{real:a,imag:i},backend:n});return n.disposeIntermediateTensorInfo(r),n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(i),l}else return ed({attrs:{shape:s.shape,dtype:s.dtype,value:1},backend:n})}var cte={kernelName:rl,backendName:"webgl",kernelFunc:F4};function dte(e){let{inputs:t,backend:n,attrs:s}=e,{axis:r}=s;if(t.length===1)return H2({inputs:{input:t[0]},backend:n,attrs:{dim:r}});let a=t[0].shape,o=t[0].dtype;t.forEach(c=>{w.assertShapesMatch(a,c.shape,"All tensors passed to stack must have matching shapes"),w.assert(o===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let i=[],l=t.map(c=>{let d=H2({inputs:{input:c},backend:n,attrs:{dim:r}});return i.push(d),d}),u=h4({inputs:l,backend:n,attrs:{axis:r}});return i.forEach(c=>n.disposeIntermediateTensorInfo(c)),u}var hte={kernelName:al,backendName:"webgl",kernelFunc:dte},pte=class{constructor(e,t,n){this.variableNames=["x"],this.customUniforms=[{name:"value",type:"float"}],this.outputShape=t.map((l,u)=>l[0]+e[u]+l[1]);let s=e.length,r=ht(s),a=t.map(l=>l[0]).join(","),o=t.map((l,u)=>l[0]+e[u]).join(","),i=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,s);if(s===1){this.userCode=`
int start = ${a};
int end = ${o};
void main() {
int outC = getOutputCoords();
if (outC < start || outC >= end) {
setOutput(value);
} else {
setOutput(getX(outC - start));
}
}
`;return}this.userCode=`
${r} start = ${r}(${a});
${r} end = ${r}(${o});
void main() {
${r} outC = getOutputCoords();
if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {
setOutput(value);
} else {
${r} coords = outC - start;
setOutput(getX(${i}));
}
}
`}},fte=class{constructor(e,t,n){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 s=e.length,r=ht(s),a=t.map(f=>f[0]).join(","),o=t.map((f,m)=>f[0]+e[m]).join(","),i=In("rc",s),l=In("source",s),u=`${i[s-1]} < ${this.outputShape[s-1]}`,c=s===1?"source":`vec2(${l.slice(-2).join()})`,d=[`${r} rc = outputLoc;`,`${i[s-1]} += 1;
if(${u}) {
`,s===1?"":`}
rc = outputLoc;
${i[s-2]} += 1;
if(${i[s-2]} < ${this.outputShape[s-2]}) {`,s===1?"":` ${i[s-1]} += 1;
if(${u}) {`],h=s===1?"rc < start || rc >= end":"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))",p="";for(let f=0,m=s===1?2:4;f<m;f++)p+=`
${d[f]}
if (${h}) {
result[${f}] = float(value);
} else {
${r} source = rc - start;
result[${f}] = getChannel(getX(${l.join()}), ${c});
}
`;p+=s===1?"} ":"}}",this.userCode=`
const ${r} start = ${r}(${a});
const ${r} end = ${r}(${o});
void main() {
${r} outputLoc = getOutputCoords();
vec4 result = vec4(0.);
${p}
setOutput(result);
}
`}},O4=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{paddings:a,constantValue:o}=s;if(w.sizeFromShape(r.shape)===0){let u=a.map((c,d)=>c[0]+r.shape[d]+c[1]);return ed({backend:n,attrs:{shape:u,value:o,dtype:r.dtype}})}let i=Q().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new fte(r.shape,a,o):new pte(r.shape,a,o),l=[[o]];return n.runWebGLProgram(i,[r],r.dtype,l)},mte={kernelName:ro,backendName:"webgl",kernelFunc:O4},gte=`
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);
`,Ate=`
// 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;
vec4 isNaN = vec4(lessThan(a, vec4(0.0))) * vec4(lessThan(floor(b), b));
`+If+`
return result;
`,yte=ln({opSnippet:gte,packedOpSnippet:Ate}),xte={kernelName:ao,backendName:"webgl",kernelFunc:yte};function bte(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s,i=r.shape.length,l=[],u=w.parseAxisParam(a,r.shape),c=u,d=D.getAxesPermutation(c,i),h=r;d!=null&&(h=Sn({inputs:{x:r},backend:n,attrs:{perm:d}}),c=D.getInnerMostAxes(c.length,i),l.push(h)),D.assertAxesAreInnerMostDims("prod",c,i);let p;if(n.shouldExecuteOnCPU([h])){let f=n.texData.get(h.dataId).values,{outVals:m,outShape:g,outDtype:A}=EX(h.shape,h.dtype,f,c);p=n.makeTensorInfo(g,A,m)}else{let[f,m]=D.computeOutAndReduceShapes(h.shape,c),g=w.sizeFromShape(m),A=ye({inputs:{x:h},backend:n,attrs:{shape:[-1,g]}}),y=Ph(r.dtype),x=ni(A,y,"prod",n);p=ye({inputs:{x},backend:n,attrs:{shape:f}}),l.push(A),l.push(x)}if(o){l.push(p);let f=D.expandShapeToKeepDim(p.shape,u);p=ye({inputs:{x:p},backend:n,attrs:{shape:f}})}return l.forEach(f=>n.disposeIntermediateTensorInfo(f)),p}var vte={kernelName:ol,backendName:"webgl",kernelFunc:bte},P4=e=>{let{backend:t,attrs:n}=e,{start:s,stop:r,step:a,dtype:o}=n,i=RX(s,r,a,o);return t.makeTensorInfo([i.length],o,i)},wte={kernelName:Gu,backendName:"webgl",kernelFunc:P4},kte="return 1.0 / x;",Ite=Je({opSnippet:kte}),Ste={kernelName:il,backendName:"webgl",kernelFunc:Ite},Cte=js+`
return (x < 0.0) ? 0.0 : x;
`,Tte=`
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;
`,Nte=Je({opSnippet:Cte,packedOpSnippet:Tte}),Ete={kernelName:io,backendName:"webgl",kernelFunc:Nte},Rte=js+`
return (x < 0.0) ? 0.0 : min(6.0, x);
`,_te=`
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;
`,Dte=Je({opSnippet:Rte,packedOpSnippet:_te}),$te={kernelName:uo,backendName:"webgl",kernelFunc:Dte},Fte=class{constructor(e,t,n,s,r){this.variableNames=["A"],this.outputShape=[];let[a,o,i,l]=e;this.outputShape=[a,t,n,l];let u=[s&&t>1?o-1:o,s&&n>1?i-1:i],c=[s&&t>1?t-1:t,s&&n>1?n-1:n],d;r?d="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":d="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
const vec2 effectiveInputOverOutputRatioRC = vec2(
${u[0]/c[0]},
${u[1]/c[1]});
const vec2 inputShapeRC = vec2(${o}.0, ${i}.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 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);
}
`}},Ote=class{constructor(e,t,n,s,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[a,o,i,l]=e;this.outputShape=[a,t,n,l];let u=[s&&t>1?o-1:o,s&&n>1?i-1:i],c=[s&&t>1?t-1:t,s&&n>1?n-1:n],d;r?d="(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":d="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
const vec3 effectiveInputOverOutputRatioRC = vec3(
${u[0]/c[0]},
${u[1]/c[1]},
${u[1]/c[1]});
const vec3 inputShapeRC = vec3(${o}.0, ${i}.0,
${i}.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 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 < ${n-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 Pte(e){let{inputs:t,backend:n,attrs:s}=e,{images:r}=t,{alignCorners:a,halfPixelCenters:o,size:i}=s,[l,u]=i,c=Q().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new Ote(r.shape,l,u,a,o):new Fte(r.shape,l,u,a,o);return n.runWebGLProgram(c,[r],"float32")}var Mte={kernelName:lo,backendName:"webgl",kernelFunc:Pte},zte=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,s,r]=t,[,a,o]=e,i=[n&&a>1?s-1:s,n&&o>1?r-1:r],l=[n&&a>1?a-1:a,n&&o>1?o-1:o],u=i[0]/l[0],c=i[1]/l[1],d=1/u,h=1/c,p=Math.ceil(d)*2+2,f=Math.ceil(h)*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(${c});
const float invHeightScale = float(${d});
const float invWidthScale = float(${h});
const int winHeight = int(${p});
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 >= ${a}) {
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 >= ${o}) {
continue;
}
float dxR = float(dyR) * heightScale;
int topDxRIndex = int(floor(dxR));
int bottomDxRIndex = int(min(ceil(dxR), ${s-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 Lte(e){let{inputs:t,backend:n,attrs:s}=e,{images:r,dy:a}=t,{alignCorners:o}=s,i=new zte(a.shape,r.shape,o);return n.runWebGLProgram(i,[a],a.dtype)}var Bte={kernelName:bh,backendName:"webgl",kernelFunc:Lte},Wte=class{constructor(e,t,n,s,r){this.variableNames=["A"],this.outputShape=[];let[a,o,i,l]=e;this.outputShape=[a,t,n,l];let u=[s&&t>1?o-1:o,s&&n>1?i-1:i],c=[s&&t>1?t-1:t,s&&n>1?n-1:n],d=s?"0.5":"0.0",h;r?h="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":h="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
const vec2 effectiveInputOverOutputRatioRC = vec2(
${u[0]/c[0]},
${u[1]/c[1]});
const vec2 inputShapeRC = vec2(${o}.0, ${i}.0);
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
ivec2 yRC = coords.yz;
// Fractional source index.
vec2 sourceFracIndexRC = ${h};
// Compute the coordinators of nearest neighbor point.
ivec2 sourceNearestRC = ivec2(
min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${d})));
float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d);
setOutput(newValue);
}
`}},Vte=class{constructor(e,t,n,s,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[a,o,i,l]=e;this.outputShape=[a,t,n,l];let u=[s&&t>1?o-1:o,s&&n>1?i-1:i],c=[s&&t>1?t-1:t,s&&n>1?n-1:n],d=s?"0.5":"0.0",h;r?h="max((vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC, vec3(0.0))":h="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
const vec3 effectiveInputOverOutputRatioRC = vec3(
${u[0]/c[0]},
${u[1]/c[1]},
${u[1]/c[1]});
const vec3 inputShapeRC = vec3(${o}.0, ${i}.0,
${i}.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 = ${h};
// Compute the coordinators of nearest neighbor point.
ivec3 sourceNearestRC = ivec3(
min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${d})));
// Should we calculate next column and row elements in 2x2 packed cell.
bool hasNextCol = d < ${l-1};
bool hasNextRow = coords.z < ${n-1};
vec4 newValue = vec4(
getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d),
hasNextCol ? getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d + 1)
: 0.0,
hasNextRow ? getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d)
: 0.0,
(hasNextRow && hasNextCol) ?
getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d + 1) : 0.0);
setOutput(newValue);
}
`}};function Ute(e){let{inputs:t,backend:n,attrs:s}=e,{images:r}=t,{alignCorners:a,halfPixelCenters:o,size:i}=s,[l,u]=i,c=Q().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new Vte(r.shape,l,u,a,o):new Wte(r.shape,l,u,a,o);return n.runWebGLProgram(c,[r],r.dtype)}var Hte={kernelName:ju,backendName:"webgl",kernelFunc:Ute},Gte=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,s,r]=t,[,a,o]=e,i=[n&&a>1?s-1:s,n&&o>1?r-1:r],l=[n&&a>1?a-1:a,n&&o>1?o-1:o],u=i[0]/l[0],c=i[1]/l[1],d=1/u,h=1/c,p=Math.ceil(d)*2+2,f=Math.ceil(h)*2+2;this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
int r = coords[1];
int c = coords[2];
float accumulator = 0.0;
const float heightScale = float(${u});
const float widthScale = float(${c});
const float invHeightScale = float(${d});
const float invWidthScale = float(${h});
const int winHeight = int(${p});
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 >= ${a}) {
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 >= ${o}) {
continue;
}
float sourceFracRow =
float(${i[0]}) *
(float(dyR) / float(${l[0]}));
float sourceFracCol =
float(${i[1]}) *
(float(dyC) / float(${l[1]}));
int sourceNearestRow = int(min(
float(int(${s}) - 1),
${n} ? float(round(sourceFracRow)) :
float(floor(sourceFracRow))));
int sourceNearestCol = int(min(
float(int(${r}) - 1),
${n} ? float(round(sourceFracCol)) :
float(floor(sourceFracCol))));
if (r == sourceNearestRow && c == sourceNearestCol) {
accumulator += getDy(b, dyR, dyC, d);
}
}
}
// End loop over dy
setOutput(accumulator);
}
`}};function jte(e){let{inputs:t,backend:n,attrs:s}=e,{images:r,dy:a}=t,{alignCorners:o}=s,i=new Gte(a.shape,r.shape,o);return n.runWebGLProgram(i,[a],a.dtype)}var qte={kernelName:xh,backendName:"webgl",kernelFunc:jte},Xte=class{constructor(e,t){this.variableNames=["x"];let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);if(this.outputShape=e,n===1){this.userCode=`
void main() {
int coord = getOutputCoords();
setOutput(getX(${e[0]} - coord - 1));
}
`;return}let s=o=>t.indexOf(o)!==-1&&e[o]!==1?`${e[o]} - coords[${o}] - 1`:`coords[${o}]`,r=e.map((o,i)=>s(i)).join(","),a=ht(n);this.userCode=`
void main() {
${a} coords = getOutputCoords();
setOutput(getX(${r}));
}
`}},Kte=class{constructor(e,t){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);this.outputShape=e;let s=In("rc",n),r=`${s[n-1]} + 1 < ${this.outputShape[n-1]}`,a=`${s[n-2]} + 1 < ${this.outputShape[n-2]}`,o=ht(n);n===1?this.userCode=`
void main(){
int rc = getOutputCoords();
vec4 result = vec4(0.);
result.r = getChannel(getX(${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() {
${o} rc = getOutputCoords();
vec4 result = vec4(0.);
result.r = ${i(s.slice())};
if(${r}){
result.g = ${l(s.slice())};
}
if(${a}) {
result.b = ${u(s.slice())};
if(${r}) {
result.a = ${c(s.slice())};
}
}
setOutput(result);
}
`;function i(p){return d(p)}function l(p){return p[n-1]="("+p[n-1]+" + 1)",d(p)}function u(p){return p[n-2]="("+p[n-2]+" + 1)",d(p)}function c(p){return p[n-1]="("+p[n-1]+" + 1)",p[n-2]="("+p[n-2]+" + 1)",d(p)}function d(p){let f=e.map((A,y)=>h(y,p)),m=f.join(","),g=f.slice(-2).join(",");return`getChannel(getX(${m}), vec2(${g}))`}function h(p,f){return t.indexOf(p)!==-1&&e[p]!==1?`${e[p]} - ${f[p]} - 1`:`${f[p]}`}}};function Zte(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{dims:a}=s,o=r.shape.length,i=w.parseAxisParam(a,r.shape);if(o===0)return Yn({inputs:{x:r},backend:n});let l=Q().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Kte(r.shape,i):new Xte(r.shape,i);return n.runWebGLProgram(l,[r],r.dtype)}var Yte={kernelName:co,backendName:"webgl",kernelFunc:Zte},Jte=class{constructor(e,t){this.variableNames=["Image"],this.outputShape=[],this.customUniforms=[{name:"params",type:"vec4"}];let n=e[1],s=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 < ${s} && coordY >= 0 && coordY < ${n}) {
outputValue = getImage(coords[0], coordY, coordX, coords[3]);
}
setOutput(outputValue);
}
`}},Qte={kernelName:kl,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:s}=e,{radians:r,fillValue:a,center:o}=t,i=n,l=new Jte(s.shape,a),[u,c]=D.getImageCenter(o,s.shape[1],s.shape[2]),d=[[u,c,Math.sin(r),Math.cos(r)]];return i.runWebGLProgram(l,[s],s.dtype,d)}},ene=`
// OpenGL ES does not support round function.
// The algorithm is based on banker's rounding.
float base = floor(x);
if ((x - base) < 0.5) {
return floor(x);
} else if ((x - base) > 0.5) {
return ceil(x);
} else {
if (mod(base, 2.0) == 0.0) {
return base;
} else {
return base + 1.0;
}
}
`,tne=Je({opSnippet:ene}),nne={kernelName:ho,backendName:"webgl",kernelFunc:tne},sne="return inversesqrt(x);",rne=Je({opSnippet:sne,cpuKernelImpl:_X}),ane={kernelName:po,backendName:"webgl",kernelFunc:rne},M4=class{constructor(e,t,n,s,r,a,o=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=a;let i=ht(r.length),l=ht(a.length),u="";n===1?u="i":n===2&&(u="i, j");let c=`getIndices(${u})`,d="";s===1?d="i":s===2&&(d="i, coords[1]");let h=`getUpdates(${d})`,p=t>1?"strides[j]":"strides";this.userCode=`
${i} strides = ${i}(${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 < ${t}; j++) {
int index = round(${c});
flattenedIndex += index * ${p};
}
if (flattenedIndex == coords[0]) {
sum += ${h};
found = true;
}
}
setOutput(mix(getDefaultValue(), sum, float(found)));
}
`}};function one(e){let{inputs:t,backend:n,attrs:s}=e,{indices:r,updates:a}=t,{shape:o}=s,{sliceRank:i,numUpdates:l,sliceSize:u,strides:c,outputSize:d}=D.calculateShapes(a,r,o),h=[d/u,u];if(d===0)return n.makeTensorInfo(o,r.dtype);let p=ye({inputs:{x:r},backend:n,attrs:{shape:[l,i]}}),f=ye({inputs:{x:a},backend:n,attrs:{shape:[l,u]}}),m=n.makeTensorInfo([],"float32",new Float32Array([0])),g=new M4(l,i,p.shape.length,f.shape.length,c,h),A=n.runWebGLProgram(g,[f,p,m],f.dtype),y=ye({inputs:{x:A},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(A),n.disposeIntermediateTensorInfo(m),y}var ine={kernelName:ul,backendName:"webgl",kernelFunc:one},lne=class{constructor(e,t,n){this.variableNames=["c","a","b"],this.outputShape=t;let s,r;if(n>4)throw Error(`Where for rank ${n} is not yet supported`);if(n===1)r="resRC",s="resRC";else{let o=["resRC.x","resRC.y","resRC.z","resRC.w"],i=[],l=[];for(let u=0;u<t.length;u++)l.push(`${o[u]}`),u<e&&i.push(`${o[u]}`);s=i.join(),r=l.join()}let a=ht(n);this.userCode=`
void main() {
${a} resRC = getOutputCoords();
float cVal = getC(${s});
if (cVal >= 1.0) {
setOutput(getA(${r}));
} else {
setOutput(getB(${r}));
}
}
`}};function une(e){let{inputs:t,backend:n}=e,{condition:s,t:r,e:a}=t,o=new lne(s.shape.length,r.shape,r.shape.length);return n.runWebGLProgram(o,[s,r,a],Cs(r.dtype,a.dtype))}var cne={kernelName:cl,backendName:"webgl",kernelFunc:une},dne=`
// Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
// see: https://arxiv.org/abs/1706.02515
float scaleAlpha = ${D.SELU_SCALEALPHA};
float scale = ${D.SELU_SCALE};
return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
`,hne=Je({opSnippet:dne}),pne={kernelName:dl,backendName:"webgl",kernelFunc:hne},z4="return 1.0 / (1.0 + exp(-1.0 * x));",fne=Je({opSnippet:z4,packedOpSnippet:z4,cpuKernelImpl:DX}),mne={kernelName:mo,backendName:"webgl",kernelFunc:fne},gne=`
if (isnan(x)) { return 0.0; }
return sign(x);
`,Ane=Je({opSnippet:gne}),yne={kernelName:fl,backendName:"webgl",kernelFunc:Ane},xne=Y6+`
return sin(x);
`,bne=Je({opSnippet:xne}),vne={kernelName:fo,backendName:"webgl",kernelFunc:bne},wne=`
float e2x = exp(x);
return (e2x - 1.0 / e2x) / 2.0;
`,kne=Je({opSnippet:wne}),Ine={kernelName:pl,backendName:"webgl",kernelFunc:kne},Sne=`
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;
`,Cne=Je({opSnippet:Sne}),Tne={kernelName:ml,backendName:"webgl",kernelFunc:Cne},Nne=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockShape:a,paddings:o}=s;w.assert(r.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");let i=a.reduce((A,y)=>A*y),l=[[0,0]];l.push(...o);for(let A=1+a.length;A<r.shape.length;++A)l.push([0,0]);let u=[],c=O4({inputs:{x:r},backend:n,attrs:{paddings:l,constantValue:0}}),d=D.getReshaped(c.shape,a,i,!1),h=D.getPermuted(d.length,a.length,!1),p=D.getReshapedPermuted(c.shape,a,i,!1),f=ye({inputs:{x:c},backend:n,attrs:{shape:d}}),m=Sn({inputs:{x:f},backend:n,attrs:{perm:h}}),g=ye({inputs:{x:m},backend:n,attrs:{shape:p}});return u.push(c),u.push(f),u.push(m),u.forEach(A=>n.disposeIntermediateTensorInfo(A)),g},Ene={kernelName:gl,backendName:"webgl",kernelFunc:Nne};function Rne(e){let{inputs:t,backend:n}=e,{indices:s,values:r,denseShape:a,defaultValue:o}=t;if(a.shape.length!==1)throw new Error(`Dense shape must be a vector, saw:
${a.shape}`);if(s.shape.length!==2)throw new Error(`Indices must be a matrix, saw:
${s.shape}`);if(r.shape.length!==1)throw new Error(`Values must be a vector, saw:
${r.shape}`);if(o.shape.length!==0)throw new Error(`Default value must be a scalar, saw:
${o.shape}`);let i=n.readSync(s.dataId),l=n.readSync(r.dataId),u=n.readSync(a.dataId),c=n.readSync(o.dataId)[0],[d,h,p,f,m]=FX(i,s.shape,s.dtype,l,r.dtype,u,c);return[n.makeTensorInfo(h,s.dtype,d),n.makeTensorInfo([h[0]],r.dtype,p),n.makeTensorInfo([f.length],"bool",new Uint8Array(f.map(g=>Number(g)))),n.makeTensorInfo([m.length],s.dtype,new Int32Array(m))]}var _ne={kernelName:vh,backendName:"webgl",kernelFunc:Rne};function Dne(e){let{inputs:t,backend:n}=e,{inputIndices:s,inputShape:r,newShape:a}=t;if(s.shape.length!==2)throw new Error(`Input indices should be a matrix but received shape ${s.shape}`);if(r.shape.length!==1)throw new Error(`Input shape should be a vector but received shape ${r.shape}`);if(a.shape.length!==1)throw new Error(`Target shape should be a vector but received shape ${a.shape}`);let o=Array.from(n.readSync(r.dataId)),i=n.readSync(s.dataId),l=Array.from(n.readSync(a.dataId)),[u,c,d]=OX(i,s.shape,s.dtype,o,l);return[n.makeTensorInfo(c,s.dtype,u),n.makeTensorInfo([d.length],a.dtype,new Int32Array(d))]}var $ne={kernelName:wh,backendName:"webgl",kernelFunc:Dne};function Fne(e){let{inputs:t,backend:n}=e,{data:s,indices:r,segmentIds:a}=t;if(s.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(a.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
${a.shape}`);let o=n.readSync(s.dataId),i=n.readSync(r.dataId),l=n.readSync(a.dataId),[u,c]=z6(o,s.shape,s.dtype,i,l,!0);return n.makeTensorInfo(c,s.dtype,u)}var One={kernelName:kh,backendName:"webgl",kernelFunc:Fne};function Pne(e){let{inputs:t,backend:n}=e,{data:s,indices:r,segmentIds:a}=t;if(s.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(a.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
${a.shape}`);let o=n.readSync(s.dataId),i=n.readSync(r.dataId),l=n.readSync(a.dataId),[u,c]=z6(o,s.shape,s.dtype,i,l);return n.makeTensorInfo(c,s.dtype,u)}var Mne={kernelName:Ih,backendName:"webgl",kernelFunc:Pne};function zne(e){let{inputs:t,backend:n,attrs:s}=e,{sparseIndices:r,sparseValues:a,defaultValue:o}=t,{outputShape:i}=s,{sliceRank:l,numUpdates:u,strides:c,outputSize:d}=D.calculateShapes(a,r,i),h=!1,p=new M4(u,l,r.shape.length,a.shape.length,c,[d,1],h),f=n.runWebGLProgram(p,[a,r,o],a.dtype),m=ye({inputs:{x:f},backend:n,attrs:{shape:i}});return n.disposeIntermediateTensorInfo(f),m}var Lne={kernelName:Sh,backendName:"webgl",kernelFunc:zne};function Bne(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{numOrSizeSplits:a,axis:o}=s,i=w.parseAxisParam(o,r.shape)[0],l=D.prepareSplitSize(r,a,i),u=r.shape.length,c=new Array(u).fill(0),d=r.shape.slice();return l.map(h=>{let p=[...d];p[i]=h;let f=cu({inputs:{x:r},backend:n,attrs:{begin:c,size:p}});return c[i]+=h,f})}var Wne={kernelName:Al,backendName:"webgl",kernelFunc:Bne},L4="return sqrt(x);",Vne=Je({opSnippet:L4,packedOpSnippet:L4,cpuKernelImpl:PX}),Une={kernelName:go,backendName:"webgl",kernelFunc:Vne},Hne="return x * x;",Gne=Je({opSnippet:Hne}),jne={kernelName:qu,backendName:"webgl",kernelFunc:Gne},B4="return (a - b) * (a - b);",qne=ln({opSnippet:B4,packedOpSnippet:B4}),Xne={kernelName:xo,backendName:"webgl",kernelFunc:qne};function Kne({inputs:e,attrs:t,backend:n}){let{x:s}=e,r=js+`
return x > 0.0 ? 1.0 : float(${t.alpha});
`,a=new ha(s.shape,r);return n.runWebGLProgram(a,[s],s.dtype)}var Zne={kernelName:Gr,backendName:"webgl",kernelFunc:Kne},Yne=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=n;let s=n.length,r=ht(n.length),a=ht(n.length),o="";if(s===1)o="coords * strides + begin";else{let i=0;o=n.map((l,u)=>(i++,n.length===1?`coords * strides[${u}] + begin[${u}]`:`coords[${i-1}] * strides[${u}] + begin[${u}]`)).join(",")}this.userCode=`
${r} begin = ${r}(${e});
${r} strides = ${r}(${t});
void main() {
${a} coords = getOutputCoords();
setOutput(getX(${o}));
}
`}};function Jne(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{begin:a,end:o,strides:i,beginMask:l,endMask:u,ellipsisMask:c,newAxisMask:d,shrinkAxisMask:h}=s,{nonStrided:p,$begin:f,$strides:m,size:g,newShape:A,outShape:y}=xn.sliceInfo(r.shape,a,o,i,l,u,c,d,h),x=ye({inputs:{x:r},backend:n,attrs:{shape:A}}),b;if(p){let k=cu({inputs:{x},backend:n,attrs:{begin:f,size:g}});b=ye({inputs:{x:k},backend:n,attrs:{shape:y}}),n.disposeIntermediateTensorInfo(k)}else if(y.some(k=>k===0))b=n.makeTensorInfo(y,r.dtype,[]);else if(n.shouldExecuteOnCPU([x])){let C=n.texData.get(x.dataId).values,_=We(x.shape,x.dtype,C),O=MX(y,_,m,f);b=n.makeTensorInfo(y,x.dtype,O.values)}else{let S=new Yne(f,m,y);b=n.runWebGLProgram(S,[x],x.dtype)}let v=ye({inputs:{x:b},backend:n,attrs:{shape:y}});return n.disposeIntermediateTensorInfo(x),n.disposeIntermediateTensorInfo(b),v}var Qne={kernelName:yl,backendName:"webgl",kernelFunc:Jne};function ese(e){let{inputs:t,backend:n,attrs:s}=e,{separator:r,nGramWidths:a,leftPad:o,rightPad:i,padWidth:l,preserveShortSequences:u}=s,{data:c,dataSplits:d}=t,h=n.readSync(c.dataId),p=n.readSync(d.dataId),[f,m]=zX(h,p,r,a,o,i,l,u);return[n.makeTensorInfo([f.length],"string",f),n.makeTensorInfo(d.shape,"int32",m)]}var tse={kernelName:Ch,backendName:"webgl",kernelFunc:ese};function nse(e){let{inputs:t,backend:n,attrs:s}=e,{skipEmpty:r}=s,{input:a,delimiter:o}=t;if(a.dtype!=="string")throw new Error("Input must be of datatype string");if(a.shape.length!==1)throw new Error(`Input must be a vector, got shape: ${a.shape}`);if(o.shape.length!==0)throw new Error(`Delimiter must be a scalar, got shape: ${o.shape}`);let i=n.readSync(a.dataId),l=n.readSync(o.dataId)[0],[u,c,d]=LX(i,l,r),h=c.length;return[n.makeTensorInfo([h,2],"int32",u),n.makeTensorInfo([h],"string",c),n.makeTensorInfo([2],"int32",new Int32Array(d))]}var sse={kernelName:Th,backendName:"webgl",kernelFunc:nse};function rse(e){let{inputs:t,backend:n,attrs:s}=e,{numBuckets:r}=s,{input:a}=t;if(a.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 o=n.readSync(a.dataId),i=BX(o,r);return n.makeTensorInfo(a.shape,"int32",i)}var ase={kernelName:Nh,backendName:"webgl",kernelFunc:rse},ose="return tan(x);",ise=Je({opSnippet:ose}),lse={kernelName:vo,backendName:"webgl",kernelFunc:ise},use=`
float e2x = exp(-2.0 * abs(x));
return sign(x) * (1.0 - e2x) / (1.0 + e2x);
`,cse=Je({opSnippet:use}),dse={kernelName:wo,backendName:"webgl",kernelFunc:cse},hse=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let a=0;a<n.length;a++)n[a]=e[a]*t[a];this.outputShape=n,this.rank=n.length;let s=ht(this.rank),r=pse(e);this.userCode=`
void main() {
${s} resRC = getOutputCoords();
setOutput(getA(${r}));
}
`}};function pse(e){let t=e.length;if(t>5)throw Error(`Tile for rank ${t} is not yet supported`);if(t===1)return`imod(resRC, ${e[0]})`;let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],s=[];for(let r=0;r<e.length;r++)s.push(`imod(${n[r]}, ${e[r]})`);return s.join()}function W4(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{reps:a}=s;if(r.dtype==="string"||r.shape.length>5){let l=n.readSync(r.dataId),u=r.dtype==="string"?l.map(h=>w.decodeString(h)):l,c=We(r.shape,r.dtype,u),d=VX(c,a);return n.makeTensorInfo(d.shape,d.dtype,d.values)}let o=new hse(r.shape,a);return n.runWebGLProgram(o,[r],r.dtype)}var fse={kernelName:Hr,backendName:"webgl",kernelFunc:W4},mse=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));
}
}
`}},gse=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 si(e,t){t!==null&&e.disposeIntermediateTensorInfo(t)}function V4(e){let t=1;for(;t<e;)t*=2;return t}function Ase(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{k:a,sorted:o}=s,i=Q().getNumber("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD"),l=Q().getNumber("TOPK_K_CPU_HANDOFF_THRESHOLD"),u=r.shape,c=u[u.length-1];if(n.shouldExecuteOnCPU([r])||c<i||a>l){let O=n.readSync(r.dataId),[E,R]=UX(O,u,r.dtype,a,o);return[n.makeTensorInfo(E.shape,E.dtype,E.values),n.makeTensorInfo(R.shape,R.dtype,R.values)]}if(a===0)return u[u.length-1]=0,[n.makeTensorInfo(u,r.dtype,[]),n.makeTensorInfo(u,"int32",[])];if(c===1)return[r,ed({attrs:{shape:u,dtype:"int32",value:0},backend:n})];let d=n.texData.get(r.dataId),h=d!==null&&d.isPacked,p=h?n.unpackTensor(r):r,m=w.sizeFromShape(u)/c,g=ye({inputs:{x:p},attrs:{shape:[m,c]},backend:n});h&&si(n,p);let A=V4(a),y=V4(c),x=null,b=()=>x===null?[g,g]:[g,x],v=(O,E,R)=>{let T=b(),P=new mse(R),j=[[c],[x===null?1:0],[Number.NEGATIVE_INFINITY],[O],[E]],q=x;x=n.runWebGLProgram(P,T,"int32",j),si(n,q)};for(let O=1;O<A;O*=2){let E=O*2;for(let R=O;R>=1;R/=2)v(E,R,[m,y])}for(let O=y;O>A;O/=2){let E=b(),R=new gse([m,O/2]),P=[[c],[x===null?1:0],[A]],V=x;x=n.runWebGLProgram(R,E,"int32",P),si(n,V);let j=A/2,q=j*2;for(let X=j;X>=1;X/=2)v(q,X,x.shape)}let k=x;x=cu({inputs:{x},backend:n,attrs:{begin:0,size:[m,a]}}),si(n,k);let S=T4({inputs:{x:g,indices:x},backend:n,attrs:{axis:1,batchDims:1}});si(n,g);let C=u.slice(0,-1);C.push(a),k=x,x=ye({inputs:{x},attrs:{shape:C},backend:n}),si(n,k);let _=S;return S=ye({inputs:{x:S},attrs:{shape:C},backend:n}),si(n,_),[S,x]}var yse={kernelName:xl,backendName:"webgl",kernelFunc:Ase},xse=class{constructor(e,t,n,s,r,a){this.variableNames=["Image","Transforms"],this.outputShape=a;let o=n==="nearest"?1:2,i;switch(s){case"constant":i=1;break;case"reflect":i=2;break;case"wrap":i=3;break;case"nearest":i=4;break;default:i=1;break}this.userCode=`
float mapCoord(float outCoord, float len) {
float inCoord = outCoord;
if(${i} == 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 (${i} == 3) {
if (inCoord < 0.0) {
if (len <= 1.0) {
inCoord = 0.0;
} else {
float sz = len - 1.0;
inCoord += len * (float(int(float(-inCoord / sz))) + 1.0);
}
} else if (inCoord > len - 1.0) {
if (len <= 1.0) {
inCoord = 0.0;
} else {
float sz = len - 1.0;
inCoord -= len * float(int(float(inCoord / sz)));
}
}
return clamp(inCoord, 0.0, len - 1.0);
} else if (${i} == 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(${e}));
if (${o} == 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 bse(e){let{inputs:t,backend:n,attrs:s}=e,{image:r,transforms:a}=t,{interpolation:o,fillMode:i,fillValue:l,outputShape:u}=s,[c,d,h,p]=r.shape,[f,m]=u!=null?u:[d,h],g=[c,f,m,p],A=new xse(d,h,o,i,l,g);return n.runWebGLProgram(A,[r,a],"float32")}var vse={kernelName:bl,backendName:"webgl",kernelFunc:bse};function wse(e){let{inputs:t,attrs:n,backend:s}=e,{axis:r}=n,{x:a}=t;nu(a,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");let o=s.readSync(a.dataId),{outputValues:i,outputShape:l,indices:u}=HX(o,r,a.shape,a.dtype);return[s.makeTensorInfo(l,a.dtype,i),s.makeTensorInfo([u.length],"int32",u)]}var kse={kernelName:Eh,backendName:"webgl",kernelFunc:wse};function Ise(e){let{inputs:t,backend:n,attrs:s}=e,{value:r}=t,{axis:a}=s;a<0&&(a+=r.shape.length);let o=r,i=o.shape.length,l=r.shape[a],u=new Array(i-1),c=0;for(let m=0;m<i;m++)m!==a&&(u[c++]=o.shape[m]);let d=[],h=new Array(i).fill(0),p=o.shape.slice();p[a]=1;let f=new Array(l);for(let m=0;m<f.length;m++){h[a]=m;let g=cu({inputs:{x:o},backend:n,attrs:{begin:h,size:p}}),A=ye({inputs:{x:g},backend:n,attrs:{shape:u}});f[m]=A,d.push(g)}return d.forEach(m=>n.disposeIntermediateTensorInfo(m)),f}var Sse={kernelName:vl,backendName:"webgl",kernelFunc:Ise},Cse=class{constructor(e,t){this.variableNames=["x","segmentIds"];let n=e.windowSize,s=e.batchSize,r=e.inSize,a=e.numSegments,o=a*Math.ceil(r/n);this.outputShape=[s,o];let i="0.0",l="sumValue",u=Math.floor(n/4)*4,c=n%4,d=`
sumValue += dot(values, segFilter);
`,h="";r%n>0&&(h=`
if (inIdx < 0 || inIdx >= ${r}) {
return initializationValue;
}
`);let p="";r%n>0&&(p=`
if (inIdx < 0 || inIdx >= ${r}) {
return -1.0;
}
`),this.userCode=`
const float initializationValue = ${i};
float getValue(int batch, int inIdx) {
${h}
return getX(batch, inIdx);
}
float getSegmentIdAtIndex(int inIdx) {
${p}
return getSegmentIds(inIdx);
}
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
int outIdx = coords[1];
int inOffset = int(floor(float(outIdx) / float(
${a})) * float(${n}));
int currentSeg = int(mod(float(outIdx), float(${a})));
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
);
${d}
}
int inIdx = inOffset + ${u};
if (${c===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
);
${d}
} else if (${c===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
);
${d}
} else if (${c===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
);
${d}
}
setOutput(${l});
}
`}};function Tse(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,segmentIds:a}=t,{numSegments:o}=s,i=r.shape.length,l=[],u=0,c=D.getAxesPermutation([u],i),d=r;c!=null&&(d=Sn({inputs:{x:r},backend:n,attrs:{perm:c}}),l.push(d),u=D.getInnerMostAxes(1,i)[0]);let h=D.segment_util.computeOutShape(d.shape,u,o),p=w.sizeFromShape([d.shape[u]]),f=ye({inputs:{x:d},backend:n,attrs:{shape:[-1,p]}});l.push(f);let m=Ph(r.dtype),g=(b,v,k,S,C)=>{let _=b.shape[0],O=b.shape[1],E=D.segment_util.segOpComputeOptimalWindowSize(O,C),R={windowSize:E,inSize:O,batchSize:_,numSegments:C},T=new Cse(R,v),P=n.compileAndRun(T,[b,k],S);if(l.push(P),P.shape[1]===C)return P;let V=P4({backend:n,attrs:{start:0,stop:C,step:1,dtype:"float32"}}),j=W4({inputs:{x:V},backend:n,attrs:{reps:[O/E]}});return l.push(V),l.push(j),g(P,v,j,S,C)},A=g(f,"unsortedSegmentSum",a,m,o),y=ye({inputs:{x:A},backend:n,attrs:{shape:h}}),x=y;if(c!=null){l.push(y);let b=D.getUndoAxesPermutation(c);x=Sn({inputs:{x},backend:n,attrs:{perm:b}})}return l.forEach(b=>n.disposeIntermediateTensorInfo(b)),x}var Nse={kernelName:Xu,backendName:"webgl",kernelFunc:Tse},Ese=[see,oee,UK,GK,XK,YK,QK,nZ,rZ,oZ,cZ,hZ,mZ,yZ,SZ,vZ,NZ,DZ,RZ,PZ,zZ,BZ,HZ,YZ,QZ,aY,iY,dY,fY,IK,xY,EY,_Y,kY,OY,MY,$Y,BY,UY,jY,XY,ZY,QY,aJ,iJ,tJ,cJ,pJ,mJ,xJ,kJ,TJ,RJ,_J,DJ,FJ,PJ,zJ,BJ,VJ,jJ,KJ,JJ,eQ,sQ,oQ,cQ,fQ,kK,gQ,AY,xQ,wQ,SQ,CK,EQ,$Q,OQ,VQ,LQ,jQ,KQ,QQ,lee,gee,fee,bee,wee,Iee,hee,Cee,Nee,Dee,Pee,Bee,Xee,_K,Zee,Qee,nte,ate,tY,lte,cte,hte,mte,xte,NK,vte,wte,nY,Hee,Ste,$te,Ete,$K,Mte,Bte,Hte,qte,Yte,Qte,nne,ane,ine,cne,pne,mne,yne,vne,Ine,KZ,jee,Tne,Ene,_ne,$ne,One,Mne,Lne,Wne,Une,jne,Xne,Zne,Qne,tse,sse,ase,Gee,BK,lse,dse,fse,yse,vse,WK,kse,Sse,Nse,ute];for(let e of Ese)To(e);var Pn;(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"})(Pn||(Pn={}));var td;(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"})(td||(td={}));var U4;function Rse(e){U4=e.wasm.cwrap(Io,null,["number","array","number","number","array","number","number","number","number","number","number","number","number"])}function _se(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a,bias:o,preluActivationWeights:i}=t;if(r.dtype!=="float32"||a.dtype!=="float32")throw new Error("_FusedMatMul for non non-float32 tensors not yet supported.");let{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:d}=s,h=n.dataIdMap.get(r.dataId).id,p=n.dataIdMap.get(a.dataId).id,f=0;if(o!=null){let C=n.dataIdMap.get(o.dataId);if(C.shape.length!==1)throw new Error(`_FusedMatMul only supports rank-1 bias but got rank ${C.shape.length}.`);f=C.id}let m=i==null?0:n.dataIdMap.get(i.dataId).id,g=td[c];if(g==null)throw new Error(`${c} activation not yet supported for FusedConv2D in the wasm backend.`);let A=l?r.shape[2]:r.shape[1],y=u?a.shape[1]:a.shape[2],x=r.shape[0],b=n.makeOutput([x,A,y],r.dtype),v=n.dataIdMap.get(b.dataId).id,k=new Uint8Array(new Int32Array(r.shape).buffer),S=new Uint8Array(new Int32Array(a.shape).buffer);return U4(h,k,r.shape.length,p,S,a.shape.length,l,u,g,f,m,d||0,v),b}var Dse={kernelName:Io,backendName:"wasm",setupFunc:Rse,kernelFunc:_se};function un(e){let t;function n(r){t=r.wasm.cwrap(e,null,["number","number"])}function s(r){let{backend:a,inputs:{x:o}}=r,i=a.dataIdMap.get(o.dataId).id,l=a.makeOutput(o.shape,o.dtype),u=a.dataIdMap.get(l.dataId).id;return w.sizeFromShape(l.shape)===0||t(i,u),l}return{kernelName:e,backendName:"wasm",setupFunc:n,kernelFunc:s}}var $se=un(ki);function Cn(e,t,n){let s;function r(o){s=o.wasm.cwrap(e,null,["number","array","number","number","array","number","number","number"])}function a(o){let{backend:i,inputs:l}=o,{a:u,b:c}=l,d=i.dataIdMap.get(u.dataId).id,h=i.dataIdMap.get(c.dataId).id,p=n!=null?n:u.dtype,f=D.assertAndGetBroadcastShape(u.shape,c.shape),m=i.makeOutput(f,p);if(w.sizeFromShape(f)===0)return m;let g=new Uint8Array(new Int32Array(u.shape).buffer),A=new Uint8Array(new Int32Array(c.shape).buffer),y=i.dataIdMap.get(m.dataId).id,x=()=>s(d,g,u.shape.length,h,A,c.shape.length,Pn[u.dtype],y);if(t&&u.dtype==="float32")return x(),m;let b=D.getBroadcastDims(u.shape,f),v=D.getBroadcastDims(c.shape,f),k=b.every((C,_)=>C===_),S=v.every((C,_)=>C===_);if(k&&S)return x(),m;throw new Error(`Broadcasting along outer dims is not yet supported for ${u.dtype} ${e}.`)}return{kernelName:e,backendName:"wasm",setupFunc:r,kernelFunc:a}}var Fse=!0,Ose=Cn(Vr,Fse),H4;function Pse(e){H4=e.wasm.cwrap(Ta,null,["array","number","number","number"])}function Mse(e){let{inputs:t,backend:n}=e,s=n.makeOutput(t[0].shape,t[0].dtype);if(w.sizeFromShape(s.shape)===0)return s;let r=t.map(i=>n.dataIdMap.get(i.dataId).id),a=new Uint8Array(new Int32Array(r).buffer),o=n.dataIdMap.get(s.dataId).id;return H4(a,r.length,Pn[s.dtype],o),s}var zse={kernelName:Ta,backendName:"wasm",setupFunc:Pse,kernelFunc:Mse};function $f(e){let{inputs:{x:t},backend:n}=e,s=n.makeOutput(t.shape,t.dtype),r=n.typedArrayFromHeap(t);return n.typedArrayFromHeap(s).set(r),s}var Lse={kernelName:ja,backendName:"wasm",kernelFunc:$f},G4;function Bse(e){G4=e.wasm.cwrap(ko,null,["number","array","number","number","number","array","number"])}function pu(e){let{inputs:t,backend:n,attrs:s}=e,[r,a]=Vse(t.x.shape,s.perm),o=!0;for(let f=0;f<a.length;f++)a[f]!==f&&(o=!1);let i=Wse(t.x.shape,s.perm),l={dataId:t.x.dataId,shape:r,dtype:t.x.dtype};if(o){let f=$f({inputs:t,backend:n});return f.shape=i,f}let u=n.makeOutput(i,l.dtype),c=n.dataIdMap.get(l.dataId).id,d=n.dataIdMap.get(u.dataId).id,h=new Uint8Array(new Int32Array(a).buffer),p=new Uint8Array(new Int32Array(l.shape).buffer);return G4(c,p,l.shape.length,Pn[l.dtype],d,h,a.length),u}function Wse(e,t){let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[t[s]];return n}function Vse(e,t){let n=[],s=[];for(let r=0;r<e.length;++r)e[r]!==1&&n.push(e[r]),e[t[r]]!==1&&s.push(t[r]);for(let r=0;r<s.length;++r){let a=-1;for(let o=0;o<s.length;++o)s[o]>=r&&(a===-1||s[a]>s[o])&&(a=o);s[a]=r}return[n,s]}var Use={kernelName:ko,backendName:"wasm",kernelFunc:pu,setupFunc:Bse};function fa(e,t,n){let s=e.shape,r=e.shape.length,a=w.parseAxisParam(t,s),o=a,i=D.getAxesPermutation(o,r),l=null,u=!1;if(i!=null){let c=new Array(r);for(let p=0;p<c.length;p++)c[p]=s[i[p]];o=D.getInnerMostAxes(o.length,r),l=pu({inputs:{x:e},attrs:{perm:i},backend:n});let d=n.dataIdMap.get(e.dataId).id;n.dataIdMap.get(l.dataId).id!==d&&(u=!0)}return{transposed:l,originalAxes:a,axes:o,inputWasTransposed:u}}var j4;function Hse(e){j4=e.wasm.cwrap(Ci,null,["number, number, number"])}function Gse(e){let{backend:t,inputs:n,attrs:s}=e,{axis:r,keepDims:a}=s,{x:o}=n,l=t.dataIdMap.get(o.dataId).id,u=o,{transposed:c,axes:d,originalAxes:h,inputWasTransposed:p}=fa(o,r,t);if(p){let x=t.dataIdMap.get(c.dataId).id;u=c,l=x}let f=u.shape.length;D.assertAxesAreInnerMostDims("all",d,f);let[m,g]=D.computeOutAndReduceShapes(u.shape,d),A=w.sizeFromShape(g),y=t.makeOutput(m,o.dtype);if(w.sizeFromShape(u.shape)!==0){let x=t.dataIdMap.get(y.dataId).id;j4(l,A,x)}if(p&&t.disposeData(c.dataId),a){let x=D.expandShapeToKeepDim(y.shape,h);y.shape=x}return y}var jse={kernelName:Ci,backendName:"wasm",setupFunc:Hse,kernelFunc:Gse},q4;function qse(e){q4=e.wasm.cwrap(Ti,null,["number, number, number"])}function Xse(e){let{backend:t,inputs:n,attrs:s}=e,{axis:r,keepDims:a}=s,{x:o}=n,l=t.dataIdMap.get(o.dataId).id,u=o,{transposed:c,axes:d,originalAxes:h,inputWasTransposed:p}=fa(o,r,t);if(p){let x=t.dataIdMap.get(c.dataId).id;u=c,l=x}let f=u.shape.length;D.assertAxesAreInnerMostDims("any",d,f);let[m,g]=D.computeOutAndReduceShapes(u.shape,d),A=w.sizeFromShape(g),y=t.makeOutput(m,o.dtype);if(w.sizeFromShape(u.shape)!==0){let x=t.dataIdMap.get(y.dataId).id;q4(l,A,x)}if(p&&t.disposeData(c.dataId),a){let x=D.expandShapeToKeepDim(y.shape,h);y.shape=x}return y}var Kse={kernelName:Ti,backendName:"wasm",setupFunc:qse,kernelFunc:Xse},X4;function Zse(e){X4=e.wasm.cwrap(Na,null,["number","number","number","number","number"])}function Yse(e){let{backend:t,inputs:n,attrs:s}=e,{axis:r}=s,{x:a}=n,o=t.dataIdMap.get(a.dataId).id,i=o,l=a,{transposed:u,axes:c,inputWasTransposed:d}=fa(a,r,t);if(d){let A=t.dataIdMap.get(u.dataId).id;A!==o&&(l=u,i=A)}let h=l.shape.slice(0,-1),p=t.makeOutput(h,"int32"),f=t.dataIdMap.get(p.dataId).id,m=w.sizeFromShape(p.shape),g=l.shape[c[0]];return X4(i,Pn[l.dtype],m,g,f),d&&t.disposeData(u.dataId),p}var Jse={kernelName:Na,backendName:"wasm",kernelFunc:Yse,setupFunc:Zse},K4;function Qse(e){K4=e.wasm.cwrap(Ea,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function ere(e){let{inputs:t,attrs:n,backend:s}=e,r=t.x,a=s.dataIdMap.get(r.dataId).id,{filterSize:o,strides:i,pad:l,dimRoundingMode:u}=n,c=D.computePool2DInfo(r.shape,o,i,1,l,u),d=c.filterHeight,h=c.filterWidth,p=c.padInfo.top,f=c.padInfo.right,m=c.padInfo.bottom,g=c.padInfo.left,A=c.strideHeight,y=c.strideWidth,x=c.inChannels;if(c.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${c.dataFormat}'. Please use 'channelsLast'.`);if(c.dilationWidth!==1||c.dilationHeight!==1)throw new Error(`was backend only supports average pooling with dilation = [1, 1], got [${c.dilationHeight}, ${c.dilationWidth}].`);let b=s.makeOutput(c.outShape,"float32"),v=s.dataIdMap.get(b.dataId).id;return K4(a,r.shape[0],r.shape[1],r.shape[2],d,h,p,f,m,g,A,y,x,v),b}var tre={kernelName:Ea,backendName:"wasm",setupFunc:Qse,kernelFunc:ere};function Mn(e){let{inputs:t,attrs:n}=e,{x:s}=t,{shape:r}=n,a=w.sizeFromShape(s.shape),o=w.inferFromImplicitShape(r,a);return w.assert(a===w.sizeFromShape(o),()=>`new shape: ${o}, old shape: ${s.shape}. New shape and old shape must have the same number of elements.`),e.backend.incRef(s.dataId),{dataId:s.dataId,shape:o,dtype:s.dtype}}var nre={kernelName:ll,backendName:"wasm",kernelFunc:Mn},Z4;function sre(e){Z4=e.wasm.cwrap(Ra,null,["number","array","number","number","array","number","number","number","number"])}function rre(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a}=t,{transposeA:o,transposeB:i}=s;if(r.dtype!=="float32"||a.dtype!=="float32")throw new Error("BatchMatMul for non non-float32 tensors not yet supported.");let l=r.shape.length,u=a.shape.length,c=o?r.shape[l-2]:r.shape[l-1],d=i?a.shape[u-1]:a.shape[u-2],h=o?r.shape[l-1]:r.shape[l-2],p=i?a.shape[u-2]:a.shape[u-1],f=r.shape.slice(0,-2),m=a.shape.slice(0,-2),g=w.sizeFromShape(f),A=w.sizeFromShape(m),y=g===A||g===1||A===1;w.assert(l>=2&&u>=2&&y,()=>`Error in matMul: the input batch dimensions must either be the same or at least one input batch dimension must be 1. Got input batch dimensions of (${f}) and (${m}).`);let b=(g>A?r.shape.slice(0,-2):a.shape.slice(0,-2)).concat([h,p]);w.assert(c===d,()=>`Error in matMul: inner shapes (${c}) and (${d}) of Tensors with shapes ${r.shape} and ${a.shape} and transposeA=${o} and transposeB=${i} must match.`);let v=o?[g,c,h]:[g,h,c],k=i?[A,p,d]:[A,d,p],S=Mn({inputs:{x:r},backend:n,attrs:{shape:v}}),C=Mn({inputs:{x:a},backend:n,attrs:{shape:k}}),_=n.dataIdMap.get(S.dataId).id,O=n.dataIdMap.get(C.dataId).id,E=o?S.shape[2]:S.shape[1],R=i?C.shape[1]:C.shape[2],T=Math.max(g,A),P=n.makeOutput([T,E,R],S.dtype),V=n.dataIdMap.get(P.dataId).id,j=new Uint8Array(new Int32Array(S.shape).buffer),q=new Uint8Array(new Int32Array(C.shape).buffer);return Z4(_,j,S.shape.length,O,q,C.shape.length,o,i,V),n.disposeData(S.dataId),n.disposeData(C.dataId),P.shape=b,P}var are={kernelName:Ra,backendName:"wasm",setupFunc:sre,kernelFunc:rre};function nd(e){let{inputs:{x:t},attrs:{begin:n,size:s},backend:r}=e,[a,o]=xn.parseSliceParams(t,n,s),i=xn.isSliceContinous(t.shape,a,o),l=r.readSync(t.dataId),u=r.makeOutput(o,t.dtype),c=w.computeStrides(t.shape),d=r.dataIdMap.get(u.dataId);if(i){let f=xn.computeFlatOffset(a,c);return t.dtype==="string"?d.stringBytes=l.slice(f,f+w.sizeFromShape(o)):r.typedArrayFromHeap(u).set(l.subarray(f,f+w.sizeFromShape(o))),u}if(t.dtype==="string"){let f=uf(l,a,o,t.shape,t.dtype);return d.stringBytes=f,u}let h=r.typedArrayFromHeap(u),p=t.shape.length;if(p===2)ore(l,c[0],h,a,o);else if(p===3)ire(l,c[0],c[1],h,a,o);else if(p===4)lre(l,c[0],c[1],c[2],h,a,o);else{let f=uf(l,a,o,t.shape,t.dtype);h.set(f)}return u}function ore(e,t,n,s,r){let a=0,o=s[0],i=s[1],l=o+r[0];for(let u=o;u<l;u++){let c=u*t+i;n.set(e.subarray(c,c+r[1]),a),a+=r[1]}}function ire(e,t,n,s,r,a){let o=0,i=r[0],l=r[1],u=r[2],c=i+a[0],d=l+a[1];for(let h=i;h<c;h++)for(let p=l;p<d;p++){let f=h*t+p*n+u;s.set(e.subarray(f,f+a[2]),o),o+=a[2]}}function lre(e,t,n,s,r,a,o){let i=0,l=a[0],u=a[1],c=a[2],d=l+o[0],h=u+o[1],p=c+o[2],f=a[3];for(let m=l;m<d;m++)for(let g=u;g<h;g++)for(let A=c;A<p;A++){let y=m*t+g*n+A*s+f;r.set(e.subarray(y,y+o[3]),i),i+=o[3]}}var ure={kernelName:hl,backendName:"wasm",kernelFunc:nd};function cre(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockShape:a,crops:o}=s,i=a.reduce((A,y)=>A*y),l=D.getReshaped(r.shape,a,i),u=D.getPermuted(l.length,a.length),c=D.getReshapedPermuted(r.shape,a,i),d=D.getSliceBeginCoords(o,a.length),h=D.getSliceSize(c,o,a.length),p=Mn({inputs:{x:r},backend:n,attrs:{shape:l}}),f=pu({inputs:{x:p},backend:n,attrs:{perm:u}}),m=Mn({inputs:{x:f},backend:n,attrs:{shape:c}}),g=nd({inputs:{x:m},backend:n,attrs:{begin:d,size:h}});return n.disposeData(p.dataId),n.disposeData(f.dataId),n.disposeData(p.dataId),g}var dre={kernelName:$i,backendName:"wasm",kernelFunc:cre};function Ff(e){let{inputs:{x:t},attrs:{dtype:n},backend:s}=e,r=s.makeOutput(t.shape,n),a=s.typedArrayFromHeap(t);return s.typedArrayFromHeap(r).set(a),r}var hre={kernelName:_a,backendName:"wasm",kernelFunc:Ff},pre=un(Da),Y4;function fre(e){Y4=e.wasm.cwrap(Ur,null,["number","number","number","number"])}function mre(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{clipValueMin:a,clipValueMax:o}=s,i=n.dataIdMap.get(r.dataId).id,l=n.makeOutput(r.shape,r.dtype),u=n.dataIdMap.get(l.dataId).id;return Y4(i,a,o,u),l}var gre={kernelName:Ur,backendName:"wasm",setupFunc:fre,kernelFunc:mre};function J4(e){let{inputs:t,backend:n}=e,s=w.parseAxisParam(e.attrs.axis,t[0].shape)[0],r=D.computeOutShape(t.map(p=>p.shape),s),a=t.filter(p=>w.sizeFromShape(p.shape)>0);if(a.length===1)return $f({inputs:{x:a[0]},backend:n});let o=n.makeOutput(r,t[0].dtype);if(w.sizeFromShape(r)===0)return o;let i=a.map(p=>p.shape);if(D.assertParamsConsistent(i,s),a[0].dtype==="string"){let p=a.map(x=>{let b=w.sizeFromShape(x.shape.slice(s));return Mn({inputs:{x},backend:n,attrs:{shape:[-1,b]}})}),f=p.map(x=>({vals:n.readSync(x.dataId),shape:x.shape}));r=D.computeOutShape(p.map(x=>x.shape),1);let m=p[0].shape[0]===1,g=p2(f,r,t[0].dtype,m),A=D.computeOutShape(a.map(x=>x.shape),s);o.shape=A;let y=n.dataIdMap.get(o.dataId);return y.stringBytes=D.fromStringArrayToUint8(g),p.forEach(x=>n.disposeData(x.dataId)),o}let l=w.sizeFromShape(a[0].shape.slice(0,s)),u=0,c=a.map(p=>{let f=w.sizeFromShape(p.shape.slice(s));return u+=f,f}),d=a.map(p=>n.typedArrayFromHeap(p)),h=n.typedArrayFromHeap(o);for(let p=0;p<l;p++){let f=p*u;for(let m=0;m<d.length;m++){let g=c[m],A=p*g,y=d[m].subarray(A,A+g);h.set(y,f),f+=g}}return o}var Are={kernelName:Fi,backendName:"wasm",kernelFunc:J4},Q4;function yre(e){Q4=e.wasm.cwrap($a,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function xre(e){let{inputs:t,attrs:n,backend:s}=e,{x:r,filter:a}=t,o=s.dataIdMap.get(r.dataId).id,i=s.dataIdMap.get(a.dataId).id,{strides:l,dilations:u,pad:c,dimRoundingMode:d,dataFormat:h}=n,p=D.convertConv2DDataFormat(h),f=D.computeConv2DInfo(r.shape,a.shape,l,u,c,d,!1,p),m=f.filterHeight,g=f.filterWidth,A=f.padInfo.top,y=f.padInfo.right,x=f.padInfo.bottom,b=f.padInfo.left,v=f.dilationHeight,k=f.dilationWidth,S=f.strideHeight,C=f.strideWidth,_=f.inChannels,O=f.outChannels,E=f.padInfo.type==="SAME"?1:0;if(f.dataFormat!=="channelsLast")throw new Error(`wasm backend Conv2D does not support dataFormat:'${f.dataFormat}'. Please use 'channelsLast'.`);let R=s.makeOutput(f.outShape,"float32"),T=s.dataIdMap.get(R.dataId).id;return Q4(o,r.shape[0],r.shape[1],r.shape[2],i,m,g,A,y,x,b,E,v,k,S,C,_,O,T),R}var bre={kernelName:$a,backendName:"wasm",setupFunc:yre,kernelFunc:xre},ek;function vre(e){ek=e.wasm.cwrap(Fa,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 wre(e){let{backend:t,inputs:n,attrs:s}=e,{dy:r,filter:a}=n,{strides:o,pad:i,dataFormat:l,dimRoundingMode:u,inputShape:c}=s,d=1,h=D.convertConv2DDataFormat(l),p=D.computeConv2DInfo(c,a.shape,o,d,i,u,!1,h),{batchSize:f,filterHeight:m,filterWidth:g,inChannels:A,inHeight:y,inWidth:x,outChannels:b,outHeight:v,outWidth:k,strideHeight:S,strideWidth:C}=p,_=m-1-p.padInfo.top,O=g-1-p.padInfo.left,E=p.dataFormat==="channelsLast",R=w.computeStrides(p.inShape),T=w.computeStrides(r.shape),[P,V,j]=w.computeStrides(a.shape),q=R[0],X=E?R[1]:R[2],ee=E?R[2]:1,te=E?1:R[1],ne=T[0],se=E?T[1]:T[2],J=E?T[2]:1,ie=E?1:T[1],le=t.makeOutput(p.inShape,"float32"),he=t.dataIdMap.get(le.dataId).id,Ae=t.dataIdMap.get(r.dataId).id,Ce=t.dataIdMap.get(a.dataId).id;return ek(Ae,Ce,f,m,g,y,x,A,v,k,b,S,C,_,O,P,V,j,q,X,ee,te,ne,se,J,ie,he),le}var kre={kernelName:Fa,backendName:"wasm",setupFunc:vre,kernelFunc:wre},Ire=un(Oa),Sre=un(Pa),G2;(function(e){e[e.bilinear=0]="bilinear",e[e.nearest=1]="nearest"})(G2||(G2={}));var tk;function Cre(e){tk=e.wasm.cwrap(Oi,null,["number","number","number","number","array","number","number","number","number","number"])}function Tre(e){let{backend:t,inputs:n,attrs:s}=e,{method:r,extrapolationValue:a,cropSize:o}=s,{image:i,boxes:l,boxInd:u}=n,c=l.shape[0],[d,h]=o,p=[c,d,h,i.shape[3]],f=t.dataIdMap.get(i.dataId),m;i.dtype!=="float32"&&(m=Ff({backend:t,inputs:{x:i},attrs:{dtype:"float32"}}),f=t.dataIdMap.get(m.dataId));let g=f.id,A=t.dataIdMap.get(l.dataId).id,y=t.dataIdMap.get(u.dataId).id,x=t.makeOutput(p,"float32"),b=t.dataIdMap.get(x.dataId).id,v=new Uint8Array(new Int32Array(i.shape).buffer);return tk(g,A,y,c,v,d,h,G2[r],a,b),m!=null&&t.disposeData(m.dataId),x}var Nre={kernelName:Oi,backendName:"wasm",setupFunc:Cre,kernelFunc:Tre},nk;function Ere(e){nk=e.wasm.cwrap(Ma,null,["number","number","number","number","number","number"])}function Rre(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,exclusive:o,reverse:i}=s,l=r.shape.length;w.assert(r.dtype==="float32"||r.dtype==="int32",()=>`cumsum does not support ${r.dtype} tensors in the WASM backend`);let u=D.getAxesPermutation([a],l),c=r;u!==null&&(c=pu({inputs:{x:r},attrs:{perm:u},backend:n}));let d=D.getInnerMostAxes(1,l)[0];D.assertAxesAreInnerMostDims("cumsum",[d],l);let h=n.makeOutput(c.shape,c.dtype),p=c.shape[d],f=n.dataIdMap.get(c.dataId).id,m=n.dataIdMap.get(h.dataId).id;nk(f,o?1:0,i?1:0,p,m,Pn[r.dtype]);let g=h;if(u!==null){let A=D.getUndoAxesPermutation(u);g=pu({inputs:{x:h},attrs:{perm:A},backend:n}),n.disposeData(c.dataId),n.disposeData(h.dataId)}return g}var _re={kernelName:Ma,backendName:"wasm",setupFunc:Ere,kernelFunc:Rre},sk;function Dre(e){sk=e.wasm.cwrap(Pi,null,["number","number","number","array","number","array","array","number","number"])}function $re(e){let{backend:t,inputs:n,attrs:s}=e,{x:r}=n,{blockSize:a,dataFormat:o}=s;w.assert(a>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${a}`);let i=r.shape[0],l=o==="NHWC"?r.shape[1]:r.shape[2],u=o==="NHWC"?r.shape[2]:r.shape[3],c=o==="NHWC"?r.shape[3]:r.shape[1],d=l*a,h=u*a,p=c/(a*a),f=o==="NHWC"?[i,d,h,p]:[i,p,d,h],m=t.makeOutput(f,"float32"),A=t.dataIdMap.get(r.dataId).id,y=new Uint8Array(new Int32Array(w.computeStrides(r.shape)).buffer),x=new Uint8Array(new Int32Array(f).buffer),b=new Uint8Array(new Int32Array(w.computeStrides(f)).buffer),v=t.dataIdMap.get(m.dataId).id;return sk(A,a,o==="NHWC"?1:0,y,r.shape.length-1,x,b,f.length,v),m}var Fre={kernelName:Pi,backendName:"wasm",setupFunc:Dre,kernelFunc:$re},rk;function Ore(e){rk=e.wasm.cwrap(za,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Pre(e){let{inputs:t,attrs:n,backend:s}=e,{x:r,filter:a}=t,o=s.dataIdMap.get(r.dataId).id,i=s.dataIdMap.get(a.dataId).id,{strides:l,dilations:u,pad:c,dimRoundingMode:d}=n,h=u==null?[1,1]:u,p=D.computeConv2DInfo(r.shape,a.shape,l,h,c,d,!0),f=p.filterHeight,m=p.filterWidth,g=p.padInfo.top,A=p.padInfo.right,y=p.padInfo.bottom,x=p.padInfo.left,b=p.dilationHeight,v=p.dilationWidth,k=p.strideHeight,S=p.strideWidth,C=p.inChannels,_=p.outChannels,O=p.padInfo.type==="SAME"?1:0;if(p.dataFormat!=="channelsLast")throw new Error(`wasm backend DepthwiseConv2dNative does not support dataFormat:'${p.dataFormat}'. Please use 'channelsLast'.`);let E=s.makeOutput(p.outShape,"float32"),R=s.dataIdMap.get(E.dataId).id;return rk(o,r.shape[0],r.shape[1],r.shape[2],i,f,m,g,A,y,x,O,b,v,k,S,C,_,R),E}var Mre={kernelName:za,backendName:"wasm",setupFunc:Ore,kernelFunc:Pre},zre=un(Ba),Lre=!1,Bre=Cn(zi,Lre,"bool"),Wre=un(Wa);function j2(e){let{inputs:t,attrs:n,backend:s}=e,{input:r}=t,{dim:a}=n,o=r.shape.length,i=r.shape.slice(),l=a;return a<0&&(w.assert(-(o+1)<=a,()=>`Axis must be in the interval [${-(o+1)}, ${o}]`),l=o+a+1),i.splice(l,0,1),Mn({inputs:{x:r},backend:s,attrs:{shape:i}})}var Vre={kernelName:Li,backendName:"wasm",kernelFunc:j2};function ak(e){let{attrs:{shape:t,value:n,dtype:s},backend:r}=e,a=r.makeOutput(t,s);return r.typedArrayFromHeap(a).fill(n),a}var Ure={kernelName:Bu,backendName:"wasm",kernelFunc:ak},ok;function Hre(e){ok=e.wasm.cwrap(Wi,null,["number","number","number","number","number","number"])}function Gre(e){let{inputs:t,backend:n}=e,{image:s}=t,r=n.makeOutput(s.shape,s.dtype),a=n.dataIdMap.get(s.dataId).id,o=n.dataIdMap.get(r.dataId).id,[i,l,u,c]=s.shape;return ok(a,i,l,u,c,o),r}var jre={kernelName:Wi,backendName:"wasm",kernelFunc:Gre,setupFunc:Hre},qre=un(Va),Xre=!1,Kre=Cn(Ua,Xre),ik;function Zre(e){ik=e.wasm.cwrap(Ha,null,["number","number","number","number","number","number","number"])}function Yre(e){let{backend:t,inputs:n,attrs:s}=e,{varianceEpsilon:r}=s,{x:a,mean:o,variance:i,offset:l,scale:u}=n,c=t.dataIdMap.get(a.dataId).id,d=t.dataIdMap.get(o.dataId).id,h=t.dataIdMap.get(i.dataId).id,p=l!=null?t.dataIdMap.get(l.dataId).id:0,f=u!=null?t.dataIdMap.get(u.dataId).id:0,m=t.makeOutput(a.shape,a.dtype);if(w.sizeFromShape(a.shape)===0)return m;let g=t.dataIdMap.get(m.dataId).id;return ik(c,d,h,p,f,r,g),m}var Jre={kernelName:Ha,backendName:"wasm",setupFunc:Zre,kernelFunc:Yre},lk;function Qre(e){lk=e.wasm.cwrap(So,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function eae(e){let{inputs:t,attrs:n,backend:s}=e,{x:r,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dilations:c,dataFormat:d,dimRoundingMode:h,activation:p,leakyreluAlpha:f}=n,m=D.computeConv2DInfo(r.shape,a.shape,l,c,u,h),g=td[p];if(g==null)throw new Error(`${p} activation not yet supported for FusedConv2D in the wasm backend.`);let A=s.dataIdMap.get(r.dataId).id,y=s.dataIdMap.get(a.dataId).id,x=m.outChannels,b=0;if(o!=null){let J=s.dataIdMap.get(o.dataId);if(J.shape.length!==1)throw new Error(`FusedConv2D only supports rank-1 bias but got rank ${J.shape.length}.`);if(J.shape[0]!==x)throw new Error(`FusedConv2D bias shape (${J.shape}) does not match the number of output channels (${x})`);b=J.id}let v=m.filterHeight,k=m.filterWidth,S=m.padInfo.top,C=m.padInfo.right,_=m.padInfo.bottom,O=m.padInfo.left,E=m.dilationHeight,R=m.dilationWidth,T=m.strideHeight,P=m.strideWidth,V=m.inChannels,j=m.padInfo.type==="SAME"?1:0,q=m.batchSize,X=m.inHeight,ee=m.inWidth;if(d!=="NHWC")throw new Error(`wasm backend FusedConv2D does not support dataFormat:'${d}'. Please use 'NHWC'.`);let te=s.makeOutput(m.outShape,"float32"),ne=s.dataIdMap.get(te.dataId).id,se=i==null?0:s.dataIdMap.get(i.dataId).id;return lk(A,q,X,ee,y,v,k,b,S,C,_,O,j,E,R,T,P,V,x,g,se,f||0,ne),te}var tae={kernelName:So,backendName:"wasm",setupFunc:Qre,kernelFunc:eae},uk;function nae(e){uk=e.wasm.cwrap(Co,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 sae(e){let{inputs:t,attrs:n,backend:s}=e,{x:r,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dilations:c,dataFormat:d,dimRoundingMode:h,activation:p,leakyreluAlpha:f}=n,m=D.computeConv2DInfo(r.shape,a.shape,l,c,u,h,!0),g=td[p];if(g==null)throw new Error(`${p} activation not yet supported for FusedDepthwiseConv2D in the wasm backend.`);let A=s.dataIdMap.get(r.dataId).id,y=s.dataIdMap.get(a.dataId).id,x=m.outChannels,b=0;if(o!=null){let J=s.dataIdMap.get(o.dataId);if(J.shape.length!==1)throw new Error(`FusedDepthwiseConv2D only supports rank-1 bias but got rank ${J.shape.length}.`);if(J.shape[0]!==x)throw new Error(`FusedDepthwiseConv2D bias shape (${J.shape}) does not match the number of output channels (${x})`);b=J.id}let v=m.filterHeight,k=m.filterWidth,S=m.padInfo.top,C=m.padInfo.right,_=m.padInfo.bottom,O=m.padInfo.left,E=m.dilationHeight,R=m.dilationWidth,T=m.strideHeight,P=m.strideWidth,V=m.inChannels,j=m.padInfo.type==="SAME"?1:0,q=m.batchSize,X=m.inHeight,ee=m.inWidth;if(d!=="NHWC")throw new Error(`wasm backend FusedDepthwiseConv2D does not support dataFormat:'${d}'. Please use 'NHWC'.`);let te=s.makeOutput(m.outShape,"float32"),ne=s.dataIdMap.get(te.dataId).id,se=i==null?0:s.dataIdMap.get(i.dataId).id;return uk(A,q,X,ee,y,v,k,b,S,C,_,O,j,E,R,T,P,V,x,g,se,f||0,ne),te}var rae={kernelName:Co,backendName:"wasm",setupFunc:nae,kernelFunc:sae},ck;function aae(e){ck=e.wasm.cwrap(Ui,null,["number","number","number","number","number","number","array","number"])}function oae(e){let{backend:t,inputs:n}=e,{params:s,indices:r}=n,[a,o,i,l]=cg.prepareAndValidate(s,r),u=t.makeOutput(a,s.dtype);if(o===0)return u;let c=r.shape,d=c[c.length-1],p=t.dataIdMap.get(s.dataId).id,m=t.dataIdMap.get(r.dataId).id,g=new Uint8Array(new Int32Array(l).buffer),A=t.dataIdMap.get(u.dataId).id;return ck(p,Pn[s.dtype],m,o,d,i,g,A),u}var iae={kernelName:Ui,backendName:"wasm",setupFunc:aae,kernelFunc:oae},dk;function lae(e){dk=e.wasm.cwrap("Gather",null,["number","number","array","number","number","number","array","number"])}function uae(e){let{backend:t,inputs:n,attrs:s}=e,{x:r,indices:a}=n,{axis:o,batchDims:i}=s,l=w.parseAxisParam(o,r.shape)[0],u=D.segment_util.collectGatherOpShapeInfo(r,a,l,i),c=Mn({inputs:{x:r},attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]},backend:t}),d=w.sizeFromShape(a.shape),h=Mn({inputs:{x:a},attrs:{shape:[u.batchSize,d/u.batchSize]},backend:t}),p=[u.batchSize,u.outerSize,d/u.batchSize,u.sliceSize],f=t.makeOutput(p,r.dtype);if(w.sizeFromShape(r.shape)===0)return f;let m=c.shape.length-1,A=t.dataIdMap.get(c.dataId).id,x=t.dataIdMap.get(h.dataId).id,b=t.dataIdMap.get(f.dataId).id,v=new Uint8Array(new Int32Array(w.computeStrides(c.shape)).buffer),k=new Uint8Array(new Int32Array(w.computeStrides(p)).buffer);return dk(A,Pn[r.dtype],v,m,x,u.batchSize,k,b),t.disposeData(c.dataId),t.disposeData(h.dataId),f.shape=u.outputShape,f}var cae={kernelName:Vi,backendName:"wasm",setupFunc:lae,kernelFunc:uae},dae=!1,hae=Cn(Hi,dae,"bool"),pae=!1,fae=Cn(Ga,pae,"bool"),hk;function mae(e){hk=e.wasm.cwrap(qa,null,["number","number","number"])}function gae(e){let{inputs:{x:t},attrs:{alpha:n},backend:s}=e,r=s.dataIdMap.get(t.dataId).id,a=s.makeOutput(t.shape,t.dtype);if(w.sizeFromShape(t.shape)!==0){let o=s.dataIdMap.get(a.dataId).id;hk(r,n,o)}return a}var Aae={kernelName:qa,backendName:"wasm",setupFunc:mae,kernelFunc:gae},yae=!1,xae=Cn(Xi,yae,"bool"),bae=!1,vae=Cn(Ki,bae,"bool"),wae=un(Xa),kae=!1,Iae=Cn(Yi,kae,"bool"),pk;function Sae(e){pk=e.wasm.cwrap(Ka,null,["number, number, number"])}function Cae(e){let{backend:t,inputs:n,attrs:s}=e,{reductionIndices:r,keepDims:a}=s,{x:o}=n,l=t.dataIdMap.get(o.dataId).id,u=o,{transposed:c,axes:d,originalAxes:h,inputWasTransposed:p}=fa(o,r,t);if(p){let x=t.dataIdMap.get(c.dataId).id;u=c,l=x}let f=u.shape.length;D.assertAxesAreInnerMostDims("max",d,f);let[m,g]=D.computeOutAndReduceShapes(u.shape,d),A=w.sizeFromShape(g),y=t.makeOutput(m,o.dtype);if(w.sizeFromShape(u.shape)!==0){let x=t.dataIdMap.get(y.dataId).id;pk(l,A,x)}if(p&&t.disposeData(c.dataId),a){let x=D.expandShapeToKeepDim(y.shape,h);y.shape=x}return y}var Tae={kernelName:Ka,backendName:"wasm",setupFunc:Sae,kernelFunc:Cae},Nae=!1,Eae=Cn(Za,Nae),fk;function Rae(e){fk=e.wasm.cwrap(Ya,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function _ae(e){let{inputs:t,attrs:n,backend:s}=e,r=t.x,a=s.dataIdMap.get(r.dataId).id,{filterSize:o,strides:i,pad:l,dimRoundingMode:u}=n,c=D.computePool2DInfo(r.shape,o,i,1,l,u),d=c.filterHeight,h=c.filterWidth,p=c.padInfo.top,f=c.padInfo.right,m=c.padInfo.bottom,g=c.padInfo.left,A=c.dilationHeight,y=c.dilationWidth,x=c.strideHeight,b=c.strideWidth,v=c.inChannels,k=c.outChannels;if(c.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${c.dataFormat}'. Please use 'channelsLast'.`);let S=s.makeOutput(c.outShape,"float32"),C=s.dataIdMap.get(S.dataId).id;return fk(a,r.shape[0],r.shape[1],r.shape[2],d,h,p,f,m,g,A,y,x,b,v,k,C),S}var Dae={kernelName:Ya,backendName:"wasm",setupFunc:Rae,kernelFunc:_ae},mk;function $ae(e){mk=e.wasm.cwrap(Ja,null,["number, number, number"])}function Fae(e){let{backend:t,inputs:n,attrs:s}=e,{axis:r,keepDims:a}=s,{x:o}=n,i=t.dataIdMap.get(o.dataId).id,l=i,u=o,{transposed:c,axes:d,originalAxes:h,inputWasTransposed:p}=fa(o,r,t),f=d;if(p){let b=t.dataIdMap.get(c.dataId).id;b!==i&&(u=c,l=b,f=D.getInnerMostAxes(f.length,u.shape.length))}D.assertAxesAreInnerMostDims("mean",f,u.shape.length);let[m,g]=D.computeOutAndReduceShapes(u.shape,f),A=w.sizeFromShape(g),y=u;u.dtype!=="float32"&&(y=Ff({backend:t,inputs:{x:u},attrs:{dtype:"float32"}}),l=t.dataIdMap.get(y.dataId).id);let x=t.makeOutput(m,"float32");if(w.sizeFromShape(u.shape)!==0){let b=t.dataIdMap.get(x.dataId).id;mk(l,A,b)}if(p&&t.disposeData(c.dataId),a){let b=D.expandShapeToKeepDim(x.shape,h);x.shape=b}return u.dtype!=="float32"&&t.disposeData(y.dataId),x}var Oae={kernelName:Ja,backendName:"wasm",setupFunc:$ae,kernelFunc:Fae},gk;function Pae(e){gk=e.wasm.cwrap(Qa,null,["number, number, number"])}function Mae(e){let{backend:t,inputs:n,attrs:s}=e,{axis:r,keepDims:a}=s,{x:o}=n,i=t.dataIdMap.get(o.dataId).id,l=i,u=o,{transposed:c,axes:d,originalAxes:h,inputWasTransposed:p}=fa(o,r,t);if(p){let x=t.dataIdMap.get(c.dataId).id;x!==i&&(u=c,l=x)}let f=u.shape.length;D.assertAxesAreInnerMostDims("min",d,f);let[m,g]=D.computeOutAndReduceShapes(u.shape,d),A=w.sizeFromShape(g),y=t.makeOutput(m,u.dtype);if(w.sizeFromShape(u.shape)!==0){let x=t.dataIdMap.get(y.dataId).id;gk(l,A,x)}if(p&&t.disposeData(c.dataId),a){let x=D.expandShapeToKeepDim(y.shape,h);y.shape=x}return y}var zae={kernelName:Qa,backendName:"wasm",setupFunc:Pae,kernelFunc:Mae},Lae=!1,Bae=Cn(eo,Lae),q2;(function(e){e[e.reflect=0]="reflect",e[e.symmetric=1]="symmetric"})(q2||(q2={}));var Ak;function Wae(e){Ak=e.wasm.cwrap(to,null,["number","array","number","number","array","array","number","number"])}function Vae(e){let{inputs:{x:t},backend:n,attrs:{paddings:s,mode:r}}=e,a=s.map((f,m)=>f[0]+t.shape[m]+f[1]),o=n.dataIdMap.get(t.dataId).id,i=n.makeOutput(a,t.dtype),l=n.dataIdMap.get(i.dataId).id,u=new Uint8Array(new Int32Array(t.shape).buffer),c=s.map(f=>f[0]),d=s.map(f=>f[1]),h=new Uint8Array(new Int32Array(c).buffer),p=new Uint8Array(new Int32Array(d).buffer);return Ak(o,u,t.shape.length,Pn[t.dtype],h,p,q2[r],l),i}var Uae={kernelName:to,backendName:"wasm",kernelFunc:Vae,setupFunc:Wae},Hae=!0,Gae=Cn(no,Hae),jae=un(Qi);function X2(e,t){let n=new Int32Array(e.wasm.HEAPU8.buffer,t,4),s=n[0],r=n[1],a=n[2],o=n[3];return e.wasm._free(t),{pSelectedIndices:s,selectedSize:r,pSelectedScores:a,pValidOutputs:o}}var yk;function qae(e){yk=e.wasm.cwrap(tl,"number",["number","number","number","number","number"])}function Xae(e){let{backend:t,inputs:n,attrs:s}=e,{iouThreshold:r,maxOutputSize:a,scoreThreshold:o}=s,{boxes:i,scores:l}=n,u=t.dataIdMap.get(i.dataId).id,c=t.dataIdMap.get(l.dataId).id,d=yk(u,c,a,r,o),{pSelectedIndices:h,selectedSize:p,pSelectedScores:f,pValidOutputs:m}=X2(t,d);return t.wasm._free(f),t.wasm._free(m),t.makeOutput([p],"int32",h)}var Kae={kernelName:tl,backendName:"wasm",setupFunc:qae,kernelFunc:Xae},xk;function Zae(e){xk=e.wasm.cwrap(nl,"number",["number","number","number","number","number","bool"])}function Yae(e){let{backend:t,inputs:n,attrs:s}=e,{iouThreshold:r,maxOutputSize:a,scoreThreshold:o,padToMaxOutputSize:i}=s,{boxes:l,scores:u}=n,c=t.dataIdMap.get(l.dataId).id,d=t.dataIdMap.get(u.dataId).id,h=xk(c,d,a,r,o,i),{pSelectedIndices:p,selectedSize:f,pSelectedScores:m,pValidOutputs:g}=X2(t,h);t.wasm._free(m);let A=t.makeOutput([f],"int32",p),y=t.makeOutput([],"int32",g);return[A,y]}var Jae={kernelName:nl,backendName:"wasm",setupFunc:Zae,kernelFunc:Yae},bk;function Qae(e){bk=e.wasm.cwrap(sl,"number",["number","number","number","number","number","number"])}function eoe(e){let{backend:t,inputs:n,attrs:s}=e,{iouThreshold:r,maxOutputSize:a,scoreThreshold:o,softNmsSigma:i}=s,{boxes:l,scores:u}=n,c=t.dataIdMap.get(l.dataId).id,d=t.dataIdMap.get(u.dataId).id,h=bk(c,d,a,r,o,i),{pSelectedIndices:p,selectedSize:f,pSelectedScores:m,pValidOutputs:g}=X2(t,h);t.wasm._free(g);let A=t.makeOutput([f],"int32",p),y=t.makeOutput([f],"float32",m);return[A,y]}var toe={kernelName:sl,backendName:"wasm",setupFunc:Qae,kernelFunc:eoe},noe=!1,soe=Cn(el,noe,"bool"),vk;function roe(e){vk=e.wasm.cwrap(so,null,["number","number","number","number","number"])}function aoe(e){let{inputs:t,backend:n,attrs:s}=e,{indices:r}=t,{depth:a,onValue:o,offValue:i}=s,l=n.makeOutput([...r.shape,a],"int32"),u=n.dataIdMap.get(l.dataId).id,d=n.dataIdMap.get(r.dataId).id;return vk(d,a,o,i,u),l}var ooe={kernelName:so,backendName:"wasm",setupFunc:roe,kernelFunc:aoe};function ioe(e){let{inputs:{x:t},backend:n}=e,s=n.makeOutput(t.shape,t.dtype);return n.typedArrayFromHeap(s).fill(1),s}var loe={kernelName:rl,backendName:"wasm",kernelFunc:ioe};function uoe(e){let{inputs:t,backend:n,attrs:s}=e,{axis:r}=s;if(t.length===1)return j2({inputs:{input:t[0]},backend:n,attrs:{dim:r}});let a=t[0].shape,o=t[0].dtype;t.forEach(c=>{w.assertShapesMatch(a,c.shape,"All tensors passed to stack must have matching shapes"),w.assert(o===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let i=[],l=t.map(c=>{let d=j2({inputs:{input:c},backend:n,attrs:{dim:r}});return i.push(d),d}),u=J4({inputs:l,backend:n,attrs:{axis:r}});return i.forEach(c=>n.disposeData(c.dataId)),u}var coe={kernelName:al,backendName:"wasm",kernelFunc:uoe},wk;function doe(e){wk=e.wasm.cwrap(ro,null,["number","array","number","number","array","array","number","number"])}function hoe(e){let{inputs:{x:t},backend:n,attrs:{paddings:s,constantValue:r}}=e,a=s.map((m,g)=>m[0]+t.shape[g]+m[1]);if(w.sizeFromShape(t.shape)===0)return ak({backend:n,attrs:{shape:a,value:r,dtype:t.dtype}});let o=n.dataIdMap.get(t.dataId).id,i=n.makeOutput(a,t.dtype),u=n.dataIdMap.get(i.dataId).id,c=new Uint8Array(new Int32Array(t.shape).buffer),d=s.map(m=>m[0]),h=s.map(m=>m[1]),p=new Uint8Array(new Int32Array(d).buffer),f=new Uint8Array(new Int32Array(h).buffer);return wk(o,c,t.shape.length,Pn[t.dtype],p,f,r,u),i}var kk={kernelName:ro,backendName:"wasm",kernelFunc:hoe,setupFunc:doe},poe=!1,foe=Cn(ao,poe),Ik;function moe(e){Ik=e.wasm.cwrap(oo,null,["number","number","number"])}function goe(e){let{inputs:t,backend:n}=e,{x:s,alpha:r}=t,a=n.dataIdMap.get(s.dataId).id,o=n.dataIdMap.get(r.dataId).id,i=n.makeOutput(s.shape,"float32"),l=n.dataIdMap.get(i.dataId).id;return Ik(a,o,l),i}var Aoe={kernelName:oo,backendName:"wasm",setupFunc:moe,kernelFunc:goe},Sk;function yoe(e){Sk=e.wasm.cwrap(ol,null,["number","number","number","number"])}function xoe(e){let{backend:t,inputs:n,attrs:s}=e,{axis:r,keepDims:a}=s,{x:o}=n,i=t.dataIdMap.get(o.dataId).id,l=i,u=o,{transposed:c,axes:d,originalAxes:h,inputWasTransposed:p}=fa(o,r,t),f=d;if(p){let x=t.dataIdMap.get(c.dataId).id;x!==i&&(u=c,l=x,f=D.getInnerMostAxes(f.length,u.shape.length))}D.assertAxesAreInnerMostDims("prod",f,u.shape.length);let[m,g]=D.computeOutAndReduceShapes(u.shape,f),A=w.sizeFromShape(g),y=t.makeOutput(m,u.dtype);if(w.sizeFromShape(u.shape)!==0){let x=t.dataIdMap.get(y.dataId).id;Sk(l,A,Pn[y.dtype],x)}if(p&&t.disposeData(c.dataId),a){let x=D.expandShapeToKeepDim(y.shape,h);y.shape=x}return y}var boe={kernelName:ol,backendName:"wasm",setupFunc:yoe,kernelFunc:xoe},voe=e=>{let{backend:t,attrs:n}=e,{start:s,stop:r,step:a,dtype:o}=n,i=g2(s,r,a,o),l=t.makeOutput([i.length],o);return t.typedArrayFromHeap(l).set(i),l},woe={kernelName:Gu,backendName:"wasm",kernelFunc:voe},koe=!0,Ioe=Cn(La,koe),Soe=un(io),Coe=un(uo),Ck;function Toe(e){Ck=e.wasm.cwrap(lo,null,["number","number","number","number","number","number","number","number","number","number"])}function Noe(e){let{backend:t,inputs:n,attrs:s}=e,{images:r}=n,{alignCorners:a,halfPixelCenters:o,size:i}=s,[l,u]=i,[c,d,h,p]=r.shape,f=[c,l,u,p],m=t.dataIdMap.get(r.dataId),g;m.dtype!=="float32"&&(g=Ff({backend:t,inputs:{x:r},attrs:{dtype:"float32"}}),m=t.dataIdMap.get(g.dataId));let A=m.id,y=t.makeOutput(f,"float32");if(w.sizeFromShape(r.shape)===0)return y;let x=t.dataIdMap.get(y.dataId).id;return Ck(A,c,d,h,p,l,u,a?1:0,o?1:0,x),g!=null&&t.disposeData(g.dataId),y}var Eoe={kernelName:lo,backendName:"wasm",setupFunc:Toe,kernelFunc:Noe},Tk;function Roe(e){Tk=e.wasm.cwrap(co,null,["number","array","number","array","number","number"])}function _oe(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{dims:a}=s,o=w.parseAxisParam(a,r.shape);if(r.shape.length===0)return $f({inputs:{x:r},backend:n});let i=n.makeOutput(r.shape,r.dtype),l=n.dataIdMap.get(r.dataId).id,u=n.dataIdMap.get(i.dataId).id,c=new Uint8Array(new Int32Array(o).buffer),d=new Uint8Array(new Int32Array(r.shape).buffer);Tk(l,c,o.length,d,r.shape.length,u);let h=Mn({inputs:{x:i},attrs:{shape:r.shape},backend:n});return n.disposeData(i.dataId),h}var Doe={kernelName:co,backendName:"wasm",kernelFunc:_oe,setupFunc:Roe},Nk;function $oe(e){Nk=e.wasm.cwrap(kl,null,["number","number","number","number","number","number","number","number","array","number","number"])}function Foe(e){let{inputs:t,backend:n,attrs:s}=e,{image:r}=t,{radians:a,fillValue:o,center:i}=s,l=n.makeOutput(r.shape,r.dtype),u=n.dataIdMap.get(r.dataId).id,c=n.dataIdMap.get(l.dataId).id,[d,h,p,f]=r.shape,[m,g]=D.getImageCenter(i,h,p),A=o===0,y=255,x=typeof o=="number"?[o,o,o,A?0:y]:[...o,y],b=new Uint8Array(new Int32Array(x).buffer);return Nk(u,d,h,p,f,a,m,g,b,x.length,c),l}var Ooe={kernelName:kl,backendName:"wasm",kernelFunc:Foe,setupFunc:$oe},Poe=un(ho),Moe=un(po),Ek;function zoe(e){Ek=e.wasm.cwrap(ul,null,["number","number","number","number","number","number","array","number","number"])}function Loe(e){let{backend:t,inputs:n,attrs:s}=e,{indices:r,updates:a}=n,{shape:o}=s,i=t.makeOutput(o,a.dtype);if(w.sizeFromShape(o)===0)return i;let{sliceRank:l,numUpdates:u,sliceSize:c,strides:d,outputSize:h}=dg.calculateShapes(a,r,o),f=t.dataIdMap.get(r.dataId).id,g=t.dataIdMap.get(a.dataId).id,A=new Uint8Array(new Int32Array(d).buffer),y=t.dataIdMap.get(i.dataId).id;return Ek(f,g,Pn[a.dtype],l,u,c,A,h,y),i}var Boe={kernelName:ul,backendName:"wasm",setupFunc:zoe,kernelFunc:Loe},Rk;function Woe(e){Rk=e.wasm.cwrap("SelectV2",null,["number","number","number","number","number"])}function Voe(e){let{inputs:t,backend:n}=e,{condition:s,t:r,e:a}=t,o=n.dataIdMap.get(s.dataId).id,i=n.dataIdMap.get(r.dataId).id,l=n.dataIdMap.get(a.dataId).id,u=n.makeOutput(r.shape,r.dtype),c=n.dataIdMap.get(u.dataId).id,d=s.shape.length,h=r.shape.length,p=d===0||d>1||h===1?1:w.sizeFromShape(r.shape.slice(1));return Rk(o,i,l,p,c),u}var Uoe={kernelName:cl,backendName:"wasm",kernelFunc:Voe,setupFunc:Woe},_k;function Hoe(e){_k=e.wasm.cwrap(mo,null,["number","number"])}function Goe(e){let{backend:t,inputs:{x:n}}=e,s=t.dataIdMap.get(n.dataId).id,r=t.makeOutput(n.shape,n.dtype),a=t.dataIdMap.get(r.dataId).id;return w.sizeFromShape(r.shape)===0||_k(s,a),r}var joe={kernelName:"Sigmoid",backendName:"wasm",setupFunc:Hoe,kernelFunc:Goe},qoe=un(fo),Dk;function Xoe(e){Dk=e.wasm.cwrap(yo,null,["number","number","number","number"])}function Koe(e){let{backend:t,inputs:{logits:n},attrs:{dim:s}}=e,r=t.dataIdMap.get(n.dataId).id,a=t.makeOutput(n.shape,n.dtype),o=t.dataIdMap.get(a.dataId).id,i=n.shape[s],l=w.sizeFromShape(n.shape)/i;return w.sizeFromShape(a.shape)===0||Dk(r,o,i,l),a}var Zoe={kernelName:yo,backendName:"wasm",setupFunc:Xoe,kernelFunc:Koe};function Yoe(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockShape:a,paddings:o}=s,i=w.sizeFromShape(a),l=[[0,0]];l.push(...o);for(let k=1+a.length;k<r.shape.length;++k)l.push([0,0]);let u=kk.kernelFunc({inputs:{x:r},backend:n,attrs:{paddings:l,constantValue:0}}),c=D.getReshaped(u.shape,a,i,!1),d=D.getPermuted(c.length,a.length,!1),h=D.getReshapedPermuted(u.shape,a,i,!1),m=Mn({inputs:{x:u},backend:n,attrs:{shape:c}}),y=pu({inputs:{x:m},backend:n,attrs:{perm:d}}),v=Mn({inputs:{x:y},backend:n,attrs:{shape:h}});return n.disposeData(u.dataId),n.disposeData(m.dataId),n.disposeData(y.dataId),v}var Joe={kernelName:gl,backendName:"wasm",kernelFunc:Yoe};function Qoe(e){let{inputs:t,attrs:n,backend:s}=e,{x:r}=t,{numOrSizeSplits:a,axis:o}=n,i=w.parseAxisParam(o,r.shape)[0],l=D.prepareSplitSize(r,a,i),u=new Array(r.shape.length).fill(0),c=r.shape.slice();return l.map(d=>{let h=[...c];h[i]=d;let p=nd({inputs:{x:r},attrs:{begin:u,size:h},backend:s});return u[i]+=d,p})}var eie={kernelName:Al,backendName:"wasm",kernelFunc:Qoe},tie=un(go),nie=un(qu),sie=!0,rie=Cn(xo,sie),$k;function aie(e){$k=e.wasm.cwrap(Gr,null,["number","number","number"])}function oie(e){let{backend:t,inputs:n,attrs:s}=e,{alpha:r}=s,{x:a}=n,o=t.dataIdMap.get(a.dataId).id,i=t.makeOutput(a.shape,a.dtype),l=t.dataIdMap.get(i.dataId).id;return $k(o,r,l),i}var iie={kernelName:Gr,backendName:"wasm",setupFunc:aie,kernelFunc:oie},Fk;function lie(e){Fk=e.wasm.cwrap(yl,null,["number","array","number","array","array","array","array","array","number","number"])}function uie(e){let{backend:t,inputs:n,attrs:s}=e,{x:r}=n,{begin:a,end:o,strides:i}=s;i==null&&(i=new Array(a.length));let{beginMask:l,endMask:u,ellipsisMask:c,newAxisMask:d,shrinkAxisMask:h}=s,p=D.slice_util.maskToAxes(c);if(p.length>1)throw new Error("Multiple ellipses in slice is not allowed.");if(c!==0&&d!==0)throw new Error("Using both ellipsisMask and newAxisMask is not yet supported.");if(c!==0&&h!==0)throw new Error("Using both ellipsisMask and shrinkAxisMask is not yet supported.");let f=r.shape.length-a.length,m=D.slice_util.maskToAxes(d),g=r.shape.slice();m.forEach(E=>{a[E]=0,o[E]=1,g.splice(E,0,1)});let A=Mn({inputs:{x:r},attrs:{shape:g},backend:t}),{begin:y,end:x,strides:b}=D.slice_util.getNormalizedAxes(A.shape,p,f,a,o,i,l,u,c);a=y,o=x,i=b;let v=D.slice_util.maskToAxes(h);v.forEach(E=>{o[E]=a[E]+1,i[E]=1});let k=D.slice_util.computeOutShape(a,o,i),S=k.filter((E,R)=>v.indexOf(R)===-1);if(i.every(E=>E===1)){let E=nd({inputs:{x:A},attrs:{begin:a,size:k},backend:t});t.disposeData(A.dataId);let R=Mn({inputs:{x:E},attrs:{shape:S},backend:t});return t.disposeData(E.dataId),R}let _=t.makeOutput(S,"float32");if(!S.some(E=>E===0)){let E=t.dataIdMap.get(A.dataId).id,R=new Uint8Array(new Int32Array(w.computeStrides(A.shape)).buffer),T=new Uint8Array(new Int32Array(a).buffer),P=new Uint8Array(new Int32Array(o).buffer),V=new Uint8Array(new Int32Array(i).buffer),j=new Uint8Array(new Int32Array(S).buffer),q=new Uint8Array(new Int32Array(w.computeStrides(S)).buffer),X=t.dataIdMap.get(_.dataId).id;Fk(E,R,A.shape.length,T,P,V,j,q,S.length,X)}t.disposeData(A.dataId);let O=Mn({inputs:{x:_},attrs:{shape:S},backend:t});return t.disposeData(_.dataId),O}var cie={kernelName:yl,backendName:"wasm",setupFunc:lie,kernelFunc:uie},die=!0,hie=Cn(bo,die),Ok;function pie(e){Ok=e.wasm.cwrap(Ao,null,["number, number, number"])}function fie(e){let{backend:t,inputs:n,attrs:s}=e,{axis:r,keepDims:a}=s,{x:o}=n,i=t.dataIdMap.get(o.dataId).id,l=i,u=o,{transposed:c,axes:d,originalAxes:h,inputWasTransposed:p}=fa(o,r,t),f=d;if(p){let x=t.dataIdMap.get(c.dataId).id;x!==i&&(u=c,l=x,f=D.getInnerMostAxes(f.length,u.shape.length))}D.assertAxesAreInnerMostDims("sum",f,u.shape.length);let[m,g]=D.computeOutAndReduceShapes(u.shape,f),A=w.sizeFromShape(g),y=t.makeOutput(m,u.dtype);if(w.sizeFromShape(u.shape)!==0){let x=t.dataIdMap.get(y.dataId).id;Ok(l,A,x)}if(p&&t.disposeData(c.dataId),a){let x=D.expandShapeToKeepDim(y.shape,h);y.shape=x}return y}var mie={kernelName:Ao,backendName:"wasm",setupFunc:pie,kernelFunc:fie},gie=un(vo),Aie=un(wo),Pk;function yie(e){Pk=e.wasm.cwrap(Hr,null,["number","array","number","array","number","number"])}function xie(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,a=n.dataIdMap.get(r.dataId).id,{reps:o}=s,i=new Array(r.shape.length);for(let h=0;h<i.length;h++)i[h]=r.shape[h]*o[h];let l=new Uint8Array(new Int32Array(r.shape).buffer),u=new Uint8Array(new Int32Array(i).buffer),c=n.makeOutput(i,r.dtype),d=n.dataIdMap.get(c.dataId).id;return Pk(a,l,r.shape.length,u,i.length,Pn[c.dtype],d),c}var bie={kernelName:Hr,backendName:"wasm",setupFunc:yie,kernelFunc:xie},Mk;function vie(e){Mk=e.wasm.cwrap(xl,null,["number","array","number","number","number","bool","number","number"])}var wie=({inputs:e,backend:t,attrs:n})=>{let{x:s}=e,{k:r,sorted:a}=n,o=t.dataIdMap.get(s.dataId).id,i=new Uint8Array(new Int32Array(s.shape).buffer),l=s.shape.slice();l[l.length-1]=r;let u=t.makeOutput(l,s.dtype),c=t.dataIdMap.get(u.dataId).id,d=t.makeOutput(l,"int32"),h=t.dataIdMap.get(d.dataId).id;return Mk(o,i,s.shape.length,Pn[s.dtype],r,a,c,h),[u,d]},kie={kernelName:xl,backendName:"wasm",setupFunc:vie,kernelFunc:wie},zk;function Iie(e){zk=e.wasm.cwrap(bl,null,["number","number","bool","number","number","number","number","number","number","array","number","number","number","number","number"])}function Sie(e){let{backend:t,inputs:n,attrs:s}=e,{image:r,transforms:a}=n,{interpolation:o,fillMode:i,fillValue:l,outputShape:u}=s,[c,d,h,p]=r.shape,[f,m]=u!=null?u:[d,h],g=[c,f,m,p],A=new Uint8Array(new Int32Array(w.computeStrides(r.shape)).buffer),y=t.makeOutput(g,r.dtype),x=t.dataIdMap.get(y.dataId).id,v=t.dataIdMap.get(r.dataId).id,S=t.dataIdMap.get(a.dataId).id,C=o==="nearest"?1:2,_;switch(i){case"constant":_=1;break;case"reflect":_=2;break;case"wrap":_=3;break;case"nearest":_=4;break;default:_=1;break}return zk(v,S,a.shape[0]>1,c,f,m,p,h,d,A,r.shape.length-1,C,_,l,x),y}var Cie={kernelName:bl,backendName:"wasm",setupFunc:Iie,kernelFunc:Sie};function Tie(e){let{inputs:t,backend:n,attrs:s}=e,{value:r}=t,{axis:a}=s;a<0&&(a+=r.shape.length);let o=r.shape[a],i=r.shape.length,l=new Array(i-1),u=0;for(let p=0;p<i;p++)p!==a&&(l[u++]=r.shape[p]);let c=new Array(o),d=new Array(i).fill(0),h=r.shape.slice();h[a]=1;for(let p=0;p<c.length;p++)d[a]=p,c[p]=nd({inputs:{x:r},attrs:{begin:d,size:h},backend:n});return c.map(({dataId:p,dtype:f})=>({dataId:p,dtype:f,shape:l}))}var Nie={kernelName:vl,backendName:"wasm",kernelFunc:Tie};function Eie(e){let{inputs:{x:t},backend:n}=e,s=n.makeOutput(t.shape,t.dtype);return n.typedArrayFromHeap(s).fill(0),s}var Rie={kernelName:wl,backendName:"wasm",kernelFunc:Eie},_ie=[$se,Ose,zse,jse,Kse,Jse,tre,are,dre,hre,pre,gre,Are,bre,kre,Ire,Sre,Nre,_re,Fre,Mre,zre,Bre,Wre,Vre,Ure,jre,qre,Kre,Dse,Jre,tae,rae,iae,cae,hae,fae,Lse,Aae,xae,vae,wae,Iae,Tae,Eae,Dae,Oae,zae,Bae,Uae,Gae,jae,Kae,Jae,toe,soe,ooe,loe,coe,kk,foe,Aoe,boe,woe,Ioe,Soe,Coe,nre,Eoe,Doe,Ooe,Moe,Poe,Boe,Uoe,joe,qoe,ure,Zoe,Joe,eie,tie,nie,rie,iie,cie,hie,mie,gie,Aie,bie,kie,Cie,Use,Nie,Rie];for(let e of _ie)To(e);var K2=Q();K2.registerFlag("WASM_HAS_SIMD_SUPPORT",async()=>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])));K2.registerFlag("WASM_HAS_MULTITHREAD_SUPPORT",async()=>{if(K2.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 Lk=Ia(dS()),Die='var Module={};function threadPrintErr(){var text=Array.prototype.slice.call(arguments).join(" ");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;this.alert=threadAlert;Module["instantiateWasm"]=function(info,receiveInstance){var instance=new WebAssembly.Instance(Module["wasmModule"],info);Module["wasmModule"]=null;receiveInstance(instance);return instance.exports};function moduleLoaded(){}this.onmessage=function(e){try{if(e.data.cmd==="load"){Module["wasmModule"]=e.data.wasmModule;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).then(function(instance){Module=instance;moduleLoaded()})}else if(e.data.cmd==="objectTransfer"){Module["PThread"].receiveObjectTransfer(e.data)}else if(e.data.cmd==="run"){Module["__performance_now_clock_drift"]=performance.now()-e.data.time;Module["__emscripten_thread_init"](e.data.threadInfoStruct,0,0);var max=e.data.stackBase;var top=e.data.stackBase+e.data.stackSize;Module["establishStackSpace"](top,max);Module["_emscripten_tls_init"]();Module["PThread"].receiveObjectTransfer(e.data);Module["PThread"].setThreadStatus(Module["_pthread_self"](),1);try{var result=Module["invokeEntryPoint"](e.data.start_routine,e.data.arg);if(!Module["getNoExitRuntime"]())Module["PThread"].threadExit(result)}catch(ex){if(ex==="Canceled!"){Module["PThread"].threadCancel()}else if(ex!="unwind"){if(ex instanceof Module["ExitStatus"]){if(Module["getNoExitRuntime"]()){}else{Module["PThread"].threadExit(ex.status)}}else{Module["PThread"].threadExit(-2);throw ex}}}}else if(e.data.cmd==="cancel"){if(Module["_pthread_self"]()){Module["PThread"].threadCancel()}}else if(e.data.target==="setimmediate"){}else if(e.data.cmd==="processThreadQueue"){if(Module["_pthread_self"]()){Module["_emscripten_current_thread_process_queued_calls"]()}}else{err("worker.js received unknown command "+e.data.cmd);err(e.data)}}catch(ex){err("worker.js onmessage() captured an uncaught exception: "+ex);if(ex&&ex.stack)err(ex.stack);throw ex}};if(typeof process==="object"&&typeof process.versions==="object"&&typeof process.versions.node==="string"){self={location:{href:__filename}};var onmessage=this.onmessage;var nodeWorkerThreads=require("worker_threads");global.Worker=nodeWorkerThreads.Worker;var parentPort=nodeWorkerThreads.parentPort;parentPort.on("message",function(data){onmessage({data:data})});var nodeFS=require("fs");var nodeRead=function(filename){return nodeFS.readFileSync(filename,"utf8")};function globalEval(x){global.require=require;global.Module=Module;eval.call(null,x)}importScripts=function(f){globalEval(nodeRead(f))};postMessage=function(msg){parentPort.postMessage(msg)};if(typeof performance==="undefined"){performance={now:function(){return Date.now()}}}}',$ie=Ia(hS()),Bk=class extends Du{constructor(e){super();this.wasm=e,this.dataIdNextNumber=1,this.wasm.tfjs.init(),this.dataIdMap=new Ud(this,wr())}write(e,t,n){let s={id:this.dataIdNextNumber++};return this.move(s,e,t,n,1),s}numDataIds(){return this.dataIdMap.numDataIds()}async time(e){let t=w.now();return e(),{kernelMs:w.now()-t}}move(e,t,n,s,r){let a=this.dataIdNextNumber++;if(s==="string"){let u=t;this.dataIdMap.set(e,{id:a,stringBytes:u,shape:n,dtype:s,memoryOffset:null,refCount:r});return}let o=w.sizeFromShape(n),i=o*w.bytesPerElement(s),l=this.wasm._malloc(i);this.dataIdMap.set(e,{id:a,memoryOffset:l,shape:n,dtype:s,refCount:r}),this.wasm.tfjs.registerTensor(a,o,l),t!=null&&this.wasm.HEAPU8.set(new Uint8Array(t.buffer,t.byteOffset,i),l)}async read(e){return this.readSync(e)}readSync(e){let{memoryOffset:t,dtype:n,shape:s,stringBytes:r}=this.dataIdMap.get(e);if(n==="string")return r;let a=this.wasm.HEAPU8.slice(t,t+w.sizeFromShape(s)*w.bytesPerElement(n));return Pie(a.buffer,n)}disposeData(e,t=!1){if(this.dataIdMap.has(e)){let n=this.dataIdMap.get(e);if(n.refCount--,!t&&n.refCount>0)return!1;this.wasm._free(n.memoryOffset),this.wasm.tfjs.disposeData(n.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,n){let s;if(n==null)s=this.write(null,e,t);else{let r=this.dataIdNextNumber++;s={id:r},this.dataIdMap.set(s,{id:r,memoryOffset:n,shape:e,dtype:t,refCount:1});let a=w.sizeFromShape(e);this.wasm.tfjs.registerTensor(r,a,n)}return{dataId:s,shape:e,dtype:t}}typedArrayFromHeap({shape:e,dtype:t,dataId:n}){let s=this.wasm.HEAPU8.buffer,{memoryOffset:r}=this.dataIdMap.get(n),a=w.sizeFromShape(e);switch(t){case"float32":return new Float32Array(s,r,a);case"int32":return new Int32Array(s,r,a);case"bool":return new Uint8Array(s,r,a);default:throw new Error(`Unknown dtype ${t}`)}}};function Fie(e){return(t,n)=>(w.fetch(e,{credentials:"same-origin"}).then(s=>{s.ok||t.env.a(`failed to load wasm binary file at '${e}'`),s.arrayBuffer().then(r=>{WebAssembly.instantiate(r,t).then(a=>{n(a.instance,a.module)})})}),{})}function Wk(e,t,n){if(Of!=null)return Of;let s="tfjs-backend-wasm.wasm";return e&&t?s="tfjs-backend-wasm-threaded-simd.wasm":e&&(s="tfjs-backend-wasm-simd.wasm"),rd!=null&&rd[s]!=null?rd[s]:n+s}async function Oie(){let[e,t]=await Promise.all([Q().getAsync("WASM_HAS_SIMD_SUPPORT"),Q().getAsync("WASM_HAS_MULTITHREAD_SUPPORT")]);return new Promise((n,s)=>{let r={};r.locateFile=(i,l)=>{if(i.endsWith(".worker.js")){let u=Die,c=new Blob([u],{type:"application/javascript"});return URL.createObjectURL(c)}return i.endsWith(".wasm")?Wk(e,t,sd!=null?sd:l):l+i},Z2&&(r.instantiateWasm=Fie(Wk(e,t,sd!=null?sd:"")));let a=!1;r.onAbort=()=>{if(a||ad)return;ad=!0,s({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 o;t&&e&&Of==null?(r.mainScriptUrlOrBlob=new Blob(["var WasmBackendModuleThreadedSimd = "+Lk.default.toString()],{type:"text/javascript"}),o=(0,Lk.default)(r)):o=(0,$ie.default)(r),o.then(i=>{a=!0,ad=!1;let l=null;i.tfjs={init:i.cwrap("init",null,[]),registerTensor:i.cwrap("register_tensor",null,["number","number","number"]),disposeData:i.cwrap("dispose_data",l,["number"]),dispose:i.cwrap("dispose",l,[])},n({wasm:i})})})}function Pie(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 Mie=["tfjs-backend-wasm.wasm","tfjs-backend-wasm-simd.wasm","tfjs-backend-wasm-threaded-simd.wasm"],Of=null,sd=null,rd={},ad=!1,Z2=!1;function zie(e,t=!1){if(Ag("setWasmPath has been deprecated in favor of setWasmPaths and will be removed in a future release."),ad)throw new Error("The WASM backend was already initialized. Make sure you call `setWasmPath()` before you call `tf.setBackend()` or `tf.ready()`");Of=e,Z2=t}function Lie(e,t=!1){if(ad)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")sd=e;else{rd=e;let n=Mie.filter(s=>rd[s]==null);if(n.length>0)throw new Error(`There were no entries found for the following binaries: ${n.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.`)}Z2=t}var Bie="3.9.0",Wie=2;_l("wasm",async()=>{let{wasm:e}=await Oie();return new Bk(e)},Wie);var Vie={tfjs:pS,"tfjs-core":fS,"tfjs-data":mS,"tfjs-layers":gS,"tfjs-converter":AS,"tfjs-backend-cpu":yS,"tfjs-backend-webgl":xS,"tfjs-backend-wasm":bS};var zn={name:"humangl",priority:99,canvas:null,gl:null,width:1024,height:1024,extensions:[],webGLattr:{alpha:!1,antialias:!1,premultipliedAlpha:!1,preserveDrawingBuffer:!1,depth:!1,stencil:!1,failIfMajorPerformanceCaveat:!1,desynchronized:!0}};function Uie(){let e=zn.gl;!e||(zn.extensions=e.getSupportedExtensions())}function Vk(){if(!yg(zn.name)){try{zn.canvas=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(zn.width,zn.height):document.createElement("canvas")}catch(e){ue("error: cannot create canvas:",e);return}try{zn.gl=zn.canvas.getContext("webgl2",zn.webGLattr)}catch(e){ue("error: cannot get WebGL2 context:",e);return}try{hf(2,zn.gl)}catch(e){ue("error: cannot set WebGL2 context:",e);return}try{let e=new vf(zn.gl);_l(zn.name,()=>new lu(e),zn.priority)}catch(e){ue("error: cannot register WebGL backend:",e);return}try{Sl("webgl").forEach(t=>{let n={...t,backendName:zn.name};To(n)})}catch(e){ue("error: cannot update WebGL backend registration:",e);return}try{os.set("WEBGL_VERSION",2)}catch(e){ue("error: cannot set WebGL backend flags:",e);return}Uie(),ue("backend registered:",zn.name)}}function Uk(e,t){let n=[e.startPoint[0]*t[0],e.startPoint[1]*t[1]],s=[e.endPoint[0]*t[0],e.endPoint[1]*t[1]];return{startPoint:n,endPoint:s}}function id(e){return[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])]}function ld(e){return[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2]}function ud(e,t,n){let s=t.shape[1],r=t.shape[2],a=[[e.startPoint[1]/s,e.startPoint[0]/r,e.endPoint[1]/s,e.endPoint[0]/r]];return _e.cropAndResize(t,a,[0],n)}function Pf(e,t=1.5){let n=ld(e),s=id(e),r=[t*s[0]/2,t*s[1]/2],a=[n[0]-r[0],n[1]-r[1]],o=[n[0]+r[0],n[1]+r[1]];return{startPoint:a,endPoint:o,landmarks:e.landmarks}}function Mf(e){let t=ld(e),n=id(e),r=Math.max(...n)/2,a=[Math.round(t[0]-r),Math.round(t[1]-r)],o=[Math.round(t[0]+r),Math.round(t[1]+r)];return{startPoint:a,endPoint:o,landmarks:e.landmarks}}function Y2(e){let t=e.map(a=>a[0]),n=e.map(a=>a[1]),s=[Math.min(...t),Math.min(...n)],r=[Math.max(...t),Math.max(...n)];return{startPoint:s,endPoint:r,landmarks:e}}var Hk=e=>({startPoint:Re(e,[0,0],[-1,2]),endPoint:Re(e,[0,2],[-1,2])});var zf=[[1,0,0],[0,1,0],[0,0,1]];function Hie(e){return e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI))}function Gk(e,t){let n=Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]);return Hie(n)}function jk(e,t){return[[1,0,e],[0,1,t],[0,0,1]]}function ma(e,t){let n=0;for(let s=0;s<e.length;s++)n+=e[s]*t[s];return n}function Gie(e,t){let n=[];for(let s=0;s<e.length;s++)n.push(e[s][t]);return n}function qk(e,t){let n=[],s=e.length;for(let r=0;r<s;r++){n.push([]);for(let a=0;a<s;a++)n[r].push(ma(e[r],Gie(t,a)))}return n}function J2(e,t){let n=Math.cos(e),s=Math.sin(e),r=[[n,-s,0],[s,n,0],[0,0,1]],a=jk(t[0],t[1]),o=qk(a,r),i=jk(-t[0],-t[1]);return qk(o,i)}function Xk(e){let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],n=[e[0][2],e[1][2]],s=[-ma(t[0],n),-ma(t[1],n)];return[t[0].concat(s[0]),t[1].concat(s[1]),[0,0,1]]}function Kk(e,t){return[ma(e,t[0]),ma(e,t[1])]}function Zk(e){let t={strides:[e/16,e/8],anchors:[2,6]},n=[];for(let s=0;s<t.strides.length;s++){let r=t.strides[s],a=Math.floor((e+r-1)/r),o=Math.floor((e+r-1)/r),i=t.anchors[s];for(let l=0;l<a;l++){let u=r*(l+.5);for(let c=0;c<o;c++){let d=r*(c+.5);for(let h=0;h<i;h++)n.push([d,u])}}}return n}var Yk=6;function jie(e,t,n){let s=Re(e,[0,1],[-1,2]),r=ae(s,t),a=Re(e,[0,3],[-1,2]),o=de(a,n),i=de(r,n),l=de(o,2),u=ge(i,l),c=ae(i,l),d=L(u,n),h=L(c,n);return Ol([d,h],1)}var Jk=class{constructor(t,n){this.model=t,this.anchorsData=Zk(t.inputs[0].shape[1]),this.anchors=Ms(this.anchorsData),this.inputSize=t.inputs[0].shape[2],this.config=n}async getBoundingBoxes(t,n){if(!t||t.isDisposedInternal||t.shape.length!==4||t.shape[1]<1||t.shape[2]<1)return null;let[s,r,a]=H(()=>{let c=_e.resizeBilinear(t,[this.inputSize,this.inputSize]),d=ge(de(c,127.5),.5),h=this.model.execute(d),p;if(Array.isArray(h)){let A=h.sort((v,k)=>v.size-k.size),y=ft([A[0],A[2]],2),x=ft([A[1],A[3]],2),b=ft([x,y],1);p=lt(b,0)}else p=lt(h);let f=jie(p,this.anchors,[this.inputSize,this.inputSize]),m=Re(p,[0,0],[-1,1]),g=lt(Hn(m));return[p,f,g]});this.config=gn(this.config,n);let o=await _e.nonMaxSuppressionAsync(r,a,this.config.face.detector.maxDetected,this.config.face.detector.iouThreshold,this.config.face.detector.minConfidence),i=await o.array();K(o);let l=[],u=await a.data();for(let c=0;c<i.length;c++){let d=u[i[c]];if(d>this.config.face.detector.minConfidence){let h=Re(r,[i[c],0],[1,-1]),p=Hk(h);K(h);let f=this.anchorsData[i[c]],m=H(()=>U(lt(Re(s,[i[c],Yk-1],[1,-1])),[Yk,-1]));l.push({box:p,landmarks:m,anchor:f,confidence:d})}}return K(s),K(r),K(a),{boxes:l,scaleFactor:[t.shape[2]/this.inputSize,t.shape[1]/this.inputSize]}}};async function Qk(e){let t=await mt(gt(e.modelBasePath,e.face.detector.modelPath),{fromTFHub:e.face.detector.modelPath.includes("tfhub.dev")}),n=new Jk(t,e);return!t||!t.modelUrl?ue("load model failed:",e.face.detector.modelPath):e.debug&&ue("load model:",t.modelUrl),n}var hr={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:[61,185,40,39,37,0,267,269,270,409,291],lipsLowerOuter:[146,91,181,84,17,314,405,321,375,291],lipsUpperInner:[78,191,80,81,82,13,312,311,310,415,308],lipsLowerInner:[78,95,88,178,87,14,317,402,318,324,308],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]},Q2=[{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]}],cd=[[.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]],ri=[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 qie=[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],Xie=[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],Kie=[33,133,362,263,1,78,308],jle=qie.map(e=>cd[e]),qle=Xie.map(e=>cd[e]),Xle=Kie.map(e=>cd[e]);var ey=hr.leftEyeLower0,ty=hr.rightEyeLower0,fu={leftBounds:[ey[0],ey[ey.length-1]],rightBounds:[ty[0],ty[ty.length-1]]},e8={count:468,mouth:13,symmetryLine:[13,hr.midwayBetweenEyes[0]]},Zie={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},mu={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};function Lf(e,t,n,s){for(let r=0;r<Q2.length;r++){let{key:a,indices:o}=Q2[r],i=hr[`${n}${a}`];if(!s||s.includes(a))for(let l=0;l<o.length;l++){let u=o[l];e[i[l]]=[t[u][0],t[u][1],(t[u][2]+e[i[l]][2])/2]}}}var ny=class{constructor(t,n,s){var r,a;this.storedBoxes=[],this.boundingBoxDetector=t,this.meshDetector=n,this.irisModel=s,this.boxSize=((r=t==null?void 0:t.model)==null?void 0:r.inputs[0].shape[2])||0,this.meshSize=(n==null?void 0:n.inputs[0].shape[2])||((a=t==null?void 0:t.model)==null?void 0:a.inputs[0].shape[2]),this.irisSize=(s==null?void 0:s.inputs[0].shape[1])||0,this.irisEnlarge=2.3,this.skipped=0,this.detectedFaces=0}transformRawCoords(t,n,s,r){let a=id({startPoint:n.startPoint,endPoint:n.endPoint}),o=t.map(d=>[a[0]/this.meshSize*(d[0]-this.meshSize/2),a[1]/this.meshSize*(d[1]-this.meshSize/2),d[2]]),i=s!==0?J2(s,[0,0]):zf,l=s!==0?o.map(d=>[...Kk(d,i),d[2]]):o,u=s!==0?Xk(r):zf,c=[...ld({startPoint:n.startPoint,endPoint:n.endPoint}),1];return l.map(d=>[Math.round(d[0]+ma(c,u[0])),Math.round(d[1]+ma(c,u[1])),Math.round(d[2])])}getLeftToRightEyeDepthDifference(t){let n=t[fu.leftBounds[0]][2],s=t[fu.rightBounds[0]][2];return n-s}getEyeBox(t,n,s,r,a=!1){let o=Mf(Pf(Y2([t[s],t[r]]),this.irisEnlarge)),i=id(o),l=_e.cropAndResize(n,[[o.startPoint[1]/this.meshSize,o.startPoint[0]/this.meshSize,o.endPoint[1]/this.meshSize,o.endPoint[0]/this.meshSize]],[0],[this.irisSize,this.irisSize]);if(a&&os.flags.IS_BROWSER){let u=_e.flipLeftRight(l);K(l),l=u}return{box:o,boxSize:i,crop:l}}getEyeCoords(t,n,s,r=!1){let a=[];for(let o=0;o<mu.numCoordinates;o++){let i=t[o*3],l=t[o*3+1],u=t[o*3+2];a.push([(r?1-i/this.irisSize:i/this.irisSize)*s[0]+n.startPoint[0],l/this.irisSize*s[1]+n.startPoint[1],u])}return{rawCoords:a,iris:a.slice(mu.index)}}getAdjustedIrisCoords(t,n,s){let r=t[hr[`${s}EyeUpper0`][mu.upperCenter]][2],a=t[hr[`${s}EyeLower0`][mu.lowerCenter]][2],o=(r+a)/2;return n.map((i,l)=>{let u=o;return l===2?u=r:l===4&&(u=a),[i[0],i[1],u]})}correctFaceRotation(t,n,s){let[r,a]=n.landmarks.length>=e8.count?e8.symmetryLine:Zie.symmetryLine,o=Gk(n.landmarks[r],n.landmarks[a]),i=ld({startPoint:n.startPoint,endPoint:n.endPoint}),l=[i[0]/s.shape[2],i[1]/s.shape[1]],u=_e.rotateWithOffset(s,o,0,l),c=J2(-o,i),d=t.face.mesh.enabled?ud({startPoint:n.startPoint,endPoint:n.endPoint},u,[this.meshSize,this.meshSize]):ud({startPoint:n.startPoint,endPoint:n.endPoint},u,[this.boxSize,this.boxSize]),h=de(d,255);return K(d),K(u),[o,c,h]}async augmentIris(t,n){let{box:s,boxSize:r,crop:a}=this.getEyeBox(t,n,fu.leftBounds[0],fu.leftBounds[1],!0),{box:o,boxSize:i,crop:l}=this.getEyeBox(t,n,fu.rightBounds[0],fu.rightBounds[1]),u=ft([a,l]);K(a),K(l);let c=this.irisModel.predict(u);K(u);let d=await c.data();K(c);let h=d.slice(0,mu.numCoordinates*3),{rawCoords:p,iris:f}=this.getEyeCoords(h,s,r,!0),m=d.slice(mu.numCoordinates*3),{rawCoords:g,iris:A}=this.getEyeCoords(m,o,i),y=this.getLeftToRightEyeDepthDifference(t);Math.abs(y)<30?(Lf(t,p,"left",null),Lf(t,g,"right",null)):y<1?Lf(t,p,"left",["EyeUpper0","EyeLower0"]):Lf(t,g,"right",["EyeUpper0","EyeLower0"]);let x=this.getAdjustedIrisCoords(t,f,"left"),b=this.getAdjustedIrisCoords(t,A,"right");return t.concat(x).concat(b)}async predict(t,n){let s=!1,r;if((this.skipped===0||this.skipped>n.face.detector.skipFrames||!n.face.mesh.enabled||!n.skipFrame)&&(r=await this.boundingBoxDetector.getBoundingBoxes(t,n),this.skipped=0),n.skipFrame&&this.skipped++,!n.skipFrame||r&&r.boxes&&(!n.face.mesh.enabled||r.boxes.length!==this.detectedFaces&&this.detectedFaces!==n.face.detector.maxDetected)){this.storedBoxes=[],this.detectedFaces=0;for(let i of r.boxes){let l=await i.box.startPoint.data(),u=await i.box.endPoint.data(),c=await i.landmarks.array();this.storedBoxes.push({startPoint:l,endPoint:u,landmarks:c,confidence:i.confidence})}this.storedBoxes.length>0&&(s=!0)}if(s){if(!r||!r.boxes||r.boxes.length===0)return this.storedBoxes=[],this.detectedFaces=0,null;for(let i=0;i<this.storedBoxes.length;i++){let l=Uk({startPoint:this.storedBoxes[i].startPoint,endPoint:this.storedBoxes[i].endPoint},r.scaleFactor),u=Pf(l),c=Mf(u),d=this.storedBoxes[i].landmarks,h=this.storedBoxes[i].confidence;this.storedBoxes[i]={...c,confidence:h,landmarks:d}}}r&&r.boxes&&r.boxes.forEach(i=>{K(i.box.startPoint),K(i.box.endPoint),K(i.landmarks)});let a=[],o=[];for(let i of this.storedBoxes){let l,u=0,c;if(n.face.detector.rotation&&n.face.mesh.enabled&&os.flags.IS_BROWSER)[u,c,l]=this.correctFaceRotation(n,i,t);else{c=zf;let d=t.clone(),h=n.face.mesh.enabled?ud({startPoint:i.startPoint,endPoint:i.endPoint},d,[this.meshSize,this.meshSize]):ud({startPoint:i.startPoint,endPoint:i.endPoint},d,[this.boxSize,this.boxSize]);l=de(h,255),K(h),K(d)}if(!n.face.mesh.enabled)a.push({mesh:[],box:i,faceConfidence:null,boxConfidence:i.confidence,confidence:i.confidence,image:l});else{let[d,h,p]=this.meshDetector.execute(l);K(d);let f=(await h.data())[0];K(h);let m=U(p,[-1,3]),g=await m.array();if(K(p),K(m),f<n.face.detector.minConfidence)i.confidence=f,K(l);else{n.face.iris.enabled&&(g=await this.augmentIris(g,l));let A=this.transformRawCoords(g,i,u,c);i={...Pf(Y2(A),1.5),confidence:i.confidence},n.face.detector.rotation&&n.face.mesh.enabled&&n.face.description.enabled&&os.flags.IS_BROWSER&&([u,c,l]=this.correctFaceRotation(n,i,t)),a.push({mesh:A,box:i,faceConfidence:f,boxConfidence:i.confidence,confidence:f,image:l}),i={...Mf(i),confidence:i.confidence,faceConfidence:f}}}o.push(i)}return n.face.mesh.enabled&&(this.storedBoxes=o.filter(i=>i.confidence>n.face.detector.minConfidence)),this.detectedFaces=a.length,a}};var Dt=[null,null,null],sy;async function t8(e,t){let n=await sy.predict(e,t),s=[],r=0;for(let a of n||[]){if(!a||a.isDisposedInternal)continue;let o=a.mesh.map(c=>[c[0]/(e.shape[2]||0),c[1]/(e.shape[1]||0),c[2]/sy.meshSize]),i={};if(a.mesh&&a.mesh.length>0)for(let c of Object.keys(hr))i[c]=hr[c].map(d=>a.mesh[d]);let l=a.box?[Math.trunc(Math.max(0,a.box.startPoint[0])),Math.trunc(Math.max(0,a.box.startPoint[1])),Math.trunc(Math.min(e.shape[2]||0,a.box.endPoint[0])-Math.max(0,a.box.startPoint[0])),Math.trunc(Math.min(e.shape[1]||0,a.box.endPoint[1])-Math.max(0,a.box.startPoint[1]))]:[0,0,0,0],u=a.box?[a.box.startPoint[0]/(e.shape[2]||0),a.box.startPoint[1]/(e.shape[1]||0),(a.box.endPoint[0]-a.box.startPoint[0])/(e.shape[2]||0),(a.box.endPoint[1]-a.box.startPoint[1])/(e.shape[1]||0)]:[0,0,0,0];s.push({id:r++,score:Math.round(100*a.faceConfidence||100*a.boxConfidence||0)/100,boxScore:Math.round(100*a.boxConfidence)/100,faceScore:Math.round(100*a.faceConfidence)/100,box:l,boxRaw:u,mesh:a.mesh,meshRaw:o,annotations:i,tensor:a.image}),a.coords&&K(a.coords)}return s}async function ry(e){return!Dt[0]&&e.face.enabled||!Dt[1]&&e.face.mesh.enabled||!Dt[2]&&e.face.iris.enabled?(Dt=await Promise.all([!Dt[0]&&e.face.enabled?Qk(e):null,!Dt[1]&&e.face.mesh.enabled?mt(gt(e.modelBasePath,e.face.mesh.modelPath),{fromTFHub:e.face.mesh.modelPath.includes("tfhub.dev")}):null,!Dt[2]&&e.face.iris.enabled?mt(gt(e.modelBasePath,e.face.iris.modelPath),{fromTFHub:e.face.iris.modelPath.includes("tfhub.dev")}):null]),e.face.mesh.enabled&&(!Dt[1]||!Dt[1].modelUrl?ue("load model failed:",e.face.mesh.modelPath):e.debug&&ue("load model:",Dt[1].modelUrl)),e.face.iris.enabled&&(!Dt[2]||!Dt[2].modelUrl?ue("load model failed:",e.face.iris.modelPath):e.debug&&ue("load model:",Dt[2].modelUrl))):e.debug&&(Dt[0]&&ue("cached model:",Dt[0].model.modelUrl),Dt[1]&&ue("cached model:",Dt[1].modelUrl),Dt[2]&&ue("cached model:",Dt[2].modelUrl)),sy=new ny(Dt[0],Dt[1],Dt[2]),Dt}var n8=ri,s8=cd;var qs,Bf=[],r8=0,ay=Number.MAX_SAFE_INTEGER;async function oy(e){let t=gt(e.modelBasePath,e.face.description.modelPath);return qs?e.debug&&ue("cached model:",t):(qs=await mt(t),qs?e.debug&&ue("load model:",t):ue("load model failed:",e.face.description.modelPath)),qs}function iy(e,t,n=2){if(!e||!t||(e==null?void 0:e.length)===0||(t==null?void 0:t.length)===0||(e==null?void 0:e.length)!==(t==null?void 0:t.length))return 0;let s=5*e.map((a,o)=>Math.abs(e[o]-t[o])**n).reduce((a,o)=>a+o,0)**(1/n);return Math.max(0,100-s)/100}function a8(e,t,n=0){let s={similarity:0,name:"",source:"",embedding:[]};if(!e||!t||!Array.isArray(e)||!Array.isArray(t))return s;for(let r of t)if(r.embedding&&r.name){let a=iy(e,r.embedding);a>n&&a>s.similarity&&(s={...r,similarity:a})}return s}function ly(e){return H(()=>{let n=e.image||e.tensor||e;if(!(n instanceof Ge))return null;let s=[[.05,.15,.85,.85]];if(!qs.inputs[0].shape)return null;let r=n.shape.length===3?_e.cropAndResize(Ot(n,0),s,[0],[qs.inputs[0].shape[2],qs.inputs[0].shape[1]]):_e.cropAndResize(n,s,[0],[qs.inputs[0].shape[2],qs.inputs[0].shape[1]]);return L(r,255)})}async function uy(e,t,n,s){var r,a;return qs?ay<t.face.description.skipFrames&&t.skipFrame&&r8===s&&((r=Bf[n])==null?void 0:r.age)&&((a=Bf[n])==null?void 0:a.age)>0?(ay++,Bf[n]):(ay=0,new Promise(async o=>{let i=ly(e),l,u={age:0,gender:"unknown",genderScore:0,descriptor:[]};if(t.face.description.enabled&&(l=await qs.predict(i)),K(i),l){let c=await l.find(A=>A.shape[1]===1).data(),d=Math.trunc(200*Math.abs(c[0]-.5))/100;d>t.face.description.minConfidence&&(u.gender=c[0]<=.5?"female":"male",u.genderScore=Math.min(.99,d));let p=(await er(l.find(A=>A.shape[1]===100),1).data())[0],f=await l.find(A=>A.shape[1]===100).data();u.age=Math.round(f[p-1]>f[p+1]?10*p-100*f[p-1]:10*p+100*f[p+1])/10;let g=await l.find(A=>A.shape[1]===1024).data();u.descriptor=[...g],l.forEach(A=>K(A))}Bf[n]=u,r8=s,o(u)})):null}var Yie=["angry","disgust","fear","happy","sad","surprise","neutral"],Xs,Wf=[],o8=0,cy=Number.MAX_SAFE_INTEGER,dy=[.2989,.587,.114];async function hy(e){return Xs?e.debug&&ue("cached model:",Xs.modelUrl):(Xs=await mt(gt(e.modelBasePath,e.face.emotion.modelPath)),!Xs||!Xs.modelUrl?ue("load model failed:",e.face.emotion.modelPath):e.debug&&ue("load model:",Xs.modelUrl)),Xs}async function py(e,t,n,s){return Xs?cy<t.face.emotion.skipFrames&&t.skipFrame&&o8===s&&Wf[n]&&Wf[n].length>0?(cy++,Wf[n]):(cy=0,new Promise(async r=>{let a=_e.resizeBilinear(e,[Xs.inputs[0].shape[2],Xs.inputs[0].shape[1]],!1),[o,i,l]=an(a,3,3);K(a);let u=L(o,dy[0]),c=L(i,dy[1]),d=L(l,dy[2]);K(o),K(i),K(l);let h=Vh([u,c,d]);K(u),K(c),K(d);let p=H(()=>L(ge(h,.5),2));K(h);let f=[];if(t.face.emotion.enabled){let m=await Xs.predict(p),g=await m.data();K(m);for(let A=0;A<g.length;A++)g[A]>t.face.emotion.minConfidence&&f.push({score:Math.min(.99,Math.trunc(100*g[A])/100),emotion:Yie[A]});f.sort((A,y)=>y.score-A.score)}K(p),Wf[n]=f,o8=s,r(f)})):null}var dd=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],i8=dd.length,hd=dd.reduce((e,t,n)=>(e[t]=n,e),{}),Jie=[["leftHip","leftShoulder"],["leftElbow","leftShoulder"],["leftElbow","leftWrist"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["rightHip","rightShoulder"],["rightElbow","rightShoulder"],["rightElbow","rightWrist"],["rightHip","rightKnee"],["rightKnee","rightAnkle"],["leftShoulder","rightShoulder"],["leftHip","rightHip"]],Qie=Jie.map(([e,t])=>[hd[e],hd[t]]),l8=[["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 u8(e){let t=e.reduce(({maxX:n,maxY:s,minX:r,minY:a},{position:{x:o,y:i}})=>({maxX:Math.max(n,o),maxY:Math.max(s,i),minX:Math.min(r,o),minY:Math.min(a,i)}),{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 c8(e,[t,n],[s,r]){let a=t/s,o=n/r,i=(u,c)=>({id:c,score:u.score,boxRaw:[u.box[0]/r,u.box[1]/s,u.box[2]/r,u.box[3]/s],box:[Math.trunc(u.box[0]*o),Math.trunc(u.box[1]*a),Math.trunc(u.box[2]*o),Math.trunc(u.box[3]*a)],keypoints:u.keypoints.map(({score:d,part:h,position:p})=>({score:d,part:h,position:[Math.trunc(p.x*o),Math.trunc(p.y*a)],positionRaw:[p.x/s,p.y/s]}))});return e.map((u,c)=>i(u,c))}var fy=class{constructor(t,n){this.priorityQueue=new Array(t),this.numberOfElements=-1,this.getElementValue=n}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 n=2*t;if(n<this.numberOfElements&&this.less(n,n+1)&&n++,!this.less(t,n))break;this.exchange(t,n),t=n}}getValueAt(t){return this.getElementValue(this.priorityQueue[t])}less(t,n){return this.getValueAt(t)<this.getValueAt(n)}exchange(t,n){let s=this.priorityQueue[t];this.priorityQueue[t]=this.priorityQueue[n],this.priorityQueue[n]=s}};function my(e,t,n,s){return{y:s.get(e,t,n),x:s.get(e,t,n+i8)}}function gy(e,t,n){let{heatmapY:s,heatmapX:r,id:a}=e,{y:o,x:i}=my(s,r,a,n);return{x:e.heatmapX*t+i,y:e.heatmapY*t+o}}function Ay(e,t,n){return e<t?t:e>n?n:e}function d8(e,t,n,s){let r=n-e,a=s-t;return r*r+a*a}function yy(e,t){return{x:e.x+t.x,y:e.y+t.y}}var Vf=1,gu=16,ele=50**2;function h8(e,t,n,s,r,a,o=2){let i=A=>({y:a.get(A.y,A.x,e),x:a.get(A.y,A.x,a.shape[2]/2+e)}),l=(A,y,x)=>({y:Ay(Math.round(A.y/gu),0,y-1),x:Ay(Math.round(A.x/gu),0,x-1)}),[u,c]=s.shape,d=l(t.position,u,c),h=i(d),f=yy(t.position,h);for(let A=0;A<o;A++){let y=l(f,u,c),x=my(y.y,y.x,n,r);f=yy({x:y.x*gu,y:y.y*gu},{x:x.x,y:x.y})}let m=l(f,u,c),g=s.get(m.y,m.x,n);return{position:f,part:dd[n],score:g}}function tle(e,t,n,s,r){let a=l8.map(([h,p])=>[hd[h],hd[p]]),o=a.map(([,h])=>h),i=a.map(([h])=>h),l=t.shape[2],u=o.length,c=new Array(l),d=gy(e.part,gu,n);c[e.part.id]={score:e.score,part:dd[e.part.id],position:d};for(let h=u-1;h>=0;--h){let p=o[h],f=i[h];c[p]&&!c[f]&&(c[f]=h8(h,c[p],f,t,n,r))}for(let h=0;h<u;++h){let p=i[h],f=o[h];c[p]&&!c[f]&&(c[f]=h8(h,c[p],f,t,n,s))}return c}function nle(e,t,n,s,r){let[a,o]=r.shape,i=!0,l=Math.max(n-Vf,0),u=Math.min(n+Vf+1,a);for(let c=l;c<u;++c){let d=Math.max(s-Vf,0),h=Math.min(s+Vf+1,o);for(let p=d;p<h;++p)if(r.get(c,p,e)>t){i=!1;break}if(!i)break}return i}function sle(e,t){let[n,s,r]=t.shape,a=new fy(n*s*r,({score:o})=>o);for(let o=0;o<n;++o)for(let i=0;i<s;++i)for(let l=0;l<r;++l){let u=t.get(o,i,l);u<e||nle(l,u,o,i,t)&&a.enqueue({score:u,part:{heatmapY:o,heatmapX:i,id:l}})}return a}function p8(e,{x:t,y:n},s){return e.some(({keypoints:r})=>{var o;let a=(o=r[s])==null?void 0:o.position;return a?d8(n,t,a.y,a.x)<=ele:!1})}function rle(e,t){return t.reduce((s,{position:r,score:a},o)=>(p8(e,r,o)||(s+=a),s),0)/t.length}function f8(e,t,n,s,r,a){let o=[],i=sle(a,t);for(;o.length<r&&!i.empty();){let l=i.dequeue(),u=gy(l.part,gu,e);if(p8(o,u,l.part.id))continue;let c=tle(l,t,e,n,s);c=c.filter(p=>p.score>a);let d=rle(o,c),h=u8(c);d>a&&o.push({keypoints:c,box:h,score:Math.round(100*d)/100})}return o}var Jn,ale=["MobilenetV1/offset_2/BiasAdd","MobilenetV1/heatmap_2/BiasAdd","MobilenetV1/displacement_fwd_2/BiasAdd","MobilenetV1/displacement_bwd_2/BiasAdd"];async function xy(e,t){let n=H(()=>{if(!Jn.inputs[0].shape)return[];let o=_e.resizeBilinear(e,[Jn.inputs[0].shape[2],Jn.inputs[0].shape[1]]),i=ge(de(ce(o,"float32"),127.5),1),u=Jn.execute(i,ale).map(c=>lt(c,[0]));return u[1]=u[1].sigmoid(),u}),s=await Promise.all(n.map(o=>o.buffer()));for(let o of n)K(o);let r=await f8(s[0],s[1],s[2],s[3],t.body.maxDetected,t.body.minConfidence);return Jn.inputs[0].shape?c8(r,[e.shape[1],e.shape[2]],[Jn.inputs[0].shape[2],Jn.inputs[0].shape[1]]):[]}async function by(e){return Jn?e.debug&&ue("cached model:",Jn.modelUrl):(Jn=await mt(gt(e.modelBasePath,e.body.modelPath)),!Jn||!Jn.modelUrl?ue("load model failed:",e.body.modelPath):e.debug&&ue("load model:",Jn.modelUrl)),Jn}function Uf(e){return[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])]}function pd(e){return[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2]}function m8(e,t,n){let s=t.shape[1],r=t.shape[2],a=[[e.startPoint[1]/s,e.startPoint[0]/r,e.endPoint[1]/s,e.endPoint[0]/r]];return _e.cropAndResize(t,a,[0],n)}function g8(e,t){let n=[e.startPoint[0]*t[0],e.startPoint[1]*t[1]],s=[e.endPoint[0]*t[0],e.endPoint[1]*t[1]],r=e.palmLandmarks.map(a=>[a[0]*t[0],a[1]*t[1]]);return{startPoint:n,endPoint:s,palmLandmarks:r,confidence:e.confidence}}function Hf(e,t=1.5){let n=pd(e),s=Uf(e),r=[t*s[0]/2,t*s[1]/2],a=[n[0]-r[0],n[1]-r[1]],o=[n[0]+r[0],n[1]+r[1]];return{startPoint:a,endPoint:o,palmLandmarks:e.palmLandmarks}}function Gf(e){let t=pd(e),n=Uf(e),r=Math.max(...n)/2,a=[t[0]-r,t[1]-r],o=[t[0]+r,t[1]+r];return{startPoint:a,endPoint:o,palmLandmarks:e.palmLandmarks}}var A8=[{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 vy=class{constructor(t){this.model=t,this.anchors=A8.map(n=>[n.x,n.y]),this.anchorsTensor=Ms(this.anchors),this.inputSize=this.model&&this.model.inputs&&this.model.inputs[0].shape?this.model.inputs[0].shape[2]:0,this.inputSizeTensor=Mt([this.inputSize,this.inputSize]),this.doubleInputSizeTensor=Mt([this.inputSize*2,this.inputSize*2])}normalizeBoxes(t){return H(()=>{let n=Re(t,[0,0],[-1,2]),s=Re(t,[0,2],[-1,2]),r=ae(de(n,this.inputSizeTensor),this.anchorsTensor),a=de(s,this.doubleInputSizeTensor),o=L(ge(r,a),this.inputSizeTensor),i=L(ae(r,a),this.inputSizeTensor);return Ol([o,i],1)})}normalizeLandmarks(t,n){return H(()=>{let s=ae(de(U(t,[-1,7,2]),this.inputSizeTensor),this.anchors[n]);return L(s,this.inputSizeTensor)})}async getBoxes(t,n){let s=this.model.predict(t),r=lt(s);K(s);let a=H(()=>lt(Hn(Re(r,[0,0],[-1,1])))),o=await a.data(),i=Re(r,[0,1],[-1,4]),l=this.normalizeBoxes(i);K(i);let u=await _e.nonMaxSuppressionAsync(l,o,n.hand.maxDetected,n.hand.iouThreshold,n.hand.minConfidence),c=await u.array();K(a),K(u);let d=[];for(let h of c)if(o[h]>=n.hand.minConfidence){let p=Re(l,[h,0],[1,-1]),f=Re(r,[h,5],[1,14]),m=H(()=>U(this.normalizeLandmarks(f,h),[-1,2]));K(f),d.push({box:p,palmLandmarks:m,confidence:o[h]})}return K(r),K(l),d}async estimateHandBounds(t,n){let s=t.shape[1],r=t.shape[2],a=H(()=>ge(de(_e.resizeBilinear(t,[this.inputSize,this.inputSize]),127.5),1)),o=await this.getBoxes(a,n);K(a);let i=[];if(!o||o.length===0)return i;for(let l of o){let u=await l.box.data(),c=u.slice(0,2),d=u.slice(2,4),h=await l.palmLandmarks.array();K(l.box),K(l.palmLandmarks),i.push(g8({startPoint:c,endPoint:d,palmLandmarks:h,confidence:l.confidence},[r/this.inputSize,s/this.inputSize]))}return i}};function ole(e){return e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI))}function y8(e,t){let n=Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]);return ole(n)}var x8=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]];function ga(e,t){let n=0;for(let s=0;s<e.length;s++)n+=e[s]*t[s];return n}function ile(e,t){let n=[];for(let s=0;s<e.length;s++)n.push(e[s][t]);return n}function b8(e,t){let n=[],s=e.length;for(let r=0;r<s;r++){n.push([]);for(let a=0;a<s;a++)n[r].push(ga(e[r],ile(t,a)))}return n}function wy(e,t){let n=Math.cos(e),s=Math.sin(e),r=[[n,-s,0],[s,n,0],[0,0,1]],a=x8(t[0],t[1]),o=b8(a,r),i=x8(-t[0],-t[1]);return b8(o,i)}function v8(e){let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],n=[e[0][2],e[1][2]],s=[-ga(t[0],n),-ga(t[1],n)];return[t[0].concat(s[0]),t[1].concat(s[1]),[0,0,1]]}function ky(e,t){return[ga(e,t[0]),ga(e,t[1])]}var lle=5,w8=1.65,k8=[0,5,9,13,17,1,2],ule=0,cle=2,Iy=class{constructor(t,n){var s;this.handDetector=t,this.handPoseModel=n,this.inputSize=(s=this.handPoseModel)==null?void 0:s.inputs[0].shape[2],this.storedBoxes=[],this.skipped=0,this.detectedHands=0}calculateLandmarksBoundingBox(t){let n=t.map(o=>o[0]),s=t.map(o=>o[1]),r=[Math.min(...n),Math.min(...s)],a=[Math.max(...n),Math.max(...s)];return{startPoint:r,endPoint:a}}getBoxForPalmLandmarks(t,n){let s=t.map(a=>ky([...a,1],n)),r=this.calculateLandmarksBoundingBox(s);return Hf(Gf(r),lle)}getBoxForHandLandmarks(t){let n=this.calculateLandmarksBoundingBox(t),s=Hf(Gf(n),w8);s.palmLandmarks=[];for(let r=0;r<k8.length;r++)s.palmLandmarks.push(t[k8[r]].slice(0,2));return s}transformRawCoords(t,n,s,r){let a=Uf(n),o=[a[0]/this.inputSize,a[1]/this.inputSize,(a[0]+a[1])/this.inputSize/2],i=t.map(p=>[o[0]*(p[0]-this.inputSize/2),o[1]*(p[1]-this.inputSize/2),o[2]*p[2]]),l=wy(s,[0,0]),u=i.map(p=>[...ky(p,l),p[2]]),c=v8(r),d=[...pd(n),1],h=[ga(d,c[0]),ga(d,c[1])];return u.map(p=>[Math.trunc(p[0]+h[0]),Math.trunc(p[1]+h[1]),Math.trunc(p[2])])}async estimateHands(t,n){let s=!1,r;(this.skipped===0||this.skipped>n.hand.skipFrames||!n.hand.landmarks||!n.skipFrame)&&(r=await this.handDetector.estimateHandBounds(t,n),this.skipped=0),n.skipFrame&&this.skipped++,r&&r.length>0&&(r.length!==this.detectedHands&&this.detectedHands!==n.hand.maxDetected||!n.hand.landmarks)&&(this.detectedHands=0,this.storedBoxes=[...r],this.storedBoxes.length>0&&(s=!0));let a=[];for(let o=0;o<this.storedBoxes.length;o++){let i=this.storedBoxes[o];if(!!i)if(n.hand.landmarks){let l=n.hand.rotation?y8(i.palmLandmarks[ule],i.palmLandmarks[cle]):0,u=pd(i),c=[u[0]/t.shape[2],u[1]/t.shape[1]],d=n.hand.rotation&&os.flags.IS_BROWSER?_e.rotateWithOffset(t,l,0,c):t.clone(),h=wy(-l,u),p=s?this.getBoxForPalmLandmarks(i.palmLandmarks,h):i,f=m8(p,d,[this.inputSize,this.inputSize]),m=de(f,255);K(f),K(d);let[g,A]=await this.handPoseModel.predict(m);K(m);let y=(await g.data())[0];if(K(g),y>=n.hand.minConfidence){let x=U(A,[-1,3]),b=await x.array();K(A),K(x);let v=this.transformRawCoords(b,p,l,h),k=this.getBoxForHandLandmarks(v);this.storedBoxes[o]={...k,confidence:y};let S={landmarks:v,confidence:y,box:{topLeft:k.startPoint,bottomRight:k.endPoint}};a.push(S)}else this.storedBoxes[o]=null;K(A)}else{let l=Hf(Gf(i),w8),u={confidence:i.confidence,box:{topLeft:l.startPoint,bottomRight:l.endPoint}};a.push(u)}}return this.storedBoxes=this.storedBoxes.filter(o=>o!==null),this.detectedHands=a.length,a}};var Ue={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=>Ue.nameMapping[e],getPoints:e=>Ue.pointsMapping[e]},Tn={none:0,half:1,full:2,nameMapping:{0:"none",1:"half",2:"full"},getName:e=>Tn.nameMapping[e]},Be={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=>Be.nameMapping[e]};var ai={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 I8(e,t,n,s){let r=(t-s)/(e-n),a=Math.atan(r)*180/Math.PI;return a<=0?a=-a:a>0&&(a=180-a),a}function S8(e,t){let n=I8(e[0],e[1],t[0],t[1]);if(e.length===2)return n;let s=I8(e[1],e[2],t[1],t[2]);return[n,s]}function C8(e,t=1){let n=0,s=0,r=0;return e>=75&&e<=105?n=1*t:e>=25&&e<=155?s=1*t:r=1*t,[n,s,r]}function dle(e,t,n){let s=e[0]-t[0],r=e[0]-n[0],a=t[0]-n[0],o=e[1]-t[1],i=e[1]-n[1],l=t[1]-n[1],u=e[2]-t[2],c=e[2]-n[2],d=t[2]-n[2],h=Math.sqrt(s*s+o*o+u*u),p=Math.sqrt(r*r+i*i+c*c),f=Math.sqrt(a*a+l*l+d*d),m=(f*f+h*h-p*p)/(2*f*h);m>1?m=1:m<-1&&(m=-1);let g=Math.acos(m);g=57.2958*g%180;let A;return g>ai.NO_CURL_START_LIMIT?A=Tn.none:g>ai.HALF_CURL_START_LIMIT?A=Tn.half:A=Tn.full,A}function T8(e,t,n,s){let r;return s===Math.abs(e)?e>0?r=Be.horizontalLeft:r=Be.horizontalRight:s===Math.abs(t)?t>0?r=Be.horizontalLeft:r=Be.horizontalRight:n>0?r=Be.horizontalLeft:r=Be.horizontalRight,r}function N8(e,t,n,s){let r;return s===Math.abs(e)?e<0?r=Be.verticalDown:r=Be.verticalUp:s===Math.abs(t)?t<0?r=Be.verticalDown:r=Be.verticalUp:n<0?r=Be.verticalDown:r=Be.verticalUp,r}function hle(e,t,n,s,r,a,o,i){let l,u=N8(e,t,n,s),c=T8(r,a,o,i);return u===Be.verticalUp?c===Be.horizontalLeft?l=Be.diagonalUpLeft:l=Be.diagonalUpRight:c===Be.horizontalLeft?l=Be.diagonalDownLeft:l=Be.diagonalDownRight,l}function ple(e,t,n,s){let r=e[0]-t[0],a=e[0]-n[0],o=t[0]-n[0],i=e[1]-t[1],l=e[1]-n[1],u=t[1]-n[1],c=Math.max(Math.abs(r),Math.abs(a),Math.abs(o)),d=Math.max(Math.abs(i),Math.abs(l),Math.abs(u)),h=0,p=0,f=0,m=d/(c+1e-5);m>1.5?h+=ai.DISTANCE_VOTE_POWER:m>.66?p+=ai.DISTANCE_VOTE_POWER:f+=ai.DISTANCE_VOTE_POWER;let g=Math.sqrt(r*r+i*i),A=Math.sqrt(a*a+l*l),y=Math.sqrt(o*o+u*u),x=Math.max(g,A,y),b=e[0],v=e[1],k=n[0],S=n[1];x===g?(k=n[0],S=n[1]):x===y&&(b=t[0],v=t[1]);let O=S8([b,v],[k,S]),E=C8(O,ai.TOTAL_ANGLE_VOTE_POWER);h+=E[0],p+=E[1],f+=E[2];for(let T of s){let P=C8(T,ai.SINGLE_ANGLE_VOTE_POWER);h+=P[0],p+=P[1],f+=P[2]}let R;return h===Math.max(h,p,f)?R=N8(l,i,u,d):f===Math.max(p,f)?R=T8(a,r,o,c):R=hle(l,i,u,d,a,r,o,c),R}function Sy(e){let t=[],n=[];for(let a of Ue.all){let o=Ue.getPoints(a),i=[],l=[];for(let u of o){let c=e[u[0]],d=e[u[1]],h=S8(c,d),p=h[0],f=h[1];i.push(p),l.push(f)}t.push(i),n.push(l)}let s=[],r=[];for(let a of Ue.all){let o=a===Ue.thumb?1:0,i=Ue.getPoints(a),l=e[i[o][0]],u=e[i[o+1][1]],c=e[i[3][1]],d=dle(l,u,c),h=ple(l,u,c,t[a].slice(o));s[a]=d,r[a]=h}return{curls:s,directions:r}}var fd=class{constructor(t){this.name=t,this.curls={},this.directions={},this.weights=[1,1,1,1,1],this.weightsRelative=[1,1,1,1,1]}addCurl(t,n,s){typeof this.curls[t]=="undefined"&&(this.curls[t]=[]),this.curls[t].push([n,s])}addDirection(t,n,s){this.directions[t]||(this.directions[t]=[]),this.directions[t].push([n,s])}setWeight(t,n){this.weights[t]=n;let s=this.weights.reduce((r,a)=>r+a,0);this.weightsRelative=this.weights.map(r=>r*5/s)}matchAgainst(t,n){let s=0;for(let r in t){let a=t[r],o=this.curls[r];if(typeof o=="undefined"){s+=this.weightsRelative[r];continue}for(let[i,l]of o)if(a===i){s+=l*this.weightsRelative[r];break}}for(let r in n){let a=n[r],o=this.directions[r];if(typeof o=="undefined"){s+=this.weightsRelative[r];continue}for(let[i,l]of o)if(a===i){s+=l*this.weightsRelative[r];break}}return s/10}};var Aa=new fd("thumbs up");Aa.addCurl(Ue.thumb,Tn.none,1);Aa.addDirection(Ue.thumb,Be.verticalUp,1);Aa.addDirection(Ue.thumb,Be.diagonalUpLeft,.25);Aa.addDirection(Ue.thumb,Be.diagonalUpRight,.25);for(let e of[Ue.index,Ue.middle,Ue.ring,Ue.pinky])Aa.addCurl(e,Tn.full,1),Aa.addDirection(e,Be.horizontalLeft,1),Aa.addDirection(e,Be.horizontalRight,1);var Bt=new fd("victory");Bt.addCurl(Ue.thumb,Tn.half,.5);Bt.addCurl(Ue.thumb,Tn.none,.5);Bt.addDirection(Ue.thumb,Be.verticalUp,1);Bt.addDirection(Ue.thumb,Be.diagonalUpLeft,1);Bt.addCurl(Ue.index,Tn.none,1);Bt.addDirection(Ue.index,Be.verticalUp,.75);Bt.addDirection(Ue.index,Be.diagonalUpLeft,1);Bt.addCurl(Ue.middle,Tn.none,1);Bt.addDirection(Ue.middle,Be.verticalUp,1);Bt.addDirection(Ue.middle,Be.diagonalUpLeft,.75);Bt.addCurl(Ue.ring,Tn.full,1);Bt.addDirection(Ue.ring,Be.verticalUp,.2);Bt.addDirection(Ue.ring,Be.diagonalUpLeft,1);Bt.addDirection(Ue.ring,Be.horizontalLeft,.2);Bt.addCurl(Ue.pinky,Tn.full,1);Bt.addDirection(Ue.pinky,Be.verticalUp,.2);Bt.addDirection(Ue.pinky,Be.diagonalUpLeft,1);Bt.addDirection(Ue.pinky,Be.horizontalLeft,.2);Bt.setWeight(Ue.index,2);Bt.setWeight(Ue.middle,2);var E8=[Aa,Bt];var fle=.7;function R8(e){let t=Sy(e),n={};for(let s of Ue.all)n[Ue.getName(s)]={curl:Tn.getName(t.curls[s]),direction:Be.getName(t.directions[s])};return n}function _8(e){let t=Sy(e),n=[];for(let s of E8){let r=s.matchAgainst(t.curls,t.directions);r>=fle&&n.push({name:s.name,confidence:r})}return n}var D8={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]},ya,xa,$8;async function Cy(e,t){let n=await $8.estimateHands(e,t);if(!n)return[];let s=[];for(let r=0;r<n.length;r++){let a={};if(n[r].landmarks)for(let c of Object.keys(D8))a[c]=D8[c].map(d=>n[r].landmarks[d]);let o=n[r].landmarks,i=[Number.MAX_SAFE_INTEGER,Number.MAX_SAFE_INTEGER,0,0],l=[0,0,0,0];if(o&&o.length>0){for(let c of o)c[0]<i[0]&&(i[0]=c[0]),c[1]<i[1]&&(i[1]=c[1]),c[0]>i[2]&&(i[2]=c[0]),c[1]>i[3]&&(i[3]=c[1]);i[2]-=i[0],i[3]-=i[1],l=[i[0]/(e.shape[2]||0),i[1]/(e.shape[1]||0),i[2]/(e.shape[2]||0),i[3]/(e.shape[1]||0)]}else i=n[r].box?[Math.trunc(Math.max(0,n[r].box.topLeft[0])),Math.trunc(Math.max(0,n[r].box.topLeft[1])),Math.trunc(Math.min(e.shape[2]||0,n[r].box.bottomRight[0])-Math.max(0,n[r].box.topLeft[0])),Math.trunc(Math.min(e.shape[1]||0,n[r].box.bottomRight[1])-Math.max(0,n[r].box.topLeft[1]))]:[0,0,0,0],l=[n[r].box.topLeft[0]/(e.shape[2]||0),n[r].box.topLeft[1]/(e.shape[1]||0),(n[r].box.bottomRight[0]-n[r].box.topLeft[0])/(e.shape[2]||0),(n[r].box.bottomRight[1]-n[r].box.topLeft[1])/(e.shape[1]||0)];let u=R8(o);s.push({id:r,score:Math.round(100*n[r].confidence)/100,box:i,boxRaw:l,keypoints:o,annotations:a,landmarks:u})}return s}async function Ty(e){!ya||!xa?([ya,xa]=await Promise.all([e.hand.enabled?mt(gt(e.modelBasePath,e.hand.detector.modelPath),{fromTFHub:e.hand.detector.modelPath.includes("tfhub.dev")}):null,e.hand.landmarks?mt(gt(e.modelBasePath,e.hand.skeleton.modelPath),{fromTFHub:e.hand.skeleton.modelPath.includes("tfhub.dev")}):null]),e.hand.enabled&&(!ya||!ya.modelUrl?ue("load model failed:",e.hand.detector.modelPath):e.debug&&ue("load model:",ya.modelUrl),!xa||!xa.modelUrl?ue("load model failed:",e.hand.skeleton.modelPath):e.debug&&ue("load model:",xa.modelUrl))):(e.debug&&ue("cached model:",ya.modelUrl),e.debug&&ue("cached model:",xa.modelUrl));let t=new vy(ya);return $8=new Iy(t,xa),[ya,xa]}var F8=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftPalm","rightPalm","leftIndex","rightIndex","leftPinky","rightPinky","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle","leftHeel","rightHeel","leftFoot","rightFoot","midHip","forehead","leftThumb","leftHand","rightThumb","rightHand"],O8=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","left:15","right:16","left:17","right:18","left:19","right:20","left:21","right:22","leftChest","rightChest","neck","forehead","left:27","right:28","left:29","right:30"];var Ln;async function jf(e){return Ln?e.debug&&ue("cached model:",Ln.modelUrl):(Ln=await mt(gt(e.modelBasePath,e.body.modelPath)),Ln.width=parseInt(Ln.signature.inputs["input_1:0"].tensorShape.dim[2].size),Ln.height=parseInt(Ln.signature.inputs["input_1:0"].tensorShape.dim[1].size),!Ln||!Ln.modelUrl?ue("load model failed:",e.body.modelPath):e.debug&&ue("load model:",Ln.modelUrl)),Ln}async function Ny(e,t){if(!Ln)return[];if(!t.body.enabled)return[];let n={width:e.shape[2]||0,height:e.shape[1]||0},s=_e.resizeBilinear(e,[Ln.width,Ln.height],!1),r=de(s,[255]);K(s);let a=await Ln.predict(r),o=a.find(g=>g.size===195||g.size===155),i=await(o==null?void 0:o.data())||[];a.forEach(g=>K(g)),K(r);let l=[],u=(i==null?void 0:i.length)===195?F8:O8,c=5;for(let g=0;g<i.length/c;g++)l.push({id:g,part:u[g],position:[Math.trunc(n.width*i[c*g+0]/255),Math.trunc(n.height*i[c*g+1]/255),Math.trunc(i[c*g+2])+0],positionRaw:[i[c*g+0]/255,i[c*g+1]/255,i[c*g+2]+0],score:(100-Math.trunc(100/(1+Math.exp(i[c*g+3]))))/100,presence:(100-Math.trunc(100/(1+Math.exp(i[c*g+4]))))/100});let d=l.map(g=>g.position[0]),h=l.map(g=>g.position[1]),p=[Math.min(...d),Math.min(...h),Math.max(...d)-Math.min(...d),Math.max(...h)-Math.min(...d)],f=[0,0,0,0],m=l.reduce((g,A)=>A.score>g?A.score:g,0);return[{id:0,score:m,box:p,boxRaw:f,keypoints:l}]}var Bn,pr=[],Ey=[0,0,0,0],Ry=[0,0,0,0],qf=0,_y=Number.MAX_SAFE_INTEGER,mle=["head","neck","rightShoulder","rightElbow","rightWrist","chest","leftShoulder","leftElbow","leftWrist","pelvis","rightHip","rightKnee","rightAnkle","leftHip","leftKnee","leftAnkle"];async function P8(e){return Bn?e.debug&&ue("cached model:",Bn.modelUrl):(Bn=await mt(gt(e.modelBasePath,e.body.modelPath)),!Bn||!Bn.modelUrl?ue("load model failed:",e.body.modelPath):e.debug&&ue("load model:",Bn.modelUrl)),Bn}function gle(e,t){let[n,s]=e.shape;return H(()=>{let r=(i,l)=>ge(i,L(de(i,Ie(l,"int32")),Ie(l,"int32"))),a=U(e,[s*n]),o=hs(a,0).dataSync()[0];if(o>t){let i=er(a,0),l=r(i,n).dataSync()[0],u=de(i,Ie(n,"int32")).dataSync()[0];return[l,u,o]}return[0,0,o]})}async function Dy(e,t){return _y<t.body.skipFrames&&t.skipFrame&&Object.keys(pr).length>0?(_y++,[{id:0,score:qf,box:Ey,boxRaw:Ry,keypoints:pr}]):(_y=0,new Promise(async n=>{let s=H(()=>{if(!Bn.inputs[0].shape)return null;let u=_e.resizeBilinear(e,[Bn.inputs[0].shape[2],Bn.inputs[0].shape[1]],!1);return L(u,2).sub(1)}),r;if(t.body.enabled&&(r=await Bn.predict(s)),K(s),r){pr.length=0;let u=r.squeeze();K(r);let c=u.unstack(2);K(u);for(let d=0;d<c.length;d++){let[h,p,f]=gle(c[d],t.body.minConfidence);qf>t.body.minConfidence&&pr.push({score:Math.round(100*f)/100,part:mle[d],positionRaw:[h/Bn.inputs[0].shape[2],p/Bn.inputs[0].shape[1]],position:[Math.round(e.shape[2]*h/Bn.inputs[0].shape[2]),Math.round(e.shape[1]*p/Bn.inputs[0].shape[1])]})}c.forEach(d=>K(d))}qf=pr.reduce((u,c)=>c.score>u?c.score:u,0);let a=pr.map(u=>u.position[0]),o=pr.map(u=>u.position[1]);Ey=[Math.min(...a),Math.min(...o),Math.max(...a)-Math.min(...a),Math.max(...o)-Math.min(...o)];let i=pr.map(u=>u.positionRaw[0]),l=pr.map(u=>u.positionRaw[1]);Ry=[Math.min(...i),Math.min(...l),Math.max(...i)-Math.min(...i),Math.max(...l)-Math.min(...l)],n([{id:0,score:qf,box:Ey,boxRaw:Ry,keypoints:pr}])}))}var fr,vs=[],$y=[0,0,0,0],Dr=[0,0,0,0],$r=0,Fy=Number.MAX_SAFE_INTEGER,M8=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"];async function Oy(e){return fr?e.debug&&ue("cached model:",fr.modelUrl):(fr=await mt(gt(e.modelBasePath,e.body.modelPath)),!fr||!fr.modelUrl?ue("load model failed:",e.body.modelPath):e.debug&&ue("load model:",fr.modelUrl)),fr}async function Ale(e,t,n){vs.length=0;let s=e[0][0];for(let u=0;u<s.length;u++)$r=s[u][2],$r>t.body.minConfidence&&vs.push({score:Math.round(100*$r)/100,part:M8[u],positionRaw:[s[u][1],s[u][0]],position:[Math.round((n.shape[2]||0)*s[u][1]),Math.round((n.shape[1]||0)*s[u][0])]});$r=vs.reduce((u,c)=>c.score>u?c.score:u,0);let r=vs.map(u=>u.position[0]),a=vs.map(u=>u.position[1]);$y=[Math.min(...r),Math.min(...a),Math.max(...r)-Math.min(...r),Math.max(...a)-Math.min(...a)];let o=vs.map(u=>u.positionRaw[0]),i=vs.map(u=>u.positionRaw[1]);Dr=[Math.min(...o),Math.min(...i),Math.max(...o)-Math.min(...o),Math.max(...i)-Math.min(...i)];let l=[];return l.push({id:0,score:$r,box:$y,boxRaw:Dr,keypoints:vs}),l}async function yle(e,t,n){let s=[];for(let r=0;r<e[0].length;r++){let a=e[0][r];if($r=Math.round(100*a[51+4])/100,!($r<t.body.minConfidence)){vs.length=0;for(let o=0;o<17;o++){let i=Math.round(100*a[3*o+2])/100;i>t.body.minConfidence&&vs.push({part:M8[o],score:i,positionRaw:[a[3*o+1],a[3*o+0]],position:[Math.trunc(a[3*o+1]*(n.shape[2]||0)),Math.trunc(a[3*o+0]*(n.shape[1]||0))]})}Dr=[a[51+1],a[51+0],a[51+3]-a[51+1],a[51+2]-a[51+0]],s.push({id:r,score:$r,boxRaw:Dr,box:[Math.trunc(Dr[0]*(n.shape[2]||0)),Math.trunc(Dr[1]*(n.shape[1]||0)),Math.trunc(Dr[2]*(n.shape[2]||0)),Math.trunc(Dr[3]*(n.shape[1]||0))],keypoints:vs})}}return s}async function Py(e,t){return Fy<t.body.skipFrames&&t.skipFrame&&Object.keys(vs).length>0?(Fy++,[{id:0,score:$r,box:$y,boxRaw:Dr,keypoints:vs}]):(Fy=0,new Promise(async n=>{let s=H(()=>{if(!fr.inputs[0].shape)return null;let i=fr.inputs[0].shape[2];i===-1&&(i=256);let l=_e.resizeBilinear(e,[i,i],!1);return ce(l,"int32")}),r;t.body.enabled&&(r=await fr.predict(s)),K(s),r||n([]);let a=await r.array(),o;r.shape[2]===17?o=await Ale(a,t,e):r.shape[2]===56&&(o=await yle(a,t,e)),K(r),n(o)}))}var Au=[{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 Qn,My=[],zy=Number.MAX_SAFE_INTEGER,Xf=2.5;async function Ly(e){if(Qn)e.debug&&ue("cached model:",Qn.modelUrl);else{Qn=await mt(gt(e.modelBasePath,e.object.modelPath));let t=Object.values(Qn.modelSignature.inputs);if(Qn.inputSize=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):null,!Qn.inputSize)throw new Error(`Human: Cannot determine model inputSize: ${e.object.modelPath}`);!Qn||!Qn.modelUrl?ue("load model failed:",e.object.modelPath):e.debug&&ue("load model:",Qn.modelUrl)}return Qn}async function xle(e,t,n,s){let r=0,a=[];for(let u of[1,2,4])H(async()=>{var g,A;let c=u*13,d=(g=e.find(y=>y.shape[1]===c**2&&y.shape[2]===Au.length))==null?void 0:g.squeeze(),h=(A=e.find(y=>y.shape[1]===c**2&&y.shape[2]<Au.length))==null?void 0:A.squeeze(),f=await h.reshape([-1,4,h.shape[1]/4]).argMax(2).array(),m=await d.array();for(let y=0;y<d.shape[0];y++)for(let x=0;x<d.shape[1];x++){let b=m[y][x];if(b>s.object.minConfidence&&x!==61){let v=(.5+Math.trunc(y%c))/c,k=(.5+Math.trunc(y/c))/c,S=f[y].map(V=>V*(c/u/t)),[C,_]=[v-Xf/u*S[0],k-Xf/u*S[1]],[O,E]=[v+Xf/u*S[2]-C,k+Xf/u*S[3]-_],R=[C,_,O,E];R=R.map(V=>Math.max(0,Math.min(V,1)));let T=[R[0]*n[0],R[1]*n[1],R[2]*n[0],R[3]*n[1]],P={id:r++,score:Math.round(100*b)/100,class:x+1,label:Au[x].label,box:T.map(V=>Math.trunc(V)),boxRaw:R};a.push(P)}}});e.forEach(u=>K(u));let o=a.map(u=>[u.boxRaw[1],u.boxRaw[0],u.boxRaw[3],u.boxRaw[2]]),i=a.map(u=>u.score),l=[];if(o&&o.length>0){let u=await _e.nonMaxSuppressionAsync(o,i,s.object.maxDetected,s.object.iouThreshold,s.object.minConfidence);l=await u.data(),K(u)}return a=a.filter((u,c)=>l.includes(c)).sort((u,c)=>c.score-u.score),a}async function By(e,t){return zy<t.object.skipFrames&&t.skipFrame&&My.length>0?(zy++,My):(zy=0,new Promise(async n=>{let s=[e.shape[2],e.shape[1]],r=_e.resizeBilinear(e,[Qn.inputSize,Qn.inputSize],!1),a=de(r,255),o=a.transpose([0,3,1,2]);K(a),K(r);let i;t.object.enabled&&(i=await Qn.predict(o)),K(o);let l=await xle(i,Qn.inputSize,s,t);My=l,n(l)}))}var es,Wy=[],Vy=Number.MAX_SAFE_INTEGER;async function Uy(e){if(es)e.debug&&ue("cached model:",es.modelUrl);else{es=await mt(gt(e.modelBasePath,e.object.modelPath));let t=Object.values(es.modelSignature.inputs);if(es.inputSize=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):null,!es.inputSize)throw new Error(`Human: Cannot determine model inputSize: ${e.object.modelPath}`);!es||!es.modelUrl?ue("load model failed:",e.object.modelPath):e.debug&&ue("load model:",es.modelUrl)}return es}async function ble(e,t,n,s){if(!e)return[];let r=[],a=await e.array(),o=lt(e);K(e);let i=an(o,6,1);K(o);let l=Dn([i[1],i[0],i[3],i[2]],1),u=lt(l),c=lt(i[4]),d=lt(i[5]);i.forEach(m=>K(m));let h=await _e.nonMaxSuppressionAsync(u,c,s.object.maxDetected,s.object.iouThreshold,s.object.minConfidence);K(u),K(c),K(d);let p=await h.data();K(h);let f=0;for(let m of p){let g=Math.trunc(100*a[0][m][4])/100,A=a[0][m][5],y=Au[A].label,[x,b]=[a[0][m][0]/t,a[0][m][1]/t],v=[x,b,a[0][m][2]/t-x,a[0][m][3]/t-b],k=[Math.trunc(v[0]*n[0]),Math.trunc(v[1]*n[1]),Math.trunc(v[2]*n[0]),Math.trunc(v[3]*n[1])];r.push({id:f++,score:g,class:A,label:y,box:k,boxRaw:v})}return r}async function Hy(e,t){return Vy<t.object.skipFrames&&t.skipFrame&&Wy.length>0?(Vy++,Wy):(Vy=0,new Promise(async n=>{let s=[e.shape[2],e.shape[1]],r=_e.resizeBilinear(e,[es.inputSize,es.inputSize]),a=t.object.enabled?es.execute(r,["tower_0/detections"]):null;K(r);let o=await ble(a,es.inputSize,s,t);Wy=o,n(o)}))}function vle(e,t,n){let s=function(i,l,u){let c=new RegExp("\\b"+l+" \\w+ (\\w+)","ig");i.replace(c,(d,h)=>(u[h]=0,d))},r=function(i,l){let u=e.createShader(l);if(e.shaderSource(u,i),e.compileShader(u),!e.getShaderParameter(u,e.COMPILE_STATUS))throw new Error("Filter: GL compile failed",e.getShaderInfoLog(u));return u};this.uniform={},this.attribute={};let a=r(t,e.VERTEX_SHADER),o=r(n,e.FRAGMENT_SHADER);if(this.id=e.createProgram(),e.attachShader(this.id,a),e.attachShader(this.id,o),e.linkProgram(this.id),!e.getProgramParameter(this.id,e.LINK_STATUS))throw new Error("Filter: GL link failed",e.getProgramInfoLog(this.id));e.useProgram(this.id),s(t,"attribute",this.attribute);for(let i in this.attribute)this.attribute[i]=e.getAttribLocation(this.id,i);s(t,"uniform",this.uniform),s(n,"uniform",this.uniform);for(let i in this.uniform)this.uniform[i]=e.getUniformLocation(this.id,i)}function z8(e){e||(e={});let t=0,n=null,s=!1,r=-1,a=[null,null],o=[],i=-1,l=-1,u=null,c=null,d={},h=e.canvas||document.createElement("canvas"),p={},f={INTERMEDIATE:1},m=h.getContext("webgl");if(!m)throw new Error("Filter: getContext() failed");this.addFilter=function(v){let k=Array.prototype.slice.call(arguments,1),S=d[v];o.push({func:S,args:k})},this.reset=function(){o=[]};let g=function(v,k){if(!(v===i&&k===l)){if(h.width=v,i=v,h.height=k,l=k,!u){let S=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]);u=m.createBuffer(),m.bindBuffer(m.ARRAY_BUFFER,u),m.bufferData(m.ARRAY_BUFFER,S,m.STATIC_DRAW),m.pixelStorei(m.UNPACK_PREMULTIPLY_ALPHA_WEBGL,!0)}m.viewport(0,0,i,l),a=[null,null]}},A=function(v,k){let S=m.createFramebuffer();m.bindFramebuffer(m.FRAMEBUFFER,S);let C=m.createRenderbuffer();m.bindRenderbuffer(m.RENDERBUFFER,C);let _=m.createTexture();return m.bindTexture(m.TEXTURE_2D,_),m.texImage2D(m.TEXTURE_2D,0,m.RGBA,v,k,0,m.RGBA,m.UNSIGNED_BYTE,null),m.texParameteri(m.TEXTURE_2D,m.TEXTURE_MAG_FILTER,m.LINEAR),m.texParameteri(m.TEXTURE_2D,m.TEXTURE_MIN_FILTER,m.LINEAR),m.texParameteri(m.TEXTURE_2D,m.TEXTURE_WRAP_S,m.CLAMP_TO_EDGE),m.texParameteri(m.TEXTURE_2D,m.TEXTURE_WRAP_T,m.CLAMP_TO_EDGE),m.framebufferTexture2D(m.FRAMEBUFFER,m.COLOR_ATTACHMENT0,m.TEXTURE_2D,_,0),m.bindTexture(m.TEXTURE_2D,null),m.bindFramebuffer(m.FRAMEBUFFER,null),{fbo:S,texture:_}},y=function(v){return a[v]=a[v]||A(i,l),a[v]},x=function(v=null){var _,O;let k=null,S=null,C=!1;t===0?k=n:k=(_=y(r))==null?void 0:_.texture,t++,s&&!(v&f.INTERMEDIATE)?(S=null,C=t%2==0):(r=(r+1)%2,S=(O=y(r))==null?void 0:O.fbo),m.bindTexture(m.TEXTURE_2D,k),m.bindFramebuffer(m.FRAMEBUFFER,S),m.uniform1f(c.uniform.flipY,C?-1:1),m.drawArrays(m.TRIANGLES,0,6)};this.apply=function(v){if(g(v.width,v.height),t=0,n||(n=m.createTexture()),m.bindTexture(m.TEXTURE_2D,n),m.texParameteri(m.TEXTURE_2D,m.TEXTURE_WRAP_S,m.CLAMP_TO_EDGE),m.texParameteri(m.TEXTURE_2D,m.TEXTURE_WRAP_T,m.CLAMP_TO_EDGE),m.texParameteri(m.TEXTURE_2D,m.TEXTURE_MIN_FILTER,m.NEAREST),m.texParameteri(m.TEXTURE_2D,m.TEXTURE_MAG_FILTER,m.NEAREST),m.texImage2D(m.TEXTURE_2D,0,m.RGBA,m.RGBA,m.UNSIGNED_BYTE,v),o.length===0)return x(),h;for(let k=0;k<o.length;k++){s=k===o.length-1;let S=o[k];S.func.apply(this,S.args||[])}return h};let b=function(v){if(p[v])return c=p[v],m.useProgram(c.id),c;let k={};k.VERTEX_IDENTITY=["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.);","}"].join(`
`),k.FRAGMENT_IDENTITY=["precision highp float;","varying vec2 vUv;","uniform sampler2D texture;","void main(void) {","gl_FragColor = texture2D(texture, vUv);","}"].join(`
`),c=new vle(m,k.VERTEX_IDENTITY,v);let S=Float32Array.BYTES_PER_ELEMENT,C=4*S;return m.enableVertexAttribArray(c.attribute.pos),m.vertexAttribPointer(c.attribute.pos,2,m.FLOAT,!1,C,0*S),m.enableVertexAttribArray(c.attribute.uv),m.vertexAttribPointer(c.attribute.uv,2,m.FLOAT,!1,C,2*S),p[v]=c,c};d.colorMatrix=function(v){let k=new Float32Array(v);k[4]/=255,k[9]/=255,k[14]/=255,k[19]/=255;let S=k[18]===1&&k[3]===0&&k[8]===0&&k[13]===0&&k[15]===0&&k[16]===0&&k[17]===0&&k[19]===0?d.colorMatrix.SHADER.WITHOUT_ALPHA:d.colorMatrix.SHADER.WITH_ALPHA,C=b(S);m.uniform1fv(C.uniform.m,k),x()},d.colorMatrix.SHADER={},d.colorMatrix.SHADER.WITH_ALPHA=["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];","}"].join(`
`),d.colorMatrix.SHADER.WITHOUT_ALPHA=["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;","}"].join(`
`),d.brightness=function(v){let k=(v||0)+1;d.colorMatrix([k,0,0,0,0,0,k,0,0,0,0,0,k,0,0,0,0,0,1,0])},d.saturation=function(v){let k=(v||0)*2/3+1,S=(k-1)*-.5;d.colorMatrix([k,S,S,0,0,S,k,S,0,0,S,S,k,0,0,0,0,0,1,0])},d.desaturate=function(){d.saturation(-1)},d.contrast=function(v){let k=(v||0)+1,S=-128*(k-1);d.colorMatrix([k,0,0,0,S,0,k,0,0,S,0,0,k,0,S,0,0,0,1,0])},d.negative=function(){d.contrast(-2)},d.hue=function(v){v=(v||0)/180*Math.PI;let k=Math.cos(v),S=Math.sin(v),C=.213,_=.715,O=.072;d.colorMatrix([C+k*(1-C)+S*-C,_+k*-_+S*-_,O+k*-O+S*(1-O),0,0,C+k*-C+S*.143,_+k*(1-_)+S*.14,O+k*-O+S*-.283,0,0,C+k*-C+S*-(1-C),_+k*-_+S*_,O+k*(1-O)+S*O,0,0,0,0,0,1,0])},d.desaturateLuminance=function(){d.colorMatrix([.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,0,0,0,1,0])},d.sepia=function(){d.colorMatrix([.393,.7689999,.18899999,0,0,.349,.6859999,.16799999,0,0,.272,.5339999,.13099999,0,0,0,0,0,1,0])},d.brownie=function(){d.colorMatrix([.5997023498159715,.34553243048391263,-.2708298674538042,0,47.43192855600873,-.037703249837783157,.8609577587992641,.15059552388459913,0,-36.96841498319127,.24113635128153335,-.07441037908422492,.44972182064877153,0,-7.562075277591283,0,0,0,1,0])},d.vintagePinhole=function(){d.colorMatrix([.6279345635605994,.3202183420819367,-.03965408211312453,0,9.651285835294123,.02578397704808868,.6441188644374771,.03259127616149294,0,7.462829176470591,.0466055556782719,-.0851232987247891,.5241648018700465,0,5.159190588235296,0,0,0,1,0])},d.kodachrome=function(){d.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])},d.technicolor=function(){d.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])},d.polaroid=function(){d.colorMatrix([1.438,-.062,-.062,0,0,-.122,1.378,-.122,0,0,-.016,-.016,1.483,0,0,0,0,0,1,0])},d.shiftToBGR=function(){d.colorMatrix([0,0,1,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1,0])},d.convolution=function(v){let k=new Float32Array(v),S=1/i,C=1/l,_=b(d.convolution.SHADER);m.uniform1fv(_.uniform.m,k),m.uniform2f(_.uniform.px,S,C),x()},d.convolution.SHADER=["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);","vec4 c12 = texture2D(texture, vec2(vUv.x, vUv.y - px.y));","vec4 c13 = texture2D(texture, vec2(vUv.x + px.x, vUv.y - px.y));","vec4 c21 = texture2D(texture, vec2(vUv.x - px.x, vUv.y) );","vec4 c22 = texture2D(texture, vUv);","vec4 c23 = texture2D(texture, vec2(vUv.x + px.x, vUv.y) );","vec4 c31 = texture2D(texture, vec2(vUv.x - px.x, vUv.y + px.y) );","vec4 c32 = texture2D(texture, vec2(vUv.x, vUv.y + px.y) );","vec4 c33 = texture2D(texture, vUv + px );","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;","}"].join(`
`),d.detectEdges=function(){d.convolution.call(this,[0,1,0,1,-4,1,0,1,0])},d.sobelX=function(){d.convolution.call(this,[-1,0,1,-2,0,2,-1,0,1])},d.sobelY=function(){d.convolution.call(this,[-1,-2,-1,0,0,0,1,2,1])},d.sharpen=function(v){let k=v||1;d.convolution.call(this,[0,-1*k,0,-1*k,1+4*k,-1*k,0,-1*k,0])},d.emboss=function(v){let k=v||1;d.convolution.call(this,[-2*k,-1*k,0,-1*k,1,1*k,0,1*k,2*k])},d.blur=function(v){let k=v/7/i,S=v/7/l,C=b(d.blur.SHADER);m.uniform2f(C.uniform.px,0,S),x(f.INTERMEDIATE),m.uniform2f(C.uniform.px,k,0),x()},d.blur.SHADER=["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;","}"].join(`
`),d.pixelate=function(v){let k=v/i,S=v/l,C=b(d.pixelate.SHADER);m.uniform2f(C.uniform.size,k,S),x()},d.pixelate.SHADER=["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);","}"].join(`
`)}var Kf=2048,Ee,It,Wt;function oi(e,t){let n;if(!e)throw new Error("Human: Input is missing");if(!(e instanceof Ge)&&!(typeof Image!="undefined"&&e instanceof Image)&&!(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("Human: Input type is not recognized");if(e instanceof Ge)if(e.shape&&e.shape.length===4&&e.shape[0]===1&&e.shape[3]===3)n=Os(e);else throw new Error(`Human: Input tensor shape must be [1, height, width, 3] and instead was ${e.shape}`);else{let r=e.naturalWidth||e.videoWidth||e.width||e.shape&&e.shape[1]>0,a=e.naturalHeight||e.videoHeight||e.height||e.shape&&e.shape[2]>0;if(!r||!a)return{tensor:null,canvas:Ee};let o=r,i=a;if(o>Kf&&(o=Kf,i=o*a/r),i>Kf&&(i=Kf,o=i*r/a),t.filter.width>0?o=t.filter.width:t.filter.height>0&&(o=r*(t.filter.height/a)),t.filter.height>0?i=t.filter.height:t.filter.width>0&&(i=a*(t.filter.width/r)),!o||!i)throw new Error("Human: Input cannot determine dimension");(!Ee||(Ee==null?void 0:Ee.width)!==o||(Ee==null?void 0:Ee.height)!==i)&&(Ee=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(o,i):document.createElement("canvas"),(Ee==null?void 0:Ee.width)!==o&&(Ee.width=o),(Ee==null?void 0:Ee.height)!==i&&(Ee.height=i));let l=Ee.getContext("2d");if(e instanceof ImageData?l.putImageData(e,0,0):t.filter.flip&&typeof l.translate!="undefined"?(l.translate(r,0),l.scale(-1,1),l.drawImage(e,0,0,r,a,0,0,Ee==null?void 0:Ee.width,Ee==null?void 0:Ee.height),l.setTransform(1,0,0,1,0,0)):l.drawImage(e,0,0,r,a,0,0,Ee==null?void 0:Ee.width,Ee==null?void 0:Ee.height),t.filter.enabled){if((!Wt||!It||Ee.width!==It.width||(Ee==null?void 0:Ee.height)!==(It==null?void 0:It.height))&&(It=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(Ee==null?void 0:Ee.width,Ee==null?void 0:Ee.height):document.createElement("canvas"),(It==null?void 0:It.width)!==(Ee==null?void 0:Ee.width)&&(It.width=Ee==null?void 0:Ee.width),(It==null?void 0:It.height)!==(Ee==null?void 0:Ee.height)&&(It.height=Ee==null?void 0:Ee.height),Wt=os.flags.IS_BROWSER?new z8({canvas:It}):null),!Wt)return{tensor:null,canvas:Ee};Wt.reset(),Wt.addFilter("brightness",t.filter.brightness),t.filter.contrast!==0&&Wt.addFilter("contrast",t.filter.contrast),t.filter.sharpness!==0&&Wt.addFilter("sharpen",t.filter.sharpness),t.filter.blur!==0&&Wt.addFilter("blur",t.filter.blur),t.filter.saturation!==0&&Wt.addFilter("saturation",t.filter.saturation),t.filter.hue!==0&&Wt.addFilter("hue",t.filter.hue),t.filter.negative&&Wt.addFilter("negative"),t.filter.sepia&&Wt.addFilter("sepia"),t.filter.vintage&&Wt.addFilter("brownie"),t.filter.sepia&&Wt.addFilter("sepia"),t.filter.kodachrome&&Wt.addFilter("kodachrome"),t.filter.technicolor&&Wt.addFilter("technicolor"),t.filter.polaroid&&Wt.addFilter("polaroid"),t.filter.pixelate!==0&&Wt.addFilter("pixelate",t.filter.pixelate),Wt.apply(Ee)}else It=Ee,Wt&&(Wt=null);if(!n){let u;if(It.data){let c=[It.height,It.width,3];u=Lh(It.data,c,"int32")}else if(It instanceof ImageData)u=ls?ls.fromPixels(It):null;else if(t.backend==="webgl"||t.backend==="humangl"){let c=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(o,i):document.createElement("canvas");c.width=o,c.height=i;let d=c.getContext("2d");d==null||d.drawImage(It,0,0),u=ls?ls.fromPixels(c):null}else{let c=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(o,i):document.createElement("canvas");c.width=o,c.height=i;let d=c.getContext("2d");d==null||d.drawImage(It,0,0);let h=d==null?void 0:d.getImageData(0,0,o,i);u=ls?ls.fromPixels(h):null}if(u){let c=ce(u,"float32");n=Ot(c,0),K(u),K(c)}}}let s=t.filter.return?It:null;return{tensor:n,canvas:s}}var ws,Gy=!1;async function Zf(e){return ws?e.debug&&ue("cached model:",ws.modelUrl):(ws=await mt(gt(e.modelBasePath,e.segmentation.modelPath)),!ws||!ws.modelUrl?ue("load model failed:",e.segmentation.modelPath):e.debug&&ue("load model:",ws.modelUrl)),ws}async function jy(e){var f,m;let t=((f=e.tensor)==null?void 0:f.shape[1])||0,n=((m=e.tensor)==null?void 0:m.shape[2])||0;if(!e.tensor||!ws||!ws.inputs[0].shape)return null;let s=_e.resizeBilinear(e.tensor,[ws.inputs[0].shape[1],ws.inputs[0].shape[2]],!1),r=de(s,255),a=ws.predict(r);K(s),K(r);let o=lt(a,0),i;if(o.shape[2]===2){let g=o.softmax(),[A,y]=ms(g,2),x=Ot(y,2),b=Ot(x,0);K(g),K(A),K(y);let v=_e.cropAndResize(b,[[0,0,.5,.5]],[0],[t,n]);i=lt(v,0),K(v),K(x),K(b)}else i=_e.resizeBilinear(o,[t,n]);if(typeof document=="undefined")return i.data();let l=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(t,n):document.createElement("canvas");l.width=t,l.height=n,ls&&await ls.toPixels(i,l),K(i),K(o),K(a);let u=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(t,n):document.createElement("canvas");u.width=t,u.height=n;let c=u.getContext("2d");c.filter="blur(8px",await c.drawImage(l,0,0);let d=c.getImageData(0,0,t,n).data,h=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(t,n):document.createElement("canvas");h.width=t,h.height=n;let p=h.getContext("2d");return e.canvas&&await p.drawImage(e.canvas,0,0),p.globalCompositeOperation="darken",p.filter="blur(8px)",await p.drawImage(l,0,0),p.globalCompositeOperation="source-over",p.filter="none",e.canvas=h,d}async function L8(e,t,n){var a;if(Gy)return null;Gy=!0,ws||await Zf(n);let s=oi(e,n),r=await jy(s);if(K(s.tensor),t&&r){let o=oi(t,n),i=o.canvas;K(o.tensor);let l=s.canvas,u=(a=l.getContext("2d"))==null?void 0:a.getImageData(0,0,l.width,l.height).data,c=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(l.width,l.height):document.createElement("canvas");c.width=l.width,c.height=l.height;let d=c.getContext("2d");d.globalCompositeOperation="copy",d.drawImage(i,0,0,c.width,c.height);let h=d.getImageData(0,0,c.width,c.height);for(let p=0;p<c.width*c.height;p++)h.data[4*p+0]=(255-r[4*p+0])/255*h.data[4*p+0]+r[4*p+0]/255*u[4*p+0],h.data[4*p+1]=(255-r[4*p+1])/255*h.data[4*p+1]+r[4*p+1]/255*u[4*p+1],h.data[4*p+2]=(255-r[4*p+2])/255*h.data[4*p+2]+r[4*p+2]/255*u[4*p+2],h.data[4*p+3]=(255-r[4*p+3])/255*h.data[4*p+3]+r[4*p+3]/255*u[4*p+3];d.putImageData(h,0,0),s.canvas=c}return Gy=!1,s.canvas}async function B8(e){e.config.async?[e.models.face,e.models.emotion,e.models.handpose,e.models.posenet,e.models.blazepose,e.models.efficientpose,e.models.movenet,e.models.nanodet,e.models.centernet,e.models.faceres,e.models.segmentation]=await Promise.all([e.models.face||(e.config.face.enabled?ry(e.config):null),e.models.emotion||(e.config.face.enabled&&e.config.face.emotion.enabled?hy(e.config):null),e.models.handpose||(e.config.hand.enabled?Ty(e.config):null),e.models.posenet||(e.config.body.enabled&&e.config.body.modelPath.includes("posenet")?by(e.config):null),e.models.blazepose||(e.config.body.enabled&&e.config.body.modelPath.includes("blazepose")?jf(e.config):null),e.models.efficientpose||(e.config.body.enabled&&e.config.body.modelPath.includes("efficientpose")?P8(e.config):null),e.models.movenet||(e.config.body.enabled&&e.config.body.modelPath.includes("movenet")?Oy(e.config):null),e.models.nanodet||(e.config.object.enabled&&e.config.object.modelPath.includes("nanodet")?Ly(e.config):null),e.models.centernet||(e.config.object.enabled&&e.config.object.modelPath.includes("centernet")?Uy(e.config):null),e.models.faceres||(e.config.face.enabled&&e.config.face.description.enabled?oy(e.config):null),e.models.segmentation||(e.config.segmentation.enabled?Zf(e.config):null)]):(e.config.face.enabled&&!e.models.face&&(e.models.face=await ry(e.config)),e.config.face.enabled&&e.config.face.emotion.enabled&&!e.models.emotion&&(e.models.emotion=await hy(e.config)),e.config.hand.enabled&&!e.models.handpose&&(e.models.handpose=await Ty(e.config)),e.config.body.enabled&&!e.models.posenet&&e.config.body.modelPath.includes("posenet")&&(e.models.posenet=await by(e.config)),e.config.body.enabled&&!e.models.blazepose&&e.config.body.modelPath.includes("blazepose")&&(e.models.blazepose=await jf(e.config)),e.config.body.enabled&&!e.models.efficientpose&&e.config.body.modelPath.includes("efficientpose")&&(e.models.efficientpose=await jf(e.config)),e.config.body.enabled&&!e.models.movenet&&e.config.body.modelPath.includes("movenet")&&(e.models.movenet=await Oy(e.config)),e.config.object.enabled&&!e.models.nanodet&&e.config.object.modelPath.includes("nanodet")&&(e.models.nanodet=await Ly(e.config)),e.config.object.enabled&&!e.models.centernet&&e.config.object.modelPath.includes("centernet")&&(e.models.centernet=await Uy(e.config)),e.config.face.enabled&&e.config.face.description.enabled&&!e.models.faceres&&(e.models.faceres=await oy(e.config)),e.config.segmentation.enabled&&!e.models.segmentation&&(e.models.segmentation=await Zf(e.config)))}var wle=e=>{let t=(d,h)=>Math.atan2(d[1]-h[1],d[0]-h[0]);if(!e.annotations.rightEyeIris||!e.annotations.leftEyeIris)return{bearing:0,strength:0};let n=[0,-.1],s=1,r=e.mesh[33][2]>e.mesh[263][2],a=r?e.mesh[473]:e.mesh[468],o=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],i=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=[(o[0]-a[0])/i[0]-n[0],s*(a[1]-o[1])/i[1]-n[1]],u=Math.sqrt(l[0]**2+l[1]**2);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}},kle=(e,t)=>{let n=g=>{let A=Math.sqrt(g[0]*g[0]+g[1]*g[1]+g[2]*g[2]);return g[0]/=A,g[1]/=A,g[2]/=A,g},s=(g,A)=>{let y=g[0]-A[0],x=g[1]-A[1],b=g[2]-A[2];return[y,x,b]},r=(g,A)=>{let y=g[1]*A[2]-g[2]*A[1],x=g[2]*A[0]-g[0]*A[2],b=g[0]*A[1]-g[1]*A[0];return[y,x,b]},a=g=>{let[A,y,x,b,v,k,S,C,_]=g,O,E,R;return b<1?b>-1?(R=Math.asin(b),E=Math.atan2(-S,A),O=Math.atan2(-k,v)):(R=-Math.PI/2,E=-Math.atan2(C,_),O=0):(R=Math.PI/2,E=Math.atan2(C,_),O=0),isNaN(O)&&(O=0),isNaN(E)&&(E=0),isNaN(R)&&(R=0),{pitch:2*-O,yaw:2*-E,roll:2*-R}},o=g=>{let A=(x,b,v,k)=>Math.atan2(k-b,v-x);return{pitch:A(g[10][1],g[10][2],g[152][1],g[152][2]),yaw:A(g[33][0],g[33][2],g[263][0],g[263][2]),roll:A(g[33][0],g[33][1],g[263][0],g[263][1])}},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 l=Math.max(e.boxRaw[2]*t[0],e.boxRaw[3]*t[1])/1.5,u=[i[10],i[152],i[234],i[454]].map(g=>[g[0]*t[0]/l,g[1]*t[1]/l,g[2]]),c=n(s(u[1],u[0])),d=n(s(u[3],u[2])),h=n(r(d,c));d=r(c,h);let p=[d[0],d[1],d[2],c[0],c[1],c[2],h[0],h[1],h[2]],f=a(p),m=i.length===478?wle(e):{bearing:0,strength:0};return{angle:f,matrix:p,gaze:m}},qy=async(e,t)=>{var d,h,p,f,m,g;let n,s,r,a,o,i,l,u=[];e.state="run:face",n=Ye();let c=await t8(t,e.config);if(e.performance.face=Math.trunc(Ye()-n),!t.shape||t.shape.length!==4)return[];if(!c)return[];for(let A=0;A<c.length;A++){if(e.analyze("Get Face"),!c[A].tensor||c[A].tensor.isDisposedInternal){ue("Face object is disposed:",c[A].tensor);continue}let y=kle(c[A],[t.shape[2],t.shape[1]]);e.analyze("Start Emotion:"),e.config.async?o=e.config.face.emotion.enabled?py(c[A].tensor||dn([]),e.config,A,c.length):{}:(e.state="run:emotion",n=Ye(),o=e.config.face.emotion.enabled?await py(c[A].tensor||dn([]),e.config,A,c.length):{},e.performance.emotion=Math.trunc(Ye()-n)),e.analyze("End Emotion:"),e.analyze("Start Description:"),e.config.async?l=e.config.face.description.enabled?uy(c[A].tensor||dn([]),e.config,A,c.length):[]:(e.state="run:description",n=Ye(),l=e.config.face.description.enabled?await uy(c[A].tensor||dn([]),e.config,A,c.length):[],e.performance.embedding=Math.trunc(Ye()-n)),e.analyze("End Description:"),e.config.async&&([s,a,o,i,l,r]=await Promise.all([s,a,o,i,l,r])),e.analyze("Finish Face:"),!e.config.face.iris.enabled&&((h=(d=c[A])==null?void 0:d.annotations)==null?void 0:h.leftEyeIris)&&((f=(p=c[A])==null?void 0:p.annotations)==null?void 0:f.rightEyeIris)&&(delete c[A].annotations.leftEyeIris,delete c[A].annotations.rightEyeIris);let x=((m=c[A].annotations)==null?void 0:m.leftEyeIris)&&((g=c[A].annotations)==null?void 0:g.rightEyeIris)?Math.max(Math.abs(c[A].annotations.leftEyeIris[3][0]-c[A].annotations.leftEyeIris[1][0]),Math.abs(c[A].annotations.rightEyeIris[4][1]-c[A].annotations.rightEyeIris[2][1]))/t.shape[2]:0,b=e.config.face.detector.return?lt(c[A].tensor):null;K(c[A].tensor),c[A].tensor&&delete c[A].tensor,u.push({...c[A],id:A,age:l.age,gender:l.gender,genderScore:l.genderScore,embedding:l.descriptor,emotion:o,iris:x!==0?Math.trunc(500/x/11.7)/100:0,rotation:y,tensor:b}),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),u};var W8=e=>{if(!e)return[];let t=[];for(let n=0;n<e.length;n++){let s=e[n].keypoints.find(l=>l.part==="leftWrist"),r=e[n].keypoints.find(l=>l.part==="rightWrist"),a=e[n].keypoints.find(l=>l.part==="nose");a&&s&&r&&s.position.y<a.position.y&&r.position.y<a.position.y?t.push({body:n,gesture:"i give up"}):a&&s&&s.position.y<a.position.y?t.push({body:n,gesture:"raise left hand"}):a&&r&&r.position.y<a.position.y&&t.push({body:n,gesture:"raise right hand"});let o=e[n].keypoints.find(l=>l.part==="leftShoulder"),i=e[n].keypoints.find(l=>l.part==="rightShoulder");o&&i&&t.push({body:n,gesture:`leaning ${o.position.y>i.position.y?"left":"right"}`})}return t},V8=e=>{if(!e)return[];let t=[];for(let n=0;n<e.length;n++)if(e[n].mesh&&e[n].mesh.length>0){let s=e[n].mesh[33][2]-e[n].mesh[263][2];Math.abs(s)<10?t.push({face:n,gesture:"facing center"}):t.push({face:n,gesture:`facing ${s<0?"left":"right"}`}),Math.abs(e[n].mesh[374][1]-e[n].mesh[386][1])/Math.abs(e[n].mesh[443][1]-e[n].mesh[450][1])<.2&&t.push({face:n,gesture:"blink left eye"}),Math.abs(e[n].mesh[145][1]-e[n].mesh[159][1])/Math.abs(e[n].mesh[223][1]-e[n].mesh[230][1])<.2&&t.push({face:n,gesture:"blink right eye"});let o=Math.min(100,500*Math.abs(e[n].mesh[13][1]-e[n].mesh[14][1])/Math.abs(e[n].mesh[10][1]-e[n].mesh[152][1]));o>10&&t.push({face:n,gesture:`mouth ${Math.trunc(o)}% open`});let i=e[n].mesh[152][2];Math.abs(i)>10&&t.push({face:n,gesture:`head ${i<0?"up":"down"}`})}return t},U8=e=>{if(!e)return[];let t=[];for(let n=0;n<e.length;n++){if(!e[n].annotations||!e[n].annotations.leftEyeIris||!e[n].annotations.rightEyeIris)continue;let s=e[n].annotations.leftEyeIris[3][0]-e[n].annotations.leftEyeIris[1][0],r=e[n].annotations.leftEyeIris[4][1]-e[n].annotations.leftEyeIris[2][1],a=Math.abs(s*r),o=e[n].annotations.rightEyeIris[3][0]-e[n].annotations.rightEyeIris[1][0],i=e[n].annotations.rightEyeIris[4][1]-e[n].annotations.rightEyeIris[2][1],l=Math.abs(o*i),u=!1;Math.abs(a-l)/Math.max(a,l)<.25&&(u=!0,t.push({iris:n,gesture:"facing center"}));let d=Math.abs(e[n].mesh[33][0]-e[n].annotations.rightEyeIris[0][0])/e[n].box[2],h=Math.abs(e[n].mesh[263][0]-e[n].annotations.leftEyeIris[0][0])/e[n].box[2];(h>.06||d>.06)&&(u=!1),h>.06&&t.push({iris:n,gesture:"looking right"}),d>.06&&t.push({iris:n,gesture:"looking left"});let p=Math.abs(e[n].mesh[145][1]-e[n].annotations.rightEyeIris[0][1])/e[n].box[3],f=Math.abs(e[n].mesh[374][1]-e[n].annotations.leftEyeIris[0][1])/e[n].box[3];(f<.01||p<.01||f>.022||p>.022)&&(u=!1),(f<.01||p<.01)&&t.push({iris:n,gesture:"looking down"}),(f>.022||p>.022)&&t.push({iris:n,gesture:"looking up"}),u&&t.push({iris:n,gesture:"looking center"})}return t},H8=e=>{if(!e)return[];let t=[];for(let n=0;n<e.length;n++){let s=[];for(let[a,o]of Object.entries(e[n].annotations))a!=="palmBase"&&Array.isArray(o)&&s.push({name:a.toLowerCase(),position:o[0]});if(s&&s.length>0){let a=s.reduce((i,l)=>i.position[2]<l.position[2]?i:l);t.push({hand:n,gesture:`${a.name} forward`});let o=s.reduce((i,l)=>i.position[1]<l.position[1]?i:l);t.push({hand:n,gesture:`${o.name} up`})}let r=_8(e[n].keypoints);for(let a of r)t.push({hand:n,gesture:a.name})}return t};var Zy={};d5(Zy,{all:()=>Cle,body:()=>q8,canvas:()=>Sle,face:()=>j8,gesture:()=>G8,hand:()=>X8,object:()=>K8,options:()=>ba,person:()=>Ile});var ba={color:"rgba(173, 216, 230, 0.6)",labelColor:"rgba(173, 216, 230, 1)",shadowColor:"black",font:'small-caps 14px "Segoe UI"',lineHeight:18,lineWidth:4,pointSize:2,roundRect:8,drawPoints:!1,drawLabels:!0,drawBoxes:!0,drawPolygons:!0,drawGaze:!0,fillPolygons:!1,useDepth:!0,useCurves:!1,bufferedOutput:!0},Yf=e=>Math.round(e*180/Math.PI);function Xy(e,t,n,s=0,r){e.fillStyle=r.useDepth&&s?`rgba(${127.5+2*s}, ${127.5-2*s}, 255, 0.3)`:r.color,e.beginPath(),e.arc(t,n,r.pointSize,0,2*Math.PI),e.fill()}function md(e,t,n,s,r,a){if(e.beginPath(),a.useCurves){let o=(t+t+s)/2,i=(n+n+r)/2;e.ellipse(o,i,s/2,r/2,0,0,2*Math.PI)}else e.lineWidth=a.lineWidth,e.moveTo(t+a.roundRect,n),e.lineTo(t+s-a.roundRect,n),e.quadraticCurveTo(t+s,n,t+s,n+a.roundRect),e.lineTo(t+s,n+r-a.roundRect),e.quadraticCurveTo(t+s,n+r,t+s-a.roundRect,n+r),e.lineTo(t+a.roundRect,n+r),e.quadraticCurveTo(t,n+r,t,n+r-a.roundRect),e.lineTo(t,n+a.roundRect),e.quadraticCurveTo(t,n,t+a.roundRect,n),e.closePath();e.stroke()}function Ky(e,t=[],n){if(!(t===void 0||t.length===0)){e.beginPath(),e.moveTo(t[0][0],t[0][1]);for(let s of t){let r=s[2]||0;e.strokeStyle=n.useDepth&&r?`rgba(${127.5+2*r}, ${127.5-2*r}, 255, 0.3)`:n.color,e.fillStyle=n.useDepth&&r?`rgba(${127.5+2*r}, ${127.5-2*r}, 255, 0.3)`:n.color,e.lineTo(s[0],Math.round(s[1]))}e.stroke(),n.fillPolygons&&(e.closePath(),e.fill())}}function gd(e,t=[],n){if(!(t===void 0||t.length===0)){if(!n.useCurves||t.length<=2){Ky(e,t,n);return}e.moveTo(t[0][0],t[0][1]);for(let s=0;s<t.length-2;s++){let r=(t[s][0]+t[s+1][0])/2,a=(t[s][1]+t[s+1][1])/2;e.quadraticCurveTo(t[s][0],t[s][1],r,a)}e.quadraticCurveTo(t[t.length-2][0],t[t.length-2][1],t[t.length-1][0],t[t.length-1][1]),e.stroke(),n.fillPolygons&&(e.closePath(),e.fill())}}async function G8(e,t,n){let s=gn(ba,n);if(!t||!e||!(e instanceof HTMLCanvasElement))return;let r=e.getContext("2d");if(!r)return;r.font=s.font,r.fillStyle=s.color;let a=1;for(let o=0;o<t.length;o++){let i=[],l=[];if([i,l]=Object.entries(t[o]),l.length>1&&l[1].length>0){let u=i[1]>0?`#${i[1]}`:"",c=`${i[0]} ${u}: ${l[1]}`;s.shadowColor&&s.shadowColor!==""&&(r.fillStyle=s.shadowColor,r.fillText(c,8,2+a*s.lineHeight)),r.fillStyle=s.labelColor,r.fillText(c,6,0+a*s.lineHeight),a+=1}}}async function j8(e,t,n){var a,o,i,l;let s=gn(ba,n);if(!t||!e||!(e instanceof HTMLCanvasElement))return;let r=e.getContext("2d");if(!!r)for(let u of t){r.font=s.font,r.strokeStyle=s.color,r.fillStyle=s.color,s.drawBoxes&&md(r,u.box[0],u.box[1],u.box[2],u.box[3],s);let c=[];if(c.push(`face: ${Math.trunc(100*u.score)}%`),u.genderScore&&c.push(`${u.gender||""} ${Math.trunc(100*u.genderScore)}%`),u.age&&c.push(`age: ${u.age||""}`),u.iris&&c.push(`distance: ${u.iris}`),u.emotion&&u.emotion.length>0){let d=u.emotion.map(h=>`${Math.trunc(100*h.score)}% ${h.emotion}`);d.length>3&&(d.length=3),c.push(d.join(" "))}u.rotation&&u.rotation.angle&&u.rotation.gaze&&(u.rotation.angle.roll&&c.push(`roll: ${Yf(u.rotation.angle.roll)}\xB0 yaw:${Yf(u.rotation.angle.yaw)}\xB0 pitch:${Yf(u.rotation.angle.pitch)}\xB0`),u.rotation.gaze.bearing&&c.push(`gaze: ${Yf(u.rotation.gaze.bearing)}\xB0`)),c.length===0&&c.push("face"),r.fillStyle=s.color;for(let d=c.length-1;d>=0;d--){let h=Math.max(u.box[0],0),p=d*s.lineHeight+u.box[1];s.shadowColor&&s.shadowColor!==""&&(r.fillStyle=s.shadowColor,r.fillText(c[d],h+5,p+16)),r.fillStyle=s.labelColor,r.fillText(c[d],h+4,p+15)}if(r.lineWidth=1,u.mesh&&u.mesh.length>0){if(s.drawPoints)for(let d of u.mesh)Xy(r,d[0],d[1],d[2],s);if(s.drawPolygons){r.lineWidth=1;for(let d=0;d<ri.length/3;d++){let h=[ri[d*3+0],ri[d*3+1],ri[d*3+2]].map(p=>u.mesh[p]);Ky(r,h,s)}if(u.annotations&&u.annotations.leftEyeIris){r.strokeStyle=s.useDepth?"rgba(255, 200, 255, 0.3)":s.color,r.beginPath();let d=Math.abs(u.annotations.leftEyeIris[3][0]-u.annotations.leftEyeIris[1][0])/2,h=Math.abs(u.annotations.leftEyeIris[4][1]-u.annotations.leftEyeIris[2][1])/2;r.ellipse(u.annotations.leftEyeIris[0][0],u.annotations.leftEyeIris[0][1],d,h,0,0,2*Math.PI),r.stroke(),s.fillPolygons&&(r.fillStyle=s.useDepth?"rgba(255, 255, 200, 0.3)":s.color,r.fill())}if(u.annotations&&u.annotations.rightEyeIris){r.strokeStyle=s.useDepth?"rgba(255, 200, 255, 0.3)":s.color,r.beginPath();let d=Math.abs(u.annotations.rightEyeIris[3][0]-u.annotations.rightEyeIris[1][0])/2,h=Math.abs(u.annotations.rightEyeIris[4][1]-u.annotations.rightEyeIris[2][1])/2;r.ellipse(u.annotations.rightEyeIris[0][0],u.annotations.rightEyeIris[0][1],d,h,0,0,2*Math.PI),r.stroke(),s.fillPolygons&&(r.fillStyle=s.useDepth?"rgba(255, 255, 200, 0.3)":s.color,r.fill())}if(s.drawGaze&&((o=(a=u.rotation)==null?void 0:a.gaze)==null?void 0:o.strength)&&((l=(i=u.rotation)==null?void 0:i.gaze)==null?void 0:l.bearing)&&u.annotations.leftEyeIris&&u.annotations.rightEyeIris&&u.annotations.leftEyeIris[0]&&u.annotations.rightEyeIris[0]){r.strokeStyle="pink",r.beginPath();let d=[u.annotations.leftEyeIris[0][0]+Math.sin(u.rotation.gaze.bearing)*u.rotation.gaze.strength*u.box[3],u.annotations.leftEyeIris[0][1]+Math.cos(u.rotation.gaze.bearing)*u.rotation.gaze.strength*u.box[2]];r.moveTo(u.annotations.leftEyeIris[0][0],u.annotations.leftEyeIris[0][1]),r.lineTo(d[0],d[1]);let h=[u.annotations.rightEyeIris[0][0]+Math.sin(u.rotation.gaze.bearing)*u.rotation.gaze.strength*u.box[3],u.annotations.rightEyeIris[0][1]+Math.cos(u.rotation.gaze.bearing)*u.rotation.gaze.strength*u.box[2]];r.moveTo(u.annotations.rightEyeIris[0][0],u.annotations.rightEyeIris[0][1]),r.lineTo(h[0],h[1]),r.stroke()}}}}}async function q8(e,t,n){var a;let s=gn(ba,n);if(!t||!e||!(e instanceof HTMLCanvasElement))return;let r=e.getContext("2d");if(!!r){r.lineJoin="round";for(let o=0;o<t.length;o++){if(r.strokeStyle=s.color,r.fillStyle=s.color,r.lineWidth=s.lineWidth,r.font=s.font,s.drawBoxes&&t[o].box&&((a=t[o].box)==null?void 0:a.length)===4&&(md(r,t[o].box[0],t[o].box[1],t[o].box[2],t[o].box[3],s),s.drawLabels&&(s.shadowColor&&s.shadowColor!==""&&(r.fillStyle=s.shadowColor,r.fillText(`body ${100*t[o].score}%`,t[o].box[0]+3,1+t[o].box[1]+s.lineHeight,t[o].box[2])),r.fillStyle=s.labelColor,r.fillText(`body ${100*t[o].score}%`,t[o].box[0]+2,0+t[o].box[1]+s.lineHeight,t[o].box[2]))),s.drawPoints)for(let i=0;i<t[o].keypoints.length;i++)r.fillStyle=s.useDepth&&t[o].keypoints[i].position[2]?`rgba(${127.5+2*(t[o].keypoints[i].position[2]||0)}, ${127.5-2*(t[o].keypoints[i].position[2]||0)}, 255, 0.5)`:s.color,Xy(r,t[o].keypoints[i].position[0],t[o].keypoints[i].position[1],0,s);if(s.drawLabels&&(r.font=s.font,t[o].keypoints))for(let i of t[o].keypoints)r.fillStyle=s.useDepth&&i.position[2]?`rgba(${127.5+2*i.position[2]}, ${127.5-2*i.position[2]}, 255, 0.5)`:s.color,r.fillText(`${i.part} ${Math.trunc(100*i.score)}%`,i.position[0]+4,i.position[1]+4);if(s.drawPolygons&&t[o].keypoints){let i,l=[];l.length=0,i=t[o].keypoints.find(u=>u.part==="leftShoulder"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="rightShoulder"),i&&l.push([i.position[0],i.position[1]]),gd(r,l,s),l.length=0,i=t[o].keypoints.find(u=>u.part==="rightShoulder"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="rightHip"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="leftHip"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="leftShoulder"),i&&l.push([i.position[0],i.position[1]]),l.length===4&&Ky(r,l,s),l.length=0,i=t[o].keypoints.find(u=>u.part==="leftHip"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="leftKnee"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="leftAnkle"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="leftHeel"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="leftFoot"),i&&l.push([i.position[0],i.position[1]]),gd(r,l,s),l.length=0,i=t[o].keypoints.find(u=>u.part==="rightHip"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="rightKnee"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="rightAnkle"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="rightHeel"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="rightFoot"),i&&l.push([i.position[0],i.position[1]]),gd(r,l,s),l.length=0,i=t[o].keypoints.find(u=>u.part==="leftShoulder"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="leftElbow"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="leftWrist"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="leftPalm"),i&&l.push([i.position[0],i.position[1]]),gd(r,l,s),l.length=0,i=t[o].keypoints.find(u=>u.part==="rightShoulder"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="rightElbow"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="rightWrist"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="rightPalm"),i&&l.push([i.position[0],i.position[1]]),gd(r,l,s)}}}}async function X8(e,t,n){let s=gn(ba,n);if(!t||!e||!(e instanceof HTMLCanvasElement))return;let r=e.getContext("2d");if(!!r){r.lineJoin="round",r.font=s.font;for(let a of t){if(s.drawBoxes&&(r.strokeStyle=s.color,r.fillStyle=s.color,md(r,a.box[0],a.box[1],a.box[2],a.box[3],s),s.drawLabels&&(s.shadowColor&&s.shadowColor!==""&&(r.fillStyle=s.shadowColor,r.fillText("hand",a.box[0]+3,1+a.box[1]+s.lineHeight,a.box[2])),r.fillStyle=s.labelColor,r.fillText("hand",a.box[0]+2,0+a.box[1]+s.lineHeight,a.box[2])),r.stroke()),s.drawPoints&&a.keypoints&&a.keypoints.length>0)for(let o of a.keypoints)r.fillStyle=s.useDepth?`rgba(${127.5+2*o[2]}, ${127.5-2*o[2]}, 255, 0.5)`:s.color,Xy(r,o[0],o[1],0,s);if(s.drawLabels){let o=(i,l)=>{r.fillStyle=s.useDepth?`rgba(${127.5+2*i[i.length-1][2]}, ${127.5-2*i[i.length-1][2]}, 255, 0.5)`:s.color,r.fillText(l,i[i.length-1][0]+4,i[i.length-1][1]+4)};r.font=s.font,o(a.annotations.index,"index"),o(a.annotations.middle,"middle"),o(a.annotations.ring,"ring"),o(a.annotations.pinky,"pinky"),o(a.annotations.thumb,"thumb"),o(a.annotations.palm,"palm")}if(s.drawPolygons){let o=i=>{if(!!i)for(let l=0;l<i.length;l++)r.beginPath(),r.strokeStyle=s.useDepth?`rgba(${127.5+2*i[l][2]}, ${127.5-2*i[l][2]}, 255, 0.5)`:s.color,r.moveTo(i[l>0?l-1:0][0],i[l>0?l-1:0][1]),r.lineTo(i[l][0],i[l][1]),r.stroke()};r.lineWidth=s.lineWidth,o(a.annotations.index),o(a.annotations.middle),o(a.annotations.ring),o(a.annotations.pinky),o(a.annotations.thumb)}}}}async function K8(e,t,n){let s=gn(ba,n);if(!t||!e||!(e instanceof HTMLCanvasElement))return;let r=e.getContext("2d");if(!!r){r.lineJoin="round",r.font=s.font;for(let a of t)if(s.drawBoxes){if(r.strokeStyle=s.color,r.fillStyle=s.color,md(r,a.box[0],a.box[1],a.box[2],a.box[3],s),s.drawLabels){let o=`${a.label} ${Math.round(100*a.score)}%`;s.shadowColor&&s.shadowColor!==""&&(r.fillStyle=s.shadowColor,r.fillText(o,a.box[0]+3,1+a.box[1]+s.lineHeight,a.box[2])),r.fillStyle=s.labelColor,r.fillText(o,a.box[0]+2,0+a.box[1]+s.lineHeight,a.box[2])}r.stroke()}}}async function Ile(e,t,n){let s=gn(ba,n);if(!t||!e||!(e instanceof HTMLCanvasElement))return;let r=e.getContext("2d");if(!!r){r.lineJoin="round",r.font=s.font;for(let a=0;a<t.length;a++)if(s.drawBoxes){if(r.strokeStyle=s.color,r.fillStyle=s.color,md(r,t[a].box[0],t[a].box[1],t[a].box[2],t[a].box[3],s),s.drawLabels){let o=`person #${a}`;s.shadowColor&&s.shadowColor!==""&&(r.fillStyle=s.shadowColor,r.fillText(o,t[a].box[0]+3,1+t[a].box[1]+s.lineHeight,t[a].box[2])),r.fillStyle=s.labelColor,r.fillText(o,t[a].box[0]+2,0+t[a].box[1]+s.lineHeight,t[a].box[2])}r.stroke()}}}async function Sle(e,t){if(!e||!t||!(e instanceof HTMLCanvasElement)||!(t instanceof HTMLCanvasElement))return;let n=e.getContext("2d");n==null||n.drawImage(e,0,0)}async function Cle(e,t,n){let s=Ye(),r=gn(ba,n);if(!t||!e||!(e instanceof HTMLCanvasElement))return null;let a=Promise.all([j8(e,t.face,r),q8(e,t.body,r),X8(e,t.hand,r),K8(e,t.object,r),G8(e,t.gesture,r)]);return t.performance.draw=Math.trunc(Ye()-s),a}function Z8(e,t,n,s,r){var i,l,u,c,d,h,p,f,m,g,A,y,x,b,v,k;let a=0,o=[];for(let S of e){let C={id:a++,face:S,body:null,hands:{left:null,right:null},gestures:[],box:[0,0,0,0]};for(let P of t)S.box[0]>P.box[0]&&S.box[0]<P.box[0]+P.box[2]&&S.box[1]+S.box[3]>P.box[1]&&S.box[1]+S.box[3]<P.box[1]+P.box[3]&&(C.body=P);if(C.body)for(let P of n)P.box[0]+P.box[2]>C.body.box[0]&&P.box[0]+P.box[2]<C.body.box[0]+C.body.box[2]&&P.box[1]+P.box[3]>C.body.box[1]&&P.box[1]+P.box[3]<C.body.box[1]+C.body.box[3]&&C.hands&&(C.hands.left=P),P.box[0]<C.body.box[0]+C.body.box[2]&&P.box[0]>C.body.box[0]&&P.box[1]+P.box[3]>C.body.box[1]&&P.box[1]+P.box[3]<C.body.box[1]+C.body.box[3]&&C.hands&&(C.hands.right=P);for(let P of s)P.face!==void 0&&P.face===S.id?(i=C.gestures)==null||i.push(P):P.iris!==void 0&&P.iris===S.id?(l=C.gestures)==null||l.push(P):P.body!==void 0&&P.body===((u=C.body)==null?void 0:u.id)?(c=C.gestures)==null||c.push(P):P.hand!==void 0&&P.hand===((h=(d=C.hands)==null?void 0:d.left)==null?void 0:h.id)?(p=C.gestures)==null||p.push(P):P.hand!==void 0&&P.hand===((m=(f=C.hands)==null?void 0:f.right)==null?void 0:m.id)&&((g=C.gestures)==null||g.push(P));let _=[],O=[],E=P=>{P&&P.length===4&&(_.push(P[0],P[0]+P[2]),O.push(P[1],P[1]+P[3]))};E((A=C.face)==null?void 0:A.box),E((y=C.body)==null?void 0:y.box),E((b=(x=C.hands)==null?void 0:x.left)==null?void 0:b.box),E((k=(v=C.hands)==null?void 0:v.right)==null?void 0:k.box);let R=Math.min(..._),T=Math.min(...O);C.box=[R,T,Math.max(..._)-R,Math.max(...O)-T],r&&r[1]&&r[2]&&(C.boxRaw=[C.box[0]/r[2],C.box[1]/r[1],C.box[2]/r[2],C.box[3]/r[1]]),o.push(C)}return o}var $e={face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0};function Y8(e){var s,r,a,o,i,l,u,c,d,h,p,f,m,g,A,y,x,b,v,k,S;if(!e)return{face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0};let t=Date.now()-e.timestamp,n=t<1e3?8-Math.log(t+1):1;if($e.canvas=e.canvas,!$e.body||e.body.length!==$e.body.length)$e.body=JSON.parse(JSON.stringify(e.body));else for(let C=0;C<e.body.length;C++){let _=e.body[C].box.map((R,T)=>((n-1)*$e.body[C].box[T]+R)/n),O=e.body[C].boxRaw.map((R,T)=>((n-1)*$e.body[C].boxRaw[T]+R)/n),E=e.body[C].keypoints.map((R,T)=>({score:R.score,part:R.part,position:[$e.body[C].keypoints[T]?((n-1)*$e.body[C].keypoints[T].position[0]+R.position[0])/n:R.position[0],$e.body[C].keypoints[T]?((n-1)*$e.body[C].keypoints[T].position[1]+R.position[1])/n:R.position[1]],positionRaw:[$e.body[C].keypoints[T]?((n-1)*$e.body[C].keypoints[T].positionRaw[0]+R.positionRaw[0])/n:R.position[0],$e.body[C].keypoints[T]?((n-1)*$e.body[C].keypoints[T].positionRaw[1]+R.positionRaw[1])/n:R.position[1]]}));$e.body[C]={...e.body[C],box:_,boxRaw:O,keypoints:E}}if(!$e.hand||e.hand.length!==$e.hand.length)$e.hand=JSON.parse(JSON.stringify(e.hand));else for(let C=0;C<e.hand.length;C++){let _=e.hand[C].box.map((P,V)=>((n-1)*$e.hand[C].box[V]+P)/n),O=e.hand[C].boxRaw.map((P,V)=>((n-1)*$e.hand[C].boxRaw[V]+P)/n),E=e.hand[C].keypoints.map((P,V)=>P.map((j,q)=>((n-1)*$e.hand[C].keypoints[V][q]+j)/n)),R=Object.keys(e.hand[C].annotations),T={};for(let P of R)T[P]=e.hand[C].annotations[P].map((V,j)=>V.map((q,X)=>((n-1)*$e.hand[C].annotations[P][j][X]+q)/n));$e.hand[C]={...e.hand[C],box:_,boxRaw:O,keypoints:E,annotations:T}}if(!$e.face||e.face.length!==$e.face.length)$e.face=JSON.parse(JSON.stringify(e.face));else for(let C=0;C<e.face.length;C++){let _=e.face[C].box.map((R,T)=>((n-1)*$e.face[C].box[T]+R)/n),O=e.face[C].boxRaw.map((R,T)=>((n-1)*$e.face[C].boxRaw[T]+R)/n),E={matrix:[0,0,0,0,0,0,0,0,0],angle:{roll:0,yaw:0,pitch:0},gaze:{bearing:0,strength:0}};E.matrix=(s=e.face[C].rotation)==null?void 0:s.matrix,E.angle={roll:((n-1)*(((a=(r=$e.face[C].rotation)==null?void 0:r.angle)==null?void 0:a.roll)||0)+(((i=(o=e.face[C].rotation)==null?void 0:o.angle)==null?void 0:i.roll)||0))/n,yaw:((n-1)*(((u=(l=$e.face[C].rotation)==null?void 0:l.angle)==null?void 0:u.yaw)||0)+(((d=(c=e.face[C].rotation)==null?void 0:c.angle)==null?void 0:d.yaw)||0))/n,pitch:((n-1)*(((p=(h=$e.face[C].rotation)==null?void 0:h.angle)==null?void 0:p.pitch)||0)+(((m=(f=e.face[C].rotation)==null?void 0:f.angle)==null?void 0:m.pitch)||0))/n},E.gaze={bearing:((n-1)*(((A=(g=$e.face[C].rotation)==null?void 0:g.gaze)==null?void 0:A.bearing)||0)+(((x=(y=e.face[C].rotation)==null?void 0:y.gaze)==null?void 0:x.bearing)||0))/n,strength:((n-1)*(((v=(b=$e.face[C].rotation)==null?void 0:b.gaze)==null?void 0:v.strength)||0)+(((S=(k=e.face[C].rotation)==null?void 0:k.gaze)==null?void 0:S.strength)||0))/n},$e.face[C]={...e.face[C],rotation:E,box:_,boxRaw:O}}if(!$e.object||e.object.length!==$e.object.length)$e.object=JSON.parse(JSON.stringify(e.object));else for(let C=0;C<e.object.length;C++){let _=e.object[C].box.map((E,R)=>((n-1)*$e.object[C].box[R]+E)/n),O=e.object[C].boxRaw.map((E,R)=>((n-1)*$e.object[C].boxRaw[R]+E)/n);$e.object[C]={...e.object[C],box:_,boxRaw:O}}if(e.persons){let C=e.persons;if(!$e.persons||C.length!==$e.persons.length)$e.persons=JSON.parse(JSON.stringify(C));else for(let _=0;_<C.length;_++)$e.persons[_].box=C[_].box.map((O,E)=>((n-1)*$e.persons[_].box[E]+O)/n)}return e.gesture&&($e.gesture=e.gesture),e.performance&&($e.performance=e.performance),$e}var Jf=`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==`,Qf=`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`;var Yy="2.1.4";var yu,Ad,yd,ii,li,xu,e0,xd,t0,n0,s0,r0,a0=class{constructor(t){as(this,yu,void 0);as(this,Ad,void 0);as(this,yd,void 0);as(this,ii,void 0);as(this,li,void 0);as(this,xu,void 0);this.analyze=(...t)=>{if(!mn(this,Ad))return;let n=this.tf.engine().state.numTensors,s=mn(this,yu);Ds(this,yu,n);let r=n-s;r!==0&&ue(...t,r)};as(this,e0,t=>{if(!mn(this,yd))return null;if(!t)return"input is not defined";if(this.tf.ENV.flags.IS_NODE&&!(t instanceof Ge))return"input must be a tensor";try{this.tf.getBackend()}catch(n){return"backend not loaded"}return null});as(this,xd,async(t=!1)=>{var n;if(this.config.backend&&this.config.backend.length>0&&t||this.tf.getBackend()!==this.config.backend){let s=Ye();if(this.state="backend",this.config.backend&&this.config.backend.length>0){if(typeof window=="undefined"&&typeof WorkerGlobalScope!="undefined"&&this.config.debug&&ue("running inside web worker"),this.tf.ENV.flags.IS_BROWSER&&this.config.backend==="tensorflow"&&(ue("override: backend set to tensorflow while running in browser"),this.config.backend="humangl"),this.tf.ENV.flags.IS_NODE&&(this.config.backend==="webgl"||this.config.backend==="humangl")&&(ue("override: backend set to webgl while running in nodejs"),this.config.backend="tensorflow"),this.tf.ENV.flags.IS_BROWSER&&this.config.backend==="webgpu")if(typeof navigator=="undefined"||typeof navigator.gpu=="undefined")ue("override: backend set to webgpu but browser does not support webgpu"),this.config.backend="humangl";else{let a=await navigator.gpu.requestAdapter();this.config.debug&&ue("enumerated webgpu adapter:",a)}this.config.backend==="humangl"&&Vk();let r=Object.keys(this.tf.engine().registryFactory);if(this.config.debug&&ue("available backends:",r),r.includes(this.config.backend)||(ue(`error: backend ${this.config.backend} not found in registry`),this.config.backend=this.tf.ENV.flags.IS_NODE?"tensorflow":"humangl",ue(`override: using backend ${this.config.backend} instead`)),this.config.debug&&ue("setting backend:",this.config.backend),this.config.backend==="wasm"){if(this.config.debug&&ue("wasm path:",this.config.wasmPath),typeof((n=this.tf)==null?void 0:n.setWasmPaths)!="undefined")this.tf.setWasmPaths(this.config.wasmPath);else throw new Error("Human: WASM backend is not loaded");let a=await this.tf.env().getAsync("WASM_HAS_SIMD_SUPPORT"),o=await this.tf.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT");this.config.debug&&ue(`wasm execution: ${a?"SIMD":"no SIMD"} ${o?"multithreaded":"singlethreaded"}`),this.config.debug&&!a&&ue("warning: wasm simd support is not enabled")}try{await this.tf.setBackend(this.config.backend)}catch(a){ue("error: cannot set backend:",this.config.backend,a)}}if(this.tf.getBackend()==="webgl"||this.tf.getBackend()==="humangl"){this.tf.ENV.set("CHECK_COMPUTATION_FOR_ERRORS",!1),this.tf.ENV.set("WEBGL_CPU_FORWARD",!0),this.tf.ENV.set("WEBGL_PACK_DEPTHWISECONV",!0),this.tf.ENV.set("WEBGL_USE_SHAPES_UNIFORMS",!0),typeof this.config.deallocate!="undefined"&&this.config.deallocate&&(ue("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",!0),this.tf.ENV.set("WEBGL_DELETE_TEXTURE_THRESHOLD",0));let r=await this.tf.backend().getGPGPUContext().gl;this.config.debug&&ue(`gl version:${r.getParameter(r.VERSION)} renderer:${r.getParameter(r.RENDERER)}`)}this.tf.enableProdMode(),await this.tf.ready(),this.performance.backend=Math.trunc(Ye()-s)}});this.next=t=>Y8(t||this.result);as(this,t0,async t=>{if(this.config.cacheSensitivity===0)return!1;let n=32;if(!t.shape[1]||!t.shape[2])return!1;let s=_e.resizeBilinear(t,[Math.trunc(t.shape[1]/n),Math.trunc(t.shape[2]/n)]),r=await s.data(),a=0;for(let l=0;l<r.length/3;l++)a+=r[3*l+2];s.dispose();let o=100*(Math.max(a,mn(this,li))/Math.min(a,mn(this,li))-1);Ds(this,li,a);let i=o<Math.max(this.config.cacheSensitivity,mn(this,xu));return Ds(this,xu,o>10*this.config.cacheSensitivity?0:o),i});as(this,n0,async()=>{let t=(r,a="application/octet-stream")=>fetch(`data:${a};base64,${r}`).then(o=>o.blob()),n,s;switch(this.config.warmup){case"face":n=await t(Jf);break;case"full":n=await t(Qf);break;default:n=null}if(n){let r=await createImageBitmap(n);s=await this.detect(r,this.config),r.close()}return s});as(this,s0,async()=>new Promise(t=>{let n,s=0;switch(this.config.warmup){case"face":s=256,n="data:image/jpeg;base64,"+Jf;break;case"full":case"body":s=1200,n="data:image/jpeg;base64,"+Qf;break;default:n=null}let r=new Image;r.onload=async()=>{let a=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(s,s):document.createElement("canvas");a.width=r.naturalWidth,a.height=r.naturalHeight;let o=a.getContext("2d");o==null||o.drawImage(r,0,0);let i=await this.detect(a,this.config);t(i)},n?r.src=n:t(null)}));as(this,r0,async()=>{let t=r=>Buffer.from(r,"base64"),n;if(this.config.warmup==="face"&&(n=t(Jf)),(this.config.warmup==="body"||this.config.warmup==="full")&&(n=t(Qf)),!n)return null;let s;if(typeof void 0!="undefined"){let r=(void 0).decodeJpeg(n),a=r.expandDims(0);this.tf.dispose(r),s=await this.detect(a,this.config),this.tf.dispose(a)}else this.config.debug&&ue("Warmup tfjs-node not loaded");return s});a0.version=Yy,Object.defineProperty(this,"version",{value:Yy}),$m.wasmPath=`https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@${_x}/dist/`,this.config=gn($m,t||{}),this.tf=od,this.draw=Zy,this.state="idle",Ds(this,yu,0),Ds(this,Ad,!1),Ds(this,yd,!1),Ds(this,ii,!0),Ds(this,xu,0),this.performance={backend:0,load:0,image:0,frames:0,cached:0,changed:0,total:0,draw:0},this.models={face:null,posenet:null,blazepose:null,efficientpose:null,movenet:null,handpose:null,age:null,gender:null,emotion:null,embedding:null,nanodet:null,centernet:null,faceres:null,segmentation:null},this.result={face:[],body:[],hand:[],gesture:[],object:[],performance:{},timestamp:0,persons:[]},this.image=n=>oi(n,this.config),this.faceTriangulation=n8,this.faceUVMap=s8,this.sysinfo=p5(),Ds(this,li,1)}similarity(t,n){return iy(t,n)}segmentation(t,n){return L8(t,n,this.config)}enhance(t){return ly(t)}match(t,n,s=0){return a8(t,n,s)}async load(t){this.state="load";let n=Ye();t&&(this.config=gn(this.config,t)),mn(this,ii)&&(this.config.debug&&ue(`version: ${a0.version}`),this.config.debug&&ue(`tfjs version: ${this.tf.version_core}`),this.config.debug&&ue("platform:",this.sysinfo.platform),this.config.debug&&ue("agent:",this.sysinfo.agent),await mn(this,xd).call(this,!0),this.tf.ENV.flags.IS_BROWSER&&(this.config.debug&&ue("configuration:",this.config),this.config.debug&&ue("tf flags:",this.tf.ENV.flags))),await B8(this),mn(this,ii)&&(this.config.debug&&ue("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),Ds(this,ii,!1));let s=Math.trunc(Ye()-n);s>(this.performance.load||0)&&(this.performance.load=s)}async detect(t,n){return new Promise(async s=>{this.state="config";let r,a;this.config=gn(this.config,n),this.state="check";let o=mn(this,e0).call(this,t);o&&(ue(o,t),s({error:o}));let i=Ye();await mn(this,xd).call(this),await this.load(),r=Ye();let l=oi(t,this.config);if(this.performance.image=Math.trunc(Ye()-r),this.analyze("Get Image:"),this.config.segmentation.enabled&&l&&l.tensor&&(this.analyze("Start Segmentation:"),this.state="run:segmentation",r=Ye(),await jy(l),a=Math.trunc(Ye()-r),a>0&&(this.performance.segmentation=a),l.canvas&&(K(l.tensor),l=oi(l.canvas,this.config)),this.analyze("End Segmentation:")),!l||!l.tensor){ue("could not convert input to tensor"),s({error:"could not convert input to tensor"});return}r=Ye(),this.config.skipFrame=await mn(this,t0).call(this,l.tensor),this.performance.frames||(this.performance.frames=0),this.performance.cached||(this.performance.cached=0),this.performance.frames++,this.config.skipFrame&&this.performance.cached++,this.performance.changed=Math.trunc(Ye()-r),this.analyze("Check Changed:");let u=[],c=[],d=[],h=[];this.config.async?(u=this.config.face.enabled?qy(this,l.tensor):[],this.performance.face&&delete this.performance.face):(this.state="run:face",r=Ye(),u=this.config.face.enabled?await qy(this,l.tensor):[],a=Math.trunc(Ye()-r),a>0&&(this.performance.face=a)),this.analyze("Start Body:"),this.config.async?(this.config.body.modelPath.includes("posenet")?c=this.config.body.enabled?xy(l.tensor,this.config):[]:this.config.body.modelPath.includes("blazepose")?c=this.config.body.enabled?Ny(l.tensor,this.config):[]:this.config.body.modelPath.includes("efficientpose")?c=this.config.body.enabled?Dy(l.tensor,this.config):[]:this.config.body.modelPath.includes("movenet")&&(c=this.config.body.enabled?Py(l.tensor,this.config):[]),this.performance.body&&delete this.performance.body):(this.state="run:body",r=Ye(),this.config.body.modelPath.includes("posenet")?c=this.config.body.enabled?await xy(l.tensor,this.config):[]:this.config.body.modelPath.includes("blazepose")?c=this.config.body.enabled?await Ny(l.tensor,this.config):[]:this.config.body.modelPath.includes("efficientpose")?c=this.config.body.enabled?await Dy(l.tensor,this.config):[]:this.config.body.modelPath.includes("movenet")&&(c=this.config.body.enabled?await Py(l.tensor,this.config):[]),a=Math.trunc(Ye()-r),a>0&&(this.performance.body=a)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.config.async?(d=this.config.hand.enabled?Cy(l.tensor,this.config):[],this.performance.hand&&delete this.performance.hand):(this.state="run:hand",r=Ye(),d=this.config.hand.enabled?await Cy(l.tensor,this.config):[],a=Math.trunc(Ye()-r),a>0&&(this.performance.hand=a)),this.analyze("End Hand:"),this.analyze("Start Object:"),this.config.async?(this.config.object.modelPath.includes("nanodet")?h=this.config.object.enabled?By(l.tensor,this.config):[]:this.config.object.modelPath.includes("centernet")&&(h=this.config.object.enabled?Hy(l.tensor,this.config):[]),this.performance.object&&delete this.performance.object):(this.state="run:object",r=Ye(),this.config.object.modelPath.includes("nanodet")?h=this.config.object.enabled?await By(l.tensor,this.config):[]:this.config.object.modelPath.includes("centernet")&&(h=this.config.object.enabled?await Hy(l.tensor,this.config):[]),a=Math.trunc(Ye()-r),a>0&&(this.performance.object=a)),this.analyze("End Object:"),this.config.async&&([u,c,d,h]=await Promise.all([u,c,d,h]));let p=[];this.config.gesture.enabled&&(r=Ye(),p=[...V8(u),...W8(c),...H8(d),...U8(u)],this.config.async?this.performance.gesture&&delete this.performance.gesture:this.performance.gesture=Math.trunc(Ye()-r)),this.performance.total=Math.trunc(Ye()-i),this.state="idle",this.result={face:u,body:c,hand:d,gesture:p,object:h,performance:this.performance,canvas:l.canvas,timestamp:Date.now(),get persons(){var f;return Z8(u,c,d,p,(f=l==null?void 0:l.tensor)==null?void 0:f.shape)}},K(l.tensor),s(this.result)})}async warmup(t){let n=Ye();if(t&&(this.config=gn(this.config,t)),!this.config.warmup||this.config.warmup==="none")return{error:"null"};let s;typeof createImageBitmap=="function"?s=await mn(this,n0).call(this):typeof Image!="undefined"?s=await mn(this,s0).call(this):s=await mn(this,r0).call(this);let r=Ye();return this.config.debug&&ue("Warmup",this.config.warmup,Math.round(r-n),"ms",s),s}},Nle=a0;yu=new WeakMap,Ad=new WeakMap,yd=new WeakMap,ii=new WeakMap,li=new WeakMap,xu=new WeakMap,e0=new WeakMap,xd=new WeakMap,t0=new WeakMap,n0=new WeakMap,s0=new WeakMap,r0=new WeakMap;export{Nle as Human,Nle as default};
/**
* @license
* Copyright 2017 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/**
* @license
* Copyright 2018 Google LLC
*
* Use of this source code is governed by an MIT-style
* license that can be found in the LICENSE file or at
* https://opensource.org/licenses/MIT.
* =============================================================================
*/
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
* =============================================================================
*/
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/**
* @license
* Copyright 2019 Google LLC
*
* Use of this source code is governed by an MIT-style
* license that can be found in the LICENSE file or at
* https://opensource.org/licenses/MIT.
* =============================================================================
*/
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
* =============================================================================
*/
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/**
* @license
* Copyright 2020 Google Inc. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/**
* @license
* Copyright 2020 Google LLC
*
* Use of this source code is governed by an MIT-style
* license that can be found in the LICENSE file or at
* https://opensource.org/licenses/MIT.
* =============================================================================
*/
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the License);
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an AS IS BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/**
* @license
* Copyright 2021 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/**
* @license
* Copyright 2021 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* https://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/** @license See the LICENSE file. */
//# sourceMappingURL=human.esm.js.map
Reference in New Issue View Git Blame Copy Permalink