mirror of https://github.com/vladmandic/human
5156 lines
1.3 MiB
5156 lines
1.3 MiB
|
|
/*
|
|
Human library
|
|
homepage: <https://github.com/vladmandic/human>
|
|
author: <https://github.com/vladmandic>'
|
|
*/
|
|
|
|
var P8=Object.create,Sh=Object.defineProperty,L8=Object.getPrototypeOf,W8=Object.prototype.hasOwnProperty,B8=Object.getOwnPropertyNames,V8=Object.getOwnPropertyDescriptor;var pf=e=>Sh(e,"__esModule",{value:!0});var q2=(e,t)=>()=>(t||(t={exports:{}},e(t.exports,t)),t.exports),xr=(e,t)=>{for(var n in t)Sh(e,n,{get:t[n],enumerable:!0})},U8=(e,t,n)=>{if(t&&typeof t=="object"||typeof t=="function")for(let r of B8(t))!W8.call(e,r)&&r!=="default"&&Sh(e,r,{get:()=>t[r],enumerable:!(n=V8(t,r))||n.enumerable});return e},Th=e=>U8(pf(Sh(e!=null?P8(L8(e)):{},"default",e&&e.__esModule&&"default"in e?{get:()=>e.default,enumerable:!0}:{value:e,enumerable:!0})),e);var X2=(e,t,n)=>{if(!t.has(e))throw TypeError("Cannot "+n)},Ne=(e,t,n)=>(X2(e,t,"read from private field"),n?n.call(e):t.get(e)),ia=(e,t,n,r)=>(X2(e,t,"write to private field"),r?r.call(e,n):t.set(e,n),n);var P6=q2(z6=>{pf(z6);xr(z6,{MediaPipeFaceMesh:()=>zg,load:()=>Jae});var zg=class{constructor(t,n,r,a){this.facePipeline=new Og(t,n,r),this.config=a}async estimateFaces(t,n){let r=await this.facePipeline.predict(t,n),a=[];for(let s of r||[]){if(s.isDisposedInternal)continue;let i=s.coords?s.coords.arraySync():[],o=i.map(h=>[h[0]/t.shape[2],h[1]/t.shape[1],h[2]/this.facePipeline.meshSize]),l={};if(i&&i.length>0)for(let h of Object.keys(Jr))l[h]=Jr[h].map(d=>i[d]);let u=s.box?[Math.max(0,s.box.startPoint[0]),Math.max(0,s.box.startPoint[1]),Math.min(t.shape[1],s.box.endPoint[0])-s.box.startPoint[0],Math.min(t.shape[2],s.box.endPoint[1])-s.box.startPoint[1]]:0,c=s.box?[Math.max(0,s.box.startPoint[0]/t.shape[2]),Math.max(0,s.box.startPoint[1]/t.shape[1]),Math.min(t.shape[1],s.box.endPoint[0]-s.box.startPoint[0])/t.shape[2],Math.min(t.shape[2],s.box.endPoint[1]-s.box.startPoint[1])/t.shape[1]]:[];a.push({confidence:s.faceConfidence||s.boxConfidence||0,boxConfidence:s.boxConfidence,faceConfidence:s.faceConfidence,box:u,mesh:i,boxRaw:c,meshRaw:o,annotations:l,image:s.image?s.image.clone():null}),s.coords&&s.coords.dispose(),s.image&&s.image.dispose()}return a}},Wi=[null,null,null];async function Jae(e){Wi=await Promise.all([!Wi[0]&&e.face.enabled?C6(e):null,!Wi[1]&&e.face.mesh.enabled?Ot(e.face.mesh.modelPath,{fromTFHub:e.face.mesh.modelPath.includes("tfhub.dev")}):null,!Wi[2]&&e.face.iris.enabled?Ot(e.face.iris.modelPath,{fromTFHub:e.face.iris.modelPath.includes("tfhub.dev")}):null]);let t=new zg(Wi[0],Wi[1],Wi[2],e);return e.face.mesh.enabled&&e.debug&&Fe(`load model: ${e.face.mesh.modelPath.match(/\/(.*)\./)[1]}`),e.face.iris.enabled&&e.debug&&Fe(`load model: ${e.face.iris.modelPath.match(/\/(.*)\./)[1]}`),t}z6.triangulation=Li});var C0=q2(i2=>{pf(i2);xr(i2,{NUM_KEYPOINTS:()=>rse,connectedPartIndices:()=>sse,partChannels:()=>ose,partIds:()=>o2,partNames:()=>nse,poseChain:()=>ise});var nse=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],rse=i2.partNames.length,o2=i2.partNames.reduce((e,t,n)=>(e[t]=n,e),{}),ase=[["leftHip","leftShoulder"],["leftElbow","leftShoulder"],["leftElbow","leftWrist"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["rightHip","rightShoulder"],["rightElbow","rightShoulder"],["rightElbow","rightWrist"],["rightHip","rightKnee"],["rightKnee","rightAnkle"],["leftShoulder","rightShoulder"],["leftHip","rightHip"]],sse=ase.map(([e,t])=>[o2[e],o2[t]]),ise=[["nose","leftEye"],["leftEye","leftEar"],["nose","rightEye"],["rightEye","rightEar"],["nose","leftShoulder"],["leftShoulder","leftElbow"],["leftElbow","leftWrist"],["leftShoulder","leftHip"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["nose","rightShoulder"],["rightShoulder","rightElbow"],["rightElbow","rightWrist"],["rightShoulder","rightHip"],["rightHip","rightKnee"],["rightKnee","rightAnkle"]],ose=["left_face","right_face","right_upper_leg_front","right_lower_leg_back","right_upper_leg_back","left_lower_leg_front","left_upper_leg_front","left_upper_leg_back","left_lower_leg_back","right_feet","right_lower_leg_front","left_feet","torso_front","torso_back","right_upper_arm_front","right_upper_arm_back","right_lower_arm_back","left_lower_arm_front","left_upper_arm_front","left_upper_arm_back","left_lower_arm_back","right_hand","right_lower_arm_front","left_hand"]});function Fe(...e){let t=new Date,n=`${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)}function K2(){let e,t;if(typeof navigator!="undefined"){let n=navigator.userAgent.match(/\(([^()]+)\)/g);n&&n[0]&&(e=n[0].match(/\(([^()]+)\)/g)[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 ${process.version}`);return{platform:e,agent:t}}var Eh={};xr(Eh,{Abs:()=>so,Acos:()=>io,Acosh:()=>oo,AdadeltaOptimizer:()=>tp,AdagradOptimizer:()=>np,AdamOptimizer:()=>rp,AdamaxOptimizer:()=>ap,Add:()=>Ra,AddN:()=>fs,All:()=>Dh,Any:()=>Oh,ArgMax:()=>ms,ArgMin:()=>yu,Asin:()=>lo,Asinh:()=>uo,Atan:()=>co,Atan2:()=>po,Atanh:()=>ho,AvgPool:()=>As,AvgPool3D:()=>gu,AvgPool3DGrad:()=>Ph,AvgPoolGrad:()=>zh,BackendWasm:()=>O3,BatchMatMul:()=>ys,BatchToSpaceND:()=>xu,Bincount:()=>Lh,BroadcastTo:()=>c5,Callback:()=>Sv,CallbackList:()=>I7,Cast:()=>gs,Ceil:()=>xs,ClipByValue:()=>Fa,Complex:()=>Wh,ComplexAbs:()=>wu,Concat:()=>fo,Conv2D:()=>ws,Conv2DBackpropFilter:()=>Bh,Conv2DBackpropInput:()=>bs,Conv3D:()=>bu,Conv3DBackpropFilterV2:()=>Vh,Conv3DBackpropInputV2:()=>Uh,Cos:()=>_s,Cosh:()=>mo,CropAndResize:()=>Ao,Cumsum:()=>vs,CustomCallback:()=>S7,DataStorage:()=>Rh,DenseBincount:()=>Hh,DepthToSpace:()=>yo,DepthwiseConv2dNative:()=>ks,DepthwiseConv2dNativeBackpropFilter:()=>jh,DepthwiseConv2dNativeBackpropInput:()=>Gh,Diag:()=>qh,Dilation2D:()=>_u,Dilation2DBackpropFilter:()=>Kh,Dilation2DBackpropInput:()=>Xh,ENV:()=>wr,EarlyStopping:()=>Ev,Elu:()=>go,EluGrad:()=>Zh,Environment:()=>l5,Equal:()=>wo,Erf:()=>xo,Exp:()=>Ns,ExpandDims:()=>bo,Expm1:()=>_o,FFT:()=>Yh,Fill:()=>vu,FlipLeftRight:()=>vo,Floor:()=>Ss,FloorDiv:()=>Ts,FromPixels:()=>dd,FusedBatchNorm:()=>Es,FusedConv2D:()=>oi,FusedDepthwiseConv2D:()=>li,GPGPUContext:()=>bp,GatherNd:()=>Io,GatherV2:()=>ko,GraphModel:()=>s6,Greater:()=>No,GreaterEqual:()=>Cs,History:()=>N7,IFFT:()=>Jh,Identity:()=>Rs,Imag:()=>Qh,InputSpec:()=>Qt,IsFinite:()=>So,IsInf:()=>To,IsNan:()=>Eo,KernelBackend:()=>fu,LRN:()=>Nu,LRNGrad:()=>td,LayerVariable:()=>w7,LayersModel:()=>ya,LeakyRelu:()=>Fs,Less:()=>Co,LessEqual:()=>Ro,LinSpace:()=>ed,Log:()=>Ms,Log1p:()=>Fo,LogSoftmax:()=>h5,LogicalAnd:()=>Mo,LogicalNot:()=>ku,LogicalOr:()=>Iu,MathBackendCPU:()=>lp,MathBackendWebGL:()=>Ll,Max:()=>$s,MaxPool:()=>Os,MaxPool3D:()=>Su,MaxPool3DGrad:()=>rd,MaxPoolGrad:()=>nd,MaxPoolWithArgmax:()=>ad,Maximum:()=>Ds,Mean:()=>zs,Min:()=>Ps,Minimum:()=>Ls,MirrorPad:()=>Tu,Mod:()=>$o,MomentumOptimizer:()=>sp,Multinomial:()=>sd,Multiply:()=>Ws,Neg:()=>Do,NonMaxSuppressionV3:()=>zo,NonMaxSuppressionV4:()=>Po,NonMaxSuppressionV5:()=>Lo,NotEqual:()=>Oo,OP_SCOPE_SUFFIX:()=>_5,OneHot:()=>Bs,OnesLike:()=>Wo,Optimizer:()=>pa,Pack:()=>Bo,PadV2:()=>Vs,Pool:()=>Qk,Pow:()=>Us,Prelu:()=>Hs,Prod:()=>Vo,RMSPropOptimizer:()=>ip,RNN:()=>Zr,Range:()=>Eu,Rank:()=>If,Real:()=>id,RealDiv:()=>Is,Reciprocal:()=>Uo,Reduction:()=>yn,Relu:()=>js,Relu6:()=>qs,Reshape:()=>Ho,ResizeBilinear:()=>Gs,ResizeBilinearGrad:()=>ld,ResizeNearestNeighbor:()=>Cu,ResizeNearestNeighborGrad:()=>od,Reverse:()=>Xs,RotateWithOffset:()=>al,Round:()=>Ks,Rsqrt:()=>Zs,SGDOptimizer:()=>uc,ScatterNd:()=>jo,Select:()=>Go,Selu:()=>qo,Sequential:()=>Kl,Sigmoid:()=>Js,Sign:()=>Zo,Sin:()=>Ys,Sinh:()=>Ko,Slice:()=>Xo,Softmax:()=>ti,Softplus:()=>Yo,SpaceToBatchND:()=>Ru,SparseToDense:()=>ud,SplitV:()=>Jo,Sqrt:()=>Qs,Square:()=>Fu,SquaredDifference:()=>ni,Step:()=>$a,StridedSlice:()=>Qo,Sub:()=>ri,Sum:()=>ei,SymbolicTensor:()=>Cr,Tan:()=>el,Tanh:()=>ai,Tensor:()=>Ge,TensorBuffer:()=>Wt,Tile:()=>Ma,TopK:()=>tl,Transform:()=>cd,Transpose:()=>si,Unique:()=>hd,Unpack:()=>nl,UnsortedSegmentSum:()=>Mu,Variable:()=>Wu,ZerosLike:()=>rl,_FusedMatMul:()=>ii,abs:()=>Bt,acos:()=>Yf,acosh:()=>Jf,add:()=>ie,addN:()=>La,all:()=>kd,any:()=>ju,argMax:()=>Gu,argMin:()=>Qf,asin:()=>em,asinh:()=>tm,atan:()=>nm,atan2:()=>rm,atanh:()=>am,avgPool:()=>Xu,avgPool3d:()=>om,backend:()=>rx,backend_util:()=>R,basicLSTMCell:()=>RN,batchNorm:()=>mi,batchNorm2d:()=>ox,batchNorm3d:()=>lx,batchNorm4d:()=>ux,batchToSpaceND:()=>Ku,bincount:()=>cx,booleanMaskAsync:()=>OE,broadcastTo:()=>Zu,browser:()=>dl,buffer:()=>Ue,callbacks:()=>nre,cast:()=>ge,ceil:()=>lm,clipByValue:()=>Sn,clone:()=>zr,complex:()=>Da,concat:()=>lt,concat1d:()=>hx,concat2d:()=>yl,concat3d:()=>dx,concat4d:()=>px,constraints:()=>q3,conv1d:()=>Nd,conv2d:()=>ua,conv2dTranspose:()=>Sd,conv3d:()=>cm,conv3dTranspose:()=>QN,copyRegisteredKernels:()=>n9,cos:()=>Yu,cosh:()=>Td,cosineWindow:()=>zm,cumsum:()=>Ed,customGrad:()=>Wr,data:()=>i6,denseBincount:()=>mx,deprecationWarn:()=>Kf,depthToSpace:()=>hm,depthwiseConv2d:()=>gl,deregisterOp:()=>are,device_util:()=>Vu,diag:()=>oS,dilation2d:()=>dm,disableDeprecationWarnings:()=>jI,dispose:()=>Me,disposeVariables:()=>GI,div:()=>be,divNoNan:()=>pm,dot:()=>Ax,dropout:()=>zx,elu:()=>xl,enableDebugMode:()=>HI,enableProdMode:()=>UI,enclosingPowerOfTwo:()=>Px,engine:()=>Pr,env:()=>J,equal:()=>Ba,erf:()=>fm,exp:()=>Jn,expandDims:()=>mn,expm1:()=>mm,eye:()=>Am,fft:()=>oc,fill:()=>Ju,findBackend:()=>Zf,findBackendFactory:()=>JI,floor:()=>wl,floorDiv:()=>vd,forceHalfFloat:()=>Kb,fused:()=>ja,gather:()=>Ai,gatherND:()=>Ox,gather_util:()=>Vf,getBackend:()=>ZI,getGradient:()=>_f,getKernel:()=>pd,getKernelsForBackend:()=>il,gpgpu_util:()=>xb,grad:()=>OS,grads:()=>zS,greater:()=>ur,greaterEqual:()=>Ua,ifft:()=>Il,imag:()=>Cd,image:()=>tt,inTopKAsync:()=>qE,initializers:()=>e7,input:()=>p7,io:()=>Nn,irfft:()=>Gd,isFinite:()=>yx,isInf:()=>gx,isNaN:()=>xx,keep:()=>Zt,kernel_impls:()=>Hr,layers:()=>d7,leakyRelu:()=>Qu,less:()=>Rd,lessEqual:()=>yi,linalg:()=>Zx,linspace:()=>wx,loadGraphModel:()=>Ot,loadLayersModel:()=>_ne,localResponseNormalization:()=>ym,log:()=>zn,log1p:()=>Fd,logSigmoid:()=>_x,logSoftmax:()=>$d,logSumExp:()=>wm,logicalAnd:()=>cr,logicalNot:()=>ec,logicalOr:()=>Dd,logicalXor:()=>Nx,losses:()=>cR,matMul:()=>Ke,math:()=>P5,max:()=>Qn,maxPool:()=>tc,maxPool3d:()=>bm,maxPoolWithArgmax:()=>Sx,maximum:()=>Br,mean:()=>Tt,memory:()=>_d,metrics:()=>kv,min:()=>_l,minimum:()=>vl,mirrorPad:()=>_m,mod:()=>vm,model:()=>wne,models:()=>Iv,moments:()=>Od,movingAverage:()=>LE,mul:()=>P,multiRNNCell:()=>dT,multinomial:()=>Tx,neg:()=>St,nextFrame:()=>op,norm:()=>Zd,notEqual:()=>xi,oneHot:()=>hl,ones:()=>Vr,onesLike:()=>Pn,op:()=>O,outerProduct:()=>yT,pad:()=>ca,pad1d:()=>wT,pad2d:()=>_T,pad3d:()=>kT,pad4d:()=>NT,pool:()=>Ex,pow:()=>ha,prelu:()=>rc,print:()=>F5,prod:()=>zd,profile:()=>kr,rand:()=>DT,randomGamma:()=>LT,randomNormal:()=>Cx,randomUniform:()=>kl,range:()=>Pd,ready:()=>KI,real:()=>ac,reciprocal:()=>Nm,registerBackend:()=>fl,registerCallbackConstructor:()=>vne,registerGradient:()=>d5,registerKernel:()=>ui,registerOp:()=>rre,regularizers:()=>Nv,relu:()=>Ur,relu6:()=>Ld,removeBackend:()=>YI,reshape:()=>G,reverse:()=>Ln,reverse1d:()=>XT,reverse2d:()=>ZT,reverse3d:()=>JT,reverse4d:()=>eE,rfft:()=>lc,round:()=>Sm,rsqrt:()=>Wd,scalar:()=>Ie,scatterND:()=>Dx,scatter_util:()=>Uf,selu:()=>Bd,separableConv2d:()=>Tm,sequential:()=>bne,serialization:()=>ae,setBackend:()=>XI,setPlatform:()=>QI,setWasmPath:()=>yY,setWasmPaths:()=>gY,setWebGLContext:()=>yp,setdiff1dAsync:()=>Rx,shared:()=>Bm,sigmoid:()=>On,sign:()=>Em,signal:()=>uR,sin:()=>Vd,sinh:()=>Ud,slice:()=>$e,slice1d:()=>Hd,slice2d:()=>Cm,slice3d:()=>jd,slice4d:()=>sc,slice_util:()=>fn,softmax:()=>ic,softplus:()=>bl,spaceToBatchND:()=>nc,sparseToDense:()=>Om,spectral:()=>lR,split:()=>Ut,sqrt:()=>an,square:()=>ht,squaredDifference:()=>qd,squeeze:()=>Ha,stack:()=>An,step:()=>Nl,stridedSlice:()=>Rm,sub:()=>we,sum:()=>Re,sumOutType:()=>yd,tan:()=>Fm,tanh:()=>Al,tensor:()=>vr,tensor1d:()=>hn,tensor2d:()=>En,tensor3d:()=>wd,tensor4d:()=>NE,tensor5d:()=>SE,tensor6d:()=>TE,tensor_util:()=>br,test_util:()=>ex,tidy:()=>B,tile:()=>Va,time:()=>qI,topk:()=>Mm,train:()=>bi,transpose:()=>ot,truncatedNormal:()=>Xd,unique:()=>Kd,unregisterGradient:()=>t9,unregisterKernel:()=>e9,unsortedSegmentSum:()=>$m,unstack:()=>hr,upcastType:()=>lr,util:()=>v,valueAndGrad:()=>PS,valueAndGrads:()=>LS,variable:()=>Fx,variableGrads:()=>bx,version:()=>Uae,version_converter:()=>rae,version_core:()=>VI,version_cpu:()=>Nw,version_layers:()=>iy,version_wasm:()=>P3,version_webgl:()=>Xb,webgl:()=>DL,webgl_util:()=>qw,where:()=>Tn,whereAsync:()=>Dm,zeros:()=>$t,zerosLike:()=>qe});var H8=Object.create,Ch=Object.defineProperty,j8=Object.getPrototypeOf,G8=Object.prototype.hasOwnProperty,q8=Object.getOwnPropertyNames,X8=Object.getOwnPropertyDescriptor,K8=e=>Ch(e,"__esModule",{value:!0}),rt=(e,t)=>()=>(t||(t={exports:{}},e(t.exports,t)),t.exports),We=(e,t)=>{for(var n in t)Ch(e,n,{get:t[n],enumerable:!0})},Z8=(e,t,n)=>{if(t&&typeof t=="object"||typeof t=="function")for(let r of q8(t))!G8.call(e,r)&&r!=="default"&&Ch(e,r,{get:()=>t[r],enumerable:!(n=X8(t,r))||n.enumerable});return e},no=e=>Z8(K8(Ch(e!=null?H8(j8(e)):{},"default",e&&e.__esModule&&"default"in e?{get:()=>e.default,enumerable:!0}:{value:e,enumerable:!0})),e),Y8=rt(()=>{}),J8=rt((e,t)=>{(function(n,r,a){function s(u){var c=this,h=l();c.next=function(){var d=2091639*c.s0+c.c*23283064365386963e-26;return c.s0=c.s1,c.s1=c.s2,c.s2=d-(c.c=d|0)},c.c=1,c.s0=h(" "),c.s1=h(" "),c.s2=h(" "),c.s0-=h(u),c.s0<0&&(c.s0+=1),c.s1-=h(u),c.s1<0&&(c.s1+=1),c.s2-=h(u),c.s2<0&&(c.s2+=1),h=null}function i(u,c){return c.c=u.c,c.s0=u.s0,c.s1=u.s1,c.s2=u.s2,c}function o(u,c){var h=new s(u),d=c&&c.state,p=h.next;return p.int32=function(){return h.next()*4294967296|0},p.double=function(){return p()+(p()*2097152|0)*11102230246251565e-32},p.quick=p,d&&(typeof d=="object"&&i(d,h),p.state=function(){return i(h,{})}),p}function l(){var u=4022871197,c=function(h){h=h.toString();for(var d=0;d<h.length;d++){u+=h.charCodeAt(d);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}r&&r.exports?r.exports=o:a&&a.amd?a(function(){return o}):this.alea=o})(e,typeof t=="object"&&t,typeof define=="function"&&define)}),Q8=rt((e,t)=>{(function(n,r,a){function s(l){var u=this,c="";u.x=0,u.y=0,u.z=0,u.w=0,u.next=function(){var d=u.x^u.x<<11;return u.x=u.y,u.y=u.z,u.z=u.w,u.w^=u.w>>>19^d^d>>>8},l===(l|0)?u.x=l:c+=l;for(var h=0;h<c.length+64;h++)u.x^=c.charCodeAt(h)|0,u.next()}function i(l,u){return u.x=l.x,u.y=l.y,u.z=l.z,u.w=l.w,u}function o(l,u){var c=new s(l),h=u&&u.state,d=function(){return(c.next()>>>0)/4294967296};return d.double=function(){do var p=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},d.int32=c.next,d.quick=d,h&&(typeof h=="object"&&i(h,c),d.state=function(){return i(c,{})}),d}r&&r.exports?r.exports=o:a&&a.amd?a(function(){return o}):this.xor128=o})(e,typeof t=="object"&&t,typeof define=="function"&&define)}),ek=rt((e,t)=>{(function(n,r,a){function s(l){var u=this,c="";u.next=function(){var d=u.x^u.x>>>2;return u.x=u.y,u.y=u.z,u.z=u.w,u.w=u.v,(u.d=u.d+362437|0)+(u.v=u.v^u.v<<4^(d^d<<1))|0},u.x=0,u.y=0,u.z=0,u.w=0,u.v=0,l===(l|0)?u.x=l:c+=l;for(var h=0;h<c.length+64;h++)u.x^=c.charCodeAt(h)|0,h==c.length&&(u.d=u.x<<10^u.x>>>4),u.next()}function i(l,u){return u.x=l.x,u.y=l.y,u.z=l.z,u.w=l.w,u.v=l.v,u.d=l.d,u}function o(l,u){var c=new s(l),h=u&&u.state,d=function(){return(c.next()>>>0)/4294967296};return d.double=function(){do var p=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},d.int32=c.next,d.quick=d,h&&(typeof h=="object"&&i(h,c),d.state=function(){return i(c,{})}),d}r&&r.exports?r.exports=o:a&&a.amd?a(function(){return o}):this.xorwow=o})(e,typeof t=="object"&&t,typeof define=="function"&&define)}),tk=rt((e,t)=>{(function(n,r,a){function s(l){var u=this;u.next=function(){var h=u.x,d=u.i,p,f,m;return p=h[d],p^=p>>>7,f=p^p<<24,p=h[d+1&7],f^=p^p>>>10,p=h[d+3&7],f^=p^p>>>3,p=h[d+4&7],f^=p^p<<7,p=h[d+7&7],p=p^p<<13,f^=p^p<<9,h[d]=f,u.i=d+1&7,f};function c(h,d){var p,f,m=[];if(d===(d|0))f=m[0]=d;else for(d=""+d,p=0;p<d.length;++p)m[p&7]=m[p&7]<<15^d.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],h.x=m,h.i=0,p=256;p>0;--p)h.next()}c(u,l)}function i(l,u){return u.x=l.x.slice(),u.i=l.i,u}function o(l,u){l==null&&(l=+new Date);var c=new s(l),h=u&&u.state,d=function(){return(c.next()>>>0)/4294967296};return d.double=function(){do var p=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},d.int32=c.next,d.quick=d,h&&(h.x&&i(h,c),d.state=function(){return i(c,{})}),d}r&&r.exports?r.exports=o:a&&a.amd?a(function(){return o}):this.xorshift7=o})(e,typeof t=="object"&&t,typeof define=="function"&&define)}),nk=rt((e,t)=>{(function(n,r,a){function s(l){var u=this;u.next=function(){var h=u.w,d=u.X,p=u.i,f,m;return u.w=h=h+1640531527|0,m=d[p+34&127],f=d[p=p+1&127],m^=m<<13,f^=f<<17,m^=m>>>15,f^=f>>>12,m=d[p]=m^f,u.i=p,m+(h^h>>>16)|0};function c(h,d){var p,f,m,A,y,g=[],b=128;for(d===(d|0)?(f=d,d=null):(d=d+"\0",f=0,b=Math.max(b,d.length)),m=0,A=-32;A<b;++A)d&&(f^=d.charCodeAt((A+32)%d.length)),A===0&&(y=f),f^=f<<10,f^=f>>>15,f^=f<<4,f^=f>>>13,A>=0&&(y=y+1640531527|0,p=g[A&127]^=f+y,m=p==0?m+1:0);for(m>=128&&(g[(d&&d.length||0)&127]=-1),m=127,A=4*128;A>0;--A)f=g[m+34&127],p=g[m=m+1&127],f^=f<<13,p^=p<<17,f^=f>>>15,p^=p>>>12,g[m]=f^p;h.w=y,h.X=g,h.i=m}c(u,l)}function i(l,u){return u.i=l.i,u.w=l.w,u.X=l.X.slice(),u}function o(l,u){l==null&&(l=+new Date);var c=new s(l),h=u&&u.state,d=function(){return(c.next()>>>0)/4294967296};return d.double=function(){do var p=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},d.int32=c.next,d.quick=d,h&&(h.X&&i(h,c),d.state=function(){return i(c,{})}),d}r&&r.exports?r.exports=o:a&&a.amd?a(function(){return o}):this.xor4096=o})(e,typeof t=="object"&&t,typeof define=="function"&&define)}),rk=rt((e,t)=>{(function(n,r,a){function s(l){var u=this,c="";u.next=function(){var d=u.b,p=u.c,f=u.d,m=u.a;return d=d<<25^d>>>7^p,p=p-f|0,f=f<<24^f>>>8^m,m=m-d|0,u.b=d=d<<20^d>>>12^p,u.c=p=p-f|0,u.d=f<<16^p>>>16^m,u.a=m-d|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 h=0;h<c.length+20;h++)u.b^=c.charCodeAt(h)|0,u.next()}function i(l,u){return u.a=l.a,u.b=l.b,u.c=l.c,u.d=l.d,u}function o(l,u){var c=new s(l),h=u&&u.state,d=function(){return(c.next()>>>0)/4294967296};return d.double=function(){do var p=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},d.int32=c.next,d.quick=d,h&&(typeof h=="object"&&i(h,c),d.state=function(){return i(c,{})}),d}r&&r.exports?r.exports=o:a&&a.amd?a(function(){return o}):this.tychei=o})(e,typeof t=="object"&&t,typeof define=="function"&&define)}),ff=rt(()=>{}),ak=rt((e,t)=>{(function(n,r){var a=this,s=256,i=6,o=52,l="random",u=r.pow(s,i),c=r.pow(2,o),h=c*2,d=s-1,p;function f(w,x,N){var S=[];x=x==!0?{entropy:!0}:x||{};var T=g(y(x.entropy?[w,_(n)]:w==null?b():w,3),S),M=new m(S),D=function(){for(var z=M.g(i),W=u,U=0;z<c;)z=(z+U)*s,W*=s,U=M.g(1);for(;z>=h;)z/=2,W/=2,U>>>=1;return(z+U)/W};return D.int32=function(){return M.g(4)|0},D.quick=function(){return M.g(4)/4294967296},D.double=D,g(_(M.S),n),(x.pass||N||function(z,W,U,H){return H&&(H.S&&A(H,M),z.state=function(){return A(M,{})}),U?(r[l]=z,W):z})(D,T,"global"in x?x.global:this==r,x.state)}r["seed"+l]=f;function m(w){var x,N=w.length,S=this,T=0,M=S.i=S.j=0,D=S.S=[];for(N||(w=[N++]);T<s;)D[T]=T++;for(T=0;T<s;T++)D[T]=D[M=d&M+w[T%N]+(x=D[T])],D[M]=x;(S.g=function(z){for(var W,U=0,H=S.i,X=S.j,j=S.S;z--;)W=j[H=d&H+1],U=U*s+j[d&(j[H]=j[X=d&X+W])+(j[X]=W)];return S.i=H,S.j=X,U})(s)}function A(w,x){return x.i=w.i,x.j=w.j,x.S=w.S.slice(),x}function y(w,x){var N=[],S=typeof w,T;if(x&&S=="object")for(T in w)try{N.push(y(w[T],x-1))}catch(M){}return N.length?N:S=="string"?w:w+"\0"}function g(w,x){for(var N=w+"",S,T=0;T<N.length;)x[d&T]=d&(S^=x[d&T]*19)+N.charCodeAt(T++);return _(x)}function b(){try{var w;return p&&(w=p.randomBytes)?w=w(s):(w=new Uint8Array(s),(a.crypto||a.msCrypto).getRandomValues(w)),_(w)}catch(S){var x=a.navigator,N=x&&x.plugins;return[+new Date,a,N,a.screen,_(n)]}}function _(w){return String.fromCharCode.apply(0,w)}if(g(r.random(),n),typeof t=="object"&&t.exports){t.exports=f;try{p=ff()}catch(w){}}else typeof define=="function"&&define.amd&&define(function(){return f})})([],Math)}),sk=rt((e,t)=>{var n=J8(),r=Q8(),a=ek(),s=tk(),i=nk(),o=rk(),l=ak();l.alea=n,l.xor128=r,l.xorwow=a,l.xorshift7=s,l.xor4096=i,l.tychei=o,t.exports=l}),ik=rt((e,t)=>{(function(n,r,a){function s(u){var c=this,h=l();c.next=function(){var d=2091639*c.s0+c.c*23283064365386963e-26;return c.s0=c.s1,c.s1=c.s2,c.s2=d-(c.c=d|0)},c.c=1,c.s0=h(" "),c.s1=h(" "),c.s2=h(" "),c.s0-=h(u),c.s0<0&&(c.s0+=1),c.s1-=h(u),c.s1<0&&(c.s1+=1),c.s2-=h(u),c.s2<0&&(c.s2+=1),h=null}function i(u,c){return c.c=u.c,c.s0=u.s0,c.s1=u.s1,c.s2=u.s2,c}function o(u,c){var h=new s(u),d=c&&c.state,p=h.next;return p.int32=function(){return h.next()*4294967296|0},p.double=function(){return p()+(p()*2097152|0)*11102230246251565e-32},p.quick=p,d&&(typeof d=="object"&&i(d,h),p.state=function(){return i(h,{})}),p}function l(){var u=4022871197,c=function(h){h=h.toString();for(var d=0;d<h.length;d++){u+=h.charCodeAt(d);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}r&&r.exports?r.exports=o:a&&a.amd?a(function(){return o}):this.alea=o})(e,typeof t=="object"&&t,typeof define=="function"&&define)}),ok=rt((e,t)=>{(function(n,r,a){function s(l){var u=this,c="";u.x=0,u.y=0,u.z=0,u.w=0,u.next=function(){var d=u.x^u.x<<11;return u.x=u.y,u.y=u.z,u.z=u.w,u.w^=u.w>>>19^d^d>>>8},l===(l|0)?u.x=l:c+=l;for(var h=0;h<c.length+64;h++)u.x^=c.charCodeAt(h)|0,u.next()}function i(l,u){return u.x=l.x,u.y=l.y,u.z=l.z,u.w=l.w,u}function o(l,u){var c=new s(l),h=u&&u.state,d=function(){return(c.next()>>>0)/4294967296};return d.double=function(){do var p=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},d.int32=c.next,d.quick=d,h&&(typeof h=="object"&&i(h,c),d.state=function(){return i(c,{})}),d}r&&r.exports?r.exports=o:a&&a.amd?a(function(){return o}):this.xor128=o})(e,typeof t=="object"&&t,typeof define=="function"&&define)}),lk=rt((e,t)=>{(function(n,r,a){function s(l){var u=this,c="";u.next=function(){var d=u.x^u.x>>>2;return u.x=u.y,u.y=u.z,u.z=u.w,u.w=u.v,(u.d=u.d+362437|0)+(u.v=u.v^u.v<<4^(d^d<<1))|0},u.x=0,u.y=0,u.z=0,u.w=0,u.v=0,l===(l|0)?u.x=l:c+=l;for(var h=0;h<c.length+64;h++)u.x^=c.charCodeAt(h)|0,h==c.length&&(u.d=u.x<<10^u.x>>>4),u.next()}function i(l,u){return u.x=l.x,u.y=l.y,u.z=l.z,u.w=l.w,u.v=l.v,u.d=l.d,u}function o(l,u){var c=new s(l),h=u&&u.state,d=function(){return(c.next()>>>0)/4294967296};return d.double=function(){do var p=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},d.int32=c.next,d.quick=d,h&&(typeof h=="object"&&i(h,c),d.state=function(){return i(c,{})}),d}r&&r.exports?r.exports=o:a&&a.amd?a(function(){return o}):this.xorwow=o})(e,typeof t=="object"&&t,typeof define=="function"&&define)}),uk=rt((e,t)=>{(function(n,r,a){function s(l){var u=this;u.next=function(){var h=u.x,d=u.i,p,f,m;return p=h[d],p^=p>>>7,f=p^p<<24,p=h[d+1&7],f^=p^p>>>10,p=h[d+3&7],f^=p^p>>>3,p=h[d+4&7],f^=p^p<<7,p=h[d+7&7],p=p^p<<13,f^=p^p<<9,h[d]=f,u.i=d+1&7,f};function c(h,d){var p,f,m=[];if(d===(d|0))f=m[0]=d;else for(d=""+d,p=0;p<d.length;++p)m[p&7]=m[p&7]<<15^d.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],h.x=m,h.i=0,p=256;p>0;--p)h.next()}c(u,l)}function i(l,u){return u.x=l.x.slice(),u.i=l.i,u}function o(l,u){l==null&&(l=+new Date);var c=new s(l),h=u&&u.state,d=function(){return(c.next()>>>0)/4294967296};return d.double=function(){do var p=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},d.int32=c.next,d.quick=d,h&&(h.x&&i(h,c),d.state=function(){return i(c,{})}),d}r&&r.exports?r.exports=o:a&&a.amd?a(function(){return o}):this.xorshift7=o})(e,typeof t=="object"&&t,typeof define=="function"&&define)}),ck=rt((e,t)=>{(function(n,r,a){function s(l){var u=this;u.next=function(){var h=u.w,d=u.X,p=u.i,f,m;return u.w=h=h+1640531527|0,m=d[p+34&127],f=d[p=p+1&127],m^=m<<13,f^=f<<17,m^=m>>>15,f^=f>>>12,m=d[p]=m^f,u.i=p,m+(h^h>>>16)|0};function c(h,d){var p,f,m,A,y,g=[],b=128;for(d===(d|0)?(f=d,d=null):(d=d+"\0",f=0,b=Math.max(b,d.length)),m=0,A=-32;A<b;++A)d&&(f^=d.charCodeAt((A+32)%d.length)),A===0&&(y=f),f^=f<<10,f^=f>>>15,f^=f<<4,f^=f>>>13,A>=0&&(y=y+1640531527|0,p=g[A&127]^=f+y,m=p==0?m+1:0);for(m>=128&&(g[(d&&d.length||0)&127]=-1),m=127,A=4*128;A>0;--A)f=g[m+34&127],p=g[m=m+1&127],f^=f<<13,p^=p<<17,f^=f>>>15,p^=p>>>12,g[m]=f^p;h.w=y,h.X=g,h.i=m}c(u,l)}function i(l,u){return u.i=l.i,u.w=l.w,u.X=l.X.slice(),u}function o(l,u){l==null&&(l=+new Date);var c=new s(l),h=u&&u.state,d=function(){return(c.next()>>>0)/4294967296};return d.double=function(){do var p=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},d.int32=c.next,d.quick=d,h&&(h.X&&i(h,c),d.state=function(){return i(c,{})}),d}r&&r.exports?r.exports=o:a&&a.amd?a(function(){return o}):this.xor4096=o})(e,typeof t=="object"&&t,typeof define=="function"&&define)}),hk=rt((e,t)=>{(function(n,r,a){function s(l){var u=this,c="";u.next=function(){var d=u.b,p=u.c,f=u.d,m=u.a;return d=d<<25^d>>>7^p,p=p-f|0,f=f<<24^f>>>8^m,m=m-d|0,u.b=d=d<<20^d>>>12^p,u.c=p=p-f|0,u.d=f<<16^p>>>16^m,u.a=m-d|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 h=0;h<c.length+20;h++)u.b^=c.charCodeAt(h)|0,u.next()}function i(l,u){return u.a=l.a,u.b=l.b,u.c=l.c,u.d=l.d,u}function o(l,u){var c=new s(l),h=u&&u.state,d=function(){return(c.next()>>>0)/4294967296};return d.double=function(){do var p=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},d.int32=c.next,d.quick=d,h&&(typeof h=="object"&&i(h,c),d.state=function(){return i(c,{})}),d}r&&r.exports?r.exports=o:a&&a.amd?a(function(){return o}):this.tychei=o})(e,typeof t=="object"&&t,typeof define=="function"&&define)}),dk=rt((e,t)=>{(function(n,r){var a=this,s=256,i=6,o=52,l="random",u=r.pow(s,i),c=r.pow(2,o),h=c*2,d=s-1,p;function f(w,x,N){var S=[];x=x==!0?{entropy:!0}:x||{};var T=g(y(x.entropy?[w,_(n)]:w==null?b():w,3),S),M=new m(S),D=function(){for(var z=M.g(i),W=u,U=0;z<c;)z=(z+U)*s,W*=s,U=M.g(1);for(;z>=h;)z/=2,W/=2,U>>>=1;return(z+U)/W};return D.int32=function(){return M.g(4)|0},D.quick=function(){return M.g(4)/4294967296},D.double=D,g(_(M.S),n),(x.pass||N||function(z,W,U,H){return H&&(H.S&&A(H,M),z.state=function(){return A(M,{})}),U?(r[l]=z,W):z})(D,T,"global"in x?x.global:this==r,x.state)}r["seed"+l]=f;function m(w){var x,N=w.length,S=this,T=0,M=S.i=S.j=0,D=S.S=[];for(N||(w=[N++]);T<s;)D[T]=T++;for(T=0;T<s;T++)D[T]=D[M=d&M+w[T%N]+(x=D[T])],D[M]=x;(S.g=function(z){for(var W,U=0,H=S.i,X=S.j,j=S.S;z--;)W=j[H=d&H+1],U=U*s+j[d&(j[H]=j[X=d&X+W])+(j[X]=W)];return S.i=H,S.j=X,U})(s)}function A(w,x){return x.i=w.i,x.j=w.j,x.S=w.S.slice(),x}function y(w,x){var N=[],S=typeof w,T;if(x&&S=="object")for(T in w)try{N.push(y(w[T],x-1))}catch(M){}return N.length?N:S=="string"?w:w+"\0"}function g(w,x){for(var N=w+"",S,T=0;T<N.length;)x[d&T]=d&(S^=x[d&T]*19)+N.charCodeAt(T++);return _(x)}function b(){try{var w;return p&&(w=p.randomBytes)?w=w(s):(w=new Uint8Array(s),(a.crypto||a.msCrypto).getRandomValues(w)),_(w)}catch(S){var x=a.navigator,N=x&&x.plugins;return[+new Date,a,N,a.screen,_(n)]}}function _(w){return String.fromCharCode.apply(0,w)}if(g(r.random(),n),typeof t=="object"&&t.exports){t.exports=f;try{p=ff()}catch(w){}}else typeof define=="function"&&define.amd&&define(function(){return f})})([],Math)}),pk=rt((e,t)=>{var n=ik(),r=ok(),a=lk(),s=uk(),i=ck(),o=hk(),l=dk();l.alea=n,l.xor128=r,l.xorwow=a,l.xorshift7=s,l.xor4096=i,l.tychei=o,t.exports=l}),pu=rt(()=>{}),fk=rt(()=>{}),mk=rt(()=>{}),Ak=rt((e,t)=>{var n=function(){var r=typeof document!="undefined"&&document.currentScript?document.currentScript.src:void 0;return typeof __filename!="undefined"&&(r=r||__filename),function(a){a=a||{};function s(){return Q.buffer!=He&&nn(Q.buffer),bn}function i(){return Q.buffer!=He&&nn(Q.buffer),It}function o(){return Q.buffer!=He&&nn(Q.buffer),_n}function l(){return Q.buffer!=He&&nn(Q.buffer),Kn}function u(){return Q.buffer!=He&&nn(Q.buffer),pn}var c=typeof a!="undefined"?a:{},h,d;c.ready=new Promise(function(I,E){h=I,d=E});var p={},f;for(f in c)c.hasOwnProperty(f)&&(p[f]=c[f]);var m=[],A="./this.program",y=function(I,E){throw E},g=!1,b=!1,_=!1,w=!1;g=typeof window=="object",b=typeof importScripts=="function",_=typeof process=="object"&&typeof process.versions=="object"&&typeof process.versions.node=="string",w=!g&&!_&&!b;var x=c.ENVIRONMENT_IS_PTHREAD||!1;x&&(He=c.buffer);var N="";function S(I){return c.locateFile?c.locateFile(I,N):N+I}var T,M,D,z,W,U;if(_){b?N=pu().dirname(N)+"/":N=__dirname+"/",T=function(I,E){return W||(W=require("fs")),U||(U=pu()),I=U.normalize(I),W.readFileSync(I,E?null:"utf8")},D=function(I){var E=T(I,!0);return E.buffer||(E=new Uint8Array(E)),me(E.buffer),E},process.argv.length>1&&(A=process.argv[1].replace(/\\/g,"/")),m=process.argv.slice(2),process.on("uncaughtException",function(I){if(!(I instanceof du))throw I}),process.on("unhandledRejection",ra),y=function(I){process.exit(I)},c.inspect=function(){return"[Emscripten Module object]"};var H;try{H=fk()}catch(I){throw console.error('The "worker_threads" module is not supported in this node.js build - perhaps a newer version is needed?'),I}global.Worker=H.Worker}else w?(typeof read!="undefined"&&(T=function(I){return read(I)}),D=function(I){var E;return typeof readbuffer=="function"?new Uint8Array(readbuffer(I)):(E=read(I,"binary"),me(typeof E=="object"),E)},typeof scriptArgs!="undefined"?m=scriptArgs:typeof arguments!="undefined"&&(m=arguments),typeof quit=="function"&&(y=function(I){quit(I)}),typeof print!="undefined"&&(typeof console=="undefined"&&(console={}),console.log=print,console.warn=console.error=typeof printErr!="undefined"?printErr:print)):(g||b)&&(b?N=self.location.href:typeof document!="undefined"&&document.currentScript&&(N=document.currentScript.src),typeof r!="undefined"&&r&&(N=r),N.indexOf("blob:")!==0?N=N.substr(0,N.lastIndexOf("/")+1):N="",_?(T=function(I,E){return W||(W=require("fs")),U||(U=pu()),I=U.normalize(I),W.readFileSync(I,E?null:"utf8")},D=function(I){var E=T(I,!0);return E.buffer||(E=new Uint8Array(E)),me(E.buffer),E}):(T=function(I){var E=new XMLHttpRequest;return E.open("GET",I,!1),E.send(null),E.responseText},b&&(D=function(I){var E=new XMLHttpRequest;return E.open("GET",I,!1),E.responseType="arraybuffer",E.send(null),new Uint8Array(E.response)}),M=function(I,E,L){var q=new XMLHttpRequest;q.open("GET",I,!0),q.responseType="arraybuffer",q.onload=function(){if(q.status==200||q.status==0&&q.response){E(q.response);return}L()},q.onerror=L,q.send(null)}),z=function(I){document.title=I});_&&typeof performance=="undefined"&&(global.performance=mk().performance);var X=c.print||console.log.bind(console),j=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&&(A=c.thisProgram),c.quit&&(y=c.quit);var ee=Atomics.load,Y=Atomics.store,se=Atomics.compareExchange,te;c.wasmBinary&&(te=c.wasmBinary);var oe=c.noExitRuntime||!0;typeof WebAssembly!="object"&&ra("no native wasm support detected");var Q,pe,le=!1,Ae;function me(I,E){I||ra("Assertion failed: "+E)}function Se(I){var E=c["_"+I];return me(E,"Cannot call unknown function "+I+", make sure it is exported"),E}function Ee(I,E,L,q,fe){var ue={string:function(In){var to=0;if(In!=null&&In!==0){var G2=(In.length<<2)+1;to=Ji(G2),st(In,to,G2)}return to},array:function(In){var to=Ji(In.length);return Qe(In,to),to}};function he(In){return E==="string"?ze(In):E==="boolean"?Boolean(In):In}var ve=Se(I),it=[],Xt=0;if(q)for(var Pt=0;Pt<q.length;Pt++){var Ta=ue[L[Pt]];Ta?(Xt===0&&(Xt=hu()),it[Pt]=Ta(q[Pt])):it[Pt]=q[Pt]}var eo=ve.apply(null,it);return eo=he(eo),Xt!==0&&Yi(Xt),eo}function Oe(I,E,L,q){L=L||[];var fe=L.every(function(he){return he==="number"}),ue=E!=="string";return ue&&fe&&!q?Se(I):function(){return Ee(I,E,L,arguments,q)}}function Le(I,E,L){for(var q=E+L,fe="";!(E>=q);){var ue=I[E++];if(!ue)return fe;if(!(ue&128)){fe+=String.fromCharCode(ue);continue}var he=I[E++]&63;if((ue&224)==192){fe+=String.fromCharCode((ue&31)<<6|he);continue}var ve=I[E++]&63;if((ue&240)==224?ue=(ue&15)<<12|he<<6|ve:ue=(ue&7)<<18|he<<12|ve<<6|I[E++]&63,ue<65536)fe+=String.fromCharCode(ue);else{var it=ue-65536;fe+=String.fromCharCode(55296|it>>10,56320|it&1023)}}return fe}function ze(I,E){return I?Le(i(),I,E):""}function at(I,E,L,q){if(!(q>0))return 0;for(var fe=L,ue=L+q-1,he=0;he<I.length;++he){var ve=I.charCodeAt(he);if(ve>=55296&&ve<=57343){var it=I.charCodeAt(++he);ve=65536+((ve&1023)<<10)|it&1023}if(ve<=127){if(L>=ue)break;E[L++]=ve}else if(ve<=2047){if(L+1>=ue)break;E[L++]=192|ve>>6,E[L++]=128|ve&63}else if(ve<=65535){if(L+2>=ue)break;E[L++]=224|ve>>12,E[L++]=128|ve>>6&63,E[L++]=128|ve&63}else{if(L+3>=ue)break;E[L++]=240|ve>>18,E[L++]=128|ve>>12&63,E[L++]=128|ve>>6&63,E[L++]=128|ve&63}}return E[L]=0,L-fe}function st(I,E,L){return at(I,i(),E,L)}function ct(I){for(var E=0,L=0;L<I.length;++L){var q=I.charCodeAt(L);q>=55296&&q<=57343&&(q=65536+((q&1023)<<10)|I.charCodeAt(++L)&1023),q<=127?++E:q<=2047?E+=2:q<=65535?E+=3:E+=4}return E}function Qe(I,E){s().set(I,E)}function At(I,E){return I%E>0&&(I+=E-I%E),I}var He,bn,It,Xn,tn,_n,Kn,Dn,pn;function nn(I){He=I,c.HEAP8=bn=new Int8Array(I),c.HEAP16=Xn=new Int16Array(I),c.HEAP32=_n=new Int32Array(I),c.HEAPU8=It=new Uint8Array(I),c.HEAPU16=tn=new Uint16Array(I),c.HEAPU32=Kn=new Uint32Array(I),c.HEAPF32=Dn=new Float32Array(I),c.HEAPF64=pn=new Float64Array(I)}var $r=c.INITIAL_MEMORY||16777216;if(x)Q=c.wasmMemory,He=c.buffer;else if(c.wasmMemory)Q=c.wasmMemory;else if(Q=new WebAssembly.Memory({initial:$r/65536,maximum:2147483648/65536,shared:!0}),!(Q.buffer instanceof SharedArrayBuffer))throw j("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"),_&&console.log("(on node you may need: --experimental-wasm-threads --experimental-wasm-bulk-memory and also use a recent version)"),Error("bad memory");Q&&(He=Q.buffer),$r=He.byteLength,nn(He);var ar,sr=[],_a=[],ta=[],va=[],Hi=[],gr=!1,ah=!1;x||_a.push({func:function(){wh()}}),x&&(gr=!0);function Y0(){if(!x){if(c.preRun)for(typeof c.preRun=="function"&&(c.preRun=[c.preRun]);c.preRun.length;)oh(c.preRun.shift());Gi(sr)}}function sh(){gr=!0,Gi(_a)}function J0(){x||Gi(ta)}function ih(){x||(ah=!0)}function vn(){if(!x){if(c.postRun)for(typeof c.postRun=="function"&&(c.postRun=[c.postRun]);c.postRun.length;)Q0(c.postRun.shift());Gi(Hi)}}function oh(I){sr.unshift(I)}function Q0(I){Hi.unshift(I)}var na=0,ka=null,us=null;function e1(I){me(!x,"addRunDependency cannot be used in a pthread worker"),na++,c.monitorRunDependencies&&c.monitorRunDependencies(na)}function t1(I){if(na--,c.monitorRunDependencies&&c.monitorRunDependencies(na),na==0&&(ka!==null&&(clearInterval(ka),ka=null),us)){var E=us;us=null,E()}}c.preloadedImages={},c.preloadedAudios={};function ra(I){c.onAbort&&c.onAbort(I),x&&console.error("Pthread aborting at "+new Error().stack),I+="",j(I),le=!0,Ae=1,I="abort("+I+"). Build with -s ASSERTIONS=1 for more info.";var E=new WebAssembly.RuntimeError(I);throw d(E),E}function lh(I,E){return String.prototype.startsWith?I.startsWith(E):I.indexOf(E)===0}var ji="data:application/octet-stream;base64,";function uh(I){return lh(I,ji)}var n1="file://";function ch(I){return lh(I,n1)}var kn="tfjs-backend-wasm-threaded-simd.wasm";uh(kn)||(kn=S(kn));function r1(I){try{if(I==kn&&te)return new Uint8Array(te);if(D)return D(I);throw"both async and sync fetching of the wasm failed"}catch(E){ra(E)}}function hh(){if(!te&&(g||b)){if(typeof fetch=="function"&&!ch(kn))return fetch(kn,{credentials:"same-origin"}).then(function(I){if(!I.ok)throw"failed to load wasm binary file at '"+kn+"'";return I.arrayBuffer()}).catch(function(){return r1(kn)});if(M)return new Promise(function(I,E){M(kn,function(L){I(new Uint8Array(L))},E)})}return Promise.resolve().then(function(){return r1(kn)})}function a1(){var I={a:X1};function E(he,ve){var it=he.exports;if(c.asm=it,ar=c.asm.F,pe=ve,!x){var Xt=Te.unusedWorkers.length;Te.unusedWorkers.forEach(function(Pt){Te.loadWasmModuleToWorker(Pt,function(){--Xt||t1("wasm-instantiate")})})}}x||e1("wasm-instantiate");function L(he){E(he.instance,he.module)}function q(he){return hh().then(function(ve){return WebAssembly.instantiate(ve,I)}).then(he,function(ve){j("failed to asynchronously prepare wasm: "+ve),ra(ve)})}function fe(){return!te&&typeof WebAssembly.instantiateStreaming=="function"&&!uh(kn)&&!ch(kn)&&typeof fetch=="function"?fetch(kn,{credentials:"same-origin"}).then(function(he){var ve=WebAssembly.instantiateStreaming(he,I);return ve.then(L,function(it){return j("wasm streaming compile failed: "+it),j("falling back to ArrayBuffer instantiation"),q(L)})}):q(L)}if(c.instantiateWasm)try{var ue=c.instantiateWasm(I,E);return ue}catch(he){return j("Module.instantiateWasm callback failed with error: "+he),!1}return fe().catch(d),{}}var dh={8991:function(I,E){setTimeout(function(){W2(I,E)},0)}};function s1(){Te.initRuntime()}function Gi(I){for(;I.length>0;){var E=I.shift();if(typeof E=="function"){E(c);continue}var L=E.func;typeof L=="number"?E.arg===void 0?ar.get(L)():ar.get(L)(E.arg):L(E.arg===void 0?null:E.arg)}}function qi(I,E){if(I<=0||I>s().length||I&!0||E<0)return-28;if(E==0)return 0;E>=2147483647&&(E=Infinity);var L=Atomics.load(o(),Qi>>2),q=0;if(L==I){var fe=Atomics.compareExchange(o(),Qi>>2,L,0);if(fe==L&&(--E,q=1,E<=0))return 1}var ue=Atomics.notify(o(),I>>2,E);if(ue>=0)return ue+q;throw"Atomics.notify returned an unexpected value "+ue}c._emscripten_futex_wake=qi;function i1(I){if(x)throw"Internal Error! killThread() can only ever be called from main application thread!";if(!I)throw"Internal Error! Null pthread_ptr in killThread!";o()[I+12>>2]=0;var E=Te.pthreads[I];E.worker.terminate(),Te.freeThreadData(E),Te.runningWorkers.splice(Te.runningWorkers.indexOf(E.worker),1),E.worker.pthread=void 0}function o1(I){if(x)throw"Internal Error! cancelThread() can only ever be called from main application thread!";if(!I)throw"Internal Error! Null pthread_ptr in cancelThread!";var E=Te.pthreads[I];E.worker.postMessage({cmd:"cancel"})}function l1(I){if(x)throw"Internal Error! cleanupThread() can only ever be called from main application thread!";if(!I)throw"Internal Error! Null pthread_ptr in cleanupThread!";o()[I+12>>2]=0;var E=Te.pthreads[I];if(E){var L=E.worker;Te.returnWorkerToPool(L)}}var Te={unusedWorkers:[],runningWorkers:[],initMainThreadBlock:function(){for(var I=8,E=0;E<I;++E)Te.allocateUnusedWorker()},initRuntime:function(){for(var I=hs(228),E=0;E<228/4;++E)l()[I/4+E]=0;o()[I+12>>2]=I;var L=I+152;o()[L>>2]=L;for(var q=hs(512),E=0;E<128;++E)l()[q/4+E]=0;Atomics.store(l(),I+100>>2,q),Atomics.store(l(),I+40>>2,I),Ih(I,!b,1),L2(I)},initWorker:function(){},pthreads:{},threadExitHandlers:[],setThreadStatus:function(){},runExitHandlers:function(){for(;Te.threadExitHandlers.length>0;)Te.threadExitHandlers.pop()();x&&Zi()&&P2()},threadExit:function(I){var E=Zi();E&&(Atomics.store(l(),E+4>>2,I),Atomics.store(l(),E+0>>2,1),Atomics.store(l(),E+56>>2,1),Atomics.store(l(),E+60>>2,0),Te.runExitHandlers(),qi(E+0,2147483647),Ih(0,0,0),x&&postMessage({cmd:"exit"}))},threadCancel:function(){Te.runExitHandlers();var I=Zi();Atomics.store(l(),I+4>>2,-1),Atomics.store(l(),I+0>>2,1),qi(I+0,2147483647),Ih(0,0,0),postMessage({cmd:"cancelDone"})},terminateAllThreads:function(){for(var I in Te.pthreads){var E=Te.pthreads[I];E&&E.worker&&Te.returnWorkerToPool(E.worker)}Te.pthreads={};for(var L=0;L<Te.unusedWorkers.length;++L){var q=Te.unusedWorkers[L];q.terminate()}Te.unusedWorkers=[];for(var L=0;L<Te.runningWorkers.length;++L){var q=Te.runningWorkers[L],E=q.pthread;Te.freeThreadData(E),q.terminate()}Te.runningWorkers=[]},freeThreadData:function(I){if(I){if(I.threadInfoStruct){var E=o()[I.threadInfoStruct+100>>2];o()[I.threadInfoStruct+100>>2]=0,cu(E),cu(I.threadInfoStruct)}I.threadInfoStruct=0,I.allocatedOwnStack&&I.stackBase&&cu(I.stackBase),I.stackBase=0,I.worker&&(I.worker.pthread=null)}},returnWorkerToPool:function(I){Te.runWithoutMainThreadQueuedCalls(function(){delete Te.pthreads[I.pthread.threadInfoStruct],Te.unusedWorkers.push(I),Te.runningWorkers.splice(Te.runningWorkers.indexOf(I),1),Te.freeThreadData(I.pthread),I.pthread=void 0})},runWithoutMainThreadQueuedCalls:function(I){o()[j2>>2]=0;try{I()}finally{o()[j2>>2]=1}},receiveObjectTransfer:function(I){},loadWasmModuleToWorker:function(I,E){I.onmessage=function(L){var q=L.data,fe=q.cmd;if(I.pthread&&(Te.currentProxiedOperationCallerThread=I.pthread.threadInfoStruct),q.targetThread&&q.targetThread!=Zi()){var ue=Te.pthreads[q.targetThread];ue?ue.worker.postMessage(L.data,q.transferList):console.error('Internal error! Worker sent a message "'+fe+'" to target pthread '+q.targetThread+", but that thread no longer exists!"),Te.currentProxiedOperationCallerThread=void 0;return}if(fe==="processQueuedMainThreadWork")cf();else if(fe==="spawnThread")gh(L.data);else if(fe==="cleanupThread")l1(q.thread);else if(fe==="killThread")i1(q.thread);else if(fe==="cancelThread")o1(q.thread);else if(fe==="loaded")I.loaded=!0,E&&E(I),I.runPthread&&(I.runPthread(),delete I.runPthread);else if(fe==="print")X("Thread "+q.threadId+": "+q.text);else if(fe==="printErr")j("Thread "+q.threadId+": "+q.text);else if(fe==="alert")alert("Thread "+q.threadId+": "+q.text);else if(fe==="exit"){var he=I.pthread&&Atomics.load(l(),I.pthread.threadInfoStruct+64>>2);he&&Te.returnWorkerToPool(I)}else if(fe==="exitProcess")try{z8(q.returnCode)}catch(ve){if(ve instanceof du)return;throw ve}else fe==="cancelDone"?Te.returnWorkerToPool(I):fe==="objectTransfer"?Te.receiveObjectTransfer(L.data):L.data.target==="setimmediate"?I.postMessage(L.data):j("worker sent an unknown command "+fe);Te.currentProxiedOperationCallerThread=void 0},I.onerror=function(L){j("pthread sent an error! "+L.filename+":"+L.lineno+": "+L.message)},_&&(I.on("message",function(L){I.onmessage({data:L})}),I.on("error",function(L){I.onerror(L)}),I.on("exit",function(L){})),I.postMessage({cmd:"load",urlOrBlob:c.mainScriptUrlOrBlob||r,wasmMemory:Q,wasmModule:pe})},allocateUnusedWorker:function(){var I=S("tfjs-backend-wasm-threaded-simd.worker.js");Te.unusedWorkers.push(new Worker(I))},getNewWorker:function(){return Te.unusedWorkers.length==0&&(Te.allocateUnusedWorker(),Te.loadWasmModuleToWorker(Te.unusedWorkers[0])),Te.unusedWorkers.length>0?Te.unusedWorkers.pop():null},busySpinWait:function(I){for(var E=performance.now()+I;performance.now()<E;);}};function u1(I,E){U2(I,E),Yi(I)}c.establishStackSpace=u1;function c1(){return oe}c.getNoExitRuntime=c1;function h1(I,E){return ar.get(I)(E)}c.invokeEntryPoint=h1;function d1(I,E,L,q){ra("Assertion failed: "+ze(I)+", at: "+[E?ze(E):"unknown filename",L,q?ze(q):"unknown function"])}function p1(I,E){var L=_main(I,E)}var cs;_?cs=function(){var I=process.hrtime();return I[0]*1e3+I[1]/1e6}:x?cs=function(){return performance.now()-c.__performance_now_clock_drift}:typeof dateNow!="undefined"?cs=dateNow:cs=function(){return performance.now()};function f1(I){return o()[O2()>>2]=I,I}function m1(I,E){if(x)return Ia(1,1,I,E)}function A1(I,E){if(I==E)postMessage({cmd:"processQueuedMainThreadWork"});else if(x)postMessage({targetThread:I,cmd:"processThreadQueue"});else{var L=Te.pthreads[I],q=L&&L.worker;if(!q)return;q.postMessage({cmd:"processThreadQueue"})}return 1}function y1(){ra()}function g1(I,E,L){var q=v1(E,L);return dh[I].apply(null,q)}function x1(I,E){}function w1(I,E,L){if(I<=0||I>s().length||I&!0)return-28;if(g){if(Atomics.load(o(),I>>2)!=E)return-6;for(var q=performance.now(),fe=q+L,ue=Atomics.exchange(o(),Qi>>2,I);;){if(q=performance.now(),q>fe)return ue=Atomics.exchange(o(),Qi>>2,0),-73;if(ue=Atomics.exchange(o(),Qi>>2,0),ue==0)break;if(cf(),Atomics.load(o(),I>>2)!=E)return-6;ue=Atomics.exchange(o(),Qi>>2,I)}return 0}else{var he=Atomics.wait(o(),I>>2,E,L);if(he==="timed-out")return-73;if(he==="not-equal")return-6;if(he==="ok")return 0;throw"Atomics.wait returned an unexpected value "+he}}function b1(I,E,L){i().copyWithin(I,E,E+L)}function _1(){return _?require("os").cpus().length:navigator.hardwareConcurrency}function Ia(I,E){for(var L=arguments.length-2,q=hu(),fe=L,ue=Ji(fe*8),he=ue>>3,ve=0;ve<L;ve++){var it=arguments[2+ve];u()[he+ve]=it}var Xt=V2(I,fe,ue,E);return Yi(q),Xt}var au=[],su=[];function v1(I,E){su.length=0;var L;for(E>>=2;L=i()[I++];){var q=L<105;q&&E&1&&E++,su.push(q?u()[E++>>1]:o()[E]),++E}return su}function k1(I,E,L){au.length=E;for(var q=L>>3,fe=0;fe<E;fe++)au[fe]=u()[q+fe];var ue=I<0,he=ue?dh[-I-1]:q1[I];return he.apply(null,au)}function I1(){return i().length}function N1(I){try{return Q.grow(I-He.byteLength+65535>>>16),nn(Q.buffer),1}catch(E){}}function S1(I){var E=I1();if(I<=E)return!1;var L=2147483648;if(I>L)return!1;for(var q=1;q<=4;q*=2){var fe=E*(1+.2/q);fe=Math.min(fe,I+100663296);var ue=Math.min(L,At(Math.max(I,fe),65536)),he=N1(ue);if(he)return!0}return!1}var Ve={inEventHandler:0,removeAllEventListeners:function(){for(var I=Ve.eventHandlers.length-1;I>=0;--I)Ve._removeHandler(I);Ve.eventHandlers=[],Ve.deferredCalls=[]},registerRemoveEventListeners:function(){Ve.removeEventListenersRegistered||(va.push(Ve.removeAllEventListeners),Ve.removeEventListenersRegistered=!0)},deferredCalls:[],deferCall:function(I,E,L){function q(he,ve){if(he.length!=ve.length)return!1;for(var it in he)if(he[it]!=ve[it])return!1;return!0}for(var fe in Ve.deferredCalls){var ue=Ve.deferredCalls[fe];if(ue.targetFunction==I&&q(ue.argsList,L))return}Ve.deferredCalls.push({targetFunction:I,precedence:E,argsList:L}),Ve.deferredCalls.sort(function(he,ve){return he.precedence<ve.precedence})},removeDeferredCalls:function(I){for(var E=0;E<Ve.deferredCalls.length;++E)Ve.deferredCalls[E].targetFunction==I&&(Ve.deferredCalls.splice(E,1),--E)},canPerformEventHandlerRequests:function(){return Ve.inEventHandler&&Ve.currentEventHandler.allowsDeferredCalls},runDeferredCalls:function(){if(Ve.canPerformEventHandlerRequests())for(var I=0;I<Ve.deferredCalls.length;++I){var E=Ve.deferredCalls[I];Ve.deferredCalls.splice(I,1),--I,E.targetFunction.apply(null,E.argsList)}},eventHandlers:[],removeAllHandlersOnTarget:function(I,E){for(var L=0;L<Ve.eventHandlers.length;++L)Ve.eventHandlers[L].target==I&&(!E||E==Ve.eventHandlers[L].eventTypeString)&&Ve._removeHandler(L--)},_removeHandler:function(I){var E=Ve.eventHandlers[I];E.target.removeEventListener(E.eventTypeString,E.eventListenerFunc,E.useCapture),Ve.eventHandlers.splice(I,1)},registerOrRemoveHandler:function(I){var E=function(q){++Ve.inEventHandler,Ve.currentEventHandler=I,Ve.runDeferredCalls(),I.handlerFunc(q),Ve.runDeferredCalls(),--Ve.inEventHandler};if(I.callbackfunc)I.eventListenerFunc=E,I.target.addEventListener(I.eventTypeString,E,I.useCapture),Ve.eventHandlers.push(I),Ve.registerRemoveEventListeners();else for(var L=0;L<Ve.eventHandlers.length;++L)Ve.eventHandlers[L].target==I.target&&Ve.eventHandlers[L].eventTypeString==I.eventTypeString&&Ve._removeHandler(L--)},queueEventHandlerOnThread_iiii:function(I,E,L,q,fe){var ue=hu(),he=Ji(12);o()[he>>2]=L,o()[he+4>>2]=q,o()[he+8>>2]=fe,hf(0,I,637534208,E,q,he),Yi(ue)},getTargetThreadForEventCallback:function(I){switch(I){case 1:return 0;case 2:return Te.currentProxiedOperationCallerThread;default:return I}},getNodeNameForTarget:function(I){return I?I==window?"#window":I==screen?"#screen":I&&I.nodeName?I.nodeName:"":""},fullscreenEnabled:function(){return document.fullscreenEnabled||document.webkitFullscreenEnabled}};function T1(I){var E=ct(I)+1,L=hs(E);return st(I,L,E),L}function E1(I,E,L,q){var fe=hu(),ue=Ji(12),he=0;E&&(he=T1(E)),o()[ue>>2]=he,o()[ue+4>>2]=L,o()[ue+8>>2]=q,hf(0,I,657457152,0,he,ue),Yi(fe)}function C1(I,E,L,q){E=E?ze(E):"",E1(I,E,L,q)}function R1(I){return I>2?ze(I):I}var F1=[0,typeof document!="undefined"?document:0,typeof window!="undefined"?window:0];function M1(I){I=R1(I);var E=F1[I]||(typeof document!="undefined"?document.querySelector(I):void 0);return E}function iu(I){return M1(I)}function ph(I,E,L){var q=iu(I);if(!q)return-4;if(q.canvasSharedPtr&&(o()[q.canvasSharedPtr>>2]=E,o()[q.canvasSharedPtr+4>>2]=L),q.offscreenCanvas||!q.controlTransferredOffscreen){q.offscreenCanvas&&(q=q.offscreenCanvas);var fe=!1;if(q.GLctxObject&&q.GLctxObject.GLctx){var ue=q.GLctxObject.GLctx.getParameter(2978);fe=ue[0]===0&&ue[1]===0&&ue[2]===q.width&&ue[3]===q.height}q.width=E,q.height=L,fe&&q.GLctxObject.GLctx.viewport(0,0,E,L)}else if(q.canvasSharedPtr){var he=o()[q.canvasSharedPtr+8>>2];return C1(he,I,E,L),1}else return-4;return 0}function fh(I,E,L){return x?Ia(2,1,I,E,L):ph(I,E,L)}function $1(I,E,L){var q=iu(I);return q?ph(I,E,L):fh(I,E,L)}function D1(I){}function O1(I,E){}function z1(I){var E=I.getExtension("ANGLE_instanced_arrays");if(E)return I.vertexAttribDivisor=function(L,q){E.vertexAttribDivisorANGLE(L,q)},I.drawArraysInstanced=function(L,q,fe,ue){E.drawArraysInstancedANGLE(L,q,fe,ue)},I.drawElementsInstanced=function(L,q,fe,ue,he){E.drawElementsInstancedANGLE(L,q,fe,ue,he)},1}function P1(I){var E=I.getExtension("OES_vertex_array_object");if(E)return I.createVertexArray=function(){return E.createVertexArrayOES()},I.deleteVertexArray=function(L){E.deleteVertexArrayOES(L)},I.bindVertexArray=function(L){E.bindVertexArrayOES(L)},I.isVertexArray=function(L){return E.isVertexArrayOES(L)},1}function L1(I){var E=I.getExtension("WEBGL_draw_buffers");if(E)return I.drawBuffers=function(L,q){E.drawBuffersWEBGL(L,q)},1}function W1(I){return!!(I.multiDrawWebgl=I.getExtension("WEBGL_multi_draw"))}var nt={counter:1,buffers:[],programs:[],framebuffers:[],renderbuffers:[],textures:[],uniforms:[],shaders:[],vaos:[],contexts:{},offscreenCanvases:{},timerQueriesEXT:[],programInfos:{},stringCache:{},unpackAlignment:4,recordError:function(I){nt.lastError||(nt.lastError=I)},getNewId:function(I){for(var E=nt.counter++,L=I.length;L<E;L++)I[L]=null;return E},getSource:function(I,E,L,q){for(var fe="",ue=0;ue<E;++ue){var he=q?o()[q+ue*4>>2]:-1;fe+=ze(o()[L+ue*4>>2],he<0?void 0:he)}return fe},createContext:function(I,E){var L=I.getContext("webgl",E);if(!L)return 0;var q=nt.registerContext(L,E);return q},registerContext:function(I,E){var L=hs(8);o()[L+4>>2]=Zi();var q={handle:L,attributes:E,version:E.majorVersion,GLctx:I};return I.canvas&&(I.canvas.GLctxObject=q),nt.contexts[L]=q,(typeof E.enableExtensionsByDefault=="undefined"||E.enableExtensionsByDefault)&&nt.initExtensions(q),L},makeContextCurrent:function(I){return nt.currentContext=nt.contexts[I],c.ctx=Na=nt.currentContext&&nt.currentContext.GLctx,!(I&&!Na)},getContext:function(I){return nt.contexts[I]},deleteContext:function(I){nt.currentContext===nt.contexts[I]&&(nt.currentContext=null),typeof Ve=="object"&&Ve.removeAllHandlersOnTarget(nt.contexts[I].GLctx.canvas),nt.contexts[I]&&nt.contexts[I].GLctx.canvas&&(nt.contexts[I].GLctx.canvas.GLctxObject=void 0),cu(nt.contexts[I].handle),nt.contexts[I]=null},initExtensions:function(I){if(I||(I=nt.currentContext),!I.initExtensionsDone){I.initExtensionsDone=!0;var E=I.GLctx;z1(E),P1(E),L1(E),E.disjointTimerQueryExt=E.getExtension("EXT_disjoint_timer_query"),W1(E);var L=E.getSupportedExtensions()||[];L.forEach(function(q){q.indexOf("lose_context")<0&&q.indexOf("debug")<0&&E.getExtension(q)})}},populateUniformTable:function(I){for(var E=nt.programs[I],L=nt.programInfos[I]={uniforms:{},maxUniformLength:0,maxAttributeLength:-1,maxUniformBlockNameLength:-1},q=L.uniforms,fe=Na.getProgramParameter(E,35718),ue=0;ue<fe;++ue){var he=Na.getActiveUniform(E,ue),ve=he.name;L.maxUniformLength=Math.max(L.maxUniformLength,ve.length+1),ve.slice(-1)=="]"&&(ve=ve.slice(0,ve.lastIndexOf("[")));var it=Na.getUniformLocation(E,ve);if(it){var Xt=nt.getNewId(nt.uniforms);q[ve]=[he.size,Xt],nt.uniforms[Xt]=it;for(var Pt=1;Pt<he.size;++Pt){var Ta=ve+"["+Pt+"]";it=Na.getUniformLocation(E,Ta),Xt=nt.getNewId(nt.uniforms),nt.uniforms[Xt]=it}}}}},B1=["default","low-power","high-performance"];function V1(I,E){var L=E>>2,q=o()[L+(24>>2)],fe={alpha:!!o()[L+(0>>2)],depth:!!o()[L+(4>>2)],stencil:!!o()[L+(8>>2)],antialias:!!o()[L+(12>>2)],premultipliedAlpha:!!o()[L+(16>>2)],preserveDrawingBuffer:!!o()[L+(20>>2)],powerPreference:B1[q],failIfMajorPerformanceCaveat:!!o()[L+(28>>2)],majorVersion:o()[L+(32>>2)],minorVersion:o()[L+(36>>2)],enableExtensionsByDefault:o()[L+(40>>2)],explicitSwapControl:o()[L+(44>>2)],proxyContextToMainThread:o()[L+(48>>2)],renderViaOffscreenBackBuffer:o()[L+(52>>2)]},ue=iu(I);if(!ue||fe.explicitSwapControl)return 0;var he=nt.createContext(ue,fe);return he}function U1(I,E){return V1(I,E)}var Xi={mappings:{},buffers:[null,[],[]],printChar:function(I,E){var L=Xi.buffers[I];E===0||E===10?((I===1?X:j)(Le(L,0)),L.length=0):L.push(E)},varargs:void 0,get:function(){Xi.varargs+=4;var I=o()[Xi.varargs-4>>2];return I},getStr:function(I){var E=ze(I);return E},get64:function(I,E){return I}};function mh(I){return x?Ia(3,1,I):0}function Ah(I,E,L,q,fe){if(x)return Ia(4,1,I,E,L,q,fe)}function yh(I,E,L,q){if(x)return Ia(5,1,I,E,L,q);for(var fe=0,ue=0;ue<L;ue++){for(var he=o()[E+ue*8>>2],ve=o()[E+(ue*8+4)>>2],it=0;it<ve;it++)Xi.printChar(I,i()[he+it]);fe+=ve}return o()[q>>2]=fe,0}function H1(I){var E=Te.threadExitHandlers.pop();I&&E()}function j1(I,E){Te.threadExitHandlers.push(function(){ar.get(I)(E)})}function gh(I){if(x)throw"Internal Error! spawnThread() can only ever be called from main application thread!";var E=Te.getNewWorker();if(E.pthread!==void 0)throw"Internal error!";if(!I.pthread_ptr)throw"Internal error, no pthread ptr!";Te.runningWorkers.push(E);for(var L=hs(128*4),q=0;q<128;++q)o()[L+q*4>>2]=0;var fe=I.stackBase+I.stackSize,ue=Te.pthreads[I.pthread_ptr]={worker:E,stackBase:I.stackBase,stackSize:I.stackSize,allocatedOwnStack:I.allocatedOwnStack,threadInfoStruct:I.pthread_ptr},he=ue.threadInfoStruct>>2;Atomics.store(l(),he+(64>>2),I.detached),Atomics.store(l(),he+(100>>2),L),Atomics.store(l(),he+(40>>2),ue.threadInfoStruct),Atomics.store(l(),he+(80>>2),I.stackSize),Atomics.store(l(),he+(76>>2),fe),Atomics.store(l(),he+(104>>2),I.stackSize),Atomics.store(l(),he+(104+8>>2),fe),Atomics.store(l(),he+(104+12>>2),I.detached);var ve=z2(),it=ve+40;Atomics.store(l(),he+(172>>2),it),E.pthread=ue;var Xt={cmd:"run",start_routine:I.startRoutine,arg:I.arg,threadInfoStruct:I.pthread_ptr,stackBase:I.stackBase,stackSize:I.stackSize};E.runPthread=function(){Xt.time=performance.now(),E.postMessage(Xt,I.transferList)},E.loaded&&(E.runPthread(),delete E.runPthread)}function G1(I,E,L,q){if(typeof SharedArrayBuffer=="undefined")return j("Current environment does not support SharedArrayBuffer, pthreads are not available!"),6;if(!I)return j("pthread_create called with a null thread pointer!"),28;var fe=[],ue=0;if(x&&(fe.length===0||ue))return B2(687865856,I,E,L,q);if(ue)return ue;var he=0,ve=0,it=0;E&&E!=-1?(he=o()[E>>2],he+=81920,ve=o()[E+8>>2],it=o()[E+12>>2]!==0):he=2097152;var Xt=ve==0;Xt?ve=H2(16,he):(ve-=he,me(ve>0));for(var Pt=hs(228),Ta=0;Ta<228>>2;++Ta)l()[(Pt>>2)+Ta]=0;o()[I>>2]=Pt,o()[Pt+12>>2]=Pt;var eo=Pt+152;o()[eo>>2]=eo;var In={stackBase:ve,stackSize:he,allocatedOwnStack:Xt,detached:it,startRoutine:L,pthread_ptr:Pt,arg:q,transferList:fe};return x?(In.cmd="spawnThread",postMessage(In,fe)):gh(In),0}function xh(I){if(x)return Ia(6,1,I);switch(I){case 30:return 16384;case 85:var E=2147483648;return E/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 f1(28),-1}x||Te.initMainThreadBlock();var Na,q1=[null,m1,fh,mh,Ah,yh,xh],X1={e:d1,r:p1,x:A1,b:y1,y:g1,j:x1,c:w1,d:qi,f:cs,p:b1,z:_1,u:k1,q:S1,v:$1,i:D1,t:O1,w:U1,m:mh,n:Ah,g:yh,o:s1,a:Q||c.wasmMemory,k:H1,l:j1,h:G1,s:xh},D2=a1(),wh=c.___wasm_call_ctors=function(){return(wh=c.___wasm_call_ctors=c.asm.A).apply(null,arguments)},K1=c._init=function(){return(K1=c._init=c.asm.B).apply(null,arguments)},Z1=c._register_tensor=function(){return(Z1=c._register_tensor=c.asm.C).apply(null,arguments)},Y1=c._dispose_data=function(){return(Y1=c._dispose_data=c.asm.D).apply(null,arguments)},J1=c._dispose=function(){return(J1=c._dispose=c.asm.E).apply(null,arguments)},Q1=c._Abs=function(){return(Q1=c._Abs=c.asm.G).apply(null,arguments)},ef=c._Add=function(){return(ef=c._Add=c.asm.H).apply(null,arguments)},tf=c._AddN=function(){return(tf=c._AddN=c.asm.I).apply(null,arguments)},nf=c._ArgMax=function(){return(nf=c._ArgMax=c.asm.J).apply(null,arguments)},rf=c._AvgPool=function(){return(rf=c._AvgPool=c.asm.K).apply(null,arguments)},af=c._BatchMatMul=function(){return(af=c._BatchMatMul=c.asm.L).apply(null,arguments)},sf=c._Ceil=function(){return(sf=c._Ceil=c.asm.M).apply(null,arguments)},of=c._ClipByValue=function(){return(of=c._ClipByValue=c.asm.N).apply(null,arguments)},lf=c._Conv2D=function(){return(lf=c._Conv2D=c.asm.O).apply(null,arguments)},bh=c._Conv2DBackpropInput=function(){return(bh=c._Conv2DBackpropInput=c.asm.P).apply(null,arguments)},_h=c._Cos=function(){return(_h=c._Cos=c.asm.Q).apply(null,arguments)},ou=c._CropAndResize=function(){return(ou=c._CropAndResize=c.asm.R).apply(null,arguments)},Ki=c._Cumsum=function(){return(Ki=c._Cumsum=c.asm.S).apply(null,arguments)},uf=c._DepthToSpace=function(){return(uf=c._DepthToSpace=c.asm.T).apply(null,arguments)},lu=c._DepthwiseConv2dNative=function(){return(lu=c._DepthwiseConv2dNative=c.asm.U).apply(null,arguments)},K=c._Equal=function(){return(K=c._Equal=c.asm.V).apply(null,arguments)},re=c._Exp=function(){return(re=c._Exp=c.asm.W).apply(null,arguments)},Ce=c._FlipLeftRight=function(){return(Ce=c._FlipLeftRight=c.asm.X).apply(null,arguments)},et=c._Floor=function(){return(et=c._Floor=c.asm.Y).apply(null,arguments)},Ct=c._FloorDiv=function(){return(Ct=c._FloorDiv=c.asm.Z).apply(null,arguments)},xt=c._FusedBatchNorm=function(){return(xt=c._FusedBatchNorm=c.asm._).apply(null,arguments)},je=c._FusedConv2D=function(){return(je=c._FusedConv2D=c.asm.$).apply(null,arguments)},Xe=c._FusedDepthwiseConv2D=function(){return(Xe=c._FusedDepthwiseConv2D=c.asm.aa).apply(null,arguments)},rn=c._Gather=function(){return(rn=c._Gather=c.asm.ba).apply(null,arguments)},aa=c._GatherNd=function(){return(aa=c._GatherNd=c.asm.ca).apply(null,arguments)},sa=c._Greater=function(){return(sa=c._Greater=c.asm.da).apply(null,arguments)},vh=c._GreaterEqual=function(){return(vh=c._GreaterEqual=c.asm.ea).apply(null,arguments)},uu=c._LeakyRelu=function(){return(uu=c._LeakyRelu=c.asm.fa).apply(null,arguments)},Zn=c._Less=function(){return(Zn=c._Less=c.asm.ga).apply(null,arguments)},Sa=c._LessEqual=function(){return(Sa=c._LessEqual=c.asm.ha).apply(null,arguments)},kh=c._Log=function(){return(kh=c._Log=c.asm.ia).apply(null,arguments)},G4=c._LogicalAnd=function(){return(G4=c._LogicalAnd=c.asm.ja).apply(null,arguments)},q4=c._Max=function(){return(q4=c._Max=c.asm.ka).apply(null,arguments)},X4=c._MaxPool=function(){return(X4=c._MaxPool=c.asm.la).apply(null,arguments)},K4=c._Maximum=function(){return(K4=c._Maximum=c.asm.ma).apply(null,arguments)},Z4=c._Mean=function(){return(Z4=c._Mean=c.asm.na).apply(null,arguments)},Y4=c._Min=function(){return(Y4=c._Min=c.asm.oa).apply(null,arguments)},J4=c._Minimum=function(){return(J4=c._Minimum=c.asm.pa).apply(null,arguments)},Q4=c._Multiply=function(){return(Q4=c._Multiply=c.asm.qa).apply(null,arguments)},e8=c._Neg=function(){return(e8=c._Neg=c.asm.ra).apply(null,arguments)},t8=c._NonMaxSuppressionV3=function(){return(t8=c._NonMaxSuppressionV3=c.asm.sa).apply(null,arguments)},n8=c._NonMaxSuppressionV4=function(){return(n8=c._NonMaxSuppressionV4=c.asm.ta).apply(null,arguments)},r8=c._NonMaxSuppressionV5=function(){return(r8=c._NonMaxSuppressionV5=c.asm.ua).apply(null,arguments)},a8=c._NotEqual=function(){return(a8=c._NotEqual=c.asm.va).apply(null,arguments)},s8=c._OneHot=function(){return(s8=c._OneHot=c.asm.wa).apply(null,arguments)},i8=c._PadV2=function(){return(i8=c._PadV2=c.asm.xa).apply(null,arguments)},o8=c._Pow=function(){return(o8=c._Pow=c.asm.ya).apply(null,arguments)},l8=c._Prelu=function(){return(l8=c._Prelu=c.asm.za).apply(null,arguments)},u8=c._Prod=function(){return(u8=c._Prod=c.asm.Aa).apply(null,arguments)},c8=c._RealDiv=function(){return(c8=c._RealDiv=c.asm.Ba).apply(null,arguments)},h8=c._Relu=function(){return(h8=c._Relu=c.asm.Ca).apply(null,arguments)},d8=c._Relu6=function(){return(d8=c._Relu6=c.asm.Da).apply(null,arguments)},p8=c._ResizeBilinear=function(){return(p8=c._ResizeBilinear=c.asm.Ea).apply(null,arguments)},f8=c._Reverse=function(){return(f8=c._Reverse=c.asm.Fa).apply(null,arguments)},m8=c._RotateWithOffset=function(){return(m8=c._RotateWithOffset=c.asm.Ga).apply(null,arguments)},A8=c._Round=function(){return(A8=c._Round=c.asm.Ha).apply(null,arguments)},y8=c._Rsqrt=function(){return(y8=c._Rsqrt=c.asm.Ia).apply(null,arguments)},g8=c._ScatterNd=function(){return(g8=c._ScatterNd=c.asm.Ja).apply(null,arguments)},x8=c._SelectV2=function(){return(x8=c._SelectV2=c.asm.Ka).apply(null,arguments)},w8=c._Sigmoid=function(){return(w8=c._Sigmoid=c.asm.La).apply(null,arguments)},b8=c._Sin=function(){return(b8=c._Sin=c.asm.Ma).apply(null,arguments)},_8=c._Softmax=function(){return(_8=c._Softmax=c.asm.Na).apply(null,arguments)},v8=c._Sqrt=function(){return(v8=c._Sqrt=c.asm.Oa).apply(null,arguments)},k8=c._Square=function(){return(k8=c._Square=c.asm.Pa).apply(null,arguments)},I8=c._SquaredDifference=function(){return(I8=c._SquaredDifference=c.asm.Qa).apply(null,arguments)},N8=c._Step=function(){return(N8=c._Step=c.asm.Ra).apply(null,arguments)},S8=c._StridedSlice=function(){return(S8=c._StridedSlice=c.asm.Sa).apply(null,arguments)},T8=c._Sub=function(){return(T8=c._Sub=c.asm.Ta).apply(null,arguments)},E8=c._Sum=function(){return(E8=c._Sum=c.asm.Ua).apply(null,arguments)},C8=c._Tanh=function(){return(C8=c._Tanh=c.asm.Va).apply(null,arguments)},R8=c._Tile=function(){return(R8=c._Tile=c.asm.Wa).apply(null,arguments)},F8=c._TopK=function(){return(F8=c._TopK=c.asm.Xa).apply(null,arguments)},M8=c._Transpose=function(){return(M8=c._Transpose=c.asm.Ya).apply(null,arguments)},$8=c.__FusedMatMul=function(){return($8=c.__FusedMatMul=c.asm.Za).apply(null,arguments)},hs=c._malloc=function(){return(hs=c._malloc=c.asm._a).apply(null,arguments)},cu=c._free=function(){return(cu=c._free=c.asm.$a).apply(null,arguments)},O2=c.___errno_location=function(){return(O2=c.___errno_location=c.asm.ab).apply(null,arguments)},z2=c._emscripten_get_global_libc=function(){return(z2=c._emscripten_get_global_libc=c.asm.bb).apply(null,arguments)},Zi=c._pthread_self=function(){return(Zi=c._pthread_self=c.asm.cb).apply(null,arguments)},P2=c.___pthread_tsd_run_dtors=function(){return(P2=c.___pthread_tsd_run_dtors=c.asm.db).apply(null,arguments)},cf=c._emscripten_main_thread_process_queued_calls=function(){return(cf=c._emscripten_main_thread_process_queued_calls=c.asm.eb).apply(null,arguments)},D8=c._emscripten_current_thread_process_queued_calls=function(){return(D8=c._emscripten_current_thread_process_queued_calls=c.asm.fb).apply(null,arguments)},L2=c._emscripten_register_main_browser_thread_id=function(){return(L2=c._emscripten_register_main_browser_thread_id=c.asm.gb).apply(null,arguments)},W2=c.__emscripten_do_dispatch_to_thread=function(){return(W2=c.__emscripten_do_dispatch_to_thread=c.asm.hb).apply(null,arguments)},B2=c._emscripten_sync_run_in_main_thread_4=function(){return(B2=c._emscripten_sync_run_in_main_thread_4=c.asm.ib).apply(null,arguments)},V2=c._emscripten_run_in_main_runtime_thread_js=function(){return(V2=c._emscripten_run_in_main_runtime_thread_js=c.asm.jb).apply(null,arguments)},hf=c.__emscripten_call_on_thread=function(){return(hf=c.__emscripten_call_on_thread=c.asm.kb).apply(null,arguments)},O8=c._emscripten_tls_init=function(){return(O8=c._emscripten_tls_init=c.asm.lb).apply(null,arguments)},Ih=c.__emscripten_thread_init=function(){return(Ih=c.__emscripten_thread_init=c.asm.mb).apply(null,arguments)},hu=c.stackSave=function(){return(hu=c.stackSave=c.asm.nb).apply(null,arguments)},Yi=c.stackRestore=function(){return(Yi=c.stackRestore=c.asm.ob).apply(null,arguments)},Ji=c.stackAlloc=function(){return(Ji=c.stackAlloc=c.asm.pb).apply(null,arguments)},U2=c._emscripten_stack_set_limits=function(){return(U2=c._emscripten_stack_set_limits=c.asm.qb).apply(null,arguments)},H2=c._memalign=function(){return(H2=c._memalign=c.asm.rb).apply(null,arguments)},j2=c.__emscripten_allow_main_runtime_queued_calls=9880,Qi=c.__emscripten_main_thread_futex=11368;c.cwrap=Oe,c.PThread=Te,c.PThread=Te,c.wasmMemory=Q,c.ExitStatus=du;var Nh;function du(I){this.name="ExitStatus",this.message="Program terminated with exit("+I+")",this.status=I}us=function I(){Nh||df(),Nh||(us=I)};function df(I){if(I=I||m,na>0)return;if(x){h(c),postMessage({cmd:"loaded"});return}if(Y0(),na>0)return;function E(){Nh||(Nh=!0,c.calledRun=!0,!le&&(sh(),J0(),h(c),c.onRuntimeInitialized&&c.onRuntimeInitialized(),vn()))}c.setStatus?(c.setStatus("Running..."),setTimeout(function(){setTimeout(function(){c.setStatus("")},1),E()},1)):E()}c.run=df;function z8(I,E){if(!(E&&oe&&I===0)){if(!E&&x)throw postMessage({cmd:"exitProcess",returnCode:I}),new du(I);oe||(Te.terminateAllThreads(),Ae=I,ih(),c.onExit&&c.onExit(I),le=!0),y(I,new du(I))}}if(c.preInit)for(typeof c.preInit=="function"&&(c.preInit=[c.preInit]);c.preInit.length>0;)c.preInit.pop()();return x&&(oe=!1,Te.initWorker()),df(),a.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)}),yk=rt((e,t)=>{var n=function(){var r=typeof document!="undefined"&&document.currentScript?document.currentScript.src:void 0;return typeof __filename!="undefined"&&(r=r||__filename),function(a){a=a||{};var s=typeof a!="undefined"?a:{},i,o;s.ready=new Promise(function(K,re){i=K,o=re});var l={},u;for(u in s)s.hasOwnProperty(u)&&(l[u]=s[u]);var c=[],h="./this.program",d=function(K,re){throw re},p=!1,f=!1,m=!1,A=!1;p=typeof window=="object",f=typeof importScripts=="function",m=typeof process=="object"&&typeof process.versions=="object"&&typeof process.versions.node=="string",A=!p&&!m&&!f;var y="";function g(K){return s.locateFile?s.locateFile(K,y):y+K}var b,_,w,x,N,S;m?(f?y=pu().dirname(y)+"/":y=__dirname+"/",b=function(K,re){return N||(N=require("fs")),S||(S=pu()),K=S.normalize(K),N.readFileSync(K,re?null:"utf8")},w=function(K){var re=b(K,!0);return re.buffer||(re=new Uint8Array(re)),X(re.buffer),re},process.argv.length>1&&(h=process.argv[1].replace(/\\/g,"/")),c=process.argv.slice(2),process.on("uncaughtException",function(K){if(!(K instanceof uf))throw K}),process.on("unhandledRejection",gr),d=function(K){process.exit(K)},s.inspect=function(){return"[Emscripten Module object]"}):A?(typeof read!="undefined"&&(b=function(K){return read(K)}),w=function(K){var re;return typeof readbuffer=="function"?new Uint8Array(readbuffer(K)):(re=read(K,"binary"),X(typeof re=="object"),re)},typeof scriptArgs!="undefined"?c=scriptArgs:typeof arguments!="undefined"&&(c=arguments),typeof quit=="function"&&(d=function(K){quit(K)}),typeof print!="undefined"&&(typeof console=="undefined"&&(console={}),console.log=print,console.warn=console.error=typeof printErr!="undefined"?printErr:print)):(p||f)&&(f?y=self.location.href:typeof document!="undefined"&&document.currentScript&&(y=document.currentScript.src),r&&(y=r),y.indexOf("blob:")!==0?y=y.substr(0,y.lastIndexOf("/")+1):y="",b=function(K){var re=new XMLHttpRequest;return re.open("GET",K,!1),re.send(null),re.responseText},f&&(w=function(K){var re=new XMLHttpRequest;return re.open("GET",K,!1),re.responseType="arraybuffer",re.send(null),new Uint8Array(re.response)}),_=function(K,re,Ce){var et=new XMLHttpRequest;et.open("GET",K,!0),et.responseType="arraybuffer",et.onload=function(){if(et.status==200||et.status==0&&et.response){re(et.response);return}Ce()},et.onerror=Ce,et.send(null)},x=function(K){document.title=K});var T=s.print||console.log.bind(console),M=s.printErr||console.warn.bind(console);for(u in l)l.hasOwnProperty(u)&&(s[u]=l[u]);l=null,s.arguments&&(c=s.arguments),s.thisProgram&&(h=s.thisProgram),s.quit&&(d=s.quit);var D;s.wasmBinary&&(D=s.wasmBinary);var z=s.noExitRuntime||!0;typeof WebAssembly!="object"&&gr("no native wasm support detected");var W,U=!1,H;function X(K,re){K||gr("Assertion failed: "+re)}function j(K){var re=s["_"+K];return X(re,"Cannot call unknown function "+K+", make sure it is exported"),re}function ee(K,re,Ce,et,Ct){var xt={string:function(Zn){var Sa=0;if(Zn!=null&&Zn!==0){var kh=(Zn.length<<2)+1;Sa=ou(kh),pe(Zn,Sa,kh)}return Sa},array:function(Zn){var Sa=ou(Zn.length);return le(Zn,Sa),Sa}};function je(Zn){return re==="string"?oe(Zn):re==="boolean"?Boolean(Zn):Zn}var Xe=j(K),rn=[],aa=0;if(et)for(var sa=0;sa<et.length;sa++){var vh=xt[Ce[sa]];vh?(aa===0&&(aa=bh()),rn[sa]=vh(et[sa])):rn[sa]=et[sa]}var uu=Xe.apply(null,rn);return uu=je(uu),aa!==0&&_h(aa),uu}function Y(K,re,Ce,et){Ce=Ce||[];var Ct=Ce.every(function(je){return je==="number"}),xt=re!=="string";return xt&&Ct&&!et?j(K):function(){return ee(K,re,Ce,arguments,et)}}var se=typeof TextDecoder!="undefined"?new TextDecoder("utf8"):void 0;function te(K,re,Ce){for(var et=re+Ce,Ct=re;K[Ct]&&!(Ct>=et);)++Ct;if(Ct-re>16&&K.subarray&&se)return se.decode(K.subarray(re,Ct));for(var xt="";re<Ct;){var je=K[re++];if(!(je&128)){xt+=String.fromCharCode(je);continue}var Xe=K[re++]&63;if((je&224)==192){xt+=String.fromCharCode((je&31)<<6|Xe);continue}var rn=K[re++]&63;if((je&240)==224?je=(je&15)<<12|Xe<<6|rn:je=(je&7)<<18|Xe<<12|rn<<6|K[re++]&63,je<65536)xt+=String.fromCharCode(je);else{var aa=je-65536;xt+=String.fromCharCode(55296|aa>>10,56320|aa&1023)}}return xt}function oe(K,re){return K?te(Ee,K,re):""}function Q(K,re,Ce,et){if(!(et>0))return 0;for(var Ct=Ce,xt=Ce+et-1,je=0;je<K.length;++je){var Xe=K.charCodeAt(je);if(Xe>=55296&&Xe<=57343){var rn=K.charCodeAt(++je);Xe=65536+((Xe&1023)<<10)|rn&1023}if(Xe<=127){if(Ce>=xt)break;re[Ce++]=Xe}else if(Xe<=2047){if(Ce+1>=xt)break;re[Ce++]=192|Xe>>6,re[Ce++]=128|Xe&63}else if(Xe<=65535){if(Ce+2>=xt)break;re[Ce++]=224|Xe>>12,re[Ce++]=128|Xe>>6&63,re[Ce++]=128|Xe&63}else{if(Ce+3>=xt)break;re[Ce++]=240|Xe>>18,re[Ce++]=128|Xe>>12&63,re[Ce++]=128|Xe>>6&63,re[Ce++]=128|Xe&63}}return re[Ce]=0,Ce-Ct}function pe(K,re,Ce){return Q(K,Ee,re,Ce)}function le(K,re){Se.set(K,re)}function Ae(K,re){return K%re>0&&(K+=re-K%re),K}var me,Se,Ee,Oe,Le,ze,at,st,ct;function Qe(K){me=K,s.HEAP8=Se=new Int8Array(K),s.HEAP16=Oe=new Int16Array(K),s.HEAP32=ze=new Int32Array(K),s.HEAPU8=Ee=new Uint8Array(K),s.HEAPU16=Le=new Uint16Array(K),s.HEAPU32=at=new Uint32Array(K),s.HEAPF32=st=new Float32Array(K),s.HEAPF64=ct=new Float64Array(K)}var At=s.INITIAL_MEMORY||16777216,He,bn=[],It=[],Xn=[],tn=[],_n=!1;It.push({func:function(){hh()}});function Kn(){if(s.preRun)for(typeof s.preRun=="function"&&(s.preRun=[s.preRun]);s.preRun.length;)$r(s.preRun.shift());ka(bn)}function Dn(){_n=!0,ka(It)}function pn(){ka(Xn)}function nn(){if(s.postRun)for(typeof s.postRun=="function"&&(s.postRun=[s.postRun]);s.postRun.length;)ar(s.postRun.shift());ka(tn)}function $r(K){bn.unshift(K)}function ar(K){tn.unshift(K)}var sr=0,_a=null,ta=null;function va(K){sr++,s.monitorRunDependencies&&s.monitorRunDependencies(sr)}function Hi(K){if(sr--,s.monitorRunDependencies&&s.monitorRunDependencies(sr),sr==0&&(_a!==null&&(clearInterval(_a),_a=null),ta)){var re=ta;ta=null,re()}}s.preloadedImages={},s.preloadedAudios={};function gr(K){s.onAbort&&s.onAbort(K),K+="",M(K),U=!0,H=1,K="abort("+K+"). Build with -s ASSERTIONS=1 for more info.";var re=new WebAssembly.RuntimeError(K);throw o(re),re}function ah(K,re){return String.prototype.startsWith?K.startsWith(re):K.indexOf(re)===0}var Y0="data:application/octet-stream;base64,";function sh(K){return ah(K,Y0)}var J0="file://";function ih(K){return ah(K,J0)}var vn="tfjs-backend-wasm.wasm";sh(vn)||(vn=g(vn));function oh(K){try{if(K==vn&&D)return new Uint8Array(D);if(w)return w(K);throw"both async and sync fetching of the wasm failed"}catch(re){gr(re)}}function Q0(){if(!D&&(p||f)){if(typeof fetch=="function"&&!ih(vn))return fetch(vn,{credentials:"same-origin"}).then(function(K){if(!K.ok)throw"failed to load wasm binary file at '"+vn+"'";return K.arrayBuffer()}).catch(function(){return oh(vn)});if(_)return new Promise(function(K,re){_(vn,function(Ce){K(new Uint8Array(Ce))},re)})}return Promise.resolve().then(function(){return oh(vn)})}function na(){var K={a:kn};function re(je,Xe){var rn=je.exports;s.asm=rn,W=s.asm.g,Qe(W.buffer),He=s.asm.m,Hi("wasm-instantiate")}va("wasm-instantiate");function Ce(je){re(je.instance)}function et(je){return Q0().then(function(Xe){return WebAssembly.instantiate(Xe,K)}).then(je,function(Xe){M("failed to asynchronously prepare wasm: "+Xe),gr(Xe)})}function Ct(){return!D&&typeof WebAssembly.instantiateStreaming=="function"&&!sh(vn)&&!ih(vn)&&typeof fetch=="function"?fetch(vn,{credentials:"same-origin"}).then(function(je){var Xe=WebAssembly.instantiateStreaming(je,K);return Xe.then(Ce,function(rn){return M("wasm streaming compile failed: "+rn),M("falling back to ArrayBuffer instantiation"),et(Ce)})}):et(Ce)}if(s.instantiateWasm)try{var xt=s.instantiateWasm(K,re);return xt}catch(je){return M("Module.instantiateWasm callback failed with error: "+je),!1}return Ct().catch(o),{}}function ka(K){for(;K.length>0;){var re=K.shift();if(typeof re=="function"){re(s);continue}var Ce=re.func;typeof Ce=="number"?re.arg===void 0?He.get(Ce)():He.get(Ce)(re.arg):Ce(re.arg===void 0?null:re.arg)}}function us(){gr()}function e1(K,re,Ce){Ee.copyWithin(K,re,re+Ce)}function t1(){return Ee.length}function ra(K){try{return W.grow(K-me.byteLength+65535>>>16),Qe(W.buffer),1}catch(re){}}function lh(K){var re=t1(),Ce=2147483648;if(K>Ce)return!1;for(var et=1;et<=4;et*=2){var Ct=re*(1+.2/et);Ct=Math.min(Ct,K+100663296);var xt=Math.min(Ce,Ae(Math.max(K,Ct),65536)),je=ra(xt);if(je)return!0}return!1}var ji={mappings:{},buffers:[null,[],[]],printChar:function(K,re){var Ce=ji.buffers[K];re===0||re===10?((K===1?T:M)(te(Ce,0)),Ce.length=0):Ce.push(re)},varargs:void 0,get:function(){ji.varargs+=4;var K=ze[ji.varargs-4>>2];return K},getStr:function(K){var re=oe(K);return re},get64:function(K,re){return K}};function uh(K){return 0}function n1(K,re,Ce,et,Ct){}function ch(K,re,Ce,et){for(var Ct=0,xt=0;xt<Ce;xt++){for(var je=ze[re+xt*8>>2],Xe=ze[re+(xt*8+4)>>2],rn=0;rn<Xe;rn++)ji.printChar(K,Ee[je+rn]);Ct+=Xe}return ze[et>>2]=Ct,0}var kn={a:us,d:e1,e:lh,f:uh,c:n1,b:ch},r1=na(),hh=s.___wasm_call_ctors=function(){return(hh=s.___wasm_call_ctors=s.asm.h).apply(null,arguments)},a1=s._init=function(){return(a1=s._init=s.asm.i).apply(null,arguments)},dh=s._register_tensor=function(){return(dh=s._register_tensor=s.asm.j).apply(null,arguments)},s1=s._dispose_data=function(){return(s1=s._dispose_data=s.asm.k).apply(null,arguments)},Gi=s._dispose=function(){return(Gi=s._dispose=s.asm.l).apply(null,arguments)},qi=s._Abs=function(){return(qi=s._Abs=s.asm.n).apply(null,arguments)},i1=s._Add=function(){return(i1=s._Add=s.asm.o).apply(null,arguments)},o1=s._AddN=function(){return(o1=s._AddN=s.asm.p).apply(null,arguments)},l1=s._ArgMax=function(){return(l1=s._ArgMax=s.asm.q).apply(null,arguments)},Te=s._AvgPool=function(){return(Te=s._AvgPool=s.asm.r).apply(null,arguments)},u1=s._BatchMatMul=function(){return(u1=s._BatchMatMul=s.asm.s).apply(null,arguments)},c1=s._Ceil=function(){return(c1=s._Ceil=s.asm.t).apply(null,arguments)},h1=s._ClipByValue=function(){return(h1=s._ClipByValue=s.asm.u).apply(null,arguments)},d1=s._Conv2D=function(){return(d1=s._Conv2D=s.asm.v).apply(null,arguments)},p1=s._Conv2DBackpropInput=function(){return(p1=s._Conv2DBackpropInput=s.asm.w).apply(null,arguments)},cs=s._Cos=function(){return(cs=s._Cos=s.asm.x).apply(null,arguments)},f1=s._CropAndResize=function(){return(f1=s._CropAndResize=s.asm.y).apply(null,arguments)},m1=s._Cumsum=function(){return(m1=s._Cumsum=s.asm.z).apply(null,arguments)},A1=s._DepthToSpace=function(){return(A1=s._DepthToSpace=s.asm.A).apply(null,arguments)},y1=s._DepthwiseConv2dNative=function(){return(y1=s._DepthwiseConv2dNative=s.asm.B).apply(null,arguments)},g1=s._Equal=function(){return(g1=s._Equal=s.asm.C).apply(null,arguments)},x1=s._Exp=function(){return(x1=s._Exp=s.asm.D).apply(null,arguments)},w1=s._FlipLeftRight=function(){return(w1=s._FlipLeftRight=s.asm.E).apply(null,arguments)},b1=s._Floor=function(){return(b1=s._Floor=s.asm.F).apply(null,arguments)},_1=s._FloorDiv=function(){return(_1=s._FloorDiv=s.asm.G).apply(null,arguments)},Ia=s._FusedBatchNorm=function(){return(Ia=s._FusedBatchNorm=s.asm.H).apply(null,arguments)},au=s._FusedConv2D=function(){return(au=s._FusedConv2D=s.asm.I).apply(null,arguments)},su=s._FusedDepthwiseConv2D=function(){return(su=s._FusedDepthwiseConv2D=s.asm.J).apply(null,arguments)},v1=s._Gather=function(){return(v1=s._Gather=s.asm.K).apply(null,arguments)},k1=s._GatherNd=function(){return(k1=s._GatherNd=s.asm.L).apply(null,arguments)},I1=s._Greater=function(){return(I1=s._Greater=s.asm.M).apply(null,arguments)},N1=s._GreaterEqual=function(){return(N1=s._GreaterEqual=s.asm.N).apply(null,arguments)},S1=s._LeakyRelu=function(){return(S1=s._LeakyRelu=s.asm.O).apply(null,arguments)},Ve=s._Less=function(){return(Ve=s._Less=s.asm.P).apply(null,arguments)},T1=s._LessEqual=function(){return(T1=s._LessEqual=s.asm.Q).apply(null,arguments)},E1=s._Log=function(){return(E1=s._Log=s.asm.R).apply(null,arguments)},C1=s._LogicalAnd=function(){return(C1=s._LogicalAnd=s.asm.S).apply(null,arguments)},R1=s._Max=function(){return(R1=s._Max=s.asm.T).apply(null,arguments)},F1=s._MaxPool=function(){return(F1=s._MaxPool=s.asm.U).apply(null,arguments)},M1=s._Maximum=function(){return(M1=s._Maximum=s.asm.V).apply(null,arguments)},iu=s._Mean=function(){return(iu=s._Mean=s.asm.W).apply(null,arguments)},ph=s._Min=function(){return(ph=s._Min=s.asm.X).apply(null,arguments)},fh=s._Minimum=function(){return(fh=s._Minimum=s.asm.Y).apply(null,arguments)},$1=s._Multiply=function(){return($1=s._Multiply=s.asm.Z).apply(null,arguments)},D1=s._Neg=function(){return(D1=s._Neg=s.asm._).apply(null,arguments)},O1=s._NonMaxSuppressionV3=function(){return(O1=s._NonMaxSuppressionV3=s.asm.$).apply(null,arguments)},z1=s._NonMaxSuppressionV4=function(){return(z1=s._NonMaxSuppressionV4=s.asm.aa).apply(null,arguments)},P1=s._NonMaxSuppressionV5=function(){return(P1=s._NonMaxSuppressionV5=s.asm.ba).apply(null,arguments)},L1=s._NotEqual=function(){return(L1=s._NotEqual=s.asm.ca).apply(null,arguments)},W1=s._OneHot=function(){return(W1=s._OneHot=s.asm.da).apply(null,arguments)},nt=s._PadV2=function(){return(nt=s._PadV2=s.asm.ea).apply(null,arguments)},B1=s._Pow=function(){return(B1=s._Pow=s.asm.fa).apply(null,arguments)},V1=s._Prelu=function(){return(V1=s._Prelu=s.asm.ga).apply(null,arguments)},U1=s._Prod=function(){return(U1=s._Prod=s.asm.ha).apply(null,arguments)},Xi=s._RealDiv=function(){return(Xi=s._RealDiv=s.asm.ia).apply(null,arguments)},mh=s._Relu=function(){return(mh=s._Relu=s.asm.ja).apply(null,arguments)},Ah=s._Relu6=function(){return(Ah=s._Relu6=s.asm.ka).apply(null,arguments)},yh=s._ResizeBilinear=function(){return(yh=s._ResizeBilinear=s.asm.la).apply(null,arguments)},H1=s._Reverse=function(){return(H1=s._Reverse=s.asm.ma).apply(null,arguments)},j1=s._RotateWithOffset=function(){return(j1=s._RotateWithOffset=s.asm.na).apply(null,arguments)},gh=s._Round=function(){return(gh=s._Round=s.asm.oa).apply(null,arguments)},G1=s._Rsqrt=function(){return(G1=s._Rsqrt=s.asm.pa).apply(null,arguments)},xh=s._ScatterNd=function(){return(xh=s._ScatterNd=s.asm.qa).apply(null,arguments)},Na=s._SelectV2=function(){return(Na=s._SelectV2=s.asm.ra).apply(null,arguments)},q1=s._Sigmoid=function(){return(q1=s._Sigmoid=s.asm.sa).apply(null,arguments)},X1=s._Sin=function(){return(X1=s._Sin=s.asm.ta).apply(null,arguments)},D2=s._Softmax=function(){return(D2=s._Softmax=s.asm.ua).apply(null,arguments)},wh=s._Sqrt=function(){return(wh=s._Sqrt=s.asm.va).apply(null,arguments)},K1=s._Square=function(){return(K1=s._Square=s.asm.wa).apply(null,arguments)},Z1=s._SquaredDifference=function(){return(Z1=s._SquaredDifference=s.asm.xa).apply(null,arguments)},Y1=s._Step=function(){return(Y1=s._Step=s.asm.ya).apply(null,arguments)},J1=s._StridedSlice=function(){return(J1=s._StridedSlice=s.asm.za).apply(null,arguments)},Q1=s._Sub=function(){return(Q1=s._Sub=s.asm.Aa).apply(null,arguments)},ef=s._Sum=function(){return(ef=s._Sum=s.asm.Ba).apply(null,arguments)},tf=s._Tanh=function(){return(tf=s._Tanh=s.asm.Ca).apply(null,arguments)},nf=s._Tile=function(){return(nf=s._Tile=s.asm.Da).apply(null,arguments)},rf=s._TopK=function(){return(rf=s._TopK=s.asm.Ea).apply(null,arguments)},af=s._Transpose=function(){return(af=s._Transpose=s.asm.Fa).apply(null,arguments)},sf=s.__FusedMatMul=function(){return(sf=s.__FusedMatMul=s.asm.Ga).apply(null,arguments)},of=s._malloc=function(){return(of=s._malloc=s.asm.Ha).apply(null,arguments)},lf=s._free=function(){return(lf=s._free=s.asm.Ia).apply(null,arguments)},bh=s.stackSave=function(){return(bh=s.stackSave=s.asm.Ja).apply(null,arguments)},_h=s.stackRestore=function(){return(_h=s.stackRestore=s.asm.Ka).apply(null,arguments)},ou=s.stackAlloc=function(){return(ou=s.stackAlloc=s.asm.La).apply(null,arguments)};s.cwrap=Y;var Ki;function uf(K){this.name="ExitStatus",this.message="Program terminated with exit("+K+")",this.status=K}ta=function K(){Ki||lu(),Ki||(ta=K)};function lu(K){if(K=K||c,sr>0||(Kn(),sr>0))return;function re(){Ki||(Ki=!0,s.calledRun=!0,!U&&(Dn(),pn(),i(s),s.onRuntimeInitialized&&s.onRuntimeInitialized(),nn()))}s.setStatus?(s.setStatus("Running..."),setTimeout(function(){setTimeout(function(){s.setStatus("")},1),re()},1)):re()}if(s.run=lu,s.preInit)for(typeof s.preInit=="function"&&(s.preInit=[s.preInit]);s.preInit.length>0;)s.preInit.pop()();return lu(),a.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)}),gk=rt((e,t)=>{(function(n,r,a){function s(u){var c=this,h=l();c.next=function(){var d=2091639*c.s0+c.c*23283064365386963e-26;return c.s0=c.s1,c.s1=c.s2,c.s2=d-(c.c=d|0)},c.c=1,c.s0=h(" "),c.s1=h(" "),c.s2=h(" "),c.s0-=h(u),c.s0<0&&(c.s0+=1),c.s1-=h(u),c.s1<0&&(c.s1+=1),c.s2-=h(u),c.s2<0&&(c.s2+=1),h=null}function i(u,c){return c.c=u.c,c.s0=u.s0,c.s1=u.s1,c.s2=u.s2,c}function o(u,c){var h=new s(u),d=c&&c.state,p=h.next;return p.int32=function(){return h.next()*4294967296|0},p.double=function(){return p()+(p()*2097152|0)*11102230246251565e-32},p.quick=p,d&&(typeof d=="object"&&i(d,h),p.state=function(){return i(h,{})}),p}function l(){var u=4022871197,c=function(h){h=h.toString();for(var d=0;d<h.length;d++){u+=h.charCodeAt(d);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}r&&r.exports?r.exports=o:a&&a.amd?a(function(){return o}):this.alea=o})(e,typeof t=="object"&&t,typeof define=="function"&&define)}),xk=rt((e,t)=>{(function(n,r,a){function s(l){var u=this,c="";u.x=0,u.y=0,u.z=0,u.w=0,u.next=function(){var d=u.x^u.x<<11;return u.x=u.y,u.y=u.z,u.z=u.w,u.w^=u.w>>>19^d^d>>>8},l===(l|0)?u.x=l:c+=l;for(var h=0;h<c.length+64;h++)u.x^=c.charCodeAt(h)|0,u.next()}function i(l,u){return u.x=l.x,u.y=l.y,u.z=l.z,u.w=l.w,u}function o(l,u){var c=new s(l),h=u&&u.state,d=function(){return(c.next()>>>0)/4294967296};return d.double=function(){do var p=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},d.int32=c.next,d.quick=d,h&&(typeof h=="object"&&i(h,c),d.state=function(){return i(c,{})}),d}r&&r.exports?r.exports=o:a&&a.amd?a(function(){return o}):this.xor128=o})(e,typeof t=="object"&&t,typeof define=="function"&&define)}),wk=rt((e,t)=>{(function(n,r,a){function s(l){var u=this,c="";u.next=function(){var d=u.x^u.x>>>2;return u.x=u.y,u.y=u.z,u.z=u.w,u.w=u.v,(u.d=u.d+362437|0)+(u.v=u.v^u.v<<4^(d^d<<1))|0},u.x=0,u.y=0,u.z=0,u.w=0,u.v=0,l===(l|0)?u.x=l:c+=l;for(var h=0;h<c.length+64;h++)u.x^=c.charCodeAt(h)|0,h==c.length&&(u.d=u.x<<10^u.x>>>4),u.next()}function i(l,u){return u.x=l.x,u.y=l.y,u.z=l.z,u.w=l.w,u.v=l.v,u.d=l.d,u}function o(l,u){var c=new s(l),h=u&&u.state,d=function(){return(c.next()>>>0)/4294967296};return d.double=function(){do var p=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},d.int32=c.next,d.quick=d,h&&(typeof h=="object"&&i(h,c),d.state=function(){return i(c,{})}),d}r&&r.exports?r.exports=o:a&&a.amd?a(function(){return o}):this.xorwow=o})(e,typeof t=="object"&&t,typeof define=="function"&&define)}),bk=rt((e,t)=>{(function(n,r,a){function s(l){var u=this;u.next=function(){var h=u.x,d=u.i,p,f,m;return p=h[d],p^=p>>>7,f=p^p<<24,p=h[d+1&7],f^=p^p>>>10,p=h[d+3&7],f^=p^p>>>3,p=h[d+4&7],f^=p^p<<7,p=h[d+7&7],p=p^p<<13,f^=p^p<<9,h[d]=f,u.i=d+1&7,f};function c(h,d){var p,f,m=[];if(d===(d|0))f=m[0]=d;else for(d=""+d,p=0;p<d.length;++p)m[p&7]=m[p&7]<<15^d.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],h.x=m,h.i=0,p=256;p>0;--p)h.next()}c(u,l)}function i(l,u){return u.x=l.x.slice(),u.i=l.i,u}function o(l,u){l==null&&(l=+new Date);var c=new s(l),h=u&&u.state,d=function(){return(c.next()>>>0)/4294967296};return d.double=function(){do var p=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},d.int32=c.next,d.quick=d,h&&(h.x&&i(h,c),d.state=function(){return i(c,{})}),d}r&&r.exports?r.exports=o:a&&a.amd?a(function(){return o}):this.xorshift7=o})(e,typeof t=="object"&&t,typeof define=="function"&&define)}),_k=rt((e,t)=>{(function(n,r,a){function s(l){var u=this;u.next=function(){var h=u.w,d=u.X,p=u.i,f,m;return u.w=h=h+1640531527|0,m=d[p+34&127],f=d[p=p+1&127],m^=m<<13,f^=f<<17,m^=m>>>15,f^=f>>>12,m=d[p]=m^f,u.i=p,m+(h^h>>>16)|0};function c(h,d){var p,f,m,A,y,g=[],b=128;for(d===(d|0)?(f=d,d=null):(d=d+"\0",f=0,b=Math.max(b,d.length)),m=0,A=-32;A<b;++A)d&&(f^=d.charCodeAt((A+32)%d.length)),A===0&&(y=f),f^=f<<10,f^=f>>>15,f^=f<<4,f^=f>>>13,A>=0&&(y=y+1640531527|0,p=g[A&127]^=f+y,m=p==0?m+1:0);for(m>=128&&(g[(d&&d.length||0)&127]=-1),m=127,A=4*128;A>0;--A)f=g[m+34&127],p=g[m=m+1&127],f^=f<<13,p^=p<<17,f^=f>>>15,p^=p>>>12,g[m]=f^p;h.w=y,h.X=g,h.i=m}c(u,l)}function i(l,u){return u.i=l.i,u.w=l.w,u.X=l.X.slice(),u}function o(l,u){l==null&&(l=+new Date);var c=new s(l),h=u&&u.state,d=function(){return(c.next()>>>0)/4294967296};return d.double=function(){do var p=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},d.int32=c.next,d.quick=d,h&&(h.X&&i(h,c),d.state=function(){return i(c,{})}),d}r&&r.exports?r.exports=o:a&&a.amd?a(function(){return o}):this.xor4096=o})(e,typeof t=="object"&&t,typeof define=="function"&&define)}),vk=rt((e,t)=>{(function(n,r,a){function s(l){var u=this,c="";u.next=function(){var d=u.b,p=u.c,f=u.d,m=u.a;return d=d<<25^d>>>7^p,p=p-f|0,f=f<<24^f>>>8^m,m=m-d|0,u.b=d=d<<20^d>>>12^p,u.c=p=p-f|0,u.d=f<<16^p>>>16^m,u.a=m-d|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 h=0;h<c.length+20;h++)u.b^=c.charCodeAt(h)|0,u.next()}function i(l,u){return u.a=l.a,u.b=l.b,u.c=l.c,u.d=l.d,u}function o(l,u){var c=new s(l),h=u&&u.state,d=function(){return(c.next()>>>0)/4294967296};return d.double=function(){do var p=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},d.int32=c.next,d.quick=d,h&&(typeof h=="object"&&i(h,c),d.state=function(){return i(c,{})}),d}r&&r.exports?r.exports=o:a&&a.amd?a(function(){return o}):this.tychei=o})(e,typeof t=="object"&&t,typeof define=="function"&&define)}),kk=rt((e,t)=>{(function(n,r){var a=(0,eval)("this"),s=256,i=6,o=52,l="random",u=r.pow(s,i),c=r.pow(2,o),h=c*2,d=s-1,p;function f(w,x,N){var S=[];x=x==!0?{entropy:!0}:x||{};var T=g(y(x.entropy?[w,_(n)]:w==null?b():w,3),S),M=new m(S),D=function(){for(var z=M.g(i),W=u,U=0;z<c;)z=(z+U)*s,W*=s,U=M.g(1);for(;z>=h;)z/=2,W/=2,U>>>=1;return(z+U)/W};return D.int32=function(){return M.g(4)|0},D.quick=function(){return M.g(4)/4294967296},D.double=D,g(_(M.S),n),(x.pass||N||function(z,W,U,H){return H&&(H.S&&A(H,M),z.state=function(){return A(M,{})}),U?(r[l]=z,W):z})(D,T,"global"in x?x.global:this==r,x.state)}r["seed"+l]=f;function m(w){var x,N=w.length,S=this,T=0,M=S.i=S.j=0,D=S.S=[];for(N||(w=[N++]);T<s;)D[T]=T++;for(T=0;T<s;T++)D[T]=D[M=d&M+w[T%N]+(x=D[T])],D[M]=x;(S.g=function(z){for(var W,U=0,H=S.i,X=S.j,j=S.S;z--;)W=j[H=d&H+1],U=U*s+j[d&(j[H]=j[X=d&X+W])+(j[X]=W)];return S.i=H,S.j=X,U})(s)}function A(w,x){return x.i=w.i,x.j=w.j,x.S=w.S.slice(),x}function y(w,x){var N=[],S=typeof w,T;if(x&&S=="object")for(T in w)try{N.push(y(w[T],x-1))}catch(M){}return N.length?N:S=="string"?w:w+"\0"}function g(w,x){for(var N=w+"",S,T=0;T<N.length;)x[d&T]=d&(S^=x[d&T]*19)+N.charCodeAt(T++);return _(x)}function b(){try{var w;return p&&(w=p.randomBytes)?w=w(s):(w=new Uint8Array(s),(a.crypto||a.msCrypto).getRandomValues(w)),_(w)}catch(S){var x=a.navigator,N=x&&x.plugins;return[+new Date,a,N,a.screen,_(n)]}}function _(w){return String.fromCharCode.apply(0,w)}if(g(r.random(),n),typeof t=="object"&&t.exports){t.exports=f;try{p=ff()}catch(w){}}else typeof define=="function"&&define.amd&&define(function(){return f})})([],Math)}),Z2=rt((e,t)=>{var n=gk(),r=xk(),a=wk(),s=bk(),i=_k(),o=vk(),l=kk();l.alea=n,l.xor128=r,l.xorwow=a,l.xorshift7=s,l.xor4096=i,l.tychei=o,t.exports=l}),Ik=rt(()=>{}),Nk="3.3.0",Sk="3.3.0",Tk="3.3.0",Ek="3.3.0",Ck="3.3.0",Rk=1e-7,Fk=1e-4,Rh=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}},fu=class{refCount(e){return ir("refCount")}incRef(e){return ir("incRef")}timerAvailable(){return!0}time(e){return ir("time")}read(e){return ir("read")}readSync(e){return ir("readSync")}numDataIds(){return ir("numDataIds")}disposeData(e,t){return ir("disposeData")}write(e,t,n){return ir("write")}move(e,t,n,r,a){return ir("move")}memory(){return ir("memory")}floatPrecision(){return ir("floatPrecision")}epsilon(){return this.floatPrecision()===32?Rk:Fk}dispose(){return ir("dispose")}};function ir(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 Y2(e){let t=e.length,n=0,r=0;for(;t>0;)r=Math.random()*t|0,t--,n=e[t],e[t]=e[r],e[r]=n}function Mk(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,r,a,s=0;for(;n>0;)s=Math.random()*n|0,n--,r=e[n],a=t[n],e[n]=e[s],t[n]=t[s],e[s]=r,t[s]=a}function mu(e,t,n){return Math.max(e,Math.min(t,n))}function $k(e){return e%2==0?e:e+1}function Dk(e){let t=0;for(let n=0;n<e.length;n++)t+=e[n];return t}function Ok(e,t){let n=Math.random();return t*n+(1-n)*e}function zk(e,t){let n=0;for(let r=0;r<e.length;r++){let a=Number(e[r])-Number(t[r]);n+=a*a}return n}function F(e,t){if(!e)throw new Error(typeof t=="string"?t:t())}function un(e,t,n=""){F(oa(e,t),()=>n+` Shapes ${e} and ${t} must match`)}function ds(e){F(e!=null,()=>"The input to the tensor constructor must be a non-null value.")}function ps(e,t=[],n=!1){if(t==null&&(t=[]),Array.isArray(e)||cn(e)&&!n)for(let r=0;r<e.length;++r)ps(e[r],t,n);else t.push(e);return t}function Lt(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 Pk(e){return e.length===0}function oa(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 Kt(e){return e%1==0}function Lk(e){if(Math.tanh!=null)return Math.tanh(e);if(e===Infinity)return 1;if(e===-Infinity)return-1;{let t=Math.exp(2*e);return(t-1)/(t+1)}}function Wk(e){let t=Math.ceil(Math.sqrt(e));return[t,Math.ceil(e/t)]}function Bk(e){let t=new Uint32Array(e);for(let n=0;n<e;++n)t[n]=n;return Y2(t),t}function Au(e,t){return t<=e.length?e:e+" ".repeat(t-e.length)}function Vk(e,t=r=>0,n){return new Promise((r,a)=>{let s=0,i=()=>{if(e()){r();return}s++;let o=t(s);if(n!=null&&s>=n){a();return}setTimeout(i,o)};i()})}function Uk(e,t){let n=1,r=-1;for(let s=0;s<e.length;++s)if(e[s]>=0)n*=e[s];else if(e[s]===-1){if(r!==-1)throw Error(`Shapes can only have 1 implicit size. Found -1 at dim ${r} and dim ${s}`);r=s}else if(e[s]<0)throw Error(`Shapes can not be < 0. Found ${e[s]} at dim ${s}`);if(r===-1){if(t>0&&t!==n)throw Error(`Size(${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} / ${n}`);let a=e.slice();return a[r]=t/n,a}function or(e,t){let n=t.length;return e=e==null?t.map((r,a)=>a):[].concat(e),F(e.every(r=>r>=-n&&r<n),()=>`All values in axis param must be in range [-${n}, ${n}) but got axis ${e}`),F(e.every(r=>Kt(r)),()=>`All values in axis param must be integers but got axis ${e}`),e.map(r=>r<0?n+r:r)}function J2(e,t){let n=[],r=[],a=t!=null&&Array.isArray(t)&&t.length===0,s=t==null||a?null:or(t,e).sort(),i=0;for(let o=0;o<e.length;++o){if(s!=null){if(s[i]===o&&e[o]!==1)throw new Error(`Can't squeeze axis ${o} since its dim '${e[o]}' is not 1`);(s[i]==null||s[i]>o)&&e[o]===1&&(n.push(e[o]),r.push(o)),s[i]<=o&&i++}e[o]!==1&&(n.push(e[o]),r.push(o))}return{newShape:n,keptDims:r}}function Q2(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 e5(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 t5(e,t){for(let n=0;n<e.length;n++){let r=e[n];if(isNaN(r)||!isFinite(r))throw Error(`A tensor of type ${t} being uploaded contains ${r}.`)}}function n5(e){return e==="bool"||e==="complex64"||e==="float32"||e==="int32"||e==="string"}function Hk(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 mf(e){if(e==="float32"||e==="int32")return 4;if(e==="complex64")return 8;if(e==="bool")return 1;throw new Error(`Unknown dtype ${e}`)}function r5(e){if(e==null)return 0;let t=0;return e.forEach(n=>t+=n.length),t}function Ea(e){return typeof e=="string"||e instanceof String}function a5(e){return typeof e=="boolean"}function s5(e){return typeof e=="number"}function Fh(e){return Array.isArray(e)?Fh(e[0]):e instanceof Float32Array?"float32":e instanceof Int32Array||e instanceof Uint8Array?"int32":s5(e)?"float32":Ea(e)?"string":a5(e)?"bool":"float32"}function Ca(e){return!!(e&&e.constructor&&e.call&&e.apply)}function Mh(e,t){for(let n=t;n<e;++n)if(e%n==0)return n;return e}function ro(e){let t=e.length;if(t<2)return[];let n=new Array(t-1);n[t-2]=e[t-1];for(let r=t-3;r>=0;--r)n[r]=n[r+1]*e[r+1];return n}function i5(e,t,n){let r=new Array;if(t.length===1){let a=t[0];for(let s=0;s<a;s++)r[s]=n[e+s]}else{let a=t[0],s=t.slice(1),i=s.reduce((o,l)=>o*l);for(let o=0;o<a;o++)r[o]=i5(e+o*i,s,n)}return r}function ao(e,t){if(e.length===0)return t[0];let n=e.reduce((r,a)=>r*a);if(n===0)return[];if(n!==t.length)throw new Error(`[${e}] does not match the input size ${t.length}.`);return i5(0,e,t)}function Af(e,t){let n=$h(e,t);for(let r=0;r<n.length;r++)n[r]=1;return n}function $h(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 jk(e,t){let n=e.reduce((r,a)=>r*a,1);if(t==null||t==="float32")return ao(e,new Float32Array(n));if(t==="int32")return ao(e,new Int32Array(n));if(t==="bool")return ao(e,new Uint8Array(n));throw new Error(`Unknown data type ${t}`)}function yf(e){e.forEach(t=>{F(Number.isInteger(t)&&t>=0,()=>`Tensor must have a shape comprised of positive integers but got shape [${e}].`)})}function Gk(e,t,n){if(t===0)return 0;if(t===1)return e[0];let r=e[e.length-1];for(let a=0;a<e.length-1;++a)r+=n[a]*e[a];return r}function qk(e,t,n){if(t===0)return[];if(t===1)return[e];let r=new Array(t);for(let a=0;a<r.length-1;++a)r[a]=Math.floor(e/n[a]),e-=r[a]*n[a];return r[r.length-1]=e,r}function gf(e){return e&&e.then&&typeof e.then=="function"}var o5="tfjsflags",l5=class{constructor(e){this.global=e,this.flags={},this.flagRegistry={},this.urlFlags={},this.populateURLFlags()}setPlatform(e,t){this.platform!=null&&console.warn(`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 r=this.urlFlags[e];console.warn(`Setting feature override from URL ${e}: ${r}.`),this.set(e,r)}}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(gf(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=Xk(this.global.location.search);o5 in e&&e[o5].split(",").forEach(t=>{let[n,r]=t.split(":");this.urlFlags[n]=Kk(n,r)})}};function Xk(e){let t={};return e.replace(/[?&]([^=?&]+)(?:=([^&]*))?/g,(n,...r)=>(Zk(t,r[0],r[1]),r.join("="))),t}function Zk(e,t,n){e[decodeURIComponent(t)]=decodeURIComponent(n||"")}function Kk(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 ${e}.`)}function J(){return wr}var wr=null;function Yk(e){wr=e}var xf;function u5(){if(xf==null){let e;if(typeof window!="undefined")e=window;else if(typeof global!="undefined")e=global;else if(typeof process!="undefined")e=process;else if(typeof self!="undefined")e=self;else throw new Error("Could not find a global object");xf=e}return xf}function Jk(){let e=u5();return e._tfGlobals==null&&(e._tfGlobals=new Map),e._tfGlobals}function wf(e,t){let n=Jk();if(n.has(e))return n.get(e);{let r=t();return n.set(e,r),n.get(e)}}var so="Abs",io="Acos",oo="Acosh",Ra="Add",fs="AddN",Dh="All",Oh="Any",ms="ArgMax",yu="ArgMin",lo="Asin",uo="Asinh",co="Atan",ho="Atanh",po="Atan2",As="AvgPool",zh="AvgPoolGrad",gu="AvgPool3D",Ph="AvgPool3DGrad",ys="BatchMatMul",xu="BatchToSpaceND",Lh="Bincount",c5="BroadcastTo",gs="Cast",xs="Ceil",Fa="ClipByValue",Wh="Complex",wu="ComplexAbs",fo="Concat",ws="Conv2D",Bh="Conv2DBackpropFilter",bs="Conv2DBackpropInput",bu="Conv3D",Vh="Conv3DBackpropFilterV2",Uh="Conv3DBackpropInputV2",_s="Cos",mo="Cosh",vs="Cumsum",Ao="CropAndResize",Hh="DenseBincount",yo="DepthToSpace",ks="DepthwiseConv2dNative",jh="DepthwiseConv2dNativeBackpropFilter",Gh="DepthwiseConv2dNativeBackpropInput",qh="Diag",_u="Dilation2D",Xh="Dilation2DBackpropInput",Kh="Dilation2DBackpropFilter",Is="RealDiv",go="Elu",Zh="EluGrad",xo="Erf",wo="Equal",Ns="Exp",bo="ExpandDims",_o="Expm1",Yh="FFT",vu="Fill",vo="FlipLeftRight",Ss="Floor",Ts="FloorDiv",Es="FusedBatchNorm",ko="GatherV2",Io="GatherNd",No="Greater",Cs="GreaterEqual",Rs="Identity",Jh="IFFT",Qh="Imag",So="IsFinite",To="IsInf",Eo="IsNan",Fs="LeakyRelu",Co="Less",Ro="LessEqual",ed="LinSpace",Ms="Log",Fo="Log1p",Mo="LogicalAnd",ku="LogicalNot",Iu="LogicalOr",h5="LogSoftmax",Nu="LRN",td="LRNGrad",$s="Max",Ds="Maximum",Os="MaxPool",nd="MaxPoolGrad",Su="MaxPool3D",rd="MaxPool3DGrad",ad="MaxPoolWithArgmax",zs="Mean",Ps="Min",Ls="Minimum",Tu="MirrorPad",$o="Mod",sd="Multinomial",Ws="Multiply",Do="Neg",Oo="NotEqual",zo="NonMaxSuppressionV3",Po="NonMaxSuppressionV4",Lo="NonMaxSuppressionV5",Wo="OnesLike",Bs="OneHot",Bo="Pack",Vs="PadV2",Qk="Pool",Us="Pow",Hs="Prelu",Vo="Prod",Eu="Range",id="Real",Uo="Reciprocal",js="Relu",Ho="Reshape",Cu="ResizeNearestNeighbor",od="ResizeNearestNeighborGrad",Gs="ResizeBilinear",ld="ResizeBilinearGrad",qs="Relu6",Xs="Reverse",Ks="Round",Zs="Rsqrt",jo="ScatterNd",Go="Select",qo="Selu",Xo="Slice",Ys="Sin",Ko="Sinh",Zo="Sign",Js="Sigmoid",Yo="Softplus",Qs="Sqrt",ei="Sum",Ru="SpaceToBatchND",Jo="SplitV",ti="Softmax",ni="SquaredDifference",Fu="Square",ri="Sub",ud="SparseToDense",Qo="StridedSlice",el="Tan",ai="Tanh",Ma="Tile",tl="TopK",cd="Transform",si="Transpose",hd="Unique",nl="Unpack",Mu="UnsortedSegmentSum",rl="ZerosLike",$a="Step",dd="FromPixels",al="RotateWithOffset",ii="_FusedMatMul",oi="FusedConv2D",li="FusedDepthwiseConv2D",sl=wf("kernelRegistry",()=>new Map),$u=wf("gradRegistry",()=>new Map);function pd(e,t){let n=bf(e,t);return sl.get(n)}function _f(e){return $u.get(e)}function il(e){let t=sl.entries(),n=[];for(;;){let{done:r,value:a}=t.next();if(r)break;let[s,i]=a,[o]=s.split("_");o===e&&n.push(i)}return n}function ui(e){let{kernelName:t,backendName:n}=e,r=bf(t,n);sl.has(r)&&console.warn(`The kernel '${t}' for backend '${n}' is already registered`),sl.set(r,e)}function d5(e){let{kernelName:t}=e;$u.has(t)&&J().getBool("DEBUG")&&console.warn(`Overriding the gradient for '${t}'`),$u.set(t,e)}function e9(e,t){let n=bf(e,t);if(!sl.has(n))throw new Error(`The kernel '${e}' for backend '${t}' is not registered`);sl.delete(n)}function t9(e){if(!$u.has(e))throw new Error(`The gradient '${e}' for backend is not registered`);$u.delete(e)}function n9(e,t){il(e).forEach(n=>{let r=Object.assign({},n,{backendName:t});ui(r)})}function bf(e,t){return`${t}_${e}`}var v={};We(v,{arraysEqual:()=>oa,assert:()=>F,assertNonNegativeIntegerDimensions:()=>yf,assertNonNull:()=>ds,assertShapesMatch:()=>un,bytesFromStringArray:()=>r5,bytesPerElement:()=>mf,checkConversionForErrors:()=>t5,clamp:()=>mu,computeStrides:()=>ro,createScalarValue:()=>r9,createShuffledIndices:()=>Bk,decodeString:()=>md,distSquared:()=>zk,encodeString:()=>Ou,fetch:()=>a9,flatten:()=>ps,getArrayFromDType:()=>e5,getTypedArrayFromDType:()=>Q2,hasEncodingLoss:()=>Hk,indexToLoc:()=>qk,inferDtype:()=>Fh,inferFromImplicitShape:()=>Uk,isBoolean:()=>a5,isFunction:()=>Ca,isInt:()=>Kt,isNumber:()=>s5,isPromise:()=>gf,isScalarShape:()=>Pk,isString:()=>Ea,isTypedArray:()=>cn,isValidDtype:()=>n5,locToIndex:()=>Gk,makeOnesTypedArray:()=>Af,makeZerosNestedTypedArray:()=>jk,makeZerosTypedArray:()=>$h,nearestDivisor:()=>Mh,nearestLargerEven:()=>$k,now:()=>Du,parseAxisParam:()=>or,randUniform:()=>Ok,repeatedTry:()=>Vk,rightPad:()=>Au,shuffle:()=>Y2,shuffleCombo:()=>Mk,sizeFromShape:()=>Lt,sizeToSquarishShape:()=>Wk,squeezeShape:()=>J2,sum:()=>Dk,tanh:()=>Lk,toNestedArray:()=>ao,toTypedArray:()=>fd});function r9(e,t){return t==="string"?Ou(e):fd([e],t)}function s9(e,t){return e instanceof Float32Array&&t==="float32"||e instanceof Int32Array&&t==="int32"||e instanceof Uint8Array&&t==="bool"}function fd(e,t){if(t==="string")throw new Error("Cannot convert a string[] to a TypedArray");if(Array.isArray(e)&&(e=ps(e)),J().getBool("DEBUG")&&t5(e,t),s9(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 r=0;r<n.length;++r)Math.round(e[r])!==0&&(n[r]=1);return n}else throw new Error(`Unknown data type ${t}`)}function Du(){return J().platform.now()}function a9(e,t){return J().platform.fetch(e,t)}function Ou(e,t="utf-8"){return t=t||"utf-8",J().platform.encode(e,t)}function md(e,t="utf-8"){return t=t||"utf-8",J().platform.decode(e,t)}var l9=class{constructor(e,t){this.backendTimer=e,this.logger=t,t==null&&(this.logger=new o9)}profileKernel(e,t,n){let r,a=()=>{r=n()},s,i=Du();if(this.backendTimer.timerAvailable())s=this.backendTimer.time(a);else{a();for(let o of r)o.dataSync();s=Promise.resolve({kernelMs:Du()-i})}if(J().getBool("CHECK_COMPUTATION_FOR_ERRORS"))for(let o=0;o<r.length;o++){let l=r[o];l.data().then(u=>{i9(u,l.dtype,e)})}return{kernelName:e,outputs:r,inputs:t,timeMs:s.then(o=>o.kernelMs),extraInfo:s.then(o=>o.getExtraProfileInfo!=null?o.getExtraProfileInfo():"")}}logKernelProfile(e){let{kernelName:t,outputs:n,timeMs:r,inputs:a,extraInfo:s}=e;n.forEach(i=>{Promise.all([i.data(),r,s]).then(o=>{this.logger.logKernelProfile(t,i,o[0],o[1],a,o[2])})})}};function i9(e,t,n){if(t!=="float32")return!1;for(let r=0;r<e.length;r++){let a=e[r];if(isNaN(a)||!isFinite(a))return console.warn(`Found ${a} in the result of '${n}'`),!0}return!1}var o9=class{logKernelProfile(e,t,n,r,a,s){let i=typeof r=="number"?Au(`${r}ms`,9):r.error,o=Au(e,25),l=t.rank,u=t.size,c=Au(t.shape.toString(),14),h="";for(let d in a){let p=a[d];if(p!=null){let f=p.shape||t.shape,m=f.length;h+=`${d}: ${m}D ${m>0?f:""} `}}console.log(`%c${o} %c${i} %c${l}D ${c} %c${u} %c${h} %c${s}`,"font-weight:bold","color:red","color:blue","color: orange","color: green","color: steelblue")}};function u9(e,t,n){let r={},a={};for(let l=0;l<t.length;l++)r[t[l].id]=!0;for(let l=0;l<e.length;l++){let u=e[l],c=u.inputs;for(let h in c){let d=c[h],p=!1;for(let f=0;f<t.length;f++)if(r[d.id]){u.outputs.forEach(m=>r[m.id]=!0),p=!0,a[u.id]=!0;break}if(p)break}}let s={};s[n.id]=!0;let i={};for(let l=e.length-1;l>=0;l--){let u=e[l],c=u.inputs;for(let h=0;h<u.outputs.length;h++)if(s[u.outputs[h].id]){for(let d in c)s[c[d].id]=!0,i[u.id]=!0;break}}let o=[];for(let l=0;l<e.length;l++){let u=e[l];if(a[u.id]&&i[u.id]){let c={};for(let d in u.inputs){let p=u.inputs[d];r[p.id]&&(c[d]=p)}let h=Object.assign({},u);h.inputs=c,h.outputs=u.outputs,o.push(h)}}return o}function c9(e,t,n,r){for(let a=t.length-1;a>=0;a--){let s=t[a],i=[];if(s.outputs.forEach(l=>{let u=e[l.id];u!=null?i.push(u):i.push(null)}),s.gradient==null)throw new Error(`Cannot compute gradient: gradient function not found for ${s.kernelName}.`);let o=s.gradient(i);for(let l in s.inputs){if(!(l in o))throw new Error(`Cannot backprop through input ${l}. Available gradients found: ${Object.keys(o)}.`);let u=n(()=>o[l]());if(u.dtype!=="float32")throw new Error(`Error in gradient for op ${s.kernelName}. The gradient of input ${l} must have 'float32' dtype, but has '${u.dtype}'`);let c=s.inputs[l];if(!oa(u.shape,c.shape))throw new Error(`Error in gradient for op ${s.kernelName}. The gradient of input '${l}' has shape '${u.shape}', which does not match the shape of the input '${c.shape}'`);if(e[c.id]==null)e[c.id]=u;else{let h=e[c.id];e[c.id]=r(h,u),h.dispose()}}}}var p5=20,zu=3,vf=7;function d9(e,t,n,r){let a=ro(t),s=h9(e,t,n,a),i=t.length,o=Ad(e,t,n,a,s),l=["Tensor"];return r&&(l.push(` dtype: ${n}`),l.push(` rank: ${i}`),l.push(` shape: [${t}]`),l.push(" values:")),l.push(o.map(u=>" "+u).join(`
|
|
`)),l.join(`
|
|
`)}function h9(e,t,n,r){let a=Lt(t),s=r[r.length-1],i=new Array(s).fill(0),o=t.length,l=n==="complex64"?Lu(e):e;if(o>1)for(let u=0;u<a/s;u++){let c=u*s;for(let h=0;h<s;h++)i[h]=Math.max(i[h],Pu(l[c+h],0,n).length)}return i}function Pu(e,t,n){let r;return Array.isArray(e)?r=`${parseFloat(e[0].toFixed(vf))} + ${parseFloat(e[1].toFixed(vf))}j`:Ea(e)?r=`'${e}'`:n==="bool"?r=f5(e):r=parseFloat(e.toFixed(vf)).toString(),Au(r,t)}function f5(e){return e===0?"false":"true"}function Ad(e,t,n,r,a,s=!0){let i=n==="complex64"?2:1,o=t[0],l=t.length;if(l===0){if(n==="complex64"){let m=Lu(e);return[Pu(m[0],0,n)]}return n==="bool"?[f5(e[0])]:[e[0].toString()]}if(l===1){if(o>p5){let A=zu*i,y=Array.from(e.slice(0,A)),g=Array.from(e.slice((o-zu)*i,o*i));return n==="complex64"&&(y=Lu(y),g=Lu(g)),["["+y.map((b,_)=>Pu(b,a[_],n)).join(", ")+", ..., "+g.map((b,_)=>Pu(b,a[o-zu+_],n)).join(", ")+"]"]}let m=n==="complex64"?Lu(e):Array.from(e);return["["+m.map((A,y)=>Pu(A,a[y],n)).join(", ")+"]"]}let u=t.slice(1),c=r.slice(1),h=r[0]*i,d=[];if(o>p5){for(let m=0;m<zu;m++){let A=m*h,y=A+h;d.push(...Ad(e.slice(A,y),u,n,c,a,!1))}d.push("...");for(let m=o-zu;m<o;m++){let A=m*h,y=A+h;d.push(...Ad(e.slice(A,y),u,n,c,a,m===o-1))}}else for(let m=0;m<o;m++){let A=m*h,y=A+h;d.push(...Ad(e.slice(A,y),u,n,c,a,m===o-1))}let p=l===2?",":"";d[0]="["+d[0]+p;for(let m=1;m<d.length-1;m++)d[m]=" "+d[m]+p;let f=`,
|
|
`;for(let m=2;m<l;m++)f+=`
|
|
`;return d[d.length-1]=" "+d[d.length-1]+"]"+(s?"":f),d}function Lu(e){let t=[];for(let n=0;n<e.length;n+=2)t.push([e[n],e[n+1]]);return t}var Wt=class{constructor(e,t,n){if(this.dtype=t,this.shape=e.slice(),this.size=Lt(e),n!=null){let r=n.length;F(r===this.size,()=>`Length of values '${r}' does not match the size inferred by the shape '${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||e5(t,this.size),this.strides=ro(e)}set(e,...t){t.length===0&&(t=[0]),F(t.length===this.rank,()=>`The number of provided coordinates (${t.length}) must match the rank (${this.rank})`);let n=this.locToIndex(t);this.values[n]=e}get(...e){e.length===0&&(e=[0]);let t=0;for(let r of e){if(r<0||r>=this.shape[t]){let a=`Requested out of range element at ${e}. Buffer shape=${this.shape}`;throw new Error(a)}t++}let n=e[e.length-1];for(let r=0;r<e.length-1;++r)n+=this.strides[r]*e[r];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 Dr().makeTensor(this.values,this.shape,this.dtype)}},Dr=null,ol=null,p9=null;function f9(e){Dr=e}function m9(e){ol=e}function A9(e){p9=e}var Ge=class{constructor(e,t,n,r){this.kept=!1,this.isDisposedInternal=!1,this.shape=e.slice(),this.dtype=t||"float32",this.size=Lt(e),this.strides=ro(e),this.dataId=n,this.id=r,this.rankType=this.rank<5?this.rank.toString():"higher"}get rank(){return this.shape.length}async buffer(){let e=await this.data();return ol.buffer(this.shape,this.dtype,e)}bufferSync(){return ol.buffer(this.shape,this.dtype,this.dataSync())}async array(){let e=await this.data();return ao(this.shape,e)}arraySync(){return ao(this.shape,this.dataSync())}async data(){this.throwIfDisposed();let e=Dr().read(this.dataId);if(this.dtype==="string"){let t=await e;try{return t.map(n=>md(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=Dr().readSync(this.dataId);if(this.dtype==="string")try{return e.map(t=>md(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 Dr().read(this.dataId);return this.dtype==="string"?e:new Uint8Array(e.buffer)}dispose(){this.isDisposed||(Dr().disposeTensor(this),this.isDisposedInternal=!0)}get isDisposed(){return this.isDisposedInternal}throwIfDisposed(){if(this.isDisposed)throw new Error("Tensor is disposed.")}print(e=!1){return ol.print(this,e)}clone(){return this.throwIfDisposed(),ol.clone(this)}toString(e=!1){let t=this.dataSync();return d9(t,this.shape,this.dtype,e)}cast(e){return this.throwIfDisposed(),ol.cast(this,e)}variable(e=!0,t,n){return this.throwIfDisposed(),Dr().makeVariable(this,e,t,n)}};Object.defineProperty(Ge,Symbol.hasInstance,{value:e=>!!e&&e.data!=null&&e.dataSync!=null&&e.throwIfDisposed!=null});function Z(){return wf("Tensor",()=>Ge)}Z();var Wu=class extends Ge{constructor(e,t,n,r){super(e.shape,e.dtype,e.dataId,r);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(!oa(e.shape,this.shape))throw new Error(`shape of the new value (${e.shape}) and previous value (${this.shape}) must match`);Dr().disposeTensor(this),this.dataId=e.dataId,Dr().incRef(this,null)}dispose(){Dr().disposeVariable(this),this.isDisposedInternal=!0}};Object.defineProperty(Wu,Symbol.hasInstance,{value:e=>e instanceof Ge&&e.assign!=null&&e.assign instanceof Function});var br={};We(br,{assertTypesMatch:()=>m5,getTensorsInContainer:()=>kf,isTensorInList:()=>y9,makeTypesMatch:()=>Nt});var If;(function(e){e.R0="R0",e.R1="R1",e.R2="R2",e.R3="R3",e.R4="R4",e.R5="R5",e.R6="R6"})(If||(If={}));var Nf;(function(e){e.float32="float32",e.int32="int32",e.bool="int32",e.complex64="complex64"})(Nf||(Nf={}));var Sf;(function(e){e.float32="float32",e.int32="int32",e.bool="bool",e.complex64="complex64"})(Sf||(Sf={}));var Tf;(function(e){e.float32="float32",e.int32="float32",e.bool="float32",e.complex64="complex64"})(Tf||(Tf={}));var Ef;(function(e){e.float32="complex64",e.int32="complex64",e.bool="complex64",e.complex64="complex64"})(Ef||(Ef={}));var g9={float32:Tf,int32:Nf,bool:Sf,complex64:Ef};function lr(e,t){if(e==="string"||t==="string"){if(e==="string"&&t==="string")return"string";throw new Error(`Can not upcast ${e} with ${t}`)}return g9[e][t]}function yd(e){return lr(e,"int32")}function Nt(e,t){if(e.dtype===t.dtype)return[e,t];let n=lr(e.dtype,t.dtype);return[e.cast(n),t.cast(n)]}function m5(e,t){F(e.dtype===t.dtype,()=>`The dtypes of the first(${e.dtype}) and second(${t.dtype}) input must match`)}function y9(e,t){return t.some(n=>n.id===e.id)}function kf(e){let t=[],n=new Set;return A5(e,t,n),t}function A5(e,t,n){if(e==null)return;if(e instanceof Ge){t.push(e);return}if(!x9(e))return;let r=e;for(let a in r){let s=r[a];n.has(s)||(n.add(s),A5(s,t,n))}}function x9(e){return Array.isArray(e)||typeof e=="object"}function Cf(e){return e.kernelName!=null}var y5=class{constructor(){this.registeredVariables={},this.nextTapeNodeId=0,this.numBytes=0,this.numTensors=0,this.numStringTensors=0,this.numDataBuffers=0,this.gradientDepth=0,this.kernelDepth=0,this.scopeStack=[],this.numDataMovesStack=[],this.nextScopeId=0,this.tensorInfo=new WeakMap,this.profiling=!1,this.activeProfile={newBytes:0,newTensors:0,peakBytes:0,kernels:[],result:null,get kernelNames(){return Array.from(new Set(this.kernels.map(e=>e.name)))}}}dispose(){for(let e in this.registeredVariables)this.registeredVariables[e].dispose()}},Bu=class{constructor(e){this.ENV=e,this.registry={},this.registryFactory={},this.pendingBackendInitId=0,this.state=new y5}async ready(){if(this.pendingBackendInit!=null)return this.pendingBackendInit.then(()=>{});if(this.backendInstance!=null)return;let e=this.getSortedBackends();for(let t=0;t<e.length;t++){let n=e[t];if(await this.initializeBackend(n).success){await this.setBackend(n);return}}throw new Error("Could not initialize any backends, all backend initializations failed.")}get backend(){if(this.pendingBackendInit!=null)throw new Error(`Backend '${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 '${e}' has not yet been initialized. Make sure to await tf.ready() or await tf.setBackend() before calling other methods`);this.setBackend(e)}return this.backendInstance}backendNames(){return Object.keys(this.registryFactory)}findBackend(e){if(!(e in this.registry))if(e in this.registryFactory){let{asyncInit:t}=this.initializeBackend(e);if(t)return null}else return null;return this.registry[e]}findBackendFactory(e){return e in this.registryFactory?this.registryFactory[e].factory:null}registerBackend(e,t,n=1){return e in this.registryFactory?(console.warn(`${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 l9(this.backendInstance),!0}setupRegisteredKernels(){il(this.backendName).forEach(e=>{e.setupFunc!=null&&e.setupFunc(this.backendInstance)})}disposeRegisteredKernels(e){il(e).forEach(t=>{t.disposeFunc!=null&&t.disposeFunc(this.registry[e])})}initializeBackend(e){let t=this.registryFactory[e];if(t==null)throw new Error(`Cannot initialize backend ${e}, no registration found.`);try{let n=t.factory();if(n&&!(n instanceof fu)&&typeof n.then=="function"){let r=++this.pendingBackendInitId,a=n.then(s=>r<this.pendingBackendInitId?!1:(this.registry[e]=s,this.pendingBackendInit=null,!0)).catch(s=>(r<this.pendingBackendInitId||(this.pendingBackendInit=null,console.warn(`Initialization of backend ${e} failed`),console.warn(s.stack||s.message)),!1));return this.pendingBackendInit=a,{success:a,asyncInit:!0}}else return this.registry[e]=n,{success:!0,asyncInit:!1}}catch(n){return console.warn(`Initialization of backend ${e} failed`),console.warn(n.stack||n.message),{success:!1,asyncInit:!1}}}removeBackend(e){if(!(e in this.registryFactory))throw new Error(`${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:r,asyncInit:a}=this.initializeBackend(n);if(a||r)return{name:n,asyncInit:a}}throw new Error("Could not initialize any backends, all backend initializations failed.")}moveData(e,t){let n=this.state.tensorInfo.get(t),r=n.backend,a=this.readSync(t),s=r.refCount(t);r.disposeData(t,!0),n.backend=e,e.move(t,a,n.shape,n.dtype,s),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 r;return this.scopedRun(()=>this.startScope(n),()=>this.endScope(r),()=>(r=t(),r instanceof Promise&&console.error("Cannot return a Promise inside of tidy."),r))}scopedRun(e,t,n){e();try{let r=n();return t(),r}catch(r){throw t(),r}}nextTensorId(){return Bu.nextTensorId++}nextVariableId(){return Bu.nextVariableId++}clone(e){let t=$.runKernel(Rs,{x:e}),n={x:e},r=s=>({x:()=>{let i="float32",o={x:s},l={dtype:i};return $.runKernel(gs,o,l)}}),a=[];return this.addTapeNode(this.state.activeScope.name,n,[t],r,a,{}),t}runKernel(e,t,n){if(pd(e,this.backendName)==null)throw new Error(`Kernel '${e}' not registered for backend '${this.backendName}'`);return this.runKernelFunc({kernelName:e,inputs:t,attrs:n})}shouldCheckForMemLeaks(){return this.ENV.getBool("IS_TEST")}checkKernelForMemLeak(e,t,n){let r=this.backend.numDataIds(),a=0;n.forEach(o=>{a+=o.dtype==="complex64"?3:1});let s=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],i=r-t-a-s;if(i>0)throw new Error(`Backend '${this.backendName}' has an internal memory leak (${i} data ids) after running '${e}'`)}runKernelFunc(e){let t,n=[],r=this.isTapeOn(),a=this.state.numBytes,s=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);let i;this.backendName==null&&this.backend;let o,l=Cf(e)?e.kernelName:this.state.activeScope!=null?this.state.activeScope.name:"";if(Cf(e)){let{kernelName:p,inputs:f,attrs:m}=e;this.backendName==null&&this.backend;let A=pd(p,this.backendName);F(A!=null,()=>`Cannot find registered kernel '${p}' for backend '${this.backendName}'`),i=()=>{let y=this.backend.numDataIds();o=A.kernelFunc({inputs:f,attrs:m,backend:this.backend});let g=Array.isArray(o)?o:[o];this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(p,y,g);let b=g.map(_=>{if(_.rank!=null)return _;let{dataId:w,shape:x,dtype:N}=_;return this.makeTensorFromDataId(w,x,N)});if(r){let _=this.getTensorsForGradient(p,f,b);n=this.saveTensorsForBackwardMode(_)}return b}}else{let{forwardFunc:p}=e,f=m=>{!r||(n=m.map(A=>this.keep(this.clone(A))))};i=()=>{let m=this.backend.numDataIds();o=this.tidy(()=>p(this.backend,f));let A=Array.isArray(o)?o:[o];return this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(l,m,A),A}}let{inputs:u,attrs:c}=e,h=Cf(e)?null:e.backwardsFunc,d;return this.scopedRun(()=>this.state.kernelDepth++,()=>this.state.kernelDepth--,()=>{!this.ENV.getBool("DEBUG")&&!this.state.profiling?t=i():(d=this.profiler.profileKernel(l,u,()=>i()),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(d),t=d.outputs)}),r&&this.addTapeNode(l,u,t,h,n,c),this.state.profiling&&this.state.activeProfile.kernels.push({name:l,bytesAdded:this.state.numBytes-a,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-s,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(u).map(p=>u[p]!=null?u[p].shape:null),outputShapes:t.map(p=>p.shape),kernelTimeMs:d.timeMs,extraInfo:d.extraInfo}),Array.isArray(o)?t:t[0]}saveTensorsForBackwardMode(e){return e.map(t=>this.keep(this.clone(t)))}getTensorsForGradient(e,t,n){let r=_f(e);if(r!=null){let a=r.inputsToSave||[],s=r.outputsToSave||[],i;r.saveAllInputs?(F(Array.isArray(t),()=>"saveAllInputs is true, expected inputs to be an array."),i=Object.keys(t).map(l=>t[l])):i=a.map(l=>t[l]);let o=n.filter((l,u)=>s[u]);return i.concat(o)}return[]}makeTensor(e,t,n,r){if(e==null)throw new Error("Values passed to engine.makeTensor() are null");n=n||"float32",r=r||this.backend;let a=e;n==="string"&&Ea(e[0])&&(a=e.map(o=>Ou(o)));let s=r.write(a,t,n),i=new Ge(t,n,s,this.nextTensorId());if(this.trackTensor(i,r),n==="string"){let o=this.state.tensorInfo.get(s),l=r5(a);this.state.numBytes+=l-o.bytes,o.bytes=l}return i}makeTensorFromDataId(e,t,n,r){n=n||"float32";let a=new Ge(t,n,e,this.nextTensorId());return this.trackTensor(a,r),a}makeVariable(e,t=!0,n,r){n=n||this.nextVariableId().toString(),r!=null&&r!==e.dtype&&(e=e.cast(r));let a=new Wu(e,t,n,this.nextTensorId());if(this.state.registeredVariables[a.name]!=null)throw new Error(`Variable with name ${a.name} was already registered`);return this.state.registeredVariables[a.name]=a,this.incRef(a,this.backend),a}trackTensor(e,t){this.state.numTensors++,e.dtype==="string"&&this.state.numStringTensors++;let n=0;e.dtype!=="complex64"&&e.dtype!=="string"&&(n=e.size*mf(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 Wu||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*mf(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(r=>r.totalBytesSnapshot)),this.state.activeProfile.newBytes=this.state.numBytes-t,this.state.activeProfile.newTensors=this.state.numTensors-n;for(let r of this.state.activeProfile.kernels)r.kernelTimeMs=await r.kernelTimeMs,r.extraInfo=await r.extraInfo;return this.state.activeProfile}isTapeOn(){return this.state.gradientDepth>0&&this.state.kernelDepth===0}addTapeNode(e,t,n,r,a,s){let i={id:this.state.nextTapeNodeId++,kernelName:e,inputs:t,outputs:n,saved:a},o=_f(e);o!=null&&(r=o.gradFunc),r!=null&&(i.gradient=l=>(l=l.map((u,c)=>{if(u==null){let h=n[c],d=$h(h.size,h.dtype);return this.makeTensor(d,h.shape,h.dtype)}return u}),r(l.length>1?l:l[0],a,s))),this.state.activeTape.push(i)}keep(e){return e.kept=!0,e}startTape(){this.state.gradientDepth===0&&(this.state.activeTape=[]),this.state.gradientDepth++}endTape(){this.state.gradientDepth--}startScope(e){let t={track:[],name:"unnamed scope",id:this.state.nextScopeId++};e&&(t.name=e),this.state.scopeStack.push(t),this.state.activeScope=t}endScope(e){let t=kf(e),n=new Set(t.map(a=>a.id));for(let a=0;a<this.state.activeScope.track.length;a++){let s=this.state.activeScope.track[a];!s.kept&&!n.has(s.id)&&s.dispose()}let r=this.state.scopeStack.pop();this.state.activeScope=this.state.scopeStack.length===0?null:this.state.scopeStack[this.state.scopeStack.length-1],t.forEach(a=>{!a.kept&&a.scopeId===r.id&&this.track(a)})}gradients(e,t,n,r=!1){if(F(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 a=this.scopedRun(()=>this.startTape(),()=>this.endTape(),()=>this.tidy("forward",e));F(a instanceof Ge,()=>"The result y returned by f() must be a tensor.");let s=u9(this.state.activeTape,t,a);if(!r&&s.length===0&&t.length>0)throw new Error("Cannot compute gradient of y=f(x) with respect to x. Make sure that the f you passed encloses all operations that lead from x to y.");return this.tidy("backward",()=>{let i={};i[a.id]=n==null?w9(a.shape):n,c9(i,s,l=>this.tidy(l),b9);let o=t.map(l=>i[l.id]);return this.state.gradientDepth===0&&(this.state.activeTape.forEach(l=>{for(let u of l.saved)u.dispose()}),this.state.activeTape=null),{value:a,grads:o}})}customGrad(e){return F(Ca(e),()=>"The f passed in customGrad(f) must be a function."),(...t)=>{F(t.every(i=>i instanceof Ge),()=>"The args passed in customGrad(f)(x1, x2,...) must all be tensors");let n,r={};t.forEach((i,o)=>{r[o]=i});let a=(i,o)=>(n=e(...t,o),F(n.value instanceof Ge,()=>"The function f passed in customGrad(f) must return an object where `obj.value` is a tensor"),F(Ca(n.gradFunc),()=>"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function."),n.value),s=(i,o)=>{let l=n.gradFunc(i,o),u=Array.isArray(l)?l:[l];F(u.length===t.length,()=>"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns the same number of tensors as inputs passed to f(...)."),F(u.every(h=>h 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((h,d)=>{c[d]=()=>h}),c};return this.runKernelFunc({forwardFunc:a,backwardsFunc:s,inputs:r})}}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=Du(),n=await this.backend.time(e);return n.wallMs=Du()-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 y5;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}};Bu.nextTensorId=0;Bu.nextVariableId=0;function w9(e){let t=Af(Lt(e),"float32");return $.makeTensor(t,e,"float32")}function g5(){let e=u5();if(e._tfengine==null){let t=new l5(e);e._tfengine=new Bu(t)}return Yk(e._tfengine.ENV),f9(()=>e._tfengine),e._tfengine}var $=g5();function b9(e,t){let n={a:e,b:t};return $.runKernel(Ra,n)}var Vu={};We(Vu,{isBrowser:()=>x5,isMobile:()=>_9});function v9(){return typeof navigator!="undefined"&&navigator!=null}function _9(){if(v9()){let e=navigator.userAgent||navigator.vendor||window.opera;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(e)||/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(e.substr(0,4))}return!1}function x5(){return typeof window!="undefined"&&window.document!=null||typeof WorkerGlobalScope!="undefined"}var _r=J();_r.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.")});_r.registerFlag("IS_BROWSER",()=>x5());_r.registerFlag("IS_NODE",()=>typeof process!="undefined"&&typeof process.versions!="undefined"&&typeof process.versions.node!="undefined");_r.registerFlag("IS_CHROME",()=>typeof navigator!="undefined"&&navigator!=null&&navigator.userAgent!=null&&/Chrome/.test(navigator.userAgent)&&/Google Inc/.test(navigator.vendor));_r.registerFlag("PROD",()=>!1);_r.registerFlag("TENSORLIKE_CHECK_SHAPE_CONSISTENCY",()=>_r.getBool("DEBUG"));_r.registerFlag("DEPRECATION_WARNINGS_ENABLED",()=>!0);_r.registerFlag("IS_TEST",()=>!1);_r.registerFlag("CHECK_COMPUTATION_FOR_ERRORS",()=>!0);_r.registerFlag("WRAP_TO_IMAGEBITMAP",()=>!1);function Or(e,t){let n=e;if(cn(e))return t==="string"?[]:[e.length];if(!Array.isArray(e))return[];let r=[];for(;Array.isArray(n)||cn(n)&&t!=="string";)r.push(n.length),n=n[0];return Array.isArray(e)&&J().getBool("TENSORLIKE_CHECK_SHAPE_CONSISTENCY")&&w5(e,r,[]),r}function w5(e,t,n){if(n=n||[],!Array.isArray(e)&&!cn(e)){F(t.length===0,()=>`Element arr[${n.join("][")}] is a primitive, but should be an array/TypedArray of ${t[0]} elements`);return}F(t.length>0,()=>`Element arr[${n.join("][")}] should be a primitive, but is an array of ${e.length} elements`),F(e.length===t[0],()=>`Element arr[${n.join("][")}] should have ${t[0]} elements, but has ${e.length} elements`);let r=t.slice(1);for(let a=0;a<e.length;++a)w5(e[a],r,n.concat(a))}function b5(e,t,n,r){if(e!=="string_or_numeric"){if(e==null)throw new Error("Expected dtype cannot be null.");if(e!=="numeric"&&e!==t||e==="numeric"&&t==="string")throw new Error(`Argument '${n}' passed to '${r}' must be ${e} tensor, but got ${t} tensor`)}}function C(e,t,n,r="numeric"){if(e instanceof Ge)return b5(r,e.dtype,t,n),e;let a=Fh(e);if(a!=="string"&&["bool","int32","float32"].indexOf(r)>=0&&(a=r),b5(r,a,t,n),e==null||!cn(e)&&!Array.isArray(e)&&typeof e!="number"&&typeof e!="boolean"&&typeof e!="string"){let o=e==null?"null":e.constructor.name;throw new Error(`Argument '${t}' passed to '${n}' must be a Tensor or TensorLike, but got '${o}'`)}let s=Or(e,a);!cn(e)&&!Array.isArray(e)&&(e=[e]);let i=a!=="string"?fd(e,a):ps(e,[],!0);return $.makeTensor(i,s,a)}function Uu(e,t,n,r="numeric"){if(!Array.isArray(e))throw new Error(`Argument ${t} passed to ${n} must be a \`Tensor[]\` or \`TensorLike[]\``);return e.map((a,s)=>C(a,`${t}[${s}]`,n,r))}var _5="__op";function O(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 ${t.length} keys.`);let n=t[0],r=e[n];n.endsWith("_")&&(n=n.substring(0,n.length-1)),n=n+_5;let a=(...s)=>{$.startScope(n);try{let i=r(...s);return gf(i)&&console.error("Cannot return a Promise inside of tidy."),$.endScope(i),i}catch(i){throw $.endScope(null),i}};return Object.defineProperty(a,"name",{value:n,configurable:!0}),a}function k9(e,t){let n=C(e,"real","complex"),r=C(t,"imag","complex");un(n.shape,r.shape,`real and imag shapes, ${n.shape} and ${r.shape}, must match in call to tf.complex().`);let a={real:n,imag:r};return $.runKernel(Wh,a)}var Da=O({complex_:k9});function Oa(e,t,n,r){if(r==null&&(r=Fh(e)),r==="complex64")throw new Error("Cannot construct a complex64 tensor directly. Please use tf.complex(real, imag).");if(!cn(e)&&!Array.isArray(e)&&typeof e!="number"&&typeof e!="boolean"&&typeof e!="string")throw new Error("values passed to tensor(values) must be a number/boolean/string or an array of numbers/booleans/strings, or a TypedArray");if(t!=null){yf(t);let a=Lt(t),s=Lt(n);F(a===s,()=>`Based on the provided shape, [${t}], the tensor should have ${a} values but has ${s}`);for(let i=0;i<n.length;++i){let o=n[i],l=i===n.length-1?o!==Lt(t.slice(i)):!0;F(n[i]===t[i]||!l,()=>`Error creating a new Tensor. Inferred shape (${n}) does not match the provided shape (${t}). `)}}return!cn(e)&&!Array.isArray(e)&&(e=[e]),t=t||n,e=r!=="string"?fd(e,r):ps(e,[],!0),$.makeTensor(e,t,r)}function vr(e,t,n){let r=Or(e,n);return Oa(e,t,r,n)}var Rf={float32:4,float16:2,int32:4,uint16:2,uint8:1,bool:1,complex64:8},gd=4;async function N9(e,t){let n=[],r=[],a=Array.isArray(e)?e.map(i=>i.name):Object.keys(e);for(let i=0;i<a.length;++i){let o=a[i],l=Array.isArray(e)?e[i].tensor:e[o];if(l.dtype!=="float32"&&l.dtype!=="int32"&&l.dtype!=="bool"&&l.dtype!=="string"&&l.dtype!=="complex64")throw new Error(`Unsupported dtype in weight '${o}': ${l.dtype}`);let u={name:o,shape:l.shape,dtype:l.dtype};if(l.dtype==="string"){let c=new Promise(async h=>{let d=await l.bytes(),p=d.reduce((A,y)=>A+y.length,0)+gd*d.length,f=new Uint8Array(p),m=0;for(let A=0;A<d.length;A++){let y=d[A],g=new Uint8Array(new Uint32Array([y.length]).buffer);f.set(g,m),m+=gd,f.set(y,m),m+=y.length}h(f)});r.push(c)}else r.push(l.data());t!=null&&(u.group=t),n.push(u)}let s=await Promise.all(r);return{data:I9(s),specs:n}}function v5(e,t){let n={},r,a=0;for(let s of t){let i=s.name,o=s.dtype,l=s.shape,u=Lt(l),c;if("quantization"in s){let h=s.quantization;if(h.dtype==="uint8"||h.dtype==="uint16"){if(!("min"in h&&"scale"in h))throw new Error(`Weight ${s.name} with quantization ${h.dtype} doesn't have corresponding metadata min and scale.`)}else if(h.dtype==="float16"){if(o!=="float32")throw new Error(`Weight ${s.name} is quantized with ${h.dtype} which only supports weights of type float32 not ${o}.`)}else throw new Error(`Weight ${s.name} has unknown quantization dtype ${h.dtype}. Supported quantization dtypes are: 'uint8', 'uint16', and 'float16'.`);let d=Rf[h.dtype],p=e.slice(a,a+u*d),f=h.dtype==="uint8"?new Uint8Array(p):new Uint16Array(p);if(o==="float32")if(h.dtype==="uint8"||h.dtype==="uint16"){c=new Float32Array(f.length);for(let m=0;m<f.length;m++){let A=f[m];c[m]=A*h.scale+h.min}}else if(h.dtype==="float16")r===void 0&&(r=S9()),c=r(f);else throw new Error(`Unsupported quantization type ${h.dtype} for weight type float32.`);else if(o==="int32"){if(h.dtype!=="uint8"&&h.dtype!=="uint16")throw new Error(`Unsupported quantization type ${h.dtype} for weight type int32.`);c=new Int32Array(f.length);for(let m=0;m<f.length;m++){let A=f[m];c[m]=Math.round(A*h.scale+h.min)}}else throw new Error(`Unsupported dtype in weight '${i}': ${o}`);a+=u*d}else if(o==="string"){let h=Lt(s.shape);c=[];for(let d=0;d<h;d++){let p=new Uint32Array(e.slice(a,a+gd))[0];a+=gd;let f=new Uint8Array(e.slice(a,a+p));c.push(f),a+=p}}else{let h=Rf[o],d=e.slice(a,a+u*h);if(o==="float32")c=new Float32Array(d);else if(o==="int32")c=new Int32Array(d);else if(o==="bool")c=new Uint8Array(d);else if(o==="complex64"){c=new Float32Array(d);let p=new Float32Array(c.length/2),f=new Float32Array(c.length/2);for(let y=0;y<p.length;y++)p[y]=c[y*2],f[y]=c[y*2+1];let m=vr(p,l,"float32"),A=vr(f,l,"float32");n[i]=Da(m,A),m.dispose(),A.dispose()}else throw new Error(`Unsupported dtype in weight '${i}': ${o}`);a+=u*h}o!=="complex64"&&(n[i]=vr(c,l,o))}return n}function I9(e){if(e===null)throw new Error(`Invalid input value: ${JSON.stringify(e)}`);let t=0,n=[];e.forEach(s=>{if(t+=s.byteLength,n.push(s.byteLength===s.buffer.byteLength?s:new s.constructor(s)),!(s instanceof Float32Array||s instanceof Int32Array||s instanceof Uint8Array))throw new Error(`Unsupported TypedArray subtype: ${s.constructor.name}`)});let r=new Uint8Array(t),a=0;return n.forEach(s=>{r.set(new Uint8Array(s.buffer),a),a+=s.byteLength}),r.buffer}var Ff=typeof Buffer!="undefined"&&(typeof Blob=="undefined"||typeof atob=="undefined"||typeof btoa=="undefined");function k5(e){return Ff?Buffer.byteLength(e):new Blob([e]).size}function T9(e){if(Ff)return Buffer.from(e).toString("base64");let t=new Uint8Array(e),n="";for(let r=0,a=t.length;r<a;r++)n+=String.fromCharCode(t[r]);return btoa(n)}function E9(e){if(Ff){let r=Buffer.from(e,"base64");return r.buffer.slice(r.byteOffset,r.byteOffset+r.byteLength)}let t=atob(e),n=new Uint8Array(t.length);for(let r=0;r<t.length;++r)n.set([t.charCodeAt(r)],r);return n.buffer}function Mf(e){if(e.length===1)return e[0];let t=0;e.forEach(a=>{t+=a.byteLength});let n=new Uint8Array(t),r=0;return e.forEach(a=>{n.set(new Uint8Array(a),r),r+=a.byteLength}),n.buffer}function I5(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 Hu(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:k5(JSON.stringify(e.modelTopology)),weightSpecsBytes:e.weightSpecs==null?0:k5(JSON.stringify(e.weightSpecs)),weightDataBytes:e.weightData==null?0:e.weightData.byteLength}}function C9(){let e=n=>{let r=n<<13,a=0;for(;(r&8388608)==0;)a-=8388608,r<<=1;return r&=~8388608,a+=947912704,r|a},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 R9(){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 F9(){let e=new Uint32Array(64);for(let t=0;t<64;t++)e[t]=1024;return e[0]=e[32]=0,e}function S9(){let e=C9(),t=R9(),n=F9();return r=>{let a=new ArrayBuffer(4*r.length),s=new Uint32Array(a);for(let i=0;i<r.length;i++){let o=r[i],l=e[n[o>>10]+(o&1023)]+t[o>>10];s[i]=l}return new Float32Array(a)}}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 r=[];return(t==="load"?Rt.getInstance().loadRouters:Rt.getInstance().saveRouters).forEach(a=>{let s=a(e,n);s!==null&&r.push(s)}),r}},M9=e=>Rt.registerSaveRouter(e),$9=e=>Rt.registerLoadRouter(e),D9=e=>Rt.getSaveHandlers(e),O9=(e,t)=>Rt.getLoadHandlers(e,t),$f="tensorflowjs",Df=1,ci="models_store",za="model_info_store";function N5(){if(!J().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 Of(e){let t=e.result;t.createObjectStore(ci,{keyPath:"modelPath"}),t.createObjectStore(za,{keyPath:"modelPath"})}var hi=class{constructor(e){if(this.indexedDB=N5(),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,r)=>{let a=this.indexedDB.open($f,Df);a.onupgradeneeded=()=>Of(a),a.onsuccess=()=>{let s=a.result;if(t==null){let i=s.transaction(ci,"readonly"),o=i.objectStore(ci).get(this.modelPath);o.onsuccess=()=>{if(o.result==null)return s.close(),r(new Error(`Cannot find model with path '${this.modelPath}' in IndexedDB.`));n(o.result.modelArtifacts)},o.onerror=l=>(s.close(),r(o.error)),i.oncomplete=()=>s.close()}else{let i=Hu(t),o=s.transaction(za,"readwrite"),l=o.objectStore(za),u=l.put({modelPath:this.modelPath,modelArtifactsInfo:i}),c;u.onsuccess=()=>{c=s.transaction(ci,"readwrite");let h=c.objectStore(ci).put({modelPath:this.modelPath,modelArtifacts:t,modelArtifactsInfo:i});h.onsuccess=()=>n({modelArtifactsInfo:i}),h.onerror=d=>{l=o.objectStore(za);let p=l.delete(this.modelPath);p.onsuccess=()=>(s.close(),r(h.error)),p.onerror=f=>(s.close(),r(h.error))}},u.onerror=h=>(s.close(),r(u.error)),o.oncomplete=()=>{c==null?s.close():c.oncomplete=()=>s.close()}}},a.onerror=s=>r(a.error)})}};hi.URL_SCHEME="indexeddb://";var S5=e=>J().getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(hi.URL_SCHEME)?z9(e.slice(hi.URL_SCHEME.length)):null;Rt.registerSaveRouter(S5);Rt.registerLoadRouter(S5);function z9(e){return new hi(e)}function P9(e){return e.startsWith(hi.URL_SCHEME)?e.slice(hi.URL_SCHEME.length):e}var L9=class{constructor(){this.indexedDB=N5()}async listModels(){return new Promise((e,t)=>{let n=this.indexedDB.open($f,Df);n.onupgradeneeded=()=>Of(n),n.onsuccess=()=>{let r=n.result,a=r.transaction(za,"readonly"),s=a.objectStore(za).getAll();s.onsuccess=()=>{let i={};for(let o of s.result)i[o.modelPath]=o.modelArtifactsInfo;e(i)},s.onerror=i=>(r.close(),t(s.error)),a.oncomplete=()=>r.close()},n.onerror=r=>t(n.error)})}async removeModel(e){return e=P9(e),new Promise((t,n)=>{let r=this.indexedDB.open($f,Df);r.onupgradeneeded=()=>Of(r),r.onsuccess=()=>{let a=r.result,s=a.transaction(za,"readwrite"),i=s.objectStore(za),o=i.get(e),l;o.onsuccess=()=>{if(o.result==null)return a.close(),n(new Error(`Cannot find model with path '${e}' in IndexedDB.`));{let u=i.delete(e),c=()=>{l=a.transaction(ci,"readwrite");let h=l.objectStore(ci).delete(e);h.onsuccess=()=>t(o.result.modelArtifactsInfo),h.onerror=d=>n(o.error)};u.onsuccess=c,u.onerror=h=>(c(),a.close(),n(o.error))}},o.onerror=u=>(a.close(),n(o.error)),s.oncomplete=()=>{l==null?a.close():l.oncomplete=()=>a.close()}},r.onerror=a=>n(r.error)})}},la="/",ll="tensorflowjs_models",T5="info",W9="model_topology",B9="weight_specs",V9="weight_data",U9="model_metadata";function E5(e){return{info:[ll,e,T5].join(la),topology:[ll,e,W9].join(la),weightSpecs:[ll,e,B9].join(la),weightData:[ll,e,V9].join(la),modelMetadata:[ll,e,U9].join(la)}}function H9(e){let t=e.split(la);if(t.length<3)throw new Error(`Invalid key format: ${e}`);return t.slice(1,t.length-1).join(la)}function j9(e){return e.startsWith(di.URL_SCHEME)?e.slice(di.URL_SCHEME.length):e}var di=class{constructor(e){if(!J().getBool("IS_BROWSER")||typeof window=="undefined"||typeof window.localStorage=="undefined")throw new Error("The current environment does not support local storage.");if(this.LS=window.localStorage,e==null||!e)throw new Error("For local storage, modelPath must not be null, undefined or empty.");this.modelPath=e,this.keys=E5(this.modelPath)}async save(e){if(e.modelTopology instanceof ArrayBuffer)throw new Error("BrowserLocalStorage.save() does not support saving model topology in binary formats yet.");{let t=JSON.stringify(e.modelTopology),n=JSON.stringify(e.weightSpecs),r=Hu(e);try{this.LS.setItem(this.keys.info,JSON.stringify(r)),this.LS.setItem(this.keys.topology,t),this.LS.setItem(this.keys.weightSpecs,n),this.LS.setItem(this.keys.weightData,T9(e.weightData));let a={format:e.format,generatedBy:e.generatedBy,convertedBy:e.convertedBy};return e.signature!=null&&(a.signature=e.signature),e.userDefinedMetadata!=null&&(a.userDefinedMetadata=e.userDefinedMetadata),e.modelInitializer!=null&&(a.modelInitializer=e.modelInitializer),this.LS.setItem(this.keys.modelMetadata,JSON.stringify(a)),{modelArtifactsInfo:r}}catch(a){throw this.LS.removeItem(this.keys.info),this.LS.removeItem(this.keys.topology),this.LS.removeItem(this.keys.weightSpecs),this.LS.removeItem(this.keys.weightData),this.LS.removeItem(this.keys.modelMetadata),new Error(`Failed to save model '${this.modelPath}' to local storage: size quota being exceeded is a possible cause of this failure: modelTopologyBytes=${r.modelTopologyBytes}, weightSpecsBytes=${r.weightSpecsBytes}, weightDataBytes=${r.weightDataBytes}.`)}}}async load(){let e=JSON.parse(this.LS.getItem(this.keys.info));if(e==null)throw new Error(`In local storage, there is no model with name '${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 '${this.modelPath}' is missing.`);t.modelTopology=n;let r=JSON.parse(this.LS.getItem(this.keys.weightSpecs));if(r==null)throw new Error(`In local storage, the weight specs of model '${this.modelPath}' are missing.`);t.weightSpecs=r;let a=this.LS.getItem(this.keys.modelMetadata);if(a!=null){let i=JSON.parse(a);t.format=i.format,t.generatedBy=i.generatedBy,t.convertedBy=i.convertedBy,i.signature!=null&&(t.signature=i.signature),i.userDefinedMetadata!=null&&(t.userDefinedMetadata=i.userDefinedMetadata),i.modelInitializer!=null&&(t.modelInitializer=i.modelInitializer)}let s=this.LS.getItem(this.keys.weightData);if(s==null)throw new Error(`In local storage, the binary weight values of model '${this.modelPath}' are missing.`);return t.weightData=E9(s),t}};di.URL_SCHEME="localstorage://";var C5=e=>J().getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(di.URL_SCHEME)?G9(e.slice(di.URL_SCHEME.length)):null;Rt.registerSaveRouter(C5);Rt.registerLoadRouter(C5);function G9(e){return new di(e)}var q9=class{constructor(){F(J().getBool("IS_BROWSER"),()=>"Current environment is not a web browser"),F(typeof window=="undefined"||typeof window.localStorage!="undefined",()=>"Current browser does not appear to support localStorage"),this.LS=window.localStorage}async listModels(){let e={},t=ll+la,n=la+T5;for(let r=0;r<this.LS.length;++r){let a=this.LS.key(r);if(a.startsWith(t)&&a.endsWith(n)){let s=H9(a);e[s]=JSON.parse(this.LS.getItem(a))}}return e}async removeModel(e){e=j9(e);let t=E5(e);if(this.LS.getItem(t.info)==null)throw new Error(`Cannot find model at path '${e}'`);let n=JSON.parse(this.LS.getItem(t.info));return this.LS.removeItem(t.info),this.LS.removeItem(t.topology),this.LS.removeItem(t.weightSpecs),this.LS.removeItem(t.weightData),n}},ul="://",Yn=class{constructor(){this.managers={}}static getInstance(){return Yn.instance==null&&(Yn.instance=new Yn),Yn.instance}static registerManager(e,t){F(e!=null,()=>"scheme must not be undefined or null."),e.endsWith(ul)&&(e=e.slice(0,e.indexOf(ul))),F(e.length>0,()=>"scheme must not be an empty string.");let n=Yn.getInstance();F(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 xd(e){if(e.indexOf(ul)===-1)throw new Error(`The url string provided does not contain a scheme. Supported schemes are: ${Yn.getSchemes().join(",")}`);return{scheme:e.split(ul)[0],path:e.split(ul)[1]}}async function R5(e,t,n=!1){F(e!==t,()=>`Old path and new path are the same: '${e}'`);let r=Rt.getLoadHandlers(e);F(r.length>0,()=>`Copying failed because no load handler is found for source URL ${e}.`),F(r.length<2,()=>`Copying failed because more than one (${r.length}) load handlers for source URL ${e}.`);let a=r[0],s=Rt.getSaveHandlers(t);F(s.length>0,()=>`Copying failed because no save handler is found for destination URL ${t}.`),F(s.length<2,()=>`Copying failed because more than one (${r.length}) save handlers for destination URL ${t}.`);let i=s[0],o=xd(e).scheme,l=xd(e).path,u=o===xd(e).scheme,c=await a.load();n&&u&&await Yn.getManager(o).removeModel(l);let h=await i.save(c);return n&&!u&&await Yn.getManager(o).removeModel(l),h.modelArtifactsInfo}async function X9(){let e=Yn.getSchemes(),t={};for(let n of e){let r=await Yn.getManager(n).listModels();for(let a in r){let s=n+ul+a;t[s]=r[a]}}return t}async function K9(e){let t=xd(e);return Yn.getManager(t.scheme).removeModel(t.path)}async function Z9(e,t){return R5(e,t,!1)}async function Y9(e,t){return R5(e,t,!0)}var J9=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(J().get("IS_BROWSER")){J().setPlatform("browser",new J9);try{Yn.registerManager(di.URL_SCHEME,new q9)}catch(e){}try{Yn.registerManager(hi.URL_SCHEME,new L9)}catch(e){}}var Q9={importFetch:()=>Y8()},zf,eI=class{constructor(){this.util=require("util"),this.textEncoder=new this.util.TextEncoder}fetch(e,t){return J().global.fetch!=null?J().global.fetch(e,t):(zf==null&&(zf=Q9.importFetch()),zf(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)}};J().get("IS_NODE")&&J().setPlatform("node",new eI);function Ue(e,t="float32",n){return t=t||"float32",yf(e),new Wt(e,t,n)}function tI(e,t){let n=C(e,"x","cast");if(!n5(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 r={x:n},a={dtype:t};return $.runKernel(gs,r,a)}var ge=O({cast_:tI});function nI(e){let t={x:C(e,"x","clone","string_or_numeric")};return $.runKernel(Rs,t)}var zr=O({clone_:nI});function F5(e,t=!1){console.log(e.toString(t))}g5();var rI={buffer:Ue,cast:ge,clone:zr,print:F5};m9(rI);var Nn={};We(Nn,{browserFiles:()=>aI,browserHTTPRequest:()=>iI,concatenateArrayBuffers:()=>Mf,copyModel:()=>Z9,decodeWeights:()=>v5,encodeWeights:()=>N9,fromMemory:()=>oI,getLoadHandlers:()=>O9,getModelArtifactsInfoForJSON:()=>Hu,getSaveHandlers:()=>D9,http:()=>Lf,isHTTPScheme:()=>Pf,listModels:()=>X9,loadWeights:()=>sI,moveModel:()=>Y9,registerLoadRouter:()=>$9,registerSaveRouter:()=>M9,removeModel:()=>K9,weightsLoaderFactory:()=>M5,withSaveHandler:()=>lI});var uI="model",cI=".json",hI=".weights.bin";function $5(e){return new Promise(t=>setTimeout(t)).then(e)}var cl=class{constructor(e){if(!J().getBool("IS_BROWSER"))throw new Error("browserDownloads() cannot proceed because the current environment is not a browser.");e.startsWith(cl.URL_SCHEME)&&(e=e.slice(cl.URL_SCHEME.length)),(e==null||e.length===0)&&(e=uI),this.modelTopologyFileName=e+cI,this.weightDataFileName=e+hI}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}],r={modelTopology:e.modelTopology,format:e.format,generatedBy:e.generatedBy,convertedBy:e.convertedBy,weightsManifest:n};e.signature!=null&&(r.signature=e.signature),e.userDefinedMetadata!=null&&(r.userDefinedMetadata=e.userDefinedMetadata),e.modelInitializer!=null&&(r.modelInitializer=e.modelInitializer);let a=window.URL.createObjectURL(new Blob([JSON.stringify(r)],{type:"application/json"})),s=this.jsonAnchor==null?document.createElement("a"):this.jsonAnchor;if(s.download=this.modelTopologyFileName,s.href=a,await $5(()=>s.dispatchEvent(new MouseEvent("click"))),e.weightData!=null){let i=this.weightDataAnchor==null?document.createElement("a"):this.weightDataAnchor;i.download=this.weightDataFileName,i.href=t,await $5(()=>i.dispatchEvent(new MouseEvent("click")))}return{modelArtifactsInfo:Hu(e)}}}};cl.URL_SCHEME="downloads://";var dI=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.files=e}async load(){let e=this.files[0],t=this.files.slice(1);return new Promise((n,r)=>{let a=new FileReader;a.onload=s=>{let i=JSON.parse(s.target.result),o=i.modelTopology;if(o==null){r(new Error(`modelTopology field is missing from file ${e.name}`));return}t.length===0&&n({modelTopology:o});let l=i.weightsManifest;if(l==null){r(new Error(`weightManifest field is missing from file ${e.name}`));return}let u;try{u=this.checkManifestAndWeightFiles(l,t)}catch(p){r(p);return}let c=[],h=[],d=[];l.forEach(p=>{p.paths.forEach(f=>{h.push(f),d.push(null)}),c.push(...p.weights)}),l.forEach(p=>{p.paths.forEach(f=>{let m=new FileReader;m.onload=A=>{let y=A.target.result,g=h.indexOf(f);if(d[g]=y,d.indexOf(null)===-1){let b={modelTopology:o,weightSpecs:c,weightData:Mf(d),format:i.format,generatedBy:i.generatedBy,convertedBy:i.convertedBy};i.signature!=null&&(b.signature=i.signature),i.userDefinedMetadata!=null&&(b.userDefinedMetadata=i.userDefinedMetadata),i.modelInitializer!=null&&(b.modelInitializer=i.modelInitializer),n(b)}},m.onerror=A=>r(`Failed to weights data from file of path '${f}'.`),m.readAsArrayBuffer(u[f])})})},a.onerror=s=>r(`Failed to read model topology and weights manifest JSON from file '${e.name}'. BrowserFiles supports loading Keras-style tf.Model artifacts only.`),a.readAsText(e)})}checkManifestAndWeightFiles(e,t){let n=[],r=t.map(s=>I5(s.name)),a={};for(let s of e)s.paths.forEach(i=>{let o=I5(i);if(n.indexOf(o)!==-1)throw new Error(`Duplicate file basename found in weights manifest: '${o}'`);if(n.push(o),r.indexOf(o)===-1)throw new Error(`Weight file with basename '${o}' is not provided.`);a[i]=t[r.indexOf(o)]});if(n.length!==t.length)throw new Error(`Mismatch in the number of files in weights manifest (${n.length}) and the number of weight files provided (${t.length}).`);return a}},fI=e=>J().getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(cl.URL_SCHEME)?pI(e.slice(cl.URL_SCHEME.length)):null;Rt.registerSaveRouter(fI);function pI(e="model"){return new cl(e)}function aI(e){return new dI(e)}function D5(e,t,n,r){i(e),n=n==null?0:n,r=r==null?1:r,o(n,r);let a=0,s=l=>(l.then(u=>{let c=n+ ++a/e.length*(r-n);return t(c),u}),l);function i(l){F(l!=null&&Array.isArray(l)&&l.length>0,()=>"promises must be a none empty array")}function o(l,u){F(l>=0&&l<=1,()=>`Progress fraction must be in range [0, 1], but got startFraction ${l}`),F(u>=0&&u<=1,()=>`Progress fraction must be in range [0, 1], but got endFraction ${u}`),F(u>=l,()=>`startFraction must be no more than endFraction, but got startFraction ${l} and endFraction ${u}`)}return Promise.all(e.map(s))}async function O5(e,t){t==null&&(t={});let n=t.fetchFunc==null?J().platform.fetch:t.fetchFunc,r=e.map(u=>n(u,t.requestInit,{isBinary:!0})),a=0,s=.5,i=(t.onProgress==null?await Promise.all(r):await D5(r,t.onProgress,a,s)).map(u=>u.arrayBuffer()),o=.5,l=1;return t.onProgress==null?await Promise.all(i):await D5(i,t.onProgress,o,l)}async function sI(e,t="",n,r){return M5(a=>O5(a,{requestInit:r}))(e,t,n)}function M5(e){return async(t,n="",r)=>{let a=t.map(()=>!1),s={},i=r!=null?r.map(()=>!1):[],o=[];if(t.forEach((p,f)=>{let m=0;p.weights.forEach(A=>{let y="quantization"in A?A.quantization.dtype:A.dtype,g=Rf[y]*Lt(A.shape),b=()=>{a[f]=!0,s[f]==null&&(s[f]=[]),s[f].push({manifestEntry:A,groupOffset:m,sizeBytes:g})};r!=null?r.forEach((_,w)=>{_===A.name&&(b(),i[w]=!0)}):b(),o.push(A.name),m+=g})}),!i.every(p=>p)){let p=r.filter((f,m)=>!i[m]);throw new Error(`Could not find weights in manifest with names: ${p.join(", ")}.
|
|
Manifest JSON has weights with names: ${o.join(", ")}.`)}let l=a.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),h={},d=0;return l.forEach(p=>{let f=t[p].paths.length,m=0;for(let b=0;b<f;b++)m+=c[d+b].byteLength;let A=new ArrayBuffer(m),y=new Uint8Array(A),g=0;for(let b=0;b<f;b++){let _=new Uint8Array(c[d+b]);y.set(_,g),g+=_.byteLength}s[p].forEach(b=>{let _=A.slice(b.groupOffset,b.groupOffset+b.sizeBytes),w=v5(_,[b.manifestEntry]);for(let x in w)h[x]=w[x]}),d+=f}),h}}var mI="application/octet-stream",AI="application/json",Wf=class{constructor(e,t){if(this.DEFAULT_METHOD="POST",t==null&&(t={}),this.weightPathPrefix=t.weightPathPrefix,this.onProgress=t.onProgress,this.weightUrlConverter=t.weightUrlConverter,t.fetchFunc!=null?(F(typeof t.fetchFunc=="function",()=>"Must pass a function that matches the signature of `fetch` (see https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API)"),this.fetch=t.fetchFunc):this.fetch=J().platform.fetch,F(e!=null&&e.length>0,()=>"URL path for http must not be null, undefined or empty."),Array.isArray(e)&&F(e.length===2,()=>`URL paths for http must have a length of 2, (actual length is ${e.length}).`),this.path=e,t.requestInit!=null&&t.requestInit.body!=null)throw new Error("requestInit is expected to have no pre-existing body, but has one.");this.requestInit=t.requestInit||{}}async save(e){if(e.modelTopology instanceof ArrayBuffer)throw new Error("BrowserHTTPRequest.save() does not support saving model topology in binary formats yet.");let t=Object.assign({method:this.DEFAULT_METHOD},this.requestInit);t.body=new FormData;let n=[{paths:["./model.weights.bin"],weights:e.weightSpecs}],r={modelTopology:e.modelTopology,format:e.format,generatedBy:e.generatedBy,convertedBy:e.convertedBy,weightsManifest:n};e.signature!=null&&(r.signature=e.signature),e.userDefinedMetadata!=null&&(r.userDefinedMetadata=e.userDefinedMetadata),e.modelInitializer!=null&&(r.modelInitializer=e.modelInitializer),t.body.append("model.json",new Blob([JSON.stringify(r)],{type:AI}),"model.json"),e.weightData!=null&&t.body.append("model.weights.bin",new Blob([e.weightData],{type:mI}),"model.weights.bin");let a=await this.fetch(this.path,t);if(a.ok)return{modelArtifactsInfo:Hu(e),responses:[a]};throw new Error(`BrowserHTTPRequest.save() failed due to HTTP response status ${a.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(p){let f=`Failed to parse model JSON of response from ${this.path}.`;throw this.path.endsWith(".pb")?f+=" 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.":f+=" Please make sure the server is serving valid JSON for this request.",new Error(f)}let n=t.modelTopology,r=t.weightsManifest,a=t.generatedBy,s=t.convertedBy,i=t.format,o=t.signature,l=t.userDefinedMetadata;if(n==null&&r==null)throw new Error(`The JSON from HTTP path ${this.path} contains neither model topology or manifest for weights.`);let u,c;r!=null&&([u,c]=await this.loadWeights(r));let h={modelTopology:n,weightSpecs:u,weightData:c,generatedBy:a,convertedBy:s,format:i};o!=null&&(h.signature=o),l!=null&&(h.userDefinedMetadata=l);let d=t.modelInitializer;return d&&(h.modelInitializer=d),h}async loadWeights(e){let t=Array.isArray(this.path)?this.path[1]:this.path,[n,r]=yI(t),a=this.weightPathPrefix||n,s=[];for(let u of e)s.push(...u.weights);let i=[],o=[];for(let u of e)for(let c of u.paths)this.weightUrlConverter!=null?o.push(this.weightUrlConverter(c)):i.push(a+c+r);this.weightUrlConverter&&i.push(...await Promise.all(o));let l=await O5(i,{requestInit:this.requestInit,fetchFunc:this.fetch,onProgress:this.onProgress});return[s,Mf(l)]}};Wf.URL_SCHEME_REGEX=/^https?:\/\//;function yI(e){let t=e.lastIndexOf("/"),n=e.lastIndexOf("?"),r=e.substring(0,t),a=n>t?e.substring(n):"";return[r+"/",a]}function Pf(e){return e.match(Wf.URL_SCHEME_REGEX)!=null}var z5=(e,t)=>{if(typeof fetch=="undefined"&&(t==null||t.fetchFunc==null))return null;{let n=!0;if(Array.isArray(e)?n=e.every(r=>Pf(r)):n=Pf(e),n)return Lf(e,t)}return null};Rt.registerSaveRouter(z5);Rt.registerLoadRouter(z5);function Lf(e,t){return new Wf(e,t)}function iI(e,t){return Lf(e,t)}var Bf=class{constructor(e){this.modelArtifacts=e}async load(){return this.modelArtifacts}},gI=class{constructor(e){this.saveHandler=e}async save(e){return this.saveHandler(e)}};function oI(e,t,n,r){return arguments.length===1?e.modelTopology!=null||e.weightSpecs!=null?new Bf(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 Bf({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 Bf({modelTopology:e,weightSpecs:t,weightData:n,trainingConfig:r}))}function lI(e){return new gI(e)}var P5={};We(P5,{confusionMatrix:()=>xI});function wI(e,t,n=!1,r=!1){let a=C(e,"a","matMul"),s=C(t,"b","matMul");[a,s]=Nt(a,s);let i={a,b:s},o={transposeA:n,transposeB:r};return $.runKernel(ys,i,o)}var Ke=O({matMul_:wI});function bI(e,t,n=1,r=0){if(t<2)throw new Error(`Error in oneHot: depth must be >=2, but it is ${t}`);let a={indices:C(e,"indices","oneHot","int32")},s={depth:t,onValue:n,offValue:r};return $.runKernel(Bs,a,s)}var hl=O({oneHot_:bI});function _I(e,t){let n=C(e,"x","transpose");if(t==null&&(t=n.shape.map((s,i)=>i).reverse()),F(n.rank===t.length,()=>`Error in transpose: rank of input ${n.rank} must match length of perm ${t}.`),t.forEach(s=>{F(s>=0&&s<n.rank,()=>`All entries in 'perm' must be between 0 and ${n.rank-1} but got ${t}`)}),n.rank<=1)return n.clone();let r={x:n},a={perm:t};return $.runKernel(si,r,a)}var ot=O({transpose_:_I});function vI(e,t,n){let r=C(e,"labels","confusionMatrix"),a=C(t,"predictions","confusionMatrix");F(n==null||n>0&&Number.isInteger(n),()=>`If provided, numClasses must be a positive integer, but got ${n}`),F(r.rank===1,()=>`Expected the rank of labels to be 1, but got ${r.rank}`),F(a.rank===1,()=>`Expected the rank of predictions to be 1, but got ${a.rank}`),F(r.shape[0]===a.shape[0],()=>`Mismatch in the number of examples: ${r.shape[0]} vs. ${a.shape[0]}. Labels and predictions should have the same number of elements.`),F(n>0&&Number.isInteger(n),()=>`numClasses is required to be a positive integer, but got ${n}`);let s=hl(ge(r,"int32"),n),i=hl(ge(a,"int32"),n),o=ot(s),l=Ke(o,i);return ge(l,"int32")}var xI=O({confusionMatrix_:vI}),dl={};We(dl,{fromPixels:()=>NI,fromPixelsAsync:()=>kI,toPixels:()=>II});function wd(e,t,n){if(ds(e),t!=null&&t.length!==3)throw new Error("tensor3d() requires shape to have three numbers");let r=Or(e,n);if(r.length!==3&&r.length!==1)throw new Error("tensor3d() requires values to be number[][][] or flat/TypedArray");if(r.length===1&&t==null)throw new Error("tensor3d() requires shape to be provided when `values` are a flat array");return Oa(e,t,r,n)}var pl;function L5(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,r=!1,a=!1,s=!1,i=!1,o=!1;if(e.data instanceof Uint8Array)n=!0;else if(typeof ImageData!="undefined"&&e instanceof ImageData)r=!0;else if(typeof HTMLVideoElement!="undefined"&&e instanceof HTMLVideoElement)a=!0;else if(typeof HTMLImageElement!="undefined"&&e instanceof HTMLImageElement)s=!0;else if(e.getContext!=null)i=!0;else if(typeof ImageBitmap!="undefined"&&e instanceof ImageBitmap)o=!0;else throw new Error(`pixels passed to tf.browser.fromPixels() must be either an HTMLVideoElement, HTMLImageElement, HTMLCanvasElement, ImageData in browser, or OffscreenCanvas, ImageData in webworker or {data: Uint32Array, width: number, height: number}, but was ${e.constructor.name}`);if(a){let d=2;if(a&&e.readyState<d)throw new Error("The video element has not loaded data yet. Please wait for `loadeddata` event on the <video> element.")}if(pd(dd,$.backendName)!=null){let d={pixels:e},p={numChannels:t};return $.runKernel(dd,d,p)}let[l,u]=a?[e.videoWidth,e.videoHeight]:[e.width,e.height],c;i?c=e.getContext("2d").getImageData(0,0,l,u).data:r||n?c=e.data:(s||a||o)&&(pl==null&&(pl=document.createElement("canvas").getContext("2d")),pl.canvas.width=l,pl.canvas.height=u,pl.drawImage(e,0,0,l,u),c=pl.getImageData(0,0,l,u).data);let h;if(t===4)h=new Int32Array(c);else{let d=l*u;h=new Int32Array(d*t);for(let p=0;p<d;p++)for(let f=0;f<t;++f)h[p*t+f]=c[p*4+f]}return wd(h,[u,l,t],"int32")}function SI(e){return e!=null&&e.data instanceof Uint8Array}function TI(){return typeof window!="undefined"&&typeof ImageBitmap!="undefined"&&window.hasOwnProperty("createImageBitmap")}function EI(e){return e!=null&&e.width!==0&&e.height!==0}function CI(e){return TI()&&!(e instanceof ImageBitmap)&&EI(e)&&!SI(e)}async function kI(e,t=3){let n=null;if(J().getBool("WRAP_TO_IMAGEBITMAP")&&CI(e)){let r;try{r=await createImageBitmap(e,{premultiplyAlpha:"none"})}catch(a){r=null}r!=null&&r.width===e.width&&r.height===e.height?n=r:n=e}else n=e;return L5(n,t)}async function II(e,t){let n=C(e,"img","toPixels");if(!(e instanceof Ge)){let u=n;n=ge(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[r,a]=n.shape.slice(0,2),s=n.rank===2?1:n.shape[2];if(s>4||s===2)throw new Error(`toPixels only supports depth of size 1, 3 or 4 but got ${s}`);if(n.dtype!=="float32"&&n.dtype!=="int32")throw new Error(`Unsupported type for toPixels: ${n.dtype}. Please use float32 or int32 tensors.`);let i=await n.data(),o=n.dtype==="float32"?255:1,l=new Uint8ClampedArray(a*r*4);for(let u=0;u<r*a;++u){let c=[0,0,0,255];for(let d=0;d<s;d++){let p=i[u*s+d];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}.`);s===1?(c[0]=p*o,c[1]=p*o,c[2]=p*o):c[d]=p*o}let h=u*4;l[h+0]=Math.round(c[0]),l[h+1]=Math.round(c[1]),l[h+2]=Math.round(c[2]),l[h+3]=Math.round(c[3])}if(t!=null){t.width=a,t.height=r;let u=t.getContext("2d"),c=new ImageData(l,a,r);u.putImageData(c,0,0)}return n!==e&&n.dispose(),l}var NI=O({fromPixels_:L5}),Vf={};We(Vf,{prepareAndValidate:()=>W5});function W5(e,t){let n=e.shape.length,r=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(r<1)throw new Error(`tf.gatherND() expects the indices to be rank 1 or higher, but the rank was ${r}.`);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[r-1]>n)throw new Error(`index innermost dimension length must be <= tensor rank; saw: ${t.shape[r-1]} vs. ${n}`);if(Lt(e.shape)===0)throw new Error(`Requested more than 0 entries, but input is empty. Input shape: ${e.shape}.`);let a=t.shape,s=a[a.length-1],i=1;for(let h=0;h<a.length-1;++h)i*=a[h];let o=e.shape,l=a.slice();l.pop();let u=1;for(let h=s;h<n;++h)u*=o[h],l.push(o[h]);let c=[...ro(e.shape).map(h=>h/u),1].slice(0,s);return[l,i,u,c]}var Uf={};We(Uf,{calculateShapes:()=>B5,validateInput:()=>jf,validateUpdateShape:()=>Hf});function Hf(e,t,n){let r=t.rank>1?t.shape[t.rank-1]:1,a=t.rank>1?t.rank-1:1,s=`Must have updates.shape = indices.shape[:batchDim] + shape[sliceDim:], got updates.shape: ${n.shape}, indices.shape: ${t.shape}, shape: ${e}, sliceDim: ${r}, and batchDim: ${a}.`;if(n.rank<a)throw new Error(s+` update.rank < ${a}. `);if(e.length<r+(n.rank-a))throw new Error(s+` Output shape length < ${r+(n.rank-a)}`);if(n.rank!==a+e.length-r)throw new Error(s+` update.rank != ${a+e.length-r}`);for(let i=0;i<a;++i)if(n.shape[i]!==t.shape[i])throw new Error(s+` updates.shape[${i}] (${n.shape[i]}) != indices.shape[${i}] (${t.shape[i]}).`);for(let i=0;i<n.rank-a;++i)if(n.shape[i+a]!==e[i+r])throw new Error(s+` updates.shape[${i+a}] (${n.shape[i+a]}) != shape[${i+a}] (${e[i+a]})`)}function jf(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: ${e.shape}`)}Hf(n,t,e)}function B5(e,t,n){let r=t.shape.length,a=r>1?t.shape[r-1]:1,s=n.length,i=1;for(let h=a;h<s;++h)i*=n[h];let o=a<1?1:a,l=Lt(t.shape)/o,u=[...ro(n.slice(0,a)),1],c=Lt(n);return{sliceRank:a,numUpdates:l,sliceSize:i,strides:u,outputSize:c}}var fn={};We(fn,{assertParamsValid:()=>RI,computeFlatOffset:()=>MI,computeOutShape:()=>V5,getNormalizedAxes:()=>H5,isSliceContinous:()=>FI,maskToAxes:()=>bd,parseSliceParams:()=>Z5,sliceInfo:()=>$I,startForAxis:()=>X5,startIndicesWithElidedDims:()=>j5,stopForAxis:()=>K5,stopIndicesWithElidedDims:()=>G5,stridesForAxis:()=>q5,stridesWithElidedDims:()=>U5});function RI(e,t,n){let r=e.shape.length;F(r===t.length,()=>`Error in slice${r}D: Length of begin ${t} must match the rank of the array (${r}).`),F(r===n.length,()=>`Error in slice${r}D: Length of size ${n} must match the rank of the array (${r}).`);for(let a=0;a<r;++a)F(t[a]+n[a]<=e.shape[a],()=>`Error in slice${r}D: begin[${a}] + size[${a}] (${t[a]+n[a]}) would overflow input.shape[${a}] (${e.shape[a]})`)}function bd(e){let t=[],n=0;for(;e>0;)e&1&&t.push(n),e/=2,n++;return t}function V5(e,t,n){let r=[];for(let a=0;a<e.length;a++)r[a]=Math.ceil((t[a]-e[a])/n[a]);return r}function U5(e,t,n,r){let a=[...e];for(let s=a.length;s<r.length;s++)a.push(1);for(let s=0;s<n;s++)s===0?a[t]=1:(a.splice(t,0,1),a.pop());return a}function Y5(e,t,n){return n<=e?n:n-(t-1)}function J5(e,t){let n=[];for(let r=0;r<e;r++)n.push(t+r);return n}function H5(e,t,n,r,a,s,i,o,l){let u=e.length,c=new Array(u),h=new Array(u),d=new Array(u);if(t.length&&n>0){let p=t[0],f=n+1;c=j5(i,p,f,r,e),h=G5(o,p,f,a,e),d=U5(s,p,f,e)}else for(let p=0;p<u;p++)c[p]=X5(i,r,s,e,p,l),h[p]=K5(o,a,s,e,p,l),d[p]=q5(s,p,l);return{begin:c,end:h,strides:d}}function j5(e,t,n,r,a){let s=[...a],i=J5(n,t);for(let o=0;o<s.length;o++)if(i.indexOf(o)>-1)s[o]=0;else{let l=Y5(t,n,o),u=r[l];e&1<<l&&(u=0),s[o]=u}return s}function G5(e,t,n,r,a){let s=[...a],i=J5(n,t);for(let o=0;o<s.length;o++)if(i.indexOf(o)>-1)s[o]=Number.MAX_SAFE_INTEGER;else{let l=Y5(t,n,o),u=r[l];e&1<<l&&(u=Number.MAX_SAFE_INTEGER),s[o]=u}for(let o=0;o<s.length;o++){let l=a[o];s[o]<0&&(s[o]+=l),s[o]=mu(0,s[o],a[o])}return s}function q5(e,t,n){let r=e[t];return(n&1<<t||r==null)&&(r=1),r}function X5(e,t,n,r,a,s){let i=t[a],o=n[a]||1;(e&1<<a||s&1<<a||i==null)&&(o>0?i=Number.MIN_SAFE_INTEGER:i=Number.MAX_SAFE_INTEGER);let l=r[a];return i<0&&(i+=l),i=mu(0,i,l-1),i}function K5(e,t,n,r,a,s){let i=t[a],o=n[a]||1;(e&1<<a||s&1<<a||i==null)&&(o>0?i=Number.MAX_SAFE_INTEGER:i=Number.MIN_SAFE_INTEGER);let l=r[a];return i<0&&(i+=l),o>0?i=mu(0,i,l):i=mu(-1,i,l-1),i}function FI(e,t,n){let r=n.length;for(let a=0;a<n.length;a++)if(n[a]>1){r=a;break}for(let a=r+1;a<n.length;a++)if(t[a]>0||n[a]!==e[a])return!1;return!0}function MI(e,t){let n=e.length>0?e[e.length-1]:1;for(let r=0;r<e.length-1;r++)n+=e[r]*t[r];return n}function Z5(e,t,n){let r,a=e.shape.length;typeof t=="number"?r=[t,...new Array(a-1).fill(0)]:t.length<a?r=t.concat(new Array(a-t.length).fill(0)):r=t.slice(),r.forEach(i=>{F(i!==-1,()=>"slice() does not support negative begin indexing.")});let s;return n==null?s=new Array(a).fill(-1):typeof n=="number"?s=[n,...new Array(a-1).fill(-1)]:n.length<a?s=n.concat(new Array(a-n.length).fill(-1)):s=n,s=s.map((i,o)=>i>=0?i:(F(i===-1,()=>`Negative size values should be exactly -1 but got ${i} for the slice() size at index ${o}.`),e.shape[o]-r[o])),[r,s]}function $I(e,t,n,r,a,s,i,o,l){let u=t.slice(),c=n.slice(),h=r;r==null&&(h=new Array(u.length));let d=bd(i);if(d.length>1)throw new Error("Multiple ellipses in slice is not allowed.");if(i!==0&&o!==0)throw new Error("Using both ellipsisMask and newAxisMask is not yet supported.");if(i!==0&&l!==0)throw new Error("Using both ellipsisMask and shrinkAxisMask is not yet supported.");let p=e.length-u.length,f=bd(o),m=e.slice();f.forEach(x=>{u[x]=0,c[x]=1,m.splice(x,0,1)});let{begin:A,end:y,strides:g}=H5(m,d,p,u,c,h,a,s,i);u=A,c=y,h=g;let b=bd(l);b.forEach(x=>{c[x]=u[x]+1,h[x]=1});let _=V5(u,c,h),w=_.filter((x,N)=>b.indexOf(N)===-1);return{nonStrided:h.every(x=>x===1),$begin:u,$end:c,$strides:h,size:_,newShape:m,outShape:w}}var ae={};We(ae,{Serializable:()=>Q5,SerializationMap:()=>pi,registerClass:()=>Pa});var Q5=class{getClassName(){return this.constructor.className}static fromConfig(e,t){return new e(t)}},pi=class{constructor(){this.classNameMap={}}static getMap(){return pi.instance==null&&(pi.instance=new pi),pi.instance}static register(e){pi.getMap().classNameMap[e.className]=[e,e.fromConfig]}};function Pa(e){F(e.className!=null,()=>"Class being registered does not have the static className property defined."),F(typeof e.className=="string",()=>"className is required to be a string, but got type "+typeof e.className),F(e.className.length>0,()=>"Class being registered has an empty-string as its className, which is disallowed."),pi.register(e)}var ex={};We(ex,{TEST_EPSILON_FLOAT16:()=>tx,encodeStrings:()=>nx,expectArrayBuffersEqual:()=>WI,expectArraysClose:()=>DI,expectArraysEqual:()=>zI,expectNumbersClose:()=>PI,expectPromiseToFail:()=>OI,expectValuesInRange:()=>LI,testEpsilon:()=>Gf});var BI=.001,tx=.1;function DI(e,t,n){return n==null&&(n=Gf()),qf(e,t,(r,a)=>Xf(r,a,n))}function Gf(){return $.backend.floatPrecision()===32?BI:tx}function qf(e,t,n){let r=!0;if((cn(e)||cn(t))&&(r=!1),cn(e)&&cn(t)&&(r=!0),r){let i=e.constructor.name,o=t.constructor.name;if(i!==o)throw new Error(`Arrays are of different type. Actual: ${i}. Expected: ${o}`)}if(Array.isArray(e)&&Array.isArray(t)){let i=Or(e),o=Or(t);if(!oa(i,o))throw new Error(`Arrays have different shapes. Actual: [${i}]. Expected: [${o}]`)}let a=cn(e)?e:ps(e),s=cn(t)?t:ps(t);if(a.length!==s.length)throw new Error(`Arrays have different lengths actual: ${a.length} vs expected: ${s.length}.
|
|
Actual: ${a}.
|
|
Expected: ${s}.`);for(let i=0;i<s.length;++i){let o=a[i],l=s[i];if(!n(o,l))throw new Error(`Arrays differ: actual[${i}] = ${o}, expected[${i}] = ${l}.
|
|
Actual: ${a}.
|
|
Expected: ${s}.`)}}function OI(e,t){e().then(()=>t.fail(),()=>t())}function zI(e,t){let n=typeof t=="string"||typeof t=="number"||typeof t=="boolean"?[t]:t;return Ea(e)||Ea(e[0])||Ea(t)||Ea(t[0])?qf(e,n,(r,a)=>r==a):qf(e,t,(r,a)=>Xf(r,a,0))}function PI(e,t,n){if(n==null&&(n=Gf()),!Xf(e,t,n))throw new Error(`Numbers differ: actual === ${e}, expected === ${t}`)}function Xf(e,t,n){return!isFinite(e)&&!isFinite(t)?!0:!(isNaN(e)||isNaN(t)||Math.abs(e-t)>n)}function LI(e,t,n){for(let r=0;r<e.length;r++)if(e[r]<t||e[r]>n)throw new Error(`Value out of range:${e[r]} low: ${t}, high: ${n}`)}function WI(e,t){expect(new Float32Array(e)).toEqual(new Float32Array(t))}function nx(e){for(let t=0;t<e.length;t++){let n=e[t];Array.isArray(n)?nx(n):e[t]=Ou(n)}return e}var VI="3.3.0";function UI(){J().set("PROD",!0)}function HI(){J().set("DEBUG",!0)}function jI(){J().set("DEPRECATION_WARNINGS_ENABLED",!1),console.warn("TensorFlow.js deprecation warnings have been disabled.")}function Kf(e){J().getBool("DEPRECATION_WARNINGS_ENABLED")&&console.warn(e+" You can disable deprecation warnings with tf.disableDeprecationWarnings().")}A9(Kf);function GI(){$.disposeVariables()}function Pr(){return $}function _d(){return $.memory()}function kr(e){return $.profile(e)}function B(e,t){return $.tidy(e,t)}function Me(e){kf(e).forEach(t=>t.dispose())}function Zt(e){return $.keep(e)}function qI(e){return $.time(e)}function XI(e){return $.setBackend(e)}function KI(){return $.ready()}function ZI(){return $.backendName}function YI(e){$.removeBackend(e)}function Zf(e){return $.findBackend(e)}function JI(e){return $.findBackendFactory(e)}function fl(e,t,n=1){return $.registerBackend(e,t,n)}function rx(){return $.backend}function QI(e,t){J().setPlatform(e,t)}function eN(e,t){let n=C(e,"a","add"),r=C(t,"b","add");[n,r]=Nt(n,r);let a={a:n,b:r};return $.runKernel(Ra,a)}var ie=O({add_:eN});function tN(e,t){let n=C(e,"a","floorDiv"),r=C(t,"b","floorDiv");[n,r]=Nt(n,r);let a={a:n,b:r};return $.runKernel(Ts,a)}var vd=O({floorDiv_:tN});function nN(e,t){let n=C(e,"a","div"),r=C(t,"b","div");if([n,r]=Nt(n,r),n.dtype==="int32"&&r.dtype==="int32")return vd(n,r);let a={a:n,b:r},s={};return $.runKernel(Is,a,s)}var be=O({div_:nN});function rN(e,t){let n=C(e,"a","mul"),r=C(t,"b","mul");[n,r]=Nt(n,r);let a={a:n,b:r};return $.runKernel(Ws,a)}var P=O({mul_:rN});function aN(e){let t=C(e,"x","abs");if(t.dtype==="complex64"){let n={x:t};return $.runKernel(wu,n)}else{let n={x:t};return $.runKernel(so,n)}}var Bt=O({abs_:aN});function sN(e){let t={x:C(e,"x","acos")};return $.runKernel(io,t)}var Yf=O({acos_:sN});function iN(e){let t={x:C(e,"x","acosh")};return $.runKernel(oo,t)}var Jf=O({acosh_:iN});function oN(e){F(Array.isArray(e),()=>"The argument passed to tf.addN() must be a list of tensors"),F(e.length>=1,()=>`Must pass at least one tensor to tf.addN(), but got ${e.length}`);let t=e.map((a,s)=>C(a,`tensors${s}`,"addN")),n=t[0];t.forEach(a=>{if(a.dtype!==n.dtype)throw new Error("All tensors passed to tf.addN() must have the same dtype")}),t.forEach(a=>{if(!oa(a.shape,n.shape))throw new Error("All tensors passed to tf.addN() must have the same shape")});let r=t;return $.runKernel(fs,r)}var La=O({addN_:oN});function lN(e,t=null,n=!1){let r={x:C(e,"x","all","bool")},a={axis:t,keepDims:n};return $.runKernel(Dh,r,a)}var kd=O({all_:lN});function uN(e,t=null,n=!1){let r={x:C(e,"x","any","bool")},a={axis:t,keepDims:n};return $.runKernel(Oh,r,a)}var ju=O({any_:uN});function cN(e,t=0){let n={x:C(e,"x","argMax")},r={axis:t};return $.runKernel(ms,n,r)}var Gu=O({argMax_:cN});function hN(e,t=0){let n={x:C(e,"x","argMin")},r={axis:t};return $.runKernel(yu,n,r)}var Qf=O({argMin_:hN});function dN(e){let t={x:C(e,"x","asin")};return $.runKernel(lo,t)}var em=O({asin_:dN});function pN(e){let t={x:C(e,"x","asinh")};return $.runKernel(uo,t)}var tm=O({asinh_:pN});function fN(e){let t={x:C(e,"x","atan")};return $.runKernel(co,t)}var nm=O({atan_:fN});function mN(e,t){let n=C(e,"a","atan2"),r=C(t,"b","atan2");[n,r]=Nt(n,r);let a={a:n,b:r};return $.runKernel(po,a)}var rm=O({atan2_:mN});function AN(e){let t={x:C(e,"x","atanh")};return $.runKernel(ho,t)}var am=O({atanh_:AN});function yN(e,t,n,r,a="NHWC",s){let i=e[3],o=[...t,i],l=ax(a);return qu(e,o,n,s,r,null,null,l)}function sx(e,t,n,r,a,s,i="channelsLast"){let[o,l]=Id(t),u;if(i==="channelsLast")u=[o,l,e[3],e[3]];else if(i==="channelsFirst")u=[o,l,e[1],e[1]];else throw new Error(`Unknown dataFormat ${i}`);return qu(e,u,n,r,a,s,!1,i)}function gN(e,t,n,r,a,s,i="NDHWC"){let[o,l,u]=sm(t),c,h;if(i==="NDHWC")h="channelsLast",c=[o,l,u,e[4],e[4]];else if(i==="NCDHW")h="channelsFirst",c=[o,l,u,e[1],e[1]];else throw new Error(`Unknown dataFormat ${i}`);return ix(e,c,n,r,a,!1,h,s)}function qu(e,t,n,r,a,s,i=!1,o="channelsLast"){let[l,u,c,h]=[-1,-1,-1,-1];if(o==="channelsLast")[l,u,c,h]=e;else if(o==="channelsFirst")[l,h,u,c]=e;else throw new Error(`Unknown dataFormat ${o}`);let[d,p,,f]=t,[m,A]=Id(n),[y,g]=Id(r),b=ml(d,y),_=ml(p,g),{padInfo:w,outHeight:x,outWidth:N}=xN(a,u,c,m,A,b,_,s,o),S=i?f*h:f,T;return o==="channelsFirst"?T=[l,S,x,N]:o==="channelsLast"&&(T=[l,x,N,S]),{batchSize:l,dataFormat:o,inHeight:u,inWidth:c,inChannels:h,outHeight:x,outWidth:N,outChannels:S,padInfo:w,strideHeight:m,strideWidth:A,filterHeight:d,filterWidth:p,effectiveFilterHeight:b,effectiveFilterWidth:_,dilationHeight:y,dilationWidth:g,inShape:e,outShape:T,filterShape:t}}function ix(e,t,n,r,a,s=!1,i="channelsLast",o){let[l,u,c,h,d]=[-1,-1,-1,-1,-1];if(i==="channelsLast")[l,u,c,h,d]=e;else if(i==="channelsFirst")[l,d,u,c,h]=e;else throw new Error(`Unknown dataFormat ${i}`);let[p,f,m,,A]=t,[y,g,b]=sm(n),[_,w,x]=sm(r),N=ml(p,_),S=ml(f,w),T=ml(m,x),{padInfo:M,outDepth:D,outHeight:z,outWidth:W}=wN(a,u,c,h,y,g,b,N,S,T,o),U=s?A*d:A,H;return i==="channelsFirst"?H=[l,U,D,z,W]:i==="channelsLast"&&(H=[l,D,z,W,U]),{batchSize:l,dataFormat:i,inDepth:u,inHeight:c,inWidth:h,inChannels:d,outDepth:D,outHeight:z,outWidth:W,outChannels:U,padInfo:M,strideDepth:y,strideHeight:g,strideWidth:b,filterDepth:p,filterHeight:f,filterWidth:m,effectiveFilterDepth:N,effectiveFilterHeight:S,effectiveFilterWidth:T,dilationDepth:_,dilationHeight:w,dilationWidth:x,inShape:e,outShape:H,filterShape:t}}function bN(e,t,n,r,a){r==null&&(r=im(e,t,n));let s=e[0],i=e[1],o=fi((s-t+2*r)/n+1,a),l=fi((i-t+2*r)/n+1,a);return[o,l]}function _N(e,t,n,r,a,s){a==null&&(a=im(e,t,r));let i=e[0],o=e[1],l=e[2],u=fi((i-t+2*a)/r+1,s),c=fi((o-t+2*a)/r+1,s),h=fi((l-t+2*a)/r+1,s);return[u,c,h,n]}function im(e,t,n,r=1){let a=ml(t,r);return Math.floor((e[0]*(n-1)-n+a)/2)}function Id(e){return typeof e=="number"?[e,e,e]:e.length===2?[e[0],e[1],1]:e}function sm(e){return typeof e=="number"?[e,e,e]:e}function ml(e,t){return t<=1?e:e+(e-1)*(t-1)}function xN(e,t,n,r,a,s,i,o,l){let u,c,h;if(typeof e=="number"){u={top:e,bottom:e,left:e,right:e,type:e===0?"VALID":"NUMBER"};let d=bN([t,n],s,r,e,o);c=d[0],h=d[1]}else if(e==="same"){c=Math.ceil(t/r),h=Math.ceil(n/a);let d=Math.max(0,(c-1)*r+s-t),p=Math.max(0,(h-1)*a+i-n),f=Math.floor(d/2),m=d-f,A=Math.floor(p/2),y=p-A;u={top:f,bottom:m,left:A,right:y,type:"SAME"}}else if(e==="valid")u={top:0,bottom:0,left:0,right:0,type:"VALID"},c=Math.ceil((t-s+1)/r),h=Math.ceil((n-i+1)/a);else if(typeof e=="object"){let d=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:d,bottom:p,left:f,right:m,type:d===0&&p===0&&f===0&&m===0?"VALID":"EXPLICIT"},c=fi((t-s+d+p)/r+1,o),h=fi((n-i+f+m)/a+1,o)}else throw Error(`Unknown padding parameter: ${e}`);return{padInfo:u,outHeight:c,outWidth:h}}function wN(e,t,n,r,a,s,i,o,l,u,c){let h,d,p,f;if(typeof e=="number"){h={top:e,bottom:e,left:e,right:e,front:e,back:e,type:e===0?"VALID":"NUMBER"};let m=_N([t,n,r,1],o,1,a,e,c);d=m[0],p=m[1],f=m[2]}else if(e==="same"){d=Math.ceil(t/a),p=Math.ceil(n/s),f=Math.ceil(r/i);let m=(d-1)*a+o-t,A=(p-1)*s+l-n,y=(f-1)*i+u-r,g=Math.floor(m/2),b=m-g,_=Math.floor(A/2),w=A-_,x=Math.floor(y/2),N=y-x;h={top:_,bottom:w,left:x,right:N,front:g,back:b,type:"SAME"}}else if(e==="valid")h={top:0,bottom:0,left:0,right:0,front:0,back:0,type:"VALID"},d=Math.ceil((t-o+1)/a),p=Math.ceil((n-l+1)/s),f=Math.ceil((r-u+1)/i);else throw Error(`Unknown padding parameter: ${e}`);return{padInfo:h,outDepth:d,outHeight:p,outWidth:f}}function fi(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 Wa(e){let[t,n,r]=Id(e);return t===1&&n===1&&r===1}function Lr(e,t){return Wa(e)||Wa(t)}function ax(e){if(e==="NHWC")return"channelsLast";if(e==="NCHW")return"channelsFirst";throw new Error(`Unknown dataFormat ${e}`)}function vN(e,t){let n={x:C(e,"x","reshape","string_or_numeric")},r={shape:t};return $.runKernel(Ho,n,r)}var G=O({reshape_:vN});function kN(e,t,n,r,a){let s=C(e,"x","avgPool","float32"),i=1;F(Lr(n,i),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${n} and dilations '${i}'`);let o=s,l=!1;s.rank===3&&(l=!0,o=G(s,[1,s.shape[0],s.shape[1],s.shape[2]])),F(o.rank===4,()=>`Error in avgPool: x must be rank 4 but got rank ${o.rank}.`),a!=null&&F(Kt(r),()=>`Error in avgPool: pad must be an integer when using, dimRoundingMode ${a} but got pad ${r}.`);let u={x:o},c={filterSize:t,strides:n,pad:r,dimRoundingMode:a},h=$.runKernel(As,u,c);return h=ge(h,s.dtype),l?G(h,[h.shape[1],h.shape[2],h.shape[3]]):h}var Xu=O({avgPool_:kN});function IN(e,t,n,r,a,s="NDHWC"){let i=C(e,"x","avgPool3d","float32"),o=i,l=!1;i.rank===4&&(l=!0,o=G(i,[1,i.shape[0],i.shape[1],i.shape[2],i.shape[3]])),F(o.rank===5,()=>`Error in avgPool3d: x must be rank 5 but got rank ${o.rank}.`),F(s==="NDHWC",()=>`Error in avgPool3d: Only NDHWC is currently supported, but got dataFormat of ${s}`),a!=null&&F(Kt(r),()=>`Error in avgPool3d: pad must be an integer when using, dimRoundingMode ${a} but got pad ${r}.`);let u={x:o},c={filterSize:t,strides:n,pad:r,dimRoundingMode:a,dataFormat:s},h=$.runKernel(gu,u,c);return h=ge(h,o.dtype),l?G(h,[h.shape[1],h.shape[2],h.shape[3],h.shape[4]]):h}var om=O({avgPool3d_:IN});function NN(e,t=0){F(e.length>=1,()=>"Pass at least one tensor to concat");let n=Uu(e,"tensors","concat","string_or_numeric");if(n[0].dtype==="complex64"&&n.forEach(s=>{if(s.dtype!=="complex64")throw new Error(`Cannot concatenate complex64 tensors with a tensor
|
|
with dtype ${s.dtype}. `)}),n.length===1)return zr(n[0]);let r=n,a={axis:t};return $.runKernel(fo,r,a)}var lt=O({concat_:NN});function SN(e){let t={x:C(e,"x","sigmoid")};return $.runKernel(Js,t)}var On=O({sigmoid_:SN});function TN(e,t,n){let r=C(e,"x","slice","string_or_numeric");if(r.rank===0)throw new Error("Slicing scalar is not possible");let a={x:r},s={begin:t,size:n};return $.runKernel(Xo,a,s)}var $e=O({slice_:TN});function EN(e){let t={x:C(e,"x","tanh")};return $.runKernel(ai,t)}var Al=O({tanh_:EN});function CN(e,t,n,r,a,s){let i=C(e,"forgetBias","basicLSTMCell"),o=C(t,"lstmKernel","basicLSTMCell"),l=C(n,"lstmBias","basicLSTMCell"),u=C(r,"data","basicLSTMCell"),c=C(a,"c","basicLSTMCell"),h=C(s,"h","basicLSTMCell"),d=lt([u,h],1),p=Ke(d,o),f=ie(p,l),m=f.shape[0],A=f.shape[1]/4,y=[m,A],g=$e(f,[0,0],y),b=$e(f,[0,A],y),_=$e(f,[0,A*2],y),w=$e(f,[0,A*3],y),x=ie(P(On(g),Al(b)),P(c,On(ie(i,_)))),N=P(Al(x),On(w));return[x,N]}var RN=O({basicLSTMCell_:CN});function FN(e,t,n){let r=C(e,"x","batchToSpaceND"),a=t.reduce((o,l)=>o*l);F(r.rank>=1+t.length,()=>`input rank is ${r.rank} but should be > than blockShape.length ${t.length}`),F(n.length===t.length,()=>`crops.length is ${n.length} but should be equal to blockShape.length ${t.length}`),F(r.shape[0]%a==0,()=>`input tensor batch is ${r.shape[0]} but is not divisible by the product of the elements of blockShape ${t.join(" * ")} === ${a}`);let s={x:r},i={blockShape:t,crops:n};return $.runKernel(xu,s,i)}var Ku=O({batchToSpaceND_:FN});function MN(e){let t;return e.rank===0||e.rank===1?t=G(e,[1,1,1,e.size]):e.rank===2?t=G(e,[1,1,e.shape[0],e.shape[1]]):e.rank===3?t=G(e,[1,e.shape[0],e.shape[1],e.shape[2]]):t=e,t}function $N(e,t,n,r,a,s){s==null&&(s=.001);let i=C(e,"x","batchNorm"),o=C(t,"mean","batchNorm"),l=C(n,"variance","batchNorm"),u;a!=null&&(u=C(a,"scale","batchNorm"));let c;r!=null&&(c=C(r,"offset","batchNorm")),F(o.rank===l.rank,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),F(c==null||o.rank===c.rank,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),F(u==null||o.rank===u.rank,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let h={x:MN(i),scale:u,offset:c,mean:o,variance:l},d={varianceEpsilon:s},p=$.runKernel(Es,h,d);return G(p,i.shape)}var mi=O({batchNorm_:$N});function DN(e,t,n,r,a,s){let i=C(e,"x","batchNorm"),o=C(t,"mean","batchNorm"),l=C(n,"variance","batchNorm"),u;a!=null&&(u=C(a,"scale","batchNorm"));let c;return r!=null&&(c=C(r,"offset","batchNorm")),F(i.rank===2,()=>`Error in batchNorm2D: x must be rank 2 but got rank ${i.rank}.`),F(o.rank===2||o.rank===1,()=>`Error in batchNorm2D: mean must be rank 2 or rank 1 but got rank ${o.rank}.`),F(l.rank===2||l.rank===1,()=>`Error in batchNorm2D: variance must be rank 2 or rank 1 but got rank ${l.rank}.`),u!=null&&F(u.rank===2||u.rank===1,()=>`Error in batchNorm2D: scale must be rank 2 or rank 1 but got rank ${u.rank}.`),c!=null&&F(c.rank===2||c.rank===1,()=>`Error in batchNorm2D: offset must be rank 2 or rank 1 but got rank ${c.rank}.`),mi(i,o,l,c,u,s)}var ox=O({batchNorm2d_:DN});function ON(e,t,n,r,a,s){let i=C(e,"x","batchNorm"),o=C(t,"mean","batchNorm"),l=C(n,"variance","batchNorm"),u;a!=null&&(u=C(a,"scale","batchNorm"));let c;return r!=null&&(c=C(r,"offset","batchNorm")),F(i.rank===3,()=>`Error in batchNorm3D: x must be rank 3 but got rank ${i.rank}.`),F(o.rank===3||o.rank===1,()=>`Error in batchNorm3D: mean must be rank 3 or rank 1 but got rank ${o.rank}.`),F(l.rank===3||l.rank===1,()=>`Error in batchNorm3D: variance must be rank 3 or rank 1 but got rank ${l.rank}.`),u!=null&&F(u.rank===3||u.rank===1,()=>`Error in batchNorm3D: scale must be rank 3 or rank 1 but got rank ${u.rank}.`),c!=null&&F(c.rank===3||c.rank===1,()=>`Error in batchNorm3D: offset must be rank 3 or rank 1 but got rank ${c.rank}.`),mi(i,o,l,c,u,s)}var lx=O({batchNorm3d_:ON});function zN(e,t,n,r,a,s){let i=C(e,"x","batchNorm"),o=C(t,"mean","batchNorm"),l=C(n,"variance","batchNorm"),u;a!=null&&(u=C(a,"scale","batchNorm"));let c;return r!=null&&(c=C(r,"offset","batchNorm")),F(i.rank===4,()=>`Error in batchNorm4D: x must be rank 4 but got rank ${i.rank}.`),F(o.rank===4||o.rank===1,()=>`Error in batchNorm4D: mean must be rank 4 or rank 1 but got rank ${o.rank}.`),F(l.rank===4||l.rank===1,()=>`Error in batchNorm4D: variance must be rank 4 or rank 1 but got rank ${l.rank}.`),u!=null&&F(u.rank===4||u.rank===1,()=>`Error in batchNorm4D: scale must be rank 4 or rank 1 but got rank ${u.rank}.`),c!=null&&F(c.rank===4||c.rank===1,()=>`Error in batchNorm4D: offset must be rank 4 or rank 1 but got rank ${c.rank}.`),mi(i,o,l,c,u,s)}var ux=O({batchNorm4d_:zN});function PN(e,t,n){let r=C(e,"x","bincount"),a=C(t,"weights","bincount");F(r.dtype==="int32",()=>`Error in bincount: input dtype must be int32, but got ${r.dtype}`),F(n>=0,()=>`size must be non-negative, but got ${n}.`),F(a.size===r.size||a.size===0,()=>`Error in bincount: weights must have the same size as input or0-length, but got input shape: ${r.shape}, weights shape: ${a.shape}.`);let s={x:r,weights:a},i={size:n};return $.runKernel(Lh,s,i)}var cx=O({bincount_:PN});function LN(e,t){let n=C(e,"broadcastTo","x"),r=n.shape;if(t.some(l=>!(l>0)||l%1!=0))throw new Error(`broadcastTo(): Invalid broadcast shape [${t}].`);if(t.length<n.rank)throw new Error(`broadcastTo(): shape.length=${t.length} < input.rank=${n.rank}.`);if(t.length>n.rank){let l=n.shape.slice();for(;l.length<t.length;)l.unshift(1);n=G(n,l)}let a=n.shape,s=Array.from(t);for(let l=t.length-1;l>=0;l--)if(a[l]===t[l])s[l]=1;else if(n.shape[l]!==1)throw new Error(`broadcastTo(): [${r}] cannot be broadcast to [${t}].`);if(s.map((l,u)=>l>1?u:-1).filter(l=>l>=0).length===0)return zr(n);let i={x:n},o={reps:s};return $.runKernel(Ma,i,o)}var Zu=O({broadcastTo_:LN});function WN(e){let t={x:C(e,"x","ceil")};return $.runKernel(xs,t)}var lm=O({ceil_:WN});function BN(e,t,n){let r=C(e,"x","clipByValue");F(t<=n,()=>`Error in clip: min (${t}) must be less than or equal to max (${n}).`);let a={x:r},s={clipValueMin:t,clipValueMax:n};return $.runKernel(Fa,a,s)}var Sn=O({clipByValue_:BN});function VN(e){return lt(e,0)}var hx=O({concat1d_:VN});function UN(e,t){return lt(e,t)}var yl=O({concat2d_:UN});function HN(e,t){return lt(e,t)}var dx=O({concat3d_:HN});function jN(e,t){return lt(e,t)}var px=O({concat4d_:jN});function GN(e,t,n,r,a="NHWC",s=[1,1],i){let o=C(e,"x","conv2d"),l=C(t,"filter","conv2d"),u=o,c=!1;o.rank===3&&(c=!0,u=G(o,[1,o.shape[0],o.shape[1],o.shape[2]])),F(u.rank===4,()=>`Error in conv2d: input must be rank 4, but got rank ${u.rank}.`),F(l.rank===4,()=>`Error in conv2d: filter must be rank 4, but got rank ${l.rank}.`),i!=null&&F(Kt(r),()=>`Error in conv2d: pad must be an integer when using, dimRoundingMode ${i} but got pad ${r}.`);let h=a==="NHWC"?u.shape[3]:u.shape[1];F(h===l.shape[2],()=>`Error in conv2d: depth of input (${h}) must match input depth for filter ${l.shape[2]}.`),F(Lr(n,s),()=>`Error in conv2D: Either strides or dilations must be 1. Got strides ${n} and dilations '${s}'`);let d={x:u,filter:l},p={strides:n,pad:r,dataFormat:a,dilations:s,dimRoundingMode:i},f=$.runKernel(ws,d,p);return c?G(f,[f.shape[1],f.shape[2],f.shape[3]]):f}var ua=O({conv2d_:GN});function qN(e,t,n,r,a="NWC",s=1,i){let o=C(e,"x","conv1d"),l=C(t,"filter","conv1d"),u=o,c=!1;o.rank===2&&(c=!0,u=G(o,[1,o.shape[0],o.shape[1]])),F(u.rank===3,()=>`Error in conv1d: input must be rank 3, but got rank ${u.rank}.`),F(l.rank===3,()=>`Error in conv1d: filter must be rank 3, but got rank ${l.rank}.`),i!=null&&F(Kt(r),()=>`Error in conv1d: pad must be an integer when using, dimRoundingMode ${i} but got pad ${r}.`),F(u.shape[2]===l.shape[1],()=>`Error in conv1d: depth of input (${u.shape[2]}) must match input depth for filter ${l.shape[1]}.`),F(Lr(n,s),()=>`Error in conv1D: Either stride or dilation must be 1. Got stride ${n} and dilation '${s}'`),F(a==="NWC",()=>`Error in conv1d: got dataFormat of ${a} but only NWC is currently supported.`);let h=G(l,[1,l.shape[0],l.shape[1],l.shape[2]]),d=G(u,[u.shape[0],1,u.shape[1],u.shape[2]]),p=ua(d,h,[1,n],r,"NHWC",[1,s],i);return c?G(p,[p.shape[2],p.shape[3]]):G(p,[p.shape[0],p.shape[2],p.shape[3]])}var Nd=O({conv1d_:qN});function XN(e,t,n,r,a,s="NHWC",i){F(e.length===t.rank,()=>`Length of inShape (${e.length}) and rank of dy (${t.rank}) must match`);let o=e,l=t,u=!1;t.rank===3&&(u=!0,l=G(t,[1,t.shape[0],t.shape[1],t.shape[2]]),o=[1,e[0],e[1],e[2]]),F(o.length===4,()=>`Error in conv2dDerInput: inShape must be length 4, but got length ${o.length}.`),F(l.rank===4,()=>`Error in conv2dDerInput: dy must be rank 4, but got rank ${l.rank}`),F(n.rank===4,()=>`Error in conv2dDerInput: filter must be rank 4, but got rank ${n.rank}`);let c=s==="NHWC"?o[3]:o[1],h=s==="NHWC"?l.shape[3]:l.shape[1];F(c===n.shape[2],()=>`Error in conv2dDerInput: depth of input (${c}) must match input depth for filter ${n.shape[2]}.`),F(h===n.shape[3],()=>`Error in conv2dDerInput: depth of output (${h}) must match output depth for filter ${n.shape[3]}.`),i!=null&&F(Kt(a),()=>`Error in conv2dDerInput: pad must be an integer when using, dimRoundingMode ${i} but got pad ${a}.`);let d={dy:l,filter:n},p={strides:r,pad:a,dataFormat:s,dimRoundingMode:i,inputShape:o},f=$.runKernel(bs,d,p);return u?G(f,[f.shape[1],f.shape[2],f.shape[3]]):f}var um=O({conv2DBackpropInput_:XN});function KN(e,t,n,r,a,s){let i=C(e,"x","conv2dTranspose"),o=C(t,"filter","conv2dTranspose");return um(n,i,o,r,a,"NHWC",s)}var Sd=O({conv2dTranspose_:KN});function ZN(e,t,n,r,a="NDHWC",s=[1,1,1]){let i=C(e,"x","conv3d"),o=C(t,"filter","conv3d"),l=i,u=!1;i.rank===4&&(u=!0,l=G(i,[1,i.shape[0],i.shape[1],i.shape[2],i.shape[3]])),F(l.rank===5,()=>`Error in conv3d: input must be rank 5, but got rank ${l.rank}.`),F(o.rank===5,()=>`Error in conv3d: filter must be rank 5, but got rank ${o.rank}.`),F(l.shape[4]===o.shape[3],()=>`Error in conv3d: depth of input (${l.shape[4]}) must match input depth for filter ${o.shape[3]}.`),F(Lr(n,s),()=>`Error in conv3D: Either strides or dilations must be 1. Got strides ${n} and dilations '${s}'`),F(a==="NDHWC",()=>`Error in conv3d: got dataFormat of ${a} but only NDHWC is currently supported.`);let c={x:l,filter:o},h={strides:n,pad:r,dataFormat:a,dilations:s},d=$.runKernel(bu,c,h);return u?G(d,[d.shape[1],d.shape[2],d.shape[3],d.shape[4]]):d}var cm=O({conv3d_:ZN});function YN(e,t,n,r,a){F(e.length===t.rank,()=>`Length of inShape (${e.length}) and rank of dy (${t.rank}) must match`);let s=e,i=t,o=!1;t.rank===4&&(o=!0,i=G(t,[1,t.shape[0],t.shape[1],t.shape[2],t.shape[3]]),s=[1,e[0],e[1],e[2],e[3]]);let l=s[4],u=i.shape[4];F(s.length===5,()=>`Error in conv3dDerInput: inShape must be length 5, but got length ${s.length}.`),F(i.rank===5,()=>`Error in conv3dDerInput: dy must be rank 5, but got rank ${i.rank}`),F(n.rank===5,()=>`Error in conv3dDerInput: filter must be rank 5, but got rank ${n.rank}`),F(l===n.shape[3],()=>`Error in conv3dDerInput: depth of input (${l}) must match input depth for filter ${n.shape[3]}.`),F(u===n.shape[4],()=>`Error in conv3dDerInput: depth of output (${u}) must match output depth for filter ${n.shape[4]}.`);let c={dy:i,filter:n},h={pad:a,strides:r,inputShape:s},d=$.runKernel(Uh,c,h);return o?G(d,[d.shape[1],d.shape[2],d.shape[3],d.shape[4]]):d}var fx=O({conv3DBackpropInput_:YN});function JN(e,t,n,r,a){let s=C(e,"x","conv3dTranspose"),i=C(t,"filter","conv3dTranspose");return fx(n,s,i,r,a)}var QN=O({conv3dTranspose_:JN});function eS(e){let t={x:C(e,"x","cos")};return $.runKernel(_s,t)}var Yu=O({cos_:eS});function tS(e){let t={x:C(e,"x","cosh")};return $.runKernel(mo,t)}var Td=O({cosh_:tS});function nS(e,t=0,n=!1,r=!1){let a={x:C(e,"x","cumsum")},s={axis:t,exclusive:n,reverse:r};return $.runKernel(vs,a,s)}var Ed=O({cumsum_:nS});function rS(e,t,n,r=!1){let a=C(e,"x","denseBincount"),s=C(t,"weights","denseBincount");F(a.dtype==="int32",()=>`Error in denseBincount: input dtype must be int32, but got ${a.dtype}`),F(a.rank<=2,()=>`Error in denseBincount: input must be at most rank 2, but got rank ${a.rank}.`),F(n>=0,()=>`size must be non-negative, but got ${n}.`),F(s.size===a.size||s.size===0,()=>`Error in denseBincount: weights must have the same shape as x or 0-length, but got x shape: ${a.shape}, weights shape: ${s.shape}.`);let i={x:a,weights:s},o={size:n,binaryOutput:r};return $.runKernel(Hh,i,o)}var mx=O({denseBincount_:rS});function aS(e,t,n="NHWC"){let r=C(e,"x","depthToSpace"),a=n==="NHWC"?r.shape[1]:r.shape[2],s=n==="NHWC"?r.shape[2]:r.shape[3],i=n==="NHWC"?r.shape[3]:r.shape[1];F(a*t>=0,()=>`Negative dimension size caused by overflow when multiplying
|
|
${a} and ${t} for depthToSpace with input shape
|
|
${r.shape}`),F(s*t>=0,()=>`Negative dimension size caused by overflow when multiplying
|
|
${s} and ${t} for depthToSpace with input shape
|
|
${r.shape}`),F(i%(t*t)==0,()=>`Dimension size must be evenly divisible by ${t*t} but is ${i} for depthToSpace with input shape ${r.shape}`);let o={x:r},l={blockSize:t,dataFormat:n};return $.runKernel(yo,o,l)}var hm=O({depthToSpace_:aS});function sS(e,t,n,r,a="NHWC",s=[1,1],i){let o=C(e,"x","depthwiseConv2d"),l=C(t,"filter","depthwiseConv2d"),u=o,c=!1;o.rank===3&&(c=!0,u=G(o,[1,o.shape[0],o.shape[1],o.shape[2]])),F(u.rank===4,()=>`Error in depthwiseConv2d: input must be rank 4, but got rank ${u.rank}.`),F(l.rank===4,()=>`Error in depthwiseConv2d: filter must be rank 4, but got rank ${l.rank}.`),F(u.shape[3]===l.shape[2],()=>`Error in depthwiseConv2d: number of input channels (${u.shape[3]}) must match the inChannels dimension in filter ${l.shape[2]}.`),i!=null&&F(Kt(r),()=>`Error in depthwiseConv2d: pad must be an integer when using, dimRoundingMode ${i} but got pad ${r}.`);let h={x:u,filter:l},d={strides:n,pad:r,dataFormat:a,dilations:s,dimRoundingMode:i},p=$.runKernel(ks,h,d);return c?G(p,[p.shape[1],p.shape[2],p.shape[3]]):p}var gl=O({depthwiseConv2d_:sS});function iS(e){let t={x:C(e,"x","diag")};return $.runKernel(qh,t)}var oS=O({diag_:iS});function lS(e,t,n,r,a=[1,1],s="NHWC"){let i=C(e,"x","dilation2d"),o=C(t,"filter","dilation2d");F(i.rank===3||i.rank===4,()=>`Error in dilation2d: input must be rank 3 or 4, but got rank ${i.rank}.`),F(o.rank===3,()=>`Error in dilation2d: filter must be rank 3, but got rank ${o.rank}.`),F(s==="NHWC",()=>`Error in dilation2d: Only NHWC is currently supported, but got dataFormat of ${s}`);let l=i,u=!1;i.rank===3&&(l=G(i,[1,i.shape[0],i.shape[1],i.shape[2]]),u=!0);let c={x:l,filter:o},h={strides:n,pad:r,dilations:a},d=$.runKernel(_u,c,h);return u?G(d,[d.shape[1],d.shape[2],d.shape[3]]):d}var dm=O({dilation2d_:lS});function uS(e,t){let n=e.length,r=[];for(let a=0;a<n;a++){let s=n-1-a,i=e[s]||1;(t[t.length-1-a]||1)>1&&i===1&&r.unshift(s)}return r}function Vt(e,t){let n=[];for(let r=0;r<t.length;r++){let a=e[e.length-r-1],s=t.length-r-1,i=t[s];(a==null||a===1&&i>1)&&n.unshift(s)}return n}function wt(e,t){let n=[],r=Math.max(e.length,t.length);for(let a=0;a<r;a++){let s=e[e.length-a-1];s==null&&(s=1);let i=t[t.length-a-1];if(i==null&&(i=1),s===1)n.unshift(i);else if(i===1)n.unshift(s);else if(s!==i){let o=`Operands could not be broadcast together with shapes ${e} and ${t}.`;throw Error(o)}else n.unshift(s)}return n}function cS(e,t){let n=C(e,"a","equal"),r=C(t,"b","equal");[n,r]=Nt(n,r),wt(n.shape,r.shape);let a={a:n,b:r};return $.runKernel(wo,a)}var Ba=O({equal_:cS});function hS(e,t,n){let r=C(t,"a","where"),a=C(n,"b","where"),s=C(e,"condition","where","bool"),i=wt(r.shape,a.shape),o=Zu(r,i),l=Zu(a,i);s.rank===1&&F(s.shape[0]===r.shape[0],()=>"The first dimension of `a` must match the size of `condition`."),s.rank!==1&&un(s.shape,l.shape,"Error in where: ");let u={condition:s,t:o,e:l};return $.runKernel(Go,u)}var Tn=O({where_:hS});function dS(e){let t={x:C(e,"x","zerosLike")};return $.runKernel(rl,t)}var qe=O({zerosLike_:dS});function pS(e,t){let n=C(e,"a","div"),r=C(t,"b","div");[n,r]=Nt(n,r);let a=be(n,r),s=qe(a),i=Ba(r,s);return Tn(i,s,a)}var pm=O({divNoNan_:pS});function fS(e,t){let n=C(e,"t1","dot"),r=C(t,"t2","dot");F((n.rank===1||n.rank===2)&&(r.rank===1||r.rank===2),()=>`Error in dot: inputs must all be rank 1 or 2, but got ranks ${n.rank} and ${r.rank}.`);let a=n.rank===1?n.size:n.shape[1],s=r.rank===1?r.size:r.shape[0];if(F(a===s,()=>`Error in dot: inner dimensions of inputs must match, but got ${a} and ${s}.`),n.rank===1&&r.rank===1){let i=G(n,[1,-1]),o=G(r,[-1,1]),l=Ke(i,o);return G(l,[])}else if(n.rank===1&&r.rank===2){let i=G(n,[1,-1]),o=G(r,[r.shape[0],r.shape[1]]),l=Ke(i,o);return G(l,[l.size])}else if(n.rank===2&&r.rank===1){let i=G(r,[-1,1]),o=Ke(n,i);return G(o,[o.size])}else{let i=G(r,[r.shape[0],r.shape[1]]);return Ke(n,i)}}var Ax=O({dot_:fS});function mS(e){let t={x:C(e,"x","elu")};return $.runKernel(go,t)}var xl=O({elu_:mS});function AS(e){let t=C(e,"x","erf");F(t.dtype==="int32"||t.dtype==="float32",()=>"Input dtype must be `int32` or `float32`."),t.dtype==="int32"&&(t=ge(t,"float32"));let n={x:t};return $.runKernel(xo,n)}var fm=O({erf_:AS});function yS(e){let t={x:C(e,"x","exp")};return $.runKernel(Ns,t)}var Jn=O({exp_:yS});function gS(e,t=0){let n=C(e,"x","expandDims","string_or_numeric");F(t<=n.rank,()=>"Axis must be <= rank of the tensor");let r={input:n},a={dim:t};return $.runKernel(bo,r,a)}var mn=O({expandDims_:gS});function xS(e){let t={x:C(e,"x","expm1")};return $.runKernel(_o,t)}var mm=O({expm1_:xS});function wS(e,t){let n=C(e,"x","tile","string_or_numeric");F(n.rank===t.length,()=>`Error in transpose: rank of input ${n.rank} must match length of reps ${t}.`);let r={x:n},a={reps:t};return $.runKernel(Ma,r,a)}var Va=O({tile_:wS});function bS(e,t,n,r="float32"){t==null&&(t=e);let a=Ue([e,t],r),s=e<=t?e:t;for(let o=0;o<s;++o)a.set(1,o,o);let i=G(a.toTensor(),[e,t]);if(n==null)return i;if(n.length===1)return Va(mn(i,0),[n[0],1,1]);if(n.length===2)return Va(mn(mn(i,0),0),[n[0],n[1],1,1]);if(n.length===3)return Va(mn(mn(mn(i,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 Am=O({eye_:bS});function Ju(e,t,n){let r={shape:e,value:t,dtype:n};return $.runKernel(vu,{},r)}function _S(e){let t={x:C(e,"x","floor")};return $.runKernel(Ss,t)}var wl=O({floor_:_S});function vS(e,t,n=0,r=0){let a=C(e,"x","gather"),s=C(t,"indices","gather","int32"),i={x:a,indices:s},o={axis:n,batchDims:r};return $.runKernel(ko,i,o)}var Ai=O({gather_:vS});function kS(e,t){let n=C(e,"a","greater"),r=C(t,"b","greater");[n,r]=Nt(n,r),wt(n.shape,r.shape);let a={a:n,b:r};return $.runKernel(No,a)}var ur=O({greater_:kS});function IS(e,t){let n=C(e,"a","greaterEqual"),r=C(t,"b","greaterEqual");[n,r]=Nt(n,r),wt(n.shape,r.shape);let a={a:n,b:r};return $.runKernel(Cs,a)}var Ua=O({greaterEqual_:IS});function NS(e){let t={input:C(e,"input","imag")};return $.runKernel(Qh,t)}var Cd=O({imag_:NS});function SS(e){let t={x:C(e,"x","isFinite")};return $.runKernel(So,t)}var yx=O({isFinite_:SS});function TS(e){let t={x:C(e,"x","isInf")};return $.runKernel(To,t)}var gx=O({isInf_:TS});function ES(e){let t={x:C(e,"x","isNaN")};return $.runKernel(Eo,t)}var xx=O({isNaN_:ES});function CS(e,t=.2){let n={x:C(e,"x","leakyRelu")},r={alpha:t};return $.runKernel(Fs,n,r)}var Qu=O({leakyRelu_:CS});function RS(e,t){let n=C(e,"a","less"),r=C(t,"b","less");[n,r]=Nt(n,r),wt(n.shape,r.shape);let a={a:n,b:r};return $.runKernel(Co,a)}var Rd=O({less_:RS});function FS(e,t){let n=C(e,"a","lessEqual"),r=C(t,"b","lessEqual");[n,r]=Nt(n,r),wt(n.shape,r.shape);let a={a:n,b:r};return $.runKernel(Ro,a)}var yi=O({lessEqual_:FS});function wx(e,t,n){if(n<=0)throw new Error("The number of values should be positive.");let r={start:e,stop:t,num:n};return $.runKernel(ed,{},r)}function MS(e,t=5,n=1,r=1,a=.5){let s=C(e,"x","localResponseNormalization");F(s.rank===4||s.rank===3,()=>`Error in localResponseNormalization: x must be rank 3 or 4 but got
|
|
rank ${s.rank}.`),F(Kt(t),()=>`Error in localResponseNormalization: depthRadius must be an integer but got depthRadius ${t}.`);let i=s,o=!1;s.rank===3&&(o=!0,i=G(s,[1,s.shape[0],s.shape[1],s.shape[2]]));let l={x:i},u={depthRadius:t,bias:n,alpha:r,beta:a},c=$.runKernel(Nu,l,u);return o?G(c,[c.shape[1],c.shape[2],c.shape[3]]):c}var ym=O({localResponseNormalization_:MS});function $S(e){let t={x:C(e,"x","log")};return $.runKernel(Ms,t)}var zn=O({log_:$S});function DS(e){let t={x:C(e,"x","log1p")};return $.runKernel(Fo,t)}var Fd=O({log1p_:DS});function OS(e){return F(Ca(e),()=>"The f passed in grad(f) must be a function"),(t,n)=>{let r=C(t,"x","tf.grad","string_or_numeric"),a=n!=null?C(n,"dy","tf.grad"):null;return $.tidy(()=>{let{value:s,grads:i}=$.gradients(()=>e(r),[r],a);return a!=null&&un(s.shape,a.shape,"The shape of dy passed in grad(f)(x, dy) must match the shape returned by f(x)"),Md(i),i[0]})}}function zS(e){return F(Ca(e),()=>"The f passed in grads(f) must be a function"),(t,n)=>{F(Array.isArray(t),()=>"The args passed in grads(f)(args) must be an array of `Tensor`s or `TensorLike`s");let r=Uu(t,"args","tf.grads","string_or_numeric"),a=n!=null?C(n,"dy","tf.grads"):null;return $.tidy(()=>{let{value:s,grads:i}=$.gradients(()=>e(...r),r,a);return a!=null&&un(s.shape,a.shape,"The shape of dy passed in grads(f)([x1,...], dy) must match the shape returned by f([x1,...])"),Md(i),i})}}function PS(e){return F(Ca(e),()=>"The f passed in valueAndGrad(f) must be a function"),(t,n)=>{F(t instanceof Ge,()=>"The x passed in valueAndGrad(f)(x) must be a tensor"),F(n==null||n instanceof Ge,()=>"The dy passed in valueAndGrad(f)(x, dy) must be a tensor");let{grads:r,value:a}=$.gradients(()=>e(t),[t],n);return Md(r),{grad:r[0],value:a}}}function LS(e){return F(Ca(e),()=>"The f passed in valueAndGrads(f) must be a function"),(t,n)=>{F(Array.isArray(t)&&t.every(a=>a instanceof Ge),()=>"The args passed in valueAndGrads(f)(args) must be array of tensors"),F(n==null||n instanceof Ge,()=>"The dy passed in valueAndGrads(f)(args, dy) must be a tensor");let r=$.gradients(()=>e(...t),t,n);return n!=null&&un(r.value.shape,n.shape,"The shape of dy passed in valueAndGrads(f)([x1,...], dy) must match the shape returned by f([x1,...])"),Md(r.grads),r}}function bx(e,t){F(Ca(e),()=>"The f passed in variableGrads(f) must be a function"),F(t==null||Array.isArray(t)&&t.every(u=>u instanceof Wu),()=>"The varList passed in variableGrads(f, varList) must be an array of variables");let n=t!=null;if(!n){t=[];for(let u in $.registeredVariables)t.push($.registeredVariables[u])}let r=n?t.filter(u=>!u.trainable):null,a=t.length;t=t.filter(u=>u.trainable),F(t.length>0,()=>`variableGrads() expects at least one of the input variables to be trainable, but none of the ${a} variables is trainable.`);let s=!0,{value:i,grads:o}=$.gradients(e,t,null,s);F(o.some(u=>u!=null),()=>"Cannot find a connection between any variable and the result of the loss function y=f(x). Please make sure the operations that use variables are inside the function f passed to minimize()."),F(i.rank===0,()=>`The f passed in variableGrads(f) must return a scalar, but it returned a rank-${i.rank} tensor`);let l={};return t.forEach((u,c)=>{o[c]!=null&&(l[u.name]=o[c])}),r!=null&&r.forEach(u=>l[u.name]=null),{value:i,grads:l}}function Wr(e){return $.customGrad(e)}function Md(e){if(e.filter(t=>t==null).length>0)throw new Error(`Cannot compute gradient of y=f(x) with respect to x. Make sure that
|
|
the f you passed encloses all operations that lead from x to y.`)}function WS(e){let t={x:C(e,"x","neg")};return $.runKernel(Do,t)}var St=O({neg_:WS});function BS(e){let t={x:C(e,"x","softplus")};return $.runKernel(Yo,t)}var bl=O({softplus_:BS});function VS(e){let t=C(e,"x","logSigmoid");return Wr(n=>({value:St(bl(St(n))),gradFunc:r=>P(r,On(St(n)))}))(t)}var _x=O({logSigmoid_:VS});function US(e,t=null,n=!1){let r={x:C(e,"x","max")},a={reductionIndices:t,keepDims:n};return $.runKernel($s,r,a)}var Qn=O({max_:US});function HS(e,t){let n=C(e,"a","sub"),r=C(t,"b","sub");[n,r]=Nt(n,r);let a={a:n,b:r};return $.runKernel(ri,a)}var we=O({sub_:HS});function jS(e,t=null,n=!1){let r=C(e,"x","sum");r.dtype==="bool"&&(r=ge(r,"int32"));let a={x:r},s={axis:t,keepDims:n};return $.runKernel(ei,a,s)}var Re=O({sum_:jS});function GS(e,t=-1){let n=C(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 Wr((r,a)=>{let s=!0,i=Qn(r,t,!0),o=we(r,i),l=we(ge(o,"float32"),zn(Re(Jn(o),t,s)));return a([l]),{value:l,gradFunc:(u,c)=>{let[h]=c,d=!0,p=Jn(h);return we(u,P(Re(u,t,d),p))}}})(n)}var $d=O({logSoftmax_:GS});function gm(e,t){for(let n=0;n<e.length;++n)if(e[e.length-n-1]!==t-1-n)return!1;return!0}function vx(e,t,n){let r=e.length+t.length,a=[],s=0,i=0;for(let o=0;o<r;o++)n.indexOf(o)===-1?a.push(e[s++]):a.push(t[i++]);return a}function kx(e,t){let n=[],r=e.length;for(let s=0;s<r;s++)t.indexOf(s)===-1&&n.push(e[s]);let a=t.map(s=>e[s]);return[n,a]}function gi(e,t){let n=t.map(r=>1);return vx(e,n,t)}function qS(e,t,n){F(gm(t,n),()=>`${e} supports only inner-most axes for now. Got axes ${t} and rank-${n} input.`)}function Ix(e,t){if(gm(e,t))return null;let n=[];for(let r=0;r<t;++r)e.indexOf(r)===-1&&n.push(r);return e.forEach(r=>n.push(r)),n}function xm(e){return e.map((t,n)=>[n,t]).sort((t,n)=>t[1]-n[1]).map(t=>t[0])}function XS(e,t){let n=[];for(let r=t-e;r<t;++r)n.push(r);return n}function KS(e,t=null,n=!1){let r=C(e,"x","logSumExp"),a=or(t,r.shape),s=Qn(r,a,!0),i=we(r,s),o=Jn(i),l=Re(o,a),u=zn(l),c=ie(G(s,u.shape),u);if(n){let h=gi(c.shape,a);return G(c,h)}return c}var wm=O({logSumExp_:KS});function ZS(e,t){let n=C(e,"a","logicalAnd","bool"),r=C(t,"b","logicalAnd","bool");wt(n.shape,r.shape);let a={a:n,b:r};return $.runKernel(Mo,a)}var cr=O({logicalAnd_:ZS});function YS(e){let t={x:C(e,"x","logicalNot","bool")};return $.runKernel(ku,t)}var ec=O({logicalNot_:YS});function JS(e,t){let n=C(e,"a","logicalOr","bool"),r=C(t,"b","logicalOr","bool");wt(n.shape,r.shape);let a={a:n,b:r};return $.runKernel(Iu,a)}var Dd=O({logicalOr_:JS});function QS(e,t){let n=C(e,"a","logicalXor","bool"),r=C(t,"b","logicalXor","bool");return wt(n.shape,r.shape),cr(Dd(e,t),ec(cr(e,t)))}var Nx=O({logicalXor_:QS});function eT(e,t,n,r,a){let s=C(e,"x","maxPool"),i=1,o=s,l=!1;s.rank===3&&(l=!0,o=G(s,[1,s.shape[0],s.shape[1],s.shape[2]])),F(o.rank===4,()=>`Error in maxPool: input must be rank 4 but got rank ${o.rank}.`),F(Lr(n,i),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${n} and dilations '${i}'`),a!=null&&F(Kt(r),()=>`Error in maxPool: pad must be an integer when using, dimRoundingMode ${a} but got pad ${r}.`);let u={x:o},c={filterSize:t,strides:n,pad:r,dimRoundingMode:a},h=$.runKernel(Os,u,c);return l?G(h,[h.shape[1],h.shape[2],h.shape[3]]):h}var tc=O({maxPool_:eT});function tT(e,t=[1,1,1],n,r,a,s="NDHWC"){let i=C(e,"x","maxPool3d"),o=i,l=!1;i.rank===4&&(l=!0,o=G(i,[1,i.shape[0],i.shape[1],i.shape[2],i.shape[3]])),F(o.rank===5,()=>`Error in maxPool3d: x must be rank 5 but got rank ${o.rank}.`),F(s==="NDHWC",()=>`Error in maxPool3d: Only NDHWC is currently supported, but got dataFormat of ${s}`),a!=null&&F(Kt(r),()=>`Error in maxPool3d: pad must be an integer when using, dimRoundingMode ${a} but got pad ${r}.`);let u={x:o},c={filterSize:t,strides:n,pad:r,dimRoundingMode:a,dataFormat:s},h=$.runKernel(Su,u,c);return l?G(h,[h.shape[1],h.shape[2],h.shape[3],h.shape[4]]):h}var bm=O({maxPool3d_:tT});function nT(e,t,n,r,a=!1){let s={x:C(e,"x","maxPoolWithArgmax")},i={filterSize:t,strides:n,pad:r,includeBatchInIndex:a},o=$.runKernel(ad,s,i);return{result:o[0],indexes:o[1]}}var Sx=O({maxPoolWithArgmax_:nT});function rT(e,t){let n=C(e,"a","maximum"),r=C(t,"b","maximum");[n,r]=Nt(n,r),n.dtype==="bool"&&(n=ge(n,"int32"),r=ge(r,"int32")),wt(n.shape,r.shape);let a={a:n,b:r};return $.runKernel(Ds,a)}var Br=O({maximum_:rT});function aT(e,t=null,n=!1){let r={x:C(e,"x","mean")},a={axis:t,keepDims:n};return $.runKernel(zs,r,a)}var Tt=O({mean_:aT});function sT(e,t=null,n=!1){let r={x:C(e,"x","min")},a={axis:t,keepDims:n};return $.runKernel(Ps,r,a)}var _l=O({min_:sT});function iT(e,t){let n=C(e,"a","minimum"),r=C(t,"b","minimum");[n,r]=Nt(n,r),n.dtype==="bool"&&(n=ge(n,"int32"),r=ge(r,"int32")),wt(n.shape,r.shape);let a={a:n,b:r};return $.runKernel(Ls,a)}var vl=O({minimum_:iT});function oT(e,t,n){F(n==="reflect"||n==="symmetric",()=>`Invalid mode. Mode must be either reflect or symmetric. Got ${n}.`);let r=C(e,"x","mirrorPad");if(r.rank===0)throw new Error("mirrorPad(scalar) is not defined. Pass non-scalar to mirrorPad");F(t.length===r.rank,()=>`Padding doesn't match input. Must be ${r.rank}. Got ${t.length}.`);let a=n==="reflect"?1:0;for(let o=0;o<r.rank;o++)F(t[o].length===2,()=>"Invalid number of paddings. Must be length of 2 each."),F(t[o][0]>=0&&t[o][0]<=r.shape[o]-a&&t[o][1]>=0&&t[o][1]<=r.shape[o]-a,()=>`Padding in dimension ${o} cannot be greater than or equal to ${r.shape[o]-a} or less than 0 for input of shape ${r.shape}`);let s={paddings:t,mode:n},i={x:r};return $.runKernel(Tu,i,s)}var _m=O({mirrorPad_:oT});function lT(e,t){let n=C(e,"a","mod"),r=C(t,"b","mod");[n,r]=Nt(n,r);let a={a:n,b:r};return $.runKernel($o,a)}var vm=O({mod_:lT});function uT(e){let t=C(e,"x","square"),n={};return $.runKernel("Square",{x:t},n)}var ht=O({square_:uT});function cT(e,t=null,n=!1){e=C(e,"x","moments");let r=or(t,e.shape),a=Tt(e,r,n),s=a.shape;n||(s=gi(a.shape,r));let i=ht(we(ge(e,"float32"),G(a,s))),o=Tt(i,r,n);return{mean:a,variance:o}}var Od=O({moments_:cT});function hT(e,t,n,r){let a=C(t,"data","multiRNNCell"),s=Uu(n,"c","multiRNNCell"),i=Uu(r,"h","multiRNNCell"),o=a,l=[];for(let h=0;h<e.length;h++){let d=e[h](o,s[h],i[h]);l.push(d[0]),l.push(d[1]),o=d[1]}let u=[],c=[];for(let h=0;h<l.length;h+=2)u.push(l[h]),c.push(l[h+1]);return[u,c]}var dT=O({multiRNNCell_:hT});function pT(e,t,n,r=!1){let a=C(e,"logits","multinomial"),s=a.size,i=a.rank;if(s<2)throw new Error(`Error in multinomial: you need at least 2 outcomes, but got ${s}.`);if(i>2)throw new Error(`Rank of probabilities must be 1 or 2, but is ${i}`);n=n||Math.random();let o={logits:i===1?G(a,[1,-1]):a},l={numSamples:t,seed:n,normalized:r},u=$.runKernel(sd,o,l);return i===1?G(u,[u.size]):u}var Tx=O({multinomial_:pT});function fT(e,t){let n=C(e,"a","notEqual"),r=C(t,"b","notEqual");[n,r]=Nt(n,r),wt(n.shape,r.shape);let a={a:n,b:r};return $.runKernel(Oo,a)}var xi=O({notEqual_:fT});function $t(e,t="float32"){if(t==="complex64"){let r=$t(e,"float32"),a=$t(e,"float32");return Da(r,a)}let n=$h(Lt(e),t);return $.makeTensor(n,e,t)}function Vr(e,t="float32"){if(t==="complex64"){let r=Vr(e,"float32"),a=$t(e,"float32");return Da(r,a)}let n=Af(Lt(e),t);return $.makeTensor(n,e,t)}function mT(e){let t={x:C(e,"x","onesLike")};return $.runKernel(Wo,t)}var Pn=O({onesLike_:mT});function AT(e,t){let n=C(e,"v1","outerProduct"),r=C(t,"v2","outerProduct");F(n.rank===1&&r.rank===1,()=>`Error in outerProduct: inputs must be rank 1, but got ranks ${n.rank} and ${r.rank}.`);let a=G(n,[-1,1]),s=G(r,[1,-1]);return Ke(a,s)}var yT=O({outerProduct_:AT});function gT(e,t,n=0){let r=C(e,"x","pad");if(r.rank===0)throw new Error("pad(scalar) is not defined. Pass non-scalar to pad");let a={paddings:t,constantValue:n},s={x:r};return $.runKernel(Vs,s,a)}var ca=O({pad_:gT});function xT(e,t,n=0){return F(t.length===2,()=>"Invalid number of paddings. Must be length of 2."),ca(e,[t],n)}var wT=O({pad1d_:xT});function bT(e,t,n=0){return F(t.length===2&&t[0].length===2&&t[1].length===2,()=>"Invalid number of paddings. Must be length of 2 each."),ca(e,t,n)}var _T=O({pad2d_:bT});function vT(e,t,n=0){return F(t.length===3&&t[0].length===2&&t[1].length===2&&t[2].length===2,()=>"Invalid number of paddings. Must be length of 2 each."),ca(e,t,n)}var kT=O({pad3d_:vT});function IT(e,t,n=0){return F(t.length===4&&t[0].length===2&&t[1].length===2&&t[2].length===2&&t[3].length===2,()=>"Invalid number of paddings. Must be length of 2 each."),ca(e,t,n)}var NT=O({pad4d_:IT});function ST(e,t,n){let r=C(e,"x","spaceToBatchND");F(r.rank>=1+t.length,()=>`input rank ${r.rank} should be > than [blockShape] ${t.length}`),F(n.length===t.length,()=>`paddings.shape[0] ${n.length} must be equal to [blockShape] ${t.length}`),F(r.shape.reduce((i,o,l)=>l>0&&l<=t.length?i&&(o+n[l-1][0]+n[l-1][1])%t[l-1]==0:i,!0),()=>`input spatial dimensions ${r.shape.slice(1)} with paddings ${n.toString()} must be divisible by blockShapes ${t.toString()}`);let a={x:r},s={blockShape:t,paddings:n};return $.runKernel(Ru,a,s)}var nc=O({spaceToBatchND_:ST});function CT(e,t,n,r,a,s){a==null&&(a=[1,1]),s==null&&(s=1),r===0&&(r="valid");let i=C(e,"x","maxPool"),o=i,l=!1;i.rank===3&&(l=!0,o=G(i,[1,i.shape[0],i.shape[1],i.shape[2]])),F(Lr(s,a),()=>`Error in pool: Either strides or dilations must be 1. Got strides ${s} and dilations '${a}'`);let u=sx(o.shape,t,s,a,r),c=[u.dilationHeight,u.dilationWidth],h;r==="same"?h=ET([u.filterHeight,u.filterWidth],c):h=[[0,0],[0,0]];let d=c[0]===1&&c[1]===1,[p,f]=TT([u.inHeight,u.inWidth],c,h),m=d?r:"valid",A=d?o:nc(o,c,p),y=(n==="avg"?()=>Xu(A,t,s,m):()=>tc(A,t,s,m))(),g=d?y:Ku(y,c,f);return l?G(g,[g.shape[1],g.shape[2],g.shape[3]]):g}function TT(e,t,n){let r=n.map(c=>c[0]),a=n.map(c=>c[1]),s=e.concat(r,a),i=t.map((c,h)=>(c-s[h]%c)%c),o=a.map((c,h)=>c+i[h]),l=t.map((c,h)=>[r[h],o[h]]),u=t.map((c,h)=>[0,i[h]]);return[l,u]}function ET(e,t){let n=e.map((s,i)=>s+(s-1)*(t[i]-1)).map(s=>s-1),r=n.map(s=>Math.floor(s/2)),a=n.map((s,i)=>s-r[i]);return n.map((s,i)=>[r[i],a[i]])}var Ex=O({pool_:CT});function RT(e,t){let n=C(e,"base","pow"),r=C(t,"exp","pow");[n,r]=Nt(n,r);let a={a:n,b:r};return $.runKernel(Us,a)}var ha=O({pow_:RT});function FT(e,t){let n=C(e,"x","prelu"),r=C(t,"alpha","prelu"),a={x:n,alpha:r};return $.runKernel(Hs,a)}var rc=O({prelu_:FT});function MT(e,t=null,n=!1){let r=C(e,"x","prod");r.dtype==="bool"&&(r=ge(r,"int32"));let a={x:r},s={axis:t,keepDims:n};return $.runKernel(Vo,a,s)}var zd=O({prod_:MT});function $T(e,t,n){let r=Lt(e),a=null;if(n==null||n==="float32")a=new Float32Array(r);else if(n==="int32")a=new Int32Array(r);else if(n==="bool")a=new Uint8Array(r);else throw new Error(`Unknown data type ${n}`);for(let s=0;s<r;s++)a[s]=t();return $.makeTensor(a,e,n)}var DT=O({rand_:$T}),km=no(sk()),Im=class{constructor(e,t,n,r,a){this.mean=e,this.stdDev=t,this.dtype=n,this.nextVal=NaN,this.truncated=r,this.truncated&&(this.upper=this.mean+this.stdDev*2,this.lower=this.mean-this.stdDev*2);let s=a||Math.random();this.random=km.alea(s.toString())}nextValue(){if(!isNaN(this.nextVal)){let r=this.nextVal;return this.nextVal=NaN,r}let e,t,n=!1;for(;!n;){let r,a,s;do r=2*this.random()-1,a=2*this.random()-1,s=r*r+a*a;while(s>=1||s===0);let i=Math.sqrt(-2*Math.log(s)/s);e=this.mean+this.stdDev*r*i,t=this.mean+this.stdDev*a*i,(!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}},OT=class{constructor(e,t,n,r){this.alpha=e,this.beta=1/t,this.dtype=n;let a=r||Math.random();this.randu=km.alea(a.toString()),this.randn=new Im(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,r,a,s;for(;;){do r=this.randn.nextValue(),s=1+this.c*r;while(s<=0);if(s*=s*s,e=r*r,t=1-.331*e*e,n=.5*e+this.d*(1-s+Math.log(s)),a=this.randu(),a<t||Math.log(a)<n)break}return s=1/this.beta*this.d*s,this.alpha<1&&(s*=Math.pow(this.randu(),1/this.alpha)),this.convertValue(s)}convertValue(e){return this.dtype==="float32"?e:Math.round(e)}},zT=class{constructor(e=0,t=1,n,r){if(this.canReturnFloat=()=>this.dtype==null||this.dtype==="float32",this.min=e,this.range=t-e,this.dtype=n,r==null&&(r=Math.random()),typeof r=="number"&&(r=r.toString()),!this.canReturnFloat()&&this.range<=1)throw new Error(`The difference between ${e} - ${t} <= 1 and dtype is not float`);this.random=km.alea(r)}convertValue(e){return this.canReturnFloat()?e:Math.round(e)}nextValue(){return this.convertValue(this.min+this.range*this.random())}};function PT(e,t,n=1,r="float32",a){if(n==null&&(n=1),r==null&&(r="float32"),r!=="float32"&&r!=="int32")throw new Error(`Unsupported data type ${r}`);let s=new OT(t,n,r,a),i=Ue(e,r);for(let o=0;o<i.values.length;o++)i.values[o]=s.nextValue();return i.toTensor()}var LT=O({randomGamma_:PT});function WT(e,t=0,n=1,r,a){if(r!=null&&r==="bool")throw new Error(`Unsupported data type ${r}`);let s=new Im(t,n,r,!1,a),i=Ue(e,r);for(let o=0;o<i.values.length;o++)i.values[o]=s.nextValue();return i.toTensor()}var Cx=O({randomNormal_:WT});function BT(e,t=0,n=1,r="float32",a){let s=Ue(e,r),i=new zT(t,n,null,a);for(let o=0;o<s.values.length;o++)s.values[o]=i.nextValue();return s.toTensor()}var kl=O({randomUniform_:BT});function Pd(e,t,n=1,r="float32"){if(n===0)throw new Error("Cannot have a step of zero");let a={start:e,stop:t,step:n,dtype:r};return $.runKernel(Eu,{},a)}function VT(e){let t={input:C(e,"input","real")};return $.runKernel(id,t)}var ac=O({real_:VT});function UT(e){let t={x:C(e,"x","reciprocal")};return $.runKernel(Uo,t)}var Nm=O({reciprocal_:UT});function HT(e){let t={x:C(e,"x","relu")};return $.runKernel(js,t)}var Ur=O({relu_:HT});function jT(e){let t={x:C(e,"x","relu6")};return $.runKernel(qs,t)}var Ld=O({relu6_:jT});function GT(e,t){let n={x:C(e,"x","reverse")},r={dims:t};return $.runKernel(Xs,n,r)}var Ln=O({reverse_:GT});function qT(e){let t=C(e,"x","reverse");return F(t.rank===1,()=>`Error in reverse1D: x must be rank 1 but got rank ${t.rank}.`),Ln(t,0)}var XT=O({reverse1d_:qT});function KT(e,t){let n=C(e,"x","reverse");return F(n.rank===2,()=>`Error in reverse2D: x must be rank 2 but got rank ${n.rank}.`),Ln(n,t)}var ZT=O({reverse2d_:KT});function YT(e,t){let n=C(e,"x","reverse");return F(n.rank===3,()=>`Error in reverse3D: x must be rank 3 but got rank ${n.rank}.`),Ln(n,t)}var JT=O({reverse3d_:YT});function QT(e,t){let n=C(e,"x","reverse");return F(n.rank===4,()=>`Error in reverse4D: x must be rank 4 but got rank ${n.rank}.`),Ln(n,t)}var eE=O({reverse4d_:QT});function tE(e){let t={x:C(e,"x","round")};return $.runKernel(Ks,t)}var Sm=O({round_:tE});function nE(e){let t={x:C(e,"x","rsqrt")};return $.runKernel(Zs,t)}var Wd=O({rsqrt_:nE});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 Oa(e,[],[],t)}function rE(e){let t={x:C(e,"x","selu")};return $.runKernel(qo,t)}var Bd=O({selu_:rE});function aE(e,t,n,r,a,s=[1,1],i="NHWC"){let o=C(e,"x","separableConv2d"),l=C(t,"depthwiseFilter","separableConv2d"),u=C(n,"pointwiseFilter","separableConv2d"),c=o,h=!1;if(o.rank===3&&(h=!0,c=G(o,[1,o.shape[0],o.shape[1],o.shape[2]])),i==="NCHW")throw new Error("separableConv2d currently does not support dataFormat NCHW; only NHWC is supported");F(c.rank===4,()=>`Error in separableConv2d: input must be rank 4, but got rank ${c.rank}.`),F(l.rank===4,()=>`Error in separableConv2d: depthwise filter must be rank 4, but got rank ${l.rank}.`),F(u.rank===4,()=>`Error in separableConv2d: pointwise filter must be rank 4, but got rank ${l.rank}.`),F(u.shape[0]===1,()=>`Error in separableConv2d: the first dimension of pointwise filter must be 1, but got ${u.shape[0]}.`),F(u.shape[1]===1,()=>`Error in separableConv2d: the second dimension of pointwise filter must be 1, but got ${u.shape[1]}.`);let d=l.shape[2],p=l.shape[3];F(u.shape[2]===d*p,()=>`Error in separableConv2d: the third dimension of pointwise filter must be ${d*p}, but got ${u.shape[2]}.`);let f=gl(c,l,r,a,i,s),m=ua(f,u,1,"valid",i);return h?G(m,[m.shape[1],m.shape[2],m.shape[3]]):m}var Tm=O({separableConv2d_:aE});async function sE(e,t){let n=C(e,"x","setdiff1d"),r=C(t,"y","setdiff1d");F(n.dtype===r.dtype,()=>`x and y should have the same dtype, but got x (${n.dtype}) and y (${r.dtype}).`),F(n.rank===1,()=>`x should be 1D tensor, but got x (${n.shape}).`),F(r.rank===1,()=>`y should be 1D tensor, but got y (${r.shape}).`);let a=await n.data(),s=await r.data(),i=new Set(s),o=0;for(let c=0;c<a.length;c++)i.has(a[c])||o++;let l=new Wt([o],n.dtype),u=new Wt([o],"int32");for(let c=0,h=0;c<a.length;c++)i.has(a[c])||(l.values[h]=a[c],u.values[h]=c,h++);return[l.toTensor(),u.toTensor()]}var Rx=sE;function iE(e){let t={x:C(e,"x","sign")};return $.runKernel(Zo,t)}var Em=O({sign_:iE});function oE(e){let t={x:C(e,"x","sin")};return $.runKernel(Ys,t)}var Vd=O({sin_:oE});function lE(e){let t={x:C(e,"x","sinh")};return $.runKernel(Ko,t)}var Ud=O({sinh_:lE});function uE(e,t,n){let r=C(e,"x","slice1d");return F(r.rank===1,()=>`slice1d expects a rank-1 tensor, but got a rank-${r.rank} tensor`),$e(r,[t],[n])}var Hd=O({slice1d_:uE});function cE(e,t,n){let r=C(e,"x","slice2d");return F(r.rank===2,()=>`slice2d expects a rank-2 tensor, but got a rank-${r.rank} tensor`),$e(r,t,n)}var Cm=O({slice2d_:cE});function hE(e,t,n){let r=C(e,"x","slice3d");return F(r.rank===3,()=>`slice3d expects a rank-3 tensor, but got a rank-${r.rank} tensor`),$e(r,t,n)}var jd=O({slice3d_:hE});function dE(e,t,n){let r=C(e,"x","slice4d");return F(r.rank===4,()=>`slice4d expects a rank-4 tensor, but got a rank-${r.rank} tensor`),$e(r,t,n)}var sc=O({slice4d_:dE});function pE(e,t=-1){let n=C(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 r={logits:n},a={dim:t};return $.runKernel(ti,r,a)}var ic=O({softmax_:pE});function fE(e){F(e.dtype==="complex64",()=>`The dtype for tf.spectral.fft() must be complex64 but got ${e.dtype}.`);let t={input:e};return $.runKernel(Yh,t)}var oc=O({fft_:fE});function mE(e){F(e.dtype==="complex64",()=>`The dtype for tf.spectral.ifft() must be complex64 but got ${e.dtype}.`);let t={input:e};return $.runKernel(Jh,t)}var Il=O({ifft_:mE});function AE(e){let t=e.shape[e.shape.length-1],n=e.size/t,r;if(t<=2){let a=G(e,[n,t]);r=Il(a)}else{let a=[n,2*(t-1)],s=G(ac(e),[n,t]),i=G(Cd(e),[n,t]),o=Ln($e(s,[0,1],[n,t-2]),1),l=P(Ln($e(i,[0,1],[n,t-2]),1),Ie(-1)),u=lt([s,o],1),c=lt([i,l],1),h=G(Da(u,c),[a[0],a[1]]);r=Il(h)}if(r=ac(r),e.rank===3&&e.shape[0]!==0){let a=r,s=e.shape[0];r=G(r,[s,r.shape[0]/s,r.shape[1]]),a.dispose()}return r}var Gd=O({irfft_:AE});function yE(e,t,n=0){let r={x:C(e,"x","split")},a={numOrSizeSplits:t,axis:n};return $.runKernel(Jo,r,a)}var Ut=O({split_:yE});function gE(e,t){F(e.dtype==="float32",()=>`The dtype for rfft() must be real value but got ${e.dtype}`);let n=e.shape[e.shape.length-1],r=e.size/n,a;if(t!=null&&t<n){let f=e.shape.map(A=>0),m=e.shape.map(A=>A);m[e.shape.length-1]=t,a=$e(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,a=lt([e,$t(f)],e.shape.length-1),n=t}else a=e;let s=qe(a),i=G(Da(a,s),[r,n]),o=oc(i),l=Math.floor(n/2)+1,u=ac(o),c=Cd(o),h=Ut(u,[l,n-l],u.shape.length-1),d=Ut(c,[l,n-l],c.shape.length-1),p=a.shape.slice();return p[a.shape.length-1]=l,G(Da(h[0],d[0]),p)}var lc=O({rfft_:gE});function xE(e){let t={x:C(e,"x","sqrt")};return $.runKernel(Qs,t)}var an=O({sqrt_:xE});function wE(e,t){let n=C(e,"a","squaredDifference"),r=C(t,"b","squaredDifference");[n,r]=Nt(n,r),wt(n.shape,r.shape);let a={a:n,b:r},s={};return $.runKernel(ni,a,s)}var qd=O({squaredDifference_:wE});function bE(e,t){let n=C(e,"x","squeeze");return G(n,J2(n.shape,t).newShape)}var Ha=O({squeeze_:bE});function _E(e,t=0){let n=Uu(e,"tensors","stack","string_or_numeric");F(n.length>=1,()=>"Pass at least one tensor to tf.stack"),n.length>0&&F(t<=n[0].rank,()=>"Axis must be <= rank of the tensor");let r=n,a={axis:t};return $.runKernel(Bo,r,a)}var An=O({stack_:_E});function vE(e,t=0){let n={x:C(e,"x","step")},r={alpha:t};return $.runKernel($a,n,r)}var Nl=O({step_:vE});function kE(e,t,n,r,a=0,s=0,i=0,o=0,l=0){let u={x:C(e,"x","stridedSlice")},c={begin:t,end:n,strides:r,beginMask:a,endMask:s,ellipsisMask:i,newAxisMask:o,shrinkAxisMask:l};return $.runKernel(Qo,u,c)}var Rm=O({stridedSlice_:kE});function IE(e){let t={x:C(e,"x","tan")};return $.runKernel(el,t)}var Fm=O({tan_:IE});function hn(e,t){ds(e);let n=Or(e,t);if(n.length!==1)throw new Error("tensor1d() requires values to be a flat/TypedArray");return Oa(e,null,n,t)}function En(e,t,n){if(ds(e),t!=null&&t.length!==2)throw new Error("tensor2d() requires shape to have two numbers");let r=Or(e,n);if(r.length!==2&&r.length!==1)throw new Error("tensor2d() requires values to be number[][] or flat/TypedArray");if(r.length===1&&t==null)throw new Error("tensor2d() requires shape to be provided when `values` are a flat/TypedArray");return Oa(e,t,r,n)}function NE(e,t,n){if(ds(e),t!=null&&t.length!==4)throw new Error("tensor4d() requires shape to have four numbers");let r=Or(e,n);if(r.length!==4&&r.length!==1)throw new Error("tensor4d() requires values to be number[][][][] or flat/TypedArray");if(r.length===1&&t==null)throw new Error("tensor4d() requires shape to be provided when `values` are a flat array");return Oa(e,t,r,n)}function SE(e,t,n){if(ds(e),t!=null&&t.length!==5)throw new Error("tensor5d() requires shape to have five numbers");let r=Or(e,n);if(r.length!==5&&r.length!==1)throw new Error("tensor5d() requires values to be number[][][][][] or flat/TypedArray");if(r.length===1&&t==null)throw new Error("tensor5d() requires shape to be provided when `values` are a flat array");return Oa(e,t,r,n)}function TE(e,t,n){if(ds(e),t!=null&&t.length!==6)throw new Error("tensor6d() requires shape to have six numbers");let r=Or(e,n);if(r.length!==6&&r.length!==1)throw new Error("tensor6d() requires values to be number[][][][][][] or flat/TypedArray");if(r.length===1&&t==null)throw new Error("tensor6d() requires shape to be provided when `values` are a flat array");return t=t||r,Oa(e,t,r,n)}function EE(e,t=1,n=!0){let r=C(e,"x","topk");if(r.rank===0)throw new Error("topk() expects the input to be of rank 1 or higher");let a=r.shape[r.shape.length-1];if(t>a)throw new Error(`'k' passed to topk() must be <= the last dimension (${a}) but got ${t}`);let s={x:r},i={k:t,sorted:n},[o,l]=$.runKernel(tl,s,i);return{values:o,indices:l}}var Mm=O({topk_:EE});function CE(e,t=0,n=1,r,a){if(r!=null&&r==="bool")throw new Error("Unsupported data type $ { dtype }");let s=new Im(t,n,r,!0,a),i=Ue(e,r);for(let o=0;o<i.values.length;o++)i.values[o]=s.nextValue();return i.toTensor()}var Xd=O({truncatedNormal_:CE});function RE(e,t=0){let n=C(e,"x","unique","string_or_numeric");F(n.rank>0,()=>"The input tensor must be at least 1D");let r={x:n},a={axis:t},[s,i]=$.runKernel(hd,r,a);return{values:s,indices:i}}var Kd=O({unique_:RE});function FE(e,t,n){let r=C(e,"x","unsortedSegmentSum"),a=C(t,"segmentIds","unsortedSegmentSum","int32");F(Kt(n),()=>"numSegments must be of dtype int");let s={x:r,segmentIds:a},i={numSegments:n};return $.runKernel(Mu,s,i)}var $m=O({unsortedSegmentSum_:FE});function ME(e,t=0){let n=C(e,"x","unstack","string_or_numeric");F(t>=-n.shape.length&&t<n.shape.length,()=>`Axis = ${t} is not in [-${n.shape.length}, ${n.shape.length})`);let r={value:n},a={axis:t};return $.runKernel(nl,r,a)}var hr=O({unstack_:ME});function Fx(e,t=!0,n,r){return $.makeVariable(e,t,n,r)}function Mx(e,t){let n=[];for(let s=0;s<t.length;s++)t[s]&&n.push(s);let r=Ue(e,"int32"),a=Ue([n.length,e.length],"int32");for(let s=0;s<n.length;s++){let i=r.indexToLoc(n[s]),o=s*e.length;a.values.set(i,o)}return a.toTensor()}async function $E(e){let t=C(e,"condition","whereAsync","bool"),n=await t.data(),r=Mx(t.shape,n);return e!==t&&t.dispose(),r}var Dm=$E;async function DE(e,t,n){let r=C(e,"tensor","boolMask"),a=C(t,"mask","boolMask","bool"),s=n==null?0:n,i=a.rank,o=r.shape;F(i>0,()=>"mask cannot be scalar"),un(o.slice(s,s+i),a.shape,"mask's shape must match the first K dimensions of tensor's shape,");let l=1;for(let m=s;m<s+i;m++)l*=o[m];let u=o.slice(0,s).concat([l],o.slice(s+i)),c=G(r,u),h=G(a,[-1]),d=await Dm(h),p=Ha(d,[1]),f=Ai(c,p,s);return e!==r&&r.dispose(),t!==a&&a.dispose(),p.dispose(),c.dispose(),h.dispose(),d.dispose(),f}var OE=DE;function zE(e,t="euclidean",n=null,r=!1){e=C(e,"x","norm");let a=$x(e,t,n),s=a.shape;if(r){let i=or(n,e.shape);s=gi(a.shape,i)}return G(a,s)}function $x(e,t,n=null){if(e.rank===0)return Bt(e);if(e.rank!==1&&n===null)return $x(G(e,[-1]),t,n);if(e.rank===1||typeof n=="number"||Array.isArray(n)&&n.length===1){if(t===1)return Re(Bt(e),n);if(t===Infinity)return Qn(Bt(e),n);if(t===-Infinity)return _l(Bt(e),n);if(t==="euclidean"||t===2)return an(Re(ha(Bt(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 Qn(Re(Bt(e),n[0]),n[1]-1);if(t===Infinity)return Qn(Re(Bt(e),n[1]),n[0]);if(t===-Infinity)return _l(Re(Bt(e),n[1]),n[0]);if(t==="fro"||t==="euclidean")return an(Re(ht(e),n));throw new Error(`Error in norm: invalid ord value: ${t}`)}throw new Error(`Error in norm: invalid axis: ${n}`)}var Zd=O({norm_:zE});function PE(e,t,n,r,a=!0){let s=C(e,"v","movingAverage"),i=C(t,"x","movingAverage"),o=C(n,"decay","movingAverage");m5(s,i),F(oa(s.shape,i.shape),()=>"Shape mismatch in v and x");let l=Ie(1),u=we(l,o),c=P(we(i,s),u);if(a){F(r!=null,()=>"When using zeroDebias: true, step is required.");let h=C(r,"step","movingAverage");c=be(c,we(l,ha(o,h)))}return ie(s,c)}var LE=O({movingAverage_:PE});function WE(e,t,n){let r=C(e,"indices","scatterND","int32"),a=C(t,"updates","scatterND");jf(a,r,n);let s={indices:r,updates:a},i={shape:n};return $.runKernel(jo,s,i)}var Dx=O({scatterND_:WE});function BE(e,t,n,r){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 a=e.rank>0?e.shape[0]:1,s=e.rank>1?e.shape[1]:1;if(n.length!==s)throw new Error(`outputShape has incorrect number of elements:, ${n.length}, should be: ${s}.`);let i=t.size;if(!(t.rank===0||t.rank===1&&i===a))throw new Error(`sparseValues has incorrect shape ${t.shape}, should be [] or [${a}]`);if(t.dtype!==r.dtype)throw new Error("sparseValues.dtype must match defaultValues.dtype")}function VE(e,t,n,r=0){let a=C(e,"sparseIndices","sparseToDense","int32"),s=C(t,"sparseValues","sparseToDense"),i=C(r,"defaultValue","sparseToDense",s.dtype);BE(a,s,n,i);let o={sparseIndices:a,sparseValues:s,defaultValue:i},l={outputShape:n};return $.runKernel(ud,o,l)}var Om=O({sparseToDense_:VE});function UE(e,t){let n=C(t,"indices","gatherND","int32"),r={params:C(e,"x","gatherND"),indices:n};return $.runKernel(Io,r)}var Ox=O({gatherND_:UE});function HE(e,t){if(t==null)return e.shape.slice();if(oa(e.shape,t))return t;if(e.shape.length===t.length){let n=[];for(let r=0;r<e.shape.length;r++)t[r]==null&&e.shape[r]!=null?n.push(e.shape[r]):n.push(t[r]);return n}return t}function jE(e,t,n,r){let a=C(e,"x","dropout");if(F(a.dtype==="float32",()=>`x has to be a floating point tensor since it's going to be scaled, but got a ${a.dtype} tensor instead.`),F(t>=0&&t<1,()=>`rate must be a float in the range [0, 1), but got ${t}.`),t===0)return e instanceof Ge?a.clone():a;let s=HE(a,n),i=1-t,o=be(wl(ie(kl(s,0,1,"float32",r),i)),i);return P(a,o)}var zx=O({dropout_:jE});function Px(e){return Math.floor(Math.pow(2,Math.ceil(Math.log(e)/Math.log(2))))}function zm(e,t,n){let r=1-e%2,a=new Float32Array(e);for(let s=0;s<e;++s){let i=2*Math.PI*s/(e+r-1);a[s]=t-n*Math.cos(i)}return hn(a,"float32")}async function GE(e,t,n=1){let r=C(e,"predictions","inTopK"),a=C(t,"targets","inTopK");F(r.rank>1,()=>`inTopK() expects the predictions to be of rank 2 or higher, but got ${r.rank}`),F(r.rank-1===a.rank,()=>`predictions rank should be 1 larger than targets rank, but got predictions rank ${r.rank} and targets rank ${a.rank}`),un(r.shape.slice(0,r.shape.length-1),a.shape,"predictions's shape should be align with the targets' shape, except the last dimension.");let s=r.shape[r.shape.length-1];F(n>0&&n<=s,()=>`'k' passed to inTopK() must be > 0 && <= the predictions last dimension (${s}), but got ${n}`);let i=await r.data(),o=await a.data(),[l,u]=[i.length/s,s],c=Q2("bool",l);for(let h=0;h<l;h++){let d=h*u,p=i.subarray(d,d+u),f=[];for(let m=0;m<p.length;m++)f.push({value:p[m],index:m});f.sort((m,A)=>A.value-m.value),c[h]=0;for(let m=0;m<n;m++)if(f[m].index===o[h]){c[h]=1;break}}return e!==r&&r.dispose(),t!==a&&a.dispose(),vr(c,a.shape,"bool")}var qE=GE,ja={};We(ja,{conv2d:()=>XE,depthwiseConv2d:()=>KE,matMul:()=>ZE});function YE(e,t,n,r,a,s="NHWC",i){let o=e;e.rank===3&&(o=G(e,[1,e.shape[0],e.shape[1],e.shape[2]]));let l=t;l.rank===3&&(l=G(t,[1,t.shape[0],t.shape[1],t.shape[2]])),F(o.rank===4,()=>`Error in conv2dDerFilter: input must be rank 4, but got shape ${o.shape}.`),F(l.rank===4,()=>`Error in conv2dDerFilter: dy must be rank 4, but got shape ${l.shape}.`),F(n.length===4,()=>`Error in conv2dDerFilter: filterShape must be length 4, but got ${n}.`);let u=s==="NHWC"?o.shape[3]:o.shape[1],c=s==="NHWC"?l.shape[3]:l.shape[1];F(u===n[2],()=>`Error in conv2dDerFilter: depth of input ${u}) must match input depth in filter (${n[2]}.`),F(c===n[3],()=>`Error in conv2dDerFilter: depth of dy (${c}) must match output depth for filter (${n[3]}).`),i!=null&&F(Kt(a),()=>`Error in conv2dDerFilter: pad must be an integer when using, dimRoundingMode ${i} but got pad ${a}.`);let h={x:o,dy:l},d={strides:r,pad:a,dataFormat:s,dimRoundingMode:i,filterShape:n};return $.runKernel(Bh,h,d)}var Pm=O({conv2DBackpropFilter_:YE});function Yd(e,t,n){if(n==null||n==="linear")return e;if(n==="relu")return P(e,Nl(t));throw new Error(`Cannot compute gradient for fused activation ${n}.`)}function Jd(e,t){let n=t,r=Vt(e.shape,t.shape);return r.length>0&&(n=Re(n,r)),G(n,e.shape)}function Qd(e,t,n,r){if(t==="linear")return e;if(t==="relu")return Ur(e);if(t==="elu")return xl(e);if(t==="relu6")return Ld(e);if(t==="prelu")return rc(e,n);if(t==="leakyrelu")return Qu(e,r);throw new Error(`Unknown fused activation ${t}.`)}var ep=(e,t)=>!(e>0)||t==="linear";function JE({x:e,filter:t,strides:n,pad:r,dataFormat:a="NHWC",dilations:s=[1,1],dimRoundingMode:i,bias:o,activation:l="linear",preluActivationWeights:u,leakyreluAlpha:c}){if(l=l||"linear",ep($.state.gradientDepth,l)===!1){let w=ua(e,t,n,r,a,s,i);return o!=null&&(w=ie(w,o)),Qd(w,l,u,c)}let h=C(e,"x","conv2d"),d=C(t,"filter","conv2d"),p=h,f=!1;h.rank===3&&(f=!0,p=G(h,[1,h.shape[0],h.shape[1],h.shape[2]])),F(p.rank===4,()=>`Error in fused conv2d: input must be rank 4, but got rank ${p.rank}.`),F(d.rank===4,()=>`Error in fused conv2d: filter must be rank 4, but got rank ${d.rank}.`),i!=null&&F(Kt(r),()=>`Error in fused conv2d: pad must be an integer when using, dimRoundingMode ${i} but got pad ${r}.`),F(p.shape[3]===d.shape[2],()=>`Error in conv2d: depth of input (${p.shape[3]}) must match input depth for filter ${d.shape[2]}.`),F(Lr(n,s),()=>`Error in conv2D: Either strides or dilations must be 1. Got strides ${n} and dilations '${s}'`),F(a==="NHWC",()=>`Error in conv2d: got dataFormat of ${a} but only NHWC is currently supported.`);let m=qu(p.shape,d.shape,n,s,r,i),A;o!=null&&(A=C(o,"bias","fused conv2d"),[A]=Nt(A,h),wt(m.outShape,A.shape));let y;u!=null&&(y=C(u,"prelu weights","fused conv2d"));let g=(w,x)=>{let[N,S,T,M]=x,D=Yd(w,T,l);F(Wa(s),()=>`Error in gradient of fused conv2D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '${s}'`);let z=um(S.shape,D,N,n,r),W=Pm(S,D,N.shape,n,r),U=[z,W];if(M!=null){let H=Jd(M,D);U.push(H)}return U},b={x:p,filter:d,bias:A,preluActivationWeights:y},_={strides:n,pad:r,dataFormat:a,dilations:s,dimRoundingMode:i,activation:l,leakyreluAlpha:c};return o==null?Wr((w,x,N)=>{let S=$.runKernel(oi,b,_);return N([x,w,S]),f&&(S=G(S,[S.shape[1],S.shape[2],S.shape[3]])),{value:S,gradFunc:g}})(p,d):Wr((w,x,N,S)=>{let T=$.runKernel(oi,b,_);return S([x,w,T,N]),f&&(T=G(T,[T.shape[1],T.shape[2],T.shape[3]])),{value:T,gradFunc:g}})(p,d,A)}var XE=O({fusedConv2d_:JE});function QE(e,t,n,r,a,s=[1,1],i){let o=e;e.rank===3&&(o=G(e,[1,e.shape[0],e.shape[1],e.shape[2]]));let l=t;l.rank===3&&(l=G(t,[1,t.shape[0],t.shape[1],t.shape[2]]));let u={x:o,dy:l},c={strides:r,pad:a,dimRoundingMode:i,dilations:s,filterShape:n};return $.runKernel(jh,u,c)}var Lx=O({depthwiseConv2dNativeBackpropFilter_:QE});function eC(e,t,n,r,a,s=[1,1],i){let o=t,l=!1;t.rank===3&&(l=!0,o=G(t,[1,t.shape[0],t.shape[1],t.shape[2]]));let u={dy:o,filter:n},c={strides:r,pad:a,dimRoundingMode:i,dilations:s,inputShape:e},h=$.runKernel(Gh,u,c);return l?G(h,[h.shape[1],h.shape[2],h.shape[3]]):h}var Wx=O({depthwiseConv2dNativeBackpropInput_:eC});function tC({x:e,filter:t,strides:n,pad:r,dataFormat:a="NHWC",dilations:s=[1,1],dimRoundingMode:i,bias:o,activation:l="linear",preluActivationWeights:u,leakyreluAlpha:c}){if(ep($.state.gradientDepth,l)===!1){let w=gl(e,t,n,r,a,s,i);return o!=null&&(w=ie(w,o)),Qd(w,l,u,c)}let h=C(e,"x","depthwiseConv2d"),d=C(t,"filter","depthwiseConv2d"),p=h,f=!1;h.rank===3&&(f=!0,p=G(h,[1,h.shape[0],h.shape[1],h.shape[2]])),F(p.rank===4,()=>`Error in fused depthwiseConv2d: input must be rank 4, but got rank ${p.rank}.`),F(d.rank===4,()=>`Error in fused depthwiseConv2d: filter must be rank 4, but got rank ${d.rank}.`),F(p.shape[3]===d.shape[2],()=>`Error in fused depthwiseConv2d: number of input channels (${p.shape[3]}) must match the inChannels dimension in filter ${d.shape[2]}.`),s==null&&(s=[1,1]),F(Lr(n,s),()=>`Error in fused depthwiseConv2d: Either strides or dilations must be 1. Got strides ${n} and dilations '${s}'`),i!=null&&F(Kt(r),()=>`Error in fused depthwiseConv2d: pad must be an integer when using dimRoundingMode ${i} but got pad ${r}.`);let m=qu(p.shape,d.shape,n,s,r,i,!0),A;o!=null&&(A=C(o,"bias","fused conv2d"),[A]=Nt(A,h),wt(m.outShape,A.shape));let y;u!=null&&(y=C(u,"prelu weights","fused depthwiseConv2d"));let g=(w,x)=>{F(Wa(s),()=>`Error in gradient of fused depthwiseConv2d: dilation rates greater than 1 are not yet supported. Got dilations '${s}'`);let[N,S,T,M]=x,D=Yd(w,T,l),z=Wx(S.shape,D,N,n,r,s,i),W=Lx(S,D,N.shape,n,r,s,i);if(M!=null){let U=Jd(A,D);return[z,W,U]}return[z,W]},b={x:p,filter:d,bias:A,preluActivationWeights:y},_={strides:n,pad:r,dataFormat:a,dilations:s,dimRoundingMode:i,activation:l,leakyreluAlpha:c};return o==null?Wr((w,x,N)=>{let S=$.runKernel(li,b,_);return N([x,w,S]),f&&(S=G(S,[S.shape[1],S.shape[2],S.shape[3]])),{value:S,gradFunc:g}})(p,d):Wr((w,x,N,S)=>{let T=$.runKernel(li,b,_);return S([x,w,T,N]),f&&(T=G(T,[T.shape[1],T.shape[2],T.shape[3]])),{value:T,gradFunc:g}})(p,d,A)}var KE=O({fusedDepthwiseConv2d_:tC});function nC({a:e,b:t,transposeA:n=!1,transposeB:r=!1,bias:a,activation:s="linear",preluActivationWeights:i,leakyreluAlpha:o}){if(ep($.state.gradientDepth,s)===!1){let M=Ke(e,t,n,r);return a!=null&&(M=ie(M,a)),Qd(M,s,i,o)}let l=C(e,"a","fused matMul"),u=C(t,"b","fused matMul");[l,u]=Nt(l,u);let c=n?l.shape[l.rank-2]:l.shape[l.rank-1],h=r?u.shape[u.rank-1]:u.shape[u.rank-2],d=n?l.shape[l.rank-1]:l.shape[l.rank-2],p=r?u.shape[u.rank-2]:u.shape[u.rank-1],f=l.shape.slice(0,-2),m=u.shape.slice(0,-2),A=Lt(f),y=Lt(m);F(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 ${u.rank}.`),F(oa(f,m),()=>`Error in fused matMul: outer dimensions (${f}) and (${m}) of Tensors with shapes ${l.shape} and ${u.shape} must match.`),F(c===h,()=>`Error in fused matMul: inner shapes (${c}) and (${h}) of Tensors with shapes ${l.shape} and ${u.shape} and transposeA=${n} and transposeB=${r} must match.`);let g=l.shape.slice(0,-2).concat([d,p]),b=n?G(l,[A,c,d]):G(l,[A,d,c]),_=r?G(u,[y,p,h]):G(u,[y,h,p]),w;a!=null&&(w=C(a,"bias","fused matMul"),[w]=Nt(w,l),wt(g,w.shape));let x;i!=null&&(x=C(i,"prelu weights","fused matMul"));let N=(M,D)=>{let[z,W,U,H]=D,X=Yd(G(M,U.shape),U,s),j,ee;if(!n&&!r?(j=Ke(X,W,!1,!0),ee=Ke(z,X,!0,!1)):!n&&r?(j=Ke(X,W,!1,!1),ee=Ke(X,z,!0,!1)):n&&!r?(j=Ke(W,X,!1,!0),ee=Ke(z,X,!1,!1)):(j=Ke(W,X,!0,!0),ee=Ke(X,z,!0,!0)),a!=null){let Y=Jd(H,X);return[j,ee,Y]}else return[j,ee]},S={a:b,b:_,bias:w,preluActivationWeights:x},T={transposeA:n,transposeB:r,activation:s,leakyreluAlpha:o};return a==null?Wr((M,D,z)=>{let W=$.runKernel(ii,S,T);return z([M,D,W]),{value:G(W,g),gradFunc:N}})(b,_):Wr((M,D,z,W)=>{let U=$.runKernel(ii,S,T);return W([M,D,U,z]),{value:G(U,g),gradFunc:N}})(b,_,w)}var ZE=O({fusedMatMul_:nC});function rC(e){return zm(e,.54,.46)}var aC=O({hammingWindow_:rC});function sC(e){return zm(e,.5,.5)}var Bx=O({hannWindow_:sC});function iC(e,t,n,r=!1,a=0){let s=0,i=[];for(;s+t<=e.size;)i.push($e(e,s,t)),s+=n;if(r)for(;s<e.size;){let o=s+t-e.size,l=lt([$e(e,s,t-o),Ju([o],a)]);i.push(l),s+=n}return i.length===0?En([],[0,t]):G(lt(i),[i.length,t])}var Vx=O({frame_:iC});function oC(e,t,n,r,a=Bx){r==null&&(r=Px(t));let s=Vx(e,t,n),i=P(s,a(t)),o=[];for(let l=0;l<s.shape[0];l++)o.push(lc($e(i,[l,0],[1,t]),r));return lt(o)}var lC=O({stft_:oC});function uC(e,t,n,r,a="bilinear",s=0){let i=C(e,"image","cropAndResize"),o=C(t,"boxes","cropAndResize","float32"),l=C(n,"boxInd","cropAndResize","int32"),u=o.shape[0];F(i.rank===4,()=>`Error in cropAndResize: image must be rank 4,but got rank ${i.rank}.`),F(o.rank===2&&o.shape[1]===4,()=>`Error in cropAndResize: boxes must be have size [${u},4] but had shape ${o.shape}.`),F(l.rank===1&&l.shape[0]===u,()=>`Error in cropAndResize: boxInd must be have size [${u}] but had shape ${o.shape}.`),F(r.length===2,()=>`Error in cropAndResize: cropSize must be of length 2, but got length ${r.length}.`),F(r[0]>=1&&r[1]>=1,()=>`cropSize must be atleast [1,1], but was ${r}`),F(a==="bilinear"||a==="nearest",()=>`method must be bilinear or nearest, but was ${a}`);let c={image:i,boxes:o,boxInd:l},h={method:a,extrapolationValue:s,cropSize:r};return $.runKernel(Ao,c,h)}var cC=O({cropAndResize_:uC});function hC(e){let t=C(e,"image","flipLeftRight","float32");F(t.rank===4,()=>`Error in flipLeftRight: image must be rank 4,but got rank ${t.rank}.`);let n={image:t};return $.runKernel(vo,n,{})}var dC=O({flipLeftRight_:hC});function pC(e,t,n=0,r=.5){let a=C(e,"image","rotateWithOffset","float32");F(a.rank===4,()=>`Error in rotateWithOffset: image must be rank 4,but got rank ${a.rank}.`);let s={image:a},i={radians:t,fillValue:n,center:r};return $.runKernel(al,s,i)}var fC=O({rotateWithOffset_:pC});function Sl(e,t,n,r,a,s){r==null&&(r=.5),a==null&&(a=Number.NEGATIVE_INFINITY),s==null&&(s=0);let i=e.shape[0];return n=Math.min(n,i),F(0<=r&&r<=1,()=>`iouThreshold must be in [0, 1], but was '${r}'`),F(e.rank===2,()=>`boxes must be a 2D tensor, but was of rank '${e.rank}'`),F(e.shape[1]===4,()=>`boxes must have 4 columns, but 2nd dimension was ${e.shape[1]}`),F(t.rank===1,()=>"scores must be a 1D tensor"),F(t.shape[0]===i,()=>`scores has incompatible shape with boxes. Expected ${i}, but was ${t.shape[0]}`),F(0<=s&&s<=1,()=>`softNmsSigma must be in [0, 1], but was '${s}'`),{maxOutputSize:n,iouThreshold:r,scoreThreshold:a,softNmsSigma:s}}function mC(e,t,n,r=.5,a=Number.NEGATIVE_INFINITY){let s=C(e,"boxes","nonMaxSuppression"),i=C(t,"scores","nonMaxSuppression"),o=Sl(s,i,n,r,a);n=o.maxOutputSize,r=o.iouThreshold,a=o.scoreThreshold;let l={maxOutputSize:n,iouThreshold:r,scoreThreshold:a};return $.runKernel(zo,{boxes:s,scores:i},l)}var AC=O({nonMaxSuppression_:mC});function gC(e,t,n){let r=yC(e,t,n),a=r<0?-(r+1):r;e.splice(a,0,t)}function yC(e,t,n){return wC(e,t,n||xC)}function xC(e,t){return e>t?1:e<t?-1:0}function wC(e,t,n){let r=0,a=e.length,s=0,i=!1;for(;r<a;){s=r+(a-r>>>1);let o=n(t,e[s]);o>0?r=s+1:(a=s,i=!o)}return i?r:-r-1}function Ux(e,t,n,r,a){return Lm(e,t,n,r,a,0)}function Hx(e,t,n,r,a,s){return Lm(e,t,n,r,a,0,!1,s,!0)}function jx(e,t,n,r,a,s){return Lm(e,t,n,r,a,s,!0)}function Lm(e,t,n,r,a,s,i=!1,o=!1,l=!1){let u=[];for(let A=0;A<t.length;A++)t[A]>a&&u.push({score:t[A],boxIndex:A,suppressBeginIndex:0});u.sort(Gx);let c=s>0?-.5/s:0,h=[],d=[];for(;h.length<n&&u.length>0;){let A=u.pop(),{score:y,boxIndex:g,suppressBeginIndex:b}=A;if(y<a)break;let _=!1;for(let w=h.length-1;w>=b;--w){let x=bC(e,g,h[w]);if(x>=r){_=!0;break}if(A.score=A.score*_C(r,c,x),A.score<=a)break}A.suppressBeginIndex=h.length,_||(A.score===y?(h.push(g),d.push(A.score)):A.score>a&&gC(u,A,Gx))}let p=h.length,f=n-p;o&&f>0&&(h.push(...new Array(f).fill(0)),d.push(...new Array(f).fill(0)));let m={selectedIndices:h};return i&&(m.selectedScores=d),l&&(m.validOutputs=p),m}function bC(e,t,n){let r=e.subarray(t*4,t*4+4),a=e.subarray(n*4,n*4+4),s=Math.min(r[0],r[2]),i=Math.min(r[1],r[3]),o=Math.max(r[0],r[2]),l=Math.max(r[1],r[3]),u=Math.min(a[0],a[2]),c=Math.min(a[1],a[3]),h=Math.max(a[0],a[2]),d=Math.max(a[1],a[3]),p=(o-s)*(l-i),f=(h-u)*(d-c);if(p<=0||f<=0)return 0;let m=Math.max(s,u),A=Math.max(i,c),y=Math.min(o,h),g=Math.min(l,d),b=Math.max(y-m,0)*Math.max(g-A,0);return b/(p+f-b)}function _C(e,t,n){let r=Math.exp(t*n*n);return n<=e?r:0}function Gx(e,t){return e.score-t.score||e.score===t.score&&t.boxIndex-e.boxIndex}async function vC(e,t,n,r=.5,a=Number.NEGATIVE_INFINITY){let s=C(e,"boxes","nonMaxSuppressionAsync"),i=C(t,"scores","nonMaxSuppressionAsync"),o=Sl(s,i,n,r,a);n=o.maxOutputSize,r=o.iouThreshold,a=o.scoreThreshold;let l=await Promise.all([s.data(),i.data()]),u=l[0],c=l[1],{selectedIndices:h}=Ux(u,c,n,r,a);return s!==e&&s.dispose(),i!==t&&i.dispose(),hn(h,"int32")}var kC=vC;function IC(e,t,n,r=.5,a=Number.NEGATIVE_INFINITY,s=0){let i=C(e,"boxes","nonMaxSuppression"),o=C(t,"scores","nonMaxSuppression"),l=Sl(i,o,n,r,a,s);n=l.maxOutputSize,r=l.iouThreshold,a=l.scoreThreshold,s=l.softNmsSigma;let u={boxes:i,scores:o},c={maxOutputSize:n,iouThreshold:r,scoreThreshold:a,softNmsSigma:s},h=$.runKernel(Lo,u,c);return{selectedIndices:h[0],selectedScores:h[1]}}var NC=O({nonMaxSuppressionWithScore_:IC});async function SC(e,t,n,r=.5,a=Number.NEGATIVE_INFINITY,s=0){let i=C(e,"boxes","nonMaxSuppressionAsync"),o=C(t,"scores","nonMaxSuppressionAsync"),l=Sl(i,o,n,r,a,s);n=l.maxOutputSize,r=l.iouThreshold,a=l.scoreThreshold,s=l.softNmsSigma;let u=await Promise.all([i.data(),o.data()]),c=u[0],h=u[1],{selectedIndices:d,selectedScores:p}=jx(c,h,n,r,a,s);return i!==e&&i.dispose(),o!==t&&o.dispose(),{selectedIndices:hn(d,"int32"),selectedScores:hn(p)}}var TC=SC;function EC(e,t,n,r=.5,a=Number.NEGATIVE_INFINITY,s=!1){let i=C(e,"boxes","nonMaxSuppression"),o=C(t,"scores","nonMaxSuppression"),l=Sl(i,o,n,r,a,null),u=l.maxOutputSize,c=l.iouThreshold,h=l.scoreThreshold,d={boxes:i,scores:o},p={maxOutputSize:u,iouThreshold:c,scoreThreshold:h,padToMaxOutputSize:s},f=$.runKernel(Po,d,p);return{selectedIndices:f[0],validOutputs:f[1]}}var CC=O({nonMaxSuppressionPadded_:EC});async function RC(e,t,n,r=.5,a=Number.NEGATIVE_INFINITY,s=!1){let i=C(e,"boxes","nonMaxSuppressionAsync"),o=C(t,"scores","nonMaxSuppressionAsync"),l=Sl(i,o,n,r,a,null),u=l.maxOutputSize,c=l.iouThreshold,h=l.scoreThreshold,[d,p]=await Promise.all([i.data(),o.data()]),{selectedIndices:f,validOutputs:m}=Hx(d,p,u,c,h,s);return i!==e&&i.dispose(),o!==t&&o.dispose(),{selectedIndices:hn(f,"int32"),validOutputs:Ie(m,"int32")}}var FC=RC;function MC(e,t,n=!1,r=!1){let a=C(e,"images","resizeBilinear");F(a.rank===3||a.rank===4,()=>`Error in resizeBilinear: x must be rank 3 or 4, but got rank ${a.rank}.`),F(t.length===2,()=>`Error in resizeBilinear: new shape must 2D, but got shape ${t}.`),F(r===!1||n===!1,()=>"Error in resizeBilinear: If halfPixelCenters is true, alignCorners must be false.");let s=a,i=!1;a.rank===3&&(i=!0,s=G(a,[1,a.shape[0],a.shape[1],a.shape[2]]));let[]=t,o={images:s},l={alignCorners:n,halfPixelCenters:r,size:t},u=$.runKernel(Gs,o,l);return i?G(u,[u.shape[1],u.shape[2],u.shape[3]]):u}var qx=O({resizeBilinear_:MC});function $C(e,t,n=!1,r=!1){let a=C(e,"images","resizeNearestNeighbor");F(a.rank===3||a.rank===4,()=>`Error in resizeNearestNeighbor: x must be rank 3 or 4, but got rank ${a.rank}.`),F(t.length===2,()=>`Error in resizeNearestNeighbor: new shape must 2D, but got shape ${t}.`),F(a.dtype==="float32"||a.dtype==="int32",()=>"`images` must have `int32` or `float32` as dtype"),F(r===!1||n===!1,()=>"Error in resizeNearestNeighbor: If halfPixelCenters is true, alignCorners must be false.");let s=a,i=!1;a.rank===3&&(i=!0,s=G(a,[1,a.shape[0],a.shape[1],a.shape[2]]));let[]=t,o={images:s},l={alignCorners:n,halfPixelCenters:r,size:t},u=$.runKernel(Cu,o,l);return i?G(u,[u.shape[1],u.shape[2],u.shape[3]]):u}var Xx=O({resizeNearestNeighbor_:$C});function DC(e,t,n="nearest",r="constant",a=0,s){let i=C(e,"image","transform","float32"),o=C(t,"transforms","transform","float32");F(i.rank===4,()=>`Error in transform: image must be rank 4,but got rank ${i.rank}.`),F(o.rank===2&&(o.shape[0]===i.shape[0]||o.shape[0]===1)&&o.shape[1]===8,()=>"Error in transform: Input transform should be batch x 8 or 1 x 8"),F(s==null||s.length===2,()=>`Error in transform: outputShape must be [height, width] or null, but got ${s}.`);let l={image:i,transforms:o},u={interpolation:n,fillMode:r,fillValue:a,outputShape:s};return $.runKernel(cd,l,u)}var OC=O({transform_:DC});function zC(e,t,n){F(t%1==0,()=>`bandPart(): numLower must be an integer, got ${t}.`),F(n%1==0,()=>`bandPart(): numUpper must be an integer, got ${n}.`);let r=C(e,"a","bandPart");F(r.rank>=2,()=>`bandPart(): Rank must be at least 2, got ${r.rank}.`);let a=r.shape,[s,i]=r.shape.slice(-2);if(!(t<=s))throw new Error(`bandPart(): numLower (${t}) must not be greater than the number of rows (${s}).`);if(!(n<=i))throw new Error(`bandPart(): numUpper (${n}) must not be greater than the number of columns (${i}).`);t<0&&(t=s),n<0&&(n=i);let o=G(Pd(0,s,1,"int32"),[-1,1]),l=Pd(0,i,1,"int32"),u=we(o,l),c=cr(yi(u,Ie(+t,"int32")),Ua(u,Ie(-n,"int32"))),h=$t([s,i],r.dtype);return G(An(hr(G(r,[-1,s,i])).map(d=>Tn(c,d,h))),a)}var PC=O({bandPart_:zC});function LC(e){let t;if(Array.isArray(e)){t=!1,F(e!=null&&e.length>0,()=>"Gram-Schmidt process: input must not be null, undefined, or empty");let a=e[0].shape[0];for(let s=1;s<e.length;++s)F(e[s].shape[0]===a,()=>`Gram-Schmidt: Non-unique lengths found in the input vectors: (${e[s].shape[0]} vs. ${a})`)}else t=!0,e=Ut(e,e.shape[0],0).map(a=>Ha(a,[0]));F(e.length<=e[0].shape[0],()=>`Gram-Schmidt: Number of vectors (${e.length}) exceeds number of dimensions (${e[0].shape[0]}).`);let n=[],r=e;for(let a=0;a<e.length;++a)n.push($.tidy(()=>{let s=r[a];if(a>0)for(let i=0;i<a;++i){let o=P(Re(P(n[i],s)),n[i]);s=we(s,o)}return be(s,Zd(s,"euclidean"))}));return t?An(n,0):n}var WC=O({gramSchmidt_:LC});function BC(e,t=!1){if(F(e.rank>=2,()=>`qr() requires input tensor to have a rank >= 2, but got rank ${e.rank}`),e.rank===2)return Kx(e,t);{let n=e.shape.slice(0,e.shape.length-2).reduce((l,u)=>l*u),r=hr(G(e,[n,e.shape[e.shape.length-2],e.shape[e.shape.length-1]]),0),a=[],s=[];r.forEach(l=>{let[u,c]=Kx(l,t);a.push(u),s.push(c)});let i=G(An(a,0),e.shape),o=G(An(s,0),e.shape);return[i,o]}}function Kx(e,t=!1){return $.tidy(()=>{F(e.shape.length===2,()=>`qr2d() requires a 2D Tensor, but got a ${e.shape.length}D Tensor.`);let n=e.shape[0],r=e.shape[1],a=Am(n),s=zr(e),i=En([[1]],[1,1]),o=zr(i),l=n>=r?r:n;for(let u=0;u<l;++u){let c=s,h=o,d=a;[o,s,a]=$.tidy(()=>{let p=$e(s,[u,u],[n-u,1]),f=Zd(p),m=$e(s,[u,u],[1,1]),A=Tn(ur(m,0),En([[-1]]),En([[1]])),y=we(m,P(A,f)),g=be(p,y);g.shape[0]===1?o=zr(i):o=lt([i,$e(g,[1,0],[g.shape[0]-1,g.shape[1]])],0);let b=St(be(Ke(A,y),f)),_=$e(s,[u,0],[n-u,r]),w=P(b,o),x=ot(o);if(u===0)s=we(_,Ke(w,Ke(x,_)));else{let T=we(_,Ke(w,Ke(x,_)));s=lt([$e(s,[0,0],[u,r]),T],0)}let N=ot(w),S=$e(a,[0,u],[n,a.shape[1]-u]);if(u===0)a=we(S,Ke(Ke(S,o),N));else{let T=we(S,Ke(Ke(S,o),N));a=lt([$e(a,[0,0],[n,u]),T],1)}return[o,s,a]}),Me([c,h,d])}return!t&&n>r&&(a=$e(a,[0,0],[n,r]),s=$e(s,[0,0],[r,r])),[a,s]})}var VC=O({qr_:BC}),yn;(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"})(yn||(yn={}));function UC(e,t,n=yn.SUM_BY_NONZERO_WEIGHTS){let r=C(e,"losses","computeWeightedLoss"),a=null;t!=null&&(a=C(t,"weights","computeWeightedLoss"));let s=a==null?r:P(r,a);if(n===yn.NONE)return s;if(n===yn.SUM)return Re(s);if(n===yn.MEAN){if(a==null)return Tt(s);{let i=r.size/a.size,o=be(Re(s),Re(a));return i>1?be(o,Ie(i)):o}}if(n===yn.SUM_BY_NONZERO_WEIGHTS){if(a==null)return be(Re(s),Ie(r.size));{let i=P(a,Vr(r.shape)),o=ge(Re(xi(i,Ie(0))),"float32");return be(Re(s),o)}}throw Error(`Unknown reduction: ${n}`)}var da=O({computeWeightedLoss_:UC});function HC(e,t,n,r=yn.SUM_BY_NONZERO_WEIGHTS){let a=C(e,"labels","absoluteDifference"),s=C(t,"predictions","absoluteDifference"),i=null;n!=null&&(i=C(n,"weights","absoluteDifference")),un(a.shape,s.shape,"Error in absoluteDifference: ");let o=Bt(we(a,s));return da(o,i,r)}var jC=O({absoluteDifference_:HC});function GC(e,t,n,r,a=yn.SUM_BY_NONZERO_WEIGHTS){let s=C(e,"labels","cosineDistance"),i=C(t,"predictions","cosineDistance"),o=null;r!=null&&(o=C(r,"weights","cosineDistance")),un(s.shape,i.shape,"Error in cosineDistance: ");let l=Ie(1),u=we(l,Re(P(s,i),n,!0));return da(u,o,a)}var qC=O({cosineDistance_:GC});function XC(e,t,n,r=yn.SUM_BY_NONZERO_WEIGHTS){let a=C(e,"labels","hingeLoss"),s=C(t,"predictions","hingeLoss"),i=null;n!=null&&(i=C(n,"weights","hingeLoss")),un(a.shape,s.shape,"Error in hingeLoss: ");let o=Ie(1);a=we(P(Ie(2),a),o);let l=Ur(we(o,P(a,s)));return da(l,i,r)}var KC=O({hingeLoss_:XC});function ZC(e,t,n,r=1,a=yn.SUM_BY_NONZERO_WEIGHTS){let s=C(e,"labels","huberLoss"),i=C(t,"predictions","huberLoss"),o=null;n!=null&&(o=C(n,"weights","huberLoss")),un(s.shape,i.shape,"Error in huberLoss: ");let l=Ie(r),u=Bt(we(i,s)),c=vl(u,l),h=we(u,c),d=ie(P(Ie(.5),ht(c)),P(l,h));return da(d,o,a)}var YC=O({huberLoss_:ZC});function JC(e,t,n,r=1e-7,a=yn.SUM_BY_NONZERO_WEIGHTS){let s=C(e,"labels","logLoss"),i=C(t,"predictions","logLoss"),o=null;n!=null&&(o=C(n,"weights","logLoss")),un(s.shape,i.shape,"Error in logLoss: ");let l=Ie(1),u=Ie(r),c=St(P(s,zn(ie(i,u)))),h=P(we(l,s),zn(ie(we(l,i),u))),d=we(c,h);return da(d,o,a)}var QC=O({logLoss_:JC});function eR(e,t,n,r=yn.SUM_BY_NONZERO_WEIGHTS){let a=C(e,"labels","meanSquaredError"),s=C(t,"predictions","meanSquaredError"),i=null;n!=null&&(i=C(n,"weights","meanSquaredError")),un(a.shape,s.shape,"Error in meanSquaredError: ");let o=qd(a,s);return da(o,i,r)}var tR=O({meanSquaredError_:eR});function nR(e,t){let n=C(e,"labels","sigmoidCrossEntropyWithLogits"),r=C(t,"logits","sigmoidCrossEntropyWithLogits");un(n.shape,r.shape,"Error in sigmoidCrossEntropyWithLogits: ");let a=Ur(r),s=P(r,n),i=Fd(Jn(St(Bt(r))));return ie(we(a,s),i)}function rR(e,t,n,r=0,a=yn.SUM_BY_NONZERO_WEIGHTS){let s=C(e,"multiClassLabels","sigmoidCrossEntropy"),i=C(t,"logits","sigmoidCrossEntropy"),o=null;if(n!=null&&(o=C(n,"weights","sigmoidCrossEntropy")),un(s.shape,i.shape,"Error in sigmoidCrossEntropy: "),r>0){let u=Ie(r),c=Ie(1),h=Ie(.5);s=ie(P(s,we(c,u)),P(h,u))}let l=nR(s,i);return da(l,o,a)}var aR=O({sigmoidCrossEntropy_:rR});function sR(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 Wr((r,a,s)=>{let i=wm(a,[n],!0),o=we(ge(a,"float32"),i);s([r,o]);let l=St(P(o,r));return{value:Re(l,[n]),gradFunc:(u,c)=>{let[h,d]=c,p=gi(u.shape,[n]);return[P(G(u,p),we(ge(h,"float32"),Jn(d))),P(G(u,p),we(Jn(d),ge(h,"float32")))]}}})(e,t)}function iR(e,t,n,r=0,a=yn.SUM_BY_NONZERO_WEIGHTS){let s=C(e,"onehotLabels","softmaxCrossEntropy"),i=C(t,"logits","softmaxCrossEntropy"),o=null;if(n!=null&&(o=C(n,"weights","softmaxCrossEntropy")),un(s.shape,i.shape,"Error in softmaxCrossEntropy: "),r>0){let u=Ie(r),c=Ie(1),h=Ie(s.shape[1]);s=ie(P(s,we(c,u)),be(u,h))}let l=sR(s,i);return da(l,o,a)}var oR=O({softmaxCrossEntropy_:iR}),lR={fft:oc,ifft:Il,rfft:lc,irfft:Gd},uR={hammingWindow:aC,hannWindow:Bx,frame:Vx,stft:lC},tt={flipLeftRight:dC,resizeNearestNeighbor:Xx,resizeBilinear:qx,rotateWithOffset:fC,cropAndResize:cC,nonMaxSuppression:AC,nonMaxSuppressionAsync:kC,nonMaxSuppressionWithScore:NC,nonMaxSuppressionWithScoreAsync:TC,nonMaxSuppressionPadded:CC,nonMaxSuppressionPaddedAsync:FC,transform:OC},Zx={bandPart:PC,gramSchmidt:WC,qr:VC},cR={absoluteDifference:jC,computeWeightedLoss:da,cosineDistance:qC,hingeLoss:KC,huberLoss:YC,logLoss:QC,meanSquaredError:tR,sigmoidCrossEntropy:aR,softmaxCrossEntropy:oR},pa=class extends Q5{minimize(e,t=!1,n){let{value:r,grads:a}=this.computeGradients(e,n);if(n!=null){let s=n.map(i=>({name:i.name,tensor:a[i.name]}));this.applyGradients(s)}else this.applyGradients(a);return Me(a),t?r:(r.dispose(),null)}get iterations(){return this.iterations_==null&&(this.iterations_=0),this.iterations_}incrementIterations(){this.iterations_=this.iterations+1}computeGradients(e,t){return bx(e,t)}dispose(){this.iterations_!=null&&Me(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 ${this.getClassName()}`)}async extractIterations(e){return this.iterations_=(await e[0].tensor.data())[0],e.slice(1)}};Object.defineProperty(pa,Symbol.hasInstance,{value:e=>e.minimize!=null&&e.computeGradients!=null&&e.applyGradients!=null});var tp=class extends pa{constructor(e,t,n=null){super();this.learningRate=e,this.rho=t,this.epsilon=n,this.accumulatedGrads=[],this.accumulatedUpdates=[],n==null&&(this.epsilon=$.backend.epsilon())}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,n)=>{let r=$.registeredVariables[t],a=!1;this.accumulatedGrads[n]==null&&(this.accumulatedGrads[n]={originalName:`${t}/accum_grad`,variable:B(()=>qe(r).variable(a))}),this.accumulatedUpdates[n]==null&&(this.accumulatedUpdates[n]={originalName:`${t}/accum_var`,variable:B(()=>qe(r).variable(a))});let s=Array.isArray(e)?e[n].tensor:e[t];if(s==null)return;let i=this.accumulatedGrads[n].variable,o=this.accumulatedUpdates[n].variable;B(()=>{let l=ie(P(i,this.rho),P(ht(s),1-this.rho)),u=P(be(an(ie(o,this.epsilon)),an(ie(i,this.epsilon))),s),c=ie(P(o,this.rho),P(ht(u),1-this.rho));i.assign(l),o.assign(c);let h=ie(P(u,-this.learningRate),r);r.assign(h)})}),this.incrementIterations()}dispose(){this.accumulatedUpdates!=null&&(Me(this.accumulatedGrads.map(e=>e.variable)),Me(this.accumulatedUpdates.map(e=>e.variable)))}async getWeights(){let e=[...this.accumulatedGrads,...this.accumulatedUpdates];return[await this.saveIterations()].concat(e.map(t=>({name:t.originalName,tensor:t.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=e.length/2,n=!1;this.accumulatedGrads=e.slice(0,t).map(r=>({originalName:r.name,variable:r.tensor.variable(n)})),this.accumulatedUpdates=e.slice(t,t*2).map(r=>({originalName:r.name,variable:r.tensor.variable(n)}))}getConfig(){return{learningRate:this.learningRate,rho:this.rho,epsilon:this.epsilon}}static fromConfig(e,t){return new e(t.learningRate,t.rho,t.epsilon)}};tp.className="Adadelta";Pa(tp);var np=class extends pa{constructor(e,t=.1){super();this.learningRate=e,this.initialAccumulatorValue=t,this.accumulatedGrads=[]}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,n)=>{let r=$.registeredVariables[t];if(this.accumulatedGrads[n]==null){let i=!1;this.accumulatedGrads[n]={originalName:`${t}/accumulator`,variable:B(()=>Ju(r.shape,this.initialAccumulatorValue).variable(i))}}let a=Array.isArray(e)?e[n].tensor:e[t];if(a==null)return;let s=this.accumulatedGrads[n].variable;B(()=>{let i=ie(s,ht(a));s.assign(i);let o=ie(P(be(a,an(ie(i,$.backend.epsilon()))),-this.learningRate),r);r.assign(o)})}),this.incrementIterations()}dispose(){this.accumulatedGrads!=null&&Me(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)}};np.className="Adagrad";Pa(np);var rp=class extends pa{constructor(e,t,n,r=null){super();this.learningRate=e,this.beta1=t,this.beta2=n,this.epsilon=r,this.accumulatedFirstMoment=[],this.accumulatedSecondMoment=[],B(()=>{this.accBeta1=Ie(t).variable(),this.accBeta2=Ie(n).variable()}),r==null&&(this.epsilon=$.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(n=>n.name):Object.keys(e);B(()=>{let n=we(1,this.accBeta1),r=we(1,this.accBeta2);t.forEach((a,s)=>{let i=$.registeredVariables[a],o=!1;this.accumulatedFirstMoment[s]==null&&(this.accumulatedFirstMoment[s]={originalName:`${a}/m`,variable:B(()=>qe(i).variable(o))}),this.accumulatedSecondMoment[s]==null&&(this.accumulatedSecondMoment[s]={originalName:`${a}/v`,variable:B(()=>qe(i).variable(o))});let l=Array.isArray(e)?e[s].tensor:e[a];if(l==null)return;let u=this.accumulatedFirstMoment[s].variable,c=this.accumulatedSecondMoment[s].variable,h=ie(P(u,this.beta1),P(l,1-this.beta1)),d=ie(P(c,this.beta2),P(ht(l),1-this.beta2)),p=be(h,n),f=be(d,r);u.assign(h),c.assign(d);let m=ie(P(be(p,ie(an(f),this.epsilon)),-this.learningRate),i);i.assign(m)}),this.accBeta1.assign(P(this.accBeta1,this.beta1)),this.accBeta2.assign(P(this.accBeta2,this.beta2))}),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.accBeta2.dispose(),this.accumulatedFirstMoment!=null&&Me(this.accumulatedFirstMoment.map(e=>e.variable)),this.accumulatedSecondMoment!=null&&Me(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),B(()=>{this.accBeta1.assign(ha(this.beta1,this.iterations_+1)),this.accBeta2.assign(ha(this.beta2,this.iterations_+1))});let t=e.length/2,n=!1;this.accumulatedFirstMoment=e.slice(0,t).map(r=>({originalName:r.name,variable:r.tensor.variable(n)})),this.accumulatedSecondMoment=e.slice(t,t*2).map(r=>({originalName:r.name,variable:r.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)}};rp.className="Adam";Pa(rp);var ap=class extends pa{constructor(e,t,n,r=null,a=0){super();this.learningRate=e,this.beta1=t,this.beta2=n,this.epsilon=r,this.decay=a,this.accumulatedFirstMoment=[],this.accumulatedWeightedInfNorm=[],B(()=>{this.iteration=Ie(0).variable(),this.accBeta1=Ie(t).variable()}),r==null&&(this.epsilon=$.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(n=>n.name):Object.keys(e);B(()=>{let n=we(1,this.accBeta1),r=be(-this.learningRate,ie(P(this.iteration,this.decay),1));t.forEach((a,s)=>{let i=$.registeredVariables[a],o=!1;this.accumulatedFirstMoment[s]==null&&(this.accumulatedFirstMoment[s]={originalName:`${a}/m`,variable:qe(i).variable(o)}),this.accumulatedWeightedInfNorm[s]==null&&(this.accumulatedWeightedInfNorm[s]={originalName:`${a}/v`,variable:qe(i).variable(o)});let l=Array.isArray(e)?e[s].tensor:e[a];if(l==null)return;let u=this.accumulatedFirstMoment[s].variable,c=this.accumulatedWeightedInfNorm[s].variable,h=ie(P(u,this.beta1),P(l,1-this.beta1)),d=P(c,this.beta2),p=Bt(l),f=Br(d,p);u.assign(h),c.assign(f);let m=ie(P(be(r,n),be(h,ie(f,this.epsilon))),i);i.assign(m)}),this.iteration.assign(ie(this.iteration,1)),this.accBeta1.assign(P(this.accBeta1,this.beta1))}),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.iteration.dispose(),this.accumulatedFirstMoment!=null&&Me(this.accumulatedFirstMoment.map(e=>e.variable)),this.accumulatedWeightedInfNorm!=null&&Me(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)}};ap.className="Adamax";Pa(ap);var uc=class extends pa{constructor(e){super();this.learningRate=e,this.setLearningRate(e)}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,n)=>{let r=Array.isArray(e)?e[n].tensor:e[t];if(r==null)return;let a=$.registeredVariables[t];B(()=>{let s=ie(P(this.c,r),a);a.assign(s)})}),this.incrementIterations()}setLearningRate(e){this.learningRate=e,this.c!=null&&this.c.dispose(),this.c=Zt(Ie(-e))}dispose(){this.c.dispose()}async getWeights(){return[await this.saveIterations()]}async setWeights(e){if(e=await this.extractIterations(e),e.length!==0)throw new Error("SGD optimizer does not have settable weights.")}getConfig(){return{learningRate:this.learningRate}}static fromConfig(e,t){return new e(t.learningRate)}};uc.className="SGD";Pa(uc);var sp=class extends uc{constructor(e,t,n=!1){super(e);this.learningRate=e,this.momentum=t,this.useNesterov=n,this.accumulations=[],this.m=Ie(this.momentum)}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,n)=>{let r=$.registeredVariables[t];if(this.accumulations[n]==null){let i=!1;this.accumulations[n]={originalName:`${t}/momentum`,variable:B(()=>qe(r).variable(i))}}let a=this.accumulations[n].variable,s=Array.isArray(e)?e[n].tensor:e[t];s!=null&&B(()=>{let i,o=ie(P(this.m,a),s);this.useNesterov?i=ie(P(this.c,ie(s,P(o,this.m))),r):i=ie(P(this.c,o),r),a.assign(o),r.assign(i)})}),this.incrementIterations()}dispose(){this.m.dispose(),this.accumulations!=null&&Me(this.accumulations.map(e=>e.variable))}setMomentum(e){this.momentum=e}async getWeights(){return[await this.saveIterations()].concat(this.accumulations.map(e=>({name:e.originalName,tensor:e.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=!1;this.accumulations=e.map(n=>({originalName:n.name,variable:n.tensor.variable(t)}))}getConfig(){return{learningRate:this.learningRate,momentum:this.momentum,useNesterov:this.useNesterov}}static fromConfig(e,t){return new e(t.learningRate,t.momentum,t.useNesterov)}};sp.className="Momentum";Pa(sp);var ip=class extends pa{constructor(e,t=.9,n=0,r=null,a=!1){super();if(this.learningRate=e,this.decay=t,this.momentum=n,this.epsilon=r,this.accumulatedMeanSquares=[],this.accumulatedMoments=[],this.accumulatedMeanGrads=[],this.centered=a,r==null&&(this.epsilon=$.backend.epsilon()),e==null)throw new Error("learningRate for RMSPropOptimizer must be defined.")}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,n)=>{let r=$.registeredVariables[t],a=!1;this.accumulatedMeanSquares[n]==null&&(this.accumulatedMeanSquares[n]={originalName:`${t}/rms`,variable:B(()=>qe(r).variable(a))}),this.accumulatedMoments[n]==null&&(this.accumulatedMoments[n]={originalName:`${t}/momentum`,variable:B(()=>qe(r).variable(a))}),this.accumulatedMeanGrads[n]==null&&this.centered&&(this.accumulatedMeanGrads[n]={originalName:`${t}/mg`,variable:B(()=>qe(r).variable(a))});let s=Array.isArray(e)?e[n].tensor:e[t];if(s==null)return;let i=this.accumulatedMeanSquares[n].variable,o=this.accumulatedMoments[n].variable;B(()=>{let l=ie(P(i,this.decay),P(ht(s),1-this.decay));if(this.centered){let u=this.accumulatedMeanGrads[n].variable,c=ie(P(u,this.decay),P(s,1-this.decay)),h=be(P(s,this.learningRate),an(we(l,ie(ht(c),this.epsilon)))),d=ie(P(o,this.momentum),h);i.assign(l),u.assign(c),o.assign(d);let p=we(r,d);r.assign(p)}else{let u=ie(P(i,this.decay),P(ht(s),1-this.decay)),c=ie(P(o,this.momentum),be(P(s,this.learningRate),an(ie(u,this.epsilon))));i.assign(u),o.assign(c);let h=we(r,c);r.assign(h)}})}),this.incrementIterations()}dispose(){this.accumulatedMeanSquares!=null&&Me(this.accumulatedMeanSquares.map(e=>e.variable)),this.accumulatedMeanGrads!=null&&this.centered&&Me(this.accumulatedMeanGrads.map(e=>e.variable)),this.accumulatedMoments!=null&&Me(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(r=>({originalName:r.name,variable:r.tensor.variable(n)})),this.accumulatedMoments=e.slice(t,t*2).map(r=>({originalName:r.name,variable:r.tensor.variable(n)})),this.centered&&(this.accumulatedMeanGrads=e.slice(t*2,t*3).map(r=>({originalName:r.name,variable:r.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)}};ip.className="RMSProp";Pa(ip);var wi=class{static sgd(e){return new uc(e)}static momentum(e,t,n=!1){return new sp(e,t,n)}static rmsprop(e,t=.9,n=0,r=null,a=!1){return new ip(e,t,n,r,a)}static adam(e=.001,t=.9,n=.999,r=null){return new rp(e,t,n,r)}static adadelta(e=.001,t=.95,n=null){return new tp(e,t,n)}static adamax(e=.002,t=.9,n=.999,r=null,a=0){return new ap(e,t,n,r,a)}static adagrad(e,t=.1){return new np(e,t)}},bi={sgd:wi.sgd,momentum:wi.momentum,adadelta:wi.adadelta,adagrad:wi.adagrad,rmsprop:wi.rmsprop,adamax:wi.adamax,adam:wi.adam},hR=(()=>typeof requestAnimationFrame!="undefined"?requestAnimationFrame:typeof setImmediate!="undefined"?setImmediate:e=>e())();function op(){return new Promise(e=>hR(()=>e()))}var R={};We(R,{ERF_A1:()=>_R,ERF_A2:()=>vR,ERF_A3:()=>kR,ERF_A4:()=>IR,ERF_A5:()=>NR,ERF_P:()=>bR,PARALLELIZE_THRESHOLD:()=>Wm,SELU_SCALE:()=>Jx,SELU_SCALEALPHA:()=>Yx,applyActivation:()=>Qd,assertAndGetBroadcastShape:()=>wt,assertAxesAreInnerMostDims:()=>qS,assertParamsConsistent:()=>dR,assignToTypedArray:()=>$R,axesAreInnerMostDims:()=>gm,calculateShapes:()=>B5,combineLocations:()=>vx,complexWithEvenIndex:()=>RR,complexWithOddIndex:()=>FR,computeConv2DInfo:()=>qu,computeConv3DInfo:()=>ix,computeDefaultPad:()=>im,computeDilation2DInfo:()=>yN,computeOptimalWindowSize:()=>fR,computeOutAndReduceShapes:()=>kx,computeOutShape:()=>pR,computePool2DInfo:()=>sx,computePool3DInfo:()=>gN,convertConv2DDataFormat:()=>ax,eitherStridesOrDilationsAreOne:()=>Lr,expandShapeToKeepDim:()=>gi,exponent:()=>OR,exponents:()=>DR,fromStringArrayToUint8:()=>LR,fromUint8ToStringArray:()=>PR,getAxesPermutation:()=>Ix,getBroadcastDims:()=>uS,getComplexWithIndex:()=>MR,getFusedBiasGradient:()=>Jd,getFusedDyActivation:()=>Yd,getImageCenter:()=>mR,getInnerMostAxes:()=>XS,getPermuted:()=>yR,getReductionAxes:()=>Vt,getReshaped:()=>AR,getReshapedPermuted:()=>gR,getSliceBeginCoords:()=>xR,getSliceSize:()=>wR,getUndoAxesPermutation:()=>xm,log:()=>TR,mergeRealAndImagArrays:()=>ER,prepareAndValidate:()=>W5,prepareSplitSize:()=>zR,segment_util:()=>Qx,shouldFuse:()=>ep,slice_util:()=>fn,splitRealAndImagArrays:()=>CR,tupleValuesAreOne:()=>Wa,upcastType:()=>lr,validateInput:()=>jf,validateUpdateShape:()=>Hf,warn:()=>SR});function dR(e,t){let n=e[0].length;e.forEach((a,s)=>{F(a.length===n,()=>`Error in concat${n}D: rank of tensors[${s}] must be the same as the rank of the rest (${n})`)}),F(t>=0&&t<n,()=>`Error in concat${n}D: axis must be between 0 and ${n-1}.`);let r=e[0];e.forEach((a,s)=>{for(let i=0;i<n;i++)F(i===t||a[i]===r[i],()=>`Error in concat${n}D: Shape of tensors[${s}] (${a}) does not match the shape of the rest (${r}) along the non-concatenated axis ${s}.`)})}function pR(e,t){let n=e[0].slice();for(let r=1;r<e.length;r++)n[t]+=e[r][t];return n}var Wm=30;function fR(e){return e<=Wm?e:Mh(e,Math.floor(Math.sqrt(e)))}function mR(e,t,n){let r=n*(typeof e=="number"?e:e[0]),a=t*(typeof e=="number"?e:e[1]);return[r,a]}function AR(e,t,n,r=!0){let a=[];if(r)a=a.concat(t.slice(0)),a.push(e[0]/n),a=a.concat(e.slice(1));else{a=a.concat(e[0]);let s=t.length;for(let i=0;i<s;++i)a=a.concat([e[i+1]/t[i],t[i]]);a=a.concat(e.slice(s+1))}return a}function yR(e,t,n=!0){let r=[];if(n){r.push(t);for(let a=t+1;a<e;++a)a<=2*t?(r.push(a),r.push(a-(t+1))):r.push(a)}else{let a=[],s=[];for(let i=1;i<e;++i)i>=t*2+1||i%2==1?s.push(i):a.push(i);r.push(...a),r.push(0),r.push(...s)}return r}function gR(e,t,n,r=!0){let a=[];r?a.push(e[0]/n):a.push(e[0]*n);for(let s=1;s<e.length;++s)s<=t.length?r?a.push(t[s-1]*e[s]):a.push(e[s]/t[s-1]):a.push(e[s]);return a}function xR(e,t){let n=[0];for(let r=0;r<t;++r)n.push(e[r][0]);return n}function wR(e,t,n){let r=e.slice(0,1);for(let a=0;a<n;++a)r.push(e[a+1]-t[a][0]-t[a][1]);return r}var Yx=1.7580993408473768,Jx=1.0507009873554805,bR=.3275911,_R=.254829592,vR=-.284496736,kR=1.421413741,IR=-1.453152027,NR=1.061405429;function SR(...e){J().getBool("IS_TEST")||console.warn(...e)}function TR(...e){J().getBool("IS_TEST")||console.log(...e)}function ER(e,t){if(e.length!==t.length)throw new Error(`Cannot merge real and imag arrays of different lengths. real:${e.length}, imag: ${t.length}.`);let n=new Float32Array(e.length*2);for(let r=0;r<n.length;r+=2)n[r]=e[r/2],n[r+1]=t[r/2];return n}function CR(e){let t=new Float32Array(e.length/2),n=new Float32Array(e.length/2);for(let r=0;r<e.length;r+=2)t[r/2]=e[r],n[r/2]=e[r+1];return{real:t,imag:n}}function RR(e){let t=Math.ceil(e.length/4),n=new Float32Array(t),r=new Float32Array(t);for(let a=0;a<e.length;a+=4)n[Math.floor(a/4)]=e[a],r[Math.floor(a/4)]=e[a+1];return{real:n,imag:r}}function FR(e){let t=Math.floor(e.length/4),n=new Float32Array(t),r=new Float32Array(t);for(let a=2;a<e.length;a+=4)n[Math.floor(a/4)]=e[a],r[Math.floor(a/4)]=e[a+1];return{real:n,imag:r}}function MR(e,t){let n=e[t*2],r=e[t*2+1];return{real:n,imag:r}}function $R(e,t,n,r){e[r*2]=t,e[r*2+1]=n}function DR(e,t){let n=new Float32Array(e/2),r=new Float32Array(e/2);for(let a=0;a<Math.ceil(e/2);a++){let s=(t?2:-2)*Math.PI*(a/e);n[a]=Math.cos(s),r[a]=Math.sin(s)}return{real:n,imag:r}}function OR(e,t,n){let r=(n?2:-2)*Math.PI*(e/t),a=Math.cos(r),s=Math.sin(r);return{real:a,imag:s}}function zR(e,t,n=0){let r=[];if(typeof t=="number")F(e.shape[n]%t==0,()=>"Number of splits must evenly divide the axis."),r=new Array(t).fill(e.shape[n]/t);else{let a=t.reduce((i,o)=>(o===-1&&(i+=1),i),0);F(a<=1,()=>"There should be only one negative value in split array.");let s=t.indexOf(-1);if(s!==-1){let i=t.reduce((o,l)=>l>0?o+l:o);t[s]=e.shape[n]-i}F(e.shape[n]===t.reduce((i,o)=>i+o),()=>"The sum of sizes must match the size of the axis dimension."),r=t}return r}var Qx={};We(Qx,{collectGatherOpShapeInfo:()=>VR,computeOutShape:()=>BR,segOpComputeOptimalWindowSize:()=>WR});function WR(e,t){let n=!1,r;for(e<=Wm?(r=e,n=!0):r=Mh(e,Math.floor(Math.sqrt(e)));!n;)r>t||r===e?n=!0:r=Mh(e,r+1);return r}function BR(e,t,n){let r=[],a=e.length;for(let s=0;s<a;s++)s!==t?r.push(e[s]):r.push(n);return r}function VR(e,t,n,r){let a=t.shape.length,s=e.shape.length;if(r!==0&&(r<-a||r>a))throw new Error(`Expect batchDims in the range of [-${a}, ${a}], but got ${r}`);if(r<0&&(r+=a),r>s)throw new Error(`batchDims (${r}) must be less than rank(x) (
|
|
${s}).`);if(n<r)throw new Error(`batchDims (${r}) must be less than or equal to axis (${n}).`);for(let h=0;h<r;++h)if(e.shape[h]!==t.shape[h])throw new Error(`x.shape[${h}]: ${e.shape[h]} should be equal to indices.shape[${h}]: ${t.shape[h]}.`);let i=e.shape[n],o=[],l=1,u=1,c=1;for(let h=0;h<r;++h)o.push(e.shape[h]),l*=e.shape[h];for(let h=r;h<n;h++)o.push(e.shape[h]),u*=e.shape[h];for(let h=r;h<a;h++)o.push(t.shape[h]);for(let h=n+1;h<s;h++)o.push(e.shape[h]),c*=e.shape[h];return{batchSize:l,sliceSize:c,outerSize:u,dimSize:i,outputShape:o}}function PR(e){try{return e.map(t=>md(t))}catch(t){throw new Error(`Failed to decode encoded string bytes into utf-8, error: ${t}`)}}function LR(e){return e.map(t=>Ou(t))}var Hr={};We(Hr,{nonMaxSuppressionV3Impl:()=>Ux,nonMaxSuppressionV4Impl:()=>Hx,nonMaxSuppressionV5Impl:()=>jx,whereImpl:()=>Mx});function ke(e,t){Array.isArray(e)||(e=[e]),e.forEach(n=>{n!=null&&v.assert(n.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the CPU backend.`)})}var UR=Hr.whereImpl,lp=class extends fu{constructor(){super();this.blockSize=48,this.firstUse=!0,this.data=new Rh(this,Pr())}nextDataId(){return lp.nextDataId++}write(e,t,n){this.firstUse&&(this.firstUse=!1,J().get("IS_NODE")&&R.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 r={id:this.nextDataId()};return this.data.set(r,{values:e,dtype:n,refCount:1}),r}makeTensorInfo(e,t,n){let r;if(t==="string"&&n!=null&&n.length>0&&v.isString(n[0])){let a=n.map(s=>v.encodeString(s));r=this.write(a,e,t)}else r=this.write(n,e,t);return{dataId:r,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,r,a){this.data.set(e,{values:t,dtype:r,refCount:a})}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 r=this.readSync(n.real.dataId),a=this.readSync(n.imag.dataId);return R.mergeRealAndImagArrays(r,a)}return this.data.get(e).values}bufferSync(e){let t=this.readSync(e.dataId),n=t;if(e.dtype==="string")try{n=t.map(r=>v.decodeString(r))}catch(r){throw new Error("Failed to decode encoded string bytes into utf-8")}return Ue(e.shape,e.dtype,n)}makeOutput(e,t,n){let r=this.write(e,t,n);return Pr().makeTensorFromDataId(r,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=v.now();return e(),{kernelMs:v.now()-t}}memory(){return{unreliable:!0,reasons:["The reported memory is an upper bound. Due to automatic garbage collection, the true allocated memory may be less."]}}where(e){ke([e],"where");let t=this.readSync(e.dataId);return UR(e.shape,t)}dispose(){}floatPrecision(){return 32}epsilon(){return super.epsilon()}};lp.nextDataId=0;var Bm={};We(Bm,{addImpl:()=>tw,bincountImpl:()=>Vm,bincountReduceImpl:()=>nw,ceilImpl:()=>rw,concatImpl:()=>Um,expImpl:()=>aw,expm1Impl:()=>sw,floorImpl:()=>iw,gatherV2Impl:()=>ow,greaterImpl:()=>lw,lessImpl:()=>uw,linSpaceImpl:()=>cw,logImpl:()=>hw,maxImpl:()=>dw,maximumImpl:()=>pw,minimumImpl:()=>fw,multiplyImpl:()=>Hm,negImpl:()=>mw,notEqualImpl:()=>Aw,prodImpl:()=>yw,rangeImpl:()=>Gm,rsqrtImpl:()=>gw,simpleAbsImpl:()=>ew,sliceImpl:()=>up,squaredDifferenceImpl:()=>xw,stridedSliceImpl:()=>ww,subImpl:()=>bw,tileImpl:()=>_w,topKImpl:()=>vw,transposeImpl:()=>jm,uniqueImpl:()=>kw});function ew(e){let t=new Float32Array(e.length);for(let n=0;n<e.length;++n)t[n]=Math.abs(e[n]);return t}var HR=e=>{let{x:t}=e.inputs,n=e.backend;ke(t,"abs");let r=new Float32Array(v.sizeFromShape(t.shape)),a=n.data.get(t.dataId).values;return r=ew(a),n.makeOutput(r,t.shape,"float32")},jR={kernelName:so,backendName:"cpu",kernelFunc:HR};function Dt(e){return(t,n,r,a,s)=>{let i=R.assertAndGetBroadcastShape(t,n),o=i.length,l=v.computeStrides(i),u=v.sizeFromShape(i),c=v.getTypedArrayFromDType(s,u),h=t.length,d=n.length,p=v.computeStrides(t),f=v.computeStrides(n),m=R.getBroadcastDims(t,i),A=R.getBroadcastDims(n,i);if(m.length+A.length===0)for(let y=0;y<c.length;++y)c[y]=e(r[y%r.length],a[y%a.length]);else for(let y=0;y<c.length;++y){let g=v.indexToLoc(y,o,l),b=g.slice(-h);m.forEach(N=>b[N]=0);let _=v.locToIndex(b,h,p),w=g.slice(-d);A.forEach(N=>w[N]=0);let x=v.locToIndex(w,d,f);c[y]=e(r[_],a[x])}return[c,i]}}function Wn(e){let{inputs:t,backend:n}=e,{real:r,imag:a}=t,s=n.data.get(r.dataId).values,i=n.data.get(a.dataId).values,o=n.makeTensorInfo(r.shape,"complex64"),l=n.data.get(o.dataId);return l.complexTensorInfos={real:n.makeTensorInfo(r.shape,"float32",s),imag:n.makeTensorInfo(a.shape,"float32",i)},o}var GR={kernelName:Wh,backendName:"cpu",kernelFunc:Wn};function cp(e,t,n="float32"){if(n==="complex64"){let a=cp(e,t,"float32"),s=cp(e,t,"float32");return Wn({inputs:{real:a,imag:s},backend:e})}let r=v.makeZerosTypedArray(v.sizeFromShape(t),n);return e.makeTensorInfo(t,n,r)}function jr(e){let{inputs:t,backend:n}=e,{x:r}=t;return n.incRef(r.dataId),{dataId:r.dataId,shape:r.shape,dtype:r.dtype}}var qR={kernelName:Rs,backendName:"cpu",kernelFunc:jr};function _i(e){let{inputs:t,backend:n}=e,{input:r}=t,a=n.data.get(r.dataId).complexTensorInfos.real,s=n.data.get(a.dataId).values;return n.makeTensorInfo(a.shape,a.dtype,s)}var XR={kernelName:id,backendName:"cpu",kernelFunc:_i};function Ga(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{dtype:s}=r;if(s==="complex64"){if(a.dtype==="complex64")return jr({inputs:{x:a},backend:n});let i=cp(n,a.shape,a.dtype),o=Ga({inputs:{x:a},backend:n,attrs:{dtype:"float32"}}),l=Wn({inputs:{real:o,imag:i},backend:n});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}if(a.dtype==="complex64"){let i=_i({inputs:{input:a},backend:n}),o=Ga({inputs:{x:i},backend:n,attrs:{dtype:s}});return n.disposeIntermediateTensorInfo(i),o}if(!v.hasEncodingLoss(a.dtype,s)){let i=jr({inputs:{x:a},backend:n});return{dataId:i.dataId,shape:i.shape,dtype:s}}if(s==="int32"){let i=n.data.get(a.dataId).values,o=Int32Array.from(i);return n.makeTensorInfo(a.shape,"int32",o)}if(s==="bool"){let i=n.data.get(a.dataId).values,o=v.toTypedArray([0],a.dtype),[l,u]=Dt((c,h)=>c!==h?1:0)(a.shape,[],i,o,"bool");return n.makeTensorInfo(u,"bool",l)}throw new Error(`Error in Cast: failed to cast ${a.dtype} to ${s}`)}var KR={kernelName:gs,backendName:"cpu",kernelFunc:Ga};function Yt(e,t,n,r){return n==null?({inputs:a,backend:s})=>{let{a:i,b:o}=a,l=s;ke([i,o],e);let u=l.data.get(i.dataId).values,c=l.data.get(o.dataId).values,h=r||i.dtype,[d,p]=t(i.shape,o.shape,u,c,h);return l.makeTensorInfo(p,h,d)}:({inputs:a,backend:s})=>{let{a:i,b:o}=a,l=s;if(i.dtype==="complex64"||o.dtype==="complex64"){let u=Ga({inputs:{x:i},backend:l,attrs:{dtype:"complex64"}}),c=l.data.get(u.dataId),h=c.complexTensorInfos.real,d=c.complexTensorInfos.imag,p=l.data.get(h.dataId).values,f=l.data.get(d.dataId).values,m=Ga({inputs:{x:o},backend:l,attrs:{dtype:"complex64"}}),A=l.data.get(m.dataId),y=A.complexTensorInfos.real,g=A.complexTensorInfos.imag,b=l.data.get(y.dataId).values,_=l.data.get(g.dataId).values,[w,x,N]=n(i.shape,o.shape,p,f,b,_),S=l.makeTensorInfo(N,"float32",w),T=l.makeTensorInfo(N,"float32",x),M=Wn({inputs:{real:S,imag:T},backend:l});return l.disposeIntermediateTensorInfo(u),l.disposeIntermediateTensorInfo(m),l.disposeIntermediateTensorInfo(S),l.disposeIntermediateTensorInfo(T),M}else{let u=l.data.get(i.dataId).values,c=l.data.get(o.dataId).values,h=r||i.dtype,[d,p]=t(i.shape,o.shape,u,c,h);return l.makeTensorInfo(p,h,d)}}}function qm(e){return(t,n,r,a,s,i)=>{let o=R.assertAndGetBroadcastShape(t,n),l=v.sizeFromShape(o),u=o.length,c=v.computeStrides(o),h=v.getTypedArrayFromDType("float32",l),d=v.getTypedArrayFromDType("float32",l),p=R.getBroadcastDims(t,o),f=R.getBroadcastDims(n,o),m=R.mergeRealAndImagArrays(r,a),A=R.mergeRealAndImagArrays(s,i),y=t.length,g=v.computeStrides(t),b=n.length,_=v.computeStrides(n);if(p.length+f.length===0)for(let w=0;w<h.length;w++){let x=w%m.length,N=w%A.length,S=e(m[x*2],m[x*2+1],A[N*2],A[N*2+1]);h[w]=S.real,d[w]=S.imag}else for(let w=0;w<h.length;w++){let x=v.indexToLoc(w,u,c),N=x.slice(-y);p.forEach(z=>N[z]=0);let S=v.locToIndex(N,y,g),T=x.slice(-b);f.forEach(z=>T[z]=0);let M=v.locToIndex(T,b,_),D=e(m[S*2],m[S*2+1],A[M*2],A[M*2+1]);h[w]=D.real,d[w]=D.imag}return[h,d,o]}}var tw=Dt((e,t)=>e+t),ZR=qm((e,t,n,r)=>({real:e+n,imag:t+r})),cc=Yt(Ra,tw,ZR),YR={kernelName:Ra,backendName:"cpu",kernelFunc:cc};function Vm(e,t,n,r,a){let s=v.sizeFromShape(r),i=v.makeZerosTypedArray(a,n);for(let o=0;o<e.length;o++){let l=e[o];if(l<0)throw new Error("Input x must be non-negative!");l>=a||(s>0?i[l]+=t[o]:i[l]+=1)}return i}function nw(e,t,n,r=!1){let a=e.shape[0],s=e.shape[1],i=Ue([a,n],t.dtype);for(let o=0;o<a;o++)for(let l=0;l<s;l++){let u=e.get(o,l);if(u<0)throw new Error("Input x must be non-negative!");u>=n||(r?i.set(1,o,u):t.size>0?i.set(i.get(o,u)+t.get(o,l),o,u):i.set(i.get(o,u)+1,o,u))}return i}function Tl(e){return(t,n,r)=>{let a=v.getTypedArrayFromDType(n,t.length);for(let s=0;s<t.length;++s)a[s]=e(t[s],r);return a}}function ut(e,t,n){return({inputs:r,attrs:a,backend:s})=>{let{x:i}=r;if(ke(i,e),i.dtype==="string"||n==="string")throw new Error("unaryKernelFunc does not support string input/output");let o=s,l=o.data.get(i.dataId).values,u=v.sizeFromShape(i.shape),c=n||i.dtype,h=v.getArrayFromDType(c,u);for(let d=0;d<u;++d)h[d]=t(l[d],a);return o.makeTensorInfo(i.shape,c,h)}}function El(e,t,n){return({inputs:r,attrs:a,backend:s})=>{let{x:i}=r;if(ke(i,e),i.dtype==="string"||n==="string")throw new Error("unaryKernelFunc does not support string input/output");let o=s,l=o.data.get(i.dataId).values,u=n||i.dtype,c=t(l,u,a);return o.makeTensorInfo(i.shape,u,c)}}var rw=Tl(e=>Math.ceil(e)),JR=El(xs,rw),QR={kernelName:xs,backendName:"cpu",kernelFunc:JR};function Um(e,t,n,r){let a=v.getArrayFromDType(n,v.sizeFromShape(t));if(r&&n!=="string"){let s=0;e.forEach(i=>{let o=v.sizeFromShape(i.shape);a.set(i.vals,s),s+=o})}else{let s=0;e.forEach(i=>{let o=n==="string"?R.fromUint8ToStringArray(i.vals):i.vals,l=0;for(let u=0;u<i.shape[0];++u){let c=u*t[1]+s;for(let h=0;h<i.shape[1];++h)a[c+h]=o[l++]}s+=i.shape[1]})}return a}var aw=Tl(e=>Math.exp(e)),Iw=El(Ns,aw),eF={kernelName:Ns,backendName:"cpu",kernelFunc:Iw},sw=Tl(e=>Math.expm1(e)),tF=El(_o,sw),nF={kernelName:_o,backendName:"cpu",kernelFunc:tF},iw=Tl(e=>Math.floor(e)),rF=El(Ss,iw),aF={kernelName:Ss,backendName:"cpu",kernelFunc:rF};function ow(e,t,n){let r=Ue(n,e.dtype);for(let a=0;a<r.size;++a){let s=r.indexToLoc(a).slice(),i=s[0],o=s[2],l=t.locToIndex([i,o]);s[2]=t.values[l];let u=e.locToIndex(s);r.values[a]=e.values[u]}return r}var lw=Dt((e,t)=>e>t?1:0),sF=Yt(No,lw,null,"bool"),iF={kernelName:No,backendName:"cpu",kernelFunc:sF},uw=Dt((e,t)=>e<t?1:0),oF=Yt(Co,uw,null,"bool"),lF={kernelName:Co,backendName:"cpu",kernelFunc:oF};function cw(e,t,n){let r=(t-e)/(n-1),a=v.makeZerosTypedArray(n,"float32");a[0]=e;for(let s=1;s<a.length;s++)a[s]=a[s-1]+r;return a}var hw=Tl(e=>Math.log(e)),uF=El(Ms,hw),cF={kernelName:Ms,backendName:"cpu",kernelFunc:uF};function dw(e,t,n,r){let a=v.getTypedArrayFromDType(r,v.sizeFromShape(n));for(let s=0;s<a.length;++s){let i=s*t,o=e[i];for(let l=0;l<t;++l){let u=e[i+l];u>o&&(o=u)}a[s]=o}return a}var pw=Dt((e,t)=>Math.max(e,t)),hF=Yt(Ds,pw),dF={kernelName:Ds,backendName:"cpu",kernelFunc:hF},fw=Dt((e,t)=>Math.min(e,t)),pF=Yt(Ls,fw),fF={kernelName:Ls,backendName:"cpu",kernelFunc:pF},Hm=Dt((e,t)=>e*t),mF=qm((e,t,n,r)=>({real:e*n-t*r,imag:e*r+t*n})),Xm=Yt(Ws,Hm,mF),AF={kernelName:Ws,backendName:"cpu",kernelFunc:Xm};function mw(e,t,n){let r=v.createScalarValue(-1,n);return Hm([],t,r,e,n)}function yF(e){let{inputs:t,backend:n}=e,{x:r}=t;ke(r,"neg");let a=n.data.get(r.dataId).values,[s,i]=mw(a,r.shape,r.dtype);return n.makeTensorInfo(i,r.dtype,s)}var gF={kernelName:Do,backendName:"cpu",kernelFunc:yF},Aw=Dt((e,t)=>e!==t?1:0),xF=Yt(Oo,Aw,null,"bool"),wF={kernelName:Oo,backendName:"cpu",kernelFunc:xF};function jm(e,t,n,r,a){let s=t.length,i=v.sizeFromShape(t),o=v.computeStrides(t),l=v.computeStrides(a),u=v.getTypedArrayFromDType(n,v.sizeFromShape(a));for(let c=0;c<i;++c){let h=v.indexToLoc(c,s,o),d=new Array(h.length);for(let f=0;f<d.length;f++)d[f]=h[r[f]];let p=v.locToIndex(d,s,l);u[p]=e[c]}return u}function dr(e){let{inputs:t,attrs:n,backend:r}=e,{x:a}=t,{perm:s}=n;ke(a,"transpose");let i=a.shape.length,o=new Array(i);for(let c=0;c<o.length;c++)o[c]=a.shape[s[c]];let l=r.data.get(a.dataId).values,u=jm(l,a.shape,a.dtype,s,o);return{dataId:r.write(u,o,a.dtype),shape:o,dtype:a.dtype}}var bF={kernelName:si,backendName:"cpu",kernelFunc:dr};function yw(e,t,n,r){let[a,s]=R.computeOutAndReduceShapes(e,r),i=lr(t,"int32"),o=v.makeZerosTypedArray(v.sizeFromShape(a),i),l=v.sizeFromShape(s);for(let u=0;u<o.length;++u){let c=u*l,h=1;for(let d=0;d<l;++d)h*=n[c+d];o[u]=h}return{outVals:o,outShape:a,outDtype:i}}function _F(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r;ke(a,"prod");let o=a.shape.length,l=v.parseAxisParam(s,a.shape),u=R.getAxesPermutation(l,o),c=l,h=a,d=[];u!=null&&(h=dr({inputs:{x:a},backend:n,attrs:{perm:u}}),d.push(h),c=R.getInnerMostAxes(c.length,o));let p=n.data.get(h.dataId).values,{outVals:f,outShape:m,outDtype:A}=yw(h.shape,h.dtype,p,c),y=m;return i&&(y=R.expandShapeToKeepDim(m,l)),d.forEach(g=>n.disposeIntermediateTensorInfo(g)),n.makeTensorInfo(y,A,f)}var vF={kernelName:Vo,backendName:"cpu",kernelFunc:_F};function Gm(e,t,n,r){let a=e===t,s=e<t&&n<0,i=t<e&&n>1;if(a||s||i)return v.makeZerosTypedArray(0,r);let o=Math.abs(Math.ceil((t-e)/n)),l=v.makeZerosTypedArray(o,r);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 gw=Tl(e=>1/Math.sqrt(e)),kF=El(Zs,gw),IF={kernelName:Zs,backendName:"cpu",kernelFunc:kF};function up(e,t,n,r,a){let s=fn.isSliceContinous(r,t,n),i=v.sizeFromShape(n),o=v.computeStrides(r);if(s){let h=fn.computeFlatOffset(t,o);return a==="string"?e.slice(h,h+i):e.subarray(h,h+i)}let l=a==="string"?R.fromUint8ToStringArray(e):e,u=Ue(r,a,l),c=Ue(n,a);for(let h=0;h<c.size;++h){let d=c.indexToLoc(h),p=d.map((f,m)=>f+t[m]);c.set(u.get(...p),...d)}return a==="string"?R.fromStringArrayToUint8(c.values):c.values}function vi(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{begin:s,size:i}=r;ke(a,"slice");let[o,l]=fn.parseSliceParams(a,s,i);fn.assertParamsValid(a,o,l);let u=n.data.get(a.dataId).values,c=up(u,o,l,a.shape,a.dtype);return n.makeTensorInfo(l,a.dtype,c)}var NF={kernelName:Xo,backendName:"cpu",kernelFunc:vi},xw=Dt((e,t)=>{let n=e-t;return n*n}),SF=Yt(ni,xw),TF={kernelName:ni,backendName:"cpu",kernelFunc:SF};function ww(e,t,n,r){let a=Ue(e,t.dtype);for(let s=0;s<a.size;s++){let i=a.indexToLoc(s),o=new Array(i.length);for(let l=0;l<o.length;l++)o[l]=i[l]*n[l]+r[l];a.set(t.get(...o),...i)}return a}var bw=Dt((e,t)=>e-t),EF=qm((e,t,n,r)=>({real:e-n,imag:t-r})),Km=Yt(ri,bw,EF),CF={kernelName:ri,backendName:"cpu",kernelFunc:Km};function _w(e,t){let n=new Array(e.rank);for(let a=0;a<n.length;a++)n[a]=e.shape[a]*t[a];let r=Ue(n,e.dtype);for(let a=0;a<r.values.length;++a){let s=r.indexToLoc(a),i=new Array(e.rank);for(let l=0;l<i.length;l++)i[l]=s[l]%e.shape[l];let o=e.locToIndex(i);r.values[a]=e.values[o]}return r}function vw(e,t,n,r,a){let s=t[t.length-1],[i,o]=[e.length/s,s],l=v.getTypedArrayFromDType(n,i*r),u=v.getTypedArrayFromDType("int32",i*r);for(let h=0;h<i;h++){let d=h*o,p=e.subarray(d,d+o),f=[];for(let g=0;g<p.length;g++)f.push({value:p[g],index:g});f.sort((g,b)=>b.value-g.value);let m=h*r,A=l.subarray(m,m+r),y=u.subarray(m,m+r);for(let g=0;g<r;g++)A[g]=f[g].value,y[g]=f[g].index}let c=t.slice();return c[c.length-1]=r,[Ue(c,n,l),Ue(c,"int32",u)]}function kw(e,t,n,r){let a=v.parseAxisParam(t,n)[0],s=[1,n[0],1];for(let f=0;f<a;f++)s[0]*=n[f];s[1]=n[a];for(let f=a+1;f<n.length;f++)s[2]*=n[f];let i={},o=new Int32Array(n[a]),l=new Wt(s,r,e),u=[],c=s[0]===1&&s[2]===1;for(let f=0;f<n[a];f++){let m;if(c)m=e[f].toString();else{let A=[];for(let y=0;y<s[0];y++)for(let g=0;g<s[2];g++)A.push(l.get(y,f,g));m=A.join(",")}if(i[m]!==void 0)o[f]=i[m];else{let A=Object.keys(i).length;i[m]=A,o[f]=A,u.push(f)}}let h=s.slice();h[1]=Object.keys(i).length;let d=new Wt(h,r);u.forEach((f,m)=>{for(let A=0;A<s[0];A++)for(let y=0;y<s[2];y++)d.set(l.get(A,f,y),A,m,y)});let p=n.slice();return p[a]=h[1],{outputValues:d.values,outputShape:p,indices:o}}var Nw="3.3.0";fl("cpu",()=>new lp,1);var Sw=ut(go,e=>e>=0?e:Math.exp(e)-1),RF={kernelName:go,backendName:"cpu",kernelFunc:Sw};function Tw(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{alpha:s}=r;ke([a],"leakyRelu");let i=v.sizeFromShape(a.shape),o=n.data.get(a.dataId).values,l=v.getTypedArrayFromDType("float32",i);for(let u=0;u<o.length;u++)l[u]=o[u]<0?s*o[u]:o[u];return n.makeTensorInfo(a.shape,"float32",l)}var FF={kernelName:Fs,backendName:"cpu",kernelFunc:Tw},MF=Dt((e,t)=>e<0?t*e:e);function Ew(e){let{inputs:t,backend:n}=e,{x:r,alpha:a}=t;ke([r,a],"prelu");let s=n.data.get(r.dataId).values,i=n.data.get(a.dataId).values,[o,l]=MF(r.shape,a.shape,s,i,r.dtype);return n.makeTensorInfo(l,r.dtype,o)}var $F={kernelName:Hs,backendName:"cpu",kernelFunc:Ew},Cw=ut(js,e=>Math.max(0,e)),DF={kernelName:js,backendName:"cpu",kernelFunc:Cw},Rw=ut(qs,e=>Math.min(Math.max(0,e),6)),OF={kernelName:qs,backendName:"cpu",kernelFunc:Rw};function Zm(e,t,n,r,a){if(n==="linear")return jr({inputs:{x:t},backend:e});if(n==="relu")return Cw({inputs:{x:t},backend:e});if(n==="elu")return Sw({inputs:{x:t},backend:e});if(n==="relu6")return Rw({inputs:{x:t},backend:e});if(n==="prelu")return Ew({inputs:{x:t,alpha:r},backend:e});if(n==="leakyrelu")return Tw({inputs:{x:t},backend:e,attrs:{alpha:a}});throw new Error(`Activation ${n} has not been implemented for the CPU backend.`)}function bt(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{shape:s}=r,i=v.sizeFromShape(a.shape),o=v.inferFromImplicitShape(s,i),l=v.sizeFromShape(o);v.assert(i===l,()=>`The new shape (${o}) has ${l} elements and the old shape (${a.shape}) has ${i} elements. The new shape and old shape must have the same number of elements.`),n.incRef(a.dataId);let u=n.data.get(a.dataId);if(u.complexTensorInfos!=null){let c=u.complexTensorInfos.real,h=u.complexTensorInfos.imag;c.shape=o,h.shape=o}return{dataId:a.dataId,shape:o,dtype:a.dtype}}var zF={kernelName:Ho,backendName:"cpu",kernelFunc:bt};function Fw(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s}=t,{transposeA:i,transposeB:o}=r;ke([a,s],"matMul");let l=a.shape.length,u=s.shape.length,c=i?a.shape[l-2]:a.shape[l-1],h=o?s.shape[u-1]:s.shape[u-2],d=i?a.shape[l-1]:a.shape[l-2],p=o?s.shape[u-2]:s.shape[u-1],f=a.shape.slice(0,-2),m=s.shape.slice(0,-2),A=v.sizeFromShape(f),y=v.sizeFromShape(m),g=A===y||A===1||y===1;v.assert(l>=2&&u>=2&&g,()=>`Error in matMul: the input batch dimensions must either be the same or at least one input batch dimension must be 1. Got input batch dimensions of (${f}) and (${m}).`);let b=(A>y?a.shape.slice(0,-2):s.shape.slice(0,-2)).concat([d,p]);v.assert(c===h,()=>`Error in matMul: inner shapes (${c}) and (${h}) of Tensors with shapes ${a.shape} and ${s.shape} and transposeA=${i} and transposeB=${o} must match.`);let _=i?[A,c,d]:[A,d,c],w=o?[y,p,h]:[y,h,p],x=bt({inputs:{x:a},backend:n,attrs:{shape:_}}),N=bt({inputs:{x:s},backend:n,attrs:{shape:w}}),S=i?x.shape[1]:x.shape[2],T=i?x.shape[2]:x.shape[1],M=o?N.shape[1]:N.shape[2],D=Math.max(A,y),z=n.data.get(x.dataId).values,W=n.data.get(N.dataId).values,U=v.computeStrides(x.shape),H=v.computeStrides(N.shape),[X,j,ee]=i?[U[0],1,U[1]]:[U[0],U[1],1],[Y,se,te]=o?[1,H[1],H[0]]:[H[1],1,H[0]],oe=T*M,Q=Ue([D,T,M],x.dtype),pe=Q.values,le=n.blockSize;for(let Ae=0;Ae<D;Ae++)for(let me=0;me<T;me+=le)for(let Se=0;Se<M;Se+=le)for(let Ee=0;Ee<S;Ee+=le){let Oe=Math.min(me+le,T),Le=Math.min(Se+le,M),ze=Math.min(Ee+le,S);for(let at=me;at<Oe;at++)for(let st=Se;st<Le;st++){let ct=0;for(let Qe=Ee;Qe<ze;Qe++){let At=Math.min(Ae,A-1)*X,He=Math.min(Ae,y-1)*te,bn=z[At+at*j+Qe*ee],It=W[Qe*Y+st*se+He];ct+=bn*It}pe[Ae*oe+(at*M+st)]+=ct}}return n.disposeIntermediateTensorInfo(x),n.disposeIntermediateTensorInfo(N),n.makeTensorInfo(b,Q.dtype,Q.values)}var PF={kernelName:ys,backendName:"cpu",kernelFunc:Fw};function LF(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:h}=r,d,p,f,m=[];d=Fw({inputs:{a,b:s},attrs:{transposeA:l,transposeB:u},backend:n}),i&&(p=cc({inputs:{a:d,b:i},backend:n}),m.push(d),d=p),c&&(f=Zm(n,d,c,o,h),m.push(d),d=f);for(let A of m)n.disposeIntermediateTensorInfo(A);return d}var WF={kernelName:ii,backendName:"cpu",kernelFunc:LF},BF=ut(io,e=>Math.acos(e)),VF={kernelName:io,backendName:"cpu",kernelFunc:BF},UF=ut(oo,e=>Math.acosh(e)),HF={kernelName:oo,backendName:"cpu",kernelFunc:UF};function jF(e){let{inputs:t,backend:n}=e,r=t;ke(t,"addN");let a=r.map(o=>n.data.get(o.dataId).values),s=Ue(r[0].shape,r[0].dtype),i=s.values;for(let o=0;o<r.length;o++){let l=a[o];for(let u=0;u<i.length;u++)i[u]+=l[u]}return n.makeTensorInfo(s.shape,s.dtype,s.values)}var GF={kernelName:fs,backendName:"cpu",kernelFunc:jF};function qF(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r;ke(a,"all");let o=v.parseAxisParam(s,a.shape),l=o,u=R.getAxesPermutation(l,a.shape.length),c=a;u!=null&&(c=dr({inputs:{x:a},backend:n,attrs:{perm:u}}),l=R.getInnerMostAxes(l.length,a.shape.length)),R.assertAxesAreInnerMostDims("all",l,c.shape.length);let[h,d]=R.computeOutAndReduceShapes(c.shape,l),p=v.sizeFromShape(d),f=v.makeZerosTypedArray(v.sizeFromShape(h),c.dtype),m=n.data.get(c.dataId).values;for(let y=0;y<f.length;++y){let g=y*p,b=m[g];for(let _=0;_<p;++_){let w=m[g+_];b=b&&w}f[y]=b}u!=null&&n.disposeIntermediateTensorInfo(c);let A=n.makeTensorInfo(h,c.dtype,f);if(i){let y=R.expandShapeToKeepDim(h,o),g=bt({inputs:{x:A},backend:n,attrs:{shape:y}});return n.disposeIntermediateTensorInfo(A),g}return A}var XF={kernelName:Dh,backendName:"cpu",kernelFunc:qF};function KF(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r;ke(a,"any");let o=v.parseAxisParam(s,a.shape),l=o,u=R.getAxesPermutation(l,a.shape.length),c=a;u!=null&&(c=dr({inputs:{x:a},backend:n,attrs:{perm:u}}),l=R.getInnerMostAxes(l.length,a.shape.length)),R.assertAxesAreInnerMostDims("any",l,c.shape.length);let[h,d]=R.computeOutAndReduceShapes(c.shape,l),p=v.sizeFromShape(d),f=v.makeZerosTypedArray(v.sizeFromShape(h),c.dtype),m=n.data.get(c.dataId).values;for(let y=0;y<f.length;++y){let g=y*p,b=m[g];for(let _=0;_<p;++_){let w=m[g+_];b=b||w}f[y]=b}u!=null&&n.disposeIntermediateTensorInfo(c);let A=n.makeTensorInfo(h,c.dtype,f);if(i){let y=R.expandShapeToKeepDim(h,o),g=bt({inputs:{x:A},backend:n,attrs:{shape:y}});return n.disposeIntermediateTensorInfo(A),g}return A}var ZF={kernelName:Oh,backendName:"cpu",kernelFunc:KF};function YF(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r;ke(a,"argMax");let i=v.parseAxisParam(s,a.shape),o=R.getAxesPermutation(i,a.shape.length),l=a,u=[];o!=null&&(l=dr({inputs:{x:a},backend:n,attrs:{perm:o}}),u.push(l),i=R.getInnerMostAxes(i.length,l.shape.length)),i=[i[0]],R.assertAxesAreInnerMostDims("argMax",i,l.shape.length);let[c,h]=R.computeOutAndReduceShapes(l.shape,i),d=v.sizeFromShape(c),p=v.makeZerosTypedArray(d,"int32"),f=v.sizeFromShape(h),m=n.data.get(l.dataId).values;for(let A=0;A<p.length;++A){let y=A*f,g=m[y],b=0;for(let _=0;_<f;++_){let w=m[y+_];w>g&&(g=w,b=_)}p[A]=b}return u.forEach(A=>n.disposeIntermediateTensorInfo(A)),n.makeTensorInfo(c,"int32",p)}var JF={kernelName:ms,backendName:"cpu",kernelFunc:YF};function QF(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r;ke(a,"argMin");let i=v.parseAxisParam(s,a.shape),o=R.getAxesPermutation(i,a.shape.length),l=a,u=[];o!=null&&(l=dr({inputs:{x:a},backend:n,attrs:{perm:o}}),u.push(l),i=R.getInnerMostAxes(i.length,l.shape.length)),i=[i[0]],R.assertAxesAreInnerMostDims("argMin",i,l.shape.length);let[c,h]=R.computeOutAndReduceShapes(l.shape,i),d=v.sizeFromShape(c),p=v.makeZerosTypedArray(d,"int32"),f=v.sizeFromShape(h),m=n.data.get(l.dataId).values;for(let A=0;A<p.length;++A){let y=A*f,g=m[y],b=0;for(let _=0;_<f;++_){let w=m[y+_];w<g&&(g=w,b=_)}p[A]=b}return u.forEach(A=>n.disposeIntermediateTensorInfo(A)),n.makeTensorInfo(c,"int32",p)}var eM={kernelName:yu,backendName:"cpu",kernelFunc:QF},tM=ut(lo,e=>Math.asin(e)),nM={kernelName:lo,backendName:"cpu",kernelFunc:tM},rM=ut(uo,e=>Math.asinh(e)),aM={kernelName:uo,backendName:"cpu",kernelFunc:rM},sM=ut(co,e=>Math.atan(e)),iM={kernelName:co,backendName:"cpu",kernelFunc:sM},oM=Dt((e,t)=>Math.atan2(e,t)),lM=Yt(po,oM),uM={kernelName:po,backendName:"cpu",kernelFunc:lM},cM=ut(ho,e=>Math.atanh(e)),hM={kernelName:ho,backendName:"cpu",kernelFunc:cM};function Ym(e,t,n,r,a,s){let i=a.strideHeight,o=a.strideWidth,l=a.dilationHeight,u=a.dilationWidth,c=a.effectiveFilterHeight,h=a.effectiveFilterWidth,d=a.padInfo.top,p=a.padInfo.left,f=s==="max"?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,m=Ue(a.outShape,n),A=m.values,y=a.outShape[1]*a.outShape[2]*a.outShape[3],g=a.outShape[2]*a.outShape[3],b=a.outShape[3];for(let _=0;_<a.batchSize;++_){let w=_*y,x=_*r[0];for(let N=0;N<a.inChannels;++N)for(let S=0;S<a.outHeight;++S){let T=S*i-d,M=Math.max(0,T),D=Math.min(a.inHeight,c+T),z=w+S*g;for(let W=0;W<a.outWidth;++W){let U=W*o-p,H=Math.max(0,U),X=Math.min(a.inWidth,h+U),j=f,ee=0,Y=0;for(let te=M;te<D;te+=l){let oe=x+te*r[1];for(let Q=H;Q<X;Q+=u){let pe=oe+Q*r[2],le=e[pe+N];s==="max"&&le>j?j=le:s==="avg"&&(ee+=le,Y++)}if(isNaN(j))break}let se=z+W*b+N;A[se]=s==="avg"?ee/Y:j}}}return m}function Mw(e,t,n,r,a=!1,s=!1){let i=Ue(r.outShape,"int32"),o=r.strideHeight,l=r.strideWidth,u=r.dilationHeight,c=r.dilationWidth,h=r.effectiveFilterHeight,d=r.effectiveFilterWidth,p=r.padInfo.top,f=r.padInfo.left,m=Ue(t,n,e);for(let A=0;A<r.batchSize;++A)for(let y=0;y<r.inChannels;++y)for(let g=0;g<r.outHeight;++g){let b=g*o-p,_=b;for(;_<0;)_+=u;let w=Math.min(r.inHeight,h+b);for(let x=0;x<r.outWidth;++x){let N=x*l-f,S=N;for(;S<0;)S+=c;let T=Math.min(r.inWidth,d+N),M=Number.NEGATIVE_INFINITY,D=-1;for(let z=_;z<w;z+=u){let W=z-b;for(let U=S;U<T;U+=c){let H=U-N,X=m.get(A,z,U,y);X>M&&(M=X,a?D=s?((A*r.inHeight+z)*r.inWidth+U)*r.inChannels+y:(z*r.inWidth+U)*r.inChannels+y:D=W*d+H)}}i.set(D,A,g,x,y)}}return i}function $w(e,t,n,r,a,s){let i=a.strideDepth,o=a.strideHeight,l=a.strideWidth,u=a.dilationDepth,c=a.dilationHeight,h=a.dilationWidth,d=a.effectiveFilterDepth,p=a.effectiveFilterHeight,f=a.effectiveFilterWidth,m=a.padInfo.front,A=a.padInfo.top,y=a.padInfo.left,g=s==="max"?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,b=Ue(a.outShape,n),_=b.values,w=a.outShape[1]*a.outShape[2]*a.outShape[3]*a.outShape[4],x=a.outShape[2]*a.outShape[3]*a.outShape[4],N=a.outShape[3]*a.outShape[4],S=a.outShape[4];for(let T=0;T<a.batchSize;++T){let M=T*w,D=T*r[0];for(let z=0;z<a.inChannels;++z)for(let W=0;W<a.outDepth;++W){let U=W*i-m,H=U;for(;H<0;)H+=u;let X=Math.min(a.inDepth,d+U),j=M+W*x;for(let ee=0;ee<a.outHeight;++ee){let Y=ee*o-A,se=Y;for(;se<0;)se+=c;let te=Math.min(a.inHeight,p+Y),oe=j+ee*N;for(let Q=0;Q<a.outWidth;++Q){let pe=Q*l-y,le=pe;for(;le<0;)le+=h;let Ae=Math.min(a.inWidth,f+pe),me=oe+Q*S,Se=g,Ee=0,Oe=0;for(let ze=H;ze<X;ze+=u){let at=D+ze*r[1];for(let st=se;st<te;st+=c){let ct=at+st*r[2];for(let Qe=le;Qe<Ae;Qe+=h){let At=ct+Qe*r[3],He=e[At+z];if(s==="max"&&He>Se?Se=He:s==="avg"&&(Ee+=He,Oe++),isNaN(Se))break}if(isNaN(Se))break}if(isNaN(Se))break}let Le=me+z;_[Le]=s==="avg"?Ee/Oe:Se}}}}return b}function dM(e,t){let n=Ue(t.outShape,"int32"),r=t.strideDepth,a=t.strideHeight,s=t.strideWidth,i=t.dilationDepth,o=t.dilationHeight,l=t.dilationWidth,u=t.effectiveFilterDepth,c=t.effectiveFilterHeight,h=t.effectiveFilterWidth,d=t.padInfo.front,p=t.padInfo.top,f=t.padInfo.left;for(let m=0;m<t.batchSize;++m)for(let A=0;A<t.inChannels;++A)for(let y=0;y<t.outDepth;++y){let g=y*r-d,b=g;for(;b<0;)b+=i;let _=Math.min(t.inDepth,u+g);for(let w=0;w<t.outHeight;++w){let x=w*a-p,N=x;for(;N<0;)N+=o;let S=Math.min(t.inHeight,c+x);for(let T=0;T<t.outWidth;++T){let M=T*s-f,D=M;for(;D<0;)D+=l;let z=Math.min(t.inWidth,h+M),W=Number.NEGATIVE_INFINITY,U=-1;for(let H=b;H<_;H+=i){let X=H-g;for(let j=N;j<S;j+=o){let ee=j-x;for(let Y=D;Y<z;Y+=l){let se=Y-M,te=e.get(m,H,j,Y,A);te>=W&&(W=te,U=X*c*h+ee*c+se)}}}n.set(U,m,y,w,T,A)}}}return n}function pM(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t;ke(a,"avgPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=r,u=1;v.assert(R.eitherStridesOrDilationsAreOne(i,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let c=R.computePool2DInfo(a.shape,s,i,u,o,l),h;if(c.filterWidth===1&&c.filterHeight===1&&v.arraysEqual(c.inShape,c.outShape))h=jr({inputs:{x:a},backend:n});else{let d=n.data.get(a.dataId).values,p=v.computeStrides(a.shape),f=Ym(d,a.shape,a.dtype,p,c,"avg");h=n.makeTensorInfo(c.outShape,a.dtype,f.values)}return h}var fM={kernelName:As,backendName:"cpu",kernelFunc:pM};function mM(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:u}=r;ke(a,"avgPool3d");let c=R.computePool3DInfo(a.shape,s,i,1,o,l,u),h=n.data.get(a.dataId).values,d=$w(h,a.shape,a.dtype,v.computeStrides(a.shape),c,"avg");return n.makeTensorInfo(d.shape,"float32",d.values)}var AM={kernelName:gu,backendName:"cpu",kernelFunc:mM};function yM(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=r;ke([a,s],"avgPool3DGrad");let c=R.computePool3DInfo(s.shape,i,o,1,l,u),h=c.strideDepth,d=c.strideHeight,p=c.strideWidth,f=c.filterDepth,m=c.filterHeight,A=c.filterWidth,y=c.dilationDepth,g=c.dilationHeight,b=c.dilationWidth,_=c.effectiveFilterDepth,w=c.effectiveFilterHeight,x=c.effectiveFilterWidth,N=_-1-c.padInfo.front,S=x-1-c.padInfo.left,T=w-1-c.padInfo.top,M=Ue(s.shape,"float32"),D=1/(f*m*A),z=n.bufferSync(a);for(let W=0;W<c.batchSize;++W)for(let U=0;U<c.inChannels;++U)for(let H=0;H<c.inDepth;++H)for(let X=0;X<c.inHeight;++X)for(let j=0;j<c.inWidth;++j){let ee=H-N,Y=X-T,se=j-S,te=0;for(let oe=0;oe<_;oe+=y){let Q=(ee+oe)/h;if(!(Q<0||Q>=c.outDepth||Math.floor(Q)!==Q))for(let pe=0;pe<w;pe+=g){let le=(Y+pe)/d;if(!(le<0||le>=c.outHeight||Math.floor(le)!==le))for(let Ae=0;Ae<x;Ae+=b){let me=(se+Ae)/p;me<0||me>=c.outWidth||Math.floor(me)!==me||(te+=z.get(W,Q,le,me,U))}}}M.set(te*D,W,H,X,j,U)}return n.makeTensorInfo(M.shape,M.dtype,M.values)}var gM={kernelName:Ph,backendName:"cpu",kernelFunc:yM};function xM(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s;ke([a,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:u}=r,c=R.computePool2DInfo(i.shape,o,l,1,u),h=c.strideHeight,d=c.strideWidth,p=c.filterHeight,f=c.filterWidth,m=c.dilationHeight,A=c.dilationWidth,y=c.effectiveFilterHeight,g=c.effectiveFilterWidth,b=g-1-c.padInfo.left,_=y-1-c.padInfo.top,w=Ue(i.shape,"float32"),x=1/(p*f),N=n.data.get(a.dataId).values,S=Ue(a.shape,"float32",N);for(let T=0;T<c.batchSize;++T)for(let M=0;M<c.inChannels;++M)for(let D=0;D<c.inHeight;++D)for(let z=0;z<c.inWidth;++z){let W=D-_,U=z-b,H=0;for(let X=0;X<y;X+=m){let j=(W+X)/h;if(!(j<0||j>=c.outHeight||Math.floor(j)!==j))for(let ee=0;ee<g;ee+=A){let Y=(U+ee)/d;Y<0||Y>=c.outWidth||Math.floor(Y)!==Y||(H+=S.get(T,j,Y,M))}}w.set(H*x,T,D,z,M)}return n.makeTensorInfo(w.shape,w.dtype,w.values)}var wM={kernelName:zh,backendName:"cpu",kernelFunc:xM};function bM(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,scale:s,offset:i,mean:o,variance:l}=t;v.assert(o.shape.length===l.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),v.assert(i==null||o.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),v.assert(s==null||o.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks."),ke([a,o,l,s,i],"batchNorm");let{varianceEpsilon:u}=r;u==null&&(u=.001);let c=n.data.get(a.dataId).values,h=n.data.get(o.dataId).values,d=n.data.get(l.dataId).values,p=s?n.data.get(s.dataId).values:new Float32Array([1]),f=i?n.data.get(i.dataId).values:new Float32Array([0]),m=new Float32Array(c.length),A=f.length,y=p.length,g=d.length,b=h.length,_=0,w=0,x=0,N=0;for(let S=0;S<c.length;++S)m[S]=f[_++]+(c[S]-h[w++])*p[x++]/Math.sqrt(d[N++]+u),_>=A&&(_=0),w>=b&&(w=0),x>=y&&(x=0),N>=g&&(N=0);return n.makeTensorInfo(a.shape,a.dtype,m)}var _M={kernelName:Es,backendName:"cpu",kernelFunc:bM};function vM(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,crops:i}=r;ke([a],"batchToSpaceND");let o=s.reduce((y,g)=>y*g),l=R.getReshaped(a.shape,s,o),u=R.getPermuted(l.length,s.length),c=R.getReshapedPermuted(a.shape,s,o),h=R.getSliceBeginCoords(i,s.length),d=R.getSliceSize(c,i,s.length),p=bt({inputs:{x:a},backend:n,attrs:{shape:l}}),f=dr({inputs:{x:p},backend:n,attrs:{perm:u}}),m=bt({inputs:{x:f},backend:n,attrs:{shape:c}}),A=vi({inputs:{x:m},backend:n,attrs:{begin:h,size:d}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(m),A}var kM={kernelName:xu,backendName:"cpu",kernelFunc:vM};function IM(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i}=r,o=n.data.get(a.dataId).values,l=n.data.get(s.dataId).values,u=Vm(o,l,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,u)}var NM={kernelName:Lh,backendName:"cpu",kernelFunc:IM},SM=ut(Fa,(e,t)=>{let n=t;return e>n.clipValueMax?n.clipValueMax:e<n.clipValueMin?n.clipValueMin:e}),TM={kernelName:Fa,backendName:"cpu",kernelFunc:SM},EM=e=>{let{x:t}=e.inputs,n=e.backend,r=new Float32Array(v.sizeFromShape(t.shape)),a=n.data.get(t.dataId),s=a.complexTensorInfos.real,i=a.complexTensorInfos.imag,o=n.data.get(s.dataId).values,l=n.data.get(i.dataId).values;for(let u=0;u<o.length;u++){let c=o[u],h=l[u];r[u]=Math.hypot(c,h)}return n.makeOutput(r,t.shape,"float32")},CM={kernelName:wu,backendName:"cpu",kernelFunc:EM};function Cl(e){let{inputs:t,backend:n}=e,{input:r}=t,a=n.data.get(r.dataId).complexTensorInfos.imag,s=n.data.get(a.dataId).values;return n.makeTensorInfo(a.shape,a.dtype,s)}var RM={kernelName:Qh,backendName:"cpu",kernelFunc:Cl};function Rl(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r,s=v.parseAxisParam(a,t[0].shape)[0],i=R.computeOutShape(t.map(m=>m.shape),s);if(v.sizeFromShape(i)===0)return n.makeTensorInfo(i,t[0].dtype,[]);let o=t.filter(m=>v.sizeFromShape(m.shape)>0);if(o.length===1)return jr({inputs:{x:o[0]},backend:n});let l=o.map(m=>m.shape);if(R.assertParamsConsistent(l,s),o[0].dtype==="complex64"){let m=o.map(_=>_i({inputs:{input:_},backend:n})),A=o.map(_=>Cl({inputs:{input:_},backend:n})),y=Rl({inputs:m,backend:n,attrs:{axis:s}}),g=Rl({inputs:A,backend:n,attrs:{axis:s}}),b=Wn({inputs:{real:y,imag:g},backend:n});return m.forEach(_=>n.disposeIntermediateTensorInfo(_)),A.forEach(_=>n.disposeIntermediateTensorInfo(_)),n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(g),b}let u=o.map(m=>{let A=v.sizeFromShape(m.shape.slice(s));return bt({inputs:{x:m},backend:n,attrs:{shape:[-1,A]}})}),c=u.map(m=>({vals:n.data.get(m.dataId).values,shape:m.shape}));i=R.computeOutShape(u.map(m=>m.shape),1);let h=u[0].shape[0]===1,d=Um(c,i,t[0].dtype,h),p=R.computeOutShape(o.map(m=>m.shape),s),f=n.makeTensorInfo(p,t[0].dtype,d);return u.forEach(m=>n.disposeIntermediateTensorInfo(m)),f}var FM={kernelName:fo,backendName:"cpu",kernelFunc:Rl};function Dw(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:u,dimRoundingMode:c}=r;ke([a,s],"conv2d");let h=R.convertConv2DDataFormat(l),d=R.computeConv2DInfo(a.shape,s.shape,i,u,o,c,!1,h),p=d.filterHeight,f=d.filterWidth,m=d.dilationHeight,A=d.dilationWidth,y=d.padInfo.left,g=d.padInfo.top,b=d.dataFormat==="channelsLast",_=new Wt(d.outShape,a.dtype),w=v.computeStrides(a.shape),x=v.computeStrides(s.shape),N=w[0],S=b?w[1]:w[2],T=b?w[2]:1,M=b?1:w[1],D=_.strides[0],z=b?_.strides[1]:_.strides[2],W=b?_.strides[2]:1,U=b?1:_.strides[1],H=n.data.get(a.dataId).values,X=n.data.get(s.dataId).values,j=_.values;for(let ee=0;ee<d.batchSize;++ee){let Y=ee*N,se=ee*D;for(let te=0;te<d.outHeight;++te){let oe=se+te*z,Q=te*d.strideHeight-g;for(let pe=0;pe<p;++pe){let le=Q+pe*m;if(le<0||le>=d.inHeight)continue;let Ae=pe*x[0],me=Y+le*S;for(let Se=0;Se<d.outWidth;++Se){let Ee=oe+Se*W,Oe=Se*d.strideWidth-y;for(let Le=0;Le<f;++Le){let ze=Oe+Le*A;if(ze<0||ze>=d.inWidth)continue;let at=Ae+Le*x[1],st=me+ze*T,ct=at;for(let Qe=0;Qe<d.inChannels;++Qe){let At=H[st+Qe*M];for(let He=0;He<d.outChannels;++He)j[Ee+He*U]+=At*X[ct+He];ct+=d.outChannels}}}}}}return n.makeTensorInfo(_.shape,_.dtype,j)}var MM={kernelName:ws,backendName:"cpu",kernelFunc:Dw};function $M(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:u,filterShape:c}=r;ke([a,s],"conv2dBackpropFilter");let h=R.convertConv2DDataFormat(l),d=R.computeConv2DInfo(a.shape,c,i,1,o,u,!1,h),{strideHeight:p,strideWidth:f,filterHeight:m,filterWidth:A}=d,y=d.dataFormat==="channelsLast",g=new Wt(d.filterShape,"float32"),b=d.padInfo.left,_=d.padInfo.top,w=n.data.get(a.dataId).values,x=n.data.get(s.dataId).values,N=new Wt(a.shape,a.dtype,w),S=new Wt(s.shape,s.dtype,x);for(let T=0;T<m;++T){let M=Math.max(0,Math.ceil((_-T)/p)),D=Math.min(d.outHeight,(d.inHeight+_-T)/p);for(let z=0;z<A;++z){let W=Math.max(0,Math.ceil((b-z)/f)),U=Math.min(d.outWidth,(d.inWidth+b-z)/f);for(let H=0;H<d.inChannels;++H)for(let X=0;X<d.outChannels;++X){let j=0;for(let ee=0;ee<d.batchSize;++ee)for(let Y=M;Y<D;++Y){let se=T+Y*p-_;for(let te=W;te<U;++te){let oe=z+te*f-b;y?j+=N.get(ee,se,oe,H)*S.get(ee,Y,te,X):j+=N.get(ee,H,se,oe)*S.get(ee,X,Y,te)}}g.set(j,T,z,H,X)}}}return n.makeTensorInfo(g.shape,g.dtype,g.values)}var DM={kernelName:Bh,backendName:"cpu",kernelFunc:$M};function OM(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:u,dimRoundingMode:c}=r;ke([a,s],"conv2dBackpropInput");let h=v.computeStrides(s.shape),d=v.computeStrides(a.shape),p=R.convertConv2DDataFormat(u),f=R.computeConv2DInfo(i,s.shape,o,1,l,c,!1,p),m=new Wt(f.inShape,"float32"),A=m.values,y=n.data.get(a.dataId).values,g=n.data.get(s.dataId).values,[b,_,w]=h,{batchSize:x,filterHeight:N,filterWidth:S,inChannels:T,inHeight:M,inWidth:D,outChannels:z,outHeight:W,outWidth:U,strideHeight:H,strideWidth:X}=f;p=f.dataFormat;let j=N-1-f.padInfo.top,ee=S-1-f.padInfo.left,Y=p==="channelsLast",se=m.strides[0],te=Y?m.strides[1]:m.strides[2],oe=Y?m.strides[2]:1,Q=Y?1:m.strides[1],pe=d[0],le=Y?d[1]:d[2],Ae=Y?d[2]:1,me=Y?1:d[1];for(let Se=0;Se<x;++Se)for(let Ee=0;Ee<T;++Ee)for(let Oe=0;Oe<M;++Oe){let Le=Oe-j,ze=Math.max(0,Math.ceil(Le/H)),at=Math.min(W,(N+Le)/H);for(let st=0;st<D;++st){let ct=st-ee,Qe=Math.max(0,Math.ceil(ct/X)),At=Math.min(U,(S+ct)/X),He=0;for(let It=ze;It<at;++It){let Xn=It*H-Le;for(let tn=Qe;tn<At;++tn){let _n=tn*X-ct,Kn=pe*Se+le*It+Ae*tn,Dn=b*(N-1-Xn)+_*(S-1-_n)+w*Ee;for(let pn=0;pn<z;++pn){let nn=y[Kn+me*pn],$r=g[Dn+pn];He+=nn*$r}}}let bn=se*Se+te*Oe+oe*st+Q*Ee;A[bn]=He}}return n.makeTensorInfo(m.shape,m.dtype,m.values)}var zM={kernelName:bs,backendName:"cpu",kernelFunc:OM};function PM(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r;ke([a,s],"conv3d");let u=R.computeConv3DInfo(a.shape,s.shape,i,l,o),{filterDepth:c,filterHeight:h,filterWidth:d,dilationDepth:p,dilationHeight:f,dilationWidth:m,padInfo:A}=u,y=A.front,g=A.left,b=A.top,_=new Wt(u.outShape,a.dtype),w=n.data.get(a.dataId).values,x=n.data.get(s.dataId).values,N=_.values,S=v.computeStrides(a.shape),T=v.computeStrides(s.shape);for(let M=0;M<u.batchSize;++M){let D=M*S[0],z=M*_.strides[0];for(let W=0;W<u.outDepth;++W){let U=z+W*_.strides[1],H=W*u.strideDepth-y;for(let X=0;X<c;++X){let j=H+X*p;if(j<0||j>=u.inDepth)continue;let ee=X*T[0],Y=D+j*S[1];for(let se=0;se<u.outHeight;++se){let te=U+se*_.strides[2],oe=se*u.strideHeight-b;for(let Q=0;Q<h;++Q){let pe=oe+Q*f;if(pe<0||pe>=u.inHeight)continue;let le=ee+Q*T[1],Ae=Y+pe*S[2];for(let me=0;me<u.outWidth;++me){let Se=te+me*u.outChannels,Ee=me*u.strideWidth-g;for(let Oe=0;Oe<d;++Oe){let Le=Ee+Oe*m;if(Le<0||Le>=u.inWidth)continue;let ze=le+Oe*T[2],at=Ae+Le*u.inChannels,st=ze;for(let ct=0;ct<u.inChannels;++ct){let Qe=w[at+ct];for(let At=0;At<u.outChannels;++At)N[Se+At]+=Qe*x[st+At];st+=u.outChannels}}}}}}}}return n.makeTensorInfo(_.shape,_.dtype,_.values)}var LM={kernelName:bu,backendName:"cpu",kernelFunc:PM};function WM(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,filterShape:l}=r;ke([a,s],"conv3dBackpropFilterV2");let u=v.computeStrides(a.shape),c=v.computeStrides(s.shape),h=R.computeConv3DInfo(a.shape,l,i,1,o),d=h.strideDepth,p=h.strideHeight,f=h.strideWidth,m=h.filterDepth,A=h.filterHeight,y=h.filterWidth,g=new Wt(h.filterShape,"float32"),b=g.values,[_,w,x,N]=g.strides,S=n.data.get(s.dataId).values,[T,M,D,z]=c,W=n.data.get(a.dataId).values,[U,H,X,j]=u,ee=h.padInfo.front,Y=h.padInfo.left,se=h.padInfo.top;for(let te=0;te<m;++te){let oe=Math.max(0,Math.ceil((ee-te)/d)),Q=Math.min(h.outDepth,(h.inDepth+ee-te)/d),pe=te*_;for(let le=0;le<A;++le){let Ae=Math.max(0,Math.ceil((se-le)/p)),me=Math.min(h.outHeight,(h.inHeight+se-le)/p),Se=le*w+pe;for(let Ee=0;Ee<y;++Ee){let Oe=Math.max(0,Math.ceil((Y-Ee)/f)),Le=Math.min(h.outWidth,(h.inWidth+Y-Ee)/f),ze=Ee*x+Se;for(let at=0;at<h.inChannels;++at){let st=at*N+ze;for(let ct=0;ct<h.outChannels;++ct){let Qe=0;for(let At=0;At<h.batchSize;++At){let He=At*U,bn=At*T;for(let It=oe;It<Q;++It){let Xn=(te+It*d-ee)*H+He,tn=It*M+bn;for(let _n=Ae;_n<me;++_n){let Kn=(le+_n*p-se)*X+Xn,Dn=_n*D+tn;for(let pn=Oe;pn<Le;++pn){let nn=(Ee+pn*f-Y)*j+Kn,$r=pn*z+Dn;Qe+=W[nn+at]*S[$r+ct]}}}}b[st+ct]=Qe}}}}}return n.makeTensorInfo(g.shape,g.dtype,g.values)}var BM={kernelName:Vh,backendName:"cpu",kernelFunc:WM};function VM(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{pad:i,strides:o,inputShape:l}=r;ke([a],"conv3dBackpropInputV2");let u=v.computeStrides(a.shape),c=v.computeStrides(s.shape),h=R.computeConv3DInfo(l,s.shape,o,1,i),d=new Wt(h.inShape,"float32"),p=d.values,[f,m,A,y]=d.strides,g=n.data.get(a.dataId).values,[b,_,w,x]=u,N=n.data.get(s.dataId).values,[S,T,M,D]=c,{batchSize:z,filterDepth:W,filterHeight:U,filterWidth:H,inChannels:X,inDepth:j,inHeight:ee,inWidth:Y,outChannels:se,outDepth:te,outHeight:oe,outWidth:Q,strideDepth:pe,strideHeight:le,strideWidth:Ae}=h,me=W-1-h.padInfo.front,Se=U-1-h.padInfo.top,Ee=H-1-h.padInfo.left;for(let Oe=0;Oe<z;++Oe)for(let Le=0;Le<X;++Le)for(let ze=0;ze<j;++ze){let at=ze-me,st=Math.max(0,Math.ceil(at/pe)),ct=Math.min(te,(W+at)/pe);for(let Qe=0;Qe<ee;++Qe){let At=Qe-Se,He=Math.max(0,Math.ceil(At/le)),bn=Math.min(oe,(U+At)/le);for(let It=0;It<Y;++It){let Xn=It-Ee,tn=Math.max(0,Math.ceil(Xn/Ae)),_n=Math.min(Q,(H+Xn)/Ae),Kn=0;for(let Dn=st;Dn<ct;++Dn){let pn=Dn*pe-at;for(let nn=He;nn<bn;++nn){let $r=nn*le-At;for(let ar=tn;ar<_n;++ar){let sr=ar*Ae-Xn,_a=b*Oe+_*Dn+w*nn+x*ar,ta=S*(W-1-pn)+T*(U-1-$r)+M*(H-1-sr)+D*Le;for(let va=0;va<se;++va){let Hi=g[_a+va],gr=N[ta+va];Kn+=Hi*gr}}}}p[f*Oe+m*ze+A*Qe+y*It+Le]=Kn}}}return n.makeTensorInfo(d.shape,d.dtype,d.values)}var UM={kernelName:Uh,backendName:"cpu",kernelFunc:VM},HM=ut(_s,e=>Math.cos(e)),jM={kernelName:_s,backendName:"cpu",kernelFunc:HM},GM=ut(mo,e=>Math.cosh(e)),qM={kernelName:mo,backendName:"cpu",kernelFunc:GM};function XM(e){let{inputs:t,backend:n,attrs:r}=e,{image:a,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:u}=r,[c,h,d,p]=a.shape,f=s.shape[0],[m,A]=o,y=Ue([f,m,A,p],"float32"),g=n.data.get(s.dataId).values,b=n.data.get(i.dataId).values,_=n.data.get(a.dataId).values,w=v.computeStrides(a.shape),x=v.computeStrides(y.shape);for(let N=0;N<f;N++){let S=N*4,T=g[S],M=g[S+1],D=g[S+2],z=g[S+3],W=b[N];if(W>=c)continue;let U=m>1?(D-T)*(h-1)/(m-1):0,H=A>1?(z-M)*(d-1)/(A-1):0;for(let X=0;X<m;X++){let j=m>1?T*(h-1)+X*U:.5*(T+D)*(h-1);if(j<0||j>h-1){for(let ee=0;ee<A;ee++)for(let Y=0;Y<p;Y++){let se=Y+ee*x[2]+X*x[1]+N*x[0];y.values[se]=u}continue}if(l==="bilinear"){let ee=Math.floor(j),Y=Math.ceil(j),se=j-ee;for(let te=0;te<A;te++){let oe=A>1?M*(d-1)+te*H:.5*(M+z)*(d-1);if(oe<0||oe>d-1){for(let Ae=0;Ae<p;Ae++){let me=Ae+te*x[2]+X*x[1]+N*x[0];y.values[me]=u}continue}let Q=Math.floor(oe),pe=Math.ceil(oe),le=oe-Q;for(let Ae=0;Ae<p;Ae++){let me=Ae+Q*w[2]+ee*w[1]+W*w[0],Se=_[me];me=Ae+pe*w[2]+ee*w[1]+W*w[0];let Ee=_[me];me=Ae+Q*w[2]+Y*w[1]+W*w[0];let Oe=_[me];me=Ae+pe*w[2]+Y*w[1]+W*w[0];let Le=_[me],ze=Se+(Ee-Se)*le,at=Oe+(Le-Oe)*le;me=Ae+te*x[2]+X*x[1]+N*x[0],y.values[me]=ze+(at-ze)*se}}}else for(let ee=0;ee<A;++ee){let Y=A>1?M*(d-1)+ee*H:.5*(M+z)*(d-1);if(Y<0||Y>d-1){for(let oe=0;oe<p;oe++){let Q=oe+ee*x[2]+X*x[1]+N*x[0];y.values[Q]=u}continue}let se=Math.round(Y),te=Math.round(j);for(let oe=0;oe<p;oe++){let Q=oe+se*w[2]+te*w[1]+W*w[0],pe=oe+ee*x[2]+X*x[1]+N*x[0];y.values[pe]=_[Q]}}}}return n.makeTensorInfo(y.shape,y.dtype,y.values)}var KM={kernelName:Ao,backendName:"cpu",kernelFunc:XM};function ZM(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=r;ke(a,"cumsum");let l=R.getAxesPermutation([s],a.shape.length),u=a;l!=null&&(u=dr({inputs:{x:a},backend:n,attrs:{perm:l}}));let c=R.getInnerMostAxes(1,a.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 h=lr(u.dtype,"int32"),d=v.makeZerosTypedArray(v.sizeFromShape(u.shape),h),p=n.data.get(u.dataId).values,f=u.shape[u.shape.length-1],m=o?(y,g)=>y+f-g-1:(y,g)=>y+g;for(let y=0;y<p.length;y+=f)for(let g=0;g<f;g++){let b=m(y,g);if(g===0)d[b]=i?0:p[b];else{let _=m(y,g-1);d[b]=i?p[_]+d[_]:p[b]+d[_]}}let A=n.makeTensorInfo(u.shape,h,d);if(l!=null){let y=R.getUndoAxesPermutation(l),g=dr({inputs:{x:A},backend:n,attrs:{perm:y}});return n.disposeIntermediateTensorInfo(A),n.disposeIntermediateTensorInfo(u),g}return A}var YM={kernelName:vs,backendName:"cpu",kernelFunc:ZM};function JM(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i,binaryOutput:o}=r;if(a.shape.length===1){let l=n.data.get(a.dataId).values,u=n.data.get(s.dataId).values,c=Vm(l,u,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,c)}else if(a.shape.length===2){let l=n.bufferSync(a),u=n.bufferSync(s),c=nw(l,u,i,o);return n.makeTensorInfo(c.shape,s.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${a.shape.length}.`)}var QM={kernelName:Hh,backendName:"cpu",kernelFunc:JM};function e$(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockSize:s,dataFormat:i}=r;v.assert(i==="NHWC",()=>`Only NHWC dataFormat supported on CPU for depthToSpace. Got ${i}`),v.assert(s>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${s}`);let o=a.shape[0],l=a.shape[1],u=a.shape[2],c=a.shape[3],h=l*s,d=u*s,p=c/(s*s),f=n.data.get(a.dataId).values,m=new Float32Array(o*h*d*p),A=0;for(let y=0;y<o;++y)for(let g=0;g<h;++g){let b=Math.floor(g/s),_=g%s;for(let w=0;w<d;++w){let x=Math.floor(w/s),N=w%s,S=(_*s+N)*p;for(let T=0;T<p;++T){let M=T+S+c*(x+u*(b+l*y));m[A++]=f[M]}}}return n.makeTensorInfo([o,h,d,p],a.dtype,m)}var t$={kernelName:yo,backendName:"cpu",kernelFunc:e$};function Ow(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l,dimRoundingMode:u}=r;ke([a,s],"depthwiseConv2DNative");let c=v.computeStrides(a.shape),h=v.computeStrides(s.shape),d=l;d==null&&(d=[1,1]),v.assert(R.eitherStridesOrDilationsAreOne(i,d),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${d}'`);let p=R.computeConv2DInfo(a.shape,s.shape,i,d,o,u,!0),{filterHeight:f,filterWidth:m,dilationHeight:A,dilationWidth:y,padInfo:g}=p,b=g.left,_=g.top,w=p.outChannels/p.inChannels,x=new Wt(p.outShape,a.dtype),N=n.data.get(a.dataId).values,S=n.data.get(s.dataId).values,T=x.values;for(let M=0;M<p.batchSize;++M){let D=M*c[0],z=M*x.strides[0];for(let W=0;W<p.outHeight;++W){let U=z+W*x.strides[1],H=W*p.strideHeight-b;for(let X=0;X<f;++X){let j=H+X*A;if(j<0||j>=p.inHeight)continue;let ee=X*h[0],Y=D+j*c[1];for(let se=0;se<p.outWidth;++se){let te=U+se*x.strides[2],oe=se*p.strideWidth-_;for(let Q=0;Q<m;++Q){let pe=oe+Q*y;if(pe<0||pe>=p.inWidth)continue;let le=ee+Q*h[1],Ae=Y+pe*p.inChannels,me=te,Se=le;for(let Ee=0;Ee<p.inChannels;++Ee){let Oe=N[Ae+Ee];for(let Le=0;Le<w;++Le)T[me+Le]+=Oe*S[Se+Le];me+=w,Se+=w}}}}}}return n.makeTensorInfo(x.shape,x.dtype,x.values)}var n$={kernelName:ks,backendName:"cpu",kernelFunc:Ow};function r$(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,filterShape:c}=r;ke([a,s],"depthwiseConv2dNativeBackpropFilter");let h=R.computeConv2DInfo(a.shape,c,i,o,l,u,!0),{strideHeight:d,strideWidth:p,filterHeight:f,filterWidth:m}=h,A=new Wt(h.filterShape,"float32"),y=h.padInfo.left,g=h.padInfo.top,b=h.outChannels/h.inChannels,_=n.data.get(a.dataId).values,w=new Wt(a.shape,a.dtype,_),x=n.data.get(s.dataId).values,N=new Wt(s.shape,s.dtype,x);for(let S=0;S<f;++S){let T=Math.max(0,Math.ceil((g-S)/d)),M=Math.min(h.outHeight,(h.inHeight+g-S)/d);for(let D=0;D<m;++D){let z=Math.max(0,Math.ceil((y-D)/p)),W=Math.min(h.outWidth,(h.inWidth+y-D)/p);for(let U=0;U<h.outChannels;++U){let H=Math.trunc(U/b),X=U%b,j=0;for(let ee=0;ee<h.batchSize;++ee)for(let Y=T;Y<M;++Y){let se=S+Y*d-g;for(let te=z;te<W;++te){let oe=D+te*p-y;j+=w.get(ee,se,oe,H)*N.get(ee,Y,te,U)}}A.set(j,S,D,H,X)}}}return n.makeTensorInfo(A.shape,A.dtype,A.values)}var a$={kernelName:jh,backendName:"cpu",kernelFunc:r$};function s$(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,inputShape:c}=r;ke([a,s],"depthwiseConv2DNativeBackpropInput");let h=v.computeStrides(a.shape),d=v.computeStrides(s.shape),p=R.computeConv2DInfo(c,s.shape,i,o,l,u,!0),f=new Wt(p.inShape,"float32"),m=f.values,[A,y,g]=f.strides,b=n.data.get(a.dataId).values,[_,w,x]=h,N=n.data.get(s.dataId).values,[S,T,M]=d,{batchSize:D,filterHeight:z,filterWidth:W,inChannels:U,inHeight:H,inWidth:X,outChannels:j,outHeight:ee,outWidth:Y,strideHeight:se,strideWidth:te}=p,oe=z-1-p.padInfo.top,Q=W-1-p.padInfo.left,pe=j/U;for(let le=0;le<D;++le)for(let Ae=0;Ae<U;++Ae)for(let me=0;me<H;++me){let Se=me-oe,Ee=Math.max(0,Math.ceil(Se/se)),Oe=Math.min(ee,(z+Se)/se);for(let Le=0;Le<X;++Le){let ze=Le-Q,at=Math.max(0,Math.ceil(ze/te)),st=Math.min(Y,(W+ze)/te),ct=0;for(let Qe=Ee;Qe<Oe;++Qe){let At=Qe*se-Se;for(let He=at;He<st;++He){let bn=He*te-ze,It=_*le+w*Qe+x*He,Xn=S*(z-1-At)+T*(W-1-bn)+M*Ae;for(let tn=0;tn<pe;++tn){let _n=Ae*pe+tn,Kn=b[It+_n],Dn=N[Xn+tn];ct+=Kn*Dn}}}m[A*le+y*me+g*Le+Ae]=ct}}return n.makeTensorInfo(f.shape,f.dtype,f.values)}var i$={kernelName:Gh,backendName:"cpu",kernelFunc:s$};function o$(e){let{inputs:t,backend:n}=e,{x:r}=t,a=v.sizeFromShape(r.shape),s=n.data.get(r.dataId).values,i=Ue([a,a],r.dtype),o=i.values;for(let u=0;u<s.length;u++)o[u*a+u]=s[u];let l=[...r.shape,...r.shape];return n.makeTensorInfo(l,i.dtype,i.values)}var l$={kernelName:qh,backendName:"cpu",kernelFunc:o$},u$={kernelName:_u,backendName:"cpu",kernelFunc:({inputs:e,backend:t,attrs:n})=>{let{x:r,filter:a}=e,{strides:s,pad:i,dilations:o}=n,l=t,u=l.data.get(r.dataId).values,c=r.shape.length,h=l.data.get(a.dataId).values,d=a.shape.length,{batchSize:p,inHeight:f,inWidth:m,inChannels:A,outHeight:y,outWidth:g,padInfo:b,strideHeight:_,strideWidth:w,filterHeight:x,filterWidth:N,dilationHeight:S,dilationWidth:T,outShape:M}=R.computeDilation2DInfo(r.shape,a.shape,s,i,"NHWC",o),D=v.sizeFromShape(M),z=M.length,W=v.getArrayFromDType(r.dtype,D);for(let U=0;U<p;++U)for(let H=0;H<y;++H){let X=H*_-b.top;for(let j=0;j<g;++j){let ee=j*w-b.left;for(let Y=0;Y<A;++Y){let se=Number.MIN_SAFE_INTEGER;for(let oe=0;oe<x;++oe){let Q=X+oe*S;if(Q>=0&&Q<f)for(let pe=0;pe<N;++pe){let le=ee+pe*T;if(le>=0&&le<m){let Ae=v.locToIndex([U,Q,le,Y],c,v.computeStrides(r.shape)),me=v.locToIndex([oe,pe,Y],d,v.computeStrides(a.shape)),Se=u[Ae]+h[me];Se>se&&(se=Se)}}}let te=v.locToIndex([U,H,j,Y],z,v.computeStrides(M));W[te]=se}}}return{dataId:l.write(v.toTypedArray(W,r.dtype),M,r.dtype),shape:M,dtype:r.dtype}}},c$={kernelName:Kh,backendName:"cpu",kernelFunc:({inputs:e,backend:t,attrs:n})=>{let{x:r,filter:a,dy:s}=e,{strides:i,pad:o,dilations:l}=n,u=t,c=v.toNestedArray(r.shape,u.data.get(r.dataId).values),h=v.toNestedArray(a.shape,u.data.get(a.dataId).values),{batchSize:d,inHeight:p,inWidth:f,inChannels:m,outHeight:A,outWidth:y,padInfo:g,strideHeight:b,strideWidth:_,filterHeight:w,filterWidth:x,dilationHeight:N,dilationWidth:S,outShape:T}=R.computeDilation2DInfo(r.shape,a.shape,i,o,"NHWC",l);v.assert(s.rank===T.length,()=>`Error in ${Kh}, dy must have the same rank as output ${T.length}, but got ${s.rank}`);let M=v.toNestedArray(T,u.data.get(s.dataId).values),D=v.makeZerosNestedTypedArray(a.shape,a.dtype);for(let z=0;z<d;++z)for(let W=0;W<A;++W){let U=W*b-g.top;for(let H=0;H<y;++H){let X=H*_-g.left;for(let j=0;j<m;++j){let ee=Number.MIN_SAFE_INTEGER,Y=0,se=0;for(let te=0;te<w;++te){let oe=U+te*N;if(oe>=0&&oe<p)for(let Q=0;Q<x;++Q){let pe=X+Q*S;if(pe>=0&&pe<f){let le=c[z][oe][pe][j]+h[te][Q][j];le>ee&&(ee=le,Y=te,se=Q)}}}D[Y][se][j]+=M[z][W][H][j]}}}return{dataId:u.write(v.toTypedArray(D,r.dtype),a.shape,a.dtype),shape:a.shape,dtype:a.dtype}}},h$={kernelName:Xh,backendName:"cpu",kernelFunc:({inputs:e,backend:t,attrs:n})=>{let{x:r,filter:a,dy:s}=e,{strides:i,pad:o,dilations:l}=n,u=t,c=v.toNestedArray(r.shape,u.data.get(r.dataId).values),h=v.toNestedArray(a.shape,u.data.get(a.dataId).values),{batchSize:d,inHeight:p,inWidth:f,inChannels:m,outHeight:A,outWidth:y,padInfo:g,strideHeight:b,strideWidth:_,filterHeight:w,filterWidth:x,dilationHeight:N,dilationWidth:S,outShape:T}=R.computeDilation2DInfo(r.shape,a.shape,i,o,"NHWC",l);v.assert(s.rank===T.length,()=>`Error in ${Xh}, dy must have the same rank as output ${T.length}, but got ${s.rank}`);let M=v.toNestedArray(T,u.data.get(s.dataId).values),D=v.makeZerosNestedTypedArray(r.shape,r.dtype);for(let z=0;z<d;++z)for(let W=0;W<A;++W){let U=W*b-g.top;for(let H=0;H<y;++H){let X=H*_-g.left;for(let j=0;j<m;++j){let ee=Number.MIN_SAFE_INTEGER,Y=U<0?0:U,se=X<0?0:X;for(let te=0;te<w;++te){let oe=U+te*N;if(oe>=0&&oe<p)for(let Q=0;Q<x;++Q){let pe=X+Q*S;if(pe>=0&&pe<f){let le=c[z][oe][pe][j]+h[te][Q][j];le>ee&&(ee=le,Y=oe,se=pe)}}}D[z][Y][se][j]+=M[z][W][H][j]}}}return{dataId:u.write(v.toTypedArray(D,r.dtype),r.shape,r.dtype),shape:r.shape,dtype:r.dtype}}};function d$(e){let{inputs:t,backend:n}=e,{dy:r,y:a}=t;ke([r,a],"eluGrad");let s=new Float32Array(v.sizeFromShape(a.shape)),i=n.data.get(a.dataId).values,o=n.data.get(r.dataId).values;for(let l=0;l<i.length;++l){let u=i[l];u>=1?s[l]=o[l]:s[l]=o[l]*(u+1)}return n.makeTensorInfo(a.shape,"float32",s)}var p$={kernelName:Zh,backendName:"cpu",kernelFunc:d$},f$=Dt((e,t)=>e===t?1:0),zw=Yt(wo,f$,null,"bool"),m$={kernelName:wo,backendName:"cpu",kernelFunc:zw},A$=R.ERF_P,y$=R.ERF_A1,g$=R.ERF_A2,x$=R.ERF_A3,w$=R.ERF_A4,b$=R.ERF_A5,_$=ut(xo,e=>{let t=Math.sign(e),n=Math.abs(e),r=1/(1+A$*n);return t*(1-((((b$*r+w$)*r+x$)*r+g$)*r+y$)*r*Math.exp(-n*n))}),v$={kernelName:xo,backendName:"cpu",kernelFunc:_$};function hp(e){let{inputs:t,backend:n,attrs:r}=e,{input:a}=t,{dim:s}=r,i=a.shape.length,o=a.shape.slice(),l=s;return s<0&&(v.assert(-(i+1)<=s,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+s+1),o.splice(l,0,1),bt({inputs:{x:a},backend:n,attrs:{shape:o}})}var k$={kernelName:bo,backendName:"cpu",kernelFunc:hp},I$=Dt((e,t)=>e/t),Jm=Yt(Is,I$),Qm={kernelName:Is,backendName:"cpu",kernelFunc:Jm};function Pw(e,t,n){let r=e.shape,a=r[0],s=r[1],i=n.data.get(e.dataId),o=i.complexTensorInfos.real,l=i.complexTensorInfos.imag,u=[a,s],c=v.sizeFromShape(u),h=v.getTypedArrayFromDType("float32",c),d=v.getTypedArrayFromDType("float32",c);for(let A=0;A<a;A++){let y=vi({inputs:{x:o},backend:n,attrs:{begin:[A,0],size:[1,s]}}),g=vi({inputs:{x:l},backend:n,attrs:{begin:[A,0],size:[1,s]}}),b=Wn({inputs:{real:y,imag:g},backend:n}),{real:_,imag:w}=N$(b,t,n),x=R.mergeRealAndImagArrays(_,w);for(let N=0;N<s;N++){let S=R.getComplexWithIndex(x,N);h[A*s+N]=S.real,d[A*s+N]=S.imag}n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(g),n.disposeIntermediateTensorInfo(b)}let p=n.makeTensorInfo(u,"float32",h),f=n.makeTensorInfo(u,"float32",d),m=Wn({inputs:{real:p,imag:f},backend:n});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),m}function N$(e,t,n){let r=v.sizeFromShape(e.shape),a=n.data.get(e.dataId),s=n.data.get(a.complexTensorInfos.real.dataId).values,i=n.data.get(a.complexTensorInfos.imag.dataId).values;if(S$(r)){let o=eA(s,i,r,t,n),l=[e.shape[0],e.shape[1]];if(t){let u=n.makeTensorInfo(l,"float32",o.real),c=n.makeTensorInfo(l,"float32",o.imag),h=n.makeTensorInfo([],"float32",v.createScalarValue(r,"float32")),d=jr({inputs:{x:h},backend:n}),p=Qm.kernelFunc({inputs:{a:u,b:h},backend:n}),f=Qm.kernelFunc({inputs:{a:c,b:d},backend:n}),m=n.data.get(p.dataId).values,A=n.data.get(f.dataId).values;return n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),{real:m,imag:A}}return o}else{let o=R.mergeRealAndImagArrays(s,i),l=T$(o,r,t);return R.splitRealAndImagArrays(l)}}function S$(e){return(e&e-1)==0}function eA(e,t,n,r,a){if(n===1)return{real:e,imag:t};let s=R.mergeRealAndImagArrays(e,t),i=n/2,o=R.complexWithEvenIndex(s),l=o.real,u=o.imag,c=[l.length],h=a.makeTensorInfo(c,"float32",l),d=a.makeTensorInfo(c,"float32",u),p=Wn({inputs:{real:h,imag:d},backend:a}),f=R.complexWithOddIndex(s),m=f.real,A=f.imag,y=[m.length],g=a.makeTensorInfo(y,"float32",m),b=a.makeTensorInfo(y,"float32",A),_=Wn({inputs:{real:g,imag:b},backend:a}),w=eA(l,u,i,r,a),x=w.real,N=w.imag,S=[x.length],T=a.makeTensorInfo(S,"float32",x),M=a.makeTensorInfo(S,"float32",N),D=Wn({inputs:{real:T,imag:M},backend:a}),z=eA(m,A,i,r,a),W=z.real,U=z.imag,H=[W.length],X=a.makeTensorInfo(H,"float32",W),j=a.makeTensorInfo(H,"float32",U),ee=Wn({inputs:{real:X,imag:j},backend:a}),Y=R.exponents(n,r),se=[Y.real.length],te=a.makeTensorInfo(se,"float32",Y.real),oe=a.makeTensorInfo(se,"float32",Y.imag),Q=Wn({inputs:{real:te,imag:oe},backend:a}),pe=Xm({inputs:{a:Q,b:ee},backend:a}),le=cc({inputs:{a:D,b:pe},backend:a}),Ae=Km({inputs:{a:D,b:pe},backend:a}),me=_i({inputs:{input:le},backend:a}),Se=_i({inputs:{input:Ae},backend:a}),Ee=Cl({inputs:{input:le},backend:a}),Oe=Cl({inputs:{input:Ae},backend:a}),Le=Rl({inputs:[me,Se],backend:a,attrs:{axis:0}}),ze=Rl({inputs:[Ee,Oe],backend:a,attrs:{axis:0}}),at=a.data.get(Le.dataId).values,st=a.data.get(ze.dataId).values;return a.disposeIntermediateTensorInfo(h),a.disposeIntermediateTensorInfo(d),a.disposeIntermediateTensorInfo(p),a.disposeIntermediateTensorInfo(g),a.disposeIntermediateTensorInfo(b),a.disposeIntermediateTensorInfo(_),a.disposeIntermediateTensorInfo(T),a.disposeIntermediateTensorInfo(M),a.disposeIntermediateTensorInfo(D),a.disposeIntermediateTensorInfo(X),a.disposeIntermediateTensorInfo(j),a.disposeIntermediateTensorInfo(ee),a.disposeIntermediateTensorInfo(te),a.disposeIntermediateTensorInfo(oe),a.disposeIntermediateTensorInfo(Q),a.disposeIntermediateTensorInfo(pe),a.disposeIntermediateTensorInfo(le),a.disposeIntermediateTensorInfo(Ae),a.disposeIntermediateTensorInfo(me),a.disposeIntermediateTensorInfo(Ee),a.disposeIntermediateTensorInfo(Se),a.disposeIntermediateTensorInfo(Oe),a.disposeIntermediateTensorInfo(Le),a.disposeIntermediateTensorInfo(ze),{real:at,imag:st}}function T$(e,t,n){let r=new Float32Array(t*2);for(let a=0;a<t;a++){let s=0,i=0;for(let o=0;o<t;o++){let l=R.exponent(a*o,t,n),u=R.getComplexWithIndex(e,o);s+=u.real*l.real-u.imag*l.imag,i+=u.real*l.imag+u.imag*l.real}n&&(s/=t,i/=t),R.assignToTypedArray(r,s,i,a)}return r}function E$(e){let{inputs:t,backend:n}=e,{input:r}=t,a=v.sizeFromShape(r.shape),s=r.shape[r.shape.length-1],i=a/s,o=bt({inputs:{x:r},backend:n,attrs:{shape:[i,s]}}),l=Pw(o,!1,n),u=bt({inputs:{x:l},backend:n,attrs:{shape:r.shape}});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(l),u}var C$={kernelName:Yh,backendName:"cpu",kernelFunc:E$};function tA(e){let{backend:t,attrs:n}=e,{shape:r,value:a,dtype:s}=n,i=s||v.inferDtype(a),o=v.getArrayFromDType(i,v.sizeFromShape(r));return R$(o,a,i),t.makeTensorInfo(r,i,o)}var F$={kernelName:vu,backendName:"cpu",kernelFunc:tA};function R$(e,t,n){e.fill(t)}var M$={kernelName:vo,backendName:"cpu",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:r}=e,a=n,s=v.getTypedArrayFromDType(r.dtype,v.sizeFromShape(r.shape)),[i,o,l,u]=r.shape,c=a.data.get(r.dataId).values;for(let h=0;h<i;h++){let d=h*l*o*u;for(let p=0;p<o;p++){let f=p*(l*u);for(let m=0;m<l;m++){let A=m*u;for(let y=0;y<u;y++){let g=[i,p,m,y][2],b=Math.round(l-g),_=d+f+A+y,w=c[_];if(b>=0&&b<l){let x=b*u,N=d+f+x+y;w=c[N]}s[_]=w}}}}return{dataId:a.write(s,r.shape,r.dtype),shape:r.shape,dtype:r.dtype}}},$$=Dt((e,t)=>Math.floor(e/t)),D$=Yt(Ts,$$,null,"int32"),O$={kernelName:Ts,backendName:"cpu",kernelFunc:D$};function z$(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dataFormat:c,dilations:h,dimRoundingMode:d,activation:p,leakyreluAlpha:f}=r,m=Dw({inputs:{x:a,filter:s},backend:n,attrs:{strides:l,pad:u,dataFormat:c,dilations:h,dimRoundingMode:d}});if(i){let A=m;m=cc({inputs:{a:m,b:i},backend:n}),n.disposeIntermediateTensorInfo(A)}if(p){let A=m;m=Zm(n,m,p,o,f),n.disposeIntermediateTensorInfo(A)}return m}var P$={kernelName:oi,backendName:"cpu",kernelFunc:z$};function L$(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dataFormat:c,dilations:h,dimRoundingMode:d,activation:p,leakyreluAlpha:f}=r,m=Ow({inputs:{x:a,filter:s},backend:n,attrs:{strides:l,pad:u,dataFormat:c,dilations:h,dimRoundingMode:d}});if(i){let A=m;m=cc({inputs:{a:m,b:i},backend:n}),n.disposeIntermediateTensorInfo(A)}if(p){let A=m;m=Zm(n,m,p,o,f),n.disposeIntermediateTensorInfo(A)}return m}var W$={kernelName:li,backendName:"cpu",kernelFunc:L$};function B$(e){let{inputs:t,backend:n}=e,{params:r,indices:a}=t,s=v.sizeFromShape(r.shape),i=a.shape,o=i[i.length-1],[l,u,c,h]=R.prepareAndValidate(r,a);if(u===0)return n.makeTensorInfo(l,r.dtype,[]);let d=Ue([u,c],r.dtype),p=n.data.get(a.dataId).values,f=n.data.get(r.dataId).values;for(let m=0;m<u;m++){let A=[],y=0;for(let g=0;g<o;g++){let b=p[m*o+g];y+=b*h[g],A.push(b)}if(y<0||y>=s/c)throw new Error(`Invalid indices: ${A} does not index into ${r.shape}`);for(let g=0;g<c;g++)d.values[m*c+g]=f[y*c+g]}return n.makeTensorInfo(l,d.dtype,d.values)}var V$={kernelName:Io,backendName:"cpu",kernelFunc:B$};function U$(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,indices:s}=t,{axis:i,batchDims:o}=r;ke([a,s],"gatherV2");let l=o;o==null&&(l=0);let u=v.sizeFromShape(s.shape),c=v.parseAxisParam(i,a.shape)[0],h=R.segment_util.collectGatherOpShapeInfo(a,s,c,l),d=bt({inputs:{x:a},backend:n,attrs:{shape:[h.batchSize,h.outerSize,h.dimSize,h.sliceSize]}}),p=bt({inputs:{x:s},backend:n,attrs:{shape:[h.batchSize,u/h.batchSize]}}),f=[h.batchSize,h.outerSize,u/h.batchSize,h.sliceSize],m=n.bufferSync(p),A=n.bufferSync(d),y=ow(A,m,f);return n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),n.makeTensorInfo(h.outputShape,y.dtype,y.values)}var H$={kernelName:ko,backendName:"cpu",kernelFunc:U$},j$=Dt((e,t)=>e>=t?1:0),G$=Yt(Cs,j$,null,"bool"),q$={kernelName:Cs,backendName:"cpu",kernelFunc:G$};function X$(e){let{inputs:t,backend:n}=e,{input:r}=t,a=v.sizeFromShape(r.shape),s=r.shape[r.shape.length-1],i=a/s,o=bt({inputs:{x:r},backend:n,attrs:{shape:[i,s]}}),l=Pw(o,!0,n),u=bt({inputs:{x:l},backend:n,attrs:{shape:r.shape}});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(l),u}var K$={kernelName:Jh,backendName:"cpu",kernelFunc:X$},Z$=ut(So,e=>Number.isFinite(e)?1:0,"bool"),Y$={kernelName:So,backendName:"cpu",kernelFunc:Z$},J$=ut(To,e=>Math.abs(e)===Infinity?1:0,"bool"),Q$={kernelName:To,backendName:"cpu",kernelFunc:J$},eD=ut(Eo,e=>Number.isNaN(e)?1:0,"bool"),tD={kernelName:Eo,backendName:"cpu",kernelFunc:eD},nD=Dt((e,t)=>e<=t?1:0),rD=Yt(Ro,nD,null,"bool"),aD={kernelName:Ro,backendName:"cpu",kernelFunc:rD};function sD(e){let{backend:t,attrs:n}=e,{start:r,stop:a,num:s}=n,i=cw(r,a,s);return t.makeTensorInfo([i.length],"float32",i)}var iD={kernelName:ed,backendName:"cpu",kernelFunc:sD},oD=ut(Fo,e=>Math.log1p(e)),lD={kernelName:Fo,backendName:"cpu",kernelFunc:oD},uD=Dt((e,t)=>e&&t),cD=Yt(Mo,uD,null,"bool"),hD={kernelName:Mo,backendName:"cpu",kernelFunc:cD},dD=ut(ku,e=>e?0:1,"bool"),pD={kernelName:ku,backendName:"cpu",kernelFunc:dD},fD=Dt((e,t)=>e||t),mD=Yt(Iu,fD,null,"bool"),AD={kernelName:Iu,backendName:"cpu",kernelFunc:mD};function yD(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=r;ke(a,"LRN");let u=a.shape[3],c=u-1,h=n.data.get(a.dataId).values,d=v.sizeFromShape(a.shape),p=new Float32Array(d);function f(m){let A=m%u,y=m-A+Math.max(0,A-s),g=m-A+Math.min(A+s,c),b=0;for(;y<=g;y++){let _=h[y];b+=_*_}return b}for(let m=0;m<d;m++){let A=f(m),y=h[m]*Math.pow(i+o*A,-l);p[m]=y}return n.makeTensorInfo(a.shape,a.dtype,p)}var gD={kernelName:Nu,backendName:"cpu",kernelFunc:yD};function xD(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:u,beta:c}=r;ke(i,"LRNGrad");let h=v.sizeFromShape(i.shape),d=i.shape[3],p=n.data.get(i.dataId).values,f=n.data.get(a.dataId).values,m=n.data.get(s.dataId).values,A=new Float32Array(h),y=h;for(let g=0;g<y;g++){let b=g%d,_=g-b+Math.max(0,b-o),w=g-b+Math.min(d,b+o+1),x=0;for(let N=_;N<w;N++)x+=Math.pow(f[N],2);x=u*x+l;for(let N=_;N<w;N++){let S=-2*u*c*f[N]*m[g]/x;g===N&&(S+=Math.pow(x,-c)),S*=p[g],A[N]+=S}}return n.makeTensorInfo(i.shape,a.dtype,A)}var wD={kernelName:td,backendName:"cpu",kernelFunc:xD};function Lw(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{reductionIndices:s,keepDims:i}=r,o=n,l=a.shape,u=l.length,c=v.parseAxisParam(s,l),h=c,d=R.getAxesPermutation(h,u),p=o.data.get(a.dataId).values;if(d!=null){let _=new Array(u);for(let w=0;w<_.length;w++)_[w]=l[d[w]];p=jm(p,l,a.dtype,d,_),h=R.getInnerMostAxes(h.length,u),l=_}ke(a,"max"),R.assertAxesAreInnerMostDims("max",h,u);let[f,m]=R.computeOutAndReduceShapes(l,h),A=v.sizeFromShape(m),y=dw(p,A,f,a.dtype),g=o.write(y,f,a.dtype),b=f;return i&&(b=R.expandShapeToKeepDim(f,c)),{dataId:g,shape:b,dtype:a.dtype}}var bD={kernelName:$s,backendName:"cpu",kernelFunc:Lw};function _D(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t;ke(a,"maxPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=r,u=1;v.assert(R.eitherStridesOrDilationsAreOne(i,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let c=R.computePool2DInfo(a.shape,s,i,u,o,l),h;if(c.filterWidth===1&&c.filterHeight===1&&v.arraysEqual(c.inShape,c.outShape))h=jr({inputs:{x:a},backend:n});else{let d=n.data.get(a.dataId).values,p=v.computeStrides(a.shape),f=Ym(d,a.shape,a.dtype,p,c,"max");h=n.makeTensorInfo(c.outShape,a.dtype,f.values)}return h}var vD={kernelName:Os,backendName:"cpu",kernelFunc:_D};function kD(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:u}=r;ke(a,"maxPool3d");let c=R.computePool3DInfo(a.shape,s,i,1,o,l,u),h=n.data.get(a.dataId).values,d=$w(h,a.shape,a.dtype,v.computeStrides(a.shape),c,"max");return n.makeTensorInfo(d.shape,"float32",d.values)}var ID={kernelName:Su,backendName:"cpu",kernelFunc:kD};function ND(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=r;ke([a,s],"maxPool3DGrad");let c=R.computePool3DInfo(s.shape,i,o,1,l,u),h=n.bufferSync(s),d=dM(h,c),p=c.strideDepth,f=c.strideHeight,m=c.strideWidth,A=c.dilationDepth,y=c.dilationHeight,g=c.dilationWidth,b=c.effectiveFilterDepth,_=c.effectiveFilterHeight,w=c.effectiveFilterWidth,x=b-1-c.padInfo.front,N=w-1-c.padInfo.left,S=_-1-c.padInfo.top,T=Ue(s.shape,"float32"),M=n.bufferSync(a);for(let D=0;D<c.batchSize;++D)for(let z=0;z<c.inChannels;++z)for(let W=0;W<c.inDepth;++W)for(let U=0;U<c.inHeight;++U)for(let H=0;H<c.inWidth;++H){let X=W-x,j=U-S,ee=H-N,Y=0;for(let se=0;se<b;se+=A){let te=(X+se)/p;if(!(te<0||te>=c.outDepth||Math.floor(te)!==te))for(let oe=0;oe<_;oe+=y){let Q=(j+oe)/f;if(!(Q<0||Q>=c.outHeight||Math.floor(Q)!==Q))for(let pe=0;pe<w;pe+=g){let le=(ee+pe)/m;if(le<0||le>=c.outWidth||Math.floor(le)!==le)continue;let Ae=b*_*w-1-d.get(D,te,Q,le,z),me=se*_*w+oe*w+pe,Se=Ae===me?1:0;Se!==0&&(Y+=M.get(D,te,Q,le,z)*Se)}}}T.set(Y,D,W,U,H,z)}return n.makeTensorInfo(T.shape,T.dtype,T.values)}var SD={kernelName:rd,backendName:"cpu",kernelFunc:ND};function TD(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s,output:i}=t,o=s;ke([s,i],"maxPoolGrad");let{filterSize:l,strides:u,pad:c,dimRoundingMode:h}=r,d=R.computePool2DInfo(o.shape,l,u,1,c,h),p=n.data.get(o.dataId).values,f=Ue(d.outShape,o.dtype,Mw(p,o.shape,o.dtype,d).values),m=d.strideHeight,A=d.strideWidth,y=d.dilationHeight,g=d.dilationWidth,b=d.effectiveFilterHeight,_=d.effectiveFilterWidth,w=_-1-d.padInfo.left,x=b-1-d.padInfo.top,N=Ue(o.shape,"float32"),S=n.data.get(a.dataId).values,T=Ue(a.shape,"float32",S);for(let M=0;M<d.batchSize;++M)for(let D=0;D<d.inChannels;++D)for(let z=0;z<d.inHeight;++z)for(let W=0;W<d.inWidth;++W){let U=z-x,H=W-w,X=0;for(let j=0;j<b;j+=y){let ee=(U+j)/m;if(!(ee<0||ee>=d.outHeight||Math.floor(ee)!==ee))for(let Y=0;Y<_;Y+=g){let se=(H+Y)/A;if(se<0||se>=d.outWidth||Math.floor(se)!==se)continue;let te=b*_-1-f.get(M,ee,se,D),oe=j*_+Y,Q=te===oe?1:0;Q!==0&&(X+=T.get(M,ee,se,D)*Q)}}N.set(X,M,z,W,D)}return n.makeTensorInfo(N.shape,N.dtype,N.values)}var ED={kernelName:nd,backendName:"cpu",kernelFunc:TD};function CD(e,t,n,r,a){let s=v.computeStrides(t),i=Ym(e,t,n,s,a,"max"),o=Mw(e,t,n,a,!0,r);return[i.values,o.values]}var RD={kernelName:ad,backendName:"cpu",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:r}=e,{filterSize:a,strides:s,pad:i,includeBatchInIndex:o}=t,l=n;ke(r,"MaxPoolWithArgmax");let u=l.data.get(r.dataId).values,c=R.computePool2DInfo(r.shape,a,s,[1,1],i),[h,d]=CD(u,r.shape,r.dtype,o,c),p=l.write(h,c.outShape,r.dtype),f=l.write(d,c.outShape,r.dtype);return[{dataId:p,shape:c.outShape,dtype:r.dtype},{dataId:f,shape:c.outShape,dtype:"int32"}]}};function dp(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r;ke(a,"sum");let o;a.dtype==="bool"?o=Ga({inputs:{x:a},backend:n,attrs:{dtype:"int32"}}):o=jr({inputs:{x:a},backend:n});let l=o.shape.length,u=v.parseAxisParam(s,o.shape),c=R.getAxesPermutation(u,l),h=u,d=o;c!=null&&(d=dr({inputs:{x:o},backend:n,attrs:{perm:c}}),h=R.getInnerMostAxes(h.length,l)),R.assertAxesAreInnerMostDims("sum",h,d.shape.length);let[p,f]=R.computeOutAndReduceShapes(d.shape,h),m=R.upcastType(d.dtype,"int32"),A=cp(n,p,m),y=v.sizeFromShape(f),g=n.data.get(A.dataId).values,b=n.data.get(d.dataId).values;for(let _=0;_<g.length;++_){let w=_*y,x=0;for(let N=0;N<y;++N)x+=b[w+N];g[_]=x}if(i){let _=R.expandShapeToKeepDim(A.shape,u),w=A;A=bt({inputs:{x:A},backend:n,attrs:{shape:_}}),n.disposeIntermediateTensorInfo(w)}return n.disposeIntermediateTensorInfo(o),c!=null&&n.disposeIntermediateTensorInfo(d),A}var FD={kernelName:ei,backendName:"cpu",kernelFunc:dp};function MD(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=v.parseAxisParam(s,a.shape),l=R.computeOutAndReduceShapes(a.shape,o)[1],u=v.sizeFromShape(l),c=[],h=n.makeTensorInfo([],"float32",new Float32Array([u]));c.push(h);let d=Ga({inputs:{x:a},backend:n,attrs:{dtype:"float32"}});c.push(d);let p=Jm({inputs:{a:d,b:h},backend:n});c.push(p);let f=dp({inputs:{x:p},backend:n,attrs:{axis:s,keepDims:i}});return c.forEach(m=>n.disposeIntermediateTensorInfo(m)),f}var $D={kernelName:zs,backendName:"cpu",kernelFunc:MD};function DD(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r;ke(a,"min");let o=v.parseAxisParam(s,a.shape),l=o,u=R.getAxesPermutation(l,a.shape.length),c=a;u!=null&&(c=dr({inputs:{x:a},backend:n,attrs:{perm:u}}),l=R.getInnerMostAxes(l.length,a.shape.length)),R.assertAxesAreInnerMostDims("min",l,c.shape.length);let[h,d]=R.computeOutAndReduceShapes(c.shape,l),p=v.sizeFromShape(d),f=v.makeZerosTypedArray(v.sizeFromShape(h),c.dtype),m=n.data.get(c.dataId).values;for(let y=0;y<f.length;++y){let g=y*p,b=m[g];for(let _=0;_<p;++_){let w=m[g+_];w<b&&(b=w)}f[y]=b}u!=null&&n.disposeIntermediateTensorInfo(c);let A=n.makeTensorInfo(h,c.dtype,f);if(i){let y=R.expandShapeToKeepDim(h,o),g=bt({inputs:{x:A},backend:n,attrs:{shape:y}});return n.disposeIntermediateTensorInfo(A),g}return A}var OD={kernelName:Ps,backendName:"cpu",kernelFunc:DD};function zD(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{paddings:s,mode:i}=r;ke(a,"mirrorPad");let o=s.map((g,b)=>g[0]+a.shape[b]+g[1]),l=s.map(g=>g[0]),u=s.map((g,b)=>g[0]+a.shape[b]),c=i==="reflect"?0:1,h=n.data.get(a.dataId).values,d=a.shape.length,p=v.computeStrides(a.shape),f=v.sizeFromShape(o),m=o.length,A=v.computeStrides(o),y=v.getTypedArrayFromDType(a.dtype,f);for(let g=0;g<f;g++){let b=v.indexToLoc(g,m,A);for(let w=0;w<m;w++)b[w]<l[w]?b[w]=l[w]*2-b[w]-c:b[w]>=u[w]&&(b[w]=(u[w]-1)*2-b[w]+c);b=b.map((w,x)=>w-l[x]);let _=v.locToIndex(b,d,p);y[g]=h[_]}return{dataId:n.write(y,o,a.dtype),shape:o,dtype:a.dtype}}var PD={kernelName:Tu,backendName:"cpu",kernelFunc:zD},LD=Dt((e,t)=>{let n=e%t;return e<0&&t<0||e>=0&&t>=0?n:(n+t)%t}),WD=Yt($o,LD),BD={kernelName:$o,backendName:"cpu",kernelFunc:WD},VD=no(pk());function Ww(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{dim:s}=r,i=a.shape.length,o=s;if(o===-1&&(o=i-1),o!==i-1)throw Error(`Softmax along a non-last dimension is not yet supported. Logits was rank ${i} and dim was ${o}`);let l=v.parseAxisParam([o],a.shape),u=Lw({inputs:{x:a},backend:n,attrs:{reductionIndices:l,keepDims:!1}}),c=R.expandShapeToKeepDim(u.shape,l),h=bt({inputs:{x:u},backend:n,attrs:{shape:c}}),d=Km({inputs:{a,b:h},backend:n}),p=Iw({inputs:{x:d},backend:n}),f=dp({inputs:{x:p},backend:n,attrs:{axis:l,keepDims:!1}}),m=bt({inputs:{x:f},backend:n,attrs:{shape:c}}),A=Jm({inputs:{a:p,b:m},backend:n});return n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(m),A}var UD={kernelName:ti,backendName:"cpu",kernelFunc:Ww};function HD(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{numSamples:s,seed:i,normalized:o}=r;ke(a,"multinomial");let l=o?a:Ww({inputs:{logits:a},backend:n,attrs:{dim:-1}}),u=l.shape[0],c=l.shape[1],h=n.data.get(l.dataId).values,d=[u,s],p=v.makeZerosTypedArray(v.sizeFromShape(d),"int32");for(let f=0;f<u;++f){let m=f*c,A=new Float32Array(c-1);A[0]=h[m];for(let b=1;b<A.length;++b)A[b]=A[b-1]+h[m+b];let y=VD.alea(i.toString()),g=f*s;for(let b=0;b<s;++b){let _=y();p[g+b]=A.length;for(let w=0;w<A.length;w++)if(_<A[w]){p[g+b]=w;break}}}return o||n.disposeIntermediateTensorInfo(l),n.makeTensorInfo(d,"int32",p)}var jD={kernelName:sd,backendName:"cpu",kernelFunc:HD},GD=Hr.nonMaxSuppressionV3Impl;function qD(e){let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l}=r;ke(a,"NonMaxSuppression");let u=n.data.get(a.dataId).values,c=n.data.get(s.dataId).values,{selectedIndices:h}=GD(u,c,i,o,l);return n.makeTensorInfo([h.length],"int32",new Int32Array(h))}var XD={kernelName:zo,backendName:"cpu",kernelFunc:qD},KD=Hr.nonMaxSuppressionV4Impl;function ZD(e){let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,padToMaxOutputSize:u}=r;ke(a,"NonMaxSuppressionPadded");let c=n.data.get(a.dataId).values,h=n.data.get(s.dataId).values,{selectedIndices:d,validOutputs:p}=KD(c,h,i,o,l,u);return[n.makeTensorInfo([d.length],"int32",new Int32Array(d)),n.makeTensorInfo([],"int32",new Int32Array([p]))]}var YD={kernelName:Po,backendName:"cpu",kernelFunc:ZD},JD=Hr.nonMaxSuppressionV5Impl;function QD(e){let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,softNmsSigma:u}=r;ke(a,"NonMaxSuppressionWithScore");let c=n.data.get(a.dataId).values,h=n.data.get(s.dataId).values,d=i,p=o,f=l,m=u,{selectedIndices:A,selectedScores:y}=JD(c,h,d,p,f,m);return[n.makeTensorInfo([A.length],"int32",new Int32Array(A)),n.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var eO={kernelName:Lo,backendName:"cpu",kernelFunc:QD};function tO(e){let{inputs:t,backend:n,attrs:r}=e,{indices:a}=t,{depth:s,onValue:i,offValue:o}=r;ke(a,"oneHot");let l=v.sizeFromShape(a.shape),u=new Float32Array(l*s);u.fill(o);let c=n.data.get(a.dataId).values;for(let h=0;h<l;++h)c[h]>=0&&c[h]<s&&(u[h*s+c[h]]=i);return n.makeTensorInfo([...a.shape,s],"int32",u)}var nO={kernelName:Bs,backendName:"cpu",kernelFunc:tO};function pp(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="string")throw new Error("zerosLike is not supported for string tensors");if(r.dtype==="complex64"){let a=_i({inputs:{input:r},backend:n}),s=pp({inputs:{x:a},backend:n}),i=Cl({inputs:{input:r},backend:n}),o=pp({inputs:{x:i},backend:n}),l=Wn({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return tA({backend:n,attrs:{shape:r.shape,value:0,dtype:r.dtype}})}var rO={kernelName:rl,backendName:"cpu",kernelFunc:pp};function Bw(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="string")throw new Error("onesLike is not supported for string tensors");if(r.dtype==="complex64"){let a=_i({inputs:{input:r},backend:n}),s=Bw({inputs:{x:a},backend:n}),i=Cl({inputs:{input:r},backend:n}),o=pp({inputs:{x:i},backend:n}),l=Wn({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return tA({backend:n,attrs:{shape:r.shape,value:1,dtype:r.dtype}})}var aO={kernelName:Wo,backendName:"cpu",kernelFunc:Bw};function Vw(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r;if(t.length===1)return hp({inputs:{input:t[0]},backend:n,attrs:{dim:a}});let s=t[0].shape,i=t[0].dtype;t.forEach(c=>{v.assertShapesMatch(s,c.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(c=>{let h=hp({inputs:{input:c},backend:n,attrs:{dim:a}});return o.push(h),h}),u=Rl({inputs:l,backend:n,attrs:{axis:a}});return o.forEach(c=>n.disposeIntermediateTensorInfo(c)),u}var sO={kernelName:Bo,backendName:"cpu",kernelFunc:Vw};function iO(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{paddings:s,constantValue:i}=r;ke(a,"pad");let o=s.map((y,g)=>y[0]+a.shape[g]+y[1]),l=s.map(y=>y[0]),u=n.data.get(a.dataId).values,c=v.sizeFromShape(a.shape),h=a.shape.length,d=v.computeStrides(a.shape),p=v.sizeFromShape(o),f=o.length,m=v.computeStrides(o),A=v.getTypedArrayFromDType(a.dtype,p);i!==0&&A.fill(i);for(let y=0;y<c;y++){let g=v.indexToLoc(y,h,d).map((_,w)=>_+l[w]),b=v.locToIndex(g,f,m);A[b]=u[y]}return{dataId:n.write(A,o,a.dtype),shape:o,dtype:a.dtype}}var Uw={kernelName:Vs,backendName:"cpu",kernelFunc:iO},oO=Dt((e,t)=>Math.pow(e,t)),lO=Yt(Us,oO),uO={kernelName:Us,backendName:"cpu",kernelFunc:lO};function cO(e){let{backend:t,attrs:n}=e,{start:r,stop:a,dtype:s,step:i}=n,o=Gm(r,a,i,s);return t.makeTensorInfo([o.length],s,o)}var hO={kernelName:Eu,backendName:"cpu",kernelFunc:cO},dO=ut(Uo,e=>1/e),pO={kernelName:Uo,backendName:"cpu",kernelFunc:dO};function fO(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r;ke(a,"resizeBilinear");let l=v.computeStrides(a.shape),[u,c]=o,[h,d,p,f]=a.shape,m=n.data.get(a.dataId).values,A=new Float32Array(v.sizeFromShape([h,u,c,f])),y=[s&&u>1?d-1:d,s&&c>1?p-1:p],g=[s&&u>1?u-1:u,s&&c>1?c-1:c],b=0,_=y[0]/g[0],w=y[1]/g[1];for(let x=0;x<h;x++)for(let N=0;N<u;N++){let S;i?S=_*(N+.5)-.5:S=_*N;let T=Math.max(0,Math.floor(S)),M=S-T,D=Math.min(d-1,Math.ceil(S)),z=x*l[0]+T*l[1],W=x*l[0]+D*l[1];for(let U=0;U<c;U++){let H;i?H=w*(U+.5)-.5:H=w*U;let X=Math.max(0,Math.floor(H)),j=H-X,ee=Math.min(p-1,Math.ceil(H)),Y=z+X*l[2],se=W+X*l[2],te=z+ee*l[2],oe=W+ee*l[2];for(let Q=0;Q<f;Q++){let pe=m[Y+Q],le=m[se+Q],Ae=m[te+Q],me=m[oe+Q],Se=pe+(Ae-pe)*j,Ee=le+(me-le)*j,Oe=Se+(Ee-Se)*M;A[b++]=Oe}}}return n.makeTensorInfo([h,u,c,f],"float32",A)}var mO={kernelName:Gs,backendName:"cpu",kernelFunc:fO};function AO(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r;ke([s,a],"resizeBilinearGrad");let o=v.computeStrides(a.shape),[l,u,c,h]=a.shape,[,d,p]=s.shape,f=new Float32Array(l*u*c*h),m=[i&&d>1?u-1:u,i&&p>1?c-1:c],A=[i&&d>1?d-1:d,i&&p>1?p-1:p],y=m[0]/A[0],g=m[1]/A[1],b=n.data.get(s.dataId).values,_=0;for(let w=0;w<l;w++){let x=w*o[0];for(let N=0;N<d;N++){let S=N*y,T=Math.floor(S),M=Math.min(Math.ceil(S),u-1),D=x+T*o[1],z=x+M*o[1],W=S-T,U=1-W;for(let H=0;H<p;H++){let X=H*g,j=Math.floor(X),ee=Math.min(Math.ceil(X),c-1),Y=X-j,se=1-Y,te=D+j*o[2],oe=D+ee*o[2],Q=z+j*o[2],pe=z+ee*o[2],le=U*se,Ae=U*Y,me=W*se,Se=W*Y;for(let Ee=0;Ee<h;Ee++){let Oe=b[_++];f[te+Ee]+=Oe*le,f[oe+Ee]+=Oe*Ae,f[Q+Ee]+=Oe*me,f[pe+Ee]+=Oe*Se}}}}return n.makeTensorInfo([l,c,u,h],"float32",f)}var yO={kernelName:ld,backendName:"cpu",kernelFunc:AO};function gO(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r;ke(a,"resizeNearestNeighbor");let l=v.computeStrides(a.shape),[u,c]=o,[h,d,p,f]=a.shape,m=n.data.get(a.dataId).values,A=new Float32Array(h*u*c*f),y=[s&&u>1?d-1:d,s&&c>1?p-1:p],g=[s&&u>1?u-1:u,s&&c>1?c-1:c],b=y[0]/g[0],_=y[1]/g[1],w=0;for(let x=0;x<h;x++){let N=x*l[0];for(let S=0;S<u;S++){let T=i?b*(S+.5):b*S,M=Math.min(d-1,s?Math.round(T):Math.floor(T));i&&(M=Math.max(0,M));let D=N+M*l[1];for(let z=0;z<c;z++){let W=i?_*(z+.5):_*z,U=Math.min(p-1,s?Math.round(W):Math.floor(W));i&&(U=Math.max(0,U));let H=D+U*l[2];for(let X=0;X<f;X++){let j=m[H+X];A[w++]=j}}}}return n.makeTensorInfo([h,u,c,f],a.dtype,A)}var xO={kernelName:Cu,backendName:"cpu",kernelFunc:gO};function wO(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r;ke([s,a],"resizeNearestNeighborGrad");let o=v.computeStrides(a.shape),l=v.computeStrides(s.shape),[u,c,h,d]=a.shape,[,p,f]=s.shape,m=new Float32Array(u*c*h*d),A=n.data.get(s.dataId).values,y=[i&&p>1?c-1:c,i&&f>1?h-1:h],g=[i&&p>1?p-1:p,i&&f>1?f-1:f],b=y[0]/g[0],_=y[1]/g[1],w=1/b,x=1/_,N=Math.ceil(w)*2+2,S=Math.ceil(x)*2+2;for(let T=0;T<u;T++){let M=T*o[0];for(let D=0;D<c;D++){let z=M+D*o[1],W=Math.floor(D*w),U=Math.floor(W-N/2);for(let H=0;H<h;H++){let X=z+H*o[2],j=Math.floor(H*x),ee=Math.floor(j-S/2);for(let Y=0;Y<d;Y++){let se=0;for(let te=0;te<N;te++){let oe=te+U;if(oe<0||oe>=p)continue;let Q=M+oe*l[1],pe=oe*b,le=Math.min(c-1,i?Math.round(pe):Math.floor(pe));if(D===le)for(let Ae=0;Ae<S;Ae++){let me=Ae+ee;if(me<0||me>=f)continue;let Se=Q+me*l[2],Ee=me*_,Oe=Math.min(h-1,i?Math.round(Ee):Math.floor(Ee));H===Oe&&(se+=A[Se+Y])}}m[X+Y]=se}}}}return n.makeTensorInfo(a.shape,a.dtype,m)}var bO={kernelName:od,backendName:"cpu",kernelFunc:wO};function _O(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{dims:s}=r;ke(a,"reverse");let i=a.shape.length,o=v.parseAxisParam(s,a.shape);if(i===0)return jr({inputs:{x:a},backend:n});let l=new Wt(a.shape,a.dtype),u=n.bufferSync(a);for(let c=0;c<l.size;c++){let h=l.indexToLoc(c),d=h.slice();o.forEach(p=>d[p]=a.shape[p]-1-d[p]),l.set(u.get(...d),...h)}return n.makeTensorInfo(l.shape,l.dtype,l.values)}var vO={kernelName:Xs,backendName:"cpu",kernelFunc:_O},kO={kernelName:al,backendName:"cpu",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:r}=e,{radians:a,fillValue:s,center:i}=t,o=n,l=v.getTypedArrayFromDType(r.dtype,v.sizeFromShape(r.shape)),[u,c,h,d]=r.shape,[p,f]=R.getImageCenter(i,c,h),m=255,A=Math.sin(a),y=Math.cos(a),g=o.data.get(r.dataId).values;for(let b=0;b<u;b++){let _=b*h*c*d;for(let w=0;w<c;w++){let x=w*(h*d);for(let N=0;N<h;N++){let S=N*d;for(let T=0;T<d;T++){let M=[u,w,N,T],D=M[2],z=M[1],W=(D-p)*y-(z-f)*A,U=(D-p)*A+(z-f)*y;W=Math.round(W+p),U=Math.round(U+f);let H=s;if(typeof s!="number"&&(T===3?H=m:H=s[T]),W>=0&&W<h&&U>=0&&U<c){let j=U*(h*d),ee=W*d,Y=_+j+ee+T;H=g[Y]}let X=_+x+S+T;l[X]=H}}}}return{dataId:o.write(l,r.shape,r.dtype),shape:r.shape,dtype:r.dtype}}},IO=ut(Ks,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}),NO={kernelName:Ks,backendName:"cpu",kernelFunc:IO};function Hw(e,t,n,r,a,s,i,o,l,u){let c=[r/a,a],h=e.values,d=t.values;if(r===0)return Ue(n,t.dtype);let p=Ue(c,t.dtype);p.values.fill(l);for(let f=0;f<s;f++){let m=[],A=0;for(let y=0;y<i;y++){let g=h[f*i+y];m.push(g),A+=g*o[y]}if(A<0||A>=r/a)throw new Error(`Invalid indices: ${m} does not index into ${n}`);for(let y=0;y<a;y++)u?p.values[A*a+y]+=d[f*a+y]:p.values[A*a+y]=t.rank===0?d[0]:d[f*a+y]}return p}function SO(e){let{inputs:t,backend:n,attrs:r}=e,{indices:a,updates:s}=t,{shape:i}=r,{sliceRank:o,numUpdates:l,sliceSize:u,strides:c,outputSize:h}=R.calculateShapes(s,a,i),d=!0,p=n.bufferSync(a),f=n.bufferSync(s),m=Hw(p,f,i,h,u,l,o,c,0,d);return n.makeTensorInfo(i,m.dtype,m.values)}var TO={kernelName:jo,backendName:"cpu",kernelFunc:SO};function EO(e){let{inputs:t,backend:n}=e,{condition:r,t:a,e:s}=t;ke([r,a,s],"select");let i=r.shape.length,o=n.data.get(r.dataId).values,l=n.data.get(a.dataId).values,u=n.data.get(s.dataId).values,c=lr(a.dtype,s.dtype),h=v.makeZerosTypedArray(v.sizeFromShape(a.shape),c),d=0,p=i===0||i>1||a.shape.length===1?1:v.sizeFromShape(a.shape.slice(1));for(let f=0;f<o.length;f++)for(let m=0;m<p;m++)o[f]===1?h[d++]=l[f]:h[d++]=u[f];return n.makeTensorInfo(a.shape,c,h)}var CO={kernelName:Go,backendName:"cpu",kernelFunc:EO},RO=R.SELU_SCALEALPHA,FO=R.SELU_SCALE,MO=ut(qo,e=>e>=0?FO*e:RO*(Math.exp(e)-1)),$O={kernelName:qo,backendName:"cpu",kernelFunc:MO},DO=ut(Js,e=>1/(1+Math.exp(-e))),OO={kernelName:Js,backendName:"cpu",kernelFunc:DO},zO=ut(Zo,e=>e<0?-1:e>0?1:0),PO={kernelName:Zo,backendName:"cpu",kernelFunc:zO},LO=ut(Ys,e=>Math.sin(e)),WO={kernelName:Ys,backendName:"cpu",kernelFunc:LO},BO=ut(Ko,e=>Math.sinh(e)),VO={kernelName:Ko,backendName:"cpu",kernelFunc:BO},UO=11920928955078125e-23,jw=Math.log(UO)+2,HO=ut(Yo,e=>{let t=e>-jw,n=e<jw,r=Math.exp(e),a;return n?a=r:t?a=e:a=Math.log(1+r),a}),jO={kernelName:Yo,backendName:"cpu",kernelFunc:HO};function GO(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,paddings:i}=r;ke([a],"spaceToBatchND");let o=v.sizeFromShape(s),l=[[0,0]];l.push(...i);for(let A=1+s.length;A<a.shape.length;++A)l.push([0,0]);let u=Uw.kernelFunc({inputs:{x:a},backend:n,attrs:{paddings:l,constantValue:0}}),c=R.getReshaped(u.shape,s,o,!1),h=R.getPermuted(c.length,s.length,!1),d=R.getReshapedPermuted(u.shape,s,o,!1),p=bt({inputs:{x:u},backend:n,attrs:{shape:c}}),f=dr({inputs:{x:p},backend:n,attrs:{perm:h}}),m=bt({inputs:{x:f},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),m}var qO={kernelName:Ru,backendName:"cpu",kernelFunc:GO};function XO(e){let{inputs:t,backend:n,attrs:r}=e,{sparseIndices:a,sparseValues:s,defaultValue:i}=t,{outputShape:o}=r,{sliceRank:l,numUpdates:u,sliceSize:c,strides:h,outputSize:d}=R.calculateShapes(s,a,o),p=!1,f=n.bufferSync(a),m=n.bufferSync(s),A=n.data.get(i.dataId).values[0],y=Hw(f,m,o,d,c,u,l,h,A,p);return n.makeTensorInfo(o,y.dtype,y.values)}var KO={kernelName:ud,backendName:"cpu",kernelFunc:XO};function ZO(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{numOrSizeSplits:s,axis:i}=r,o=v.parseAxisParam(i,a.shape)[0],l=R.prepareSplitSize(a,s,o),u=new Array(a.shape.length).fill(0),c=a.shape.slice();return l.map(h=>{let d=[...c];d[o]=h;let p=vi({inputs:{x:a},backend:n,attrs:{begin:u,size:d}});return u[o]+=h,p})}var YO={kernelName:Jo,backendName:"cpu",kernelFunc:ZO},JO=ut(Qs,e=>Math.sqrt(e)),QO={kernelName:Qs,backendName:"cpu",kernelFunc:JO},ez={kernelName:Fu,backendName:"cpu",kernelFunc:({inputs:e,backend:t})=>{let{x:n}=e,r=t;ke(n,"square");let a=r.data.get(n.dataId).values,s=new Float32Array(a.length);for(let i=0;i<a.length;++i){let o=a[i];s[i]=o*o}return{dataId:r.write(s,n.shape,n.dtype),shape:n.shape,dtype:n.dtype}}},tz=ut($a,(e,t)=>{let n=t;return isNaN(e)?NaN:e>0?1:n.alpha}),nz={kernelName:$a,backendName:"cpu",kernelFunc:tz};function rz(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{begin:s,end:i,strides:o,beginMask:l,endMask:u,ellipsisMask:c,newAxisMask:h,shrinkAxisMask:d}=r;ke(a,"stridedSlice");let{nonStrided:p,$begin:f,$strides:m,size:A,newShape:y,outShape:g}=fn.sliceInfo(a.shape,s,i,o,l,u,c,h,d),b=bt({inputs:{x:a},backend:n,attrs:{shape:y}}),_;if(p){let x=vi({inputs:{x:b},backend:n,attrs:{begin:f,size:A}});_=bt({inputs:{x},backend:n,attrs:{shape:g}}),n.disposeIntermediateTensorInfo(x)}else if(g.some(x=>x===0))_=n.makeTensorInfo(g,a.dtype,[]);else{let x=n.bufferSync(b),N=ww(g,x,m,f);_=n.makeTensorInfo(N.shape,N.dtype,N.values)}let w=bt({inputs:{x:_},backend:n,attrs:{shape:g}});return n.disposeIntermediateTensorInfo(b),n.disposeIntermediateTensorInfo(_),w}var az={kernelName:Qo,backendName:"cpu",kernelFunc:rz},sz=ut(el,e=>Math.tan(e)),iz={kernelName:el,backendName:"cpu",kernelFunc:sz},oz=ut(ai,e=>Math.tanh(e)),lz={kernelName:ai,backendName:"cpu",kernelFunc:oz};function uz(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{reps:s}=r;ke(a,"tile");let i=_w(n.bufferSync(a),s);return n.makeTensorInfo(i.shape,i.dtype,i.values)}var cz={kernelName:Ma,backendName:"cpu",kernelFunc:uz};function hz(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{k:s,sorted:i}=r;ke(a,"topk");let o=n.data.get(a.dataId).values,[l,u]=vw(o,a.shape,a.dtype,s,i);return[n.makeTensorInfo(l.shape,l.dtype,l.values),n.makeTensorInfo(u.shape,u.dtype,u.values)]}var dz={kernelName:tl,backendName:"cpu",kernelFunc:hz};function mz(e){let{inputs:t,attrs:n,backend:r}=e,{image:a,transforms:s}=t,{interpolation:i,fillMode:o,fillValue:l,outputShape:u}=n,[c,h,d,p]=a.shape,[f,m]=u!=null?u:[h,d],A=[c,f,m,p],y=v.computeStrides(a.shape),g=y[0],b=y[1],_=y[2],w=v.getTypedArrayFromDType(a.dtype,v.sizeFromShape(A));w.fill(l);let x=r.data.get(a.dataId).values,N=r.data.get(s.dataId).values;for(let S=0;S<c;++S){let T=s.shape[0]===1?N:N.subarray(S*8,S*8+8);for(let M=0;M<f;++M)for(let D=0;D<m;++D)for(let z=0;z<p;++z){let W,U=T[6]*D+T[7]*M+1;if(U===0)continue;let H=(T[0]*D+T[1]*M+T[2])/U,X=(T[3]*D+T[4]*M+T[5])/U,j=Gw(H,d,o),ee=Gw(X,h,o);switch(i){case"nearest":W=pz(x,h,d,g,b,_,S,ee,j,z,l);break;case"bilinear":W=fz(x,h,d,g,b,_,S,ee,j,z,l);break;default:throw new Error(`Error in Transform: Expect 'nearest' or 'bilinear', but got ${i}`)}let Y=S*g+M*b+D*_+z;w[Y]=W}return r.makeTensorInfo(A,a.dtype,w)}return{dataId:r.write(w,A,a.dtype),shape:a.shape,dtype:a.dtype}}var Az={kernelName:cd,backendName:"cpu",kernelFunc:mz};function Gw(e,t,n){switch(n){case"reflect":return yz(e,t);case"wrap":return gz(e,t);case"nearest":return wz(e,t);case"constant":default:return xz(e,t)}}function yz(e,t){let n=e;if(n<0)if(t<=1)n=0;else{let r=2*t;n<r&&(n=r*Math.trunc(-n/r)+n),n=n<-t?n+r:-n-1}else if(n>t-1)if(t<=1)n=0;else{let r=2*t;n-=r*Math.trunc(n/r),n>=t&&(n=r-n-1)}return v.clamp(0,n,t-1)}function gz(e,t){let n=e;if(n<0)if(t<=1)n=0;else{let r=t-1;n+=t*(Math.trunc(-n/r)+1)}else if(n>t-1)if(t<=1)n=0;else{let r=t-1;n-=t*Math.trunc(n/r)}return v.clamp(0,n,t-1)}function xz(e,t){return e}function wz(e,t){return v.clamp(0,e,t-1)}function hc(e,t,n,r,a,s,i,o,l,u,c){let h=i*r+o*a+l*s+u;return 0<=o&&o<t&&0<=l&&l<n?e[h]:c}function pz(e,t,n,r,a,s,i,o,l,u,c){let h=Math.round(o),d=Math.round(l);return hc(e,t,n,r,a,s,i,h,d,u,c)}function fz(e,t,n,r,a,s,i,o,l,u,c){let h=Math.floor(o),d=Math.floor(l),p=h+1,f=d+1,m=(f-l)*hc(e,t,n,r,a,s,i,h,d,u,c)+(l-d)*hc(e,t,n,r,a,s,i,h,f,u,c),A=(f-l)*hc(e,t,n,r,a,s,i,p,d,u,c)+(l-d)*hc(e,t,n,r,a,s,i,p,f,u,c);return(p-o)*m+(o-h)*A}function bz(e){let{inputs:t,attrs:n,backend:r}=e,{axis:a}=n,{x:s}=t;ke(s,"unique");let i=r.data.get(s.dataId).values,{outputValues:o,outputShape:l,indices:u}=kw(i,a,s.shape,s.dtype);return[r.makeTensorInfo(l,s.dtype,o),r.makeTensorInfo([u.length],"int32",u)]}var _z={kernelName:hd,backendName:"cpu",kernelFunc:bz};function vz(e){let{inputs:t,backend:n,attrs:r}=e,{value:a}=t,{axis:s}=r;s<0&&(s+=a.shape.length);let i=a.shape.length,o=a.shape[s],l=new Array(i-1),u=0;for(let p=0;p<i;p++)p!==s&&(l[u++]=a.shape[p]);let c=new Array(i).fill(0),h=a.shape.slice();h[s]=1;let d=new Array(o);for(let p=0;p<d.length;p++){c[s]=p;let f=vi({inputs:{x:a},backend:n,attrs:{begin:c,size:h}});d[p]=bt({inputs:{x:f},backend:n,attrs:{shape:l}}),n.disposeIntermediateTensorInfo(f)}return d}var kz={kernelName:nl,backendName:"cpu",kernelFunc:vz};function Iz(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,segmentIds:s}=t,{numSegments:i}=r;ke(a,"unsortedSegmentSum");let o=a.shape.length,l=s.shape.length,u=[],c=[],h=o-l,d=s;for(let f=0;f<h;++f){let m=hp({inputs:{input:d},backend:n,attrs:{dim:f+1}});d=m,c.push(m)}for(let f=0;f<i;++f){let m=v.createScalarValue(f,"int32"),A=n.makeTensorInfo([],"int32",m),y=zw({inputs:{a:A,b:d},backend:n}),g=Ga({inputs:{x:y},backend:n,attrs:{dtype:"float32"}}),b=Xm({inputs:{a:g,b:a},backend:n}),_=dp({inputs:{x:b},backend:n,attrs:{axis:0,keepDims:!1}});u.push(_),c.push(A),c.push(y),c.push(g),c.push(b),c.push(_)}let p=Vw({inputs:u,backend:n,attrs:{axis:0}});return c.forEach(f=>n.disposeIntermediateTensorInfo(f)),p}var Nz={kernelName:Mu,backendName:"cpu",kernelFunc:Iz},Sz=[WF,jR,VF,HF,YR,GF,XF,ZF,JF,eM,nM,aM,iM,uM,hM,fM,AM,gM,wM,PF,_M,kM,NM,KR,QR,TM,GR,CM,FM,DM,zM,MM,BM,UM,LM,jM,qM,KM,YM,QM,t$,n$,a$,i$,l$,u$,h$,c$,Qm,RF,p$,m$,v$,eF,k$,nF,C$,F$,M$,aF,O$,P$,W$,V$,H$,iF,q$,qR,K$,RM,Y$,Q$,tD,FF,lF,aD,iD,cF,lD,hD,pD,AD,gD,wD,dF,vD,ID,SD,ED,RD,bD,$D,OD,fF,PD,BD,jD,AF,gF,XD,YD,eO,wF,nO,aO,sO,Uw,uO,$F,vF,hO,XR,pO,DF,OF,zF,mO,yO,xO,bO,vO,kO,NO,IF,TO,CO,$O,OO,PO,WO,VO,NF,UD,jO,qO,KO,YO,QO,ez,TF,nz,az,CF,FD,iz,lz,cz,dz,bF,Az,_z,kz,Nz,rO];for(let e of Sz)ui(e);var qw={};We(qw,{assertNotComplex:()=>Fl,bindCanvasToFramebuffer:()=>Cz,bindColorTextureToFramebuffer:()=>mp,bindTextureToProgramUniformSampler:()=>lb,bindTextureUnit:()=>sb,bindVertexBufferToProgramAttribute:()=>nA,callAndCheck:()=>_e,canBeRepresented:()=>Xw,createFragmentShader:()=>Yw,createFramebuffer:()=>ab,createProgram:()=>Jw,createStaticIndexBuffer:()=>tb,createStaticVertexBuffer:()=>eb,createTexture:()=>nb,createVertexShader:()=>Zw,getBatchDim:()=>ki,getExtensionOrThrow:()=>dc,getFramebufferErrorMessage:()=>ub,getMaxTexturesInShader:()=>db,getNumChannels:()=>Tz,getProgramUniformLocation:()=>ob,getProgramUniformLocationOrThrow:()=>ib,getRowsCols:()=>Ii,getShapeAs3D:()=>Ap,getTextureShapeFromLogicalShape:()=>cb,getWebGLDisjointQueryTimerVersion:()=>pb,getWebGLErrorMessage:()=>Kw,getWebGLMaxTextureSize:()=>hb,hasExtension:()=>er,isCapableOfRenderingToFloatTexture:()=>fb,isDownloadFloatTextureEnabled:()=>mb,isReshapeFree:()=>fc,isWebGLFenceEnabled:()=>Ab,isWebGLVersionEnabled:()=>aA,linkProgram:()=>Qw,resetMaxTextureSize:()=>Rz,resetMaxTexturesInShader:()=>Fz,unbindColorTextureFromFramebuffer:()=>rA,unbindTextureUnit:()=>Ez,validateFramebuffer:()=>pc,validateProgram:()=>fp,validateTextureSize:()=>rb});var Ni={},sA={alpha:!1,antialias:!1,premultipliedAlpha:!1,preserveDrawingBuffer:!1,depth:!1,stencil:!1,failIfMajorPerformanceCaveat:!0};function yp(e,t){Ni[e]=t}function Gr(e){if(!(e in Ni)){let n=Mz(e);if(n!==null)Ni[e]=n;else return console.log("Could not get context for WebGL version",e),null}let t=Ni[e];return t.isContextLost()?(delete Ni[e],Gr(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),Ni[e])}function $z(e){if(typeof OffscreenCanvas!="undefined"&&e===2)return new OffscreenCanvas(300,150);if(typeof document!="undefined")return document.createElement("canvas");throw new Error("Cannot create a canvas in this context")}function Mz(e){if(e!==1&&e!==2)throw new Error("Cannot get WebGL rendering context, WebGL is disabled.");let t=$z(e);return t.addEventListener("webglcontextlost",n=>{n.preventDefault(),delete Ni[e]},!1),e===1?t.getContext("webgl",sA)||t.getContext("experimental-webgl",sA):t.getContext("webgl2",sA)}var mc;(function(e){e[e.DENSE=0]="DENSE",e[e.SHARED_BATCH=1]="SHARED_BATCH"})(mc||(mc={}));var tr;(function(e){e[e.RENDER=0]="RENDER",e[e.UPLOAD=1]="UPLOAD",e[e.PIXELS=2]="PIXELS",e[e.DOWNLOAD=3]="DOWNLOAD"})(tr||(tr={}));var sn;(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"})(sn||(sn={}));function Ac(e,t){return[t,e]}function Dz(e,t){return e*t}function yc(e){let t=v.sizeFromShape(e),n=Math.ceil(t/4);return v.sizeToSquarishShape(n)}function Ml(e,t){return[Math.max(1,Math.ceil(t/2)),Math.max(1,Math.ceil(e/2))]}function Oz(e,t){let[n,r]=Ml(e,t);return n*r*4}function iA(e,t){let n=e,r,a,s,i,o,l,u,c,h,d;return J().getNumber("WEBGL_VERSION")===2?(r=n.R32F,a=n.R16F,s=n.RGBA16F,i=n.RGBA32F,o=n.RED,u=4,c=1,h=n.HALF_FLOAT,d=n.FLOAT):(r=e.RGBA,a=e.RGBA,s=e.RGBA,i=n.RGBA,o=e.RGBA,u=4,c=4,h=t!=null?t.HALF_FLOAT_OES:null,d=e.FLOAT),l=e.RGBA,{internalFormatFloat:r,internalFormatHalfFloat:a,internalFormatPackedHalfFloat:s,internalFormatPackedFloat:i,textureFormatFloat:o,downloadTextureFormat:l,downloadUnpackNumChannels:u,defaultNumChannels:c,textureTypeHalfFloat:h,textureTypeFloat:d}}function _e(e,t){let n=t();return J().getBool("DEBUG")&&zz(e),n}function zz(e){let t=e.getError();if(t!==e.NO_ERROR)throw new Error("WebGL Error: "+Kw(e,t))}var Pz=596e-10,Lz=65504;function Xw(e){return!!(J().getBool("WEBGL_RENDER_FLOAT32_ENABLED")||e===0||Pz<Math.abs(e)&&Math.abs(e)<Lz)}function Kw(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 dc(e,t){return fa(e,()=>e.getExtension(t),'Extension "'+t+'" not supported on this browser.')}function Zw(e,t){let n=fa(e,()=>e.createShader(e.VERTEX_SHADER),"Unable to create vertex WebGLShader.");if(_e(e,()=>e.shaderSource(n,t)),_e(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 Yw(e,t){let n=fa(e,()=>e.createShader(e.FRAGMENT_SHADER),"Unable to create fragment WebGLShader.");if(_e(e,()=>e.shaderSource(n,t)),_e(e,()=>e.compileShader(n)),e.getShaderParameter(n,e.COMPILE_STATUS)===!1)throw Wz(t,e.getShaderInfoLog(n)),new Error("Failed to compile fragment shader.");return n}var Bz=/ERROR: [0-9]+:([0-9]+):/g;function Wz(e,t){let n=Bz.exec(t);if(n==null){console.log(`Couldn't parse line number in error: ${t}`),console.log(e);return}let r=+n[1],a=e.split(`
|
|
`),s=a.length.toString().length+2,i=a.map((h,d)=>v.rightPad((d+1).toString(),s)+h),o=0;for(let h=0;h<i.length;h++)o=Math.max(i[h].length,o);let l=i.slice(0,r-1),u=i.slice(r-1,r),c=i.slice(r);console.log(l.join(`
|
|
`)),console.log(t.split(`
|
|
`)[0]),console.log(`%c ${v.rightPad(u[0],o)}`,"border:1px solid red; background-color:#e3d2d2; color:#a61717"),console.log(c.join(`
|
|
`))}function Jw(e){return fa(e,()=>e.createProgram(),"Unable to create WebGLProgram.")}function Qw(e,t){if(_e(e,()=>e.linkProgram(t)),e.getProgramParameter(t,e.LINK_STATUS)===!1)throw console.log(e.getProgramInfoLog(t)),new Error("Failed to link vertex and fragment shaders.")}function fp(e,t){if(_e(e,()=>e.validateProgram(t)),e.getProgramParameter(t,e.VALIDATE_STATUS)===!1)throw console.log(e.getProgramInfoLog(t)),new Error("Shader program validation failed.")}function eb(e,t){let n=fa(e,()=>e.createBuffer(),"Unable to create WebGLBuffer");return _e(e,()=>e.bindBuffer(e.ARRAY_BUFFER,n)),_e(e,()=>e.bufferData(e.ARRAY_BUFFER,t,e.STATIC_DRAW)),n}function tb(e,t){let n=fa(e,()=>e.createBuffer(),"Unable to create WebGLBuffer");return _e(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,n)),_e(e,()=>e.bufferData(e.ELEMENT_ARRAY_BUFFER,t,e.STATIC_DRAW)),n}function Tz(){return J().getNumber("WEBGL_VERSION")===2?1:4}function nb(e){return fa(e,()=>e.createTexture(),"Unable to create WebGLTexture.")}function rb(e,t){let n=J().getNumber("WEBGL_MAX_TEXTURE_SIZE");if(e<=0||t<=0){let r=`[${e}x${t}]`;throw new Error("Requested texture size "+r+" is invalid.")}if(e>n||t>n){let r=`[${e}x${t}]`,a=`[${n}x${n}]`;throw new Error("Requested texture size "+r+" greater than WebGL maximum on this browser / GPU "+a+".")}}function ab(e){return fa(e,()=>e.createFramebuffer(),"Unable to create WebGLFramebuffer.")}function nA(e,t,n,r,a,s,i){let o=e.getAttribLocation(t,n);return o===-1?!1:(_e(e,()=>e.bindBuffer(e.ARRAY_BUFFER,r)),_e(e,()=>e.vertexAttribPointer(o,a,e.FLOAT,!1,s,i)),_e(e,()=>e.enableVertexAttribArray(o)),!0)}function sb(e,t,n){yb(e,n),_e(e,()=>e.activeTexture(e.TEXTURE0+n)),_e(e,()=>e.bindTexture(e.TEXTURE_2D,t))}function Ez(e,t){yb(e,t),_e(e,()=>e.activeTexture(e.TEXTURE0+t)),_e(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function ib(e,t,n){return fa(e,()=>e.getUniformLocation(t,n),'uniform "'+n+'" not present in program.')}function ob(e,t,n){return e.getUniformLocation(t,n)}function lb(e,t,n,r){_e(e,()=>sb(e,t,r)),_e(e,()=>e.uniform1i(n,r))}function Cz(e){_e(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),_e(e,()=>e.viewport(0,0,e.canvas.width,e.canvas.height)),_e(e,()=>e.scissor(0,0,e.canvas.width,e.canvas.height))}function mp(e,t,n){_e(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,n)),_e(e,()=>e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,t,0))}function rA(e,t){_e(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,t)),_e(e,()=>e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,null,0))}function pc(e){let t=e.checkFramebufferStatus(e.FRAMEBUFFER);if(t!==e.FRAMEBUFFER_COMPLETE)throw new Error("Error binding framebuffer: "+ub(e,t))}function ub(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 ${t}`}}function fa(e,t,n){let r=_e(e,()=>t());if(r==null)throw new Error(n);return r}function yb(e,t){let n=e.MAX_COMBINED_TEXTURE_IMAGE_UNITS-1,r=t+e.TEXTURE0;if(r<e.TEXTURE0||r>n){let a=`[gl.TEXTURE0, gl.TEXTURE${n}]`;throw new Error(`textureUnit must be in ${a}.`)}}function ki(e,t=2){return v.sizeFromShape(e.slice(0,e.length-t))}function Ii(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 Ap(e){let t=[1,1,1];return e.length===0||e.length===1&&e[0]===1||(t=[ki(e),...Ii(e)]),t}function cb(e,t=!1){let n=J().getNumber("WEBGL_MAX_TEXTURE_SIZE");t&&(n=n*2,e=e.map((a,s)=>s>=e.length-2?v.nearestLargerEven(e[s]):e[s]),e.length===1&&(e=[2,e[0]])),e.length!==2&&(e=v.squeezeShape(e).newShape);let r=v.sizeFromShape(e);if(e.length<=1&&r<=n)return[1,r];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 a=ki(e),s=2,i=2;return e.length&&([s,i]=Ii(e)),r=a*(s/2)*(i/2),v.sizeToSquarishShape(r).map(o=>o*2)}return v.sizeToSquarishShape(r)}function gp(e){return e%2==0}function fc(e,t){if(e=e.slice(-2),t=t.slice(-2),v.arraysEqual(e,t)||!e.length||!t.length||e[0]===0||e[1]===0||t[0]===0||t[1]===0)return!0;if(e.length!==t.length){let n=e.slice(-1)[0],r=t.slice(-1)[0];if(n===r||gp(n)&&gp(r)&&(e[0]===1||t[0]===1))return!0}return e[1]===t[1]&&gp(e[0])&&gp(t[0])}var xp,wp;function hb(e){if(xp==null){let t=Gr(e);xp=t.getParameter(t.MAX_TEXTURE_SIZE)}return xp}function Rz(){xp=null}function Fz(){wp=null}function db(e){if(wp==null){let t=Gr(e);wp=t.getParameter(t.MAX_TEXTURE_IMAGE_UNITS)}return Math.min(16,wp)}function pb(e){if(e===0)return 0;let t,n=Gr(e);return er(n,"EXT_disjoint_timer_query_webgl2")&&e===2?t=2:er(n,"EXT_disjoint_timer_query")?t=1:t=0,t}function er(e,t){return e.getExtension(t)!=null}function aA(e){try{if(Gr(e)!=null)return!0}catch(t){return console.log("Error when getting WebGL context: ",t),!1}return!1}function fb(e){if(e===0)return!1;let t=Gr(e);if(e===1){if(!er(t,"OES_texture_float"))return!1}else if(!er(t,"EXT_color_buffer_float"))return!1;return oA(t)}function mb(e){if(e===0)return!1;let t=Gr(e);if(e===1){if(!er(t,"OES_texture_float")||!er(t,"WEBGL_color_buffer_float"))return!1}else{if(er(t,"EXT_color_buffer_float"))return oA(t);let n="EXT_color_buffer_half_float";if(er(t,n)){let r=t.getExtension(n);return Vz(t,r)}return!1}return oA(t)}function oA(e){let t=iA(e),n=e.createTexture();e.bindTexture(e.TEXTURE_2D,n);let r=1,a=1;e.texImage2D(e.TEXTURE_2D,0,t.internalFormatFloat,r,a,0,t.textureFormatFloat,t.textureTypeFloat,null);let s=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,s),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,n,0);let i=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(n),e.deleteFramebuffer(s),i}function Vz(e,t){let n=iA(e,t),r=e.createTexture();e.bindTexture(e.TEXTURE_2D,r);let a=1,s=1;e.texImage2D(e.TEXTURE_2D,0,n.internalFormatHalfFloat,a,s,0,n.textureFormatFloat,n.textureTypeHalfFloat,null);let i=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,i),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,r,0);let o=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(r),e.deleteFramebuffer(i),o}function Ab(e){return e!==2?!1:Gr(e).fenceSync!=null}function Fl(e,t){Array.isArray(e)||(e=[e]),e.forEach(n=>{n!=null&&v.assert(n.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the WebGL backend.`)})}var De=J();De.registerFlag("HAS_WEBGL",()=>De.getNumber("WEBGL_VERSION")>0);De.registerFlag("WEBGL_VERSION",()=>aA(2)?2:aA(1)?1:0);De.registerFlag("WEBGL_CHECK_NUMERICAL_PROBLEMS",()=>!1);De.registerFlag("WEBGL_BUFFER_SUPPORTED",()=>De.get("WEBGL_VERSION")===2);De.registerFlag("WEBGL_CPU_FORWARD",()=>!0);De.registerFlag("WEBGL_FORCE_F16_TEXTURES",()=>!1);De.registerFlag("WEBGL_PACK",()=>De.getBool("HAS_WEBGL"));De.registerFlag("WEBGL_PACK_NORMALIZATION",()=>De.getBool("WEBGL_PACK"));De.registerFlag("WEBGL_PACK_CLIP",()=>De.getBool("WEBGL_PACK"));De.registerFlag("WEBGL_PACK_DEPTHWISECONV",()=>!1);De.registerFlag("WEBGL_PACK_BINARY_OPERATIONS",()=>De.getBool("WEBGL_PACK"));De.registerFlag("WEBGL_PACK_UNARY_OPERATIONS",()=>De.getBool("WEBGL_PACK"));De.registerFlag("WEBGL_PACK_ARRAY_OPERATIONS",()=>De.getBool("WEBGL_PACK"));De.registerFlag("WEBGL_PACK_IMAGE_OPERATIONS",()=>De.getBool("WEBGL_PACK"));De.registerFlag("WEBGL_PACK_REDUCE",()=>De.getBool("WEBGL_PACK"));De.registerFlag("WEBGL_LAZILY_UNPACK",()=>De.getBool("WEBGL_PACK"));De.registerFlag("WEBGL_CONV_IM2COL",()=>De.getBool("WEBGL_PACK"));De.registerFlag("WEBGL_MAX_TEXTURE_SIZE",()=>hb(De.getNumber("WEBGL_VERSION")));De.registerFlag("WEBGL_MAX_TEXTURES_IN_SHADER",()=>db(De.getNumber("WEBGL_VERSION")));De.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION",()=>{let e=De.getNumber("WEBGL_VERSION");return e===0?0:pb(e)});De.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE",()=>De.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0&&!Vu.isMobile());De.registerFlag("WEBGL_RENDER_FLOAT32_CAPABLE",()=>fb(De.getNumber("WEBGL_VERSION")));De.registerFlag("WEBGL_RENDER_FLOAT32_ENABLED",()=>De.getBool("WEBGL_FORCE_F16_TEXTURES")?!1:De.getBool("WEBGL_RENDER_FLOAT32_CAPABLE"));De.registerFlag("WEBGL_DOWNLOAD_FLOAT_ENABLED",()=>mb(De.getNumber("WEBGL_VERSION")));De.registerFlag("WEBGL_FENCE_API_ENABLED",()=>Ab(De.getNumber("WEBGL_VERSION")));De.registerFlag("WEBGL_SIZE_UPLOAD_UNIFORM",()=>De.getBool("WEBGL_RENDER_FLOAT32_ENABLED")?4:0);De.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}.`)});De.registerFlag("WEBGL_FLUSH_THRESHOLD",()=>Vu.isMobile()&&De.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}.`)});function gn(){let e,t,n,r,a,s,i,o,l,u;return J().getNumber("WEBGL_VERSION")===2?(e="#version 300 es",t="in",n="out",r="in",a="texture",s="outputColor",i="out vec4 outputColor;",o=`
|
|
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",r="varying",a="texture2D",s="gl_FragColor",i="",o=`
|
|
#define isnan(value) isnan_custom(value)
|
|
bool isnan_custom(float val) {
|
|
return (val > 0. || val < 1. || val == 0.) ? false : true;
|
|
}
|
|
bvec4 isnan_custom(vec4 val) {
|
|
return bvec4(isnan(val.x), isnan(val.y), isnan(val.z), isnan(val.w));
|
|
}
|
|
`,l=`
|
|
uniform float INFINITY;
|
|
|
|
bool isinf(float val) {
|
|
return abs(val) == INFINITY;
|
|
}
|
|
bvec4 isinf(vec4 val) {
|
|
return equal(abs(val), vec4(INFINITY));
|
|
}
|
|
`,u=`
|
|
int round(float value) {
|
|
return int(floor(value + 0.5));
|
|
}
|
|
|
|
ivec4 round(vec4 value) {
|
|
return ivec4(floor(value + vec4(0.5)));
|
|
}
|
|
`),{version:e,attribute:t,varyingVs:n,varyingFs:r,texture2D:a,output:s,defineOutput:i,defineSpecialNaN:o,defineSpecialInf:l,defineRound:u}}function Si(e,t,n="index"){let r=v.computeStrides(t);return r.map((a,s)=>{let i=`int ${e[s]} = ${n} / ${a}`,o=s===r.length-1?`int ${e[s+1]} = ${n} - ${e[s]} * ${a}`:`index -= ${e[s]} * ${a}`;return`${i}; ${o};`}).join("")}function lA(e){let t=v.computeStrides(e).map(n=>n.toString());return`
|
|
int getFlatIndex(ivec3 coords) {
|
|
return coords.x * ${t[0]} + coords.y * ${t[1]} + coords.z;
|
|
}
|
|
`}var gb=`
|
|
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;
|
|
}
|
|
`,Uz=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=mc.DENSE;let t=yc(e),n=gn();this.outputShape=e,this.userCode=`
|
|
ivec3 outCoordsFromFlatIndex(int index) {
|
|
${Si(["r","c","d"],e)}
|
|
return ivec3(r, c, d);
|
|
}
|
|
|
|
void main() {
|
|
ivec2 resTexRC = ivec2(resultUV.yx *
|
|
vec2(${t[0]}, ${t[1]}));
|
|
int index = 4 * (resTexRC.x * ${t[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);
|
|
}
|
|
|
|
${n.output} = result;
|
|
}
|
|
`}},Hz=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=mc.DENSE;let t=yc(e),n=gn();this.outputShape=e,this.userCode=`
|
|
ivec3 outCoordsFromFlatIndex(int index) {
|
|
${Si(["r","c","d"],e)}
|
|
return ivec3(r, c, d);
|
|
}
|
|
|
|
void main() {
|
|
ivec2 resTexRC = ivec2(resultUV.yx *
|
|
vec2(${t[0]}, ${t[1]}));
|
|
int index = 4 * (resTexRC.x * ${t[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));
|
|
}
|
|
|
|
${n.output} = result;
|
|
}
|
|
`}},jz=class{constructor(e){this.variableNames=["A"],this.outTexUsage=tr.DOWNLOAD;let t=gn();this.outputShape=e,this.userCode=`
|
|
${gb}
|
|
|
|
void main() {
|
|
float x = getAAtOutCoords();
|
|
${t.output} = encode_float(x);
|
|
}
|
|
`}},Gz=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=tr.DOWNLOAD;let t=gn();this.outputShape=e,this.userCode=`
|
|
${gb}
|
|
|
|
void main() {
|
|
ivec3 coords = getOutputCoords();
|
|
float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));
|
|
${t.output} = encode_float(x);
|
|
}
|
|
`}},qz=class{constructor(e,t,n=!1){this.variableNames=["A"];let r=gn(),[a,s]=t;this.outputShape=e;let i="result";n&&(i="floor(result * 255. + 0.5)"),this.userCode=`
|
|
${lA(e)}
|
|
|
|
void main() {
|
|
ivec3 coords = getOutputCoords();
|
|
|
|
int flatIndex = getFlatIndex(coords);
|
|
int offset = imod(flatIndex, 4);
|
|
|
|
flatIndex = idiv(flatIndex, 4, 1.);
|
|
|
|
int r = flatIndex / ${s};
|
|
int c = imod(flatIndex, ${s});
|
|
vec2 uv = (vec2(c, r) + halfCR) / vec2(${s}.0, ${a}.0);
|
|
vec4 values = ${r.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];
|
|
}
|
|
|
|
${r.output} = vec4(${i}, 0., 0., 0.);
|
|
}
|
|
`}},Xz=class{constructor(e,t,n=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let r=gn(),[a,s]=t;this.outputShape=e;let i="",o="result";n&&(o="floor(result * 255. + 0.5)");for(let l=0;l<=1;l++)for(let u=0;u<=1;u++){let c=l*2+u;i+=`
|
|
localCoords = coords;
|
|
if(localCoords[2] + ${u} < ${e[2]}) {
|
|
localCoords[2] += ${u};
|
|
if(localCoords[1] + ${l} < ${e[1]}) {
|
|
localCoords[1] += ${l};
|
|
|
|
flatIndex = getFlatIndex(localCoords);
|
|
offset = imod(flatIndex, 4);
|
|
|
|
flatIndex = idiv(flatIndex, 4, 1.);
|
|
|
|
r = flatIndex / ${s};
|
|
c = imod(flatIndex, ${s});
|
|
uv = (vec2(c, r) + halfCR) / vec2(${s}.0, ${a}.0);
|
|
values = ${r.texture2D}(A, uv);
|
|
|
|
if(offset == 0) {
|
|
result[${c}] = values[0];
|
|
} else if(offset == 1) {
|
|
result[${c}] = values[1];
|
|
} else if(offset == 2) {
|
|
result[${c}] = values[2];
|
|
} else {
|
|
result[${c}] = values[3];
|
|
}
|
|
}
|
|
}
|
|
`}this.userCode=`
|
|
${lA(e)}
|
|
|
|
void main() {
|
|
ivec3 coords = getOutputCoords();
|
|
|
|
vec4 result = vec4(0.);
|
|
int flatIndex, r, c, offset;
|
|
ivec3 localCoords;
|
|
vec2 uv;
|
|
vec4 values;
|
|
|
|
${i}
|
|
|
|
${r.output} = ${o};
|
|
}
|
|
`}},xb={};We(xb,{bindVertexProgramAttributeStreams:()=>Tb,createBufferFromOutputTexture:()=>Rb,createFloat16MatrixTexture:()=>kb,createFloat16PackedMatrixTexture:()=>Sb,createFloat32MatrixTexture:()=>vb,createIndexBuffer:()=>_b,createPackedMatrixTexture:()=>Nb,createUnsignedBytesMatrixTexture:()=>Ib,createVertexBuffer:()=>bb,createVertexShader:()=>wb,downloadByteEncodedFloatMatrixFromOutputTexture:()=>Mb,downloadFloat32MatrixFromBuffer:()=>Fb,downloadMatrixFromPackedOutputTexture:()=>Db,downloadPackedMatrixFromBuffer:()=>$b,getInternalFormatForFloat16MatrixTexture:()=>cA,getInternalFormatForFloat16PackedMatrixTexture:()=>pA,getInternalFormatForFloat32MatrixTexture:()=>uA,getInternalFormatForPackedMatrixTexture:()=>dA,getInternalFormatForUnsignedBytesMatrixTexture:()=>hA,uploadDenseMatrixToTexture:()=>Eb,uploadPixelDataToTexture:()=>Cb});function wb(e){let t=gn(),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 Zw(e,n)}function bb(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 eb(e,t)}function _b(e){let t=new Uint16Array([0,1,2,2,1,3]);return tb(e,t)}function gc(e,t,n,r,a,s){rb(t,n);let i=nb(e),o=e.TEXTURE_2D;return _e(e,()=>e.bindTexture(o,i)),_e(e,()=>e.texParameteri(o,e.TEXTURE_WRAP_S,e.CLAMP_TO_EDGE)),_e(e,()=>e.texParameteri(o,e.TEXTURE_WRAP_T,e.CLAMP_TO_EDGE)),_e(e,()=>e.texParameteri(o,e.TEXTURE_MIN_FILTER,e.NEAREST)),_e(e,()=>e.texParameteri(o,e.TEXTURE_MAG_FILTER,e.NEAREST)),_e(e,()=>e.texImage2D(o,0,r,t,n,0,a,s,null)),_e(e,()=>e.bindTexture(e.TEXTURE_2D,null)),i}function uA(e){return e.internalFormatFloat}function vb(e,t,n,r){let[a,s]=Ac(t,n);return gc(e,a,s,uA(r),r.textureFormatFloat,e.FLOAT)}function cA(e){return e.internalFormatHalfFloat}function kb(e,t,n,r){let[a,s]=Ac(t,n);return gc(e,a,s,cA(r),r.textureFormatFloat,r.textureTypeHalfFloat)}function hA(e){return e.downloadTextureFormat}function Ib(e,t,n,r){let[a,s]=Ac(t,n);return gc(e,a,s,hA(r),e.RGBA,e.UNSIGNED_BYTE)}function dA(e){return e.internalFormatPackedFloat}function Nb(e,t,n,r){let[a,s]=Ml(t,n);return gc(e,a,s,dA(r),e.RGBA,e.FLOAT)}function pA(e){return e.internalFormatPackedHalfFloat}function Sb(e,t,n,r){let[a,s]=Ml(t,n);return gc(e,a,s,pA(r),e.RGBA,r.textureTypeHalfFloat)}function Tb(e,t,n){let r=0,a=3*4,s=3*4+2*4;return _e(e,()=>e.bindBuffer(e.ARRAY_BUFFER,n)),nA(e,t,"clipSpacePos",n,3,s,r)&&nA(e,t,"uv",n,2,s,a)}function Eb(e,t,n,r,a,s){_e(e,()=>e.bindTexture(e.TEXTURE_2D,t));let i,o,l;a instanceof Uint8Array?(i=new Uint8Array(n*r*4),o=e.UNSIGNED_BYTE,l=e.RGBA):(i=new Float32Array(n*r*4),o=e.FLOAT,l=s.internalFormatPackedFloat),i.set(a),_e(e,()=>e.texImage2D(e.TEXTURE_2D,0,l,n,r,0,e.RGBA,o,i)),_e(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function Cb(e,t,n){_e(e,()=>e.bindTexture(e.TEXTURE_2D,t)),n.data instanceof Uint8Array?_e(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,n.width,n.height,0,e.RGBA,e.UNSIGNED_BYTE,n.data)):_e(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,e.RGBA,e.UNSIGNED_BYTE,n)),_e(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function Rb(e,t,n,r){let a=e.createBuffer();_e(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,a));let s=4*4*t*n;return _e(e,()=>e.bufferData(e.PIXEL_PACK_BUFFER,s,e.STREAM_READ)),_e(e,()=>e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,0)),_e(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,null)),a}function Fb(e,t,n){let r=e,a=new Float32Array(n);return r.bindBuffer(r.PIXEL_PACK_BUFFER,t),r.getBufferSubData(r.PIXEL_PACK_BUFFER,0,a),r.bindBuffer(r.PIXEL_PACK_BUFFER,null),a}function Mb(e,t,n,r){let[a,s]=Ac(t,n),i=4,o=new Uint8Array(Dz(t*n,i));return _e(e,()=>e.readPixels(0,0,a,s,r.downloadTextureFormat,e.UNSIGNED_BYTE,o)),new Float32Array(o.buffer)}function $b(e,t,n,r,a,s,i,o){let l=e,u=new Float32Array(Oz(s,i));return l.bindBuffer(l.PIXEL_PACK_BUFFER,t),l.getBufferSubData(l.PIXEL_PACK_BUFFER,0,u),l.bindBuffer(l.PIXEL_PACK_BUFFER,null),u}function Db(e,t,n){let r=new Float32Array(t*n*4);return _e(e,()=>e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,r)),r}var bp=class{constructor(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.vertexAttrsAreBound=!1,this.itemsToPoll=[];let t=J().getNumber("WEBGL_VERSION");e!=null?(this.gl=e,yp(t,e)):this.gl=Gr(t);let n="WEBGL_color_buffer_float",r="EXT_color_buffer_half_float";if(J().getNumber("WEBGL_VERSION")===1){let a="OES_texture_float",s="OES_texture_half_float";if(this.textureFloatExtension=dc(this.gl,a),er(this.gl,s))this.textureHalfFloatExtension=dc(this.gl,s);else if(J().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),er(this.gl,r))this.colorBufferHalfFloatExtension=dc(this.gl,r);else if(J().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",er(this.gl,n))this.colorBufferFloatExtension=this.gl.getExtension(n);else if(er(this.gl,r))this.colorBufferHalfFloatExtension=this.gl.getExtension(r);else throw new Error("GL context does not support color renderable floats");this.vertexBuffer=bb(this.gl),this.indexBuffer=_b(this.gl),this.framebuffer=ab(this.gl),this.textureConfig=iA(this.gl,this.textureHalfFloatExtension)}get debug(){return J().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;_e(e,()=>e.finish()),_e(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),_e(e,()=>e.deleteFramebuffer(this.framebuffer)),_e(e,()=>e.bindBuffer(e.ARRAY_BUFFER,null)),_e(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null)),_e(e,()=>e.deleteBuffer(this.indexBuffer)),this.disposed=!0}createFloat32MatrixTexture(e,t){return this.throwIfDisposed(),vb(this.gl,e,t,this.textureConfig)}createFloat16MatrixTexture(e,t){return this.throwIfDisposed(),kb(this.gl,e,t,this.textureConfig)}createUnsignedBytesMatrixTexture(e,t){return this.throwIfDisposed(),Ib(this.gl,e,t,this.textureConfig)}uploadPixelDataToTexture(e,t){this.throwIfDisposed(),Cb(this.gl,e,t)}uploadDenseMatrixToTexture(e,t,n,r){this.throwIfDisposed(),Eb(this.gl,e,t,n,r,this.textureConfig)}createFloat16PackedMatrixTexture(e,t){return this.throwIfDisposed(),Sb(this.gl,e,t,this.textureConfig)}createPackedMatrixTexture(e,t){return this.throwIfDisposed(),Nb(this.gl,e,t,this.textureConfig)}deleteMatrixTexture(e){this.throwIfDisposed(),this.outputTexture===e&&(rA(this.gl,this.framebuffer),this.outputTexture=null),_e(this.gl,()=>this.gl.deleteTexture(e))}downloadByteEncodedFloatMatrixFromOutputTexture(e,t,n){return this.downloadMatrixDriver(e,()=>Mb(this.gl,t,n,this.textureConfig))}downloadPackedMatrixFromBuffer(e,t,n,r,a,s){return $b(this.gl,e,t,n,r,a,s,this.textureConfig)}downloadFloat32MatrixFromBuffer(e,t){return Fb(this.gl,e,t)}createBufferFromTexture(e,t,n){this.bindTextureToFrameBuffer(e);let r=Rb(this.gl,t,n,this.textureConfig);return this.unbindTextureToFrameBuffer(),r}createAndWaitForFence(){let e=this.createFence(this.gl);return this.pollFence(e)}createFence(e){let t,n;if(J().getBool("WEBGL_FENCE_API_ENABLED")){let r=e,a=r.fenceSync(r.SYNC_GPU_COMMANDS_COMPLETE,0);e.flush(),n=()=>{let s=r.clientWaitSync(a,0,0);return s===r.ALREADY_SIGNALED||s===r.CONDITION_SATISFIED},t=a}else J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(t=this.beginQuery(),this.endQuery(),n=()=>this.isQueryAvailable(t,J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))):n=()=>!0;return{query:t,isFencePassed:n}}downloadMatrixFromPackedTexture(e,t,n){return this.downloadMatrixDriver(e,()=>Db(this.gl,t,n))}createProgram(e){this.throwIfDisposed();let t=this.gl,n=Yw(t,e),r=wb(t),a=Jw(t);return _e(t,()=>t.attachShader(a,r)),_e(t,()=>t.attachShader(a,n)),Qw(t,a),this.debug&&fp(t,a),this.vertexAttrsAreBound||(this.setProgram(a),this.vertexAttrsAreBound=Tb(t,this.program,this.vertexBuffer)),a}deleteProgram(e){this.throwIfDisposed(),e===this.program&&(this.program=null),e!=null&&_e(this.gl,()=>this.gl.deleteProgram(e))}setProgram(e){this.throwIfDisposed(),this.program=e,this.program!=null&&this.debug&&fp(this.gl,this.program),_e(this.gl,()=>this.gl.useProgram(e))}getUniformLocation(e,t,n=!0){return this.throwIfDisposed(),n?ib(this.gl,e,t):ob(this.gl,e,t)}getAttributeLocation(e,t){return this.throwIfDisposed(),_e(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(),lb(this.gl,e,t,n)}setOutputMatrixTexture(e,t,n){this.setOutputMatrixTextureDriver(e,n,t)}setOutputPackedMatrixTexture(e,t,n){this.throwIfDisposed();let[r,a]=Ml(t,n);this.setOutputMatrixTextureDriver(e,r,a)}setOutputMatrixWriteRegion(e,t,n,r){this.setOutputMatrixWriteRegionDriver(n,e,r,t)}setOutputPackedMatrixWriteRegion(e,t,n,r){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")}debugValidate(){this.program!=null&&fp(this.gl,this.program),pc(this.gl)}executeProgram(){this.throwIfDisposed(),this.throwIfNoProgram();let e=this.gl;this.debug&&this.debugValidate(),_e(e,()=>e.drawElements(e.TRIANGLES,6,e.UNSIGNED_SHORT,0))}blockUntilAllProgramsCompleted(){this.throwIfDisposed(),_e(this.gl,()=>this.gl.finish())}getQueryTimerExtension(){return this.disjointQueryTimerExtension==null&&(this.disjointQueryTimerExtension=dc(this.gl,J().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(J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let n=this.gl,r=this.getQueryTimerExtensionWebGL2(),a=n.createQuery();return n.beginQuery(r.TIME_ELAPSED_EXT,a),a}let e=this.getQueryTimerExtensionWebGL1(),t=e.createQueryEXT();return e.beginQueryEXT(e.TIME_ELAPSED_EXT,t),t}endQuery(){if(J().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 v.repeatedTry(()=>this.disposed||this.isQueryAvailable(e,J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))),this.getQueryTime(e,J().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,r=this.getQueryTimerExtensionWebGL2(),a=n.getQueryParameter(e,n.QUERY_RESULT_AVAILABLE);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(r.GPU_DISJOINT_EXT)),a&&!this.disjoint}else{let n=this.getQueryTimerExtensionWebGL1(),r=n.getQueryObjectEXT(e,n.QUERY_RESULT_AVAILABLE_EXT);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(n.GPU_DISJOINT_EXT)),r&&!this.disjoint}}pollFence(e){return new Promise(t=>{this.addItemToPoll(()=>e.isFencePassed(),()=>t())})}pollItems(){let e=Kz(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)&&v.repeatedTry(()=>(this.pollItems(),this.itemsToPoll.length===0))}bindTextureToFrameBuffer(e){this.throwIfDisposed(),mp(this.gl,e,this.framebuffer),this.debug&&pc(this.gl)}unbindTextureToFrameBuffer(){this.outputTexture!=null?(mp(this.gl,this.outputTexture,this.framebuffer),this.debug&&pc(this.gl)):rA(this.gl,this.framebuffer)}downloadMatrixDriver(e,t){this.bindTextureToFrameBuffer(e);let n=t();return this.unbindTextureToFrameBuffer(),n}setOutputMatrixTextureDriver(e,t,n){this.throwIfDisposed();let r=this.gl;mp(r,e,this.framebuffer),this.debug&&pc(r),this.outputTexture=e,_e(r,()=>r.viewport(0,0,t,n)),_e(r,()=>r.scissor(0,0,t,n))}setOutputMatrixWriteRegionDriver(e,t,n,r){this.throwIfDisposed(),_e(this.gl,()=>this.gl.scissor(e,t,n,r))}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 Kz(e){let t=0;for(;t<e.length&&e[t]();++t);return t-1}var{getBroadcastDims:Ob}=R;function aP(e,t,n,r){let a=[];e.forEach(p=>{let f=v.sizeFromShape(p.shapeInfo.logicalShape);p.shapeInfo.isUniform?a.push(`uniform float ${p.name}${f>1?`[${f}]`:""};`):(a.push(`uniform sampler2D ${p.name};`),a.push(`uniform int offset${p.name};`))});let s=a.join(`
|
|
`),i=e.map(p=>Zz(p,t,r)).join(`
|
|
`),o=t.texShape,l=gn(),u=Qz(l),c,h,d=nP(l);return t.isPacked?(c=Yz(t.logicalShape,o),h=tP(l)):(c=Jz(t.logicalShape,o),h=eP(l)),r&&(d+=rP),[d,u,h,s,c,i,n].join(`
|
|
`)}function $l(e){let t=e.shapeInfo.logicalShape;switch(t.length){case 0:return sP(e);case 1:return iP(e);case 2:return oP(e);case 3:return lP(e);case 4:return uP(e);case 5:return cP(e);case 6:return hP(e);default:throw new Error(`${t.length}-D input sampling is not yet supported`)}}function zb(e){switch(e.shapeInfo.logicalShape.length){case 0:return dP(e);case 1:return pP(e);case 2:return fP(e);case 3:return mP(e);default:return AP(e)}}function Zz(e,t,n=!1){let r="";n?r+=zb(e):r+=$l(e);let a=e.shapeInfo.logicalShape,s=t.logicalShape;return a.length<=s.length&&(n?r+=yP(e,t):r+=gP(e,t)),r}function Yz(e,t){switch(e.length){case 0:return Pb();case 1:return xP(e,t);case 2:return _P(e,t);case 3:return wP(e,t);default:return bP(e,t)}}function Jz(e,t){switch(e.length){case 0:return Pb();case 1:return vP(e,t);case 2:return TP(e,t);case 3:return kP(e,t);case 4:return IP(e,t);case 5:return NP(e,t);case 6:return SP(e,t);default:throw new Error(`${e.length}-D output sampling is not yet supported`)}}function Qz(e){return`
|
|
float sampleTexture(sampler2D textureSampler, vec2 uv) {
|
|
return ${e.texture2D}(textureSampler, uv).r;
|
|
}
|
|
`}function eP(e){return`
|
|
void setOutput(float val) {
|
|
${e.output} = vec4(val, 0, 0, 0);
|
|
}
|
|
`}function tP(e){return`
|
|
void setOutput(vec4 val) {
|
|
${e.output} = val;
|
|
}
|
|
`}function nP(e){return`${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);
|
|
}
|
|
|
|
${EP}
|
|
${CP}
|
|
${RP}
|
|
`}var EP=`
|
|
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);
|
|
}
|
|
`,CP=`
|
|
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);
|
|
}
|
|
`,RP=`
|
|
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);
|
|
}
|
|
`,rP=`
|
|
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 Pb(){return`
|
|
int getOutputCoords() {
|
|
return 0;
|
|
}
|
|
`}function xP(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];return n[0]===1?`
|
|
int getOutputCoords() {
|
|
return 2 * int(resultUV.x * ${n[1]}.0);
|
|
}
|
|
`:n[1]===1?`
|
|
int getOutputCoords() {
|
|
return 2 * int(resultUV.y * ${n[0]}.0);
|
|
}
|
|
`:`
|
|
int getOutputCoords() {
|
|
ivec2 resTexRC = ivec2(resultUV.yx *
|
|
vec2(${n[0]}, ${n[1]}));
|
|
return 2 * (resTexRC.x * ${n[1]} + resTexRC.y);
|
|
}
|
|
`}function vP(e,t){return t[0]===1?`
|
|
int getOutputCoords() {
|
|
return int(resultUV.x * ${t[1]}.0);
|
|
}
|
|
`:t[1]===1?`
|
|
int getOutputCoords() {
|
|
return int(resultUV.y * ${t[0]}.0);
|
|
}
|
|
`:`
|
|
int getOutputCoords() {
|
|
ivec2 resTexRC = ivec2(resultUV.yx *
|
|
vec2(${t[0]}, ${t[1]}));
|
|
return resTexRC.x * ${t[1]} + resTexRC.y;
|
|
}
|
|
`}function wP(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[2]/2),a=r*Math.ceil(e[1]/2);return`
|
|
ivec3 getOutputCoords() {
|
|
ivec2 resTexRC = ivec2(resultUV.yx *
|
|
vec2(${n[0]}, ${n[1]}));
|
|
int index = resTexRC.x * ${n[1]} + resTexRC.y;
|
|
|
|
int b = index / ${a};
|
|
index -= b * ${a};
|
|
|
|
int r = 2 * (index / ${r});
|
|
int c = imod(index, ${r}) * 2;
|
|
|
|
return ivec3(b, r, c);
|
|
}
|
|
`}function kP(e,t){let n=Si(["r","c","d"],e);return`
|
|
ivec3 getOutputCoords() {
|
|
ivec2 resTexRC = ivec2(resultUV.yx *
|
|
vec2(${t[0]}, ${t[1]}));
|
|
int index = resTexRC.x * ${t[1]} + resTexRC.y;
|
|
${n}
|
|
return ivec3(r, c, d);
|
|
}
|
|
`}function bP(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[e.length-1]/2),a=r*Math.ceil(e[e.length-2]/2),s=a,i="",o="b, r, c";for(let l=2;l<e.length-1;l++)s*=e[e.length-l-1],i=`
|
|
int b${l} = index / ${s};
|
|
index -= b${l} * ${s};
|
|
`+i,o=`b${l}, `+o;return`
|
|
ivec${e.length} getOutputCoords() {
|
|
ivec2 resTexRC = ivec2(resultUV.yx *
|
|
vec2(${n[0]}, ${n[1]}));
|
|
int index = resTexRC.x * ${n[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}(${o});
|
|
}
|
|
`}function IP(e,t){let n=Si(["r","c","d","d2"],e);return`
|
|
ivec4 getOutputCoords() {
|
|
ivec2 resTexRC = ivec2(resultUV.yx *
|
|
vec2(${t[0]}, ${t[1]}));
|
|
int index = resTexRC.x * ${t[1]} + resTexRC.y;
|
|
${n}
|
|
return ivec4(r, c, d, d2);
|
|
}
|
|
`}function NP(e,t){let n=Si(["r","c","d","d2","d3"],e);return`
|
|
ivec5 getOutputCoords() {
|
|
ivec2 resTexRC = ivec2(resultUV.yx * vec2(${t[0]},
|
|
${t[1]}));
|
|
|
|
int index = resTexRC.x * ${t[1]} + resTexRC.y;
|
|
|
|
${n}
|
|
|
|
ivec5 outShape = ivec5(r, c, d, d2, d3);
|
|
return outShape;
|
|
}
|
|
`}function SP(e,t){let n=Si(["r","c","d","d2","d3","d4"],e);return`
|
|
ivec6 getOutputCoords() {
|
|
ivec2 resTexRC = ivec2(resultUV.yx *
|
|
vec2(${t[0]}, ${t[1]}));
|
|
int index = resTexRC.x * ${t[1]} + resTexRC.y;
|
|
|
|
${n}
|
|
|
|
ivec6 result = ivec6(r, c, d, d2, d3, d4);
|
|
return result;
|
|
}
|
|
`}function _P(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(v.arraysEqual(e,t))return`
|
|
ivec2 getOutputCoords() {
|
|
return 2 * ivec2(resultUV.yx * vec2(${n[0]}, ${n[1]}));
|
|
}
|
|
`;let r=Math.ceil(e[1]/2);return`
|
|
ivec2 getOutputCoords() {
|
|
ivec2 resTexRC = ivec2(resultUV.yx *
|
|
vec2(${n[0]}, ${n[1]}));
|
|
|
|
int index = resTexRC.x * ${n[1]} + resTexRC.y;
|
|
int r = 2 * (index / ${r});
|
|
int c = imod(index, ${r}) * 2;
|
|
|
|
return ivec2(r, c);
|
|
}
|
|
`}function TP(e,t){return v.arraysEqual(e,t)?`
|
|
ivec2 getOutputCoords() {
|
|
return ivec2(resultUV.yx * vec2(${t[0]}, ${t[1]}));
|
|
}
|
|
`:e[1]===1?`
|
|
ivec2 getOutputCoords() {
|
|
ivec2 resTexRC = ivec2(resultUV.yx *
|
|
vec2(${t[0]}, ${t[1]}));
|
|
int index = resTexRC.x * ${t[1]} + resTexRC.y;
|
|
return ivec2(index, 0);
|
|
}
|
|
`:e[0]===1?`
|
|
ivec2 getOutputCoords() {
|
|
ivec2 resTexRC = ivec2(resultUV.yx *
|
|
vec2(${t[0]}, ${t[1]}));
|
|
int index = resTexRC.x * ${t[1]} + resTexRC.y;
|
|
return ivec2(0, index);
|
|
}
|
|
`:`
|
|
ivec2 getOutputCoords() {
|
|
ivec2 resTexRC = ivec2(resultUV.yx *
|
|
vec2(${t[0]}, ${t[1]}));
|
|
int index = resTexRC.x * ${t[1]} + resTexRC.y;
|
|
int r = index / ${e[1]};
|
|
int c = index - r * ${e[1]};
|
|
return ivec2(r, c);
|
|
}
|
|
`}function Ti(e){return`offset${e}`}function dP(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),r=gn();return`
|
|
vec4 ${n}() {
|
|
return ${r.texture2D}(${t}, halfCR);
|
|
}
|
|
`}function sP(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1);if(e.shapeInfo.isUniform)return`float ${n}() {return ${t};}`;let[r,a]=e.shapeInfo.texShape;if(r===1&&a===1)return`
|
|
float ${n}() {
|
|
return sampleTexture(${t}, halfCR);
|
|
}
|
|
`;let[s,i]=e.shapeInfo.texShape,o=Ti(t);return`
|
|
float ${n}() {
|
|
vec2 uv = uvFromFlat(${s}, ${i}, ${o});
|
|
return sampleTexture(${t}, uv);
|
|
}
|
|
`}function pP(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),r=e.shapeInfo.texShape,a=[Math.ceil(r[0]/2),Math.ceil(r[1]/2)],s=gn();return`
|
|
vec4 ${n}(int index) {
|
|
vec2 uv = packedUVfrom1D(
|
|
${a[0]}, ${a[1]}, index);
|
|
return ${s.texture2D}(${t}, uv);
|
|
}
|
|
`}function iP(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1);if(e.shapeInfo.isUniform)return`
|
|
float ${n}(int index) {
|
|
${Dl(e)}
|
|
}
|
|
`;let r=e.shapeInfo.texShape,a=r[0],s=r[1];if(s===1&&a===1)return`
|
|
float ${n}(int index) {
|
|
return sampleTexture(${t}, halfCR);
|
|
}
|
|
`;let i=Ti(t);return s===1?`
|
|
float ${n}(int index) {
|
|
vec2 uv = vec2(0.5, (float(index + ${i}) + 0.5) / ${a}.0);
|
|
return sampleTexture(${t}, uv);
|
|
}
|
|
`:a===1?`
|
|
float ${n}(int index) {
|
|
vec2 uv = vec2((float(index + ${i}) + 0.5) / ${s}.0, 0.5);
|
|
return sampleTexture(${t}, uv);
|
|
}
|
|
`:`
|
|
float ${n}(int index) {
|
|
vec2 uv = uvFromFlat(${a}, ${s}, index + ${i});
|
|
return sampleTexture(${t}, uv);
|
|
}
|
|
`}function fP(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape,s=a[0],i=a[1],o=gn();if(a!=null&&v.arraysEqual(t,a))return`
|
|
vec4 ${r}(int row, int col) {
|
|
vec2 uv = (vec2(col, row) + halfCR) / vec2(${i}.0, ${s}.0);
|
|
|
|
return ${o.texture2D}(${n}, uv);
|
|
}
|
|
`;let l=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)],u=Math.ceil(t[1]/2);return`
|
|
vec4 ${r}(int row, int col) {
|
|
vec2 uv = packedUVfrom2D(${u}, ${l[0]}, ${l[1]}, row, col);
|
|
return ${o.texture2D}(${n}, uv);
|
|
}
|
|
`}function oP(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape;if(a!=null&&v.arraysEqual(t,a)){let h=a[0],d=a[1];return`
|
|
float ${r}(int row, int col) {
|
|
vec2 uv = (vec2(col, row) + halfCR) / vec2(${d}.0, ${h}.0);
|
|
return sampleTexture(${n}, uv);
|
|
}
|
|
`}let{newShape:s,keptDims:i}=v.squeezeShape(t),o=s;if(o.length<t.length){let h=Ol(e,o),d=["row","col"];return`
|
|
${$l(h)}
|
|
float ${r}(int row, int col) {
|
|
return ${r}(${zl(d,i)});
|
|
}
|
|
`}if(e.shapeInfo.isUniform)return`
|
|
float ${r}(int row, int col) {
|
|
int index = round(dot(vec2(row, col), vec2(${t[1]}, 1)));
|
|
${Dl(e)}
|
|
}
|
|
`;let l=a[0],u=a[1],c=Ti(n);return u===1?`
|
|
float ${r}(int row, int col) {
|
|
float index = dot(vec3(row, col, ${c}), vec3(${t[1]}, 1, 1));
|
|
vec2 uv = vec2(0.5, (index + 0.5) / ${l}.0);
|
|
return sampleTexture(${n}, uv);
|
|
}
|
|
`:l===1?`
|
|
float ${r}(int row, int col) {
|
|
float index = dot(vec3(row, col, ${c}), vec3(${t[1]}, 1, 1));
|
|
vec2 uv = vec2((index + 0.5) / ${u}.0, 0.5);
|
|
return sampleTexture(${n}, uv);
|
|
}
|
|
`:`
|
|
float ${r}(int row, int col) {
|
|
// Explicitly use integer operations as dot() only works on floats.
|
|
int index = row * ${t[1]} + col + ${c};
|
|
vec2 uv = uvFromFlat(${l}, ${u}, index);
|
|
return sampleTexture(${n}, uv);
|
|
}
|
|
`}function mP(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape,s=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)];if(t[0]===1){let h=t.slice(1),d=[1,2],p=Ol(e,h),f=["b","row","col"];return`
|
|
${zb(p)}
|
|
vec4 ${r}(int b, int row, int col) {
|
|
return ${r}(${zl(f,d)});
|
|
}
|
|
`}let i=s[0],o=s[1],l=Math.ceil(t[2]/2),u=l*Math.ceil(t[1]/2),c=gn();return`
|
|
vec4 ${r}(int b, int row, int col) {
|
|
vec2 uv = packedUVfrom3D(
|
|
${i}, ${o}, ${u}, ${l}, b, row, col);
|
|
return ${c.texture2D}(${n}, uv);
|
|
}
|
|
`}function lP(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[1]*t[2],s=t[2],{newShape:i,keptDims:o}=v.squeezeShape(t),l=i;if(l.length<t.length){let f=Ol(e,l),m=["row","col","depth"];return`
|
|
${$l(f)}
|
|
float ${r}(int row, int col, int depth) {
|
|
return ${r}(${zl(m,o)});
|
|
}
|
|
`}if(e.shapeInfo.isUniform)return`
|
|
float ${r}(int row, int col, int depth) {
|
|
int index = round(dot(vec3(row, col, depth),
|
|
vec3(${a}, ${s}, 1)));
|
|
${Dl(e)}
|
|
}
|
|
`;let u=e.shapeInfo.texShape,c=u[0],h=u[1],d=e.shapeInfo.flatOffset;if(h===a&&d==null)return`
|
|
float ${r}(int row, int col, int depth) {
|
|
float texR = float(row);
|
|
float texC = dot(vec2(col, depth), vec2(${s}, 1));
|
|
vec2 uv = (vec2(texC, texR) + halfCR) /
|
|
vec2(${h}.0, ${c}.0);
|
|
return sampleTexture(${n}, uv);
|
|
}
|
|
`;if(h===s&&d==null)return`
|
|
float ${r}(int row, int col, int depth) {
|
|
float texR = dot(vec2(row, col), vec2(${t[1]}, 1));
|
|
float texC = float(depth);
|
|
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${h}.0, ${c}.0);
|
|
return sampleTexture(${n}, uv);
|
|
}
|
|
`;let p=Ti(n);return`
|
|
float ${r}(int row, int col, int depth) {
|
|
// Explicitly use integer operations as dot() only works on floats.
|
|
int index = row * ${a} + col * ${s} + depth + ${p};
|
|
vec2 uv = uvFromFlat(${c}, ${h}, index);
|
|
return sampleTexture(${n}, uv);
|
|
}
|
|
`}function AP(e){let t=e.shapeInfo.logicalShape,n=t.length,r=e.name,a="get"+r.charAt(0).toUpperCase()+r.slice(1),s=e.shapeInfo.texShape,i=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)],o=i[0],l=i[1],u=Math.ceil(t[n-1]/2),c=u*Math.ceil(t[n-2]/2),h="int b, int row, int col",d=`b * ${c} + (row / 2) * ${u} + (col / 2)`;for(let f=2;f<n-1;f++)h=`int b${f}, `+h,c*=t[n-f-1],d=`b${f} * ${c} + `+d;let p=gn();return`
|
|
vec4 ${a}(${h}) {
|
|
int index = ${d};
|
|
int texR = index / ${l};
|
|
int texC = index - texR * ${l};
|
|
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${l}, ${o});
|
|
return ${p.texture2D}(${r}, uv);
|
|
}
|
|
`}function uP(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[3],s=t[2]*a,i=t[1]*s,{newShape:o,keptDims:l}=v.squeezeShape(t);if(o.length<t.length){let f=Ol(e,o),m=["row","col","depth","depth2"];return`
|
|
${$l(f)}
|
|
float ${r}(int row, int col, int depth, int depth2) {
|
|
return ${r}(${zl(m,l)});
|
|
}
|
|
`}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}, ${s}, ${a}, 1)));
|
|
${Dl(e)}
|
|
}
|
|
`;let u=e.shapeInfo.flatOffset,c=e.shapeInfo.texShape,h=c[0],d=c[1];if(d===i&&u==null)return`
|
|
float ${r}(int row, int col, int depth, int depth2) {
|
|
float texR = float(row);
|
|
float texC =
|
|
dot(vec3(col, depth, depth2),
|
|
vec3(${s}, ${a}, 1));
|
|
vec2 uv = (vec2(texC, texR) + halfCR) /
|
|
vec2(${d}.0, ${h}.0);
|
|
return sampleTexture(${n}, uv);
|
|
}
|
|
`;if(d===a&&u==null)return`
|
|
float ${r}(int row, int col, int depth, int depth2) {
|
|
float texR = dot(vec3(row, col, depth),
|
|
vec3(${t[1]*t[2]}, ${t[2]}, 1));
|
|
float texC = float(depth2);
|
|
vec2 uv = (vec2(texC, texR) + halfCR) /
|
|
vec2(${d}.0, ${h}.0);
|
|
return sampleTexture(${n}, uv);
|
|
}
|
|
`;let p=Ti(n);return`
|
|
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 * ${s} +
|
|
depth * ${a} + depth2;
|
|
vec2 uv = uvFromFlat(${h}, ${d}, index + ${p});
|
|
return sampleTexture(${n}, uv);
|
|
}
|
|
`}function cP(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[4],s=t[3]*a,i=t[2]*s,o=t[1]*i,{newShape:l,keptDims:u}=v.squeezeShape(t);if(l.length<t.length){let m=Ol(e,l),A=["row","col","depth","depth2","depth3"];return`
|
|
${$l(m)}
|
|
float ${r}(int row, int col, int depth, int depth2, int depth3) {
|
|
return ${r}(${zl(A,u)});
|
|
}
|
|
`}if(e.shapeInfo.isUniform)return`
|
|
float ${r}(int row, int col, int depth, int depth2, int depth3) {
|
|
float index = dot(
|
|
vec4(row, col, depth, depth2),
|
|
vec4(${o}, ${i}, ${s}, ${a})) +
|
|
depth3;
|
|
${Dl(e)}
|
|
}
|
|
`;let c=e.shapeInfo.flatOffset,h=e.shapeInfo.texShape,d=h[0],p=h[1];if(p===o&&c==null)return`
|
|
float ${r}(int row, int col, int depth, int depth2, int depth3) {
|
|
int texR = row;
|
|
float texC = dot(vec4(col, depth, depth2, depth3),
|
|
vec4(${i}, ${s}, ${a}, 1));
|
|
vec2 uv = (vec2(texC, texR) + halfCR) /
|
|
vec2(${p}.0, ${d}.0);
|
|
return sampleTexture(${n}, uv);
|
|
}
|
|
`;if(p===a&&c==null)return`
|
|
float ${r}(int row, int col, int depth, int depth2, int depth3) {
|
|
float texR = dot(
|
|
vec4(row, col, depth, depth2),
|
|
vec4(${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, ${d}.0);
|
|
return sampleTexture(${n}, uv);
|
|
}
|
|
`;let f=Ti(n);return`
|
|
float ${r}(int row, int col, int depth, int depth2, int depth3) {
|
|
// Explicitly use integer operations as dot() only works on floats.
|
|
int index = row * ${o} + col * ${i} + depth * ${s} +
|
|
depth2 * ${a} + depth3 + ${f};
|
|
vec2 uv = uvFromFlat(${d}, ${p}, index);
|
|
return sampleTexture(${n}, uv);
|
|
}
|
|
`}function hP(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),{newShape:a,keptDims:s}=v.squeezeShape(t);if(a.length<t.length){let A=Ol(e,a),y=["row","col","depth","depth2","depth3","depth4"];return`
|
|
${$l(A)}
|
|
float ${r}(int row, int col, int depth,
|
|
int depth2, int depth3, int depth4) {
|
|
return ${r}(${zl(y,s)});
|
|
}
|
|
`}let i=t[5],o=t[4]*i,l=t[3]*o,u=t[2]*l,c=t[1]*u;if(e.shapeInfo.isUniform)return`
|
|
float ${r}(int row, int col, int depth,
|
|
int depth2, int depth3, int depth4) {
|
|
int index = round(dot(
|
|
vec4(row, col, depth, depth2),
|
|
vec4(${c}, ${u}, ${l}, ${o})) +
|
|
dot(
|
|
vec2(depth3, depth4),
|
|
vec2(${i}, 1)));
|
|
${Dl(e)}
|
|
}
|
|
`;let h=e.shapeInfo.flatOffset,d=e.shapeInfo.texShape,p=d[0],f=d[1];if(f===c&&h==null)return`
|
|
float ${r}(int row, int col, int depth,
|
|
int depth2, int depth3, int depth4) {
|
|
int texR = row;
|
|
float texC = dot(vec4(col, depth, depth2, depth3),
|
|
vec4(${u}, ${l}, ${o}, ${i})) +
|
|
float(depth4);
|
|
vec2 uv = (vec2(texC, texR) + halfCR) /
|
|
vec2(${f}.0, ${p}.0);
|
|
return sampleTexture(${n}, uv);
|
|
}
|
|
`;if(f===i&&h==null)return`
|
|
float ${r}(int row, int col, int depth,
|
|
int depth2, int depth3, int depth4) {
|
|
float texR = dot(vec4(row, col, depth, depth2),
|
|
vec4(${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 ${r}(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 * ${o} + depth3 * ${i} + depth4 + ${m};
|
|
vec2 uv = uvFromFlat(${p}, ${f}, index);
|
|
return sampleTexture(${n}, uv);
|
|
}
|
|
`}function Dl(e){let t=e.name,n=v.sizeFromShape(e.shapeInfo.logicalShape);return n<2?`return ${t};`:`
|
|
for (int i = 0; i < ${n}; i++) {
|
|
if (i == index) {
|
|
return ${t}[i];
|
|
}
|
|
}
|
|
`}function yP(e,t){let n=e.name,r=n.charAt(0).toUpperCase()+n.slice(1),a="get"+r+"AtOutCoords",s=e.shapeInfo.logicalShape.length,i=t.logicalShape.length,o=Ob(e.shapeInfo.logicalShape,t.logicalShape),l=dt(i),u=i-s,c,h=["x","y","z","w","u","v"];s===0?c="":i<2&&o.length>=1?c="coords = 0;":c=o.map(A=>`coords.${h[A+u]} = 0;`).join(`
|
|
`);let d="";i<2&&s>0?d="coords":d=e.shapeInfo.logicalShape.map((A,y)=>`coords.${h[y+u]}`).join(", ");let p="return outputValue;",f=v.sizeFromShape(e.shapeInfo.logicalShape)===1,m=v.sizeFromShape(t.logicalShape)===1;if(s===1&&!f&&!m)p=`
|
|
return vec4(outputValue.xy, outputValue.xy);
|
|
`;else if(f&&!m)i===1?p=`
|
|
return vec4(outputValue.x, outputValue.x, 0., 0.);
|
|
`:p=`
|
|
return vec4(outputValue.x);
|
|
`;else if(o.length){let A=s-2,y=s-1;o.indexOf(A)>-1&&o.indexOf(y)>-1?p="return vec4(outputValue.x);":o.indexOf(A)>-1?p="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":o.indexOf(y)>-1&&(p="return vec4(outputValue.xx, outputValue.zz);")}return`
|
|
vec4 ${a}() {
|
|
${l} coords = getOutputCoords();
|
|
${c}
|
|
vec4 outputValue = get${r}(${d});
|
|
${p}
|
|
}
|
|
`}function gP(e,t){let n=e.name,r=n.charAt(0).toUpperCase()+n.slice(1),a="get"+r+"AtOutCoords",s=t.texShape,i=e.shapeInfo.texShape,o=e.shapeInfo.logicalShape.length,l=t.logicalShape.length;if(!e.shapeInfo.isUniform&&o===l&&e.shapeInfo.flatOffset==null&&v.arraysEqual(i,s))return`
|
|
float ${a}() {
|
|
return sampleTexture(${n}, resultUV);
|
|
}
|
|
`;let u=dt(l),c=Ob(e.shapeInfo.logicalShape,t.logicalShape),h=l-o,d,p=["x","y","z","w","u","v"];o===0?d="":l<2&&c.length>=1?d="coords = 0;":d=c.map(m=>`coords.${p[m+h]} = 0;`).join(`
|
|
`);let f="";return l<2&&o>0?f="coords":f=e.shapeInfo.logicalShape.map((m,A)=>`coords.${p[A+h]}`).join(", "),`
|
|
float ${a}() {
|
|
${u} coords = getOutputCoords();
|
|
${d}
|
|
return get${r}(${f});
|
|
}
|
|
`}function dt(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 ${e} is not yet supported`)}function Ol(e,t){let n=JSON.parse(JSON.stringify(e));return n.shapeInfo.logicalShape=t,n}function zl(e,t){return t.map(n=>e[n]).join(", ")}function FP(e,t,n,r){let a=t.userCode,s=n.map((p,f)=>{let m={logicalShape:p.shape,texShape:p.isUniform?null:p.texData.texShape,isUniform:p.isUniform,isPacked:p.isUniform?!1:p.texData.isPacked,flatOffset:null};return p.texData!=null&&p.texData.slice!=null&&p.texData.slice.flatOffset>0&&(m.flatOffset=p.texData.slice.flatOffset),{name:t.variableNames[f],shapeInfo:m}}),i=s.map(p=>p.shapeInfo),o={logicalShape:r.shape,texShape:r.texData.texShape,isUniform:!1,isPacked:r.texData.isPacked,flatOffset:null},l=aP(s,o,a,t.packedInputs),u=e.createProgram(l),c=null,h=e.getUniformLocation(u,"NAN",!1);J().getNumber("WEBGL_VERSION")===1&&(c=e.getUniformLocation(u,"INFINITY",!1));let d={};for(let p=0;p<t.variableNames.length;p++){let f=t.variableNames[p],m=!1;d[f]=e.getUniformLocation(u,f,m),d[`offset${f}`]=e.getUniformLocation(u,`offset${f}`,m)}return{program:t,source:l,webGLProgram:u,uniformLocations:d,inShapeInfos:i,outShapeInfo:o,infLoc:c,nanLoc:h}}function Lb(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,r)=>{let a=n.logicalShape,s=t[r],i=s.shape;if(!v.arraysEqual(a,i))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${a} and ${i} must match`);if(n.isUniform&&s.isUniform)return;let o=n.texShape,l=s.isUniform?null:s.texData.texShape;if(!v.arraysEqual(o,l))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${o} and ${l} must match`)})}function MP(e,t,n,r,a){Lb(t.inShapeInfos,n),Lb([t.outShapeInfo],[r]);let s=r.texData.texture,i=r.texData.texShape;r.texData.isPacked?e.setOutputPackedMatrixTexture(s,i[0],i[1]):e.setOutputMatrixTexture(s,i[0],i[1]),e.setProgram(t.webGLProgram),J().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&e.gl.uniform1f(t.infLoc,Infinity),t.nanLoc!==null&&e.gl.uniform1f(t.nanLoc,NaN),n.forEach((o,l)=>{let u=t.program.variableNames[l],c=t.uniformLocations[u],h=t.uniformLocations[`offset${u}`];if(c!=null){if(o.isUniform){if(v.sizeFromShape(o.shape)<2)e.gl.uniform1f(c,o.uniformValues[0]);else{let d=o.uniformValues;d instanceof Float32Array||(d=new Float32Array(d)),e.gl.uniform1fv(c,d)}return}o.texData.slice!=null&&h!=null&&e.gl.uniform1i(h,o.texData.slice.flatOffset),e.setInputMatrixTexture(o.texData.texture,c,l)}}),a!=null&&a(e,t.webGLProgram),e.executeProgram()}function $P(e,t,n){let r="";t.concat(n).forEach(i=>{let o=i.texData!=null&&i.texData.slice!=null&&i.texData.slice.flatOffset>0,l=i.isUniform?"uniform":i.texData.texShape;r+=`${i.shape}_${l}_${o}`});let a=e.userCode,s=e.constructor.name;return s+="_"+r+"_"+a,s}var{addImpl:DP,bincountImpl:Wb,bincountReduceImpl:OP,ceilImpl:zP,concatImpl:PP,expImpl:LP,expm1Impl:WP,floorImpl:BP,gatherV2Impl:VP,greaterImpl:UP,lessImpl:HP,linSpaceImpl:jP,logImpl:GP,maxImpl:qP,maximumImpl:XP,minimumImpl:KP,multiplyImpl:ZP,negImpl:YP,prodImpl:JP,rangeImpl:QP,rsqrtImpl:eL,simpleAbsImpl:Bb,sliceImpl:tL,stridedSliceImpl:nL,subImpl:rL,tileImpl:aL,topKImpl:sL,transposeImpl:fA,uniqueImpl:iL}=Bm;function Vb(e,t){return["x","y","z","w","u","v"].slice(0,t).map(n=>`${e}.${n}`)}function xn(e,t){return t===1?[e]:Vb(e,t)}function oL(e,t){if(e===1)return"rc";let n="";for(let r=0;r<e;r++)n+=t[r],r<e-1&&(n+=",");return n}var hL=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=xn("rc",t),r=dt(t),a=lL(t,e,n),s=uL(t,e[e.length-1],e[e.length-2],n),i=cL(e,n);this.userCode=`
|
|
void main() {
|
|
${r} rc = getOutputCoords();
|
|
|
|
if(${a}) {
|
|
setOutput(vec4(0));
|
|
} else {
|
|
${s}
|
|
|
|
setOutput(vec4(${i}));
|
|
}
|
|
}
|
|
`}}};function dL(e,t){let n=[];for(let r=0;r<=1;r++)for(let a=0;a<=1;a++){let s=`${r===0?"r":"rp1"}, ${a===0?"c":"cp1"}`;for(let i=2;i<e;i++)s=`${t[t.length-1-i]},`+s;n.push(s)}return n}function lL(e,t,n){if(e===1)return`rc > ${t[0]}`;let r="";for(let a=e-2;a<e;a++)r+=`${n[a]} >= ${t[a]}`,a<e-1&&(r+="||");return r}function uL(e,t,n,r){if(e===1)return"";let a=r.slice(-2);return`
|
|
int r = ${a[0]};
|
|
int c = ${a[1]};
|
|
int rp1 = r + 1;
|
|
int cp1 = c + 1;
|
|
|
|
bool cEdge = cp1 >= ${t};
|
|
bool rEdge = rp1 >= ${n};
|
|
`}function cL(e,t){let n=e.length,r=dL(n,t);return n===1?`getA(rc),
|
|
rc + 1 >= ${e[0]} ? 0. : getA(rc + 1),
|
|
0, 0`:`getA(${r[0]}),
|
|
cEdge ? 0. : getA(${r[1]}),
|
|
rEdge ? 0. : getA(${r[2]}),
|
|
rEdge || cEdge ? 0. : getA(${r[3]})`}var Ub=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let n="";for(let r=0;r<4;r++){let a="thisRC = rc;";r%2==1&&(a+="thisRC.z += 1;"),r>1&&(a+="thisRC.y += 1;"),n+=`
|
|
${a}
|
|
${r>0?"if(thisRC.y < rows && thisRC.z < cols){":""}
|
|
int flatIndex = getFlatIndex(thisRC);
|
|
|
|
ivec3 inputRC = inputCoordsFromReshapedOutCoords(flatIndex);
|
|
vec2 inputRCInnerDims = vec2(float(inputRC.y),float(inputRC.z));
|
|
|
|
result[${r}] =
|
|
getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);
|
|
${r>0?"}":""}
|
|
`}this.userCode=`
|
|
${pL(t)}
|
|
${lA(e)}
|
|
|
|
void main() {
|
|
ivec3 rc = getOutputCoords();
|
|
|
|
vec4 result = vec4(0.);
|
|
|
|
ivec3 thisRC;
|
|
int rows = ${e[1]};
|
|
int cols = ${e[2]};
|
|
|
|
${n}
|
|
|
|
setOutput(result);
|
|
}
|
|
`}};function pL(e){return`
|
|
ivec3 inputCoordsFromReshapedOutCoords(int index) {
|
|
${Si(["r","c","d"],e)}
|
|
return ivec3(r, c, d);
|
|
}
|
|
`}var fL=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(e,t,n){let r=jb(t,n),a=Gb(e,r,n);a in this.freeTextures||(this.freeTextures[a]=[]),a in this.usedTextures||(this.usedTextures[a]=[]);let s=Hb(e,r,this.gpgpu.gl,this.gpgpu.textureConfig,n);if(this.freeTextures[a].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=s,this.log();let o=this.freeTextures[a].shift();return this.usedTextures[a].push(o),o}let i;return r===sn.PACKED_2X2_FLOAT32?i=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):r===sn.PACKED_2X2_FLOAT16?i=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):r===sn.UNPACKED_FLOAT32?i=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):r===sn.UNPACKED_FLOAT16?i=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):r===sn.PACKED_4X1_UNSIGNED_BYTE&&(i=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[a].push(i),this.numUsedTextures++,this._numBytesAllocated+=s,this.log(),i}releaseTexture(e,t,n,r){if(this.freeTextures==null)return;let a=jb(n,r),s=Gb(t,a,r);s in this.freeTextures||(this.freeTextures[s]=[]);let i=Hb(t,a,this.gpgpu.gl,this.gpgpu.textureConfig,r),o=J().get("WEBGL_DELETE_TEXTURE_THRESHOLD");o!==-1&&this._numBytesAllocated>o?(this.gpgpu.deleteMatrixTexture(e),this._numBytesAllocated-=i):(this.freeTextures[s].push(e),this.numFreeTextures++,this._numBytesFree+=i),this.numUsedTextures--;let l=this.usedTextures[s],u=l.indexOf(e);if(u<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l.splice(u,1),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${this.numFreeTextures} / ${this.numUsedTextures}`,`(${e})`);let t=this._numBytesFree/this._numBytesAllocated;console.log(`Bytes allocated: ${this._numBytesAllocated}`),console.log(`Bytes unused: ${this._numBytesFree} (${Math.round(100*t)}%)`)}get numBytesAllocated(){return this._numBytesAllocated}get numBytesFree(){return this._numBytesFree}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){if(this.freeTextures!=null){for(let e in this.freeTextures)this.freeTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t)});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 mL(e,t){let n=e;if(t===n.R32F)return 4;if(t===n.R16F)return 2;if(t===n.RGBA32F||t===e.RGBA)return 16;if(t===n.RGBA16F)return 8;throw new Error(`Unknown internal format ${t}`)}function Hb(e,t,n,r,a){let s=AL(t,r),i;if(a){let[l,u]=Ml(e[0],e[1]);i=l*u}else{let[l,u]=Ac(e[0],e[1]);i=l*u}let o=mL(n,s);return i*o}function AL(e,t){switch(e){case sn.PACKED_2X2_FLOAT32:return dA(t);case sn.PACKED_2X2_FLOAT16:return pA(t);case sn.UNPACKED_FLOAT32:return uA(t);case sn.UNPACKED_FLOAT16:return cA(t);case sn.PACKED_4X1_UNSIGNED_BYTE:return hA(t);default:throw new Error(`Unknown physical texture type ${e}`)}}function yL(e){return J().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?e?sn.PACKED_2X2_FLOAT32:sn.UNPACKED_FLOAT32:e?sn.PACKED_2X2_FLOAT16:sn.UNPACKED_FLOAT16}function jb(e,t){if(e===tr.UPLOAD)return sn.PACKED_2X2_FLOAT32;if(e===tr.RENDER||e==null)return yL(t);if(e===tr.DOWNLOAD||e===tr.PIXELS)return sn.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${e}`)}function Gb(e,t,n){return`${e[0]}_${e[1]}_${t}_${n}`}var qa=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.userCode=`
|
|
float unaryOperation(float x) {
|
|
${t}
|
|
}
|
|
|
|
void main() {
|
|
float x = getAAtOutCoords();
|
|
float y = unaryOperation(x);
|
|
|
|
setOutput(y);
|
|
}
|
|
`}},Ir="if (isnan(x)) return x;",gL="return x;",qb="return abs(x);",xL="return (x >= 0.0) ? x : (exp(x) - 1.0);",wL=Ir+`
|
|
return (x < 0.0) ? 0.0 : x;
|
|
`,bL=Ir+`
|
|
return (x < 0.0) ? 0.0 : min(6.0, x);
|
|
`,_p="return x;",_L="return x;",vL=`
|
|
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;
|
|
`,kL=`
|
|
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;
|
|
`,IL=`
|
|
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;
|
|
`,Pl=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.userCode=`
|
|
vec4 unaryOperation(vec4 x) {
|
|
${t}
|
|
}
|
|
|
|
void main() {
|
|
vec4 x = getAAtOutCoords();
|
|
vec4 y = unaryOperation(x);
|
|
|
|
setOutput(y);
|
|
}
|
|
`}},NL=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=e;let t=e.length,n=xn("rc",t),r=dt(t),a=oL(t,n),s=n.slice(-2),i=t<=1?"rc":`vec2(${s.join(",")})`;this.userCode=`
|
|
void main() {
|
|
${r} rc = getOutputCoords();
|
|
vec4 packedInput = getA(${a});
|
|
|
|
setOutput(getChannel(packedInput, ${i}));
|
|
}
|
|
`}},SL=Hr.whereImpl,TL=1e-7,EL=1e-4,mA={};function CL(e){return e in mA||(mA[e]={}),mA[e]}var RL=128,FL=600;function ML(){return J().global.screen==null?1024:J().global.screen.height*J().global.screen.width*window.devicePixelRatio*FL/1024/1024}var Ll=class extends fu{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.warnedAboutCPUBackend=!1,this.pendingDeletes=0,this.disposed=!1,!J().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");if(e==null){let t=Gr(J().getNumber("WEBGL_VERSION"));this.binaryCache=CL(J().getNumber("WEBGL_VERSION")),this.gpgpu=new bp(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 fL(this.gpgpu),this.numMBBeforeWarning=ML(),this.texData=new Rh(this,Pr())}nextDataId(){return Ll.nextDataId++}numDataIds(){return this.texData.numDataIds()+(this.cpuBackend?this.cpuBackend.numDataIds():0)-this.pendingDeletes}write(e,t,n){if((J().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||J().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 r={id:this.nextDataId()};return this.texData.set(r,{shape:t,dtype:n,values:e,usage:tr.UPLOAD,refCount:1}),r}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,r,a){if(J().getBool("DEBUG")&&this.checkNumericalProblems(t),r==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(e,{shape:n,dtype:r,values:t,usage:tr.UPLOAD,refCount:a})}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}readSync(e){let t=this.texData.get(e),{values:n,dtype:r,complexTensorInfos:a,slice:s,shape:i,isPacked:o}=t;if(s!=null){let h;o?h=new Pl(i,_p):h=new qa(i,_p);let d=this.runWebGLProgram(h,[{dataId:e,shape:i,dtype:r}],r),p=this.readSync(d.dataId);return this.disposeIntermediateTensorInfo(d),p}if(n!=null)return this.convertAndCacheOnCPU(e);if(r==="string")return n;let l=this.activeTimers!=null,u;l&&(u=v.now());let c;if(r==="complex64"){let h=this.readSync(a.real.dataId),d=this.readSync(a.imag.dataId);c=R.mergeRealAndImagArrays(h,d)}else c=this.getValuesFromTexture(e);return l&&(this.downloadWaitMs+=v.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:r,slice:a,dtype:s,complexTensorInfos:i,isPacked:o}=t;if(a!=null){let p;o?p=new Pl(r,_p):p=new qa(r,_p);let f=this.runWebGLProgram(p,[{dataId:e,shape:r,dtype:s}],s),m=this.read(f.dataId);return this.disposeIntermediateTensorInfo(f),m}if(n!=null)return this.convertAndCacheOnCPU(e);if(!J().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&J().getNumber("WEBGL_VERSION")===2)throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");let l=null,u;if(s!=="complex64"&&J().get("WEBGL_BUFFER_SUPPORTED")){u=this.decode(e);let p=this.texData.get(u.dataId);l=this.gpgpu.createBufferFromTexture(p.texture,...yc(r))}this.pendingRead.set(e,[]),s!=="complex64"&&await this.gpgpu.createAndWaitForFence();let c;if(s==="complex64"){let p=await Promise.all([this.read(i.real.dataId),this.read(i.imag.dataId)]),f=p[0],m=p[1];c=R.mergeRealAndImagArrays(f,m)}else if(l==null)c=this.getValuesFromTexture(e);else{let p=v.sizeFromShape(r);c=this.gpgpu.downloadFloat32MatrixFromBuffer(l,p)}u!=null&&this.disposeIntermediateTensorInfo(u);let h=this.convertAndCacheOnCPU(e,c),d=this.pendingRead.get(e);return this.pendingRead.delete(e),d.forEach(p=>p(h)),this.pendingDisposal.has(e)&&(this.pendingDisposal.delete(e),this.disposeData(e)&&Pr().removeDataId(e,this),this.pendingDeletes--),h}bufferSync(e){let t=this.readSync(e.dataId),n=t;if(e.dtype==="string")try{n=t.map(r=>v.decodeString(r))}catch(r){throw new Error("Failed to decode encoded string bytes into utf-8")}return Ue(e.shape,e.dtype,n)}checkNumericalProblems(e){if(e!=null)for(let t=0;t<e.length;t++){let n=e[t];if(!Xw(n))throw J().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 ${n} cannot be represented on this device.`)}}getValuesFromTexture(e){let{shape:t,dtype:n,isPacked:r}=this.texData.get(e),a=v.sizeFromShape(t);if(J().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let h=this.decode(e),d=this.texData.get(h.dataId),p=this.gpgpu.downloadMatrixFromPackedTexture(d.texture,...yc(t)).subarray(0,a);return this.disposeIntermediateTensorInfo(h),p}let s=J().getBool("WEBGL_PACK")&&r===!0,i=s?Ap(t):t,o=s?new Gz(i):new jz(i),l=this.runWebGLProgram(o,[{shape:i,dtype:n,dataId:e}],"float32"),u=this.texData.get(l.dataId),c=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(u.texture,u.texShape[0],u.texShape[1]).subarray(0,a);return this.disposeIntermediateTensorInfo(l),c}timerAvailable(){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}async time(e){let t=this.activeTimers,n=[],r=!1;this.programTimersStack==null?(this.programTimersStack=n,r=!0):this.activeTimers.push(n),this.activeTimers=n,e();let a=v.flatten(this.activeTimers.map(o=>o.query)).filter(o=>o!=null),s=v.flatten(this.activeTimers.map(o=>o.name)).filter(o=>o!=null);this.activeTimers=t,r&&(this.programTimersStack=null);let i={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};if(J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let o=await Promise.all(a);i.kernelMs=v.sum(o),i.getExtraProfileInfo=()=>o.map((l,u)=>({name:s[u],ms:l})).map(l=>`${l.name}: ${l.ms}`).join(", ")}else i.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,i}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:v.now(),endMs:null}}endTimer(e){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=v.now(),e)}async getQueryTime(e){if(J().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:r,usage:a,isPacked:s,slice:i}=this.texData.get(e),o=i&&i.origDataId||e,l=this.dataRefCount.get(o);l>1?this.dataRefCount.set(o,l-1):(this.dataRefCount.delete(o),t!=null&&(this.numBytesInGPU-=this.computeBytes(r,n),this.textureManager.releaseTexture(t,r,a,s)));let u=this.texData.get(e);u.texture=null,u.texShape=null,u.isPacked=!1,u.slice=null}getTexture(e){return this.uploadToGPU(e),this.texData.get(e).texture}getDataInfo(e){return this.texData.get(e)}getCPUBackend(){return J().getBool("WEBGL_CPU_FORWARD")?(this.cpuBackend==null&&(this.cpuBackend=Pr().findBackend("cpu")),this.cpuBackend):null}shouldExecuteOnCPU(e,t=RL){let n=this.getCPUBackend();return!J().getBool("IS_TEST")&&!this.warnedAboutCPUBackend&&n==null&&(console.warn("Your application contains ops that are small enough to be executed on the CPU backend, however the CPU backend cannot be found. Consider importing the CPU backend (@tensorflow/tfjs-backend-cpu) for better performance."),this.warnedAboutCPUBackend=!0),n!=null&&e.every(r=>this.texData.get(r.dataId).texture==null&&v.sizeFromShape(r.shape)<t)}getGPGPUContext(){return this.gpgpu}where(e){R.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let t=e.dataSync();return SL(e.shape,t)}packedUnaryOp(e,t,n){let r=new Pl(e.shape,t),a=this.compileAndRun(r,[e],n);return Pr().makeTensorFromDataId(a.dataId,a.shape,a.dtype)}abs(e){if(this.shouldExecuteOnCPU([e])&&e.dtype!=="complex64"){let r=Bb(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,r)}if(J().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,qb,e.dtype);let t=new qa(e.shape,qb),n=this.compileAndRun(t,[e]);return Pr().makeTensorFromDataId(n.dataId,n.shape,n.dtype)}makeTensorInfo(e,t,n){let r;if(t==="string"&&n!=null&&n.length>0&&v.isString(n[0])){let a=n.map(s=>v.encodeString(s));r=this.write(a,e,t)}else r=this.write(n,e,t);return this.texData.get(r).usage=null,{dataId:r,shape:e,dtype:t}}makeOutput(e,t,n){let{dataId:r}=this.makeTensorInfo(e,t,n);return Pr().makeTensorFromDataId(r,e,t,this)}unpackTensor(e){let t=new NL(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){let t=new hL(e.shape),n=!0;return this.runWebGLProgram(t,[e],e.dtype,null,n)}packedReshape(e,t){let n=[ki(e.shape),...Ii(e.shape)],r={dtype:e.dtype,shape:n,dataId:e.dataId},a=[ki(t),...Ii(t)],s=new Ub(a,n),i=!0,o=this.runWebGLProgram(s,[r],e.dtype,null,i);return{dataId:o.dataId,shape:t,dtype:o.dtype}}decode(e){let t=this.texData.get(e),{isPacked:n,shape:r,dtype:a}=t,s=Ap(r),i;n?i=new Hz(s):i=new Uz(s);let o=!0,l=this.runWebGLProgram(i,[{shape:s,dtype:a,dataId:e}],a,null,o);return{dtype:a,shape:r,dataId:l.dataId}}runWebGLProgram(e,t,n,r,a=!1){let s=this.makeTensorInfo(e.outputShape,n),i=this.texData.get(s.dataId);if(e.packedOutput&&(i.isPacked=!0),e.outPackingScheme===mc.DENSE){let m=yc(e.outputShape);i.texShape=m.map(A=>A*2)}if(e.outTexUsage!=null&&(i.usage=e.outTexUsage),v.sizeFromShape(s.shape)===0)return i.values=v.getTypedArrayFromDType(s.dtype,0),s;let o=[],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 A=this.texData.get(m.dataId);if(A.texture==null){if(!e.packedInputs&&v.sizeFromShape(m.shape)<=J().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:m.shape,texData:null,isUniform:!0,uniformValues:A.values};e.packedInputs&&(A.isPacked=!0,A.shape=m.shape)}else if(!!A.isPacked!=!!e.packedInputs)m=A.isPacked?this.unpackTensor(m):this.packTensor(m),o.push(m),A=this.texData.get(m.dataId);else if(A.isPacked&&!fc(A.shape,m.shape)){let y=m,g=m.shape;m.shape=A.shape,m=this.packedReshape(m,g),o.push(m),A=this.texData.get(m.dataId),y.shape=g}return this.uploadToGPU(m.dataId),{shape:m.shape,texData:A,isUniform:!1}});this.uploadToGPU(s.dataId);let u={shape:s.shape,texData:i,isUniform:!1},c=$P(e,l,u),h=this.getAndSaveBinary(c,()=>FP(this.gpgpu,e,l,u)),d=this.activeTimers!=null,p;d&&(p=this.startTimer()),MP(this.gpgpu,h,l,u,r),o.forEach(m=>this.disposeIntermediateTensorInfo(m)),d&&(p=this.endTimer(p),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(p)}));let f=J().get("WEBGL_FLUSH_THRESHOLD");if(f>0){let m=v.now();m-this.lastGlFlushTime>f&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=m)}if(!J().getBool("WEBGL_LAZILY_UNPACK")&&i.isPacked&&a===!1){let m=this.unpackTensor(s);return this.disposeIntermediateTensorInfo(s),m}return s}compileAndRun(e,t,n,r,a=!1){return n=n||t[0].dtype,this.runWebGLProgram(e,t,n,r,a)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(J().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(e=>{this.gpgpu.deleteProgram(this.binaryCache[e].webGLProgram),delete this.binaryCache[e]}),this.textureManager.dispose(),this.canvas!=null&&typeof HTMLCanvasElement!="undefined"&&this.canvas instanceof HTMLCanvasElement?this.canvas.remove():this.canvas=null,this.gpgpuCreatedLocally&&(this.gpgpu.program=null,this.gpgpu.dispose()),this.disposed=!0)}floatPrecision(){return this.floatPrecisionValue==null&&(this.floatPrecisionValue=B(()=>{if(!J().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=J().getBool("DEBUG");J().set("DEBUG",!1);let t=this.abs(Ie(1e-8)).dataSync()[0];if(J().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?TL:EL}uploadToGPU(e){let t=this.texData.get(e),{shape:n,dtype:r,values:a,texture:s,usage:i,isPacked:o}=t;if(s!=null)return;let l=this.activeTimers!=null,u;l&&(u=v.now());let c=t.texShape;if(c==null&&(c=cb(n,o),t.texShape=c),a!=null){let h=Ap(n),d,p=c[1],f=c[0],m=a instanceof Uint8Array;o?([p,f]=Ml(c[0],c[1]),d=new Xz(h,[f,p],m)):d=new qz(h,[f,p],m);let A=this.makeTensorInfo([f,p],r);m?this.texData.get(A.dataId).usage=tr.PIXELS:this.texData.get(A.dataId).usage=tr.UPLOAD,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(A.dataId),p,f,a);let y=!0,g=this.runWebGLProgram(d,[A],r,null,y),b=this.texData.get(g.dataId);t.texture=b.texture,t.texShape=b.texShape,t.isPacked=b.isPacked,t.usage=b.usage,this.disposeIntermediateTensorInfo(A),this.texData.delete(g.dataId),t.values=null,l&&(this.uploadWaitMs+=v.now()-u)}else{let h=this.acquireTexture(c,i,r,o);t.texture=h}}convertAndCacheOnCPU(e,t){let n=this.texData.get(e),{dtype:r}=n;return this.releaseGPUData(e),t!=null&&(n.values=$L(t,r)),n.values}acquireTexture(e,t,n,r){if(this.numBytesInGPU+=this.computeBytes(e,n),!this.warnedAboutMemory&&this.numBytesInGPU>this.numMBBeforeWarning*1024*1024){let a=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(`High memory usage in GPU: ${a} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(e,t,r)}computeBytes(e,t){return e[0]*e[1]*v.bytesPerElement(t)}};Ll.nextDataId=0;function $L(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 r=0;r<n.length;++r)n[r]=Math.round(e[r]);return n}else throw new Error(`Unknown dtype ${t}`)}var Xb="3.3.0";function Kb(){J().set("WEBGL_FORCE_F16_TEXTURES",!0)}Vu.isBrowser()&&fl("webgl",()=>new Ll,2);var DL={forceHalfFloat:Kb},Zb=`
|
|
if (isnan(a)) return a;
|
|
if (isnan(b)) return b;
|
|
`,Wl=class{constructor(e,t,n){this.variableNames=["A","B"],this.outputShape=R.assertAndGetBroadcastShape(t,n),this.userCode=`
|
|
float binaryOperation(float a, float b) {
|
|
${e}
|
|
}
|
|
|
|
void main() {
|
|
float a = getAAtOutCoords();
|
|
float b = getBAtOutCoords();
|
|
setOutput(binaryOperation(a, b));
|
|
}
|
|
`}},vp=`
|
|
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;
|
|
`,xc=class{constructor(e,t,n,r=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=R.assertAndGetBroadcastShape(t,n);let a=this.outputShape.length,s="";if(r)if(a===0||v.sizeFromShape(this.outputShape)===1)s=`
|
|
result.y = 0.;
|
|
result.z = 0.;
|
|
result.w = 0.;
|
|
`;else if(s=`
|
|
${dt(a)} coords = getOutputCoords();
|
|
`,a===1)s+=`
|
|
result.y = (coords + 1) >= ${this.outputShape[0]} ? 0. : result.y;
|
|
result.z = 0.;
|
|
result.w = 0.;
|
|
`;else{let i=xn("coords",a);s+=`
|
|
bool nextRowOutOfBounds =
|
|
(${i[a-2]} + 1) >= ${this.outputShape[a-2]};
|
|
bool nextColOutOfBounds =
|
|
(${i[a-1]} + 1) >= ${this.outputShape[a-1]};
|
|
result.y = nextColOutOfBounds ? 0. : result.y;
|
|
result.z = nextRowOutOfBounds ? 0. : result.z;
|
|
result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;
|
|
`}this.userCode=`
|
|
vec4 binaryOperation(vec4 a, vec4 b) {
|
|
${e}
|
|
}
|
|
|
|
void main() {
|
|
vec4 a = getAAtOutCoords();
|
|
vec4 b = getBAtOutCoords();
|
|
|
|
vec4 result = binaryOperation(a, b);
|
|
${s}
|
|
|
|
setOutput(result);
|
|
}
|
|
`}};function Bn(e){let{inputs:t,backend:n}=e,{x:r}=t;return n.incRef(r.dataId),{dataId:r.dataId,shape:r.shape,dtype:r.dtype}}var OL={kernelName:Rs,backendName:"webgl",kernelFunc:Bn};function Xa(e){let{inputs:t,backend:n}=e,{real:r,imag:a}=t,s=n.makeTensorInfo(r.shape,"complex64"),i=n.texData.get(s.dataId),o=Bn({inputs:{x:r},backend:n}),l=Bn({inputs:{x:a},backend:n});return i.complexTensorInfos={real:o,imag:l},s}var zL={kernelName:Wh,backendName:"webgl",kernelFunc:Xa},Yb="return (a < 0.) ? b * a : a;",Jb=`
|
|
vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
|
|
return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
|
|
`;function PL(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{alpha:s}=r,i=n.makeTensorInfo([],"float32",v.createScalarValue(s,"float32")),o=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new xc(Jb,a.shape,i.shape):new Wl(Yb,a.shape,i.shape),l=n.runWebGLProgram(o,[a,i],a.dtype);return n.disposeIntermediateTensorInfo(i),l}var LL={kernelName:Fs,backendName:"webgl",kernelFunc:PL},Qb="return (a < 0.) ? b * a : a;",e_=`
|
|
vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
|
|
return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
|
|
`;function WL(e){let{inputs:t,backend:n}=e,{x:r,alpha:a}=t,s=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new xc(e_,r.shape,a.shape):new Wl(Qb,r.shape,a.shape);return n.runWebGLProgram(s,[r,a],r.dtype)}var BL={kernelName:Hs,backendName:"webgl",kernelFunc:WL},t_="if (isnan(x)) return x;",VL=`
|
|
if (isnan(a)) return a;
|
|
if (isnan(b)) return b;
|
|
`,UL=`
|
|
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 Ye({opSnippet:e,packedOpSnippet:t,cpuKernelImpl:n,dtype:r}){return({inputs:a,backend:s})=>{let{x:i}=a,o=s,l=r||i.dtype;if(o.shouldExecuteOnCPU([i])&&n!=null){let h=o.texData.get(i.dataId),d=n(h.values,l);return o.makeTensorInfo(i.shape,l,d)}let u=J().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,c;return u?c=new Pl(i.shape,t):c=new qa(i.shape,e),o.runWebGLProgram(c,[i],l)}}function on({opSnippet:e,packedOpSnippet:t,checkOutOfBounds:n=!1,supportsComplex:r=!1,cpuKernelImpl:a,dtype:s}){return({inputs:i,backend:o})=>{let{a:l,b:u}=i,c=o;if(r&&l.dtype==="complex64"){let f=c.texData.get(l.dataId),m=c.texData.get(u.dataId),[A,y]=[[f.complexTensorInfos.real,m.complexTensorInfos.real],[f.complexTensorInfos.imag,m.complexTensorInfos.imag]].map(b=>{let[_,w]=b,x={dataId:_.dataId,dtype:_.dtype,shape:l.shape},N={dataId:w.dataId,dtype:w.dtype,shape:u.shape},S=new Wl(e,l.shape,u.shape);return c.runWebGLProgram(S,[x,N],lr(_.dtype,w.dtype))}),g=Xa({inputs:{real:A,imag:y},backend:c});return c.disposeIntermediateTensorInfo(A),c.disposeIntermediateTensorInfo(y),g}let h=s||lr(l.dtype,u.dtype);if(c.shouldExecuteOnCPU([l,u])&&a!=null){let f=c.texData.get(l.dataId),m=c.texData.get(u.dataId),[A,y]=a(l.shape,u.shape,f.values,m.values,h),g=c.makeTensorInfo(y,h),b=c.texData.get(g.dataId);return b.values=A,g}let d=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,p;return d?p=new xc(t,l.shape,u.shape,n):p=new Wl(e,l.shape,u.shape),c.runWebGLProgram(p,[l,u],h)}}function kp(e,t=!1){if(e==="linear")return t?_L:gL;if(e==="relu")return t?kL:wL;if(e==="elu")return t?vL:xL;if(e==="relu6")return t?IL:bL;if(e==="prelu")return t?e_:Qb;if(e==="leakyrelu")return t?Jb:Yb;throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}var n_=class{constructor(e,t,n,r=!1,a=!1,s=!1,i=null,o=!1,l=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=n;let u=r?e[1]:e[2],c=Math.ceil(u/2),h=r?"i * 2, rc.y":"rc.y, i * 2",d=a?"rc.z, i * 2":"i * 2, rc.z",p=r?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],f=a?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],m="",A="";i&&(o?m=`vec4 activation(vec4 a) {
|
|
vec4 b = getPreluActivationWeightsAtOutCoords();
|
|
${i}
|
|
}`:l?m=`vec4 activation(vec4 a) {
|
|
vec4 b = getLeakyreluAlphaAtOutCoords();
|
|
${i}
|
|
}`:m=`vec4 activation(vec4 x) {
|
|
${i}
|
|
}`,A="result = activation(result);");let y=s?"result += getBiasAtOutCoords();":"";s&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),l&&this.variableNames.push("leakyreluAlpha");let g="rc.x",b="rc.x";e[0]<t[0]?g=`int(min(float(rc.x), ${e[0]-1}.))`:t[0]<e[0]&&(b=`int(min(float(rc.x), ${t[0]-1}.))`),this.userCode=`
|
|
${m}
|
|
|
|
const float sharedDimension = ${c}.0;
|
|
|
|
vec4 dot2x2ARowBCol(ivec3 rc) {
|
|
vec4 result = vec4(0);
|
|
for (int i = 0; i < ${c}; i++) {
|
|
int batchA = ${g};
|
|
int batchB = ${b};
|
|
vec4 a = getMatrixA(batchA, ${h});
|
|
vec4 b = getMatrixB(batchB, ${d});
|
|
|
|
// These swizzled products need to be separately added.
|
|
// See: https://github.com/tensorflow/tfjs/issues/1735
|
|
result += (${p[0]} * ${f[0]});
|
|
result += (${p[1]} * ${f[1]});
|
|
}
|
|
return result;
|
|
}
|
|
|
|
void main() {
|
|
ivec3 rc = getOutputCoords();
|
|
vec4 result = dot2x2ARowBCol(rc);
|
|
|
|
${y}
|
|
|
|
${A}
|
|
|
|
setOutput(result);
|
|
}
|
|
`}},r_={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},a_=class{constructor(e,t,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=R.assertAndGetBroadcastShape(t,n),this.userCode=`
|
|
float binaryOpComplex(
|
|
float areal, float aimag, float breal, float bimag) {
|
|
${e}
|
|
}
|
|
|
|
void main() {
|
|
float areal = getARealAtOutCoords();
|
|
float aimag = getAImagAtOutCoords();
|
|
float breal = getBRealAtOutCoords();
|
|
float bimag = getBImagAtOutCoords();
|
|
setOutput(binaryOpComplex(areal, aimag, breal, bimag));
|
|
}
|
|
`}},s_="return a * b;";function i_(e){let{inputs:t,backend:n}=e,{a:r,b:a}=t,s=R.upcastType(r.dtype,a.dtype);if(r.dtype==="complex64"){let o=n.texData.get(r.dataId),l=n.texData.get(a.dataId),u=new a_(r_.REAL,r.shape,a.shape),c=new a_(r_.IMAG,r.shape,a.shape),h=[{dataId:o.complexTensorInfos.real.dataId,dtype:o.complexTensorInfos.real.dtype,shape:r.shape},{dataId:o.complexTensorInfos.imag.dataId,dtype:o.complexTensorInfos.imag.dtype,shape:r.shape},{dataId:l.complexTensorInfos.real.dataId,dtype:l.complexTensorInfos.real.dtype,shape:a.shape},{dataId:l.complexTensorInfos.imag.dataId,dtype:l.complexTensorInfos.imag.dtype,shape:a.shape}],d=n.runWebGLProgram(u,h,"float32"),p=n.runWebGLProgram(c,h,"float32"),f=Xa({inputs:{real:d,imag:p},backend:n});return n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),f}if(n.shouldExecuteOnCPU([r,a])){let o=n.texData.get(r.dataId),l=n.texData.get(a.dataId),[u,c]=ZP(r.shape,a.shape,o.values,l.values,s),h=n.makeTensorInfo(c,s),d=n.texData.get(h.dataId);return d.values=u,h}let i;return J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?i=new xc(s_,r.shape,a.shape):i=new Wl(s_,r.shape,a.shape),n.runWebGLProgram(i,[r,a],s)}var HL={kernelName:Ws,backendName:"webgl",kernelFunc:i_};function jL(e,t,n){let r=[ki(e.shape),...Ii(e.shape)],a={dtype:e.dtype,shape:r,dataId:e.dataId},s=[ki(t),...Ii(t)],i=new Ub(s,r),o=!0,l=n.runWebGLProgram(i,[a],e.dtype,null,o);return{dataId:l.dataId,shape:t,dtype:l.dtype}}function xe(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{shape:s}=r,i=n,o=v.sizeFromShape(a.shape),l=v.inferFromImplicitShape(s,o),u=v.sizeFromShape(l);v.assert(o===u,()=>`The new shape (${l}) has ${u} elements and the old shape (${a.shape}) has ${o} elements. The new shape and old shape must have the same number of elements.`);let c=i.texData.get(a.dataId);return c.isPacked&&!fc(a.shape,l)&&!(c.texture!==null&&fc(c.shape,l))?jL(a,l,i):(i.incRef(a.dataId),{dataId:a.dataId,shape:l,dtype:a.dtype})}var GL={kernelName:Ho,backendName:"webgl",kernelFunc:xe},o_=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:r,inSize:a,outSize:s}=e;this.outputShape=[r,s];let i=Math.floor(n/4)*4,o=n%4,l="sumValue += dot(values, ones);";if(t!=null){let c=1/t;l=`sumValue += dot(values * ${v.isInt(c)?c.toPrecision(2):c}, ones);`}let u="";a%n>0&&(u=`
|
|
if (inIdx < 0 || inIdx >= ${a}) {
|
|
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 < ${i}; i += 4) {
|
|
int inIdx = inOffset + i;
|
|
vec4 values = vec4(
|
|
getValue(batch, inIdx),
|
|
getValue(batch, inIdx + 1),
|
|
getValue(batch, inIdx + 2),
|
|
getValue(batch, inIdx + 3)
|
|
);
|
|
|
|
${l}
|
|
}
|
|
|
|
int inIdx = inOffset + ${i};
|
|
if (${o===1}) {
|
|
vec4 values = vec4(getValue(batch, inIdx), 0.0, 0.0, 0.0);
|
|
|
|
${l}
|
|
} else if (${o===2}) {
|
|
vec4 values = vec4(
|
|
getValue(batch, inIdx),
|
|
getValue(batch, inIdx + 1), 0.0, 0.0);
|
|
|
|
${l}
|
|
} else if (${o===3}) {
|
|
vec4 values = vec4(
|
|
getValue(batch, inIdx),
|
|
getValue(batch, inIdx + 1),
|
|
getValue(batch, inIdx + 2), 0.0);
|
|
|
|
${l}
|
|
}
|
|
setOutput(sumValue);
|
|
}
|
|
`}},qL=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:r,inSize:a,outSize:s}=e;this.outputShape=[r,s];let i="0.0",o="";t==="prod"?i="1.0":t==="min"?(i="1.0 / 1e-20",o="min"):t==="max"&&(i="-1.0 / 1e-20",o="max");let l=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="sum"?l="sumValue":t==="prod"?l="prodValue":t==="all"?l="allValue":t==="any"&&(l="anyValue");let u=Math.floor(n/4)*4,c=n%4,h=`
|
|
if (${t==="sum"}) {
|
|
sumValue += dot(values, ones);
|
|
} else if (${t==="prod"}) {
|
|
vec2 tmp = vec2(values[0], values[1]) * vec2(values[2], values[3]);
|
|
prodValue *= tmp[0] * tmp[1];
|
|
} else {
|
|
minMaxValue = ${o}(values, minMaxValue);
|
|
}
|
|
`,d="vec4";t==="all"?(i="1.0",h=`
|
|
bool reducedAllValue = all(values);
|
|
float floatedReducedAllValue = float(reducedAllValue);
|
|
allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0);
|
|
`,d="bvec4"):t==="any"&&(i="0.0",h=`
|
|
bool reducedAnyValue = any(values);
|
|
float floatedReducedAnyValue = float(reducedAnyValue);
|
|
anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);
|
|
`,d="bvec4");let p="";a%n>0&&(p=`
|
|
if (inIdx < 0 || inIdx >= ${a}) {
|
|
return initializationValue;
|
|
}
|
|
`),this.userCode=`
|
|
const float initializationValue = ${i};
|
|
const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
|
|
|
|
float getValue(int batch, int inIdx) {
|
|
${p}
|
|
return getX(batch, inIdx);
|
|
}
|
|
|
|
void main() {
|
|
ivec2 coords = getOutputCoords();
|
|
int batch = coords[0];
|
|
int outIdx = coords[1];
|
|
int inOffset = outIdx * ${n};
|
|
|
|
vec4 minMaxValue = vec4(${i});
|
|
float prodValue = 1.0;
|
|
float sumValue = 0.0;
|
|
float allValue = 1.0;
|
|
float anyValue = 0.0;
|
|
|
|
for (int i = 0; i < ${u}; i += 4) {
|
|
int inIdx = inOffset + i;
|
|
${d} values = ${d}(
|
|
getValue(batch, inIdx),
|
|
getValue(batch, inIdx + 1),
|
|
getValue(batch, inIdx + 2),
|
|
getValue(batch, inIdx + 3)
|
|
);
|
|
|
|
${h}
|
|
}
|
|
|
|
int inIdx = inOffset + ${u};
|
|
if (${c===1}) {
|
|
${d} values = ${d}(
|
|
getValue(batch, inIdx),
|
|
initializationValue,
|
|
initializationValue,
|
|
initializationValue
|
|
);
|
|
|
|
${h}
|
|
} else if (${c===2}) {
|
|
${d} values = ${d}(
|
|
getValue(batch, inIdx),
|
|
getValue(batch, inIdx + 1),
|
|
initializationValue,
|
|
initializationValue
|
|
);
|
|
|
|
${h}
|
|
} else if (${c===3}) {
|
|
${d} values = ${d}(
|
|
getValue(batch, inIdx),
|
|
getValue(batch, inIdx + 1),
|
|
getValue(batch, inIdx + 2),
|
|
initializationValue
|
|
);
|
|
|
|
${h}
|
|
}
|
|
setOutput(${l});
|
|
}
|
|
`}};function XL(e){let t=[];for(;t.length===0||t[t.length-1].outSize!==1;){let n=t.length?t[t.length-1].outSize:e[1],r=R.computeOptimalWindowSize(n);t.push({inSize:n,windowSize:r,outSize:Math.ceil(n/r)})}return t}function Ei(e,t,n,r){let a=XL(e.shape),s=e;for(let i=0;i<a.length;i++){let{inSize:o,windowSize:l,outSize:u}=a[i],c,h;n==="mean"?c=i===0?new o_({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u},o):new o_({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u}):c=new qL({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u},n),h=s,s=r.runWebGLProgram(c,[s],t),h.dataId!==e.dataId&&r.disposeIntermediateTensorInfo(h)}return s}var ZL=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[t[s]];this.outputShape=n,this.rank=n.length;let r=dt(this.rank),a=KL(t);this.userCode=`
|
|
void main() {
|
|
${r} resRC = getOutputCoords();
|
|
setOutput(getA(${a}));
|
|
}
|
|
`}};function KL(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"],r=new Array(t);for(let a=0;a<e.length;a++)r[e[a]]=n[a];return r.join()}var YL=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 ${this.rank} is not yet supported.`);let r=dt(this.rank),a=Vb("rc",this.rank),s=new Array(this.rank);for(let u=0;u<t.length;u++)s[t[u]]=a[u];let i=`vec2(${s.slice(-2).join()})`,o=`++${a[this.rank-1]} < ${n[this.rank-1]}`,l=`getChannel(getA(${s.join()}), ${i})`;this.userCode=`
|
|
void main() {
|
|
${r} rc = getOutputCoords();
|
|
vec4 result = vec4(0.);
|
|
result[0] = ${l};
|
|
if(${o}) {
|
|
result[1] = ${l};
|
|
}
|
|
--${a[this.rank-1]};
|
|
if(++${a[this.rank-2]} < ${n[this.rank-2]}) {
|
|
result[2] = ${l};
|
|
if(${o}) {
|
|
result[3] = ${l};
|
|
}
|
|
}
|
|
setOutput(result);
|
|
}
|
|
`}};function Ip(e,t,n){let r=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new YL(e.shape,t):new ZL(e.shape,t);return n.runWebGLProgram(r,[e],e.dtype)}function JL(e,t,n,r){let a=t,s=e.shape.length,i=v.parseAxisParam(a,e.shape),o=i,l=R.getAxesPermutation(o,s),u=l!=null,c=e;u&&(c=Ip(e,l,r),o=R.getInnerMostAxes(o.length,s)),R.assertAxesAreInnerMostDims("sum",o,s);let[h,d]=R.computeOutAndReduceShapes(c.shape,o),p=h;n&&(p=R.expandShapeToKeepDim(h,i));let f=v.sizeFromShape(d),m=v.sizeFromShape(e.shape)/f,A=xe({inputs:{x:c},attrs:{shape:[m,f]},backend:r}),y=yd(e.dtype),g=Ei(A,y,"sum",r),b=xe({inputs:{x:g},attrs:{shape:p},backend:r});return r.disposeIntermediateTensorInfo(A),r.disposeIntermediateTensorInfo(g),u&&r.disposeIntermediateTensorInfo(c),b}function AA(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r;return JL(a,s,i,n)}var QL={kernelName:ei,backendName:"webgl",kernelFunc:AA};function Cn(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{perm:s}=r,i=n,o=a.shape.length,l=new Array(o);for(let c=0;c<l.length;c++)l[c]=a.shape[s[c]];let u;if(i.shouldExecuteOnCPU([a])){let c=i.texData.get(a.dataId).values,h=fA(c,a.shape,a.dtype,s,l);u=i.makeTensorInfo(l,a.dtype);let d=i.texData.get(u.dataId);d.values=h}else u=Ip(a,s,i);return u}var eW={kernelName:si,backendName:"webgl",kernelFunc:Cn},l_=1e3;function Np({a:e,b:t,transposeA:n,transposeB:r,backend:a,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:o=0,activation:l=null}){let u=e.shape.length,c=t.shape.length,h=n?e.shape[u-2]:e.shape[u-1],d=r?t.shape[c-1]:t.shape[c-2],p=n?e.shape[u-1]:e.shape[u-2],f=r?t.shape[c-2]:t.shape[c-1],m=e.shape.slice(0,-2),A=t.shape.slice(0,-2),y=v.sizeFromShape(m),g=v.sizeFromShape(A),b=y===g||y===1||g===1;v.assert(u>=2&&c>=2&&b,()=>`Error in matMul: the input batch dimensions must either be the same or at least one input batch dimension must be 1. Got input batch dimensions of (${m}) and (${A}).`);let _=(y>g?e.shape.slice(0,-2):t.shape.slice(0,-2)).concat([p,f]);v.assert(h===d,()=>`Error in matMul: inner shapes (${h}) and (${d}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${n} and transposeB=${r} must match.`);let w=n?[y,h,p]:[y,p,h],x=r?[g,f,d]:[g,d,f],N=xe({inputs:{x:e},backend:a,attrs:{shape:w}}),S=xe({inputs:{x:t},backend:a,attrs:{shape:x}}),T=[N,S],M=Math.max(y,g),D=n?N.shape[1]:N.shape[2],z=s!=null,W=i!=null,U=l==="leakyrelu",H=l!=null?kp(l,!0):null,X=z||W||U||H!=null,j;if((p===1||f===1)&&D>l_&&X===!1){let Y=N,se=S;n&&(Y=Cn({inputs:{x:N},backend:a,attrs:{perm:[0,2,1]}}),T.push(Y)),r&&(se=Cn({inputs:{x:S},backend:a,attrs:{perm:[0,2,1]}}),T.push(se));let te=f!==1,oe=f===1,Q=Y;te&&(Q=xe({inputs:{x:Y},backend:a,attrs:{shape:[M,D,1]}}),T.push(Q));let pe=f===1?2:1,le=se;oe&&(le=xe({inputs:{x:se},backend:a,attrs:{shape:[M,1,D]}}),T.push(le));let Ae=i_({inputs:{a:Q,b:le},backend:a});j=AA({inputs:{x:Ae},backend:a,attrs:{axis:pe,keepDims:!0}}),T.push(Ae)}else{let Y=lr(e.dtype,t.dtype),se=new n_(w,x,[M,p,f],n,r,z,H,W,U),te=[N,S];if(s!=null&&te.push(s),W&&te.push(i),U){let oe=a.makeTensorInfo([],"float32",v.createScalarValue(o,"float32"));te.push(oe),T.push(oe)}j=a.runWebGLProgram(se,te,Y)}let ee=xe({inputs:{x:j},backend:a,attrs:{shape:_}});T.push(j);for(let Y of T)a.disposeIntermediateTensorInfo(Y);return ee}function tW(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:h}=r;return Np({a,b:s,transposeA:l,transposeB:u,backend:n,bias:i,preluActivationWeights:o,leakyreluAlpha:h,activation:c})}var nW={kernelName:ii,backendName:"webgl",kernelFunc:tW},u_="return abs(x);";function rW(e){let{inputs:t,backend:n}=e,{x:r}=t;if(n.shouldExecuteOnCPU([r])&&r.dtype!=="complex64"){let s=n.texData.get(r.dataId),i=Bb(s.values);return n.makeTensorInfo(r.shape,r.dtype,i)}let a;return J().getBool("WEBGL_PACK_UNARY_OPERATIONS")?a=new Pl(r.shape,u_):a=new qa(r.shape,u_),n.runWebGLProgram(a,[r],r.dtype)}var aW={kernelName:so,backendName:"webgl",kernelFunc:rW},sW=Ir+`
|
|
if (abs(x) > 1.) {
|
|
return NAN;
|
|
}
|
|
return acos(x);
|
|
`,iW=Ye({opSnippet:sW}),oW={kernelName:io,backendName:"webgl",kernelFunc:iW},lW=Ir+`
|
|
if (x < 1.0) return NAN;
|
|
return log(x + sqrt(x * x - 1.0));`,uW=Ye({opSnippet:lW}),cW={kernelName:oo,backendName:"webgl",kernelFunc:uW},c_="return a + b;",hW=on({opSnippet:c_,packedOpSnippet:c_,supportsComplex:!0,cpuKernelImpl:DP}),dW={kernelName:Ra,backendName:"webgl",kernelFunc:hW},pW=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((a,s)=>`T${s}`);let n=[];this.variableNames.forEach(a=>{n.push(`float v${a} = get${a}AtOutCoords();`)});let r=this.variableNames.map(a=>`v${a}`).join(" + ");this.userCode=`
|
|
void main() {
|
|
${n.join(`
|
|
`)}
|
|
|
|
float result = ${r};
|
|
setOutput(result);
|
|
}
|
|
`}},fW=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((a,s)=>`T${s}`);let n=[];this.variableNames.forEach(a=>{n.push(`vec4 v${a} = get${a}AtOutCoords();`)});let r=this.variableNames.map(a=>`v${a}`).join(" + ");this.userCode=`
|
|
void main() {
|
|
${n.join(`
|
|
`)}
|
|
|
|
vec4 result = ${r};
|
|
setOutput(result);
|
|
}
|
|
`}};function Sp(e){let{inputs:t,backend:n}=e,r=t;if(r.length===1)return Bn({inputs:{x:r[0]},backend:n});if(r.length>J().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let o=Math.floor(r.length/2),l=Sp({inputs:r.slice(0,o),backend:n}),u=Sp({inputs:r.slice(o),backend:n});return Sp({inputs:[l,u],backend:n})}let a=r.map(o=>o.dtype).reduce((o,l)=>lr(o,l)),s=r.map(o=>o.shape),i=J().getBool("WEBGL_PACK")?new fW(r[0].shape,s):new pW(r[0].shape,s);return n.runWebGLProgram(i,r,a)}var mW={kernelName:fs,backendName:"webgl",kernelFunc:Sp};function AW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),u=l,c=R.getAxesPermutation(u,o),h=a;c!=null&&(h=Cn({inputs:{x:a},backend:n,attrs:{perm:c}}),u=R.getInnerMostAxes(u.length,o)),R.assertAxesAreInnerMostDims("all",u,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,u),f=v.sizeFromShape(p),m=xe({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=Ei(m,m.dtype,"all",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=xe({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=xe({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),c!=null&&n.disposeIntermediateTensorInfo(h),y}var yW={kernelName:Dh,backendName:"webgl",kernelFunc:AW};function gW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),u=l,c=R.getAxesPermutation(u,o),h=a;c!=null&&(h=Cn({inputs:{x:a},backend:n,attrs:{perm:c}}),u=R.getInnerMostAxes(u.length,o)),R.assertAxesAreInnerMostDims("any",u,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,u),f=v.sizeFromShape(p),m=xe({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=Ei(m,m.dtype,"any",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=xe({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=xe({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),c!=null&&n.disposeIntermediateTensorInfo(h),y}var xW={kernelName:Oh,backendName:"webgl",kernelFunc:gW},wW=class{constructor(e,t,n){this.variableNames=["A"];let{windowSize:r,batchSize:a,outSize:s}=e;n||this.variableNames.push("bestIndicesA"),this.outputShape=[a,s];let i=t==="max"?">":"<",o=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 * ${r};
|
|
|
|
int bestIndex = inOffset;
|
|
float bestValue = getA(batch, bestIndex);
|
|
|
|
for (int i = 0; i < ${r}; i++) {
|
|
int inIdx = ${o};
|
|
float candidate = getA(batch, inIdx);
|
|
if (candidate ${i} bestValue) {
|
|
bestValue = candidate;
|
|
bestIndex = inIdx;
|
|
}
|
|
}
|
|
setOutput(float(bestIndex));
|
|
}
|
|
`}},bW=class{constructor(e,t,n,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,v.assert(e.length>2,()=>`Packed arg${n.charAt(0).toUpperCase()+n.slice(1)} supports only inputs with rank above 2.`);let a=e[e.length-1],s=Math.ceil(a/t);this.outputShape=e.slice(0,-1),s>1&&this.outputShape.push(s),r||this.variableNames.push("bestIndicesA");let i=this.outputShape,o=i.length,l=dt(o),u=xn("coords",o),c,h;if(s===1){h=o+1;let N=dt(h);c=`
|
|
${N} sourceLocR = ${N}(${u.join()}, 0);
|
|
++${u[o-1]};
|
|
${N} sourceLocG = ${N}(${u.join()}, 0);
|
|
++${u[o-2]};
|
|
${N} sourceLocA = ${N}(${u.join()}, 0);
|
|
--${u[o-1]};
|
|
${N} sourceLocB = ${N}(${u.join()}, 0);
|
|
--${u[o-2]};`}else h=o,c=`
|
|
${l} sourceLocR = coords;
|
|
++${u[o-1]};
|
|
${l} sourceLocG = coords;
|
|
++${u[o-2]};
|
|
${l} sourceLocA = coords;
|
|
--${u[o-1]};
|
|
${l} sourceLocB = coords;
|
|
--${u[o-2]};`;let d=["x","y","z","w","u","v"].slice(0,h),p="."+d[h-1],f=d.map(N=>"int "+N),m=xn("sourceLocR",h-1).concat("inIdx.r"),A=xn("sourceLocG",h-1).concat("inIdx.g"),y=xn("sourceLocB",h-1).concat("inIdx.b"),g=xn("sourceLocA",h-1).concat("inIdx.a"),b=n==="max"?"greaterThan":"lessThan",_=r?"":`
|
|
inIdx = round(vec4(getBestIndicesAChannel(${m.join()}),
|
|
getBestIndicesAChannel(${A.join()}),
|
|
getBestIndicesAChannel(${y.join()}),
|
|
getBestIndicesAChannel(${g.join()})));`,w=`vec4(
|
|
getAChannel(${m.join()}),
|
|
hasNextCol ? getAChannel(${A.join()}) : 0.,
|
|
hasNextRow ? getAChannel(${y.join()}) : 0.,
|
|
hasNextRow && hasNextCol ? getAChannel(${g.join()}) : 0.)`,x=r?"":`
|
|
float getBestIndicesAChannel(${f.join()}) {
|
|
return getChannel(getBestIndicesA(${d.join()}),
|
|
vec2(${d.slice(-2).join()}));
|
|
}`;this.userCode=`
|
|
float getAChannel(${f.join()}) {
|
|
return getChannel(getA(${d.join()}),
|
|
vec2(${d.slice(-2).join()}));
|
|
}
|
|
${x}
|
|
void main() {
|
|
${l} coords = getOutputCoords();
|
|
bool hasNextCol = ${u[o-1]} < ${i[o-1]-1};
|
|
bool hasNextRow = ${u[o-2]} < ${i[o-2]-1};
|
|
${c}
|
|
ivec4 srcIdx = ivec4(sourceLocR${p}, sourceLocG${p},
|
|
sourceLocB${p}, sourceLocA${p}) * ${t};
|
|
ivec4 inIdx = srcIdx;
|
|
vec4 bestIndex = vec4(inIdx);
|
|
vec4 bestValue = ${w};
|
|
|
|
for (int i = 0; i < ${t}; i++) {
|
|
inIdx = srcIdx;
|
|
${_}
|
|
vec4 candidate = ${w};
|
|
bvec4 nan = isnan(candidate);
|
|
bvec4 replace = bvec4(
|
|
vec4(${b}(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 h_(e,t,n,r=null){let a=t.shape[0],s=t.shape[1];r!=null&&(a=r.shape[0],s=r.shape[1]);let i=R.computeOptimalWindowSize(s),o={windowSize:i,inSize:s,batchSize:a,outSize:Math.ceil(s/i)},l=new wW(o,n,r==null),u=[t];r!=null&&u.push(r);let c=e.runWebGLProgram(l,u,"int32");if(c.shape[1]===1)return c;let h=h_(e,t,n,c);return e.disposeIntermediateTensorInfo(c),h}function d_(e,t,n,r=null){let a=r!=null?r.shape:t.shape,s=a[a.length-1],i=R.computeOptimalWindowSize(s),o=new bW(a,i,n,r==null),l=r==null?[t]:[t,r],u=e.runWebGLProgram(o,l,"int32");if(u.shape.length===t.shape.length){let c=d_(e,t,n,u);return e.disposeIntermediateTensorInfo(u),c}return u}function p_(e,t,n,r){let a=[n];if(R.assertAxesAreInnerMostDims("arg"+r.charAt(0).toUpperCase()+r.slice(1),a,t.shape.length),!J().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let s=[],[i,o]=R.computeOutAndReduceShapes(t.shape,a),l=v.sizeFromShape(o),u=xe({inputs:{x:t},backend:e,attrs:{shape:[-1,l]}});s.push(u);let c=h_(e,u,r);s.push(c);let h=xe({inputs:{x:c},backend:e,attrs:{shape:i}});return s.forEach(d=>e.disposeIntermediateTensorInfo(d)),h}return d_(e,t,r)}function _W(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r,i=v.parseAxisParam(s,a.shape),o=R.getAxesPermutation(i,a.shape.length),l=a,u=[];o!=null&&(l=Cn({inputs:{x:a},backend:n,attrs:{perm:o}}),u.push(l),i=R.getInnerMostAxes(i.length,l.shape.length)),R.assertAxesAreInnerMostDims("argMax",[i[0]],l.shape.length);let c=p_(n,l,i[0],"max");return u.forEach(h=>n.disposeIntermediateTensorInfo(h)),c}var vW={kernelName:ms,backendName:"webgl",kernelFunc:_W};function kW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r,i=v.parseAxisParam(s,a.shape),o=R.getAxesPermutation(i,a.shape.length),l=a,u=[];o!=null&&(l=Cn({inputs:{x:a},backend:n,attrs:{perm:o}}),u.push(l),i=R.getInnerMostAxes(i.length,l.shape.length)),R.assertAxesAreInnerMostDims("argMin",[i[0]],l.shape.length);let c=p_(n,l,i[0],"min");return u.forEach(h=>n.disposeIntermediateTensorInfo(h)),c}var IW={kernelName:yu,backendName:"webgl",kernelFunc:kW},NW=Ir+`
|
|
if (abs(x) > 1.) {
|
|
return NAN;
|
|
}
|
|
return asin(x);
|
|
`,SW=Ye({opSnippet:NW}),TW={kernelName:lo,backendName:"webgl",kernelFunc:SW},EW=Ir+"return log(x + sqrt(x * x + 1.0));",CW=Ye({opSnippet:EW}),RW={kernelName:uo,backendName:"webgl",kernelFunc:CW},FW=Ir+`
|
|
return atan(x);
|
|
`,MW=Ye({opSnippet:FW}),$W={kernelName:co,backendName:"webgl",kernelFunc:MW},DW=VL+`
|
|
return atan(a, b);
|
|
`,OW=`
|
|
vec4 result = atan(a, b);
|
|
vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
|
|
`+UL+`
|
|
return result;
|
|
`,zW=on({opSnippet:DW,packedOpSnippet:OW}),PW={kernelName:po,backendName:"webgl",kernelFunc:zW},LW=Ir+`
|
|
if ((x < -1.0) || (x > 1.0)) return NAN;
|
|
return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,WW=Ye({opSnippet:LW}),BW={kernelName:ho,backendName:"webgl",kernelFunc:WW},wc=class{constructor(e,t,n,r=!1,a=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideHeight,o=e.strideWidth,l=e.dilationHeight,u=e.dilationWidth,c=e.effectiveFilterHeight,h=e.effectiveFilterWidth,d=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`,A=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,y="0.0";if(f||(y="-1.0 / 1e-20"),n){let N=">=";this.userCode=`
|
|
const ivec2 strides = ivec2(${i}, ${o});
|
|
const ivec2 pads = ivec2(${d}, ${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 < ${h};
|
|
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 ${N} currMinMaxValue) {
|
|
minMaxValue = value;
|
|
minMaxValueFound = 1.0;
|
|
minMaxPosition = ${r?a?m:A:`wR * ${h} + wC`};
|
|
}
|
|
}
|
|
}
|
|
setOutput(float(minMaxPosition));
|
|
}
|
|
`;return}let g="max",b=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(b="avgValue / count");let _=Math.floor(s/4)*4,w=s%4,x=`
|
|
if (${f}) {
|
|
avgValue += dot(values, ones);
|
|
} else {
|
|
minMaxValue = ${g}(values, minMaxValue);
|
|
}
|
|
`;this.userCode=`
|
|
const ivec2 strides = ivec2(${i}, ${o});
|
|
const ivec2 pads = ivec2(${d}, ${p});
|
|
const float initializationValue = ${y};
|
|
const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
|
|
|
|
float count = 0.0;
|
|
|
|
float getValue(int batch, int xR, int xC, int d) {
|
|
if (xC < 0 || xC >= ${e.inWidth}) {
|
|
return initializationValue;
|
|
}
|
|
count += 1.0;
|
|
return getX(batch, xR, xC, d);
|
|
}
|
|
|
|
void main() {
|
|
ivec4 coords = getOutputCoords();
|
|
int batch = coords[0];
|
|
int d = coords[3];
|
|
|
|
ivec2 xRCCorner = coords.yz * strides - pads;
|
|
int xRCorner = xRCCorner.x;
|
|
int xCCorner = xRCCorner.y;
|
|
|
|
// max/min x(?, ?, d) to get y(yR, yC, d).
|
|
// ? = to be determined
|
|
vec4 minMaxValue = vec4(${y});
|
|
float avgValue = 0.0;
|
|
count = 0.0;
|
|
|
|
for (int wR = 0; wR < ${c};
|
|
wR += ${l}) {
|
|
int xR = xRCorner + wR;
|
|
|
|
if (xR < 0 || xR >= ${e.inHeight}) {
|
|
continue;
|
|
}
|
|
|
|
for (int wC = 0; wC < ${_}; 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)
|
|
);
|
|
|
|
${x}
|
|
}
|
|
|
|
int xC = xCCorner + ${_};
|
|
if (${w===1}) {
|
|
vec4 values = vec4(
|
|
getValue(batch, xR, xC, d),
|
|
initializationValue,
|
|
initializationValue,
|
|
initializationValue
|
|
);
|
|
|
|
${x}
|
|
} else if (${w===2}) {
|
|
vec4 values = vec4(
|
|
getValue(batch, xR, xC, d),
|
|
getValue(batch, xR, xC + ${u}, d),
|
|
initializationValue,
|
|
initializationValue
|
|
);
|
|
|
|
${x}
|
|
} else if (${w===3}) {
|
|
vec4 values = vec4(
|
|
getValue(batch, xR, xC, d),
|
|
getValue(batch, xR, xC + ${u}, d),
|
|
getValue(batch, xR, xC + 2 * ${u}, d),
|
|
initializationValue
|
|
);
|
|
|
|
${x}
|
|
}
|
|
}
|
|
setOutput(${b});
|
|
}
|
|
`}},yA=class{constructor(e,t,n,r=!1,a=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideDepth,o=e.strideHeight,l=e.strideWidth,u=e.dilationDepth,c=e.dilationHeight,h=e.dilationWidth,d=e.effectiveFilterDepth,p=e.effectiveFilterHeight,f=e.effectiveFilterWidth,m=e.padInfo.front,A=e.padInfo.top,y=e.padInfo.left;this.outputShape=e.outShape;let g=t==="avg",b="0.0";if(g||(b="-1.0 / 1e-20"),n){let T=">=";this.userCode=`
|
|
const ivec3 strides =
|
|
ivec3(${i}, ${o}, ${l});
|
|
const ivec3 pads = ivec3(${m}, ${A}, ${y});
|
|
|
|
void main() {
|
|
ivec5 coords = getOutputCoords();
|
|
int batch = coords.x;
|
|
int ch = coords.u;
|
|
|
|
ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
|
|
int xDCorner = xCorner.x;
|
|
int xRCorner = xCorner.y;
|
|
int xCCorner = xCorner.z;
|
|
|
|
// max/min x(?, ?, ?, ch) to get y(yD, yR, yC, ch).
|
|
// ? = to be determined
|
|
float minMaxValue = 0.0;
|
|
float minMaxValueFound = 0.0;
|
|
int minMaxPosition = 0;
|
|
|
|
for (int wD = 0; wD < ${d};
|
|
wD += ${u}) {
|
|
int xD = xDCorner + wD;
|
|
|
|
if (xD < 0 || xD >= ${e.inDepth}) {
|
|
continue;
|
|
}
|
|
|
|
for (int wR = 0; wR < ${p};
|
|
wR += ${c}) {
|
|
int xR = xRCorner + wR;
|
|
|
|
if (xR < 0 || xR >= ${e.inHeight}) {
|
|
continue;
|
|
}
|
|
|
|
for (int wC = 0; wC < ${f};
|
|
wC += ${h}) {
|
|
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 ${T} currMinMaxValue) {
|
|
minMaxValue = value;
|
|
minMaxValueFound = 1.0;
|
|
minMaxPosition = ${r?a?`(((batch * ${e.inDepth} + xD) * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`((xD * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`wD * ${p} * ${f} +
|
|
wR * ${f} + wC`};
|
|
}
|
|
}
|
|
}
|
|
}
|
|
setOutput(float(minMaxPosition));
|
|
}
|
|
`;return}let _="max",w=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(w="avgValue / count");let x=Math.floor(s/4)*4,N=s%4,S=`
|
|
if (${g}) {
|
|
avgValue += dot(values, ones);
|
|
} else {
|
|
minMaxValue = ${_}(values, minMaxValue);
|
|
}
|
|
`;this.userCode=`
|
|
const ivec3 strides =
|
|
ivec3(${i}, ${o}, ${l});
|
|
const ivec3 pads = ivec3(${m}, ${A}, ${y});
|
|
const float initializationValue = ${b};
|
|
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 >= ${e.inWidth}) {
|
|
return initializationValue;
|
|
}
|
|
count += 1.0;
|
|
return getX(batch, xD, xR, xC, ch);
|
|
}
|
|
|
|
void main() {
|
|
ivec5 coords = getOutputCoords();
|
|
int batch = coords.x;
|
|
int ch = coords.u;
|
|
|
|
ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
|
|
int xDCorner = xCorner.x;
|
|
int xRCorner = xCorner.y;
|
|
int xCCorner = xCorner.z;
|
|
|
|
// max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).
|
|
// ? = to be determined
|
|
vec4 minMaxValue = vec4(${b});
|
|
float avgValue = 0.0;
|
|
count = 0.0;
|
|
|
|
for (int wD = 0; wD < ${d};
|
|
wD += ${u}) {
|
|
int xD = xDCorner + wD;
|
|
|
|
if (xD < 0 || xD >= ${e.inDepth}) {
|
|
continue;
|
|
}
|
|
|
|
for (int wR = 0; wR < ${p};
|
|
wR += ${c}) {
|
|
int xR = xRCorner + wR;
|
|
|
|
if (xR < 0 || xR >= ${e.inHeight}) {
|
|
continue;
|
|
}
|
|
|
|
for (int wC = 0; wC < ${x}; wC += 4) {
|
|
int xC = xCCorner + wC * ${h};
|
|
|
|
vec4 values = vec4(
|
|
getValue(batch, xD, xR, xC, ch),
|
|
getValue(batch, xD, xR, xC + ${h}, ch),
|
|
getValue(batch, xD, xR, xC + 2 * ${h}, ch),
|
|
getValue(batch, xD, xR, xC + 3 * ${h}, ch)
|
|
);
|
|
|
|
${S}
|
|
}
|
|
|
|
int xC = xCCorner + ${x};
|
|
if (${N===1}) {
|
|
vec4 values = vec4(
|
|
getValue(batch, xD, xR, xC, ch),
|
|
initializationValue,
|
|
initializationValue,
|
|
initializationValue
|
|
);
|
|
|
|
${S}
|
|
} else if (${N===2}) {
|
|
vec4 values = vec4(
|
|
getValue(batch, xD, xR, xC, ch),
|
|
getValue(batch, xD, xR, xC + ${h}, ch),
|
|
initializationValue,
|
|
initializationValue
|
|
);
|
|
|
|
${S}
|
|
} else if (${N===3}) {
|
|
vec4 values = vec4(
|
|
getValue(batch, xD, xR, xC, ch),
|
|
getValue(batch, xD, xR, xC + ${h}, ch),
|
|
getValue(batch, xD, xR, xC + 2 * ${h}, ch),
|
|
initializationValue
|
|
);
|
|
|
|
${S}
|
|
}
|
|
}
|
|
setOutput(${w});
|
|
}
|
|
}
|
|
`}};function VW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t;Fl(a,"avgPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=r,u=1;v.assert(R.eitherStridesOrDilationsAreOne(i,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let c=R.computePool2DInfo(a.shape,s,i,u,o,l);if(c.filterWidth===1&&c.filterHeight===1&&v.arraysEqual(c.inShape,c.outShape))return Bn({inputs:{x:a},backend:n});let h=new wc(c,"avg",!1);return n.runWebGLProgram(h,[a],"float32")}var UW={kernelName:As,backendName:"webgl",kernelFunc:VW};function HW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:u}=r,c=[1,1,1],h=R.computePool3DInfo(a.shape,s,i,c,o,l,u),d=new yA(h,"avg",!1);return n.runWebGLProgram(d,[a],"float32")}var jW={kernelName:gu,backendName:"webgl",kernelFunc:HW},GW=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterHeight,l=e.effectiveFilterWidth,u=o-1-e.padInfo.top,c=l-1-e.padInfo.left,h=1/(t*n);this.userCode=`
|
|
const ivec2 pads = ivec2(${u}, ${c});
|
|
const float avgMultiplier = float(${h});
|
|
|
|
void main() {
|
|
ivec4 coords = getOutputCoords();
|
|
int b = coords[0];
|
|
int d = coords[3];
|
|
|
|
ivec2 dyRCCorner = coords.yz - pads;
|
|
int dyRCorner = dyRCCorner.x;
|
|
int dyCCorner = dyRCCorner.y;
|
|
|
|
// Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).
|
|
// ? = to be determined. : = across all values in that axis.
|
|
float dotProd = 0.0;
|
|
for (int wR = 0; wR < ${o};
|
|
wR += ${s}) {
|
|
float dyR = float(dyRCorner + wR) / ${r}.0;
|
|
|
|
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
|
|
continue;
|
|
}
|
|
int idyR = int(dyR);
|
|
|
|
for (int wC = 0; wC < ${l};
|
|
wC+= ${i}) {
|
|
float dyC = float(dyCCorner + wC) / ${a}.0;
|
|
|
|
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
|
|
fract(dyC) > 0.0) {
|
|
continue;
|
|
}
|
|
int idyC = int(dyC);
|
|
|
|
float dyValue = getDy(b, idyR, idyC, d);
|
|
|
|
dotProd += dyValue * avgMultiplier;
|
|
}
|
|
}
|
|
setOutput(dotProd);
|
|
}
|
|
`}},qW=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,c=e.effectiveFilterDepth,h=e.effectiveFilterHeight,d=e.effectiveFilterWidth,p=c-1-e.padInfo.front,f=h-1-e.padInfo.top,m=d-1-e.padInfo.left,A=1/(t*n*r);this.userCode=`
|
|
const ivec3 pads = ivec3(${p}, ${f}, ${m});
|
|
const float avgMultiplier = float(${A});
|
|
|
|
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 += ${o}) {
|
|
float dyD = float(dyDCorner + wD) / ${a}.0;
|
|
|
|
if (dyD < 0.0 || dyD >= ${e.outDepth}.0 || fract(dyD) > 0.0) {
|
|
continue;
|
|
}
|
|
int idyD = int(dyD);
|
|
|
|
for (int wR = 0; wR < ${h};
|
|
wR += ${l}) {
|
|
float dyR = float(dyRCorner + wR) / ${s}.0;
|
|
|
|
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 ||
|
|
fract(dyR) > 0.0) {
|
|
continue;
|
|
}
|
|
int idyR = int(dyR);
|
|
|
|
for (int wC = 0; wC < ${d};
|
|
wC += ${u}) {
|
|
float dyC = float(dyCCorner + wC) / ${i}.0;
|
|
|
|
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
|
|
fract(dyC) > 0.0) {
|
|
continue;
|
|
}
|
|
int idyC = int(dyC);
|
|
|
|
float dyValue = getDy(batch, idyD, idyR, idyC, ch);
|
|
|
|
dotProd += dyValue * avgMultiplier;
|
|
}
|
|
}
|
|
}
|
|
setOutput(dotProd);
|
|
}
|
|
`}};function XW(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s,{filterSize:o,strides:l,pad:u,dimRoundingMode:c}=r,h=[1,1,1],d=R.computePool3DInfo(i.shape,o,l,h,u,c),p=new qW(d);return n.runWebGLProgram(p,[a],i.dtype)}var KW={kernelName:Ph,backendName:"webgl",kernelFunc:XW};function ZW(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s;Fl([a,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:u}=r,c=R.computePool2DInfo(i.shape,o,l,1,u),h=new GW(c);return n.runWebGLProgram(h,[a],i.dtype)}var YW={kernelName:zh,backendName:"webgl",kernelFunc:ZW};function JW(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s}=t,{transposeA:i,transposeB:o}=r;return Np({a,b:s,transposeA:i,transposeB:o,backend:n})}var QW={kernelName:ys,backendName:"webgl",kernelFunc:JW},eB=class{constructor(e,t,n,r,a,s){this.outputShape=[],this.variableNames=["x","mean","variance"],R.assertAndGetBroadcastShape(e,t),R.assertAndGetBroadcastShape(e,n);let i="0.0";r!=null&&(R.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="1.0";a!=null&&(R.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
|
|
void main() {
|
|
float x = getXAtOutCoords();
|
|
float mean = getMeanAtOutCoords();
|
|
float variance = getVarianceAtOutCoords();
|
|
float offset = ${i};
|
|
float scale = ${o};
|
|
float inv = scale * inversesqrt(variance + float(${s}));
|
|
setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));
|
|
}
|
|
`}},tB=class{constructor(e,t,n,r,a,s){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],R.assertAndGetBroadcastShape(e,t),R.assertAndGetBroadcastShape(e,n);let i="vec4(0.0)";r!=null&&(R.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="vec4(1.0)";a!=null&&(R.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
|
|
void main() {
|
|
vec4 offset = ${i};
|
|
vec4 scale = ${o};
|
|
|
|
vec4 x = getXAtOutCoords();
|
|
vec4 mean = getMeanAtOutCoords();
|
|
vec4 variance = getVarianceAtOutCoords();
|
|
|
|
vec4 inv = scale * inversesqrt(variance + vec4(${s}));
|
|
|
|
setOutput((x - mean) * inv + offset);
|
|
}
|
|
`}},nB=({inputs:e,backend:t,attrs:n})=>{let{x:r,mean:a,variance:s,offset:i,scale:o}=e;v.assert(a.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),v.assert(i==null||a.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),v.assert(o==null||a.shape.length===o.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:l}=n;l==null&&(l=.001);let u=[r,a,s],c=null;i!=null&&(c=i.shape,u.push(i));let h=null;o!=null&&(h=o.shape,u.push(o));let d=J().getBool("WEBGL_PACK_NORMALIZATION")?new tB(r.shape,a.shape,s.shape,c,h,l):new eB(r.shape,a.shape,s.shape,c,h,l);return t.runWebGLProgram(d,u,u[0].dtype)},rB={kernelName:Es,backendName:"webgl",kernelFunc:nB},sB=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=dt(this.rank),n=`uniform int start[${this.rank}];`,r=aB(this.rank),a,s=e.map((i,o)=>`sourceLoc.${gA[o]} = start[${o}] + coords.${gA[o]};`);a=`
|
|
${t} sourceLoc;
|
|
${t} coords = getOutputCoords();
|
|
${s.join(`
|
|
`)}
|
|
`,this.userCode=`
|
|
${n}
|
|
void main() {
|
|
${a}
|
|
setOutput(getSource(${r}));
|
|
}
|
|
`}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${this.rank}) of the program must match the length of start (${e.length})`);return(t,n)=>{this.startLoc==null&&(this.startLoc=t.getUniformLocationNoThrow(n,"start"),this.startLoc==null)||t.gl.uniform1iv(this.startLoc,e)}}},gA=["x","y","z","w","u","v"];function aB(e){if(e===1)return"sourceLoc";if(e<=6)return gA.slice(0,e).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}var iB=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length;let t=dt(this.rank),n=xn("coords",this.rank),r=xn("sourceLoc",this.rank),a=this.rank===1?"sourceLoc":`vec2(${r.slice(-2).join()})`,s=`getChannel(getSource(${r.join()}), ${a})`,i=`
|
|
result.x = ${s};
|
|
if (++${n[this.rank-1]} < ${e[this.rank-1]}) {
|
|
++${r[this.rank-1]};
|
|
result.y = ${s};
|
|
--${r[this.rank-1]};
|
|
}
|
|
`,o=this.rank===1?"":`
|
|
--${n[this.rank-1]};
|
|
if (++${n[this.rank-2]} < ${e[this.rank-2]}) {
|
|
++${r[this.rank-2]};
|
|
result.z = ${s};
|
|
if (++${n[this.rank-1]} < ${e[this.rank-1]}) {
|
|
++${r[this.rank-1]};
|
|
result.w = ${s};
|
|
}
|
|
}
|
|
`,l=this.rank<=4?`sourceLoc = coords +
|
|
${t}(${e.map((u,c)=>`start[${c}]`).join()});`:e.map((u,c)=>`${r[c]} = ${n[c]} + start[${c}];`).join(`
|
|
`);this.userCode=`
|
|
uniform int start[${this.rank}];
|
|
void main() {
|
|
${t} coords = getOutputCoords();
|
|
${t} sourceLoc;
|
|
${l}
|
|
vec4 result = vec4(0.);
|
|
${i}
|
|
${o}
|
|
setOutput(result);
|
|
}
|
|
`}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${this.rank}) of the program must match the length of start (${e.length})`);return(t,n)=>{this.startLoc==null&&(this.startLoc=t.getUniformLocationNoThrow(n,"start"),this.startLoc==null)||t.gl.uniform1iv(this.startLoc,e)}}};function oB(e,t,n,r){let a=r.texData.get(e.dataId),s=r.makeTensorInfo(n,e.dtype),i=r.texData.get(s.dataId);Object.assign(i,a),i.refCount=1,i.shape=n,i.dtype=e.dtype;let o=fn.computeFlatOffset(t,v.computeStrides(e.shape));a.slice&&(o+=a.slice.flatOffset),i.slice={flatOffset:o,origDataId:a.slice&&a.slice.origDataId||e.dataId};let l=r.dataRefCount.get(i.slice.origDataId)||1;return r.dataRefCount.set(i.slice.origDataId,l+1),s}function bc(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{begin:s,size:i}=r,[o,l]=fn.parseSliceParams(a,s,i);if(fn.assertParamsValid(a,o,l),v.sizeFromShape(l)===0)return n.makeTensorInfo(l,a.dtype,[]);if(n.shouldExecuteOnCPU([a])||a.dtype==="string"){let h=n.texData.get(a.dataId),d=tL(h.values,o,l,a.shape,a.dtype);return n.makeTensorInfo(l,a.dtype,d)}let{isPacked:u}=n.texData.get(a.dataId),c=fn.isSliceContinous(a.shape,o,l);if(u||!c){let h=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new iB(l):new sB(l),d=h.getCustomSetupFunc(o);return n.runWebGLProgram(h,[a],a.dtype,d)}return n.uploadToGPU(a.dataId),oB(a,o,l,n)}var lB={kernelName:Xo,backendName:"webgl",kernelFunc:bc},uB=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,crops:i}=r;v.assert(a.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((g,b)=>g*b),l=R.getReshaped(a.shape,s,o),u=R.getPermuted(l.length,s.length),c=R.getReshapedPermuted(a.shape,s,o),h=R.getSliceBeginCoords(i,s.length),d=R.getSliceSize(c,i,s.length),p=[],f=xe({inputs:{x:a},backend:n,attrs:{shape:l}}),m=Cn({inputs:{x:f},backend:n,attrs:{perm:u}}),A=xe({inputs:{x:m},backend:n,attrs:{shape:c}}),y=bc({inputs:{x:A},backend:n,attrs:{begin:h,size:d}});return p.push(f),p.push(m),p.push(A),p.forEach(g=>n.disposeIntermediateTensorInfo(g)),y},cB={kernelName:xu,backendName:"webgl",kernelFunc:uB};function hB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i}=r,o=n.readSync(a.dataId),l=n.readSync(s.dataId),u=Wb(o,l,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,u)}var dB={kernelName:Lh,backendName:"webgl",kernelFunc:hB},pB="return float(a != b);",f_=on({opSnippet:pB,dtype:"bool"}),fB={kernelName:Oo,backendName:"webgl",kernelFunc:f_};function _c(e){let{inputs:t,backend:n}=e,{input:r}=t,a=n.texData.get(r.dataId);return Bn({inputs:{x:a.complexTensorInfos.real},backend:n})}var mB={kernelName:id,backendName:"webgl",kernelFunc:_c},AB="return float(int(x));";function yB(e,t){let n=new qa(e.shape,AB),r=t.runWebGLProgram(n,[e],"int32");return{dataId:r.dataId,shape:r.shape,dtype:r.dtype}}function xA(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{dtype:s}=r;if(s==="complex64"){if(a.dtype==="complex64")return Bn({inputs:{x:a},backend:n});let i=$t(a.shape),o=xA({inputs:{x:a},backend:n,attrs:{dtype:"float32"}}),l=Xa({inputs:{real:o,imag:i},backend:n});return i.dispose(),n.disposeIntermediateTensorInfo(o),l}if(a.dtype==="complex64"){let i=_c({inputs:{input:a},backend:n}),o=xA({inputs:{x:i},backend:n,attrs:{dtype:s}});return n.disposeIntermediateTensorInfo(i),o}if(!v.hasEncodingLoss(a.dtype,s)){let i=Bn({inputs:{x:a},backend:n});return{dataId:i.dataId,shape:i.shape,dtype:s}}if(s==="int32")return yB(a,n);if(s==="bool"){let i=n.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),o=f_({inputs:{a,b:i},backend:n});return n.disposeIntermediateTensorInfo(i),o}throw new Error(`Error in Cast: failed to cast ${a.dtype} to ${s}`)}var gB={kernelName:gs,backendName:"webgl",kernelFunc:xA},m_="return ceil(x);",xB=Ye({opSnippet:m_,packedOpSnippet:m_,cpuKernelImpl:zP}),wB={kernelName:xs,backendName:"webgl",kernelFunc:xB},bB=class{constructor(e){this.variableNames=["A"],this.outputShape=e,this.userCode=`
|
|
uniform float minVal;
|
|
uniform float maxVal;
|
|
|
|
void main() {
|
|
float value = getAAtOutCoords();
|
|
if (isnan(value)) {
|
|
setOutput(value);
|
|
return;
|
|
}
|
|
|
|
setOutput(clamp(value, minVal, maxVal));
|
|
}
|
|
`}getCustomSetupFunc(e,t){return(n,r)=>{this.minLoc==null&&(this.minLoc=n.getUniformLocationNoThrow(r,"minVal"),this.maxLoc=n.getUniformLocationNoThrow(r,"maxVal")),n.gl.uniform1f(this.minLoc,e),n.gl.uniform1f(this.maxLoc,t)}}},_B=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.userCode=`
|
|
uniform float minVal;
|
|
uniform float maxVal;
|
|
|
|
void main() {
|
|
vec4 value = getAAtOutCoords();
|
|
|
|
if (any(isnan(value))) {
|
|
setOutput(value);
|
|
return;
|
|
}
|
|
|
|
setOutput(clamp(value, vec4(minVal), vec4(maxVal)));
|
|
}
|
|
`}getCustomSetupFunc(e,t){return(n,r)=>{this.minLoc==null&&(this.minLoc=n.getUniformLocationNoThrow(r,"minVal"),this.maxLoc=n.getUniformLocationNoThrow(r,"maxVal")),n.gl.uniform1f(this.minLoc,e),n.gl.uniform1f(this.maxLoc,t)}}};function vB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{clipValueMin:s,clipValueMax:i}=r,o;J().getBool("WEBGL_PACK_CLIP")?o=new _B(a.shape):o=new bB(a.shape);let l=o.getCustomSetupFunc(s,i);return n.runWebGLProgram(o,[a],a.dtype,l)}var kB={kernelName:Fa,backendName:"webgl",kernelFunc:vB},IB=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 A_(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function NB(e){let{inputs:t,backend:n}=e,{x:r}=t,a=n.texData.get(r.dataId),s=new IB(r.shape),i=[A_(r,a.complexTensorInfos.real),A_(r,a.complexTensorInfos.imag)];return n.runWebGLProgram(s,i,i[0].dtype)}var SB={kernelName:wu,backendName:"webgl",kernelFunc:NB},TB=class{constructor(e){this.outputShape=[],this.outputShape=R.computeOutShape(e,1),this.variableNames=e.map((s,i)=>`T${i}`);let t=new Array(e.length-1);t[0]=e[0][1];for(let s=1;s<t.length;s++)t[s]=t[s-1]+e[s][1];let n=[`if (yC < ${t[0]}) setOutput(getT0(yR, yC));`];for(let s=1;s<t.length;s++){let i=t[s-1];n.push(`else if (yC < ${t[s]}) setOutput(getT${s}(yR, yC-${i}));`)}let r=t.length,a=t[t.length-1];n.push(`else setOutput(getT${r}(yR, yC-${a}));`),this.userCode=`
|
|
void main() {
|
|
ivec2 coords = getOutputCoords();
|
|
int yR = coords.x;
|
|
int yC = coords.y;
|
|
|
|
${n.join(`
|
|
`)}
|
|
}
|
|
`}},EB=class{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=R.computeOutShape(e,t);let n=this.outputShape,r=n.length,a=dt(r),s=xn("coords",r),i=["x","y","z","w","u","v"].slice(0,r);this.variableNames=e.map((f,m)=>`T${m}`);let o=new Array(e.length-1);o[0]=e[0][t];for(let f=1;f<o.length;f++)o[f]=o[f-1]+e[f][t];let l=i[t],u=i.slice(-2),c=i.join(),h=`if (${l} < ${o[0]}) {
|
|
return getChannel(
|
|
getT0(${c}), vec2(${u.join()}));
|
|
}`;for(let f=1;f<o.length;f++){let m=o[f-1];h+=`
|
|
if (${l} < ${o[f]} && ${l} >= ${o[f-1]}) {
|
|
return getChannel(
|
|
getT${f}(${Tp(i,l,m)}),
|
|
vec2(${Tp(u,l,m)}));
|
|
}`}let d=o.length,p=o[o.length-1];h+=`
|
|
return getChannel(
|
|
getT${d}(${Tp(i,l,p)}),
|
|
vec2(${Tp(u,l,p)}));`,this.userCode=`
|
|
float getValue(${i.map(f=>"int "+f)}) {
|
|
${h}
|
|
}
|
|
|
|
void main() {
|
|
${a} coords = getOutputCoords();
|
|
vec4 result = vec4(getValue(${s}), 0., 0., 0.);
|
|
|
|
${s[r-1]} = ${s[r-1]} + 1;
|
|
if (${s[r-1]} < ${n[r-1]}) {
|
|
result.g = getValue(${s});
|
|
}
|
|
|
|
${s[r-2]} = ${s[r-2]} + 1;
|
|
if (${s[r-2]} < ${n[r-2]}) {
|
|
result.a = getValue(${s});
|
|
}
|
|
|
|
${s[r-1]} = ${s[r-1]} - 1;
|
|
if (${s[r-2]} < ${n[r-2]} &&
|
|
${s[r-1]} < ${n[r-1]}) {
|
|
result.b = getValue(${s});
|
|
}
|
|
setOutput(result);
|
|
}
|
|
`}};function Tp(e,t,n){let r=e.indexOf(t);return e.map((a,s)=>s===r?`${a} - ${n}`:a).join()}function Ep(e){let{inputs:t,backend:n}=e,{input:r}=t,a=n.texData.get(r.dataId);return Bn({inputs:{x:a.complexTensorInfos.imag},backend:n})}var CB={kernelName:Qh,backendName:"webgl",kernelFunc:Ep};function Bl(e,t,n){let r=e[0].dtype;if(r==="complex64"){let u=e.map(f=>_c({inputs:{input:f},backend:n})),c=e.map(f=>Ep({inputs:{input:f},backend:n})),h=Bl(u,t,n),d=Bl(c,t,n),p=Xa({inputs:{real:h,imag:d},backend:n});return u.forEach(f=>n.disposeIntermediateTensorInfo(f)),c.forEach(f=>n.disposeIntermediateTensorInfo(f)),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),p}if(r==="string"){let{tensors2D:u,outShape:c}=y_(e,t,n),h=u.map(A=>({vals:n.readSync(A.dataId),shape:A.shape})),d=u[0].shape[0]===1,p=PP(h,c,r,d),f=R.computeOutShape(e.map(A=>A.shape),t),m=n.makeTensorInfo(f,r,p);return u.forEach(A=>n.disposeIntermediateTensorInfo(A)),m}if(e.length>J().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){let u=Math.floor(e.length/2),c=Bl(e.slice(0,u),t,n),h=Bl(e.slice(u),t,n),d=Bl([c,h],t,n);return n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(h),d}if(J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&e[0].shape.length>1){let u=new EB(e.map(c=>c.shape),t);return n.runWebGLProgram(u,e,r)}let{tensors2D:a,outShape:s}=y_(e,t,n),i=new TB(a.map(u=>u.shape)),o=n.runWebGLProgram(i,a,r);a.forEach(u=>n.disposeIntermediateTensorInfo(u));let l=xe({inputs:{x:o},attrs:{shape:s},backend:n});return n.disposeIntermediateTensorInfo(o),l}function y_(e,t,n){let r=R.computeOutShape(e.map(a=>a.shape),t);return{tensors2D:e.map(a=>xe({inputs:{x:a},attrs:{shape:[-1,v.sizeFromShape(a.shape.slice(t))]},backend:n})),outShape:r}}function g_(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r,s=v.parseAxisParam(a,t[0].shape)[0],i=R.computeOutShape(t.map(u=>u.shape),s);if(v.sizeFromShape(i)===0)return n.makeTensorInfo(i,t[0].dtype,[]);let o=t.filter(u=>v.sizeFromShape(u.shape)>0);if(o.length===1)return Bn({inputs:{x:o[0]},backend:n});let l=o.map(u=>u.shape);return R.assertParamsConsistent(l,s),Bl(o,s,n)}var RB={kernelName:fo,backendName:"webgl",kernelFunc:g_},x_=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.padInfo.top,i=e.padInfo.left,o=e.strideHeight,l=e.strideWidth,u=e.dilationHeight,c=e.dilationWidth,h=e.filterHeight,d=e.filterWidth,p=Math.floor(e.inChannels/4)*4,f=e.inChannels%4,m=e.dataFormat==="channelsLast",A=m?1:2,y=m?2:3,g=m?3:1,b="",_="";n&&(r?b=`float activation(float a) {
|
|
float b = getPreluActivationWeightsAtOutCoords();
|
|
${n}
|
|
}`:a?b=`float activation(float a) {
|
|
float b = getLeakyreluAlphaAtOutCoords();
|
|
${n}
|
|
}`:b=`
|
|
float activation(float x) {
|
|
${n}
|
|
}
|
|
`,_="result = activation(result);");let w=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
|
|
${b}
|
|
|
|
const ivec2 strides = ivec2(${o}, ${l});
|
|
const ivec2 pads = ivec2(${s}, ${i});
|
|
|
|
void main() {
|
|
ivec4 coords = getOutputCoords();
|
|
int batch = coords[0];
|
|
int d2 = coords[${g}];
|
|
|
|
ivec2 xRCCorner =
|
|
ivec2(coords[${A}], coords[${y}]) * strides - pads;
|
|
int xRCorner = xRCCorner.x;
|
|
int xCCorner = xRCCorner.y;
|
|
|
|
// Convolve x(?, ?, d1) with w(:, :, d1, d2) to get y(yR, yC, d2).
|
|
// ? = to be determined. : = across all values in that axis.
|
|
float dotProd = 0.0;
|
|
for (int wR = 0; wR < ${h}; wR++) {
|
|
int xR = xRCorner + wR * ${u};
|
|
|
|
if (xR < 0 || xR >= ${e.inHeight}) {
|
|
continue;
|
|
}
|
|
|
|
for (int wC = 0; wC < ${d}; 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;
|
|
${w}
|
|
${_}
|
|
setOutput(result);
|
|
}
|
|
`}},FB=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,n=e.padInfo.top,r=e.padInfo.left,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,c=e.filterDepth,h=e.filterHeight,d=e.filterWidth,p=Math.floor(e.inChannels/4)*4,f=e.inChannels%4;this.userCode=`
|
|
const ivec3 strides = ivec3(${a}, ${s}, ${i});
|
|
const ivec3 pads = ivec3(${t}, ${n}, ${r});
|
|
|
|
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 * ${o};
|
|
|
|
if (xF < 0 || xF >= ${e.inDepth}) {
|
|
continue;
|
|
}
|
|
|
|
for (int wR = 0; wR < ${h}; wR++) {
|
|
int xR = xRCorner + wR * ${l};
|
|
|
|
if (xR < 0 || xR >= ${e.inHeight}) {
|
|
continue;
|
|
}
|
|
|
|
for (int wC = 0; wC < ${d}; wC++) {
|
|
int xC = xCCorner + wC * ${u};
|
|
|
|
if (xC < 0 || xC >= ${e.inWidth}) {
|
|
continue;
|
|
}
|
|
|
|
for (int d1 = 0; d1 < ${p}; d1 += 4) {
|
|
vec4 xValues = vec4(
|
|
getX(batch, xF, xR, xC, d1),
|
|
getX(batch, xF, xR, xC, d1 + 1),
|
|
getX(batch, xF, xR, xC, d1 + 2),
|
|
getX(batch, xF, xR, xC, d1 + 3)
|
|
);
|
|
vec4 wValues = vec4(
|
|
getW(wF, wR, wC, d1, d2),
|
|
getW(wF, wR, wC, d1 + 1, d2),
|
|
getW(wF, wR, wC, d1 + 2, d2),
|
|
getW(wF, wR, wC, d1 + 3, d2)
|
|
);
|
|
|
|
dotProd += dot(xValues, wValues);
|
|
}
|
|
|
|
if (${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);
|
|
}
|
|
`}},MB=class{constructor(e,t,n){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let{filterWidth:r,inChannels:a,strideWidth:s,strideHeight:i,padInfo:o,outWidth:l,dilationWidth:u,dilationHeight:c,dataFormat:h}=n,{left:d,top:p}=o,f=a*r,m=gn(),A=h==="channelsLast",y=A?0:1,g=A?1:2,b="";for(let _=0;_<=1;_++)for(let w=0;w<=1;w++)b+=`
|
|
blockIndex = rc.y + ${w};
|
|
pos = rc.x + ${_};
|
|
|
|
if(blockIndex < ${e[1]} && pos < ${e[0]}) {
|
|
offsetY = int(blockIndex / (${l})) * ${i} - ${p};
|
|
d0 = offsetY + ${c} * (pos / ${f});
|
|
|
|
if(d0 < ${t[y]} && d0 >= 0) {
|
|
|
|
offsetX = int(mod(float(blockIndex), ${l}.) * ${s}. - ${d}.);
|
|
d1 = offsetX + ${u} * (int(mod(float(pos), ${f}.) / ${a}.));
|
|
|
|
if(d1 < ${t[g]} && d1 >= 0) {
|
|
|
|
ch = int(mod(float(pos), ${a}.));
|
|
|
|
if (${A}) {
|
|
innerDims = vec2(d1, ch);
|
|
result[${_*2+w}] = getChannel(
|
|
getA(d0, int(innerDims.x),
|
|
int(innerDims.y)), innerDims);
|
|
} else {
|
|
innerDims = vec2(d0, d1);
|
|
result[${_*2+w}] = 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;
|
|
|
|
${b}
|
|
|
|
${m.output} = result;
|
|
}
|
|
`}};function w_({x:e,filter:t,convInfo:n,backend:r,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let l=e.shape,u=r.texData.get(e.dataId),c=n.inChannels,h=l[0]*l[1]*l[2],d=n.outChannels,p=n.dataFormat==="channelsLast",f=!1,m=!1,A,y=[],g=(h===1||d===1)&&c>l_,b=l[2]%2!=0&&!!u.isPacked;if(g||!J().getBool("WEBGL_LAZILY_UNPACK")||!J().getBool("WEBGL_PACK_BINARY_OPERATIONS")||!b){let _=p?l[0]*l[1]*l[2]:l[0]*l[2]*l[3],w=xe({inputs:{x:e},backend:r,attrs:{shape:[1,_,n.inChannels]}}),x=xe({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}}),N=Np({a:w,b:x,transposeA:f,transposeB:m,backend:r,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i});A=xe({inputs:{x:N},backend:r,attrs:{shape:n.outShape}}),y.push(w),y.push(x),y.push(N)}else{let _=p?l[0]*l[1]*(l[2]+1):l[0]*l[2]*(l[3]+1),w={dataId:e.dataId,shape:[1,_,n.inChannels],dtype:e.dtype},x=u.shape;u.shape=u.shape.slice(),u.shape[u.shape.length-2]++,v.assert(fc(u.shape,w.shape),()=>`packed reshape ${u.shape} to ${w.shape} isn't free`);let N=xe({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}});y.push(N);let S=Np({a:w,b:N,backend:r,transposeA:f,transposeB:m,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),T=r.texData.get(S.dataId);v.assert(T.isPacked,()=>"batchMatMul result is expected to be packed"),u.shape=x,T.shape=n.outShape,A=Bn({inputs:{x:S},backend:r}),A.shape=n.outShape,y.push(S)}for(let _ of y)r.disposeIntermediateTensorInfo(_);return A}function b_({x:e,filter:t,convInfo:n,backend:r,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let{filterWidth:l,filterHeight:u,inChannels:c,outWidth:h,outHeight:d,dataFormat:p}=n,f=p==="channelsLast",m=l*u*c,A=d*h,y=[m,A],g=!0,b=!1,_=[],w=xe({inputs:{x:e},backend:r,attrs:{shape:e.shape.slice(1)}}),x=xe({inputs:{x:t},backend:r,attrs:{shape:[1,m,v.sizeFromShape(t.shape)/m]}});_.push(w),_.push(x);let N=new MB(y,w.shape,n),S=r.runWebGLProgram(N,[w],"float32"),T=xe({inputs:{x:S},backend:r,attrs:{shape:[1,y[0],y[1]]}});_.push(S),_.push(T);let M=a!=null,D=s!=null,z=o==="leakyrelu",W=o?kp(o,!0):null,U=new n_(T.shape,x.shape,[1,A,n.outChannels],g,b,M,W,D,z),H=[T,x];if(a&&H.push(a),D&&H.push(s),z){let Y=r.makeTensorInfo([],"float32",v.createScalarValue(i,"float32"));H.push(Y),_.push(Y)}let X=r.runWebGLProgram(U,H,"float32"),j=f?[1,d,h,n.outChannels]:[1,n.outChannels,d,h],ee=xe({inputs:{x:X},backend:r,attrs:{shape:j}});_.push(X);for(let Y of _)r.disposeIntermediateTensorInfo(Y);return ee}function $B(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:u,dimRoundingMode:c}=r,h=R.convertConv2DDataFormat(l),d=R.computeConv2DInfo(a.shape,s.shape,i,u,o,c,!1,h),p;if(d.filterHeight===1&&d.filterWidth===1&&d.dilationHeight===1&&d.dilationWidth===1&&d.strideHeight===1&&d.strideWidth===1&&(d.padInfo.type==="SAME"||d.padInfo.type==="VALID"))p=w_({x:a,filter:s,convInfo:d,backend:n});else if(J().getBool("WEBGL_CONV_IM2COL")&&a.shape[0]===1)p=b_({x:a,filter:s,convInfo:d,backend:n});else{let m=new x_(d);p=n.runWebGLProgram(m,[a,s],"float32")}let f=xe({inputs:{x:p},backend:n,attrs:{shape:d.outShape}});return n.disposeIntermediateTensorInfo(p),f}var DB={kernelName:ws,backendName:"webgl",kernelFunc:$B},OB=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,a=e.padInfo.left,s=e.dataFormat==="channelsLast";this.userCode=`
|
|
void main() {
|
|
ivec4 coords = getOutputCoords();
|
|
int wR = coords.x;
|
|
int wC = coords.y;
|
|
int d1 = coords.z;
|
|
int d2 = coords.w;
|
|
|
|
// Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2).
|
|
// ? = to be determined. : = across all values in that axis.
|
|
float dotProd = 0.0;
|
|
|
|
for (int b = 0; b < ${e.batchSize}; b++) {
|
|
for (int yR = 0; yR < ${e.outHeight}; yR++) {
|
|
int xR = wR + yR * ${t} - ${r};
|
|
|
|
if (xR < 0 || xR >= ${e.inHeight}) {
|
|
continue;
|
|
}
|
|
|
|
for (int yC = 0; yC < ${e.outWidth}; yC++) {
|
|
int xC = wC + yC * ${n} - ${a};
|
|
|
|
if (xC < 0 || xC >= ${e.inWidth}) {
|
|
continue;
|
|
}
|
|
|
|
if (${s}) {
|
|
float dyValue = getDy(b, yR, yC, d2);
|
|
float xValue = getX(b, xR, xC, d1);
|
|
dotProd += (xValue * dyValue);
|
|
} else {
|
|
float dyValue = getDy(b, d2, yR, yC);
|
|
float xValue = getX(b, d1, xR, xC);
|
|
dotProd += (xValue * dyValue);
|
|
}
|
|
|
|
}
|
|
}
|
|
}
|
|
setOutput(dotProd);
|
|
}
|
|
`}},zB=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=e.dataFormat==="channelsLast",i=t-1-e.padInfo.top,o=n-1-e.padInfo.left,l=s?1:2,u=s?2:3,c=s?3:1;this.userCode=`
|
|
const ivec2 pads = ivec2(${i}, ${o});
|
|
|
|
void main() {
|
|
ivec4 coords = getOutputCoords();
|
|
int batch = coords[0];
|
|
int d1 = coords[${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) / ${r}.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) / ${a}.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 < ${e.outChannels}; d2++) {
|
|
|
|
if (${s}) {
|
|
float xValue = getDy(batch, idyR, idyC, d2);
|
|
float wValue = getW(wRPerm, wCPerm, d1, d2);
|
|
dotProd += xValue * wValue;
|
|
} else {
|
|
float xValue = getDy(batch, d2, idyR, idyC);
|
|
float wValue = getW(wRPerm, wCPerm, d1, d2);
|
|
dotProd += xValue * wValue;
|
|
}
|
|
|
|
}
|
|
}
|
|
}
|
|
setOutput(dotProd);
|
|
}
|
|
`}},PB=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,a=e.padInfo.front,s=e.padInfo.top,i=e.padInfo.left;this.userCode=`
|
|
void main() {
|
|
ivec5 coords = getOutputCoords();
|
|
int wF = coords.x;
|
|
int wR = coords.y;
|
|
int wC = coords.z;
|
|
int d1 = coords.w;
|
|
int d2 = coords.u;
|
|
|
|
float dotProd = 0.0;
|
|
|
|
for (int b = 0; b < ${e.batchSize}; b++) {
|
|
for (int yF = 0; yF < ${e.outDepth}; yF++) {
|
|
int xF = wF + yF * ${t} - ${a};
|
|
|
|
if (xF < 0 || xF >= ${e.inDepth}) {
|
|
continue;
|
|
}
|
|
|
|
for (int yR = 0; yR < ${e.outHeight}; yR++) {
|
|
int xR = wR + yR * ${n} - ${s};
|
|
|
|
if (xR < 0 || xR >= ${e.inHeight}) {
|
|
continue;
|
|
}
|
|
|
|
for (int yC = 0; yC < ${e.outWidth}; yC++) {
|
|
int xC = wC + yC * ${r} - ${i};
|
|
|
|
if (xC < 0 || xC >= ${e.inWidth}) {
|
|
continue;
|
|
}
|
|
|
|
float dyValue = getDy(b, yF, yR, yC, d2);
|
|
float xValue = getX(b, xF, xR, xC, d1);
|
|
dotProd += (xValue * dyValue);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
setOutput(dotProd);
|
|
}
|
|
`}},LB=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=t-1-e.padInfo.front,l=n-1-e.padInfo.top,u=r-1-e.padInfo.left;this.userCode=`
|
|
const ivec3 pads = ivec3(${o}, ${l}, ${u});
|
|
|
|
void main() {
|
|
ivec5 coords = getOutputCoords();
|
|
int batch = coords.x;
|
|
int d1 = coords.u;
|
|
|
|
|
|
ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
|
|
int dyFCorner = dyCorner.x;
|
|
int dyRCorner = dyCorner.y;
|
|
int dyCCorner = dyCorner.z;
|
|
|
|
float dotProd = 0.0;
|
|
for (int wF = 0; wF < ${t}; wF++) {
|
|
float dyF = float(dyFCorner + wF) / ${a}.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) / ${s}.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 < ${r}; wC++) {
|
|
float dyC = float(dyCCorner + wC) / ${i}.0;
|
|
|
|
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
|
|
fract(dyC) > 0.0) {
|
|
continue;
|
|
}
|
|
int idyC = int(dyC);
|
|
|
|
int wCPerm = ${r} - 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 WB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:u,filterShape:c}=r,h=R.convertConv2DDataFormat(l),d=R.computeConv2DInfo(a.shape,c,i,1,o,u,!1,h),p=new OB(d);return n.runWebGLProgram(p,[a,s],"float32")}var BB={kernelName:Bh,backendName:"webgl",kernelFunc:WB};function VB(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:u,dimRoundingMode:c}=r,h=R.convertConv2DDataFormat(u),d=R.computeConv2DInfo(i,s.shape,o,1,l,c,!1,h),p=new zB(d);return n.runWebGLProgram(p,[a,s],"float32")}var UB={kernelName:bs,backendName:"webgl",kernelFunc:VB};function HB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r,u=R.computeConv3DInfo(a.shape,s.shape,i,l,o),c=new FB(u);return n.runWebGLProgram(c,[a,s],"float32")}var jB={kernelName:bu,backendName:"webgl",kernelFunc:HB};function GB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,filterShape:l}=r,u=R.computeConv3DInfo(a.shape,l,i,1,o),c=new PB(u);return n.runWebGLProgram(c,[a,s],"float32")}var qB={kernelName:Vh,backendName:"webgl",kernelFunc:GB};function XB(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{pad:i,strides:o,inputShape:l}=r,u=R.computeConv3DInfo(l,s.shape,o,1,i),c=new LB(u);return n.runWebGLProgram(c,[a,s],"float32")}var KB={kernelName:Uh,backendName:"webgl",kernelFunc:XB},ZB=t_+`
|
|
return cos(x);
|
|
`,YB=Ye({opSnippet:ZB}),JB={kernelName:_s,backendName:"webgl",kernelFunc:YB},QB=`
|
|
float e2x = exp(-x);
|
|
return (e2x + 1.0 / e2x) / 2.0;
|
|
`,eV=Ye({opSnippet:QB}),tV={kernelName:mo,backendName:"webgl",kernelFunc:eV},nV=class{constructor(e,t,n,r,a){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[s,i,o,l]=e,[u]=t,[c,h]=n;this.outputShape=[u,c,h,l];let d=r==="bilinear"?1:0,[p,f]=[`${i-1}.0`,`${o-1}.0`],[m,A,y]=c>1?[`${(i-1)/(c-1)}`,"(y2-y1) * height_ratio",`y1*${p} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${p}`],[g,b,_]=h>1?[`${(o-1)/(h-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(${g});
|
|
void main() {
|
|
ivec4 coords = getOutputCoords();
|
|
int b = coords[0];
|
|
int y = coords[1];
|
|
int x = coords[2];
|
|
int d = coords[3];
|
|
|
|
// get box vals
|
|
float y1 = getBoxes(b,0);
|
|
float x1 = getBoxes(b,1);
|
|
float y2 = getBoxes(b,2);
|
|
float x2 = getBoxes(b,3);
|
|
|
|
// get image in batch index
|
|
int bInd = round(getBoxInd(b));
|
|
if(bInd < 0 || bInd >= ${s}) {
|
|
return;
|
|
}
|
|
|
|
float height_scale = ${A};
|
|
float width_scale = ${b};
|
|
|
|
float in_y = ${y};
|
|
if( in_y < 0.0 || in_y > ${p} ) {
|
|
setOutput(float(${a}));
|
|
return;
|
|
}
|
|
float in_x = ${_};
|
|
if( in_x < 0.0 || in_x > ${f} ) {
|
|
setOutput(float(${a}));
|
|
return;
|
|
}
|
|
|
|
vec2 sourceFracIndexCR = vec2(in_x,in_y);
|
|
if(${d} == 1) {
|
|
// Compute the four integer indices.
|
|
ivec2 sourceFloorCR = ivec2(sourceFracIndexCR);
|
|
ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR));
|
|
|
|
float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d);
|
|
float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d);
|
|
float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);
|
|
float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);
|
|
|
|
vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);
|
|
|
|
float top = topLeft + (topRight - topLeft) * fracCR.x;
|
|
float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;
|
|
float newValue = top + (bottom - top) * fracCR.y;
|
|
setOutput(newValue);
|
|
} else {
|
|
// Compute the coordinators of nearest neighbor point.
|
|
ivec2 sourceNearestCR = ivec2(floor(
|
|
sourceFracIndexCR + vec2(0.5,0.5)));
|
|
float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);
|
|
setOutput(newValue);
|
|
}
|
|
}
|
|
`}},rV=e=>{let{inputs:t,backend:n,attrs:r}=e,{image:a,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:u}=r,c=new nV(a.shape,s.shape,o,l,u);return n.runWebGLProgram(c,[a,s,i],"float32")},aV={kernelName:Ao,backendName:"webgl",kernelFunc:rV},k_=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=e;let r=e.length,a=t?"0.0":`getX(${__(r,"coords")})`,s=e[e.length-1],i="",o="";t?(i=n?`end != ${s-1}`:"end != 0",o=n?"end + 1":"end - 1"):(i=n?`end + pow2 < ${s}`:"end >= pow2",o=n?"end + pow2":"end - pow2"),this.userCode=`
|
|
uniform float index;
|
|
void main() {
|
|
${dt(r)} coords = getOutputCoords();
|
|
int end = ${v_(r,"coords")};
|
|
float val = ${a};
|
|
int pow2 = int(pow(2.0, index));
|
|
if (${i}) {
|
|
int idx = ${o};
|
|
${v_(r,"coords")} = idx;
|
|
val += getX(${__(r,"coords")});
|
|
}
|
|
setOutput(val);
|
|
}
|
|
`}getCustomSetupFunc(e){return(t,n)=>{this.index==null&&(this.index=t.getUniformLocation(n,"index")),t.gl.uniform1f(this.index,e)}}};function __(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 ${e} is not yet supported`)}function v_(e,t){if(e===1)return`${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 ${e} is not yet supported`)}function sV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=r,l=a.shape.length,u=R.getAxesPermutation([s],l),c=a;u!=null&&(c=Cn({inputs:{x:a},backend:n,attrs:{perm:u}}));let h=R.getInnerMostAxes(1,l)[0];if(h!==l-1)throw new Error(`WebGL cumsum shader expects an inner-most axis=${a.shape.length-1} but got axis=${s}`);let d=c.shape[h],p=Bn({inputs:{x:c},backend:n});for(let f=0;f<=Math.ceil(Math.log2(d))-1;f++){let m=new k_(c.shape,!1,o),A=m.getCustomSetupFunc(f),y=p;p=n.runWebGLProgram(m,[p],p.dtype,A),n.disposeIntermediateTensorInfo(y)}if(i){let f=new k_(c.shape,i,o),m=p;p=n.runWebGLProgram(f,[p],p.dtype),n.disposeIntermediateTensorInfo(m)}if(u!=null){let f=R.getUndoAxesPermutation(u),m=Cn({inputs:{x:p},backend:n,attrs:{perm:f}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(c),m}return p}var iV={kernelName:vs,backendName:"webgl",kernelFunc:sV};function oV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i,binaryOutput:o}=r;if(a.shape.length===1){let l=n.readSync(a.dataId),u=n.readSync(s.dataId),c=Wb(l,u,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,c)}else if(a.shape.length===2){let l=n.bufferSync(a),u=n.bufferSync(s),c=OP(l,u,i,o);return n.makeTensorInfo(c.shape,s.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${a.shape.length}.`)}var lV={kernelName:Hh,backendName:"webgl",kernelFunc:oV},uV=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 cV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockSize:s,dataFormat:i}=r;v.assert(s>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${s}`);let o=a.shape[0],l=i==="NHWC"?a.shape[1]:a.shape[2],u=i==="NHWC"?a.shape[2]:a.shape[3],c=i==="NHWC"?a.shape[3]:a.shape[1],h=l*s,d=u*s,p=c/(s*s),f=i==="NHWC"?[o,h,d,p]:[o,p,h,d],m=new uV(f,s,i);return n.runWebGLProgram(m,[a],a.dtype)}var hV={kernelName:yo,backendName:"webgl",kernelFunc:cV},I_=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.inHeight,i=e.inWidth,o=e.padInfo.top,l=e.padInfo.left,u=e.strideHeight,c=e.strideWidth,h=e.dilationHeight,d=e.dilationWidth,p=e.filterHeight,f=e.filterWidth,m=e.outChannels/e.inChannels,A="",y="";n&&(r?A=`float activation(float a) {
|
|
float b = getPreluActivationWeightsAtOutCoords();
|
|
${n}
|
|
}`:a?A=`float activation(float a) {
|
|
float b = getLeakyreluAlphaAtOutCoords();
|
|
${n}
|
|
}`:A=`
|
|
float activation(float x) {
|
|
${n}
|
|
}
|
|
`,y="result = activation(result);");let g=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
|
|
${A}
|
|
|
|
const ivec2 strides = ivec2(${u}, ${c});
|
|
const ivec2 pads = ivec2(${o}, ${l});
|
|
|
|
void main() {
|
|
ivec4 coords = getOutputCoords();
|
|
int batch = coords.x;
|
|
ivec2 xRCCorner = coords.yz * strides - pads;
|
|
int d2 = coords.w;
|
|
int d1 = d2 / ${m};
|
|
int q = d2 - d1 * ${m};
|
|
|
|
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 < ${p}; wR++) {
|
|
int xR = xRCorner + wR * ${h};
|
|
|
|
if (xR < 0 || xR >= ${s}) {
|
|
continue;
|
|
}
|
|
|
|
for (int wC = 0; wC < ${f}; wC++) {
|
|
int xC = xCCorner + wC * ${d};
|
|
|
|
if (xC < 0 || xC >= ${i}) {
|
|
continue;
|
|
}
|
|
|
|
float xVal = getX(batch, xR, xC, d1);
|
|
float wVal = getW(wR, wC, d1, q);
|
|
dotProd += xVal * wVal;
|
|
}
|
|
}
|
|
|
|
float result = dotProd;
|
|
${g}
|
|
${y}
|
|
setOutput(result);
|
|
}
|
|
`}},N_=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e.outShape;let s=e.inHeight,i=e.inWidth,o=e.padInfo.top,l=e.padInfo.left,u=e.strideHeight,c=e.strideWidth,h=e.dilationHeight,d=e.dilationWidth,p=e.filterHeight,f=e.filterWidth,m=f,A="int xR; int xC; int xCOffset;";for(let _=0;_<p;_++)for(let w=0;w<f;w++)A+=`
|
|
vec4 xTexelR${_}C${w*2} = vec4(0.);
|
|
vec4 wR${_}C${w} = vec4(0.);
|
|
vec4 xR${_}C${w} = vec4(0.);`;for(let _=0;_<p;_++)for(let w=0;w<m;w++){let x=w*2;if(A+=`
|
|
xR = xRCorner + ${_*h};
|
|
xC = xCCorner + ${x*d};
|
|
`,c===1){if(x<f&&(l%2==1?A+=`
|
|
xCOffset = xC + 1;
|
|
if(xR >= 0 && xR < ${s} && xCOffset >= 0 && xCOffset < ${i}) {
|
|
xTexelR${_}C${x} = getX(batch, xR, xCOffset, d1);
|
|
|
|
// Need to manually clear unused channels in case
|
|
// we're reading from recycled texture.
|
|
if(xCOffset + 1 >= ${i}) {
|
|
xTexelR${_}C${x}.zw = vec2(0.);
|
|
}
|
|
} else {
|
|
xTexelR${_}C${x} = vec4(0.);
|
|
}
|
|
|
|
xCOffset = xC + 1 - 2;
|
|
if(xR >= 0 && xR < ${s} && xCOffset >= 0 && xCOffset < ${i}) {
|
|
vec4 previous = getX(batch, xR, xCOffset, d1);
|
|
|
|
// Need to manually clear unused channels in case
|
|
// we're reading from recycled texture.
|
|
if(xCOffset + 1 >= ${i}) {
|
|
previous.zw = vec2(0.);
|
|
}
|
|
|
|
xR${_}C${x} = vec4(previous.zw, xTexelR${_}C${x}.xy);
|
|
} else {
|
|
xR${_}C${x} = vec4(0, 0, xTexelR${_}C${x}.xy);
|
|
}
|
|
`:A+=`
|
|
if(xR >= 0 && xR < ${s} && xC >= 0 && xC < ${i}) {
|
|
xTexelR${_}C${x} = getX(batch, xR, xC, d1);
|
|
} else {
|
|
xTexelR${_}C${x} = vec4(0.);
|
|
}
|
|
|
|
xR${_}C${x} = xTexelR${_}C${x};
|
|
`,x+1<f)){let N=l%2==0?v.nearestLargerEven(d):d;d%2==0&&l%2==1||d%2!=0&&l%2!=1?(A+=`
|
|
xCOffset = xC + ${l%2} + ${N};
|
|
|
|
if(xR >= 0 && xR < ${s} &&
|
|
xCOffset >= 0 && xCOffset < ${i}) {
|
|
xTexelR${_}C${x+2} = getX(batch, xR, xCOffset, d1);
|
|
}
|
|
`,d>1&&(A+=`
|
|
xCOffset -= 2;
|
|
if(xR >= 0 && xR < ${s} &&
|
|
xCOffset >= 0 && xCOffset < ${i}) {
|
|
xTexelR${_}C${x} = getX(batch, xR, xCOffset, d1);
|
|
} else {
|
|
xTexelR${_}C${x} = vec4(0.);
|
|
}
|
|
`),A+=`
|
|
xR${_}C${x+1} = vec4(
|
|
xTexelR${_}C${x}.zw, xTexelR${_}C${x+2}.xy);
|
|
`):A+=`
|
|
xCOffset = xC + ${N};
|
|
|
|
if(xR >= 0 && xR < ${s} &&
|
|
xCOffset >= 0 && xCOffset < ${i}) {
|
|
xTexelR${_}C${x+2} = getX(batch, xR, xCOffset, d1);
|
|
}
|
|
|
|
xR${_}C${x+1} = xTexelR${_}C${x+2};
|
|
`}}else x<f&&(A+=`
|
|
if(xR >= 0 && xR < ${s}) {
|
|
`,l%2==1?(A+=`
|
|
xCOffset = xC + 1 - ${c};
|
|
if(xCOffset >= 0 && xCOffset < ${i}) {
|
|
xTexelR${_}C${x} = getX(batch, xR, xCOffset, d1);
|
|
} else {
|
|
xTexelR${_}C${x} = vec4(0.);
|
|
}
|
|
|
|
if(xC + 1 >= 0 && xC + 1 < ${i}) {
|
|
xTexelR${_}C${x+2} = getX(batch, xR, xC + 1, d1);
|
|
} else {
|
|
xTexelR${_}C${x+2} = vec4(0.);
|
|
}
|
|
|
|
xR${_}C${x} = vec4(
|
|
xTexelR${_}C${x}.zw, xTexelR${_}C${x+2}.zw);
|
|
`,x+1<f&&(A+=`
|
|
vec4 final = vec4(0.);
|
|
xCOffset = xC + 1 + ${c};
|
|
if(xCOffset >= 0 && xCOffset < ${i}) {
|
|
final = getX(batch, xR, xCOffset, d1);
|
|
}
|
|
xR${_}C${x+1} = vec4(xTexelR${_}C${x+2}.xy, final.xy);
|
|
`)):(A+=`
|
|
if(xC >= 0 && xC < ${i}) {
|
|
xTexelR${_}C${x} = getX(batch, xR, xC, d1);
|
|
} else {
|
|
xTexelR${_}C${x} = vec4(0.);
|
|
}
|
|
|
|
xCOffset = xC + ${c};
|
|
if(xCOffset >= 0 && xCOffset < ${i}) {
|
|
xTexelR${_}C${x+2} = getX(batch, xR, xCOffset, d1);
|
|
} else {
|
|
xTexelR${_}C${x+2} = vec4(0.);
|
|
}
|
|
|
|
xR${_}C${x} = vec4(
|
|
xTexelR${_}C${x}.xy, xTexelR${_}C${x+2}.xy);
|
|
`,x+1<f&&(A+=`
|
|
xR${_}C${x+1} = vec4(
|
|
xTexelR${_}C${x}.zw, xTexelR${_}C${x+2}.zw);
|
|
`)),A+="}");x<f&&(A+=`
|
|
vec4 wTexelR${_}C${x} = getW(${_}, ${x}, d1, q);
|
|
wR${_}C${x} = vec4(wTexelR${_}C${x}.xz, wTexelR${_}C${x}.xz);
|
|
`,x+1<f&&(A+=`
|
|
vec4 wTexelR${_}C${x+1} = getW(${_}, ${x+1}, d1, q);
|
|
wR${_}C${x+1} =
|
|
vec4(wTexelR${_}C${x+1}.xz, wTexelR${_}C${x+1}.xz);`))}for(let _=0;_<p;_++)for(let w=0;w<f;w++)A+=`dotProd += xR${_}C${w} * wR${_}C${w};`;let y="",g="";n&&(r?y=`vec4 activation(vec4 a) {
|
|
vec4 b = getPreluActivationWeightsAtOutCoords();
|
|
${n}
|
|
}`:a?y=`vec4 activation(vec4 a) {
|
|
vec4 b = getLeakyreluAlphaAtOutCoords();
|
|
${n}
|
|
}`:y=`vec4 activation(vec4 x) {
|
|
${n}
|
|
}`,g="result = activation(result);");let b=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
|
|
${y}
|
|
|
|
const ivec2 strides = ivec2(${u}, ${c});
|
|
const ivec2 pads = ivec2(${o}, ${l});
|
|
|
|
void main() {
|
|
|
|
ivec4 coords = getOutputCoords();
|
|
int batch = coords.x;
|
|
ivec2 xRCCorner = coords.yz * strides - pads;
|
|
int d2 = coords.w;
|
|
int d1 = d2;
|
|
int q = 0;
|
|
int xRCorner = xRCCorner.x;
|
|
int xCCorner = xRCCorner.y;
|
|
|
|
vec4 dotProd = vec4(0.);
|
|
|
|
${A}
|
|
|
|
vec4 result = dotProd;
|
|
${b}
|
|
${g}
|
|
setOutput(result);
|
|
}
|
|
`}};function dV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l,dimRoundingMode:u}=r,c=l;c==null&&(c=[1,1]),v.assert(R.eitherStridesOrDilationsAreOne(i,c),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${c}'`);let h=R.computeConv2DInfo(a.shape,s.shape,i,c,o,u,!0),d;return J().getBool("WEBGL_PACK_DEPTHWISECONV")&&h.strideWidth<=2&&h.outChannels/h.inChannels==1?d=new N_(h):d=new I_(h),n.runWebGLProgram(d,[a,s],"float32")}var pV={kernelName:ks,backendName:"webgl",kernelFunc:dV},fV=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,a=e.padInfo.left,s=e.outChannels/e.inChannels;this.userCode=`
|
|
void main() {
|
|
ivec4 coords = getOutputCoords();
|
|
int wR = coords.x;
|
|
int wC = coords.y;
|
|
int d1 = coords.z;
|
|
int dm = coords.w;
|
|
int d2 = d1 * ${s} + dm;
|
|
|
|
float dotProd = 0.0;
|
|
|
|
// TO DO: Vec4 over the batch size
|
|
for (int b = 0; b < ${e.batchSize}; b++) {
|
|
for (int yR = 0; yR < ${e.outHeight}; yR++) {
|
|
int xR = wR + yR * ${t} - ${r};
|
|
|
|
if (xR < 0 || xR >= ${e.inHeight}) {
|
|
continue;
|
|
}
|
|
|
|
for (int yC = 0; yC < ${e.outWidth}; yC++) {
|
|
int xC = wC + yC * ${n} - ${a};
|
|
|
|
if (xC < 0 || xC >= ${e.inWidth}) {
|
|
continue;
|
|
}
|
|
|
|
float dyValue = getDy(b, yR, yC, d2);
|
|
float xValue = getX(b, xR, xC, d1);
|
|
dotProd += (xValue * dyValue);
|
|
}
|
|
}
|
|
}
|
|
setOutput(dotProd);
|
|
}
|
|
`}},mV=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=t-1-e.padInfo.top,i=n-1-e.padInfo.left,o=e.outChannels/e.inChannels;this.userCode=`
|
|
const ivec2 pads = ivec2(${s}, ${i});
|
|
|
|
void main() {
|
|
ivec4 coords = getOutputCoords();
|
|
int batch = coords[0];
|
|
int d1 = coords[3];
|
|
ivec2 dyCorner = coords.yz - pads;
|
|
int dyRCorner = dyCorner.x;
|
|
int dyCCorner = dyCorner.y;
|
|
|
|
float dotProd = 0.0;
|
|
|
|
for (int wR = 0; wR < ${t}; wR++) {
|
|
float dyR = float(dyRCorner + wR) / ${r}.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) / ${a}.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 < ${o}; dm++) {
|
|
int d2 = d1 * ${o} + dm;
|
|
float xValue = getDy(batch, idyR, idyC, d2);
|
|
float wValue = getW(wRPerm, wCPerm, d1, dm);
|
|
dotProd += xValue * wValue;
|
|
}
|
|
}
|
|
}
|
|
setOutput(dotProd);
|
|
}
|
|
`}};function AV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,filterShape:c}=r,h=R.computeConv2DInfo(a.shape,c,i,o,l,u,!0),d=new fV(h);return n.runWebGLProgram(d,[a,s],"float32")}var yV={kernelName:jh,backendName:"webgl",kernelFunc:AV};function gV(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,inputShape:c}=r,h=R.computeConv2DInfo(c,s.shape,i,o,l,u,!0),d=new mV(h);return n.runWebGLProgram(d,[a,s],"float32")}var xV={kernelName:Gh,backendName:"webgl",kernelFunc:gV},wV=class{constructor(e){this.variableNames=["X"],this.outputShape=[e,e],this.userCode=`
|
|
void main() {
|
|
ivec2 coords = getOutputCoords();
|
|
float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;
|
|
setOutput(val);
|
|
}
|
|
`}};function bV(e){let{inputs:t,backend:n}=e,{x:r}=t,a=[...r.shape,...r.shape],s=v.sizeFromShape(r.shape),i=xe({inputs:{x:r},backend:n,attrs:{shape:[s]}}),o=new wV(s),l=n.runWebGLProgram(o,[i],i.dtype),u=xe({inputs:{x:l},backend:n,attrs:{shape:a}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(l),u}var _V={kernelName:qh,backendName:"webgl",kernelFunc:bV},vV=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:n,padInfo:r,strideHeight:a,strideWidth:s,filterHeight:i,filterWidth:o,dilationHeight:l,dilationWidth:u}=e,{top:c,left:h}=r;this.userCode=`
|
|
const ivec2 strides = ivec2(${a}, ${s});
|
|
const ivec2 pads = ivec2(${c}, ${h});
|
|
const float neg_infinity = -3.4e38;
|
|
|
|
void main() {
|
|
ivec4 coords = getOutputCoords();
|
|
int batch = coords.x;
|
|
int d1 = coords.w;
|
|
ivec2 outTopLeftCorner =
|
|
coords.yz * strides - pads;
|
|
int hBeg = outTopLeftCorner.x;
|
|
int wBeg = outTopLeftCorner.y;
|
|
|
|
float curVal = neg_infinity;
|
|
for (int h = 0; h < ${i}; h++) {
|
|
int hIn = hBeg + h * ${l};
|
|
|
|
if (hIn >= 0 && hIn < ${t}) {
|
|
for (int w = 0; w < ${o}; w++) {
|
|
int wIn = wBeg + w * ${u};
|
|
|
|
if (wIn >= 0 && wIn < ${n}) {
|
|
float xVal = getX(batch, hIn, wIn, d1);
|
|
float wVal = getW(h, w, d1);
|
|
|
|
float val = xVal + wVal;
|
|
if (val > curVal) {
|
|
curVal = val;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
float result = curVal;
|
|
setOutput(result);
|
|
}
|
|
`}};function kV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r,u=R.computeDilation2DInfo(a.shape,s.shape,i,o,"NHWC",l),c,h=new vV(u);c=n.runWebGLProgram(h,[a,s],"float32");let d=xe({inputs:{x:c},backend:n,attrs:{shape:u.outShape}});return n.disposeIntermediateTensorInfo(c),d}var IV={kernelName:_u,backendName:"webgl",kernelFunc:kV},NV="return (x >= 0.0) ? x : (exp(x) - 1.0);",SV=`
|
|
vec4 result;
|
|
|
|
result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);
|
|
result.g = (x.g >= 0.0) ? x.g : (exp(x.g) - 1.0);
|
|
result.b = (x.b >= 0.0) ? x.b : (exp(x.b) - 1.0);
|
|
result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);
|
|
|
|
return result;
|
|
`,TV=Ye({opSnippet:NV,packedOpSnippet:SV}),EV={kernelName:go,backendName:"webgl",kernelFunc:TV},CV="return (b >= 1.0) ? a : a * (b + 1.0);",RV=`
|
|
vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
|
|
return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
|
|
`,FV=e=>{let{inputs:t,backend:n}=e,{dy:r,y:a}=t,s=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new xc(RV,r.shape,a.shape):new Wl(CV,r.shape,a.shape);return n.runWebGLProgram(s,[r,a],r.dtype)},MV={kernelName:Zh,backendName:"webgl",kernelFunc:FV},$V=`
|
|
return vec4(equal(a, b));
|
|
`,DV="return float(a == b);",OV=on({opSnippet:DV,packedOpSnippet:$V,dtype:"bool"}),zV={kernelName:wo,backendName:"webgl",kernelFunc:OV},PV=`
|
|
// Error function is calculated approximately with elementary function.
|
|
// See "Handbook of Mathematical Functions with Formulas,
|
|
// Graphs, and Mathematical Tables", Abramowitz and Stegun.
|
|
float p = ${R.ERF_P};
|
|
float a1 = ${R.ERF_A1};
|
|
float a2 = ${R.ERF_A2};
|
|
float a3 = ${R.ERF_A3};
|
|
float a4 = ${R.ERF_A4};
|
|
float a5 = ${R.ERF_A5};
|
|
|
|
float sign = sign(x);
|
|
x = abs(x);
|
|
float t = 1.0 / (1.0 + p * x);
|
|
return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));
|
|
`,LV=Ye({opSnippet:PV}),WV={kernelName:xo,backendName:"webgl",kernelFunc:LV},S_="return exp(x);",T_=Ye({opSnippet:S_,packedOpSnippet:S_,cpuKernelImpl:LP}),BV={kernelName:Ns,backendName:"webgl",kernelFunc:T_};function wA(e){let{inputs:t,attrs:n,backend:r}=e,{dim:a}=n,{input:s}=t,i=s.shape.length,o=s.shape.slice(),l=a;return a<0&&(v.assert(-(i+1)<=a,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+a+1),o.splice(l,0,1),xe({inputs:{x:s},backend:r,attrs:{shape:o}})}var VV={kernelName:bo,backendName:"webgl",kernelFunc:wA},E_="return exp(x) - 1.0;",UV=Ye({opSnippet:E_,packedOpSnippet:E_,cpuKernelImpl:WP}),HV={kernelName:_o,backendName:"webgl",kernelFunc:UV},C_=class{constructor(e,t,n){this.variableNames=["real","imag"];let r=t[1];this.outputShape=t;let a=n?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,s=n?`${r}.0`:"1.0",i;if(e==="real")i="return real * expR - imag * expI;";else if(e==="imag")i="return real * expI + imag * expR;";else throw new Error(`FFT component must be either "real" or "imag", got ${e}.`);this.userCode=`
|
|
const float exponentMultiplier = ${a};
|
|
|
|
float unaryOpComplex(float real, float expR, float imag, float expI) {
|
|
${i}
|
|
}
|
|
|
|
float mulMatDFT(int batch, int index) {
|
|
float indexRatio = float(index) / float(${r});
|
|
float exponentMultiplierTimesIndexRatio =
|
|
exponentMultiplier * indexRatio;
|
|
|
|
float result = 0.0;
|
|
|
|
for (int i = 0; i < ${r}; i++) {
|
|
// x = (-2|2 * PI / N) * index * i;
|
|
float x = exponentMultiplierTimesIndexRatio * float(i);
|
|
float expR = cos(x);
|
|
float expI = sin(x);
|
|
float real = getReal(batch, i);
|
|
float imag = getImag(batch, i);
|
|
|
|
result +=
|
|
unaryOpComplex(real, expR, imag, expI) / ${s};
|
|
}
|
|
|
|
return result;
|
|
}
|
|
|
|
void main() {
|
|
ivec2 coords = getOutputCoords();
|
|
setOutput(mulMatDFT(coords[0], coords[1]));
|
|
}
|
|
`}};function R_(e,t,n){let r=n.texData.get(e.dataId),a=v.sizeFromShape(e.shape),s=e.shape[e.shape.length-1],i=a/s,o=xe({inputs:{x:e},backend:n,attrs:{shape:[i,s]}}),l=o.shape,u=new C_("real",l,t),c=new C_("imag",l,t),h=[{dataId:r.complexTensorInfos.real.dataId,dtype:r.complexTensorInfos.real.dtype,shape:l},{dataId:r.complexTensorInfos.imag.dataId,dtype:r.complexTensorInfos.imag.dtype,shape:l}],d=n.runWebGLProgram(u,h,"float32"),p=n.runWebGLProgram(c,h,"float32"),f=Xa({inputs:{real:d,imag:p},backend:n});n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p);let m=xe({inputs:{x:f},backend:n,attrs:{shape:e.shape}});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(f),m}function jV(e){let{inputs:t,backend:n}=e,{input:r}=t;return R_(r,!1,n)}var GV={kernelName:Yh,backendName:"webgl",kernelFunc:jV},qV=class{constructor(e,t){this.outputShape=[],this.variableNames=["x"],this.outputShape=e,this.userCode=`
|
|
uniform float value;
|
|
void main() {
|
|
// Input can be obtained from uniform value.
|
|
setOutput(value);
|
|
}
|
|
`}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}};function bA(e){let{backend:t,attrs:n}=e,{shape:r,value:a}=n,{dtype:s}=n;if(s=s||v.inferDtype(a),s==="string"){let i=v.getArrayFromDType(s,v.sizeFromShape(r));return i.fill(a),t.makeTensorInfo(r,s,i)}else{let i=new qV(r,a),o=i.getCustomSetupFunc(a);return t.runWebGLProgram(i,[],s,o)}}var XV={kernelName:vu,backendName:"webgl",kernelFunc:bA},KV=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;
|
|
float outputValue;
|
|
if(coordX >= 0 && coordX < ${t}) {
|
|
outputValue = getImage(coords[0], coords[1], coordX, coords[3]);
|
|
} else {
|
|
outputValue = getImage(coords[0], coords[1], coords[2], coords[3]);
|
|
}
|
|
setOutput(outputValue);
|
|
}
|
|
`}},ZV={kernelName:vo,backendName:"webgl",kernelFunc:({inputs:e,backend:t})=>{let{image:n}=e,r=t,a=new KV(n.shape);return r.runWebGLProgram(a,[n],n.dtype)}},F_="return floor(x);",YV=Ye({opSnippet:F_,packedOpSnippet:F_,cpuKernelImpl:BP}),JV={kernelName:Ss,backendName:"webgl",kernelFunc:YV},QV=`
|
|
float s = sign(a) * sign(b);
|
|
int ia = round(a);
|
|
int ib = round(b);
|
|
if (ib != 0) {
|
|
// Windows (D3D) wants guaranteed non-zero int division at compile-time.
|
|
return float(idiv(ia, ib, s));
|
|
} else {
|
|
return NAN;
|
|
}
|
|
`,eU=`
|
|
ivec4 ia = round(a);
|
|
ivec4 ib = round(b);
|
|
bvec4 cond = notEqual(ib, ivec4(0));
|
|
ivec4 result = ivec4(0);
|
|
vec4 s = sign(a) * sign(b);
|
|
|
|
// Windows (D3D) wants guaranteed non-zero int division at compile-time.
|
|
if (cond[0]) {
|
|
result[0] = idiv(ia[0], ib[0], s[0]);
|
|
}
|
|
if (cond[1]) {
|
|
result[1] = idiv(ia[1], ib[1], s[1]);
|
|
}
|
|
if (cond[2]) {
|
|
result[2] = idiv(ia[2], ib[2], s[2]);
|
|
}
|
|
if (cond[3]) {
|
|
result[3] = idiv(ia[3], ib[3], s[3]);
|
|
}
|
|
return vec4(result);
|
|
`,tU=on({opSnippet:QV,packedOpSnippet:eU,dtype:"int32"}),nU={kernelName:Ts,backendName:"webgl",kernelFunc:tU},rU=class{constructor(e){this.variableNames=["A"];let t=gn(),[n,r]=e;this.outputShape=e,this.userCode=`
|
|
void main() {
|
|
ivec3 coords = getOutputCoords();
|
|
int texR = coords[0];
|
|
int texC = coords[1];
|
|
int depth = coords[2];
|
|
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${r}.0, ${n}.0);
|
|
|
|
vec4 values = ${t.texture2D}(A, uv);
|
|
float value;
|
|
if (depth == 0) {
|
|
value = values.r;
|
|
} else if (depth == 1) {
|
|
value = values.g;
|
|
} else if (depth == 2) {
|
|
value = values.b;
|
|
} else if (depth == 3) {
|
|
value = values.a;
|
|
}
|
|
|
|
setOutput(floor(value * 255.0 + 0.5));
|
|
}
|
|
`}},aU=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let t=gn(),[n,r]=e;this.outputShape=e,this.userCode=`
|
|
void main() {
|
|
ivec3 coords = getOutputCoords();
|
|
int texR = coords[0];
|
|
int texC = coords[1];
|
|
int depth = coords[2];
|
|
|
|
vec4 result = vec4(0.);
|
|
|
|
for(int row=0; row<=1; row++) {
|
|
for(int col=0; col<=1; col++) {
|
|
texC = coords[1] + row;
|
|
depth = coords[2] + col;
|
|
|
|
vec2 uv = (vec2(texC, texR) + halfCR) /
|
|
vec2(${r}.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;
|
|
}
|
|
`}},iU={kernelName:dd,backendName:"webgl",kernelFunc:sU},Vl;function sU(e){let{inputs:t,backend:n,attrs:r}=e,{pixels:a}=t,{numChannels:s}=r,i=typeof HTMLVideoElement!="undefined"&&a instanceof HTMLVideoElement,o=typeof HTMLImageElement!="undefined"&&a instanceof HTMLImageElement,[l,u]=i?[a.videoWidth,a.videoHeight]:[a.width,a.height],c=[u,l],h=[u,l,s];(o||i)&&(Vl==null&&(Vl=document.createElement("canvas").getContext("2d")),Vl.canvas.width=l,Vl.canvas.height=u,Vl.drawImage(a,0,0,l,u),a=Vl.canvas);let d=n.makeTensorInfo(c,"int32");n.texData.get(d.dataId).usage=tr.PIXELS,n.gpgpu.uploadPixelDataToTexture(n.getTexture(d.dataId),a);let p=J().getBool("WEBGL_PACK")?new aU(h):new rU(h),f=n.runWebGLProgram(p,[d],"int32");return n.disposeData(d.dataId),f}function oU(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dataFormat:c,dilations:h,dimRoundingMode:d,activation:p,leakyreluAlpha:f}=r,m=R.convertConv2DDataFormat(c),A=R.computeConv2DInfo(a.shape,s.shape,l,h,u,d,!1,m),y,g=[];if(A.filterHeight===1&&A.filterWidth===1&&A.dilationHeight===1&&A.dilationWidth===1&&A.strideHeight===1&&A.strideWidth===1&&(A.padInfo.type==="SAME"||A.padInfo.type==="VALID"))y=w_({x:a,filter:s,convInfo:A,backend:n,bias:i,activation:p,preluActivationWeights:o,leakyreluAlpha:f});else if(J().getBool("WEBGL_CONV_IM2COL")&&a.shape[0]===1)y=b_({x:a,filter:s,convInfo:A,backend:n,bias:i,activation:p,preluActivationWeights:o,leakyreluAlpha:f});else{let _=i!=null,w=o!=null,x=p==="leakyrelu",N=p?kp(p,!1):null,S=new x_(A,_,N,w,x),T=[a,s];if(i&&T.push(i),o&&T.push(o),x){let M=n.makeTensorInfo([],"float32",v.createScalarValue(f,"float32"));T.push(M),g.push(M)}y=n.runWebGLProgram(S,T,"float32")}let b=xe({inputs:{x:y},backend:n,attrs:{shape:A.outShape}});return g.push(y),g.forEach(_=>n.disposeIntermediateTensorInfo(_)),b}var lU={kernelName:oi,backendName:"webgl",kernelFunc:oU};function uU(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:c,dimRoundingMode:h,activation:d,leakyreluAlpha:p}=r,f=[],m=c;m==null&&(m=[1,1]),v.assert(R.eitherStridesOrDilationsAreOne(l,m),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${m}'`);let A=R.computeConv2DInfo(a.shape,s.shape,l,m,u,h,!0),y=J().getBool("WEBGL_PACK_DEPTHWISECONV")&&A.strideWidth<=2&&A.outChannels/A.inChannels==1,g=d?kp(d,y):null,b=[a,s],_=i!=null,w=o!=null,x=d==="leakyrelu";if(_&&b.push(i),w&&b.push(o),x){let T=n.makeTensorInfo([],"float32",v.createScalarValue(p,"float32"));b.push(T),f.push(T)}let N;y?N=new N_(A,_,g,w,x):N=new I_(A,_,g,w,x);let S=n.runWebGLProgram(N,b,"float32");return f.forEach(T=>n.disposeIntermediateTensorInfo(T)),S}var cU={kernelName:li,backendName:"webgl",kernelFunc:uU},hU=class{constructor(e,t,n){this.sliceDim=e,this.strides=t,this.variableNames=["x","indices"],this.outputShape=n;let r=dt(t.length),a=dt(n.length),s=this.sliceDim>1?"strides[j]":"strides";this.userCode=`
|
|
${r} strides = ${r}(${this.strides});
|
|
void main() {
|
|
${a} coords = getOutputCoords();
|
|
int flattenIndex = 0;
|
|
for (int j = 0; j < ${this.sliceDim}; j++) {
|
|
int index = round(getIndices(coords[0], j));
|
|
flattenIndex += index * ${s};
|
|
}
|
|
setOutput(getX(flattenIndex, coords[1]));
|
|
}
|
|
`}};function dU(e){let{inputs:t,backend:n}=e,{params:r,indices:a}=t,s=a.shape,i=s[s.length-1],[o,l,u,c]=R.prepareAndValidate(r,a),h=xe({inputs:{x:a},backend:n,attrs:{shape:[l,i]}}),d=xe({inputs:{x:r},backend:n,attrs:{shape:[v.sizeFromShape(r.shape)/u,u]}}),p=new hU(i,c,[l,u]),f=n.runWebGLProgram(p,[d,h],d.dtype),m=xe({inputs:{x:f},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(f),m}var pU={kernelName:Io,backendName:"webgl",kernelFunc:dU},mU=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let n=dt(this.rank),r=fU(e,2);this.userCode=`
|
|
void main() {
|
|
${n} resRC = getOutputCoords();
|
|
setOutput(getA(${r}));
|
|
}
|
|
`}};function fU(e,t){let n=["resRC.x","resRC.y","resRC.z","resRC.w"],r=[];for(let a=0;a<e.length;a++)a===2?r.push("int(getIndices(resRC.x, resRC.z))"):r.push(`${n[a]}`);return r.join()}function AU(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,indices:s}=t,{axis:i,batchDims:o}=r,l=v.parseAxisParam(i,a.shape)[0],u=R.segment_util.collectGatherOpShapeInfo(a,s,l,o),c=v.sizeFromShape(s.shape),h=[],d=xe({inputs:{x:a},backend:n,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),p=xe({inputs:{x:s},backend:n,attrs:{shape:[u.batchSize,c/u.batchSize]}});h.push(d),h.push(p);let f=[u.batchSize,u.outerSize,c/u.batchSize,u.sliceSize];if(n.shouldExecuteOnCPU([a,s])||a.dtype==="string"){let g=n.bufferSync(p),b=n.bufferSync(d),_=VP(b,g,f);return h.forEach(w=>n.disposeIntermediateTensorInfo(w)),n.makeTensorInfo(u.outputShape,_.dtype,_.values)}let m=new mU(d.shape,f),A=n.runWebGLProgram(m,[d,p],d.dtype);h.push(A);let y=xe({inputs:{x:A},backend:n,attrs:{shape:u.outputShape}});return h.forEach(g=>n.disposeIntermediateTensorInfo(g)),y}var yU={kernelName:ko,backendName:"webgl",kernelFunc:AU},gU="return float(a > b);",xU=`
|
|
return vec4(greaterThan(a, b));
|
|
`,wU=on({opSnippet:gU,packedOpSnippet:xU,cpuKernelImpl:UP,dtype:"bool"}),bU={kernelName:No,backendName:"webgl",kernelFunc:wU},_U="return float(a >= b);",vU=`
|
|
return vec4(greaterThanEqual(a, b));
|
|
`,kU=on({opSnippet:_U,packedOpSnippet:vU,dtype:"bool"}),IU={kernelName:Cs,backendName:"webgl",kernelFunc:kU};function NU(e){let{inputs:t,backend:n}=e,{input:r}=t;return R_(r,!0,n)}var SU={kernelName:Jh,backendName:"webgl",kernelFunc:NU},TU="return float(!isnan(x) && !isinf(x));",EU=Ye({opSnippet:TU,dtype:"bool"}),CU={kernelName:So,backendName:"webgl",kernelFunc:EU},RU="return float(isinf(x));",FU=Ye({opSnippet:RU,dtype:"bool"}),MU={kernelName:To,backendName:"webgl",kernelFunc:FU},$U="return float(isnan(x));",DU=Ye({opSnippet:$U,dtype:"bool"}),OU={kernelName:Eo,backendName:"webgl",kernelFunc:DU},zU="return float(a < b);",PU=`
|
|
return vec4(lessThan(a, b));
|
|
`,LU=on({opSnippet:zU,packedOpSnippet:PU,cpuKernelImpl:HP,dtype:"bool"}),WU={kernelName:Co,backendName:"webgl",kernelFunc:LU},BU="return float(a <= b);",VU=`
|
|
return vec4(lessThanEqual(a, b));
|
|
`,UU=on({opSnippet:BU,packedOpSnippet:VU,dtype:"bool"}),HU={kernelName:Ro,backendName:"webgl",kernelFunc:UU};function jU(e){let{backend:t,attrs:n}=e,{start:r,stop:a,num:s}=n,i=jP(r,a,s);return t.makeTensorInfo([i.length],"float32",i)}var GU={kernelName:ed,backendName:"webgl",kernelFunc:jU},qU=`if (x < 0.0) return NAN;
|
|
return log(x);`,XU=`
|
|
vec4 result = log(x);
|
|
vec4 isNaN = vec4(lessThan(x, vec4(0.0)));
|
|
result.r = isNaN.r == 1.0 ? NAN : result.r;
|
|
result.g = isNaN.g == 1.0 ? NAN : result.g;
|
|
result.b = isNaN.b == 1.0 ? NAN : result.b;
|
|
result.a = isNaN.a == 1.0 ? NAN : result.a;
|
|
|
|
return result;
|
|
`,KU=Ye({opSnippet:qU,packedOpSnippet:XU,cpuKernelImpl:GP}),ZU={kernelName:Ms,backendName:"webgl",kernelFunc:KU},YU="return log(1.0 + x);",JU=Ye({opSnippet:YU}),QU={kernelName:Fo,backendName:"webgl",kernelFunc:JU},eH="return float(a >= 1.0 && b >= 1.0);",tH=`
|
|
return vec4(
|
|
vec4(greaterThanEqual(a, vec4(1.0))) *
|
|
vec4(greaterThanEqual(b, vec4(1.0))));
|
|
`,nH=on({opSnippet:eH,packedOpSnippet:tH,dtype:"bool"}),rH={kernelName:Mo,backendName:"webgl",kernelFunc:nH},aH="return float(!(x >= 1.0));",sH=Ye({opSnippet:aH}),iH={kernelName:ku,backendName:"webgl",kernelFunc:sH},oH="return float(a >= 1.0 || b >= 1.0);",lH=`
|
|
return min(
|
|
vec4(greaterThanEqual(a, vec4(1.0))) +
|
|
vec4(greaterThanEqual(b, vec4(1.0))),
|
|
vec4(1.0));
|
|
`,uH=on({opSnippet:oH,packedOpSnippet:lH,dtype:"bool"}),cH={kernelName:Iu,backendName:"webgl",kernelFunc:uH},hH=class{constructor(e,t,n,r,a){this.variableNames=["x"],this.outputShape=[];let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${n}) + float(${r}) * sum`;a===.5?o=`inversesqrt(${l})`:a===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${a}));`,this.userCode=`
|
|
void main() {
|
|
ivec4 coords = getOutputCoords();
|
|
int b = coords[0];
|
|
int r = coords[1];
|
|
int c = coords[2];
|
|
int d = coords[3];
|
|
float x = getX(b, r, c, d);
|
|
float sum = 0.0;
|
|
for (int j = -${s}; j <= ${s}; j++) {
|
|
int idx = d + j;
|
|
if (idx >= 0 && idx <= ${i}) {
|
|
float z = getX(b, r, c, idx);
|
|
sum += z * z;
|
|
}
|
|
}
|
|
float val = x * ${o};
|
|
setOutput(val);
|
|
}
|
|
`}},dH=class{constructor(e,t,n,r,a){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${n}) + float(${r}) * sum`;a===.5?o=`inversesqrt(${l})`:a===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${a}));`,this.userCode=`
|
|
void main() {
|
|
ivec4 coords = getOutputCoords();
|
|
int b = coords.x;
|
|
int r = coords.y;
|
|
int c = coords.z;
|
|
int d = coords.w;
|
|
|
|
bool hasNextCol = d < ${this.outputShape[3]};
|
|
bool hasNextRow = c < ${this.outputShape[2]};
|
|
|
|
vec4 sum = vec4(0.);
|
|
vec4 xFragAtOutputCoords = getX(b, r, c, d);
|
|
|
|
vec4 xAtOutputCoords = vec4(
|
|
getChannel(xFragAtOutputCoords, vec2(c, d)),
|
|
hasNextCol ?
|
|
getChannel(xFragAtOutputCoords, vec2(c, d + 1)) : 0.0,
|
|
hasNextRow ?
|
|
getChannel(xFragAtOutputCoords , vec2(c + 1, d)) : 0.0,
|
|
(hasNextRow && hasNextCol) ?
|
|
getChannel(xFragAtOutputCoords, vec2(c + 1, d + 1)) : 0.0
|
|
);
|
|
|
|
int firstChannel = d - ${s};
|
|
vec2 cache = vec2(0.);
|
|
if(firstChannel >= 0){
|
|
vec4 firstChannelFrag = getX(b, r, c, firstChannel);
|
|
cache.x = getChannel(firstChannelFrag, vec2(c, firstChannel));
|
|
if(hasNextRow){
|
|
cache.y = getChannel(firstChannelFrag, vec2(c + 1, firstChannel));
|
|
}
|
|
}
|
|
|
|
ivec2 depth = ivec2(d, d + 1);
|
|
for (int j = - ${s}; j <= ${s}; j++) {
|
|
ivec2 idx = depth + j;
|
|
bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));
|
|
bvec2 belowUpperBound = lessThanEqual(idx, ivec2(${i}));
|
|
|
|
bool depthInRange = aboveLowerBound.x && belowUpperBound.x;
|
|
bool depthPlusOneInRange = aboveLowerBound.y && belowUpperBound.y;
|
|
|
|
if(depthInRange || depthPlusOneInRange){
|
|
vec4 z = vec4(0.);
|
|
vec4 xFragAtCurrentDepth;
|
|
z.xz = cache.xy;
|
|
if(depthPlusOneInRange && hasNextCol){
|
|
xFragAtCurrentDepth = idx.y != d ?
|
|
getX(b, r, c, idx.y) : xFragAtOutputCoords;
|
|
z.y = getChannel(xFragAtCurrentDepth, vec2(c, idx.y));
|
|
if(hasNextRow){
|
|
z.w = getChannel(xFragAtCurrentDepth, vec2(c + 1, idx.y));
|
|
}
|
|
}
|
|
cache.xy = z.yw;
|
|
sum += z * z;
|
|
}
|
|
}
|
|
vec4 result = xAtOutputCoords * ${o};
|
|
setOutput(result);
|
|
}
|
|
`}},pH=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=r,u=J().getBool("WEBGL_PACK_NORMALIZATION")?new dH(a.shape,s,i,o,l):new hH(a.shape,s,i,o,l);return n.runWebGLProgram(u,[a],a.dtype)},fH={kernelName:Nu,backendName:"webgl",kernelFunc:pH},mH=class{constructor(e,t,n,r,a){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=n,this.alpha=r,this.beta=a,this.userCode=`
|
|
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 = ${this.depth};
|
|
|
|
float norm = 0.0;
|
|
for (int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k) {
|
|
if (k < depthBegin){
|
|
continue;
|
|
}
|
|
else if (k >= depthBegin && k < depthEnd) {
|
|
norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k);
|
|
}
|
|
else {
|
|
break;
|
|
}
|
|
}
|
|
|
|
norm = float(${r}) * norm + float(${n});
|
|
|
|
for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){
|
|
if (k < depthBegin){
|
|
continue;
|
|
}
|
|
else if (k >= depthBegin && k < depthEnd){
|
|
float dyi = -2.0 * float(${r})
|
|
* float(${a})
|
|
* getInputImage(b ,r ,c, k) * getOutputImage(b, r, c, d)
|
|
/ norm;
|
|
if (k == d) {
|
|
dyi += pow(norm, -1.0 * ${a});
|
|
}
|
|
if (k == coords[3]) {
|
|
dyi *= getDy(b, r, c, d);
|
|
result += dyi;
|
|
}
|
|
}
|
|
else {
|
|
break;
|
|
}
|
|
}
|
|
}
|
|
setOutput(result);
|
|
}
|
|
`}},AH=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:u,beta:c}=r,h=new mH(a.shape,o,l,u,c);return n.runWebGLProgram(h,[a,s,i],a.dtype)},yH={kernelName:td,backendName:"webgl",kernelFunc:AH};function gH(e,t,n,r){let a=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/a,i=xe({inputs:{x:e},attrs:{shape:[s,a]},backend:r}),o=Ei(i,e.dtype,"max",r),l=xe({inputs:{x:o},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}function M_(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{reductionIndices:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),u=l,c=R.getAxesPermutation(u,o),h=c!=null,d=n.shouldExecuteOnCPU([a]),p=a;if(h){if(d){let g=n.texData.get(p.dataId).values,b=new Array(o);for(let x=0;x<b.length;x++)b[x]=a.shape[c[x]];let _=fA(g,a.shape,a.dtype,c,b);p=n.makeTensorInfo(b,a.dtype);let w=n.texData.get(p.dataId);w.values=_}else p=Ip(a,c,n);u=R.getInnerMostAxes(u.length,o)}R.assertAxesAreInnerMostDims("max",u,o);let[f,m]=R.computeOutAndReduceShapes(p.shape,u),A=f;i&&(A=R.expandShapeToKeepDim(f,l));let y;if(d){let g=n.texData.get(p.dataId).values,b=qP(g,v.sizeFromShape(m),A,a.dtype);y=n.makeTensorInfo(A,a.dtype);let _=n.texData.get(y.dataId);_.values=b}else y=gH(p,m,A,n);return h&&n.disposeIntermediateTensorInfo(p),y}var xH={kernelName:$s,backendName:"webgl",kernelFunc:M_},wH=Zb+`
|
|
return max(a, b);
|
|
`,bH=`
|
|
vec4 result = vec4(max(a, b));
|
|
vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
|
|
`+vp+`
|
|
return result;
|
|
`,_H=on({opSnippet:wH,packedOpSnippet:bH,cpuKernelImpl:XP}),vH={kernelName:Ds,backendName:"webgl",kernelFunc:_H};function kH(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t;Fl(a,"maxPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=r,u=1;v.assert(R.eitherStridesOrDilationsAreOne(i,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let c=R.computePool2DInfo(a.shape,s,i,u,o,l);if(c.filterWidth===1&&c.filterHeight===1&&v.arraysEqual(c.inShape,c.outShape))return Bn({inputs:{x:a},backend:n});let h=new wc(c,"max",!1);return n.runWebGLProgram(h,[a],a.dtype)}var IH={kernelName:Os,backendName:"webgl",kernelFunc:kH};function NH(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dataFormat:l,dimRoundingMode:u}=r,c=[1,1,1],h=R.computePool3DInfo(a.shape,s,i,c,o,u,l),d=new yA(h,"max",!1);return n.runWebGLProgram(d,[a],a.dtype)}var SH={kernelName:Su,backendName:"webgl",kernelFunc:NH},TH=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideHeight,n=e.strideWidth,r=e.dilationHeight,a=e.effectiveFilterHeight,s=e.effectiveFilterWidth,i=a-1-e.padInfo.top,o=s-1-e.padInfo.left,l=a*s-1;this.userCode=`
|
|
const ivec2 pads = ivec2(${i}, ${o});
|
|
|
|
void main() {
|
|
ivec4 coords = getOutputCoords();
|
|
int b = coords[0];
|
|
int d = coords[3];
|
|
|
|
ivec2 dyRCCorner = coords.yz - pads;
|
|
int dyRCorner = dyRCCorner.x;
|
|
int dyCCorner = dyRCCorner.y;
|
|
|
|
// Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).
|
|
// ? = to be determined. : = across all values in that axis.
|
|
float dotProd = 0.0;
|
|
for (int wR = 0; wR < ${a};
|
|
wR += ${r}) {
|
|
float dyR = float(dyRCorner + wR) / ${t}.0;
|
|
|
|
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
|
|
continue;
|
|
}
|
|
int idyR = int(dyR);
|
|
|
|
for (int wC = 0; wC < ${s}; wC++) {
|
|
float dyC = float(dyCCorner + wC) / ${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 * ${s} + wC;
|
|
float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);
|
|
|
|
dotProd += dyValue * mask;
|
|
}
|
|
}
|
|
setOutput(dotProd);
|
|
}
|
|
`}},EH=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,a=e.dilationDepth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterDepth,l=e.effectiveFilterHeight,u=e.effectiveFilterWidth,c=o-1-e.padInfo.front,h=l-1-e.padInfo.top,d=u-1-e.padInfo.left,p=o*l*u-1;this.userCode=`
|
|
const ivec3 pads = ivec3(${c}, ${h}, ${d});
|
|
|
|
void main() {
|
|
ivec5 coords = getOutputCoords();
|
|
int batch = coords.x;
|
|
int ch = coords.u;
|
|
|
|
ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
|
|
int dyDCorner = dyCorner.x;
|
|
int dyRCorner = dyCorner.y;
|
|
int dyCCorner = dyCorner.z;
|
|
|
|
// Convolve dy(?, ?, ?, ch) with pos mask(:, :, :, d) to get
|
|
// dx(xD, xR, xC, ch).
|
|
// ? = to be determined. : = across all values in that axis.
|
|
float dotProd = 0.0;
|
|
|
|
for (int wD = 0; wD < ${o};
|
|
wD += ${a}) {
|
|
float dyD = float(dyDCorner + wD) / ${t}.0;
|
|
|
|
if (dyD < 0.0 || dyD >= ${e.outDepth}.0 || fract(dyD) > 0.0) {
|
|
continue;
|
|
}
|
|
int idyD = int(dyD);
|
|
|
|
for (int wR = 0; wR < ${l};
|
|
wR += ${s}) {
|
|
float dyR = float(dyRCorner + wR) / ${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 += ${i}) {
|
|
float dyC = float(dyCCorner + wC) / ${r}.0;
|
|
|
|
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
|
|
fract(dyC) > 0.0) {
|
|
continue;
|
|
}
|
|
int idyC = int(dyC);
|
|
|
|
float dyValue = getDy(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 CH(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s,{filterSize:o,strides:l,pad:u,dimRoundingMode:c}=r,h=[1,1,1],d=R.computePool3DInfo(i.shape,o,l,h,u,c),p=new yA(d,"max",!0),f=n.runWebGLProgram(p,[i],i.dtype),m=new EH(d),A=n.runWebGLProgram(m,[a,f],i.dtype);return n.disposeIntermediateTensorInfo(f),A}var RH={kernelName:rd,backendName:"webgl",kernelFunc:CH};function FH(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s,output:i}=t,o=s;Fl([s,i],"maxPoolGrad");let{filterSize:l,strides:u,pad:c,dimRoundingMode:h}=r,d=R.computePool2DInfo(o.shape,l,u,1,c,h),p=!0,f=new wc(d,"max",p),m=n.runWebGLProgram(f,[o],o.dtype),A=new TH(d),y=n.runWebGLProgram(A,[a,m],o.dtype);return n.disposeIntermediateTensorInfo(m),y}var MH={kernelName:nd,backendName:"webgl",kernelFunc:FH};function $H(e,t,n,r){let a=new wc(n,"max",!1),s=r.runWebGLProgram(a,[e],"float32");a=new wc(n,"max",!0,!0,t);let i=r.runWebGLProgram(a,[e],"float32");return[s,i]}var DH={kernelName:ad,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:r}=e,{filterSize:a,strides:s,pad:i,includeBatchInIndex:o}=t,l=n;v.assert(r.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${r.shape.length}.`);let u=[1,1];v.assert(R.eitherStridesOrDilationsAreOne(s,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${u}'`);let c=R.computePool2DInfo(r.shape,a,s,u,i),[h,d]=$H(r,o,c,l);return[h,d]}};function OH(e,t,n,r){let a=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/a,i=xe({inputs:{x:e},attrs:{shape:[s,a]},backend:r}),o=Ei(i,"float32","mean",r),l=xe({inputs:{x:o},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}var zH={kernelName:zs,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:r}=e,{keepDims:a,axis:s}=t,i=n,o=r.shape.length,l=v.parseAxisParam(s,r.shape),u=l,c=R.getAxesPermutation(u,o),h=c!=null,d=i.shouldExecuteOnCPU([r]),p=[],f=r;if(h){if(d){let b=i.texData.get(f.dataId).values,_=new Array(o);for(let N=0;N<_.length;N++)_[N]=r.shape[c[N]];let w=fA(b,r.shape,r.dtype,c,_);f=i.makeTensorInfo(_,r.dtype);let x=i.texData.get(f.dataId);x.values=w}else f=Ip(r,c,i);p.push(f),u=R.getInnerMostAxes(u.length,o)}R.assertAxesAreInnerMostDims("sum",u,o);let[m,A]=R.computeOutAndReduceShapes(f.shape,u),y=m;a&&(y=R.expandShapeToKeepDim(m,l));let g=OH(f,A,y,i);for(let b of p)i.disposeIntermediateTensorInfo(b);return g}};function PH(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),u=l,c=R.getAxesPermutation(u,o),h=a;c!=null&&(h=Cn({inputs:{x:a},backend:n,attrs:{perm:c}}),u=R.getInnerMostAxes(u.length,a.shape.length)),R.assertAxesAreInnerMostDims("min",u,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,u),f=v.sizeFromShape(p),m=xe({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=Ei(m,m.dtype,"min",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=xe({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=xe({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),c!=null&&n.disposeIntermediateTensorInfo(h),y}var LH={kernelName:Ps,backendName:"webgl",kernelFunc:PH},WH=Zb+`
|
|
return min(a, b);
|
|
`,BH=`
|
|
vec4 result = vec4(min(a, b));
|
|
vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
|
|
`+vp+`
|
|
return result;
|
|
`,VH=on({opSnippet:WH,packedOpSnippet:BH,cpuKernelImpl:KP}),UH={kernelName:Ls,backendName:"webgl",kernelFunc:VH},HH=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((u,c)=>u[0]+e[c]+u[1]);let r=e.length,a=dt(r),s=t.map(u=>u[0]).join(","),i=t.map((u,c)=>u[0]+e[c]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r),l=n==="reflect"?0:1;if(r===1){this.userCode=`
|
|
int start = ${s};
|
|
int end = ${i};
|
|
|
|
void main() {
|
|
int outC = getOutputCoords();
|
|
if (outC < start) {
|
|
outC = start * 2 - outC - ${l};
|
|
} else if(outC >= end) {
|
|
outC = (end - 1) * 2 - outC + ${l};
|
|
}
|
|
setOutput(getX(outC - start));
|
|
}
|
|
`;return}this.userCode=`
|
|
${a} start = ${a}(${s});
|
|
${a} end = ${a}(${i});
|
|
|
|
void main() {
|
|
${a} outC = getOutputCoords();
|
|
for (int i = 0; i < ${r}; 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};
|
|
}
|
|
}
|
|
${a} coords = outC - start;
|
|
setOutput(getX(${o}));
|
|
}
|
|
`}},jH=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 r=e.length,a=dt(r),s=t.map(p=>p[0]).join(","),i=t.map((p,f)=>p[0]+e[f]).join(","),o=xn("rc",r),l=xn("source",r),u=`${o[r-1]} < ${this.outputShape[r-1]}`,c=r===1?"source":`vec2(${l.slice(-2).join()})`,h=n==="reflect"?0:1,d="";if(r===1){let p=`
|
|
${a} source = rc;
|
|
if (source < start) {
|
|
source = start * 2 - source - ${h};
|
|
} else if (source >= end) {
|
|
source = (end - 1) * 2 - source + ${h};
|
|
}
|
|
source -= start;
|
|
`;d=`
|
|
${a} rc = outputLoc;
|
|
${p}
|
|
result[0] = getChannel(getX(${l.join()}), ${c});
|
|
${o[r-1]} += 1;
|
|
if(${u}) {
|
|
${p}
|
|
result[1] = getChannel(getX(${l.join()}), ${c});
|
|
}
|
|
`}else{let p=`
|
|
${a} source = rc;
|
|
${a} lt = ${a}(lessThan(source, start));
|
|
${a} gte = ${a}(greaterThanEqual(source, end));
|
|
${a} orig = 1 - (lt + gte);
|
|
source = orig * source +
|
|
lt * (start * 2 - source - ${h}) +
|
|
gte * ((end - 1) * 2 - source + ${h});
|
|
source -= start;
|
|
`;d=`
|
|
${a} rc = outputLoc;
|
|
${p}
|
|
result[0] = getChannel(getX(${l.join()}), ${c});
|
|
${o[r-1]} += 1;
|
|
if(${u}) {
|
|
${p}
|
|
result[1] = getChannel(getX(${l.join()}), ${c});
|
|
}
|
|
rc = outputLoc;
|
|
${o[r-2]} += 1;
|
|
if(${o[r-2]} < ${this.outputShape[r-2]}) {
|
|
${p}
|
|
result[2] = getChannel(getX(${l.join()}), ${c});
|
|
${o[r-1]} += 1;
|
|
if(${u}) {
|
|
${p}
|
|
result[3] = getChannel(getX(${l.join()}), ${c});
|
|
}
|
|
}
|
|
`}this.userCode=`
|
|
const ${a} start = ${a}(${s});
|
|
const ${a} end = ${a}(${i});
|
|
|
|
void main() {
|
|
${a} outputLoc = getOutputCoords();
|
|
vec4 result = vec4(0.);
|
|
${d}
|
|
setOutput(result);
|
|
}
|
|
`}},GH=({inputs:e,backend:t,attrs:n})=>{let{x:r}=e,{paddings:a,mode:s}=n,i=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new jH(r.shape,a,s):new HH(r.shape,a,s);return t.runWebGLProgram(i,[r],r.dtype)},qH={kernelName:Tu,backendName:"webgl",kernelFunc:GH},XH=`if (b == 0.0) return NAN;
|
|
return mod(a, b);`,KH=`
|
|
vec4 result = mod(a, b);
|
|
vec4 isNaN = vec4(equal(b, vec4(0.0)));
|
|
`+vp+`
|
|
return result;
|
|
`,ZH=on({opSnippet:XH,packedOpSnippet:KH}),YH={kernelName:$o,backendName:"webgl",kernelFunc:ZH},JH=class{constructor(e,t,n){this.variableNames=["probs"],this.outputShape=[e,n],this.userCode=`
|
|
uniform float seed;
|
|
|
|
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}));
|
|
}
|
|
`}getCustomSetupFunc(e){return(t,n)=>{this.seedLoc==null&&(this.seedLoc=t.getUniformLocation(n,"seed")),t.gl.uniform1f(this.seedLoc,e)}}},QH=`
|
|
if (a == b) {
|
|
return 1.0;
|
|
};
|
|
return a / b;`,ej=`
|
|
// 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;
|
|
`,$_=on({opSnippet:QH,packedOpSnippet:ej,checkOutOfBounds:!0}),tj={kernelName:Is,backendName:"webgl",kernelFunc:$_},D_="return a - b;",O_=on({opSnippet:D_,packedOpSnippet:D_,supportsComplex:!0,cpuKernelImpl:rL}),nj={kernelName:ri,backendName:"webgl",kernelFunc:O_};function z_(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{dim:s}=r,i=v.parseAxisParam([s],a.shape),o=M_({inputs:{x:a},backend:n,attrs:{reductionIndices:i,keepDims:!1}}),l=R.expandShapeToKeepDim(o.shape,i),u=xe({inputs:{x:o},backend:n,attrs:{shape:l}}),c=O_({inputs:{a,b:u},backend:n}),h=T_({inputs:{x:c},backend:n}),d=AA({inputs:{x:h},backend:n,attrs:{axis:i,keepDims:!1}}),p=xe({inputs:{x:d},backend:n,attrs:{shape:l}}),f=$_({inputs:{a:h,b:p},backend:n});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),f}var rj={kernelName:ti,backendName:"webgl",kernelFunc:z_};function aj(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{numSamples:s,seed:i,normalized:o}=r,l=o?a:z_({inputs:{logits:a},backend:n,attrs:{dim:a.shape.length-1}}),u=l.shape[0],c=l.shape[1],h=new JH(u,c,s),d=h.getCustomSetupFunc(i),p=n.runWebGLProgram(h,[l],"int32",d);return o||n.disposeIntermediateTensorInfo(l),p}var sj={kernelName:sd,backendName:"webgl",kernelFunc:aj},P_="return -x;";function ij(e){let{inputs:t,backend:n}=e,{x:r}=t;if(n.shouldExecuteOnCPU([r])){let s=n.texData.get(r.dataId),[i,o]=YP(s.values,r.shape,r.dtype);return n.makeTensorInfo(o,r.dtype,i)}let a;return J().getBool("WEBGL_PACK_UNARY_OPERATIONS")?a=new Pl(r.shape,P_):a=new qa(r.shape,P_),n.runWebGLProgram(a,[r],r.dtype)}var oj={kernelName:Do,backendName:"webgl",kernelFunc:ij},lj=Hr.nonMaxSuppressionV3Impl;function uj(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l}=r,u=n.readSync(a.dataId),c=n.readSync(s.dataId),{selectedIndices:h}=lj(u,c,i,o,l);return n.makeTensorInfo([h.length],"int32",new Int32Array(h))}var cj={kernelName:zo,backendName:"webgl",kernelFunc:uj},hj=Hr.nonMaxSuppressionV4Impl;function dj(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,padToMaxOutputSize:u}=r,c=n.readSync(a.dataId),h=n.readSync(s.dataId),{selectedIndices:d,validOutputs:p}=hj(c,h,i,o,l,u);return[n.makeTensorInfo([d.length],"int32",new Int32Array(d)),n.makeTensorInfo([],"int32",new Int32Array([p]))]}var pj={kernelName:Po,backendName:"webgl",kernelFunc:dj},fj=Hr.nonMaxSuppressionV5Impl;function mj(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,softNmsSigma:u}=r,c=n.readSync(a.dataId),h=n.readSync(s.dataId),d=i,p=o,f=l,m=u,{selectedIndices:A,selectedScores:y}=fj(c,h,d,p,f,m);return[n.makeTensorInfo([A.length],"int32",new Int32Array(A)),n.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var Aj={kernelName:Lo,backendName:"webgl",kernelFunc:mj},yj=class{constructor(e,t,n,r){this.variableNames=["indices"],this.outputShape=[e,t],this.userCode=`
|
|
void main() {
|
|
ivec2 coords = getOutputCoords();
|
|
int index = round(getIndices(coords.x));
|
|
setOutput(mix(float(${r}), float(${n}),
|
|
float(index == coords.y)));
|
|
}
|
|
`}},gj=e=>{let{inputs:t,backend:n,attrs:r}=e,{indices:a}=t,{depth:s,onValue:i,offValue:o}=r,l=v.sizeFromShape(a.shape),u=new yj(l,s,i,o),c=xe({inputs:{x:a},backend:n,attrs:{shape:[l]}}),h=n.runWebGLProgram(u,[c],a.dtype);n.disposeIntermediateTensorInfo(c);let d=[...a.shape,s],p=xe({inputs:{x:h},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(h),p},xj={kernelName:Bs,backendName:"webgl",kernelFunc:gj};function Cp(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="complex64"){let a=_c({inputs:{input:r},backend:n}),s=Cp({inputs:{x:a},backend:n}),i=Ep({inputs:{input:r},backend:n}),o=Cp({inputs:{x:i},backend:n}),l=Xa({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return bA({attrs:{shape:r.shape,dtype:r.dtype,value:r.dtype==="string"?"":0},backend:n})}var wj={kernelName:rl,backendName:"webgl",kernelFunc:Cp};function L_(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(r.dtype==="complex64"){let a=_c({inputs:{input:r},backend:n}),s=L_({inputs:{x:a},backend:n}),i=Ep({inputs:{input:r},backend:n}),o=Cp({inputs:{x:i},backend:n}),l=Xa({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return bA({attrs:{shape:r.shape,dtype:r.dtype,value:1},backend:n})}var bj={kernelName:Wo,backendName:"webgl",kernelFunc:L_};function _j(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r;if(t.length===1)return wA({inputs:{input:t[0]},backend:n,attrs:{dim:a}});let s=t[0].shape,i=t[0].dtype;t.forEach(c=>{v.assertShapesMatch(s,c.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(c=>{let h=wA({inputs:{input:c},backend:n,attrs:{dim:a}});return o.push(h),h}),u=g_({inputs:l,backend:n,attrs:{axis:a}});return o.forEach(c=>n.disposeIntermediateTensorInfo(c)),u}var vj={kernelName:Bo,backendName:"webgl",kernelFunc:_j},kj=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((l,u)=>l[0]+e[u]+l[1]);let r=e.length,a=dt(r),s=t.map(l=>l[0]).join(","),i=t.map((l,u)=>l[0]+e[u]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r);if(r===1){this.userCode=`
|
|
int start = ${s};
|
|
int end = ${i};
|
|
uniform float value;
|
|
|
|
void main() {
|
|
int outC = getOutputCoords();
|
|
if (outC < start || outC >= end) {
|
|
setOutput(value);
|
|
} else {
|
|
setOutput(getX(outC - start));
|
|
}
|
|
}
|
|
`;return}this.userCode=`
|
|
${a} start = ${a}(${s});
|
|
${a} end = ${a}(${i});
|
|
uniform float value;
|
|
|
|
void main() {
|
|
${a} outC = getOutputCoords();
|
|
if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {
|
|
setOutput(value);
|
|
} else {
|
|
${a} coords = outC - start;
|
|
setOutput(getX(${o}));
|
|
}
|
|
}
|
|
`}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}},Ij=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((f,m)=>f[0]+e[m]+f[1]);let r=e.length,a=dt(r),s=t.map(f=>f[0]).join(","),i=t.map((f,m)=>f[0]+e[m]).join(","),o=xn("rc",r),l=xn("source",r),u=`${o[r-1]} < ${this.outputShape[r-1]}`,c=r===1?"source":`vec2(${l.slice(-2).join()})`,h=[`${a} rc = outputLoc;`,`${o[r-1]} += 1;
|
|
if(${u}) {
|
|
`,r===1?"":`}
|
|
rc = outputLoc;
|
|
${o[r-2]} += 1;
|
|
if(${o[r-2]} < ${this.outputShape[r-2]}) {`,r===1?"":` ${o[r-1]} += 1;
|
|
if(${u}) {`],d=r===1?"rc < start || rc >= end":"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))",p="";for(let f=0,m=r===1?2:4;f<m;f++)p+=`
|
|
${h[f]}
|
|
if (${d}) {
|
|
result[${f}] = float(value);
|
|
} else {
|
|
${a} source = rc - start;
|
|
result[${f}] = getChannel(getX(${l.join()}), ${c});
|
|
}
|
|
`;p+=r===1?"} ":"}}",this.userCode=`
|
|
const ${a} start = ${a}(${s});
|
|
const ${a} end = ${a}(${i});
|
|
uniform float value;
|
|
|
|
void main() {
|
|
${a} outputLoc = getOutputCoords();
|
|
vec4 result = vec4(0.);
|
|
${p}
|
|
setOutput(result);
|
|
}
|
|
`}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}},W_=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{paddings:s,constantValue:i}=r,o=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Ij(a.shape,s,i):new kj(a.shape,s,i),l=o.getCustomSetupFunc(i);return n.runWebGLProgram(o,[a],a.dtype,l)},Nj={kernelName:Vs,backendName:"webgl",kernelFunc:W_},Sj=`
|
|
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);
|
|
`,Tj=`
|
|
// 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));
|
|
`+vp+`
|
|
return result;
|
|
`,Ej=on({opSnippet:Sj,packedOpSnippet:Tj}),Cj={kernelName:Us,backendName:"webgl",kernelFunc:Ej};function Rj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=[],u=v.parseAxisParam(s,a.shape),c=u,h=R.getAxesPermutation(c,o),d=a;h!=null&&(d=Cn({inputs:{x:a},backend:n,attrs:{perm:h}}),c=R.getInnerMostAxes(c.length,o),l.push(d)),R.assertAxesAreInnerMostDims("prod",c,o);let p;if(n.shouldExecuteOnCPU([d])){let f=n.texData.get(d.dataId).values,{outVals:m,outShape:A,outDtype:y}=JP(d.shape,d.dtype,f,c);p=n.makeTensorInfo(A,y,m)}else{let[f,m]=R.computeOutAndReduceShapes(d.shape,c),A=v.sizeFromShape(m),y=xe({inputs:{x:d},backend:n,attrs:{shape:[-1,A]}}),g=yd(a.dtype),b=Ei(y,g,"prod",n);p=xe({inputs:{x:b},backend:n,attrs:{shape:f}}),l.push(y),l.push(b)}if(i){l.push(p);let f=R.expandShapeToKeepDim(p.shape,u);p=xe({inputs:{x:p},backend:n,attrs:{shape:f}})}return l.forEach(f=>n.disposeIntermediateTensorInfo(f)),p}var Fj={kernelName:Vo,backendName:"webgl",kernelFunc:Rj},B_=e=>{let{backend:t,attrs:n}=e,{start:r,stop:a,step:s,dtype:i}=n,o=QP(r,a,s,i);return t.makeTensorInfo([o.length],i,o)},Mj={kernelName:Eu,backendName:"webgl",kernelFunc:B_},$j="return 1.0 / x;",Dj=Ye({opSnippet:$j}),Oj={kernelName:Uo,backendName:"webgl",kernelFunc:Dj},zj=Ir+`
|
|
return (x < 0.0) ? 0.0 : x;
|
|
`,Pj=`
|
|
vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));
|
|
bvec4 isNaN = isnan(x);
|
|
|
|
result.r = isNaN.r ? x.r : result.r;
|
|
result.g = isNaN.g ? x.g : result.g;
|
|
result.b = isNaN.b ? x.b : result.b;
|
|
result.a = isNaN.a ? x.a : result.a;
|
|
|
|
return result;
|
|
`,Lj=Ye({opSnippet:zj,packedOpSnippet:Pj}),Wj={kernelName:js,backendName:"webgl",kernelFunc:Lj},Bj=Ir+`
|
|
return (x < 0.0) ? 0.0 : min(6.0, x);
|
|
`,Vj=`
|
|
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;
|
|
`,Uj=Ye({opSnippet:Bj,packedOpSnippet:Vj}),Hj={kernelName:qs,backendName:"webgl",kernelFunc:Uj},jj=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let u=[r&&t>1?i-1:i,r&&n>1?o-1:o],c=[r&&t>1?t-1:t,r&&n>1?n-1:n],h;a?h="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":h="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
|
|
const vec2 effectiveInputOverOutputRatioRC = vec2(
|
|
${u[0]/c[0]},
|
|
${u[1]/c[1]});
|
|
const vec2 inputShapeRC = vec2(${i}.0, ${o}.0);
|
|
|
|
void main() {
|
|
ivec4 coords = getOutputCoords();
|
|
int b = coords[0];
|
|
int d = coords[3];
|
|
ivec2 yRC = coords.yz;
|
|
|
|
// Fractional source index.
|
|
vec2 sourceFracIndexRC = ${h};
|
|
|
|
// 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);
|
|
}
|
|
`}},Gj=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let u=[r&&t>1?i-1:i,r&&n>1?o-1:o],c=[r&&t>1?t-1:t,r&&n>1?n-1:n],h;a?h="(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":h="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
|
|
const vec3 effectiveInputOverOutputRatioRC = vec3(
|
|
${u[0]/c[0]},
|
|
${u[1]/c[1]},
|
|
${u[1]/c[1]});
|
|
const vec3 inputShapeRC = vec3(${i}.0, ${o}.0,
|
|
${o}.0);
|
|
|
|
float getAValue(int b, int r, int c, int d) {
|
|
return getChannel(getA(b, r, c, d), vec2(c, d));
|
|
}
|
|
|
|
void main() {
|
|
ivec4 coords = getOutputCoords();
|
|
int b = coords[0];
|
|
int d = coords[3];
|
|
// Calculate values for next column in yRC.z.
|
|
ivec3 yRC = coords.yzz + ivec3(0, 0, 1);
|
|
|
|
// Fractional source index.
|
|
vec3 sourceFracIndexRC = ${h};
|
|
|
|
// 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 qj(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,u]=o,c=J().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new Gj(a.shape,l,u,s,i):new jj(a.shape,l,u,s,i);return n.runWebGLProgram(c,[a],"float32")}var Xj={kernelName:Gs,backendName:"webgl",kernelFunc:qj},Kj=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,r,a]=t,[,s,i]=e,o=[n&&s>1?r-1:r,n&&i>1?a-1:a],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],u=o[0]/l[0],c=o[1]/l[1],h=1/u,d=1/c,p=Math.ceil(h)*2+2,f=Math.ceil(d)*2+2;this.userCode=`
|
|
void main() {
|
|
ivec4 coords = getOutputCoords();
|
|
int b = coords[0];
|
|
int d = coords[3];
|
|
int r = coords[1];
|
|
int c = coords[2];
|
|
|
|
float accumulator = 0.0;
|
|
|
|
const float heightScale = float(${u});
|
|
const float widthScale = float(${c});
|
|
|
|
const float invHeightScale = float(${h});
|
|
const float invWidthScale = float(${d});
|
|
|
|
const int winHeight = int(${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 >= ${s}) {
|
|
continue;
|
|
}
|
|
|
|
for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {
|
|
int dyC = dyCOffset + startDyC;
|
|
|
|
// Guard against the window exceeding the bounds of dy
|
|
if (dyC < 0 || dyC >= ${i}) {
|
|
continue;
|
|
}
|
|
|
|
float dxR = float(dyR) * heightScale;
|
|
int topDxRIndex = int(floor(dxR));
|
|
int bottomDxRIndex = int(min(ceil(dxR), ${r-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), ${a-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 Zj(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r,o=new Kj(s.shape,a.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var Yj={kernelName:ld,backendName:"webgl",kernelFunc:Zj},Jj=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let u=[r&&t>1?i-1:i,r&&n>1?o-1:o],c=[r&&t>1?t-1:t,r&&n>1?n-1:n],h=r?"0.5":"0.0",d;a?d="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":d="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
|
|
const vec2 effectiveInputOverOutputRatioRC = vec2(
|
|
${u[0]/c[0]},
|
|
${u[1]/c[1]});
|
|
const vec2 inputShapeRC = vec2(${i}.0, ${o}.0);
|
|
|
|
void main() {
|
|
ivec4 coords = getOutputCoords();
|
|
int b = coords[0];
|
|
int d = coords[3];
|
|
ivec2 yRC = coords.yz;
|
|
|
|
// Fractional source index.
|
|
vec2 sourceFracIndexRC = ${d};
|
|
|
|
// Compute the coordinators of nearest neighbor point.
|
|
ivec2 sourceNearestRC = ivec2(
|
|
min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${h})));
|
|
float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d);
|
|
|
|
setOutput(newValue);
|
|
}
|
|
`}};function Qj(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,u]=o,c=new Jj(a.shape,l,u,s,i);return n.runWebGLProgram(c,[a],a.dtype)}var eG={kernelName:Cu,backendName:"webgl",kernelFunc:Qj},tG=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,r,a]=t,[,s,i]=e,o=[n&&s>1?r-1:r,n&&i>1?a-1:a],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],u=o[0]/l[0],c=o[1]/l[1],h=1/u,d=1/c,p=Math.ceil(h)*2+2,f=Math.ceil(d)*2+2;this.userCode=`
|
|
void main() {
|
|
ivec4 coords = getOutputCoords();
|
|
int b = coords[0];
|
|
int d = coords[3];
|
|
int r = coords[1];
|
|
int c = coords[2];
|
|
|
|
float accumulator = 0.0;
|
|
|
|
const float heightScale = float(${u});
|
|
const float widthScale = float(${c});
|
|
|
|
const float invHeightScale = float(${h});
|
|
const float invWidthScale = float(${d});
|
|
|
|
const int winHeight = int(${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 >= ${s}) {
|
|
continue;
|
|
}
|
|
|
|
for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {
|
|
int dyC = dyCOffset + startDyC;
|
|
|
|
// Guard against the window exceeding the bounds of dy
|
|
if (dyC < 0 || dyC >= ${i}) {
|
|
continue;
|
|
}
|
|
|
|
float sourceFracRow =
|
|
float(${o[0]}) *
|
|
(float(dyR) / float(${l[0]}));
|
|
|
|
float sourceFracCol =
|
|
float(${o[1]}) *
|
|
(float(dyC) / float(${l[1]}));
|
|
|
|
int sourceNearestRow = int(min(
|
|
float(int(${r}) - 1),
|
|
${n} ? float(round(sourceFracRow)) :
|
|
float(floor(sourceFracRow))));
|
|
|
|
int sourceNearestCol = int(min(
|
|
float(int(${a}) - 1),
|
|
${n} ? float(round(sourceFracCol)) :
|
|
float(floor(sourceFracCol))));
|
|
|
|
if (r == sourceNearestRow && c == sourceNearestCol) {
|
|
accumulator += getDy(b, dyR, dyC, d);
|
|
}
|
|
}
|
|
}
|
|
// End loop over dy
|
|
|
|
setOutput(accumulator);
|
|
}
|
|
`}};function nG(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r,o=new tG(s.shape,a.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var rG={kernelName:od,backendName:"webgl",kernelFunc:nG},aG=class{constructor(e,t){this.variableNames=["x"];let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);if(this.outputShape=e,n===1){this.userCode=`
|
|
void main() {
|
|
int coord = getOutputCoords();
|
|
setOutput(getX(${e[0]} - coord - 1));
|
|
}
|
|
`;return}let r=i=>t.indexOf(i)!==-1&&e[i]!==1?`${e[i]} - coords[${i}] - 1`:`coords[${i}]`,a=e.map((i,o)=>r(o)).join(","),s=dt(n);this.userCode=`
|
|
void main() {
|
|
${s} coords = getOutputCoords();
|
|
setOutput(getX(${a}));
|
|
}
|
|
`}},sG=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-${n} tensor is not yet supported`);this.outputShape=e;let r=xn("rc",n),a=`${r[n-1]} + 1 < ${this.outputShape[n-1]}`,s=`${r[n-2]} + 1 < ${this.outputShape[n-2]}`,i=dt(n);n===1?this.userCode=`
|
|
void main(){
|
|
int rc = getOutputCoords();
|
|
vec4 result = vec4(0.);
|
|
result.r = getChannel(getX(${e[0]} - rc - 1),
|
|
${e[0]} - rc - 1);
|
|
if(${a}){
|
|
result.g = getChannel(getX(${e[0]} - (rc + 1) - 1),
|
|
${e[0]} - (rc + 1) - 1);
|
|
}
|
|
setOutput(result);
|
|
}
|
|
`:this.userCode=`
|
|
void main() {
|
|
${i} rc = getOutputCoords();
|
|
vec4 result = vec4(0.);
|
|
result.r = ${o(r.slice())};
|
|
if(${a}){
|
|
result.g = ${l(r.slice())};
|
|
}
|
|
if(${s}) {
|
|
result.b = ${u(r.slice())};
|
|
if(${a}) {
|
|
result.a = ${c(r.slice())};
|
|
}
|
|
}
|
|
setOutput(result);
|
|
}
|
|
`;function o(p){return h(p)}function l(p){return p[n-1]="("+p[n-1]+" + 1)",h(p)}function u(p){return p[n-2]="("+p[n-2]+" + 1)",h(p)}function c(p){return p[n-1]="("+p[n-1]+" + 1)",p[n-2]="("+p[n-2]+" + 1)",h(p)}function h(p){let f=e.map((y,g)=>d(g,p)),m=f.join(","),A=f.slice(-2).join(",");return`getChannel(getX(${m}), vec2(${A}))`}function d(p,f){return t.indexOf(p)!==-1&&e[p]!==1?`${e[p]} - ${f[p]} - 1`:`${f[p]}`}}};function iG(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{dims:s}=r,i=a.shape.length,o=v.parseAxisParam(s,a.shape);if(i===0)return Bn({inputs:{x:a},backend:n});let l=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new sG(a.shape,o):new aG(a.shape,o);return n.runWebGLProgram(l,[a],a.dtype)}var oG={kernelName:Xs,backendName:"webgl",kernelFunc:iG},lG=class{constructor(e,t){this.variableNames=["Image"],this.outputShape=[];let n=e[1],r=e[2];this.outputShape=e;let a="";typeof t=="number"?a=`float outputValue = ${t.toFixed(2)};`:a=`
|
|
vec3 fill = vec3(${t.join(",")});
|
|
float outputValue = fill[coords[3]];`,this.userCode=`
|
|
uniform vec4 params;
|
|
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]));
|
|
${a}
|
|
if(coordX >= 0 && coordX < ${r} && coordY >= 0 && coordY < ${n}) {
|
|
outputValue = getImage(coords[0], coordY, coordX, coords[3]);
|
|
}
|
|
setOutput(outputValue);
|
|
}
|
|
`}getCustomSetupFunc(e,t,n,r){return(a,s)=>{this.paramsLoc==null&&(this.paramsLoc=a.getUniformLocationNoThrow(s,"params")),a.gl.uniform4f(this.paramsLoc,e,t,n,r)}}},uG={kernelName:al,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:r}=e,{radians:a,fillValue:s,center:i}=t,o=n,l=new lG(r.shape,s),[u,c]=R.getImageCenter(i,r.shape[1],r.shape[2]),h=l.getCustomSetupFunc(u,c,Math.sin(a),Math.cos(a));return o.runWebGLProgram(l,[r],r.dtype,h)}},cG=`
|
|
// OpenGL ES does not support round function.
|
|
// The algorithm is based on banker's rounding.
|
|
float base = floor(x);
|
|
if ((x - base) < 0.5) {
|
|
return floor(x);
|
|
} else if ((x - base) > 0.5) {
|
|
return ceil(x);
|
|
} else {
|
|
if (mod(base, 2.0) == 0.0) {
|
|
return base;
|
|
} else {
|
|
return base + 1.0;
|
|
}
|
|
}
|
|
`,hG=Ye({opSnippet:cG}),dG={kernelName:Ks,backendName:"webgl",kernelFunc:hG},pG="return inversesqrt(x);",fG=Ye({opSnippet:pG,cpuKernelImpl:eL}),mG={kernelName:Zs,backendName:"webgl",kernelFunc:fG},V_=class{constructor(e,t,n,r,a,s,i=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=s;let o=dt(a.length),l=dt(s.length),u="";n===1?u="i":n===2&&(u="i, j");let c=`getIndices(${u})`,h="";r===1?h="i":r===2&&(h="i, coords[1]");let d=`getUpdates(${h})`,p=t>1?"strides[j]":"strides";this.userCode=`
|
|
${o} strides = ${o}(${a});
|
|
|
|
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 += ${d};
|
|
found = true;
|
|
}
|
|
}
|
|
setOutput(mix(getDefaultValue(), sum, float(found)));
|
|
}
|
|
`}};function AG(e){let{inputs:t,backend:n,attrs:r}=e,{indices:a,updates:s}=t,{shape:i}=r,{sliceRank:o,numUpdates:l,sliceSize:u,strides:c,outputSize:h}=R.calculateShapes(s,a,i),d=[h/u,u];if(h===0)return n.makeTensorInfo(i,a.dtype);let p=xe({inputs:{x:a},backend:n,attrs:{shape:[l,o]}}),f=xe({inputs:{x:s},backend:n,attrs:{shape:[l,u]}}),m=n.makeTensorInfo([],"float32",new Float32Array([0])),A=new V_(l,o,p.shape.length,f.shape.length,c,d),y=n.runWebGLProgram(A,[f,p,m],f.dtype),g=xe({inputs:{x:y},backend:n,attrs:{shape:i}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(m),g}var yG={kernelName:jo,backendName:"webgl",kernelFunc:AG},gG=class{constructor(e,t,n){this.variableNames=["c","a","b"],this.outputShape=t;let r,a;if(n>4)throw Error(`Where for rank ${n} is not yet supported`);if(n===1)a="resRC",r="resRC";else{let i=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[],l=[];for(let u=0;u<t.length;u++)l.push(`${i[u]}`),u<e&&o.push(`${i[u]}`);r=o.join(),a=l.join()}let s=dt(n);this.userCode=`
|
|
void main() {
|
|
${s} resRC = getOutputCoords();
|
|
float cVal = getC(${r});
|
|
if (cVal >= 1.0) {
|
|
setOutput(getA(${a}));
|
|
} else {
|
|
setOutput(getB(${a}));
|
|
}
|
|
}
|
|
`}};function xG(e){let{inputs:t,backend:n}=e,{condition:r,t:a,e:s}=t,i=new gG(r.shape.length,a.shape,a.shape.length);return n.runWebGLProgram(i,[r,a,s],lr(a.dtype,s.dtype))}var wG={kernelName:Go,backendName:"webgl",kernelFunc:xG},bG=`
|
|
// Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
|
|
// see: https://arxiv.org/abs/1706.02515
|
|
float scaleAlpha = ${R.SELU_SCALEALPHA};
|
|
float scale = ${R.SELU_SCALE};
|
|
return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
|
|
`,_G=Ye({opSnippet:bG}),vG={kernelName:qo,backendName:"webgl",kernelFunc:_G},kG="return 1.0 / (1.0 + exp(-1.0 * x));",IG=Ye({opSnippet:kG}),NG={kernelName:Js,backendName:"webgl",kernelFunc:IG},SG=`
|
|
if (isnan(x)) { return 0.0; }
|
|
return sign(x);
|
|
`,TG=Ye({opSnippet:SG}),EG={kernelName:Zo,backendName:"webgl",kernelFunc:TG},CG=t_+`
|
|
return sin(x);
|
|
`,RG=Ye({opSnippet:CG}),FG={kernelName:Ys,backendName:"webgl",kernelFunc:RG},MG=`
|
|
float e2x = exp(x);
|
|
return (e2x - 1.0 / e2x) / 2.0;
|
|
`,$G=Ye({opSnippet:MG}),DG={kernelName:Ko,backendName:"webgl",kernelFunc:$G},OG=`
|
|
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;
|
|
`,zG=Ye({opSnippet:OG}),PG={kernelName:Yo,backendName:"webgl",kernelFunc:zG},LG=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,paddings:i}=r;v.assert(a.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((y,g)=>y*g),l=[[0,0]];l.push(...i);for(let y=1+s.length;y<a.shape.length;++y)l.push([0,0]);let u=[],c=W_({inputs:{x:a},backend:n,attrs:{paddings:l,constantValue:0}}),h=R.getReshaped(c.shape,s,o,!1),d=R.getPermuted(h.length,s.length,!1),p=R.getReshapedPermuted(c.shape,s,o,!1),f=xe({inputs:{x:c},backend:n,attrs:{shape:h}}),m=Cn({inputs:{x:f},backend:n,attrs:{perm:d}}),A=xe({inputs:{x:m},backend:n,attrs:{shape:p}});return u.push(c),u.push(f),u.push(m),u.forEach(y=>n.disposeIntermediateTensorInfo(y)),A},WG={kernelName:Ru,backendName:"webgl",kernelFunc:LG};function BG(e){let{inputs:t,backend:n,attrs:r}=e,{sparseIndices:a,sparseValues:s,defaultValue:i}=t,{outputShape:o}=r,{sliceRank:l,numUpdates:u,strides:c,outputSize:h}=R.calculateShapes(s,a,o),d=!1,p=new V_(u,l,a.shape.length,s.shape.length,c,[h,1],d),f=n.runWebGLProgram(p,[s,a,i],s.dtype),m=xe({inputs:{x:f},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(f),m}var VG={kernelName:ud,backendName:"webgl",kernelFunc:BG};function UG(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{numOrSizeSplits:s,axis:i}=r,o=v.parseAxisParam(i,a.shape)[0],l=R.prepareSplitSize(a,s,o),u=a.shape.length,c=new Array(u).fill(0),h=a.shape.slice();return l.map(d=>{let p=[...h];p[o]=d;let f=bc({inputs:{x:a},backend:n,attrs:{begin:c,size:p}});return c[o]+=d,f})}var HG={kernelName:Jo,backendName:"webgl",kernelFunc:UG},jG="return sqrt(x);",GG=Ye({opSnippet:jG}),qG={kernelName:Qs,backendName:"webgl",kernelFunc:GG},XG="return x * x;",KG=Ye({opSnippet:XG}),ZG={kernelName:Fu,backendName:"webgl",kernelFunc:KG},U_="return (a - b) * (a - b);",YG=on({opSnippet:U_,packedOpSnippet:U_}),JG={kernelName:ni,backendName:"webgl",kernelFunc:YG};function QG({inputs:e,attrs:t,backend:n}){let{x:r}=e,a=Ir+`
|
|
return x > 0.0 ? 1.0 : float(${t.alpha});
|
|
`,s=new qa(r.shape,a);return n.runWebGLProgram(s,[r],r.dtype)}var eq={kernelName:$a,backendName:"webgl",kernelFunc:QG},tq=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=n;let r=n.length,a=dt(n.length),s=dt(n.length),i="";if(r===1)i="coords * strides + begin";else{let o=0;i=n.map((l,u)=>(o++,n.length===1?`coords * strides[${u}] + begin[${u}]`:`coords[${o-1}] * strides[${u}] + begin[${u}]`)).join(",")}this.userCode=`
|
|
${a} begin = ${a}(${e});
|
|
${a} strides = ${a}(${t});
|
|
|
|
void main() {
|
|
${s} coords = getOutputCoords();
|
|
setOutput(getX(${i}));
|
|
}
|
|
`}};function nq(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{begin:s,end:i,strides:o,beginMask:l,endMask:u,ellipsisMask:c,newAxisMask:h,shrinkAxisMask:d}=r,{nonStrided:p,$begin:f,$strides:m,size:A,newShape:y,outShape:g}=fn.sliceInfo(a.shape,s,i,o,l,u,c,h,d),b=xe({inputs:{x:a},backend:n,attrs:{shape:y}}),_;if(p){let x=bc({inputs:{x:b},backend:n,attrs:{begin:f,size:A}});_=xe({inputs:{x},backend:n,attrs:{shape:g}}),n.disposeIntermediateTensorInfo(x)}else if(g.some(x=>x===0))_=n.makeTensorInfo(g,a.dtype,[]);else if(n.shouldExecuteOnCPU([b])){let x=n.texData.get(b.dataId).values,N=Ue(b.shape,b.dtype,x),S=nL(g,N,m,f);_=n.makeTensorInfo(g,b.dtype,S.values)}else{let x=new tq(f,m,g);_=n.runWebGLProgram(x,[b],b.dtype)}let w=xe({inputs:{x:_},backend:n,attrs:{shape:g}});return n.disposeIntermediateTensorInfo(b),n.disposeIntermediateTensorInfo(_),w}var rq={kernelName:Qo,backendName:"webgl",kernelFunc:nq},aq="return tan(x);",sq=Ye({opSnippet:aq}),iq={kernelName:el,backendName:"webgl",kernelFunc:sq},oq=`
|
|
float e2x = exp(-2.0 * abs(x));
|
|
return sign(x) * (1.0 - e2x) / (1.0 + e2x);
|
|
`,lq=Ye({opSnippet:oq}),uq={kernelName:ai,backendName:"webgl",kernelFunc:lq},hq=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[s]*t[s];this.outputShape=n,this.rank=n.length;let r=dt(this.rank),a=cq(e);this.userCode=`
|
|
void main() {
|
|
${r} resRC = getOutputCoords();
|
|
setOutput(getA(${a}));
|
|
}
|
|
`}};function cq(e){let t=e.length;if(t>5)throw Error(`Tile for rank ${t} is not yet supported`);if(t===1)return`imod(resRC, ${e[0]})`;let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],r=[];for(let a=0;a<e.length;a++)r.push(`imod(${n[a]}, ${e[a]})`);return r.join()}function H_(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{reps:s}=r;if(a.dtype==="string"){let o=n.readSync(a.dataId).map(c=>v.decodeString(c)),l=Ue(a.shape,a.dtype,o),u=aL(l,s);return n.makeTensorInfo(u.shape,u.dtype,u.values)}let i=new hq(a.shape,s);return n.runWebGLProgram(i,[a],a.dtype)}var dq={kernelName:Ma,backendName:"webgl",kernelFunc:H_};function pq(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{k:s,sorted:i}=r,o=n.readSync(a.dataId),[l,u]=sL(o,a.shape,a.dtype,s,i);return[n.makeTensorInfo(l.shape,l.dtype,l.values),n.makeTensorInfo(u.shape,u.dtype,u.values)]}var fq={kernelName:tl,backendName:"webgl",kernelFunc:pq},mq=class{constructor(e,t,n,r,a,s){this.variableNames=["Image","Transforms"],this.outputShape=s;let i=n==="nearest"?1:2,o;switch(r){case"constant":o=1;break;case"reflect":o=2;break;case"wrap":o=3;break;case"nearest":o=4;break;default:o=1;break}this.userCode=`
|
|
float mapCoord(float outCoord, float len) {
|
|
float inCoord = outCoord;
|
|
if(${o} == 2) {
|
|
if (inCoord < 0.0) {
|
|
if (len <= 1.0) {
|
|
inCoord = 0.0;
|
|
} else {
|
|
float sz2 = 2.0 * len;
|
|
if (inCoord < sz2) {
|
|
inCoord = sz2 * float(int(float(-inCoord / sz2))) +
|
|
inCoord;
|
|
}
|
|
inCoord = inCoord < -len ? inCoord + sz2 : -inCoord - 1.0;
|
|
}
|
|
} else if (inCoord > len - 1.0) {
|
|
if (len <= 1.0) {
|
|
inCoord = 0.0;
|
|
} else {
|
|
float sz2 = 2.0 * len;
|
|
inCoord -= sz2 * float(int(float(inCoord / sz2)));
|
|
if (inCoord >= len) {
|
|
inCoord = sz2 - inCoord - 1.0;
|
|
}
|
|
}
|
|
}
|
|
return clamp(inCoord, 0.0, len - 1.0);
|
|
} else if (${o} == 3) {
|
|
if (inCoord < 0.0) {
|
|
if (len <= 1.0) {
|
|
inCoord = 0.0;
|
|
} else {
|
|
float sz = len - 1.0;
|
|
inCoord += len * (float(int(float(-inCoord / sz))) + 1.0);
|
|
}
|
|
} else if (inCoord > len - 1.0) {
|
|
if (len <= 1.0) {
|
|
inCoord = 0.0;
|
|
} else {
|
|
float sz = len - 1.0;
|
|
inCoord -= len * float(int(float(inCoord / sz)));
|
|
}
|
|
}
|
|
return clamp(inCoord, 0.0, len - 1.0);
|
|
} else if (${o} == 4) {
|
|
return clamp(outCoord, 0.0, len - 1.0);
|
|
} else {
|
|
return outCoord;
|
|
}
|
|
}
|
|
|
|
float readWithFillValue(int batch, int coordY, int coordX,
|
|
int channel) {
|
|
float outputValue;
|
|
if (0 <= coordY && coordY < ${e} && 0 <= coordX && coordX < ${t}) {
|
|
outputValue = getImage(batch, coordY, coordX, channel);
|
|
} else {
|
|
outputValue = float(${a});
|
|
}
|
|
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(${a});
|
|
} else {
|
|
float inX = (a1 * xf + a2 * yf + a3) / projection;
|
|
float inY = (b1 * xf + b2 * yf + b3) / projection;
|
|
float mapX = mapCoord(inX, float(${t}));
|
|
float mapY = mapCoord(inY, float(${e}));
|
|
|
|
if (${i} == 1) {
|
|
int coordY = int(round(mapY));
|
|
int coordX = int(round(mapX));
|
|
outputValue = readWithFillValue(batch, coordY, coordX,
|
|
channel);
|
|
} else {
|
|
float yFloor = floor(mapY);
|
|
float xFloor = floor(mapX);
|
|
float yCeil = yFloor + 1.0;
|
|
float xCeil = xFloor + 1.0;
|
|
float valueYFloor = (xCeil - mapX) *
|
|
readWithFillValue(batch, int(yFloor), int(xFloor), channel) +
|
|
(mapX - xFloor) *
|
|
readWithFillValue(batch, int(yFloor), int(xCeil), channel);
|
|
float valueYCeil = (xCeil - mapX) *
|
|
readWithFillValue(batch, int(yCeil), int(xFloor), channel) +
|
|
(mapX - xFloor) *
|
|
readWithFillValue(batch, int(yCeil), int(xCeil), channel);
|
|
outputValue = (yCeil - mapY) * valueYFloor +
|
|
(mapY - yFloor) * valueYCeil;
|
|
}
|
|
}
|
|
setOutput(outputValue);
|
|
}
|
|
`}};function Aq(e){let{inputs:t,backend:n,attrs:r}=e,{image:a,transforms:s}=t,{interpolation:i,fillMode:o,fillValue:l,outputShape:u}=r,[c,h,d,p]=a.shape,[f,m]=u!=null?u:[h,d],A=[c,f,m,p],y=new mq(h,d,i,o,l,A);return n.runWebGLProgram(y,[a,s],"float32")}var yq={kernelName:cd,backendName:"webgl",kernelFunc:Aq};function gq(e){let{inputs:t,attrs:n,backend:r}=e,{axis:a}=n,{x:s}=t;Fl(s,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");let i=r.readSync(s.dataId),{outputValues:o,outputShape:l,indices:u}=iL(i,a,s.shape,s.dtype);return[r.makeTensorInfo(l,s.dtype,o),r.makeTensorInfo([u.length],"int32",u)]}var xq={kernelName:hd,backendName:"webgl",kernelFunc:gq};function wq(e){let{inputs:t,backend:n,attrs:r}=e,{value:a}=t,{axis:s}=r;s<0&&(s+=a.shape.length);let i=a,o=i.shape.length,l=a.shape[s],u=new Array(o-1),c=0;for(let m=0;m<o;m++)m!==s&&(u[c++]=i.shape[m]);let h=[],d=new Array(o).fill(0),p=i.shape.slice();p[s]=1;let f=new Array(l);for(let m=0;m<f.length;m++){d[s]=m;let A=bc({inputs:{x:i},backend:n,attrs:{begin:d,size:p}}),y=xe({inputs:{x:A},backend:n,attrs:{shape:u}});f[m]=y,h.push(A)}return h.forEach(m=>n.disposeIntermediateTensorInfo(m)),f}var bq={kernelName:nl,backendName:"webgl",kernelFunc:wq},_q=class{constructor(e,t){this.variableNames=["x","segmentIds"];let n=e.windowSize,r=e.batchSize,a=e.inSize,s=e.numSegments,i=s*Math.ceil(a/n);this.outputShape=[r,i];let o="0.0",l="sumValue",u=Math.floor(n/4)*4,c=n%4,h=`
|
|
sumValue += dot(values, segFilter);
|
|
`,d="";a%n>0&&(d=`
|
|
if (inIdx < 0 || inIdx >= ${a}) {
|
|
return initializationValue;
|
|
}
|
|
`);let p="";a%n>0&&(p=`
|
|
if (inIdx < 0 || inIdx >= ${a}) {
|
|
return -1.0;
|
|
}
|
|
`),this.userCode=`
|
|
const float initializationValue = ${o};
|
|
|
|
float getValue(int batch, int inIdx) {
|
|
${d}
|
|
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(
|
|
${s})) * float(${n}));
|
|
int currentSeg = int(mod(float(outIdx), float(${s})));
|
|
|
|
float sumValue = 0.0;
|
|
|
|
for (int i = 0; i < ${u}; i += 4) {
|
|
int inIdx = inOffset + i;
|
|
vec4 values = vec4(
|
|
getValue(batch, inIdx),
|
|
getValue(batch, inIdx + 1),
|
|
getValue(batch, inIdx + 2),
|
|
getValue(batch, inIdx + 3)
|
|
);
|
|
|
|
vec4 segFilter = vec4(
|
|
int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
|
|
int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
|
|
int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,
|
|
int(getSegmentIdAtIndex(inIdx + 3)) == currentSeg ? 1 : 0
|
|
);
|
|
|
|
${h}
|
|
}
|
|
|
|
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
|
|
);
|
|
|
|
${h}
|
|
} else if (${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
|
|
);
|
|
|
|
${h}
|
|
} else if (${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
|
|
);
|
|
|
|
${h}
|
|
}
|
|
setOutput(${l});
|
|
}
|
|
`}};function vq(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,segmentIds:s}=t,{numSegments:i}=r,o=a.shape.length,l=[],u=0,c=R.getAxesPermutation([u],o),h=a;c!=null&&(h=Cn({inputs:{x:a},backend:n,attrs:{perm:c}}),l.push(h),u=R.getInnerMostAxes(1,o)[0]);let d=R.segment_util.computeOutShape(h.shape,u,i),p=v.sizeFromShape([h.shape[u]]),f=xe({inputs:{x:h},backend:n,attrs:{shape:[-1,p]}});l.push(f);let m=yd(a.dtype),A=(_,w,x,N,S)=>{let T=_.shape[0],M=_.shape[1],D=R.segment_util.segOpComputeOptimalWindowSize(M,S),z={windowSize:D,inSize:M,batchSize:T,numSegments:S},W=new _q(z,w),U=n.compileAndRun(W,[_,x],N);if(l.push(U),U.shape[1]===S)return U;let H=B_({backend:n,attrs:{start:0,stop:S,step:1,dtype:"float32"}}),X=H_({inputs:{x:H},backend:n,attrs:{reps:[M/D]}});return l.push(H),l.push(X),A(U,w,X,N,S)},y=A(f,"unsortedSegmentSum",s,m,i),g=xe({inputs:{x:y},backend:n,attrs:{shape:d}}),b=g;if(c!=null){l.push(g);let _=R.getUndoAxesPermutation(c);b=Cn({inputs:{x:b},backend:n,attrs:{perm:_}})}return l.forEach(_=>n.disposeIntermediateTensorInfo(_)),b}var kq={kernelName:Mu,backendName:"webgl",kernelFunc:vq},Iq=[fH,yH,nW,aW,oW,cW,dW,mW,yW,xW,vW,IW,TW,RW,PW,$W,BW,jW,UW,KW,YW,QW,rB,cB,dB,gB,wB,kB,SB,zL,RB,BB,UB,DB,qB,KB,jB,JB,tV,aV,iV,lV,hV,yV,xV,pV,_V,IV,EV,MV,zV,WV,BV,VV,HV,GV,XV,ZV,JV,nU,iU,lU,cU,pU,yU,bU,IU,OL,SU,CB,CU,MU,OU,LL,WU,HU,GU,QU,ZU,rH,iH,cH,xH,SH,IH,RH,MH,DH,vH,zH,LH,UH,qH,YH,sj,HL,oj,cj,pj,Aj,fB,xj,bj,vj,Nj,Cj,BL,Fj,Mj,mB,tj,Oj,Hj,Wj,GL,Xj,Yj,eG,rG,oG,uG,dG,mG,yG,wG,vG,NG,EG,FG,DG,lB,rj,PG,WG,VG,HG,qG,ZG,JG,eq,rq,nj,QL,iq,uq,dq,fq,yq,eW,xq,bq,kq,wj];for(let e of Iq)ui(e);var Vn;(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"})(Vn||(Vn={}));var vc;(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"})(vc||(vc={}));var j_;function Nq(e){j_=e.wasm.cwrap(ii,null,["number","array","number","number","array","number","number","number","number","number","number","number","number"])}function Sq(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s,bias:i,preluActivationWeights:o}=t;if(a.dtype!=="float32"||s.dtype!=="float32")throw new Error("_FusedMatMul for non non-float32 tensors not yet supported.");let{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:h}=r,d=n.dataIdMap.get(a.dataId).id,p=n.dataIdMap.get(s.dataId).id,f=0;if(i!=null){let S=n.dataIdMap.get(i.dataId);if(S.shape.length!==1)throw new Error(`_FusedMatMul only supports rank-1 bias but got rank ${S.shape.length}.`);f=S.id}let m=o==null?0:n.dataIdMap.get(o.dataId).id,A=vc[c];if(A==null)throw new Error(`${c} activation not yet supported for FusedConv2D in the wasm backend.`);let y=l?a.shape[2]:a.shape[1],g=u?s.shape[1]:s.shape[2],b=a.shape[0],_=n.makeOutput([b,y,g],a.dtype),w=n.dataIdMap.get(_.dataId).id,x=new Uint8Array(new Int32Array(a.shape).buffer),N=new Uint8Array(new Int32Array(s.shape).buffer);return j_(d,x,a.shape.length,p,N,s.shape.length,l,u,A,f,m,h||0,w),_}var Tq={kernelName:ii,backendName:"wasm",setupFunc:Nq,kernelFunc:Sq};function Rn(e){let t;function n(a){t=a.wasm.cwrap(e,null,["number","number"])}function r(a){let{backend:s,inputs:{x:i}}=a,o=s.dataIdMap.get(i.dataId).id,l=s.makeOutput(i.shape,i.dtype),u=s.dataIdMap.get(l.dataId).id;return v.sizeFromShape(l.shape)===0||t(o,u),l}return{kernelName:e,backendName:"wasm",setupFunc:n,kernelFunc:r}}var Eq=Rn(so);function wn(e,t,n){let r;function a(i){r=i.wasm.cwrap(e,null,["number","array","number","number","array","number","number","number"])}function s(i){let{backend:o,inputs:l}=i,{a:u,b:c}=l,h=o.dataIdMap.get(u.dataId).id,d=o.dataIdMap.get(c.dataId).id,p=n!=null?n:u.dtype,f=R.assertAndGetBroadcastShape(u.shape,c.shape),m=o.makeOutput(f,p);if(v.sizeFromShape(f)===0)return m;let A=new Uint8Array(new Int32Array(u.shape).buffer),y=new Uint8Array(new Int32Array(c.shape).buffer),g=o.dataIdMap.get(m.dataId).id,b=()=>r(h,A,u.shape.length,d,y,c.shape.length,Vn[u.dtype],g);if(t&&u.dtype==="float32")return b(),m;let _=R.getBroadcastDims(u.shape,f),w=R.getBroadcastDims(c.shape,f),x=_.every((S,T)=>S===T),N=w.every((S,T)=>S===T);if(x&&N)return b(),m;throw new Error(`Broadcasting along outer dims is not yet supported for ${u.dtype} ${e}.`)}return{kernelName:e,backendName:"wasm",setupFunc:a,kernelFunc:s}}var Cq=!0,Rq=wn(Ra,Cq),G_;function Fq(e){G_=e.wasm.cwrap(fs,null,["array","number","number","number"])}function Mq(e){let{inputs:t,backend:n}=e,r=n.makeOutput(t[0].shape,t[0].dtype);if(v.sizeFromShape(r.shape)===0)return r;let a=t.map(o=>n.dataIdMap.get(o.dataId).id),s=new Uint8Array(new Int32Array(a).buffer),i=n.dataIdMap.get(r.dataId).id;return G_(s,a.length,Vn[r.dtype],i),r}var $q={kernelName:fs,backendName:"wasm",setupFunc:Fq,kernelFunc:Mq};function Rp(e){let{inputs:{x:t},backend:n}=e,r=n.makeOutput(t.shape,t.dtype),a=n.typedArrayFromHeap(t);return n.typedArrayFromHeap(r).set(a),r}var Dq={kernelName:Rs,backendName:"wasm",kernelFunc:Rp},q_;function Oq(e){q_=e.wasm.cwrap(si,null,["number","array","number","number","number","array","number"])}function Fp(e){let{inputs:t,backend:n,attrs:r}=e,[a,s]=Pq(t.x.shape,r.perm),i=!0;for(let f=0;f<s.length;f++)s[f]!==f&&(i=!1);let o=zq(t.x.shape,r.perm),l={dataId:t.x.dataId,shape:a,dtype:t.x.dtype};if(i){let f=Rp({inputs:t,backend:n});return f.shape=o,f}let u=n.makeOutput(o,l.dtype),c=n.dataIdMap.get(l.dataId).id,h=n.dataIdMap.get(u.dataId).id,d=new Uint8Array(new Int32Array(s).buffer),p=new Uint8Array(new Int32Array(l.shape).buffer);return q_(c,p,l.shape.length,Vn[l.dtype],h,d,s.length),u}function zq(e,t){let n=new Array(e.length);for(let r=0;r<n.length;r++)n[r]=e[t[r]];return n}function Pq(e,t){let n=[],r=[];for(let a=0;a<e.length;++a)e[a]!==1&&n.push(e[a]),e[t[a]]!==1&&r.push(t[a]);for(let a=0;a<r.length;++a){let s=-1;for(let i=0;i<r.length;++i)r[i]>=a&&(s===-1||r[s]>r[i])&&(s=i);r[s]=a}return[n,r]}var Lq={kernelName:si,backendName:"wasm",kernelFunc:Fp,setupFunc:Oq};function Ul(e,t,n){let r=e.shape,a=e.shape.length,s=v.parseAxisParam(t,r),i=s,o=R.getAxesPermutation(i,a),l=null,u=!1;if(o!=null){let c=new Array(a);for(let d=0;d<c.length;d++)c[d]=r[o[d]];i=R.getInnerMostAxes(i.length,a),l=Fp({inputs:{x:e},attrs:{perm:o},backend:n});let h=n.dataIdMap.get(e.dataId).id;n.dataIdMap.get(l.dataId).id!==h&&(u=!0)}return{transposed:l,originalAxes:s,axes:i,inputWasTransposed:u}}var X_;function Wq(e){X_=e.wasm.cwrap(ms,null,["number","number","number","number","number"])}function Bq(e){let{backend:t,inputs:n,attrs:r}=e,{axis:a}=r,{x:s}=n,i=t.dataIdMap.get(s.dataId).id,o=i,l=s,{transposed:u,axes:c,inputWasTransposed:h}=Ul(s,a,t);if(h){let y=t.dataIdMap.get(u.dataId).id;y!==i&&(l=u,o=y)}let d=l.shape.slice(0,-1),p=t.makeOutput(d,"int32"),f=t.dataIdMap.get(p.dataId).id,m=v.sizeFromShape(p.shape),A=l.shape[c[0]];return X_(o,Vn[l.dtype],m,A,f),h&&t.disposeData(u.dataId),p}var Vq={kernelName:ms,backendName:"wasm",kernelFunc:Bq,setupFunc:Wq},K_;function Uq(e){K_=e.wasm.cwrap(As,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Hq(e){let{inputs:t,attrs:n,backend:r}=e,a=t.x,s=r.dataIdMap.get(a.dataId).id,{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=n,c=R.computePool2DInfo(a.shape,i,o,1,l,u),h=c.filterHeight,d=c.filterWidth,p=c.padInfo.top,f=c.padInfo.right,m=c.padInfo.bottom,A=c.padInfo.left,y=c.strideHeight,g=c.strideWidth,b=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 _=r.makeOutput(c.outShape,"float32"),w=r.dataIdMap.get(_.dataId).id;return K_(s,a.shape[0],a.shape[1],a.shape[2],h,d,p,f,m,A,y,g,b,w),_}var jq={kernelName:As,backendName:"wasm",setupFunc:Uq,kernelFunc:Hq};function Nr(e){let{inputs:t,attrs:n}=e,{x:r}=t,{shape:a}=n,s=v.sizeFromShape(r.shape),i=v.inferFromImplicitShape(a,s);return v.assert(s===v.sizeFromShape(i),()=>`new shape: ${i}, old shape: ${r.shape}. New shape and old shape must have the same number of elements.`),e.backend.incRef(r.dataId),{dataId:r.dataId,shape:i,dtype:r.dtype}}var Gq={kernelName:Ho,backendName:"wasm",kernelFunc:Nr},Z_;function qq(e){Z_=e.wasm.cwrap(ys,null,["number","array","number","number","array","number","number","number","number"])}function Xq(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s}=t,{transposeA:i,transposeB:o}=r;if(a.dtype!=="float32"||s.dtype!=="float32")throw new Error("BatchMatMul for non non-float32 tensors not yet supported.");let l=a.shape.length,u=s.shape.length,c=i?a.shape[l-2]:a.shape[l-1],h=o?s.shape[u-1]:s.shape[u-2],d=i?a.shape[l-1]:a.shape[l-2],p=o?s.shape[u-2]:s.shape[u-1],f=a.shape.slice(0,-2),m=s.shape.slice(0,-2),A=v.sizeFromShape(f),y=v.sizeFromShape(m),g=A===y||A===1||y===1;v.assert(l>=2&&u>=2&&g,()=>`Error in matMul: the input batch dimensions must either be the same or at least one input batch dimension must be 1. Got input batch dimensions of (${f}) and (${m}).`);let b=(A>y?a.shape.slice(0,-2):s.shape.slice(0,-2)).concat([d,p]);v.assert(c===h,()=>`Error in matMul: inner shapes (${c}) and (${h}) of Tensors with shapes ${a.shape} and ${s.shape} and transposeA=${i} and transposeB=${o} must match.`);let _=i?[A,c,d]:[A,d,c],w=o?[y,p,h]:[y,h,p],x=Nr({inputs:{x:a},backend:n,attrs:{shape:_}}),N=Nr({inputs:{x:s},backend:n,attrs:{shape:w}}),S=n.dataIdMap.get(x.dataId).id,T=n.dataIdMap.get(N.dataId).id,M=i?x.shape[2]:x.shape[1],D=o?N.shape[1]:N.shape[2],z=Math.max(A,y),W=n.makeOutput([z,M,D],x.dtype),U=n.dataIdMap.get(W.dataId).id,H=new Uint8Array(new Int32Array(x.shape).buffer),X=new Uint8Array(new Int32Array(N.shape).buffer);return Z_(S,H,x.shape.length,T,X,N.shape.length,i,o,U),n.disposeData(x.dataId),n.disposeData(N.dataId),W.shape=b,W}var Kq={kernelName:ys,backendName:"wasm",setupFunc:qq,kernelFunc:Xq};function Mp(e){let{inputs:{x:t},attrs:{dtype:n},backend:r}=e,a=r.makeOutput(t.shape,n),s=r.typedArrayFromHeap(t);return r.typedArrayFromHeap(a).set(s),a}var Zq={kernelName:gs,backendName:"wasm",kernelFunc:Mp},Yq=Rn(xs),Y_;function Jq(e){Y_=e.wasm.cwrap(Fa,null,["number","number","number","number"])}function Qq(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{clipValueMin:s,clipValueMax:i}=r,o=n.dataIdMap.get(a.dataId).id,l=n.makeOutput(a.shape,a.dtype),u=n.dataIdMap.get(l.dataId).id;return Y_(o,s,i,u),l}var eX={kernelName:Fa,backendName:"wasm",setupFunc:Jq,kernelFunc:Qq};function J_(e){let{inputs:t,backend:n}=e,r=v.parseAxisParam(e.attrs.axis,t[0].shape)[0],a=R.computeOutShape(t.map(p=>p.shape),r),s=t.filter(p=>v.sizeFromShape(p.shape)>0);if(s.length===1)return Rp({inputs:{x:s[0]},backend:n});let i=n.makeOutput(a,t[0].dtype);if(v.sizeFromShape(a)===0)return i;let o=s.map(p=>p.shape);if(R.assertParamsConsistent(o,r),s[0].dtype==="string"){let p=s.map(b=>{let _=v.sizeFromShape(b.shape.slice(r));return Nr({inputs:{x:b},backend:n,attrs:{shape:[-1,_]}})}),f=p.map(b=>({vals:n.readSync(b.dataId),shape:b.shape}));a=R.computeOutShape(p.map(b=>b.shape),1);let m=p[0].shape[0]===1,A=Um(f,a,t[0].dtype,m),y=R.computeOutShape(s.map(b=>b.shape),r);i.shape=y;let g=n.dataIdMap.get(i.dataId);return g.stringBytes=R.fromStringArrayToUint8(A),p.forEach(b=>n.disposeData(b.dataId)),i}let l=v.sizeFromShape(s[0].shape.slice(0,r)),u=0,c=s.map(p=>{let f=v.sizeFromShape(p.shape.slice(r));return u+=f,f}),h=s.map(p=>n.typedArrayFromHeap(p)),d=n.typedArrayFromHeap(i);for(let p=0;p<l;p++){let f=p*u;for(let m=0;m<h.length;m++){let A=c[m],y=p*A,g=h[m].subarray(y,y+A);d.set(g,f),f+=A}}return i}var tX={kernelName:fo,backendName:"wasm",kernelFunc:J_},Q_;function nX(e){Q_=e.wasm.cwrap(ws,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function rX(e){let{inputs:t,attrs:n,backend:r}=e,{x:a,filter:s}=t,i=r.dataIdMap.get(a.dataId).id,o=r.dataIdMap.get(s.dataId).id,{strides:l,dilations:u,pad:c,dimRoundingMode:h,dataFormat:d}=n,p=R.convertConv2DDataFormat(d),f=R.computeConv2DInfo(a.shape,s.shape,l,u,c,h,!1,p),m=f.filterHeight,A=f.filterWidth,y=f.padInfo.top,g=f.padInfo.right,b=f.padInfo.bottom,_=f.padInfo.left,w=f.dilationHeight,x=f.dilationWidth,N=f.strideHeight,S=f.strideWidth,T=f.inChannels,M=f.outChannels,D=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 z=r.makeOutput(f.outShape,"float32"),W=r.dataIdMap.get(z.dataId).id;return Q_(i,a.shape[0],a.shape[1],a.shape[2],o,m,A,y,g,b,_,D,w,x,N,S,T,M,W),z}var aX={kernelName:ws,backendName:"wasm",setupFunc:nX,kernelFunc:rX},e3;function sX(e){e3=e.wasm.cwrap(bs,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 iX(e){let{backend:t,inputs:n,attrs:r}=e,{dy:a,filter:s}=n,{strides:i,pad:o,dataFormat:l,dimRoundingMode:u,inputShape:c}=r,h=1,d=R.convertConv2DDataFormat(l),p=R.computeConv2DInfo(c,s.shape,i,h,o,u,!1,d),{batchSize:f,filterHeight:m,filterWidth:A,inChannels:y,inHeight:g,inWidth:b,outChannels:_,outHeight:w,outWidth:x,strideHeight:N,strideWidth:S}=p,T=m-1-p.padInfo.top,M=A-1-p.padInfo.left,D=p.dataFormat==="channelsLast",z=v.computeStrides(p.inShape),W=v.computeStrides(a.shape),[U,H,X]=v.computeStrides(s.shape),j=z[0],ee=D?z[1]:z[2],Y=D?z[2]:1,se=D?1:z[1],te=W[0],oe=D?W[1]:W[2],Q=D?W[2]:1,pe=D?1:W[1],le=t.makeOutput(p.inShape,"float32"),Ae=t.dataIdMap.get(le.dataId).id,me=t.dataIdMap.get(a.dataId).id,Se=t.dataIdMap.get(s.dataId).id;return e3(me,Se,f,m,A,g,b,y,w,x,_,N,S,T,M,U,H,X,j,ee,Y,se,te,oe,Q,pe,Ae),le}var oX={kernelName:bs,backendName:"wasm",setupFunc:sX,kernelFunc:iX},lX=Rn(_s),_A;(function(e){e[e.bilinear=0]="bilinear",e[e.nearest=1]="nearest"})(_A||(_A={}));var t3;function uX(e){t3=e.wasm.cwrap(Ao,null,["number","number","number","number","array","number","number","number","number","number"])}function cX(e){let{backend:t,inputs:n,attrs:r}=e,{method:a,extrapolationValue:s,cropSize:i}=r,{image:o,boxes:l,boxInd:u}=n,c=l.shape[0],[h,d]=i,p=[c,h,d,o.shape[3]],f=t.dataIdMap.get(o.dataId),m;o.dtype!=="float32"&&(m=Mp({backend:t,inputs:{x:o},attrs:{dtype:"float32"}}),f=t.dataIdMap.get(m.dataId));let A=f.id,y=t.dataIdMap.get(l.dataId).id,g=t.dataIdMap.get(u.dataId).id,b=t.makeOutput(p,"float32"),_=t.dataIdMap.get(b.dataId).id,w=new Uint8Array(new Int32Array(o.shape).buffer);return t3(A,y,g,c,w,h,d,_A[a],s,_),m!=null&&t.disposeData(m.dataId),b}var hX={kernelName:Ao,backendName:"wasm",setupFunc:uX,kernelFunc:cX},n3;function dX(e){n3=e.wasm.cwrap(vs,null,["number","number","number","number","number","number"])}function pX(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=r,l=a.shape.length;v.assert(a.dtype==="float32"||a.dtype==="int32",()=>`cumsum does not support ${a.dtype} tensors in the WASM backend`);let u=R.getAxesPermutation([s],l),c=a;u!==null&&(c=Fp({inputs:{x:a},attrs:{perm:u},backend:n}));let h=R.getInnerMostAxes(1,l)[0];R.assertAxesAreInnerMostDims("cumsum",[h],l);let d=n.makeOutput(c.shape,c.dtype),p=c.shape[h],f=n.dataIdMap.get(c.dataId).id,m=n.dataIdMap.get(d.dataId).id;n3(f,i?1:0,o?1:0,p,m,Vn[a.dtype]);let A=d;if(u!==null){let y=R.getUndoAxesPermutation(u);A=Fp({inputs:{x:d},attrs:{perm:y},backend:n}),n.disposeData(c.dataId),n.disposeData(d.dataId)}return A}var fX={kernelName:vs,backendName:"wasm",setupFunc:dX,kernelFunc:pX},r3;function mX(e){r3=e.wasm.cwrap(yo,null,["number","number","number","array","number","array","array","number","number"])}function AX(e){let{backend:t,inputs:n,attrs:r}=e,{x:a}=n,{blockSize:s,dataFormat:i}=r;v.assert(s>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${s}`);let o=a.shape[0],l=i==="NHWC"?a.shape[1]:a.shape[2],u=i==="NHWC"?a.shape[2]:a.shape[3],c=i==="NHWC"?a.shape[3]:a.shape[1],h=l*s,d=u*s,p=c/(s*s),f=i==="NHWC"?[o,h,d,p]:[o,p,h,d],m=t.makeOutput(f,"float32"),A=t.dataIdMap.get(a.dataId).id,y=new Uint8Array(new Int32Array(v.computeStrides(a.shape)).buffer),g=new Uint8Array(new Int32Array(f).buffer),b=new Uint8Array(new Int32Array(v.computeStrides(f)).buffer),_=t.dataIdMap.get(m.dataId).id;return r3(A,s,i==="NHWC"?1:0,y,a.shape.length-1,g,b,f.length,_),m}var yX={kernelName:yo,backendName:"wasm",setupFunc:mX,kernelFunc:AX},a3;function gX(e){a3=e.wasm.cwrap(ks,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function xX(e){let{inputs:t,attrs:n,backend:r}=e,{x:a,filter:s}=t,i=r.dataIdMap.get(a.dataId).id,o=r.dataIdMap.get(s.dataId).id,{strides:l,dilations:u,pad:c,dimRoundingMode:h}=n,d=u==null?[1,1]:u,p=R.computeConv2DInfo(a.shape,s.shape,l,d,c,h,!0),f=p.filterHeight,m=p.filterWidth,A=p.padInfo.top,y=p.padInfo.right,g=p.padInfo.bottom,b=p.padInfo.left,_=p.dilationHeight,w=p.dilationWidth,x=p.strideHeight,N=p.strideWidth,S=p.inChannels,T=p.outChannels,M=p.padInfo.type==="SAME"?1:0;if(p.dataFormat!=="channelsLast")throw new Error(`wasm backend DepthwiseConv2dNative does not support dataFormat:'${p.dataFormat}'. Please use 'channelsLast'.`);let D=r.makeOutput(p.outShape,"float32"),z=r.dataIdMap.get(D.dataId).id;return a3(i,a.shape[0],a.shape[1],a.shape[2],o,f,m,A,y,g,b,M,_,w,x,N,S,T,z),D}var wX={kernelName:ks,backendName:"wasm",setupFunc:gX,kernelFunc:xX},bX=!1,_X=wn(wo,bX,"bool"),vX=Rn(Ns);function vA(e){let{inputs:t,attrs:n,backend:r}=e,{input:a}=t,{dim:s}=n,i=a.shape.length,o=a.shape.slice(),l=s;return s<0&&(v.assert(-(i+1)<=s,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+s+1),o.splice(l,0,1),Nr({inputs:{x:a},backend:r,attrs:{shape:o}})}var kX={kernelName:bo,backendName:"wasm",kernelFunc:vA};function IX(e){let{attrs:{shape:t,value:n,dtype:r},backend:a}=e,s=a.makeOutput(t,r);return a.typedArrayFromHeap(s).fill(n),s}var NX={kernelName:vu,backendName:"wasm",kernelFunc:IX},s3;function SX(e){s3=e.wasm.cwrap(vo,null,["number","number","number","number","number","number"])}function TX(e){let{inputs:t,backend:n}=e,{image:r}=t,a=n.makeOutput(r.shape,r.dtype),s=n.dataIdMap.get(r.dataId).id,i=n.dataIdMap.get(a.dataId).id,[o,l,u,c]=r.shape;return s3(s,o,l,u,c,i),a}var EX={kernelName:vo,backendName:"wasm",kernelFunc:TX,setupFunc:SX},CX=Rn(Ss),RX=!1,FX=wn(Ts,RX),i3;function MX(e){i3=e.wasm.cwrap(Es,null,["number","number","number","number","number","number","number"])}function $X(e){let{backend:t,inputs:n,attrs:r}=e,{varianceEpsilon:a}=r,{x:s,mean:i,variance:o,offset:l,scale:u}=n,c=t.dataIdMap.get(s.dataId).id,h=t.dataIdMap.get(i.dataId).id,d=t.dataIdMap.get(o.dataId).id,p=l!=null?t.dataIdMap.get(l.dataId).id:0,f=u!=null?t.dataIdMap.get(u.dataId).id:0,m=t.makeOutput(s.shape,s.dtype);if(v.sizeFromShape(s.shape)===0)return m;let A=t.dataIdMap.get(m.dataId).id;return i3(c,h,d,p,f,a,A),m}var DX={kernelName:Es,backendName:"wasm",setupFunc:MX,kernelFunc:$X},o3;function OX(e){o3=e.wasm.cwrap(oi,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 zX(e){let{inputs:t,attrs:n,backend:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:c,dataFormat:h,dimRoundingMode:d,activation:p,leakyreluAlpha:f}=n,m=R.computeConv2DInfo(a.shape,s.shape,l,c,u,d),A=vc[p];if(A==null)throw new Error(`${p} activation not yet supported for FusedConv2D in the wasm backend.`);let y=r.dataIdMap.get(a.dataId).id,g=r.dataIdMap.get(s.dataId).id,b=m.outChannels,_=0;if(i!=null){let Q=r.dataIdMap.get(i.dataId);if(Q.shape.length!==1)throw new Error(`FusedConv2D only supports rank-1 bias but got rank ${Q.shape.length}.`);if(Q.shape[0]!==b)throw new Error(`FusedConv2D bias shape (${Q.shape}) does not match the number of output channels (${b})`);_=Q.id}let w=m.filterHeight,x=m.filterWidth,N=m.padInfo.top,S=m.padInfo.right,T=m.padInfo.bottom,M=m.padInfo.left,D=m.dilationHeight,z=m.dilationWidth,W=m.strideHeight,U=m.strideWidth,H=m.inChannels,X=m.padInfo.type==="SAME"?1:0,j=m.batchSize,ee=m.inHeight,Y=m.inWidth;if(h!=="NHWC")throw new Error(`wasm backend FusedConv2D does not support dataFormat:'${h}'. Please use 'NHWC'.`);let se=r.makeOutput(m.outShape,"float32"),te=r.dataIdMap.get(se.dataId).id,oe=o==null?0:r.dataIdMap.get(o.dataId).id;return o3(y,j,ee,Y,g,w,x,_,N,S,T,M,X,D,z,W,U,H,b,A,oe,f||0,te),se}var PX={kernelName:oi,backendName:"wasm",setupFunc:OX,kernelFunc:zX},l3;function LX(e){l3=e.wasm.cwrap(li,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 WX(e){let{inputs:t,attrs:n,backend:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:c,dataFormat:h,dimRoundingMode:d,activation:p,leakyreluAlpha:f}=n,m=R.computeConv2DInfo(a.shape,s.shape,l,c,u,d,!0),A=vc[p];if(A==null)throw new Error(`${p} activation not yet supported for FusedDepthwiseConv2D in the wasm backend.`);let y=r.dataIdMap.get(a.dataId).id,g=r.dataIdMap.get(s.dataId).id,b=m.outChannels,_=0;if(i!=null){let Q=r.dataIdMap.get(i.dataId);if(Q.shape.length!==1)throw new Error(`FusedDepthwiseConv2D only supports rank-1 bias but got rank ${Q.shape.length}.`);if(Q.shape[0]!==b)throw new Error(`FusedDepthwiseConv2D bias shape (${Q.shape}) does not match the number of output channels (${b})`);_=Q.id}let w=m.filterHeight,x=m.filterWidth,N=m.padInfo.top,S=m.padInfo.right,T=m.padInfo.bottom,M=m.padInfo.left,D=m.dilationHeight,z=m.dilationWidth,W=m.strideHeight,U=m.strideWidth,H=m.inChannels,X=m.padInfo.type==="SAME"?1:0,j=m.batchSize,ee=m.inHeight,Y=m.inWidth;if(h!=="NHWC")throw new Error(`wasm backend FusedDepthwiseConv2D does not support dataFormat:'${h}'. Please use 'NHWC'.`);let se=r.makeOutput(m.outShape,"float32"),te=r.dataIdMap.get(se.dataId).id,oe=o==null?0:r.dataIdMap.get(o.dataId).id;return l3(y,j,ee,Y,g,w,x,_,N,S,T,M,X,D,z,W,U,H,b,A,oe,f||0,te),se}var BX={kernelName:li,backendName:"wasm",setupFunc:LX,kernelFunc:WX},u3;function VX(e){u3=e.wasm.cwrap(Io,null,["number","number","number","number","number","number","array","number"])}function UX(e){let{backend:t,inputs:n}=e,{params:r,indices:a}=n,[s,i,o,l]=Vf.prepareAndValidate(r,a),u=t.makeOutput(s,r.dtype);if(i===0)return u;let c=a.shape,h=c[c.length-1],d=t.dataIdMap.get(r.dataId).id,p=t.dataIdMap.get(a.dataId).id,f=new Uint8Array(new Int32Array(l).buffer),m=t.dataIdMap.get(u.dataId).id;return u3(d,Vn[r.dtype],p,i,h,o,f,m),u}var HX={kernelName:Io,backendName:"wasm",setupFunc:VX,kernelFunc:UX},c3;function jX(e){c3=e.wasm.cwrap("Gather",null,["number","number","array","number","number","number","array","number"])}function GX(e){let{backend:t,inputs:n,attrs:r}=e,{x:a,indices:s}=n,{axis:i,batchDims:o}=r,l=v.parseAxisParam(i,a.shape)[0],u=R.segment_util.collectGatherOpShapeInfo(a,s,l,o),c=Nr({inputs:{x:a},attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]},backend:t}),h=v.sizeFromShape(s.shape),d=Nr({inputs:{x:s},attrs:{shape:[u.batchSize,h/u.batchSize]},backend:t}),p=[u.batchSize,u.outerSize,h/u.batchSize,u.sliceSize],f=t.makeOutput(p,a.dtype);if(v.sizeFromShape(a.shape)===0)return f;let m=c.shape.length-1,A=t.dataIdMap.get(c.dataId).id,y=t.dataIdMap.get(d.dataId).id,g=t.dataIdMap.get(f.dataId).id,b=new Uint8Array(new Int32Array(v.computeStrides(c.shape)).buffer),_=new Uint8Array(new Int32Array(v.computeStrides(p)).buffer);return c3(A,Vn[a.dtype],b,m,y,u.batchSize,_,g),t.disposeData(c.dataId),t.disposeData(d.dataId),f.shape=u.outputShape,f}var qX={kernelName:ko,backendName:"wasm",setupFunc:jX,kernelFunc:GX},XX=!1,KX=wn(No,XX,"bool"),ZX=!1,YX=wn(Cs,ZX,"bool"),h3;function JX(e){h3=e.wasm.cwrap(Fs,null,["number","number","number"])}function QX(e){let{inputs:{x:t},attrs:{alpha:n},backend:r}=e,a=r.dataIdMap.get(t.dataId).id,s=r.makeOutput(t.shape,t.dtype);if(v.sizeFromShape(t.shape)!==0){let i=r.dataIdMap.get(s.dataId).id;h3(a,n,i)}return s}var eK={kernelName:Fs,backendName:"wasm",setupFunc:JX,kernelFunc:QX},tK=!1,nK=wn(Co,tK,"bool"),rK=!1,aK=wn(Ro,rK,"bool"),sK=Rn(Ms),iK=!1,oK=wn(Mo,iK,"bool"),d3;function lK(e){d3=e.wasm.cwrap($s,null,["number, number, number"])}function uK(e){let{backend:t,inputs:n,attrs:r}=e,{reductionIndices:a,keepDims:s}=r,{x:i}=n,o=t.dataIdMap.get(i.dataId).id,l=i,{transposed:u,axes:c,originalAxes:h,inputWasTransposed:d}=Ul(i,a,t);if(d){let g=t.dataIdMap.get(u.dataId).id;l=u,o=g}let p=l.shape.length;R.assertAxesAreInnerMostDims("max",c,p);let[f,m]=R.computeOutAndReduceShapes(l.shape,c),A=v.sizeFromShape(m),y=t.makeOutput(f,i.dtype);if(v.sizeFromShape(l.shape)!==0){let g=t.dataIdMap.get(y.dataId).id;d3(o,A,g)}if(d&&t.disposeData(u.dataId),s){let g=R.expandShapeToKeepDim(y.shape,h);y.shape=g}return y}var cK={kernelName:$s,backendName:"wasm",setupFunc:lK,kernelFunc:uK},hK=!1,dK=wn(Ds,hK),p3;function pK(e){p3=e.wasm.cwrap(Os,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function fK(e){let{inputs:t,attrs:n,backend:r}=e,a=t.x,s=r.dataIdMap.get(a.dataId).id,{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=n,c=R.computePool2DInfo(a.shape,i,o,1,l,u),h=c.filterHeight,d=c.filterWidth,p=c.padInfo.top,f=c.padInfo.right,m=c.padInfo.bottom,A=c.padInfo.left,y=c.dilationHeight,g=c.dilationWidth,b=c.strideHeight,_=c.strideWidth,w=c.inChannels,x=c.outChannels;if(c.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${c.dataFormat}'. Please use 'channelsLast'.`);let N=r.makeOutput(c.outShape,"float32"),S=r.dataIdMap.get(N.dataId).id;return p3(s,a.shape[0],a.shape[1],a.shape[2],h,d,p,f,m,A,y,g,b,_,w,x,S),N}var mK={kernelName:Os,backendName:"wasm",setupFunc:pK,kernelFunc:fK},f3;function AK(e){f3=e.wasm.cwrap(zs,null,["number, number, number"])}function yK(e){let{backend:t,inputs:n,attrs:r}=e,{axis:a,keepDims:s}=r,{x:i}=n,o=t.dataIdMap.get(i.dataId).id,l=o,u=i,{transposed:c,axes:h,originalAxes:d,inputWasTransposed:p}=Ul(i,a,t),f=h;if(p){let _=t.dataIdMap.get(c.dataId).id;_!==o&&(u=c,l=_,f=R.getInnerMostAxes(f.length,u.shape.length))}R.assertAxesAreInnerMostDims("mean",f,u.shape.length);let[m,A]=R.computeOutAndReduceShapes(u.shape,f),y=v.sizeFromShape(A),g=u;u.dtype!=="float32"&&(g=Mp({backend:t,inputs:{x:u},attrs:{dtype:"float32"}}),l=t.dataIdMap.get(g.dataId).id);let b=t.makeOutput(m,"float32");if(v.sizeFromShape(u.shape)!==0){let _=t.dataIdMap.get(b.dataId).id;f3(l,y,_)}if(p&&t.disposeData(c.dataId),s){let _=R.expandShapeToKeepDim(b.shape,d);b.shape=_}return u.dtype!=="float32"&&t.disposeData(g.dataId),b}var gK={kernelName:zs,backendName:"wasm",setupFunc:AK,kernelFunc:yK},m3;function xK(e){m3=e.wasm.cwrap(Ps,null,["number, number, number"])}function wK(e){let{backend:t,inputs:n,attrs:r}=e,{axis:a,keepDims:s}=r,{x:i}=n,o=t.dataIdMap.get(i.dataId).id,l=o,u=i,{transposed:c,axes:h,originalAxes:d,inputWasTransposed:p}=Ul(i,a,t);if(p){let b=t.dataIdMap.get(c.dataId).id;b!==o&&(u=c,l=b)}let f=u.shape.length;R.assertAxesAreInnerMostDims("min",h,f);let[m,A]=R.computeOutAndReduceShapes(u.shape,h),y=v.sizeFromShape(A),g=t.makeOutput(m,u.dtype);if(v.sizeFromShape(u.shape)!==0){let b=t.dataIdMap.get(g.dataId).id;m3(l,y,b)}if(p&&t.disposeData(c.dataId),s){let b=R.expandShapeToKeepDim(g.shape,d);g.shape=b}return g}var bK={kernelName:Ps,backendName:"wasm",setupFunc:xK,kernelFunc:wK},_K=!1,vK=wn(Ls,_K),kK=!0,IK=wn(Ws,kK),NK=Rn(Do);function kA(e,t){let n=new Int32Array(e.wasm.HEAPU8.buffer,t,4),r=n[0],a=n[1],s=n[2],i=n[3];return e.wasm._free(t),{pSelectedIndices:r,selectedSize:a,pSelectedScores:s,pValidOutputs:i}}var A3;function SK(e){A3=e.wasm.cwrap(zo,"number",["number","number","number","number","number"])}function TK(e){let{backend:t,inputs:n,attrs:r}=e,{iouThreshold:a,maxOutputSize:s,scoreThreshold:i}=r,{boxes:o,scores:l}=n,u=t.dataIdMap.get(o.dataId).id,c=t.dataIdMap.get(l.dataId).id,h=A3(u,c,s,a,i),{pSelectedIndices:d,selectedSize:p,pSelectedScores:f,pValidOutputs:m}=kA(t,h);return t.wasm._free(f),t.wasm._free(m),t.makeOutput([p],"int32",d)}var EK={kernelName:zo,backendName:"wasm",setupFunc:SK,kernelFunc:TK},y3;function CK(e){y3=e.wasm.cwrap(Po,"number",["number","number","number","number","number","bool"])}function RK(e){let{backend:t,inputs:n,attrs:r}=e,{iouThreshold:a,maxOutputSize:s,scoreThreshold:i,padToMaxOutputSize:o}=r,{boxes:l,scores:u}=n,c=t.dataIdMap.get(l.dataId).id,h=t.dataIdMap.get(u.dataId).id,d=y3(c,h,s,a,i,o),{pSelectedIndices:p,selectedSize:f,pSelectedScores:m,pValidOutputs:A}=kA(t,d);t.wasm._free(m);let y=t.makeOutput([f],"int32",p),g=t.makeOutput([],"int32",A);return[y,g]}var FK={kernelName:Po,backendName:"wasm",setupFunc:CK,kernelFunc:RK},g3;function MK(e){g3=e.wasm.cwrap(Lo,"number",["number","number","number","number","number","number"])}function $K(e){let{backend:t,inputs:n,attrs:r}=e,{iouThreshold:a,maxOutputSize:s,scoreThreshold:i,softNmsSigma:o}=r,{boxes:l,scores:u}=n,c=t.dataIdMap.get(l.dataId).id,h=t.dataIdMap.get(u.dataId).id,d=g3(c,h,s,a,i,o),{pSelectedIndices:p,selectedSize:f,pSelectedScores:m,pValidOutputs:A}=kA(t,d);t.wasm._free(A);let y=t.makeOutput([f],"int32",p),g=t.makeOutput([f],"float32",m);return[y,g]}var DK={kernelName:Lo,backendName:"wasm",setupFunc:MK,kernelFunc:$K},OK=!1,zK=wn(Oo,OK,"bool"),x3;function PK(e){x3=e.wasm.cwrap(Bs,null,["number","number","number","number","number"])}function LK(e){let{inputs:t,backend:n,attrs:r}=e,{indices:a}=t,{depth:s,onValue:i,offValue:o}=r,l=n.makeOutput([...a.shape,s],"int32"),u=n.dataIdMap.get(l.dataId).id,c=n.dataIdMap.get(a.dataId).id;return x3(c,s,i,o,u),l}var WK={kernelName:Bs,backendName:"wasm",setupFunc:PK,kernelFunc:LK};function BK(e){let{inputs:{x:t},backend:n}=e,r=n.makeOutput(t.shape,t.dtype);return n.typedArrayFromHeap(r).fill(1),r}var VK={kernelName:Wo,backendName:"wasm",kernelFunc:BK};function UK(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r;if(t.length===1)return vA({inputs:{input:t[0]},backend:n,attrs:{dim:a}});let s=t[0].shape,i=t[0].dtype;t.forEach(c=>{v.assertShapesMatch(s,c.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(c=>{let h=vA({inputs:{input:c},backend:n,attrs:{dim:a}});return o.push(h),h}),u=J_({inputs:l,backend:n,attrs:{axis:a}});return o.forEach(c=>n.disposeData(c.dataId)),u}var HK={kernelName:Bo,backendName:"wasm",kernelFunc:UK},w3;function jK(e){w3=e.wasm.cwrap(Vs,null,["number","array","number","number","array","array","number","number"])}function GK(e){let{inputs:{x:t},backend:n,attrs:{paddings:r,constantValue:a}}=e,s=r.map((f,m)=>f[0]+t.shape[m]+f[1]),i=n.dataIdMap.get(t.dataId).id,o=n.makeOutput(s,t.dtype),l=n.dataIdMap.get(o.dataId).id,u=new Uint8Array(new Int32Array(t.shape).buffer),c=r.map(f=>f[0]),h=r.map(f=>f[1]),d=new Uint8Array(new Int32Array(c).buffer),p=new Uint8Array(new Int32Array(h).buffer);return w3(i,u,t.shape.length,Vn[t.dtype],d,p,a,l),o}var qK={kernelName:Vs,backendName:"wasm",kernelFunc:GK,setupFunc:jK},XK=!1,KK=wn(Us,XK),b3;function ZK(e){b3=e.wasm.cwrap(Hs,null,["number","number","number"])}function YK(e){let{inputs:t,backend:n}=e,{x:r,alpha:a}=t,s=n.dataIdMap.get(r.dataId).id,i=n.dataIdMap.get(a.dataId).id,o=n.makeOutput(r.shape,"float32"),l=n.dataIdMap.get(o.dataId).id;return b3(s,i,l),o}var JK={kernelName:Hs,backendName:"wasm",setupFunc:ZK,kernelFunc:YK},_3;function QK(e){_3=e.wasm.cwrap(Vo,null,["number","number","number","number"])}function eZ(e){let{backend:t,inputs:n,attrs:r}=e,{axis:a,keepDims:s}=r,{x:i}=n,o=t.dataIdMap.get(i.dataId).id,l=o,u=i,{transposed:c,axes:h,originalAxes:d,inputWasTransposed:p}=Ul(i,a,t),f=h;if(p){let b=t.dataIdMap.get(c.dataId).id;b!==o&&(u=c,l=b,f=R.getInnerMostAxes(f.length,u.shape.length))}R.assertAxesAreInnerMostDims("prod",f,u.shape.length);let[m,A]=R.computeOutAndReduceShapes(u.shape,f),y=v.sizeFromShape(A),g=t.makeOutput(m,u.dtype);if(v.sizeFromShape(u.shape)!==0){let b=t.dataIdMap.get(g.dataId).id;_3(l,y,Vn[g.dtype],b)}if(p&&t.disposeData(c.dataId),s){let b=R.expandShapeToKeepDim(g.shape,d);g.shape=b}return g}var tZ={kernelName:Vo,backendName:"wasm",setupFunc:QK,kernelFunc:eZ},nZ=e=>{let{backend:t,attrs:n}=e,{start:r,stop:a,step:s,dtype:i}=n,o=Gm(r,a,s,i),l=t.makeOutput([o.length],i);return t.typedArrayFromHeap(l).set(o),l},rZ={kernelName:Eu,backendName:"wasm",kernelFunc:nZ},aZ=!0,sZ=wn(Is,aZ),iZ=Rn(js),oZ=Rn(qs),v3;function lZ(e){v3=e.wasm.cwrap(Gs,null,["number","number","number","number","number","number","number","number","number","number"])}function uZ(e){let{backend:t,inputs:n,attrs:r}=e,{images:a}=n,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,u]=o,[c,h,d,p]=a.shape,f=[c,l,u,p],m=t.dataIdMap.get(a.dataId),A;m.dtype!=="float32"&&(A=Mp({backend:t,inputs:{x:a},attrs:{dtype:"float32"}}),m=t.dataIdMap.get(A.dataId));let y=m.id,g=t.makeOutput(f,"float32");if(v.sizeFromShape(a.shape)===0)return g;let b=t.dataIdMap.get(g.dataId).id;return v3(y,c,h,d,p,l,u,s?1:0,i?1:0,b),A!=null&&t.disposeData(A.dataId),g}var cZ={kernelName:Gs,backendName:"wasm",setupFunc:lZ,kernelFunc:uZ},k3;function hZ(e){k3=e.wasm.cwrap(Xs,null,["number","array","number","array","number","number"])}function dZ(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{dims:s}=r,i=v.parseAxisParam(s,a.shape);if(a.shape.length===0)return Rp({inputs:{x:a},backend:n});let o=n.makeOutput(a.shape,a.dtype),l=n.dataIdMap.get(a.dataId).id,u=n.dataIdMap.get(o.dataId).id,c=new Uint8Array(new Int32Array(i).buffer),h=new Uint8Array(new Int32Array(a.shape).buffer);k3(l,c,i.length,h,a.shape.length,u);let d=Nr({inputs:{x:o},attrs:{shape:a.shape},backend:n});return n.disposeData(o.dataId),d}var pZ={kernelName:Xs,backendName:"wasm",kernelFunc:dZ,setupFunc:hZ},I3;function fZ(e){I3=e.wasm.cwrap(al,null,["number","number","number","number","number","number","number","number","array","number","number"])}function mZ(e){let{inputs:t,backend:n,attrs:r}=e,{image:a}=t,{radians:s,fillValue:i,center:o}=r,l=n.makeOutput(a.shape,a.dtype),u=n.dataIdMap.get(a.dataId).id,c=n.dataIdMap.get(l.dataId).id,[h,d,p,f]=a.shape,[m,A]=R.getImageCenter(o,d,p),y=i===0,g=255,b=typeof i=="number"?[i,i,i,y?0:g]:[...i,g],_=new Uint8Array(new Int32Array(b).buffer);return I3(u,h,d,p,f,s,m,A,_,b.length,c),l}var AZ={kernelName:al,backendName:"wasm",kernelFunc:mZ,setupFunc:fZ},yZ=Rn(Ks),gZ=Rn(Zs),N3;function xZ(e){N3=e.wasm.cwrap(jo,null,["number","number","number","number","number","number","array","number","number"])}function wZ(e){let{backend:t,inputs:n,attrs:r}=e,{indices:a,updates:s}=n,{shape:i}=r,o=t.makeOutput(i,s.dtype);if(v.sizeFromShape(i)===0)return o;let{sliceRank:l,numUpdates:u,sliceSize:c,strides:h,outputSize:d}=Uf.calculateShapes(s,a,i),p=t.dataIdMap.get(a.dataId).id,f=t.dataIdMap.get(s.dataId).id,m=new Uint8Array(new Int32Array(h).buffer),A=t.dataIdMap.get(o.dataId).id;return N3(p,f,Vn[s.dtype],l,u,c,m,d,A),o}var bZ={kernelName:jo,backendName:"wasm",setupFunc:xZ,kernelFunc:wZ},S3;function _Z(e){S3=e.wasm.cwrap("SelectV2",null,["number","number","number","number","number"])}function vZ(e){let{inputs:t,backend:n}=e,{condition:r,t:a,e:s}=t,i=n.dataIdMap.get(r.dataId).id,o=n.dataIdMap.get(a.dataId).id,l=n.dataIdMap.get(s.dataId).id,u=n.makeOutput(a.shape,a.dtype),c=n.dataIdMap.get(u.dataId).id,h=r.shape.length,d=a.shape.length,p=h===0||h>1||d===1?1:v.sizeFromShape(a.shape.slice(1));return S3(i,o,l,p,c),u}var kZ={kernelName:Go,backendName:"wasm",kernelFunc:vZ,setupFunc:_Z},T3;function IZ(e){T3=e.wasm.cwrap(Js,null,["number","number"])}function NZ(e){let{backend:t,inputs:{x:n}}=e,r=t.dataIdMap.get(n.dataId).id,a=t.makeOutput(n.shape,n.dtype),s=t.dataIdMap.get(a.dataId).id;return v.sizeFromShape(a.shape)===0||T3(r,s),a}var SZ={kernelName:"Sigmoid",backendName:"wasm",setupFunc:IZ,kernelFunc:NZ},TZ=Rn(Ys);function $p(e){let{inputs:{x:t},attrs:{begin:n,size:r},backend:a}=e,[s,i]=fn.parseSliceParams(t,n,r),o=fn.isSliceContinous(t.shape,s,i),l=a.readSync(t.dataId),u=a.makeOutput(i,t.dtype),c=v.computeStrides(t.shape),h=a.dataIdMap.get(u.dataId);if(o){let f=fn.computeFlatOffset(s,c);return t.dtype==="string"?h.stringBytes=l.slice(f,f+v.sizeFromShape(i)):a.typedArrayFromHeap(u).set(l.subarray(f,f+v.sizeFromShape(i))),u}if(t.dtype==="string"){let f=up(l,s,i,t.shape,t.dtype);return h.stringBytes=f,u}let d=a.typedArrayFromHeap(u),p=t.shape.length;if(p===2)EZ(l,c[0],d,s,i);else if(p===3)CZ(l,c[0],c[1],d,s,i);else if(p===4)RZ(l,c[0],c[1],c[2],d,s,i);else{let f=up(l,s,i,t.shape,t.dtype);d.set(f)}return u}function EZ(e,t,n,r,a){let s=0,i=r[0],o=r[1],l=i+a[0];for(let u=i;u<l;u++){let c=u*t+o;n.set(e.subarray(c,c+a[1]),s),s+=a[1]}}function CZ(e,t,n,r,a,s){let i=0,o=a[0],l=a[1],u=a[2],c=o+s[0],h=l+s[1];for(let d=o;d<c;d++)for(let p=l;p<h;p++){let f=d*t+p*n+u;r.set(e.subarray(f,f+s[2]),i),i+=s[2]}}function RZ(e,t,n,r,a,s,i){let o=0,l=s[0],u=s[1],c=s[2],h=l+i[0],d=u+i[1],p=c+i[2],f=s[3];for(let m=l;m<h;m++)for(let A=u;A<d;A++)for(let y=c;y<p;y++){let g=m*t+A*n+y*r+f;a.set(e.subarray(g,g+i[3]),o),o+=i[3]}}var FZ={kernelName:Xo,backendName:"wasm",kernelFunc:$p},E3;function MZ(e){E3=e.wasm.cwrap(ti,null,["number","number","number","number"])}function $Z(e){let{backend:t,inputs:{logits:n},attrs:{dim:r}}=e,a=t.dataIdMap.get(n.dataId).id,s=t.makeOutput(n.shape,n.dtype),i=t.dataIdMap.get(s.dataId).id,o=n.shape[r],l=v.sizeFromShape(n.shape)/o;return v.sizeFromShape(s.shape)===0||E3(a,i,o,l),s}var DZ={kernelName:ti,backendName:"wasm",setupFunc:MZ,kernelFunc:$Z};function OZ(e){let{inputs:t,attrs:n,backend:r}=e,{x:a}=t,{numOrSizeSplits:s,axis:i}=n,o=v.parseAxisParam(i,a.shape)[0],l=R.prepareSplitSize(a,s,o),u=new Array(a.shape.length).fill(0),c=a.shape.slice();return l.map(h=>{let d=[...c];d[o]=h;let p=$p({inputs:{x:a},attrs:{begin:u,size:d},backend:r});return u[o]+=h,p})}var zZ={kernelName:Jo,backendName:"wasm",kernelFunc:OZ},PZ=Rn(Qs),LZ=Rn(Fu),WZ=!0,BZ=wn(ni,WZ),C3;function VZ(e){C3=e.wasm.cwrap($a,null,["number","number","number"])}function UZ(e){let{backend:t,inputs:n,attrs:r}=e,{alpha:a}=r,{x:s}=n,i=t.dataIdMap.get(s.dataId).id,o=t.makeOutput(s.shape,s.dtype),l=t.dataIdMap.get(o.dataId).id;return C3(i,a,l),o}var HZ={kernelName:$a,backendName:"wasm",setupFunc:VZ,kernelFunc:UZ},R3;function jZ(e){R3=e.wasm.cwrap(Qo,null,["number","array","number","array","array","array","array","array","number","number"])}function GZ(e){let{backend:t,inputs:n,attrs:r}=e,{x:a}=n,{begin:s,end:i,strides:o}=r;o==null&&(o=new Array(s.length));let{beginMask:l,endMask:u,ellipsisMask:c,newAxisMask:h,shrinkAxisMask:d}=r,p=R.slice_util.maskToAxes(c);if(p.length>1)throw new Error("Multiple ellipses in slice is not allowed.");if(c!==0&&h!==0)throw new Error("Using both ellipsisMask and newAxisMask is not yet supported.");if(c!==0&&d!==0)throw new Error("Using both ellipsisMask and shrinkAxisMask is not yet supported.");let f=a.shape.length-s.length,m=R.slice_util.maskToAxes(h),A=a.shape.slice();m.forEach(M=>{s[M]=0,i[M]=1,A.splice(M,0,1)});let y=Nr({inputs:{x:a},attrs:{shape:A},backend:t}),{begin:g,end:b,strides:_}=R.slice_util.getNormalizedAxes(y.shape,p,f,s,i,o,l,u,c);s=g,i=b,o=_;let w=R.slice_util.maskToAxes(d);w.forEach(M=>{i[M]=s[M]+1,o[M]=1});let x=R.slice_util.computeOutShape(s,i,o),N=x.filter((M,D)=>w.indexOf(D)===-1);if(o.every(M=>M===1)){let M=$p({inputs:{x:y},attrs:{begin:s,size:x},backend:t});t.disposeData(y.dataId);let D=Nr({inputs:{x:M},attrs:{shape:N},backend:t});return t.disposeData(M.dataId),D}let S=t.makeOutput(N,"float32");if(!N.some(M=>M===0)){let M=t.dataIdMap.get(y.dataId).id,D=new Uint8Array(new Int32Array(v.computeStrides(y.shape)).buffer),z=new Uint8Array(new Int32Array(s).buffer),W=new Uint8Array(new Int32Array(i).buffer),U=new Uint8Array(new Int32Array(o).buffer),H=new Uint8Array(new Int32Array(N).buffer),X=new Uint8Array(new Int32Array(v.computeStrides(N)).buffer),j=t.dataIdMap.get(S.dataId).id;R3(M,D,y.shape.length,z,W,U,H,X,N.length,j)}t.disposeData(y.dataId);let T=Nr({inputs:{x:S},attrs:{shape:N},backend:t});return t.disposeData(S.dataId),T}var qZ={kernelName:Qo,backendName:"wasm",setupFunc:jZ,kernelFunc:GZ},XZ=!0,KZ=wn(ri,XZ),F3;function ZZ(e){F3=e.wasm.cwrap(ei,null,["number, number, number"])}function YZ(e){let{backend:t,inputs:n,attrs:r}=e,{axis:a,keepDims:s}=r,{x:i}=n,o=t.dataIdMap.get(i.dataId).id,l=o,u=i,{transposed:c,axes:h,originalAxes:d,inputWasTransposed:p}=Ul(i,a,t),f=h;if(p){let b=t.dataIdMap.get(c.dataId).id;b!==o&&(u=c,l=b,f=R.getInnerMostAxes(f.length,u.shape.length))}R.assertAxesAreInnerMostDims("sum",f,u.shape.length);let[m,A]=R.computeOutAndReduceShapes(u.shape,f),y=v.sizeFromShape(A),g=t.makeOutput(m,u.dtype);if(v.sizeFromShape(u.shape)!==0){let b=t.dataIdMap.get(g.dataId).id;F3(l,y,b)}if(p&&t.disposeData(c.dataId),s){let b=R.expandShapeToKeepDim(g.shape,d);g.shape=b}return g}var JZ={kernelName:ei,backendName:"wasm",setupFunc:ZZ,kernelFunc:YZ},QZ=Rn(ai),M3;function eY(e){M3=e.wasm.cwrap(Ma,null,["number","array","number","array","number","number"])}function tY(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,s=n.dataIdMap.get(a.dataId).id,{reps:i}=r,o=new Array(a.shape.length);for(let d=0;d<o.length;d++)o[d]=a.shape[d]*i[d];let l=new Uint8Array(new Int32Array(a.shape).buffer),u=new Uint8Array(new Int32Array(o).buffer),c=n.makeOutput(o,a.dtype),h=n.dataIdMap.get(c.dataId).id;return M3(s,l,a.shape.length,u,o.length,Vn[c.dtype],h),c}var nY={kernelName:Ma,backendName:"wasm",setupFunc:eY,kernelFunc:tY},$3;function rY(e){$3=e.wasm.cwrap(tl,null,["number","array","number","number","number","bool","number","number"])}var aY=({inputs:e,backend:t,attrs:n})=>{let{x:r}=e,{k:a,sorted:s}=n,i=t.dataIdMap.get(r.dataId).id,o=new Uint8Array(new Int32Array(r.shape).buffer),l=r.shape.slice();l[l.length-1]=a;let u=t.makeOutput(l,r.dtype),c=t.dataIdMap.get(u.dataId).id,h=t.makeOutput(l,"int32"),d=t.dataIdMap.get(h.dataId).id;return $3(i,o,r.shape.length,Vn[r.dtype],a,s,c,d),[u,h]},sY={kernelName:tl,backendName:"wasm",setupFunc:rY,kernelFunc:aY};function iY(e){let{inputs:t,backend:n,attrs:r}=e,{value:a}=t,{axis:s}=r;s<0&&(s+=a.shape.length);let i=a.shape[s],o=a.shape.length,l=new Array(o-1),u=0;for(let p=0;p<o;p++)p!==s&&(l[u++]=a.shape[p]);let c=new Array(i),h=new Array(o).fill(0),d=a.shape.slice();d[s]=1;for(let p=0;p<c.length;p++)h[s]=p,c[p]=$p({inputs:{x:a},attrs:{begin:h,size:d},backend:n});return c.map(({dataId:p,dtype:f})=>({dataId:p,dtype:f,shape:l}))}var oY={kernelName:nl,backendName:"wasm",kernelFunc:iY};function lY(e){let{inputs:{x:t},backend:n}=e,r=n.makeOutput(t.shape,t.dtype);return n.typedArrayFromHeap(r).fill(0),r}var uY={kernelName:rl,backendName:"wasm",kernelFunc:lY},cY=[Eq,Rq,$q,Vq,jq,Kq,Zq,Yq,eX,tX,aX,oX,lX,hX,fX,yX,wX,_X,vX,kX,NX,EX,CX,FX,Tq,DX,PX,BX,HX,qX,KX,YX,Dq,eK,nK,aK,sK,oK,cK,dK,mK,gK,bK,vK,IK,NK,EK,FK,DK,zK,WK,VK,HK,qK,KK,JK,tZ,rZ,sZ,iZ,oZ,Gq,cZ,pZ,AZ,gZ,yZ,bZ,kZ,SZ,TZ,FZ,DZ,zZ,PZ,LZ,BZ,HZ,qZ,KZ,JZ,QZ,nY,sY,Lq,oY,uY];for(let e of cY)ui(e);var IA=J();IA.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])));IA.registerFlag("WASM_HAS_MULTITHREAD_SUPPORT",async()=>{if(IA.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 D3=no(Ak()),hY='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()}}}}',dY=no(yk()),O3=class extends fu{constructor(e){super();this.wasm=e,this.dataIdNextNumber=1,this.wasm.tfjs.init(),this.dataIdMap=new Rh(this,Pr())}write(e,t,n){let r={id:this.dataIdNextNumber++};return this.move(r,e,t,n,1),r}numDataIds(){return this.dataIdMap.numDataIds()}async time(e){let t=v.now();return e(),{kernelMs:v.now()-t}}move(e,t,n,r,a){let s=this.dataIdNextNumber++;if(r==="string"){let u=t;this.dataIdMap.set(e,{id:s,stringBytes:u,shape:n,dtype:r,memoryOffset:null,refCount:a});return}let i=v.sizeFromShape(n),o=i*v.bytesPerElement(r),l=this.wasm._malloc(o);this.dataIdMap.set(e,{id:s,memoryOffset:l,shape:n,dtype:r,refCount:a}),this.wasm.tfjs.registerTensor(s,i,l),t!=null&&this.wasm.HEAPU8.set(new Uint8Array(t.buffer,t.byteOffset,o),l)}async read(e){return this.readSync(e)}readSync(e){let{memoryOffset:t,dtype:n,shape:r,stringBytes:a}=this.dataIdMap.get(e);if(n==="string")return a;let s=this.wasm.HEAPU8.slice(t,t+v.sizeFromShape(r)*v.bytesPerElement(n));return pY(s.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(),this.wasm=null}memory(){return{unreliable:!1}}makeOutput(e,t,n){let r;if(n==null)r=this.write(null,e,t);else{let a=this.dataIdNextNumber++;r={id:a},this.dataIdMap.set(r,{id:a,memoryOffset:n,shape:e,dtype:t,refCount:1});let s=v.sizeFromShape(e);this.wasm.tfjs.registerTensor(a,s,n)}return{dataId:r,shape:e,dtype:t}}typedArrayFromHeap({shape:e,dtype:t,dataId:n}){let r=this.wasm.HEAPU8.buffer,{memoryOffset:a}=this.dataIdMap.get(n),s=v.sizeFromShape(e);switch(t){case"float32":return new Float32Array(r,a,s);case"int32":return new Int32Array(r,a,s);case"bool":return new Uint8Array(r,a,s);default:throw new Error(`Unknown dtype ${t}`)}}};function fY(e){return(t,n)=>(v.fetch(e,{credentials:"same-origin"}).then(r=>{r.ok||t.env.a(`failed to load wasm binary file at '${e}'`),r.arrayBuffer().then(a=>{WebAssembly.instantiate(a,t).then(s=>{n(s.instance)})})}),{})}function z3(e,t,n){if(Dp!=null)return Dp;let r="tfjs-backend-wasm.wasm";return e&&t?r="tfjs-backend-wasm-threaded-simd.wasm":e&&(r="tfjs-backend-wasm-simd.wasm"),kc!=null&&kc[r]!=null?kc[r]:n+r}async function mY(){let[e,t]=await Promise.all([J().getAsync("WASM_HAS_SIMD_SUPPORT"),J().getAsync("WASM_HAS_MULTITHREAD_SUPPORT")]);return new Promise((n,r)=>{let a={};a.locateFile=(o,l)=>{if(o.endsWith(".worker.js")){let u=hY,c=new Blob([u],{type:"application/javascript"});return URL.createObjectURL(c)}return o.endsWith(".wasm")?z3(e,t,Ic!=null?Ic:l):l+o},NA&&(a.instantiateWasm=fY(z3(e,t,Ic!=null?Ic:"")));let s=!1;a.onAbort=()=>{s||Nc||(Nc=!0,r({message:"Make sure the server can serve the `.wasm` file relative to the bundled js file. For more details see https://github.com/tensorflow/tfjs/blob/master/tfjs-backend-wasm/README.md#using-bundlers"}))};let i;t&&e&&Dp==null?(a.mainScriptUrlOrBlob=new Blob(["var WasmBackendModuleThreadedSimd = "+D3.default.toString()],{type:"text/javascript"}),i=(0,D3.default)(a)):i=(0,dY.default)(a),i.then(o=>{s=!0,Nc=!1;let l=null;o.tfjs={init:o.cwrap("init",null,[]),registerTensor:o.cwrap("register_tensor",null,["number","number","number"]),disposeData:o.cwrap("dispose_data",l,["number"]),dispose:o.cwrap("dispose",l,[])},n({wasm:o})})})}function pY(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 AY=["tfjs-backend-wasm.wasm","tfjs-backend-wasm-simd.wasm","tfjs-backend-wasm-threaded-simd.wasm"],Dp=null,Ic=null,kc={},Nc=!1,NA=!1;function yY(e,t=!1){if(Kf("setWasmPath has been deprecated in favor of setWasmPaths and will be removed in a future release."),Nc)throw new Error("The WASM backend was already initialized. Make sure you call `setWasmPath()` before you call `tf.setBackend()` or `tf.ready()`");Dp=e,NA=t}function gY(e,t=!1){if(Nc)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")Ic=e;else{kc=e;let n=AY.filter(r=>kc[r]==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.`)}NA=t}var P3="3.3.0",xY=2;fl("wasm",async()=>{let{wasm:e}=await mY();return new O3(e)},xY);Z().prototype.abs=function(){return this.throwIfDisposed(),Bt(this)};Z().prototype.acos=function(){return this.throwIfDisposed(),Yf(this)};Z().prototype.acosh=function(){return this.throwIfDisposed(),Jf(this)};Z().prototype.add=function(e){return this.throwIfDisposed(),ie(this,e)};Z().prototype.all=function(e,t){return this.throwIfDisposed(),kd(this,e,t)};Z().prototype.any=function(e,t){return this.throwIfDisposed(),ju(this,e,t)};Z().prototype.argMax=function(e){return this.throwIfDisposed(),Gu(this,e)};Z().prototype.argMin=function(e){return this.throwIfDisposed(),Qf(this,e)};Z().prototype.asScalar=function(){return this.throwIfDisposed(),F(this.size===1,()=>"The array must have only 1 element."),G(this,[])};Z().prototype.asType=function(e){return this.throwIfDisposed(),ge(this,e)};Z().prototype.as1D=function(){return this.throwIfDisposed(),G(this,[this.size])};Z().prototype.as2D=function(e,t){return this.throwIfDisposed(),G(this,[e,t])};Z().prototype.as3D=function(e,t,n){return this.throwIfDisposed(),G(this,[e,t,n])};Z().prototype.as4D=function(e,t,n,r){return this.throwIfDisposed(),G(this,[e,t,n,r])};Z().prototype.as5D=function(e,t,n,r,a){return this.throwIfDisposed(),G(this,[e,t,n,r,a])};Z().prototype.asin=function(){return this.throwIfDisposed(),em(this)};Z().prototype.asinh=function(){return this.throwIfDisposed(),tm(this)};Z().prototype.atan=function(){return this.throwIfDisposed(),nm(this)};Z().prototype.atan2=function(e){return this.throwIfDisposed(),rm(this,e)};Z().prototype.atanh=function(){return this.throwIfDisposed(),am(this)};Z().prototype.avgPool=function(e,t,n,r){return this.throwIfDisposed(),Xu(this,e,t,n,r)};Z().prototype.batchToSpaceND=function(e,t){return this.throwIfDisposed(),Ku(this,e,t)};Z().prototype.batchNorm=function(e,t,n,r,a){return this.throwIfDisposed(),mi(this,e,t,n,r,a)};Z().prototype.broadcastTo=function(e){return this.throwIfDisposed(),Zu(this,e)};Z().prototype.cast=function(e){return this.throwIfDisposed(),ge(this,e)};Z().prototype.ceil=function(){return this.throwIfDisposed(),lm(this)};Z().prototype.clipByValue=function(e,t){return this.throwIfDisposed(),Sn(this,e,t)};Z().prototype.concat=function(e,t){return this.throwIfDisposed(),e instanceof Ge&&(e=[e]),lt([this,...e],t)};Z().prototype.conv1d=function(e,t,n,r,a,s){return this.throwIfDisposed(),Nd(this,e,t,n,r,a,s)};Z().prototype.conv2dTranspose=function(e,t,n,r,a){return this.throwIfDisposed(),Sd(this,e,t,n,r,a)};Z().prototype.conv2d=function(e,t,n,r,a,s){return this.throwIfDisposed(),ua(this,e,t,n,r,a,s)};Z().prototype.cos=function(){return this.throwIfDisposed(),Yu(this)};Z().prototype.cosh=function(){return this.throwIfDisposed(),Td(this)};Z().prototype.cumsum=function(e,t,n){return this.throwIfDisposed(),Ed(this,e,t,n)};Z().prototype.depthToSpace=function(e,t){return this.throwIfDisposed(),hm(this,e,t)};Z().prototype.depthwiseConv2d=function(e,t,n,r,a,s){return this.throwIfDisposed(),gl(this,e,t,n,r,a,s)};Z().prototype.dilation2d=function(e,t,n,r,a){return this.throwIfDisposed(),dm(this,e,t,n,r,a)};Z().prototype.divNoNan=function(e){return this.throwIfDisposed(),pm(this,e)};Z().prototype.div=function(e){return this.throwIfDisposed(),be(this,e)};Z().prototype.dot=function(e){return this.throwIfDisposed(),Ax(this,e)};Z().prototype.elu=function(){return this.throwIfDisposed(),xl(this)};Z().prototype.equal=function(e){return this.throwIfDisposed(),Ba(this,e)};Z().prototype.erf=function(){return this.throwIfDisposed(),fm(this)};Z().prototype.exp=function(){return this.throwIfDisposed(),Jn(this)};Z().prototype.expandDims=function(e){return this.throwIfDisposed(),mn(this,e)};Z().prototype.expm1=function(){return this.throwIfDisposed(),mm(this)};Z().prototype.fft=function(){return this.throwIfDisposed(),oc(this)};Z().prototype.flatten=function(){return this.throwIfDisposed(),G(this,[this.size])};Z().prototype.floor=function(){return this.throwIfDisposed(),wl(this)};Z().prototype.floorDiv=function(e){return this.throwIfDisposed(),vd(this,e)};Z().prototype.gather=function(e,t){return this.throwIfDisposed(),Ai(this,e,t)};Z().prototype.greaterEqual=function(e){return this.throwIfDisposed(),Ua(this,e)};Z().prototype.greater=function(e){return this.throwIfDisposed(),ur(this,e)};Z().prototype.ifft=function(){return this.throwIfDisposed(),Il(this)};Z().prototype.irfft=function(){return this.throwIfDisposed(),Gd(this)};Z().prototype.isFinite=function(){return this.throwIfDisposed(),yx(this)};Z().prototype.isInf=function(){return this.throwIfDisposed(),gx(this)};Z().prototype.isNaN=function(){return this.throwIfDisposed(),xx(this)};Z().prototype.leakyRelu=function(e){return this.throwIfDisposed(),Qu(this,e)};Z().prototype.lessEqual=function(e){return this.throwIfDisposed(),yi(this,e)};Z().prototype.less=function(e){return this.throwIfDisposed(),Rd(this,e)};Z().prototype.localResponseNormalization=function(e,t,n,r){return this.throwIfDisposed(),ym(this,e,t,n,r)};Z().prototype.logSigmoid=function(){return this.throwIfDisposed(),_x(this)};Z().prototype.logSoftmax=function(e){return this.throwIfDisposed(),$d(this,e)};Z().prototype.logSumExp=function(e,t){return this.throwIfDisposed(),wm(this,e,t)};Z().prototype.log=function(){return this.throwIfDisposed(),zn(this)};Z().prototype.log1p=function(){return this.throwIfDisposed(),Fd(this)};Z().prototype.logicalAnd=function(e){return this.throwIfDisposed(),cr(this,e)};Z().prototype.logicalNot=function(){return this.throwIfDisposed(),ec(this)};Z().prototype.logicalOr=function(e){return this.throwIfDisposed(),Dd(this,e)};Z().prototype.logicalXor=function(e){return this.throwIfDisposed(),Nx(this,e)};Z().prototype.matMul=function(e,t,n){return this.throwIfDisposed(),Ke(this,e,t,n)};Z().prototype.maxPool=function(e,t,n,r){return this.throwIfDisposed(),tc(this,e,t,n,r)};Z().prototype.max=function(e,t){return this.throwIfDisposed(),Qn(this,e,t)};Z().prototype.maximum=function(e){return this.throwIfDisposed(),Br(this,e)};Z().prototype.mean=function(e,t){return this.throwIfDisposed(),Tt(this,e,t)};Z().prototype.min=function(e,t){return this.throwIfDisposed(),_l(this,e,t)};Z().prototype.minimum=function(e){return this.throwIfDisposed(),vl(this,e)};Z().prototype.mirrorPad=function(e,t){return this.throwIfDisposed(),_m(this,e,t)};Z().prototype.mod=function(e){return this.throwIfDisposed(),vm(this,e)};Z().prototype.mul=function(e){return this.throwIfDisposed(),P(this,e)};Z().prototype.neg=function(){return this.throwIfDisposed(),St(this)};Z().prototype.norm=function(e,t,n){return this.throwIfDisposed(),Zd(this,e,t,n)};Z().prototype.notEqual=function(e){return this.throwIfDisposed(),xi(this,e)};Z().prototype.oneHot=function(e,t=1,n=0){return this.throwIfDisposed(),hl(this,e,t,n)};Z().prototype.onesLike=function(){return this.throwIfDisposed(),Pn(this)};Z().prototype.pad=function(e,t){return this.throwIfDisposed(),ca(this,e,t)};Z().prototype.pool=function(e,t,n,r,a){return this.throwIfDisposed(),Ex(this,e,t,n,r,a)};Z().prototype.pow=function(e){return this.throwIfDisposed(),ha(this,e)};Z().prototype.prelu=function(e){return this.throwIfDisposed(),rc(this,e)};Z().prototype.prod=function(e,t){return this.throwIfDisposed(),zd(this,e,t)};Z().prototype.reciprocal=function(){return this.throwIfDisposed(),Nm(this)};Z().prototype.relu=function(){return this.throwIfDisposed(),Ur(this)};Z().prototype.relu6=function(){return this.throwIfDisposed(),Ld(this)};Z().prototype.reshapeAs=function(e){return this.throwIfDisposed(),G(this,e.shape)};Z().prototype.reshape=function(e){return this.throwIfDisposed(),G(this,e)};Z().prototype.resizeBilinear=function(e,t,n){return this.throwIfDisposed(),qx(this,e,t,n)};Z().prototype.resizeNearestNeighbor=function(e,t,n){return this.throwIfDisposed(),Xx(this,e,t,n)};Z().prototype.reverse=function(e){return this.throwIfDisposed(),Ln(this,e)};Z().prototype.rfft=function(){return this.throwIfDisposed(),lc(this)};Z().prototype.round=function(){return this.throwIfDisposed(),Sm(this)};Z().prototype.rsqrt=function(){return this.throwIfDisposed(),Wd(this)};Z().prototype.selu=function(){return this.throwIfDisposed(),Bd(this)};Z().prototype.separableConv2d=function(e,t,n,r,a,s){return this.throwIfDisposed(),Tm(this,e,t,n,r,a,s)};Z().prototype.sigmoid=function(){return this.throwIfDisposed(),On(this)};Z().prototype.sign=function(){return this.throwIfDisposed(),Em(this)};Z().prototype.sin=function(){return this.throwIfDisposed(),Vd(this)};Z().prototype.sinh=function(){return this.throwIfDisposed(),Ud(this)};Z().prototype.slice=function(e,t){return this.throwIfDisposed(),$e(this,e,t)};Z().prototype.softmax=function(e){return this.throwIfDisposed(),ic(this,e)};Z().prototype.softplus=function(){return this.throwIfDisposed(),bl(this)};Z().prototype.spaceToBatchND=function(e,t){return this.throwIfDisposed(),nc(this,e,t)};Z().prototype.split=function(e,t){return this.throwIfDisposed(),Ut(this,e,t)};Z().prototype.sqrt=function(){return this.throwIfDisposed(),an(this)};Z().prototype.square=function(){return this.throwIfDisposed(),ht(this)};Z().prototype.squaredDifference=function(e){return this.throwIfDisposed(),qd(this,e)};Z().prototype.squeeze=function(e){return this.throwIfDisposed(),Ha(this,e)};Z().prototype.stack=function(e,t){this.throwIfDisposed();let n=e instanceof Ge?[this,e]:[this,...e];return An(n,t)};Z().prototype.step=function(e){return this.throwIfDisposed(),Nl(this,e)};Z().prototype.stridedSlice=function(e,t,n,r,a,s,i,o){return this.throwIfDisposed(),Rm(this,e,t,n,r,a,s,i,o)};Z().prototype.sub=function(e){return this.throwIfDisposed(),we(this,e)};Z().prototype.sum=function(e,t){return this.throwIfDisposed(),Re(this,e,t)};Z().prototype.tan=function(){return this.throwIfDisposed(),Fm(this)};Z().prototype.tanh=function(){return this.throwIfDisposed(),Al(this)};Z().prototype.tile=function(e){return this.throwIfDisposed(),Va(this,e)};Z().prototype.toBool=function(){return this.throwIfDisposed(),ge(this,"bool")};Z().prototype.toFloat=function(){return this.throwIfDisposed(),ge(this,"float32")};Z().prototype.toInt=function(){return this.throwIfDisposed(),ge(this,"int32")};Z().prototype.topk=function(e,t){return this.throwIfDisposed(),Mm(this,e,t)};Z().prototype.transpose=function(e){return this.throwIfDisposed(),ot(this,e)};Z().prototype.unique=function(e){return this.throwIfDisposed(),Kd(this,e)};Z().prototype.unsortedSegmentSum=function(e,t){return this.throwIfDisposed(),$m(this,e,t)};Z().prototype.unstack=function(e){return this.throwIfDisposed(),hr(this,e)};Z().prototype.where=function(e,t){return this.throwIfDisposed(),Tn(e,this,t)};Z().prototype.zerosLike=function(){return this.throwIfDisposed(),qe(this)};var L3={kernelName:so,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>P(e,Nl(ge(n,"float32"),-1))}}},wY={kernelName:io,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>{let r=ht(ge(n,"float32")),a=an(we(Ie(1),r));return St(be(e,a))}}}},bY={kernelName:oo,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>{let r=an(we(ht(ge(n,"float32")),1));return be(e,r)}}}},_Y={kernelName:Ra,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,r]=t,a=wt(n.shape,r.shape);return{a:()=>{let s=e,i=Vt(n.shape,a);return i.length>0&&(s=Re(s,i)),G(s,n.shape)},b:()=>{let s=e,i=Vt(r.shape,a);return i.length>0&&(s=Re(s,i)),G(s,r.shape)}}}},vY={kernelName:fs,saveAllInputs:!0,gradFunc:(e,t)=>{let n={};return t.forEach((r,a)=>{n[a]=()=>e.clone()}),n}},kY={kernelName:ms,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>qe(n)}}},IY={kernelName:yu,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>qe(n)}}},NY={kernelName:lo,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>be(e,an(we(Ie(1),ht(ge(n,"float32")))))}}},SY={kernelName:uo,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>{let r=an(ie(Ie(1),ht(ge(n,"float32"))));return be(e,r)}}}},TY={kernelName:po,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,r]=t,a=wt(n.shape,r.shape);return{a:()=>{let s=ie(ht(n),ht(r)),i=P(e,be(r,s)),o=Vt(n.shape,a);return o.length>0&&(i=Re(i,o)),G(i,n.shape)},b:()=>{let s=ie(ht(n),ht(r)),i=St(P(e,be(n,s))),o=Vt(r.shape,a);return o.length>0&&(i=Re(i,o)),G(i,r.shape)}}}},EY={kernelName:co,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>be(e,ie(ht(ge(n,"float32")),1))}}},CY={kernelName:ho,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>be(e,we(Ie(1),ht(ge(n,"float32"))))}}};function RY(e,t,n,r,a,s){let i=C(e,"dy","avgPool3dGrad"),o=C(t,"input","avgPool3dGrad"),l=i,u=o,c=!1;o.rank===4&&(c=!0,l=G(i,[1,i.shape[0],i.shape[1],i.shape[2],i.shape[3]]),u=G(o,[1,o.shape[0],o.shape[1],o.shape[2],o.shape[3]])),F(l.rank===5,()=>`Error in avgPool3dGrad: dy must be rank 5 but got rank ${l.rank}.`),F(u.rank===5,()=>`Error in avgPool3dGrad: input must be rank 5 but got rank ${u.rank}.`),s!=null&&F(Kt(a),()=>`Error in avgPool3dGrad: pad must be an integer when using, dimRoundingMode ${s} but got pad ${a}.`);let h={dy:l,input:u},d={filterSize:n,strides:r,pad:a,dimRoundingMode:s},p=$.runKernel(Ph,h,d);return c?G(p,[p.shape[1],p.shape[2],p.shape[3],p.shape[4]]):p}var FY=O({avgPool3dGrad_:RY}),MY={kernelName:gu,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[r]=t,{filterSize:a,strides:s,pad:i,dimRoundingMode:o}=n;return{x:()=>FY(e,r,a,s,i,o)}}};function $Y(e,t,n,r,a){let s=C(e,"dy","avgPoolGrad"),i=C(t,"input","avgPoolGrad");F(i.rank===s.rank,()=>`Rank of input (${i.rank}) does not match rank of dy (${s.rank})`);let o=i,l=s,u=!1;i.rank===3&&(u=!0,o=G(i,[1,i.shape[0],i.shape[1],i.shape[2]]),l=G(s,[1,s.shape[0],s.shape[1],s.shape[2]])),F(l.rank===4,()=>`Error in avgPoolGrad: dy must be rank 4 but got rank ${l.rank}.`),F(o.rank===4,()=>`Error in avgPoolGrad: input must be rank 4 but got rank ${o.rank}.`);let c={dy:l,input:o},h={filterSize:n,strides:r,pad:a},d=$.runKernel(zh,c,h);return u?G(d,[d.shape[1],d.shape[2],d.shape[3]]):d}var DY=O({avgPoolGrad_:$Y}),OY={kernelName:As,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[r]=t,{filterSize:a,strides:s,pad:i}=n;return{x:()=>DY(e,r,a,s,i)}}},zY={kernelName:ys,inputsToSave:["a","b"],gradFunc:(e,t,n)=>{let[r,a]=t,{transposeA:s,transposeB:i}=n;return!s&&!i?{a:()=>Ke(e,a,!1,!0),b:()=>Ke(r,e,!0,!1)}:!s&&i?{a:()=>Ke(e,a,!1,!1),b:()=>Ke(e,r,!0,!1)}:s&&!i?{a:()=>Ke(a,e,!1,!0),b:()=>Ke(r,e,!1,!1)}:{a:()=>Ke(a,e,!0,!0),b:()=>Ke(e,r,!0,!0)}}},PY={kernelName:xu,gradFunc:(e,t,n)=>{let{blockShape:r,crops:a}=n;return{x:()=>nc(e,r,a)}}},LY={kernelName:c5,gradFunc:(e,t,n)=>{let r=n,a=r.inputShape,s=r.shape,i=Array.from(s);for(let l=a.length-1;l>=0;l--)if(a[l]===s[l])i[l]=1;else if(a[l]!==1)throw new Error(`broadcastTo(): [${a}] cannot be broadcast to [${s}].`);let o=[];for(let l=0;l<i.length;l++)i[l]>1&&o.push(l);return{x:()=>Re(e,o,!0)}}},WY={kernelName:gs,gradFunc:e=>({x:()=>e.clone()})},BY={kernelName:xs,gradFunc:e=>({x:()=>qe(e)})},VY={kernelName:Fa,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[r]=t,{clipValueMin:a,clipValueMax:s}=n;return{x:()=>Tn(cr(Ua(r,a),yi(r,s)),e,qe(e))}}},UY={kernelName:wu,inputsToSave:["x"],gradFunc:L3.gradFunc},HY={kernelName:fo,saveAllInputs:!0,gradFunc:(e,t,n)=>{let r=t.map(o=>o.shape),{axis:a}=n,s=or(a,t[0].shape)[0],i=r.map(o=>o[s]);return Ut(e,i,s).map(o=>()=>o)}},jY={kernelName:ws,inputsToSave:["x","filter"],gradFunc:(e,t,n)=>{let[r,a]=t,{dilations:s,strides:i,pad:o,dataFormat:l}=n;return F(Wa(s),()=>`Error in gradient of conv2D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '${s}'`),{x:()=>um(r.shape,e,a,i,o,l),filter:()=>Pm(r,e,a.shape,i,o,l)}}},GY={kernelName:bs,inputsToSave:["dy","filter"],gradFunc:(e,t,n)=>{let[r,a]=t,{strides:s,pad:i,dataFormat:o,dimRoundingMode:l}=n;return{dy:()=>ua(e,a,s,i,o,1,l),filter:()=>Pm(e,r,a.shape,s,i,o,l)}}};function qY(e,t,n,r,a){let s=e;e.rank===4&&(s=G(e,[1,e.shape[0],e.shape[1],e.shape[2],e.shape[3]]));let i=t;i.rank===4&&(i=G(t,[1,t.shape[0],t.shape[1],t.shape[2],t.shape[3]])),F(s.rank===5,()=>`Error in conv3dDerFilter: input must be rank 5, but got shape ${s.shape}.`),F(i.rank===5,()=>`Error in conv3dDerFilter: dy must be rank 5, but got shape ${i.shape}.`),F(n.length===5,()=>`Error in conv3dDerFilter: filterShape must be length 5, but got ${n}.`),F(s.shape[4]===n[3],()=>`Error in conv3dDerFilter: depth of input ${s.shape[4]}) must match input depth in filter (${n[3]}.`),F(i.shape[4]===n[4],()=>`Error in conv3dDerFilter: depth of dy (${i.shape[4]}) must match output depth for filter (${n[4]}).`);let o={x:s,dy:i},l={strides:r,pad:a,filterShape:n};return $.runKernel(Vh,o,l)}var XY=O({conv3DBackpropFilter_:qY}),KY={kernelName:bu,inputsToSave:["x","filter"],gradFunc:(e,t,n)=>{let{dilations:r,strides:a,pad:s}=n;F(Wa(r),()=>`Error in gradient of conv3D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '${r}'`);let[i,o]=t;return{x:()=>fx(i.shape,e,o,a,s),filter:()=>XY(i,e,o.shape,a,s)}}},ZY={kernelName:_s,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>P(St(Vd(ge(n,"float32"))),e)}}},YY={kernelName:mo,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>P(Ud(ge(n,"float32")),e)}}},JY={kernelName:vs,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[r]=t,{axis:a,exclusive:s,reverse:i}=n;return{x:()=>{let o=Ix([a],r.rank),l=Ed(e,a,s,!i);return o!=null&&(l=ot(l,o)),l}}}},QY={kernelName:ks,inputsToSave:["x","filter"],gradFunc:(e,t,n)=>{let{dilations:r,strides:a,pad:s,dimRoundingMode:i}=n,o=r==null?[1,1]:r;F(Wa(o),()=>`Error in gradient of depthwiseConv2dNative: dilation rates greater than 1 are not yet supported. Got dilations '${o}'`);let[l,u]=t;return F(l.rank===4,()=>`Error in gradient of depthwiseConv2dNative: input must be rank 4, but got rank ${l.rank}.`),F(u.rank===4,()=>`Error in gradient of depthwiseConv2dNative: filter must be rank 4, but got rank ${u.rank}.`),F(l.shape[3]===u.shape[2],()=>`Error in gradient of depthwiseConv2d: number of input channels (${l.shape[3]}) must match the inChannels dimension in filter ${u.shape[2]}.`),F(Lr(a,o),()=>`Error in gradient of depthwiseConv2d: Either strides or dilations must be 1. Got strides ${a} and dilations '${o}'.`),i!=null&&F(Kt(s),()=>`Error in depthwiseConv2d: pad must be an integer when using, dimRoundingMode ${i} but got pad ${s}.`),{x:()=>Wx(l.shape,e,u,a,s,r,i),filter:()=>Lx(l,e,u.shape,a,s,r,i)}}},eJ={kernelName:_u,inputsToSave:["x","filter"],gradFunc:(e,t,n)=>{let[r,a]=t,s={x:r,filter:a,dy:e},i={x:r,filter:a,dy:e};return{x:()=>$.runKernel(Xh,s,n),filter:()=>$.runKernel(Kh,i,n)}}},tJ={kernelName:go,outputsToSave:[!0],gradFunc:(e,t)=>{let[n]=t,r={dy:e,y:n};return{x:()=>$.runKernel(Zh,r)}}},nJ={kernelName:xo,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t,r=P(Jn(St(ht(n))),2/Math.sqrt(Math.PI));return{x:()=>P(e,r)}}},rJ={kernelName:Ns,outputsToSave:[!0],gradFunc:(e,t)=>{let[n]=t;return{x:()=>P(e,n)}}},aJ={kernelName:bo,inputsToSave:["input"],gradFunc:(e,t)=>{let[n]=t;return{input:()=>G(e,n.shape)}}},sJ={kernelName:_o,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>P(e,Jn(n))}}},iJ={kernelName:Ss,gradFunc:e=>({x:()=>qe(e)})},oJ={kernelName:Ts,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,r]=t,a=wt(n.shape,r.shape);return{a:()=>{let s=be(e,ge(r,"float32")),i=Vt(n.shape,a);return i.length>0?G(Re(s,i),n.shape):s},b:()=>{let s=P(e,ge(n,"float32")),i=Vt(r.shape,a);i.length>0&&(s=G(Re(s,i),r.shape));let o=ht(r);return St(be(s,ge(o,"float32")))}}}},lJ={kernelName:Es,inputsToSave:["x","mean","variance","scale"],gradFunc:(e,t,n)=>{let{varianceEpsilon:r}=n,[a,s,i,o]=t,l=o==null?Ie(1):o,u=Vt(s.shape,a.shape),c=[];if(s.rank===1){for(let m=0;m<a.shape.length-1;++m)c.push(a.shape[m]);c.push(1)}let h=we(a,s),d=P(e,l),p=Wd(ie(i,Ie(r))),f=P(P(P(p,p),p),Ie(-.5));return{x:()=>s.rank===1?G(P(P(e,Va(G(p,[1,1,1,s.shape[0]]),c)),l),a.shape):G(P(P(e,p),l),a.shape),mean:()=>{let m=P(P(p,Ie(-1)),d);return s.rank===1&&(m=Re(m,u)),G(m,s.shape)},variance:()=>{let m=P(P(f,h),d);return s.rank===1&&(m=Re(m,u)),G(m,s.shape)},scale:()=>{let m=P(h,p),A=P(e,m);return s.rank===1&&(A=Re(A,u)),G(A,s.shape)},offset:()=>{let m=e;return s.rank===1&&(m=Re(m,u)),G(m,s.shape)}}}},uJ={kernelName:ko,inputsToSave:["x","indices"],gradFunc:(e,t,n)=>{let[r,a]=t,{axis:s}=n,i=or(s,r.shape)[0];return{x:()=>{let o=r.shape,l=a.size,u=o.slice(0,i),c=u.length,h=o.slice(s,o.length).slice(1),d=h.length,p=W3(0,c),f=W3(c+1,c+1+d),m=B3([u,[l],h]),A=G(e,m),y=G(a,[l]),g=B3([[c],p,f]),b=ot(A,g),_=$m(b,y,r.shape[i]),w=xm(g);return _=ot(_,w),_},indices:()=>a}}};function W3(e,t){let n=[];for(let r=e;r<t;++r)n.push(r);return n}function B3(e){let t=[];for(let n=0;n<e.length;++n)for(let r=0;r<e[n].length;++r)t.push(e[n][r]);return t}var cJ={kernelName:Cs,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,r]=t;return{a:()=>qe(n),b:()=>qe(r)}}},hJ={kernelName:Rs,gradFunc:e=>({x:()=>ge(e,"float32")})},dJ={kernelName:So,gradFunc:e=>({x:()=>qe(e)})},pJ={kernelName:To,gradFunc:e=>({x:()=>qe(e)})},fJ={kernelName:Eo,gradFunc:e=>({x:()=>qe(e)})},mJ={kernelName:Fs,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[r]=t,{alpha:a}=n,s=ur(r,0);return{x:()=>Tn(s,e,P(e,a))}}},AJ={kernelName:Fo,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>be(e,ie(n,1))}}},yJ={kernelName:Ms,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>be(e,ge(n,"float32"))}}},gJ={kernelName:h5,inputsToSave:[],outputsToSave:[!0],gradFunc:(e,t,n)=>{let[r]=t,{axis:a}=n;return{logits:()=>{let s=!0,i=Jn(r);return we(e,P(Re(e,a,s),i))}}}};function xJ(e,t,n,r=5,a=1,s=1,i=.5){let o={x:e,y:t,dy:n},l={depthRadius:r,bias:a,alpha:s,beta:i};return $.runKernel(td,o,l)}var wJ=O({localResponseNormalizationBackprop_:xJ}),bJ={kernelName:Nu,inputsToSave:["x"],outputsToSave:[!0],gradFunc:(e,t,n)=>{let[r,a]=t,{depthRadius:s,bias:i,alpha:o,beta:l}=n;return{x:()=>wJ(r,a,e,s,i,o,l)}}};function V3(e,t,n,r){return t.rank<n.rank&&(t=G(t,gi(t.shape,r))),e.rank<n.rank&&(e=G(e,gi(e.shape,r))),{x:()=>P(e,ge(Ba(n,t),e.dtype))}}var U3={kernelName:$s,inputsToSave:["x"],outputsToSave:[!0],gradFunc:(e,t,n)=>{let r=n,{reductionIndices:a}=r,s=t[0],i=t[1],o=or(a,s.shape),l=V3(e,i,s,o);return{x:()=>l.x()}}},_J={kernelName:Ds,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,r]=t;return{a:()=>P(e,ge(Ua(n,r),"float32")),b:()=>P(e,ge(Rd(n,r),"float32"))}}};function vJ(e,t,n,r,a,s,i){let o=C(e,"dy","maxPool3dGrad"),l=C(t,"input","maxPool3dGrad"),u=C(n,"output","maxPool3dGrad"),c=o,h=l,d=u,p=!1;l.rank===4&&(p=!0,c=G(o,[1,o.shape[0],o.shape[1],o.shape[2],o.shape[3]]),h=G(l,[1,l.shape[0],l.shape[1],l.shape[2],l.shape[3]]),d=G(u,[1,u.shape[0],u.shape[1],u.shape[2],u.shape[3]])),F(c.rank===5,()=>`Error in maxPool3dGrad: dy must be rank 5 but got rank ${c.rank}.`),F(h.rank===5,()=>`Error in maxPool3dGrad: input must be rank 5 but got rank ${h.rank}.`),F(d.rank===5,()=>`Error in maxPool3dGrad: output must be rank 5 but got rank ${d.rank}.`),i!=null&&F(Kt(s),()=>`Error in maxPool3dGrad: pad must be an integer when using, dimRoundingMode ${i} but got pad ${s}.`);let f={dy:c,input:h,output:d},m={filterSize:r,strides:a,pad:s,dimRoundingMode:i},A=$.runKernel(rd,f,m);return p?G(A,[A.shape[1],A.shape[2],A.shape[3],A.shape[4]]):A}var kJ=O({maxPool3dGrad_:vJ}),IJ={kernelName:Su,inputsToSave:["x"],outputsToSave:[!0],gradFunc:(e,t,n)=>{let[r,a]=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=n;return{x:()=>kJ(e,r,a,s,i,o,l)}}};function NJ(e,t,n,r,a,s,i){let o=C(e,"dy","maxPoolGrad"),l=C(t,"input","maxPoolGrad"),u=C(n,"output","maxPoolGrad");F(l.rank===o.rank,()=>`Rank of input (${l.rank}) does not match rank of dy (${o.rank})`),F(o.rank===4,()=>`Error in maxPoolGrad: dy must be rank 4 but got rank ${o.rank}.`),F(l.rank===4,()=>`Error in maxPoolGrad: input must be rank 4 but got rank ${l.rank}.`),i!=null&&F(Kt(s),()=>`Error in maxPoolGrad: pad must be an integer when using, dimRoundingMode ${i} but got pad ${s}.`);let c={dy:o,input:l,output:u},h={filterSize:r,strides:a,pad:s,dimRoundingMode:i};return $.runKernel(nd,c,h)}var SJ=O({maxPoolGrad_:NJ}),TJ={kernelName:Os,inputsToSave:["x"],outputsToSave:[!0],gradFunc:(e,t,n)=>{let[r,a]=t,{filterSize:s,strides:i,pad:o}=n;return{x:()=>SJ(e,r,a,s,i,o)}}},EJ={kernelName:zs,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[r]=t,{axis:a}=n,s=or(a,r.shape),i=kx(r.shape,s)[1],o=Lt(i);return{x:()=>{let l=r.shape.slice();s.forEach(c=>{l[c]=1});let u=G(e,l);return be(P(u,Vr(r.shape,"float32")),o)}}}},CJ={kernelName:Ps,inputsToSave:["x"],outputsToSave:[!0],gradFunc:(e,t,n)=>{let r=n,{axis:a}=r,[s,i]=t,o=or(a,s.shape),l=V3(e,i,s,o);return{x:()=>l.x()}}},RJ={kernelName:Ls,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,r]=t;return{a:()=>P(e,ge(yi(n,r),"float32")),b:()=>P(e,ge(ur(n,r),"float32"))}}},FJ={kernelName:Tu,inputsToSave:["x"],gradFunc:(e,t,n)=>{let r=t[0],{paddings:a}=n,s=a.map(i=>i[0]);return{x:()=>$e(e,s,r.shape)}}},MJ={kernelName:$o,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,r]=t,a=wt(n.shape,r.shape);return{a:()=>{let s=Vt(n.shape,a);return s.length>0?G(Re(e,s),n.shape):e},b:()=>{let s=P(e,St(wl(be(n,r)))),i=Vt(r.shape,a);return i.length>0?G(Re(s,i),r.shape):s}}}},$J={kernelName:Ws,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,r]=t,a=wt(n.shape,r.shape);return{a:()=>{let s=P(e,ge(r,"float32")),i=Vt(n.shape,a);return i.length>0?G(Re(s,i),n.shape):s},b:()=>{let s=P(e,ge(n,"float32")),i=Vt(r.shape,a);return i.length>0?G(Re(s,i),r.shape):s}}}},DJ={kernelName:Do,gradFunc:e=>({x:()=>St(e)})},OJ={kernelName:Bs,inputsToSave:["indices"],gradFunc:(e,t)=>{let n=t[0];return{indices:()=>$t(n.shape,"float32")}}},zJ={kernelName:Wo,gradFunc:e=>({x:()=>qe(e)})},PJ={kernelName:Bo,saveAllInputs:!0,gradFunc:(e,t,n)=>{let{axis:r}=n;return hr(e,r).map(a=>()=>a)}},H3={kernelName:Vs,inputsToSave:["x"],gradFunc:(e,t,n)=>{let r=t[0],{paddings:a}=n,s=a.map(i=>i[0]);return{x:()=>$e(e,s,r.shape)}}},LJ={kernelName:Us,inputsToSave:["a","b"],outputsToSave:[!0],gradFunc:(e,t)=>{let[n,r,a]=t,s=n,i=r,o=wt(s.shape,i.shape);return{a:()=>{let l=ge(i,"float32"),u=P(e,P(l,ha(s,we(l,Ie(1))))),c=Vt(s.shape,o);return c.length>0&&(u=Re(u,c)),G(u,s.shape)},b:()=>{let l=ur(s,0),u=Tn(l,zn(s),qe(s)),c=P(e,P(a,u)),h=Vt(i.shape,o);return h.length>0&&(c=Re(c,h)),G(c,i.shape)}}}},WJ={kernelName:Hs,inputsToSave:["x","alpha"],gradFunc:(e,t)=>{let[n,r]=t,a=ur(n,0);return{x:()=>Tn(a,e,P(e,r)),alpha:()=>{let s=Tn(a,qe(e),P(e,n)),i=Vt(r.shape,e.shape);return i.length>0&&(s=Re(s,i)),G(s,r.shape)}}}},BJ={kernelName:Is,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,r]=t,a=wt(n.shape,r.shape);return{a:()=>{let s=be(e,ge(r,"float32")),i=Vt(n.shape,a);return i.length>0?G(Re(s,i),n.shape):s},b:()=>{let s=P(e,ge(n,"float32")),i=Vt(r.shape,a);i.length>0&&(s=G(Re(s,i),r.shape));let o=ht(r);return St(be(s,ge(o,"float32")))}}}},VJ={kernelName:Uo,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>be(e,St(ht(n)))}}},UJ={kernelName:qs,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t,r=P(yi(n,6),Nl(n));return{x:()=>P(e,ge(r,"float32"))}}},HJ={kernelName:js,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>P(e,ge(Nl(n),"float32"))}}},jJ={kernelName:Ho,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>G(e,n.shape)}}},GJ={kernelName:Gs,inputsToSave:["images"],gradFunc:(e,t,n)=>{let[r]=t,a={dy:e,images:r};return{images:()=>$.runKernel(ld,a,n)}}},qJ={kernelName:Cu,inputsToSave:["images"],gradFunc:(e,t,n)=>{let[r]=t,a={dy:e,images:r};return{images:()=>$.runKernel(od,a,n)}}},XJ={kernelName:Xs,gradFunc:(e,t,n)=>{let{dims:r}=n,a=or(r,e.shape);return{x:()=>Ln(e,a)}}},KJ={kernelName:Ks,gradFunc:e=>({x:()=>qe(e)})},ZJ={kernelName:Zs,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>St(be(e,P(ha(n,1.5),2)))}}},YJ={kernelName:Go,inputsToSave:["condition"],gradFunc:(e,t)=>{let[n]=t;return{condition:()=>ge(qe(n),"float32"),t:()=>P(e,ge(n,e.dtype)),e:()=>P(e,ge(ec(n),e.dtype))}}},JJ={kernelName:qo,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>{let r=ur(n,Ie(0)),a=Ie(Yx),s=Ie(Jx),i=P(e,s),o=P(P(e,a),Jn(ge(n,"float32")));return Tn(r,i,o)}}}},QJ={kernelName:Js,outputsToSave:[!0],gradFunc:(e,t)=>{let[n]=t;return{x:()=>P(e,P(n,we(Ie(1),n)))}}},eQ={kernelName:Zo,gradFunc:e=>({x:()=>qe(e)})},tQ={kernelName:Ys,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>P(Yu(ge(n,"float32")),e)}}},nQ={kernelName:Ko,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>P(Td(ge(n,"float32")),e)}}},rQ={kernelName:Xo,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[r]=t,{begin:a,size:s}=n,i=r.shape,[o,l]=Z5(r,a,s),u=[];for(let c=0;c<e.rank;c++)u.push([o[c],i[c]-o[c]-l[c]]);return{x:()=>ca(e,u)}}},aQ={kernelName:ti,outputsToSave:[!0],gradFunc:(e,t,n)=>{let[r]=t,{dim:a}=n,s=!0,i=P(e,r);return{logits:()=>we(i,P(Re(i,[a],s),r))}}},sQ={kernelName:Yo,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>P(e,On(n))}}},j3={kernelName:Ru,gradFunc:(e,t,n)=>{let{blockShape:r,paddings:a}=n;return{x:()=>Ku(e,r,a)}}},G3={kernelName:Jo,gradFunc:(e,t,n)=>{let{axis:r}=n;return{x:()=>lt(e,r)}}},iQ={kernelName:Qs,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>be(e,P(an(ge(n,"float32")),2))}}},oQ={kernelName:Fu,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>P(e,P(ge(n,"float32"),2))}}},lQ={kernelName:ni,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,r]=t,a=Ie(2);return{a:()=>P(e,P(a,we(n,r))),b:()=>P(e,P(a,we(r,n)))}}},uQ={kernelName:$a,gradFunc:e=>({x:()=>qe(e)})},cQ={kernelName:ri,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,r]=t,a=wt(n.shape,r.shape);return{a:()=>{let s=e,i=Vt(n.shape,a);return i.length>0&&(s=Re(s,i)),G(s,n.shape)},b:()=>{let s=e,i=Vt(r.shape,a);return i.length>0&&(s=Re(s,i)),G(St(s),r.shape)}}}},hQ={kernelName:ei,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[r]=t,a=r.shape.slice(),{axis:s}=n;or(s,r.shape).forEach(l=>{a[l]=1});let i=G(e,a),o=P(i,Vr(r.shape,"float32"));return{x:()=>o}}},dQ={kernelName:el,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>be(e,ht(Yu(n)))}}},pQ={kernelName:ai,outputsToSave:[!0],gradFunc:(e,t)=>{let[n]=t;return{x:()=>P(we(Ie(1),ht(n)),e)}}},fQ={kernelName:Ma,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[r]=t,{reps:a}=n;return{x:()=>{let s=qe(r);if(r.rank===1)for(let i=0;i<a[0];++i)s=ie(s,$e(e,[i*r.shape[0]],[r.shape[0]]));else if(r.rank===2)for(let i=0;i<a[0];++i)for(let o=0;o<a[1];++o)s=ie(s,$e(e,[i*r.shape[0],o*r.shape[1]],[r.shape[0],r.shape[1]]));else if(r.rank===3)for(let i=0;i<a[0];++i)for(let o=0;o<a[1];++o)for(let l=0;l<a[2];++l)s=ie(s,$e(e,[i*r.shape[0],o*r.shape[1],l*r.shape[2]],[r.shape[0],r.shape[1],r.shape[2]]));else if(r.rank===4)for(let i=0;i<a[0];++i)for(let o=0;o<a[1];++o)for(let l=0;l<a[2];++l)for(let u=0;u<a[3];++u)s=ie(s,$e(e,[i*r.shape[0],o*r.shape[1],l*r.shape[2],u*r.shape[3]],[r.shape[0],r.shape[1],r.shape[2],r.shape[3]]));else throw new Error(`Gradient for tile operation is not implemented for rank-${r.rank} tensors yet.`);return s}}}},mQ={kernelName:si,gradFunc:(e,t,n)=>{let r=n,{perm:a}=r,s=xm(a);return{x:()=>ot(e,s)}}},AQ={kernelName:nl,gradFunc:(e,t,n)=>{let r=n,{axis:a}=r;return{value:()=>An(e,a)}}},gQ={kernelName:Mu,inputsToSave:["segmentIds"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>yQ(e,n)}}};function yQ(e,t){let n=Br(t,qe(t)),r=Ai(e,n),a=Ua(t,Ie(0,"int32")),s=r.rank-a.rank;for(let o=0;o<s;++o)a=mn(a,o+1);a=cr(a,Vr(r.shape,"bool"));let i=qe(r);return Tn(a,r,i)}var xQ={kernelName:rl,gradFunc:e=>({x:()=>qe(e)})},wQ=[L3,wY,bY,_Y,vY,kY,IY,NY,SY,TY,EY,CY,MY,OY,zY,PY,LY,WY,BY,VY,UY,HY,GY,jY,KY,ZY,YY,JY,QY,eJ,BJ,tJ,nJ,rJ,aJ,sJ,oJ,iJ,lJ,uJ,cJ,hJ,dJ,pJ,fJ,mJ,AJ,yJ,gJ,bJ,U3,U3,_J,IJ,TJ,EJ,CJ,RJ,FJ,MJ,$J,DJ,OJ,zJ,PJ,H3,H3,LJ,WJ,VJ,UJ,HJ,jJ,GJ,qJ,XJ,KJ,ZJ,YJ,JJ,QJ,eQ,tQ,nQ,rQ,aQ,sQ,j3,j3,G3,G3,iQ,lQ,oQ,uQ,cQ,hQ,dQ,pQ,fQ,mQ,AQ,gQ,xQ];for(let e of wQ)d5(e);var q3={};We(q3,{maxNorm:()=>bQ,minMaxNorm:()=>kQ,nonNeg:()=>vQ,unitNorm:()=>_Q});var SA;function Ht(){return SA==null&&(SA=rx().epsilon()),SA}function Sr(){return"channelsLast"}var ma=class extends Error{constructor(e){super(e);Object.setPrototypeOf(this,ma.prototype)}},Tr=class extends Error{constructor(e){super(e);Object.setPrototypeOf(this,Tr.prototype)}},V=class extends Error{constructor(e){super(e);Object.setPrototypeOf(this,V.prototype)}},Pe=class extends Error{constructor(e){super(e);Object.setPrototypeOf(this,Pe.prototype)}},X3=class extends Error{constructor(e){super(e);Object.setPrototypeOf(this,X3.prototype)}};function Ci(e,t){if(Array.isArray(e)){let n=[];for(let r=0;r<t;r++)n=n.concat(e);return n}else{let n=new Array(t);return n.fill(e),n}}function qr(e,t){if(!e)throw new X3(t)}function K3(e,t){let n=0;for(let r of e)r===t&&n++;return n}function Fn(e){return e.length===1?e[0]:e}function yt(e){return Array.isArray(e)?e:[e]}function Aa(e){let t=e.replace(/(.)([A-Z][a-z0-9]+)/g,"$1_$2").replace(/([a-z])([A-Z])/g,"$1_$2").toLowerCase();return t[0]!=="_"?t:"private"+t}function Ri(e){return e.length<=1||e.indexOf("_")===-1?e:e.replace(/[_]+(\w|$)/g,(t,n)=>n.toUpperCase())}var pr={};function TA(e){if(e==null)return null;let t={};return t.className=e.getClassName(),t.config=e.getConfig(),t}function EA(e){if(!(e==null||typeof e!="object"))if(Array.isArray(e))e.forEach(t=>EA(t));else{let t=Object.keys(e);for(let n of t){let r=e[n];r!=null&&typeof r=="object"&&(!Array.isArray(r)&&r.type==="ndarray"&&typeof r.value=="number"?e[n]=r.value:EA(r))}}}function Sc(e,t={},n={},r="object",a=!1){if(typeof e=="string"){let s=e,i;if(s in n)i=n[s];else if(s in pr)i=pr[s];else if(i=t[s],i==null)throw new V(`Unknown ${r}: ${e}. This may be due to one of the following reasons:
|
|
1. The ${r} is defined in Python, in which case it needs to be ported to TensorFlow.js or your JavaScript code.
|
|
2. The custom ${r} is defined in JavaScript, but is not registered properly with tf.serialization.registerClass().`);return i}else{let s=e;if(s.className==null||s.config==null)throw new V(`${r}: Improper config format: ${JSON.stringify(s)}.
|
|
'className' and 'config' must set.`);let i=s.className,o,l;if(i in n?[o,l]=n[i]:i in pr?[o,l]=pr.className:i in t&&([o,l]=t[i]),o==null)throw new V(`Unknown ${r}: ${i}. This may be due to one of the following reasons:
|
|
1. The ${r} is defined in Python, in which case it needs to be ported to TensorFlow.js or your JavaScript code.
|
|
2. The custom ${r} is defined in JavaScript, but is not registered properly with tf.serialization.registerClass().`);if(l!=null){let u={};for(let p of Object.keys(pr))u[p]=pr[p];for(let p of Object.keys(n))u[p]=n[p];let c=s.config;c.customObjects=u;let h=Object.assign({},pr);for(let p of Object.keys(n))pr[p]=n[p];EA(s.config);let d=l(o,s.config,n,a);return pr=Object.assign({},h),d}else{let u=Object.assign({},pr);for(let h of Object.keys(n))pr[h]=n[h];let c=new o(s.config);return pr=Object.assign({},u),c}}}function IQ(e,t){return e<t?-1:e>t?1:0}function Op(e,t){return-1*IQ(e,t)}function Ka(e){if(e==null)return e;let t=[];for(let n of e)t.indexOf(n)===-1&&t.push(n);return t}function NQ(e){if(e==null)throw new V(`Invalid value in obj: ${JSON.stringify(e)}`);for(let t in e)if(e.hasOwnProperty(t))return!1;return!0}function Fi(e,t,n){if(n!=null&&e.indexOf(n)<0)throw new V(`${n} is not a valid ${t}. Valid values are ${e} or null/undefined.`)}function CA(e,t,n=0,r=Infinity){return qr(n>=0),qr(r>=n),Array.isArray(e)&&e.length>=n&&e.length<=r&&e.every(a=>typeof a===t)}function Jt(e,t){Array.isArray(e)?(v.assert(e.length>0,()=>`${t} is unexpectedly an empty array.`),e.forEach((n,r)=>Jt(n,`element ${r+1} of ${t}`))):v.assert(Number.isInteger(e)&&e>0,()=>`Expected ${t} to be a positive integer, but got ${Z3(e)}.`)}function Z3(e){return e===null?"null":Array.isArray(e)?"["+e.map(t=>Z3(t)).join(",")+"]":typeof e=="string"?`"${e}"`:`${e}`}function SQ(e,t){let n=v.now(),r;return(...a)=>{let s=v.now();return s-n<t||(n=s,r=e(...a)),r}}function Y3(e){return e==="relu"?"relu":e==="linear"?"linear":e==="elu"?"elu":null}function RA(e,t){return B(()=>an(Re(P(e,e),t,!0)))}var Tc=class extends ae.Serializable{getConfig(){return{}}},FA=class extends Tc{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 B(()=>{let t=RA(e,this.axis),n=Sn(t,0,this.maxValue);return P(e,be(n,ie(Ht(),t)))})}getConfig(){return{maxValue:this.maxValue,axis:this.axis}}};FA.className="MaxNorm";ae.registerClass(FA);var MA=class extends Tc{constructor(e){super();this.defaultAxis=0,this.axis=e.axis!=null?e.axis:this.defaultAxis}apply(e){return B(()=>be(e,ie(Ht(),RA(e,this.axis))))}getConfig(){return{axis:this.axis}}};MA.className="UnitNorm";ae.registerClass(MA);var $A=class extends Tc{apply(e){return Ur(e)}};$A.className="NonNeg";ae.registerClass($A);var DA=class extends Tc{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 B(()=>{let t=RA(e,this.axis),n=ie(P(this.rate,Sn(t,this.minValue,this.maxValue)),P(1-this.rate,t));return P(e,be(n,ie(Ht(),t)))})}getConfig(){return{minValue:this.minValue,maxValue:this.maxValue,rate:this.rate,axis:this.axis}}};DA.className="MinMaxNorm";ae.registerClass(DA);var J3={maxNorm:"MaxNorm",minMaxNorm:"MinMaxNorm",nonNeg:"NonNeg",unitNorm:"UnitNorm"};function jt(e){return TA(e)}function Q3(e,t={}){return Sc(e,ae.SerializationMap.getMap().classNameMap,t,"constraint")}function Gt(e){if(e==null)return null;if(typeof e=="string"){let t={className:e in J3?J3[e]:e,config:{}};return Q3(t)}else return e instanceof Tc?e:Q3(e)}function bQ(e){return new FA(e)}function _Q(e){return new MA(e)}function vQ(){return new $A}function kQ(e){return new DA(e)}var e7={};We(e7,{constant:()=>CQ,glorotNormal:()=>zQ,glorotUniform:()=>OQ,heNormal:()=>PQ,heUniform:()=>LQ,identity:()=>$Q,leCunNormal:()=>WQ,leCunUniform:()=>BQ,ones:()=>EQ,orthogonal:()=>VQ,randomNormal:()=>FQ,randomUniform:()=>RQ,truncatedNormal:()=>MQ,varianceScaling:()=>DQ,zeros:()=>TQ});var UQ=["channelsFirst","channelsLast"],HQ=["nearest","bilinear"],jQ=["valid","same","causal"],GQ=["max","avg"],qQ=["sum","mul","concat","ave"],Hl=new Map;function Ft(e){Fi(UQ,"DataFormat",e)}function XQ(e){Fi(HQ,"InterpolationFormat",e)}function nr(e){Fi(jQ,"PaddingMode",e)}function t7(e){Fi(GQ,"PoolMode",e)}var Ec=[],n7="/";function Mi(e,t){Ec.push(e);try{let n=t();return Ec.pop(),n}catch(n){throw Ec.pop(),n}}function KQ(){return Ec.length===0?"":Ec.join(n7)+n7}function a7(e){if(!r7(e))throw new Error("Not a valid tensor name: '"+e+"'");return KQ()+e}function s7(e){if(!r7(e))throw new Error("Not a valid tensor name: '"+e+"'");Hl.has(e)||Hl.set(e,0);let t=Hl.get(e);if(Hl.set(e,Hl.get(e)+1),t>0){let n=`${e}_${t}`;return Hl.set(n,1),n}else return e}var ZQ=new RegExp(/^[A-Za-z0-9][-A-Za-z0-9\._\/]*$/);function r7(e){return!!e.match(ZQ)}function YQ(e){return e===parseInt(e.toString(),10)}function Za(e,t,n){t==null&&(t=0),n==null&&(n=e.length);let r=1;for(let a=t;a<n;++a)r*=e[a];return r}function i7(e){return e=Array.isArray(e)?new Float32Array(e):e,hn(e)}function jl(e){return _l(i7(e)).dataSync()[0]}function Ya(e){return Qn(i7(e)).dataSync()[0]}function Er(e,t){if(t<e)throw new V(`end (${t}) < begin (${e}) is forbidden.`);let n=[];for(let r=e;r<t;++r)n.push(r);return n}function Cc(e,t){return e.asType(t)}function Rc(e,t=-1){let n=e.shape.slice();return t<0&&(t=n.length+t+1),n.splice(t,0,1),e.reshape(n)}function JQ(e,t){return B(()=>{if(e.shape.length!==2)throw new V(`repeat() expects a rank-2 tensor, but received a rank-${e.shape.length} tensor.`);let n=Rc(e,1);return OA(n,[1,t,1])})}function QQ(e){let t=[Za(e.shape)];return e.reshape(t)}function eee(e){if(e.rank<=1)throw new V(`batchFlatten requires a minimum rank of 2. Got rank: ${e.rank}.`);let t=[e.shape[0],Za(e.shape,1)];return e.reshape(t)}function $i(e,t,n){return B(()=>{switch(e.rank){case 1:return Hd(e,t,n);case 2:return Cm(e,[t,0],[n,e.shape[1]]);case 3:return jd(e,[t,0,0],[n,e.shape[1],e.shape[2]]);case 4:return sc(e,[t,0,0,0],[n,e.shape[1],e.shape[2],e.shape[3]]);case 5:return $e(e,[t,0,0,0,0],[n,e.shape[1],e.shape[2],e.shape[3],e.shape[4]]);case 6:return $e(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 V(`sliceAlongFirstAxis() received an unsupported tensor rank: ${e.rank}`)}})}function zA(e,t,n){return B(()=>{switch(e.rank){case 1:return Hd(e,t,n);case 2:return Cm(e,[0,t],[e.shape[0],n]);case 3:return jd(e,[0,0,t],[e.shape[0],e.shape[1],n]);case 4:return sc(e,[0,0,0,t],[e.shape[0],e.shape[1],e.shape[2],n]);default:throw new V(`sliceAlongLastAxis() received an unsupported tensor rank: ${e.rank}`)}})}function zp(e,t,n,r){return B(()=>{switch(e.rank){case 1:return Hd(e,t,n);case 2:switch(r){case 1:return $i(e,t,n);case 2:return zA(e,t,n);default:throw new V(`The axis is not within the rank of the tensor ${r}`)}case 3:switch(r){case 1:return $i(e,t,n);case 2:return jd(e,[0,t,0],[e.shape[0],n,e.shape[2]]);case 3:return zA(e,t,n);default:throw new V(`The axis is not within the rank of the tensor ${r}`)}case 4:switch(r){case 1:return $i(e,t,n);case 2:return sc(e,[0,t,0,0],[e.shape[0],n,e.shape[2],e.shape[3]]);case 3:return sc(e,[0,0,t,0],[e.shape[0],e.shape[1],n,e.shape[3]]);case 4:return zA(e,t,n);default:throw new V(`The axis is not within the rank of the tensor ${r}`)}default:throw new V(`sliceAlongLastAxis() received an unsupported tensor rank: ${e.rank}`)}})}function PA(e,t=-1){let n;return t<0&&(n=e[0].rank,n!==0?t=n:t=0),t===e[0].rank&&(t=-1),lt(e,t)}function o7(e,t){switch(e.rank){case 1:return hx([e,t]);case 2:return yl([e,t],0);case 3:return dx([e,t],0);case 4:return px([e,t],0);default:throw new V(`concatAlongFirstAxis() received an unsupported tensor rank: ${e.rank}`)}}function OA(e,t){if(Array.isArray(t)||(t=[t]),e.rank!==t.length)throw new V(`The length of input n (${t.length}) does not match the number of dimensions in input x (${e.rank})`);return Va(e,t)}function Pp(e,t=0,n=1,r,a){return Cx(e,t,n,r,a)}function Xr(e,t,n,r){if(e.rank<2||t.rank<2)throw new Pe(`dot requires both inputs to be rank >= 2 but got x shape = ${e.shape} and y shape = ${t.shape}`);if(t.rank>=3){let a=e.shape.slice(-1)[0],s=t.shape.slice(-2)[0];if(a!==s)throw new Pe(`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 a=!1,s=!1;return ja.matMul({a:e,b:t,transposeA:a,transposeB:s,bias:r?LA(e.rank,r,Sr()):null,activation:n})}else{let a=e.shape.slice(),s=a.pop();e=e.reshape([-1,s]);let i=t.shape.slice(),o=i.pop(),l=i.pop(),u=[...i,o],c=Array.from({length:t.rank},(f,m)=>m===0?t.rank-2:m<=t.rank-2?m-1:m);t=t.transpose(c).reshape([l,-1]);let h=[...a,...u],d=!1,p=!1;return ja.matMul({a:e,b:t,transposeA:d,transposeB:p,bias:r?LA(e.rank,r,Sr()):null,activation:n}).reshape(h)}}function l7(e,t,n){return B(()=>(Array.isArray(t)?t=hn(t,"int32"):t=t.toInt(),Ai(e,t,n)))}function Fc(e){return P(e,e)}function LA(e,t,n){let r=t.shape;if(t.rank!==1&&t.rank!==e)throw new V(`Unexpected bias dimensions: ${t.rank}; expected it to be 1 or ${e}`);if(e===5){if(n==="channelsFirst")return r.length===1?t.reshape([1,r[0],1,1,1]):t.reshape([1,r[3],r[0],r[1],r[2]]);if(n==="channelsLast")return r.length===1?t.reshape([1,1,1,1,r[0]]):t.reshape([1].concat(r))}else if(e===4){if(n==="channelsFirst")return r.length===1?t.reshape([1,r[0],1,1]):t.reshape([1,r[2],r[0],r[1]]);if(n==="channelsLast")return r.length===1?t.reshape([1,1,1,r[0]]):t.reshape([1].concat(r))}else if(e===3){if(n==="channelsFirst")return r.length===1?t.reshape([1,r[0],1]):t.reshape([1,r[1],r[0]]);if(n==="channelsLast")return r.length===1?t.reshape([1,1,r[0]]):t.reshape([1].concat(r))}else if(e<3)return t;throw new V(`Unsupported input rank by biasAdd: ${t.rank}`)}function Kr(e,t,n){return B(()=>(n==null&&(n=Sr()),Ft(n),e.add(LA(e.rank,t,n))))}function tee(e,t=1){if(t!==1)throw new Pe(`Support for alpha values other than 1 (${t}) is not implemented yet.`);return xl(e)}function nee(e){return B(()=>be(e,Bt(e).add(1)))}function u7(e,t,n,r){return B(()=>zx(e,t,n,r))}function ree(e){return B(()=>{let t=ie(.5,P(.2,e));return Sn(t,0,1)})}function Mc(e,t,n=!1){return n?e():t()}var aee=["fanIn","fanOut","fanAvg"],see=["normal","uniform","truncatedNormal"];function iee(e){Fi(aee,"FanMode",e)}function oee(e){Fi(see,"Distribution",e)}var fr=class extends ae.Serializable{fromConfigUsesCustomObjects(){return!1}getConfig(){return{}}},WA=class extends fr{apply(e,t){return $t(e,t)}};WA.className="Zeros";ae.registerClass(WA);var Lp=class extends fr{apply(e,t){return Vr(e,t)}};Lp.className="Ones";ae.registerClass(Lp);var BA=class extends fr{constructor(e){super();if(typeof e!="object")throw new V(`Expected argument of type ConstantConfig but got ${e}`);if(e.value===void 0)throw new V(`config must have value set but got ${e}`);this.value=e.value}apply(e,t){return B(()=>P(Ie(this.value),Vr(e,t)))}getConfig(){return{value:this.value}}};BA.className="Constant";ae.registerClass(BA);var VA=class extends fr{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 kl(e,this.minval,this.maxval,t)}getConfig(){return{minval:this.minval,maxval:this.maxval,seed:this.seed}}};VA.className="RandomUniform";ae.registerClass(VA);var UA=class extends fr{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 Pe(`randomNormal does not support dType ${t}.`);return Pp(e,this.mean,this.stddev,t,this.seed)}getConfig(){return{mean:this.mean,stddev:this.stddev,seed:this.seed}}};UA.className="RandomNormal";ae.registerClass(UA);var HA=class extends fr{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 Pe(`truncatedNormal does not support dType ${t}.`);return Xd(e,this.mean,this.stddev,t,this.seed)}getConfig(){return{mean:this.mean,stddev:this.stddev,seed:this.seed}}};HA.className="TruncatedNormal";ae.registerClass(HA);var jA=class extends fr{constructor(e){super();this.gain=e.gain!=null?e.gain:1}apply(e,t){return B(()=>{if(e.length!==2||e[0]!==e[1])throw new V("Identity matrix initializer can only be used for 2D square matrices.");return P(this.gain,Am(e[0]))})}getConfig(){return{gain:this.gain}}};jA.className="Identity";ae.registerClass(jA);function lee(e,t="channelsLast"){let n,r;if(Ft(t),e.length===2)n=e[0],r=e[1];else if([3,4,5].indexOf(e.length)!==-1){if(t==="channelsFirst"){let a=Za(e,2);n=e[1]*a,r=e[0]*a}else if(t==="channelsLast"){let a=Za(e,0,e.length-2);n=e[e.length-2]*a,r=e[e.length-1]*a}}else{let a=Za(e);n=Math.sqrt(a),r=Math.sqrt(a)}return[n,r]}var Mn=class extends fr{constructor(e){super();if(e.scale<0)throw new V(`scale must be a positive float. Got: ${e.scale}`);this.scale=e.scale==null?1:e.scale,this.mode=e.mode==null?"fanIn":e.mode,iee(this.mode),this.distribution=e.distribution==null?"normal":e.distribution,oee(this.distribution),this.seed=e.seed}apply(e,t){let n=lee(e),r=n[0],a=n[1],s=this.scale;if(this.mode==="fanIn"?s/=Math.max(1,r):this.mode==="fanOut"?s/=Math.max(1,a):s/=Math.max(1,(r+a)/2),this.distribution==="normal"){let i=Math.sqrt(s);if(t=t||"float32",t!=="float32"&&t!=="int32")throw new Pe(`${this.getClassName()} does not support dType ${t}.`);return Xd(e,0,i,t,this.seed)}else{let i=Math.sqrt(3*s);return kl(e,-i,i,t)}}getConfig(){return{scale:this.scale,mode:this.mode,distribution:this.distribution,seed:this.seed}}};Mn.className="VarianceScaling";ae.registerClass(Mn);var Wp=class extends Mn{constructor(e){super({scale:1,mode:"fanAvg",distribution:"uniform",seed:e==null?null:e.seed})}getClassName(){return Mn.className}};Wp.className="GlorotUniform";ae.registerClass(Wp);var Bp=class extends Mn{constructor(e){super({scale:1,mode:"fanAvg",distribution:"normal",seed:e==null?null:e.seed})}getClassName(){return Mn.className}};Bp.className="GlorotNormal";ae.registerClass(Bp);var Vp=class extends Mn{constructor(e){super({scale:2,mode:"fanIn",distribution:"normal",seed:e==null?null:e.seed})}getClassName(){return Mn.className}};Vp.className="HeNormal";ae.registerClass(Vp);var Up=class extends Mn{constructor(e){super({scale:2,mode:"fanIn",distribution:"uniform",seed:e==null?null:e.seed})}getClassName(){return Mn.className}};Up.className="HeUniform";ae.registerClass(Up);var Hp=class extends Mn{constructor(e){super({scale:1,mode:"fanIn",distribution:"normal",seed:e==null?null:e.seed})}getClassName(){return Mn.className}};Hp.className="LeCunNormal";ae.registerClass(Hp);var jp=class extends Mn{constructor(e){super({scale:1,mode:"fanIn",distribution:"uniform",seed:e==null?null:e.seed})}getClassName(){return Mn.className}};jp.className="LeCunNormal";ae.registerClass(jp);var GA=class extends fr{constructor(e){super();if(this.DEFAULT_GAIN=1,this.gain=e.gain==null?this.DEFAULT_GAIN:e.gain,this.seed=e.seed,this.seed!=null)throw new Pe("Random seed is not implemented for Orthogonal Initializer yet.")}apply(e,t){return B(()=>{if(e.length<2)throw new Pe("Shape must be at least 2D.");e[0]*e[1]>2e3&&console.warn(`Orthogonal initializer is being called on a matrix with more than 2000 (${e[0]*e[1]}) elements: Slowness may result.`);let n=e[0]>e[1]?[e[1],e[0]]:e,r=Pp(n,0,1,"float32"),a=Zx.gramSchmidt(r);return e[0]>e[1]&&(a=a.transpose()),P(this.gain,a)})}getConfig(){return{gain:this.gain,seed:this.seed}}};GA.className="Orthogonal";ae.registerClass(GA);var c7={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 h7(e,t={}){return Sc(e,ae.SerializationMap.getMap().classNameMap,t,"initializer")}function Et(e){return TA(e)}function _t(e){if(typeof e=="string"){let t=e in c7?c7[e]:e;if(t==="GlorotNormal")return new Bp;if(t==="GlorotUniform")return new Wp;if(t==="HeNormal")return new Vp;if(t==="HeUniform")return new Up;if(t==="LeCunNormal")return new Hp;if(t==="LeCunUniform")return new jp;{let n={};return n.className=t,n.config={},h7(n)}}else return e instanceof fr?e:h7(e)}function TQ(){return new WA}function EQ(){return new Lp}function CQ(e){return new BA(e)}function RQ(e){return new VA(e)}function FQ(e){return new UA(e)}function MQ(e){return new HA(e)}function $Q(e){return new jA(e)}function DQ(e){return new Mn(e)}function OQ(e){return new Wp(e)}function zQ(e){return new Bp(e)}function PQ(e){return new Vp(e)}function LQ(e){return new Up(e)}function WQ(e){return new Hp(e)}function BQ(e){return new jp(e)}function VQ(e){return new GA(e)}var d7={};We(d7,{Layer:()=>Ze,RNN:()=>Zr,RNNCell:()=>$c,activation:()=>kee,add:()=>Mee,alphaDropout:()=>Ate,average:()=>$ee,averagePooling1d:()=>qA,averagePooling2d:()=>XA,averagePooling3d:()=>KA,avgPool1d:()=>Uee,avgPool2d:()=>jee,avgPool3d:()=>qee,avgPooling1d:()=>Hee,avgPooling2d:()=>Gee,avgPooling3d:()=>Xee,batchNormalization:()=>Wee,bidirectional:()=>lte,concatenate:()=>Dee,conv1d:()=>Aee,conv2d:()=>yee,conv2dTranspose:()=>gee,conv3d:()=>xee,convLstm2d:()=>ate,convLstm2dCell:()=>ste,cropping2D:()=>bee,dense:()=>Iee,depthwiseConv2d:()=>vee,dot:()=>Lee,dropout:()=>Nee,elu:()=>cee,embedding:()=>Fee,flatten:()=>Tee,gaussianDropout:()=>mte,gaussianNoise:()=>fte,globalAveragePooling1d:()=>Kee,globalAveragePooling2d:()=>Zee,globalMaxPool1d:()=>cte,globalMaxPool2d:()=>hte,globalMaxPooling1d:()=>f7,globalMaxPooling2d:()=>m7,gru:()=>Jee,gruCell:()=>Qee,input:()=>p7,inputLayer:()=>uee,layerNormalization:()=>Bee,leakyReLU:()=>dee,lstm:()=>ete,lstmCell:()=>tte,masking:()=>yte,maxPool1d:()=>dte,maxPool2d:()=>pte,maxPooling1d:()=>A7,maxPooling2d:()=>y7,maxPooling3d:()=>Yee,maximum:()=>Oee,minimum:()=>zee,multiply:()=>Pee,permute:()=>Ree,prelu:()=>pee,reLU:()=>hee,repeatVector:()=>Eee,reshape:()=>Cee,rnn:()=>ite,separableConv2d:()=>wee,simpleRNN:()=>nte,simpleRNNCell:()=>rte,softmax:()=>fee,spatialDropout1d:()=>See,stackedRNNCells:()=>ote,thresholdedReLU:()=>mee,timeDistributed:()=>ute,upSampling2d:()=>_ee,zeroPadding2d:()=>Vee});var gte=0;function g7(){return gte++}var Gp={};function qp(e=""){return e in Gp||(Gp[e]=0),Gp[e]+=1,e+Gp[e].toString()}function ZA(e){return Array.isArray(e)&&Array.isArray(e[0])}function Xp(e){return e.length===0?[]:Array.isArray(e[0])?e:[e]}function Be(e){let t;if(Array.isArray(e)){if(e.length!==1)throw new V(`Expected Tensor length to be 1; got ${e.length}`);t=e[0]}else t=e;return t}function pt(e){if(Array.isArray(e)&&Array.isArray(e[0])){if(e.length===1)return e=e,e[0];throw new V(`Expected exactly 1 Shape; got ${e.length}`)}else return e}function Kp(e){let t=0;for(let n of e)n.shape.length===0?t+=1:t+=n.shape.reduce((r,a)=>r*a);return t}var x7="Variable",w7=class{constructor(e,t="float32",n=x7,r=!0,a=null){this.dtype=t==null?"float32":t,this.shape=e.shape,this.id=g7(),n=n==null?x7:n,this.originalName=a7(n),this.name=s7(this.originalName),this.trainable_=r,this.constraint=a,this.val=Fx(e,this.trainable_,this.name,this.dtype)}read(){return this.assertNotDisposed(),this.val}write(e){return this.assertNotDisposed(),xte(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 xte(e,t){if(e.shape.toString()!==t.shape.toString())throw new Error("Shape mismatch: "+JSON.stringify(e.shape)+" vs. "+JSON.stringify(t.shape))}function YA(e){return e.map(t=>t.read())}function JA(e){e.forEach(t=>{t[0].write(t[1])})}var Qt=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||{}}},Cr=class{constructor(e,t,n,r,a,s,i){this.dtype=e,this.shape=t,this.sourceLayer=n,this.inputs=r,this.callArgs=a,this.outputTensorIndex=i,this.id=g7(),s!=null&&(this.originalName=a7(s),this.name=s7(this.originalName)),this.rank=t.length}},wte=0,Zp=class{constructor(e,t){this.callArgs=t,this.id=wte++,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}}},bte=0,Ze=class extends ae.Serializable{constructor(e={}){super();this._callHook=null,this._addedWeightNames=[],this._stateful=!1,this.id=bte++,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=Aa(n)+"_"+qp(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 a=null;e.batchSize!=null&&(a=e.batchSize),n=[a].concat(e.inputShape)}this.batchInputShape=n;let r=e.dtype;r==null&&(r=e.inputDType),r==null&&(r="float32"),this.dtype=r}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 Tr(`The layer has never been called and thus has no defined ${t}.`);if(this.inboundNodes.length<=e)throw new V(`Asked to get ${t} at node ${e}, but the layer has only ${this.inboundNodes.length} inbound nodes.`);return this.inboundNodes[e]}getInputAt(e){return Fn(this.getNodeAtIndex(e,"input").inputTensors)}getOutputAt(e){return Fn(this.getNodeAtIndex(e,"output").outputTensors)}get input(){if(this.inboundNodes.length>1)throw new ma(`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 ma(`Layer ${this.name} is not connected, no input to return.`);return Fn(this.getNodeAtIndex(0,"input").inputTensors)}get output(){if(this.inboundNodes.length===0)throw new ma(`Layer ${this.name} has no inbound nodes.`);if(this.inboundNodes.length>1)throw new ma(`Layer ${this.name} has multiple inbound nodes, hence the notion of "layer output" is ill-defined. Use \`getOutputAt(nodeIndex)\` instead.`);return Fn(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 V(`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 r=e[n],a=t[n];if(a==null)continue;let s=r.rank;if(a.ndim!=null&&s!==a.ndim)throw new V(`Input ${n} is incompatible with layer ${this.name}: expected ndim=${a.ndim}, found ndim=${s}`);if(a.maxNDim!=null&&s>a.maxNDim)throw new V(`Input ${n} is incompatible with layer ${this.name}: expected max_ndim=${a.maxNDim}, found ndim=${s}`);if(a.minNDim!=null&&s<a.minNDim)throw new V(`Input ${n} is incompatible with layer ${this.name}: expected min_ndim=${a.minNDim}, found ndim=${s}.`);if(a.dtype!=null&&r.dtype!==a.dtype)throw new V(`Input ${n} is incompatible with layer ${this.name} : expected dtype=${a.dtype}, found dtype=${r.dtype}.`);if(a.axes){let i=r.shape;for(let o in a.axes){let l=Number(o),u=a.axes[o],c=l>=0?i[l]:i[i.length+l];if(u!=null&&[u,null].indexOf(c)===-1)throw new V(`Input ${n} is incompatible with layer ${this.name}: expected axis ${l} of input shape to have value ${u} but got shape ${i}.`)}}if(a.shape!=null)for(let i=0;i<a.shape.length;++i){let o=a.shape[i],l=r.shape[i];if(o!=null&&l!=null&&o!==l)throw new V(`Input ${n} is incompatible with layer ${this.name}: expected shape=${a.shape}, found shape=${r.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),r=!0;for(let s of n)if(!(s instanceof Cr)){r=!1;break}let a=!0;for(let s of n)if(s instanceof Cr){a=!1;break}if(r===a)throw new V("Arguments to apply() must be all SymbolicTensors or all Tensors");return Mi(this.name,()=>{if(!this.built){this.assertInputCompatibility(e);let s=[];for(let i of yt(e))s.push(i.shape);this.build(Fn(s)),this.built=!0,this.initialWeights&&this.setWeights(this.initialWeights),this._refCount===null&&a&&(this._refCount=1)}if(this.assertInputCompatibility(e),a){let s=this.call(e,t),i=yt(s),o=[];for(let l of i)n.indexOf(l)!==-1&&(l=l.clone()),o.push(l);if(s=Fn(o),this.activityRegularizer!=null)throw new Pe("Layer invocation in the presence of activity regularizer(s) is not supported yet.");return s}else{let s=_te(e),i=this.computeOutputShape(s),o,l=vte(e);if(this.warnOnIncompatibleInputShape(Array.isArray(e)?s[0]:s),i!=null&&i.length>0&&Array.isArray(i[0])?o=i.map((u,c)=>new Cr(l,u,this,yt(e),t,this.name,c)):o=new Cr(l,i,this,yt(e),t,this.name),this.addInboundNode(e,o,null,null,s,i,t),this._refCount++,this.activityRegularizer!=null)throw new Pe("Layer invocation in the presence of activity regularizer(s) is not supported yet.");return o}})}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 ${this.name}`);else{let t=!1;this.batchInputShape.forEach((n,r)=>{n!=null&&e[r]!=null&&e[r]!==n&&(t=!0)}),t&&console.warn(`The shape of the input tensor (${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 ma(`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 ma(`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 Tr(`You tried to call countParams() on ${this.name}, but the layer is not built yet. Build it first by calling build(batchInputShape).`);return Kp(this.weights)}build(e){this.built=!0}getWeights(e=!1){return YA(e?this.trainableWeights:this.weights)}setWeights(e){B(()=>{let t=this.weights;if(t.length!==e.length)throw new V(`You called setWeights(weights) on layer "${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=[],r=YA(t);for(let a=0;a<r.length;++a){let s=r[a],i=t[a],o=e[a];if(!v.arraysEqual(s.shape,o.shape))throw new V(`Layer weight shape ${s.shape} not compatible with provided weight shape ${o.shape}`);n.push([i,o])}JA(n)})}addWeight(e,t,n,r,a,s,i){if(this._addedWeightNames.indexOf(e)!==-1)throw new V(`Duplicate weight name ${e} for layer ${this.name}`);this._addedWeightNames.push(e),n==null&&(n="float32"),this.fastWeightInitDuringBuild&&(r=_t("zeros"));let o=r.apply(t,n),l=new w7(o,n,e,s,i);return o.dispose(),a!=null&&this.addLoss(()=>a.apply(l.read())),s==null&&(s=!0),s?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 ${this.name} does not support masking, but was passed an inputMask.`);return null}return t}addInboundNode(e,t,n,r,a,s,i=null){let o=yt(e);t=yt(t),n=yt(n),r=yt(r),a=Xp(a),s=Xp(s);let l=[],u=[],c=[];for(let h of o)l.push(h.sourceLayer),u.push(h.nodeIndex),c.push(h.tensorIndex);new Zp({outboundLayer:this,inboundLayers:l,nodeIndices:u,tensorIndices:c,inputTensors:o,outputTensors:t,inputMasks:n,outputMasks:r,inputShapes:a,outputShapes:s},i);for(let h=0;h<t.length;h++)t[h].sourceLayer=this,t[h].nodeIndex=this.inboundNodes.length-1,t[h].tensorIndex=h}getConfig(){let e={name:this.name,trainable:this.trainable};return this.batchInputShape!=null&&(e.batchInputShape=this.batchInputShape),this.dtype!=null&&(e.dtype=this.dtype),e}disposeWeights(){return this.weights.forEach(e=>e.dispose()),this.weights.length}assertNotDisposed(){if(this._refCount===0)throw new Error(`Layer '${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 _te(e){e=yt(e);let t=[];for(let n of e)t.push(n.shape);return Fn(t)}function vte(e){return"float32"}function b7(e,t,n){if((t==null||n!=null&&n>0)&&(t=e.sourceLayer,n=e.nodeIndex),t.inboundNodes.length===0)return[e];{let r=t.inboundNodes[n];if(r.inboundLayers.length===0)return r.inputTensors;{let a=[];for(let s=0;s<r.inboundLayers.length;s++){let i=r.inputTensors[s],o=r.inboundLayers[s],l=r.nodeIndices[s],u=b7(i,o,l);for(let c of u)a.indexOf(c)===-1&&a.push(c)}return a}}}var Gl=class extends Ze{constructor(e){super({dtype:e.dtype,name:e.name!=null?e.name:qp("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 V("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 V("An InputLayer should be passed either a `batchInputShape` or an `inputShape`.");t=[e.batchSize].concat(e.inputShape)}else if(e.batchSize!=null)throw new V("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 r=new Cr(this.dtype,this.batchInputShape,this,[],{},this.name);r.nodeIndex=0,r.tensorIndex=0,new Zp({outboundLayer:this,inboundLayers:[],nodeIndices:[],tensorIndices:[],inputTensors:[r],outputTensors:[r],inputMasks:[null],outputMasks:[null],inputShapes:[t],outputShapes:[t]})}apply(e,t){throw new V(`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";ae.registerClass(Gl);function _7(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 V("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 Ja(e){if(e==null)return;let t=[],n=[],r=[];for(let a in e){let s=e[a];if(typeof s!="number"){let i=s;t.push(i.data()),n.push(a),r.push(i)}}if(t.length>0){let a=await Promise.all(t);for(let s=0;s<a.length;++s)e[n[s]]=a[s][0];Me(r)}}function v7(e){if(e!=null)for(let t in e){let n=e[t];typeof n!="number"&&n.dispose()}}var k7;(function(e){e[e.SILENT=0]="SILENT",e[e.VERBOSE=1]="VERBOSE"})(k7||(k7={}));var kte=125,ql=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){}},I7=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)}},Ite=class extends ql{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 r in t){let a=t[r];if(typeof a=="number")this.totals.hasOwnProperty(r)||(this.totals[r]=0),this.totals[r]=this.totals[r]+a*n;else{let s;r in this.totals?s=this.totals[r]:this.totals[r]=0;let i=B(()=>ie(this.totals[r],P(a,n)));this.totals[r]=i,s!=null&&s.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:B(()=>{let r=P(be(1,this.seen),this.totals[n]);t[n]=r,this.totals[n].dispose(),Zt(t[n])}))}},N7=class extends ql{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 a in this.history){let s=this.history[a];for(let i=0;i<s.length;++i)if(typeof s[i]!="number"){let o=s[i];e.push(o.data()),t.push(a),n.push(i)}}let r=await Promise.all(e);for(let a=0;a<r.length;++a)this.history[t[a]][n[a]].dispose(),this.history[t[a]][n[a]]=r[a][0]}},S7=class extends ql{constructor(e,t){super();if(this.currentEpoch=0,this.yieldEvery=t||"auto",this.yieldEvery==="auto"&&(this.yieldEvery=kte),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");v.isNumber(this.yieldEvery)&&(this.maybeWait=SQ(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 r=[];this.yield!=null&&(await Ja(n),r.push(this.yield(e,t,n))),r.push(op()),await Promise.all(r)}async onEpochBegin(e,t){this.currentEpoch=e,this.epochBegin!=null&&(await Ja(t),await this.epochBegin(e,t))}async onEpochEnd(e,t){let n=[];this.epochEnd!=null&&(await Ja(t),n.push(this.epochEnd(e,t))),this.yieldEvery==="epoch"&&n.push(op()),await Promise.all(n)}async onBatchBegin(e,t){this.batchBegin!=null&&(await Ja(t),await this.batchBegin(e,t))}async onBatchEnd(e,t){let n=[];this.batchEnd!=null&&(await Ja(t),n.push(this.batchEnd(e,t))),this.yieldEvery==="batch"?n.push(op()):v.isNumber(this.yieldEvery)&&n.push(this.maybeWait(this.currentEpoch,e,t)),await Promise.all(n)}async onTrainBegin(e){this.trainBegin!=null&&(await Ja(e),await this.trainBegin(e))}async onTrainEnd(e){this.trainEnd!=null&&(await Ja(e),await this.trainEnd(e))}};function T7(e,t){return e==null&&(e={}),e instanceof ql?[e]:Array.isArray(e)&&e[0]instanceof ql?e:yt(e).map(n=>new S7(n,t))}var mr=class{constructor(){}static registerCallbackConstructor(e,t){v.assert(e>=0&&Number.isInteger(e),()=>`Verbosity level is expected to be an integer >= 0, but got ${e}`),mr.checkForDuplicate(t),mr.constructors[e]==null&&(mr.constructors[e]=[]),mr.constructors[e].push(t)}static checkForDuplicate(e){for(let t in mr.constructors)mr.constructors[+t].forEach(n=>{if(n===e)throw new V("Duplicate callback constructor.")})}static clear(){mr.constructors={}}static createCallbacks(e){let t=[];for(let n in mr.constructors){let r=+n;e>=r&&t.push(...mr.constructors[r])}return t.map(n=>new n)}};mr.constructors={};function E7(e,t,n,r,a,s,i,o,l){let u=new N7,c=[new Ite,...mr.createCallbacks(t)];e!=null&&c.push(...e),c.push(u);let h=new I7(c);return h.setParams({epochs:n,initialEpoch:r,samples:a,steps:s,batchSize:i,verbose:t,doValidation:o,metrics:l}),{callbackList:h,history:u}}function Rr(e,t={},n=!1){return Sc(e,ae.SerializationMap.getMap().classNameMap,t,"layer",n)}function Yp(e,t){return B(()=>{e.dtype!=="float32"&&(e=e.asType("float32"));let n=Re(Fc(e),t,!0),r=Ju(n.shape,Ht()),a=an(Br(n,r));return be(e,a)})}function Di(e,t){return B(()=>Tt(Fc(we(t,e)),-1))}function Jp(e,t){return B(()=>Tt(Bt(we(t,e)),-1))}function Xl(e,t){return B(()=>{let n=we(e,t),r=Sn(Bt(e),Ht(),Number.MAX_VALUE),a=Bt(be(n,r));return P(100,Tt(a,-1))})}function Nte(e,t){return B(()=>{let n=Sn(t,Ht(),Number.MAX_VALUE),r=zn(ie(1,n)),a=Sn(e,Ht(),Number.MAX_VALUE),s=zn(ie(1,a));return Tt(Fc(we(r,s)),-1)})}function Ste(e,t){return B(()=>{let n=Br(0,we(1,P(e,t)));return Tt(Fc(n),-1)})}function Tte(e,t){return B(()=>{let n=Br(0,we(1,P(e,t)));return Tt(n,-1)})}function Ete(e,t){return B(()=>{let n=Re(P(e,t),-1),r=Qn(P(we(1,e),t),-1);return Br(0,ie(1,we(r,n)))})}function Cte(e,t){return B(()=>{let n=Math.log(2),r=we(t,e),a=we(ie(r,bl(P(-2,r))),n);return Tt(a,-1)})}function Dc(e,t,n=!1){return B(()=>{if(n)t=ic(t);else{let r=Re(t,t.shape.length-1,!0);t=be(t,r)}return t=Sn(t,Ht(),1-Ht()),St(Re(P(e.toFloat(),zn(t)),t.shape.length-1))})}function Qp(e,t,n=!1){return B(()=>{let r=wl(QQ(e)).toInt();t=Sn(t,Ht(),1-Ht());let a=t.shape,s=hl(r,a[a.length-1]).reshape(a);return Dc(s,t,n)})}function Rte(e,t){if(!v.arraysEqual(e.shape,t.shape))throw new V(`logits and labels must have the same shape, but got shapes ${JSON.stringify(e.shape)} and ${JSON.stringify(t.shape)}`);return B(()=>{let n=t.relu(),r=t.abs().neg();return n.sub(t.mul(e)).add(r.exp().log1p())})}function e0(e,t){return B(()=>{let n;return n=Sn(t,Ht(),1-Ht()),n=zn(be(n,we(1,n))),Tt(Rte(e,n),-1)})}function Fte(e,t){return B(()=>{let n=Sn(e,Ht(),1),r=Sn(t,Ht(),1);return Re(P(e,zn(be(n,r))),-1)})}function Mte(e,t){return B(()=>{let n=zn(ie(Ht(),t));return Tt(we(t,P(e,n)),-1)})}function QA(e,t){return B(()=>{let n=Yp(e,-1),r=Yp(t,-1),a=P(n,r);return St(Re(a,-1))})}var t0={meanSquaredError:Di,meanAbsoluteError:Jp,meanAbsolutePercentageError:Xl,meanSquaredLogarithmicError:Nte,squaredHinge:Ste,hinge:Tte,categoricalHinge:Ete,logcosh:Cte,categoricalCrossentropy:Dc,sparseCategoricalCrossentropy:Qp,binaryCrossentropy:e0,kullbackLeiblerDivergence:Fte,poisson:Mte,cosineProximity:QA};function ey(e){if(typeof e=="string"){if(e in t0)return t0[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 V(t)}else return e}function ty(e,t){return B(()=>{let n=P(.5,Pn(t)),r=Cc(ur(t,n),e.dtype);return Tt(Ba(e,r),-1)})}function ny(e,t){return B(()=>Cc(Ba(Gu(e,-1),Gu(t,-1)),"float32"))}function C7(e,t){return B(()=>cr(e.equal(1),t.equal(1)).sum().cast("float32"))}function $te(e,t){return B(()=>cr(e.equal(1),t.equal(0)).sum().cast("float32"))}function Dte(e,t){return B(()=>cr(e.equal(0),t.equal(1)).sum().cast("float32"))}function R7(e,t){return B(()=>{let n=C7(e,t),r=Dte(e,t),a=n.add(r);return Tn(ur(a,0),n.div(a),0).cast("float32")})}function Ote(e,t){return B(()=>{let n=C7(e,t),r=$te(e,t),a=n.add(r);return Tn(ur(a,0),n.div(a),0).cast("float32")})}function F7(e,t){return e0(e,t)}function M7(e,t){return e.rank===t.rank&&(e=e.squeeze([e.rank-1])),t=t.argMax(-1),t.dtype!==e.dtype&&(t=t.asType(e.dtype)),Ba(e,t).asType("float32")}var zte=Di,Pte=Di,Lte=Jp,Wte=Jp,Bte=Xl,Vte=Xl,ry=Dc,Ute=QA,$7=Qp,n0={binaryAccuracy:ty,categoricalAccuracy:ny,precision:R7,categoricalCrossentropy:ry,sparseCategoricalCrossentropy:$7,mse:zte,MSE:Pte,mae:Lte,MAE:Wte,mape:Bte,MAPE:Vte,cosine:Ute};function Hte(e){if(typeof e=="string"&&e in n0)return n0[e];if(typeof e!="string"&&e!=null)return e;throw new V(`Unknown metric ${e}`)}function r0(e){if(qr(e!==null,`Unknown LossOrMetricFn ${e}`),typeof e=="string")return e;{let t;for(let n of Object.keys(t0))if(t0[n]===e){t=n;break}if(t!==void 0)return t;for(let n of Object.keys(n0))if(n0[n]===e){t=n;break}return t!==void 0?t:e.name}}function jte(e){let t={Adagrad:()=>bi.adagrad(.01),Adadelta:()=>bi.adadelta(1,.95,Ht()),Adam:()=>bi.adam(.001,.9,.999,Ht()),Adamax:()=>bi.adamax(.002,.9,.999,Ht(),0),RMSProp:()=>bi.rmsprop(.001,.9,0,Ht()),SGD:()=>bi.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 V(`Unknown Optimizer ${e}`)}var D7=1*1024*1024;function O7(e,t,n=!1){if(e==null||typeof e!="object"||Object.getPrototypeOf(e)!==Object.prototype||!ay(e))throw new Error("User-defined metadata is expected to be a JSON object, but is not.");if(n){let r=JSON.stringify(e);r.length>D7&&console.warn(`User-defined metadata of model "${t}" is too large in size (length=${r.length} when serialized). It is not recommended to store such large objects in user-defined metadata. Please make sure its serialized length is <= ${D7}.`)}}function ay(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"||!ay(e[n]))return!1;return!0}else if(Array.isArray(e)){for(let t of e)if(!ay(t))return!1;return!0}else return!1;else{let t=typeof e;return t==="string"||t==="number"||t==="boolean"}}function Zte(e,t,n,r=console.log){let a=qte(e),s=["Layer (type)","Output shape","Param #"];a?(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 i;if(!a){s.push("Receives inputs"),i=[];for(let c in e.nodesByDepth)i.push(...e.nodesByDepth[c])}r("_".repeat(t)),a0(s,n,r),r("=".repeat(t));let o=e.layers;for(let c=0;c<o.length;++c)a?Xte(o[c],n,r):Kte(o[c],n,i,r),r((c===o.length-1?"=":"_").repeat(t));e.checkTrainableWeightsConsistency();let l=Gte(e),u=Kp(e.nonTrainableWeights);r(`Total params: ${l+u}`),r(`Trainable params: ${l}`),r(`Non-trainable params: ${u}`),r("_".repeat(t))}function Gte(e){let t;return e.collectedTrainableWeights!=null?t=Kp(e.collectedTrainableWeights):t=Kp(e.trainableWeights),t}function qte(e){let t=!0,n=[],r=[];for(let a in e.nodesByDepth)n.push(e.nodesByDepth[a]);for(let a of n){if(a.length>1||a.length===1&&a[0].inboundLayers.length>1){t=!1;break}r.push(...a)}if(t)for(let a of e.layers){let s=!1;for(let i of a.inboundNodes)if(r.indexOf(i)!==-1)if(s){t=!1;break}else s=!0;if(!t)break}return t}function a0(e,t,n=console.log){let r="";for(let a=0;a<e.length;++a)a>0&&(r=r.slice(0,r.length-1)+" "),r+=e[a],r=r.slice(0,t[a]),r+=" ".repeat(t[a]-r.length);n(r)}function Xte(e,t,n){let r;try{r=JSON.stringify(e.outputShape)}catch(o){r="multiple"}let a=e.name,s=e.getClassName(),i=[`${a} (${s})`,r,e.countParams().toString()];a0(i,t,n)}function Kte(e,t,n,r){let a;try{a=JSON.stringify(e.outputShape)}catch(c){a="multiple"}let s=[];for(let c of e.inboundNodes)if(!(n!=null&&n.length>0&&n.indexOf(c)===-1))for(let h=0;h<c.inboundLayers.length;++h){let d=c.inboundLayers[h].name,p=c.nodeIndices[h],f=c.tensorIndices[h];s.push(`${d}[${p}][${f}]`)}let i=e.name,o=e.getClassName(),l=s.length===0?"":s[0],u=[`${i} (${o})`,a,e.countParams().toString(),l];a0(u,t,r);for(let c=1;c<s.length;++c)a0(["","","",s[c]],t,r)}function z7(e,t,n){return(e==="inboundNodes"||e==="outputLayers"||e==="inputLayers")&&t===0&&typeof n=="string"}function Oc(e,t){if(e===null)return null;if(typeof e=="string")return Ri(e);if(typeof e=="number"||typeof e=="boolean")return e;if(e instanceof Array){let n=[],r=e.length;for(let a=0;a<r;++a){let s=e[a];z7(t,a,s)?n.push(s):n.push(Oc(s,t))}return n}else{let n={};for(let r of Object.keys(e)){let a=e[r];if(r==="name"&&typeof a=="string")n[r]=a;else{let s=Ri(r);n[s]=Oc(a,s)}}return n}}function sy(e,t){if(e==null)return null;if(typeof e=="string")return Aa(e);if(typeof e=="number"||typeof e=="boolean")return e;if(e instanceof Array){let n=[],r=e.length;for(let a=0;a<r;++a){let s=e[a];z7(t,a,s)?n.push(s):n.push(sy(s,t))}return n}else{let n={};for(let r of Object.keys(e)){let a=e[r],s=Aa(r);(r==="name"||r==="className")&&typeof a=="string"?n[s]=a:n[s]=sy(a,r)}return n}}var iy="3.3.0";function Yte(e,t){if(e.dtype==null||e.dtype===t.dtype)return t;try{return ge(t,e.dtype)}catch(n){throw new V(`The dtype of the feed (${t.dtype}) can not be cast to the dtype of the key '${e.name}' (${e.dtype}).`)}}var Oi=class{constructor(e){if(this.id2Value={},this.id2Mask={},this.name2Id={},e instanceof Oi)for(let t in e.id2Value)this.id2Value[t]=e.id2Value[t],t in e.id2Mask&&(this.id2Mask[t]=e.id2Mask[t]);else{if(e==null)return;for(let t of e)this.add(t.key,t.value)}}add(e,t,n){if(this.id2Value[e.id]==null)this.id2Value[e.id]=Yte(e,t),this.name2Id[e.name]=e.id,n!=null&&(this.id2Mask[e.id]=n);else throw new V(`Duplicate key: name=${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 Cr){if(this.id2Value[e.id]==null)throw new V(`Nonexistent key: ${e.name}`);return this.id2Value[e.id]}else{let t=this.name2Id[e];if(t==null)throw new V(`Feed dict has no SymbolicTensor name: ${e}`);return this.id2Value[t]}}getMask(e){if(e instanceof Cr){if(this.id2Value[e.id]==null)throw new V(`Nonexistent key: ${e.name}`);return this.id2Mask[e.id]}else{let t=this.name2Id[e];if(t==null)throw new V(`Feed dict has no SymbolicTensor name: ${e}`);return this.id2Mask[t]}}disposeMasks(){this.id2Mask!=null&&Me(this.id2Mask)}},oy={},P7={};function zc(e,t,n,r){let a=n==null?!1:n.training,s=Array.isArray(e),i=s?e:[e],o=i.map(f=>f.name),l=[],u=t.names();for(let f of o)u.indexOf(f)!==-1?l.push(t.getValue(f)):l.push(null);r!=null&&(r.maxNumTensors=-Infinity,r.minNumTensors=Infinity);let c=o.join(",")+"|"+t.names().join(","),h,d;if(oy[c]==null){let f=Jte(i,t);h=f.sorted,d=f.recipientCounts,oy[c]=h,P7[c]=d}h=oy[c],d={},a||Object.assign(d,P7[c]);let p=new Oi(t);for(let f=0;f<h.length;++f){if(r!=null){let T=_d().numTensors;T>r.maxNumTensors&&(r.maxNumTensors=T),T<r.minNumTensors&&(r.minNumTensors=T)}let m=h[f],A=m.sourceLayer;if(A instanceof Gl)continue;let y=[],g=[],b=[],_=!1;for(let T of m.inputs){let M=p.getValue(T),D=p.getMask(T);y.push(M),g.push(D),D!=null&&(_=!0),a||(d[T.name]--,d[T.name]===0&&!t.hasKey(T)&&o.indexOf(T.name)===-1&&!M.isDisposed&&T.sourceLayer.stateful!==!0&&b.push(M))}_&&(n=n||{},n.mask=g[0]);let w=yt(A.apply(y,n)),x=null;A.supportsMasking&&(x=A.computeMask(y,g));let N=Qte(m),S=Array.isArray(N)?N:[N];for(let T=0;T<S.length;++T){p.hasKey(S[T])||p.add(S[T],w[T],Array.isArray(x)?x[0]:x);let M=o.indexOf(S[T].name);M!==-1&&(l[M]=w[T])}a||Me(b)}return p.disposeMasks(),s?l:l[0]}function Jte(e,t){v.assert(e!=null&&e.length>0,()=>"Expected at least one fetch, got none");let n=[],r={};if(e.length===1){let a=L7(e[0],t);n=a.sorted,r=a.recipientMap}else{let a=new Set;for(let s of e){let{sorted:i,recipientMap:o}=L7(s,t);for(let l of i)a.has(l.name)||(n.push(l),a.add(l.name));for(let l in o)r[l]==null&&(r[l]=new Set),o[l].forEach(u=>r[l].add(u))}}return{sorted:n,recipientCounts:ene(r)}}function ene(e){let t={};for(let n in e)t[n]=e[n].size;return t}function L7(e,t){let n=new Set,r=[],a={};for(let o of t.names())n.add(o);let s=[],i=[];for(s.push(e);s.length>0;){let o=s[s.length-1];if(n.has(o.name)){s.pop();continue}let l=i[i.length-1]===s.length-1;if(o.inputs.length===0||l)s.pop(),r.push(o),n.add(o.name),l&&i.pop();else{i.push(s.length-1);for(let u of o.inputs)a[u.name]==null&&(a[u.name]=new Set),a[u.name].add(o.name),!n.has(u.name)&&s.push(u)}}return{sorted:r,recipientMap:a}}function Qte(e){let t;if(e.sourceLayer.inboundNodes.length===1)t=e.sourceLayer.output;else{let n=null;for(let r=0;r<e.sourceLayer.inboundNodes.length;++r)for(let a of e.sourceLayer.inboundNodes[r].outputTensors)if(a.id===e.id){n=r;break}t=e.sourceLayer.getOutputAt(n)}return t}var Yr=class extends Ze{constructor(e){super({});if(this.containerNodes=new Set,this.name=e.name,this.name==null){let y=this.getClassName().toLowerCase();this.name=qp(y)}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],Ka(this.inputs).length!==this.inputs.length)throw new V(`The list of inputs passed to the model is redundant. All inputs should only appear once. Found: ${this.inputs.map(y=>y.name)}`);Ka(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(y=>y.name)}`),this.inputLayers=[],this.inputLayersNodeIndices=[],this.inputLayersTensorIndices=[],this.outputLayers=[],this.outputLayersNodeIndices=[],this.outputLayersTensorIndices=[],this.layers=[],this.internalContainerRefs=[];for(let y of this.outputs){let g=y.sourceLayer,b=y.nodeIndex,_=y.tensorIndex;this.outputLayers.push(g),this.outputLayersNodeIndices.push(b),this.outputLayersTensorIndices.push(_)}for(let y of this.inputs){let g=y.sourceLayer,b=y.nodeIndex,_=y.tensorIndex;qr(b===0,"input layer has >1 nodes"),qr(_===0,"input layer has >1 tensors"),this.inputLayers.push(g),this.inputLayersNodeIndices.push(b),this.inputLayersTensorIndices.push(_)}this.inputNames=[],this.outputNames=[],this.feedInputShapes=[],this.feedInputNames=[],this.feedOutputNames=[];for(let y=0;y<this.inputLayers.length;y++){let g=this.inputLayers[y];if(!(g instanceof Gl))throw new TypeError(`Input layers to a LayersModel must be InputLayer objects. Received inputs: ${e.inputs}. Input ${y} (0-based) originates from layer type ${g.getClassName()}.`);this.inputNames.push(g.name),this.feedInputShapes.push(g.batchInputShape),this.feedInputNames.push(g.name)}for(let y of this.outputLayers)this.outputNames.push(y.name);this.internalInputShapes=this.inputs.map(y=>y.shape),this.internalOutputShapes=this.outputs.map(y=>y.shape);let t={},n={},r={},a={},s={},i=[],o=(y,g,b,_,w,x)=>{(_==null||w==null||x==null)&&(_=y.sourceLayer,w=y.nodeIndex,x=y.tensorIndex);let N=_.inboundNodes[w];if(b.indexOf(N)!==-1)throw new Tr(`The tensor ${y.name} at layer "${_.name}" is part of a cycle.`);if(g.indexOf(N)!==-1)return;this.containerNodes.add(Yr.nodeKey(_,w)),_.id in s||(s[_.id]=Object.keys(s).length),b.indexOf(N)===-1&&b.push(N);let S=N.inboundLayers.length;for(let T=0;T<S;T++){let M=N.inputTensors[T],D=N.inboundLayers[T],z=N.nodeIndices[T],W=N.tensorIndices[T];o(M,g,b,D,z,W)}for(g.push(N);b.indexOf(N)>=0;)b.splice(b.indexOf(N),1);i.push(N)},l=[],u=[];for(let y of this.outputs)o(y,l,u);let c=i.slice().reverse();for(let y of c){n[y.id]=y,y.id in t||(t[y.id]=0);let g=t[y.id],b=r[y.outboundLayer.id]==null?0:r[y.outboundLayer.id];g=Math.max(g,b),r[y.outboundLayer.id]=g,a[y.outboundLayer.id]=y.outboundLayer,t[y.id]=g;for(let _=0;_<y.inboundLayers.length;_++){let w=y.inboundLayers[_],x=y.nodeIndices[_],N=w.inboundNodes[x],S=t[N.id]==null?0:t[N.id];t[N.id]=Math.max(g+1,S),n[N.id]=N}}let h={};for(let y in t){let g=t[y];g in h||(h[g]=[]),h[g].push(n[y])}let d={};for(let y in r){let g=r[y];g in d||(d[g]=[]),d[g].push(a[y])}let p=Object.keys(d).map(y=>parseInt(y,10)).sort(Op);this.layers=[];for(let y of p){let g=d[y];g.sort((b,_)=>{let w=s[b.id],x=s[_.id];return w<x?-1:w>x?1:0});for(let b of g)b instanceof Yr&&this.internalContainerRefs.push(b),this.layers.push(b)}this.layersByDepth=d,p=Object.keys(h).map(y=>parseInt(y,10)).sort(Op);let f=this.inputs.slice(),m=[];for(let y of p)for(let g of h[y]){let b=g.outboundLayer;if(b!=null){for(let _ of g.inputTensors)if(f.indexOf(_)===-1)throw new Tr(`Graph disconnected: cannot obtain value for tensor ${_} at layer "${b.name}". The following previous layers were accessed without issue: ${m}`);for(let _ of g.outputTensors)f.push(_);m.push(b.name)}}this.nodesByDepth=h;let A=this.layers.map(y=>y.name);for(let y of A){let g=A.filter(b=>b===y).length;if(g!==1)throw new Tr(`The name "${y}" is used ${g} times in the model. All layer names should be unique. Layer names: `+JSON.stringify(A))}this.outboundNodes=[],this.inboundNodes=[],new Zp({outboundLayer:this,inboundLayers:[],nodeIndices:[],tensorIndices:[],inputTensors:this.inputs,outputTensors:this.outputs,inputMasks:this.inputs.map(y=>null),outputMasks:this.outputs.map(y=>null),inputShapes:this.inputs.map(y=>y.shape),outputShapes:this.outputs.map(y=>y.shape)}),this.built=!0,this._refCount=1}assertNotDisposed(){if(this._refCount===0)throw new Error(`Container '${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 V("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={},r=0;for(let s of this.layers)for(let i of s.weights){if(n[i.originalName]!=null)throw new V(`Duplicate weight name: ${i.originalName}`);n[i.originalName]=i,r++}let a=[];for(let s in e){let i=s;if(n[s]==null){let o=s.split("/");i=o.slice(0,-2).concat([o[o.length-1]]).join("/")}if(n[i]!=null)a.push([n[i],e[s]]);else if(t)throw new V(`Provided weight data has no target variable: ${s}`);delete n[i]}if(t){let s=[];for(let i in n)s.push(i);if(s.length>0)throw new V(`${s.length} of ${r} weights are not set: ${s}`)}JA(a)}updatedConfig(){let e=this.getConfig(),t={};return t.className=this.getClassName(),t.config=e,t.kerasVersion=`tfjs-layers ${iy}`,t.backend="TensorFlow.js",t}toJSON(e,t=!0){let n=sy(this.updatedConfig());return t?JSON.stringify(n):n}call(e,t){return B(()=>{e=yt(e);let n=new Oi;for(let r=0;r<this.inputs.length;++r)n.add(this.inputs[r],e[r]);return zc(this.outputs,n,t)})}computeMask(e,t){return B(()=>{e=yt(e);let n;return t==null?n=Ci(null,e.length):n=yt(t),this.runInternalGraph(e,n)[1]})}computeOutputShape(e){let t=Xp(e);if(t.length!==this.inputLayers.length)throw new V(`Invalid inputShape argument ${e}: model has ${this.inputLayers.length} tensor inputs.`);let n={};for(let i=0;i<t.length;i++){let o=this.inputLayers[i],l=t[i],u=o.name+"_0_0";n[u]=l}let r=Object.keys(this.nodesByDepth).map(i=>parseInt(i,10)).sort(Op);if(r.length>1)for(let i of r){let o=this.nodesByDepth[i];for(let l of o){let u=l.outboundLayer;if(this.inputLayers.map(f=>f.id).indexOf(u.id)!==-1)continue;let c=[];for(let f=0;f<l.inboundLayers.length;f++){let m=l.inboundLayers[f],A=l.nodeIndices[f],y=l.tensorIndices[f],g=`${m.name}_${A}_${y}`,b=n[g];c.push(b)}let h=u.computeOutputShape(Fn(c)),d=Xp(h),p=u.inboundNodes.indexOf(l);for(let f=0;f<d.length;f++){let m=`${u.name}_${p}_${f}`;n[m]=d[f]}}}let a=[],s=[];for(let i=0;i<this.outputLayers.length;i++){let o=this.outputLayers[i],l=this.outputLayersNodeIndices[i],u=this.outputLayersTensorIndices[i],c=`${o.name}_${l}_${u}`;s.push(c)}for(let i=0;i<s.length;i++){let o=s[i];qr(o in n),a.push(n[o])}return Fn(a)}runInternalGraph(e,t){t==null&&(t=Ci(null,e.length));let n={};for(let o=0;o<this.inputs.length;++o){let l=this.inputs[o],u=e[o],c=t[o];n[l.id]=[u,c]}let r=Object.keys(this.nodesByDepth).map(o=>parseInt(o,10)).sort(Op);for(let o of r){let l=this.nodesByDepth[o];for(let u of l){let c=u.outboundLayer,h=u.inputTensors,d=u.outputTensors,p=new Array;for(let f of h)f.id in n&&p.push(n[f.id]);if(p.length===h.length){let f={},m,A,y,g;if(u.callArgs!=null&&(f=u.callArgs),p.length===1){let[b,_]=p[0];f.mask==null&&(f.mask=_),y=yt(c.call(b,f)),g=yt(c.computeMask(b,_)),m=[b],A=[_]}else m=p.map(b=>b[0]),A=p.map(b=>b[1]),f.mask==null&&(f.mask=A),y=yt(c.call(m,f)),g=yt(c.computeMask(m,A));if(c.activityRegularizer)throw new Pe("LayersModel invocation with concrete Tensor value(s) in the presence of activity regularizer(s) is not supported yet.");for(let b=0;b<d.length;++b){let _=d[b],w=y[b],x=g[b];n[_.id]=[w,x]}}}}let a=[],s=[],i=[];for(let o of this.outputs){qr(o.id in n,`Could not compute output ${o.name} : ${o.id}`);let[l,u]=n[o.id];i.push(l.shape),a.push(l),s.push(u)}return[a,s,i]}buildNodeConversionMap(e){let t={},n;for(let r of this.layers){n=r instanceof Yr?1:0;for(let a=0;a<r.inboundNodes.length;a++){let s=Yr.nodeKey(r,a);this.containerNodes.has(s)&&(t[s]=n,n+=1)}}return t}getLayer(e,t){if(t!=null){if(this.layers.length<=t)throw new V(`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 V("Provide either a layer name or layer index");for(let n of this.layers)if(n.name===e)return n;throw new V(`No such layer: ${e}`)}calculateLosses(){return B(()=>{let e=[];for(let t of this.layers)for(let n=0;n<t.inboundNodes.length;++n){let r=Yr.nodeKey(t,n);this.containerNodes.has(r)&&e.push(...t.calculateLosses())}return e})}getConfig(){let e={name:this.name},t=this.buildNodeConversionMap(this.layers),n=[];for(let s of this.layers){let i=s.getClassName(),o=s.getConfig(),l=[];for(let c=0;c<s.inboundNodes.length;c++){let h=s.inboundNodes[c],d=Yr.nodeKey(s,c),p={};if(this.containerNodes.has(d)){if(h.callArgs)try{JSON.stringify(h.callArgs),p=h.callArgs}catch(f){console.warn(`Layer ${s.name} was passed non-serializable keyword arguments: ${h.callArgs}. They will not be included in the serialized model (and thus will be missing at deserialization time).`),p={}}if(h.inboundLayers.length>0){let f=[];for(let m=0;m<h.inboundLayers.length;m++){let A=h.inboundLayers[m],y=h.nodeIndices[m],g=h.tensorIndices[m],b=Yr.nodeKey(A,y),_=t[b];_==null&&(_=0),f.push([A.name,_,g,p])}l.push(f)}}}let u={};u.name=s.name,u.className=i,u.config=o,u.inboundNodes=l,n.push(u)}e.layers=n;let r=[];for(let s=0;s<this.inputLayers.length;s++){let i=this.inputLayers[s],o=this.inputLayersNodeIndices[s],l=Yr.nodeKey(i,o);if(!this.containerNodes.has(l))continue;let u=t[l];u==null&&(u=0);let c=this.inputLayersTensorIndices[s];r.push([i.name,u,c])}e.inputLayers=r;let a=[];for(let s=0;s<this.outputLayers.length;s++){let i=this.outputLayers[s],o=this.outputLayersNodeIndices[s],l=Yr.nodeKey(i,o);if(!this.containerNodes.has(l))continue;let u=t[l];u==null&&(u=0);let c=this.outputLayersTensorIndices[s];a.push([i.name,u,c])}return e.outputLayers=a,e}static fromConfig(e,t,n={},r=!1){let a={},s={};function i(m,A){m.name in s?s[m.name].push(A):s[m.name]=[A]}function o(m,A){let y=[],g;for(let b of A){let _=b[0],w=b[1],x=b[2];if(g=b[3]==null?{}:b[3],!(_ in a)){i(m,A);return}let N=a[_];if(N.inboundNodes.length<=w){i(m,A);return}let S=N.inboundNodes[w];y.push(S.outputTensors[x])}y.length>0&&m.apply(Fn(y),g)}function l(m){let A=m.name,y=Rr(m,t.customObjects!=null?t.customObjects:{});y.setFastWeightInitDuringBuild(r),a[A]=y,m.inboundNodes.forEach(g=>{if(!(g instanceof Array))throw new V(`Corrupted configuration, expected array for nodeData: ${g}`);i(y,g)})}let u=t.name,c=t.layers;for(let m of c)l(m);for(;!NQ(s);)for(let m of c){let A=a[m.name];if(A.name in s){let y=s[A.name];delete s[A.name];for(let g of y)o(A,g)}}let h=[],d=[],p=t.inputLayers;for(let m of p){let A=m[0],y=m[1],g=m[2];qr(A in a);let b=a[A].inboundNodes[y].outputTensors;h.push(b[g])}let f=t.outputLayers;for(let m of f){let A=m[0],y=m[1],g=m[2];qr(A in a);let b=a[A].inboundNodes[y].outputTensors;d.push(b[g])}return new e({inputs:h,outputs:d,name:u})}get stateful(){if(this._stateful)throw new V("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(){B(()=>{this.layers.forEach(e=>{e.stateful&&e.resetStates()})})}};function tne(e,t,n){let r=t.length;if(e==null||Array.isArray(e)&&e.length===0)return t.map(a=>null);if(r===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!==r)throw new Error(`Provided ${n} is an array of ${e.length} element(s), but the model has ${r} outputs. Make sure a set of weights is provided for each model output.`);return e}else if(typeof e=="object"&&Object.keys(e).length>0&&typeof e[Object.keys(e)[0]]=="object"){let a=[];return t.forEach(s=>{s in e?a.push(e[s]):a.push(null)}),a}else throw new Error(`The model has multiple (${r}) outputs, so ${n} must be either an array with ${r} elements or an object with ${t} keys. Provided ${n} not understood: ${JSON.stringify(e)}`)}function W7(e,t){return tne(e,t,"classWeight")}async function B7(e,t,n,r){if(t!=null||r!=null)throw new Error("Support sampleWeight is not implemented yet");if(n!=null){let a=B(()=>{if(e.shape.length===1)return e.clone();if(e.shape.length===2)if(e.shape[1]>1){let o=1;return e.argMax(o)}else{if(e.shape[1]===1)return e.reshape([e.shape[0]]);throw new Error(`Encountered unexpected last-dimension size (${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.`)}),s=Array.from(await a.data());Me(a);let i=[];return s.forEach(o=>{if(n[o]==null)throw new Error(`classWeight must contain all classes in the training data. The class ${o} exists in the data but not in classWeight`);i.push(n[o])}),hn(i,"float32")}else return null}function nne(e,t){return P(e,t)}var rne=32;function U7(e,t){let n,r,a=t;n=a.xs,r=a.ys,v.assert(n!=null&&r!=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 s=V7("input",e.inputNames,n),i=V7("output",e.outputNames,r),o=s[0].shape[0];v.assert(s.length===e.inputs.length,()=>`LayersModel has ${e.inputs.length} inputs, but the dataset provides ${s.length} inputs. (Expected input keys: ${JSON.stringify(e.inputNames)})`),v.assert(i.length===e.outputs.length,()=>`LayersModel has ${e.outputs.length} outputs, but the dataset provides ${i.length} outputs. (Expected output keys: ${JSON.stringify(e.outputNames)})`);for(let l=0;l<s.length;l++)v.assert(s[l].shape[0]===o,()=>`Batch size mismatch: input ${e.inputNames[l]} has ${s[l].shape[0]}; expected ${o} based on input ${e.inputNames[0]}.`);for(let l=0;l<i.length;l++)v.assert(i[l].shape[0]===o,()=>`Batch size mismatch: output ${e.outputNames[l]} has ${i[l].shape[0]}; expected ${o} based on input ${e.inputNames[0]}.`);return{xs:s,ys:i}}function V7(e,t,n){if(n instanceof Ge)return[n];if(Array.isArray(n))return v.assert(n.length===t.length,()=>`Received an array of ${n.length} Tensors, but expected ${t.length} to match the ${e} keys ${t}.`),n;{let r=[];for(let a of t){if(n[a]==null)throw new V(`The feature data generated by the dataset lacks the required ${e} key '${a}'.`);r.push(n[a])}return r}}function ane(e){if(e.length===3)throw new Pe("Validation with sample weights is not implemented yet.");return{xs:e[0],ys:e[1]}}async function ine(e,t,n){let r=n.batchesPerEpoch!=null;if(v.assert(e.optimizer!=null,()=>"You must compile a model before training/testing. Use LayersModel.compile(modelCompileConfig)."),v.assert(n!=null,()=>"For fitDataset(), the 2nd argument (config) is required, but it is not provided in this call."),v.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}`),v.assert(!r||n.batchesPerEpoch>0&&Number.isInteger(n.batchesPerEpoch),()=>`For fitDataset(), config.batchesPerEpoch is expected to be a positive integer if specified, but got ${n.batchesPerEpoch}`),v.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 a=n.validationData!=null,s,i;if(a)if(H7(n.validationData))v.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 A=ane(n.validationData);s=A.xs,i=A.ys}let o=e.makeTrainFunction(),l=e.getDedupedMetricsNames(),u;a?u=l.slice().concat(l.map(A=>"val_"+A)):u=l.slice();let c=T7(n.callbacks,n.yieldEvery),h=n.verbose==null?1:n.verbose,{callbackList:d,history:p}=E7(c,h,n.epochs,null,null,sne(t,n),null,a,u);d.setModel(e),e.history=p,await d.onTrainBegin(),e.stopTraining_=!1;let f=n.initialEpoch==null?0:n.initialEpoch,m=await t.iterator();for(;f<n.epochs;){let A={};await d.onEpochBegin(f);let y=0,g=0;for(r||(m=await t.iterator());r?y<n.batchesPerEpoch:!0;){let b=await m.next();if(r&&b.done){console.warn(`You provided \`batchesPerEpoch\` as ${n.batchesPerEpoch}, but your dataset iterator ran out of data after ${y} batches; interrupting training. Make sure that your dataset can generate at least \`batchesPerEpoch * epochs\` batches (in this case, ${n.batchesPerEpoch*n.epochs} batches). You may need to use the repeat() function when building your dataset.`);break}if(b.value!=null){let{xs:_,ys:w}=U7(e,b.value),x={};x.batch=g,x.size=_[0].shape[0],await d.onBatchBegin(g,x);let N=[];if(n.classWeight!=null){let M=W7(n.classWeight,e.outputNames);for(let D=0;D<M.length;++D)N.push(await B7(w[D],null,M[D]))}let S=_.concat(w).concat(N),T=o(S);Me(S);for(let M=0;M<l.length;++M){let D=l[M],z=T[M];x[D]=z,Zt(z)}await d.onBatchEnd(g,x),v7(x),g++,y++}if(r?y>=n.batchesPerEpoch:b.done){if(a){let _;H7(n.validationData)?_=yt(await e.evaluateDataset(n.validationData,{batches:n.validationBatches})):_=yt(e.evaluate(s,i,{batchSize:n.validationBatchSize==null?rne:n.validationBatchSize,verbose:0}));for(let w=0;w<e.metricsNames.length;++w)A[`val_${e.metricsNames[w]}`]=_[w]}break}if(e.stopTraining_)break}if(await d.onEpochEnd(f,A),f++,e.stopTraining_)break}return await d.onTrainEnd(),await e.history.syncData(),e.history}finally{e.isTraining=!1}}function sne(e,t){let n=null;return t.batchesPerEpoch!=null?n=t.batchesPerEpoch:Number.isFinite(e.size)&&(n=e.size),n}function H7(e){return typeof e.iterator=="function"}function one(e){return typeof e.next=="function"}async function lne(e,t,n){n=n||{};let r=n.batches!=null,a=e.testFunction,s=[];if(n.verbose>0)throw new Pe("Verbose mode is not implemented yet.");v.assert(!r||n.batches>0&&Number.isInteger(n.batches),()=>`Test loop expects \`batches\` to be a positive integer, but received ${JSON.stringify(n.batches)}`);let i=one(t)?t:await t.iterator(),o=0,l=0;for(;r?l<n.batches:!0;){let u=await i.next();if(s=B(()=>{if(u.value){let{xs:c,ys:h}=U7(e,u.value),d=c.concat(h),p=B(()=>a(d));if(Me(d),l===0)for(let m=0;m<p.length;++m)s.push(Ie(0));let f=d[0].shape[0];for(let m=0;m<p.length;++m){let A=p[m],y=s[m];s[m]=B(()=>ie(s[m],P(f,A))),l>0&&Me(y)}Me(p),o+=f,++l}return s}),u.done){r&&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<s.length;++u){let c=s[u];s[u]=be(s[u],o),Me(c)}return Fn(s)}function ly(e){v.assert(e>0&&Number.isInteger(e),()=>`batchSize is required to be a positive integer, but got ${e}`)}function Pc(e,t,n){return e==null?[null]:Array.isArray(e)?e.map(r=>$i(r,t,n-t)):$i(e,t,n-t)}function uy(e,t){return B(()=>e==null?null:Array.isArray(e)?e.map(n=>uy(n,t)):l7(e,t.dtype==="int32"?t:t.toInt()))}function cy(e,t){let n=[],r=0,a=null;for(;r<e;)a=r+t,a>=e&&(a=e),n.push([r,a]),r=a;return n}async function une(e,t,n,r,a,s,i,o,l,u,c,h,d,p,f){a==null&&(a=32),s==null&&(s=1),c==null&&(c=!0),d==null&&(d=0);let m=!1;if(l!=null&&u!=null&&(m=!0),f!=null&&(m=!0,p==null))throw new V("Can only use `validationSteps` when doing step-wise training, i.e., `stepsPerEpoch` must be set.");let A=e.checkNumSamples(n,a,p,"steps_per_epoch"),y;A!=null&&(y=Er(0,A)),i==null&&(i=1);let{callbackList:g,history:b}=E7(o,i,s,d,A,p,a,m,h);g.setModel(e),e.history=b,await g.onTrainBegin(),e.stopTraining_=!1;for(let _=d;_<s;++_){await g.onEpochBegin(_);let w={};if(p!=null)throw new Pe("stepsPerEpoch mode is not implemented yet.");{if(c==="batch")throw new Pe("batch shuffling is not implemneted yet");c&&v.shuffle(y);let x=hn(y),N=cy(A,a);for(let S=0;S<N.length;++S){let T={};if(await g.onBatchBegin(S,T),B(()=>{let M=N[S][0],D=N[S][1],z=$i(x,M,D-M);T.batch=S,T.size=D-M;let W=uy(n,z),U=t(W);for(let H=0;H<r.length;++H){let X=r[H],j=U[H];T[X]=j,Zt(j)}if(S===N.length-1&&m){let H=e.testLoop(l,u,a);for(let X=0;X<r.length;++X){let j=r[X],ee=H[X];Zt(ee),w["val_"+j]=ee}}}),await g.onBatchEnd(S,T),v7(T),e.stopTraining_)break}x.dispose()}if(await g.onEpochEnd(_,w),e.stopTraining_)break}return await g.onTrainEnd(),await e.history.syncData(),e.history}async function cne(e,t,n,r={}){if(e.isTraining)throw new Error("Cannot start training because another fit() call is ongoing.");e.isTraining=!0;let a,s,i,o,l,u,c;try{let h=r.batchSize==null?32:r.batchSize;ly(h);let d=!1,p=await e.standardizeUserData(t,n,r.sampleWeight,r.classWeight,d,h);a=p[0],s=p[1],c=p[2];let f=!1,m;if(r.validationData!=null&&r.validationData.length>0){if(f=!0,r.validationData.length===2)i=r.validationData[0],o=r.validationData[1];else throw r.validationData.length===3?new Pe("validationData including sample weights is not supported yet."):new V(`When passing validation data, it must contain 2 (valX, valY) or 3 (valX, valY, valSampleWeight) items; ${r.validationData} is invalid.`);let x=!0,N=await e.standardizeUserData(i,o,null,null,x,h);l=N[0],u=N[1],m=l.concat(u)}else if(r.validationSplit!=null&&r.validationSplit>0&&r.validationSplit<1){f=!0;let x=Math.floor(a[0].shape[0]*(1-r.validationSplit)),N=a[0].shape[0];l=Pc(a,x,N),a=Pc(a,0,x),u=Pc(s,x,N),s=Pc(s,0,x),m=l.concat(u)}else r.validationSteps!=null&&(f=!0);let A=a.concat(s).concat(c);e.checkTrainableWeightsConsistency();let y=e.makeTrainFunction(),g=e.getDedupedMetricsNames(),b,_;f?(e.makeTestFunction(),b=e.testFunction,_=g.slice().concat(g.map(x=>"val_"+x))):(b=null,m=[],_=g.slice());let w=T7(r.callbacks,r.yieldEvery);return await une(e,y,A,g,h,r.epochs,r.verbose,w,b,m,r.shuffle,_,r.initialEpoch,null,null)}finally{e.isTraining=!1,zi(a,t),zi(s,n),zi(l,i),zi(u,o),c!=null&&Me(c)}}function j7(e){let t=[];e instanceof Ge&&(e=[e]);for(let n=0;n<e.length;++n){let r=e[n];if(r.rank===1)t.push(Rc(r,1));else{if(r.rank===0)throw new Error("Expected tensor to be at least 1D, but received a 0D tensor (scalar).");t.push(r)}}return t}function zi(e,t){if(e==null)return;let n=[];if(t instanceof Ge)n.push(t.id);else if(Array.isArray(t))t.forEach(a=>n.push(a.id));else if(t!=null)for(let a in t){let s=t[a];n.push(s.id)}let r=[];if(e instanceof Ge)n.indexOf(e.id)===-1&&r.push(e);else if(Array.isArray(e))e.forEach(a=>{n.indexOf(a.id)===-1&&r.push(a)});else if(e!=null)for(let a in e){let s=e[a];n.indexOf(s.id)===-1&&r.push(s)}r.forEach(a=>{a.isDisposed||a.dispose()})}function hne(e){return e instanceof Ge}function hy(e){return Array.isArray(e)}function G7(e){return!hne(e)&&!hy(e)}function q7(e,t,n,r=!0,a=""){if(t==null||t.length===0){if(e!=null){let i=!1;if(hy(e)&&e.length>0)i=!0;else if(G7(e)){for(let o in e)if(e.hasOwnProperty(o)){i=!0;break}}else i=!0;if(i)throw new V(`Error when checking model ${a} expected no data, but got ${e}`)}return[]}if(e==null)return t.map(i=>null);let s;if(G7(e)){e=e,s=[];for(let i of t){if(e[i]==null)throw new V(`No data provided for "${i}". Need data for each key in: ${t}`);s.push(e[i])}}else if(hy(e)){if(e=e,e.length!==t.length)throw new V(`Error when checking model ${a}: 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}`);s=e}else{if(e=e,t.length>1)throw new V(`The model ${a} expects ${t.length} Tensor(s), but only received one Tensor. Found: Tensor with shape ${e.shape}`);s=[e]}if(s=j7(s),n!=null)for(let i=0;i<t.length;++i){if(n[i]==null)continue;let o=s[i];if(o.shape.length!==n[i].length)throw new V(`Error when checking ${a}: expected ${t[i]} to have ${n[i].length} dimension(s). but got array with shape ${o.shape}`);for(let l=0;l<n[i].length;++l){if(l===0&&!r)continue;let u=o.shape[l],c=n[i][l];if(c!=null&&c>=0&&u!==c)throw new V(`Error when checking ${a}: expected ${t[i]} to have shape [${n[i]}], but got array with shape [${o.shape}].`)}}return s}function dne(e,t,n){let r=Ka(e.map(s=>s.shape[0]));r.sort();let a=Ka(t.map(s=>s.shape[0]));if(a.sort(),r.length>1)throw new V(`All input Tensors (x) should have the same number of samples. Got array shapes: ${JSON.stringify(e.map(s=>s.shape))}`);if(a.length>1)throw new V(`All target Tensors (y) should have the same number of samples. Got array shapes: ${JSON.stringify(t.map(s=>s.shape))}`);if(r.length>0&&a.length>0&&!v.arraysEqual(r,a))throw new V(`Input Tensors should have the same number of samples as target Tensors. Found ${r[0]} input sample(s) and ${a[0]} target sample(s).`)}function pne(e,t,n){let r=[Di,e0,Dc];for(let a=0;a<e.length;++a){let s=e[a],i=t[a],o=n[a];if(i!=null){if(i===Dc&&s.shape[s.shape.length-1]===1)throw new V(`You are passing a target array of shape ${s.shape} while using a loss 'categorical_crossentropy'. 'categorical_crossentropy'expects targets to be binary matrices (1s and 0s) of shape [samples, classes].`);if(r.indexOf(i)!==-1){let l=s.shape.slice(1),u=o.slice(1);for(let c=0;c<l.length;++c){let h=l[c],d=u[c];if(d!=null&&h!==d)throw new V(`A target Tensor with shape ${s.shape} was passed for an output of shape ${o}, while using a loss function that expects targets to have the same shape as the output.`)}}}}}function X7(e,t,n,r=!0,a=""){let s;if(Array.isArray(e)){if(e.length!==t.length)throw new V(`Error when checking model ${a}: 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).`);s=e}else{if(t.length>1)throw new V(`The model expects ${t.length} ${a} Tensors, but only received one Tensor. Found: array with shape ${JSON.stringify(e.shape)}.`);s=[e]}if(n!=null)for(let i=0;i<t.length;++i){if(n[i]==null)continue;let o=s[i];if(o.shape.length!==n[i].length)throw new V(`Error when checking ${a}: expected ${t[i]} to have ${n[i].length} dimension(s), but got array with shape ${JSON.stringify(o.shape)}`);for(let l=0;l<n[i].length;++l){if(l===0&&!r)continue;let u=o.shape[l],c=n[i][l];if(c!=null&&c!==u)throw new V(`Error when checking ${a}: expected ${t[i]} to have shape ${JSON.stringify(n[i])} but got array with shape ${JSON.stringify(o.shape)}.`)}}}function fne(e,t){if(e==null||Array.isArray(e)&&e.length===0)return t.map(r=>[]);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: ${e}`);if(Array.isArray(n))return t.map(r=>n);{let r=[];for(let a of t){let s=n.hasOwnProperty(a)?n[a]:[];Array.isArray(s)||(s=[s]),r.push(s)}return r}}var mne="layers-model",ya=class extends Yr{constructor(e){super(e);this.isTraining=!1}summary(e,t,n=console.log){if(!this.built)throw new V("This model has never been called, thus its weights have not been created yet. So no summary can be displayed. Build the model first (e.g., by calling it on some test data).");Zte(this,e,t,n)}compile(e){if(e.loss==null&&(e.loss=[]),this.loss=e.loss,typeof e.optimizer=="string")this.optimizer_=jte(e.optimizer),this.isOptimizerOwned=!0;else{if(!(e.optimizer instanceof pa))throw new V("User-defined optimizer must be an instance of tf.Optimizer.");this.optimizer_=e.optimizer,this.isOptimizerOwned=!1}let t=[];if(!Array.isArray(e.loss)&&typeof e.loss!="string"&&typeof e.loss!="function"){e.loss=e.loss;for(let s in e.loss)if(this.outputNames.indexOf(s)===-1)throw new V(`Unknown entry in loss dictionary: "${s}". Only expected the following keys: ${this.outputNames}`);for(let s of this.outputNames)e.loss[s]==null&&console.warn(`Output "${s}" is missing from loss dictionary. We assume this was done on purpose, and we will not be expecting data to be passed to ${s} during training`),t.push(ey(e.loss[s]))}else if(Array.isArray(e.loss)){if(e.loss.length!==this.outputs.length)throw new V(`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(s=>ey(s))}else{let s=ey(e.loss);this.outputs.forEach(i=>{t.push(s)})}this.lossFunctions=t,this.feedOutputNames=[],this.feedOutputShapes=[],this.feedLossFns=[];for(let s=0;s<this.outputs.length;++s){let i=this.internalOutputShapes[s],o=this.outputNames[s];this.feedOutputNames.push(o),this.feedOutputShapes.push(i),this.feedLossFns.push(this.lossFunctions[s])}let n=[];this.metrics=e.metrics,this.metricsNames=["loss"],this.metricsTensors=[],Mi("loss",()=>{for(let s=0;s<this.outputs.length;++s){if(n.indexOf(s)!==-1)continue;let i=this.lossFunctions[s];this.outputs.length>1&&(this.metricsTensors.push([i,s]),this.metricsNames.push(this.outputNames[s]+"_loss"))}});let r=fne(e.metrics,this.outputNames),a=(s,i,o)=>{this.outputNames.length>1&&(i=this.outputNames[s]+"_"+i),this.metricsNames.push(i),this.metricsTensors.push([o,s])};Mi("metric",()=>{for(let s=0;s<this.outputs.length;++s){if(n.indexOf(s)!==-1)continue;let i=r[s];(o=>{let l="",u,c,h;for(let d of o){if(typeof d=="string"&&["accuracy","acc","crossentropy","ce"].indexOf(d)!==-1){let f=this.internalOutputShapes[s];f[f.length-1]===1||this.lossFunctions[s]===e0?["accuracy","acc"].indexOf(d)!==-1?c=ty:["crossentropy","ce"].indexOf(d)!==-1&&(c=F7):this.lossFunctions[s]===Qp?["accuracy","acc"].indexOf(d)!==-1?c=M7:["crossentropy","ce"].indexOf(d)!==-1&&(c=$7):["accuracy","acc"].indexOf(d)!==-1?c=ny:["crossentropy","ce"].indexOf(d)!==-1&&(c=ry);let m;["accuracy","acc"].indexOf(d)!==-1?m="acc":["crossentropy","ce"].indexOf(d)!==-1&&(m="ce"),h=c,u=l+m}else h=Hte(d),u=l+r0(d);let p;Mi(u,()=>{p=h}),a(s,u,p)}})(i)}}),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 r=n.batchSize==null?32:n.batchSize;ly(r);let a=!0,s=this.standardizeUserDataXY(e,t,a,r);try{let i=s[0].concat(s[1]);this.makeTestFunction();let o=this.testFunction,l=this.testLoop(o,i,r,n.verbose,n.steps);return Fn(l)}finally{zi(s[0],e),zi(s[1],t)}}async evaluateDataset(e,t){return this.makeTestFunction(),lne(this,e,t)}checkNumSamples(e,t,n,r="steps"){let a;if(n!=null){if(a=null,t!=null)throw new V(`If ${r} is set, batchSize must be null or undefined.Got batchSize = ${t}`)}else if(e!=null)Array.isArray(e)?a=e[0].shape[0]:a=e.shape[0];else throw new V(`Either the input data should have a defined shape, or ${r} shoud be specified.`);return a}execute(e,t){if(Array.isArray(t)&&t.length===0)throw new V("`outputs` is an empty Array, which is not allowed.");let n=Array.isArray(t),r=n?t:[t],a=this.retrieveSymbolicTensors(r),s=new Oi;if(e instanceof Ge&&(e=[e]),Array.isArray(e)){if(e.length!==this.inputs.length)throw new V(`The number of inputs provided (${e.length}) does not match the number of inputs of this model (${this.inputs.length}).`);for(let o=0;o<this.inputs.length;++o)s.add(this.inputs[o],e[o])}else for(let o of this.inputs){let l=e[o.name];if(l==null)throw new V(`No value is provided for the model's input ${o.name}`);s.add(o,l)}let i=zc(a,s);return n?i:i[0]}retrieveSymbolicTensors(e){let t=Ci(null,e.length),n=e.length;for(let r of this.layers){let a=Array.isArray(r.output)?r.output:[r.output],s=a.map(i=>i.name);for(let i=0;i<e.length;++i){let o=s.indexOf(e[i]);if(o!==-1&&(t[i]=a[o],n--),n===0)break}if(n===0)break}if(n>0){let r=[];throw t.forEach((a,s)=>{a==null&&r.push(e[s])}),new V(`Cannot find SymbolicTensors for output name(s): ${JSON.stringify(r)}`)}return t}predictLoop(e,t=32,n=!1){return B(()=>{let r=this.checkNumSamples(e);if(n)throw new Pe("Verbose predictLoop() is not implemented yet.");let a=cy(r,t),s=this.outputs.map(i=>[]);for(let i=0;i<a.length;++i)B(()=>{let o=a[i][0],l=a[i][1],u=Pc(e,o,l),c=[];if(Array.isArray(u))for(let d=0;d<u.length;++d)c.push({key:this.inputs[d],value:u[d]});else c.push({key:this.inputs[0],value:u});let h=new Oi(c);return zc(this.outputs,h)}).forEach((o,l)=>s[l].push(o));return Fn(s.map(i=>lt(i,0)))})}predict(e,t={}){let n=j7(e);X7(n,this.inputNames,this.feedInputShapes,!1);try{let r=t.batchSize==null?32:t.batchSize;return ly(r),this.predictLoop(n,r)}finally{zi(n,e)}}predictOnBatch(e){X7(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,r){if(this.optimizer_==null)throw new Tr("You must compile a model before training/testing. Use LayersModel.compile(modelCompileArgs).");let a=[];for(let s=0;s<this.feedOutputShapes.length;++s){let i=this.feedOutputShapes[s];this.feedLossFns[s]===Qp?a.push(i.slice(0,i.length-1).concat([1])):a.push(i)}if(e=q7(e,this.feedInputNames,this.feedInputShapes,!1,"input"),t=q7(t,this.feedOutputNames,a,!1,"target"),dne(e,t,null),pne(t,this.feedLossFns,this.feedOutputShapes),this.stateful&&r!=null&&r>0&&e[0].shape[0]%r!=0)throw new V(`In a stateful network, you should only pass inputs with a number of samples that is divisible by the batch size ${r}. Found: ${e[0].shape[0]} sample(s).`);return[e,t]}async standardizeUserData(e,t,n,r,a=!0,s){let[i,o]=this.standardizeUserDataXY(e,t,a,s);if(n!=null)throw new Error("sample weight is not supported yet.");let l=null;if(r!=null){let u=W7(r,this.outputNames);l=[];for(let c=0;c<u.length;++c)l.push(await B7(o[c],null,u[c]))}return[i,o,l]}testLoop(e,t,n,r=0,a){return B(()=>{let s=this.checkNumSamples(t,n,a,"steps"),i=[];if(r>0)throw new Pe("Verbose mode is not implemented yet.");if(a!=null)throw new Pe("steps mode in testLoop() is not implemented yet");{let o=cy(s,n),l=hn(Er(0,s));for(let u=0;u<o.length;++u){let c=o[u][0],h=o[u][1],d=$i(l,c,h-c),p=uy(t,d),f=e(p);if(u===0)for(let m=0;m<f.length;++m)i.push(Ie(0));for(let m=0;m<f.length;++m){let A=f[m];i[m]=ie(i[m],P(h-c,A))}}for(let u=0;u<i.length;++u)i[u]=be(i[u],s)}return i})}getDedupedMetricsNames(){let e=this.metricsNames,t=[];for(let n=0;n<e.length;++n){let r=e[n],a=r;K3(e,r)>1&&(a+=`_${K3(e.slice(0,n),r)}`),t.push(a)}return t}makeTrainFunction(){return e=>{let t=[],n=e.slice(0,this.inputs.length),r=e.slice(this.inputs.length,this.inputs.length+this.outputs.length),a=e.slice(this.inputs.length+this.outputs.length,this.inputs.length+this.outputs.length*2),s=[],i=()=>{let u=[];for(let p=0;p<this.inputs.length;++p)u.push({key:this.inputs[p],value:n[p]});let c=new Oi(u),h=zc(this.outputs,c,{training:!0}),d;for(let p=0;p<this.lossFunctions.length;++p){let f=this.lossFunctions[p](r[p],h[p]);a[p]!=null&&(f=nne(f,a[p]));let m=Tt(f);t.push(m),p===0?d=f:d=ie(d,f)}for(let p=0;p<this.metricsTensors.length;++p){let f;if(this.outputs.length>1&&p<this.outputs.length)f=t[p];else{let m=this.metricsTensors[p][0],A=this.metricsTensors[p][1];f=Tt(m(r[A],h[A]))}Zt(f),s.push(f)}return d=Tt(d),this.calculateLosses().forEach(p=>{d=ie(d,p)}),d},o=this.collectedTrainableWeights.map(u=>u.read()),l=!0;return[this.optimizer_.minimize(i,l,o)].concat(s)}}makeTestFunction(){this.testFunction=e=>B(()=>{let t=[],n,r=e.slice(0,this.inputs.length),a=e.slice(this.inputs.length,this.inputs.length+this.outputs.length),s=[];for(let l=0;l<this.inputs.length;++l)s.push({key:this.inputs[l],value:r[l]});let i=new Oi(s),o=zc(this.outputs,i);for(let l=0;l<this.lossFunctions.length;++l){let u=this.lossFunctions[l],c=Tt(u(a[l],o[l]));l===0?n=c:n=ie(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],h=Tt(u(a[c],o[c]));t.push(h)}return t})}async fit(e,t,n={}){return cne(this,e,t,n)}async fitDataset(e,t){return ine(this,e,t)}async trainOnBatch(e,t){let n=await this.standardizeUserData(e,t),r=n[0],a=n[1],s=this.makeTrainFunction()(r.concat(a)),i=[];for(let o of s){let l=await o.data();i.push(l[0])}return Me(s),Fn(i)}getNamedWeights(e){let t=[],n=e!=null&&e.trainableOnly,r=n?this.trainableWeights:this.weights,a=this.getWeights(n);for(let s=0;s<r.length;++s)n&&!r[s].trainable||t.push({name:r[s].originalName,tensor:a[s]});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=_d().numTensors;this.optimizer_.dispose(),e.numDisposedVariables+=t-_d().numTensors}return e}getLossIdentifiers(){let e;if(typeof this.loss=="string")e=Aa(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=>Aa(t))}else{let t=Object.keys(this.loss);e={};let n=this.loss;for(let r of t)if(typeof n[r]=="string")e[r]=Aa(n[r]);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[Aa(r0(this.metrics))];if(Array.isArray(this.metrics))return this.metrics.map(e=>Aa(r0(e)));{let e={};for(let t in this.metrics)e[t]=Aa(r0(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=Oc(e.optimizer_config),n=Rr(t),r;if(typeof e.loss=="string")r=Ri(e.loss);else if(Array.isArray(e.loss))r=e.loss.map(s=>Ri(s));else if(e.loss!=null){r={};for(let s in e.loss)r[s]=Ri(e.loss[s])}let a;if(Array.isArray(e.metrics))a=e.metrics.map(s=>Ri(s));else if(e.metrics!=null){a={};for(let s in e.metrics)a[s]=Ri(e.metrics[s])}this.compile({loss:r,metrics:a,optimizer:n})}async save(e,t){if(typeof e=="string"){let i=Nn.getSaveHandlers(e);if(i.length===0)throw new V(`Cannot find any save handlers for URL '${e}'`);if(i.length>1)throw new V(`Found more than one (${i.length}) save handlers for URL '${e}'`);e=i[0]}if(e.save==null)throw new V("LayersModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");let n=await Nn.encodeWeights(this.getNamedWeights(t)),r=!1,a=null,s={modelTopology:this.toJSON(a,r),format:mne,generatedBy:`TensorFlow.js tfjs-layers v${iy}`,convertedBy:null};if((t==null?!1:t.includeOptimizer)&&this.optimizer!=null){s.trainingConfig=this.getTrainingConfig();let i="optimizer",{data:o,specs:l}=await Nn.encodeWeights(await this.optimizer.getWeights(),i);n.specs.push(...l),n.data=Nn.concatenateArrayBuffers([n.data,o])}if(this.userDefinedMetadata!=null){let i=!0;O7(this.userDefinedMetadata,this.name,i),s.userDefinedMetadata=this.userDefinedMetadata}return s.weightData=n.data,s.weightSpecs=n.specs,e.save(s)}setUserDefinedMetadata(e){O7(e,this.name),this.userDefinedMetadata=e}getUserDefinedMetadata(){return this.userDefinedMetadata}};ya.className="Model";ae.registerClass(ya);var K7=class extends ya{};K7.className="Functional";ae.registerClass(K7);async function Ane(e,t){"modelTopology"in e||(e={modelTopology:e}),e=e;let n=e.modelTopology;n.model_config!=null&&(n=n.model_config);let r=Oc(n),a=Rr(r,t);if(e.weightsManifest!=null){let s=await Nn.loadWeights(e.weightsManifest,e.pathPrefix,a.weights.map(o=>o.originalName)),i={};for(let o of a.weights)i[o.originalName]=s[o.originalName];a.loadWeights(i),Me(s)}return a}async function gne(e,t){if(t==null&&(t={}),typeof e=="string"){let n=Nn.getLoadHandlers(e,t);if(n.length===0)n.push(Nn.browserHTTPRequest(e,t));else if(n.length>1)throw new V(`Found more than one (${n.length}) load handlers for URL '${e}'`);e=n[0]}return yne(e,void 0,t)}async function yne(e,t,n){if(n==null&&(n={}),e.load==null)throw new V("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");let r=await e.load(),a=r.modelTopology;a.model_config!=null&&(a=a.model_config);let s=n.strict==null?!0:n.strict,i=r.weightData!=null&&r.weightSpecs!=null&&s,o=Rr(Oc(a),t,i),l=r.trainingConfig;if(l!=null&&o.loadTrainingConfig(l),r.userDefinedMetadata!=null&&o.setUserDefinedMetadata(r.userDefinedMetadata),r.weightData!=null){if(r.weightSpecs==null)throw new V("LayersModel artifacts contains weight data, but not weight specs. Therefore loading of weights cannot proceed.");let{modelWeights:u,optimizerWeights:c}=xne(r.weightData,r.weightSpecs);o.loadWeights(u,s),o.optimizer!=null&&c.length>0&&await o.optimizer.setWeights(c),Me(u),Me(c.map(h=>h.tensor))}return o}function xne(e,t){let n=Nn.decodeWeights(e,t),r={},a=[];return t.forEach(s=>{s.group==="optimizer"?a.push({name:s.name,tensor:n[s.name]}):r[s.name]=n[s.name]}),{modelWeights:r,optimizerWeights:a}}var Kl=class extends ya{constructor(e){super({inputs:[],outputs:[]});if(e=e||{},this.trainable=!0,this.built=!1,this.name=e.name!=null?e.name:qp("sequential_"),e.layers!=null)for(let t of e.layers)this.add(t)}checkShape(e){if(e.inboundNodes[0].outputTensors[0].shape.some(t=>t<0))throw new V(`Negative dimension size caused by adding layer ${e.name} with input shape [${e.inboundNodes[0].inputTensors[0].shape}]`)}add(e){let t=e instanceof Kl||e instanceof ya,n;if(t){if(n=e,n.outputs.length!==1)throw new V("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 V("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 V("The first layer in a Sequential model must get an `inputShape` or `batchInputShape` argument.");let r=_7({batchShape:e.batchInputShape,dtype:e.dtype,name:e.name+"_input"});e.apply(r)}if(t)this.outputs=n.outputs,this.inputs=n.inputs;else{if(e.inboundNodes.length!==1)throw new V(`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 V("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=b7(this.outputs[0])}this.inboundNodes=[],new Zp({outboundLayer:this,inboundLayers:[],nodeIndices:[],tensorIndices:[],inputTensors:this.inputs,outputTensors:this.outputs,inputMasks:Ci(null,this.inputs.length),outputMasks:[null],inputShapes:this.inputs.map(r=>r.shape),outputShapes:this.outputs[0].shape})}else{let r=e.apply(this.outputs[0]);if(Array.isArray(r))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=[r],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(pt(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 ya({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 Tr("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 Tr("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 Tr("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 Tr("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={},r=!1){let a,s={};if(t instanceof Array){if(t[0].className==null||t[0].className==="Merge")throw new V("Legacy serialization format not supported yet.");a=t}else v.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."),a=t.layers,delete t.layers,s=t;let i=new e(s);if(!(i instanceof Kl))throw new Pe(`Sequential.fromConfig called on non-Sequential input: ${i}`);for(let o of a){let l=Rr(o,void 0,r);r&&l.setFastWeightInitDuringBuild(!0),i.add(l)}return i}set stopTraining(e){if(this.model==null)throw new V("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 V("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}}};Kl.className="Sequential";ae.registerClass(Kl);function wne(e){return new ya(e)}function bne(e){return new Kl(e)}function _ne(e,t){return t==null&&(t={}),gne(e,t)}function p7(e){return _7(e)}function vne(e,t){mr.registerCallbackConstructor(e,t)}var Un=class extends ae.Serializable{getConfig(){return{}}},Z7=class extends Un{apply(e,t=1){return tee(e,t)}};Z7.className="elu";ae.registerClass(Z7);var Y7=class extends Un{apply(e){return Bd(e)}};Y7.className="selu";ae.registerClass(Y7);var J7=class extends Un{apply(e){return Ur(e)}};J7.className="relu";ae.registerClass(J7);var Q7=class extends Un{apply(e){return B(()=>vl(6,Ur(e)))}};Q7.className="relu6";ae.registerClass(Q7);var ev=class extends Un{apply(e){return e}};ev.className="linear";ae.registerClass(ev);var tv=class extends Un{apply(e){return On(e)}};tv.className="sigmoid";ae.registerClass(tv);var nv=class extends Un{apply(e){return ree(e)}};nv.className="hardSigmoid";ae.registerClass(nv);var rv=class extends Un{apply(e){return bl(e)}};rv.className="softplus";ae.registerClass(rv);var av=class extends Un{apply(e){return nee(e)}};av.className="softsign";ae.registerClass(av);var sv=class extends Un{apply(e){return Al(e)}};sv.className="tanh";ae.registerClass(sv);var dy=class extends Un{apply(e,t=-1){return ic(e,t)}};dy.className="softmax";ae.registerClass(dy);var iv=class extends Un{apply(e,t=-1){return $d(e,t)}};iv.className="logSoftmax";ae.registerClass(iv);var ov=class extends Un{apply(e,t=1){return B(()=>On(e.mul(t)).mul(e))}};ov.className="swish";ae.registerClass(ov);function Qa(e){return e.getClassName()}function py(e,t={}){return Sc(e,ae.SerializationMap.getMap().classNameMap,t,"activation")}function es(e){if(e==null){let t={};return t.className="linear",t.config={},py(t)}if(typeof e=="string"){let t={};return t.className=e,t.config={},py(t)}else return e instanceof Un?e:py(e)}function fy(e){if(e!=null&&typeof e!="object")throw new Error(`Argument to L1L2 regularizer's constructor is expected to be an object, but received: ${e}`)}var lv=class extends ae.Serializable{},Lc=class extends lv{constructor(e){super();fy(e),this.l1=e==null||e.l1==null?.01:e.l1,this.l2=e==null||e.l2==null?.01:e.l2,this.hasL1=this.l1!==0,this.hasL2=this.l2!==0}apply(e){return B(()=>{let t=$t([1]);return this.hasL1&&(t=ie(t,Re(P(this.l1,Bt(e))))),this.hasL2&&(t=ie(t,Re(P(this.l2,Fc(e))))),t.asScalar()})}getConfig(){return{l1:this.l1,l2:this.l2}}static fromConfig(e,t){return new e({l1:t.l1,l2:t.l2})}};Lc.className="L1L2";ae.registerClass(Lc);function kne(e){return fy(e),new Lc({l1:e!=null?e.l1:null,l2:0})}function Ine(e){return fy(e),new Lc({l2:e!=null?e.l2:null,l1:0})}var uv={l1l2:"L1L2"};function ft(e){return TA(e)}function cv(e,t={}){return Sc(e,ae.SerializationMap.getMap().classNameMap,t,"regularizer")}function vt(e){if(e==null)return null;if(typeof e=="string"){let t={className:e in uv?uv[e]:e,config:{}};return cv(t)}else return e instanceof lv?e:cv(e)}var my=class extends Ze{constructor(e){super(e==null?{}:e);this.supportsMasking=!0,e!=null&&(this.maxValue=e.maxValue)}call(e,t){e=Be(e);let n=Ur(e);return this.maxValue!=null&&(n=Sn(n,0,this.maxValue)),n}computeOutputShape(e){return e}getConfig(){let e={maxValue:this.maxValue},t=super.getConfig();return Object.assign(e,t),e}};my.className="ReLU";ae.registerClass(my);var Ay=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=Be(e);return Qu(n,this.alpha)}computeOutputShape(e){return e}getConfig(){let e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}};Ay.className="LeakyReLU";ae.registerClass(Ay);var yy=class extends Ze{constructor(e){super(e==null?{}:e);if(this.DEFAULT_ALPHA_INITIALIZER="zeros",e==null&&(e={}),this.supportsMasking=!0,this.alphaInitializer=_t(e.alphaInitializer||this.DEFAULT_ALPHA_INITIALIZER),this.alphaRegularizer=vt(e.alphaRegularizer),this.alphaConstraint=Gt(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 V(`Expected sharedAxes to be a number or an array of numbers, but got ${e.sharedAxes}`)}build(e){e=pt(e);let t=e.slice(1);if(this.sharedAxes!=null)for(let r of this.sharedAxes)t[r-1]=1;this.alpha=this.addWeight("alpha",t,"float32",this.alphaInitializer,this.alphaRegularizer,!0,this.alphaConstraint);let n={};if(this.sharedAxes!=null)for(let r=1;r<e.length;++r)n[r]=e[r];this.inputSpec=[new Qt({ndim:e.length,axes:n})],this.built=!0}call(e,t){return e=Be(e),rc(e,this.alpha.read())}getConfig(){let e={alphaInitializer:Et(this.alphaInitializer),alphaRegularizer:ft(this.alphaRegularizer),alphaConstraint:jt(this.alphaConstraint),sharedAxes:this.sharedAxes},t=super.getConfig();return Object.assign(e,t),e}};yy.className="PReLU";ae.registerClass(yy);var gy=class extends Ze{constructor(e){super(e==null?{}:e);if(this.DEFAULT_ALPHA=1,e==null&&(e={}),e.alpha!=null&&e.alpha!==this.DEFAULT_ALPHA)throw new Pe(`Non-default alpha value (${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=Be(e);return xl(n)}computeOutputShape(e){return e}getConfig(){let e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}};gy.className="ELU";ae.registerClass(gy);var xy=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=Be(e);return n.mul(Cc(n.greater(this.theta),"float32"))}computeOutputShape(e){return e}getConfig(){let e={theta:this.theta},t=super.getConfig();return Object.assign(e,t),e}};xy.className="ThresholdedReLU";ae.registerClass(xy);var wy=class extends Ze{constructor(e){super(e==null?{}:e);this.DEFAULT_AXIS=1,e==null&&(e={}),this.softmax=new dy().apply,this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis}call(e,t){let n=Be(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}};wy.className="Softmax";ae.registerClass(wy);function Zl(e,t,n){if(typeof e=="number")return Ci(e,t);if(e.length!==t)throw new V(`The ${n} argument must be an integer or tuple of ${t} integers. Received: ${e.length} elements.`);for(let r=0;r<t;++r){let a=e[r];if(!YQ(a))throw new V(`The ${n} argument must be an integer or tuple of ${t} integers. Received: ${JSON.stringify(e)} including a non-integer number ${a}`)}return e}function Fr(e,t,n,r,a=1){if(e==null)return e;let s=t+(t-1)*(a-1),i;return n==="same"?i=e:i=e-s+1,Math.floor((i+r-1)/r)}function s0(e,t,n,r){if(e==null)return null;if(r==="valid")e=e*t+Ya([n-t,0]);else if(r==="same")e=e*t;else throw new V(`Unsupport padding mode: ${r}.`);return e}function by(e,t){return B(()=>(Ft(t),t==="channelsFirst"?ot(e,[0,2,3,1]):e))}function hv(e,t){return B(()=>(Ft(t),t==="channelsFirst"?ot(e,[0,2,3,4,1]):e))}function Nne(e,t,n,r=1,a="valid",s,i=1){return B(()=>{if(s==null&&(s=Sr()),Ft(s),e.shape.length!==3)throw new V(`The input of a conv1dWithBias operation should be 3, but is ${e.shape.length} instead.`);if(t.shape.length!==3)throw new V(`The kernel for a conv1dWithBias operation should be 3, but is ${t.shape.length} instead`);if(n!=null&&n.shape.length!==1)throw new V(`The bias for a conv1dWithBias operation should be 1, but is ${t.shape.length} instead`);if(s==="channelsFirst"&&(e=ot(e,[0,2,1])),a==="causal")throw new Pe("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");let o=Nd(e,t,r,a==="same"?"same":"valid","NWC",i);return n!=null&&(o=Kr(o,n)),o})}function dv(e,t,n,r=[1,1],a="valid",s,i,o=null){return B(()=>{if(s==null&&(s=Sr()),Ft(s),e.rank!==3&&e.rank!==4)throw new V(`conv2dWithBiasActivation expects input to be of rank 3 or 4, but received ${e.rank}.`);if(t.rank!==3&&t.rank!==4)throw new V(`conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received ${e.rank}.`);let l=by(e,s);if(a==="causal")throw new Pe("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return l=ja.conv2d({x:l,filter:t,strides:r,pad:a==="same"?"same":"valid",dilations:i,dataFormat:"NHWC",bias:n,activation:o}),s==="channelsFirst"&&(l=ot(l,[0,3,1,2])),l})}function Sne(e,t,n,r=[1,1,1],a="valid",s,i){return B(()=>{if(s==null&&(s=Sr()),Ft(s),e.rank!==4&&e.rank!==5)throw new V(`conv3dWithBias expects input to be of rank 4 or 5, but received ${e.rank}.`);if(t.rank!==4&&t.rank!==5)throw new V(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${e.rank}.`);let o=hv(e,s);if(a==="causal")throw new Pe("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return o=cm(o,t,r,a==="same"?"same":"valid","NDHWC",i),n!=null&&(o=Kr(o,n)),s==="channelsFirst"&&(o=ot(o,[0,4,1,2,3])),o})}var _y=class extends Ze{constructor(e,t){super(t);if(this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",_y.verifyArgs(t),this.rank=e,Jt(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new Pe(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=Zl(t.kernelSize,e,"kernelSize"),this.strides=Zl(t.strides==null?1:t.strides,e,"strides"),this.padding=t.padding==null?"valid":t.padding,nr(this.padding),this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Ft(this.dataFormat),this.activation=es(t.activation),this.useBias=t.useBias==null?!0:t.useBias,this.biasInitializer=_t(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=Gt(t.biasConstraint),this.biasRegularizer=vt(t.biasRegularizer),this.activityRegularizer=vt(t.activityRegularizer),this.dilationRate=Zl(t.dilationRate==null?1:t.dilationRate,e,"dilationRate"),this.rank===1&&Array.isArray(this.dilationRate)&&this.dilationRate.length!==1)throw new V(`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 V(`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 V(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(e){if(qr("kernelSize"in e,"required key 'kernelSize' not in config"),typeof e.kernelSize!="number"&&!CA(e.kernelSize,"number",1,3))throw new V(`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:Qa(this.activation),useBias:this.useBias,biasInitializer:Et(this.biasInitializer),biasRegularizer:ft(this.biasRegularizer),activityRegularizer:ft(this.activityRegularizer),biasConstraint:jt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}},Wc=class extends _y{constructor(e,t){super(e,t);this.kernel=null,Wc.verifyArgs(t),this.filters=t.filters,Jt(this.filters,"filters"),this.kernelInitializer=_t(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=Gt(t.kernelConstraint),this.kernelRegularizer=vt(t.kernelRegularizer)}build(e){e=pt(e);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new V(`The channel dimension of the input should be defined. Found ${e[t]}`);let n=e[t],r=this.kernelSize.concat([n,this.filters]);this.kernel=this.addWeight("kernel",r,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 B(()=>{e=Be(e);let n,r=this.bias==null?null:this.bias.read(),a=Y3(this.activation.getClassName());if(a!=null&&this.rank===2)n=dv(e,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate,a);else{if(this.rank===1)n=Nne(e,this.kernel.read(),r,this.strides[0],this.padding,this.dataFormat,this.dilationRate[0]);else if(this.rank===2)n=dv(e,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate);else if(this.rank===3)n=Sne(e,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate);else throw new Pe("convolutions greater than 3D are not implemented yet.");this.activation!=null&&(n=this.activation.apply(n))}return n})}computeOutputShape(e){e=pt(e);let t=[],n=this.dataFormat==="channelsLast"?e.slice(1,e.length-1):e.slice(2);for(let a=0;a<n.length;++a){let s=Fr(n[a],this.kernelSize[a],this.padding,this.strides[a],typeof this.dilationRate=="number"?this.dilationRate:this.dilationRate[a]);t.push(s)}let r=[e[0]];return this.dataFormat==="channelsLast"?(r=r.concat(t),r.push(this.filters)):(r.push(this.filters),r=r.concat(t)),r}getConfig(){let e={filters:this.filters,kernelInitializer:Et(this.kernelInitializer),kernelRegularizer:ft(this.kernelRegularizer),kernelConstraint:jt(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 V(`Convolution layer expected config.filters to be a 'number' > 0 but got ${JSON.stringify(e.filters)}`)}},Bc=class extends Wc{constructor(e){super(2,e);Bc.verifyArgs(e)}getConfig(){let e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!CA(e.kernelSize,"number",1,2))throw new V(`Conv2D expects config.kernelSize to be number or number[] with length 1 or 2, but received ${JSON.stringify(e.kernelSize)}.`)}};Bc.className="Conv2D";ae.registerClass(Bc);var i0=class extends Wc{constructor(e){super(3,e);i0.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 V(`Conv3D expects config.kernelSize to be number or [number, number, number], but received ${JSON.stringify(e.kernelSize)}.`)}};i0.className="Conv3D";ae.registerClass(i0);var vy=class extends Bc{constructor(e){super(e);if(this.inputSpec=[new Qt({ndim:4})],this.padding!=="same"&&this.padding!=="valid")throw new V(`Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=pt(e),e.length!==4)throw new V("Input should have rank 4; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new V("The channel dimension of the inputs should be defined. Found `None`.");let n=e[t],r=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",r,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new Qt({ndim:4,axes:{[t]:n}})],this.built=!0}call(e,t){return B(()=>{let n=Be(e);if(n.shape.length!==4)throw new V(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let r=n.shape,a=r[0],s,i;this.dataFormat==="channelsFirst"?(s=2,i=3):(s=1,i=2);let o=r[s],l=r[i],u=this.kernelSize[0],c=this.kernelSize[1],h=this.strides[0],d=this.strides[1],p=s0(o,h,u,this.padding),f=s0(l,d,c,this.padding),m=[a,p,f,this.filters];this.dataFormat!=="channelsLast"&&(n=ot(n,[0,2,3,1]));let A=Sd(n,this.kernel.read(),m,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(A=ot(A,[0,3,1,2])),this.bias!=null&&(A=Kr(A,this.bias.read(),this.dataFormat)),this.activation!=null&&(A=this.activation.apply(A)),A})}computeOutputShape(e){e=pt(e);let t=e.slice(),n,r,a;this.dataFormat==="channelsFirst"?(n=1,r=2,a=3):(n=3,r=1,a=2);let s=this.kernelSize[0],i=this.kernelSize[1],o=this.strides[0],l=this.strides[1];return t[n]=this.filters,t[r]=s0(t[r],o,s,this.padding),t[a]=s0(t[a],l,i,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};vy.className="Conv2DTranspose";ae.registerClass(vy);var pv=class extends Wc{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 V("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(t.kernelInitializer!=null||t.kernelRegularizer!=null||t.kernelConstraint!=null)throw new V("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 V(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(t.padding)}`);this.depthMultiplier=t.depthMultiplier==null?1:t.depthMultiplier,this.depthwiseInitializer=_t(t.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=vt(t.depthwiseRegularizer),this.depthwiseConstraint=Gt(t.depthwiseConstraint),this.pointwiseInitializer=_t(t.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=vt(t.pointwiseRegularizer),this.pointwiseConstraint=Gt(t.pointwiseConstraint)}build(e){if(e=pt(e),e.length<this.rank+2)throw new V(`Inputs to SeparableConv${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 V(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(e[t])}`);let n=e[t],r=this.kernelSize.concat([n,this.depthMultiplier]),a=[];for(let i=0;i<this.rank;++i)a.push(1);a.push(n*this.depthMultiplier,this.filters);let s=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",r,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,s,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",a,"float32",this.pointwiseInitializer,this.pointwiseRegularizer,s,this.pointwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,s,this.biasConstraint):this.bias=null,this.inputSpec=[new Qt({ndim:this.rank+2,axes:{[t]:n}})],this.built=!0}call(e,t){return B(()=>{e=Be(e);let n;if(this.rank===1)throw new Pe("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(e=ot(e,[0,2,3,1])),n=Tm(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(n=Kr(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),this.dataFormat==="channelsFirst"&&(n=ot(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=Et(this.depthwiseInitializer),e.pointwiseInitializer=Et(this.pointwiseInitializer),e.depthwiseRegularizer=ft(this.depthwiseRegularizer),e.pointwiseRegularizer=ft(this.pointwiseRegularizer),e.depthwiseConstraint=jt(this.depthwiseConstraint),e.pointwiseConstraint=jt(this.pointwiseConstraint),e}};pv.className="SeparableConv";var ky=class extends pv{constructor(e){super(2,e)}};ky.className="SeparableConv2D";ae.registerClass(ky);var o0=class extends Wc{constructor(e){super(1,e);o0.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"&&!CA(e.kernelSize,"number",1,1))throw new V(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(e.kernelSize)}.`)}};o0.className="Conv1D";ae.registerClass(o0);var Iy=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 B(()=>{if(e=Be(e),this.dataFormat==="channelsLast"){let n=zp(e,this.cropping[0][0],e.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return zp(n,this.cropping[1][0],e.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let n=zp(e,this.cropping[0][0],e.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return zp(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}};Iy.className="Cropping2D";ae.registerClass(Iy);var Ny=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,XQ(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 B(()=>{let n=Be(e),r=n.shape;if(this.dataFormat==="channelsFirst"){n=ot(n,[0,2,3,1]);let a=this.size[0]*r[2],s=this.size[1]*r[3],i=this.interpolation==="nearest"?n.resizeNearestNeighbor([a,s]):n.resizeBilinear([a,s]);return ot(i,[0,3,1,2])}else{let a=this.size[0]*r[1],s=this.size[1]*r[2];return this.interpolation==="nearest"?n.resizeNearestNeighbor([a,s]):n.resizeBilinear([a,s])}})}getConfig(){let e={size:this.size,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};Ny.className="UpSampling2D";ae.registerClass(Ny);function Tne(e,t,n=[1,1],r="valid",a,s){return B(()=>{a==null&&(a=Sr()),Ft(a);let i=by(e,a);if(e.rank!==4)throw new V(`Input for depthwiseConv2d is required to be 4-D, but is instead ${e.rank}-D`);if(t.rank!==4)throw new V(`depthwiseKernel is required to be 4-D, but is instead ${t.rank}-D`);return i=gl(i,t,n,r==="same"?"same":"valid","NHWC",s),a==="channelsFirst"&&(i=ot(i,[0,3,1,2])),i})}var Sy=class extends _y{constructor(e){super(2,e);this.depthwiseKernel=null,this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=_t(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=Gt(e.depthwiseConstraint),this.depthwiseRegularizer=vt(e.depthwiseRegularizer)}build(e){if(e=pt(e),e.length<4)throw new V(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(e)}.`);let t=this.dataFormat==="channelsFirst"?1:3;if(e[t]==null||e[t]<0)throw new V(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${e[t]}).`);let n=e[t],r=[this.kernelSize[0],this.kernelSize[1],n,this.depthMultiplier];this.depthwiseKernel=this.addWeight("depthwise_kernel",r,null,this.depthwiseInitializer,this.depthwiseRegularizer,!0,this.depthwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[n*this.depthMultiplier],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return B(()=>{e=Be(e);let n=Tne(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(n=Kr(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),n})}computeOutputShape(e){e=pt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],r=this.dataFormat==="channelsFirst"?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,a=Fr(t,this.kernelSize[0],this.padding,this.strides[0]),s=Fr(n,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[e[0],r,a,s]:[e[0],a,s,r]}getConfig(){let e=super.getConfig();return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=Et(this.depthwiseInitializer),e.depthwiseRegularizer=ft(this.depthwiseRegularizer),e.depthwiseConstraint=jt(this.depthwiseRegularizer),e}};Sy.className="DepthwiseConv2D";ae.registerClass(Sy);function fv(e,t,n,r){if(Array.isArray(e)){if(t!=null||n!=null)throw new V("When inputs is an array, neither initialState or constants should be provided");r!=null&&(n=e.slice(e.length-r,e.length),e=e.slice(0,e.length-r)),e.length>1&&(t=e.slice(1,e.length)),e=e[0]}function a(s){return s==null||Array.isArray(s)?s:[s]}return t=a(t),n=a(n),{inputs:e,initialState:t,constants:n}}function mv(e,t,n,r=!1,a,s,i=!1,o=!1){return B(()=>{let l=t.shape.length;if(l<3)throw new V(`Input should be at least 3D, but is ${l}D.`);let u=[1,0].concat(Er(2,l));if(t=ot(t,u),s!=null)throw new Pe("The rnn() functoin of the deeplearn.js backend does not support constants yet.");i&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),a!=null&&(a=a.asType("bool").asType("float32"),a.rank===l-1&&(a=mn(a,-1)),a=ot(a,u)),r&&(t=Ln(t,0),a!=null&&(a=Ln(a,0)));let c=[],h,d=n,p=t.shape[0],f=hr(t),m;a!=null&&(m=hr(a));for(let y=0;y<p;++y){let g=f[y],b=B(()=>e(g,d));if(a==null)h=b[0],d=b[1];else{let _=B(()=>{let w=m[y],x=Pn(w).sub(w),N=b[0].mul(w).add(d[0].mul(x)),S=d.map((T,M)=>b[1][M].mul(w).add(T.mul(x)));return{output:N,newStates:S}});h=_.output,d=_.newStates}o&&c.push(h)}let A;return o&&(A=An(c,1)),[h,A,d]})}var Zr=class extends Ze{constructor(e){super(e);let t;if(e.cell==null)throw new V("cell property is missing for the constructor of RNN.");if(Array.isArray(e.cell)?t=new l0({cells:e.cell}):t=e.cell,t.stateSize==null)throw new V("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 Qt({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 Er(0,e).map(t=>null)}else return this.states_}setStates(e){this.states_=e}computeOutputShape(e){ZA(e)&&(e=e[0]),e=e;let t=this.cell.stateSize;Array.isArray(t)||(t=[t]);let n=t[0],r;if(this.returnSequences?r=[e[0],e[1],n]:r=[e[0],n],this.returnState){let a=[];for(let s of t)a.push([e[0],s]);return[r].concat(a)}else return r}computeMask(e,t){return B(()=>{Array.isArray(t)&&(t=t[0]);let n=this.returnSequences?t:null;if(this.returnState){let r=this.states.map(a=>null);return[n].concat(r)}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 Pe("Constants support is not implemented in RNN yet.");ZA(e)&&(e=e[0]),e=e;let n=this.stateful?e[0]:null,r=e.slice(2);this.inputSpec[0]=new Qt({shape:[n,null,...r]});let a=[e[0]].concat(e.slice(2));if(t!=null)throw new Pe("Constants support is not implemented in RNN yet.");this.cell.build(a);let s;if(Array.isArray(this.cell.stateSize)?s=this.cell.stateSize:s=[this.cell.stateSize],this.stateSpec!=null){if(!v.arraysEqual(this.stateSpec.map(i=>i.shape[i.shape.length-1]),s))throw new V(`An initialState was passed that is not compatible with cell.stateSize. Received stateSpec=${this.stateSpec}; However cell.stateSize is ${this.cell.stateSize}`)}else this.stateSpec=s.map(i=>new Qt({shape:[null,i]}));this.stateful&&this.resetStates()}resetStates(e,t=!1){B(()=>{if(!this.stateful)throw new ma("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape[0];if(n==null)throw new V("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(this.states_==null)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(r=>$t([n,r])):this.states_=[$t([n,this.cell.stateSize])];else if(e==null)Me(this.states_),this.keptStates!=null&&(Me(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(r=>$t([n,r])):this.states_[0]=$t([n,this.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new V(`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()):Me(this.states_);for(let r=0;r<this.states_.length;++r){let a=e[r],s=Array.isArray(this.cell.stateSize)?this.cell.stateSize[r]:this.cell.stateSize,i=[n,s];if(!v.arraysEqual(a.shape,i))throw new V(`State ${r} is incompatible with layer ${this.name}: expected shape=${i}, received shape=${a.shape}`);this.states_[r]=a}}this.states_=this.states_.map(r=>Zt(r.clone()))})}apply(e,t){let n=t==null?null:t.initialState,r=t==null?null:t.constants;t==null&&(t={});let a=fv(e,n,r,this.numConstants);e=a.inputs,n=a.initialState,r=a.constants;let s=[],i=[];if(n!=null){t.initialState=n,s=s.concat(n),this.stateSpec=[];for(let o of n)this.stateSpec.push(new Qt({shape:o.shape}));i=i.concat(this.stateSpec)}if(r!=null&&(t.constants=r,s=s.concat(r),this.numConstants=r.length),s[0]instanceof Cr){let o=[e].concat(s),l=this.inputSpec.concat(i),u=this.inputSpec;this.inputSpec=l;let c=super.apply(o,t);return this.inputSpec=u,c}else return super.apply(e,t)}call(e,t){return B(()=>{let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;e=Be(e),a==null&&(this.stateful?a=this.states_:a=this.getInitialState(e));let s=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;if(a.length!==s)throw new V(`RNN Layer has ${s} state(s) but was passed ${a.length} initial state(s).`);this.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");let i={training:r},o=mv((d,p)=>{let f=this.cell.call([d].concat(p),i);return[f[0],f.slice(1)]},e,a,this.goBackwards,n,null,this.unroll,this.returnSequences),l=o[0],u=o[1],c=o[2];this.stateful&&this.resetStates(c,r);let h=this.returnSequences?u:l;return this.returnState?[h].concat(c):h})}getInitialState(e){return B(()=>{let t=$t(e.shape);return t=Re(t,[1,2]),t=Rc(t),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(n=>n>1?OA(t,[1,n]):t):this.cell.stateSize>1?[OA(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()===Zr.className&&(t.cell={className:this.cell.getClassName(),config:n}),Object.assign({},n,e,t)}static fromConfig(e,t,n={}){let r=t.cell,a=Rr(r,n);return new e(Object.assign(t,{cell:a}))}};Zr.className="RNN";ae.registerClass(Zr);var $c=class extends Ze{},u0=class extends $c{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,Jt(this.units,"units"),this.activation=es(e.activation==null?this.DEFAULT_ACTIVATION:e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=_t(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=_t(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=_t(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=vt(e.kernelRegularizer),this.recurrentRegularizer=vt(e.recurrentRegularizer),this.biasRegularizer=vt(e.biasRegularizer),this.kernelConstraint=Gt(e.kernelConstraint),this.recurrentConstraint=Gt(e.recurrentConstraint),this.biasConstraint=Gt(e.biasConstraint),this.dropout=jl([1,Ya([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=jl([1,Ya([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=pt(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 B(()=>{if(e=e,e.length!==2)throw new V(`SimpleRNNCell expects 2 input Tensors, got ${e.length}.`);let n=e[1];e=e[0];let r=t.training==null?!1:t.training;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=ts({ones:()=>Pn(e),rate:this.dropout,training:r})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=ts({ones:()=>Pn(n),rate:this.recurrentDropout,training:r}));let a,s=this.dropoutMask,i=this.recurrentDropoutMask;s!=null?a=Xr(P(e,s),this.kernel.read()):a=Xr(e,this.kernel.read()),this.bias!=null&&(a=Kr(a,this.bias.read())),i!=null&&(n=P(n,i));let o=ie(a,Xr(n,this.recurrentKernel.read()));return this.activation!=null&&(o=this.activation.apply(o)),[o,o]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Qa(this.activation),useBias:this.useBias,kernelInitializer:Et(this.kernelInitializer),recurrentInitializer:Et(this.recurrentInitializer),biasInitializer:Et(this.biasInitializer),kernelRegularizer:ft(this.kernelRegularizer),recurrentRegularizer:ft(this.recurrentRegularizer),biasRegularizer:ft(this.biasRegularizer),activityRegularizer:ft(this.activityRegularizer),kernelConstraint:jt(this.kernelConstraint),recurrentConstraint:jt(this.recurrentConstraint),biasConstraint:jt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign({},e,t)}};u0.className="SimpleRNNCell";ae.registerClass(u0);var Ty=class extends Zr{constructor(e){e.cell=new u0(e),super(e)}call(e,t){return B(()=>{this.cell.dropoutMask!=null&&(Me(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Me(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return new e(t)}};Ty.className="SimpleRNN";ae.registerClass(Ty);var c0=class extends $c{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 V("GRUCell does not support reset_after parameter set to true.");this.units=e.units,Jt(this.units,"units"),this.activation=es(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=es(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=_t(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=_t(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=_t(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=vt(e.kernelRegularizer),this.recurrentRegularizer=vt(e.recurrentRegularizer),this.biasRegularizer=vt(e.biasRegularizer),this.kernelConstraint=Gt(e.kernelConstraint),this.recurrentConstraint=Gt(e.recurrentConstraint),this.biasConstraint=Gt(e.biasConstraint),this.dropout=jl([1,Ya([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=jl([1,Ya([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=pt(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 B(()=>{if(e=e,e.length!==2)throw new V(`GRUCell expects 2 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training==null?!1:t.training,r=e[1];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=ts({ones:()=>Pn(e),rate:this.dropout,training:n,count:3})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=ts({ones:()=>Pn(r),rate:this.recurrentDropout,training:n,count:3}));let a=this.dropoutMask,s=this.recurrentDropoutMask,i,o,l;0<this.dropout&&this.dropout<1&&(e=P(e,a[0]));let u=Xr(e,this.kernel.read());this.useBias&&(u=Kr(u,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(r=P(r,s[0]));let c=this.recurrentKernel.read(),[h,d]=Ut(c,[2*this.units,this.units],c.rank-1),p=Xr(r,h),[f,m,A]=Ut(u,3,u.rank-1),[y,g]=Ut(p,2,p.rank-1);i=this.recurrentActivation.apply(ie(f,y)),o=this.recurrentActivation.apply(ie(m,g));let b=Xr(P(o,r),d);l=this.activation.apply(ie(A,b));let _=ie(P(i,r),P(ie(1,St(i)),l));return[_,_]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Qa(this.activation),recurrentActivation:Qa(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Et(this.kernelInitializer),recurrentInitializer:Et(this.recurrentInitializer),biasInitializer:Et(this.biasInitializer),kernelRegularizer:ft(this.kernelRegularizer),recurrentRegularizer:ft(this.recurrentRegularizer),biasRegularizer:ft(this.biasRegularizer),activityRegularizer:ft(this.activityRegularizer),kernelConstraint:jt(this.kernelConstraint),recurrentConstraint:jt(this.recurrentConstraint),biasConstraint:jt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign({},e,t)}};c0.className="GRUCell";ae.registerClass(c0);var Ey=class extends Zr{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 c0(e),super(e)}call(e,t){return B(()=>{this.cell.dropoutMask!=null&&(Me(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Me(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};Ey.className="GRU";ae.registerClass(Ey);var Vc=class extends $c{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,Jt(this.units,"units"),this.activation=es(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=es(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=_t(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=_t(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=_t(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.unitForgetBias=e.unitForgetBias,this.kernelRegularizer=vt(e.kernelRegularizer),this.recurrentRegularizer=vt(e.recurrentRegularizer),this.biasRegularizer=vt(e.biasRegularizer),this.kernelConstraint=Gt(e.kernelConstraint),this.recurrentConstraint=Gt(e.recurrentConstraint),this.biasConstraint=Gt(e.biasConstraint),this.dropout=jl([1,Ya([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=jl([1,Ya([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=pt(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 r;if(this.useBias){if(this.unitForgetBias){let a=this.biasInitializer,s=this.units;r=new(t=class extends fr{apply(i,o){let l=a.apply([s]),u=new Lp().apply([s]),c=a.apply([s*2]);return o7(o7(l,u),c)}},t.className="CustomInit",t)}else r=this.biasInitializer;this.bias=this.addWeight("bias",[this.units*4],null,r,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0}call(e,t){return B(()=>{let n=t.training==null?!1:t.training;if(e=e,e.length!==3)throw new V(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let r=e[1],a=e[2];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=ts({ones:()=>Pn(e),rate:this.dropout,training:n,count:4})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=ts({ones:()=>Pn(r),rate:this.recurrentDropout,training:n,count:4}));let s=this.dropoutMask,i=this.recurrentDropoutMask,o,l,u,c;0<this.dropout&&this.dropout<1&&(e=P(e,s[0]));let h=Xr(e,this.kernel.read());0<this.recurrentDropout&&this.recurrentDropout<1&&(r=P(r,i[0])),h=ie(h,Xr(r,this.recurrentKernel.read())),this.useBias&&(h=Kr(h,this.bias.read()));let[d,p,f,m]=Ut(h,4,h.rank-1);o=this.recurrentActivation.apply(d),l=this.recurrentActivation.apply(p),u=ie(P(l,a),P(o,this.activation.apply(f))),c=this.recurrentActivation.apply(m);let A=P(c,this.activation.apply(u));return[A,A,u]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Qa(this.activation),recurrentActivation:Qa(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Et(this.kernelInitializer),recurrentInitializer:Et(this.recurrentInitializer),biasInitializer:Et(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:ft(this.kernelRegularizer),recurrentRegularizer:ft(this.recurrentRegularizer),biasRegularizer:ft(this.biasRegularizer),activityRegularizer:ft(this.activityRegularizer),kernelConstraint:jt(this.kernelConstraint),recurrentConstraint:jt(this.recurrentConstraint),biasConstraint:jt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return Object.assign({},e,t)}};Vc.className="LSTMCell";ae.registerClass(Vc);var Cy=class extends Zr{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 Vc(e),super(e)}call(e,t){return B(()=>{this.cell.dropoutMask!=null&&(Me(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Me(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};Cy.className="LSTM";ae.registerClass(Cy);var l0=class extends $c{constructor(e){super(e);this.cells=e.cells}get stateSize(){let e=[];for(let t of this.cells.slice().reverse())Array.isArray(t.stateSize)?e.push(...t.stateSize):e.push(t.stateSize);return e}call(e,t){return B(()=>{e=e;let n=e.slice(1),r=[];for(let i of this.cells.slice().reverse())Array.isArray(i.stateSize)?r.push(n.splice(0,i.stateSize.length)):r.push(n.splice(0,1));r.reverse();let a=[],s;for(let i=0;i<this.cells.length;++i){let o=this.cells[i];n=r[i],i===0?s=[e[0]].concat(n):s=[s[0]].concat(n),s=o.call(s,t),a.push(s.slice(1))}n=[];for(let i of a.slice().reverse())n.push(...i);return[s[0]].concat(n)})}build(e){ZA(e)&&(e=e[0]),e=e;let t;this.cells.forEach((n,r)=>{Mi(`RNNCell_${r}`,()=>{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()}),n={cells:this.cells.map(t)};return Object.assign({},e,n)}static fromConfig(e,t,n={}){let r=[];for(let a of t.cells)r.push(Rr(a,n));return new e({cells:r})}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 YA(e)}setWeights(e){let t=[];for(let n of this.cells){let r=n.weights.length,a=e.splice(r);for(let s=0;s<n.weights.length;++s)t.push([n.weights[s],a[s]])}JA(t)}};l0.className="StackedRNNCells";ae.registerClass(l0);function ts(e){let{ones:t,rate:n,training:r=!1,count:a=1}=e,s=()=>u7(t(),n),i=()=>Mc(s,t,r);return!a||a<=1?Zt(i().clone()):Array(a).fill(void 0).map(i).map(o=>Zt(o.clone()))}var Ene=function(e,t){var n={};for(var r in e)Object.prototype.hasOwnProperty.call(e,r)&&t.indexOf(r)<0&&(n[r]=e[r]);if(e!=null&&typeof Object.getOwnPropertySymbols=="function")for(var a=0,r=Object.getOwnPropertySymbols(e);a<r.length;a++)t.indexOf(r[a])<0&&Object.prototype.propertyIsEnumerable.call(e,r[a])&&(n[r[a]]=e[r[a]]);return n},Av=class extends Zr{constructor(e){if(e.unroll)throw new Pe("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(e.cell))throw new Pe("It is not possible at the moment to stack convolutional cells.");super(e);this.inputSpec=[new Qt({ndim:5})]}call(e,t){return B(()=>{if(this.cell.dropoutMask!=null&&(Me(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Me(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),t&&t.constants)throw new V("ConvRNN2D cell does not support constants");let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}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 B(()=>{let{stateSize:t}=this.cell,n=e.shape,r=this.computeSingleOutputShape(n),a=[r[0],...r.slice(2)],s=$t(a);return Array.isArray(t)?Array(t.length).fill(s):[s]})}resetStates(e,t=!1){B(()=>{if(!this.stateful)throw new ma("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape,r=this.computeSingleOutputShape(n),a=[r[0],...r.slice(2)];if(n[0]==null)throw new V("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(this.getStates()==null)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>$t(a)):this.states_=[$t(a)];else if(e==null)Me(this.states_),this.keptStates!=null&&(Me(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>$t(a)):this.states_[0]=$t(a);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new V(`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()):Me(this.states_);for(let s=0;s<this.states_.length;++s){let i=e[s],o=a;if(!v.arraysEqual(i.shape,o))throw new V(`State ${s} is incompatible with layer ${this.name}: expected shape=${o}, received shape=${i.shape}`);this.states_[s]=i}}this.states_=this.states_.map(s=>Zt(s.clone()))})}computeSingleOutputShape(e){let{dataFormat:t,filters:n,kernelSize:r,padding:a,strides:s,dilationRate:i}=this.cell,o=t==="channelsFirst",l=e[o?3:2],u=e[o?4:3],c=Fr(l,r[0],a,s[0],i[0]),h=Fr(u,r[1],a,s[1],i[1]);return[...e.slice(0,2),...o?[n,c,h]:[c,h,n]]}};Av.className="ConvRNN2D";var h0=class extends Vc{constructor(e){let{filters:t,kernelSize:n,strides:r,padding:a,dataFormat:s,dilationRate:i}=e;super(Object.assign({},e,{units:t}));this.filters=t,Jt(this.filters,"filters"),this.kernelSize=Zl(n,2,"kernelSize"),this.kernelSize.forEach(o=>Jt(o,"kernelSize")),this.strides=Zl(r||1,2,"strides"),this.strides.forEach(o=>Jt(o,"strides")),this.padding=a||"valid",nr(this.padding),this.dataFormat=s||"channelsLast",Ft(this.dataFormat),this.dilationRate=Zl(i||1,2,"dilationRate"),this.dilationRate.forEach(o=>Jt(o,"dilationRate"))}build(e){var t;e=pt(e);let n=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[n]==null)throw new V(`The channel dimension of the input should be defined. Found ${e[n]}`);let r=e[n],a=4,s=this.kernelSize.concat([r,this.filters*a]);this.kernel=this.addWeight("kernel",s,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);let i=this.kernelSize.concat([this.filters,this.filters*a]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",i,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){let o;if(this.unitForgetBias){let l=this.biasInitializer,u=this.filters;o=new(t=class extends fr{apply(c,h){let d=l.apply([u]),p=Vr([u]),f=l.apply([u*2]);return PA([d,p,f])}},t.className="CustomInit",t)}else o=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*a],null,o,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(e,t){return B(()=>{if(e.length!==3)throw new V(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training||!1,r=e[0],a=e[1],s=e[2],i=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=ts({ones:()=>Pn(r),rate:this.dropout,training:n,count:i}));let o=this.dropoutMask,l=(Y,se,te)=>!se||!se[te]?Y:P(se[te],Y),u=l(r,o,0),c=l(r,o,1),h=l(r,o,2),d=l(r,o,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=ts({ones:()=>Pn(a),rate:this.recurrentDropout,training:n,count:i}));let p=this.recurrentDropoutMask,f=l(a,p,0),m=l(a,p,1),A=l(a,p,2),y=l(a,p,3),g=3,[b,_,w,x]=Ut(this.kernel.read(),i,g),[N,S,T,M]=this.useBias?Ut(this.bias.read(),i):[null,null,null,null];u=this.inputConv(u,b,N,this.padding),c=this.inputConv(c,_,S,this.padding),h=this.inputConv(h,w,T,this.padding),d=this.inputConv(d,x,M,this.padding);let[D,z,W,U]=Ut(this.recurrentKernel.read(),i,g);f=this.recurrentConv(f,D),m=this.recurrentConv(m,z),A=this.recurrentConv(A,W),y=this.recurrentConv(y,U);let H=this.recurrentActivation.apply(ie(u,f)),X=this.recurrentActivation.apply(ie(c,m)),j=ie(P(X,s),P(H,this.activation.apply(ie(h,A)))),ee=P(this.recurrentActivation.apply(ie(d,y)),this.activation.apply(j));return[ee,ee,j]})}getConfig(){let e=super.getConfig(),{units:t}=e,n=Ene(e,["units"]),r={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign({},n,r)}inputConv(e,t,n,r){let a=ua(e,t,this.strides,r||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return n?Kr(a,n,this.dataFormat):a}recurrentConv(e,t){return ua(e,t,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};h0.className="ConvLSTM2DCell";ae.registerClass(h0);var Ry=class extends Av{constructor(e){let t=new h0(e);super(Object.assign({},e,{cell:t}))}static fromConfig(e,t){return new e(t)}};Ry.className="ConvLSTM2D";ae.registerClass(Ry);var d0=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 r=0;r<this.noiseShape.length;++r)n.push(this.noiseShape[r]==null?t[r]:this.noiseShape[r]);return n}call(e,t){return B(()=>{this.invokeCallHook(e,t);let n=Be(e);if(0<this.rate&&this.rate<1){let r=t.training==null?!1:t.training,a=this.getNoiseShape(n);return Mc(()=>u7(n,this.rate,a,this.seed),()=>n,r)}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()}};d0.className="Dropout";ae.registerClass(d0);var Fy=class extends d0{constructor(e){super(e);this.inputSpec=[{ndim:3}]}getNoiseShape(e){let t=e.shape;return[t[0],1,t[2]]}};Fy.className="SpatialDropout1D";ae.registerClass(Fy);var My=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,Jt(this.units,"units"),this.activation=es(e.activation),e.useBias!=null&&(this.useBias=e.useBias),this.kernelInitializer=_t(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=_t(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=Gt(e.kernelConstraint),this.biasConstraint=Gt(e.biasConstraint),this.kernelRegularizer=vt(e.kernelRegularizer),this.biasRegularizer=vt(e.biasRegularizer),this.activityRegularizer=vt(e.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(e){e=pt(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=pt(e);let t=e.slice();return t[t.length-1]=this.units,t}call(e,t){return B(()=>{this.invokeCallHook(e,t);let n=Be(e),r=Y3(this.activation.getClassName()),a;return r!=null?a=Xr(n,this.kernel.read(),r,this.bias?this.bias.read():null):(a=Xr(n,this.kernel.read()),this.bias!=null&&(a=Kr(a,this.bias.read())),this.activation!=null&&(a=this.activation.apply(a))),a})}getConfig(){let e={units:this.units,activation:Qa(this.activation),useBias:this.useBias,kernelInitializer:Et(this.kernelInitializer),biasInitializer:Et(this.biasInitializer),kernelRegularizer:ft(this.kernelRegularizer),biasRegularizer:ft(this.biasRegularizer),activityRegularizer:ft(this.activityRegularizer),kernelConstraint:jt(this.kernelConstraint),biasConstraint:jt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}};My.className="Dense";ae.registerClass(My);var $y=class extends Ze{constructor(e){e=e||{},super(e),this.inputSpec=[{minNDim:3}],this.dataFormat=e.dataFormat}computeOutputShape(e){e=pt(e);for(let t of e.slice(1))if(t==null)throw new V(`The shape of the input to "Flatten" is not fully defined (got ${e.slice(1)}). Make sure to pass a complete "input_shape" or "batch_input_shape" argument to the first layer in your model.`);return[e[0],Za(e,1)]}call(e,t){return B(()=>{this.invokeCallHook(e,t);let n=Be(e);if(this.dataFormat==="channelsFirst"&&n.rank>1){let r=[0];for(let a=2;a<n.rank;++a)r.push(a);r.push(1),n=n.transpose(r)}return eee(n)})}getConfig(){let e={};this.dataFormat!=null&&(e.dataFormat=this.dataFormat);let t=super.getConfig();return Object.assign(e,t),e}};$y.className="Flatten";ae.registerClass($y);var Dy=class extends Ze{constructor(e){super(e);this.supportsMasking=!0,this.activation=es(e.activation)}call(e,t){return B(()=>{this.invokeCallHook(e,t);let n=Be(e);return this.activation.apply(n)})}getConfig(){let e={activation:Qa(this.activation)},t=super.getConfig();return Object.assign(e,t),e}};Dy.className="Activation";ae.registerClass(Dy);var Oy=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 B(()=>(e=Be(e),JQ(e,this.n)))}getConfig(){let e={n:this.n},t=super.getConfig();return Object.assign(e,t),e}};Oy.className="RepeatVector";ae.registerClass(Oy);var zy=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.",r=t.slice(),a=1,s=null;for(let o=0;o<r.length;++o){let l=r[o];if(this.isUnknown(l))if(s===null)s=o;else throw new V("Can only specifiy one unknown dimension.");else a*=l}let i=Za(e);if(s!==null){if(a===0||i%a!=0)throw new V(n);r[s]=i/a}else if(i!==a)throw new V(n);return r}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 B(()=>{this.invokeCallHook(e,t);let n=Be(e),r=n.shape,a=r.slice(0,1).concat(this.fixUnknownDimension(r.slice(1),this.targetShape));return n.reshape(a)})}getConfig(){let e={targetShape:this.targetShape},t=super.getConfig();return Object.assign(e,t),e}};zy.className="Reshape";ae.registerClass(zy);var Py=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=Er(1,e.dims.length+1);if(!v.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 Qt({ndim:this.dims.length+1})]}computeOutputShape(e){e=pt(e);let t=e.slice();return this.dims.forEach((n,r)=>{t[r+1]=e[n]}),t}call(e,t){return ot(Be(e),this.dimsIncludingBatch)}getConfig(){let e={dims:this.dims},t=super.getConfig();return Object.assign(e,t),e}};Py.className="Permute";ae.registerClass(Py);var Ly=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=Be(e),r=-1;return ju(xi(n,this.maskValue),r)}call(e,t){return B(()=>{this.invokeCallHook(e,t);let n=Be(e),r=-1,a=!0,s=ju(xi(n,this.maskValue),r,a);return n.mul(s.asType(n.dtype))})}};Ly.className="Masking";ae.registerClass(Ly);var Wy=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,Jt(this.inputDim,"inputDim"),this.outputDim=e.outputDim,Jt(this.outputDim,"outputDim"),this.embeddingsInitializer=_t(e.embeddingsInitializer||this.DEFAULT_EMBEDDINGS_INITIALIZER),this.embeddingsRegularizer=vt(e.embeddingsRegularizer),this.activityRegularizer=vt(e.activityRegularizer),this.embeddingsConstraint=Gt(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 B(()=>this.maskZero?(e=Be(e),xi(e,qe(e))):null)}computeOutputShape(e){if(e=pt(e),this.inputLength==null)return[...e,this.outputDim];let t=yt(this.inputLength);if(t.length!==e.length-1)throw new V(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);{let n=0;for(let r=0;r<t.length;++r){let a=t[r],s=e[r+1];if(a!=null&&s!=null&&a!==s)throw new V(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);a==null&&(t[n]=s),n++}}return[e[0],...t,this.outputDim]}call(e,t){return B(()=>{this.invokeCallHook(e,t);let n=Be(e);return n.dtype!=="int32"&&(n=Cc(n,"int32")),l7(this.embeddings.read(),n.as1D()).reshape(pt(this.computeOutputShape(n.shape)))})}getConfig(){let e={inputDim:this.inputDim,outputDim:this.outputDim,embeddingsInitializer:Et(this.embeddingsInitializer),embeddingsRegularizer:ft(this.embeddingsRegularizer),activityRegularizer:ft(this.activityRegularizer),embeddingsConstraint:jt(this.embeddingsConstraint),maskZero:this.maskZero,inputLength:this.inputLength},t=super.getConfig();return Object.assign(e,t),e}};Wy.className="Embedding";ae.registerClass(Wy);var Pi=class extends Ze{constructor(e){super(e||{});this.supportsMasking=!0}mergeFunction(e){throw new Pe}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 r=0;r<t.length;++r){let a=e[e.length-t.length+r],s=t[r];if(a==null||s==null||a<0||s<0)n.push(null);else if(a===1)n.push(s);else if(s===1)n.push(a);else{if(a!==s)throw new V("Operands could not be broadcast together with shapes "+JSON.stringify(e)+" "+JSON.stringify(t));n.push(a)}}return n}build(e){if(Array.isArray(e)&&!Array.isArray(e[0])&&(e=[pt(e)]),e=e,e.length<2)throw new V(`A merge layer should be called on an Array of at least 2 inputs. Got ${e.length} input(s).`);let t=[];for(let a of e)a!=null&&a[0]!==null&&t.push(a[0]);if(t=Ka(t),t.length>1)throw new V(`Can not merge tensors with different batch sizes. Got tensors with shapes: ${JSON.stringify(e)}.`);let n=e[0]==null?null:e[0].slice(1);for(let a=1;a<e.length;++a){let s=e[a]==null?null:e[a].slice(1);n=this.computeElementwiseOpOutputShape(n,s)}let r=e.map(a=>a.length);e.indexOf(null)===-1&&Ka(r).length===1?this.reshapeRequired=!1:this.reshapeRequired=!0}call(e,t){return B(()=>{if(e=e,this.reshapeRequired){let n=[],r=e.map(a=>a.rank);if(r.indexOf(null)===-1){let a=Ya(r);for(let s of e){let i=s.rank;for(let o=0;o<a-i;++o)s=Rc(s,1);n.push(s)}return this.mergeFunction(n)}else{let a=!1;for(let o of e){let l=o.rank;if(l==null){let u=o.shape,c=u[0],h=u.slice(1).concat([c]),d=o.reshape([c].concat(Za(u.slice(1))));d=ot(d,[1,0]),d=d.reshape(h),n.push(d),a=!0}else if(l>1){let u=Er(1,l).concat([0]);n.push(ot(o,u)),a=!0}else n.push(o)}let s=this.mergeFunction(n),i=s.rank;if(a){if(i==null){let o=s.shape,l=o.length,u=o[l-1],c=[u].concat(o.slice(0,o.length-1));s=ot(s.reshape([-1,u]),[1,0]).reshape(c)}else if(i>1){let o=[i-1].concat(Er(0,i-1));s=ot(s,o)}}return s}}else return this.mergeFunction(e)})}computeOutputShape(e){e=e;let t;e[0]==null?t=null:t=e[0].slice(1);for(let r=1;r<e.length;++r){let a=e[r]==null?null:e[r].slice(1);t=this.computeElementwiseOpOutputShape(t,a)}let n=[];for(let r of e)r!=null&&r[0]!==null&&n.push(r[0]);return n=Ka(n),n.length===1?t=n.concat(t):t=[null].concat(t),t}computeMask(e,t){return B(()=>{if(t==null)return null;if(!Array.isArray(t))throw new V("`mask` should be an Array");if(!Array.isArray(e))throw new V("`inputs` should be an Array");if(t.length!==e.length)throw new V(`The Array 'inputs' and 'mask' are expected to have the same length, but have different lengths (${e.length} vs ${t.length})`);if(t.every(r=>r==null))return null;t=t.map(r=>r==null?r:mn(r,0));let n=t[0];for(let r=1;r<t.length-1;++r)n=cr(n,t[r]);return n})}},By=class extends Pi{constructor(e){super(e)}mergeFunction(e){return B(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=ie(t,e[n]);return t})}};By.className="Add";ae.registerClass(By);var Vy=class extends Pi{constructor(e){super(e)}mergeFunction(e){return B(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=P(t,e[n]);return t})}};Vy.className="Multiply";ae.registerClass(Vy);var Uy=class extends Pi{constructor(e){super(e)}mergeFunction(e){return B(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=ie(t,e[n]);return P(1/e.length,t)})}};Uy.className="Average";ae.registerClass(Uy);var Hy=class extends Pi{constructor(e){super(e)}mergeFunction(e){return B(()=>{let t=e[0];for(let n=1;n<e.length;++n)t=Br(t,e[n]);return t})}};Hy.className="Maximum";ae.registerClass(Hy);var jy=class extends Pi{constructor(e){super(e)}mergeFunction(e){return B(()=>{let t=e[0];for(let n=1;n<e.length;++n)t=vl(t,e[n]);return t})}};jy.className="Minimum";ae.registerClass(jy);var Gy=class extends Pi{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 V("A `Concatenate` layer should be called on a list of at least 2 inputs");e=e;let t=!0;for(let r of e)if(r!=null){t=!1;break}if(t)return;let n=[];for(let r=0;r<e.length;++r){let a=e[r].slice();a.splice(this.axis,1);let s=!1;for(let i of n)if(v.arraysEqual(i,a)){s=!0;break}s||n.push(a)}if(n.length>1)throw new V("A `Concatenate` layer requires inputs with matching shapes except for the concat axis. Got input shapes: "+JSON.stringify(e))}mergeFunction(e){return B(()=>PA(e,this.axis))}computeOutputShape(e){if(!(Array.isArray(e)&&Array.isArray(e[0])))throw new V("A `Concatenate` layer should be called on a list of inputs.");let t=e,n=t[0].slice(),r=this.axis<0?n.length+this.axis:this.axis;for(let a of t.slice(1)){if(n[r]==null||a[r]==null){n[r]=null;break}n[r]+=a[r]}return n}computeMask(e,t){if(t==null)return null;if(!Array.isArray(t))throw new V("`mask` should be an array for Concatenate");if(!Array.isArray(e))throw new V("`inputs` should be an array for Concatenate");if(t.length!==e.length)throw new V(`Mismatch in the length of mask (${t.length}) and the legnth of inputs (${e.length})`);return B(()=>{let n=!0;if(t.forEach(s=>{if(s!=null){n=!1;return}}),n)return null;let r=[];for(let s=0;s<e.length;++s)t[s]==null?r.push(Pn(e[s]).asType("bool")):t[s].rank<e[s].rank?r.push(mn(t[s],-1)):r.push(t[s]);let a=lt(r,this.axis);return kd(a,-1,!1)})}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};Gy.className="Concatenate";ae.registerClass(Gy);function Uc(e,t){for(;e<0;)e+=t;return e}function Cne(e,t,n){if(e.shape.length>3||t.shape.length>3)throw new Pe("batchDot is not implemented for tensors of 4D or higher rank yet");if(v.assert(e.shape.length>=2,()=>`batchDot requires the rank of x to be >= 2, but got ${e.shape.length}`),v.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 Pe("batchDot is not implemented for complex64-type Tensors yet.");let r=e.shape.length,a=t.shape.length;n==null&&(n=[r-1,a-2]);let s=n;return B(()=>{let i;if(r>a){i=r-a;let l=[];for(let u=0;u<i;++u)l.push(1);t=t.reshape(t.shape.concat(l))}else if(a>r){i=a-r;let l=[];for(let u=0;u<i;++u)l.push(1);e=e.reshape(e.shape.concat(l))}else i=0;let o;if(e.shape.length===2&&t.shape.length===2)s[0]===s[1]?o=e.mul(t).sum(s[0]):o=e.transpose([1,0]).mul(t).sum(s[1]);else{let l=s[0]!==e.shape.length-1,u=s[1]===t.shape.length-1;o=e.matMul(t,l,u)}if(i>0){let l;r>a?l=r+a-3:l=r-1;let u=[];for(let c=l;c<l+i;++c)u.push(c);o=o.squeeze(u)}return o.shape.length===1&&(o=o.expandDims(1)),o})}var qy=class extends Pi{constructor(e){super(e);this.axes=e.axes,this.normalize=e.normalize==null?!1:e.normalize,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){v.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 Pe("Dot layer does not support tensors of 4D or higher rank yet.");let r=this.interpretAxes(t,n);if(t[r[0]]!==n[r[1]])throw new V(`Dimension incompatibility: ${t[r[0]]} !== ${n[r[1]]}`)}mergeFunction(e){if(e.length!==2)throw new V(`A \`Dot\` layer must be called on exactly 2 inputs, but received ${e.length} input(s).`);let t=e[0],n=e[1],r;return Array.isArray(this.axes)?r=this.axes.map((a,s)=>Uc(a,e[s].shape.length)):r=[Uc(this.axes,t.shape.length),Uc(this.axes,n.shape.length)],this.normalize&&(t=Yp(t,r[0]),n=Yp(n,r[1])),Cne(t,n,r)}interpretAxes(e,t){let n;return Array.isArray(this.axes)?n=this.axes:n=[Uc(this.axes,e.length),Uc(this.axes,t.length)],n}computeOutputShape(e){v.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 Pe("Dot layer does not support tensors of 4D or higher rank yet.");let r=this.interpretAxes(t,n);t.splice(r[0],1),n.splice(r[1],1),n.splice(0,1);let a=t.concat(n);return a.length===1&&a.push(1),a}computeMask(e,t){return null}getConfig(){let e={axes:this.axes,normalize:this.normalize},t=super.getConfig();return Object.assign(e,t),e}};qy.className="Dot";ae.registerClass(qy);var Xy=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 B(()=>{this.invokeCallHook(e,t);let n=Be(e);return Mc(()=>Pp(n.shape,0,this.stddev).add(n),()=>n,t.training||!1)})}};Xy.className="GaussianNoise";ae.registerClass(Xy);var Ky=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 B(()=>{this.invokeCallHook(e,t);let n=Be(e);return this.rate>0&&this.rate<1?Mc(()=>{let r=Math.sqrt(this.rate/(1-this.rate));return n.mul(Pp(n.shape,1,r))},()=>n,t.training||!1):n})}};Ky.className="GaussianDropout";ae.registerClass(Ky);var Zy=class extends Ze{constructor(e){super(e);this.supportsMasking=!0,this.rate=e.rate,this.noiseShape=e.noiseShape}_getNoiseShape(e){return this.noiseShape||Be(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 B(()=>{if(this.rate<1&&this.rate>0){let n=this._getNoiseShape(e);return Mc(()=>{let r=Be(e),a=1.6732632423543772,s=1.0507009873554805,i=-a*s,o=Ua(kl(n),this.rate);o=Cc(o,"float32");let l=((1-this.rate)*(1+this.rate*i**2))**-.5,u=-l*i*this.rate;return r.mul(o).add(o.add(-1).mul(i)).mul(l).add(u)},()=>Be(e),t.training||!1)}return e})}};Zy.className="AlphaDropout";ae.registerClass(Zy);function Hc(e,t,n,r,a,s=.001){let i;if(e.rank===2)i=ox(e,t,n,r,a,s);else if(e.rank===3)i=lx(e,t,n,r,a,s);else if(e.rank===4)i=ux(e,t,n,r,a,s);else throw new Pe(`batchNormalization is not implemented for array of rank ${e.rank} yet`);return i}function Rne(e,t,n,r,a=.001){return B(()=>{let s=Od(e,r),i=s.mean,o=s.variance;return[Hc(e,i,o,n,t,a),i,o]})}function Fne(e,t,n,r,a=.001){return B(()=>{let s=Od(e,r),i=s.mean,o=s.variance,l=[];for(let p of Er(0,e.rank))r.indexOf(p)!==-1?l.push(1):l.push(e.shape[p]);let u=i.reshape(l),c=o.reshape(l),h=t==null?null:t.reshape(l),d=n==null?null:n.reshape(l);return[Hc(e,u,c,d,h,a),i,o]})}function Mne(e,t,n,r,a=.001){return v.arraysEqual(r.slice().sort(),Er(0,e.rank-1))?Rne(e,t,n,r,a):Fne(e,t,n,r,a)}var Yy=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=_t(e.betaInitializer||"zeros"),this.gammaInitializer=_t(e.gammaInitializer||"ones"),this.movingMeanInitializer=_t(e.movingMeanInitializer||"zeros"),this.movingVarianceInitializer=_t(e.movingVarianceInitializer||"ones"),this.betaConstraint=Gt(e.betaConstraint),this.gammaConstraint=Gt(e.gammaConstraint),this.betaRegularizer=vt(e.betaRegularizer),this.gammaRegularizer=vt(e.gammaRegularizer)}build(e){e=pt(e);let t=this.axis>=0?this.axis:this.axis+e.length,n=e[t];if(n==null)throw new V(`Axis ${t} of input tensor should have a defined dimension but the layer received an input with shape ${JSON.stringify(e)}.`);this.inputSpec=[new Qt({ndim:e.length,axes:{[t]:n}})];let r=[n];this.scale&&(this.gamma=this.addWeight("gamma",r,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",r,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",r,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",r,null,this.movingVarianceInitializer,null,!1),this.built=!0}call(e,t){return B(()=>{let n=t.training==null?!1:t.training,r=Be(e),a=r.shape,s=a.length,i=Er(0,s),o=this.axis>=0?this.axis:this.axis+s;i.splice(o,1);let l=Ci(1,s);l[o]=a[o];let u=i.slice();u.sort();let c=!v.arraysEqual(u,Er(0,s).slice(0,s-1)),h=()=>{if(c){let A=this.movingMean.read().reshape(l),y=this.movingVariance.read().reshape(l),g=this.center?this.beta.read().reshape(l):null,b=this.scale?this.gamma.read().reshape(l):null;return Hc(r,A,y,g,b,this.epsilon)}else return Hc(r,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 h();let[d,p,f]=Mne(r,this.gamma.read(),this.beta.read(),i,this.epsilon),m=(A,y,g)=>{B(()=>{let b=1-g,_=A.read(),w=_.sub(y).mul(b);A.write(_.sub(w))})};return(()=>{m(this.movingMean,p,this.momentum),m(this.movingVariance,f,this.momentum)})(),d})}getConfig(){let e={axis:this.axis,momentum:this.momentum,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:Et(this.betaInitializer),gammaInitializer:Et(this.gammaInitializer),movingMeanInitializer:Et(this.movingMeanInitializer),movingVarianceInitializer:Et(this.movingVarianceInitializer),betaRegularizer:ft(this.betaRegularizer),gammaRegularizer:ft(this.gammaRegularizer),betaConstraint:jt(this.betaConstraint),gammaConstraint:jt(this.gammaConstraint)},t=super.getConfig();return Object.assign(e,t),e}};Yy.className="BatchNormalization";ae.registerClass(Yy);var Jy=class extends Ze{constructor(e){if(e==null&&(e={}),super(e),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=_t(e.betaInitializer||"zeros"),this.gammaInitializer=_t(e.gammaInitializer||"ones"),this.betaRegularizer=vt(e.betaRegularizer),this.gammaRegularizer=vt(e.gammaRegularizer),this.supportsMasking=!0}build(e){e=pt(e);let t=e.length;typeof this.axis=="number"&&(this.axis=[this.axis]);for(let a=0;a<this.axis.length;++a)this.axis[a]<0&&(this.axis[a]+=t);for(let a of this.axis)if(a<0||a>=t)throw new Error(`Invalid axis: ${a}`);if(this.axis.length!==Ka(this.axis).length)throw new Error(`Found duplicate axes in: ${this.axis}`);let n=this.axis.map(a=>e[a]),r=!0;this.scale?this.gamma=this.addWeight("gamma",n,"float32",this.gammaInitializer,this.gammaRegularizer,r):this.gamma=null,this.center?this.beta=this.addWeight("beta",n,"float32",this.betaInitializer,this.betaRegularizer,r):this.beta=null,this.built=!0}call(e,t){let n=Be(e),r=n.shape,a=r.length;return B(()=>{let s=!0,{mean:i,variance:o}=Od(n,this.axis,s),l=Ci(1,a);for(let f of this.axis)l[f]=r[f];let u=f=>f!=null&&f.shape.length!==a&&this.axis!==[a-1]?f.reshape(l):f,c=u(this.gamma.read()),h=u(this.beta.read()),d=[],p=[];for(let f=0;f<a;++f)this.axis.indexOf(f)!==-1?(d.push(r[f]),p.push(1)):(d.push(1),p.push(r[f]));return i=i.tile(d),o=o.tile(d),c=c.tile(p),h=h.tile(p),Hc(n,i,o,h,c,this.epsilon)})}getConfig(){let e={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:Et(this.betaInitializer),gammaInitializer:Et(this.gammaInitializer),betaRegularizer:ft(this.betaRegularizer),gammaRegularizer:ft(this.gammaRegularizer)},t=super.getConfig();return Object.assign(e,t),e}};Jy.className="LayerNormalization";ae.registerClass(Jy);function $ne(e,t,n){return B(()=>{if(e.rank!==4)throw new V(`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 V("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(n==null&&(n=Sr()),n!=="channelsLast"&&n!=="channelsFirst")throw new V(`Unknown data format: ${n}. Supported data formats are 'channelsLast' and 'channelsFirst.`);let r;return n==="channelsFirst"?r=[[0,0],[0,0],t[0],t[1]]:r=[[0,0],t[0],t[1],[0,0]],ca(e,r)})}var Qy=class extends Ze{constructor(e){if(e==null&&(e={}),super(e),this.dataFormat=e.dataFormat==null?Sr():e.dataFormat,e.padding==null)this.padding=[[1,1],[1,1]];else if(typeof e.padding=="number")this.padding=[[e.padding,e.padding],[e.padding,e.padding]];else{if(e.padding=e.padding,e.padding.length!==2)throw new V(`ZeroPadding2D expects padding to be a length-2 array, but received a length-${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 V(`ZeroPadding2D expects height padding to be a length-2 array, but received a length-${e.padding[0].length} array.`);if(t=e.padding[0],e.padding[1].length!==2)throw new V(`ZeroPadding2D expects width padding to be a length-2 array, but received a length-${e.padding[1].length} array.`);n=e.padding[1]}this.padding=[t,n]}this.inputSpec=[new Qt({ndim:4})]}computeOutputShape(e){e=pt(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 B(()=>$ne(Be(e),this.padding,this.dataFormat))}getConfig(){let e={padding:this.padding,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};Qy.className="ZeroPadding2D";ae.registerClass(Qy);function p0(e,t,n,r,a,s){return B(()=>{Ft(a),t7(s),nr(r),n==null&&(n=[1,1]),r==null&&(r="valid"),a==null&&(a=Sr()),s==null&&(s="max"),e=by(e,a);let i,o=r==="same"?"same":"valid";return s==="max"?i=tc(e,t,n,o):i=Xu(e,t,n,o),a==="channelsFirst"&&(i=ot(i,[0,3,1,2])),i})}function yv(e,t,n,r,a,s){return B(()=>{Ft(a),t7(s),nr(r),n==null&&(n=[1,1,1]),r==null&&(r="valid"),a==null&&(a=Sr()),s==null&&(s="max"),e=hv(e,a);let i,o=r==="same"?"same":"valid";return s==="max"?i=bm(e,t,n,o):i=om(e,t,n,o),a==="channelsFirst"&&(i=ot(i,[0,4,1,2,3])),i})}var gv=class extends Ze{constructor(e){if(e.poolSize==null&&(e.poolSize=2),super(e),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 V(`poolSize for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.poolSize)}`);if(Jt(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 V(`strides for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.strides)}`);Jt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,nr(this.padding),this.inputSpec=[new Qt({ndim:3})]}computeOutputShape(e){e=pt(e);let t=Fr(e[1],this.poolSize[0],this.padding,this.strides[0]);return[e[0],t,e[2]]}call(e,t){return B(()=>{this.invokeCallHook(e,t),e=Rc(Be(e),2);let n=this.poolingFunction(Be(e),[this.poolSize[0],1],[this.strides[0],1],this.padding,"channelsLast");return Ha(n,[2])})}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides},t=super.getConfig();return Object.assign(e,t),e}},eg=class extends gv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Ft(a),nr(r),p0(e,t,n,r,a,"max")}};eg.className="MaxPooling1D";ae.registerClass(eg);var tg=class extends gv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Ft(a),nr(r),p0(e,t,n,r,a,"avg")}};tg.className="AveragePooling1D";ae.registerClass(tg);var xv=class extends Ze{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2]),super(e),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 V(`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];Jt(this.poolSize,"poolSize"),Jt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Ft(this.dataFormat),nr(this.padding),this.inputSpec=[new Qt({ndim:4})]}computeOutputShape(e){e=pt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2];return t=Fr(t,this.poolSize[0],this.padding,this.strides[0]),n=Fr(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 B(()=>(this.invokeCallHook(e,t),this.poolingFunction(Be(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}},ng=class extends xv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Ft(a),nr(r),p0(e,t,n,r,a,"max")}};ng.className="MaxPooling2D";ae.registerClass(ng);var rg=class extends xv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Ft(a),nr(r),p0(e,t,n,r,a,"avg")}};rg.className="AveragePooling2D";ae.registerClass(rg);var wv=class extends Ze{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2,2]),super(e),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 V(`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];Jt(this.poolSize,"poolSize"),Jt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Ft(this.dataFormat),nr(this.padding),this.inputSpec=[new Qt({ndim:5})]}computeOutputShape(e){e=pt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],r=this.dataFormat==="channelsFirst"?e[4]:e[3];return t=Fr(t,this.poolSize[0],this.padding,this.strides[0]),n=Fr(n,this.poolSize[1],this.padding,this.strides[1]),r=Fr(r,this.poolSize[2],this.padding,this.strides[2]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n,r]:[e[0],t,n,r,e[4]]}call(e,t){return B(()=>(this.invokeCallHook(e,t),this.poolingFunction(Be(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}},ag=class extends wv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Ft(a),nr(r),yv(e,t,n,r,a,"max")}};ag.className="MaxPooling3D";ae.registerClass(ag);var sg=class extends wv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Ft(a),nr(r),yv(e,t,n,r,a,"avg")}};sg.className="AveragePooling3D";ae.registerClass(sg);var bv=class extends Ze{constructor(e){super(e);this.inputSpec=[new Qt({ndim:3})]}computeOutputShape(e){return[e[0],e[2]]}call(e,t){throw new Pe}},ig=class extends bv{constructor(e){super(e||{})}call(e,t){return B(()=>{let n=Be(e);return Tt(n,1)})}};ig.className="GlobalAveragePooling1D";ae.registerClass(ig);var og=class extends bv{constructor(e){super(e||{})}call(e,t){return B(()=>{let n=Be(e);return Qn(n,1)})}};og.className="GlobalMaxPooling1D";ae.registerClass(og);var _v=class extends Ze{constructor(e){super(e);this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Ft(this.dataFormat),this.inputSpec=[new Qt({ndim:4})]}computeOutputShape(e){return e=e,this.dataFormat==="channelsLast"?[e[0],e[3]]:[e[0],e[1]]}call(e,t){throw new Pe}getConfig(){let e={dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},lg=class extends _v{call(e,t){return B(()=>{let n=Be(e);return this.dataFormat==="channelsLast"?Tt(n,[1,2]):Tt(n,[2,3])})}};lg.className="GlobalAveragePooling2D";ae.registerClass(lg);var ug=class extends _v{call(e,t){return B(()=>{let n=Be(e);return this.dataFormat==="channelsLast"?Qn(n,[1,2]):Qn(n,[2,3])})}};ug.className="GlobalMaxPooling2D";ae.registerClass(ug);var vv=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 r=t.layer,a=Rr(r,n);delete t.layer;let s={layer:a};return Object.assign(s,t),new e(s)}},cg=class extends vv{constructor(e){super(e);this.supportsMasking=!0}build(e){if(e=pt(e),e.length<3)throw new V(`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=pt(e);let t=[e[0]].concat(e.slice(2)),n=this.layer.computeOutputShape(t),r=e[1];return[n[0],r].concat(n.slice(1))}call(e,t){return B(()=>(e=Be(e),mv((n,r)=>[Be(this.layer.call(n,t)),[]],e,[],!1,null,null,!1,!0)[1]))}};cg.className="TimeDistributed";ae.registerClass(cg);function Dne(e){Fi(qQ,"BidirectionalMergeMode",e)}var One="concat",hg=class extends vv{constructor(e){super(e);let t=e.layer.getConfig(),n={};n.className=e.layer.getClassName(),n.config=t,this.forwardLayer=Rr(n),t.goBackwards=t.goBackwards!==!0;let r={};if(r.className=e.layer.getClassName(),r.config=t,this.backwardLayer=Rr(r),this.forwardLayer.name="forward_"+this.forwardLayer.name,this.backwardLayer.name="backward_"+this.backwardLayer.name,this.mergeMode=e.mergeMode===void 0?One:e.mergeMode,Dne(this.mergeMode),e.weights)throw new Pe("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,r,a;return this.returnState&&(a=t.slice(1)),n=t[0],n=n,this.mergeMode==="concat"?(n[n.length-1]*=2,r=[n]):this.mergeMode==null?r=[n,n.slice()]:r=[n],this.returnState?this.mergeMode==null?r.concat(a).concat(a.slice()):[n].concat(a).concat(a.slice()):Fn(r)}apply(e,t){let n=t==null?null:t.initialState,r=t==null?null:t.constants;t==null&&(t={});let a=fv(e,n,r,this.numConstants);if(e=a.inputs,n=a.initialState,r=a.constants,Array.isArray(e)&&(n=e.slice(1),e=e[0]),(n==null||n.length===0)&&r==null)return super.apply(e,t);let s=[],i=[];if(n!=null){let l=n.length;if(l%2>0)throw new V("When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.");t.initialState=n,s.push(...n);let u=n.map(c=>new Qt({shape:c.shape}));this.forwardLayer.stateSpec=u.slice(0,l/2),this.backwardLayer.stateSpec=u.slice(l/2),i.push(...u)}if(r!=null)throw new Pe("Support for constants in Bidirectional layers is not implemented yet.");let o=s[0]instanceof Cr;for(let l of s)if(l instanceof Cr!==o)throw new V("The initial state of a Bidirectional layer cannot be specified as a mix of symbolic and non-symbolic tensors");if(o){let l=[e].concat(s),u=this.inputSpec.concat(i),c=this.inputSpec;this.inputSpec=u;let h=super.apply(l,t);return this.inputSpec=c,h}else return super.apply(e,t)}call(e,t){return B(()=>{let n=t.initialState,r,a;if(n==null)r=this.forwardLayer.call(e,t),a=this.backwardLayer.call(e,t);else{let o=n.slice(0,n.length/2),l=n.slice(n.length/2);r=this.forwardLayer.call(e,Object.assign(t,{initialState:o})),a=this.backwardLayer.call(e,Object.assign(t,{initialState:l}))}let s;this.returnState&&(Array.isArray(r)&&(s=r.slice(1).concat(a.slice(1))),r=r[0],a=a[0]),this.returnSequences&&(a=Ln(a,1));let i;return this.mergeMode==="concat"?i=PA([r,a]):this.mergeMode==="sum"?i=ie(r,a):this.mergeMode==="ave"?i=P(.5,ie(r,a)):this.mergeMode==="mul"?i=P(r,a):this.mergeMode==null&&(i=[r,a]),this.returnState?this.mergeMode==null?i.concat(s):[i].concat(s):i})}resetStates(e){this.forwardLayer.resetStates(),this.backwardLayer.resetStates()}build(e){Mi(this.forwardLayer.name,()=>{this.forwardLayer.build(e)}),Mi(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=Rr(t.layer);if(delete t.layer,t.numConstants!=null)throw new Pe("Deserialization of a Bidirectional layer with numConstants present is not supported yet.");let r=t;return r.layer=n,new e(r)}};hg.className="Bidirectional";ae.registerClass(hg);function uee(e){return new Gl(e)}function cee(e){return new gy(e)}function hee(e){return new my(e)}function dee(e){return new Ay(e)}function pee(e){return new yy(e)}function fee(e){return new wy(e)}function mee(e){return new xy(e)}function Aee(e){return new o0(e)}function yee(e){return new Bc(e)}function gee(e){return new vy(e)}function xee(e){return new i0(e)}function wee(e){return new ky(e)}function bee(e){return new Iy(e)}function _ee(e){return new Ny(e)}function vee(e){return new Sy(e)}function kee(e){return new Dy(e)}function Iee(e){return new My(e)}function Nee(e){return new d0(e)}function See(e){return new Fy(e)}function Tee(e){return new $y(e)}function Eee(e){return new Oy(e)}function Cee(e){return new zy(e)}function Ree(e){return new Py(e)}function Fee(e){return new Wy(e)}function Mee(e){return new By(e)}function $ee(e){return new Uy(e)}function Dee(e){return new Gy(e)}function Oee(e){return new Hy(e)}function zee(e){return new jy(e)}function Pee(e){return new Vy(e)}function Lee(e){return new qy(e)}function Wee(e){return new Yy(e)}function Bee(e){return new Jy(e)}function Vee(e){return new Qy(e)}function qA(e){return new tg(e)}function Uee(e){return qA(e)}function Hee(e){return qA(e)}function XA(e){return new rg(e)}function jee(e){return XA(e)}function Gee(e){return XA(e)}function KA(e){return new sg(e)}function qee(e){return KA(e)}function Xee(e){return KA(e)}function Kee(e){return new ig(e)}function Zee(e){return new lg(e)}function f7(e){return new og(e)}function m7(e){return new ug(e)}function A7(e){return new eg(e)}function y7(e){return new ng(e)}function Yee(e){return new ag(e)}function Jee(e){return new Ey(e)}function Qee(e){return new c0(e)}function ete(e){return new Cy(e)}function tte(e){return new Vc(e)}function nte(e){return new Ty(e)}function rte(e){return new u0(e)}function ate(e){return new Ry(e)}function ste(e){return new h0(e)}function ite(e){return new Zr(e)}function ote(e){return new l0(e)}function lte(e){return new hg(e)}function ute(e){return new cg(e)}var cte=f7,hte=m7,dte=A7,pte=y7;function fte(e){return new Xy(e)}function mte(e){return new Ky(e)}function Ate(e){return new Zy(e)}function yte(e){return new Ly(e)}var kv={};We(kv,{MAPE:()=>qne,MSE:()=>Zne,binaryAccuracy:()=>zne,binaryCrossentropy:()=>Pne,categoricalAccuracy:()=>Wne,categoricalCrossentropy:()=>Bne,cosineProximity:()=>Hne,mape:()=>Xne,meanAbsoluteError:()=>jne,meanAbsolutePercentageError:()=>Gne,meanSquaredError:()=>Kne,mse:()=>Yne,precision:()=>Vne,recall:()=>Une,sparseCategoricalAccuracy:()=>Lne});function zne(e,t){return ty(e,t)}function Pne(e,t){return F7(e,t)}function Lne(e,t){return M7(e,t)}function Wne(e,t){return ny(e,t)}function Bne(e,t){return ry(e,t)}function Vne(e,t){return R7(e,t)}function Une(e,t){return Ote(e,t)}function Hne(e,t){return QA(e,t)}function jne(e,t){return Jp(e,t)}function Gne(e,t){return Xl(e,t)}function qne(e,t){return Xl(e,t)}function Xne(e,t){return Xl(e,t)}function Kne(e,t){return Di(e,t)}function Zne(e,t){return Di(e,t)}function Yne(e,t){return Di(e,t)}var Iv={};We(Iv,{modelFromJSON:()=>Ane});var Nv={};We(Nv,{l1:()=>Qne,l1l2:()=>Jne,l2:()=>ere});function Jne(e){return new Lc(e)}function Qne(e){return kne(e)}function ere(e){return Ine(e)}var Sv=class extends ql{constructor(){super(...arguments);this.model=null}setModel(e){if(!(e instanceof ya))throw new Error("model must be a LayersModel, not some other Container");this.model=e}};function f0(e,t){return e<t}function Tv(e,t){return e>t}var Ev=class extends Sv{constructor(e){super();if(e==null&&(e={}),e.restoreBestWeights)throw new Pe("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=f0:this.mode==="max"?this.monitorFunc=Tv:this.monitor.indexOf("acc")!==-1?this.monitorFunc=Tv:this.monitorFunc=f0,this.monitorFunc===f0&&(this.minDelta*=-1)}async onTrainBegin(e){this.wait=0,this.stoppedEpoch=0,this.baseline!=null?this.best=this.baseline:this.best=this.monitorFunc===f0?Infinity:-Infinity}async onEpochEnd(e,t){await Ja(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 tre(e){return new Ev(e)}var nre={earlyStopping:tre},Mr;(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"})(Mr||(Mr={}));var Cv;(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={}))})(Cv||(Cv={}));var dg={};function rre(e,t){let n={tfOpName:e,category:"custom",inputs:[],attrs:[],customExecutor:t};dg[e]=n}function Rv(e){return dg[e]}function are(e){delete dg[e]}function k(e,t,n,r,a){let s=t.inputParams[e];if(s&&s.inputIndexStart!==void 0){let o=s.inputIndexStart,l=s.inputIndexEnd===0?void 0:s.inputIndexEnd===void 0?o+1:s.inputIndexEnd;if(s.type==="tensor")return $n(t.inputNames[s.inputIndexStart],n,r,a);if(s.type==="tensors")return t.inputNames.slice(o,l).map(h=>$n(h,n,r,a));let u=$n(t.inputNames.slice(o)[0],n,r,a),c=u.dataSync();return s.type==="number"?c[0]:v.toNestedArray(u.shape,c)}let i=t.attrParams[e];return i&&i.value}function $n(e,t,n,r){let[a,s]=Hn(e);if(r!=null){let o=r.getHashTableHandleByName(a);if(o!=null)return o}let i=n.currentContextIds.find(o=>!!t[m0(a,o)]);return i!==void 0?t[m0(a,i)][s]:void 0}function sre(e,t,n){return t[m0(e,n.currentContextId)]}function ga(e,t){let[n,r]=Hn(e);return[m0(n,t&&t.currentContextId),r]}function m0(e,t){return t?`${e}-${t}`:e}function Hn(e){let t=e.split(":");return t.length===1?[e,0]:[t[0],Number(t[t.length-1])]}function A0(e,t,n){let r=k("pad",e,t,n);if(r==="explicit"){r=k("explicitPaddings",e,t,n);let a=[[0,0],[0,0],[0,0],[0,0]];for(let s=0;s<4;s++)a[s][0]=r[s*2],a[s][1]=r[s*2+1];return a}return r}function xa(e){return e.kept?e:zr(e)}var Fv={};We(Fv,{json:()=>ire});var ire=[{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}]}],Mv={};We(Mv,{json:()=>ore});var ore=[{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}]}],$v={};We($v,{json:()=>lre});var lre=[{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"}]}],Dv={};We(Dv,{json:()=>ure});var ure=[{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"}]}],Ov={};We(Ov,{json:()=>cre});var cre=[{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"}]}],zv={};We(zv,{json:()=>hre});var hre=[{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}]}],Pv={};We(Pv,{json:()=>dre});var dre=[{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"}]}],Lv={};We(Lv,{json:()=>pre});var pre=[{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"}]}],Wv={};We(Wv,{json:()=>fre});var fre=[{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"}]}],Bv={};We(Bv,{json:()=>mre});var mre=[{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"}]}],Vv={};We(Vv,{json:()=>Are});var Are=[{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}]}],Uv={};We(Uv,{json:()=>yre});var yre=[{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}]}],Hv={};We(Hv,{json:()=>gre});var gre=[{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}]}],jv={};We(jv,{json:()=>xre});var xre=[{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"}]}],Gv={};We(Gv,{json:()=>wre});var wre=[{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}]}],qv={};We(qv,{json:()=>bre});var bre=[{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}]}],Xv={};We(Xv,{json:()=>_re});var _re=[{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:[]}],Zv=class{static get Instance(){return this._instance||(this._instance=new this)}constructor(){let e=[Fv,Mv,$v,Dv,Ov,zv,Pv,Vv,Bv,Lv,Uv,Hv,jv,Gv,qv,Xv,Wv],t=[].concat(...e.map(n=>n.json));this.opMappers=t.reduce((n,r)=>(n[r.tfOpName]=r,n),{})}transformGraph(e,t={}){let n=e.node,r=[],a=[],s=[],i=n.reduce((f,m)=>(f[m.name]=this.mapNode(m),m.op.startsWith("Placeholder")?r.push(f[m.name]):m.op==="Const"?a.push(f[m.name]):(m.input==null||m.input.length===0)&&s.push(f[m.name]),f),{}),o=[],l=[],u={},c={};t!=null&&(u=this.mapSignatureEntries(t.inputs),c=this.mapSignatureEntries(t.outputs));let h=Object.keys(i);h.forEach(f=>{let m=i[f];m.inputNames.forEach(A=>{let[y]=ga(A);m.inputs.push(i[y]),i[y].children.push(m)})}),Object.keys(c).length===0?h.forEach(f=>{let m=i[f];m.children.length===0&&l.push(m)}):Object.keys(c).forEach(f=>{let[m]=ga(f),A=i[m];A!=null&&(A.signatureKey=c[f],l.push(A))}),Object.keys(u).length>0?Object.keys(u).forEach(f=>{let[m]=ga(f),A=i[m];A&&(A.signatureKey=u[f],o.push(A))}):o=r;let d={};e.library!=null&&e.library.function!=null&&(d=e.library.function.reduce((f,m)=>(f[m.signature.name]=this.mapFunction(m),f),{}));let p={nodes:i,inputs:o,outputs:l,weights:a,placeholders:r,signature:t,functions:d};return s.length>0&&(p.initNodes=s),p}mapSignatureEntries(e){return Object.keys(e||{}).reduce((t,n)=>(t[e[n].name]=n,t),{})}mapNode(e){let t=Rv(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(r=>r.startsWith("^")?r.substr(1):r),inputs:[],children:[],inputParams:{},attrParams:{},rawAttrs:e.attr};return t.inputs!=null&&(n.inputParams=t.inputs.reduce((r,a)=>(r[a.name]={type:a.type,inputIndexStart:a.start,inputIndexEnd:a.end},r),{})),t.attrs!=null&&(n.attrParams=t.attrs.reduce((r,a)=>{let s=a.type,i;switch(a.type){case"string":i=pg(e.attr,a.tfName,a.defaultValue),i===void 0&&!!a.tfDeprecatedName&&(i=pg(e.attr,a.tfDeprecatedName,a.defaultValue));break;case"string[]":i=bg(e.attr,a.tfName,a.defaultValue),i===void 0&&!!a.tfDeprecatedName&&(i=bg(e.attr,a.tfDeprecatedName,a.defaultValue));break;case"number":i=mg(e.attr,a.tfName,a.defaultValue||0),i===void 0&&!!a.tfDeprecatedName&&(i=mg(e.attr,a.tfDeprecatedName,a.defaultValue));break;case"number[]":i=wg(e.attr,a.tfName,a.defaultValue),i===void 0&&!!a.tfDeprecatedName&&(i=wg(e.attr,a.tfDeprecatedName,a.defaultValue));break;case"bool":i=fg(e.attr,a.tfName,a.defaultValue),i===void 0&&!!a.tfDeprecatedName&&(i=fg(e.attr,a.tfDeprecatedName,a.defaultValue));break;case"bool[]":i=vg(e.attr,a.tfName,a.defaultValue),i===void 0&&!!a.tfDeprecatedName&&(i=vg(e.attr,a.tfDeprecatedName,a.defaultValue));break;case"shape":i=xg(e.attr,a.tfName,a.defaultValue),i===void 0&&!!a.tfDeprecatedName&&(i=xg(e.attr,a.tfDeprecatedName,a.defaultValue));break;case"shape[]":i=_g(e.attr,a.tfName,a.defaultValue),i===void 0&&!!a.tfDeprecatedName&&(i=_g(e.attr,a.tfDeprecatedName,a.defaultValue));break;case"dtype":i=yg(e.attr,a.tfName,a.defaultValue),i===void 0&&!!a.tfDeprecatedName&&(i=yg(e.attr,a.tfDeprecatedName,a.defaultValue));break;case"dtype[]":i=gg(e.attr,a.tfName,a.defaultValue),i===void 0&&!!a.tfDeprecatedName&&(i=gg(e.attr,a.tfDeprecatedName,a.defaultValue));break;case"func":i=Kv(e.attr,a.tfName,a.defaultValue),i===void 0&&!!a.tfDeprecatedName&&(i=Kv(e.attr,a.tfDeprecatedName,a.defaultValue));break;case"tensor":case"tensors":break;default:throw new Error(`Unsupported param type: ${a.type} for op: ${e.op}`)}return r[a.name]={value:i,type:s},r},{})),n}mapFunction(e){let t=e.nodeDef,n=[],r=[],a={};t!=null&&(a=t.reduce((u,c)=>(u[c.name]=this.mapNode(c),c.op==="Const"&&r.push(u[c.name]),u),{}));let s=[],i=[];e.signature.inputArg.forEach(u=>{let[c]=ga(u.name),h={name:c,op:"Placeholder",inputs:[],inputNames:[],category:"graph",inputParams:{},attrParams:{dtype:{value:Ag(u.type),type:"dtype"}},children:[]};h.signatureKey=u.name,s.push(h),a[c]=h}),Object.keys(a).forEach(u=>{let c=a[u];c.inputNames.forEach(h=>{let[d]=ga(h);c.inputs.push(a[d]),a[d].children.push(c)})});let o=e.ret;e.signature.outputArg.forEach(u=>{let[c,h]=ga(o[u.name]),d=a[c];d!=null&&(d.defaultOutput=h,i.push(d))});let l=this.mapArgsToSignature(e);return{nodes:a,inputs:s,outputs:i,weights:r,placeholders:n,signature:l}}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 vre(e){let t=J().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 Yv(e,t){let n=Array.isArray(e)?String.fromCharCode.apply(null,e):vre(e);return t?n:n.toLowerCase()}function pg(e,t,n,r=!1){let a=e[t];return a!=null?Yv(a.s,r):n}function fg(e,t,n){let r=e[t];return r?r.b:n}function mg(e,t,n){let r=e[t]||{},a=r.i!=null?r.i:r.f!=null?r.f:n;return typeof a=="number"?a:parseInt(a,10)}function Ag(e){switch(typeof e=="string"&&(e=Mr[e]),e){case Mr.DT_FLOAT:return"float32";case Mr.DT_INT32:case Mr.DT_INT64:case Mr.DT_INT8:case Mr.DT_UINT8:return"int32";case Mr.DT_BOOL:return"bool";case Mr.DT_DOUBLE:return"float32";case Mr.DT_STRING:return"string";default:return null}}function Kv(e,t,n){let r=e[t];return r&&r.func?r.func.name:n}function yg(e,t,n){let r=e[t];return r&&r.type?Ag(r.type):n}function gg(e,t,n){let r=e[t];return r&&r.list&&r.list.type?r.list.type.map(a=>Ag(a)):n}function Jv(e){if(!e.unknownRank)return e.dim!=null?e.dim.map(t=>typeof t.size=="number"?t.size:parseInt(t.size,10)):[]}function xg(e,t,n){let r=e[t];return r&&r.shape?Jv(r.shape):n}function wg(e,t,n){let r=e[t];return r?((r.list.f&&r.list.f.length?r.list.f:r.list.i)||[]).map(a=>typeof a=="number"?a:parseInt(a,10)):n}function bg(e,t,n,r=!1){let a=e[t];return a&&a.list&&a.list.s?a.list.s.map(s=>Yv(s,r)):n}function _g(e,t,n){let r=e[t];return r&&r.list&&r.list.shape?r.list.shape.map(a=>Jv(a)):n}function vg(e,t,n){let r=e[t];return r&&r.list&&r.list.b?r.list.b:n}var kre=class{constructor(e,t,n){this.node=e,this.tensorMap=t,this.context=n,this.inputs=[],this.attrs={},this.inputs=e.inputNames.map(r=>this.getInput(r)),e.rawAttrs!=null&&(this.attrs=Object.keys(e.rawAttrs).reduce((r,a)=>(r[a]=this.getAttr(a),r),{}))}getInput(e){return $n(e,this.tensorMap,this.context)}getAttr(e,t){let n=this.node.rawAttrs[e];if(n.tensor!=null)return $n(e,this.tensorMap,this.context);if(n.i!=null||n.f!=null)return mg(this.node.rawAttrs,e,t);if(n.s!=null)return pg(this.node.rawAttrs,e,t);if(n.b!=null)return fg(this.node.rawAttrs,e,t);if(n.shape!=null)return xg(this.node.rawAttrs,e,t);if(n.type!=null)return yg(this.node.rawAttrs,e,t);if(n.list!=null){if(n.list.i!=null||n.list.f!=null)return wg(this.node.rawAttrs,e,t);if(n.list.s!=null)return bg(this.node.rawAttrs,e,t);if(n.list.shape!=null)return _g(this.node.rawAttrs,e,t);if(n.list.b!=null)return vg(this.node.rawAttrs,e,t);if(n.list.type!=null)return gg(this.node.rawAttrs,e,t)}return t}},Ire=(e,t,n)=>{switch(e.op){case"BiasAdd":case"AddV2":case"Add":return[ie(k("a",e,t,n),k("b",e,t,n))];case"AddN":return[La(k("tensors",e,t,n))];case"FloorMod":case"Mod":return[vm(k("a",e,t,n),k("b",e,t,n))];case"Mul":return[P(k("a",e,t,n),k("b",e,t,n))];case"RealDiv":case"Div":return[be(k("a",e,t,n),k("b",e,t,n))];case"DivNoNan":return[pm(k("a",e,t,n),k("b",e,t,n))];case"FloorDiv":return[vd(k("a",e,t,n),k("b",e,t,n))];case"Sub":return[we(k("a",e,t,n),k("b",e,t,n))];case"Minimum":return[vl(k("a",e,t,n),k("b",e,t,n))];case"Maximum":return[Br(k("a",e,t,n),k("b",e,t,n))];case"Pow":return[ha(k("a",e,t,n),k("b",e,t,n))];case"SquaredDifference":return[qd(k("a",e,t,n),k("b",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Nre=(e,t,n)=>{switch(e.op){case"Abs":case"ComplexAbs":return[Bt(k("x",e,t,n))];case"Acos":return[Yf(k("x",e,t,n))];case"Acosh":return[Jf(k("x",e,t,n))];case"Asin":return[em(k("x",e,t,n))];case"Asinh":return[tm(k("x",e,t,n))];case"Atan":return[nm(k("x",e,t,n))];case"Atan2":return[rm(k("x",e,t,n),k("y",e,t,n))];case"Atanh":return[am(k("x",e,t,n))];case"Ceil":return[lm(k("x",e,t,n))];case"Complex":return[Da(k("real",e,t,n),k("imag",e,t,n))];case"Cos":return[Yu(k("x",e,t,n))];case"Cosh":return[Td(k("x",e,t,n))];case"Elu":return[xl(k("x",e,t,n))];case"Erf":return[fm(k("x",e,t,n))];case"Exp":return[Jn(k("x",e,t,n))];case"Expm1":return[mm(k("x",e,t,n))];case"Floor":return[wl(k("x",e,t,n))];case"Log":return[zn(k("x",e,t,n))];case"Log1p":return[Fd(k("x",e,t,n))];case"Imag":return[Cd(k("x",e,t,n))];case"Neg":return[St(k("x",e,t,n))];case"Reciprocal":return[Nm(k("x",e,t,n))];case"Real":return[ac(k("x",e,t,n))];case"Relu":return[Ur(k("x",e,t,n))];case"Round":return[Sm(k("x",e,t,n))];case"Selu":return[Bd(k("x",e,t,n))];case"Sigmoid":return[On(k("x",e,t,n))];case"Sin":return[Vd(k("x",e,t,n))];case"Sign":return[Em(k("x",e,t,n))];case"Sinh":return[Ud(k("x",e,t,n))];case"Softplus":return[bl(k("x",e,t,n))];case"Sqrt":return[an(k("x",e,t,n))];case"Square":return[ht(k("x",e,t,n))];case"Tanh":return[Al(k("x",e,t,n))];case"Tan":return[Fm(k("x",e,t,n))];case"ClipByValue":return[Sn(k("x",e,t,n),k("clipValueMin",e,t,n),k("clipValueMax",e,t,n))];case"Relu6":return[Ld(k("x",e,t,n))];case"Rsqrt":return[Wd($n(e.inputNames[0],t,n))];case"Prod":return[zd(k("x",e,t,n),k("axes",e,t,n))];case"LeakyRelu":return[Qu(k("x",e,t,n),k("alpha",e,t,n))];case"Prelu":return[rc(k("x",e,t,n),k("alpha",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}};function Ar(e,t,n=""){if(!(typeof e=="number"||typeof t=="number")){v.assert(e.length===t.length,()=>n+` Shapes ${e} and ${t} must match`);for(let r=0;r<e.length;r++){let a=e[r],s=t[r];v.assert(a<0||s<0||a===s,()=>n+` Shapes ${e} and ${t} must match`)}}}function Qv(e){return!(typeof e=="number"||e.some(t=>t<0))}function jc(e,t,n){let r=kg(e,n),a=!Qv(r);if(a&&t.length===0)throw new Error(`Tried to calculate elements of an empty list with non-fully-defined elementShape: ${r}`);if(a&&t.forEach(s=>{r=kg(s.shape,r)}),!Qv(r))throw new Error(`Non-fully-defined elementShape: ${r}`);return r}function kg(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 r=0;r<e.length;++r){let a=e[r],s=t[r];if(a>=0&&s>=0&&a!==s)throw new Error(`Incompatible shape during merge: ${e} vs. ${t}`);n[r]=a>=0?a:s}return n}var Sre=class{constructor(e,t,n,r,a,s,i){this.name=e,this.dtype=t,this.maxSize=n,this.elementShape=r,this.identicalElementShapes=a,this.dynamicSize=s,this.clearAfterRead=i,this.tensors=[],this.closed_=!1,this.idTensor=Ie(0),Zt(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),Ar(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,Zt(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,r)=>this.write(n,t[r]))}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 r=0;r<this.size();r++)e.push(r)}if(e.length===0)return vr([],[0].concat(this.elementShape));let n=this.readMany(e);return Ar(this.elementShape,n[0].shape,"TensorArray shape mismatch: "),An(n,0)}concat(e){if(!!e&&e!==this.dtype)throw new Error(`TensorArray dtype is ${this.dtype} but concat requested dtype ${e}`);if(this.size()===0)return vr([],[0].concat(this.elementShape));let t=[];for(let r=0;r<this.size();r++)t.push(r);let n=this.readMany(t);return Ar(this.elementShape,n[0].shape,`TensorArray shape mismatch: tensor array shape (${this.elementShape}) vs first tensor shape (${n[0].shape})`),lt(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,hr(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,r=e.map(o=>(n+=o,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. ${e.length}), and the TensorArray is not marked as dynamically resizeable`);let a=n===0?0:t.size/n,s=[];B(()=>{t=G(t,[1,n,a]);for(let o=0;o<e.length;++o){let l=o===0?0:r[o-1],u=[0,l,0],c=[1,e[o],a];s[o]=G($e(t,u,c),this.elementShape)}return s});let i=[];for(let o=0;o<e.length;o++)i[o]=o;this.writeMany(i,s)}},Gc=class{constructor(e,t,n,r=-1){this.tensors=e,this.elementShape=t,this.elementDtype=n,e!=null&&e.forEach(a=>{if(n!==a.dtype)throw new Error(`Invalid data types; op elements ${n}, but list elements ${a.dtype}`);Ar(t,a.shape,"TensorList shape mismatch: "),Zt(a)}),this.idTensor=Ie(0),this.maxNumElements=r,Zt(this.idTensor)}get id(){return this.idTensor.id}copy(){return new Gc([...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.`);Ar(e,this.elementShape,"TensorList shape mismatch: ");let r=jc(this.elementShape,this.tensors,e);return B(()=>{let a=this.tensors.map(s=>G(s,r));return An(a,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=jc(this.elementShape,this.tensors,e),r=this.tensors.pop();return Ar(r.shape,e,"TensorList shape mismatch: "),G(r,n)}pushBack(e){if(e.dtype!==this.elementDtype)throw new Error(`Invalid data types; op elements ${e.dtype}, but list elements ${this.elementDtype}`);if(Ar(e.shape,this.elementShape,"TensorList shape mismatch: "),this.maxNumElements===this.size())throw new Error("Trying to push element into a full list.");Zt(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.`);Ar(this.tensors[e].shape,t,"TensorList shape mismatch: ");let r=jc(this.elementShape,this.tensors,t);return G(this.tensors[e],r)}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.`);Ar(this.elementShape,t.shape,"TensorList shape mismatch: "),Zt(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}`);Ar(this.elementShape,n,"TensorList shape mismatch: "),e=e.slice(0,this.size());let r=jc(this.elementShape,this.tensors,n);return e.length===0?vr([],[0].concat(r)):B(()=>{let a=e.map(s=>G(this.tensors[s],r));return An(a,0)})}concat(e,t){if(!!e&&e!==this.elementDtype)throw new Error(`TensorList dtype is ${this.elementDtype} but concat requested dtype ${e}`);Ar(this.elementShape,t,"TensorList shape mismatch: ");let n=jc(this.elementShape,this.tensors,t);return this.size()===0?vr([],[0].concat(n)):B(()=>{let r=this.tensors.map(a=>G(a,n));return lt(r,0)})}};function Tre(e,t,n){let r=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 a=e.shape.slice(1);Ar(a,t,"TensorList shape mismatch: ");let s=hr(e);return new Gc(s,t,r)}function Ere(e,t,n){return new Gc([],e,t,n)}function Cre(e,t,n,r){if(t.length!==e.shape[0])throw new Error(`Expected len(indices) == tensor.shape[0], but saw: ${t.length} vs. ${e.shape[0]}`);let a=Math.max(...t);if(r!=null&&r!==-1&&a>=r)throw new Error(`Max index must be < array size (${a} vs. ${r})`);let s=new Gc([],n,e.dtype,r),i=hr(e,0);return t.forEach((o,l)=>{s.setItem(o,i[l])}),s}function Rre(e,t,n){let r=0,a=t.map(c=>(r+=c,r));if(r!==e.shape[0])throw new Error(`Expected sum of lengths to be equal to
|
|
tensor.shape[0], but sum of lengths is
|
|
${r}, and tensor's shape is: ${e.shape}`);let s=e.shape.slice(1),i=kg(s,n),o=r===0?0:e.size/r,l=B(()=>{let c=[];e=G(e,[1,r,o]);for(let h=0;h<t.length;++h){let d=h===0?0:a[h-1],p=[0,d,0],f=[1,t[h],o];c[h]=G($e(e,p,f),i)}return e.dispose(),c}),u=new Gc([],n,e.dtype,t.length);for(let c=0;c<l.length;c++)u.setItem(c,l[c]);return u}var Fre=async(e,t,n)=>{switch(e.op){case"If":case"StatelessIf":{let r=k("thenBranch",e,t,n),a=k("elseBranch",e,t,n),s=k("cond",e,t,n),i=k("args",e,t,n);return(await s.data())[0]?n.functionMap[r].executeFunctionAsync(i,n.tensorArrayMap,n.tensorListMap):n.functionMap[a].executeFunctionAsync(i,n.tensorArrayMap,n.tensorListMap)}case"While":case"StatelessWhile":{let r=k("body",e,t,n),a=k("cond",e,t,n),s=k("args",e,t,n),i=await n.functionMap[a].executeFunctionAsync(s,n.tensorArrayMap,n.tensorListMap),o=s.map(c=>c.id),l=await i[0].data();i.forEach(c=>{!c.kept&&o.indexOf(c.id)===-1&&c.dispose()});let u=s;for(;l[0];){let c=u;u=await n.functionMap[r].executeFunctionAsync(u,n.tensorArrayMap,n.tensorListMap);let h=u.map(p=>p.id);c.forEach(p=>{!p.kept&&o.indexOf(p.id)===-1&&h.indexOf(p.id)===-1&&p.dispose()});let d=await n.functionMap[a].executeFunctionAsync(u,n.tensorArrayMap,n.tensorListMap);l=await d[0].data(),d.forEach(p=>{!p.kept&&o.indexOf(p.id)===-1&&h.indexOf(p.id)===-1&&p.dispose()})}return u}case"LoopCond":{let r=k("pred",e,t,n);return[xa(r)]}case"Switch":{let r=k("pred",e,t,n),a=k("data",e,t,n);return a.kept||(a=xa(a)),(await r.data())[0]?[void 0,a]:[a,void 0]}case"Merge":{let r=e.inputNames.find(a=>$n(a,t,n)!==void 0);if(r){let a=$n(r,t,n);return[xa(a)]}return}case"Enter":{let r=k("frameName",e,t,n),a=k("tensor",e,t,n);return n.enterFrame(r),[xa(a)]}case"Exit":{let r=k("tensor",e,t,n);return n.exitFrame(),[xa(r)]}case"NextIteration":{let r=k("tensor",e,t,n);return n.nextIteration(),[xa(r)]}case"TensorArrayV3":{let r=k("size",e,t,n),a=k("dtype",e,t,n),s=k("elementShape",e,t,n),i=k("dynamicSize",e,t,n),o=k("clearAfterRead",e,t,n),l=k("identicalElementShapes",e,t,n),u=k("name",e,t,n),c=new Sre(u,a,r,s,l,i,o);return n.addTensorArray(c),[c.idTensor,Ie(1)]}case"TensorArrayWriteV3":{let r=k("tensorArrayId",e,t,n),a=k("index",e,t,n),s=k("tensor",e,t,n),i=n.getTensorArray(r.id);return i.write(a,s),[i.idTensor]}case"TensorArrayReadV3":{let r=k("tensorArrayId",e,t,n),a=k("index",e,t,n);return[n.getTensorArray(r.id).read(a)]}case"TensorArrayGatherV3":{let r=k("tensorArrayId",e,t,n),a=k("indices",e,t,n),s=k("dtype",e,t,n);return[n.getTensorArray(r.id).gather(a,s)]}case"TensorArrayScatterV3":{let r=k("tensorArrayId",e,t,n),a=k("indices",e,t,n),s=k("tensor",e,t,n),i=n.getTensorArray(r.id);return i.scatter(a,s),[i.idTensor]}case"TensorArrayConcatV3":{let r=k("tensorArrayId",e,t,n),a=n.getTensorArray(r.id),s=k("dtype",e,t,n);return[a.concat(s)]}case"TensorArraySplitV3":{let r=k("tensorArrayId",e,t,n),a=k("tensor",e,t,n),s=k("lengths",e,t,n),i=n.getTensorArray(r.id);return i.split(s,a),[i.idTensor]}case"TensorArraySizeV3":{let r=k("tensorArrayId",e,t,n),a=n.getTensorArray(r.id);return[Ie(a.size(),"int32")]}case"TensorArrayCloseV3":{let r=k("tensorArrayId",e,t,n),a=n.getTensorArray(r.id);return a.clearAndClose(),[a.idTensor]}case"TensorListSetItem":{let r=k("tensorListId",e,t,n),a=k("index",e,t,n),s=k("tensor",e,t,n),i=n.getTensorList(r.id);return i.setItem(a,s),[i.idTensor]}case"TensorListGetItem":{let r=k("tensorListId",e,t,n),a=k("index",e,t,n),s=k("elementShape",e,t,n),i=k("elementDType",e,t,n);return[n.getTensorList(r.id).getItem(a,s,i)]}case"TensorListScatterV2":case"TensorListScatter":{let r=k("indices",e,t,n),a=k("tensor",e,t,n),s=k("elementShape",e,t,n),i=k("numElements",e,t,n),o=Cre(a,r,s,i);return n.addTensorList(o),[o.idTensor]}case"TensorListReserve":case"EmptyTensorList":{let r=k("elementShape",e,t,n),a=k("elementDType",e,t,n),s;e.op==="TensorListReserve"?s="numElements":s="maxNumElements";let i=k(s,e,t,n),o=Ere(r,a,i);return n.addTensorList(o),[o.idTensor]}case"TensorListGather":{let r=k("tensorListId",e,t,n),a=k("indices",e,t,n),s=k("elementShape",e,t,n),i=k("elementDType",e,t,n);return[n.getTensorList(r.id).gather(a,i,s)]}case"TensorListStack":{let r=k("tensorListId",e,t,n),a=k("elementShape",e,t,n),s=k("elementDType",e,t,n),i=k("numElements",e,t,n);return[n.getTensorList(r.id).stack(a,s,i)]}case"TensorListFromTensor":{let r=k("tensor",e,t,n),a=k("elementShape",e,t,n),s=k("elementDType",e,t,n),i=Tre(r,a,s);return n.addTensorList(i),[i.idTensor]}case"TensorListConcat":{let r=k("tensorListId",e,t,n),a=n.getTensorList(r.id),s=k("dtype",e,t,n),i=k("elementShape",e,t,n);return[a.concat(s,i)]}case"TensorListPushBack":{let r=k("tensorListId",e,t,n),a=k("tensor",e,t,n),s=n.getTensorList(r.id);return s.pushBack(a),[s.idTensor]}case"TensorListPopBack":{let r=k("tensorListId",e,t,n),a=k("elementShape",e,t,n),s=k("elementDType",e,t,n);return[n.getTensorList(r.id).popBack(a,s)]}case"TensorListSplit":{let r=k("tensor",e,t,n),a=k("elementShape",e,t,n),s=k("lengths",e,t,n),i=Rre(r,s,a);return n.addTensorList(i),[i.idTensor]}default:throw TypeError(`Node type ${e.op} is not implemented`)}};function e6(e,t,n){let[r,a]=k("fusedOps",e,t,n),s=r==="biasadd",i=a==="prelu",o=r==="fusedbatchnorm",l=k("numArgs",e,t,n);if(s){if(i&&l!==2)throw new Error("FusedConv2d and DepthwiseConv2d with BiasAdd and Prelu must have two extra arguments: bias and alpha.");if(!i&&l!==1)throw new Error("FusedConv2d and DepthwiseConv2d with BiasAdd must have one extra argument: bias.")}if(o)throw new Error("FusedConv2d and DepthwiseConv2d with FusedBatchNorm is not supported.");let u=k("strides",e,t,n),c=A0(e,t,n),h=k("dataFormat",e,t,n).toUpperCase(),d=k("dilations",e,t,n),[p,f]=k("args",e,t,n),m=k("leakyreluAlpha",e,t,n);return{stride:u,pad:c,dataFormat:h,dilations:d,biasArg:p,preluArg:f,activationFunc:a,leakyreluAlpha:m}}var Mre=(e,t,n)=>{switch(e.op){case"Conv1D":{let r=k("stride",e,t,n),a=k("pad",e,t,n),s=k("dataFormat",e,t,n).toUpperCase(),i=k("dilation",e,t,n);return[Nd(k("x",e,t,n),k("filter",e,t,n),r,a,s,i)]}case"Conv2D":{let r=k("strides",e,t,n),a=A0(e,t,n),s=k("dataFormat",e,t,n).toUpperCase(),i=k("dilations",e,t,n);return[ua(k("x",e,t,n),k("filter",e,t,n),[r[1],r[2]],a,s,[i[1],i[2]])]}case"_FusedConv2D":{let{stride:r,pad:a,dataFormat:s,dilations:i,biasArg:o,preluArg:l,activationFunc:u,leakyreluAlpha:c}=e6(e,t,n);return[ja.conv2d({x:k("x",e,t,n),filter:k("filter",e,t,n),strides:[r[1],r[2]],pad:a,dataFormat:s,dilations:[i[1],i[2]],bias:o,activation:u,preluActivationWeights:l,leakyreluAlpha:c})]}case"FusedDepthwiseConv2dNative":{let{stride:r,pad:a,dataFormat:s,dilations:i,biasArg:o,preluArg:l,activationFunc:u,leakyreluAlpha:c}=e6(e,t,n);return[ja.depthwiseConv2d({x:k("x",e,t,n),filter:k("filter",e,t,n),strides:[r[1],r[2]],pad:a,dataFormat:s,dilations:[i[1],i[2]],bias:o,activation:u,preluActivationWeights:l,leakyreluAlpha:c})]}case"Conv2DBackpropInput":case"Conv2dTranspose":{let r=k("outputShape",e,t,n),a=k("strides",e,t,n),s=A0(e,t,n);return[Sd(k("x",e,t,n),k("filter",e,t,n),r,[a[1],a[2]],s)]}case"DepthwiseConv2dNative":case"DepthwiseConv2d":{let r=k("strides",e,t,n),a=A0(e,t,n),s=k("dilations",e,t,n),i=k("dataFormat",e,t,n).toUpperCase();return[gl(k("input",e,t,n),k("filter",e,t,n),[r[1],r[2]],a,i,[s[1],s[2]])]}case"Conv3D":{let r=k("strides",e,t,n),a=k("pad",e,t,n),s=k("dataFormat",e,t,n).toUpperCase(),i=k("dilations",e,t,n);return[cm(k("x",e,t,n),k("filter",e,t,n),[r[1],r[2],r[3]],a,s,[i[1],i[2],i[3]])]}case"AvgPool":{let r=k("strides",e,t,n),a=k("pad",e,t,n),s=k("kernelSize",e,t,n);return[Xu(k("x",e,t,n),[s[1],s[2]],[r[1],r[2]],a)]}case"MaxPool":{let r=k("strides",e,t,n),a=k("pad",e,t,n),s=k("kernelSize",e,t,n);return[tc(k("x",e,t,n),[s[1],s[2]],[r[1],r[2]],a)]}case"MaxPoolWithArgmax":{let r=k("strides",e,t,n),a=k("pad",e,t,n),s=k("kernelSize",e,t,n),i=k("includeBatchInIndex",e,t,n),{result:o,indexes:l}=Sx(k("x",e,t,n),[s[1],s[2]],[r[1],r[2]],a,i);return[o,l]}case"AvgPool3D":{let r=k("strides",e,t,n),a=k("pad",e,t,n),s=k("kernelSize",e,t,n);return[om(k("x",e,t,n),[s[1],s[2],s[3]],[r[1],r[2],r[3]],a)]}case"MaxPool3D":{let r=k("strides",e,t,n),a=k("pad",e,t,n),s=k("kernelSize",e,t,n);return[bm(k("x",e,t,n),[s[1],s[2],s[3]],[r[1],r[2],r[3]],a)]}case"Dilation2D":{let r=k("strides",e,t,n),a=k("pad",e,t,n),s=k("dilations",e,t,n),i=r[1],o=r[2],l=s[1],u=s[2];return[dm(k("x",e,t,n),k("filter",e,t,n),[i,o],a,[l,u],"NHWC")]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},$re=(e,t,n)=>{switch(e.op){case"Fill":{let r=k("shape",e,t,n),a=k("dtype",e,t,n),s=k("value",e,t,n);return[Ju(r,s,a)]}case"LinSpace":{let r=k("start",e,t,n),a=k("stop",e,t,n),s=k("num",e,t,n);return[wx(r,a,s)]}case"Multinomial":{let r=k("logits",e,t,n),a=k("numSamples",e,t,n),s=k("seed",e,t,n);return[Tx(r,a,s)]}case"OneHot":{let r=k("indices",e,t,n),a=k("depth",e,t,n),s=k("onValue",e,t,n),i=k("offValue",e,t,n);return[hl(r,a,s,i)]}case"Ones":return[Vr(k("shape",e,t,n),k("dtype",e,t,n))];case"OnesLike":return[Pn(k("x",e,t,n))];case"RandomUniform":return[kl(k("shape",e,t,n),k("minval",e,t,n),k("maxval",e,t,n),k("dtype",e,t,n))];case"Range":{let r=k("start",e,t,n),a=k("stop",e,t,n),s=k("step",e,t,n);return[Pd(r,a,s,k("dtype",e,t,n))]}case"TruncatedNormal":{let r=k("shape",e,t,n),a=k("mean",e,t,n),s=k("stdDev",e,t,n),i=k("seed",e,t,n);return[Xd(r,a,s,k("dtype",e,t,n),i)]}case"Zeros":return[$t(k("shape",e,t,n),k("dtype",e,t,n))];case"ZerosLike":return[qe(k("x",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}};function Ig(e,t,n){let r=k("boxes",e,t,n),a=k("scores",e,t,n),s=k("maxOutputSize",e,t,n),i=k("iouThreshold",e,t,n),o=k("scoreThreshold",e,t,n),l=k("softNmsSigma",e,t,n);return{boxes:r,scores:a,maxOutputSize:s,iouThreshold:i,scoreThreshold:o,softNmsSigma:l}}var Dre=async(e,t,n)=>{switch(e.op){case"NonMaxSuppressionV5":{let{boxes:r,scores:a,maxOutputSize:s,iouThreshold:i,scoreThreshold:o,softNmsSigma:l}=Ig(e,t,n),u=await tt.nonMaxSuppressionWithScoreAsync(r,a,s,i,o,l);return[u.selectedIndices,u.selectedScores]}case"NonMaxSuppressionV4":{let{boxes:r,scores:a,maxOutputSize:s,iouThreshold:i,scoreThreshold:o}=Ig(e,t,n),l=k("padToMaxOutputSize",e,t,n),u=await tt.nonMaxSuppressionPaddedAsync(r,a,s,i,o,l);return[u.selectedIndices,u.validOutputs]}case"NonMaxSuppressionV3":case"NonMaxSuppressionV2":{let{boxes:r,scores:a,maxOutputSize:s,iouThreshold:i,scoreThreshold:o}=Ig(e,t,n);return[await tt.nonMaxSuppressionAsync(r,a,s,i,o)]}case"Where":{let r=ge(k("condition",e,t,n),"bool"),a=[await Dm(r)];return r.dispose(),a}case"ListDiff":return Rx(k("x",e,t,n),k("y",e,t,n));default:throw TypeError(`Node type ${e.op} is not implemented`)}},Ore=(e,t,n)=>{switch(e.op){case"TopKV2":{let r=k("x",e,t,n),a=k("k",e,t,n),s=k("sorted",e,t,n),i=Mm(r,a,s);return[i.values,i.indices]}case"Unique":{let r=k("x",e,t,n),a=Kd(r);return[a.values,a.indices]}case"UniqueV2":{let r=k("x",e,t,n),a=k("axis",e,t,n),s=Kd(r,a);return[s.values,s.indices]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},zre=(e,t,n)=>{switch(e.op){case"Const":return t[e.name];case"PlaceholderWithDefault":let r=k("default",e,t,n);return[$n(e.name,t,n)||r];case"Placeholder":return[$n(e.name,t,n)];case"Identity":case"StopGradient":case"FakeQuantWithMinMaxVars":{let u=k("x",e,t,n);return[xa(u)]}case"IdentityN":return k("x",e,t,n).map(u=>xa(u));case"Snapshot":let a=k("x",e,t,n);return[xa(a)];case"Shape":return[hn(k("x",e,t,n).shape,"int32")];case"ShapeN":return k("x",e,t,n).map(u=>hn(u.shape));case"Size":return[Ie(k("x",e,t,n).size,"int32")];case"Rank":return[Ie(k("x",e,t,n).rank,"int32")];case"NoOp":return[Ie(1)];case"Print":let s=k("x",e,t,n),i=k("data",e,t,n),o=k("message",e,t,n),l=k("summarize",e,t,n);console.warn("The graph has a tf.print() operation,usually used for debugging, which slows down performance."),console.log(o);for(let u=0;u<i.length;u++)console.log(Array.prototype.slice.call(i[u].dataSync()).slice(0,l));return[s];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Pre=class{constructor(e,t){this.keyDType=e,this.valueDType=t,this.handle=Ie(0),this.tensorMap=new Map,Zt(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(r=>r.dispose()),this.tensorMap.clear(),B(()=>{let r=hr(t),a=n.length,s=r.length;v.assert(a===s,()=>`The number of elements doesn't match, keys has ${a} elements, the values has ${s} elements.`);for(let i=0;i<a;i++){let o=n[i],l=r[i];Zt(l),this.tensorMap.set(o,l)}return this.handle})}async find(e,t){this.checkKeyAndValueTensor(e,t);let n=await e.data();return B(()=>{let r=[];for(let a=0;a<n.length;a++){let s=n[a],i=this.findWithDefault(s,t);r.push(i)}return An(r)})}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}`)}},Lre=async(e,t,n,r)=>{switch(e.op){case"HashTable":case"HashTableV2":{let a=k("keyDType",e,t,n),s=k("valueDType",e,t,n),i=new Pre(a,s);return r.addHashTable(e.name,i),[i.handle]}case"LookupTableImport":case"LookupTableImportV2":{let a=k("tableHandle",e,t,n,r),s=k("keys",e,t,n),i=k("values",e,t,n);return[await r.getHashTableById(a.id).import(s,i)]}case"LookupTableFind":case"LookupTableFindV2":{let a=k("tableHandle",e,t,n,r),s=k("keys",e,t,n),i=k("defaultValue",e,t,n);return[await r.getHashTableById(a.id).find(s,i)]}case"LookupTableSize":case"LookupTableSizeV2":{let a=k("tableHandle",e,t,n,r);return[r.getHashTableById(a.id).tensorSize()]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},Wre=(e,t,n)=>{switch(e.op){case"ResizeBilinear":{let r=k("images",e,t,n),a=k("size",e,t,n),s=k("alignCorners",e,t,n),i=k("halfPixelCenters",e,t,n);return[tt.resizeBilinear(r,[a[0],a[1]],s,i)]}case"ResizeNearestNeighbor":{let r=k("images",e,t,n),a=k("size",e,t,n),s=k("alignCorners",e,t,n),i=k("halfPixelCenters",e,t,n);return[tt.resizeNearestNeighbor(r,[a[0],a[1]],s,i)]}case"CropAndResize":{let r=k("image",e,t,n),a=k("boxes",e,t,n),s=k("boxInd",e,t,n),i=k("cropSize",e,t,n),o=k("method",e,t,n),l=k("extrapolationValue",e,t,n);return[tt.cropAndResize(r,a,s,i,o,l)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},Bre=(e,t,n)=>{switch(e.op){case"Equal":return[Ba(k("a",e,t,n),k("b",e,t,n))];case"NotEqual":return[xi(k("a",e,t,n),k("b",e,t,n))];case"Greater":return[ur(k("a",e,t,n),k("b",e,t,n))];case"GreaterEqual":return[Ua(k("a",e,t,n),k("b",e,t,n))];case"Less":return[Rd(k("a",e,t,n),k("b",e,t,n))];case"LessEqual":return[yi(k("a",e,t,n),k("b",e,t,n))];case"LogicalAnd":return[cr(k("a",e,t,n),k("b",e,t,n))];case"LogicalNot":return[ec(k("a",e,t,n))];case"LogicalOr":return[Dd(k("a",e,t,n),k("b",e,t,n))];case"Select":case"SelectV2":return[Tn(k("condition",e,t,n),k("a",e,t,n),k("b",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Vre=(e,t,n)=>{switch(e.op){case"BatchMatMul":case"BatchMatMulV2":case"MatMul":return[Ke(k("a",e,t,n),k("b",e,t,n),k("transposeA",e,t,n),k("transposeB",e,t,n))];case"Transpose":return[ot(k("x",e,t,n),k("perm",e,t,n))];case"_FusedMatMul":let[r,a]=k("fusedOps",e,t,n),s=r==="biasadd",i=a==="prelu",o=k("numArgs",e,t,n),l=k("leakyreluAlpha",e,t,n);if(s){if(i&&o!==2)throw new Error("Fused MatMul with BiasAdd and Prelu must have two extra arguments: bias and alpha.");if(!i&&o!==1)throw new Error("Fused MatMul with BiasAdd must have one extra argument: bias.")}let[u,c]=k("args",e,t,n);return[ja.matMul({a:k("a",e,t,n),b:k("b",e,t,n),transposeA:k("transposeA",e,t,n),transposeB:k("transposeB",e,t,n),bias:u,activation:a,preluActivationWeights:c,leakyreluAlpha:l})];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Ure=(e,t,n)=>{switch(e.op){case"FusedBatchNorm":case"FusedBatchNormV2":return[mi(k("x",e,t,n),k("mean",e,t,n),k("variance",e,t,n),k("offset",e,t,n),k("scale",e,t,n),k("epsilon",e,t,n))];case"FusedBatchNormV3":return[mi(k("x",e,t,n),k("mean",e,t,n),k("variance",e,t,n),k("offset",e,t,n),k("scale",e,t,n),k("epsilon",e,t,n))];case"LRN":return[ym(k("x",e,t,n),k("radius",e,t,n),k("bias",e,t,n),k("alpha",e,t,n),k("beta",e,t,n))];case"Softmax":return[ic(k("x",e,t,n))];case"LogSoftmax":return[$d(k("x",e,t,n))];case"SparseToDense":return[Om(k("sparseIndices",e,t,n),k("outputShape",e,t,n),k("sparseValues",e,t,n),k("defaultValue",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Hre=(e,t,n)=>{switch(e.op){case"Max":{let i=k("axis",e,t,n),o=k("keepDims",e,t,n);return[Qn(k("x",e,t,n),i,o)]}case"Mean":{let i=k("axis",e,t,n),o=k("keepDims",e,t,n);return[Tt(k("x",e,t,n),i,o)]}case"Min":{let i=k("axis",e,t,n),o=k("keepDims",e,t,n);return[_l(k("x",e,t,n),i,o)]}case"Sum":{let i=k("axis",e,t,n),o=k("keepDims",e,t,n);return[Re(k("x",e,t,n),i,o)]}case"All":{let i=k("axis",e,t,n),o=k("keepDims",e,t,n);return[kd(k("x",e,t,n),i,o)]}case"Any":{let i=k("axis",e,t,n),o=k("keepDims",e,t,n);return[ju(k("x",e,t,n),i,o)]}case"ArgMax":{let i=k("axis",e,t,n);return[Gu(k("x",e,t,n),i)]}case"ArgMin":{let i=k("axis",e,t,n);return[Qf(k("x",e,t,n),i)]}case"Prod":{let i=k("axis",e,t,n),o=k("keepDims",e,t,n);return[zd(k("x",e,t,n),i,o)]}case"Cumsum":{let i=k("axis",e,t,n),o=k("exclusive",e,t,n),l=k("reverse",e,t,n);return[Ed(k("x",e,t,n),i,o,l)]}case"Bincount":let r=k("x",e,t,n),a=k("weights",e,t,n),s=k("size",e,t,n);return[cx(r,a,s)];case"DenseBincount":{let i=k("x",e,t,n),o=k("weights",e,t,n),l=k("size",e,t,n),u=k("binaryOutput",e,t,n);return[mx(i,o,l,u)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},jre=(e,t,n)=>{switch(e.op){case"ConcatV2":case"Concat":{let r=k("n",e,t,n),a=k("axis",e,t,n),s=k("tensors",e,t,n);return s=s.slice(0,r),[lt(s,a)]}case"Gather":{let r=k("x",e,t,n),a=k("indices",e,t,n);return[Ai(r,ge(a,"int32"),0)]}case"GatherV2":{let r=k("axis",e,t,n),a=k("batchDims",e,t,n),s=k("x",e,t,n),i=k("indices",e,t,n);return[Ai(s,ge(i,"int32"),r,a)]}case"Reverse":{let r=k("dims",e,t,n),a=[];for(let i=0;i<r.length;i++)r[i]&&a.push(i);let s=k("x",e,t,n);return[Ln(s,a)]}case"ReverseV2":{let r=k("axis",e,t,n),a=k("x",e,t,n);return[Ln(a,r)]}case"Slice":{let r=k("begin",e,t,n),a=k("size",e,t,n);return[$e(k("x",e,t,n),r,a)]}case"StridedSlice":{let r=k("begin",e,t,n),a=k("end",e,t,n),s=k("strides",e,t,n),i=k("beginMask",e,t,n),o=k("endMask",e,t,n),l=k("ellipsisMask",e,t,n),u=k("newAxisMask",e,t,n),c=k("shrinkAxisMask",e,t,n),h=k("x",e,t,n);return[Rm(h,r,a,s,i,o,l,u,c)]}case"Pack":return B(()=>{let r=k("axis",e,t,n),a=k("tensors",e,t,n),s=a[0].shape,i=Ha(a[0]).shape,o=a.map(l=>{let u=v.arraysEqual(l.shape,s);if(!u&&!v.arraysEqual(Ha(l).shape,i))throw new Error("the input tensors shape does not match");return u?l:G(l,s)});return[An(o,r)]});case"Unpack":{let r=k("axis",e,t,n),a=k("tensor",e,t,n);return hr(a,r)}case"Tile":{let r=k("reps",e,t,n);return[Va(k("x",e,t,n),r)]}case"Split":case"SplitV":{let r=k("axis",e,t,n),a=k("numOrSizeSplits",e,t,n),s=k("x",e,t,n);return Ut(s,a,r)}case"ScatterNd":{let r=k("indices",e,t,n),a=k("values",e,t,n),s=k("shape",e,t,n);return[Dx(r,a,s)]}case"GatherNd":{let r=k("x",e,t,n),a=k("indices",e,t,n);return[Ox(r,a)]}case"SparseToDense":{let r=k("sparseIndices",e,t,n),a=k("outputShape",e,t,n),s=k("sparseValues",e,t,n),i=k("defaultValue",e,t,n);return[Om(r,s,a,s.dtype===i.dtype?i:ge(i,s.dtype))]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},Gre=(e,t,n)=>{switch(e.op){case"FFT":return[oc(k("x",e,t,n))];case"IFFT":return[Il(k("x",e,t,n))];case"RFFT":return[lc(k("x",e,t,n))];case"IRFFT":return[Gd(k("x",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},qre=(e,t,n)=>{switch(e.op){case"Cast":return[ge(k("x",e,t,n),k("dtype",e,t,n))];case"ExpandDims":{let r=k("axis",e,t,n);return[mn(k("x",e,t,n),r)]}case"Squeeze":{let r=k("axis",e,t,n);return[Ha(k("x",e,t,n),r)]}case"Reshape":return[G(k("x",e,t,n),k("shape",e,t,n))];case"MirrorPad":return[_m(k("x",e,t,n),k("padding",e,t,n),k("mode",e,t,n))];case"PadV2":case"Pad":return[ca(k("x",e,t,n),k("padding",e,t,n),k("constantValue",e,t,n))];case"SpaceToBatchND":{let r=k("blockShape",e,t,n),a=k("paddings",e,t,n);return[nc(k("x",e,t,n),r,a)]}case"BatchToSpaceND":{let r=k("blockShape",e,t,n),a=k("crops",e,t,n);return[Ku(k("x",e,t,n),r,a)]}case"DepthToSpace":{let r=k("blockSize",e,t,n),a=k("dataFormat",e,t,n).toUpperCase();return[hm(k("x",e,t,n),r,a)]}case"BroadcastTo":return[Zu(k("x",e,t,n),k("shape",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}};function t6(e,t,n,r){let a=((s,i,o)=>{switch(s.category){case"arithmetic":return B(()=>Ire(s,i,o));case"basic_math":return B(()=>Nre(s,i,o));case"control":return Fre(s,i,o);case"convolution":return B(()=>Mre(s,i,o));case"creation":return B(()=>$re(s,i,o));case"dynamic":return Dre(s,i,o);case"evaluation":return B(()=>Ore(s,i,o));case"image":return B(()=>Wre(s,i,o));case"graph":return B(()=>zre(s,i,o));case"logical":return B(()=>Bre(s,i,o));case"matrices":return B(()=>Vre(s,i,o));case"normalization":return B(()=>Ure(s,i,o));case"reduction":return B(()=>Hre(s,i,o));case"slice_join":return B(()=>jre(s,i,o));case"spectral":return B(()=>Gre(s,i,o));case"transformation":return B(()=>qre(s,i,o));case"hash_table":return Lre(s,i,o,r);case"custom":let l=Rv(s.op);if(l&&l.customExecutor)return l.customExecutor(new kre(s,i,o));throw TypeError(`Custom op ${s.op} is not registered.`);default:throw TypeError(`Unknown op '${s.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 v.isPromise(a)?a.then(s=>[].concat(s)):[].concat(a)}var n6=class{constructor(e={},t={},n={},r={}){this.weightMap=e,this.tensorArrayMap=t,this.tensorListMap=n,this.functionMap=r,this.rootContext={id:0,frameName:"",iterationId:0},this.contexts=[this.rootContext],this.lastId=0,this.generateCurrentContextIds()}newFrame(e,t){return{id:e,frameName:t,iterationId:0}}set currentContext(e){this.contexts!==e&&(this.contexts=e,this.generateCurrentContextIds())}get currentContext(){return this.contexts}get currentContextId(){return this._currentContextIds[0]}get currentContextIds(){return this._currentContextIds}generateCurrentContextIds(){let e=[];for(let t=0;t<this.contexts.length-1;t++){let 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 a6(e,t,n,r){let a=new Set,s=[],i=null,o=null,l=new Set,u=Object.keys(e).map(d=>Hn(d)[0]),c=[];r!=null&&(c=r.map(d=>Hn(d.name)[0]));let h=[...t];for(;h.length>0;){let d=h.pop();if((r6(d)||Xre(d)||Kre(d))&&i==null&&(i=d,o=i.children.map(p=>p.name).filter(p=>a.has(p))),a.add(d.name),n[d.name]==null&&u.indexOf(d.name)===-1&&c.indexOf(d.name)===-1){if(d.inputs.length===0){s.push(d.name);continue}d.inputs.forEach(p=>{l.has(p.name)||(l.add(p.name),h.push(p))})}}return{inputs:e,outputs:t,usedNodes:a,missingInputs:s,dynamicNode:i,syncInputs:o}}function Zre(e,t,n){let{usedNodes:r,inputs:a}=n,s=[],i=Object.keys(a).map(c=>Hn(c)[0]).map(c=>e.nodes[c]),o=e.initNodes;i.forEach(c=>{r.has(c.name)&&s.push(c)}),e.weights.forEach(c=>{r.has(c.name)&&s.push(c)}),o!=null&&o.forEach(c=>{r.has(c.name)&&s.push(c)});let l=new Set,u=[];for(;s.length>0;){let c=s.pop();l.add(c.name),t[c.name]||u.push(c),c.children.forEach(h=>{!l.has(h.name)&&r.has(h.name)&&h.inputs.every(d=>l.has(d.name))&&s.push(h)})}return u}var Yre=["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"],Jre=["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"],Qre=["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2","LookupTableSize","LookupTableSizeV2"];function r6(e){return Yre.indexOf(e.op)>=0}function Xre(e){return Jre.indexOf(e.op)>=0}function Kre(e){return Qre.indexOf(e.op)>=0}var Ng=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 Ng(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(r=>r.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(a=>a.name).sort(),r=t.map(a=>a.name).sort();return n.join(this.SEPERATOR)+"--"+r.join(this.SEPERATOR)}compile(e,t){let n=a6(e,t,this.weightMap,this._initNodes),{missingInputs:r,dynamicNode:a,syncInputs:s}=n;if(a!=null)throw new Error(`This execution contains the node '${a.name}', which has the dynamic op '${a.op}'. Please use model.executeAsync() instead. Alternatively, to avoid the dynamic ops, specify the inputs [${s}]`);if(r.length>0){let i=t.map(l=>l.name),o=Object.keys(e);throw new Error(`Cannot compute the outputs [${i}] from the provided inputs [${o}]. Missing the following inputs: [${r}]`)}return Zre(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 r=n.map(c=>this.graph.nodes[Hn(c)[0]]),a=t.map(c=>Hn(c)[0]),s=a.map(c=>this.graph.nodes[c]);s.length===0&&(s=this._outputs);let i=this.getCompilationKey(r,s),o=this.compiledMap.get(i);o==null&&(o=this.compile(e,s),this.compiledMap.set(i,o));let l={},u={};return B(()=>{let c=new n6(this.weightMap,l,u,this.functionExecutorMap),h=Object.assign({},this.weightMap);Object.keys(e).forEach(f=>{let[m,A]=Hn(f),y=[];y[A]=e[f],h[m]=y});let d=this.getFrozenTensorIds(h),p={};for(let f=0;f<o.length;f++){let m=o[f];if(!h[m.name]){let A=t6(m,h,c,this._resourceManager);if(v.isPromise(A))throw new Error(`The execution of the op '${m.op}' returned a promise. Please use model.executeAsync() instead.`);h[m.name]=A,this.checkTensorForDisposal(m.name,m,h,c,d,a,p)}}return this.parent==null&&c.dispose(d),t.map(f=>$n(f,h,c))})}getFrozenTensorIds(e){let t=[].concat.apply([],Object.keys(e).map(n=>e[n]).map(n=>n.map(r=>r.id)));return new Set(t)}checkTensorForDisposal(e,t,n,r,a,s,i){t.category==="control"||s.indexOf(e)!==-1||(n[e].forEach(o=>{o!=null&&(i[o.id]=(i[o.id]||0)+t.children.length)}),t.inputs.forEach(o=>{if(o.category!=="control"){let l=sre(o.name,n,r);l!=null&&l.forEach(u=>{if(u&&!a.has(u.id)){let c=i[u.id];c===1?(u.dispose(),delete i[u.id]):c!=null&&i[u.id]--}})}}))}async executeAsync(e,t){return this._executeAsync(e,t)}async _executeAsync(e,t,n=!1,r={},a={}){n||(e=this.mapInputs(e),this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t));let s=new n6(this.weightMap,r,a,this.functionExecutorMap),i=await this.executeWithControlFlow(e,s,t,n),o=t.map(h=>$n(h,i,s)),l=o.map(h=>h.id),u=Object.keys(e).map(h=>e[h].id),c=new Set([...l,...u,...this.weightIds]);return Object.keys(i).forEach(h=>{i[h].forEach(d=>{d&&!d.isDisposed&&!c.has(d.id)&&d.dispose()})}),this.parent==null&&s.dispose(c),o}async executeFunctionAsync(e,t,n){let r=e.reduce((a,s,i)=>(a[this.inputs[i].name]=s,a),{});return this._executeAsync(r,this.outputNodes,!0,t,n)}async executeWithControlFlow(e,t,n,r){let a=Object.keys(e),s=a.map(g=>this.graph.nodes[Hn(g)[0]]),i=n.map(g=>Hn(g)[0]),o=i.map(g=>this.graph.nodes[g]);o.length===0&&(o=this._outputs);let{usedNodes:l,missingInputs:u,dynamicNode:c,syncInputs:h}=a6(e,o,this.weightMap,this._initNodes),d=[...s,...this.graph.weights,...this._initNodes||[]].map(g=>({node:g,contexts:t.currentContext})),p=Object.assign({},this.weightMap);Object.keys(e).forEach(g=>{let[b,_]=Hn(g),w=[];w[_]=e[g],p[b]=w});let f={},m=this.getFrozenTensorIds(p),A={};for(;d.length>0;){let g=this.processStack(s,d,t,p,A,m,i,f,l);await Promise.all(g)}c==null&&!r&&console.warn("This model execution did not contain any nodes with control flow or dynamic output shapes. You can use model.execute() instead.");let y=o.filter(g=>!r6(g)&&!$n(g.name,p,t)).map(g=>g.name);if(y.length>0){let g="";throw c!=null&&(g=`Alternatively, to avoid the dynamic ops, use model.execute() and specify the inputs [${h}]`),new Error(`Cannot compute the outputs [${y}] from the provided inputs [${a}]. Consider providing the following inputs: [${u}]. ${g}`)}return p}processStack(e,t,n,r,a,s,i,o,l){let u=[];for(;t.length>0;){let c=t.pop();n.currentContext=c.contexts;let h="";if(c.node.op==="Enter"&&k("isConstant",c.node,r,n)&&([h]=ga(c.node.name,n)),r[c.node.name]==null){let d=t6(c.node,r,n,this._resourceManager);h||([h]=ga(c.node.name,n));let p=n.currentContext;v.isPromise(d)?u.push(d.then(f=>(r[h]=f,n.currentContext=p,this.checkTensorForDisposal(h,c.node,r,n,s,i,o),this.processChildNodes(c.node,t,n,r,a,l),f))):(r[h]=d,this.checkTensorForDisposal(h,c.node,r,n,s,i,o),this.processChildNodes(c.node,t,n,r,a,l))}else this.processChildNodes(c.node,t,n,r,a,l)}return u}processChildNodes(e,t,n,r,a,s){e.children.forEach(i=>{let[o]=ga(i.name,n);a[o]||!s.has(i.name)||(i.op==="Merge"?i.inputNames.some(l=>!!$n(l,r,n))&&(a[o]=!0,t.push({contexts:n.currentContext,node:i})):i.inputNames.every(l=>!!$n(l,r,n))&&(a[o]=!0,t.push({contexts:n.currentContext,node:i})))})}dispose(){Object.keys(this.weightMap).forEach(e=>this.weightMap[e].forEach(t=>t.dispose()))}checkInputShapeAndType(e){Object.keys(e).forEach(t=>{let n=e[t],[r]=Hn(t),a=this.graph.nodes[r];if(a.attrParams.shape&&a.attrParams.shape.value){let s=a.attrParams.shape.value,i=s.length===n.shape.length&&n.shape.every((o,l)=>s[l]===-1||s[l]===o);v.assert(i,()=>`The shape of dict['${a.name}'] provided in model.execute(dict) must be [${s}], but was [${n.shape}]`)}a.attrParams.dtype&&a.attrParams.dtype.value&&v.assert(n.dtype===a.attrParams.dtype.value,()=>`The dtype of dict['${a.name}'] provided in model.execute(dict) must be ${a.attrParams.dtype.value}, but was ${n.dtype}`)})}mapInputs(e){let t={};for(let n in e)if(this._signature!=null&&this._signature.inputs!=null&&this._signature.inputs[n]!=null){let r=this._signature.inputs[n];t[r.name]=e[n]}else t[n]=e[n];return t}checkInputs(e){let t=Object.keys(e).filter(n=>{let[r]=Hn(n);return this.graph.nodes[r]==null});if(t.length>0)throw new Error(`The dict provided in model.execute(dict) has keys: [${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]=Hn(t);if(!this.graph.nodes[n])throw new Error(`The output '${t}' is not found in the graph`)})}},eae=class{constructor(e={},t={}){this.hashTableNameToHandle=e,this.hashTableMap=t}addHashTable(e,t){this.hashTableNameToHandle[e]=t.handle,this.hashTableMap[t.id]=t}getHashTableHandleByName(e){return this.hashTableNameToHandle[e]}getHashTableById(e){return this.hashTableMap[e]}dispose(){for(let e in this.hashTableMap)this.hashTableMap[e].clearAndClose(),delete this.hashTableMap[e];for(let e in this.hashTableNameToHandle)this.hashTableNameToHandle[e].dispose(),delete this.hashTableNameToHandle[e]}},tae="?tfjs-format=file",nae="model.json",s6=class{constructor(e,t={}){this.modelUrl=e,this.loadOptions=t,this.version="n/a",t==null&&(this.loadOptions={}),this.resourceManager=new eae}get modelVersion(){return this.version}get inputNodes(){return this.executor.inputNodes}get outputNodes(){return this.executor.outputNodes}get inputs(){return this.executor.inputs}get outputs(){return this.executor.outputs}get weights(){return this.executor.weightMap}get metadata(){return this.artifacts.userDefinedMetadata}get modelSignature(){return this.signature}findIOHandler(){let e=this.modelUrl;if(e.load!=null)this.handler=e;else if(this.loadOptions.requestInit!=null)this.handler=Nn.browserHTTPRequest(e,this.loadOptions);else{let t=Nn.getLoadHandlers(e,this.loadOptions);if(t.length===0)t.push(Nn.browserHTTPRequest(e,this.loadOptions));else if(t.length>1)throw new Error(`Found more than one (${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}.${t.versions.minConsumer}`;let r=Nn.decodeWeights(this.artifacts.weightData,this.artifacts.weightSpecs);if(this.executor=new Ng(Zv.Instance.transformGraph(t,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(r),this.executor.resourceManager=this.resourceManager,e.modelInitializer!=null&&e.modelInitializer.node!=null){let a=Zv.Instance.transformGraph(e.modelInitializer);this.initializer=new Ng(a),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializer.executeAsync({},[])}return!0}async save(e,t){if(typeof e=="string"){let n=Nn.getSaveHandlers(e);if(n.length===0)throw new Error(`Cannot find any save handlers for URL '${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 ${e.length} input tensors.`);return this.inputNodes.reduce((t,n,r)=>(t[n]=e[r],t),{})}normalizeOutputs(e){return e=e||this.outputNodes,Array.isArray(e)?e:[e]}execute(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let n=this.executor.execute(e,t);return n.length>1?n:n[0]}async executeAsync(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let n=await this.executor.executeAsync(e,t);return n.length>1?n:n[0]}convertTensorMapToTensorsMap(e){return Object.keys(e).reduce((t,n)=>(t[n]=[e[n]],t),{})}dispose(){this.executor.dispose(),this.initializer&&this.initializer.dispose(),this.resourceManager.dispose()}};async function Ot(e,t={}){if(e==null)throw new Error("modelUrl in loadGraphModel() cannot be null. Please provide a url or an IOHandler that loads the model");t==null&&(t={}),t.fromTFHub&&e.load==null&&(e.endsWith("/")||(e=e+"/"),e=`${e}${nae}${tae}`);let n=new s6(e,t);return await n.load(),n}var rae="3.3.0",i6={};We(i6,{CSVDataset:()=>l6,Dataset:()=>Yl,FileDataSource:()=>u6,TextLineDataset:()=>o6,URLDataSource:()=>c6,array:()=>aae,csv:()=>iae,func:()=>oae,generator:()=>lae,microphone:()=>cae,version_data:()=>hae,webcam:()=>uae,zip:()=>sae});var dae=no(Z2()),pae=no(Z2());function fae(e,t){return y0(e,t)}function y0(e,t,n=new Map,r=new Set){if(e==null)return null;if(r.has(e))throw new Error("Circular references are not supported.");if(n.has(e))return n.get(e);let a=t(e);if(a.recurse&&a.value!==null)throw new Error("A deep map function may not return both a value and recurse=true.");if(a.recurse)if(Jl(e)){let s=Array.isArray(e)?[]:{};r.add(e);for(let i in e){let o=e[i],l=y0(o,t,n,r);s[i]=l}return r.delete(e),s}else throw new Error(`Can't recurse into non-iterable type: ${e}`);else return n.set(e,a.value),a.value}function mae(e,t=d6){return h6(e,t)}function h6(e,t,n=new Set){let r=e[0];if(n.has(r))throw new Error("Circular references are not supported.");let a=t(e);if(a.recurse&&a.value!==null)throw new Error("A deep zip function may not return both a value and recurse=true.");if(a.recurse)if(Jl(r)){let s=Array.isArray(r)?[]:{};n.add(r);for(let i in r){let o=e.map(u=>u[i]),l=h6(o,t,n);s[i]=l}return n.delete(r),s}else throw new Error(`Can't recurse into non-iterable type: ${r}`);else return a.value}function d6(e){return e===null?null:Jl(e[0])?{value:null,recurse:!0}:{value:e,recurse:!1}}async function p6(e,t){let n=new Map;y0(e,t,n);for(let r of Array.from(n.keys())){let a=n.get(r);if(v.isPromise(a)){let s=await a;n.set(r,s)}}return y0(e,t,n)}function Jl(e){return e!=null&&!ArrayBuffer.isView(e)&&(Array.isArray(e)||typeof e=="object"&&!(e instanceof Ge))}function yae(e){return e==null||Aae(e)||Array.isArray(e)||typeof e=="object"&&e instanceof Ge||v.isTypedArray(e)}function Aae(e){return e===null||typeof e!="object"&&typeof e!="function"}function xae(e){return fae(e,gae)}function gae(e){return e instanceof Ge?{value:e.clone(),recurse:!1}:Jl(e)?{value:null,recurse:!0}:{value:e,recurse:!1}}var f6=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}},Sg=class extends f6{constructor(){super(Sg.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 r=0;r<n;r++)t[r]=this.get(this.wrap(this.begin+r));this.data=t,this.capacity=e,this.doubledCapacity=2*this.capacity,this.begin=0,this.end=n}};Sg.INITIAL_CAPACITY=32;function m6(e){return new wae(e)}function Tg(e){return new bae(e)}function _ae(e,t){return new A6(e,t)}function kae(e,t=ns.FAIL){return new vae(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 Rae(this,e)}filter(e){return new Eae(this,e)}map(e){return new Cae(this,e)}mapAsync(e){return new y6(this,e)}serialMapAsync(e){return new y6(this,e).serial()}flatmap(e){return new Fae(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 Tae(this,e,t)}columnMajorBatch(e,t=!0,n=d6){return this.rowMajorBatch(e,t).map(r=>mae(r,n))}concatenate(e,t){return new A6(m6([this,e]),t)}take(e){return e<0||e==null?this:new Sae(this,e)}skip(e){return e<0||e==null?this:new Nae(this,e)}prefetch(e){return new g6(this,e)}shuffle(e,t){return new Mae(this,e,t)}serial(){return new Iae(this)}},wae=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:xae(e),done:!1}}},bae=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: ${e.message}`,e}}},Iae=class extends en{constructor(e){super();this.upstream=e,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Serial`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){return this.upstream.next()}},Nae=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`${this.upstream.summary()} -> Skip`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;this.count++<this.maxCount;){let e=await this.upstream.next();if(e.done)return e;Me(e.value)}return this.upstream.next()}},Sae=class extends en{constructor(e,t){super();this.upstream=e,this.maxCount=t,this.count=0}summary(){return`${this.upstream.summary()} -> Take`}async next(){return this.count++>=this.maxCount?{value:null,done:!0}:this.upstream.next()}},Tae=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`${this.upstream.summary()} -> RowMajorBatch`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){let e=[];for(;e.length<this.batchSize;){let t=await this.upstream.next();if(t.done)return this.enableSmallLastBatch&&e.length>0?{value:e,done:!1}:{value:null,done:!0};e.push(t.value)}return{value:e,done:!1}}},Eae=class extends en{constructor(e,t){super();this.upstream=e,this.predicate=t,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${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;Me(e.value)}}},Cae=class extends en{constructor(e,t){super();this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Map`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=br.getTensorsInContainer(e.value),n=this.transform(e.value),r=br.getTensorsInContainer(n);for(let a of t)br.isTensorInList(a,r)||a.dispose();return{value:n,done:!1}}},Rae=class extends en{constructor(e,t){super();this.upstream=e,this.handler=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${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}}}},y6=class extends en{constructor(e,t){super();this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> AsyncMap`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=br.getTensorsInContainer(e.value),n=await this.transform(e.value),r=br.getTensorsInContainer(n);for(let a of t)br.isTensorInList(a,r)||a.dispose();return{value:n,done:!1}}},Eg=class extends en{constructor(){super();this.outputQueue=new Sg,this.lastRead=Promise.resolve({value:null,done:!1})}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;this.outputQueue.length()===0;)if(!await this.pump())return{value:null,done:!0};return{value:this.outputQueue.shift(),done:!1}}},Fae=class extends Eg{constructor(e,t){super();this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Flatmap`}async pump(){let e=await this.upstream.next();if(e.done)return!1;let t=br.getTensorsInContainer(e.value),n=this.transform(e.value),r=br.getTensorsInContainer(n);this.outputQueue.pushAll(n);for(let a of t)br.isTensorInList(a,r)||a.dispose();return!0}},A6=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}},ns;(function(e){e[e.FAIL=0]="FAIL",e[e.SHORTEST=1]="SHORTEST",e[e.LONGEST=2]="LONGEST"})(ns||(ns={}));var vae=class extends en{constructor(e,t=ns.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 r(s){return s instanceof en?{value:s.next().then(i=>(t++,i.done&&n++,i.value)),recurse:!1}:{value:null,recurse:!0}}let a=await p6(this.iterators,r);if(t===n)return{value:null,done:!0};if(n>0)switch(this.mismatchMode){case ns.FAIL:throw new Error(`Zipped streams should have the same length. Mismatched at element ${this.count}.`);case ns.SHORTEST:return{value:null,done:!0};case ns.LONGEST:default:}return this.count++,{value:a,done:!1}}async next(){return this.currentPromise=this.nextState(this.currentPromise),this.currentPromise}},g6=class extends en{constructor(e,t){super();this.upstream=e,this.bufferSize=t,this.buffer=new f6(t)}summary(){return`${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()}},Mae=class extends g6{constructor(e,t,n){super(e,t);this.upstream=e,this.windowSize=t,this.upstreamExhausted=!1,this.random=pae.alea(n||v.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;v.assert(e>0,()=>`batchSize needs to be positive, but it is
|
|
${e}`);let r;return this.size===Infinity||this.size==null?r=this.size:t?r=Math.ceil(this.size/e):r=Math.floor(this.size/e),jn(async()=>(await n.iterator()).columnMajorBatch(e,t,$ae),r)}concatenate(e){let t=this,n;return this.size===Infinity||e.size===Infinity?n=Infinity:this.size!=null&&e.size!=null?n=this.size+e.size:n=null,jn(async()=>(await t.iterator()).concatenate(await e.iterator()),n)}filter(e){let t=this,n;return this.size===Infinity?n=Infinity:n=null,jn(async()=>(await t.iterator()).filter(r=>B(()=>e(r))),n)}async forEachAsync(e){return(await this.iterator()).forEachAsync(e)}map(e){let t=this;return jn(async()=>(await t.iterator()).map(n=>B(()=>e(n))),this.size)}mapAsync(e){let t=this;return jn(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 jn(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=Infinity:n=null,jn(async()=>{let r=Tg(async()=>({value:await t.iterator(),done:!1}));return _ae(r.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,jn(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 r=this,a=dae.alea(t||v.now().toString());return jn(async()=>{let s=a.int32();return n&&(s+=a.int32()),(await r.iterator()).shuffle(e,s.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,jn(async()=>(await t.iterator()).take(e),n)}async toArray(){if(this.size===Infinity)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArray()}async toArrayForTest(){if(this.size===Infinity)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArrayForTest()}};Yl.MAX_BUFFER_SIZE=1e4;function jn(e,t=null){return new class extends Yl{constructor(){super(...arguments);this.size=t}async iterator(){return e()}}}function aae(e){return jn(async()=>m6(e),e.length)}function sae(e){if(!Jl(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 jn(async()=>{let n=await p6(e,r=>{if(r instanceof Yl)return{value:r.iterator(),recurse:!1};if(Jl(r))return{value:null,recurse:!0};throw new Error("Leaves of the structure passed to zip() must be Datasets, not primitives.")});return kae(n,ns.SHORTEST)},t)}function $ae(e){if(e===null)return null;let t=e[0];return yae(t)?{value:Dae(e),recurse:!1}:{value:null,recurse:!0}}function Dae(e){if(e.length===0)throw new Error("Can't make a batch of zero elements.");return e[0]instanceof Ge?An(e):vr(e)}var o6=class extends Yl{constructor(e){super();this.input=e}async iterator(){return(await this.input.iterator()).decodeUTF8().split(`
|
|
`).map(e=>(e.endsWith("\r")&&(e=e.slice(0,-1)),e))}},g0='"',qc=Symbol("out"),x6=Symbol("field"),x0=Symbol("quote"),Cg=Symbol("quoteafterquote"),w6=Symbol("quoteinquote"),l6=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 o6(e),t||(t={}),this.hasHeader=t.hasHeader!==!1,this.fullColumnNames=t.columnNames,this.columnConfigs=t.columnConfigs,this.configuredColumnsOnly=t.configuredColumnsOnly,t.delimWhitespace?(v.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&&v.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((r,a)=>(r[a]=r[a]+1||1,r),{}),n=Object.keys(t).filter(r=>t[r]>1);if(v.assert(n.length===0,()=>"Duplicate column names found: "+n.toString()),this.columnConfigs){for(let r of Object.keys(this.columnConfigs))if(this.fullColumnNames.indexOf(r)===-1)throw new Error('The key "'+r+'" provided in columnConfigs does not match any of the column names ('+this.fullColumnNames.toString()+").")}this.columnNamesValidated=!0}async maybeReadHeaderLine(){if(this.hasHeader){let e=await(await this.base.iterator()).next();if(e.done)throw new Error("No data was found for CSV parsing.");let t=e.value;return this.parseRow(t,!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={},r={};for(let a=0;a<this.fullColumnNames.length;a++){let s=this.fullColumnNames[a],i=this.columnConfigs?this.columnConfigs[s]:null;if(!(this.configuredColumnsOnly&&!i)){let o=t[a],l=null;if(o==="")if(i&&i.default!==void 0)l=i.default;else{if(i&&(i.required||i.isLabel))throw new Error(`Required column ${s} is empty in this line: ${e}`);l=void 0}else{let u=Number(o);if(isNaN(u))i&&i.dtype==="bool"?l=this.getBoolean(o):l=o;else if(!i||!i.dtype)l=u;else switch(i.dtype){case"float32":l=u;break;case"int32":l=Math.floor(u);break;case"bool":l=this.getBoolean(o);break;default:l=u}}i&&i.isLabel?r[s]=l:n[s]=l}}return Object.keys(r).length===0?n:{xs:n,ys:r}}getBoolean(e){return e==="1"||e.toLowerCase()==="true"?1:0}parseRow(e,t=!0){let n=[],r=0,a=e.length,s=qc;for(let i=0;i<a;i++)switch(s){case qc:switch(e.charAt(i)){case g0:r=i+1,s=x0;break;case this.delimiter:if(r=i+1,this.delimiter===" "&&this.delimWhitespace)break;n.push(""),s=qc;break;default:s=x6,r=i;break}break;case x6:switch(e.charAt(i)){case this.delimiter:n.push(e.substring(r,i)),s=qc,r=i+1;break;default:}break;case x0:switch(e.charAt(i)){case g0:s=Cg;break;default:}break;case Cg:switch(e.charAt(i)){case this.delimiter:n.push(e.substring(r,i-1)),s=qc,r=i+1;break;case g0:s=x0;break;default:s=w6;break}break;case w6:switch(e.charAt(i)){case g0:s=x0;break;default:}break;default:}if(s===Cg?n.push(e.substring(r,a-1)):n.push(e.substring(r)),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}},b6=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(J().get("IS_NODE"))throw new Error("microphone API is only supported in browser environment.");let t=new b6(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 r=this.flattenQueue(n.freqDataQueue);e=this.getTensorFromAudioDataArray(r,[this.numFrames,this.columnTruncateLength,1])}if(this.includeWaveform){let r=this.flattenQueue(n.timeDataQueue);t=this.getTensorFromAudioDataArray(r,[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(r=>{let a=setInterval(()=>{this.includeSpectrogram&&(this.analyser.getFloatFrequencyData(this.freqData),this.freqData[0]===-Infinity&&r({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(a),r({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((r,a)=>n.set(r,a*t)),n}getTensorFromAudioDataArray(e,t){let n=new Float32Array(v.sizeFromShape(t));return n.set(e,n.length-e.length),vr(n,t)}},_6=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=hn([0],"int32"),this.webcamConfig.centerCrop){let n=this.webcamConfig.resizeWidth*1/this.webcamVideoElement.width,r=this.webcamConfig.resizeHeight*1/this.webcamVideoElement.height,a=(1-n)/2,s=(1-r)/2,i=a+n,o=r+s;this.cropBox=En([s,a,o,i],[1,4])}else this.cropBox=En([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(e,t={}){if(J().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 _6(e,t);return await n.start(),n}async start(){this.webcamConfig.facingMode&&v.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=dl.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: ${t.message}`)}finally{e.dispose()}else return{value:e,done:!1}}needToResize(){return!!(this.webcamConfig.resizeWidth&&this.webcamConfig.resizeHeight&&(this.webcamVideoElement.width!==this.webcamConfig.resizeWidth||this.webcamVideoElement.height!==this.webcamConfig.resizeHeight))}cropAndResizeFrame(e){return B(()=>{let t=mn(ge(e,"float32"),0),n;n=tt.cropAndResize(t,this.cropBox,this.cropBoxInd,this.cropSize,"bilinear");let r=n.shape;return G(n,r.slice(1))})}async capture(){return(await this.next()).value}stop(){this.stream.getTracks().forEach(e=>e.stop());try{this.webcamVideoElement.srcObject=null}catch(e){console.log(e),this.webcamVideoElement.src=null}this.isClosed=!0}toArray(){throw new Error("Can not convert infinite video stream to array.")}},v6=class{},k6=class extends en{split(e){return new Oae(this,e)}},Oae=class extends k6{constructor(e,t){super();this.upstream=e,this.impl=new zae(e,t)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},zae=class extends Eg{constructor(e,t){super();this.upstream=e,this.separator=t,this.carryover=""}summary(){return`${this.upstream.summary()} -> Split('${this.separator}')`}async pump(){let e=await this.upstream.next();if(e.done)return this.carryover===""?!1:(this.outputQueue.push(this.carryover),this.carryover="",!0);let t=e.value.split(this.separator);t[0]=this.carryover+t[0];for(let n of t.slice(0,-1))this.outputQueue.push(n);return this.carryover=t[t.length-1],!0}},Lae=class extends en{decodeUTF8(){return new Pae(this)}},Pae=class extends k6{constructor(e){super();this.upstream=e,this.impl=new Wae(e)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},Wae=class extends Eg{constructor(e){super();if(this.upstream=e,J().get("IS_BROWSER"))this.decoder=new TextDecoder("utf-8");else{let{StringDecoder:t}=Ik();this.decoder=new t("utf8")}}summary(){return`${this.upstream.summary()} -> Utf8`}async pump(){let e=await this.upstream.next(),t;if(e.done)return!1;t=e.value;let n;return J().get("IS_BROWSER")?n=this.decoder.decode(t,{stream:!0}):n=this.decoder.write(Buffer.from(t.buffer)),this.outputQueue.push(n),!0}},I6=class extends Lae{constructor(e,t={}){super();this.file=e,this.options=t,v.assert(e instanceof Uint8Array||(J().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((e,t)=>{let n=this.offset+this.chunkSize;if(this.file instanceof Uint8Array)e(new Uint8Array(this.file.slice(this.offset,n)));else{let r=new FileReader;r.onload=s=>{let i=r.result;if(i instanceof ArrayBuffer&&(i=new Uint8Array(i)),!(i instanceof Uint8Array))return t(new TypeError("FileReader returned unknown type."));e(i)},r.onabort=s=>t(new Error("Aborted")),r.onerror=s=>t(new Error(s.type));let a=this.file.slice(this.offset,n);r.readAsArrayBuffer(a)}this.offset=n}),done:!1}}};async function Vae(e,t={}){let n,r;typeof e=="string"?n=e:(n=e.url,r=Bae(e));let a=await v.fetch(n,r);if(a.ok){let s=new Uint8Array(await a.arrayBuffer());return new I6(s,t)}else throw new Error(a.statusText)}var Bae=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 N6(e){return typeof e=="string"&&e.substr(0,7)==="file://"}var u6=class extends v6{constructor(e,t={}){super();this.input=e,this.options=t}async iterator(){if(N6(this.input)&&J().get("IS_NODE")){let e=require("fs");this.input=e.readFileSync(this.input.substr(7))}return new I6(this.input,this.options)}},c6=class extends v6{constructor(e,t={}){super();this.url=e,this.fileOptions=t}async iterator(){return N6(this.url)?new u6(this.url,this.fileOptions).iterator():Vae(this.url,this.fileOptions)}};function iae(e,t={}){return new l6(new c6(e),t)}function oae(e){let t=Tg(e);return jn(async()=>t)}function lae(e){return jn(async()=>{let t=await e();return Tg(()=>t.next())})}async function uae(e,t){return _6.create(e,t)}async function cae(e){return b6.create(e)}var hae="3.3.0",Uae={tfjs:Nk,"tfjs-core":Sk,"tfjs-data":Tk,"tfjs-layers":Ek,"tfjs-converter":Ck,"tfjs-backend-cpu":Nw,"tfjs-backend-webgl":Xb,"tfjs-backend-wasm":P3};var Gn={name:"humangl",priority:99,canvas:null,gl:null,width:1024,height:1024,webGLattr:{alpha:!1,antialias:!1,premultipliedAlpha:!1,preserveDrawingBuffer:!1,depth:!1,stencil:!1,failIfMajorPerformanceCaveat:!1,desynchronized:!0}};function S6(){if(!Zf(Gn.name)){Fe("backend registration:",Gn.name);try{Gn.canvas=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(Gn.width,Gn.height):document.createElement("canvas")}catch(e){Fe("error: cannot create canvas:",e);return}try{Gn.gl=Gn.canvas.getContext("webgl2",Gn.webGLattr)}catch(e){Fe("error: cannot get WebGL2 context:",e);return}try{yp(2,Gn.gl)}catch(e){Fe("error: cannot set WebGL2 context:",e);return}try{let e=new bp(Gn.gl);fl(Gn.name,()=>new Ll(e),Gn.priority)}catch(e){Fe("error: cannot register WebGL backend:",e);return}try{il("webgl").forEach(t=>{let n={...t,backendName:Gn.name};ui(n)})}catch(e){Fe("error: cannot update WebGL backend registration:",e);return}try{wr.set("WEBGL_VERSION",2)}catch(e){Fe("error: cannot set WebGL backend flags:",e);return}Fe("backend registered:",Gn.name)}}var T6=6;function Hae(e){let t={strides:[e/16,e/8],anchors:[2,6]},n=[];for(let r=0;r<t.strides.length;r++){let a=t.strides[r],s=Math.floor((e+a-1)/a),i=Math.floor((e+a-1)/a),o=t.anchors[r];for(let l=0;l<s;l++){let u=a*(l+.5);for(let c=0;c<i;c++){let h=a*(c+.5);for(let d=0;d<o;d++)n.push([h,u])}}}return n}var jae=e=>({startEndTensor:e,startPoint:$e(e,[0,0],[-1,2]),endPoint:$e(e,[0,2],[-1,2])});function Gae(e,t,n){let r=$e(e,[0,1],[-1,2]),a=ie(r,t),s=$e(e,[0,3],[-1,2]),i=be(s,n),o=be(a,n),l=be(i,2),u=we(o,l),c=ie(o,l),h=P(u,n),d=P(c,n);return yl([h,d],1)}var E6=class{constructor(t,n){this.model=t,this.anchorsData=Hae(t.inputs[0].shape[1]),this.anchors=En(this.anchorsData),this.inputSize=t.inputs[0].shape[2],this.config=n}async getBoundingBoxes(t){if(!t||t.isDisposedInternal||t.shape.length!==4||t.shape[1]<1||t.shape[2]<1)return null;let[n,r,a]=B(()=>{let d=t.resizeBilinear([this.inputSize,this.inputSize]).div(127.5).sub(.5),p=this.model.predict(d),f;if(Array.isArray(p)){let g=p.sort((x,N)=>x.size-N.size),b=lt([g[0],g[2]],2),_=lt([g[1],g[3]],2);f=lt([_,b],1).squeeze(0)}else f=p.squeeze();let m=Gae(f,this.anchors,[this.inputSize,this.inputSize]),A=$e(f,[0,0],[-1,1]),y=On(A).squeeze();return[f,m,y]}),s=await tt.nonMaxSuppressionAsync(r,a,this.config.face.detector.maxFaces,this.config.face.detector.iouThreshold,this.config.face.detector.scoreThreshold),i=s.arraySync();s.dispose();let l=i.map(h=>$e(r,[h,0],[1,-1])).map(h=>{let d=h.arraySync();return h.dispose(),d}),u=a.dataSync(),c=[];for(let h=0;h<l.length;h++){let d=i[h],p=u[d];if(p>this.config.face.detector.minConfidence){let f=jae(l[h]),m=this.anchorsData[d],A=B(()=>$e(n,[d,T6-1],[1,-1]).squeeze().reshape([T6,-1]));c.push({box:f,landmarks:A,anchor:m,confidence:p})}}return n.dispose(),r.dispose(),a.dispose(),{boxes:c,scaleFactor:[t.shape[2]/this.inputSize,t.shape[1]/this.inputSize]}}};async function C6(e){let t=await Ot(e.face.detector.modelPath,{fromTFHub:e.face.detector.modelPath.includes("tfhub.dev")}),n=new E6(t,e);return e.debug&&Fe(`load model: ${e.face.detector.modelPath.match(/\/(.*)\./)[1]}`),n}function R6(e,t){let n=[e.startPoint[0]*t[0],e.startPoint[1]*t[1]],r=[e.endPoint[0]*t[0],e.endPoint[1]*t[1]];return{startPoint:n,endPoint:r}}function Xc(e){return[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])]}function Ql(e){return[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2]}function eu(e,t,n){let r=t.shape[1],a=t.shape[2],s=[[e.startPoint[1]/r,e.startPoint[0]/a,e.endPoint[1]/r,e.endPoint[0]/a]];return tt.cropAndResize(t,s,[0],n)}function w0(e,t=1.5){let n=Ql(e),r=Xc(e),a=[t*r[0]/2,t*r[1]/2],s=[n[0]-a[0],n[1]-a[1]],i=[n[0]+a[0],n[1]+a[1]];return{startPoint:s,endPoint:i,landmarks:e.landmarks}}function b0(e){let t=Ql(e),n=Xc(e),a=Math.max(...n)/2,s=[t[0]-a,t[1]-a],i=[t[0]+a,t[1]+a];return{startPoint:s,endPoint:i,landmarks:e.landmarks}}var _0=[[1,0,0],[0,1,0],[0,0,1]];function qae(e){return e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI))}function Rg(e,t){let n=Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]);return qae(n)}function F6(e,t){return[[1,0,e],[0,1,t],[0,0,1]]}function rs(e,t){let n=0;for(let r=0;r<e.length;r++)n+=e[r]*t[r];return n}function Xae(e,t){let n=[];for(let r=0;r<e.length;r++)n.push(e[r][t]);return n}function M6(e,t){let n=[],r=e.length;for(let a=0;a<r;a++){n.push([]);for(let s=0;s<r;s++)n[a].push(rs(e[a],Xae(t,s)))}return n}function v0(e,t){let n=Math.cos(e),r=Math.sin(e),a=[[n,-r,0],[r,n,0],[0,0,1]],s=F6(t[0],t[1]),i=M6(s,a),o=F6(-t[0],-t[1]);return M6(i,o)}function $6(e){let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],n=[e[0][2],e[1][2]],r=[-rs(t[0],n),-rs(t[1],n)];return[t[0].concat(r[0]),t[1].concat(r[1]),[0,0,1]]}function D6(e,t){return[rs(e,t[0]),rs(e,t[1])]}var Jr={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]},Fg=[{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]}],Mg=[[.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]],Li=[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 Kae=[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],Zae=[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],Yae=[33,133,362,263,1,78,308],Rhe=Kae.map(e=>Mg[e]),Fhe=Zae.map(e=>Mg[e]),Mhe=Yae.map(e=>Mg[e]);var $g=Jr.leftEyeLower0,Dg=Jr.rightEyeLower0,tu={leftBounds:[$g[0],$g[$g.length-1]],rightBounds:[Dg[0],Dg[Dg.length-1]]},k0={count:468,mouth:13,symmetryLine:[13,Jr.midwayBetweenEyes[0]]},O6={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},nu={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};function I0(e,t,n,r){for(let a=0;a<Fg.length;a++){let{key:s,indices:i}=Fg[a],o=Jr[`${n}${s}`];if(!r||r.includes(s))for(let l=0;l<i.length;l++){let u=i[l];e[o[l]]=[t[u][0],t[u][1],(t[u][2]+e[o[l]][2])/2]}}}var Og=class{constructor(t,n,r){var a,s;this.storedBoxes=[],this.boundingBoxDetector=t,this.meshDetector=n,this.irisModel=r,this.boxSize=((a=t==null?void 0:t.model)==null?void 0:a.inputs[0].shape[2])||0,this.meshSize=(n==null?void 0:n.inputs[0].shape[2])||((s=t==null?void 0:t.model)==null?void 0:s.inputs[0].shape[2]),this.irisSize=(r==null?void 0:r.inputs[0].shape[1])||0,this.irisEnlarge=2.3,this.skipped=0,this.detectedFaces=0}transformRawCoords(t,n,r,a){let s=Xc({startPoint:n.startPoint,endPoint:n.endPoint}),i=t.map(h=>[s[0]/this.meshSize*(h[0]-this.meshSize/2),s[1]/this.meshSize*(h[1]-this.meshSize/2),h[2]]),o=r!==0?v0(r,[0,0]):_0,l=r!==0?i.map(h=>[...D6(h,o),h[2]]):i,u=r!==0?$6(a):_0,c=[...Ql({startPoint:n.startPoint,endPoint:n.endPoint}),1];return l.map(h=>[h[0]+rs(c,u[0]),h[1]+rs(c,u[1]),h[2]])}getLeftToRightEyeDepthDifference(t){let n=t[tu.leftBounds[0]][2],r=t[tu.rightBounds[0]][2];return n-r}getEyeBox(t,n,r,a,s=!1){let i=b0(w0(this.calculateLandmarksBoundingBox([t[r],t[a]]),this.irisEnlarge)),o=Xc(i),l=tt.cropAndResize(n,[[i.startPoint[1]/this.meshSize,i.startPoint[0]/this.meshSize,i.endPoint[1]/this.meshSize,i.endPoint[0]/this.meshSize]],[0],[this.irisSize,this.irisSize]);return s&&wr.flags.IS_BROWSER&&(l=tt.flipLeftRight(l)),{box:i,boxSize:o,crop:l}}getEyeCoords(t,n,r,a=!1){let s=[];for(let i=0;i<nu.numCoordinates;i++){let o=t[i*3],l=t[i*3+1],u=t[i*3+2];s.push([(a?1-o/this.irisSize:o/this.irisSize)*r[0]+n.startPoint[0],l/this.irisSize*r[1]+n.startPoint[1],u])}return{rawCoords:s,iris:s.slice(nu.index)}}getAdjustedIrisCoords(t,n,r){let a=t[Jr[`${r}EyeUpper0`][nu.upperCenter]][2],s=t[Jr[`${r}EyeLower0`][nu.lowerCenter]][2],i=(a+s)/2;return n.map((o,l)=>{let u=i;return l===2?u=a:l===4&&(u=s),[o[0],o[1],u]})}async predict(t,n){let r=!1,a;if((this.skipped===0||this.skipped>n.face.detector.skipFrames||!n.face.mesh.enabled||!n.videoOptimized)&&(a=await this.boundingBoxDetector.getBoundingBoxes(t),this.skipped=0),n.videoOptimized&&this.skipped++,a&&a.boxes&&(!n.face.mesh.enabled||a.boxes.length!==this.detectedFaces&&this.detectedFaces!==n.face.detector.maxFaces)){this.storedBoxes=[],this.detectedFaces=0;for(let i of a.boxes)this.storedBoxes.push({startPoint:i.box.startPoint.dataSync(),endPoint:i.box.endPoint.dataSync(),landmarks:i.landmarks,confidence:i.confidence});this.storedBoxes.length>0&&(r=!0)}if(n.face.detector.skipInitial&&this.detectedFaces===0&&(this.skipped=0),r){if(!a||!a.boxes||a.boxes.length===0)return this.storedBoxes=[],this.detectedFaces=0,null;for(let i=0;i<this.storedBoxes.length;i++){let o=R6({startPoint:this.storedBoxes[i].startPoint,endPoint:this.storedBoxes[i].endPoint},a.scaleFactor),l=w0(o),u=b0(l),c=this.storedBoxes[i].landmarks.arraySync(),h=this.storedBoxes[i].confidence;this.storedBoxes[i]={...u,confidence:h,landmarks:c}}}a&&a.boxes&&a.boxes.forEach(i=>{i.box.startPoint.dispose(),i.box.endPoint.dispose(),i.landmarks.dispose()});let s=B(()=>this.storedBoxes.map((i,o)=>{let l=i.confidence,u,c=0,h;if(n.face.detector.rotation&&n.face.mesh.enabled&&wr.flags.IS_BROWSER){let[w,x]=i.landmarks.length>=k0.count?k0.symmetryLine:O6.symmetryLine;c=Rg(i.landmarks[w],i.landmarks[x]);let N=Ql({startPoint:i.startPoint,endPoint:i.endPoint}),S=[N[0]/t.shape[2],N[1]/t.shape[1]],T=tt.rotateWithOffset(t,c,0,S);h=v0(-c,N),n.face.mesh.enabled?u=eu({startPoint:i.startPoint,endPoint:i.endPoint},T,[this.meshSize,this.meshSize]).div(255):u=eu({startPoint:i.startPoint,endPoint:i.endPoint},T,[this.boxSize,this.boxSize]).div(255)}else{h=_0;let w=t.clone();n.face.mesh.enabled?u=eu({startPoint:i.startPoint,endPoint:i.endPoint},w,[this.meshSize,this.meshSize]).div(255):u=eu({startPoint:i.startPoint,endPoint:i.endPoint},w,[this.boxSize,this.boxSize]).div(255)}if(!n.face.mesh.enabled)return{coords:null,box:i,faceConfidence:null,boxConfidence:i.confidence,confidence:i.confidence,image:u};let[,d,p]=this.meshDetector.predict(u),f=d.dataSync()[0];if(f<n.face.detector.minConfidence)return null;let A=G(p,[-1,3]).arraySync();if(n.face.iris.enabled){let{box:w,boxSize:x,crop:N}=this.getEyeBox(A,u,tu.leftBounds[0],tu.leftBounds[1],!0),{box:S,boxSize:T,crop:M}=this.getEyeBox(A,u,tu.rightBounds[0],tu.rightBounds[1]),z=this.irisModel.predict(lt([N,M])).dataSync(),W=z.slice(0,nu.numCoordinates*3),{rawCoords:U,iris:H}=this.getEyeCoords(W,w,x,!0),X=z.slice(nu.numCoordinates*3),{rawCoords:j,iris:ee}=this.getEyeCoords(X,S,T),Y=this.getLeftToRightEyeDepthDifference(A);Math.abs(Y)<30?(I0(A,U,"left",null),I0(A,j,"right",null)):Y<1?I0(A,U,"left",["EyeUpper0","EyeLower0"]):I0(A,j,"right",["EyeUpper0","EyeLower0"]);let se=this.getAdjustedIrisCoords(A,H,"left"),te=this.getAdjustedIrisCoords(A,ee,"right");A=A.concat(se).concat(te)}let y=this.transformRawCoords(A,i,c,h);i=w0(this.calculateLandmarksBoundingBox(y),1.5);let g=En(y);if(n.face.detector.rotation&&n.face.mesh.enabled&&n.face.detector.return&&wr.flags.IS_BROWSER){let[w,x]=i.landmarks.length>=k0.count?k0.symmetryLine:O6.symmetryLine;c=Rg(i.landmarks[w],i.landmarks[x]);let N=Ql({startPoint:i.startPoint,endPoint:i.endPoint}),S=[N[0]/t.shape[2],N[1]/t.shape[1]],T=tt.rotateWithOffset(t,c,0,S);h=v0(-c,N),u=eu({startPoint:i.startPoint,endPoint:i.endPoint},T,[this.meshSize,this.meshSize]).div(255)}let b={coords:g,box:i,faceConfidence:f,boxConfidence:l,image:u,rawCoords:A},_=b0(i);return this.storedBoxes[o]={..._,landmarks:y,confidence:i.confidence,faceConfidence:f},b}));return s=s.filter(i=>i!==null),n.face.mesh.enabled&&(this.storedBoxes=this.storedBoxes.filter(i=>i.faceConfidence>n.face.detector.minConfidence)),this.detectedFaces=s.length,s}calculateLandmarksBoundingBox(t){let n=t.map(i=>i[0]),r=t.map(i=>i[1]),a=[Math.min(...n),Math.min(...r)],s=[Math.max(...n),Math.max(...r)];return{startPoint:a,endPoint:s,landmarks:t}}};var M2=Th(P6());var Lg={};xr(Lg,{load:()=>Wg,predict:()=>Bg});var Pg={};function Qr(e,t){if(!t||!t.kernels)return;let n=5,r=t.kernels.filter(o=>o.kernelTimeMs>0).reduce((o,l)=>o+=l.kernelTimeMs,0),a=t.kernels.map((o,l)=>(o.id=l,o)).filter(o=>o.kernelTimeMs>0).sort((o,l)=>l.kernelTimeMs-o.kernelTimeMs),s=t.kernels.map((o,l)=>(o.id=l,o)).filter(o=>o.totalBytesSnapshot>0).sort((o,l)=>l.totalBytesSnapshot-o.totalBytesSnapshot);a.length>n&&(a.length=n),s.length>n&&(s.length=n);let i={newBytes:t.newBytes,newTensors:t.newTensors,peakBytes:t.peakBytes,numKernelOps:t.kernels.length,timeKernelOps:r,slowestKernelOps:a,largestKernelOps:s};Pg[e]=i,Fe("Human profiler",e,i)}var as,N0={age:0},S0=Number.MAX_SAFE_INTEGER;async function Wg(e){return as||(as=await Ot(e.face.age.modelPath),e.debug&&Fe(`load model: ${e.face.age.modelPath.match(/\/(.*)\./)[1]}`)),as}async function Bg(e,t){return as?S0<t.face.age.skipFrames&&t.videoOptimized&&N0.age&&N0.age>0?(S0++,N0):(t.videoOptimized?S0=0:S0=Number.MAX_SAFE_INTEGER,new Promise(async n=>{let r=tt.resizeBilinear(e,[as.inputs[0].shape[2],as.inputs[0].shape[1]],!1),a=P(r,[255]);Me(r);let s,i={age:0};if(!t.profile)t.face.age.enabled&&(s=await as.predict(a));else{let o=t.face.age.enabled?await kr(()=>as.predict(a)):{};s=o.result.clone(),o.result.dispose(),Qr("age",o)}if(a.dispose(),s){let o=s.dataSync();i.age=Math.trunc(10*o[0])/10}s.dispose(),N0=i,n(i)})):null}var Vg={};xr(Vg,{load:()=>Gg,predict:()=>qg});var wa,Ug={gender:""},T0=Number.MAX_SAFE_INTEGER,Hg=!1,jg=[.2989,.587,.114];async function Gg(e){return wa||(wa=await Ot(e.face.gender.modelPath),Hg=wa.inputs[0].shape[3]===1,e.debug&&Fe(`load model: ${e.face.gender.modelPath.match(/\/(.*)\./)[1]}`)),wa}async function qg(e,t){return wa?T0<t.face.gender.skipFrames&&t.videoOptimized&&Ug.gender!==""?(T0++,Ug):(t.videoOptimized?T0=0:T0=Number.MAX_SAFE_INTEGER,new Promise(async n=>{let r=tt.resizeBilinear(e,[wa.inputs[0].shape[2],wa.inputs[0].shape[1]],!1),a;Hg?a=B(()=>{let[o,l,u]=Ut(r,3,3),c=P(o,jg[0]),h=P(l,jg[1]),d=P(u,jg[2]);return La([c,h,d]).sub(.5).mul(2)}):a=P(r,[255]),Me(r);let s,i={gender:"",confidence:0};if(!t.profile)t.face.gender.enabled&&(s=await wa.predict(a));else{let o=t.face.gender.enabled?await kr(()=>wa.predict(a)):{};s=o.result.clone(),o.result.dispose(),Qr("gender",o)}if(a.dispose(),s){let o=s.dataSync();if(Hg)(o[0]>t.face.gender.minConfidence||o[1]>t.face.gender.minConfidence)&&(i.gender=o[0]>o[1]?"female":"male",i.confidence=o[0]>o[1]?Math.trunc(100*o[0])/100:Math.trunc(100*o[1])/100);else{let l=Math.trunc(200*Math.abs(o[0]-.5))/100;l>t.face.gender.minConfidence&&(i.gender=o[0]<=.5?"female":"male",i.confidence=Math.min(.99,l))}}s.dispose(),Ug=i,n(i)})):null}var Xg={};xr(Xg,{load:()=>Yg,predict:()=>Jg});var Qae=["angry","disgust","fear","happy","sad","surprise","neutral"],ss,Kg=[],E0=Number.MAX_SAFE_INTEGER,Zg=[.2989,.587,.114];async function Yg(e){return ss||(ss=await Ot(e.face.emotion.modelPath),e.debug&&Fe(`load model: ${e.face.emotion.modelPath.match(/\/(.*)\./)[1]}`)),ss}async function Jg(e,t){return ss?E0<t.face.emotion.skipFrames&&t.videoOptimized&&Kg.length>0?(E0++,Kg):(t.videoOptimized?E0=0:E0=Number.MAX_SAFE_INTEGER,new Promise(async n=>{let r=tt.resizeBilinear(e,[ss.inputs[0].shape[2],ss.inputs[0].shape[1]],!1),[a,s,i]=Ut(r,3,3);r.dispose();let o=P(a,Zg[0]),l=P(s,Zg[1]),u=P(i,Zg[2]);a.dispose(),s.dispose(),i.dispose();let c=La([o,l,u]);o.dispose(),l.dispose(),u.dispose();let h=B(()=>c.sub(.5).mul(2));c.dispose();let d=[];if(t.face.emotion.enabled){let p;if(t.profile){let f=await kr(()=>ss.predict(h));p=f.result.dataSync(),f.result.dispose(),Qr("emotion",f)}else{let f=await ss.predict(h);p=f.dataSync(),Me(f)}for(let f=0;f<p.length;f++)p[f]>t.face.emotion.minConfidence&&d.push({score:Math.min(.99,Math.trunc(100*p[f])/100),emotion:Qae[f]});d.sort((f,m)=>m.score-f.score)}h.dispose(),Kg=d,n(d)})):null}var ea;async function Qg(e){return ea||(ea=await Ot(e.face.embedding.modelPath),e.debug&&Fe(`load model: ${e.face.embedding.modelPath.match(/\/(.*)\./)[1]}`)),ea}function e2(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 r=e.map((s,i)=>Math.abs(e[i]-t[i])**n).reduce((s,i)=>s+i,0)**(1/n);return Math.max(Math.trunc(1e3*(1-r))/1e3,0)}function L6(e,t,n=0){let r={simmilarity:0,name:"",source:"",embedding:[]};if(!e||!t||!Array.isArray(e)||!Array.isArray(t))return r;for(let a of t)if(a.embedding&&a.name){let s=e2(e,a.embedding);s>n&&s>r.simmilarity&&(r={...a,simmilarity:s})}return r}function t2(e){return B(()=>{let n=[[.05,.15,.85,.85]],r=e.image||e.tensor;if(!(r instanceof Ge))return null;let a=r.shape.length===3?tt.cropAndResize(mn(r,0),n,[0],[ea.inputs[0].shape[2],ea.inputs[0].shape[1]]):tt.cropAndResize(r,n,[0],[ea.inputs[0].shape[2],ea.inputs[0].shape[1]]),s=[.2989,.587,.114],[i,o,l]=Ut(a,3,3),u=P(i,s[0]),c=P(o,s[1]),h=P(l,s[2]),d=La([u,c,h]),p=An([d,d,d],3).squeeze(4),f=p.sub(p.min());return f.div(f.max())})}async function n2(e,t){return ea?new Promise(async n=>{let r=[];if(t.face.embedding.enabled){let a=t2(e);if(!t.profile)r=B(()=>[...ea.predict(a).reshape([128,2]).logSumExp(1).dataSync()]);else{let s=await kr(()=>ea.predict({img_inputs:a}));r=[...s.result.dataSync()],s.result.dispose(),Qr("emotion",s)}Me(a)}n(r)}):[]}var f2={};xr(f2,{PoseNet:()=>m2,load:()=>A2});function ese(e){let[t,n,r,a]=e;return{offsets:t,heatmap:n,displacementFwd:r,displacementBwd:a}}var r2=class{constructor(t){this.model=t}predict(t){return B(()=>{let r=t.toFloat().div(127.5).sub(1).expandDims(0),s=this.model.predict(r).map(o=>o.squeeze([0])),i=ese(s);return{heatmapScores:i.heatmap.sigmoid(),offsets:i.offsets,displacementFwd:i.displacementFwd,displacementBwd:i.displacementBwd}})}dispose(){this.model.dispose()}};function a2(e){return Math.floor(e/2)}var s2=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(a2(t),t);)this.exchange(t,a2(t)),t=a2(t)}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 r=this.priorityQueue[t];this.priorityQueue[t]=this.priorityQueue[n],this.priorityQueue[n]=r}};function tse(e,t,n,r,a,s){let[i,o]=s.shape,l=!0,u=Math.max(n-a,0),c=Math.min(n+a+1,i);for(let h=u;h<c;++h){let d=Math.max(r-a,0),p=Math.min(r+a+1,o);for(let f=d;f<p;++f)if(s.get(h,f,e)>t){l=!1;break}if(!l)break}return l}function W6(e,t,n){let[r,a,s]=n.shape,i=new s2(r*a*s,({score:o})=>o);for(let o=0;o<r;++o)for(let l=0;l<a;++l)for(let u=0;u<s;++u){let c=n.get(o,l,u);c<e||tse(u,c,o,l,t,n)&&i.enqueue({score:c,part:{heatmapY:o,heatmapX:l,id:u}})}return i}var ba=Th(C0());var B6=Th(C0());function l2(e,t,n,r){return{y:r.get(e,t,n),x:r.get(e,t,n+B6.NUM_KEYPOINTS)}}function R0(e,t,n){let{heatmapY:r,heatmapX:a,id:s}=e,{y:i,x:o}=l2(r,a,s,n);return{x:e.heatmapX*t+o,y:e.heatmapY*t+i}}function u2(e,t,n){return e<t?t:e>n?n:e}function V6(e,t,n,r){let a=n-e,s=r-t;return a*a+s*s}function c2(e,t){return{x:e.x+t.x,y:e.y+t.y}}var F0=Th(C0());function U6(e,t){let n=t.shape[0],r=new Float32Array(n);for(let a=0;a<n;a++){let s=t.get(a,0),i=t.get(a,1);r[a]=e.get(s,i,a)}return r}function lse(e,t,n,r){return{y:r.get(e,t,n),x:r.get(e,t,n+F0.NUM_KEYPOINTS)}}function use(e,t){let n=[];for(let r=0;r<F0.NUM_KEYPOINTS;r++){let a=e.get(r,0).valueOf(),s=e.get(r,1).valueOf(),{x:i,y:o}=lse(a,s,r,t);n.push(o),n.push(i)}return En(n,[F0.NUM_KEYPOINTS,2])}function H6(e,t,n){return B(()=>e.toTensor().mul(Ie(t,"int32")).toFloat().add(use(e,n)))}function cse(e,t){return B(()=>{let n=e.div(Ie(t,"int32"));return e.sub(n.mul(Ie(t,"int32")))})}function j6(e){let[t,n,r]=e.shape;return B(()=>{let s=e.reshape([t*n,r]).argMax(0),i=s.div(Ie(n,"int32")).expandDims(1),o=cse(s,n).expandDims(1);return lt([i,o],1)})}var G6=ba.poseChain.map(([e,t])=>[ba.partIds[e],ba.partIds[t]]),h2=G6.map(([,e])=>e),q6=G6.map(([e])=>e),hse=16;function dse(e,t,n){let r=n.shape[2]/2;return{y:n.get(t.y,t.x,e),x:n.get(t.y,t.x,r+e)}}function d2(e,t,n,r){return{y:u2(Math.round(e.y/t),0,n-1),x:u2(Math.round(e.x/t),0,r-1)}}function X6(e,t,n,r,a,s,i,o=2){let[l,u]=r.shape,c=d2(t.position,s,l,u),h=dse(e,c,i),p=c2(t.position,h);for(let A=0;A<o;A++){let y=d2(p,s,l,u),g=l2(y.y,y.x,n,a);p=c2({x:y.x*s,y:y.y*s},{x:g.x,y:g.y})}let f=d2(p,s,l,u),m=r.get(f.y,f.x,n);return{position:p,part:ba.partNames[n],score:m}}function K6(e,t,n,r,a,s){let i=t.shape[2],o=h2.length,l=new Array(i),{part:u,score:c}=e,h=R0(u,r,n);l[u.id]={score:c,part:ba.partNames[u.id],position:h};for(let d=o-1;d>=0;--d){let p=h2[d],f=q6[d];l[p]&&!l[f]&&(l[f]=X6(d,l[p],f,t,n,r,s))}for(let d=0;d<o;++d){let p=q6[d],f=h2[d];l[p]&&!l[f]&&(l[f]=X6(d,l[p],f,t,n,r,a))}return l}async function Z6(e,t,n){let r=0,a=j6(e),s=await Promise.all([e.buffer(),t.buffer(),a.buffer()]),i=s[0],o=s[1],l=s[2],u=H6(l,hse,o),c=await u.buffer(),d=Array.from(U6(i,l)).map((f,m)=>(r+=f,{position:{y:c.get(m,0),x:c.get(m,1)},part:ba.partNames[m],score:f})),p=d.filter(f=>f.score>n);return a.dispose(),u.dispose(),{keypoints:p,score:r/d.length}}var pse=1,Y6=16;function J6(e,t,{x:n,y:r},a){return e.some(({keypoints:s})=>{let i=s[a].position;return V6(r,n,i.y,i.x)<=t})}function fse(e,t,n){return n.reduce((a,{position:s,score:i},o)=>(J6(e,t,s,o)||(a+=i),a),0)/n.length}function Q6(e,t,n,r,a,s,i){let o=[],l=W6(i,pse,e),u=a^2;for(;o.length<s&&!l.empty();){let c=l.dequeue(),h=R0(c.part,Y6,t);if(J6(o,u,h,c.part.id))continue;let d=K6(c,e,t,Y6,n,r),p=fse(o,u,d);p>i&&o.push({keypoints:d,score:p})}return o}async function e4(e){return Promise.all(e.map(t=>t.buffer()))}function mse(e,t,n){return{score:e.score,keypoints:e.keypoints.map(({score:r,part:a,position:s})=>({score:r,part:a,position:{x:Math.trunc(s.x*n),y:Math.trunc(s.y*t)}}))}}function t4(e,[t,n]){let r=e.squeeze(0),a=r.resizeBilinear([t,n]);return r.dispose(),a}function p2(e,[t,n],[r,a]){return e.map(i=>mse(i,t/r,n/a))}async function Ase(e,t,n,r){return new Promise(async a=>{let s=await e4([t.heatmapScores,t.offsets,t.displacementFwd,t.displacementBwd]),i=s[0],o=s[1],l=s[2],u=s[3],c=await Q6(i,o,l,u,n.body.nmsRadius,n.body.maxDetections,n.body.scoreThreshold),h=p2(c,[e.shape[1],e.shape[2]],[r,r]);a(h)})}async function yse(e,t,n,r){return new Promise(async a=>{let s=await Z6(t.heatmapScores,t.offsets,n.body.scoreThreshold),i=p2([s],[e.shape[1],e.shape[2]],[r,r]);a(i)})}var m2=class{constructor(t){this.baseModel=t,this.inputSize=t.model.inputs[0].shape[1],this.inputSize<128&&(this.inputSize=257)}async estimatePoses(t,n){let r=t4(t,[this.inputSize,this.inputSize]),a=this.baseModel.predict(r,n),s=n.body.maxDetections<2?await yse(t,a,n,this.inputSize):await Ase(t,a,n,this.inputSize);return a.heatmapScores.dispose(),a.offsets.dispose(),a.displacementFwd.dispose(),a.displacementBwd.dispose(),r.dispose(),s}dispose(){this.baseModel.dispose()}};async function A2(e){let t=await Ot(e.body.modelPath),n=new r2(t);return e.debug&&Fe(`load model: ${e.body.modelPath.match(/\/(.*)\./)[1]}`),new m2(n)}var b2={};xr(b2,{HandPose:()=>v2,load:()=>k2});function M0(e){return[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])]}function Kc(e){return[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2]}function n4(e,t,n){let r=t.shape[1],a=t.shape[2],s=[[e.startPoint[1]/r,e.startPoint[0]/a,e.endPoint[1]/r,e.endPoint[0]/a]];return tt.cropAndResize(t,s,[0],n)}function r4(e,t){let n=[e.startPoint[0]*t[0],e.startPoint[1]*t[1]],r=[e.endPoint[0]*t[0],e.endPoint[1]*t[1]],a=e.palmLandmarks.map(s=>[s[0]*t[0],s[1]*t[1]]);return{startPoint:n,endPoint:r,palmLandmarks:a,confidence:e.confidence}}function $0(e,t=1.5){let n=Kc(e),r=M0(e),a=[t*r[0]/2,t*r[1]/2],s=[n[0]-a[0],n[1]-a[1]],i=[n[0]+a[0],n[1]+a[1]];return{startPoint:s,endPoint:i,palmLandmarks:e.palmLandmarks}}function D0(e){let t=Kc(e),n=M0(e),a=Math.max(...n)/2,s=[t[0]-a,t[1]-a],i=[t[0]+a,t[1]+a];return{startPoint:s,endPoint:i,palmLandmarks:e.palmLandmarks}}var y2=class{constructor(t,n,r){this.model=t,this.anchors=r.map(a=>[a.x_center,a.y_center]),this.anchorsTensor=En(this.anchors),this.inputSize=n,this.inputSizeTensor=hn([n,n]),this.doubleInputSizeTensor=hn([n*2,n*2])}normalizeBoxes(t){return B(()=>{let n=$e(t,[0,0],[-1,2]),r=$e(t,[0,2],[-1,2]),a=ie(be(n,this.inputSizeTensor),this.anchorsTensor),s=be(r,this.doubleInputSizeTensor),i=P(we(a,s),this.inputSizeTensor),o=P(ie(a,s),this.inputSizeTensor);return yl([i,o],1)})}normalizeLandmarks(t,n){return B(()=>{let r=ie(be(t.reshape([-1,7,2]),this.inputSizeTensor),this.anchors[n]);return P(r,this.inputSizeTensor)})}async getBoxes(t,n){let r=this.model.predict(t),a=r.squeeze();r.dispose();let s=B(()=>On($e(a,[0,0],[-1,1])).squeeze()),i=s.dataSync(),o=$e(a,[0,1],[-1,4]),l=this.normalizeBoxes(o);o.dispose();let u=await tt.nonMaxSuppressionAsync(l,i,n.hand.maxHands,n.hand.iouThreshold,n.hand.scoreThreshold),c=u.arraySync();s.dispose(),u.dispose();let h=[];for(let d of c)if(i[d]>=n.hand.minConfidence){let p=$e(l,[d,0],[1,-1]),f=$e(a,[d,5],[1,14]),m=B(()=>this.normalizeLandmarks(f,d).reshape([-1,2]));f.dispose(),h.push({box:p,palmLandmarks:m,confidence:i[d]})}return a.dispose(),l.dispose(),h}async estimateHandBounds(t,n){let r=t.shape[1],a=t.shape[2],s=B(()=>t.resizeBilinear([this.inputSize,this.inputSize]).div(127.5).sub(1)),i=await this.getBoxes(s,n);s.dispose();let o=[];if(!i||i.length===0)return o;for(let l of i){let u=l.box.dataSync(),c=u.slice(0,2),h=u.slice(2,4),d=l.palmLandmarks.arraySync();l.box.dispose(),l.palmLandmarks.dispose(),o.push(r4({startPoint:c,endPoint:h,palmLandmarks:d,confidence:l.confidence},[a/this.inputSize,r/this.inputSize]))}return o}};function gse(e){return e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI))}function a4(e,t){let n=Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]);return gse(n)}var s4=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]];function is(e,t){let n=0;for(let r=0;r<e.length;r++)n+=e[r]*t[r];return n}function xse(e,t){let n=[];for(let r=0;r<e.length;r++)n.push(e[r][t]);return n}function i4(e,t){let n=[],r=e.length;for(let a=0;a<r;a++){n.push([]);for(let s=0;s<r;s++)n[a].push(is(e[a],xse(t,s)))}return n}function g2(e,t){let n=Math.cos(e),r=Math.sin(e),a=[[n,-r,0],[r,n,0],[0,0,1]],s=s4(t[0],t[1]),i=i4(s,a),o=s4(-t[0],-t[1]);return i4(i,o)}function o4(e){let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],n=[e[0][2],e[1][2]],r=[-is(t[0],n),-is(t[1],n)];return[t[0].concat(r[0]),t[1].concat(r[1]),[0,0,1]]}function x2(e,t){return[is(e,t[0]),is(e,t[1])]}var wse=5,l4=1.65,u4=[0,5,9,13,17,1,2],bse=0,_se=2,w2=class{constructor(t,n,r){this.handDetector=t,this.landmarkDetector=n,this.inputSize=r,this.storedBoxes=[],this.skipped=0,this.detectedHands=0}getBoxForPalmLandmarks(t,n){let r=t.map(s=>x2([...s,1],n)),a=this.calculateLandmarksBoundingBox(r);return $0(D0(a),wse)}getBoxForHandLandmarks(t){let n=this.calculateLandmarksBoundingBox(t),r=$0(D0(n),l4);r.palmLandmarks=[];for(let a=0;a<u4.length;a++)r.palmLandmarks.push(t[u4[a]].slice(0,2));return r}transformRawCoords(t,n,r,a){let s=M0(n),i=[s[0]/this.inputSize,s[1]/this.inputSize,(s[0]+s[1])/this.inputSize/2],o=t.map(p=>[i[0]*(p[0]-this.inputSize/2),i[1]*(p[1]-this.inputSize/2),i[2]*p[2]]),l=g2(r,[0,0]),u=o.map(p=>[...x2(p,l),p[2]]),c=o4(a),h=[...Kc(n),1],d=[is(h,c[0]),is(h,c[1])];return u.map(p=>[p[0]+d[0],p[1]+d[1],p[2]])}async estimateHands(t,n){let r=!1,a;(this.skipped===0||this.skipped>n.hand.skipFrames||!n.hand.landmarks||!n.videoOptimized)&&(a=await this.handDetector.estimateHandBounds(t,n),this.skipped=0),n.videoOptimized&&this.skipped++,a&&a.length>0&&(a.length!==this.detectedHands&&this.detectedHands!==n.hand.maxHands||!n.hand.landmarks)&&(this.detectedHands=0,this.storedBoxes=[...a],this.storedBoxes.length>0&&(r=!0));let s=[];n.hand.skipInitial&&this.detectedHands===0&&(this.skipped=0);for(let i=0;i<this.storedBoxes.length;i++){let o=this.storedBoxes[i];if(!!o)if(n.hand.landmarks){let l=n.hand.rotation?a4(o.palmLandmarks[bse],o.palmLandmarks[_se]):0,u=Kc(o),c=[u[0]/t.shape[2],u[1]/t.shape[1]],h=n.hand.rotation?tt.rotateWithOffset(t,l,0,c):t.clone(),d=g2(-l,u),p=r?this.getBoxForPalmLandmarks(o.palmLandmarks,d):o,f=n4(p,h,[this.inputSize,this.inputSize]),m=f.div(255);f.dispose(),h.dispose();let[A,y]=await this.landmarkDetector.predict(m);m.dispose();let g=A.dataSync()[0];if(A.dispose(),g>=n.hand.minConfidence){let b=G(y,[-1,3]),_=b.arraySync();y.dispose(),b.dispose();let w=this.transformRawCoords(_,p,l,d),x=this.getBoxForHandLandmarks(w);this.storedBoxes[i]=x;let N={landmarks:w,confidence:g,box:{topLeft:x.startPoint,bottomRight:x.endPoint}};s.push(N)}else this.storedBoxes[i]=null;y.dispose()}else{let l=$0(D0(o),l4),u={confidence:o.confidence,box:{topLeft:l.startPoint,bottomRight:l.endPoint}};s.push(u)}}return this.storedBoxes=this.storedBoxes.filter(i=>i!==null),this.detectedHands=s.length,s}calculateLandmarksBoundingBox(t){let n=t.map(i=>i[0]),r=t.map(i=>i[1]),a=[Math.min(...n),Math.min(...r)],s=[Math.max(...n),Math.max(...r)];return{startPoint:a,endPoint:s}}};var c4=[{w:1,h:1,x_center:.015625,y_center:.015625},{w:1,h:1,x_center:.015625,y_center:.015625},{w:1,h:1,x_center:.046875,y_center:.015625},{w:1,h:1,x_center:.046875,y_center:.015625},{w:1,h:1,x_center:.078125,y_center:.015625},{w:1,h:1,x_center:.078125,y_center:.015625},{w:1,h:1,x_center:.109375,y_center:.015625},{w:1,h:1,x_center:.109375,y_center:.015625},{w:1,h:1,x_center:.140625,y_center:.015625},{w:1,h:1,x_center:.140625,y_center:.015625},{w:1,h:1,x_center:.171875,y_center:.015625},{w:1,h:1,x_center:.171875,y_center:.015625},{w:1,h:1,x_center:.203125,y_center:.015625},{w:1,h:1,x_center:.203125,y_center:.015625},{w:1,h:1,x_center:.234375,y_center:.015625},{w:1,h:1,x_center:.234375,y_center:.015625},{w:1,h:1,x_center:.265625,y_center:.015625},{w:1,h:1,x_center:.265625,y_center:.015625},{w:1,h:1,x_center:.296875,y_center:.015625},{w:1,h:1,x_center:.296875,y_center:.015625},{w:1,h:1,x_center:.328125,y_center:.015625},{w:1,h:1,x_center:.328125,y_center:.015625},{w:1,h:1,x_center:.359375,y_center:.015625},{w:1,h:1,x_center:.359375,y_center:.015625},{w:1,h:1,x_center:.390625,y_center:.015625},{w:1,h:1,x_center:.390625,y_center:.015625},{w:1,h:1,x_center:.421875,y_center:.015625},{w:1,h:1,x_center:.421875,y_center:.015625},{w:1,h:1,x_center:.453125,y_center:.015625},{w:1,h:1,x_center:.453125,y_center:.015625},{w:1,h:1,x_center:.484375,y_center:.015625},{w:1,h:1,x_center:.484375,y_center:.015625},{w:1,h:1,x_center:.515625,y_center:.015625},{w:1,h:1,x_center:.515625,y_center:.015625},{w:1,h:1,x_center:.546875,y_center:.015625},{w:1,h:1,x_center:.546875,y_center:.015625},{w:1,h:1,x_center:.578125,y_center:.015625},{w:1,h:1,x_center:.578125,y_center:.015625},{w:1,h:1,x_center:.609375,y_center:.015625},{w:1,h:1,x_center:.609375,y_center:.015625},{w:1,h:1,x_center:.640625,y_center:.015625},{w:1,h:1,x_center:.640625,y_center:.015625},{w:1,h:1,x_center:.671875,y_center:.015625},{w:1,h:1,x_center:.671875,y_center:.015625},{w:1,h:1,x_center:.703125,y_center:.015625},{w:1,h:1,x_center:.703125,y_center:.015625},{w:1,h:1,x_center:.734375,y_center:.015625},{w:1,h:1,x_center:.734375,y_center:.015625},{w:1,h:1,x_center:.765625,y_center:.015625},{w:1,h:1,x_center:.765625,y_center:.015625},{w:1,h:1,x_center:.796875,y_center:.015625},{w:1,h:1,x_center:.796875,y_center:.015625},{w:1,h:1,x_center:.828125,y_center:.015625},{w:1,h:1,x_center:.828125,y_center:.015625},{w:1,h:1,x_center:.859375,y_center:.015625},{w:1,h:1,x_center:.859375,y_center:.015625},{w:1,h:1,x_center:.890625,y_center:.015625},{w:1,h:1,x_center:.890625,y_center:.015625},{w:1,h:1,x_center:.921875,y_center:.015625},{w:1,h:1,x_center:.921875,y_center:.015625},{w:1,h:1,x_center:.953125,y_center:.015625},{w:1,h:1,x_center:.953125,y_center:.015625},{w:1,h:1,x_center:.984375,y_center:.015625},{w:1,h:1,x_center:.984375,y_center:.015625},{w:1,h:1,x_center:.015625,y_center:.046875},{w:1,h:1,x_center:.015625,y_center:.046875},{w:1,h:1,x_center:.046875,y_center:.046875},{w:1,h:1,x_center:.046875,y_center:.046875},{w:1,h:1,x_center:.078125,y_center:.046875},{w:1,h:1,x_center:.078125,y_center:.046875},{w:1,h:1,x_center:.109375,y_center:.046875},{w:1,h:1,x_center:.109375,y_center:.046875},{w:1,h:1,x_center:.140625,y_center:.046875},{w:1,h:1,x_center:.140625,y_center:.046875},{w:1,h:1,x_center:.171875,y_center:.046875},{w:1,h:1,x_center:.171875,y_center:.046875},{w:1,h:1,x_center:.203125,y_center:.046875},{w:1,h:1,x_center:.203125,y_center:.046875},{w:1,h:1,x_center:.234375,y_center:.046875},{w:1,h:1,x_center:.234375,y_center:.046875},{w:1,h:1,x_center:.265625,y_center:.046875},{w:1,h:1,x_center:.265625,y_center:.046875},{w:1,h:1,x_center:.296875,y_center:.046875},{w:1,h:1,x_center:.296875,y_center:.046875},{w:1,h:1,x_center:.328125,y_center:.046875},{w:1,h:1,x_center:.328125,y_center:.046875},{w:1,h:1,x_center:.359375,y_center:.046875},{w:1,h:1,x_center:.359375,y_center:.046875},{w:1,h:1,x_center:.390625,y_center:.046875},{w:1,h:1,x_center:.390625,y_center:.046875},{w:1,h:1,x_center:.421875,y_center:.046875},{w:1,h:1,x_center:.421875,y_center:.046875},{w:1,h:1,x_center:.453125,y_center:.046875},{w:1,h:1,x_center:.453125,y_center:.046875},{w:1,h:1,x_center:.484375,y_center:.046875},{w:1,h:1,x_center:.484375,y_center:.046875},{w:1,h:1,x_center:.515625,y_center:.046875},{w:1,h:1,x_center:.515625,y_center:.046875},{w:1,h:1,x_center:.546875,y_center:.046875},{w:1,h:1,x_center:.546875,y_center:.046875},{w:1,h:1,x_center:.578125,y_center:.046875},{w:1,h:1,x_center:.578125,y_center:.046875},{w:1,h:1,x_center:.609375,y_center:.046875},{w:1,h:1,x_center:.609375,y_center:.046875},{w:1,h:1,x_center:.640625,y_center:.046875},{w:1,h:1,x_center:.640625,y_center:.046875},{w:1,h:1,x_center:.671875,y_center:.046875},{w:1,h:1,x_center:.671875,y_center:.046875},{w:1,h:1,x_center:.703125,y_center:.046875},{w:1,h:1,x_center:.703125,y_center:.046875},{w:1,h:1,x_center:.734375,y_center:.046875},{w:1,h:1,x_center:.734375,y_center:.046875},{w:1,h:1,x_center:.765625,y_center:.046875},{w:1,h:1,x_center:.765625,y_center:.046875},{w:1,h:1,x_center:.796875,y_center:.046875},{w:1,h:1,x_center:.796875,y_center:.046875},{w:1,h:1,x_center:.828125,y_center:.046875},{w:1,h:1,x_center:.828125,y_center:.046875},{w:1,h:1,x_center:.859375,y_center:.046875},{w:1,h:1,x_center:.859375,y_center:.046875},{w:1,h:1,x_center:.890625,y_center:.046875},{w:1,h:1,x_center:.890625,y_center:.046875},{w:1,h:1,x_center:.921875,y_center:.046875},{w:1,h:1,x_center:.921875,y_center:.046875},{w:1,h:1,x_center:.953125,y_center:.046875},{w:1,h:1,x_center:.953125,y_center:.046875},{w:1,h:1,x_center:.984375,y_center:.046875},{w:1,h:1,x_center:.984375,y_center:.046875},{w:1,h:1,x_center:.015625,y_center:.078125},{w:1,h:1,x_center:.015625,y_center:.078125},{w:1,h:1,x_center:.046875,y_center:.078125},{w:1,h:1,x_center:.046875,y_center:.078125},{w:1,h:1,x_center:.078125,y_center:.078125},{w:1,h:1,x_center:.078125,y_center:.078125},{w:1,h:1,x_center:.109375,y_center:.078125},{w:1,h:1,x_center:.109375,y_center:.078125},{w:1,h:1,x_center:.140625,y_center:.078125},{w:1,h:1,x_center:.140625,y_center:.078125},{w:1,h:1,x_center:.171875,y_center:.078125},{w:1,h:1,x_center:.171875,y_center:.078125},{w:1,h:1,x_center:.203125,y_center:.078125},{w:1,h:1,x_center:.203125,y_center:.078125},{w:1,h:1,x_center:.234375,y_center:.078125},{w:1,h:1,x_center:.234375,y_center:.078125},{w:1,h:1,x_center:.265625,y_center:.078125},{w:1,h:1,x_center:.265625,y_center:.078125},{w:1,h:1,x_center:.296875,y_center:.078125},{w:1,h:1,x_center:.296875,y_center:.078125},{w:1,h:1,x_center:.328125,y_center:.078125},{w:1,h:1,x_center:.328125,y_center:.078125},{w:1,h:1,x_center:.359375,y_center:.078125},{w:1,h:1,x_center:.359375,y_center:.078125},{w:1,h:1,x_center:.390625,y_center:.078125},{w:1,h:1,x_center:.390625,y_center:.078125},{w:1,h:1,x_center:.421875,y_center:.078125},{w:1,h:1,x_center:.421875,y_center:.078125},{w:1,h:1,x_center:.453125,y_center:.078125},{w:1,h:1,x_center:.453125,y_center:.078125},{w:1,h:1,x_center:.484375,y_center:.078125},{w:1,h:1,x_center:.484375,y_center:.078125},{w:1,h:1,x_center:.515625,y_center:.078125},{w:1,h:1,x_center:.515625,y_center:.078125},{w:1,h:1,x_center:.546875,y_center:.078125},{w:1,h:1,x_center:.546875,y_center:.078125},{w:1,h:1,x_center:.578125,y_center:.078125},{w:1,h:1,x_center:.578125,y_center:.078125},{w:1,h:1,x_center:.609375,y_center:.078125},{w:1,h:1,x_center:.609375,y_center:.078125},{w:1,h:1,x_center:.640625,y_center:.078125},{w:1,h:1,x_center:.640625,y_center:.078125},{w:1,h:1,x_center:.671875,y_center:.078125},{w:1,h:1,x_center:.671875,y_center:.078125},{w:1,h:1,x_center:.703125,y_center:.078125},{w:1,h:1,x_center:.703125,y_center:.078125},{w:1,h:1,x_center:.734375,y_center:.078125},{w:1,h:1,x_center:.734375,y_center:.078125},{w:1,h:1,x_center:.765625,y_center:.078125},{w:1,h:1,x_center:.765625,y_center:.078125},{w:1,h:1,x_center:.796875,y_center:.078125},{w:1,h:1,x_center:.796875,y_center:.078125},{w:1,h:1,x_center:.828125,y_center:.078125},{w:1,h:1,x_center:.828125,y_center:.078125},{w:1,h:1,x_center:.859375,y_center:.078125},{w:1,h:1,x_center:.859375,y_center:.078125},{w:1,h:1,x_center:.890625,y_center:.078125},{w:1,h:1,x_center:.890625,y_center:.078125},{w:1,h:1,x_center:.921875,y_center:.078125},{w:1,h:1,x_center:.921875,y_center:.078125},{w:1,h:1,x_center:.953125,y_center:.078125},{w:1,h:1,x_center:.953125,y_center:.078125},{w:1,h:1,x_center:.984375,y_center:.078125},{w:1,h:1,x_center:.984375,y_center:.078125},{w:1,h:1,x_center:.015625,y_center:.109375},{w:1,h:1,x_center:.015625,y_center:.109375},{w:1,h:1,x_center:.046875,y_center:.109375},{w:1,h:1,x_center:.046875,y_center:.109375},{w:1,h:1,x_center:.078125,y_center:.109375},{w:1,h:1,x_center:.078125,y_center:.109375},{w:1,h:1,x_center:.109375,y_center:.109375},{w:1,h:1,x_center:.109375,y_center:.109375},{w:1,h:1,x_center:.140625,y_center:.109375},{w:1,h:1,x_center:.140625,y_center:.109375},{w:1,h:1,x_center:.171875,y_center:.109375},{w:1,h:1,x_center:.171875,y_center:.109375},{w:1,h:1,x_center:.203125,y_center:.109375},{w:1,h:1,x_center:.203125,y_center:.109375},{w:1,h:1,x_center:.234375,y_center:.109375},{w:1,h:1,x_center:.234375,y_center:.109375},{w:1,h:1,x_center:.265625,y_center:.109375},{w:1,h:1,x_center:.265625,y_center:.109375},{w:1,h:1,x_center:.296875,y_center:.109375},{w:1,h:1,x_center:.296875,y_center:.109375},{w:1,h:1,x_center:.328125,y_center:.109375},{w:1,h:1,x_center:.328125,y_center:.109375},{w:1,h:1,x_center:.359375,y_center:.109375},{w:1,h:1,x_center:.359375,y_center:.109375},{w:1,h:1,x_center:.390625,y_center:.109375},{w:1,h:1,x_center:.390625,y_center:.109375},{w:1,h:1,x_center:.421875,y_center:.109375},{w:1,h:1,x_center:.421875,y_center:.109375},{w:1,h:1,x_center:.453125,y_center:.109375},{w:1,h:1,x_center:.453125,y_center:.109375},{w:1,h:1,x_center:.484375,y_center:.109375},{w:1,h:1,x_center:.484375,y_center:.109375},{w:1,h:1,x_center:.515625,y_center:.109375},{w:1,h:1,x_center:.515625,y_center:.109375},{w:1,h:1,x_center:.546875,y_center:.109375},{w:1,h:1,x_center:.546875,y_center:.109375},{w:1,h:1,x_center:.578125,y_center:.109375},{w:1,h:1,x_center:.578125,y_center:.109375},{w:1,h:1,x_center:.609375,y_center:.109375},{w:1,h:1,x_center:.609375,y_center:.109375},{w:1,h:1,x_center:.640625,y_center:.109375},{w:1,h:1,x_center:.640625,y_center:.109375},{w:1,h:1,x_center:.671875,y_center:.109375},{w:1,h:1,x_center:.671875,y_center:.109375},{w:1,h:1,x_center:.703125,y_center:.109375},{w:1,h:1,x_center:.703125,y_center:.109375},{w:1,h:1,x_center:.734375,y_center:.109375},{w:1,h:1,x_center:.734375,y_center:.109375},{w:1,h:1,x_center:.765625,y_center:.109375},{w:1,h:1,x_center:.765625,y_center:.109375},{w:1,h:1,x_center:.796875,y_center:.109375},{w:1,h:1,x_center:.796875,y_center:.109375},{w:1,h:1,x_center:.828125,y_center:.109375},{w:1,h:1,x_center:.828125,y_center:.109375},{w:1,h:1,x_center:.859375,y_center:.109375},{w:1,h:1,x_center:.859375,y_center:.109375},{w:1,h:1,x_center:.890625,y_center:.109375},{w:1,h:1,x_center:.890625,y_center:.109375},{w:1,h:1,x_center:.921875,y_center:.109375},{w:1,h:1,x_center:.921875,y_center:.109375},{w:1,h:1,x_center:.953125,y_center:.109375},{w:1,h:1,x_center:.953125,y_center:.109375},{w:1,h:1,x_center:.984375,y_center:.109375},{w:1,h:1,x_center:.984375,y_center:.109375},{w:1,h:1,x_center:.015625,y_center:.140625},{w:1,h:1,x_center:.015625,y_center:.140625},{w:1,h:1,x_center:.046875,y_center:.140625},{w:1,h:1,x_center:.046875,y_center:.140625},{w:1,h:1,x_center:.078125,y_center:.140625},{w:1,h:1,x_center:.078125,y_center:.140625},{w:1,h:1,x_center:.109375,y_center:.140625},{w:1,h:1,x_center:.109375,y_center:.140625},{w:1,h:1,x_center:.140625,y_center:.140625},{w:1,h:1,x_center:.140625,y_center:.140625},{w:1,h:1,x_center:.171875,y_center:.140625},{w:1,h:1,x_center:.171875,y_center:.140625},{w:1,h:1,x_center:.203125,y_center:.140625},{w:1,h:1,x_center:.203125,y_center:.140625},{w:1,h:1,x_center:.234375,y_center:.140625},{w:1,h:1,x_center:.234375,y_center:.140625},{w:1,h:1,x_center:.265625,y_center:.140625},{w:1,h:1,x_center:.265625,y_center:.140625},{w:1,h:1,x_center:.296875,y_center:.140625},{w:1,h:1,x_center:.296875,y_center:.140625},{w:1,h:1,x_center:.328125,y_center:.140625},{w:1,h:1,x_center:.328125,y_center:.140625},{w:1,h:1,x_center:.359375,y_center:.140625},{w:1,h:1,x_center:.359375,y_center:.140625},{w:1,h:1,x_center:.390625,y_center:.140625},{w:1,h:1,x_center:.390625,y_center:.140625},{w:1,h:1,x_center:.421875,y_center:.140625},{w:1,h:1,x_center:.421875,y_center:.140625},{w:1,h:1,x_center:.453125,y_center:.140625},{w:1,h:1,x_center:.453125,y_center:.140625},{w:1,h:1,x_center:.484375,y_center:.140625},{w:1,h:1,x_center:.484375,y_center:.140625},{w:1,h:1,x_center:.515625,y_center:.140625},{w:1,h:1,x_center:.515625,y_center:.140625},{w:1,h:1,x_center:.546875,y_center:.140625},{w:1,h:1,x_center:.546875,y_center:.140625},{w:1,h:1,x_center:.578125,y_center:.140625},{w:1,h:1,x_center:.578125,y_center:.140625},{w:1,h:1,x_center:.609375,y_center:.140625},{w:1,h:1,x_center:.609375,y_center:.140625},{w:1,h:1,x_center:.640625,y_center:.140625},{w:1,h:1,x_center:.640625,y_center:.140625},{w:1,h:1,x_center:.671875,y_center:.140625},{w:1,h:1,x_center:.671875,y_center:.140625},{w:1,h:1,x_center:.703125,y_center:.140625},{w:1,h:1,x_center:.703125,y_center:.140625},{w:1,h:1,x_center:.734375,y_center:.140625},{w:1,h:1,x_center:.734375,y_center:.140625},{w:1,h:1,x_center:.765625,y_center:.140625},{w:1,h:1,x_center:.765625,y_center:.140625},{w:1,h:1,x_center:.796875,y_center:.140625},{w:1,h:1,x_center:.796875,y_center:.140625},{w:1,h:1,x_center:.828125,y_center:.140625},{w:1,h:1,x_center:.828125,y_center:.140625},{w:1,h:1,x_center:.859375,y_center:.140625},{w:1,h:1,x_center:.859375,y_center:.140625},{w:1,h:1,x_center:.890625,y_center:.140625},{w:1,h:1,x_center:.890625,y_center:.140625},{w:1,h:1,x_center:.921875,y_center:.140625},{w:1,h:1,x_center:.921875,y_center:.140625},{w:1,h:1,x_center:.953125,y_center:.140625},{w:1,h:1,x_center:.953125,y_center:.140625},{w:1,h:1,x_center:.984375,y_center:.140625},{w:1,h:1,x_center:.984375,y_center:.140625},{w:1,h:1,x_center:.015625,y_center:.171875},{w:1,h:1,x_center:.015625,y_center:.171875},{w:1,h:1,x_center:.046875,y_center:.171875},{w:1,h:1,x_center:.046875,y_center:.171875},{w:1,h:1,x_center:.078125,y_center:.171875},{w:1,h:1,x_center:.078125,y_center:.171875},{w:1,h:1,x_center:.109375,y_center:.171875},{w:1,h:1,x_center:.109375,y_center:.171875},{w:1,h:1,x_center:.140625,y_center:.171875},{w:1,h:1,x_center:.140625,y_center:.171875},{w:1,h:1,x_center:.171875,y_center:.171875},{w:1,h:1,x_center:.171875,y_center:.171875},{w:1,h:1,x_center:.203125,y_center:.171875},{w:1,h:1,x_center:.203125,y_center:.171875},{w:1,h:1,x_center:.234375,y_center:.171875},{w:1,h:1,x_center:.234375,y_center:.171875},{w:1,h:1,x_center:.265625,y_center:.171875},{w:1,h:1,x_center:.265625,y_center:.171875},{w:1,h:1,x_center:.296875,y_center:.171875},{w:1,h:1,x_center:.296875,y_center:.171875},{w:1,h:1,x_center:.328125,y_center:.171875},{w:1,h:1,x_center:.328125,y_center:.171875},{w:1,h:1,x_center:.359375,y_center:.171875},{w:1,h:1,x_center:.359375,y_center:.171875},{w:1,h:1,x_center:.390625,y_center:.171875},{w:1,h:1,x_center:.390625,y_center:.171875},{w:1,h:1,x_center:.421875,y_center:.171875},{w:1,h:1,x_center:.421875,y_center:.171875},{w:1,h:1,x_center:.453125,y_center:.171875},{w:1,h:1,x_center:.453125,y_center:.171875},{w:1,h:1,x_center:.484375,y_center:.171875},{w:1,h:1,x_center:.484375,y_center:.171875},{w:1,h:1,x_center:.515625,y_center:.171875},{w:1,h:1,x_center:.515625,y_center:.171875},{w:1,h:1,x_center:.546875,y_center:.171875},{w:1,h:1,x_center:.546875,y_center:.171875},{w:1,h:1,x_center:.578125,y_center:.171875},{w:1,h:1,x_center:.578125,y_center:.171875},{w:1,h:1,x_center:.609375,y_center:.171875},{w:1,h:1,x_center:.609375,y_center:.171875},{w:1,h:1,x_center:.640625,y_center:.171875},{w:1,h:1,x_center:.640625,y_center:.171875},{w:1,h:1,x_center:.671875,y_center:.171875},{w:1,h:1,x_center:.671875,y_center:.171875},{w:1,h:1,x_center:.703125,y_center:.171875},{w:1,h:1,x_center:.703125,y_center:.171875},{w:1,h:1,x_center:.734375,y_center:.171875},{w:1,h:1,x_center:.734375,y_center:.171875},{w:1,h:1,x_center:.765625,y_center:.171875},{w:1,h:1,x_center:.765625,y_center:.171875},{w:1,h:1,x_center:.796875,y_center:.171875},{w:1,h:1,x_center:.796875,y_center:.171875},{w:1,h:1,x_center:.828125,y_center:.171875},{w:1,h:1,x_center:.828125,y_center:.171875},{w:1,h:1,x_center:.859375,y_center:.171875},{w:1,h:1,x_center:.859375,y_center:.171875},{w:1,h:1,x_center:.890625,y_center:.171875},{w:1,h:1,x_center:.890625,y_center:.171875},{w:1,h:1,x_center:.921875,y_center:.171875},{w:1,h:1,x_center:.921875,y_center:.171875},{w:1,h:1,x_center:.953125,y_center:.171875},{w:1,h:1,x_center:.953125,y_center:.171875},{w:1,h:1,x_center:.984375,y_center:.171875},{w:1,h:1,x_center:.984375,y_center:.171875},{w:1,h:1,x_center:.015625,y_center:.203125},{w:1,h:1,x_center:.015625,y_center:.203125},{w:1,h:1,x_center:.046875,y_center:.203125},{w:1,h:1,x_center:.046875,y_center:.203125},{w:1,h:1,x_center:.078125,y_center:.203125},{w:1,h:1,x_center:.078125,y_center:.203125},{w:1,h:1,x_center:.109375,y_center:.203125},{w:1,h:1,x_center:.109375,y_center:.203125},{w:1,h:1,x_center:.140625,y_center:.203125},{w:1,h:1,x_center:.140625,y_center:.203125},{w:1,h:1,x_center:.171875,y_center:.203125},{w:1,h:1,x_center:.171875,y_center:.203125},{w:1,h:1,x_center:.203125,y_center:.203125},{w:1,h:1,x_center:.203125,y_center:.203125},{w:1,h:1,x_center:.234375,y_center:.203125},{w:1,h:1,x_center:.234375,y_center:.203125},{w:1,h:1,x_center:.265625,y_center:.203125},{w:1,h:1,x_center:.265625,y_center:.203125},{w:1,h:1,x_center:.296875,y_center:.203125},{w:1,h:1,x_center:.296875,y_center:.203125},{w:1,h:1,x_center:.328125,y_center:.203125},{w:1,h:1,x_center:.328125,y_center:.203125},{w:1,h:1,x_center:.359375,y_center:.203125},{w:1,h:1,x_center:.359375,y_center:.203125},{w:1,h:1,x_center:.390625,y_center:.203125},{w:1,h:1,x_center:.390625,y_center:.203125},{w:1,h:1,x_center:.421875,y_center:.203125},{w:1,h:1,x_center:.421875,y_center:.203125},{w:1,h:1,x_center:.453125,y_center:.203125},{w:1,h:1,x_center:.453125,y_center:.203125},{w:1,h:1,x_center:.484375,y_center:.203125},{w:1,h:1,x_center:.484375,y_center:.203125},{w:1,h:1,x_center:.515625,y_center:.203125},{w:1,h:1,x_center:.515625,y_center:.203125},{w:1,h:1,x_center:.546875,y_center:.203125},{w:1,h:1,x_center:.546875,y_center:.203125},{w:1,h:1,x_center:.578125,y_center:.203125},{w:1,h:1,x_center:.578125,y_center:.203125},{w:1,h:1,x_center:.609375,y_center:.203125},{w:1,h:1,x_center:.609375,y_center:.203125},{w:1,h:1,x_center:.640625,y_center:.203125},{w:1,h:1,x_center:.640625,y_center:.203125},{w:1,h:1,x_center:.671875,y_center:.203125},{w:1,h:1,x_center:.671875,y_center:.203125},{w:1,h:1,x_center:.703125,y_center:.203125},{w:1,h:1,x_center:.703125,y_center:.203125},{w:1,h:1,x_center:.734375,y_center:.203125},{w:1,h:1,x_center:.734375,y_center:.203125},{w:1,h:1,x_center:.765625,y_center:.203125},{w:1,h:1,x_center:.765625,y_center:.203125},{w:1,h:1,x_center:.796875,y_center:.203125},{w:1,h:1,x_center:.796875,y_center:.203125},{w:1,h:1,x_center:.828125,y_center:.203125},{w:1,h:1,x_center:.828125,y_center:.203125},{w:1,h:1,x_center:.859375,y_center:.203125},{w:1,h:1,x_center:.859375,y_center:.203125},{w:1,h:1,x_center:.890625,y_center:.203125},{w:1,h:1,x_center:.890625,y_center:.203125},{w:1,h:1,x_center:.921875,y_center:.203125},{w:1,h:1,x_center:.921875,y_center:.203125},{w:1,h:1,x_center:.953125,y_center:.203125},{w:1,h:1,x_center:.953125,y_center:.203125},{w:1,h:1,x_center:.984375,y_center:.203125},{w:1,h:1,x_center:.984375,y_center:.203125},{w:1,h:1,x_center:.015625,y_center:.234375},{w:1,h:1,x_center:.015625,y_center:.234375},{w:1,h:1,x_center:.046875,y_center:.234375},{w:1,h:1,x_center:.046875,y_center:.234375},{w:1,h:1,x_center:.078125,y_center:.234375},{w:1,h:1,x_center:.078125,y_center:.234375},{w:1,h:1,x_center:.109375,y_center:.234375},{w:1,h:1,x_center:.109375,y_center:.234375},{w:1,h:1,x_center:.140625,y_center:.234375},{w:1,h:1,x_center:.140625,y_center:.234375},{w:1,h:1,x_center:.171875,y_center:.234375},{w:1,h:1,x_center:.171875,y_center:.234375},{w:1,h:1,x_center:.203125,y_center:.234375},{w:1,h:1,x_center:.203125,y_center:.234375},{w:1,h:1,x_center:.234375,y_center:.234375},{w:1,h:1,x_center:.234375,y_center:.234375},{w:1,h:1,x_center:.265625,y_center:.234375},{w:1,h:1,x_center:.265625,y_center:.234375},{w:1,h:1,x_center:.296875,y_center:.234375},{w:1,h:1,x_center:.296875,y_center:.234375},{w:1,h:1,x_center:.328125,y_center:.234375},{w:1,h:1,x_center:.328125,y_center:.234375},{w:1,h:1,x_center:.359375,y_center:.234375},{w:1,h:1,x_center:.359375,y_center:.234375},{w:1,h:1,x_center:.390625,y_center:.234375},{w:1,h:1,x_center:.390625,y_center:.234375},{w:1,h:1,x_center:.421875,y_center:.234375},{w:1,h:1,x_center:.421875,y_center:.234375},{w:1,h:1,x_center:.453125,y_center:.234375},{w:1,h:1,x_center:.453125,y_center:.234375},{w:1,h:1,x_center:.484375,y_center:.234375},{w:1,h:1,x_center:.484375,y_center:.234375},{w:1,h:1,x_center:.515625,y_center:.234375},{w:1,h:1,x_center:.515625,y_center:.234375},{w:1,h:1,x_center:.546875,y_center:.234375},{w:1,h:1,x_center:.546875,y_center:.234375},{w:1,h:1,x_center:.578125,y_center:.234375},{w:1,h:1,x_center:.578125,y_center:.234375},{w:1,h:1,x_center:.609375,y_center:.234375},{w:1,h:1,x_center:.609375,y_center:.234375},{w:1,h:1,x_center:.640625,y_center:.234375},{w:1,h:1,x_center:.640625,y_center:.234375},{w:1,h:1,x_center:.671875,y_center:.234375},{w:1,h:1,x_center:.671875,y_center:.234375},{w:1,h:1,x_center:.703125,y_center:.234375},{w:1,h:1,x_center:.703125,y_center:.234375},{w:1,h:1,x_center:.734375,y_center:.234375},{w:1,h:1,x_center:.734375,y_center:.234375},{w:1,h:1,x_center:.765625,y_center:.234375},{w:1,h:1,x_center:.765625,y_center:.234375},{w:1,h:1,x_center:.796875,y_center:.234375},{w:1,h:1,x_center:.796875,y_center:.234375},{w:1,h:1,x_center:.828125,y_center:.234375},{w:1,h:1,x_center:.828125,y_center:.234375},{w:1,h:1,x_center:.859375,y_center:.234375},{w:1,h:1,x_center:.859375,y_center:.234375},{w:1,h:1,x_center:.890625,y_center:.234375},{w:1,h:1,x_center:.890625,y_center:.234375},{w:1,h:1,x_center:.921875,y_center:.234375},{w:1,h:1,x_center:.921875,y_center:.234375},{w:1,h:1,x_center:.953125,y_center:.234375},{w:1,h:1,x_center:.953125,y_center:.234375},{w:1,h:1,x_center:.984375,y_center:.234375},{w:1,h:1,x_center:.984375,y_center:.234375},{w:1,h:1,x_center:.015625,y_center:.265625},{w:1,h:1,x_center:.015625,y_center:.265625},{w:1,h:1,x_center:.046875,y_center:.265625},{w:1,h:1,x_center:.046875,y_center:.265625},{w:1,h:1,x_center:.078125,y_center:.265625},{w:1,h:1,x_center:.078125,y_center:.265625},{w:1,h:1,x_center:.109375,y_center:.265625},{w:1,h:1,x_center:.109375,y_center:.265625},{w:1,h:1,x_center:.140625,y_center:.265625},{w:1,h:1,x_center:.140625,y_center:.265625},{w:1,h:1,x_center:.171875,y_center:.265625},{w:1,h:1,x_center:.171875,y_center:.265625},{w:1,h:1,x_center:.203125,y_center:.265625},{w:1,h:1,x_center:.203125,y_center:.265625},{w:1,h:1,x_center:.234375,y_center:.265625},{w:1,h:1,x_center:.234375,y_center:.265625},{w:1,h:1,x_center:.265625,y_center:.265625},{w:1,h:1,x_center:.265625,y_center:.265625},{w:1,h:1,x_center:.296875,y_center:.265625},{w:1,h:1,x_center:.296875,y_center:.265625},{w:1,h:1,x_center:.328125,y_center:.265625},{w:1,h:1,x_center:.328125,y_center:.265625},{w:1,h:1,x_center:.359375,y_center:.265625},{w:1,h:1,x_center:.359375,y_center:.265625},{w:1,h:1,x_center:.390625,y_center:.265625},{w:1,h:1,x_center:.390625,y_center:.265625},{w:1,h:1,x_center:.421875,y_center:.265625},{w:1,h:1,x_center:.421875,y_center:.265625},{w:1,h:1,x_center:.453125,y_center:.265625},{w:1,h:1,x_center:.453125,y_center:.265625},{w:1,h:1,x_center:.484375,y_center:.265625},{w:1,h:1,x_center:.484375,y_center:.265625},{w:1,h:1,x_center:.515625,y_center:.265625},{w:1,h:1,x_center:.515625,y_center:.265625},{w:1,h:1,x_center:.546875,y_center:.265625},{w:1,h:1,x_center:.546875,y_center:.265625},{w:1,h:1,x_center:.578125,y_center:.265625},{w:1,h:1,x_center:.578125,y_center:.265625},{w:1,h:1,x_center:.609375,y_center:.265625},{w:1,h:1,x_center:.609375,y_center:.265625},{w:1,h:1,x_center:.640625,y_center:.265625},{w:1,h:1,x_center:.640625,y_center:.265625},{w:1,h:1,x_center:.671875,y_center:.265625},{w:1,h:1,x_center:.671875,y_center:.265625},{w:1,h:1,x_center:.703125,y_center:.265625},{w:1,h:1,x_center:.703125,y_center:.265625},{w:1,h:1,x_center:.734375,y_center:.265625},{w:1,h:1,x_center:.734375,y_center:.265625},{w:1,h:1,x_center:.765625,y_center:.265625},{w:1,h:1,x_center:.765625,y_center:.265625},{w:1,h:1,x_center:.796875,y_center:.265625},{w:1,h:1,x_center:.796875,y_center:.265625},{w:1,h:1,x_center:.828125,y_center:.265625},{w:1,h:1,x_center:.828125,y_center:.265625},{w:1,h:1,x_center:.859375,y_center:.265625},{w:1,h:1,x_center:.859375,y_center:.265625},{w:1,h:1,x_center:.890625,y_center:.265625},{w:1,h:1,x_center:.890625,y_center:.265625},{w:1,h:1,x_center:.921875,y_center:.265625},{w:1,h:1,x_center:.921875,y_center:.265625},{w:1,h:1,x_center:.953125,y_center:.265625},{w:1,h:1,x_center:.953125,y_center:.265625},{w:1,h:1,x_center:.984375,y_center:.265625},{w:1,h:1,x_center:.984375,y_center:.265625},{w:1,h:1,x_center:.015625,y_center:.296875},{w:1,h:1,x_center:.015625,y_center:.296875},{w:1,h:1,x_center:.046875,y_center:.296875},{w:1,h:1,x_center:.046875,y_center:.296875},{w:1,h:1,x_center:.078125,y_center:.296875},{w:1,h:1,x_center:.078125,y_center:.296875},{w:1,h:1,x_center:.109375,y_center:.296875},{w:1,h:1,x_center:.109375,y_center:.296875},{w:1,h:1,x_center:.140625,y_center:.296875},{w:1,h:1,x_center:.140625,y_center:.296875},{w:1,h:1,x_center:.171875,y_center:.296875},{w:1,h:1,x_center:.171875,y_center:.296875},{w:1,h:1,x_center:.203125,y_center:.296875},{w:1,h:1,x_center:.203125,y_center:.296875},{w:1,h:1,x_center:.234375,y_center:.296875},{w:1,h:1,x_center:.234375,y_center:.296875},{w:1,h:1,x_center:.265625,y_center:.296875},{w:1,h:1,x_center:.265625,y_center:.296875},{w:1,h:1,x_center:.296875,y_center:.296875},{w:1,h:1,x_center:.296875,y_center:.296875},{w:1,h:1,x_center:.328125,y_center:.296875},{w:1,h:1,x_center:.328125,y_center:.296875},{w:1,h:1,x_center:.359375,y_center:.296875},{w:1,h:1,x_center:.359375,y_center:.296875},{w:1,h:1,x_center:.390625,y_center:.296875},{w:1,h:1,x_center:.390625,y_center:.296875},{w:1,h:1,x_center:.421875,y_center:.296875},{w:1,h:1,x_center:.421875,y_center:.296875},{w:1,h:1,x_center:.453125,y_center:.296875},{w:1,h:1,x_center:.453125,y_center:.296875},{w:1,h:1,x_center:.484375,y_center:.296875},{w:1,h:1,x_center:.484375,y_center:.296875},{w:1,h:1,x_center:.515625,y_center:.296875},{w:1,h:1,x_center:.515625,y_center:.296875},{w:1,h:1,x_center:.546875,y_center:.296875},{w:1,h:1,x_center:.546875,y_center:.296875},{w:1,h:1,x_center:.578125,y_center:.296875},{w:1,h:1,x_center:.578125,y_center:.296875},{w:1,h:1,x_center:.609375,y_center:.296875},{w:1,h:1,x_center:.609375,y_center:.296875},{w:1,h:1,x_center:.640625,y_center:.296875},{w:1,h:1,x_center:.640625,y_center:.296875},{w:1,h:1,x_center:.671875,y_center:.296875},{w:1,h:1,x_center:.671875,y_center:.296875},{w:1,h:1,x_center:.703125,y_center:.296875},{w:1,h:1,x_center:.703125,y_center:.296875},{w:1,h:1,x_center:.734375,y_center:.296875},{w:1,h:1,x_center:.734375,y_center:.296875},{w:1,h:1,x_center:.765625,y_center:.296875},{w:1,h:1,x_center:.765625,y_center:.296875},{w:1,h:1,x_center:.796875,y_center:.296875},{w:1,h:1,x_center:.796875,y_center:.296875},{w:1,h:1,x_center:.828125,y_center:.296875},{w:1,h:1,x_center:.828125,y_center:.296875},{w:1,h:1,x_center:.859375,y_center:.296875},{w:1,h:1,x_center:.859375,y_center:.296875},{w:1,h:1,x_center:.890625,y_center:.296875},{w:1,h:1,x_center:.890625,y_center:.296875},{w:1,h:1,x_center:.921875,y_center:.296875},{w:1,h:1,x_center:.921875,y_center:.296875},{w:1,h:1,x_center:.953125,y_center:.296875},{w:1,h:1,x_center:.953125,y_center:.296875},{w:1,h:1,x_center:.984375,y_center:.296875},{w:1,h:1,x_center:.984375,y_center:.296875},{w:1,h:1,x_center:.015625,y_center:.328125},{w:1,h:1,x_center:.015625,y_center:.328125},{w:1,h:1,x_center:.046875,y_center:.328125},{w:1,h:1,x_center:.046875,y_center:.328125},{w:1,h:1,x_center:.078125,y_center:.328125},{w:1,h:1,x_center:.078125,y_center:.328125},{w:1,h:1,x_center:.109375,y_center:.328125},{w:1,h:1,x_center:.109375,y_center:.328125},{w:1,h:1,x_center:.140625,y_center:.328125},{w:1,h:1,x_center:.140625,y_center:.328125},{w:1,h:1,x_center:.171875,y_center:.328125},{w:1,h:1,x_center:.171875,y_center:.328125},{w:1,h:1,x_center:.203125,y_center:.328125},{w:1,h:1,x_center:.203125,y_center:.328125},{w:1,h:1,x_center:.234375,y_center:.328125},{w:1,h:1,x_center:.234375,y_center:.328125},{w:1,h:1,x_center:.265625,y_center:.328125},{w:1,h:1,x_center:.265625,y_center:.328125},{w:1,h:1,x_center:.296875,y_center:.328125},{w:1,h:1,x_center:.296875,y_center:.328125},{w:1,h:1,x_center:.328125,y_center:.328125},{w:1,h:1,x_center:.328125,y_center:.328125},{w:1,h:1,x_center:.359375,y_center:.328125},{w:1,h:1,x_center:.359375,y_center:.328125},{w:1,h:1,x_center:.390625,y_center:.328125},{w:1,h:1,x_center:.390625,y_center:.328125},{w:1,h:1,x_center:.421875,y_center:.328125},{w:1,h:1,x_center:.421875,y_center:.328125},{w:1,h:1,x_center:.453125,y_center:.328125},{w:1,h:1,x_center:.453125,y_center:.328125},{w:1,h:1,x_center:.484375,y_center:.328125},{w:1,h:1,x_center:.484375,y_center:.328125},{w:1,h:1,x_center:.515625,y_center:.328125},{w:1,h:1,x_center:.515625,y_center:.328125},{w:1,h:1,x_center:.546875,y_center:.328125},{w:1,h:1,x_center:.546875,y_center:.328125},{w:1,h:1,x_center:.578125,y_center:.328125},{w:1,h:1,x_center:.578125,y_center:.328125},{w:1,h:1,x_center:.609375,y_center:.328125},{w:1,h:1,x_center:.609375,y_center:.328125},{w:1,h:1,x_center:.640625,y_center:.328125},{w:1,h:1,x_center:.640625,y_center:.328125},{w:1,h:1,x_center:.671875,y_center:.328125},{w:1,h:1,x_center:.671875,y_center:.328125},{w:1,h:1,x_center:.703125,y_center:.328125},{w:1,h:1,x_center:.703125,y_center:.328125},{w:1,h:1,x_center:.734375,y_center:.328125},{w:1,h:1,x_center:.734375,y_center:.328125},{w:1,h:1,x_center:.765625,y_center:.328125},{w:1,h:1,x_center:.765625,y_center:.328125},{w:1,h:1,x_center:.796875,y_center:.328125},{w:1,h:1,x_center:.796875,y_center:.328125},{w:1,h:1,x_center:.828125,y_center:.328125},{w:1,h:1,x_center:.828125,y_center:.328125},{w:1,h:1,x_center:.859375,y_center:.328125},{w:1,h:1,x_center:.859375,y_center:.328125},{w:1,h:1,x_center:.890625,y_center:.328125},{w:1,h:1,x_center:.890625,y_center:.328125},{w:1,h:1,x_center:.921875,y_center:.328125},{w:1,h:1,x_center:.921875,y_center:.328125},{w:1,h:1,x_center:.953125,y_center:.328125},{w:1,h:1,x_center:.953125,y_center:.328125},{w:1,h:1,x_center:.984375,y_center:.328125},{w:1,h:1,x_center:.984375,y_center:.328125},{w:1,h:1,x_center:.015625,y_center:.359375},{w:1,h:1,x_center:.015625,y_center:.359375},{w:1,h:1,x_center:.046875,y_center:.359375},{w:1,h:1,x_center:.046875,y_center:.359375},{w:1,h:1,x_center:.078125,y_center:.359375},{w:1,h:1,x_center:.078125,y_center:.359375},{w:1,h:1,x_center:.109375,y_center:.359375},{w:1,h:1,x_center:.109375,y_center:.359375},{w:1,h:1,x_center:.140625,y_center:.359375},{w:1,h:1,x_center:.140625,y_center:.359375},{w:1,h:1,x_center:.171875,y_center:.359375},{w:1,h:1,x_center:.171875,y_center:.359375},{w:1,h:1,x_center:.203125,y_center:.359375},{w:1,h:1,x_center:.203125,y_center:.359375},{w:1,h:1,x_center:.234375,y_center:.359375},{w:1,h:1,x_center:.234375,y_center:.359375},{w:1,h:1,x_center:.265625,y_center:.359375},{w:1,h:1,x_center:.265625,y_center:.359375},{w:1,h:1,x_center:.296875,y_center:.359375},{w:1,h:1,x_center:.296875,y_center:.359375},{w:1,h:1,x_center:.328125,y_center:.359375},{w:1,h:1,x_center:.328125,y_center:.359375},{w:1,h:1,x_center:.359375,y_center:.359375},{w:1,h:1,x_center:.359375,y_center:.359375},{w:1,h:1,x_center:.390625,y_center:.359375},{w:1,h:1,x_center:.390625,y_center:.359375},{w:1,h:1,x_center:.421875,y_center:.359375},{w:1,h:1,x_center:.421875,y_center:.359375},{w:1,h:1,x_center:.453125,y_center:.359375},{w:1,h:1,x_center:.453125,y_center:.359375},{w:1,h:1,x_center:.484375,y_center:.359375},{w:1,h:1,x_center:.484375,y_center:.359375},{w:1,h:1,x_center:.515625,y_center:.359375},{w:1,h:1,x_center:.515625,y_center:.359375},{w:1,h:1,x_center:.546875,y_center:.359375},{w:1,h:1,x_center:.546875,y_center:.359375},{w:1,h:1,x_center:.578125,y_center:.359375},{w:1,h:1,x_center:.578125,y_center:.359375},{w:1,h:1,x_center:.609375,y_center:.359375},{w:1,h:1,x_center:.609375,y_center:.359375},{w:1,h:1,x_center:.640625,y_center:.359375},{w:1,h:1,x_center:.640625,y_center:.359375},{w:1,h:1,x_center:.671875,y_center:.359375},{w:1,h:1,x_center:.671875,y_center:.359375},{w:1,h:1,x_center:.703125,y_center:.359375},{w:1,h:1,x_center:.703125,y_center:.359375},{w:1,h:1,x_center:.734375,y_center:.359375},{w:1,h:1,x_center:.734375,y_center:.359375},{w:1,h:1,x_center:.765625,y_center:.359375},{w:1,h:1,x_center:.765625,y_center:.359375},{w:1,h:1,x_center:.796875,y_center:.359375},{w:1,h:1,x_center:.796875,y_center:.359375},{w:1,h:1,x_center:.828125,y_center:.359375},{w:1,h:1,x_center:.828125,y_center:.359375},{w:1,h:1,x_center:.859375,y_center:.359375},{w:1,h:1,x_center:.859375,y_center:.359375},{w:1,h:1,x_center:.890625,y_center:.359375},{w:1,h:1,x_center:.890625,y_center:.359375},{w:1,h:1,x_center:.921875,y_center:.359375},{w:1,h:1,x_center:.921875,y_center:.359375},{w:1,h:1,x_center:.953125,y_center:.359375},{w:1,h:1,x_center:.953125,y_center:.359375},{w:1,h:1,x_center:.984375,y_center:.359375},{w:1,h:1,x_center:.984375,y_center:.359375},{w:1,h:1,x_center:.015625,y_center:.390625},{w:1,h:1,x_center:.015625,y_center:.390625},{w:1,h:1,x_center:.046875,y_center:.390625},{w:1,h:1,x_center:.046875,y_center:.390625},{w:1,h:1,x_center:.078125,y_center:.390625},{w:1,h:1,x_center:.078125,y_center:.390625},{w:1,h:1,x_center:.109375,y_center:.390625},{w:1,h:1,x_center:.109375,y_center:.390625},{w:1,h:1,x_center:.140625,y_center:.390625},{w:1,h:1,x_center:.140625,y_center:.390625},{w:1,h:1,x_center:.171875,y_center:.390625},{w:1,h:1,x_center:.171875,y_center:.390625},{w:1,h:1,x_center:.203125,y_center:.390625},{w:1,h:1,x_center:.203125,y_center:.390625},{w:1,h:1,x_center:.234375,y_center:.390625},{w:1,h:1,x_center:.234375,y_center:.390625},{w:1,h:1,x_center:.265625,y_center:.390625},{w:1,h:1,x_center:.265625,y_center:.390625},{w:1,h:1,x_center:.296875,y_center:.390625},{w:1,h:1,x_center:.296875,y_center:.390625},{w:1,h:1,x_center:.328125,y_center:.390625},{w:1,h:1,x_center:.328125,y_center:.390625},{w:1,h:1,x_center:.359375,y_center:.390625},{w:1,h:1,x_center:.359375,y_center:.390625},{w:1,h:1,x_center:.390625,y_center:.390625},{w:1,h:1,x_center:.390625,y_center:.390625},{w:1,h:1,x_center:.421875,y_center:.390625},{w:1,h:1,x_center:.421875,y_center:.390625},{w:1,h:1,x_center:.453125,y_center:.390625},{w:1,h:1,x_center:.453125,y_center:.390625},{w:1,h:1,x_center:.484375,y_center:.390625},{w:1,h:1,x_center:.484375,y_center:.390625},{w:1,h:1,x_center:.515625,y_center:.390625},{w:1,h:1,x_center:.515625,y_center:.390625},{w:1,h:1,x_center:.546875,y_center:.390625},{w:1,h:1,x_center:.546875,y_center:.390625},{w:1,h:1,x_center:.578125,y_center:.390625},{w:1,h:1,x_center:.578125,y_center:.390625},{w:1,h:1,x_center:.609375,y_center:.390625},{w:1,h:1,x_center:.609375,y_center:.390625},{w:1,h:1,x_center:.640625,y_center:.390625},{w:1,h:1,x_center:.640625,y_center:.390625},{w:1,h:1,x_center:.671875,y_center:.390625},{w:1,h:1,x_center:.671875,y_center:.390625},{w:1,h:1,x_center:.703125,y_center:.390625},{w:1,h:1,x_center:.703125,y_center:.390625},{w:1,h:1,x_center:.734375,y_center:.390625},{w:1,h:1,x_center:.734375,y_center:.390625},{w:1,h:1,x_center:.765625,y_center:.390625},{w:1,h:1,x_center:.765625,y_center:.390625},{w:1,h:1,x_center:.796875,y_center:.390625},{w:1,h:1,x_center:.796875,y_center:.390625},{w:1,h:1,x_center:.828125,y_center:.390625},{w:1,h:1,x_center:.828125,y_center:.390625},{w:1,h:1,x_center:.859375,y_center:.390625},{w:1,h:1,x_center:.859375,y_center:.390625},{w:1,h:1,x_center:.890625,y_center:.390625},{w:1,h:1,x_center:.890625,y_center:.390625},{w:1,h:1,x_center:.921875,y_center:.390625},{w:1,h:1,x_center:.921875,y_center:.390625},{w:1,h:1,x_center:.953125,y_center:.390625},{w:1,h:1,x_center:.953125,y_center:.390625},{w:1,h:1,x_center:.984375,y_center:.390625},{w:1,h:1,x_center:.984375,y_center:.390625},{w:1,h:1,x_center:.015625,y_center:.421875},{w:1,h:1,x_center:.015625,y_center:.421875},{w:1,h:1,x_center:.046875,y_center:.421875},{w:1,h:1,x_center:.046875,y_center:.421875},{w:1,h:1,x_center:.078125,y_center:.421875},{w:1,h:1,x_center:.078125,y_center:.421875},{w:1,h:1,x_center:.109375,y_center:.421875},{w:1,h:1,x_center:.109375,y_center:.421875},{w:1,h:1,x_center:.140625,y_center:.421875},{w:1,h:1,x_center:.140625,y_center:.421875},{w:1,h:1,x_center:.171875,y_center:.421875},{w:1,h:1,x_center:.171875,y_center:.421875},{w:1,h:1,x_center:.203125,y_center:.421875},{w:1,h:1,x_center:.203125,y_center:.421875},{w:1,h:1,x_center:.234375,y_center:.421875},{w:1,h:1,x_center:.234375,y_center:.421875},{w:1,h:1,x_center:.265625,y_center:.421875},{w:1,h:1,x_center:.265625,y_center:.421875},{w:1,h:1,x_center:.296875,y_center:.421875},{w:1,h:1,x_center:.296875,y_center:.421875},{w:1,h:1,x_center:.328125,y_center:.421875},{w:1,h:1,x_center:.328125,y_center:.421875},{w:1,h:1,x_center:.359375,y_center:.421875},{w:1,h:1,x_center:.359375,y_center:.421875},{w:1,h:1,x_center:.390625,y_center:.421875},{w:1,h:1,x_center:.390625,y_center:.421875},{w:1,h:1,x_center:.421875,y_center:.421875},{w:1,h:1,x_center:.421875,y_center:.421875},{w:1,h:1,x_center:.453125,y_center:.421875},{w:1,h:1,x_center:.453125,y_center:.421875},{w:1,h:1,x_center:.484375,y_center:.421875},{w:1,h:1,x_center:.484375,y_center:.421875},{w:1,h:1,x_center:.515625,y_center:.421875},{w:1,h:1,x_center:.515625,y_center:.421875},{w:1,h:1,x_center:.546875,y_center:.421875},{w:1,h:1,x_center:.546875,y_center:.421875},{w:1,h:1,x_center:.578125,y_center:.421875},{w:1,h:1,x_center:.578125,y_center:.421875},{w:1,h:1,x_center:.609375,y_center:.421875},{w:1,h:1,x_center:.609375,y_center:.421875},{w:1,h:1,x_center:.640625,y_center:.421875},{w:1,h:1,x_center:.640625,y_center:.421875},{w:1,h:1,x_center:.671875,y_center:.421875},{w:1,h:1,x_center:.671875,y_center:.421875},{w:1,h:1,x_center:.703125,y_center:.421875},{w:1,h:1,x_center:.703125,y_center:.421875},{w:1,h:1,x_center:.734375,y_center:.421875},{w:1,h:1,x_center:.734375,y_center:.421875},{w:1,h:1,x_center:.765625,y_center:.421875},{w:1,h:1,x_center:.765625,y_center:.421875},{w:1,h:1,x_center:.796875,y_center:.421875},{w:1,h:1,x_center:.796875,y_center:.421875},{w:1,h:1,x_center:.828125,y_center:.421875},{w:1,h:1,x_center:.828125,y_center:.421875},{w:1,h:1,x_center:.859375,y_center:.421875},{w:1,h:1,x_center:.859375,y_center:.421875},{w:1,h:1,x_center:.890625,y_center:.421875},{w:1,h:1,x_center:.890625,y_center:.421875},{w:1,h:1,x_center:.921875,y_center:.421875},{w:1,h:1,x_center:.921875,y_center:.421875},{w:1,h:1,x_center:.953125,y_center:.421875},{w:1,h:1,x_center:.953125,y_center:.421875},{w:1,h:1,x_center:.984375,y_center:.421875},{w:1,h:1,x_center:.984375,y_center:.421875},{w:1,h:1,x_center:.015625,y_center:.453125},{w:1,h:1,x_center:.015625,y_center:.453125},{w:1,h:1,x_center:.046875,y_center:.453125},{w:1,h:1,x_center:.046875,y_center:.453125},{w:1,h:1,x_center:.078125,y_center:.453125},{w:1,h:1,x_center:.078125,y_center:.453125},{w:1,h:1,x_center:.109375,y_center:.453125},{w:1,h:1,x_center:.109375,y_center:.453125},{w:1,h:1,x_center:.140625,y_center:.453125},{w:1,h:1,x_center:.140625,y_center:.453125},{w:1,h:1,x_center:.171875,y_center:.453125},{w:1,h:1,x_center:.171875,y_center:.453125},{w:1,h:1,x_center:.203125,y_center:.453125},{w:1,h:1,x_center:.203125,y_center:.453125},{w:1,h:1,x_center:.234375,y_center:.453125},{w:1,h:1,x_center:.234375,y_center:.453125},{w:1,h:1,x_center:.265625,y_center:.453125},{w:1,h:1,x_center:.265625,y_center:.453125},{w:1,h:1,x_center:.296875,y_center:.453125},{w:1,h:1,x_center:.296875,y_center:.453125},{w:1,h:1,x_center:.328125,y_center:.453125},{w:1,h:1,x_center:.328125,y_center:.453125},{w:1,h:1,x_center:.359375,y_center:.453125},{w:1,h:1,x_center:.359375,y_center:.453125},{w:1,h:1,x_center:.390625,y_center:.453125},{w:1,h:1,x_center:.390625,y_center:.453125},{w:1,h:1,x_center:.421875,y_center:.453125},{w:1,h:1,x_center:.421875,y_center:.453125},{w:1,h:1,x_center:.453125,y_center:.453125},{w:1,h:1,x_center:.453125,y_center:.453125},{w:1,h:1,x_center:.484375,y_center:.453125},{w:1,h:1,x_center:.484375,y_center:.453125},{w:1,h:1,x_center:.515625,y_center:.453125},{w:1,h:1,x_center:.515625,y_center:.453125},{w:1,h:1,x_center:.546875,y_center:.453125},{w:1,h:1,x_center:.546875,y_center:.453125},{w:1,h:1,x_center:.578125,y_center:.453125},{w:1,h:1,x_center:.578125,y_center:.453125},{w:1,h:1,x_center:.609375,y_center:.453125},{w:1,h:1,x_center:.609375,y_center:.453125},{w:1,h:1,x_center:.640625,y_center:.453125},{w:1,h:1,x_center:.640625,y_center:.453125},{w:1,h:1,x_center:.671875,y_center:.453125},{w:1,h:1,x_center:.671875,y_center:.453125},{w:1,h:1,x_center:.703125,y_center:.453125},{w:1,h:1,x_center:.703125,y_center:.453125},{w:1,h:1,x_center:.734375,y_center:.453125},{w:1,h:1,x_center:.734375,y_center:.453125},{w:1,h:1,x_center:.765625,y_center:.453125},{w:1,h:1,x_center:.765625,y_center:.453125},{w:1,h:1,x_center:.796875,y_center:.453125},{w:1,h:1,x_center:.796875,y_center:.453125},{w:1,h:1,x_center:.828125,y_center:.453125},{w:1,h:1,x_center:.828125,y_center:.453125},{w:1,h:1,x_center:.859375,y_center:.453125},{w:1,h:1,x_center:.859375,y_center:.453125},{w:1,h:1,x_center:.890625,y_center:.453125},{w:1,h:1,x_center:.890625,y_center:.453125},{w:1,h:1,x_center:.921875,y_center:.453125},{w:1,h:1,x_center:.921875,y_center:.453125},{w:1,h:1,x_center:.953125,y_center:.453125},{w:1,h:1,x_center:.953125,y_center:.453125},{w:1,h:1,x_center:.984375,y_center:.453125},{w:1,h:1,x_center:.984375,y_center:.453125},{w:1,h:1,x_center:.015625,y_center:.484375},{w:1,h:1,x_center:.015625,y_center:.484375},{w:1,h:1,x_center:.046875,y_center:.484375},{w:1,h:1,x_center:.046875,y_center:.484375},{w:1,h:1,x_center:.078125,y_center:.484375},{w:1,h:1,x_center:.078125,y_center:.484375},{w:1,h:1,x_center:.109375,y_center:.484375},{w:1,h:1,x_center:.109375,y_center:.484375},{w:1,h:1,x_center:.140625,y_center:.484375},{w:1,h:1,x_center:.140625,y_center:.484375},{w:1,h:1,x_center:.171875,y_center:.484375},{w:1,h:1,x_center:.171875,y_center:.484375},{w:1,h:1,x_center:.203125,y_center:.484375},{w:1,h:1,x_center:.203125,y_center:.484375},{w:1,h:1,x_center:.234375,y_center:.484375},{w:1,h:1,x_center:.234375,y_center:.484375},{w:1,h:1,x_center:.265625,y_center:.484375},{w:1,h:1,x_center:.265625,y_center:.484375},{w:1,h:1,x_center:.296875,y_center:.484375},{w:1,h:1,x_center:.296875,y_center:.484375},{w:1,h:1,x_center:.328125,y_center:.484375},{w:1,h:1,x_center:.328125,y_center:.484375},{w:1,h:1,x_center:.359375,y_center:.484375},{w:1,h:1,x_center:.359375,y_center:.484375},{w:1,h:1,x_center:.390625,y_center:.484375},{w:1,h:1,x_center:.390625,y_center:.484375},{w:1,h:1,x_center:.421875,y_center:.484375},{w:1,h:1,x_center:.421875,y_center:.484375},{w:1,h:1,x_center:.453125,y_center:.484375},{w:1,h:1,x_center:.453125,y_center:.484375},{w:1,h:1,x_center:.484375,y_center:.484375},{w:1,h:1,x_center:.484375,y_center:.484375},{w:1,h:1,x_center:.515625,y_center:.484375},{w:1,h:1,x_center:.515625,y_center:.484375},{w:1,h:1,x_center:.546875,y_center:.484375},{w:1,h:1,x_center:.546875,y_center:.484375},{w:1,h:1,x_center:.578125,y_center:.484375},{w:1,h:1,x_center:.578125,y_center:.484375},{w:1,h:1,x_center:.609375,y_center:.484375},{w:1,h:1,x_center:.609375,y_center:.484375},{w:1,h:1,x_center:.640625,y_center:.484375},{w:1,h:1,x_center:.640625,y_center:.484375},{w:1,h:1,x_center:.671875,y_center:.484375},{w:1,h:1,x_center:.671875,y_center:.484375},{w:1,h:1,x_center:.703125,y_center:.484375},{w:1,h:1,x_center:.703125,y_center:.484375},{w:1,h:1,x_center:.734375,y_center:.484375},{w:1,h:1,x_center:.734375,y_center:.484375},{w:1,h:1,x_center:.765625,y_center:.484375},{w:1,h:1,x_center:.765625,y_center:.484375},{w:1,h:1,x_center:.796875,y_center:.484375},{w:1,h:1,x_center:.796875,y_center:.484375},{w:1,h:1,x_center:.828125,y_center:.484375},{w:1,h:1,x_center:.828125,y_center:.484375},{w:1,h:1,x_center:.859375,y_center:.484375},{w:1,h:1,x_center:.859375,y_center:.484375},{w:1,h:1,x_center:.890625,y_center:.484375},{w:1,h:1,x_center:.890625,y_center:.484375},{w:1,h:1,x_center:.921875,y_center:.484375},{w:1,h:1,x_center:.921875,y_center:.484375},{w:1,h:1,x_center:.953125,y_center:.484375},{w:1,h:1,x_center:.953125,y_center:.484375},{w:1,h:1,x_center:.984375,y_center:.484375},{w:1,h:1,x_center:.984375,y_center:.484375},{w:1,h:1,x_center:.015625,y_center:.515625},{w:1,h:1,x_center:.015625,y_center:.515625},{w:1,h:1,x_center:.046875,y_center:.515625},{w:1,h:1,x_center:.046875,y_center:.515625},{w:1,h:1,x_center:.078125,y_center:.515625},{w:1,h:1,x_center:.078125,y_center:.515625},{w:1,h:1,x_center:.109375,y_center:.515625},{w:1,h:1,x_center:.109375,y_center:.515625},{w:1,h:1,x_center:.140625,y_center:.515625},{w:1,h:1,x_center:.140625,y_center:.515625},{w:1,h:1,x_center:.171875,y_center:.515625},{w:1,h:1,x_center:.171875,y_center:.515625},{w:1,h:1,x_center:.203125,y_center:.515625},{w:1,h:1,x_center:.203125,y_center:.515625},{w:1,h:1,x_center:.234375,y_center:.515625},{w:1,h:1,x_center:.234375,y_center:.515625},{w:1,h:1,x_center:.265625,y_center:.515625},{w:1,h:1,x_center:.265625,y_center:.515625},{w:1,h:1,x_center:.296875,y_center:.515625},{w:1,h:1,x_center:.296875,y_center:.515625},{w:1,h:1,x_center:.328125,y_center:.515625},{w:1,h:1,x_center:.328125,y_center:.515625},{w:1,h:1,x_center:.359375,y_center:.515625},{w:1,h:1,x_center:.359375,y_center:.515625},{w:1,h:1,x_center:.390625,y_center:.515625},{w:1,h:1,x_center:.390625,y_center:.515625},{w:1,h:1,x_center:.421875,y_center:.515625},{w:1,h:1,x_center:.421875,y_center:.515625},{w:1,h:1,x_center:.453125,y_center:.515625},{w:1,h:1,x_center:.453125,y_center:.515625},{w:1,h:1,x_center:.484375,y_center:.515625},{w:1,h:1,x_center:.484375,y_center:.515625},{w:1,h:1,x_center:.515625,y_center:.515625},{w:1,h:1,x_center:.515625,y_center:.515625},{w:1,h:1,x_center:.546875,y_center:.515625},{w:1,h:1,x_center:.546875,y_center:.515625},{w:1,h:1,x_center:.578125,y_center:.515625},{w:1,h:1,x_center:.578125,y_center:.515625},{w:1,h:1,x_center:.609375,y_center:.515625},{w:1,h:1,x_center:.609375,y_center:.515625},{w:1,h:1,x_center:.640625,y_center:.515625},{w:1,h:1,x_center:.640625,y_center:.515625},{w:1,h:1,x_center:.671875,y_center:.515625},{w:1,h:1,x_center:.671875,y_center:.515625},{w:1,h:1,x_center:.703125,y_center:.515625},{w:1,h:1,x_center:.703125,y_center:.515625},{w:1,h:1,x_center:.734375,y_center:.515625},{w:1,h:1,x_center:.734375,y_center:.515625},{w:1,h:1,x_center:.765625,y_center:.515625},{w:1,h:1,x_center:.765625,y_center:.515625},{w:1,h:1,x_center:.796875,y_center:.515625},{w:1,h:1,x_center:.796875,y_center:.515625},{w:1,h:1,x_center:.828125,y_center:.515625},{w:1,h:1,x_center:.828125,y_center:.515625},{w:1,h:1,x_center:.859375,y_center:.515625},{w:1,h:1,x_center:.859375,y_center:.515625},{w:1,h:1,x_center:.890625,y_center:.515625},{w:1,h:1,x_center:.890625,y_center:.515625},{w:1,h:1,x_center:.921875,y_center:.515625},{w:1,h:1,x_center:.921875,y_center:.515625},{w:1,h:1,x_center:.953125,y_center:.515625},{w:1,h:1,x_center:.953125,y_center:.515625},{w:1,h:1,x_center:.984375,y_center:.515625},{w:1,h:1,x_center:.984375,y_center:.515625},{w:1,h:1,x_center:.015625,y_center:.546875},{w:1,h:1,x_center:.015625,y_center:.546875},{w:1,h:1,x_center:.046875,y_center:.546875},{w:1,h:1,x_center:.046875,y_center:.546875},{w:1,h:1,x_center:.078125,y_center:.546875},{w:1,h:1,x_center:.078125,y_center:.546875},{w:1,h:1,x_center:.109375,y_center:.546875},{w:1,h:1,x_center:.109375,y_center:.546875},{w:1,h:1,x_center:.140625,y_center:.546875},{w:1,h:1,x_center:.140625,y_center:.546875},{w:1,h:1,x_center:.171875,y_center:.546875},{w:1,h:1,x_center:.171875,y_center:.546875},{w:1,h:1,x_center:.203125,y_center:.546875},{w:1,h:1,x_center:.203125,y_center:.546875},{w:1,h:1,x_center:.234375,y_center:.546875},{w:1,h:1,x_center:.234375,y_center:.546875},{w:1,h:1,x_center:.265625,y_center:.546875},{w:1,h:1,x_center:.265625,y_center:.546875},{w:1,h:1,x_center:.296875,y_center:.546875},{w:1,h:1,x_center:.296875,y_center:.546875},{w:1,h:1,x_center:.328125,y_center:.546875},{w:1,h:1,x_center:.328125,y_center:.546875},{w:1,h:1,x_center:.359375,y_center:.546875},{w:1,h:1,x_center:.359375,y_center:.546875},{w:1,h:1,x_center:.390625,y_center:.546875},{w:1,h:1,x_center:.390625,y_center:.546875},{w:1,h:1,x_center:.421875,y_center:.546875},{w:1,h:1,x_center:.421875,y_center:.546875},{w:1,h:1,x_center:.453125,y_center:.546875},{w:1,h:1,x_center:.453125,y_center:.546875},{w:1,h:1,x_center:.484375,y_center:.546875},{w:1,h:1,x_center:.484375,y_center:.546875},{w:1,h:1,x_center:.515625,y_center:.546875},{w:1,h:1,x_center:.515625,y_center:.546875},{w:1,h:1,x_center:.546875,y_center:.546875},{w:1,h:1,x_center:.546875,y_center:.546875},{w:1,h:1,x_center:.578125,y_center:.546875},{w:1,h:1,x_center:.578125,y_center:.546875},{w:1,h:1,x_center:.609375,y_center:.546875},{w:1,h:1,x_center:.609375,y_center:.546875},{w:1,h:1,x_center:.640625,y_center:.546875},{w:1,h:1,x_center:.640625,y_center:.546875},{w:1,h:1,x_center:.671875,y_center:.546875},{w:1,h:1,x_center:.671875,y_center:.546875},{w:1,h:1,x_center:.703125,y_center:.546875},{w:1,h:1,x_center:.703125,y_center:.546875},{w:1,h:1,x_center:.734375,y_center:.546875},{w:1,h:1,x_center:.734375,y_center:.546875},{w:1,h:1,x_center:.765625,y_center:.546875},{w:1,h:1,x_center:.765625,y_center:.546875},{w:1,h:1,x_center:.796875,y_center:.546875},{w:1,h:1,x_center:.796875,y_center:.546875},{w:1,h:1,x_center:.828125,y_center:.546875},{w:1,h:1,x_center:.828125,y_center:.546875},{w:1,h:1,x_center:.859375,y_center:.546875},{w:1,h:1,x_center:.859375,y_center:.546875},{w:1,h:1,x_center:.890625,y_center:.546875},{w:1,h:1,x_center:.890625,y_center:.546875},{w:1,h:1,x_center:.921875,y_center:.546875},{w:1,h:1,x_center:.921875,y_center:.546875},{w:1,h:1,x_center:.953125,y_center:.546875},{w:1,h:1,x_center:.953125,y_center:.546875},{w:1,h:1,x_center:.984375,y_center:.546875},{w:1,h:1,x_center:.984375,y_center:.546875},{w:1,h:1,x_center:.015625,y_center:.578125},{w:1,h:1,x_center:.015625,y_center:.578125},{w:1,h:1,x_center:.046875,y_center:.578125},{w:1,h:1,x_center:.046875,y_center:.578125},{w:1,h:1,x_center:.078125,y_center:.578125},{w:1,h:1,x_center:.078125,y_center:.578125},{w:1,h:1,x_center:.109375,y_center:.578125},{w:1,h:1,x_center:.109375,y_center:.578125},{w:1,h:1,x_center:.140625,y_center:.578125},{w:1,h:1,x_center:.140625,y_center:.578125},{w:1,h:1,x_center:.171875,y_center:.578125},{w:1,h:1,x_center:.171875,y_center:.578125},{w:1,h:1,x_center:.203125,y_center:.578125},{w:1,h:1,x_center:.203125,y_center:.578125},{w:1,h:1,x_center:.234375,y_center:.578125},{w:1,h:1,x_center:.234375,y_center:.578125},{w:1,h:1,x_center:.265625,y_center:.578125},{w:1,h:1,x_center:.265625,y_center:.578125},{w:1,h:1,x_center:.296875,y_center:.578125},{w:1,h:1,x_center:.296875,y_center:.578125},{w:1,h:1,x_center:.328125,y_center:.578125},{w:1,h:1,x_center:.328125,y_center:.578125},{w:1,h:1,x_center:.359375,y_center:.578125},{w:1,h:1,x_center:.359375,y_center:.578125},{w:1,h:1,x_center:.390625,y_center:.578125},{w:1,h:1,x_center:.390625,y_center:.578125},{w:1,h:1,x_center:.421875,y_center:.578125},{w:1,h:1,x_center:.421875,y_center:.578125},{w:1,h:1,x_center:.453125,y_center:.578125},{w:1,h:1,x_center:.453125,y_center:.578125},{w:1,h:1,x_center:.484375,y_center:.578125},{w:1,h:1,x_center:.484375,y_center:.578125},{w:1,h:1,x_center:.515625,y_center:.578125},{w:1,h:1,x_center:.515625,y_center:.578125},{w:1,h:1,x_center:.546875,y_center:.578125},{w:1,h:1,x_center:.546875,y_center:.578125},{w:1,h:1,x_center:.578125,y_center:.578125},{w:1,h:1,x_center:.578125,y_center:.578125},{w:1,h:1,x_center:.609375,y_center:.578125},{w:1,h:1,x_center:.609375,y_center:.578125},{w:1,h:1,x_center:.640625,y_center:.578125},{w:1,h:1,x_center:.640625,y_center:.578125},{w:1,h:1,x_center:.671875,y_center:.578125},{w:1,h:1,x_center:.671875,y_center:.578125},{w:1,h:1,x_center:.703125,y_center:.578125},{w:1,h:1,x_center:.703125,y_center:.578125},{w:1,h:1,x_center:.734375,y_center:.578125},{w:1,h:1,x_center:.734375,y_center:.578125},{w:1,h:1,x_center:.765625,y_center:.578125},{w:1,h:1,x_center:.765625,y_center:.578125},{w:1,h:1,x_center:.796875,y_center:.578125},{w:1,h:1,x_center:.796875,y_center:.578125},{w:1,h:1,x_center:.828125,y_center:.578125},{w:1,h:1,x_center:.828125,y_center:.578125},{w:1,h:1,x_center:.859375,y_center:.578125},{w:1,h:1,x_center:.859375,y_center:.578125},{w:1,h:1,x_center:.890625,y_center:.578125},{w:1,h:1,x_center:.890625,y_center:.578125},{w:1,h:1,x_center:.921875,y_center:.578125},{w:1,h:1,x_center:.921875,y_center:.578125},{w:1,h:1,x_center:.953125,y_center:.578125},{w:1,h:1,x_center:.953125,y_center:.578125},{w:1,h:1,x_center:.984375,y_center:.578125},{w:1,h:1,x_center:.984375,y_center:.578125},{w:1,h:1,x_center:.015625,y_center:.609375},{w:1,h:1,x_center:.015625,y_center:.609375},{w:1,h:1,x_center:.046875,y_center:.609375},{w:1,h:1,x_center:.046875,y_center:.609375},{w:1,h:1,x_center:.078125,y_center:.609375},{w:1,h:1,x_center:.078125,y_center:.609375},{w:1,h:1,x_center:.109375,y_center:.609375},{w:1,h:1,x_center:.109375,y_center:.609375},{w:1,h:1,x_center:.140625,y_center:.609375},{w:1,h:1,x_center:.140625,y_center:.609375},{w:1,h:1,x_center:.171875,y_center:.609375},{w:1,h:1,x_center:.171875,y_center:.609375},{w:1,h:1,x_center:.203125,y_center:.609375},{w:1,h:1,x_center:.203125,y_center:.609375},{w:1,h:1,x_center:.234375,y_center:.609375},{w:1,h:1,x_center:.234375,y_center:.609375},{w:1,h:1,x_center:.265625,y_center:.609375},{w:1,h:1,x_center:.265625,y_center:.609375},{w:1,h:1,x_center:.296875,y_center:.609375},{w:1,h:1,x_center:.296875,y_center:.609375},{w:1,h:1,x_center:.328125,y_center:.609375},{w:1,h:1,x_center:.328125,y_center:.609375},{w:1,h:1,x_center:.359375,y_center:.609375},{w:1,h:1,x_center:.359375,y_center:.609375},{w:1,h:1,x_center:.390625,y_center:.609375},{w:1,h:1,x_center:.390625,y_center:.609375},{w:1,h:1,x_center:.421875,y_center:.609375},{w:1,h:1,x_center:.421875,y_center:.609375},{w:1,h:1,x_center:.453125,y_center:.609375},{w:1,h:1,x_center:.453125,y_center:.609375},{w:1,h:1,x_center:.484375,y_center:.609375},{w:1,h:1,x_center:.484375,y_center:.609375},{w:1,h:1,x_center:.515625,y_center:.609375},{w:1,h:1,x_center:.515625,y_center:.609375},{w:1,h:1,x_center:.546875,y_center:.609375},{w:1,h:1,x_center:.546875,y_center:.609375},{w:1,h:1,x_center:.578125,y_center:.609375},{w:1,h:1,x_center:.578125,y_center:.609375},{w:1,h:1,x_center:.609375,y_center:.609375},{w:1,h:1,x_center:.609375,y_center:.609375},{w:1,h:1,x_center:.640625,y_center:.609375},{w:1,h:1,x_center:.640625,y_center:.609375},{w:1,h:1,x_center:.671875,y_center:.609375},{w:1,h:1,x_center:.671875,y_center:.609375},{w:1,h:1,x_center:.703125,y_center:.609375},{w:1,h:1,x_center:.703125,y_center:.609375},{w:1,h:1,x_center:.734375,y_center:.609375},{w:1,h:1,x_center:.734375,y_center:.609375},{w:1,h:1,x_center:.765625,y_center:.609375},{w:1,h:1,x_center:.765625,y_center:.609375},{w:1,h:1,x_center:.796875,y_center:.609375},{w:1,h:1,x_center:.796875,y_center:.609375},{w:1,h:1,x_center:.828125,y_center:.609375},{w:1,h:1,x_center:.828125,y_center:.609375},{w:1,h:1,x_center:.859375,y_center:.609375},{w:1,h:1,x_center:.859375,y_center:.609375},{w:1,h:1,x_center:.890625,y_center:.609375},{w:1,h:1,x_center:.890625,y_center:.609375},{w:1,h:1,x_center:.921875,y_center:.609375},{w:1,h:1,x_center:.921875,y_center:.609375},{w:1,h:1,x_center:.953125,y_center:.609375},{w:1,h:1,x_center:.953125,y_center:.609375},{w:1,h:1,x_center:.984375,y_center:.609375},{w:1,h:1,x_center:.984375,y_center:.609375},{w:1,h:1,x_center:.015625,y_center:.640625},{w:1,h:1,x_center:.015625,y_center:.640625},{w:1,h:1,x_center:.046875,y_center:.640625},{w:1,h:1,x_center:.046875,y_center:.640625},{w:1,h:1,x_center:.078125,y_center:.640625},{w:1,h:1,x_center:.078125,y_center:.640625},{w:1,h:1,x_center:.109375,y_center:.640625},{w:1,h:1,x_center:.109375,y_center:.640625},{w:1,h:1,x_center:.140625,y_center:.640625},{w:1,h:1,x_center:.140625,y_center:.640625},{w:1,h:1,x_center:.171875,y_center:.640625},{w:1,h:1,x_center:.171875,y_center:.640625},{w:1,h:1,x_center:.203125,y_center:.640625},{w:1,h:1,x_center:.203125,y_center:.640625},{w:1,h:1,x_center:.234375,y_center:.640625},{w:1,h:1,x_center:.234375,y_center:.640625},{w:1,h:1,x_center:.265625,y_center:.640625},{w:1,h:1,x_center:.265625,y_center:.640625},{w:1,h:1,x_center:.296875,y_center:.640625},{w:1,h:1,x_center:.296875,y_center:.640625},{w:1,h:1,x_center:.328125,y_center:.640625},{w:1,h:1,x_center:.328125,y_center:.640625},{w:1,h:1,x_center:.359375,y_center:.640625},{w:1,h:1,x_center:.359375,y_center:.640625},{w:1,h:1,x_center:.390625,y_center:.640625},{w:1,h:1,x_center:.390625,y_center:.640625},{w:1,h:1,x_center:.421875,y_center:.640625},{w:1,h:1,x_center:.421875,y_center:.640625},{w:1,h:1,x_center:.453125,y_center:.640625},{w:1,h:1,x_center:.453125,y_center:.640625},{w:1,h:1,x_center:.484375,y_center:.640625},{w:1,h:1,x_center:.484375,y_center:.640625},{w:1,h:1,x_center:.515625,y_center:.640625},{w:1,h:1,x_center:.515625,y_center:.640625},{w:1,h:1,x_center:.546875,y_center:.640625},{w:1,h:1,x_center:.546875,y_center:.640625},{w:1,h:1,x_center:.578125,y_center:.640625},{w:1,h:1,x_center:.578125,y_center:.640625},{w:1,h:1,x_center:.609375,y_center:.640625},{w:1,h:1,x_center:.609375,y_center:.640625},{w:1,h:1,x_center:.640625,y_center:.640625},{w:1,h:1,x_center:.640625,y_center:.640625},{w:1,h:1,x_center:.671875,y_center:.640625},{w:1,h:1,x_center:.671875,y_center:.640625},{w:1,h:1,x_center:.703125,y_center:.640625},{w:1,h:1,x_center:.703125,y_center:.640625},{w:1,h:1,x_center:.734375,y_center:.640625},{w:1,h:1,x_center:.734375,y_center:.640625},{w:1,h:1,x_center:.765625,y_center:.640625},{w:1,h:1,x_center:.765625,y_center:.640625},{w:1,h:1,x_center:.796875,y_center:.640625},{w:1,h:1,x_center:.796875,y_center:.640625},{w:1,h:1,x_center:.828125,y_center:.640625},{w:1,h:1,x_center:.828125,y_center:.640625},{w:1,h:1,x_center:.859375,y_center:.640625},{w:1,h:1,x_center:.859375,y_center:.640625},{w:1,h:1,x_center:.890625,y_center:.640625},{w:1,h:1,x_center:.890625,y_center:.640625},{w:1,h:1,x_center:.921875,y_center:.640625},{w:1,h:1,x_center:.921875,y_center:.640625},{w:1,h:1,x_center:.953125,y_center:.640625},{w:1,h:1,x_center:.953125,y_center:.640625},{w:1,h:1,x_center:.984375,y_center:.640625},{w:1,h:1,x_center:.984375,y_center:.640625},{w:1,h:1,x_center:.015625,y_center:.671875},{w:1,h:1,x_center:.015625,y_center:.671875},{w:1,h:1,x_center:.046875,y_center:.671875},{w:1,h:1,x_center:.046875,y_center:.671875},{w:1,h:1,x_center:.078125,y_center:.671875},{w:1,h:1,x_center:.078125,y_center:.671875},{w:1,h:1,x_center:.109375,y_center:.671875},{w:1,h:1,x_center:.109375,y_center:.671875},{w:1,h:1,x_center:.140625,y_center:.671875},{w:1,h:1,x_center:.140625,y_center:.671875},{w:1,h:1,x_center:.171875,y_center:.671875},{w:1,h:1,x_center:.171875,y_center:.671875},{w:1,h:1,x_center:.203125,y_center:.671875},{w:1,h:1,x_center:.203125,y_center:.671875},{w:1,h:1,x_center:.234375,y_center:.671875},{w:1,h:1,x_center:.234375,y_center:.671875},{w:1,h:1,x_center:.265625,y_center:.671875},{w:1,h:1,x_center:.265625,y_center:.671875},{w:1,h:1,x_center:.296875,y_center:.671875},{w:1,h:1,x_center:.296875,y_center:.671875},{w:1,h:1,x_center:.328125,y_center:.671875},{w:1,h:1,x_center:.328125,y_center:.671875},{w:1,h:1,x_center:.359375,y_center:.671875},{w:1,h:1,x_center:.359375,y_center:.671875},{w:1,h:1,x_center:.390625,y_center:.671875},{w:1,h:1,x_center:.390625,y_center:.671875},{w:1,h:1,x_center:.421875,y_center:.671875},{w:1,h:1,x_center:.421875,y_center:.671875},{w:1,h:1,x_center:.453125,y_center:.671875},{w:1,h:1,x_center:.453125,y_center:.671875},{w:1,h:1,x_center:.484375,y_center:.671875},{w:1,h:1,x_center:.484375,y_center:.671875},{w:1,h:1,x_center:.515625,y_center:.671875},{w:1,h:1,x_center:.515625,y_center:.671875},{w:1,h:1,x_center:.546875,y_center:.671875},{w:1,h:1,x_center:.546875,y_center:.671875},{w:1,h:1,x_center:.578125,y_center:.671875},{w:1,h:1,x_center:.578125,y_center:.671875},{w:1,h:1,x_center:.609375,y_center:.671875},{w:1,h:1,x_center:.609375,y_center:.671875},{w:1,h:1,x_center:.640625,y_center:.671875},{w:1,h:1,x_center:.640625,y_center:.671875},{w:1,h:1,x_center:.671875,y_center:.671875},{w:1,h:1,x_center:.671875,y_center:.671875},{w:1,h:1,x_center:.703125,y_center:.671875},{w:1,h:1,x_center:.703125,y_center:.671875},{w:1,h:1,x_center:.734375,y_center:.671875},{w:1,h:1,x_center:.734375,y_center:.671875},{w:1,h:1,x_center:.765625,y_center:.671875},{w:1,h:1,x_center:.765625,y_center:.671875},{w:1,h:1,x_center:.796875,y_center:.671875},{w:1,h:1,x_center:.796875,y_center:.671875},{w:1,h:1,x_center:.828125,y_center:.671875},{w:1,h:1,x_center:.828125,y_center:.671875},{w:1,h:1,x_center:.859375,y_center:.671875},{w:1,h:1,x_center:.859375,y_center:.671875},{w:1,h:1,x_center:.890625,y_center:.671875},{w:1,h:1,x_center:.890625,y_center:.671875},{w:1,h:1,x_center:.921875,y_center:.671875},{w:1,h:1,x_center:.921875,y_center:.671875},{w:1,h:1,x_center:.953125,y_center:.671875},{w:1,h:1,x_center:.953125,y_center:.671875},{w:1,h:1,x_center:.984375,y_center:.671875},{w:1,h:1,x_center:.984375,y_center:.671875},{w:1,h:1,x_center:.015625,y_center:.703125},{w:1,h:1,x_center:.015625,y_center:.703125},{w:1,h:1,x_center:.046875,y_center:.703125},{w:1,h:1,x_center:.046875,y_center:.703125},{w:1,h:1,x_center:.078125,y_center:.703125},{w:1,h:1,x_center:.078125,y_center:.703125},{w:1,h:1,x_center:.109375,y_center:.703125},{w:1,h:1,x_center:.109375,y_center:.703125},{w:1,h:1,x_center:.140625,y_center:.703125},{w:1,h:1,x_center:.140625,y_center:.703125},{w:1,h:1,x_center:.171875,y_center:.703125},{w:1,h:1,x_center:.171875,y_center:.703125},{w:1,h:1,x_center:.203125,y_center:.703125},{w:1,h:1,x_center:.203125,y_center:.703125},{w:1,h:1,x_center:.234375,y_center:.703125},{w:1,h:1,x_center:.234375,y_center:.703125},{w:1,h:1,x_center:.265625,y_center:.703125},{w:1,h:1,x_center:.265625,y_center:.703125},{w:1,h:1,x_center:.296875,y_center:.703125},{w:1,h:1,x_center:.296875,y_center:.703125},{w:1,h:1,x_center:.328125,y_center:.703125},{w:1,h:1,x_center:.328125,y_center:.703125},{w:1,h:1,x_center:.359375,y_center:.703125},{w:1,h:1,x_center:.359375,y_center:.703125},{w:1,h:1,x_center:.390625,y_center:.703125},{w:1,h:1,x_center:.390625,y_center:.703125},{w:1,h:1,x_center:.421875,y_center:.703125},{w:1,h:1,x_center:.421875,y_center:.703125},{w:1,h:1,x_center:.453125,y_center:.703125},{w:1,h:1,x_center:.453125,y_center:.703125},{w:1,h:1,x_center:.484375,y_center:.703125},{w:1,h:1,x_center:.484375,y_center:.703125},{w:1,h:1,x_center:.515625,y_center:.703125},{w:1,h:1,x_center:.515625,y_center:.703125},{w:1,h:1,x_center:.546875,y_center:.703125},{w:1,h:1,x_center:.546875,y_center:.703125},{w:1,h:1,x_center:.578125,y_center:.703125},{w:1,h:1,x_center:.578125,y_center:.703125},{w:1,h:1,x_center:.609375,y_center:.703125},{w:1,h:1,x_center:.609375,y_center:.703125},{w:1,h:1,x_center:.640625,y_center:.703125},{w:1,h:1,x_center:.640625,y_center:.703125},{w:1,h:1,x_center:.671875,y_center:.703125},{w:1,h:1,x_center:.671875,y_center:.703125},{w:1,h:1,x_center:.703125,y_center:.703125},{w:1,h:1,x_center:.703125,y_center:.703125},{w:1,h:1,x_center:.734375,y_center:.703125},{w:1,h:1,x_center:.734375,y_center:.703125},{w:1,h:1,x_center:.765625,y_center:.703125},{w:1,h:1,x_center:.765625,y_center:.703125},{w:1,h:1,x_center:.796875,y_center:.703125},{w:1,h:1,x_center:.796875,y_center:.703125},{w:1,h:1,x_center:.828125,y_center:.703125},{w:1,h:1,x_center:.828125,y_center:.703125},{w:1,h:1,x_center:.859375,y_center:.703125},{w:1,h:1,x_center:.859375,y_center:.703125},{w:1,h:1,x_center:.890625,y_center:.703125},{w:1,h:1,x_center:.890625,y_center:.703125},{w:1,h:1,x_center:.921875,y_center:.703125},{w:1,h:1,x_center:.921875,y_center:.703125},{w:1,h:1,x_center:.953125,y_center:.703125},{w:1,h:1,x_center:.953125,y_center:.703125},{w:1,h:1,x_center:.984375,y_center:.703125},{w:1,h:1,x_center:.984375,y_center:.703125},{w:1,h:1,x_center:.015625,y_center:.734375},{w:1,h:1,x_center:.015625,y_center:.734375},{w:1,h:1,x_center:.046875,y_center:.734375},{w:1,h:1,x_center:.046875,y_center:.734375},{w:1,h:1,x_center:.078125,y_center:.734375},{w:1,h:1,x_center:.078125,y_center:.734375},{w:1,h:1,x_center:.109375,y_center:.734375},{w:1,h:1,x_center:.109375,y_center:.734375},{w:1,h:1,x_center:.140625,y_center:.734375},{w:1,h:1,x_center:.140625,y_center:.734375},{w:1,h:1,x_center:.171875,y_center:.734375},{w:1,h:1,x_center:.171875,y_center:.734375},{w:1,h:1,x_center:.203125,y_center:.734375},{w:1,h:1,x_center:.203125,y_center:.734375},{w:1,h:1,x_center:.234375,y_center:.734375},{w:1,h:1,x_center:.234375,y_center:.734375},{w:1,h:1,x_center:.265625,y_center:.734375},{w:1,h:1,x_center:.265625,y_center:.734375},{w:1,h:1,x_center:.296875,y_center:.734375},{w:1,h:1,x_center:.296875,y_center:.734375},{w:1,h:1,x_center:.328125,y_center:.734375},{w:1,h:1,x_center:.328125,y_center:.734375},{w:1,h:1,x_center:.359375,y_center:.734375},{w:1,h:1,x_center:.359375,y_center:.734375},{w:1,h:1,x_center:.390625,y_center:.734375},{w:1,h:1,x_center:.390625,y_center:.734375},{w:1,h:1,x_center:.421875,y_center:.734375},{w:1,h:1,x_center:.421875,y_center:.734375},{w:1,h:1,x_center:.453125,y_center:.734375},{w:1,h:1,x_center:.453125,y_center:.734375},{w:1,h:1,x_center:.484375,y_center:.734375},{w:1,h:1,x_center:.484375,y_center:.734375},{w:1,h:1,x_center:.515625,y_center:.734375},{w:1,h:1,x_center:.515625,y_center:.734375},{w:1,h:1,x_center:.546875,y_center:.734375},{w:1,h:1,x_center:.546875,y_center:.734375},{w:1,h:1,x_center:.578125,y_center:.734375},{w:1,h:1,x_center:.578125,y_center:.734375},{w:1,h:1,x_center:.609375,y_center:.734375},{w:1,h:1,x_center:.609375,y_center:.734375},{w:1,h:1,x_center:.640625,y_center:.734375},{w:1,h:1,x_center:.640625,y_center:.734375},{w:1,h:1,x_center:.671875,y_center:.734375},{w:1,h:1,x_center:.671875,y_center:.734375},{w:1,h:1,x_center:.703125,y_center:.734375},{w:1,h:1,x_center:.703125,y_center:.734375},{w:1,h:1,x_center:.734375,y_center:.734375},{w:1,h:1,x_center:.734375,y_center:.734375},{w:1,h:1,x_center:.765625,y_center:.734375},{w:1,h:1,x_center:.765625,y_center:.734375},{w:1,h:1,x_center:.796875,y_center:.734375},{w:1,h:1,x_center:.796875,y_center:.734375},{w:1,h:1,x_center:.828125,y_center:.734375},{w:1,h:1,x_center:.828125,y_center:.734375},{w:1,h:1,x_center:.859375,y_center:.734375},{w:1,h:1,x_center:.859375,y_center:.734375},{w:1,h:1,x_center:.890625,y_center:.734375},{w:1,h:1,x_center:.890625,y_center:.734375},{w:1,h:1,x_center:.921875,y_center:.734375},{w:1,h:1,x_center:.921875,y_center:.734375},{w:1,h:1,x_center:.953125,y_center:.734375},{w:1,h:1,x_center:.953125,y_center:.734375},{w:1,h:1,x_center:.984375,y_center:.734375},{w:1,h:1,x_center:.984375,y_center:.734375},{w:1,h:1,x_center:.015625,y_center:.765625},{w:1,h:1,x_center:.015625,y_center:.765625},{w:1,h:1,x_center:.046875,y_center:.765625},{w:1,h:1,x_center:.046875,y_center:.765625},{w:1,h:1,x_center:.078125,y_center:.765625},{w:1,h:1,x_center:.078125,y_center:.765625},{w:1,h:1,x_center:.109375,y_center:.765625},{w:1,h:1,x_center:.109375,y_center:.765625},{w:1,h:1,x_center:.140625,y_center:.765625},{w:1,h:1,x_center:.140625,y_center:.765625},{w:1,h:1,x_center:.171875,y_center:.765625},{w:1,h:1,x_center:.171875,y_center:.765625},{w:1,h:1,x_center:.203125,y_center:.765625},{w:1,h:1,x_center:.203125,y_center:.765625},{w:1,h:1,x_center:.234375,y_center:.765625},{w:1,h:1,x_center:.234375,y_center:.765625},{w:1,h:1,x_center:.265625,y_center:.765625},{w:1,h:1,x_center:.265625,y_center:.765625},{w:1,h:1,x_center:.296875,y_center:.765625},{w:1,h:1,x_center:.296875,y_center:.765625},{w:1,h:1,x_center:.328125,y_center:.765625},{w:1,h:1,x_center:.328125,y_center:.765625},{w:1,h:1,x_center:.359375,y_center:.765625},{w:1,h:1,x_center:.359375,y_center:.765625},{w:1,h:1,x_center:.390625,y_center:.765625},{w:1,h:1,x_center:.390625,y_center:.765625},{w:1,h:1,x_center:.421875,y_center:.765625},{w:1,h:1,x_center:.421875,y_center:.765625},{w:1,h:1,x_center:.453125,y_center:.765625},{w:1,h:1,x_center:.453125,y_center:.765625},{w:1,h:1,x_center:.484375,y_center:.765625},{w:1,h:1,x_center:.484375,y_center:.765625},{w:1,h:1,x_center:.515625,y_center:.765625},{w:1,h:1,x_center:.515625,y_center:.765625},{w:1,h:1,x_center:.546875,y_center:.765625},{w:1,h:1,x_center:.546875,y_center:.765625},{w:1,h:1,x_center:.578125,y_center:.765625},{w:1,h:1,x_center:.578125,y_center:.765625},{w:1,h:1,x_center:.609375,y_center:.765625},{w:1,h:1,x_center:.609375,y_center:.765625},{w:1,h:1,x_center:.640625,y_center:.765625},{w:1,h:1,x_center:.640625,y_center:.765625},{w:1,h:1,x_center:.671875,y_center:.765625},{w:1,h:1,x_center:.671875,y_center:.765625},{w:1,h:1,x_center:.703125,y_center:.765625},{w:1,h:1,x_center:.703125,y_center:.765625},{w:1,h:1,x_center:.734375,y_center:.765625},{w:1,h:1,x_center:.734375,y_center:.765625},{w:1,h:1,x_center:.765625,y_center:.765625},{w:1,h:1,x_center:.765625,y_center:.765625},{w:1,h:1,x_center:.796875,y_center:.765625},{w:1,h:1,x_center:.796875,y_center:.765625},{w:1,h:1,x_center:.828125,y_center:.765625},{w:1,h:1,x_center:.828125,y_center:.765625},{w:1,h:1,x_center:.859375,y_center:.765625},{w:1,h:1,x_center:.859375,y_center:.765625},{w:1,h:1,x_center:.890625,y_center:.765625},{w:1,h:1,x_center:.890625,y_center:.765625},{w:1,h:1,x_center:.921875,y_center:.765625},{w:1,h:1,x_center:.921875,y_center:.765625},{w:1,h:1,x_center:.953125,y_center:.765625},{w:1,h:1,x_center:.953125,y_center:.765625},{w:1,h:1,x_center:.984375,y_center:.765625},{w:1,h:1,x_center:.984375,y_center:.765625},{w:1,h:1,x_center:.015625,y_center:.796875},{w:1,h:1,x_center:.015625,y_center:.796875},{w:1,h:1,x_center:.046875,y_center:.796875},{w:1,h:1,x_center:.046875,y_center:.796875},{w:1,h:1,x_center:.078125,y_center:.796875},{w:1,h:1,x_center:.078125,y_center:.796875},{w:1,h:1,x_center:.109375,y_center:.796875},{w:1,h:1,x_center:.109375,y_center:.796875},{w:1,h:1,x_center:.140625,y_center:.796875},{w:1,h:1,x_center:.140625,y_center:.796875},{w:1,h:1,x_center:.171875,y_center:.796875},{w:1,h:1,x_center:.171875,y_center:.796875},{w:1,h:1,x_center:.203125,y_center:.796875},{w:1,h:1,x_center:.203125,y_center:.796875},{w:1,h:1,x_center:.234375,y_center:.796875},{w:1,h:1,x_center:.234375,y_center:.796875},{w:1,h:1,x_center:.265625,y_center:.796875},{w:1,h:1,x_center:.265625,y_center:.796875},{w:1,h:1,x_center:.296875,y_center:.796875},{w:1,h:1,x_center:.296875,y_center:.796875},{w:1,h:1,x_center:.328125,y_center:.796875},{w:1,h:1,x_center:.328125,y_center:.796875},{w:1,h:1,x_center:.359375,y_center:.796875},{w:1,h:1,x_center:.359375,y_center:.796875},{w:1,h:1,x_center:.390625,y_center:.796875},{w:1,h:1,x_center:.390625,y_center:.796875},{w:1,h:1,x_center:.421875,y_center:.796875},{w:1,h:1,x_center:.421875,y_center:.796875},{w:1,h:1,x_center:.453125,y_center:.796875},{w:1,h:1,x_center:.453125,y_center:.796875},{w:1,h:1,x_center:.484375,y_center:.796875},{w:1,h:1,x_center:.484375,y_center:.796875},{w:1,h:1,x_center:.515625,y_center:.796875},{w:1,h:1,x_center:.515625,y_center:.796875},{w:1,h:1,x_center:.546875,y_center:.796875},{w:1,h:1,x_center:.546875,y_center:.796875},{w:1,h:1,x_center:.578125,y_center:.796875},{w:1,h:1,x_center:.578125,y_center:.796875},{w:1,h:1,x_center:.609375,y_center:.796875},{w:1,h:1,x_center:.609375,y_center:.796875},{w:1,h:1,x_center:.640625,y_center:.796875},{w:1,h:1,x_center:.640625,y_center:.796875},{w:1,h:1,x_center:.671875,y_center:.796875},{w:1,h:1,x_center:.671875,y_center:.796875},{w:1,h:1,x_center:.703125,y_center:.796875},{w:1,h:1,x_center:.703125,y_center:.796875},{w:1,h:1,x_center:.734375,y_center:.796875},{w:1,h:1,x_center:.734375,y_center:.796875},{w:1,h:1,x_center:.765625,y_center:.796875},{w:1,h:1,x_center:.765625,y_center:.796875},{w:1,h:1,x_center:.796875,y_center:.796875},{w:1,h:1,x_center:.796875,y_center:.796875},{w:1,h:1,x_center:.828125,y_center:.796875},{w:1,h:1,x_center:.828125,y_center:.796875},{w:1,h:1,x_center:.859375,y_center:.796875},{w:1,h:1,x_center:.859375,y_center:.796875},{w:1,h:1,x_center:.890625,y_center:.796875},{w:1,h:1,x_center:.890625,y_center:.796875},{w:1,h:1,x_center:.921875,y_center:.796875},{w:1,h:1,x_center:.921875,y_center:.796875},{w:1,h:1,x_center:.953125,y_center:.796875},{w:1,h:1,x_center:.953125,y_center:.796875},{w:1,h:1,x_center:.984375,y_center:.796875},{w:1,h:1,x_center:.984375,y_center:.796875},{w:1,h:1,x_center:.015625,y_center:.828125},{w:1,h:1,x_center:.015625,y_center:.828125},{w:1,h:1,x_center:.046875,y_center:.828125},{w:1,h:1,x_center:.046875,y_center:.828125},{w:1,h:1,x_center:.078125,y_center:.828125},{w:1,h:1,x_center:.078125,y_center:.828125},{w:1,h:1,x_center:.109375,y_center:.828125},{w:1,h:1,x_center:.109375,y_center:.828125},{w:1,h:1,x_center:.140625,y_center:.828125},{w:1,h:1,x_center:.140625,y_center:.828125},{w:1,h:1,x_center:.171875,y_center:.828125},{w:1,h:1,x_center:.171875,y_center:.828125},{w:1,h:1,x_center:.203125,y_center:.828125},{w:1,h:1,x_center:.203125,y_center:.828125},{w:1,h:1,x_center:.234375,y_center:.828125},{w:1,h:1,x_center:.234375,y_center:.828125},{w:1,h:1,x_center:.265625,y_center:.828125},{w:1,h:1,x_center:.265625,y_center:.828125},{w:1,h:1,x_center:.296875,y_center:.828125},{w:1,h:1,x_center:.296875,y_center:.828125},{w:1,h:1,x_center:.328125,y_center:.828125},{w:1,h:1,x_center:.328125,y_center:.828125},{w:1,h:1,x_center:.359375,y_center:.828125},{w:1,h:1,x_center:.359375,y_center:.828125},{w:1,h:1,x_center:.390625,y_center:.828125},{w:1,h:1,x_center:.390625,y_center:.828125},{w:1,h:1,x_center:.421875,y_center:.828125},{w:1,h:1,x_center:.421875,y_center:.828125},{w:1,h:1,x_center:.453125,y_center:.828125},{w:1,h:1,x_center:.453125,y_center:.828125},{w:1,h:1,x_center:.484375,y_center:.828125},{w:1,h:1,x_center:.484375,y_center:.828125},{w:1,h:1,x_center:.515625,y_center:.828125},{w:1,h:1,x_center:.515625,y_center:.828125},{w:1,h:1,x_center:.546875,y_center:.828125},{w:1,h:1,x_center:.546875,y_center:.828125},{w:1,h:1,x_center:.578125,y_center:.828125},{w:1,h:1,x_center:.578125,y_center:.828125},{w:1,h:1,x_center:.609375,y_center:.828125},{w:1,h:1,x_center:.609375,y_center:.828125},{w:1,h:1,x_center:.640625,y_center:.828125},{w:1,h:1,x_center:.640625,y_center:.828125},{w:1,h:1,x_center:.671875,y_center:.828125},{w:1,h:1,x_center:.671875,y_center:.828125},{w:1,h:1,x_center:.703125,y_center:.828125},{w:1,h:1,x_center:.703125,y_center:.828125},{w:1,h:1,x_center:.734375,y_center:.828125},{w:1,h:1,x_center:.734375,y_center:.828125},{w:1,h:1,x_center:.765625,y_center:.828125},{w:1,h:1,x_center:.765625,y_center:.828125},{w:1,h:1,x_center:.796875,y_center:.828125},{w:1,h:1,x_center:.796875,y_center:.828125},{w:1,h:1,x_center:.828125,y_center:.828125},{w:1,h:1,x_center:.828125,y_center:.828125},{w:1,h:1,x_center:.859375,y_center:.828125},{w:1,h:1,x_center:.859375,y_center:.828125},{w:1,h:1,x_center:.890625,y_center:.828125},{w:1,h:1,x_center:.890625,y_center:.828125},{w:1,h:1,x_center:.921875,y_center:.828125},{w:1,h:1,x_center:.921875,y_center:.828125},{w:1,h:1,x_center:.953125,y_center:.828125},{w:1,h:1,x_center:.953125,y_center:.828125},{w:1,h:1,x_center:.984375,y_center:.828125},{w:1,h:1,x_center:.984375,y_center:.828125},{w:1,h:1,x_center:.015625,y_center:.859375},{w:1,h:1,x_center:.015625,y_center:.859375},{w:1,h:1,x_center:.046875,y_center:.859375},{w:1,h:1,x_center:.046875,y_center:.859375},{w:1,h:1,x_center:.078125,y_center:.859375},{w:1,h:1,x_center:.078125,y_center:.859375},{w:1,h:1,x_center:.109375,y_center:.859375},{w:1,h:1,x_center:.109375,y_center:.859375},{w:1,h:1,x_center:.140625,y_center:.859375},{w:1,h:1,x_center:.140625,y_center:.859375},{w:1,h:1,x_center:.171875,y_center:.859375},{w:1,h:1,x_center:.171875,y_center:.859375},{w:1,h:1,x_center:.203125,y_center:.859375},{w:1,h:1,x_center:.203125,y_center:.859375},{w:1,h:1,x_center:.234375,y_center:.859375},{w:1,h:1,x_center:.234375,y_center:.859375},{w:1,h:1,x_center:.265625,y_center:.859375},{w:1,h:1,x_center:.265625,y_center:.859375},{w:1,h:1,x_center:.296875,y_center:.859375},{w:1,h:1,x_center:.296875,y_center:.859375},{w:1,h:1,x_center:.328125,y_center:.859375},{w:1,h:1,x_center:.328125,y_center:.859375},{w:1,h:1,x_center:.359375,y_center:.859375},{w:1,h:1,x_center:.359375,y_center:.859375},{w:1,h:1,x_center:.390625,y_center:.859375},{w:1,h:1,x_center:.390625,y_center:.859375},{w:1,h:1,x_center:.421875,y_center:.859375},{w:1,h:1,x_center:.421875,y_center:.859375},{w:1,h:1,x_center:.453125,y_center:.859375},{w:1,h:1,x_center:.453125,y_center:.859375},{w:1,h:1,x_center:.484375,y_center:.859375},{w:1,h:1,x_center:.484375,y_center:.859375},{w:1,h:1,x_center:.515625,y_center:.859375},{w:1,h:1,x_center:.515625,y_center:.859375},{w:1,h:1,x_center:.546875,y_center:.859375},{w:1,h:1,x_center:.546875,y_center:.859375},{w:1,h:1,x_center:.578125,y_center:.859375},{w:1,h:1,x_center:.578125,y_center:.859375},{w:1,h:1,x_center:.609375,y_center:.859375},{w:1,h:1,x_center:.609375,y_center:.859375},{w:1,h:1,x_center:.640625,y_center:.859375},{w:1,h:1,x_center:.640625,y_center:.859375},{w:1,h:1,x_center:.671875,y_center:.859375},{w:1,h:1,x_center:.671875,y_center:.859375},{w:1,h:1,x_center:.703125,y_center:.859375},{w:1,h:1,x_center:.703125,y_center:.859375},{w:1,h:1,x_center:.734375,y_center:.859375},{w:1,h:1,x_center:.734375,y_center:.859375},{w:1,h:1,x_center:.765625,y_center:.859375},{w:1,h:1,x_center:.765625,y_center:.859375},{w:1,h:1,x_center:.796875,y_center:.859375},{w:1,h:1,x_center:.796875,y_center:.859375},{w:1,h:1,x_center:.828125,y_center:.859375},{w:1,h:1,x_center:.828125,y_center:.859375},{w:1,h:1,x_center:.859375,y_center:.859375},{w:1,h:1,x_center:.859375,y_center:.859375},{w:1,h:1,x_center:.890625,y_center:.859375},{w:1,h:1,x_center:.890625,y_center:.859375},{w:1,h:1,x_center:.921875,y_center:.859375},{w:1,h:1,x_center:.921875,y_center:.859375},{w:1,h:1,x_center:.953125,y_center:.859375},{w:1,h:1,x_center:.953125,y_center:.859375},{w:1,h:1,x_center:.984375,y_center:.859375},{w:1,h:1,x_center:.984375,y_center:.859375},{w:1,h:1,x_center:.015625,y_center:.890625},{w:1,h:1,x_center:.015625,y_center:.890625},{w:1,h:1,x_center:.046875,y_center:.890625},{w:1,h:1,x_center:.046875,y_center:.890625},{w:1,h:1,x_center:.078125,y_center:.890625},{w:1,h:1,x_center:.078125,y_center:.890625},{w:1,h:1,x_center:.109375,y_center:.890625},{w:1,h:1,x_center:.109375,y_center:.890625},{w:1,h:1,x_center:.140625,y_center:.890625},{w:1,h:1,x_center:.140625,y_center:.890625},{w:1,h:1,x_center:.171875,y_center:.890625},{w:1,h:1,x_center:.171875,y_center:.890625},{w:1,h:1,x_center:.203125,y_center:.890625},{w:1,h:1,x_center:.203125,y_center:.890625},{w:1,h:1,x_center:.234375,y_center:.890625},{w:1,h:1,x_center:.234375,y_center:.890625},{w:1,h:1,x_center:.265625,y_center:.890625},{w:1,h:1,x_center:.265625,y_center:.890625},{w:1,h:1,x_center:.296875,y_center:.890625},{w:1,h:1,x_center:.296875,y_center:.890625},{w:1,h:1,x_center:.328125,y_center:.890625},{w:1,h:1,x_center:.328125,y_center:.890625},{w:1,h:1,x_center:.359375,y_center:.890625},{w:1,h:1,x_center:.359375,y_center:.890625},{w:1,h:1,x_center:.390625,y_center:.890625},{w:1,h:1,x_center:.390625,y_center:.890625},{w:1,h:1,x_center:.421875,y_center:.890625},{w:1,h:1,x_center:.421875,y_center:.890625},{w:1,h:1,x_center:.453125,y_center:.890625},{w:1,h:1,x_center:.453125,y_center:.890625},{w:1,h:1,x_center:.484375,y_center:.890625},{w:1,h:1,x_center:.484375,y_center:.890625},{w:1,h:1,x_center:.515625,y_center:.890625},{w:1,h:1,x_center:.515625,y_center:.890625},{w:1,h:1,x_center:.546875,y_center:.890625},{w:1,h:1,x_center:.546875,y_center:.890625},{w:1,h:1,x_center:.578125,y_center:.890625},{w:1,h:1,x_center:.578125,y_center:.890625},{w:1,h:1,x_center:.609375,y_center:.890625},{w:1,h:1,x_center:.609375,y_center:.890625},{w:1,h:1,x_center:.640625,y_center:.890625},{w:1,h:1,x_center:.640625,y_center:.890625},{w:1,h:1,x_center:.671875,y_center:.890625},{w:1,h:1,x_center:.671875,y_center:.890625},{w:1,h:1,x_center:.703125,y_center:.890625},{w:1,h:1,x_center:.703125,y_center:.890625},{w:1,h:1,x_center:.734375,y_center:.890625},{w:1,h:1,x_center:.734375,y_center:.890625},{w:1,h:1,x_center:.765625,y_center:.890625},{w:1,h:1,x_center:.765625,y_center:.890625},{w:1,h:1,x_center:.796875,y_center:.890625},{w:1,h:1,x_center:.796875,y_center:.890625},{w:1,h:1,x_center:.828125,y_center:.890625},{w:1,h:1,x_center:.828125,y_center:.890625},{w:1,h:1,x_center:.859375,y_center:.890625},{w:1,h:1,x_center:.859375,y_center:.890625},{w:1,h:1,x_center:.890625,y_center:.890625},{w:1,h:1,x_center:.890625,y_center:.890625},{w:1,h:1,x_center:.921875,y_center:.890625},{w:1,h:1,x_center:.921875,y_center:.890625},{w:1,h:1,x_center:.953125,y_center:.890625},{w:1,h:1,x_center:.953125,y_center:.890625},{w:1,h:1,x_center:.984375,y_center:.890625},{w:1,h:1,x_center:.984375,y_center:.890625},{w:1,h:1,x_center:.015625,y_center:.921875},{w:1,h:1,x_center:.015625,y_center:.921875},{w:1,h:1,x_center:.046875,y_center:.921875},{w:1,h:1,x_center:.046875,y_center:.921875},{w:1,h:1,x_center:.078125,y_center:.921875},{w:1,h:1,x_center:.078125,y_center:.921875},{w:1,h:1,x_center:.109375,y_center:.921875},{w:1,h:1,x_center:.109375,y_center:.921875},{w:1,h:1,x_center:.140625,y_center:.921875},{w:1,h:1,x_center:.140625,y_center:.921875},{w:1,h:1,x_center:.171875,y_center:.921875},{w:1,h:1,x_center:.171875,y_center:.921875},{w:1,h:1,x_center:.203125,y_center:.921875},{w:1,h:1,x_center:.203125,y_center:.921875},{w:1,h:1,x_center:.234375,y_center:.921875},{w:1,h:1,x_center:.234375,y_center:.921875},{w:1,h:1,x_center:.265625,y_center:.921875},{w:1,h:1,x_center:.265625,y_center:.921875},{w:1,h:1,x_center:.296875,y_center:.921875},{w:1,h:1,x_center:.296875,y_center:.921875},{w:1,h:1,x_center:.328125,y_center:.921875},{w:1,h:1,x_center:.328125,y_center:.921875},{w:1,h:1,x_center:.359375,y_center:.921875},{w:1,h:1,x_center:.359375,y_center:.921875},{w:1,h:1,x_center:.390625,y_center:.921875},{w:1,h:1,x_center:.390625,y_center:.921875},{w:1,h:1,x_center:.421875,y_center:.921875},{w:1,h:1,x_center:.421875,y_center:.921875},{w:1,h:1,x_center:.453125,y_center:.921875},{w:1,h:1,x_center:.453125,y_center:.921875},{w:1,h:1,x_center:.484375,y_center:.921875},{w:1,h:1,x_center:.484375,y_center:.921875},{w:1,h:1,x_center:.515625,y_center:.921875},{w:1,h:1,x_center:.515625,y_center:.921875},{w:1,h:1,x_center:.546875,y_center:.921875},{w:1,h:1,x_center:.546875,y_center:.921875},{w:1,h:1,x_center:.578125,y_center:.921875},{w:1,h:1,x_center:.578125,y_center:.921875},{w:1,h:1,x_center:.609375,y_center:.921875},{w:1,h:1,x_center:.609375,y_center:.921875},{w:1,h:1,x_center:.640625,y_center:.921875},{w:1,h:1,x_center:.640625,y_center:.921875},{w:1,h:1,x_center:.671875,y_center:.921875},{w:1,h:1,x_center:.671875,y_center:.921875},{w:1,h:1,x_center:.703125,y_center:.921875},{w:1,h:1,x_center:.703125,y_center:.921875},{w:1,h:1,x_center:.734375,y_center:.921875},{w:1,h:1,x_center:.734375,y_center:.921875},{w:1,h:1,x_center:.765625,y_center:.921875},{w:1,h:1,x_center:.765625,y_center:.921875},{w:1,h:1,x_center:.796875,y_center:.921875},{w:1,h:1,x_center:.796875,y_center:.921875},{w:1,h:1,x_center:.828125,y_center:.921875},{w:1,h:1,x_center:.828125,y_center:.921875},{w:1,h:1,x_center:.859375,y_center:.921875},{w:1,h:1,x_center:.859375,y_center:.921875},{w:1,h:1,x_center:.890625,y_center:.921875},{w:1,h:1,x_center:.890625,y_center:.921875},{w:1,h:1,x_center:.921875,y_center:.921875},{w:1,h:1,x_center:.921875,y_center:.921875},{w:1,h:1,x_center:.953125,y_center:.921875},{w:1,h:1,x_center:.953125,y_center:.921875},{w:1,h:1,x_center:.984375,y_center:.921875},{w:1,h:1,x_center:.984375,y_center:.921875},{w:1,h:1,x_center:.015625,y_center:.953125},{w:1,h:1,x_center:.015625,y_center:.953125},{w:1,h:1,x_center:.046875,y_center:.953125},{w:1,h:1,x_center:.046875,y_center:.953125},{w:1,h:1,x_center:.078125,y_center:.953125},{w:1,h:1,x_center:.078125,y_center:.953125},{w:1,h:1,x_center:.109375,y_center:.953125},{w:1,h:1,x_center:.109375,y_center:.953125},{w:1,h:1,x_center:.140625,y_center:.953125},{w:1,h:1,x_center:.140625,y_center:.953125},{w:1,h:1,x_center:.171875,y_center:.953125},{w:1,h:1,x_center:.171875,y_center:.953125},{w:1,h:1,x_center:.203125,y_center:.953125},{w:1,h:1,x_center:.203125,y_center:.953125},{w:1,h:1,x_center:.234375,y_center:.953125},{w:1,h:1,x_center:.234375,y_center:.953125},{w:1,h:1,x_center:.265625,y_center:.953125},{w:1,h:1,x_center:.265625,y_center:.953125},{w:1,h:1,x_center:.296875,y_center:.953125},{w:1,h:1,x_center:.296875,y_center:.953125},{w:1,h:1,x_center:.328125,y_center:.953125},{w:1,h:1,x_center:.328125,y_center:.953125},{w:1,h:1,x_center:.359375,y_center:.953125},{w:1,h:1,x_center:.359375,y_center:.953125},{w:1,h:1,x_center:.390625,y_center:.953125},{w:1,h:1,x_center:.390625,y_center:.953125},{w:1,h:1,x_center:.421875,y_center:.953125},{w:1,h:1,x_center:.421875,y_center:.953125},{w:1,h:1,x_center:.453125,y_center:.953125},{w:1,h:1,x_center:.453125,y_center:.953125},{w:1,h:1,x_center:.484375,y_center:.953125},{w:1,h:1,x_center:.484375,y_center:.953125},{w:1,h:1,x_center:.515625,y_center:.953125},{w:1,h:1,x_center:.515625,y_center:.953125},{w:1,h:1,x_center:.546875,y_center:.953125},{w:1,h:1,x_center:.546875,y_center:.953125},{w:1,h:1,x_center:.578125,y_center:.953125},{w:1,h:1,x_center:.578125,y_center:.953125},{w:1,h:1,x_center:.609375,y_center:.953125},{w:1,h:1,x_center:.609375,y_center:.953125},{w:1,h:1,x_center:.640625,y_center:.953125},{w:1,h:1,x_center:.640625,y_center:.953125},{w:1,h:1,x_center:.671875,y_center:.953125},{w:1,h:1,x_center:.671875,y_center:.953125},{w:1,h:1,x_center:.703125,y_center:.953125},{w:1,h:1,x_center:.703125,y_center:.953125},{w:1,h:1,x_center:.734375,y_center:.953125},{w:1,h:1,x_center:.734375,y_center:.953125},{w:1,h:1,x_center:.765625,y_center:.953125},{w:1,h:1,x_center:.765625,y_center:.953125},{w:1,h:1,x_center:.796875,y_center:.953125},{w:1,h:1,x_center:.796875,y_center:.953125},{w:1,h:1,x_center:.828125,y_center:.953125},{w:1,h:1,x_center:.828125,y_center:.953125},{w:1,h:1,x_center:.859375,y_center:.953125},{w:1,h:1,x_center:.859375,y_center:.953125},{w:1,h:1,x_center:.890625,y_center:.953125},{w:1,h:1,x_center:.890625,y_center:.953125},{w:1,h:1,x_center:.921875,y_center:.953125},{w:1,h:1,x_center:.921875,y_center:.953125},{w:1,h:1,x_center:.953125,y_center:.953125},{w:1,h:1,x_center:.953125,y_center:.953125},{w:1,h:1,x_center:.984375,y_center:.953125},{w:1,h:1,x_center:.984375,y_center:.953125},{w:1,h:1,x_center:.015625,y_center:.984375},{w:1,h:1,x_center:.015625,y_center:.984375},{w:1,h:1,x_center:.046875,y_center:.984375},{w:1,h:1,x_center:.046875,y_center:.984375},{w:1,h:1,x_center:.078125,y_center:.984375},{w:1,h:1,x_center:.078125,y_center:.984375},{w:1,h:1,x_center:.109375,y_center:.984375},{w:1,h:1,x_center:.109375,y_center:.984375},{w:1,h:1,x_center:.140625,y_center:.984375},{w:1,h:1,x_center:.140625,y_center:.984375},{w:1,h:1,x_center:.171875,y_center:.984375},{w:1,h:1,x_center:.171875,y_center:.984375},{w:1,h:1,x_center:.203125,y_center:.984375},{w:1,h:1,x_center:.203125,y_center:.984375},{w:1,h:1,x_center:.234375,y_center:.984375},{w:1,h:1,x_center:.234375,y_center:.984375},{w:1,h:1,x_center:.265625,y_center:.984375},{w:1,h:1,x_center:.265625,y_center:.984375},{w:1,h:1,x_center:.296875,y_center:.984375},{w:1,h:1,x_center:.296875,y_center:.984375},{w:1,h:1,x_center:.328125,y_center:.984375},{w:1,h:1,x_center:.328125,y_center:.984375},{w:1,h:1,x_center:.359375,y_center:.984375},{w:1,h:1,x_center:.359375,y_center:.984375},{w:1,h:1,x_center:.390625,y_center:.984375},{w:1,h:1,x_center:.390625,y_center:.984375},{w:1,h:1,x_center:.421875,y_center:.984375},{w:1,h:1,x_center:.421875,y_center:.984375},{w:1,h:1,x_center:.453125,y_center:.984375},{w:1,h:1,x_center:.453125,y_center:.984375},{w:1,h:1,x_center:.484375,y_center:.984375},{w:1,h:1,x_center:.484375,y_center:.984375},{w:1,h:1,x_center:.515625,y_center:.984375},{w:1,h:1,x_center:.515625,y_center:.984375},{w:1,h:1,x_center:.546875,y_center:.984375},{w:1,h:1,x_center:.546875,y_center:.984375},{w:1,h:1,x_center:.578125,y_center:.984375},{w:1,h:1,x_center:.578125,y_center:.984375},{w:1,h:1,x_center:.609375,y_center:.984375},{w:1,h:1,x_center:.609375,y_center:.984375},{w:1,h:1,x_center:.640625,y_center:.984375},{w:1,h:1,x_center:.640625,y_center:.984375},{w:1,h:1,x_center:.671875,y_center:.984375},{w:1,h:1,x_center:.671875,y_center:.984375},{w:1,h:1,x_center:.703125,y_center:.984375},{w:1,h:1,x_center:.703125,y_center:.984375},{w:1,h:1,x_center:.734375,y_center:.984375},{w:1,h:1,x_center:.734375,y_center:.984375},{w:1,h:1,x_center:.765625,y_center:.984375},{w:1,h:1,x_center:.765625,y_center:.984375},{w:1,h:1,x_center:.796875,y_center:.984375},{w:1,h:1,x_center:.796875,y_center:.984375},{w:1,h:1,x_center:.828125,y_center:.984375},{w:1,h:1,x_center:.828125,y_center:.984375},{w:1,h:1,x_center:.859375,y_center:.984375},{w:1,h:1,x_center:.859375,y_center:.984375},{w:1,h:1,x_center:.890625,y_center:.984375},{w:1,h:1,x_center:.890625,y_center:.984375},{w:1,h:1,x_center:.921875,y_center:.984375},{w:1,h:1,x_center:.921875,y_center:.984375},{w:1,h:1,x_center:.953125,y_center:.984375},{w:1,h:1,x_center:.953125,y_center:.984375},{w:1,h:1,x_center:.984375,y_center:.984375},{w:1,h:1,x_center:.984375,y_center:.984375},{w:1,h:1,x_center:.03125,y_center:.03125},{w:1,h:1,x_center:.03125,y_center:.03125},{w:1,h:1,x_center:.09375,y_center:.03125},{w:1,h:1,x_center:.09375,y_center:.03125},{w:1,h:1,x_center:.15625,y_center:.03125},{w:1,h:1,x_center:.15625,y_center:.03125},{w:1,h:1,x_center:.21875,y_center:.03125},{w:1,h:1,x_center:.21875,y_center:.03125},{w:1,h:1,x_center:.28125,y_center:.03125},{w:1,h:1,x_center:.28125,y_center:.03125},{w:1,h:1,x_center:.34375,y_center:.03125},{w:1,h:1,x_center:.34375,y_center:.03125},{w:1,h:1,x_center:.40625,y_center:.03125},{w:1,h:1,x_center:.40625,y_center:.03125},{w:1,h:1,x_center:.46875,y_center:.03125},{w:1,h:1,x_center:.46875,y_center:.03125},{w:1,h:1,x_center:.53125,y_center:.03125},{w:1,h:1,x_center:.53125,y_center:.03125},{w:1,h:1,x_center:.59375,y_center:.03125},{w:1,h:1,x_center:.59375,y_center:.03125},{w:1,h:1,x_center:.65625,y_center:.03125},{w:1,h:1,x_center:.65625,y_center:.03125},{w:1,h:1,x_center:.71875,y_center:.03125},{w:1,h:1,x_center:.71875,y_center:.03125},{w:1,h:1,x_center:.78125,y_center:.03125},{w:1,h:1,x_center:.78125,y_center:.03125},{w:1,h:1,x_center:.84375,y_center:.03125},{w:1,h:1,x_center:.84375,y_center:.03125},{w:1,h:1,x_center:.90625,y_center:.03125},{w:1,h:1,x_center:.90625,y_center:.03125},{w:1,h:1,x_center:.96875,y_center:.03125},{w:1,h:1,x_center:.96875,y_center:.03125},{w:1,h:1,x_center:.03125,y_center:.09375},{w:1,h:1,x_center:.03125,y_center:.09375},{w:1,h:1,x_center:.09375,y_center:.09375},{w:1,h:1,x_center:.09375,y_center:.09375},{w:1,h:1,x_center:.15625,y_center:.09375},{w:1,h:1,x_center:.15625,y_center:.09375},{w:1,h:1,x_center:.21875,y_center:.09375},{w:1,h:1,x_center:.21875,y_center:.09375},{w:1,h:1,x_center:.28125,y_center:.09375},{w:1,h:1,x_center:.28125,y_center:.09375},{w:1,h:1,x_center:.34375,y_center:.09375},{w:1,h:1,x_center:.34375,y_center:.09375},{w:1,h:1,x_center:.40625,y_center:.09375},{w:1,h:1,x_center:.40625,y_center:.09375},{w:1,h:1,x_center:.46875,y_center:.09375},{w:1,h:1,x_center:.46875,y_center:.09375},{w:1,h:1,x_center:.53125,y_center:.09375},{w:1,h:1,x_center:.53125,y_center:.09375},{w:1,h:1,x_center:.59375,y_center:.09375},{w:1,h:1,x_center:.59375,y_center:.09375},{w:1,h:1,x_center:.65625,y_center:.09375},{w:1,h:1,x_center:.65625,y_center:.09375},{w:1,h:1,x_center:.71875,y_center:.09375},{w:1,h:1,x_center:.71875,y_center:.09375},{w:1,h:1,x_center:.78125,y_center:.09375},{w:1,h:1,x_center:.78125,y_center:.09375},{w:1,h:1,x_center:.84375,y_center:.09375},{w:1,h:1,x_center:.84375,y_center:.09375},{w:1,h:1,x_center:.90625,y_center:.09375},{w:1,h:1,x_center:.90625,y_center:.09375},{w:1,h:1,x_center:.96875,y_center:.09375},{w:1,h:1,x_center:.96875,y_center:.09375},{w:1,h:1,x_center:.03125,y_center:.15625},{w:1,h:1,x_center:.03125,y_center:.15625},{w:1,h:1,x_center:.09375,y_center:.15625},{w:1,h:1,x_center:.09375,y_center:.15625},{w:1,h:1,x_center:.15625,y_center:.15625},{w:1,h:1,x_center:.15625,y_center:.15625},{w:1,h:1,x_center:.21875,y_center:.15625},{w:1,h:1,x_center:.21875,y_center:.15625},{w:1,h:1,x_center:.28125,y_center:.15625},{w:1,h:1,x_center:.28125,y_center:.15625},{w:1,h:1,x_center:.34375,y_center:.15625},{w:1,h:1,x_center:.34375,y_center:.15625},{w:1,h:1,x_center:.40625,y_center:.15625},{w:1,h:1,x_center:.40625,y_center:.15625},{w:1,h:1,x_center:.46875,y_center:.15625},{w:1,h:1,x_center:.46875,y_center:.15625},{w:1,h:1,x_center:.53125,y_center:.15625},{w:1,h:1,x_center:.53125,y_center:.15625},{w:1,h:1,x_center:.59375,y_center:.15625},{w:1,h:1,x_center:.59375,y_center:.15625},{w:1,h:1,x_center:.65625,y_center:.15625},{w:1,h:1,x_center:.65625,y_center:.15625},{w:1,h:1,x_center:.71875,y_center:.15625},{w:1,h:1,x_center:.71875,y_center:.15625},{w:1,h:1,x_center:.78125,y_center:.15625},{w:1,h:1,x_center:.78125,y_center:.15625},{w:1,h:1,x_center:.84375,y_center:.15625},{w:1,h:1,x_center:.84375,y_center:.15625},{w:1,h:1,x_center:.90625,y_center:.15625},{w:1,h:1,x_center:.90625,y_center:.15625},{w:1,h:1,x_center:.96875,y_center:.15625},{w:1,h:1,x_center:.96875,y_center:.15625},{w:1,h:1,x_center:.03125,y_center:.21875},{w:1,h:1,x_center:.03125,y_center:.21875},{w:1,h:1,x_center:.09375,y_center:.21875},{w:1,h:1,x_center:.09375,y_center:.21875},{w:1,h:1,x_center:.15625,y_center:.21875},{w:1,h:1,x_center:.15625,y_center:.21875},{w:1,h:1,x_center:.21875,y_center:.21875},{w:1,h:1,x_center:.21875,y_center:.21875},{w:1,h:1,x_center:.28125,y_center:.21875},{w:1,h:1,x_center:.28125,y_center:.21875},{w:1,h:1,x_center:.34375,y_center:.21875},{w:1,h:1,x_center:.34375,y_center:.21875},{w:1,h:1,x_center:.40625,y_center:.21875},{w:1,h:1,x_center:.40625,y_center:.21875},{w:1,h:1,x_center:.46875,y_center:.21875},{w:1,h:1,x_center:.46875,y_center:.21875},{w:1,h:1,x_center:.53125,y_center:.21875},{w:1,h:1,x_center:.53125,y_center:.21875},{w:1,h:1,x_center:.59375,y_center:.21875},{w:1,h:1,x_center:.59375,y_center:.21875},{w:1,h:1,x_center:.65625,y_center:.21875},{w:1,h:1,x_center:.65625,y_center:.21875},{w:1,h:1,x_center:.71875,y_center:.21875},{w:1,h:1,x_center:.71875,y_center:.21875},{w:1,h:1,x_center:.78125,y_center:.21875},{w:1,h:1,x_center:.78125,y_center:.21875},{w:1,h:1,x_center:.84375,y_center:.21875},{w:1,h:1,x_center:.84375,y_center:.21875},{w:1,h:1,x_center:.90625,y_center:.21875},{w:1,h:1,x_center:.90625,y_center:.21875},{w:1,h:1,x_center:.96875,y_center:.21875},{w:1,h:1,x_center:.96875,y_center:.21875},{w:1,h:1,x_center:.03125,y_center:.28125},{w:1,h:1,x_center:.03125,y_center:.28125},{w:1,h:1,x_center:.09375,y_center:.28125},{w:1,h:1,x_center:.09375,y_center:.28125},{w:1,h:1,x_center:.15625,y_center:.28125},{w:1,h:1,x_center:.15625,y_center:.28125},{w:1,h:1,x_center:.21875,y_center:.28125},{w:1,h:1,x_center:.21875,y_center:.28125},{w:1,h:1,x_center:.28125,y_center:.28125},{w:1,h:1,x_center:.28125,y_center:.28125},{w:1,h:1,x_center:.34375,y_center:.28125},{w:1,h:1,x_center:.34375,y_center:.28125},{w:1,h:1,x_center:.40625,y_center:.28125},{w:1,h:1,x_center:.40625,y_center:.28125},{w:1,h:1,x_center:.46875,y_center:.28125},{w:1,h:1,x_center:.46875,y_center:.28125},{w:1,h:1,x_center:.53125,y_center:.28125},{w:1,h:1,x_center:.53125,y_center:.28125},{w:1,h:1,x_center:.59375,y_center:.28125},{w:1,h:1,x_center:.59375,y_center:.28125},{w:1,h:1,x_center:.65625,y_center:.28125},{w:1,h:1,x_center:.65625,y_center:.28125},{w:1,h:1,x_center:.71875,y_center:.28125},{w:1,h:1,x_center:.71875,y_center:.28125},{w:1,h:1,x_center:.78125,y_center:.28125},{w:1,h:1,x_center:.78125,y_center:.28125},{w:1,h:1,x_center:.84375,y_center:.28125},{w:1,h:1,x_center:.84375,y_center:.28125},{w:1,h:1,x_center:.90625,y_center:.28125},{w:1,h:1,x_center:.90625,y_center:.28125},{w:1,h:1,x_center:.96875,y_center:.28125},{w:1,h:1,x_center:.96875,y_center:.28125},{w:1,h:1,x_center:.03125,y_center:.34375},{w:1,h:1,x_center:.03125,y_center:.34375},{w:1,h:1,x_center:.09375,y_center:.34375},{w:1,h:1,x_center:.09375,y_center:.34375},{w:1,h:1,x_center:.15625,y_center:.34375},{w:1,h:1,x_center:.15625,y_center:.34375},{w:1,h:1,x_center:.21875,y_center:.34375},{w:1,h:1,x_center:.21875,y_center:.34375},{w:1,h:1,x_center:.28125,y_center:.34375},{w:1,h:1,x_center:.28125,y_center:.34375},{w:1,h:1,x_center:.34375,y_center:.34375},{w:1,h:1,x_center:.34375,y_center:.34375},{w:1,h:1,x_center:.40625,y_center:.34375},{w:1,h:1,x_center:.40625,y_center:.34375},{w:1,h:1,x_center:.46875,y_center:.34375},{w:1,h:1,x_center:.46875,y_center:.34375},{w:1,h:1,x_center:.53125,y_center:.34375},{w:1,h:1,x_center:.53125,y_center:.34375},{w:1,h:1,x_center:.59375,y_center:.34375},{w:1,h:1,x_center:.59375,y_center:.34375},{w:1,h:1,x_center:.65625,y_center:.34375},{w:1,h:1,x_center:.65625,y_center:.34375},{w:1,h:1,x_center:.71875,y_center:.34375},{w:1,h:1,x_center:.71875,y_center:.34375},{w:1,h:1,x_center:.78125,y_center:.34375},{w:1,h:1,x_center:.78125,y_center:.34375},{w:1,h:1,x_center:.84375,y_center:.34375},{w:1,h:1,x_center:.84375,y_center:.34375},{w:1,h:1,x_center:.90625,y_center:.34375},{w:1,h:1,x_center:.90625,y_center:.34375},{w:1,h:1,x_center:.96875,y_center:.34375},{w:1,h:1,x_center:.96875,y_center:.34375},{w:1,h:1,x_center:.03125,y_center:.40625},{w:1,h:1,x_center:.03125,y_center:.40625},{w:1,h:1,x_center:.09375,y_center:.40625},{w:1,h:1,x_center:.09375,y_center:.40625},{w:1,h:1,x_center:.15625,y_center:.40625},{w:1,h:1,x_center:.15625,y_center:.40625},{w:1,h:1,x_center:.21875,y_center:.40625},{w:1,h:1,x_center:.21875,y_center:.40625},{w:1,h:1,x_center:.28125,y_center:.40625},{w:1,h:1,x_center:.28125,y_center:.40625},{w:1,h:1,x_center:.34375,y_center:.40625},{w:1,h:1,x_center:.34375,y_center:.40625},{w:1,h:1,x_center:.40625,y_center:.40625},{w:1,h:1,x_center:.40625,y_center:.40625},{w:1,h:1,x_center:.46875,y_center:.40625},{w:1,h:1,x_center:.46875,y_center:.40625},{w:1,h:1,x_center:.53125,y_center:.40625},{w:1,h:1,x_center:.53125,y_center:.40625},{w:1,h:1,x_center:.59375,y_center:.40625},{w:1,h:1,x_center:.59375,y_center:.40625},{w:1,h:1,x_center:.65625,y_center:.40625},{w:1,h:1,x_center:.65625,y_center:.40625},{w:1,h:1,x_center:.71875,y_center:.40625},{w:1,h:1,x_center:.71875,y_center:.40625},{w:1,h:1,x_center:.78125,y_center:.40625},{w:1,h:1,x_center:.78125,y_center:.40625},{w:1,h:1,x_center:.84375,y_center:.40625},{w:1,h:1,x_center:.84375,y_center:.40625},{w:1,h:1,x_center:.90625,y_center:.40625},{w:1,h:1,x_center:.90625,y_center:.40625},{w:1,h:1,x_center:.96875,y_center:.40625},{w:1,h:1,x_center:.96875,y_center:.40625},{w:1,h:1,x_center:.03125,y_center:.46875},{w:1,h:1,x_center:.03125,y_center:.46875},{w:1,h:1,x_center:.09375,y_center:.46875},{w:1,h:1,x_center:.09375,y_center:.46875},{w:1,h:1,x_center:.15625,y_center:.46875},{w:1,h:1,x_center:.15625,y_center:.46875},{w:1,h:1,x_center:.21875,y_center:.46875},{w:1,h:1,x_center:.21875,y_center:.46875},{w:1,h:1,x_center:.28125,y_center:.46875},{w:1,h:1,x_center:.28125,y_center:.46875},{w:1,h:1,x_center:.34375,y_center:.46875},{w:1,h:1,x_center:.34375,y_center:.46875},{w:1,h:1,x_center:.40625,y_center:.46875},{w:1,h:1,x_center:.40625,y_center:.46875},{w:1,h:1,x_center:.46875,y_center:.46875},{w:1,h:1,x_center:.46875,y_center:.46875},{w:1,h:1,x_center:.53125,y_center:.46875},{w:1,h:1,x_center:.53125,y_center:.46875},{w:1,h:1,x_center:.59375,y_center:.46875},{w:1,h:1,x_center:.59375,y_center:.46875},{w:1,h:1,x_center:.65625,y_center:.46875},{w:1,h:1,x_center:.65625,y_center:.46875},{w:1,h:1,x_center:.71875,y_center:.46875},{w:1,h:1,x_center:.71875,y_center:.46875},{w:1,h:1,x_center:.78125,y_center:.46875},{w:1,h:1,x_center:.78125,y_center:.46875},{w:1,h:1,x_center:.84375,y_center:.46875},{w:1,h:1,x_center:.84375,y_center:.46875},{w:1,h:1,x_center:.90625,y_center:.46875},{w:1,h:1,x_center:.90625,y_center:.46875},{w:1,h:1,x_center:.96875,y_center:.46875},{w:1,h:1,x_center:.96875,y_center:.46875},{w:1,h:1,x_center:.03125,y_center:.53125},{w:1,h:1,x_center:.03125,y_center:.53125},{w:1,h:1,x_center:.09375,y_center:.53125},{w:1,h:1,x_center:.09375,y_center:.53125},{w:1,h:1,x_center:.15625,y_center:.53125},{w:1,h:1,x_center:.15625,y_center:.53125},{w:1,h:1,x_center:.21875,y_center:.53125},{w:1,h:1,x_center:.21875,y_center:.53125},{w:1,h:1,x_center:.28125,y_center:.53125},{w:1,h:1,x_center:.28125,y_center:.53125},{w:1,h:1,x_center:.34375,y_center:.53125},{w:1,h:1,x_center:.34375,y_center:.53125},{w:1,h:1,x_center:.40625,y_center:.53125},{w:1,h:1,x_center:.40625,y_center:.53125},{w:1,h:1,x_center:.46875,y_center:.53125},{w:1,h:1,x_center:.46875,y_center:.53125},{w:1,h:1,x_center:.53125,y_center:.53125},{w:1,h:1,x_center:.53125,y_center:.53125},{w:1,h:1,x_center:.59375,y_center:.53125},{w:1,h:1,x_center:.59375,y_center:.53125},{w:1,h:1,x_center:.65625,y_center:.53125},{w:1,h:1,x_center:.65625,y_center:.53125},{w:1,h:1,x_center:.71875,y_center:.53125},{w:1,h:1,x_center:.71875,y_center:.53125},{w:1,h:1,x_center:.78125,y_center:.53125},{w:1,h:1,x_center:.78125,y_center:.53125},{w:1,h:1,x_center:.84375,y_center:.53125},{w:1,h:1,x_center:.84375,y_center:.53125},{w:1,h:1,x_center:.90625,y_center:.53125},{w:1,h:1,x_center:.90625,y_center:.53125},{w:1,h:1,x_center:.96875,y_center:.53125},{w:1,h:1,x_center:.96875,y_center:.53125},{w:1,h:1,x_center:.03125,y_center:.59375},{w:1,h:1,x_center:.03125,y_center:.59375},{w:1,h:1,x_center:.09375,y_center:.59375},{w:1,h:1,x_center:.09375,y_center:.59375},{w:1,h:1,x_center:.15625,y_center:.59375},{w:1,h:1,x_center:.15625,y_center:.59375},{w:1,h:1,x_center:.21875,y_center:.59375},{w:1,h:1,x_center:.21875,y_center:.59375},{w:1,h:1,x_center:.28125,y_center:.59375},{w:1,h:1,x_center:.28125,y_center:.59375},{w:1,h:1,x_center:.34375,y_center:.59375},{w:1,h:1,x_center:.34375,y_center:.59375},{w:1,h:1,x_center:.40625,y_center:.59375},{w:1,h:1,x_center:.40625,y_center:.59375},{w:1,h:1,x_center:.46875,y_center:.59375},{w:1,h:1,x_center:.46875,y_center:.59375},{w:1,h:1,x_center:.53125,y_center:.59375},{w:1,h:1,x_center:.53125,y_center:.59375},{w:1,h:1,x_center:.59375,y_center:.59375},{w:1,h:1,x_center:.59375,y_center:.59375},{w:1,h:1,x_center:.65625,y_center:.59375},{w:1,h:1,x_center:.65625,y_center:.59375},{w:1,h:1,x_center:.71875,y_center:.59375},{w:1,h:1,x_center:.71875,y_center:.59375},{w:1,h:1,x_center:.78125,y_center:.59375},{w:1,h:1,x_center:.78125,y_center:.59375},{w:1,h:1,x_center:.84375,y_center:.59375},{w:1,h:1,x_center:.84375,y_center:.59375},{w:1,h:1,x_center:.90625,y_center:.59375},{w:1,h:1,x_center:.90625,y_center:.59375},{w:1,h:1,x_center:.96875,y_center:.59375},{w:1,h:1,x_center:.96875,y_center:.59375},{w:1,h:1,x_center:.03125,y_center:.65625},{w:1,h:1,x_center:.03125,y_center:.65625},{w:1,h:1,x_center:.09375,y_center:.65625},{w:1,h:1,x_center:.09375,y_center:.65625},{w:1,h:1,x_center:.15625,y_center:.65625},{w:1,h:1,x_center:.15625,y_center:.65625},{w:1,h:1,x_center:.21875,y_center:.65625},{w:1,h:1,x_center:.21875,y_center:.65625},{w:1,h:1,x_center:.28125,y_center:.65625},{w:1,h:1,x_center:.28125,y_center:.65625},{w:1,h:1,x_center:.34375,y_center:.65625},{w:1,h:1,x_center:.34375,y_center:.65625},{w:1,h:1,x_center:.40625,y_center:.65625},{w:1,h:1,x_center:.40625,y_center:.65625},{w:1,h:1,x_center:.46875,y_center:.65625},{w:1,h:1,x_center:.46875,y_center:.65625},{w:1,h:1,x_center:.53125,y_center:.65625},{w:1,h:1,x_center:.53125,y_center:.65625},{w:1,h:1,x_center:.59375,y_center:.65625},{w:1,h:1,x_center:.59375,y_center:.65625},{w:1,h:1,x_center:.65625,y_center:.65625},{w:1,h:1,x_center:.65625,y_center:.65625},{w:1,h:1,x_center:.71875,y_center:.65625},{w:1,h:1,x_center:.71875,y_center:.65625},{w:1,h:1,x_center:.78125,y_center:.65625},{w:1,h:1,x_center:.78125,y_center:.65625},{w:1,h:1,x_center:.84375,y_center:.65625},{w:1,h:1,x_center:.84375,y_center:.65625},{w:1,h:1,x_center:.90625,y_center:.65625},{w:1,h:1,x_center:.90625,y_center:.65625},{w:1,h:1,x_center:.96875,y_center:.65625},{w:1,h:1,x_center:.96875,y_center:.65625},{w:1,h:1,x_center:.03125,y_center:.71875},{w:1,h:1,x_center:.03125,y_center:.71875},{w:1,h:1,x_center:.09375,y_center:.71875},{w:1,h:1,x_center:.09375,y_center:.71875},{w:1,h:1,x_center:.15625,y_center:.71875},{w:1,h:1,x_center:.15625,y_center:.71875},{w:1,h:1,x_center:.21875,y_center:.71875},{w:1,h:1,x_center:.21875,y_center:.71875},{w:1,h:1,x_center:.28125,y_center:.71875},{w:1,h:1,x_center:.28125,y_center:.71875},{w:1,h:1,x_center:.34375,y_center:.71875},{w:1,h:1,x_center:.34375,y_center:.71875},{w:1,h:1,x_center:.40625,y_center:.71875},{w:1,h:1,x_center:.40625,y_center:.71875},{w:1,h:1,x_center:.46875,y_center:.71875},{w:1,h:1,x_center:.46875,y_center:.71875},{w:1,h:1,x_center:.53125,y_center:.71875},{w:1,h:1,x_center:.53125,y_center:.71875},{w:1,h:1,x_center:.59375,y_center:.71875},{w:1,h:1,x_center:.59375,y_center:.71875},{w:1,h:1,x_center:.65625,y_center:.71875},{w:1,h:1,x_center:.65625,y_center:.71875},{w:1,h:1,x_center:.71875,y_center:.71875},{w:1,h:1,x_center:.71875,y_center:.71875},{w:1,h:1,x_center:.78125,y_center:.71875},{w:1,h:1,x_center:.78125,y_center:.71875},{w:1,h:1,x_center:.84375,y_center:.71875},{w:1,h:1,x_center:.84375,y_center:.71875},{w:1,h:1,x_center:.90625,y_center:.71875},{w:1,h:1,x_center:.90625,y_center:.71875},{w:1,h:1,x_center:.96875,y_center:.71875},{w:1,h:1,x_center:.96875,y_center:.71875},{w:1,h:1,x_center:.03125,y_center:.78125},{w:1,h:1,x_center:.03125,y_center:.78125},{w:1,h:1,x_center:.09375,y_center:.78125},{w:1,h:1,x_center:.09375,y_center:.78125},{w:1,h:1,x_center:.15625,y_center:.78125},{w:1,h:1,x_center:.15625,y_center:.78125},{w:1,h:1,x_center:.21875,y_center:.78125},{w:1,h:1,x_center:.21875,y_center:.78125},{w:1,h:1,x_center:.28125,y_center:.78125},{w:1,h:1,x_center:.28125,y_center:.78125},{w:1,h:1,x_center:.34375,y_center:.78125},{w:1,h:1,x_center:.34375,y_center:.78125},{w:1,h:1,x_center:.40625,y_center:.78125},{w:1,h:1,x_center:.40625,y_center:.78125},{w:1,h:1,x_center:.46875,y_center:.78125},{w:1,h:1,x_center:.46875,y_center:.78125},{w:1,h:1,x_center:.53125,y_center:.78125},{w:1,h:1,x_center:.53125,y_center:.78125},{w:1,h:1,x_center:.59375,y_center:.78125},{w:1,h:1,x_center:.59375,y_center:.78125},{w:1,h:1,x_center:.65625,y_center:.78125},{w:1,h:1,x_center:.65625,y_center:.78125},{w:1,h:1,x_center:.71875,y_center:.78125},{w:1,h:1,x_center:.71875,y_center:.78125},{w:1,h:1,x_center:.78125,y_center:.78125},{w:1,h:1,x_center:.78125,y_center:.78125},{w:1,h:1,x_center:.84375,y_center:.78125},{w:1,h:1,x_center:.84375,y_center:.78125},{w:1,h:1,x_center:.90625,y_center:.78125},{w:1,h:1,x_center:.90625,y_center:.78125},{w:1,h:1,x_center:.96875,y_center:.78125},{w:1,h:1,x_center:.96875,y_center:.78125},{w:1,h:1,x_center:.03125,y_center:.84375},{w:1,h:1,x_center:.03125,y_center:.84375},{w:1,h:1,x_center:.09375,y_center:.84375},{w:1,h:1,x_center:.09375,y_center:.84375},{w:1,h:1,x_center:.15625,y_center:.84375},{w:1,h:1,x_center:.15625,y_center:.84375},{w:1,h:1,x_center:.21875,y_center:.84375},{w:1,h:1,x_center:.21875,y_center:.84375},{w:1,h:1,x_center:.28125,y_center:.84375},{w:1,h:1,x_center:.28125,y_center:.84375},{w:1,h:1,x_center:.34375,y_center:.84375},{w:1,h:1,x_center:.34375,y_center:.84375},{w:1,h:1,x_center:.40625,y_center:.84375},{w:1,h:1,x_center:.40625,y_center:.84375},{w:1,h:1,x_center:.46875,y_center:.84375},{w:1,h:1,x_center:.46875,y_center:.84375},{w:1,h:1,x_center:.53125,y_center:.84375},{w:1,h:1,x_center:.53125,y_center:.84375},{w:1,h:1,x_center:.59375,y_center:.84375},{w:1,h:1,x_center:.59375,y_center:.84375},{w:1,h:1,x_center:.65625,y_center:.84375},{w:1,h:1,x_center:.65625,y_center:.84375},{w:1,h:1,x_center:.71875,y_center:.84375},{w:1,h:1,x_center:.71875,y_center:.84375},{w:1,h:1,x_center:.78125,y_center:.84375},{w:1,h:1,x_center:.78125,y_center:.84375},{w:1,h:1,x_center:.84375,y_center:.84375},{w:1,h:1,x_center:.84375,y_center:.84375},{w:1,h:1,x_center:.90625,y_center:.84375},{w:1,h:1,x_center:.90625,y_center:.84375},{w:1,h:1,x_center:.96875,y_center:.84375},{w:1,h:1,x_center:.96875,y_center:.84375},{w:1,h:1,x_center:.03125,y_center:.90625},{w:1,h:1,x_center:.03125,y_center:.90625},{w:1,h:1,x_center:.09375,y_center:.90625},{w:1,h:1,x_center:.09375,y_center:.90625},{w:1,h:1,x_center:.15625,y_center:.90625},{w:1,h:1,x_center:.15625,y_center:.90625},{w:1,h:1,x_center:.21875,y_center:.90625},{w:1,h:1,x_center:.21875,y_center:.90625},{w:1,h:1,x_center:.28125,y_center:.90625},{w:1,h:1,x_center:.28125,y_center:.90625},{w:1,h:1,x_center:.34375,y_center:.90625},{w:1,h:1,x_center:.34375,y_center:.90625},{w:1,h:1,x_center:.40625,y_center:.90625},{w:1,h:1,x_center:.40625,y_center:.90625},{w:1,h:1,x_center:.46875,y_center:.90625},{w:1,h:1,x_center:.46875,y_center:.90625},{w:1,h:1,x_center:.53125,y_center:.90625},{w:1,h:1,x_center:.53125,y_center:.90625},{w:1,h:1,x_center:.59375,y_center:.90625},{w:1,h:1,x_center:.59375,y_center:.90625},{w:1,h:1,x_center:.65625,y_center:.90625},{w:1,h:1,x_center:.65625,y_center:.90625},{w:1,h:1,x_center:.71875,y_center:.90625},{w:1,h:1,x_center:.71875,y_center:.90625},{w:1,h:1,x_center:.78125,y_center:.90625},{w:1,h:1,x_center:.78125,y_center:.90625},{w:1,h:1,x_center:.84375,y_center:.90625},{w:1,h:1,x_center:.84375,y_center:.90625},{w:1,h:1,x_center:.90625,y_center:.90625},{w:1,h:1,x_center:.90625,y_center:.90625},{w:1,h:1,x_center:.96875,y_center:.90625},{w:1,h:1,x_center:.96875,y_center:.90625},{w:1,h:1,x_center:.03125,y_center:.96875},{w:1,h:1,x_center:.03125,y_center:.96875},{w:1,h:1,x_center:.09375,y_center:.96875},{w:1,h:1,x_center:.09375,y_center:.96875},{w:1,h:1,x_center:.15625,y_center:.96875},{w:1,h:1,x_center:.15625,y_center:.96875},{w:1,h:1,x_center:.21875,y_center:.96875},{w:1,h:1,x_center:.21875,y_center:.96875},{w:1,h:1,x_center:.28125,y_center:.96875},{w:1,h:1,x_center:.28125,y_center:.96875},{w:1,h:1,x_center:.34375,y_center:.96875},{w:1,h:1,x_center:.34375,y_center:.96875},{w:1,h:1,x_center:.40625,y_center:.96875},{w:1,h:1,x_center:.40625,y_center:.96875},{w:1,h:1,x_center:.46875,y_center:.96875},{w:1,h:1,x_center:.46875,y_center:.96875},{w:1,h:1,x_center:.53125,y_center:.96875},{w:1,h:1,x_center:.53125,y_center:.96875},{w:1,h:1,x_center:.59375,y_center:.96875},{w:1,h:1,x_center:.59375,y_center:.96875},{w:1,h:1,x_center:.65625,y_center:.96875},{w:1,h:1,x_center:.65625,y_center:.96875},{w:1,h:1,x_center:.71875,y_center:.96875},{w:1,h:1,x_center:.71875,y_center:.96875},{w:1,h:1,x_center:.78125,y_center:.96875},{w:1,h:1,x_center:.78125,y_center:.96875},{w:1,h:1,x_center:.84375,y_center:.96875},{w:1,h:1,x_center:.84375,y_center:.96875},{w:1,h:1,x_center:.90625,y_center:.96875},{w:1,h:1,x_center:.90625,y_center:.96875},{w:1,h:1,x_center:.96875,y_center:.96875},{w:1,h:1,x_center:.96875,y_center:.96875},{w:1,h:1,x_center:.0625,y_center:.0625},{w:1,h:1,x_center:.0625,y_center:.0625},{w:1,h:1,x_center:.0625,y_center:.0625},{w:1,h:1,x_center:.0625,y_center:.0625},{w:1,h:1,x_center:.0625,y_center:.0625},{w:1,h:1,x_center:.0625,y_center:.0625},{w:1,h:1,x_center:.1875,y_center:.0625},{w:1,h:1,x_center:.1875,y_center:.0625},{w:1,h:1,x_center:.1875,y_center:.0625},{w:1,h:1,x_center:.1875,y_center:.0625},{w:1,h:1,x_center:.1875,y_center:.0625},{w:1,h:1,x_center:.1875,y_center:.0625},{w:1,h:1,x_center:.3125,y_center:.0625},{w:1,h:1,x_center:.3125,y_center:.0625},{w:1,h:1,x_center:.3125,y_center:.0625},{w:1,h:1,x_center:.3125,y_center:.0625},{w:1,h:1,x_center:.3125,y_center:.0625},{w:1,h:1,x_center:.3125,y_center:.0625},{w:1,h:1,x_center:.4375,y_center:.0625},{w:1,h:1,x_center:.4375,y_center:.0625},{w:1,h:1,x_center:.4375,y_center:.0625},{w:1,h:1,x_center:.4375,y_center:.0625},{w:1,h:1,x_center:.4375,y_center:.0625},{w:1,h:1,x_center:.4375,y_center:.0625},{w:1,h:1,x_center:.5625,y_center:.0625},{w:1,h:1,x_center:.5625,y_center:.0625},{w:1,h:1,x_center:.5625,y_center:.0625},{w:1,h:1,x_center:.5625,y_center:.0625},{w:1,h:1,x_center:.5625,y_center:.0625},{w:1,h:1,x_center:.5625,y_center:.0625},{w:1,h:1,x_center:.6875,y_center:.0625},{w:1,h:1,x_center:.6875,y_center:.0625},{w:1,h:1,x_center:.6875,y_center:.0625},{w:1,h:1,x_center:.6875,y_center:.0625},{w:1,h:1,x_center:.6875,y_center:.0625},{w:1,h:1,x_center:.6875,y_center:.0625},{w:1,h:1,x_center:.8125,y_center:.0625},{w:1,h:1,x_center:.8125,y_center:.0625},{w:1,h:1,x_center:.8125,y_center:.0625},{w:1,h:1,x_center:.8125,y_center:.0625},{w:1,h:1,x_center:.8125,y_center:.0625},{w:1,h:1,x_center:.8125,y_center:.0625},{w:1,h:1,x_center:.9375,y_center:.0625},{w:1,h:1,x_center:.9375,y_center:.0625},{w:1,h:1,x_center:.9375,y_center:.0625},{w:1,h:1,x_center:.9375,y_center:.0625},{w:1,h:1,x_center:.9375,y_center:.0625},{w:1,h:1,x_center:.9375,y_center:.0625},{w:1,h:1,x_center:.0625,y_center:.1875},{w:1,h:1,x_center:.0625,y_center:.1875},{w:1,h:1,x_center:.0625,y_center:.1875},{w:1,h:1,x_center:.0625,y_center:.1875},{w:1,h:1,x_center:.0625,y_center:.1875},{w:1,h:1,x_center:.0625,y_center:.1875},{w:1,h:1,x_center:.1875,y_center:.1875},{w:1,h:1,x_center:.1875,y_center:.1875},{w:1,h:1,x_center:.1875,y_center:.1875},{w:1,h:1,x_center:.1875,y_center:.1875},{w:1,h:1,x_center:.1875,y_center:.1875},{w:1,h:1,x_center:.1875,y_center:.1875},{w:1,h:1,x_center:.3125,y_center:.1875},{w:1,h:1,x_center:.3125,y_center:.1875},{w:1,h:1,x_center:.3125,y_center:.1875},{w:1,h:1,x_center:.3125,y_center:.1875},{w:1,h:1,x_center:.3125,y_center:.1875},{w:1,h:1,x_center:.3125,y_center:.1875},{w:1,h:1,x_center:.4375,y_center:.1875},{w:1,h:1,x_center:.4375,y_center:.1875},{w:1,h:1,x_center:.4375,y_center:.1875},{w:1,h:1,x_center:.4375,y_center:.1875},{w:1,h:1,x_center:.4375,y_center:.1875},{w:1,h:1,x_center:.4375,y_center:.1875},{w:1,h:1,x_center:.5625,y_center:.1875},{w:1,h:1,x_center:.5625,y_center:.1875},{w:1,h:1,x_center:.5625,y_center:.1875},{w:1,h:1,x_center:.5625,y_center:.1875},{w:1,h:1,x_center:.5625,y_center:.1875},{w:1,h:1,x_center:.5625,y_center:.1875},{w:1,h:1,x_center:.6875,y_center:.1875},{w:1,h:1,x_center:.6875,y_center:.1875},{w:1,h:1,x_center:.6875,y_center:.1875},{w:1,h:1,x_center:.6875,y_center:.1875},{w:1,h:1,x_center:.6875,y_center:.1875},{w:1,h:1,x_center:.6875,y_center:.1875},{w:1,h:1,x_center:.8125,y_center:.1875},{w:1,h:1,x_center:.8125,y_center:.1875},{w:1,h:1,x_center:.8125,y_center:.1875},{w:1,h:1,x_center:.8125,y_center:.1875},{w:1,h:1,x_center:.8125,y_center:.1875},{w:1,h:1,x_center:.8125,y_center:.1875},{w:1,h:1,x_center:.9375,y_center:.1875},{w:1,h:1,x_center:.9375,y_center:.1875},{w:1,h:1,x_center:.9375,y_center:.1875},{w:1,h:1,x_center:.9375,y_center:.1875},{w:1,h:1,x_center:.9375,y_center:.1875},{w:1,h:1,x_center:.9375,y_center:.1875},{w:1,h:1,x_center:.0625,y_center:.3125},{w:1,h:1,x_center:.0625,y_center:.3125},{w:1,h:1,x_center:.0625,y_center:.3125},{w:1,h:1,x_center:.0625,y_center:.3125},{w:1,h:1,x_center:.0625,y_center:.3125},{w:1,h:1,x_center:.0625,y_center:.3125},{w:1,h:1,x_center:.1875,y_center:.3125},{w:1,h:1,x_center:.1875,y_center:.3125},{w:1,h:1,x_center:.1875,y_center:.3125},{w:1,h:1,x_center:.1875,y_center:.3125},{w:1,h:1,x_center:.1875,y_center:.3125},{w:1,h:1,x_center:.1875,y_center:.3125},{w:1,h:1,x_center:.3125,y_center:.3125},{w:1,h:1,x_center:.3125,y_center:.3125},{w:1,h:1,x_center:.3125,y_center:.3125},{w:1,h:1,x_center:.3125,y_center:.3125},{w:1,h:1,x_center:.3125,y_center:.3125},{w:1,h:1,x_center:.3125,y_center:.3125},{w:1,h:1,x_center:.4375,y_center:.3125},{w:1,h:1,x_center:.4375,y_center:.3125},{w:1,h:1,x_center:.4375,y_center:.3125},{w:1,h:1,x_center:.4375,y_center:.3125},{w:1,h:1,x_center:.4375,y_center:.3125},{w:1,h:1,x_center:.4375,y_center:.3125},{w:1,h:1,x_center:.5625,y_center:.3125},{w:1,h:1,x_center:.5625,y_center:.3125},{w:1,h:1,x_center:.5625,y_center:.3125},{w:1,h:1,x_center:.5625,y_center:.3125},{w:1,h:1,x_center:.5625,y_center:.3125},{w:1,h:1,x_center:.5625,y_center:.3125},{w:1,h:1,x_center:.6875,y_center:.3125},{w:1,h:1,x_center:.6875,y_center:.3125},{w:1,h:1,x_center:.6875,y_center:.3125},{w:1,h:1,x_center:.6875,y_center:.3125},{w:1,h:1,x_center:.6875,y_center:.3125},{w:1,h:1,x_center:.6875,y_center:.3125},{w:1,h:1,x_center:.8125,y_center:.3125},{w:1,h:1,x_center:.8125,y_center:.3125},{w:1,h:1,x_center:.8125,y_center:.3125},{w:1,h:1,x_center:.8125,y_center:.3125},{w:1,h:1,x_center:.8125,y_center:.3125},{w:1,h:1,x_center:.8125,y_center:.3125},{w:1,h:1,x_center:.9375,y_center:.3125},{w:1,h:1,x_center:.9375,y_center:.3125},{w:1,h:1,x_center:.9375,y_center:.3125},{w:1,h:1,x_center:.9375,y_center:.3125},{w:1,h:1,x_center:.9375,y_center:.3125},{w:1,h:1,x_center:.9375,y_center:.3125},{w:1,h:1,x_center:.0625,y_center:.4375},{w:1,h:1,x_center:.0625,y_center:.4375},{w:1,h:1,x_center:.0625,y_center:.4375},{w:1,h:1,x_center:.0625,y_center:.4375},{w:1,h:1,x_center:.0625,y_center:.4375},{w:1,h:1,x_center:.0625,y_center:.4375},{w:1,h:1,x_center:.1875,y_center:.4375},{w:1,h:1,x_center:.1875,y_center:.4375},{w:1,h:1,x_center:.1875,y_center:.4375},{w:1,h:1,x_center:.1875,y_center:.4375},{w:1,h:1,x_center:.1875,y_center:.4375},{w:1,h:1,x_center:.1875,y_center:.4375},{w:1,h:1,x_center:.3125,y_center:.4375},{w:1,h:1,x_center:.3125,y_center:.4375},{w:1,h:1,x_center:.3125,y_center:.4375},{w:1,h:1,x_center:.3125,y_center:.4375},{w:1,h:1,x_center:.3125,y_center:.4375},{w:1,h:1,x_center:.3125,y_center:.4375},{w:1,h:1,x_center:.4375,y_center:.4375},{w:1,h:1,x_center:.4375,y_center:.4375},{w:1,h:1,x_center:.4375,y_center:.4375},{w:1,h:1,x_center:.4375,y_center:.4375},{w:1,h:1,x_center:.4375,y_center:.4375},{w:1,h:1,x_center:.4375,y_center:.4375},{w:1,h:1,x_center:.5625,y_center:.4375},{w:1,h:1,x_center:.5625,y_center:.4375},{w:1,h:1,x_center:.5625,y_center:.4375},{w:1,h:1,x_center:.5625,y_center:.4375},{w:1,h:1,x_center:.5625,y_center:.4375},{w:1,h:1,x_center:.5625,y_center:.4375},{w:1,h:1,x_center:.6875,y_center:.4375},{w:1,h:1,x_center:.6875,y_center:.4375},{w:1,h:1,x_center:.6875,y_center:.4375},{w:1,h:1,x_center:.6875,y_center:.4375},{w:1,h:1,x_center:.6875,y_center:.4375},{w:1,h:1,x_center:.6875,y_center:.4375},{w:1,h:1,x_center:.8125,y_center:.4375},{w:1,h:1,x_center:.8125,y_center:.4375},{w:1,h:1,x_center:.8125,y_center:.4375},{w:1,h:1,x_center:.8125,y_center:.4375},{w:1,h:1,x_center:.8125,y_center:.4375},{w:1,h:1,x_center:.8125,y_center:.4375},{w:1,h:1,x_center:.9375,y_center:.4375},{w:1,h:1,x_center:.9375,y_center:.4375},{w:1,h:1,x_center:.9375,y_center:.4375},{w:1,h:1,x_center:.9375,y_center:.4375},{w:1,h:1,x_center:.9375,y_center:.4375},{w:1,h:1,x_center:.9375,y_center:.4375},{w:1,h:1,x_center:.0625,y_center:.5625},{w:1,h:1,x_center:.0625,y_center:.5625},{w:1,h:1,x_center:.0625,y_center:.5625},{w:1,h:1,x_center:.0625,y_center:.5625},{w:1,h:1,x_center:.0625,y_center:.5625},{w:1,h:1,x_center:.0625,y_center:.5625},{w:1,h:1,x_center:.1875,y_center:.5625},{w:1,h:1,x_center:.1875,y_center:.5625},{w:1,h:1,x_center:.1875,y_center:.5625},{w:1,h:1,x_center:.1875,y_center:.5625},{w:1,h:1,x_center:.1875,y_center:.5625},{w:1,h:1,x_center:.1875,y_center:.5625},{w:1,h:1,x_center:.3125,y_center:.5625},{w:1,h:1,x_center:.3125,y_center:.5625},{w:1,h:1,x_center:.3125,y_center:.5625},{w:1,h:1,x_center:.3125,y_center:.5625},{w:1,h:1,x_center:.3125,y_center:.5625},{w:1,h:1,x_center:.3125,y_center:.5625},{w:1,h:1,x_center:.4375,y_center:.5625},{w:1,h:1,x_center:.4375,y_center:.5625},{w:1,h:1,x_center:.4375,y_center:.5625},{w:1,h:1,x_center:.4375,y_center:.5625},{w:1,h:1,x_center:.4375,y_center:.5625},{w:1,h:1,x_center:.4375,y_center:.5625},{w:1,h:1,x_center:.5625,y_center:.5625},{w:1,h:1,x_center:.5625,y_center:.5625},{w:1,h:1,x_center:.5625,y_center:.5625},{w:1,h:1,x_center:.5625,y_center:.5625},{w:1,h:1,x_center:.5625,y_center:.5625},{w:1,h:1,x_center:.5625,y_center:.5625},{w:1,h:1,x_center:.6875,y_center:.5625},{w:1,h:1,x_center:.6875,y_center:.5625},{w:1,h:1,x_center:.6875,y_center:.5625},{w:1,h:1,x_center:.6875,y_center:.5625},{w:1,h:1,x_center:.6875,y_center:.5625},{w:1,h:1,x_center:.6875,y_center:.5625},{w:1,h:1,x_center:.8125,y_center:.5625},{w:1,h:1,x_center:.8125,y_center:.5625},{w:1,h:1,x_center:.8125,y_center:.5625},{w:1,h:1,x_center:.8125,y_center:.5625},{w:1,h:1,x_center:.8125,y_center:.5625},{w:1,h:1,x_center:.8125,y_center:.5625},{w:1,h:1,x_center:.9375,y_center:.5625},{w:1,h:1,x_center:.9375,y_center:.5625},{w:1,h:1,x_center:.9375,y_center:.5625},{w:1,h:1,x_center:.9375,y_center:.5625},{w:1,h:1,x_center:.9375,y_center:.5625},{w:1,h:1,x_center:.9375,y_center:.5625},{w:1,h:1,x_center:.0625,y_center:.6875},{w:1,h:1,x_center:.0625,y_center:.6875},{w:1,h:1,x_center:.0625,y_center:.6875},{w:1,h:1,x_center:.0625,y_center:.6875},{w:1,h:1,x_center:.0625,y_center:.6875},{w:1,h:1,x_center:.0625,y_center:.6875},{w:1,h:1,x_center:.1875,y_center:.6875},{w:1,h:1,x_center:.1875,y_center:.6875},{w:1,h:1,x_center:.1875,y_center:.6875},{w:1,h:1,x_center:.1875,y_center:.6875},{w:1,h:1,x_center:.1875,y_center:.6875},{w:1,h:1,x_center:.1875,y_center:.6875},{w:1,h:1,x_center:.3125,y_center:.6875},{w:1,h:1,x_center:.3125,y_center:.6875},{w:1,h:1,x_center:.3125,y_center:.6875},{w:1,h:1,x_center:.3125,y_center:.6875},{w:1,h:1,x_center:.3125,y_center:.6875},{w:1,h:1,x_center:.3125,y_center:.6875},{w:1,h:1,x_center:.4375,y_center:.6875},{w:1,h:1,x_center:.4375,y_center:.6875},{w:1,h:1,x_center:.4375,y_center:.6875},{w:1,h:1,x_center:.4375,y_center:.6875},{w:1,h:1,x_center:.4375,y_center:.6875},{w:1,h:1,x_center:.4375,y_center:.6875},{w:1,h:1,x_center:.5625,y_center:.6875},{w:1,h:1,x_center:.5625,y_center:.6875},{w:1,h:1,x_center:.5625,y_center:.6875},{w:1,h:1,x_center:.5625,y_center:.6875},{w:1,h:1,x_center:.5625,y_center:.6875},{w:1,h:1,x_center:.5625,y_center:.6875},{w:1,h:1,x_center:.6875,y_center:.6875},{w:1,h:1,x_center:.6875,y_center:.6875},{w:1,h:1,x_center:.6875,y_center:.6875},{w:1,h:1,x_center:.6875,y_center:.6875},{w:1,h:1,x_center:.6875,y_center:.6875},{w:1,h:1,x_center:.6875,y_center:.6875},{w:1,h:1,x_center:.8125,y_center:.6875},{w:1,h:1,x_center:.8125,y_center:.6875},{w:1,h:1,x_center:.8125,y_center:.6875},{w:1,h:1,x_center:.8125,y_center:.6875},{w:1,h:1,x_center:.8125,y_center:.6875},{w:1,h:1,x_center:.8125,y_center:.6875},{w:1,h:1,x_center:.9375,y_center:.6875},{w:1,h:1,x_center:.9375,y_center:.6875},{w:1,h:1,x_center:.9375,y_center:.6875},{w:1,h:1,x_center:.9375,y_center:.6875},{w:1,h:1,x_center:.9375,y_center:.6875},{w:1,h:1,x_center:.9375,y_center:.6875},{w:1,h:1,x_center:.0625,y_center:.8125},{w:1,h:1,x_center:.0625,y_center:.8125},{w:1,h:1,x_center:.0625,y_center:.8125},{w:1,h:1,x_center:.0625,y_center:.8125},{w:1,h:1,x_center:.0625,y_center:.8125},{w:1,h:1,x_center:.0625,y_center:.8125},{w:1,h:1,x_center:.1875,y_center:.8125},{w:1,h:1,x_center:.1875,y_center:.8125},{w:1,h:1,x_center:.1875,y_center:.8125},{w:1,h:1,x_center:.1875,y_center:.8125},{w:1,h:1,x_center:.1875,y_center:.8125},{w:1,h:1,x_center:.1875,y_center:.8125},{w:1,h:1,x_center:.3125,y_center:.8125},{w:1,h:1,x_center:.3125,y_center:.8125},{w:1,h:1,x_center:.3125,y_center:.8125},{w:1,h:1,x_center:.3125,y_center:.8125},{w:1,h:1,x_center:.3125,y_center:.8125},{w:1,h:1,x_center:.3125,y_center:.8125},{w:1,h:1,x_center:.4375,y_center:.8125},{w:1,h:1,x_center:.4375,y_center:.8125},{w:1,h:1,x_center:.4375,y_center:.8125},{w:1,h:1,x_center:.4375,y_center:.8125},{w:1,h:1,x_center:.4375,y_center:.8125},{w:1,h:1,x_center:.4375,y_center:.8125},{w:1,h:1,x_center:.5625,y_center:.8125},{w:1,h:1,x_center:.5625,y_center:.8125},{w:1,h:1,x_center:.5625,y_center:.8125},{w:1,h:1,x_center:.5625,y_center:.8125},{w:1,h:1,x_center:.5625,y_center:.8125},{w:1,h:1,x_center:.5625,y_center:.8125},{w:1,h:1,x_center:.6875,y_center:.8125},{w:1,h:1,x_center:.6875,y_center:.8125},{w:1,h:1,x_center:.6875,y_center:.8125},{w:1,h:1,x_center:.6875,y_center:.8125},{w:1,h:1,x_center:.6875,y_center:.8125},{w:1,h:1,x_center:.6875,y_center:.8125},{w:1,h:1,x_center:.8125,y_center:.8125},{w:1,h:1,x_center:.8125,y_center:.8125},{w:1,h:1,x_center:.8125,y_center:.8125},{w:1,h:1,x_center:.8125,y_center:.8125},{w:1,h:1,x_center:.8125,y_center:.8125},{w:1,h:1,x_center:.8125,y_center:.8125},{w:1,h:1,x_center:.9375,y_center:.8125},{w:1,h:1,x_center:.9375,y_center:.8125},{w:1,h:1,x_center:.9375,y_center:.8125},{w:1,h:1,x_center:.9375,y_center:.8125},{w:1,h:1,x_center:.9375,y_center:.8125},{w:1,h:1,x_center:.9375,y_center:.8125},{w:1,h:1,x_center:.0625,y_center:.9375},{w:1,h:1,x_center:.0625,y_center:.9375},{w:1,h:1,x_center:.0625,y_center:.9375},{w:1,h:1,x_center:.0625,y_center:.9375},{w:1,h:1,x_center:.0625,y_center:.9375},{w:1,h:1,x_center:.0625,y_center:.9375},{w:1,h:1,x_center:.1875,y_center:.9375},{w:1,h:1,x_center:.1875,y_center:.9375},{w:1,h:1,x_center:.1875,y_center:.9375},{w:1,h:1,x_center:.1875,y_center:.9375},{w:1,h:1,x_center:.1875,y_center:.9375},{w:1,h:1,x_center:.1875,y_center:.9375},{w:1,h:1,x_center:.3125,y_center:.9375},{w:1,h:1,x_center:.3125,y_center:.9375},{w:1,h:1,x_center:.3125,y_center:.9375},{w:1,h:1,x_center:.3125,y_center:.9375},{w:1,h:1,x_center:.3125,y_center:.9375},{w:1,h:1,x_center:.3125,y_center:.9375},{w:1,h:1,x_center:.4375,y_center:.9375},{w:1,h:1,x_center:.4375,y_center:.9375},{w:1,h:1,x_center:.4375,y_center:.9375},{w:1,h:1,x_center:.4375,y_center:.9375},{w:1,h:1,x_center:.4375,y_center:.9375},{w:1,h:1,x_center:.4375,y_center:.9375},{w:1,h:1,x_center:.5625,y_center:.9375},{w:1,h:1,x_center:.5625,y_center:.9375},{w:1,h:1,x_center:.5625,y_center:.9375},{w:1,h:1,x_center:.5625,y_center:.9375},{w:1,h:1,x_center:.5625,y_center:.9375},{w:1,h:1,x_center:.5625,y_center:.9375},{w:1,h:1,x_center:.6875,y_center:.9375},{w:1,h:1,x_center:.6875,y_center:.9375},{w:1,h:1,x_center:.6875,y_center:.9375},{w:1,h:1,x_center:.6875,y_center:.9375},{w:1,h:1,x_center:.6875,y_center:.9375},{w:1,h:1,x_center:.6875,y_center:.9375},{w:1,h:1,x_center:.8125,y_center:.9375},{w:1,h:1,x_center:.8125,y_center:.9375},{w:1,h:1,x_center:.8125,y_center:.9375},{w:1,h:1,x_center:.8125,y_center:.9375},{w:1,h:1,x_center:.8125,y_center:.9375},{w:1,h:1,x_center:.8125,y_center:.9375},{w:1,h:1,x_center:.9375,y_center:.9375},{w:1,h:1,x_center:.9375,y_center:.9375},{w:1,h:1,x_center:.9375,y_center:.9375},{w:1,h:1,x_center:.9375,y_center:.9375},{w:1,h:1,x_center:.9375,y_center:.9375},{w:1,h:1,x_center:.9375,y_center:.9375}];var _2={thumb:[1,2,3,4],indexFinger:[5,6,7,8],middleFinger:[9,10,11,12],ringFinger:[13,14,15,16],pinky:[17,18,19,20],palmBase:[0]},v2=class{constructor(t){this.handPipeline=t}static getAnnotations(){return _2}async estimateHands(t,n){let r=await this.handPipeline.estimateHands(t,n);if(!r)return[];let a=[];for(let s of r){let i={};if(s.landmarks)for(let l of Object.keys(_2))i[l]=_2[l].map(u=>s.landmarks[u]);let o=s.box?[Math.max(0,s.box.topLeft[0]),Math.max(0,s.box.topLeft[1]),Math.min(t.shape[2],s.box.bottomRight[0])-s.box.topLeft[0],Math.min(t.shape[1],s.box.bottomRight[1])-s.box.topLeft[1]]:0;a.push({confidence:s.confidence,box:o,landmarks:s.landmarks,annotations:i})}return a}};async function k2(e){let[t,n]=await Promise.all([e.hand.enabled?Ot(e.hand.detector.modelPath,{fromTFHub:e.hand.detector.modelPath.includes("tfhub.dev")}):null,e.hand.landmarks?Ot(e.hand.skeleton.modelPath,{fromTFHub:e.hand.skeleton.modelPath.includes("tfhub.dev")}):null]),r=new y2(t,t==null?void 0:t.inputs[0].shape[2],c4),a=new w2(r,n,n==null?void 0:n.inputs[0].shape[2]),s=new v2(a);return e.hand.enabled&&e.debug&&Fe(`load model: ${e.hand.detector.modelPath.match(/\/(.*)\./)[1]}`),e.hand.landmarks&&e.debug&&Fe(`load model: ${e.hand.skeleton.modelPath.match(/\/(.*)\./)[1]}`),s}var I2={};xr(I2,{load:()=>N2,predict:()=>S2});var h4=["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"],d4=["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 yr;async function N2(e){return yr||(yr=await Ot(e.body.modelPath),yr.width=parseInt(yr.signature.inputs["input_1:0"].tensorShape.dim[2].size),yr.height=parseInt(yr.signature.inputs["input_1:0"].tensorShape.dim[1].size),e.debug&&Fe(`load model: ${e.body.modelPath.match(/\/(.*)\./)[1]}`)),yr}async function S2(e,t){if(!yr||!t.body.enabled)return null;let n={width:e.shape[2],height:e.shape[1]},r=tt.resizeBilinear(e,[yr.width,yr.height],!1),a=be(r,[255]);r.dispose();let s;if(t.profile){let u=await kr(()=>yr.predict(a));s=u.result.find(c=>c.size===195||c.size===155).dataSync(),u.result.forEach(c=>c.dispose()),Qr("blazepose",u)}else{let u=await yr.predict(a);s=u.find(c=>c.size===195||c.size===155).dataSync(),u.forEach(c=>c.dispose())}a.dispose();let i=[],o=s.length===195?h4:d4,l=5;for(let u=0;u<s.length/l;u++)i.push({id:u,part:o[u],position:{x:Math.trunc(n.width*s[l*u+0]/255),y:Math.trunc(n.height*s[l*u+1]/255),z:Math.trunc(s[l*u+2])+0},score:(100-Math.trunc(100/(1+Math.exp(s[l*u+3]))))/100,presence:(100-Math.trunc(100/(1+Math.exp(s[l*u+4]))))/100});return[{keypoints:i}]}var p4=e=>{if(!e)return[];let t=[];for(let n=0;n<e.length;n++){let r=e[n].keypoints.find(l=>l.part==="leftWrist"),a=e[n].keypoints.find(l=>l.part==="rightWrist"),s=e[n].keypoints.find(l=>l.part==="nose");s&&r&&a&&r.position.y<s.position.y&&a.position.y<s.position.y?t.push({body:n,gesture:"i give up"}):s&&r&&r.position.y<s.position.y?t.push({body:n,gesture:"raise left hand"}):s&&a&&a.position.y<s.position.y&&t.push({body:n,gesture:"raise right hand"});let i=e[n].keypoints.find(l=>l.part==="leftShoulder"),o=e[n].keypoints.find(l=>l.part==="rightShoulder");i&&o&&t.push({body:n,gesture:`leaning ${i.position.y>o.position.y?"left":"right"}`})}return t},f4=e=>{if(!e)return[];let t=[];for(let n=0;n<e.length;n++)if(e[n].mesh&&e[n].mesh.length>0){let r=e[n].mesh[33][2]-e[n].mesh[263][2];Math.abs(r)<10?t.push({face:n,gesture:"facing camera"}):t.push({face:n,gesture:`facing ${r<0?"right":"left"}`}),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 i=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]));i>10&&t.push({face:n,gesture:`mouth ${Math.trunc(i)}% open`});let o=e[n].mesh[152][2];Math.abs(o)>10&&t.push({face:n,gesture:`head ${o<0?"up":"down"}`})}return t},m4=e=>{if(!e)return[];let t=[];for(let n=0;n<e.length;n++){if(!e[n].annotations||!e[n].annotations.leftEyeIris||!e[n].annotations.rightEyeIris)continue;let r=e[n].annotations.leftEyeIris[3][0]-e[n].annotations.leftEyeIris[1][0],a=e[n].annotations.leftEyeIris[4][1]-e[n].annotations.leftEyeIris[2][1],s=Math.abs(r*a),i=e[n].annotations.rightEyeIris[3][0]-e[n].annotations.rightEyeIris[1][0],o=e[n].annotations.rightEyeIris[4][1]-e[n].annotations.rightEyeIris[2][1],l=Math.abs(i*o);Math.abs(s-l)/Math.max(s,l)<.25&&t.push({iris:n,gesture:"looking at camera"})}return t},A4=e=>{if(!e)return[];let t=[];for(let n=0;n<e.length;n++){let r=[];for(let[a,s]of Object.entries(e[n].annotations))a!=="palmBase"&&r.push({name:a.toLowerCase(),position:s[0]});if(r&&r.length>0){let a=r.reduce((i,o)=>i.position[2]<o.position[2]?i:o),s=r.reduce((i,o)=>i.position[1]<o.position[1]?i:o);t.push({hand:n,gesture:`${a.name} forward ${s.name} up`})}}return t};function vse(e,t,n){let r=function(o,l,u){let c=new RegExp("\\b"+l+" \\w+ (\\w+)","ig");o.replace(c,(h,d)=>(u[d]=0,h))},a=function(o,l){let u=e.createShader(l);if(e.shaderSource(u,o),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 s=a(t,e.VERTEX_SHADER),i=a(n,e.FRAGMENT_SHADER);if(this.id=e.createProgram(),e.attachShader(this.id,s),e.attachShader(this.id,i),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),r(t,"attribute",this.attribute);for(let o in this.attribute)this.attribute[o]=e.getAttribLocation(this.id,o);r(t,"uniform",this.uniform),r(n,"uniform",this.uniform);for(let o in this.uniform)this.uniform[o]=e.getUniformLocation(this.id,o)}function y4(e){e||(e={});let t=0,n=null,r=!1,a=-1,s=[null,null],i=[],o=-1,l=-1,u=null,c=null,h={},d=e.canvas||document.createElement("canvas"),p={},f={INTERMEDIATE:1},m=d.getContext("webgl");if(!m)throw new Error("Filter: getContext() failed");this.addFilter=function(w){let x=Array.prototype.slice.call(arguments,1),N=h[w];i.push({func:N,args:x})},this.reset=function(){i=[]};let A=function(w,x){if(!(w===o&&x===l)){if(d.width=w,o=w,d.height=x,l=x,!u){let N=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,N,m.STATIC_DRAW),m.pixelStorei(m.UNPACK_PREMULTIPLY_ALPHA_WEBGL,!0)}m.viewport(0,0,o,l),s=[null,null]}},y=function(w,x){let N=m.createFramebuffer();m.bindFramebuffer(m.FRAMEBUFFER,N);let S=m.createRenderbuffer();m.bindRenderbuffer(m.RENDERBUFFER,S);let T=m.createTexture();return m.bindTexture(m.TEXTURE_2D,T),m.texImage2D(m.TEXTURE_2D,0,m.RGBA,w,x,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,T,0),m.bindTexture(m.TEXTURE_2D,null),m.bindFramebuffer(m.FRAMEBUFFER,null),{fbo:N,texture:T}},g=function(w){return s[w]=s[w]||y(o,l),s[w]},b=function(w=null){var T,M;let x=null,N=null,S=!1;t===0?x=n:x=(T=g(a))==null?void 0:T.texture,t++,r&&!(w&f.INTERMEDIATE)?(N=null,S=t%2==0):(a=(a+1)%2,N=(M=g(a))==null?void 0:M.fbo),m.bindTexture(m.TEXTURE_2D,x),m.bindFramebuffer(m.FRAMEBUFFER,N),m.uniform1f(c.uniform.flipY,S?-1:1),m.drawArrays(m.TRIANGLES,0,6)};this.apply=function(w){if(A(w.width,w.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,w),i.length===0)return b(),d;for(let x=0;x<i.length;x++){r=x===i.length-1;let N=i[x];N.func.apply(this,N.args||[])}return d};let _=function(w){if(p[w])return c=p[w],m.useProgram(c.id),c;let x={};x.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(`
|
|
`),x.FRAGMENT_IDENTITY=["precision highp float;","varying vec2 vUv;","uniform sampler2D texture;","void main(void) {","gl_FragColor = texture2D(texture, vUv);","}"].join(`
|
|
`),c=new vse(m,x.VERTEX_IDENTITY,w);let N=Float32Array.BYTES_PER_ELEMENT,S=4*N;return m.enableVertexAttribArray(c.attribute.pos),m.vertexAttribPointer(c.attribute.pos,2,m.FLOAT,!1,S,0*N),m.enableVertexAttribArray(c.attribute.uv),m.vertexAttribPointer(c.attribute.uv,2,m.FLOAT,!1,S,2*N),p[w]=c,c};h.colorMatrix=function(w){let x=new Float32Array(w);x[4]/=255,x[9]/=255,x[14]/=255,x[19]/=255;let N=x[18]===1&&x[3]===0&&x[8]===0&&x[13]===0&&x[15]===0&&x[16]===0&&x[17]===0&&x[19]===0?h.colorMatrix.SHADER.WITHOUT_ALPHA:h.colorMatrix.SHADER.WITH_ALPHA,S=_(N);m.uniform1fv(S.uniform.m,x),b()},h.colorMatrix.SHADER={},h.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(`
|
|
`),h.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(`
|
|
`),h.brightness=function(w){let x=(w||0)+1;h.colorMatrix([x,0,0,0,0,0,x,0,0,0,0,0,x,0,0,0,0,0,1,0])},h.saturation=function(w){let x=(w||0)*2/3+1,N=(x-1)*-.5;h.colorMatrix([x,N,N,0,0,N,x,N,0,0,N,N,x,0,0,0,0,0,1,0])},h.desaturate=function(){h.saturation(-1)},h.contrast=function(w){let x=(w||0)+1,N=-128*(x-1);h.colorMatrix([x,0,0,0,N,0,x,0,0,N,0,0,x,0,N,0,0,0,1,0])},h.negative=function(){h.contrast(-2)},h.hue=function(w){w=(w||0)/180*Math.PI;let x=Math.cos(w),N=Math.sin(w),S=.213,T=.715,M=.072;h.colorMatrix([S+x*(1-S)+N*-S,T+x*-T+N*-T,M+x*-M+N*(1-M),0,0,S+x*-S+N*.143,T+x*(1-T)+N*.14,M+x*-M+N*-.283,0,0,S+x*-S+N*-(1-S),T+x*-T+N*T,M+x*(1-M)+N*M,0,0,0,0,0,1,0])},h.desaturateLuminance=function(){h.colorMatrix([.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,0,0,0,1,0])},h.sepia=function(){h.colorMatrix([.393,.7689999,.18899999,0,0,.349,.6859999,.16799999,0,0,.272,.5339999,.13099999,0,0,0,0,0,1,0])},h.brownie=function(){h.colorMatrix([.5997023498159715,.34553243048391263,-.2708298674538042,0,47.43192855600873,-.037703249837783157,.8609577587992641,.15059552388459913,0,-36.96841498319127,.24113635128153335,-.07441037908422492,.44972182064877153,0,-7.562075277591283,0,0,0,1,0])},h.vintagePinhole=function(){h.colorMatrix([.6279345635605994,.3202183420819367,-.03965408211312453,0,9.651285835294123,.02578397704808868,.6441188644374771,.03259127616149294,0,7.462829176470591,.0466055556782719,-.0851232987247891,.5241648018700465,0,5.159190588235296,0,0,0,1,0])},h.kodachrome=function(){h.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])},h.technicolor=function(){h.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])},h.polaroid=function(){h.colorMatrix([1.438,-.062,-.062,0,0,-.122,1.378,-.122,0,0,-.016,-.016,1.483,0,0,0,0,0,1,0])},h.shiftToBGR=function(){h.colorMatrix([0,0,1,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1,0])},h.convolution=function(w){let x=new Float32Array(w),N=1/o,S=1/l,T=_(h.convolution.SHADER);m.uniform1fv(T.uniform.m,x),m.uniform2f(T.uniform.px,N,S),b()},h.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(`
|
|
`),h.detectEdges=function(){h.convolution.call(this,[0,1,0,1,-4,1,0,1,0])},h.sobelX=function(){h.convolution.call(this,[-1,0,1,-2,0,2,-1,0,1])},h.sobelY=function(){h.convolution.call(this,[-1,-2,-1,0,0,0,1,2,1])},h.sharpen=function(w){let x=w||1;h.convolution.call(this,[0,-1*x,0,-1*x,1+4*x,-1*x,0,-1*x,0])},h.emboss=function(w){let x=w||1;h.convolution.call(this,[-2*x,-1*x,0,-1*x,1,1*x,0,1*x,2*x])},h.blur=function(w){let x=w/7/o,N=w/7/l,S=_(h.blur.SHADER);m.uniform2f(S.uniform.px,0,N),b(f.INTERMEDIATE),m.uniform2f(S.uniform.px,x,0),b()},h.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(`
|
|
`),h.pixelate=function(w){let x=w/o,N=w/l,S=_(h.pixelate.SHADER);m.uniform2f(S.uniform.size,x,N),b()},h.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 O0=2048,Mt=null,ln=null,zt=null;function T2(e,t){let n;if(e instanceof Ge)n=zr(e);else{let a=e.naturalWidth||e.videoWidth||e.width||e.shape&&e.shape[1]>0,s=e.naturalHeight||e.videoHeight||e.height||e.shape&&e.shape[2]>0,i=a,o=s;if(i>O0&&(i=O0,o=i*s/a),o>O0&&(o=O0,i=o*a/s),t.filter.width>0?i=t.filter.width:t.filter.height>0&&(i=a*(t.filter.height/s)),t.filter.height>0?o=t.filter.height:t.filter.width>0&&(o=s*(t.filter.width/a)),!i||!o)return Fe("Human: invalid input",e),{tensor:null,canvas:null};(!Mt||Mt.width!==i||Mt.height!==o)&&(Mt=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(i,o):document.createElement("canvas"),Mt.width!==i&&(Mt.width=i),Mt.height!==o&&(Mt.height=o));let l=Mt.getContext("2d");if(e instanceof ImageData?l.putImageData(e,0,0):l.drawImage(e,0,0,a,s,0,0,Mt.width,Mt.height),t.filter.enabled){if((!zt||!ln||Mt.width!==ln.width||Mt.height!==ln.height)&&(ln=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(Mt.width,Mt.height):document.createElement("canvas"),ln.width!==Mt.width&&(ln.width=Mt.width),ln.height!==Mt.height&&(ln.height=Mt.height),zt=wr.flags.IS_BROWSER?new y4({canvas:ln}):null),!zt)return{tensor:null,canvas:Mt};zt.reset(),zt.addFilter("brightness",t.filter.brightness),t.filter.contrast!==0&&zt.addFilter("contrast",t.filter.contrast),t.filter.sharpness!==0&&zt.addFilter("sharpen",t.filter.sharpness),t.filter.blur!==0&&zt.addFilter("blur",t.filter.blur),t.filter.saturation!==0&&zt.addFilter("saturation",t.filter.saturation),t.filter.hue!==0&&zt.addFilter("hue",t.filter.hue),t.filter.negative&&zt.addFilter("negative"),t.filter.sepia&&zt.addFilter("sepia"),t.filter.vintage&&zt.addFilter("brownie"),t.filter.sepia&&zt.addFilter("sepia"),t.filter.kodachrome&&zt.addFilter("kodachrome"),t.filter.technicolor&&zt.addFilter("technicolor"),t.filter.polaroid&&zt.addFilter("polaroid"),t.filter.pixelate!==0&&zt.addFilter("pixelate",t.filter.pixelate),zt.apply(Mt)}else ln=Mt,zt&&(zt=null);let u;if(ln.data){let h=[ln.height,ln.width,3];u=wd(ln.data,h,"int32")}else if(t.backend==="webgl"||ln instanceof ImageData)u=dl.fromPixels(ln);else{let h=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(i,o):document.createElement("canvas");h.width=i,h.height=o;let d=h.getContext("2d");d==null||d.drawImage(ln,0,0);let p=d==null?void 0:d.getImageData(0,0,i,o);u=dl.fromPixels(p)}let c=u.toFloat();n=c.expandDims(0),u.dispose(),c.dispose()}let r=t.filter.return?ln:null;return{tensor:n,canvas:r}}var gt={backend:"webgl",wasmPath:"../assets/",debug:!0,async:!0,profile:!1,deallocate:!1,scoped:!1,videoOptimized:!0,warmup:"face",filter:{enabled:!0,width:0,height:0,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:"../models/blazeface-back.json",rotation:!1,maxFaces:10,skipFrames:21,skipInitial:!1,minConfidence:.2,iouThreshold:.1,scoreThreshold:.2,return:!1},mesh:{enabled:!0,modelPath:"../models/facemesh.json"},iris:{enabled:!0,modelPath:"../models/iris.json"},age:{enabled:!0,modelPath:"../models/age.json",skipFrames:31},gender:{enabled:!0,minConfidence:.1,modelPath:"../models/gender.json",skipFrames:32},emotion:{enabled:!0,minConfidence:.1,skipFrames:33,modelPath:"../models/emotion.json"},embedding:{enabled:!1,modelPath:"../models/mobileface.json"}},body:{enabled:!0,modelPath:"../models/posenet.json",maxDetections:10,scoreThreshold:.3,nmsRadius:20},hand:{enabled:!0,rotation:!1,skipFrames:12,skipInitial:!1,minConfidence:.1,iouThreshold:.1,scoreThreshold:.5,maxHands:1,landmarks:!0,detector:{modelPath:"../models/handdetect.json"},skeleton:{modelPath:"../models/handskeleton.json"}}};var z0=`
|
|
/9j/4AAQSkZJRgABAQEAYABgAAD/4QBoRXhpZgAATU0AKgAAAAgABAEaAAUAAAABAAAAPgEbAAUA
|
|
AAABAAAARgEoAAMAAAABAAIAAAExAAIAAAARAAAATgAAAAAAAABgAAAAAQAAAGAAAAABcGFpbnQu
|
|
bmV0IDQuMi4xMwAA/9sAQwAGBAUGBQQGBgUGBwcGCAoQCgoJCQoUDg8MEBcUGBgXFBYWGh0lHxob
|
|
IxwWFiAsICMmJykqKRkfLTAtKDAlKCko/9sAQwEHBwcKCAoTCgoTKBoWGigoKCgoKCgoKCgoKCgo
|
|
KCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgo/8AAEQgBAAEAAwEhAAIRAQMRAf/E
|
|
AB8AAAEFAQEBAQEBAAAAAAAAAAABAgMEBQYHCAkKC//EALUQAAIBAwMCBAMFBQQEAAABfQECAwAE
|
|
EQUSITFBBhNRYQcicRQygZGhCCNCscEVUtHwJDNicoIJChYXGBkaJSYnKCkqNDU2Nzg5OkNERUZH
|
|
SElKU1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6g4SFhoeIiYqSk5SVlpeYmZqio6Slpqeoqaqys7S1
|
|
tre4ubrCw8TFxsfIycrS09TV1tfY2drh4uPk5ebn6Onq8fLz9PX29/j5+v/EAB8BAAMBAQEBAQEB
|
|
AQEAAAAAAAABAgMEBQYHCAkKC//EALURAAIBAgQEAwQHBQQEAAECdwABAgMRBAUhMQYSQVEHYXET
|
|
IjKBCBRCkaGxwQkjM1LwFWJy0QoWJDThJfEXGBkaJicoKSo1Njc4OTpDREVGR0hJSlNUVVZXWFla
|
|
Y2RlZmdoaWpzdHV2d3h5eoKDhIWGh4iJipKTlJWWl5iZmqKjpKWmp6ipqrKztLW2t7i5usLDxMXG
|
|
x8jJytLT1NXW19jZ2uLj5OXm5+jp6vLz9PX29/j5+v/aAAwDAQACEQMRAD8A+qaKACigApGOKAML
|
|
Xp8xlF5A7V4X8RtYs7PzfNImnx8sa8Kp9z3q2tEgp6angWs62ZZ5CTGoJ6DArGNz5p+UrID6EUrF
|
|
PUlW1EuN0XNW7PQ2L5j3JnoKXN0KijqNP0eYoqXBdgPuuo+ZPeupisWn2Jd4+0r924XgsQOCff3/
|
|
AJ1FzRKxDqGii6m3siiQ8F1XGfXI6YNWLfRbiRQMkcZI9fpTDluT2/h6Qy8gDPbtmtG38JeY480Z
|
|
5zSLUTZg8M28YwYxjAArXtdPt402qgHbpSaLWhma3o0Uqk7Nx9DWLaaVblgPs6qRyds2M/gRSQp9
|
|
zZOni2iWS2hlQ+kjYz9OMGrdjq89vIPPVhj+8M/lQyDq9P1WOYBlMZz1AOD+VdDaTiReOKulK0jO
|
|
tHmi0WDTlr0TyxRVhT8tJjIX+9SUxHXUV553BRQAVBcPhSBTSuxPY86+IGti0s5I7dsORy9fM3i6
|
|
8e8mfDO5P90ZrWWiJicNPpZZtxV/xrW0jQt4DOv6Vk2dEEdTY6BHuB25rpbPSo0QARjP0qTRI17W
|
|
wA/hFaMWmoQMgflQXYsDS142rU9tpqqenfNA7GgtihxkdKuRW6qMY/GkDZY8sY4Ap4hXbyB+VArk
|
|
EtuH4wPyrk/EGkOm+a3jw3suRQLc5i38SX9hJ9nnY+XnBUdPyNdFY6pa3KkkAE9l6f8AfJ/pSJT6
|
|
GhDmI+Zb4ZRycdv6ium0nUhKFydrelTsNnS2829RnrVgV6NKXNG55lWPLIM81Op+WrZkRMfmNNzT
|
|
A7GivPO4KKAEY4XNYWt3vkwPg4OK0giJdjw/xrqhm87Zs8tc7pX5A+leSajf6aHYJ50kn4AZpTep
|
|
rBWRm2Vobm4BXfyehPFdnpmnBFUY5rI2SN63tlToK0YI+KZpFF+3QdavwoKTLtoW0Toaswpk5pCb
|
|
LCxipAhoIuP2dKevHXoaYDylRyxhlwRQI4nxVoCXWZI1GfpXGtbSWjYPGP73+NIGupt6TqMsLruZ
|
|
ih4xnP5V09mQ+JLd8gn0xSYJnVaVdkook69K34zuUGunDS3Rx4qOzHVIp4rrOMY3NJQI7GivPO8K
|
|
KAILt9kZrz3xlebYiu8KCCWb0XvW0NFch6ysfO3jLVjfXLIn+pQkKorl7WxNxIPl71g2dUUdpo+l
|
|
pBGvHPet23iC8ihFosrxirkHQUFo0IF4FXI1O726CpKLacCrMJoJLYHAPpTwucHpSRJJ5e4AZI9x
|
|
UqpxzVpCuOC8cUpQUMRnXttuB4rjNdsYyeVwfXpmpGmcvcQyafMCFJjPY10eg34BUg4DcZP8jUO4
|
|
HaRq3lLNF+IHet7R7jz7c56rwa2wz9+xhiVeFy/T1PFegeaNPWigDsc0ZrzzvDNIaAM7VpNqdegr
|
|
xL4l6kywyRhseZ19lrdfAZL4jxYg3Fw20d63tJsdrDI5rm3Z3R0R0Mce1eKnQYAplIkWrMJ45oZS
|
|
NO3PHbNXIyfpSGWowSOasxLUiZdjFSqtNEMkUemKlAGKsRJjAppFAiORMjmsTVrNZEO4cfSoZSOD
|
|
1eJ7WXBUzQZ+7nkfSo7e2Ei+ZaMzxntjBX2NSU1Y6/wxqojiEFzkA8KTXYaUoWRyv3W5rSjpNHPX
|
|
+BmpSg8V6J5gUUAdhRXnneFFAGHrTfu5PpXzj8S70/aZtxzztXFbv4DKHxHI+H4GZiz9zxXXW8G3
|
|
GBXMjvLRXAx0oPGPSmMVeOnWrMTYpFI0bcg1fh54xmgovRcD3qxETSIZcRvzp+/BpEkqsBUqsM9K
|
|
q4Em4Gkxk0yRGXrVW6i8yFhkg+tJjRxGsWrxllkUMh9eK5uMz6bcebbnfG33kPcVkay2OntPKuo0
|
|
nhXI67c8qa7Lw3c+adjcEDGK1paSRhVV4s6A0or0jyRRQ1AHX0V553hRQBz+vNtt5z3xXzX8Qbdm
|
|
uic5YnOMdK3l8JnTXvlbwpYl+WySOgrp5YfLOOB9O1c62O7qQkc+9RsKChFPWp4DluOlSykaNruH
|
|
ArUgHShFNF2NT1qxGO3NBmyxGcE1N2560CFzjrUysO9JAPDDjFOVuKoQuSRTWouBkazbCa3cd8cV
|
|
wF7IISQccHBzUSWpV9C3o1x5b5GAjdQD1rs9DjC3kckbEhqKfxIzn8LOupRXqnkPccBSkUAzraK8
|
|
87wooA5rxMSI3HqK8B8bQl9Q8sffY5b/AAraXwkUviNrw9pH2W1ViMMRTdRjw4HpWNtDti9TPc4P
|
|
FQs2M5qdyyMHLcfjV63HTAoBGtap0wK0YxigpsuRDtVhVYd6GQydVwwIqdRnqKCR23I5pCMUW6gD
|
|
YNKuetAEise9KTxQBWuFyhrznxNZkXjFeN3I+tTIZg2OqmzmxNF0PO3vXp/g2+hukVl4zyPanTXv
|
|
JmVR+60dpThXpnlPceopWFAbnV0V553hSGgRynjC5FujOey14Ssp1HxNmTnc+a3kvcIpv37HoEYQ
|
|
QmMdVHSsnVbYJF5jVk0dsNzlruVIsl2wKxbjWrVHILjg1CRbZJb+ILHPzyhfStODWLQgFJFYd+el
|
|
UJM27HUIXxhga1Y5lLVLKLkMnoauxnPPrSEx7ShF+Y/n2qrc6xBbhizDAqkK1zJuvG9nbg8ZA681
|
|
ly/Ei052RO3uKAsZlx8QGd8xxvt9Aa1NH8dK7AXMcip64zigdkdrZX8F7EJLdwwNXMkrz1qRMRly
|
|
CK4TxmpidWI49felPYSOMmi80NIoOV6qRzXYeA5SskYPfirpfEjGr8LPWVHyD6U4CvQPL3ZItOYc
|
|
UDOoNFeed4Uhpks4H4iE/Z5MeleMeGULeLgjds10S+BGdL+Jc9OSBU2Huc5Nc74yvUtrcDBrJnZF
|
|
63PJdXvLy/lKWw46bvQVz82jXhkLO5Y+9ZlsYthcRnbIjY9R3q3awTRkEM3WmJI6C0ea3dGRsr1x
|
|
XY6TqW9FLHnjrUs0izpLK5DDjofSta3ckH09KRUkZuuTvFGdvPauE1Y3U6Mqbssf/rUxHPTaJPK2
|
|
ZmJPbBqzY6DCZh5xJC9s9aBJHU6dpemJjfEmfetJtI0+VPkUr/unFOxdiextHs33W07YHQHk11mk
|
|
Xb3KbZ1xIvcd6LEyWho4Nct41sTPYb16ipexCPPZN+wYGCvH1rrPAEJmvkPoc1VL4kZVvgZ6yFwK
|
|
cBXoHkkqinFaVyzo80GuE7WJRQSziPiGdthK5HQV4x4J/wBI8WPIewNdEvgRNL42emO/yj1UHNef
|
|
eNpRczbC+I17DvWT2OqJxc0sMK4TCisy41q0hfEkqj8aixdwTXNOlwvmqD9anS9tXH7uVG+hosO4
|
|
/wC0oOhrR0+6G4YNIEzsNEuCxAPNdjZruA4xxUmjINSjURksOlcbqFykbnjFA1sYGoassaknCqO5
|
|
rl7rxhGm7yBnBxuJq0rkSlYpw+NLlsfd5P8AerVsvHEqSBHwPVgcgVpyMyVXU3rXxcHYETAk+hru
|
|
/DWti6ZSTyOKzZqndHaxvvUGq2rQ+dYyqR24qWI8dvbr7LqDxyDAzXpvw6FvIxePGSM06Xxoyr/A
|
|
zviKFHNegeX1J41zUhXioGbuaSuM6wpCaBHG/EcA6HN/exxXjXw2jL67cv8A3Qa6H8CFR+NnoWpO
|
|
I4XI44rxLxrqjQzSEsQM1gdSPM9U1uR1YbmWIdXHf2rmpIb67YS28UrRlsLI3c/jW0VZGUpO5pW1
|
|
jfLNOjahawzwReYI5cjzMkDavHJ5/SrVv9uhtPtVxCPLBwzxnlT9KGghLU3tKvvPjHzbl7EGuisJ
|
|
GRxWLOg7nRXJEbDjmvSNK+aFSfSoZr0KutRkphc4NcRrdkVjL9aVio7Hk3iqS8ubhrWzUlsZY9kG
|
|
cZNc5D4aee5MclzJIFTzHAO0MfatqSOWu7bFS1srDUZEis0vIZoUxPvfcC+4/dx2xjr712XiTwXb
|
|
WmlQ6hol3cRhoFd4rlg3zY5wR0GelavQwjq7GD4etdVvSnk2wAB+9v8A8mvcfA2kXiRo0/UdcDis
|
|
ZnTTulqeoWqbUAJqWUb42X1FZlnjfjSwlGrr5S/eNdD4RkvLAAQ4yRyaUZcruVKl7TQ9I0G+mnzH
|
|
ckFwM8VuIK7ac3KF2eXiKapz5UWYxipNtMyNejNch0jSar3cjR27uoyQCRVRWom9DxTx54gu5fMi
|
|
lbKdMVjfCZPNlv5v9rFbVHpYqjGzbOn8SzFI9o715L4u0r7arYzk+lYdTqSujy7U/C0u4vHk+WwO
|
|
xuh9q3J9dgvbdVukMV1EwbDDgn04rZMwlHoZ+orZ6hfQ3RWVnQYCgZAq+8U0ln5NtBsV2yxYcfgK
|
|
JtW0CnB31LlroVwJ1nQLGDjeP7w+lb0dsFxjrWB0tHS6NuWPJ6A16ToUm63T3Gallr4S7cxiTjrX
|
|
PaxaF7dlVeSMUhxZ5jd+H7qCa4eF3DSE5x3zXN3Wk6jbyeaiFWUY6ZyPStYS5SalPmVipFbX0E4c
|
|
W0alvmPHJrag0rVvEE6LdljGpG2NRtQD+tW5XMI0uU9M8NeFo9PiQhecDIIrtrOMIoG3H4VlJm9t
|
|
C6CB06VPGM1IHLeItGS6uw+ORT7e3jsbQvj7gzUNam0JaWE+HN7NqOqX80n3FO1RXo8YzXdS+BHk
|
|
4z+KyzGPapcU2YIv7qQtiuaxvcaWqG4O6FwfSrS1JbPnrxoxkv7qIfejcitj4V2f2exumI+8+aKn
|
|
xHTT+G5d8Txlm4rjLxMsQwzWT3OiK0Mm6sEkVsAcjFc1d+FEmlGwEDPQVopaEuOpr6f4ZWNAu3tW
|
|
vHpAj5ZQcUFIWaDjGMVUMQ3cVDBmvbhY7QAV2nh+T/R1yeKhlrY31+b61FcQK6nIoJMi401WblRi
|
|
qr6PCw5UYq9y+YgOgWzNkRrx3xWjp+nx2v3FQcelAbmko9anQ4GBUNisPHWr1qMrQhS2K11HvmYV
|
|
hamcxSRZ5xRIqluS/DKAQQXZxyXrvo2FdlL4EeZjH+/ZbjNSZpswLNBrE1Gt7VE4ODVIlnh/j61F
|
|
j4lmeTGyUbq6LwdEqWbeX0YbhSqfEddP4Bddj4JIrhL5d8h7VjI6oLQqKNzelWre3yc4/ClFjaL6
|
|
wqBxxUUxwCKu5BmXRA6c+9ZjP83FSBoQuPs4BrsNBlUW659KmRrDY6G1lyQtW3Hy0lqQ1qVJnAbm
|
|
oy3b9KYJCqRj3o4zRctIlhjLHmpSuOBRbQOpLGpPFaES7UqkZzKN1KsEc87/AHUUmvPLTVGv72aQ
|
|
k7WJwKmRrQ3ud74Ltilgz4++2a6iNDXdS0gjyMU71my7GpqTbxSbMki3SViajTTHqkSeR/GeyZmg
|
|
nQHkEE1S+F+oPPavBL96I4/Cia1udVF+4dVrkW+Fq8+v4tjMDWUkdVJ6WM0cNV+F+MVmjUcZgqnP
|
|
1qpNNnkcVRLiZtxIS1UzzIF7mghlxUZpVQdq6nTVdAoAOKzkbQWhvwM6gMM1twOJYx3NOJE11Kt1
|
|
H1/pVVlwBkk+9NocXoOQ45FPj+fkUJFF2NSB700v/hTEty5ZpkjvVyUgcCq6GM9zC14/8Se6GcZQ
|
|
1574Xs5WkI2HBPHFQ1dm1KSSZ7Rotn9l0+KPHIHNacae1dy0Vjxaj5ptlhVp+2s2CJ9ppCKzuWNx
|
|
zSFc1SYrHNeNdIGpaYw25ZeRXmvheyk0jVpEdcLJ0q3ZxNKTa0O3vQHg/DNcHrsJDmsmjspnNzNt
|
|
fFIJ24GazOhC+azDmgZIOOKBsp3J2qSaZodubq58yQ4QAnmhGT3NO18pb7BORmu205LfYpyKVkWp
|
|
Oxr5gKYWoIZWgfGfloFq1qTPLubnGO1RPtxg4P0oBAkY/hBz6VNDDkZ6AU0W2WSdqkdKr9ZOaGSj
|
|
VtcLHmnOcgmmYvcz7mBLy3MbdD1q9ouiRK6bUAVeelOC1InPlidSsWMDFOCEdq3uefykqrinYqGy
|
|
rFvApMVka2DAowKAsMkRXQqwyDXn/iWyitNQ3qPl6itIvRoF8RXinW4tQ6HI6GuW8SIVBPalc6qe
|
|
5x9x97r3qruwTjrWZ0ksZ9TUmcDNAmZ9/wAoao63rR0+w22MLPtAzt6mghmfofiB76LdJBJBIp5D
|
|
d/oa7bSdWLIPnpDi9TM8TeKdas51XTbIyxd3J/pXS+E/EFxqNoFu7do5OmD60maHWrnZyDRkn/69
|
|
MlEyOR0xntVoNx+FUgYjPxg4FLCuWDZyKQr2RoRnP0qO+nEFpJITgAUzLqZnhu6+0rknOTXpOmwJ
|
|
Fbrt5yMmnHYyr6Oxb2ijaKLnPYMClwKQWK3n0hn+lachHOJ9pNNN0apQFzsY10a4v4hXQh0xpieQ
|
|
MA1XLZNjhK80cT8OdV+3Wl3A7ZZJCw+hrR1qLcjZ/CsbnfHRnFXseHJArOYYbrUs1uPhYbuatqFP
|
|
ByfSkMq3UIINYkto+87Tx6GkSxfsDbflGD7CtTw/pk4nzITtPIFMFudsukh4Rxz71paTpKwP5jcn
|
|
0qTRy0NORMDgVCqewoJTJgAoxjntTiTu7fWmFxAcnn1q3EPl+X8KZMi4gKqB1Peob/Tv7Us5bfeU
|
|
yOoq4R5nYxqT5I8xieH9J1DTbvyJELRg8ODwa9Ms5mSFV9BWiptbnNVrKdmif7Q1KLg96XIZc5Is
|
|
pNL5pqeUrmMtZs0jzV08phchaY00zH1p2ZNxjS1g+LdJOt6U9ssmxjyGp2urDjLlaZzng/wUPDqz
|
|
TSTmWeTrjpVjVk3Rvjr2rnqQ5dDvo1XUd2cTqSNk9OKxXGCeKxZ1DAxHTr2q5C/y8GokUhsz54qu
|
|
uCxzSQjQ0+FZblR2ro4bZYiMVQ0dBb7Qi5x0qzuG5QOh71LYErDufpSeWrHnimIXbjkUjLkH1Hem
|
|
gGxryc+tXI19KYmWegq9YLiLJ7mtqS945cS7QsWehqxA9dEjz4krPSxyZqbFFhGxUm6smjRM55Lk
|
|
HvSvNxXTY57kLT+9MNwKdhXGm5FIbkU7Bca1wMEVhaiuQcVhXWiZ14R6tHGanGBI2OtYkqEHjgVy
|
|
s9ErEeo6UBsHipKEZs5qpPdRxcbhx70NCSuybTNWihc5brW9Fq6vjMnFSdEIdDRi8RRKygZbHFbu
|
|
m6nb3RA3gMegNJhOm0jbXGOoxTuCc1Rz3FyoGKawz9KaAVcZqeMgCmIkB4FaUTbYwB6V00Fuzixb
|
|
0SFMuDU8Mlbs4UPeXHeiOXkUrDuXYnyKk3cVk0ap6HMxxketSMhrcwRC0dMMZFMQ3yzSeVQAeUaz
|
|
9Vj8uPd271nVV4m+GdpnHX67pCeKyLtBtNcR6xlk9RVeWTb3qRnO6trgttyIfm71z7ai8j7/AJmN
|
|
DNqUVa5Yi1AnjynHuBV+11YJhWWXcP8AZNSzqgmaEerSsf3NtIQP4mGKtRavdRgMIpVI9KjU0a7n
|
|
R6T43uYQI7qN2Tpkqciu503VVuQGAYZHQjFVc4alPlZrpKGAznpTwxOc9+lWjIlUACnM4XApiLNk
|
|
nmvnsK0NvpXZRVonmYqV52GsmanhXitTmFkSiJTSAvwrxUxXIrJ7miOfjf1pzNWxkRlqYWpgJupu
|
|
6gQbuahvIxPA6eo4pNXVioS5WmefakGhndH4INZs5DJXA10PaTurmLO21uKpSZqGMoXGnRzBiyjd
|
|
9Kx5rcQS428fSkjanLoaOliHGZFB56VswW+mtPufcBsGOAfmxz+tFkd8HpoaUx09FAtFY8DO71qb
|
|
Sms/Nb7RbecG6AEjFLS5c78t+p0djpVs9wsyQiJAdyr1rW+zqjErzSe559Sbk9S3C+MA1bjbgE1S
|
|
MSXzMVG0vNUI2tPKrAuCMnrVzNd0PhR49W/O2xrHmp4TxVMzQshpIzzQBehqesnuaI5VGzT2bitz
|
|
FEbNTC1ADS1JupgG6l3UAc14s04yR/aYRll+8BXCtLncDXFWjys9TCz5oW7GddH5qqNzWDOgQnC8
|
|
VSuo1kHzAGkPYopEY2+RWxV23Vzj5G/Kg3jWaNazhZuqNXS6TaKhB2c0jR1nJWOlhOxRxU4YkCgx
|
|
Y0OQatQyDbyaaFYe8uF4NY3iC9ltbVGj43NTIL3h7WzMihjzXVQXYYDdW9Cf2WcOJpfaRZ3g9KsQ
|
|
mupnCLIabGeaAL0LcVY3cVmzRHIxtUhetzEjZqjLUAIWpN1ArhupwagAfDKQ3Q1594v0c2bm6tx+
|
|
5Y8j+6ayrR5onThp8s7dzkZjuqAAmuBnqC7c0iwgtzSA0rWzjfGRW3ZadDu4AoNYo2rfS4v7orSh
|
|
05UA2r0pDbsTm29KRottBNyJ0wpJ9KhD7f6U0ikNWffIFBz60zVUW52ow4UcUN6EPcx44WsbgOmd
|
|
ua7TT5Bd24KHnFKnLlZFSN4koluLdueRWvp14swweG9DXoxldHlTjYtzGoo25qzEvwtUxas2jRPQ
|
|
5CNqkLVsYoYzUzdQA3dSFqBBmnqaBhuqhriCXTpVIzxUz+Fl03aSPI9QTypW2/dz0qKNw3SvOPZR
|
|
Mqin8VLKRcs3O4Cuk0w/MDjt1NBtHY6O2IIHY1pxgFaETIRwMkjtVSUEk4570MlFW5bap6dKzWm8
|
|
1tqH8aY+hp2FvGoGayNevVt7/ap4xzUvYjqTLtvLPcvJxSaVcyWsxTnFZlnT2t15xHmCtOBYwQy4
|
|
B9q7cPO+jPPxFO2qLEj5HWo42+aus4HpoX4W4FTF+KlotbHII9SFuK0MUNZqiLUDE3UbqBBupwag
|
|
Bc1DefPbyD/ZND2KjujyPWlKzuPesRZjHJXms9lMuw3StjnmphKDSLTJ7OfE3JrpbO4GQc9qlnRA
|
|
3LO82k5NbFvdADkjBoCSHyXIIIzgVQvdRigT7wzjgUzO1jHknlvG7qnp61etYFQDIpCZoqVijzXn
|
|
3iC8EmsOuaCGb/heR/s0ijkVv6fbxy3QMg5xmsnuX0Ldzut3+UYTPWk+2GJSe+M1pFtamcldalmx
|
|
1eO4XaThhWnC+TXqR2PHqL3maUJ4qRjxSEjj42qXdxVmaGs1MJoATfSbqBAG5p6mgAzTJTmNvpQU
|
|
tzzHXY83D/U1zF5FhjgV5r3Pa6FMsV5HWnLe7RhqBRdmTwagN2d2K2rPU1C5LAnPrUs6Iysbdrq6
|
|
f3gK0BrUKj/WClY05iM6xLOcQAj3NT29uznfKSzHuadzNu7NSBFjHNSm5VO9IRnajqoWMhTzXFtA
|
|
bvUfMduSeg702Qz0rS7FbTToQFwzjJqaGTFyfK5PQViyzUuFmuIdgGABya5u/vTaN5cnUHFUmLoZ
|
|
zyskwlgJweSK6zQdUEwVJeGr0aUrxPLxEfe0OrhPAqVjxWhznGRtUwatDK4jNxURbmkAm6jNABup
|
|
6tQAFqhupNtu59qUnZFwV5JHnWsHdIx96w5lz15rzT2uhRmt85xWbcxMnUGmZlB0bdxmrNvFIcfM
|
|
350mWjbs7YkDJY/jW5ZWW4jikWkdNp9mqYJFaJdEHHakUULu/VB1rLn1Ld/FgetMGYd/qWSQmSa0
|
|
/AemS32pfa7piLeLkg9z6UmQtz0W7uQ2cZx0A9BVzR7cAea6j2rPqX0L99KRat5A6Dk1wOoKZ52a
|
|
YfMORTYRLujiGWEq6/NWza2yKQVHNdOHerRy4laJo6TTnbbtb8KuM3Fdh5z3OJjbmpt3FaMxAtUZ
|
|
agBN1GaQBzTwaAAms3VbjERUGsa07RsdeFpuUuY4jUjljWTKK4j02RE4IpJYFk6imQkVl0xWarsO
|
|
mAEcUi0bNnZBR0rWtoguMCkUi21wI161mXuocEKaYXMS4u+pY/hVCSWSY4HT0pEmlouiSahdpEBl
|
|
mOceleiwWcNjClvHgJH97Hc1EmVFFi3Czy7mwIl/WtJbjP7uLgd/apQ2VNVvtsBhiPzdK5S4nAuR
|
|
nqOCaTGi9pcytPlU+XpmumtWII44rah8ZjiNIXRuWeNvvViQ/LXpJWPJbu7nCRvVkNxVsxBmqJmo
|
|
EPiXca0YLMuOlJsuKuPlsSi5IrNuG8s4HWs5VEkbwoOTKsk+FJY4rC1K53k1xTk5O7PSpwVNWRzt
|
|
4cms+WpKICtSLTETQj5q0YeBSGiys23pUguGxQMq3E59ayrm4x3yaAKiRtO2WPHcmhruKFxFajzZ
|
|
ScA44qRHoXhuMaLpxaUg6hcDLMf4F9KlhuDeXGASIl+8azZslYma68y48m1+7nFW5rtbRNhb5z1p
|
|
iMKbUg0zuW4A4rPgb7VdKXOMmpA7HRbMS7nUYiUda0lkQOBngVrS+JGdbWLRt2bAx5BqeQ/LXpnj
|
|
PQ4GJ+ashuK0MhWaoWcA0AaOmASMK7jRNPWYBmHyiuepO2x10qfcv6vYxCzYqoGK4HVYVTJrmb5l
|
|
c6oaM5TUJ8EgGsG4kLNUHT0M64OaqMMikSRsuKbnFMRLG3zVehOaGNE445NNlnVFpDMu6uie9Vo1
|
|
8z5mOAOST2pDK91cNN+5tsrH3PrW54a06KxT7fdrlh/q1Pc+tJ6IUdZGvHPLezMcnBOWbsPap5r3
|
|
ylFtbdT1xUWNWzU0/Zbwlgfmx8zGsHWtRHmMqE59aAMyNifvHPc1f0gtPdqkY5JosJHeNci2tktY
|
|
euPnNY+oXWZEVJNrZ9aun8SIq/CzodHuriIokhDIR1ronbKZr0o6o8ipoz//2Q==`,P0=`
|
|
/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAsICAoIBwsKCQoNDAsNERwSEQ8PESIZGhQcKSQrKigk
|
|
JyctMkA3LTA9MCcnOEw5PUNFSElIKzZPVU5GVEBHSEX/2wBDAQwNDREPESESEiFFLicuRUVFRUVF
|
|
RUVFRUVFRUVFRUVFRUVFRUVFRUVFRUVFRUVFRUVFRUVFRUVFRUVFRUVFRUX/wAARCASwBLADASIA
|
|
AhEBAxEB/8QAGwABAAIDAQEAAAAAAAAAAAAAAAEDAgQFBgf/xABDEAEAAgECBAMECQIDBgUFAQAA
|
|
AQIDBBEFEiExE0FRBiJhcRQjMkJSgZGhsWLBJDNyFSVTY3OSNEPR4fAHFjWCokT/xAAYAQEAAwEA
|
|
AAAAAAAAAAAAAAAAAQIDBP/EACARAQEBAQADAQEBAQEBAAAAAAABAhEDITFBEjJRIhP/2gAMAwEA
|
|
AhEDEQA/APqYAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAKNTq8OkxzfNkisQC8eb1XtRNbzXT4q7eU2nu0MntRq/D8StMccvW29ZmdvgjsTyvZjxOLj
|
|
+s8WLxn8TFPXs6Oj9oct7c14rkxz22nrB2I49KOdTjelmszfmpMeUxv/AA28OqwZ4icWWtt/SUi4
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAmdo3nsPNe0Pt
|
|
Fh09Z0+DNWL7+9O/7A3eJcZppsV5raI27esvH6jX5ddM25p79Ilo59VbUZOe2Tm/PeGvfPfT2iKR
|
|
PLv1+DO678XmW/a97U6TtOyzTbTF538/T9WjTNecm9a7126tqk3rSYxY5ta1plRZqZNXGjyZcPXl
|
|
mZmsx+qjBrsuO16xM7eXRt04JrdTltk5OWJnfaWf0a2lty5MdZnfzSn+WOHiOutFpjHa9e8bQ2fp
|
|
+alYy462pk7zXbuxjPesbRS0f6ZZV1ET1tErzXFLHo+A+1ddZf6NrI8PJHa1vN6iJi0bxMTHwfOa
|
|
zhzd61v1846utwniM6DUdb3nBaNrVmd9vjC/ZVePYirBqMWppz4rxaPgtEAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAItaK1m09ojcHnvarjM8P0vh49+a/eY8ng9D
|
|
h1fGM1rxjtGPfvbzdbjuTJxHX48cTPNltM/KsS9Dw7S49Jp6UpHaGe2vjz1y9J7LYK13vHWe7bj2
|
|
ex1tvM80ekuxW3RnW3Vm6P5jRx8H0+OYmMcb+bapo8GKPdpC6bQwtdHU8JpWkdJ/JweL6e23iU67
|
|
d4dubSqyVi9Zi0bwIs68XGp36TtEq7ZJmZmevzdbifCKWtbJinkt6eTgZPFw32t+sRurbWVzxs1y
|
|
Rv6T8V1NZNPtfq0seTm+Kevr+SZuxXjvaPiV8N4viycto9HseG6+uu08W6Rkj7UPmFck1tE1nlmP
|
|
Ld3eA8V8HVVi1pjq6Ma/pnqce/ERMTETHaUrKgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAADW19+TQ5p/p2bLS4v04Zmt5VjeQeJ4bjnLqsupv+Ka1+ERLv4reTmcNxcuC
|
|
vy3l0qdI2hlr66sT02ot0ZV7qqrInruzrVZLGSZ37JjqgYTG0K5lbaFVhDT1Ub456RPweY4hixWi
|
|
eSdpjvD1eWejz3FNHWYtkpvFo9EIseb3tS3SerOms22rfpPqZKzvvHSYUz70TExG6Gdbs2rljeJ/
|
|
Mx5L0vEzPaelnOi98c9J2bFNTFpit47+a+PVUvx9T9nOIfT+GV5p3yY/ds67wvsXqpxau+G09Lx+
|
|
r3TqrEAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADV4ljnLw3U0jvO
|
|
O0fs2lWqyUw6XLkyfYrWZkHldBEV09eveG3Fq1mI3jd4vPrOIaid8G9MP3Y38k6fNrt/rMk9Ou8s
|
|
tfXXn49rGWInuy8SO/k5Gl1E3rG/fzbOe94wTy99mbRvTrMOOvNfJWsesywniukrG/jU6fF43WYN
|
|
TmtEeJtEQ06aSmK2+bNtEd+qfSO17unF9Hmvy1y13XWyVmN4tExLxVK8PmNq5NrT58zawam+m/yc
|
|
0Xj8NpRYSvQZ7xEOdqI3rPozxayNRXe0ct/ON03jmrKB5nV4q1yTO20Obmv4c+cx8HoeI6WZpNoj
|
|
q83niYmYscU0r8aJ6T1n49zeJ+Meqm1drb9J+Kd5p136StGVem9l9TbHxLDFp7W7+sS+q1nesT6w
|
|
+PcAzVjiGHftzQ+v4f8AJpv6On8jH9ZgIAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAABp8VrW/C9TW0ztOO3b5Nxp8VmI4bn37TWYB8f1HFtTfUfR9FWJmsdZ9I7MtJxDX5s
|
|
d8ta1y0xzteaR2277rcuhycP12SceLxMeWNpjttHwlu8I0mfQ1y+D7k5YmJmY36T36Ka43z/AF1t
|
|
cI1ds+qxVj7/AEej19PCw9HJ4NoK4OIU5Y35YmZdzVTGebVZabx5jJS+Tmns81rNLm1Wrzc9rVw4
|
|
Yibbem72mXTTS0w0M3BvEta1bWrM95ie5EanY87wXgNOL6XPfxraXLhra/W28bR/dzYzarBqJxRe
|
|
bzE7Rt5vWU9n8mPHOGmS0Ypnea1naJb+k9ncNLR7u2y/WcxXO4TOoyUrN6zD0FaW5Y3hu49FiwUi
|
|
KxCvLMR0hlW0jn6ukWw3iXjOJzbDlneOj3GaN6zDzfFOH+LE7SRGo83XNSZ2lbG2/WfdlvaT2cy6
|
|
rNFInlrv1mfJ37cK4PwTTxOoidRm2+/2/KFuyMp47XB4LivXiunrH2b2iH2qn2K/J8x4fGDNxTSZ
|
|
9Nh8OviRvTyfT6xtWI+DeXs9MNZubypASqAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAOZx6/LoOWPvWiHTcf2hiZ0e8fc2mf1E5+vP/AEeuSd7RC2uKtI6QjHfeINTfwtPf
|
|
Jvty9WPfbt/lucP03gxfJf7d/wBoReYpm97zaNeLb4Ims9Nt94auDjem1Wo5PFi1onylS+1o7l8V
|
|
bxvtupjDMdNkYtXS1+Stt+m63xImEJ4xjHER2ZxMUjeUTO3VRmydBbjLJqPi08mbeVOXJPq1sl5Q
|
|
Vbkz9+rRy35rxHqzmZlVEe/Ez5LRlW5iyfR6zffaIjq1OSNZps2a21rZInafSPJhxGMl9LStLRWM
|
|
lorM/A4dkrWbYfLZC2W/7K6eubX6b4RzT+W76K8b7G6X62cu3Sten59nsm3j+OXz3/0ANGIAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA0OIYfpOHPijvNNo+fdvtXJO18k/
|
|
/OwPFYbz2ls3jx8VqW6xMdWPEdP9D4lkx/dt79flLLHbkxTPwY6nt2512ORTRzE2x4/dpE7cvkme
|
|
E4IrW3hRMxO8THRtU1FKWtvtvK2upx22rzRCtXkqzh2jtF7ZbT122b01ndnpuWuP3Z3+Ky20qDVv
|
|
fauzVy3mejZzNK8dVjqi87KLRLYtXruqvXzkQp7Qoid88R6rcl+WGlW0/Sa22mfhCZOq2x082ix6
|
|
jkm822pO8VrPdr4dNObVeDo8XW3uzMbzK+mvxT7szE27cvnu9j7PcNjSaXx8mOIzZevbrEeic5tN
|
|
+SZnpt8J4fHD9HXHO3PPW0x/DeBtJxx29vaAJQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAKNRim9Z5e89Nl4DzXtVh5babURHrSf7f3ec1+qnDorWrvvt5Pccb0n0zhmWk
|
|
Rvevv1+cPE2rGTFNZU26PFfxwa5dVkjelI2772nZnX6bbrEUq3o0d678u8wmuDL2ittvVjXdneeK
|
|
cGv4jpJ6U56+kS7+j118+GLXpakzHaWlp9NNY3tv+bbiYiNoQy1y30uyZJlrWmZnuym6q1iIJnop
|
|
yW2Te8bdWnnypQqzZOadokiIpSZntWN5lrxki19vNRxrUeBwnNNd+fJEY6/OejXLn3Xe/wDp9wyn
|
|
E8uo4lqqxblv7lJ26T6vpD5X7G8QycKzeBMbzMRM1/FH/wA/h9QwZ6ajDXLitvWzRgsAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAeL45w+dDrZvWv1OWd4+E+j2jX
|
|
12jx67TWw5Y6T2nzifU+rZ1y9eHwzDYxxEy18+DJodXfT5o96vafWPVbjyxDn1OOzHudbM0rt2UW
|
|
iI69mVtRXZq5tREb9VUoy2iIlRbJ0UX1VZ6btTLrI7V6yk62M2oisT1c7JmtkttVMUyZp6x0beDS
|
|
RWOvdKijDimvWd3G9pNRMfRcNfvZOb9Hpb0itJeP47k/3hgjaZnbaP1XxWW3T0movbNS0W645nbf
|
|
0nrMPpXs3xamoxdJiLbe/X1n8Uf3fKsOTw4jbaXo+EarJhtGTHMxeJ6xH7Sti9Zaj6x3HM4NxXFx
|
|
DS1mtoi8dJrv2l011QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AGjxLhODieOIye7kr9m8d4eM4to9RwjPXFa0ZIvG9bR0fQXmPbDFvTTZPOJmEWS/V8bs9R43NxLL
|
|
G8eFbePg1bajU5/s0l1ceKLx1hbjwRE9mOpx0y2uRTSZsm3PMw2aaKtIjo6kYo9EXpET0hVLXxYK
|
|
xC6MZvyx1lFs0RHfaPiCnU12pLyHGNDbUajBekWma2npWN3p8+opa20e9LSyZLxExTlpM+vdOdcZ
|
|
a9tPS8MyUvFrzWlI6727u1pYxYrbVmb7x+TQx6au3Nqcl7/0rcmW9axGnwZJj1novmxnZXV0fFp4
|
|
ZxLBPgTGK8xzXr5fOH0bFlpmxVyY7Rato3iYfNuG2x56Wrqa8s2jz+7Lu8O12bS6jkwzN6THNNI6
|
|
tvrN68Y4rxlx1vHa0bskAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAA4XtTTm0OKfTJ/aXdcL2pyRGjwU362yb7fkJz9eTxxyZJjyltRXzUZK7TFtl9Lbwy06YzrHwa+
|
|
fJFd/wCVt8m0bQ0eS2qzcm+1K/an+zNZFL5M1pjFXeI72ky48eGnPkvNp27+TPU6nHpMfLXaIjpE
|
|
erk5dRMxOfN1mPeisfshW1ne1a1577Y6x5R3U0zze31FOWI6ze0byU098kRlzbxM9qrMlPDpyRMR
|
|
Md5Vt/Ihp5898mWZm1pjftE91uCt7fCI7dWeHDEW3t723l6rslqxWZnasR+SYhFbzhnfxJ2jyeq9
|
|
lcGXWZcmW0zWKxHLaI7794eJx5fpfEKabT8t8l5isddo3l9S4VjrwrRUwzSJt3tav3pdOL6Y6dXD
|
|
j8HFWm+/KsU4NRXPvtWazHquWVAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAa+fXYNP9u8b+kdZBsDkZOO135cWOZn4y5Wu4xqctbe9y19Kp4njt6vi+PDm8DFMWybbzPlV
|
|
5PiGtz67UxbNbeKTtWIjaIXYpnwuaftT5tXJT3vmi1pMsrU5qIrG1V1a+5DCa7b9GFbRr5J6Wnbt
|
|
Cu+Wmk0m8956z8ZWZNorbfzcbX5rZslazPux3hUt41NTntktObJ13+zX1bek01r4/HzVm0bxPXy/
|
|
+bNfDgjVa2uOY92kdfg6ufJOKvLXtttVVSqbcta2vM7zXtHpLQy5ZtMd+vWd+7Zy3mdJHXra3f0c
|
|
vUarw7zFY5rT2hH1Lavnrgx81p3U49Pk4nE5L35MO/StfNRXR5tXnrS8W67WvfyiPSPi7uLHFK1p
|
|
jrtSsbR5Lc4RzsXBaYreP4l45esRD2HD9fnw6evvWvO3Tfr0aGk0U55ra0TFInv6uzgrXFXlx0i0
|
|
77RPlC83Yj+JW7oddqr6vHzTTw9/f6dod+L1t9m0T8pcbFSmPHER3892W0zPuz+jSbVvidkcqmfP
|
|
Sel7bekrI4n4dZnPWIrHeYnZee2Wpy8dEaml4npNZblw5qzb8M9JbYgAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAABEzFYmZnaI7yCXL1XGa0jJXT0571nbee27DiXEprp8nhbxG20W8
|
|
5cbD0ikfnKO+urTPvjoZdXqctdsmTaPSvRpWmsdZ6yztfaGplvv3lWW1tyRlz1x0vkn7Vo5atTNe
|
|
Y0+1o79V2KsZsvX7Ne5mwxnyTNvsx2iGneM/rCdRSuOsTasTt5kRFtpjqmOH4t4nk7estiMNa97R
|
|
Hwhna0iuKTEdmGWa4672nZtRele1N59Zlq6vLOSsYorEc07qcW65euzRvtXvPZy52naZ7ujr6fXV
|
|
rWdukREK8+njHgmZmPc67bq6ivVWhxxgxZLztNrT1mZ/SP4VZs0zaOvfp84WUtNsXLvtv3699+rU
|
|
z7+Jtt5qURqMnPpctaR1rMSw4ZoK57eNk6xHaJRh97Ltt7lo5Z+L1HAPZvVauZ2nFTSzMTzeJEz8
|
|
to6xPfvsZntPZ9rXxabmxzefdrv0j1dXh/BcmstW1qxTHHasR3+b0GPhGl+kWmd64dNEVjf73T7X
|
|
y8vy+Ddx6O3iRakxTH5RXrMw1/lX+3Itw2MFIraN48qRHdZi0cUjmmPen9noox1iO0fNzdXEYrTt
|
|
stcmd9aX0bJ+HePmiKTitO8TMLZ1cVjrMfqpz6ys4pjfrPRWZ9rXXptUit6zO+23VyaRHEc05L1/
|
|
w9J9ys/en1ljqdVbwYw452tlnl3jyjzbmmiMeKtYjpEbLeTXPUU8ee/+qjJpsV5rbkrFqzE1tEbT
|
|
DpYNbW21Mnu29fKWna0KbqTdjXXjld0cvQ63ltGHNPSfs2n+HUbS9c2s2UASqAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAOVxPWe99HpP8ArmP4b+r1EabT3yT3iOkesvMVtN7za07zad5l
|
|
XV5GmM9vVfEstvDx0jtaVVMlq+UJ18b5cMRvPeSuK87bUt+i2Z3PtG7zXpjkzXt6R+TXyTMzvM7t
|
|
ydHqZ+zhv1+Cv/ZuqvPTHMfOYaTMil1a1K2vHSLTELq2v+KWzThGo84rH5rq8JzedqR+ZeI7WnOS
|
|
34pYTafWXR/2Pln/AMyrKOCWnvmiPyR6O1y9585lhWJvl557Q6eo4T4dYiMvW3b3UanhldHpJtGX
|
|
e09unmjsT7eb1l4trI2t0hsZfrdNO0bzy+nzU20/+NmkzO9esz+TZxWis9dttvPv+Tn21jjaW8zn
|
|
26bTG3mp1M/Wzv3t0jyWXiKZJmsTERaZhXXDbNl8WaztWenxZLstPp5pau8frDtVrNMM5cfTfpMf
|
|
3aunxxbes9d/R09Dp8ebJi09ptFr3jtt2WyrW9wy1Jx132mK+Xq9PotT0iIU19ntLtExa3T47T+q
|
|
6nBaYvsZstZ+cT/LeMnUi0TXffo1s2m8Ws2/OIMWk5Jib5L328rS2t94Sh5TV4ppklpW6PT6rh+P
|
|
NbebTHyas8E081mZy5P2W6OFhjxNTE/hr/LoRO0Kvo9dPqctKzMxEx1la5t3tdnjnMs4noievcrO
|
|
yZjeFF1OSnNV0OG62cn1GWffj7Mz5w05joovzY7xes7TE7w0xrjPeex6Ua+j1UarBFu1o6Wj0lsN
|
|
3JfQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACrU5o0+nvlt92P3BxuM6nxNRGCs+7Tv8
|
|
2hToxm1r3m9utrTvMsonqyt7XTmcja0u3O6FMfi5t/u0/lzdJM81p9O3zdvHTwsUR5+bfPqOfX1h
|
|
dqV+3O7bs1+T31oqmI3TEM4rvCdkDGIIhlFd2daboS0NXG2bD6bufxXU1vlmu/u4us/N0+L1tTSx
|
|
kr9qk7w89j1FNZMV3jxLzvaJ8mer+LSOZqK2xZotbvljfr/89U453rXt9lse081xZtNjx7TGKu0t
|
|
DHlrevSevaN5Y6+tJ8c7VRNMt63n3ub+6/R54rERMztDYy4a5omclYmfxKcenrjtHLvtPrCnVmdb
|
|
eFe3JXmjy6eS/DrMuLVYsta9Mdt++6qLxO+0dEc8UmInr18iUfReHcXrqccb9Z27Q61Lb13eJ9nc
|
|
1Z35rTvE9avY4bTkpG8xEfB05vYxqybc07R281naGMREdoT5JQqy9mply7Q3bV3iXG1eXw7TWSka
|
|
c258t7+tpT5/BjT7MfHqndz12Z+M4lMMKyziUJJiN1WSu9fku23RaOgKNJqbaTU1t9yelo+D0cTE
|
|
xEx1iXmM1Nt3W4PqvFweDaffx9vjDbGvxz+TP66QDRiAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAOJxzU73rp6z296zsZMkYsdr2naKxvLyObNOfNfJbvad1dXkaeOdpvsc2yuZVzfbfqybutwu
|
|
s5s8R92J3dvJb3tnO4HSMegtmt3nfZvYp8SZl0z45NfSK7onH1bNcfRFqnUKJr0Y7dVtq7prjEsK
|
|
0XVpEM6028mW20IHK41aPo3J6zs4ODhdcvPnvExFevNXpMOrxi/PlrTee7PLX6Pwa09uaNlKtHg9
|
|
dM3z5d7ReOu02nu0JzZMfblrv5R5uvrcdImZ26T1mYhxs1Os7RH93PZ7axuafNfLitvbaYU3yZYt
|
|
PXs9NwHhui1HBa5LVicsb81onrEuVqNNSuS8Y67dZ6xPZa59Il9uX41vEitImZme3q2Kxbxora0T
|
|
Md/ROSa4Ztkj7c9OafL5LuGYubmyX3iu/TfbdSfVnpvZLT/XZK233+Mbbva1xRXyiPk8pwbH4N6T
|
|
adq5a71n0tD1WDL4tPe6Xr0tDpz8YVnJHWEXYxbqlBedoef4tW0XraO09HdyztSZcbUz43C+ee9b
|
|
SVMaeOfqq7+jGckQ1Yz7+7v2RN/WXPXZPjci2+2yyJaVMuy+uSJlA2d+pNoVRbeDcSxyTE+TDDlt
|
|
pdRXLTynrHrDOyiyZeVFnY9TjvXJjres71tG8MnJ4Nqt4tp7T1jrV1nRL1x2cvABKAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAHJ49qfD09cNZ97JPX5PPw2uI6j6Vrsl/ux7tfk1mWr7dOM8iLdm
|
|
vfebREefRsWldw7SxqNbWbR7lPesrn3Vteo7dYjDpMGCvfbeXQ0uLlxRLRxROfUc34p6fCHYrXlr
|
|
EejqrjY8uzCYW7MZjdVKqK9VlaxCYrsnYExBMRMJRPZA8/xPHtmpP9W2xx76vhWOInvt/C7ike7N
|
|
vwzE9kcapGfhlevTaFbFo8RqJ5vy8/RoW09ek0msxHfp3dzNoLzp4zUmZpMbT8HJyYJi20X2n0lh
|
|
ZY1li/RaidBF4w2mK3jrHaFGp1lN+tptPp5IjBkid5mIp16TKu0abBPv33vPlM7z+iPdFNcWXU5I
|
|
tkrNce/b1W5db1nTaf3ax9q0fxDW1ebNk2phty1mOu09VOm8W19orEz23j1TwfSeERFuEYMddptW
|
|
d43dvBn21eKJ75KbW+cf/JcTgMxXTb3nbljz+TpcPmc2uyZO1KRtVtGVdi0bx07qJnllsRO6rNTe
|
|
N4XVamsy8mnvPwc3R2jPwe8TPbdlxXNOPSZfhWWpwO85OFzv57qrODkzeHntSe8Sn6Rv0a3EZ218
|
|
8nXekfr1a0ZLVnqx19dWb6demXybOO7lYMvNMdW9S/VVLo0us7tPHdtUtEwJiZU3jq2Jhham8CVG
|
|
PNODNTJXvWd3qcWSubFXJWd4tG8PK3pPd1OB6veLaa89Y61/u2xfxh5c/rsgNHOAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAANLimq+i6O0xPv392rdeZ4rq/pOqnlnelOkIt5F8Z7Wj27I2I6sb25YY
|
|
V1ImY3dbQ08LRc23vZp2j5OJG+XJWle9p2h6HHtbJXFT7OOIpX+7TxT31j5rycdTh+Dpz+XaG/sw
|
|
w18PHWseULN2trBE9UcrJKBhFU7JAQi0dEomegNDUYovM7x3jb5tO1ZvpbaTLtzRExWfWPJ08kbT
|
|
Ex5NXWYYyV5omYtHWJieyeDzuizfRs19Jn6TM7Ru1uMcJxZqTkw+5f4ebqa7SV1MR4tdrx2vEfy1
|
|
axqsNOTLjnLXytVXi3Xj8+nmsxTLM16d5npPyUzpekTtSK+U7vS6vQ/SYmK1vWPS1HOn2dvvvvE/
|
|
tDO5XlcO+LbfHSd/W3o6/BdDOXPTnj3Kz38rS6Wm4FNrRyRzTH3p6RH/AKvR8L4dXSzE3jmtHn5I
|
|
mbfqLV+m4dbLSsZInHjr3iI6zLpYaxS01rHuxHRHiT9mv6s67Vj1aqL6326MrWiYa+/Q54BxPaGe
|
|
XRZpj8MquB4+Xg8zPnB7SX30to379GxpK1xcHiKz5IS8xr8PLPixH2bftLTy05o6dHYyVjLhy0t1
|
|
izjZa3pMVv3iO/qz1G2L+NbSajbNyW7xLsY8kTDz+fJXFqKZN4iZnafi6WHL0iYlStI7OO+7axW2
|
|
crFl7dW9jvE9ULN+J3ZbdFGOy+AYWpEqN7afNXLj+1Wd23KrJVMvCzseh0+auow1yU7WhY4fCdV4
|
|
OadPefcvPuz6S7jol649Tl4AJVAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAV581NPhtkvO0R+4NPi2
|
|
r8DB4dJ9+/7Q83Po2NTqLanNbLfvPaPSFDHV66sZ5ET0hRknyW2lTtMyouz0c8usx2n7s7vScKwx
|
|
zc1vu/y85p+maJh6Th+SOWeveXR4/wDLm8v+nX5mUWa9bbrInolmu5jdTNkxYFk2Isr3TuCzeGMz
|
|
+THdEyDDJO9Ja823rt2XWnya946pGvktDXta0ztWu/ybvLE9dkcoOf4GbJPWK1j49VmLh9JtE33v
|
|
Mevb9G7WsW8l1ccREISophiJ2jpDYpijbaOjOuOJ8ujOdqxsgVcsUjaETYvbaFFrgu5lVsm0yUtu
|
|
ryg43H5m+GIj1XcJzePoL4pnrWGtxmfchr8JvfHS1622if3QljzTTLes+qrNjrkiYtCzPMxnm095
|
|
YZJ6boS5teB49Tqscza97VtvWvlv8V/FOF34RrIxTM2xXjelp/eHoeA6XnzReY3ivX/0dfivDcfE
|
|
9HbDbaLx1pb0lOs+jO7K8Lis3cN+0NKcd9PmthzV5clJ2mF9J9GHHVL108dm1SznYr/Ft0tuhLb8
|
|
mNohFbMhLWy0mJ3rPXvDvcO1karBG8/WV6Wj+7kWrvDDBlvpdRGSnbzj1hpjX4z8mOx6UYYstc2O
|
|
uSk71tG7Ns5AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACZ2jeXneJ62dVl5KT9VTt8Z9W9xbWclPo+O
|
|
fft9qfSHEU1pv48ftYST23ZTDC/p0YtlVuvVjMbM5+LCZjYGWGdrTPxiHY4ffaf3cjTxz1v6xMS6
|
|
Olty2iXVj/Dk8n+ndrkhnGRo1v8AFdW3RCrZ5uiYsqrboncSu508yjmZRYQt50TfowYTbYGVrKrT
|
|
uTZjvukQnYhMIGVY2ZxPVWyrHVCWzXpVXkt3TE7Va+W4K7X3jv1auTNy3jdba0RZpamfroQN7Hk3
|
|
6wr1GTaN2OOJiu6Mu98NvgDi8Wy74d/yZ8PiPAiO2zU4nb6qIn1bugjfFE/ASp1ke9u15mbbRDZ1
|
|
Mb823kx0Ontn1OOkedoJCvT8I03gaKsz9q/WW+isRWsVjtHRKyrhe0XCfpWL6Vgr9fjjrEfeh5fF
|
|
feH0V5Dj3DPoOo+k4a/U5J6xH3ZZ7z3228evytOk7NvFbo0cdols47bSybt7HbddHVqUs2aW3Qnq
|
|
xVeu8LILR3SlZw3V/R8nhXn6u0/pLuPMXjeHT4Zruf6jLPvR9mZ8/g1xrvpz+TH7HUAaMAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAABRq9VXSYJyW79qx6yvmdo3l5viGs+maqYrO+OnSvx+KLeLZz2te1rZL2v
|
|
ed7WneZYWnZl5K72YV1xEyxmeqJljzIEWlVkszvbZp5soN3h2SJz3pP3odCnuWmPRxuERfJrZmtZ
|
|
mtY96fR28kbX3dXj/wAuTyf6bmK+9YX1s0cNtm3Sd4LFY2K23W1s16StiUJW7bp22RW3RluBuruz
|
|
mWEgrmCGWyNkoExKE1QlPmsqRDKeyBjaejWy2W3ttDUyz1QKslvehVqKTNosyyTvELabXptIJpaP
|
|
B39Ia2mz+JGpr51jdZefDx2hzuHZObNq58poJaGtjxJ2+LoaKP8ADRPo5+T3skx5OhpOmC0fBNQ0
|
|
5yTbn+bt8A0u9raiY6RHLVwY62mI6zMvaaHBGn0mPHt1iN5+aYVsACBXqMFNTgviyxvW0bSsAeE1
|
|
mkvw7V2w5Ote9besJx2er4rw2nEdNNekZa9aW9JeQjnxZLYskTW9Z2mJY7zz26fHrrdpbZsY7NGt
|
|
mxjvso1b9NmUwpx33XRO4K7VUTE1nmrvEx1bVo2VWiJE/XY4frY1WPlt0y17x6/FuPM0m+HJGTHO
|
|
1qu9pNVXVYt46Xj7VfRtnXXL5MfzexsALsgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAHM4jxOMFJphmJv529Dq
|
|
ZLfjDjPEIx450+K3v2+1MeUOHSOWFc3nJkmZnf4yujpVlqunOeFpV2nctLCZUXRM7MJtsWlRkv3Q
|
|
ky5NmpWt9RnrixVm17TtEQnJabXisRMzPSIew9n+CRoccajURvqLx5/chfOest642OGcIpoOG2w7
|
|
ROW9d72+LQvXevyejcPUU5M+SvpLeOataraw2a0dLbLqTtK1G3Es4lVWWUSoldFtmcXUbpidgXzK
|
|
GEW3TuCUSncnsDFMMLSms9EC6J6FpVzbZE5ALy0809ZbFr9GtfrEoFMzuuwz0Ueey3HbaBLDXe7i
|
|
tMOfwWnP9I+NZbuttvhs1uBRtXPb4SDm3iIvf57N7Dbl0VrS5+XrltEd+Z1Jx7cNms9N4TURRw3T
|
|
+PrcO3WszEvZOD7P6aYiMlvu16S7y1QAIAABxOPcLnUY/pWCv1tI96I+9DtgmXl68Biy7/NtUu3+
|
|
O8HnFa2s0tfd75KR5fFyMWTdhrPHVnX9R0cd21S3Rzsdm1iuqs256wrmGcT0RYSx5d047X02SMmO
|
|
esd49YRE9WcdSXhZ2O1p89NRji9J+cei1xMc3wXi+KZj1j1dTTaqmor06WjvWW+ddcu8XK8BZmAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAMMmWmKu952UZ9XFZmuP3revlDTtzWnmvO8q3XGmfHb9ZanV3yxtWeWn7y4es
|
|
vPNtDqZJ6Ts5mppvdl/XXRMyfGvSNlu/RVvtOzLfoipLT1VTKbSpvfogRkvtDVyZOhkyvQcA4Dzz
|
|
XV6yvTvTHMfvK+c9U3rkW+zvA/D21urr789cdZ8vi9KDb45rejl8Rry6iJ/FV1HP4vXbBTJEfYt1
|
|
+UpiHM295bXsqrO9l8QkZ0lZEqqLeyBZHZLGvZkhIndADKJ3TMoqWQMZ6pjsxll2jsCLSrmU2lFY
|
|
36gieyu0LJk3jbsga0wdqzK20QpyztQGprL/AFMrOE05NLkt6qdVWZxNrSe5o9vWBLiUjnzXn0vL
|
|
q555dHt8HOwV928/1z/LpzXxbYccRvzTB+jucOwxh0dI22mY3ltIrHLWIjyjZKyoAAAAACJiJjaY
|
|
3iXleM8InR5J1GniZw2n3oj7s/8Ao9Wi9a3rNbRE1mNpifNFnVs65XhcWTdt47bnFuF24dm8TFEz
|
|
p7T0/pn0a+HJux1OOrOux08d1ndqY7tillVkzExLOk7yd4YxGwluViJhE45raL0na0dtlWO0+bZr
|
|
1TKi+2zptZGTamT3b/tLacvJjiY3XaTWdYxZZ6/dtPm1zrv1z78fPcbwC7EAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABhkyV
|
|
xUm152iAZWtFazNp2iGhm1Vss8uP3aevnKrNntqLdelI7VRHRnrX/HRjx/tZREVjZXeybW6KbWZt
|
|
pCZ6S08tN7Nmbb7zCrJtyoS5145bSx5mWafelr3tsKmS/o08uXyhlly7RPV2+AcBnPNdZrK+53pS
|
|
fP4ytnPVda4y4BwHxOXV6uvu96Unz+MvVxG0bQRG0bR2G0nHLb2gCUDX12LxtFmpHeazt82wT1gH
|
|
mMN4tWs+rcr2aEV8DU5sM/cvO3yb+O0csLUTSdrLphRE8tlkZI7Atr2ZMazDJVKTYSCawi7Ksq7z
|
|
1QERvLK3ZGPrKbyCrbdnMcsbeaa18/RhvvM7oGEwTG0JmYYTIML22a2e28xELM19oURPNO4lOem+
|
|
n3ZY5+prVnMc2GYU4/L4A0a15cNf6rz/AC6fC6+NxCPOuOu/5tHJTbHj+F5/l1+BYumXJMd9o3/d
|
|
MRXYASgAAAAAAABhlxUz4rY8lYtS0bTEvH8R4ffhmo6bzhtPu29Pg9mq1Gnx6rDbFmrzVsizq2df
|
|
zXkMWTeIbNL7tbXaHLwzUctvexWn3bmPL8WFnHVL326VZ91MfFVjvvVlz79kLrcf2m7j7bNHH3bl
|
|
J2SirLQoy4t1++7G0dBC/RanxI8PJPv18/WG241+alovSdrV6w6mDNGfFF4/OPSW2b1zeTPL1aAs
|
|
zAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAVZ9RXBTe3WZ7R6iZOpzZq4ac1p+UermZMl89+a/byj0Ra9815ted59PQ32hlrXXRjH
|
|
DpCLX6ML5NlNsm/ZRqstfdXzbsZt06sLZNvNB1Za8RDWyZdo7q8udq5Mu/mIMt4md2lmy7JzZuWJ
|
|
dHgfBL8RvGo1MTXTxPSPx/8AstJ1XWpIs4BwSdbeNVqq/URPu0n73/s9hEREbRG0QUpWlYrWIisR
|
|
tER5JbSccur2gCUAAAAPM8Sry8Uyz67fwuxbzVPGsE49XGbvF42V4M0TEL33ERnktsxpk3sumK2j
|
|
admFdPFZ33VS2Mdui2J3UU6LYlFSsN2O5NkCyJ6K7T1TEsbAsxdpReerKkTFGMxvYEz0rsqtbbpC
|
|
b2VT1QEzuwtbaGUxspuJU3neWdKoiu8rq12gCI92YatLcublnzbEz1aOptyZqTuDHLfxN6R0+t5X
|
|
qdJhjBp6UiPLeXl9NSMnEKxHa1+bb8nrlvxUAAAAAAAAAAABTqtNj1eC2LLXeto/R43VabJw/VTh
|
|
ydY+7b1h7ho8V4dXiGlmvbJXrS3xRZ1fGv5rzeHN02bEW3cys3xZJx5ImtqztMS3MeTeGFjqlb2O
|
|
8btql3NpbZtYsnSBLeiWfdTjtutid+ghherHS5p0+f3vsX6T8Fkw181d4lMvEWdnHaGnw/UeNh5L
|
|
T7+PpPxbjdyWcvAAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAo1Oprgr63ntAmTqdRqK4K9etp7Q5d7Wy2m953lNrWyWm953mVd77R0
|
|
Za1104xxlN9lV8qnJl2a9s3xUXX2ybsJyRDWtl3YWydEC+2VRkzeW6q+T4tbJm+KRdfK1cmWZnlr
|
|
vNp7RC/R6HU8SycmCk7ed57Q9ZwvgOn4fEXtHi5/O9o7fJaZ6z1uRyOEezVstq6jiEbV71xevzer
|
|
rWtKxWsRFY6REeSRrJxz22gCUAAAAAANbX6aNVpL0npMRvWfSXlKamsRMVvXm+EvZXjmpaPWHzfL
|
|
oNRjzXicfWJ8phfPxFejx72x7xMzK+sXiNoiXlq+Pi6fWV/VfTNqfLJl/WTg9Pji8R70LqvMV1Gq
|
|
j/zcv6yz+lanzzZP1lWpelTET6S81Gp1P/Gyf90s412rjtnyfqql6asREdWM9+jz9eJ6yP8Az7uh
|
|
odZqMt458tpB1JvEViI3/RhzRt13/R1MNaziiZiJn5K9ZNceKZiIiQcu/WekT+iYrWI3lzdTrs+8
|
|
8uW0fJzcur1Np/zsn6g79phVaIeetqNR/wAXJ/3SwnUaj/i5P+6UD0ldonum161h5mNRqP8Ai5P1
|
|
lNtRqJjacuT9Qd22WN5aGeZyZd/KHJy59RHbLf8AVq31Gp/4uT9ZEvS8Lr/vSs2npzRtL1z53wK+
|
|
oza/HW2XJNd99pmX0Rb8VAAAAAAAAAAAAAAcHj/C5yV+l4I9+v24jzj1cLFk8nu5jeNpeW41wmdL
|
|
knU6ev1Vp96sfdn/ANFdTrXG+eq1q5F2LLtbZoY8m8d11bbSydErsYsm+zZrO/zcnBm226uhiyRK
|
|
EtrvCrJDOJTeu8A1MWX6Lqq5N/dnpb5O5ExMbx2cPNTeJb/DM/iYPDtPvY+nzhri/jDy5/W6AuwA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAa2p1UYo5adbz+xbxMlvqJ1OqjDHLXree0ejmzNrWm953tPmTPWbWneZ7yoy5YhjrXXTjH8s75N
|
|
mtkyxt0VZM2/m175N1V03yTKubMLXVXybeYLLX2VXy7eam+b0bOg4VquJW+rry4/O9uyZOq3UjVm
|
|
9r25axMzPaIdvhns1kzbZddM0p5Y47z8/R2+HcF03Doi1a8+Xzvbv+TotJnjDXkt+K8ODHp8cY8N
|
|
IpSO0RCwF2YAAAAAAAAACvUZYw6fJkntWN3k8dfHz2vLucdz8mkjFE9bz1+UOZosX1UzPm0nqI/W
|
|
MYo9FlcPNklfFGeH/NshLGun+Cz6PtHZtVZWlRLS+jxPkRpIn7rdoupHTdA5s6SI+7H6Mfo+32Y2
|
|
+To3neSIiZ7A0IjPXpXLePlMotGW3272t85datKzHZjbTVnsDj+FG/2Y/RlGP4R+jo20u7H6N1Ql
|
|
o+H8I/REY957R+jpfReiK6eOYHLtj2tttH6KrY/6Y/R2c+kjeJiFVtLG24hxpw7/AHY/RRkw9O37
|
|
O99Hrt1YX0tfOBLjcGp4XF8c+u8fs9c4dcVcGemSI61nd3IneN1orQAAAAAAAAAAAAABFqxes1tE
|
|
TE9JiUgPKcX4RbRXnNgiZwWnrH4XPi28PdXpW9JraImsxtMS8pxXhF9DecuGJtgmf+1TWW2N/la1
|
|
L7N7T5e3Vy6W3hsYcvLbqzbO9jvvCzvDR0+XeO7crO6FmGSvRThy/RtVXJ92elvk2rRvDUzU7pl4
|
|
izsd2J3jeBpcNz+Lg5LT7+Pp+Xk3W7js5eAAgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADs0NTrN96Yp6edkW8Wzm6+LNTq4pvTHO9vOfRoWtt
|
|
1mes95YWvs1s2fZldddOczLPLn2ju0MmebT3YZc2/mpm3qqllN1drsbZIhr3yzvtHf4AsvlYYseb
|
|
V5Yx4KTe0+UQ6nDvZ3UazbJqd8OKeu33peq0eh0+hxcmnxxWPOfOfm0mP+steT/ji8N9mKY9suum
|
|
L37+HHaPm9DSlaVitKxWsdohI0Y22gAgAAAAAAAAAABXnyRhw3yT92Nwef4xm8bVzET0rPJH5d12
|
|
CvLhho3rN9RWs9Z23n5y6O21YhrVYbdGOCfrrLPJRpv863zVS6FS09SvZj3lVZZRdPSqmnSWdrIE
|
|
ebOkK4ldTsgW1WKqd1oMZhEVZyRAImOjGI6rJ7IiATNd46qL02bHkiaxaoNGY2n4ImPgtyV2n0Vo
|
|
Gvlx7x2beiyTk08RPevSVUxux00+Fn2n7N+n5rRFb4AAAAAAAAAAAAAAACLVres1tETWekxKQHlu
|
|
L8InR2nPp43wz3j8P/s5dLveWrFqzW0bxPeJeV4xwmdFec+CJnDM9Y/CrY1xv8qvTZ+WYdbDk5oh
|
|
5zHk283U0eo3jaZZ2N5XYjrCnLSJhOK+8d1kxvCqzSwZvousrb7k9LfJ3nB1OLeJdLhufx9LEWn3
|
|
6e7LXN9Ofy5/W4AuxAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAETaKxMzO0Qi9646Ta07RDmZ9VbPbaOlI7Qi3i+c3TPUaqcu9adKfy0722ZXvFa9
|
|
XO1OrjrESxt66ZJmcjPUanlidmhkzTZVfLN5VWvsC2b7R3U3yqrZZtO1esz2h2+F+zWTUcuXXTNM
|
|
feKR3n5+iZLVbqRzNJo9TxHLyaekz62ntD1fDOA6fQbZL7Zc/wCKY6R8odLBgxabFGPDSKUjyiFj
|
|
SZkYa3aALKAAAAAAAAAAAAAADQ4pl2pTFH3p3n5Q33E12Tn1eSfKscsLZ+orS00eJqbW+Lfnu1tF
|
|
XaJnZsz3WpCfsyp00fWSvmPdVYOmSUDd8kR3InoQosy7JmUX7MdwZ17ro7KKT1XRPRAsrO0rYndr
|
|
79V1ZBaQiJ6JgCSIJASwrO07MpV2nqBlrv1a1o2bf2qtfLXaQUTO0sb05o3jv3ZXhjS20xEphW5h
|
|
yeJjjf7UdJWNKLziyRePsz0lux1SgAQAAAAAAAAAAAAAADG9K5KTS8Rato2mJZAPIcU4ZbQZuekT
|
|
OC3afT4NXFkmlntc2GmoxWx5K71tG0vHa/RX0GpmlutJ61t6wrY2xr8dXS5uesN+tt4ef0eaa223
|
|
2dnHk3juyreM81OaFGiy/RtZET9jJ7s/2bdutd2jqKeic3iNTsd8a2h1H0jTVtP2o6W+bZbOO+gA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABje9cdJt
|
|
adohGTLXFTmvO0fy52bJfU23t0pHaqLeL5xdK9Rnvqb+cUjtCi94xxvK3JetKuHrdZvaa1ljb10y
|
|
cnIs1Wt3naJc++TmVWvMz1YWybfMGdsm3eWek0mo4jm8PT0mfW3lDf4V7P5tdMZdRviwfvZ6/TaX
|
|
DpMMYsFIpWPTzXmf+steT8jn8L4Dp+HxF77Zc/4pjpHydYGjC3oAAAAAAAAAAAAAAAAADG9opS1p
|
|
7RG7zszN6WtPe0zLua+3Joss/wBOzhzG2OsL5+IrY09dsSyYRijbHEMvOChb7KjF0yS2LQ169Mso
|
|
S24noyrPVXWejNVKbTuw3T3REdQWU6LYlVvsyiUDPfqupPRr79VuOQX1lZEqoZxIMksd0gT2VT0l
|
|
bPZVbuCaW8i8bwr32WxbcGnkjaZa9p2ndv5qbw5+aNugLItF6TEtvTX5sMb969HMpfazc0d9stqe
|
|
vVZDdAQAAAAAAAAAAAAAAAADV1+iprtPOO/2u9bektoB4TJTJpNRbHkja1Z6uto8viVht+0HDvpG
|
|
H6Tjj6zHHvbecONw7Ltfkmeqmo6Ma69DXbbZTkr1mGWO3RneOaGbZRoM30fVzSelMnT83aef1FZ7
|
|
x3h1tBqfpGnjmn369LNc3sc3kzy9bQCzIAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAa+q1dNNXr7157VhGp1Xh70x+9f9ocy283m1p5rz3mVbrjXHjt91lz
|
|
5c9+fJ1nyjyhdM8lZlOOIiqrUXikd+kMreunnI5XEdX4dZiZcG+XmtNl/F83PeeWWHDOGanieSKY
|
|
q+5H2rz2hMzWd1Iqx1yajJXHhrNrW6REeb1nCPZumn2z62Ivl7xTyr/6uhwzhGn4Zj2xxzZJ+1kn
|
|
vLoNJnjHW7TbbsAszAAAAAAAAAAAAAAAAAAAAaPFrbaSK/itEOXt0rDf4xb/ACa/GZacRvaF58Q2
|
|
IjasQnzPIhCU92tMbZGzHmotG10C6nZkwpPRmipIllEbMIZIE7solgmJBnCyk9VMM6z1BtVllEqK
|
|
z0WRILYlluriWcSDJVbusV27gwInaSWM9ECyZ3hqamnSWxFmOSOaqRx725bNnSZNs9J+OynVY+WZ
|
|
YYr7TE+nVaIr0Ais81Yn1hKAAAAAAAAAAAAAAAAAABExvG09peU4nov9n66L0j6q/WPg9Y1OJaON
|
|
ZpL0+9HWs/EWzeVz9PbmrEtnyc3h9reHy26TWdnSr2YX6657ijLXpLX0+onSamL/AHJ6W+Tbv2aW
|
|
ekTv16JzeI1Ox6KJiYiY7Slz+E6jxdN4dp3vj6fl5Og2clnKACAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACZ2jeQRMxEbzO0Q08uqtkma4ulfO3r8lefUePMxWf
|
|
cjy9WvlzVxV6T1Z61/x0Y8f7Wc7Ur1lqVy+LqOWJ2hp6rXddon5rOF1tfmz5OkT0qzb8dWbxjp1c
|
|
biuuilJ5Z6r+IcQrixzEy8zl1E6rNt1tMztFY81sztU1eRucN4ffi2p5esRM72n0h7rS6XFo8FcO
|
|
CkVpX082nwXh3+z9FWLxHi36328vg6TZyW9ABAAAAAAAAAAAAAAAAAAAAAADj8Unm1tK/hqppHvw
|
|
y1k8/EMk+m0GOPeafiFpCZYwolnXspvHvLa9mF46gmnZmwozRUiUCBKYYsoBLOFbKAX0llEqqyzi
|
|
QXRLOJVRLOOwLIljZMEgrlhKyYYTAK5nZPN0RZjugUanHzVlz6xtLq361c+9eXItPpXX0dubTU+E
|
|
bL2lw2++O1fSW6m/VYAISAAAAAAAAAAAAAAAAAp1GbwcfTreelYEydcuMcRrM/L9nnlsV6wqpi2r
|
|
tv133mfWVkRyRtEdGFva7MzkYZNoamWN4bV4mYa9qztKIujhVppxGI8r1mJegeZpknBqKZY+7L0t
|
|
LRekWrO8TG8Ns/HJ5ZypAWZAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAADS12fp4VJ6z9qVuq1HgUiI+3bpDl589cOKZmevqprXPTbx477rDJlrhr1nq4+s182tMRP
|
|
RqaziXiZJrWekNG17ZbxWJ336M5LXRbI3dLTJrs07RMY6fan1dHLrowY+X7MVjt6N3R6Kul0EbWm
|
|
s7bz8Z+LnabQX43r7Y53php/mXj+Dnv0f1JO1x/8ZxbUzj02O15mfLtD13AvZqnDds+pmMmo26el
|
|
XX0Wh0/D8EYtNjilY7+s/NstpOOTW7QBKgAAAAAAAAAAAAAAAAAAAAAADG88tLW9I3BwJtz6nNf1
|
|
vK/DHVqYJ3pzT5y3MPZeojOWMQylEKpTVjZnDCwkqzYQyRRICATCITAJZQxhMAshnEq4ZQC2srKq
|
|
qrIBZCWNZZgwswmFloVyCu0dFcx1WyrtCBhv5NTPHXds2U5o3hIz4ffbPt+KHUcTSW5c9Jme0u2v
|
|
VYAKpAAAAAAAAAAAAAAAAYZctcVOa35R6tLrltN795/YvknNqrfhpPLH92V5isd9mWq6fHjk6rn0
|
|
ZxG8KK5Jm/wbVZiYZtqrmkqL023bkxvCiY3lJHNyRG81mHS4Rn5sNsNp64+3yaWaNrzOzHBl+i6q
|
|
mT7s9J+S+ay8mex6EIneN47SNXKAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAImYiJme0JafEs3h6fkidrZOn5eaLeJk7eOdm1Hi2vmtPTry/CHmOJcUvmvOPF1n09Pm
|
|
6HF9ZGm01qxO3R5vSY7XwzmzTy47zzTEd7en5Mfvt2/PURWdo3tvPrPlKymbktFqTtMTvHzbOLDG
|
|
f63JXbFX7FdnoODcDprZpq9TjiMMTvSn4vj8l5fxnrk91saPSa7i2hpOfbTVt5x1m0fLydzR6PDo
|
|
dPGHBXasd585n1lsRERG0dIF5OOe6tAEqgAAAAAAAAAAAAAAAAAAAAAAADX11+TRZrf0y2Gjxe22
|
|
gtH4piP3TPpXKwxtjhuYo9xq442iIblI2pC1RET2ILd9kxCqRjZmwlCSEohIJAQAAJZISDKGUd2M
|
|
MoBnVbVVCyAWVWeSuqyOwIlXZZKue4MJV2WWYT2QKbKL9YlfdRdIo35b7/Hd3KTzUrPrDh27uxpb
|
|
c2mpPwX/ABX9XAKpAAAAAAAAAAAAAACekTIp1eTwtJmv+GkyJn1oafeazbfpMzLR4jq/o8b823zX
|
|
6XNF8ERCvTcNpxLV5LauvPhx9Irv3lhztdtv8TtaWLicXrt03jzjzb2k1nid56ty3s/w+a7Uwzjn
|
|
1raejlarhmbhl/FpbxMO/fzj5p/ixSeXOvTtRfeI280ZI26tfDm3pWe63LaZx7qtGvniJ6tPLvOK
|
|
fOa9WzbJvTbza02jl3n5SSljscK1MajSxWZ96nSW88xw/VfQ9XMT9nfa3yemid43jtLeXsce88qQ
|
|
EqAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADia3UTm1l4j7OP3Y/u
|
|
7Vp2rM+kPJW1PhYcmS0+9MzKm/jbwz31weMzbV8UppazPL9q0/BF4rk1GLDSNqxPWPhCnHmnNrtT
|
|
qPKteWPm6U6OdHaZvO+SaRNvhv12Ub/q3FhtrNVj0uKOt56z6R5y9zix1w4qY6RtWsREOJ7L6OKa
|
|
S2rvX6zNM7T6Vh3mmZyOfya7eACzIAAAAAAAAAAAAAAAAAAAAAAAAAAczjVvqMVfW/8AZ03I41bf
|
|
Lp6/OVs/UVrY47NyOzUxd4bUJpEbb3Z7IiOrKIVSjZhMLJYyhKIgmGUQSDESIEbJEgQmCITEAmGU
|
|
IiGUAyhZVhDOoM4Wx2VQtqBKuyyWEgqlhKyyuyBVaGtkbNmvk7A15l1eH2300R6TMORPSXT4ZO+O
|
|
8fFefEX63gEAAAAAAAAAAAAAAAq1WPxdLlp+Kkx+y1Fvsz8gjhaDauGK8sx07y3OE3m1tT6RaP4c
|
|
vU6yMNKUx73zT0ilY3l2eF6a+m0kRl/zbzz3+Ez5M8z26fJruW6wzYq5sV8d43raNpZjRzPPaTmx
|
|
5b6bJ9rHO3zb2WJ8GWPEscY9bgzxH2t62n19GWW0eHOzHU5XbjXZ1x8WTnz2iZ7S2M1IjH2+LX0V
|
|
KTqs8zO9ot0j8nUthi1J3UaOFMTfLFo6xMbS9BwHWTqdHOO8+/hnln5eTjYMFo1WTH5VnePzXcIm
|
|
2k4zlpPSmXy/hfF5eMfJns69OA2cgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAADG/2LfJ874rW845mubliY7bPoto5qzHrDz0+yePNF41OotaJ7RWNtpV1OtfHqZ715fhu
|
|
j8adNpcVfeyzE2/vLuanhOu1nEctIxTTFa/+ZPbZ3eHcF0vDbTfFE2yzG03t32+DokynXl9+leDB
|
|
TTYKYccbUpWIhYCzEAAAAAAAAAAAAAAAAAAAAAAAAAAAAcXjE/4zDH9M/wAu04XF5/3jj/0f3Wz9
|
|
RUYmzDWxS2I7FSyjuzY1ZKpRKEygEwiWUIkGIk2QJNhKQhMIhkCYZQxhlAMoZwwZwgWQshVCyATL
|
|
CWc9ldpBhZXLOVdpQK7NfJPRdaWvknoDVvPvOnwuel4+TlXn3nS4VPvXj4QtEV0wAAAAAAAAAAAA
|
|
AAAAAVV02CmTxK4qRf8AFFeq0AAAanEsfPpZmO9Ji0NDLfkwdOsulrumiyzHlVzJrz4Ovoy26vB8
|
|
cTBa9NffLtMY77Rv8Yegx5ImkKdJoY1HC81Y+3OSbVn0mGGkmbY45u6tnrrTOu2xGO0RxCd+nNVj
|
|
qKxTV1vH2pjaGtnyzXXYdo96ZmGXEMk15b7/AGZiVerWPTYckZcNbx5wzc7hGbnxXxzPWk7x8pdF
|
|
0S9jh1OXgAlUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAcPjEf4/FP9H93ccXjMf4vDP9Mx+62fqKrx+S+GvibEFSsqyYwlVK
|
|
ZYsmIMoRKYJQIPIEiQ2ATCUQygCGUIhMAyhnDCGUIFkLIV1ZxIMpVWWSrsCuyqyyyq09ECq8tfJK
|
|
66jJ2Bp5J6upwn7dv9Lk5J951uE/av8AJaIrqAAAAAAAAAAAAAAAAAAAAAAq1Mc2myxPnWf4cmtu
|
|
XT9fR0tffk0WSe28bfq5Wbamm3326MtunwfK6PCv/AxPraZ/dz9PO97/AOqf5dHhdZrw7Dv3mOb9
|
|
XOxRFM+avpe38mvkPHf/AFWlrKba7Tzt99ZxKkfR7euyNXMTrtPHfa0z+zPiM/UR8Zj+Wbdu8HpN
|
|
M2bfzrV13M4dO2pyR61dNvj44/J/oAWZgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADj8bj63BPzdhyeNx0wz8ZWz9RWri7Nmv
|
|
VrYu0NmqaRZHZlDGGSiwxZSgCEkCBCQSCQBMJRCYgEsoYx3Z17AlMIhlCBnDOGEM4AlhZZKq4KrK
|
|
7LLKrIFN2vdfZReAaObu6/CO9vk5OePR1uEd7fJeIrqAIAAAAAAAAAAAAAAAAAAAAGtxCk5NFliI
|
|
3mI32+XVyNTyZOHTee946PQKPoeDffw4777eW/yVs60xv+ZxOnr4Okx1t05KRv8Ao41Z5q3yed5m
|
|
XY1szXRZ5jvFJ/hxItP0aOSN9q7yrtr4f2tHFM5+KT16Yq/vK/iGSbXw4vO14UcPx5MGfNbPG18m
|
|
1oj4THRsTw7VanPXVYpi3gzMcnrvCnG11JOupwuN8+a3pEQ6jT4divjxWnJExa09pbjbM5HHu90A
|
|
JUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAHM41H1GOf6nTc/jEf4Ws+lls/UX45uGekNujTwdm5RNIthKIZKLDFlsiQIShIC
|
|
EgCUJ7AmGTGO7IDzZQhMSDJMMYZQgZwzhhDOATuqssmVdgVWVWWyqtCBTeVF19lF+wNLNG7q8I+9
|
|
8nLyupwnt+S8RXUAQAAAAAAAAAAAAAAAAAAAAAAItWL1mto3iY2lyrcLyUxzix2ia2nvPeK+jrCL
|
|
OrTVnxpanhuPPemSs8l6RtE7dJj0ldpNP9GwRSZ3neZmV4cR/Vs4AJQAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAANHi1d9H
|
|
M+kt5ra+vPoskfDdOfqK4mn7Q3aNHBPZu0W0RdDOGFWcKLCJZeTGQQlCQSgASBsCYZQxhlAJTAmA
|
|
TsmAgGcM4YQyjsgRLC3VnaVcgwsrt3Z2V2QK7tbJ1bN5a9waeWO7p8Knt8nNyebpcK8vkvlFdQBA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAK9RXmwZI+ErEWjesx6wQeZwejeo0cccuW8
|
|
elpblJaaRGxVnCuss4ZrMvJEgCAASISCQIBlCYYpieoM0wx8k7gzIRueYM4Z79FcSy3QEsLJmWFp
|
|
BjaVVpZWlXMoGNmvkXXlr3kGtknu6XCf7OXkl1OEdl8orqgIAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAHmskcmtzV/rls0U62OXiWX4zErcc9GmkRfWVkSqqziWayxCPIANwBIhIJSxS
|
|
CRG6dwZwlhEs4BluMdzfqgZxLLdXuy3AmVdpZTKuZBjaVVpWWV2QlhZRdfZRcGpl7urwfrzfJy8r
|
|
rcH61vPyWitdMAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAHA4nHLxKZ9awnH2ZcY
|
|
jbW459aq8fZpfiI2IZwrqzhmsz3Ebm4JN0AMhCQSIASndiAziWUSriWcAyRujc80DM3RCfIETLCW
|
|
UsZEsJYSslXZAwlTddPZTkBp5e7r8Gj6rJPxhx8k9Xa4PG2C8/FaK10QAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAcfjcbZMFvnDWx9m5x2PqcNvS+zSxT7sNPxH62YZQwqzhRZO6UCB
|
|
KUAJTux3SDIRuAncQAmJZRLBMSgZ7iIAZRKd2DICUSlAljLCYWMLIFVukNfI2bNbIDTyT7zu8Ijb
|
|
Sz/qcG/2nf4T/wCE/wD2WnxWt4AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAHL9oL
|
|
+Hw2cm28VvEuPptfgyVj6yIn0no7/FtJfW8NzYMe3PaPd39d3iMug1WktNc2C9dvPbeP1aZ9xF+v
|
|
T471tHu2iflK2HkqWmvaZj5Surqc9Ps5bx+alTHqYHm68S1Vf/NmfnC2vGNTXvyT84Ql6A3cSvHM
|
|
sfaxVn5Ssrxyv3sM/lKB1xza8bwT3pePyWV4tpZ+/MfOEjfGrXiGlt2zV/PotrqcN/s5aT/+wLRj
|
|
FontMSlAlKEgndO6IAZQljDIEgeQljLCzOVdkCu/SGrkbF56NPNeKxMzMRHxENe0+89DwuNtHHzl
|
|
5PJr8NcnLW3Pbf7r1nCZm2gpae8zMrz4i/W6AgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAETETG0xukB4HVaeMHEtRi26RedvkyjBSfX9W77QYvC4xz7dMlYlrU7M929dWJLFc6aPK0q
|
|
7YLxPS0S22FlP6q38Zac0yR92s/KVc3tHfFf8tpbcsLRvB/dR/8ALLVnU0r9uL1+dZI1mnmdvGpv
|
|
6TOy6ym+Oto2tWJ+cJ/tW+KLK5KW+zes/KU7tG+h01p64qx8Y6NXNo6Y+uPJlp8rLf0rfG7MXtHa
|
|
0x8pZxqs9e2a8f8A7Oj7HaTHn0+f6RWM23LETfr6vRW4PoL99NT8ui7F4+vEdXXtnt+fVbXjGsr/
|
|
AOZE/OsPS29nuH27YrV+VpeV9pdPXhOtw49NG9Mld55+vXcTPd42I47qo7xSfyWV9oM8d8VJ/VxM
|
|
d8l46xWF9cV7en6o/qLfxp2I9ob+eCv/AHMo9op89P8A/wBORGmyT5R+qfo2X8P7n9Q/jTsx7RR5
|
|
6ef+4/8AuHftg/8A6cWcOSO9J/WEbWr3pY7Efzp2Lcfv5YK/9zWy8d1E/ZpSv5Oba1/+Hb9lc+LP
|
|
bFt87I7E/wAabWbiurvEx4nL/pjZzc2bJkn372t85ZXx55/BX85lucC0vPxnTxlnnjm32mOiZqUu
|
|
LJ2p4TwnVavNWaYbRTfre0bQ99pcH0bT0xb78vmtiIiNojaErMwAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAHnfarF7umzRHaZrLjYrdIen9ocPi8JyTt1xzF4eUw23rCm3R4r6bMy
|
|
wt6kdTaWLdjswmNoZontsCm0K5XWjopnuDC0dGpqG5bs08/daKV672MjbSaif6oh6Z5f2LtvptRX
|
|
0tEvUN3Jfo8f7cYve0eX4zV7B5z20xc/C8eSPuZIRficfXlcPaG7ino08HWIbePpLF2NuiyOyrHK
|
|
3fZFSwuovHVfaVF4QK5YWTM9UT0EKry6Ps1Tn4zjn8NZn9nOtLseydObiWW34cf918fWfk+PYANn
|
|
KAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAq1WKM+ly4p+/WYeBxTNd6zG0xO0
|
|
vobw3FcP0bi2em20Tbmj5Srr418V9sa2Z7qKyzi07MXUylhaU7yjqhLCeiq3ddaFNxFYW7NLNG8t
|
|
zya+WO6Va9J7FW66mvwidnrXiPY3Ny8RyUn71Jj9Ht3RPjk19HK9pMHj8D1ER3rHN+jqqtTjjNps
|
|
uOe16zAifXzfTz7kNyndpYazS9qT0mszDdoxrsi6m8LazMq6zDOsq1ZEyrt1WWlXaUCqyq0rbKbi
|
|
Fdp6PReyFd8uqv8ACsfy83aXrPZHHto89/xX2/SP/dpj6y8vx6EBq5gAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAB5n2q03LfDqqx39y39npmlxbS/TOG5se29tuavzgWzeV4mtui2
|
|
O3RRSY2hdVhqO2MvI36iu9lUsrSrvDHn6spnmSiq5jooyV6tq1VV69RC32byTh43h8otMx+r6I+Z
|
|
aK/g8TwX7bXh9Mid4iW+fjl8n1ICWb57xLBOm4zqse20Tbmj8+qKdnS9q8PhcTw5tumSm0/OHMxz
|
|
0Za+uzx3sX1t0Zxurr1ZxvspWiZYWZbsbT0QK7KLrZVZJFaqt5vbezNOTg9J/FaZeJns93wCvLwb
|
|
T/GJn92uGHldIBowAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADuAPA67F9H4l
|
|
qMW20VvO3yRWW97T4fC4rXJHSMtI/WGhVlue3b473K2KzMML4+62tujG9pnozXaOSOVFMnVbmq1t
|
|
trJRW5E7wwvUxTvCyY6CHOt7moxz6Wh9PxTzYaT61h8x1MbZK/OH0zTf+Fxf6I/htj45vL9WgLMn
|
|
mvbPFvocGWO9L7fq85p5maw9d7VYvE4JkmPu2if3eW0+PasdFNOnxfF1Y2hlykRsmY+LJ0MZjZXa
|
|
eq2eyi8oQTO0KLdZWzPRjWu6VaqtHR73g0bcI0sf0Q8Nkq93wqNuFaWP+XDTDDytwBowAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAef9q8HNpcGaI60vtPyl56k9Iew49j8ThGe
|
|
PwxFv0l4zH2U26fDfTYiyJljvsjf4sm6vJ1hrXjq2MkqLdZEVbgbMx0auGdmzNt6iHN1Ub5af6of
|
|
TdPG2nxx6Vj+HzaaTm1+nx/iyVj930ysbViPRrj45vL9SAuyc7j1efguqj+jd4/T33rD3HEcPj8O
|
|
1GP8WOY/Z4TTT7sKadHhbcsZnaCJ3TPZk6VdrKbTutmP0U2nqgrGOsr8deiuI2X09EqKM1dt3uuG
|
|
f/jdN/06/wAPE546S9rwud+Gaaf+XH8NMMPK2wGjAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAABrcRp4nDtRWPPHP8PCYusPoWSvNjtX1iYfPuWaXtX8MzCuvjfw32siu8ptXoxi
|
|
0wy5t4YulReqmazu2skbquURWFInddM7VYRGyL291KFnCcfj8e0le/Lbmn8n0N4b2Ur4nHLWmPsY
|
|
5e5a5+OXyXugBZmiY3iY9Xz7NjnTa3Ph/BeYj5PoTxftFg8Hjk2iOmWkW/Psrr418V5WrWd2faFc
|
|
V2jdnEMXWxntupmN7NiYU27iWML6dVMVnddjgVqMsdHr+CW5uE6f4Rt+7yuSsTDv+zWXn0WTHP3L
|
|
/tK+GHl+O0A1c4AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA8Dn93W56/wDM
|
|
t/L3z59qp24jn+OS38lnpr4r7ZxHQ2TEstt3PXUrt27K57rr1VT0BjKnJPRbMqMs7QlV2fYvHvrd
|
|
VknyrEfu9m8f7FZI8fVU85iJewbT45NfQBKo817W4eulzxHaZrL0rje09ItwqbfhtBVs3leai8RD
|
|
KLw1sduesL606dWFdsZT1jdhNeq6K9DlhCVUU6s4jZnt1YzAhnM71dH2bycmszY/K1d/0c6OzY4R
|
|
fwuK4p8rTstn6z8k7HrwGzkAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAHz3
|
|
Vxvr80/8y38voTwGpj/F5/8AqT/JfjTx/WVeyY6FPspc9dZPVXaOq2WEwIUTVRmjo2rNfLHRI3vZ
|
|
DJycXtX8dZh7t879nsnhcbwz23tt+r6I2nxyb+gCVBzuPY/E4PqI9K7ui19fTxNBnp60n+Aj5/pJ
|
|
3jZu1aOnnltMNussdfXbm+l3ZM9URHREdZVXTuT1Nk7boQiOkJw28PU47/htEp5eivJPLMTCZ9Vv
|
|
x7mJ3iJ9UqNHk8XR4b+tIXuhxAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAD
|
|
weqjbWZ4/wCZP8vePCaz/wDIaiP+Zb+UX408f0r9lOxWOifJhXWjfyYWllPRXYQxnrCrJHRd3YZI
|
|
6A1NJecHEsN/S0T+76bE7xE+r5dk93LW3pL6ZpMni6PDf8VIn9m2fjm8s9rgFmQxvHNS0esbMiew
|
|
PnHLyai9fS0w2aNfUTtrs3+uf5bGPqy068fF227KtSsdFlKqNGMV6myyY6sbdIQI8tlOWOi6Jhhk
|
|
j3RD0vA8nicMx9etZmHRcT2Zyb6XNT8N9/2dt0T449T2AJVAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAHhdfG3E9TH9cvdPEcXjk4zqI/q3L8aeP6xr2TsxpLOekMK6mFo6qpXSrm
|
|
OqBixvHSVmzC4OfqK7S9/wAByeLwbTW9K7fo8Fqo6Paeyl+fglI/Da0NcMPK7QC7AAB8313TiOf/
|
|
AKk/y2MHWrX4jG3E9R/1Lfyv0/aFNOrHxuU7LI7MMayGTVlHWUXhNe6Z6wIUsb9d1m20q7dkDpez
|
|
N9tRqKT5xEvRvKez9+Xis1/FSYerb5+OTyf6AFlAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAB43j9eXjN/jWJ/Z7J5L2mry8Upb8VIF8f6aGOey2eynHvOy7bowrrYSxZSwQJ2YXZ
|
|
92N4BoanrEvVexmTm4blr+HJ/aHltRHSXofYm/1Wrp5RaJaYY+X49WA0c4AD51xONuKan/qW/lbp
|
|
+0MOLRtxbU/9SU4J7KadWPjep2WQrr2WRPRk1TvsndXMpiRCb9FNu0rbTuqvKBscCjfi9PhWZeue
|
|
V9n434rafTHL1TfPxy+T/QAszAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAHmv
|
|
avHtfTZfnV6VxPajHzcNrf8ABeJFs/XnMcr4no18c+6vr2YadkY2YM57sEDLyY37Mo7MMnYGlqO0
|
|
vQ+xNfqNVb1tEfs87qZ2rL0/sVX/AHdnt65P7Q0wx8vx6UBo5wAHz/jUbcX1PT78qtO2vaCnJxjP
|
|
8Zif2amnnspp04+OjWejKJ6MKdmcMmyJn4m5ZHzEVPMwtJv0VZLbQDqezcb8RzT6Y/7vUPM+ytZt
|
|
n1OTyiIh6Ztn45N/6AFlAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABocbxeLw
|
|
nUR5xXm/Rvq8+OMuDJjntaswEeBxT0bNZ6NatZpNqz3rO0rqsdO3PxlaWEMpY+aqWXkryT0ZT2V3
|
|
7A0dVPuy9f7G124NM/iyT/Z4zWT7sw957MYfB4Fp4/FE2/WWmGHldcBowAAeM9qKcvFeb8VIly9P
|
|
0nq7ntbTbVYL+tJj93CwT76unR4/jo0nozhhTsy3Y1sWljM9Ce7HyQIm3RRlttVbaWrnt0Sh6n2U
|
|
x8vD8mSfv3/h3XN4Bi8Lg2nj8Uc36y6TeOPXugCUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAPD8RxeBxXUU26Tbmj8+quro+02Lw+I4ssdslNvzhzazvDPbq8d7GW7Dfqz2VzG
|
|
0s2qd+iu/Zn5Ksk9BVztX1mI8930zh2LwOHabH+HHWP2fNYp4+vwYvxXiP3fUqxtWIjyjZtj45/L
|
|
faQFmQADzftfj3w6fJ6WmHmsP23rvaqnNwqLfhvEvIYZ+sV038bo0noy36MK9oZQxrdMyrlnMbMZ
|
|
QKrS1M07zEestq/RRjr4utwY/wAV4j91p9V18fQdJj8LR4ccfdpEfsuREbREJbuMAAAAAAAAAAAA
|
|
BAJAAAAEAJEAJQAJQAJEAJQAJQAJEACUJAQlAJEAJQAJQJAAAEAJEAJBAAAJAABAJEJAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABwvanDzaPFmjvjv8A
|
|
tLztJ3h7HjGHx+FainnFeaPnHV4vFbeIU038VbHeGF+kso7Mb9mTdhKnLK3dRm7SIrHhGPxeP6Sv
|
|
9cT/AHfSnz72Zx+J7Q45/BWZ/Z9BbZ+OXyfQBZQABzeP4/E4NqI9Ii36S8Ng/wAx9C4jTxOH6ivr
|
|
jn+Hz3B/mQi/GvjdCnWNlsdI2V07LIlg6USrt2ZzZXMoFV+zPhGLxeOaavpbm/RVltEN72Yx+Jxm
|
|
b7dKUmf7L5+s9/HtRA2cqRACRACRACRACUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAACQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQCQQCRACRACRCQBCQBCQB
|
|
ACRACRACRACRACL1i9LVntMbPATTwdRkxT3pea/u+gPE8Xx+DxrPHlaYt+qNfGvjvtXXsi0dOrKk
|
|
dEXjZg6VMtbP2bMtXUdpEV0/Y2nNxbNf8OP+727xvsXH+N1U/wBEfy9k3nxyb+gCVQAGOWvNivX1
|
|
rMPnGGOXNNfOJ2fSZ6w+dZKeHxDPX8N7R+6L8a+L63KdoZ7q6zvEMpnowdKJ6ywmWUyqvIKM0vQ+
|
|
x+D6rU55+9aKx+TzWa36vbezmDwODYenW+95/Nphj5L6dQBo5wAAAAAAAAAAAAAAAAAAAAAAAAAA
|
|
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACAEiAAAEoA
|
|
AAAAAAAAAAAAAEAkEAkRuAkQbgkQAkQAkQAkQAl5T2nx8nEMOT8dNv0l6pwfarHvpcGWPu32/WCr
|
|
YvK4mOem6b9mGKd4Z3idmFdka0y1c892zfpMtLPaNpEV6D2Kj/Eauf6YeweQ9ieuTVz8K/3evbT4
|
|
5NfQBKoAA8FxCvJxrUx/XMvevD8Zry8fz/Haf2RfjTx/6RSOnRMyypHu9kXjowrqVSrvPRnZVl6V
|
|
kK0775MsUjvadn0nT4ow6bFijtSsVfPuFYvpPGtNTy54mfy6vorXDm8l9pEC7JIgBIgBIgBIgBIg
|
|
BIgBIhIAgBIhIAgBIgBIIBIAAhIAhIAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAJAAAAAAAAAAAAAAA
|
|
AAAAAAAAABAJQkAEAAAAAAAAAAjc3BIjdG4Mkbo5kcwMjdhzHMDPc3V8xzAs3N1fMjmBZubq+Y5g
|
|
Wbm6vmOYFm5ur5jmBZubq+Y5gWbm6vmOYFm5ur5jmBZubq+Y5gWbm6vmTzAz3N2HMnmBlu5ftFTx
|
|
OEZJ/DMW/d0t2rxKni8N1FPWkiZ9eS08e7Cy8dGGn6UhZaJljXZGnmc3UT3dPP2cnUT78xCIV6j2
|
|
H/8A9c/6f7vXPI+w8bU1U+vL/d63du5NfUiDcVSIAS8b7RV5eOb/AIqRL2TyXtNX/e2KfXH/AHlF
|
|
+NPH/pr4+2xcxx0hFpY11K7R16KM32ZWz3UaidqSgrc9kcPicWyZJjfw6T+727y3sXh2xarN+K0V
|
|
h6lvPjj3e0ASqAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAJQAAAAAkQAkQAkAAAAAAAAAAAAAAA
|
|
EgAAAAAAAAAAAAAAAAAAAAAgAAABKDcAN0bgkY8xzAyRux5kcwM9zdXNkTcFm6OZXzMeYFvMibKu
|
|
ZHMC2bo51U2RuC2bom6rc3BZzom6sBZzI52ADPnOdggFnMc6skFnMc6rc3BbznOp3RzAv50c6nml
|
|
HMC/nOf4qOY5wX85zqOc5wbHOc7X5znBsc6edr85zg2ec52vzpi4NjmY5bROG+/bllVzsNTk5dLl
|
|
n0pP8BHmMHWNmzt0aum8obm08vVjfrtnxztR0mXHzTvaZdjVRMTLkZo6yiFen9iZ2pqY/wBP93rN
|
|
3kPY+/LfPX1rE/u9XzN3HfqzdO6vmTuIZ7m7Hc3Bnu8t7TR/vHBP9E/y9Pu837SV31umn+if5Rfi
|
|
/j/01MMb1hjkrtKzBG0bMsmOZY11tOYamr6Und0LUc7XT7u3rJPqL8er9lcPhcFpbzyWm39v7O00
|
|
+FYvA4Zpsc94xxu227jv1IAgAAAAAAAAABKAAAASgASgBIgBIgBIgBIhIAAAAAAAAAAAAAAAAAAC
|
|
UACUJAAAAAAAAAAAABIAAAAAAAAAAAAAAAAAAAAg3AEbomQZbo3YzLGbAz3RNlc3YzcFs2YzdVN2
|
|
M2Bdzom6nmNwW86JurTAMuY3REJ2BB1ZRVMVBhsbSsiqeUFXLucq3lTygp5TlXcpygp5TlXcpygp
|
|
5TlXcqOUFXKjlXcrGYBXysdlswiYBVMdUTCyY6sZBWxlnMMZgGLGZZSwkDdHMiWO4MuY5mEyjcFn
|
|
N1OdVzHMC3nTzqeY5gX85zqOZPMC+Lqdbk20eb/RKOZr8QybaK/XvtH7iZ9aGlp2luzT3fg19NHS
|
|
OjbmPcYX67XH1XSZ9XIzRvMuzrK7zLkZYmYnciunb9lZ5dTk+OP+71cXeP8AZnJ/ip2nf3J/l6iL
|
|
/Fu5L9bMWZczXi6YuIbEWTzKIuyiwLt3nuO25uI4a/hx7/rLuczg8TicvFLbfdpEK6+NPH/phhjo
|
|
stLGkctUWnoxrrU3j1cnWTzZq1jzl1clo5Zcu8c+txR63iP3Tn6pv4+g4o5cVI9IiGe7CJ2iE7t3
|
|
GyN2O6dwSINwSISAlAAlACRAAlAAlACRACRCQAAAAAAAAAASgASISAAAAAAAAAAAAACQAAAAAAAA
|
|
AAAAAASAAAAAAAAAAAAAAAAIAAAQCAJljuljsCJlhMs9mOwMJYys5TkBVsjZdyHICrZPKt5E8oK4
|
|
qmKrOVOwMIqyirPY2Bjyp2ZbAI2NmSARsbMgEbI2ZAMdjZICNkbMkSCNmOzJEgx2YyzljMAwlhKy
|
|
WEwCuWErJhhMArlhLOWEgxljMpljIImWMyTKJA3N0IBO5vux3NwZbnMx3NwZczT4jf3MdPW27a3a
|
|
fJOq1XNP2KdIRfi+J2trSYfcjeF+Wm1OicVeWIiN9kai8xjY12ORqultnI1Ecsujq79XP1FovWYI
|
|
rTgeq+j8QrWZ+3Mx+r2UXeC0WG2Ti2kiN5mL807eUREvbzbaejefHJv62Iv8WUXa0WTFhVtRdlF2
|
|
rz9WUXBtc7jR9dqc2T1ttHyhvZMvJitb0jdq6XHNcNenWVN3028U99WRj6Kb02be3Tq18/SN2Lpc
|
|
3UdN9nOmZrqKX/DaJ/d0svvTLRzV3jomK6+Pd1vvWJj0ZczT0mXxNJht60hfFnQ4qu3N1cWTEgs3
|
|
Tur5k7gz3N2O5uDM3Y7m4MtxBuCQASIASIASAAAAAAACRCQAAAAAAAAEoSAAAAAAAAAAAlAAlCQA
|
|
AAAAAAAAAAASAAAAAAAAAAAAIASgAAAEJAQJQCNkbMgGOyOVnsAw5TlZ7GwMOVPKy2NgY7GzIBGx
|
|
skA2AAAAAAAAAAQkBAEghEskAxYzDPZGwK5hjMLJhjMAqmGEwumrCagomFcw2JqqtUFEsLLrV82F
|
|
o7gqljKyYYTGwMZRKUSCAQAboJnaN5Bjkneu0d5W4ccViIiOzHFWbTzNumP1Zarr8eeRMbxDW1Mx
|
|
NO67NbkhzNVnmInqzaOZrL93JyZeV0M1++7S02jvxDWxhxx033tPpC8Z6rrezWjmZyazJG2/u03h
|
|
2vFibTHoqvamiwVwY+nLGzV0+SZ1Mx8G0/45tOhzJ5lXMc3UVXRdlF1HP+iYsDPLPPy49/tz1+Te
|
|
pSIr0ho6ak5Ms5J8o2q6NImOrHV7XX488ypzTtHXo0s9t6zG7c1G1qz6ubeZiZ3UatXJG3yauSO7
|
|
cvMTEx5tPLb3prPRMVr0HB8vicNxf0+7+kt+LOJwTJyY/Bnz3tH93X36N58cWvq6LSyiyndMSlC7
|
|
mZcymLJiwLosmJVRLKLAtiU7q4lMSCzc3YxJuDMRuAlKAEgAAAlAkAAAAAABKAEgAAAAAJAAAAAA
|
|
AAAAAAAEgAAAAAAAAAAAAAkAAAAAAAAEAAAAAAAAAAAAAAAAAAAAAhIAAACAAAASgAAAAAAEAAAA
|
|
hGzJAImGMwzQDDZjNVuyNgUTVhNGxysZqDVmiu1G5NN2M4waM0+DCaN2cbGcQNGaMZq3JxMJxA1J
|
|
qx2bU4kU09slorWNwa20z02RXHbJbl26QvtFovbHWkxEdJt5y2MOHlr2U1W3jx+1hiw8vSO63lmI
|
|
XRTaEWmtY6snRHO1VpmJ+DjavpSZl2s8b7y4HFcnh0n0gha5ebJN55KRM2mdoiPN6fh+kpwXh0Wy
|
|
RHj5Otp/s5Ps1p62y31+em9aTMYt/OfVfxTiPjZ52naI7fBrI5t66xz5+a1rW7yx0eSL6iZjtEOX
|
|
qNbSletom3lENjh2fbHzbbWt3iVozruc+5ztWubf4M4ybpQ2Oboyrva0Vjza8WdDR4OkXt3n9ldX
|
|
kaePP9VtYqctYhdvt5oivTeCZ2YOxXk6ubqMfV0b9mrljfqlFcq88k7z2U5axeItDa1OPessuC8P
|
|
ya7XRWYnwqdbT/ZMilvIu4dpslNdixXja8Y5tt85djZdbDWnGOesRtXFtuw6T27No5Kx2OrKYQlC
|
|
ExKJgBnEpiyvdlEgsizKLKollFgWxLKJVRLKJBbEp3VxLKJBnuMWQJEbpBIAAAJAAAABIAAAAAAA
|
|
lAJAAAAAAAAAAAAAASAAAAAAAAAAAAAJAAAABAJABAlAAAAAAAAAAAAAAAAAAAAAAAAIAAAAAAAA
|
|
AAABAJQAAAAgAABAAI2EoBGyJhkgGPKxmqxAKpownHC+YRMdN5BrTj67R3bOn01o7p01Iv71u89o
|
|
b9a7LfBTfS1vWI2jf12VfQPSW8KX2mas+NC2iv6xMNfJpMnLtEbuuxtMRCtzF55NR5rPps1N/ctP
|
|
y6uHreE6nXZ4pak48X3rT06fB7fNeI33cbX6mI32R/MWu7XF116aDSRhxbRERs8f499bkyZeeKae
|
|
kzE2mdon81/tfxDLGOunwbzlzbx08oaHBvZHJlx48mrvaa94pu04y617576rNGLRRM0397JEd/lu
|
|
9Dw/S3x4qxffo6mm4NjwUiKY4iI9Ib1dHFY6QIaNabbrYrLfrpJtaK1rMzPZb/s+05IpP59OyLeJ
|
|
k7eNfRaOc1ue32I7fGXYpi5Y77M8OGMeOKxHSFsU3Y29deZMzirl6dlVvhLatCjJHeYQv1rXnps1
|
|
8k9/VsW6qLVmZIi1rzitlvFKRvaZ2h6TSaenC9FFY+3brM+sqeG8Prp4+kZ+lvuxPkr1mqm95nfp
|
|
DXM459676a2q1dsV7XietvNno78+CJn1cjX6mOeIm0bR33dfRU5NJjidt9t5afjG/V6JZ7I2QMNh
|
|
nyo2BhsMuVG3wAhMSbbQRAMolnE+iuGUSCyJZRKuGUSCyJZK4llEgyZMYTuCUsYSCQASISAAAlCQ
|
|
AAAAAAEoASCASAAAAAAAAAAAAlACRACQAAAAAAAAAEgCEoASCAAAAAAAAAAAAAAAAAAAAAAABAAA
|
|
AAAAAAAISAIAAAAAAQAAACASgAAAQJAQAAhIDHZhln3do7z0WS18mWsajHjmes7pg3dNi5aRMNqO
|
|
yvDHTpPRaigHZhN4hHRlaVN59JY3zRENLUavaO+yq0iNVlitJ6vNcR1MVi0zO0era1/Ea0rPvbz5
|
|
PM5MWp45qvo2GZrhmfrsnpHpHzTCseEcM/2vrr8Q1Eb4qzy44nziPN63HpYiIiI7LNHoqabBTFii
|
|
IpSNohuVxrKtWMEejPwY9G1FFmHB4mWJn7MdfnIM9JpIx15to5pbUaas/a6rqViI7MxPxqX0UT1r
|
|
O3wVzpbR2hviP5i03Y5s6a879FNtHljydhExCv8AMTPJXBnRZbz0iG5ptFjwe/l96zctMVamTJtE
|
|
yTMibu1VrdTzRMR0j0ed4lr64MVpm0RERvMz5NvX62uOJ69XhOKX1HH9bHDtFvNYnfJeOy0Z2ojX
|
|
6jjnEq6fRUmccTvN/J9H0eKcOnx45neaxEbubwHgOHg+milI3vP2resu3Wu0JQmITsmISDHZHKz2
|
|
JgFc1RMLJhGwK9iIZ7MZgEdgmAEwyiWCdwWRLKJVxKYsC2JTuriWUSDNlEsIlMAySx3SCRCQSIAS
|
|
AAACRACQAAAAAAASIASAAAAAAAAAAAAAAACRACRACQASIAAAAAAAAAAAAAAAAAAAAAAAAQCUAAAA
|
|
AAAAAAIAAAAAAAAQAAAAAACBICBICAAEJAQJQCJcLjuS2ny6fPG/LWdpd1o8T0X07SXx/e7wCdJx
|
|
Wa0jmneHQpxPDMdZmJfNtZm49weZrh0/j4o7VtSZ2+Uw0/8A7o49k92vBLc/ntFohFW9PqGXimOI
|
|
6Tu1L8T3eCx6r2t1O3JwvHjifO99v7t/Bwf2l1PXU6rS6eJ8qUm8x+so5TsekzcSjbvs4mt4rzW5
|
|
K2mbT0itesy2cHsvbvqtbmyz5xERWP2jd1tJwrTaONsOKtZ8585+cnDrzmn4Rq+IZObUROHD32n7
|
|
Vv8A0ej0uhxaXFGPFSK1j0bkY4jyZRVZVXFGUVWbGwKsk8mObekNrSW3pWf1a2aYjHbm7bNnQ1id
|
|
PW0TvuDdhJEbQABMsLW2R0ZTMQrvfbz2YWzVhpanUxEd0dWkW5c8R5uXxDX1w4pnfr5Q19XxKuOJ
|
|
2neXltVqtVxbV/RdJ715+1bypANfiOu1HENV9C0MTfNeesx2rD1PAeBYuE6aKx72W3W9/WVnBuB4
|
|
eF4dqRzZbdb5J72l160WVK02ZxCYhOwI23TsnY2BGxsnYBjsiYZsZBjMMZZSgGEolMsQDdG6NwZ7
|
|
piVe6YkFsSziVMWZRILolMSriWUSCyJTuwhMSDMRCQSI3SAlACRCQAAEoAEoASAAAAAAAAACUACR
|
|
ACQAAAAAAAAAAAAASAAAAAAAAAAAAAAAAAAACAAAAAAAAAAAAAABAAAAAAAAAAAAACBKAAAAAAAQ
|
|
JQAAAhICEbJAYTWJ7wx8KvpC0BV4ceieWGewDHlNmWwCNjZICNhIDmcZredBecdpiY69FXCOLW+i
|
|
UiZidukulmxxlx2paN4mNng+K4+I8Hy2yaTfl37TXetoCPfRxfp1qi3F48ofKMvtvxak8s6LDv61
|
|
rZji9rPaLUf5PC+bfttS0q8q3p9W/wBrRMdpUZuKdN99nzvFqPbTVz7nD8OKs+do2/mW3h4D7Xaq
|
|
ZnPrtNpqz35aRaYOHY9Zk4pNt9rR+rl6zi+OnS+WN57Rv1lXp/YrNaYtruL6zNPnGO3hxP6O5w/2
|
|
f0HDuun09Yv55Le9afznqcOvO4tBreMTHu30unnva0bWt8on+70nDuE4OHYYx4Kbesz3tPrMuhGO
|
|
IjpDOKrK9YVpsyiGUQnYGOyUgI2SlAIEmwMWMs9kTAMJYzDOYRMArmGErZhhMArlHmzmGMwDE3Ts
|
|
bAbs4swj5pgFkSziVcM4BZEsolXDKAZwyhjCYBkACQhIAAAAAAAJAAAAAAAAAAAAAAAAAAAShIAA
|
|
AAAAAAJAAAAAAAAAAAAAABAJEAAAAAAAAAAAAAAAIEoBKAAAAAAAAAAAAAAABAlAAAAAAAIAAAAA
|
|
BAkBAkBAkBAlACEgMZjdjbFW8bWrEx8YWANb6Fp+bfwab+vLDKMFK9qxH5L0bAr8OPRPKz2AY7J2
|
|
SbAjYZAI2E7AIEgIEgIEgMdkSy2NgY7MdlmyNoBXsxmFuyNgVTVjNV3KjlBRNTlXTVHKCrlIqt5T
|
|
lBhEMohlFerLlBjEMohMVTEARDKCITsAk2AEgAAAkAAAAAAAAAAAAAAAAAAAAAAAASAAAAAAAAD/
|
|
2Q==`;var E2={};xr(E2,{author:()=>I4,browser:()=>v4,bugs:()=>N4,default:()=>kse,description:()=>x4,devDependencies:()=>M4,engines:()=>E4,homepage:()=>S4,keywords:()=>F4,license:()=>T4,main:()=>b4,module:()=>_4,name:()=>g4,repository:()=>C4,scripts:()=>R4,sideEffects:()=>w4,types:()=>k4,version:()=>C2});var g4="@vladmandic/human",C2="1.1.5",x4="Human: AI-powered 3D Face Detection, Face Embedding & Recognition, Body Pose Tracking, Hand & Finger Tracking, Iris Analysis, Age & Gender & Emotion Prediction & Gesture Recognition",w4=!1,b4="dist/human.node.js",_4="dist/human.esm.js",v4="dist/human.esm.js",k4="types/src/human.d.ts",I4="Vladimir Mandic <mandic00@live.com>",N4={url:"https://github.com/vladmandic/human/issues"},S4="https://vladmandic.github.io/human/demo/index.html",T4="MIT",E4={node:">=12.0.0"},C4={type:"git",url:"git+https://github.com/vladmandic/human.git"},R4={start:"node --trace-warnings --unhandled-rejections=strict --trace-uncaught --no-deprecation demo/node.js",dev:"node --trace-warnings --unhandled-rejections=strict --trace-uncaught server/serve.js",build:"rimraf dist/* types/* typedoc/* && node --trace-warnings --unhandled-rejections=strict --trace-uncaught server/build.js",lint:"eslint src server demo",test:"npm run lint && npm run start"},F4=["tensorflowjs","face-detection","face-geometry","face-embedding","face-recognition","body-tracking","hand-tracking","iris-tracking","age-estimation","emotion-detection","gender-prediction","gesture-recognition","blazeface","blazepose"],M4={"@microsoft/api-extractor":"^7.13.2","@tensorflow/tfjs":"^3.3.0","@tensorflow/tfjs-backend-cpu":"^3.3.0","@tensorflow/tfjs-backend-wasm":"^3.3.0","@tensorflow/tfjs-backend-webgl":"^3.3.0","@tensorflow/tfjs-converter":"^3.3.0","@tensorflow/tfjs-core":"^3.3.0","@tensorflow/tfjs-data":"^3.3.0","@tensorflow/tfjs-layers":"^3.3.0","@tensorflow/tfjs-node":"^3.3.0","@tensorflow/tfjs-node-gpu":"^3.3.0","@types/node":"^14.14.34","@typescript-eslint/eslint-plugin":"^4.17.0","@typescript-eslint/parser":"^4.17.0","@vladmandic/pilogger":"^0.2.14",chokidar:"^3.5.1",dayjs:"^1.10.4",esbuild:"^0.9.2",eslint:"^7.22.0","eslint-config-airbnb-base":"^14.2.1","eslint-plugin-import":"^2.22.1","eslint-plugin-json":"^2.1.2","eslint-plugin-node":"^11.1.0","eslint-plugin-promise":"^4.3.1",rimraf:"^3.0.2","simple-git":"^2.36.2",tslib:"^2.1.0",typedoc:"^0.20.32",typescript:"^4.2.3"},kse={name:g4,version:C2,description:x4,sideEffects:w4,main:b4,module:_4,browser:v4,types:k4,author:I4,bugs:N4,homepage:S4,license:T4,engines:E4,repository:C4,scripts:R4,keywords:F4,devDependencies:M4};var R2={};xr(R2,{all:()=>Nse,body:()=>z4,canvas:()=>Ise,drawOptions:()=>de,face:()=>O4,gesture:()=>D4,hand:()=>P4});var de={color:"rgba(173, 216, 230, 0.3)",labelColor:"rgba(173, 216, 230, 1)",shadowColor:"black",font:'small-caps 16px "Segoe UI"',lineHeight:20,lineWidth:6,pointSize:2,roundRect:28,drawPoints:!1,drawLabels:!0,drawBoxes:!0,drawPolygons:!0,fillPolygons:!1,useDepth:!0,useCurves:!1,bufferedOutput:!1};function L0(e,t,n,r=null){e.fillStyle=de.useDepth&&r?`rgba(${127.5+2*(r||0)}, ${127.5-2*(r||0)}, 255, 0.3)`:de.color,e.beginPath(),e.arc(t,n,de.pointSize,0,2*Math.PI),e.fill()}function $4(e,t,n,r,a){if(e.beginPath(),de.useCurves){let s=(t+t+r)/2,i=(n+n+a)/2;e.ellipse(s,i,r/2,a/2,0,0,2*Math.PI)}else e.lineWidth=de.lineWidth,e.moveTo(t+de.roundRect,n),e.lineTo(t+r-de.roundRect,n),e.quadraticCurveTo(t+r,n,t+r,n+de.roundRect),e.lineTo(t+r,n+a-de.roundRect),e.quadraticCurveTo(t+r,n+a,t+r-de.roundRect,n+a),e.lineTo(t+de.roundRect,n+a),e.quadraticCurveTo(t,n+a,t,n+a-de.roundRect),e.lineTo(t,n+de.roundRect),e.quadraticCurveTo(t,n,t+de.roundRect,n),e.closePath();e.stroke()}function F2(e,t=[]){if(!(t===void 0||t.length===0)){e.beginPath(),e.moveTo(t[0][0],t[0][1]);for(let n of t)e.strokeStyle=de.useDepth&&n[2]?`rgba(${127.5+2*n[2]}, ${127.5-2*n[2]}, 255, 0.3)`:de.color,e.fillStyle=de.useDepth&&n[2]?`rgba(${127.5+2*n[2]}, ${127.5-2*n[2]}, 255, 0.3)`:de.color,e.lineTo(n[0],parseInt(n[1]));e.stroke(),de.fillPolygons&&(e.closePath(),e.fill())}}function W0(e,t=[]){if(!(t===void 0||t.length===0)){if(!de.useCurves||t.length<=2){F2(e,t);return}e.moveTo(t[0][0],t[0][1]);for(let n=0;n<t.length-2;n++){let r=(t[n][0]+t[n+1][0])/2,a=(t[n][1]+t[n+1][1])/2;e.quadraticCurveTo(t[n][0],t[n][1],r,a)}e.quadraticCurveTo(t[t.length-2][0],t[t.length-2][1],t[t.length-1][0],t[t.length-1][1]),e.stroke(),de.fillPolygons&&(e.closePath(),e.fill())}}async function D4(e,t){if(!t||!e||!(e instanceof HTMLCanvasElement))return;let n=e.getContext("2d");if(!n)return;n.font=de.font,n.fillStyle=de.color;let r=1;for(let a=0;a<t.length;a++){let s=[],i=[];if([s,i]=Object.entries(t[a]),i.length>1&&i[1].length>0){let o=s[1]>0?`#${s[1]}`:"",l=`${s[0]} ${o}: ${i[1]}`;de.shadowColor&&de.shadowColor!==""&&(n.fillStyle=de.shadowColor,n.fillText(l,8,2+r*de.lineHeight)),n.fillStyle=de.labelColor,n.fillText(l,6,0+r*de.lineHeight),r+=1}}}async function O4(e,t){if(!t||!e||!(e instanceof HTMLCanvasElement))return;let n=e.getContext("2d");if(!!n)for(let r of t){n.font=de.font,n.strokeStyle=de.color,n.fillStyle=de.color,de.drawBoxes&&$4(n,r.box[0],r.box[1],r.box[2],r.box[3]);let a=[];if(a.push(`face confidence: ${Math.trunc(100*r.confidence)}%`),r.genderConfidence&&a.push(`${r.gender||""} ${Math.trunc(100*r.genderConfidence)}% confident`),r.age&&a.push(`age: ${r.age||""}`),r.iris&&a.push(`iris distance: ${r.iris}`),r.emotion&&r.emotion.length>0){let s=r.emotion.map(i=>`${Math.trunc(100*i.score)}% ${i.emotion}`);a.push(s.join(" "))}r.angle&&r.angle.roll&&a.push(`roll: ${Math.trunc(100*r.angle.roll)/100} yaw:${Math.trunc(100*r.angle.yaw)/100} pitch:${Math.trunc(100*r.angle.pitch)/100}`),a.length===0&&a.push("face"),n.fillStyle=de.color;for(let s=a.length-1;s>=0;s--){let i=Math.max(r.box[0],0),o=s*de.lineHeight+r.box[1];de.shadowColor&&de.shadowColor!==""&&(n.fillStyle=de.shadowColor,n.fillText(a[s],i+5,o+16)),n.fillStyle=de.labelColor,n.fillText(a[s],i+4,o+15)}if(n.lineWidth=1,r.mesh){if(de.drawPoints)for(let s of r.mesh)L0(n,s[0],s[1],s[2]);if(de.drawPolygons){n.lineWidth=1;for(let s=0;s<Li.length/3;s++){let i=[Li[s*3+0],Li[s*3+1],Li[s*3+2]].map(o=>r.mesh[o]);F2(n,i)}if(r.annotations&&r.annotations.leftEyeIris){n.strokeStyle=de.useDepth?"rgba(255, 200, 255, 0.3)":de.color,n.beginPath();let s=Math.abs(r.annotations.leftEyeIris[3][0]-r.annotations.leftEyeIris[1][0])/2,i=Math.abs(r.annotations.leftEyeIris[4][1]-r.annotations.leftEyeIris[2][1])/2;n.ellipse(r.annotations.leftEyeIris[0][0],r.annotations.leftEyeIris[0][1],s,i,0,0,2*Math.PI),n.stroke(),de.fillPolygons&&(n.fillStyle=de.useDepth?"rgba(255, 255, 200, 0.3)":de.color,n.fill())}if(r.annotations&&r.annotations.rightEyeIris){n.strokeStyle=de.useDepth?"rgba(255, 200, 255, 0.3)":de.color,n.beginPath();let s=Math.abs(r.annotations.rightEyeIris[3][0]-r.annotations.rightEyeIris[1][0])/2,i=Math.abs(r.annotations.rightEyeIris[4][1]-r.annotations.rightEyeIris[2][1])/2;n.ellipse(r.annotations.rightEyeIris[0][0],r.annotations.rightEyeIris[0][1],s,i,0,0,2*Math.PI),n.stroke(),de.fillPolygons&&(n.fillStyle=de.useDepth?"rgba(255, 255, 200, 0.3)":de.color,n.fill())}}}}}var os=[];async function z4(e,t){if(!t||!e||!(e instanceof HTMLCanvasElement))return;let n=e.getContext("2d");if(!!n){n.lineJoin="round";for(let r=0;r<t.length;r++){if(!os[r]&&de.bufferedOutput&&(os[r]={...t[r]}),n.strokeStyle=de.color,n.lineWidth=de.lineWidth,de.drawPoints)for(let a=0;a<t[r].keypoints.length;a++)n.fillStyle=de.useDepth&&t[r].keypoints[a].position.z?`rgba(${127.5+2*t[r].keypoints[a].position.z}, ${127.5-2*t[r].keypoints[a].position.z}, 255, 0.5)`:de.color,de.bufferedOutput?(os[r].keypoints[a][0]=(os[r].keypoints[a][0]+t[r].keypoints[a].position.x)/2,os[r].keypoints[a][1]=(os[r].keypoints[a][1]+t[r].keypoints[a].position.y)/2,L0(n,os[r].keypoints[a][0],os[r].keypoints[a][1])):L0(n,t[r].keypoints[a].position.x,t[r].keypoints[a].position.y);if(de.drawLabels){n.font=de.font;for(let a of t[r].keypoints)n.fillStyle=de.useDepth&&a.position.z?`rgba(${127.5+2*a.position.z}, ${127.5-2*a.position.z}, 255, 0.5)`:de.color,n.fillText(`${a.part}`,a.position.x+4,a.position.y+4)}if(de.drawPolygons){let a,s=[];s.length=0,a=t[r].keypoints.find(i=>i.part==="leftShoulder"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightShoulder"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightHip"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftHip"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftShoulder"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),s.length===5&&F2(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="leftHip"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftKnee"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftAnkle"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftHeel"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftFoot"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),W0(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="rightHip"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightKnee"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightAnkle"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightHeel"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightFoot"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),W0(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="leftShoulder"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftElbow"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftWrist"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftPalm"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),W0(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="rightShoulder"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightElbow"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightWrist"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightPalm"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),W0(n,s)}}}}async function P4(e,t){if(!t||!e||!(e instanceof HTMLCanvasElement))return;let n=e.getContext("2d");if(!!n){n.lineJoin="round",n.font=de.font;for(let r of t){if(de.drawBoxes&&(n.strokeStyle=de.color,n.fillStyle=de.color,$4(n,r.box[0],r.box[1],r.box[2],r.box[3]),de.shadowColor&&de.shadowColor!==""&&(n.fillStyle=de.shadowColor,n.fillText("hand",r.box[0]+3,1+r.box[1]+de.lineHeight,r.box[2])),n.fillStyle=de.labelColor,n.fillText("hand",r.box[0]+2,0+r.box[1]+de.lineHeight,r.box[2]),n.stroke()),de.drawPoints&&r.landmarks&&r.landmarks.length>0)for(let a of r.landmarks)n.fillStyle=de.useDepth?`rgba(${127.5+2*a[2]}, ${127.5-2*a[2]}, 255, 0.5)`:de.color,L0(n,a[0],a[1]);if(de.drawPolygons){let a=s=>{if(!!s)for(let i=0;i<s.length;i++)n.lineWidth=de.lineWidth,n.beginPath(),n.strokeStyle=de.useDepth?`rgba(${127.5+2*s[i][2]}, ${127.5-2*s[i][2]}, 255, 0.5)`:de.color,n.moveTo(s[i>0?i-1:0][0],s[i>0?i-1:0][1]),n.lineTo(s[i][0],s[i][1]),n.stroke()};a(r.annotations.indexFinger),a(r.annotations.middleFinger),a(r.annotations.ringFinger),a(r.annotations.pinky),a(r.annotations.thumb)}}}}async function Ise(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 Nse(e,t){!t||!e||e instanceof HTMLCanvasElement&&(O4(e,t.face),z4(e,t.body),P4(e,t.hand),D4(e,t.gesture))}var mt=()=>typeof performance!="undefined"?performance.now():parseInt((Number(process.hrtime.bigint())/1e3/1e3).toString());function Zc(...e){let t=n=>n&&typeof n=="object";return e.reduce((n,r)=>(Object.keys(r||{}).forEach(a=>{let s=n[a],i=r[a];Array.isArray(s)&&Array.isArray(i)?n[a]=s.concat(...i):t(s)&&t(i)?n[a]=Zc(s,i):n[a]=i}),n),{})}var B0,Je,ru,Yc,Jc,Bi,qt,V0,Qc,U0,eh,H0,j0,G0,$2=class{constructor(t={}){B0.set(this,void 0);Je.set(this,void 0);ru.set(this,void 0);Yc.set(this,void 0);Jc.set(this,void 0);Bi.set(this,void 0);qt.set(this,(...t)=>{if(!Ne(this,Yc))return;let n=this.tf.engine().state.numTensors,r=Ne(this,ru);ia(this,ru,n);let a=n-r;a!==0&&Fe(...t,a)});V0.set(this,t=>{if(!Ne(this,Jc))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});Qc.set(this,async(t=!1)=>{if(this.config.backend&&this.config.backend!==""&&t||this.tf.getBackend()!==this.config.backend){let n=mt();if(this.state="backend",this.config.backend&&this.config.backend!==""){if(this.config.debug&&Fe("setting backend:",this.config.backend),this.config.backend==="wasm"){this.config.debug&&Fe("wasm path:",this.config.wasmPath),this.tf.setWasmPaths(this.config.wasmPath);let r=await this.tf.env().getAsync("WASM_HAS_SIMD_SUPPORT"),a=await this.tf.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT");this.config.debug&&Fe(`wasm execution: ${r?"SIMD":"no SIMD"} ${a?"multithreaded":"singlethreaded"}`),r||Fe("warning: wasm simd support is not enabled")}this.config.backend==="humangl"&&S6();try{await this.tf.setBackend(this.config.backend)}catch(r){Fe("error: cannot set backend:",this.config.backend,r)}}if(this.tf.enableProdMode(),this.tf.getBackend()==="webgl"){this.config.deallocate&&(Fe("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",this.config.deallocate),this.tf.ENV.set("WEBGL_DELETE_TEXTURE_THRESHOLD",this.config.deallocate?0:-1));let r=await this.tf.backend().getGPGPUContext().gl;this.config.debug&&Fe(`gl version:${r.getParameter(r.VERSION)} renderer:${r.getParameter(r.RENDERER)}`)}await this.tf.ready(),Ne(this,Je).backend=Math.trunc(mt()-n)}});U0.set(this,t=>{if(!t||t.length<300)return{roll:null,yaw:null,pitch:null};let n=(s,i,o,l)=>Math.atan2(l-i,o-s),r=s=>Math.abs(s*180/Math.PI%360);return{roll:n(t[33][0],t[33][1],t[263][0],t[263][1]),yaw:n(t[33][0],t[33][2],t[263][0],t[263][2]),pitch:n(t[10][1],t[10][2],t[152][1],t[152][2])}});eh.set(this,async t=>{var u,c,h,d,p,f,m;let n,r,a,s,i,o=[];this.state="run:face",n=mt();let l=await((u=this.models.face)==null?void 0:u.estimateFaces(t,this.config));if(Ne(this,Je).face=Math.trunc(mt()-n),!l)return[];for(let A of l){if(Ne(this,qt).call(this,"Get Face"),!A.image||A.image.isDisposedInternal){Fe("Face object is disposed:",A.image);continue}let y=Ne(this,U0).call(this,A.mesh);Ne(this,qt).call(this,"Start Age:"),this.config.async?r=this.config.face.age.enabled?Bg(A.image,this.config):{}:(this.state="run:age",n=mt(),r=this.config.face.age.enabled?await Bg(A.image,this.config):{},Ne(this,Je).age=Math.trunc(mt()-n)),Ne(this,qt).call(this,"Start Gender:"),this.config.async?a=this.config.face.gender.enabled?qg(A.image,this.config):{}:(this.state="run:gender",n=mt(),a=this.config.face.gender.enabled?await qg(A.image,this.config):{},Ne(this,Je).gender=Math.trunc(mt()-n)),Ne(this,qt).call(this,"Start Emotion:"),this.config.async?s=this.config.face.emotion.enabled?Jg(A.image,this.config):{}:(this.state="run:emotion",n=mt(),s=this.config.face.emotion.enabled?await Jg(A.image,this.config):{},Ne(this,Je).emotion=Math.trunc(mt()-n)),Ne(this,qt).call(this,"End Emotion:"),Ne(this,qt).call(this,"Start Embedding:"),this.config.async?i=this.config.face.embedding.enabled?n2(A,this.config):[]:(this.state="run:embedding",n=mt(),i=this.config.face.embedding.enabled?await n2(A,this.config):[],Ne(this,Je).embedding=Math.trunc(mt()-n)),Ne(this,qt).call(this,"End Emotion:"),this.config.async&&([r,a,s,i]=await Promise.all([r,a,s,i])),Ne(this,qt).call(this,"Finish Face:"),!this.config.face.iris.enabled&&((c=A==null?void 0:A.annotations)==null?void 0:c.leftEyeIris)&&((h=A==null?void 0:A.annotations)==null?void 0:h.rightEyeIris)&&(delete A.annotations.leftEyeIris,delete A.annotations.rightEyeIris);let g=((d=A.annotations)==null?void 0:d.leftEyeIris)&&((p=A.annotations)==null?void 0:p.rightEyeIris)?11.7*Math.max(Math.abs(A.annotations.leftEyeIris[3][0]-A.annotations.leftEyeIris[1][0]),Math.abs(A.annotations.rightEyeIris[4][1]-A.annotations.rightEyeIris[2][1])):0;o.push({...A,age:r.age,gender:a.gender,genderConfidence:a.confidence,emotion:s,embedding:i,iris:g!==0?Math.trunc(g)/100:0,angle:y,tensor:this.config.face.detector.return?(f=A.image)==null?void 0:f.squeeze():null}),(m=A.image)==null||m.dispose(),Ne(this,qt).call(this,"End Face")}return Ne(this,qt).call(this,"End FaceMesh:"),this.config.async&&(Ne(this,Je).face&&delete Ne(this,Je).face,Ne(this,Je).age&&delete Ne(this,Je).age,Ne(this,Je).gender&&delete Ne(this,Je).gender,Ne(this,Je).emotion&&delete Ne(this,Je).emotion),o});H0.set(this,async()=>{let t=(a,s="application/octet-stream")=>fetch(`data:${s};base64,${a}`).then(i=>i.blob()),n,r;switch(this.config.warmup){case"face":n=await t(z0);break;case"full":n=await t(P0);break;default:n=null}if(n){let a=await createImageBitmap(n);r=await this.detect(a,this.config),a.close()}return r});j0.set(this,async()=>new Promise(t=>{let n,r=0;switch(this.config.warmup){case"face":r=256,n="data:image/jpeg;base64,"+z0;break;case"full":case"body":r=1200,n="data:image/jpeg;base64,"+P0;break;default:n=null}let a=new Image;a.onload=async()=>{let s=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(r,r):document.createElement("canvas");s.width=a.naturalWidth,s.height=a.naturalHeight;let i=s.getContext("2d");i==null||i.drawImage(a,0,0);let o=await this.detect(s,this.config);t(o)},n?a.src=n:t(null)}));G0.set(this,async()=>{let t=i=>Buffer.from(i,"base64"),n=this.config.warmup==="face"?t(z0):t(P0),r=(void 0).decodeJpeg(n),a=r.expandDims(0);this.tf.dispose(r);let s=await this.detect(a,this.config);return this.tf.dispose(a),s});this.tf=Eh,this.draw=R2,ia(this,B0,E2),this.version=C2,this.config=Zc(gt,t),this.state="idle",ia(this,ru,0),ia(this,Yc,!1),ia(this,Jc,!1),ia(this,Bi,!0),ia(this,Je,{}),this.models={face:null,posenet:null,blazepose:null,handpose:null,iris:null,age:null,gender:null,emotion:null,embedding:null},this.image=n=>T2(n,this.config),this.classes={facemesh:M2,age:Lg,gender:Vg,emotion:Xg,body:this.config.body.modelPath.includes("posenet")?f2:I2,hand:b2},this.sysinfo=K2()}profileData(){return this.config.profile?Pg:{}}simmilarity(t,n){return this.config.face.embedding.enabled?e2(t,n):0}enhance(t){return t2(t)}match(t,n,r=0){return L6(t,n,r)}async load(t={}){this.state="load";let n=mt();t&&(this.config=Zc(this.config,t)),Ne(this,Bi)&&(this.config.debug&&Fe(`version: ${this.version}`),this.config.debug&&Fe(`tfjs version: ${this.tf.version_core}`),this.config.debug&&Fe("platform:",this.sysinfo.platform),this.config.debug&&Fe("agent:",this.sysinfo.agent),await Ne(this,Qc).call(this,!0),this.tf.ENV.flags.IS_BROWSER&&(this.config.debug&&Fe("configuration:",this.config),this.config.debug&&Fe("tf flags:",this.tf.ENV.flags))),this.config.async?[this.models.face,this.models.age,this.models.gender,this.models.emotion,this.models.embedding,this.models.handpose,this.models.posenet,this.models.blazepose]=await Promise.all([this.models.face||(this.config.face.enabled?M2.load(this.config):null),this.models.age||(this.config.face.enabled&&this.config.face.age.enabled?Wg(this.config):null),this.models.gender||(this.config.face.enabled&&this.config.face.gender.enabled?Gg(this.config):null),this.models.emotion||(this.config.face.enabled&&this.config.face.emotion.enabled?Yg(this.config):null),this.models.embedding||(this.config.face.enabled&&this.config.face.embedding.enabled?Qg(this.config):null),this.models.handpose||(this.config.hand.enabled?k2(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("posenet")?A2(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("blazepose")?N2(this.config):null)]):(this.config.face.enabled&&!this.models.face&&(this.models.face=await M2.load(this.config)),this.config.face.enabled&&this.config.face.age.enabled&&!this.models.age&&(this.models.age=await Wg(this.config)),this.config.face.enabled&&this.config.face.gender.enabled&&!this.models.gender&&(this.models.gender=await Gg(this.config)),this.config.face.enabled&&this.config.face.emotion.enabled&&!this.models.emotion&&(this.models.emotion=await Yg(this.config)),this.config.face.enabled&&this.config.face.embedding.enabled&&!this.models.embedding&&(this.models.embedding=await Qg(this.config)),this.config.hand.enabled&&!this.models.handpose&&(this.models.handpose=await k2(this.config)),this.config.body.enabled&&!this.models.posenet&&this.config.body.modelPath.includes("posenet")&&(this.models.posenet=await A2(this.config)),this.config.body.enabled&&!this.models.blazepose&&this.config.body.modelPath.includes("blazepose")&&(this.models.blazepose=await N2(this.config))),Ne(this,Bi)&&(this.config.debug&&Fe("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),ia(this,Bi,!1));let r=Math.trunc(mt()-n);r>(Ne(this,Je).load||0)&&(Ne(this,Je).load=r)}async detect(t,n={}){return new Promise(async r=>{var d,p,f,m;this.state="config";let a;this.config=Zc(this.config,n),this.state="check";let s=Ne(this,V0).call(this,t);s&&(Fe(s,t),r({error:s}));let i=mt();await Ne(this,Qc).call(this),await this.load(),this.config.scoped&&this.tf.engine().startScope(),Ne(this,qt).call(this,"Start Scope:"),a=mt();let o=T2(t,this.config);if(!o||!o.tensor){Fe("could not convert input to tensor"),r({error:"could not convert input to tensor"});return}Ne(this,Je).image=Math.trunc(mt()-a),Ne(this,qt).call(this,"Get Image:");let l,u,c;this.config.async?(c=this.config.face.enabled?Ne(this,eh).call(this,o.tensor):[],Ne(this,Je).face&&delete Ne(this,Je).face):(this.state="run:face",a=mt(),c=this.config.face.enabled?await Ne(this,eh).call(this,o.tensor):[],Ne(this,Je).face=Math.trunc(mt()-a)),Ne(this,qt).call(this,"Start Body:"),this.config.async?(this.config.body.modelPath.includes("posenet")?l=this.config.body.enabled?(d=this.models.posenet)==null?void 0:d.estimatePoses(o.tensor,this.config):[]:l=this.config.body.enabled?S2(o.tensor,this.config):[],Ne(this,Je).body&&delete Ne(this,Je).body):(this.state="run:body",a=mt(),this.config.body.modelPath.includes("posenet")?l=this.config.body.enabled?await((p=this.models.posenet)==null?void 0:p.estimatePoses(o.tensor,this.config)):[]:l=this.config.body.enabled?await S2(o.tensor,this.config):[],Ne(this,Je).body=Math.trunc(mt()-a)),Ne(this,qt).call(this,"End Body:"),Ne(this,qt).call(this,"Start Hand:"),this.config.async?(u=this.config.hand.enabled?(f=this.models.handpose)==null?void 0:f.estimateHands(o.tensor,this.config):[],Ne(this,Je).hand&&delete Ne(this,Je).hand):(this.state="run:hand",a=mt(),u=this.config.hand.enabled?await((m=this.models.handpose)==null?void 0:m.estimateHands(o.tensor,this.config)):[],Ne(this,Je).hand=Math.trunc(mt()-a)),Ne(this,qt).call(this,"End Hand:"),this.config.async&&([c,l,u]=await Promise.all([c,l,u])),o.tensor.dispose(),this.config.scoped&&this.tf.engine().endScope(),Ne(this,qt).call(this,"End Scope:");let h=[];this.config.gesture.enabled&&(a=mt(),h=[...f4(c),...p4(l),...A4(u),...m4(c)],this.config.async?Ne(this,Je).gesture&&delete Ne(this,Je).gesture:Ne(this,Je).gesture=Math.trunc(mt()-a)),Ne(this,Je).total=Math.trunc(mt()-i),this.state="idle",r({face:c,body:l,hand:u,gesture:h,performance:Ne(this,Je),canvas:o.canvas})})}async warmup(t={}){let n=mt();t&&(this.config=Zc(this.config,t));let r=this.config.videoOptimized;this.config.videoOptimized=!1;let a;typeof createImageBitmap=="function"?a=await Ne(this,H0).call(this):typeof Image!="undefined"?a=await Ne(this,j0).call(this):a=await Ne(this,G0).call(this),this.config.videoOptimized=r;let s=mt();return this.config.debug&&Fe("Warmup",this.config.warmup,Math.round(s-n),"ms",a),a}};B0=new WeakMap,Je=new WeakMap,ru=new WeakMap,Yc=new WeakMap,Jc=new WeakMap,Bi=new WeakMap,qt=new WeakMap,V0=new WeakMap,Qc=new WeakMap,U0=new WeakMap,eh=new WeakMap,H0=new WeakMap,j0=new WeakMap,G0=new WeakMap;var th=0,L4=!1,kt={background:"darkslategray",hover:"lightgray",itemBackground:"black",itemColor:"white",buttonBackground:"lightblue",buttonHover:"lightgreen",checkboxOn:"lightgreen",checkboxOff:"lightcoral",rangeBackground:"lightblue",rangeLabel:"white",chartColor:"lightblue"};function Sse(){if(L4)return;let e=`
|
|
:root { --rounded: 0.1rem; }
|
|
.menu { position: absolute; top: 0rem; right: 0; width: max-content; padding: 0 0.2rem 0 0.2rem; line-height: 1.8rem; z-index: 10;
|
|
box-shadow: 0 0 8px dimgrey; background: ${kt.background}; border-radius: var(--rounded); border-color: black; border-style: solid; border-width: thin; }
|
|
|
|
.menu:hover { box-shadow: 0 0 8px ${kt.hover}; }
|
|
.menu-container { display: block; max-height: 100vh; }
|
|
.menu-container-fadeout { max-height: 0; overflow: hidden; transition: max-height, 0.5s ease; }
|
|
.menu-container-fadein { max-height: 100vh; overflow: hidden; transition: max-height, 0.5s ease; }
|
|
.menu-item { display: flex; white-space: nowrap; padding: 0.2rem; cursor: default; width: 100%; }
|
|
.menu-title { cursor: pointer; }
|
|
.menu-hr { margin: 0.2rem; border: 1px solid rgba(0, 0, 0, 0.5) }
|
|
.menu-label { padding: 0; font-weight: 800; }
|
|
|
|
.menu-list { margin-right: 0.8rem; }
|
|
select:focus { outline: none; }
|
|
.menu-list-item { background: ${kt.itemBackground}; color: ${kt.itemColor}; border: none; padding: 0.2rem; font-family: inherit;
|
|
font-variant: inherit; border-radius: var(--rounded); font-weight: 800; }
|
|
|
|
.menu-chart-title { padding: 0; font-size: 0.8rem; font-weight: 800; align-items: center}
|
|
.menu-chart-canvas { background: transparent; margin: 0.2rem 0 0.2rem 0.6rem; }
|
|
|
|
.menu-button { border: 0; background: ${kt.buttonBackground}; width: -webkit-fill-available; padding: 8px; margin: 8px; cursor: pointer; box-shadow: 4px 4px 4px 0 dimgrey;
|
|
border-radius: var(--rounded); justify-content: center; font-family: inherit; font-variant: inherit; font-size: 1rem; font-weight: 800; }
|
|
.menu-button:hover { background: ${kt.buttonHover}; box-shadow: 4px 4px 4px 0 black; }
|
|
.menu-button:focus { outline: none; }
|
|
|
|
.menu-checkbox { width: 2.8rem; height: 1rem; background: ${kt.itemBackground}; margin: 0.5rem 0.5rem 0 0; position: relative; border-radius: var(--rounded); }
|
|
.menu-checkbox:after { content: 'OFF'; color: ${kt.checkboxOff}; position: absolute; right: 0.2rem; top: -0.4rem; font-weight: 800; font-size: 0.5rem; }
|
|
.menu-checkbox:before { content: 'ON'; color: ${kt.checkboxOn}; position: absolute; left: 0.3rem; top: -0.4rem; font-weight: 800; font-size: 0.5rem; }
|
|
.menu-checkbox-label { width: 1.3rem; height: 0.8rem; cursor: pointer; position: absolute; top: 0.1rem; left: 0.1rem; z-index: 1; background: ${kt.checkboxOff};
|
|
border-radius: var(--rounded); transition: left 0.6s ease; }
|
|
|
|
input[type=checkbox] { visibility: hidden; }
|
|
input[type=checkbox]:checked + label { left: 1.4rem; background: ${kt.checkboxOn}; }
|
|
|
|
.menu-range { margin: 0.2rem 0.5rem 0 0; width: 3.5rem; background: transparent; color: ${kt.rangeBackground}; }
|
|
.menu-range:before { color: ${kt.rangeLabel}; margin: 0 0.4rem 0 0; font-weight: 800; font-size: 0.6rem; position: relative; top: 0.3rem; content: attr(value); }
|
|
|
|
input[type=range] { -webkit-appearance: none; }
|
|
input[type=range]::-webkit-slider-runnable-track { width: 100%; height: 1rem; cursor: pointer; background: ${kt.itemBackground}; border-radius: var(--rounded); border: 1px; }
|
|
input[type=range]::-moz-range-track { width: 100%; height: 1rem; cursor: pointer; background: ${kt.itemBackground}; border-radius: var(--rounded); border: 1px; }
|
|
input[type=range]::-webkit-slider-thumb { border: 1px solid #000000; margin-top: 0.05rem; height: 0.9rem; width: 1rem; border-radius: var(--rounded); background: ${kt.rangeBackground}; cursor: pointer; -webkit-appearance: none; }
|
|
input[type=range]::-moz-range-thumb { border: 1px solid #000000; margin-top: 0.05rem; height: 0.9rem; width: 1rem; border-radius: var(--rounded); background: ${kt.rangeBackground}; cursor: pointer; -webkit-appearance: none; }
|
|
|
|
.svg-background { fill:darkslategrey; cursor:pointer; opacity: 0.6; }
|
|
.svg-foreground { fill:white; cursor:pointer; opacity: 0.8; }
|
|
`,t=document.createElement("style");t.innerHTML=e,document.getElementsByTagName("head")[0].appendChild(t),L4=!0}var W4=class{constructor(t,n,r,a){a&&(kt={...kt,...a}),Sse(),this.createMenu(t,n,r),this.id=0,this.instance=th,th++,this._maxFPS=0,this.hidden=0}createMenu(t,n="",r={top:null,left:null,bottom:null,right:null}){this.menu=document.createElement("div"),this.menu.id=`menu-${th}`,this.menu.className="menu",r&&(r.top&&(this.menu.style.top=r.top),r.bottom&&(this.menu.style.bottom=r.bottom),r.left&&(this.menu.style.left=r.left),r.right&&(this.menu.style.right=r.right)),this.container=document.createElement("div"),this.container.id=`menu-container-${th}`,this.container.className="menu-container menu-container-fadein";let a=document.createElement("div");a.className="menu-title",a.id=`menu-title-${th}`;let s=`<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512" style="width: 2rem; height: 2rem; vertical-align: top;">
|
|
<path d="M400 32H48A48 48 0 0 0 0 80v352a48 48 0 0 0 48 48h352a48 48 0 0 0 48-48V80a48 48 0 0 0-48-48zm-51.37 182.31L232.06 348.16a10.38 10.38 0 0 1-16.12 0L99.37 214.31C92.17 206 97.28 192 107.43 192h233.14c10.15 0 15.26 14 8.06 22.31z" class="svg-background"/>
|
|
<path d="M348.63 214.31L232.06 348.16a10.38 10.38 0 0 1-16.12 0L99.37 214.31C92.17 206 97.28 192 107.43 192h233.14c10.15 0 15.26 14 8.06 22.31z" class="svg-foreground"/>
|
|
</svg>`;n&&(a.innerHTML=`${n}${s}`),this.menu.appendChild(a),a.addEventListener("click",()=>{this.container.classList.toggle("menu-container-fadeout"),this.container.classList.toggle("menu-container-fadein"),this.menu.style.borderStyle=this.container.classList.contains("menu-container-fadeout")?"none":"solid"}),this.menu.appendChild(this.container),typeof t=="object"?t.appendChild(this.menu):document.getElementById(t).appendChild(this.menu)}get newID(){return this.id++,`menu-${this.instance}-${this.id}`}get ID(){return`menu-${this.instance}-${this.id}`}get width(){return this.menu.offsetWidth}get height(){return this.menu.offsetHeight}hide(){this.container.classList.contains("menu-container-fadein")&&(this.container.classList.toggle("menu-container-fadeout"),this.container.classList.toggle("menu-container-fadein"))}visible(){return this.container.classList.contains("menu-container-fadein")}toggle(t){if(this.container.classList.toggle("menu-container-fadeout"),this.container.classList.toggle("menu-container-fadein"),this.container.classList.contains("menu-container-fadein")&&t){let n=t.x||(t.touches&&t.touches[0]?t.touches[0].pageX:null);n&&(this.menu.style.left=`${n-this.menu.offsetWidth/2}px`),this.menu.offsetLeft<0&&(this.menu.style.left=0),this.menu.offsetLeft+this.menu.offsetWidth>window.innerWidth&&(this.menu.style.left=null,this.menu.style.right=0),this.menu.style.borderStyle="solid"}else this.menu.style.borderStyle="none"}addTitle(t){let n=document.createElement("div");return n.className="menu-title",n.id=this.newID,n.innerHTML=t,this.menu.appendChild(n),n.addEventListener("click",()=>{this.hidden=!this.hidden;let r=document.getElementsByClassName("menu");for(let a of r)a.style.display=this.hidden?"none":"block"}),n}addLabel(t){let n=document.createElement("div");return n.className="menu-item menu-label",n.id=this.newID,n.innerHTML=t,this.container.appendChild(n),n}addBool(t,n,r,a){let s=document.createElement("div");return s.className="menu-item",s.innerHTML=`<div class="menu-checkbox"><input class="menu-checkbox" type="checkbox" id="${this.newID}" ${n[r]?"checked":""}/><label class="menu-checkbox-label" for="${this.ID}"></label></div>${t}`,this.container.appendChild(s),s.addEventListener("change",i=>{n[r]=i.target.checked,a&&a(i.target.checked)}),s}async addList(t,n,r,a){let s=document.createElement("div");s.className="menu-item";let i="";for(let o of n)i+=`<option value="${o}" ${o===r?"selected":""}>${o}</option>`;return s.innerHTML=`<div class="menu-list"><select name="${this.ID}" class="menu-list-item">${i}</select><label for="${this.ID}"></label></div>${t}`,s.style.fontFamily=document.body.style.fontFamily,s.style.fontSize=document.body.style.fontSize,s.style.fontVariant=document.body.style.fontVariant,this.container.appendChild(s),s.addEventListener("change",o=>{a&&a(n[o.target.selectedIndex])}),s}addRange(t,n,r,a,s,i,o){let l=document.createElement("div");return l.className="menu-item",l.innerHTML=`<input class="menu-range" type="range" id="${this.newID}" min="${a}" max="${s}" step="${i}" value="${n[r]}">${t}`,this.container.appendChild(l),l.addEventListener("change",u=>{n[r]=parseInt(u.target.value)===parseFloat(u.target.value)?parseInt(u.target.value):parseFloat(u.target.value),u.target.setAttribute("value",u.target.value),o&&o(u.target.value)}),l.input=l.children[0],l}addHTML(t){let n=document.createElement("div");return n.className="menu-item",n.id=this.newID,t&&(n.innerHTML=t),this.container.appendChild(n),n}addButton(t,n,r){let a=document.createElement("button");return a.className="menu-item menu-button",a.style.fontFamily=document.body.style.fontFamily,a.style.fontSize=document.body.style.fontSize,a.style.fontVariant=document.body.style.fontVariant,a.type="button",a.id=this.newID,a.innerText=t,this.container.appendChild(a),a.addEventListener("click",()=>{a.innerText===t?a.innerText=n:a.innerText=t,r&&r(a.innerText!==t)}),a}addValue(t,n,r=""){let a=document.createElement("div");return a.className="menu-item",a.id=`menu-val-${t}`,a.innerText=`${t}: ${n}${r}`,this.container.appendChild(a),a}updateValue(t,n,r=""){let a=document.getElementById(`menu-val-${t}`);a?a.innerText=`${t}: ${n}${r}`:this.addValue(t,n)}addChart(t,n,r=150,a=40,s){s&&(kt.chartColor=s);let i=document.createElement("div");return i.className="menu-item menu-chart-title",i.id=this.newID,i.innerHTML=`<font color=${kt.chartColor}>${t}</font><canvas id="menu-canvas-${n}" class="menu-chart-canvas" width="${r}px" height="${a}px"></canvas>`,this.container.appendChild(i),i}async updateChart(t,n){if(!n||n.length===0)return;let r=document.getElementById(`menu-canvas-${t}`);if(!r)return;let a=r.getContext("2d");a.fillStyle=kt.background,a.fillRect(0,0,r.width,r.height);let s=r.width/n.length,i=1+Math.max(...n),o=r.height/i;for(let l=0;l<n.length;l++){let u=a.createLinearGradient(0,(i-n[l])*o,0,0);u.addColorStop(.1,kt.chartColor),u.addColorStop(.4,kt.background),a.fillStyle=u,a.fillRect(l*s,0,s-4,r.height),a.fillStyle=kt.background,a.font=`${s/1.5}px "Segoe UI"`,a.fillText(Math.round(n[l]),l*s+1,r.height-1,s-1)}}},nh=W4;var Tse=`
|
|
#gl-bench { position: absolute; right: 1rem; bottom: 1rem; z-index:1000; -webkit-user-select: none; -moz-user-select: none; user-select: none; }
|
|
#gl-bench div { position: relative; display: block; margin: 4px; padding: 0 2px 0 2px; background: darkslategray; border-radius: 0.1rem; cursor: pointer; opacity: 0.9; }
|
|
#gl-bench svg { height: 60px; margin: 0 0px 0px 4px; }
|
|
#gl-bench text { font-size: 16px; font-family: 'Lato', 'Segoe UI'; dominant-baseline: middle; text-anchor: middle; }
|
|
#gl-bench .gl-mem { font-size: 12px; fill: white; }
|
|
#gl-bench .gl-fps { font-size: 13px; fill: white; }
|
|
#gl-bench line { stroke-width: 5; stroke: white; stroke-linecap: round; }
|
|
#gl-bench polyline { fill: none; stroke: white; stroke-linecap: round; stroke-linejoin: round; stroke-width: 3.5; }
|
|
#gl-bench rect { fill: black; }
|
|
#gl-bench .opacity { stroke: black; }
|
|
`,Ese=`
|
|
<div class="gl-box">
|
|
<svg viewBox="0 0 60 60">
|
|
<text x="27" y="56" class="gl-fps">00 FPS</text>
|
|
<text x="30" y="8" class="gl-mem"></text>
|
|
<rect x="0" y="14" rx="4" ry="4" width="60" height="32"></rect>
|
|
<polyline class="gl-chart"></polyline>
|
|
</svg>
|
|
<svg viewBox="0 0 14 60" class="gl-cpu-svg">
|
|
<line x1="7" y1="38" x2="7" y2="11" class="opacity"/>
|
|
<line x1="7" y1="38" x2="7" y2="11" class="gl-cpu" stroke-dasharray="0 27"/>
|
|
<path d="M5.35 43c-.464 0-.812.377-.812.812v1.16c-.783.1972-1.421.812-1.595 1.624h-1.16c-.435 0-.812.348-.812.812s.348.812.812.812h1.102v1.653H1.812c-.464 0-.812.377-.812.812 0 .464.377.812.812.812h1.131c.1943.783.812 1.392 1.595 1.595v1.131c0 .464.377.812.812.812.464 0 .812-.377.812-.812V53.15h1.653v1.073c0 .464.377.812.812.812.464 0 .812-.377.812-.812v-1.131c.783-.1943 1.392-.812 1.595-1.595h1.131c.464 0 .812-.377.812-.812 0-.464-.377-.812-.812-.812h-1.073V48.22h1.102c.435 0 .812-.348.812-.812s-.348-.812-.812-.812h-1.16c-.1885-.783-.812-1.421-1.595-1.624v-1.131c0-.464-.377-.812-.812-.812-.464 0-.812.377-.812.812v1.073H6.162v-1.073c0-.464-.377-.812-.812-.812zm.58 3.48h2.088c.754 0 1.363.609 1.363 1.363v2.088c0 .754-.609 1.363-1.363 1.363H5.93c-.754 0-1.363-.609-1.363-1.363v-2.088c0-.754.609-1.363 1.363-1.363z" style="fill: grey"></path>
|
|
</svg>
|
|
<svg viewBox="0 0 14 60" class="gl-gpu-svg">
|
|
<line x1="7" y1="38" x2="7" y2="11" class="opacity"/>
|
|
<line x1="7" y1="38" x2="7" y2="11" class="gl-gpu" stroke-dasharray="0 27"/>
|
|
<path d="M1.94775 43.3772a.736.736 0 10-.00416 1.472c.58535.00231.56465.1288.6348.3197.07015.18975.04933.43585.04933.43585l-.00653.05405v8.671a.736.736 0 101.472 0v-1.4145c.253.09522.52785.1495.81765.1495h5.267c1.2535 0 2.254-.9752 2.254-2.185v-3.105c0-1.2075-1.00625-2.185-2.254-2.185h-5.267c-.28865 0-.5635.05405-.8165.1495.01806-.16445.04209-.598-.1357-1.0787-.22425-.6072-.9499-1.2765-2.0125-1.2765zm2.9095 3.6455c.42435 0 .7659.36225.7659.8119v2.9785c0 .44965-.34155.8119-.7659.8119s-.7659-.36225-.7659-.8119v-2.9785c0-.44965.34155-.8119.7659-.8119zm4.117 0a2.3 2.3 0 012.3 2.3 2.3 2.3 0 01-2.3 2.3 2.3 2.3 0 01-2.3-2.3 2.3 2.3 0 012.3-2.3z" style="fill: grey"></path>
|
|
</svg>
|
|
</div>
|
|
`,B4=class{constructor(t,n={}){this.css=Tse,this.svg=Ese,this.paramLogger=()=>{},this.chartLogger=()=>{},this.chartLen=20,this.chartHz=20,this.names=[],this.cpuAccums=[],this.gpuAccums=[],this.activeAccums=[],this.chart=new Array(this.chartLen),this.now=()=>performance&&performance.now?performance.now():Date.now(),this.updateUI=()=>{[].forEach.call(this.nodes["gl-gpu-svg"],o=>o.style.display=this.trackGPU?"inline":"none")},Object.assign(this,n),this.detected=0,this.finished=[],this.isFramebuffer=0,this.frameId=0;let r,a=0,s,i=o=>{++a<20?r=requestAnimationFrame(i):(this.detected=Math.ceil(1e3*a/(o-s)/70),cancelAnimationFrame(r)),s||(s=o)};if(requestAnimationFrame(i),t){let o=async(c,h)=>Promise.resolve(setTimeout(()=>{t.getError();let d=this.now()-c;h.forEach((p,f)=>{p&&(this.gpuAccums[f]+=d)})},0)),l=(c,h,d)=>{let p=h.now();c.apply(d,arguments),h.trackGPU&&h.finished.push(o(p,h.activeAccums.slice(0)))},u="drawElements";t[u]?t[u]=l(t[u],this,t):console.log("bench: cannot attach to webgl function")}if(!this.withoutUI){this.dom||(this.dom=document.body);let o=document.createElement("div");o.id="gl-bench",this.dom.appendChild(o),this.dom.insertAdjacentHTML("afterbegin",'<style id="gl-bench-style">'+this.css+"</style>"),this.dom=o,this.dom.addEventListener("click",()=>{this.trackGPU=!this.trackGPU,this.updateUI()}),this.paramLogger=((l,u,c)=>{let h=["gl-cpu","gl-gpu","gl-mem","gl-fps","gl-gpu-svg","gl-chart"],d={...h};return h.forEach(p=>d[p]=u.getElementsByClassName(p)),this.nodes=d,(p,f,m,A,y,g,b)=>{d["gl-cpu"][p].style.strokeDasharray=(f*.27).toFixed(0)+" 100",d["gl-gpu"][p].style.strokeDasharray=(m*.27).toFixed(0)+" 100",d["gl-mem"][p].innerHTML=c[p]?c[p]:A?"mem: "+A.toFixed(0)+"mb":"",d["gl-fps"][p].innerHTML="FPS: "+y.toFixed(1),l(c[p],f,m,A,y,g,b)}})(this.paramLogger,this.dom,this.names),this.chartLogger=((l,u)=>{let c={"gl-chart":u.getElementsByClassName("gl-chart")};return(h,d,p)=>{let f="",m=d.length;for(let A=0;A<m;A++){let y=(p+A+1)%m;d[y]!==void 0&&(f=f+" "+(60*A/(m-1)).toFixed(1)+","+(45-d[y]*.5/this.detected).toFixed(1))}c["gl-chart"][h].setAttribute("points",f),l(this.names[h],d,p)}})(this.chartLogger,this.dom)}}addUI(t){this.names.indexOf(t)===-1&&(this.names.push(t),this.dom&&(this.dom.insertAdjacentHTML("beforeend",this.svg),this.updateUI()),this.cpuAccums.push(0),this.gpuAccums.push(0),this.activeAccums.push(!1))}nextFrame(t){this.frameId++;let n=t||this.now();if(this.frameId<=1)this.paramFrame=this.frameId,this.paramTime=n;else{let r=n-this.paramTime;if(r>=1e3){let a=this.frameId-this.paramFrame,s=a/r*1e3;for(let i=0;i<this.names.length;i++){let o=this.cpuAccums[i]/r*100,l=this.gpuAccums[i]/r*100,u=performance&&performance.memory?performance.memory.usedJSHeapSize/(1<<20):0;this.paramLogger(i,o,l,u,s,r,a),this.cpuAccums[i]=0,Promise.all(this.finished).then(()=>{this.gpuAccums[i]=0,this.finished=[]})}this.paramFrame=this.frameId,this.paramTime=n}}if(!this.detected||!this.chartFrame)this.chartFrame=this.frameId,this.chartTime=n,this.circularId=0;else{let r=n-this.chartTime,a=this.chartHz*r/1e3;for(;--a>0&&this.detected;){let i=(this.frameId-this.chartFrame)/r*1e3;this.chart[this.circularId%this.chartLen]=i;for(let o=0;o<this.names.length;o++)this.chartLogger(o,this.chart,this.circularId);this.circularId++,this.chartFrame=this.frameId,this.chartTime=n}}}begin(t){this.updateAccums(t)}end(t){this.updateAccums(t)}updateAccums(t){let n=this.names.indexOf(t);n===-1&&(n=this.names.length,this.addUI(t));let r=this.now(),a=r-this.t0;for(let s=0;s<n+1;s++)this.activeAccums[s]&&(this.cpuAccums[s]+=a);this.activeAccums[n]=!this.activeAccums[n],this.t0=r}},V4=B4;var ls={backend:"webgl"},ne=new $2(ls),ce={baseBackground:"rgba(50, 50, 50, 1)",crop:!0,columns:2,facing:!0,useWorker:!1,worker:"worker.js",samples:["../assets/sample6.jpg","../assets/sample1.jpg","../assets/sample4.jpg","../assets/sample5.jpg","../assets/sample3.jpg","../assets/sample2.jpg"],compare:"../assets/sample-me.jpg",console:!0,maxFPSframes:10,modelsPreload:!0,busy:!1,menuWidth:0,menuHeight:0,camera:{},detectFPS:[],drawFPS:[],buffered:!1,drawWarmup:!1,drawThread:null,detectThread:null,framesDraw:0,framesDetect:0,bench:!0,lastFrame:0},ye={},q0,Vi,X0={};function Cse(...e){if(!Array.isArray(e))return e;let t="";for(let n of e)typeof n=="object"?t+=JSON.stringify(n).replace(/{|}|"|\[|\]/g,"").replace(/,/g,", "):t+=n;return t}function qn(...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")}`;ce.console&&console.log(n,...e)}function rr(e){let t=document.getElementById("status");t&&(t.innerText=e)}var Ui;async function Rse(e){var n,r,a,s,i;if(document.getElementById("compare-container").style.display=ne.config.face.embedding.enabled?"block":"none",!ne.config.face.embedding.enabled||!(((n=e==null?void 0:e.face)==null?void 0:n.length)>0)||((a=(r=e==null?void 0:e.face[0])==null?void 0:r.embedding)==null?void 0:a.length)>=64)return;if(!Ui)if(Ui=e,e.face[0].tensor){let o=ne.enhance(e.face[0]);if(o){let l=document.getElementById("orig"),u=o.squeeze();ne.tf.browser.toPixels(u,l),o.dispose(),u.dispose()}}else document.getElementById("compare-canvas").getContext("2d").drawImage(Ui.canvas,0,0,200,200);let t=ne.simmilarity((s=Ui==null?void 0:Ui.face[0])==null?void 0:s.embedding,(i=e==null?void 0:e.face[0])==null?void 0:i.embedding);document.getElementById("simmilarity").innerText=`simmilarity: ${Math.trunc(1e3*t)/10}%`}var U4=performance.now();async function K0(e){let t=X0,n=document.getElementById("canvas");if(ce.drawFPS.push(1e3/(performance.now()-U4)),ce.drawFPS.length>ce.maxFPSframes&&ce.drawFPS.shift(),U4=performance.now(),await ye.process.updateChart("FPS",ce.detectFPS),ce.buffered||!t.canvas){let h=await ne.image(e);t.canvas=h.canvas,ne.tf.dispose(h.tensor)}let r=n.getContext("2d");r.fillStyle=ce.baseBackground,r.fillRect(0,0,n.width,n.height),t.canvas?(t.canvas.width!==n.width&&(n.width=t.canvas.width),t.canvas.height!==n.height&&(n.height=t.canvas.height),r.drawImage(t.canvas,0,0,t.canvas.width,t.canvas.height,0,0,t.canvas.width,t.canvas.height)):r.drawImage(e,0,0,e.width,e.height,0,0,n.width,n.height),ne.draw.face(n,t.face),ne.draw.body(n,t.body),ne.draw.hand(n,t.hand),ne.draw.gesture(n,t.gesture),await Rse(t);let a=ne.tf.engine(),s=a.backendInstance?`gpu: ${(a.backendInstance.numBytesInGPU?a.backendInstance.numBytesInGPU:0).toLocaleString()} bytes`:"",i=`system: ${a.state.numBytes.toLocaleString()} bytes ${s} | tensors: ${a.state.numTensors.toLocaleString()}`,o=t.canvas?`processing: ${t.canvas.width} x ${t.canvas.height}`:"",l=Math.trunc(10*ce.detectFPS.reduce((h,d)=>h+d,0)/ce.detectFPS.length)/10,u=Math.trunc(10*ce.drawFPS.reduce((h,d)=>h+d,0)/ce.drawFPS.length)/10,c=ce.detectFPS.length>5&&l<5?'<font color="lightcoral">warning: your performance is low: try switching to higher performance backend, lowering resolution or disabling some models</font>':"";document.getElementById("log").innerHTML=`
|
|
video: ${ce.camera.name} | facing: ${ce.camera.facing} | screen: ${window.innerWidth} x ${window.innerHeight} camera: ${ce.camera.width} x ${ce.camera.height} ${o}<br>
|
|
backend: ${ne.tf.getBackend()} | ${i}<br>
|
|
performance: ${Cse(t.performance)}ms FPS process:${l} refresh:${u}<br>
|
|
${c}<br>
|
|
`,ce.framesDraw++,ce.lastFrame=performance.now(),ce.buffered?ce.drawThread=requestAnimationFrame(()=>K0(e,n)):!ce.buffered&&ce.drawThread&&(qn("stopping buffered refresh"),cancelAnimationFrame(ce.drawThread),ce.drawThread=null)}async function Z0(){var u;if(ce.busy)return null;ce.busy=!0;let e=document.getElementById("video"),t=document.getElementById("canvas"),n=document.getElementById("log"),r=e.srcObject?e.srcObject.getVideoTracks()[0].readyState==="live"&&e.readyState>2&&!e.paused:!1,a="";if(rr("setting up camera"),!navigator.mediaDevices)return a="camera access not supported",n.innerText+=`
|
|
${a}`,qn(a),rr(a),ce.busy=!1,a;let s,i={audio:!1,video:{facingMode:ce.facing?"user":"environment",resizeMode:ce.crop?"crop-and-scale":"none"}};window.innerWidth>window.innerHeight?i.video.width={ideal:window.innerWidth}:i.video.height={ideal:window.innerHeight-document.getElementById("menubar").offsetHeight};try{s=await navigator.mediaDevices.getUserMedia(i)}catch(c){return c.name==="PermissionDeniedError"||c.name==="NotAllowedError"?a="camera permission denied":c.name==="SourceUnavailableError"?a="camera not available":a=`camera error: ${c.message||c}`,n.innerText+=`
|
|
${a}`,rr(a),qn("camera error:",c),ce.busy=!1,a}if(s)e.srcObject=s;else return ce.busy=!1,"camera stream empty";let o=s.getVideoTracks()[0],l=o.getSettings();return ce.camera={name:(u=o.label)==null?void 0:u.toLowerCase(),width:l.width,height:l.height,facing:l.facingMode==="user"?"front":"back"},new Promise(c=>{e.onloadeddata=async()=>{e.width=e.videoWidth,e.height=e.videoHeight,t.width=e.width,t.height=e.height,t.style.width=t.width>t.height?"100vw":"",t.style.height=t.width>t.height?"":"100vh",ce.menuWidth.input.setAttribute("value",e.width),ce.menuHeight.input.setAttribute("value",e.height),r&&e.play(),r&&!ce.detectThread&&rh(e,t),ce.busy=!1,rr(""),c()}})}function H4(){if(!Vi){let e=null;Vi=new V4(e,{trackGPU:!1,chartHz:20,chartLen:20}),Vi.begin()}}function Fse(e,t,n,r){q0||(qn("creating worker thread"),q0=new Worker(ce.worker,{type:"module"}),q0.addEventListener("message",a=>{a.data.result.performance&&a.data.result.performance.total&&ce.detectFPS.push(1e3/a.data.result.performance.total),ce.detectFPS.length>ce.maxFPSframes&&ce.detectFPS.shift(),ce.bench&&(Vi||H4(),Vi.nextFrame(r)),document.getElementById("gl-bench")&&(document.getElementById("gl-bench").style.display=ce.bench?"block":"none"),X0=a.data.result,ce.framesDetect++,ce.drawThread||K0(e),ce.detectThread=requestAnimationFrame(s=>rh(e,n,s))})),q0.postMessage({image:t.data.buffer,width:n.width,height:n.height,userConfig:ls},[t.data.buffer])}function rh(e,t,n){var a;if(!(e.srcObject&&e.srcObject.getVideoTracks()[0].readyState==="live"&&e.readyState>2&&!e.paused)&&e.srcObject){ce.drawThread&&cancelAnimationFrame(ce.drawThread),ce.detectThread&&cancelAnimationFrame(ce.detectThread),ce.drawThread=null,ce.detectThread=null,e.paused?qn("camera paused"):e.srcObject.getVideoTracks()[0].readyState==="live"&&e.readyState<=2?setTimeout(()=>rh(e,t),500):qn(`camera not ready: track state: ${(a=e.srcObject)==null?void 0:a.getVideoTracks()[0].readyState} stream state: ${e.readyState}`),clearTimeout(ce.drawThread),ce.drawThread=null,qn("frame statistics: process:",ce.framesDetect,"refresh:",ce.framesDraw),qn("memory",ne.tf.engine().memory());return}if(rr(""),ce.useWorker){let s=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(t.width,t.height):document.createElement("canvas");s.width=t.width,s.height=t.height;let i=s.getContext("2d");i.drawImage(e,0,0,e.width,e.height,0,0,t.width,t.height);let o=i.getImageData(0,0,t.width,t.height);Fse(e,o,t,ls,n)}else ne.detect(e,ls).then(s=>{s.performance&&s.performance.total&&ce.detectFPS.push(1e3/s.performance.total),ce.detectFPS.length>ce.maxFPSframes&&ce.detectFPS.shift(),ce.bench&&(Vi||H4(),Vi.nextFrame(n)),document.getElementById("gl-bench")&&(document.getElementById("gl-bench").style.display=ce.bench?"block":"none"),s.error?(qn(s.error),document.getElementById("log").innerText+=`
|
|
Human error: ${s.error}`):(X0=s,ce.drawThread||K0(e),ce.framesDetect++,ce.detectThread=requestAnimationFrame(i=>rh(e,t,i)))})}async function Mse(e){return new Promise(t=>{let n=new Image;n.onload=async()=>{qn("Processing image:",encodeURI(n.src));let r=document.getElementById("canvas");n.width=n.naturalWidth,n.height=n.naturalHeight,r.width=ne.config.filter.width&&ne.config.filter.width>0?ne.config.filter.width:n.naturalWidth,r.height=ne.config.filter.height&&ne.config.filter.height>0?ne.config.filter.height:n.naturalHeight;let a=await ne.detect(n,ls);X0=a,await K0(n);let s=document.createElement("canvas");s.className="thumbnail",s.width=window.innerWidth/(ce.columns+.1),s.height=s.width*r.height/r.width,a.face&&a.face.length>0?s.title=a.face.map((o,l)=>`#${l} face: ${Math.trunc(100*o.faceConfidence)}% box: ${Math.trunc(100*o.boxConfidence)}% age: ${Math.trunc(o.age)} gender: ${Math.trunc(100*o.genderConfidence)}% ${o.gender}`).join(" | "):s.title="no face detected",s.getContext("2d").drawImage(r,0,0,r.width,r.height,0,0,s.width,s.height),document.getElementById("samples-container").appendChild(s),n.src="",t(!0)},n.src=e})}async function j4(){document.getElementById("samples-container").style.display="none",document.getElementById("canvas").style.display="block";let e=document.getElementById("video"),t=document.getElementById("canvas");if(e.srcObject!==null&&!e.paused)document.getElementById("play").style.display="block",document.getElementById("btnStart").className="button button-start",document.getElementById("btnStart").innerHTML="start<br>video",rr("paused"),e.pause();else{let n=await Z0();if(n)rr(n);else{document.getElementById("play").style.display="none";for(let r of Object.values(ye))r.hide();rr(""),document.getElementById("btnStart").className="button button-stop",document.getElementById("btnStart").innerHTML="pause<br>video",await e.play(),ce.detectThread||rh(e,t)}}}async function $se(){ls.videoOptimized=!1,document.getElementById("play").style.display="none",document.getElementById("canvas").style.display="none",document.getElementById("samples-container").style.display="block",qn("Running detection of sample images"),rr("processing images"),document.getElementById("samples-container").innerHTML="";for(let e of Object.values(ye))e.hide();for(let e of ce.samples)await Mse(e);rr("")}function Dse(){let e=[];window.innerWidth>800?e=[`${document.getElementById("btnDisplay").offsetLeft-50}px`,`${document.getElementById("btnImage").offsetLeft-50}px`,`${document.getElementById("btnProcess").offsetLeft-50}px`,`${document.getElementById("btnModel").offsetLeft-50}px`]:e=["0rem","11rem","21.1rem","33rem"],ye.display=new nh(document.body,"",{top:`${document.getElementById("menubar").offsetHeight}px`,left:e[0]}),ye.display.addBool("perf monitor",ce,"bench",t=>ce.bench=t),ye.display.addBool("buffered output",ce,"buffered",t=>ce.buffered=t),ye.display.addBool("crop & scale",ce,"crop",t=>{ce.crop=t,Z0()}),ye.display.addBool("camera facing",ce,"facing",t=>{ce.facing=t,Z0()}),ye.display.addHTML('<hr style="border-style: inset; border-color: dimgray">'),ye.display.addBool("use 3D depth",ne.draw.drawOptions,"useDepth"),ye.display.addBool("draw with curves",ne.draw.drawOptions,"useCurves"),ye.display.addBool("print labels",ne.draw.drawOptions,"drawLabels"),ye.display.addBool("draw points",ne.draw.drawOptions,"drawPoints"),ye.display.addBool("draw boxes",ne.draw.drawOptions,"drawBoxes"),ye.display.addBool("draw polygons",ne.draw.drawOptions,"drawPolygons"),ye.display.addBool("fill polygons",ne.draw.drawOptions,"fillPolygons"),ye.image=new nh(document.body,"",{top:`${document.getElementById("menubar").offsetHeight}px`,left:e[1]}),ye.image.addBool("enabled",ne.config.filter,"enabled",t=>ne.config.filter.enabled=t),ce.menuWidth=ye.image.addRange("image width",ne.config.filter,"width",0,3840,10,t=>ne.config.filter.width=parseInt(t)),ce.menuHeight=ye.image.addRange("image height",ne.config.filter,"height",0,2160,10,t=>ne.config.filter.height=parseInt(t)),ye.image.addHTML('<hr style="border-style: inset; border-color: dimgray">'),ye.image.addRange("brightness",ne.config.filter,"brightness",-1,1,.05,t=>ne.config.filter.brightness=parseFloat(t)),ye.image.addRange("contrast",ne.config.filter,"contrast",-1,1,.05,t=>ne.config.filter.contrast=parseFloat(t)),ye.image.addRange("sharpness",ne.config.filter,"sharpness",0,1,.05,t=>ne.config.filter.sharpness=parseFloat(t)),ye.image.addRange("blur",ne.config.filter,"blur",0,20,1,t=>ne.config.filter.blur=parseInt(t)),ye.image.addRange("saturation",ne.config.filter,"saturation",-1,1,.05,t=>ne.config.filter.saturation=parseFloat(t)),ye.image.addRange("hue",ne.config.filter,"hue",0,360,5,t=>ne.config.filter.hue=parseInt(t)),ye.image.addRange("pixelate",ne.config.filter,"pixelate",0,32,1,t=>ne.config.filter.pixelate=parseInt(t)),ye.image.addHTML('<hr style="border-style: inset; border-color: dimgray">'),ye.image.addBool("negative",ne.config.filter,"negative",t=>ne.config.filter.negative=t),ye.image.addBool("sepia",ne.config.filter,"sepia",t=>ne.config.filter.sepia=t),ye.image.addBool("vintage",ne.config.filter,"vintage",t=>ne.config.filter.vintage=t),ye.image.addBool("kodachrome",ne.config.filter,"kodachrome",t=>ne.config.filter.kodachrome=t),ye.image.addBool("technicolor",ne.config.filter,"technicolor",t=>ne.config.filter.technicolor=t),ye.image.addBool("polaroid",ne.config.filter,"polaroid",t=>ne.config.filter.polaroid=t),ye.process=new nh(document.body,"",{top:`${document.getElementById("menubar").offsetHeight}px`,left:e[2]}),ye.process.addList("backend",["cpu","webgl","wasm","humangl"],ne.config.backend,t=>ne.config.backend=t),ye.process.addBool("async operations",ne.config,"async",t=>ne.config.async=t),ye.process.addBool("use web worker",ce,"useWorker"),ye.process.addHTML('<hr style="border-style: inset; border-color: dimgray">'),ye.process.addLabel("model parameters"),ye.process.addRange("max objects",ne.config.face.detector,"maxFaces",1,50,1,t=>{ne.config.face.detector.maxFaces=parseInt(t),ne.config.body.maxDetections=parseInt(t),ne.config.hand.maxHands=parseInt(t)}),ye.process.addRange("skip frames",ne.config.face.detector,"skipFrames",0,50,1,t=>{ne.config.face.detector.skipFrames=parseInt(t),ne.config.face.emotion.skipFrames=parseInt(t),ne.config.face.age.skipFrames=parseInt(t),ne.config.hand.skipFrames=parseInt(t)}),ye.process.addRange("min confidence",ne.config.face.detector,"minConfidence",0,1,.05,t=>{ne.config.face.detector.minConfidence=parseFloat(t),ne.config.face.gender.minConfidence=parseFloat(t),ne.config.face.emotion.minConfidence=parseFloat(t),ne.config.hand.minConfidence=parseFloat(t)}),ye.process.addRange("score threshold",ne.config.face.detector,"scoreThreshold",.1,1,.05,t=>{ne.config.face.detector.scoreThreshold=parseFloat(t),ne.config.hand.scoreThreshold=parseFloat(t),ne.config.body.scoreThreshold=parseFloat(t)}),ye.process.addRange("overlap",ne.config.face.detector,"iouThreshold",.1,1,.05,t=>{ne.config.face.detector.iouThreshold=parseFloat(t),ne.config.hand.iouThreshold=parseFloat(t)}),ye.process.addBool("detection rotation",ne.config.face.detector,"rotation",t=>{ne.config.face.detector.rotation=t,ne.config.hand.rotation=t}),ye.process.addHTML('<hr style="border-style: inset; border-color: dimgray">'),ye.process.addButton("process sample images","process images",()=>$se()),ye.process.addHTML('<hr style="border-style: inset; border-color: dimgray">'),ye.process.addChart("FPS","FPS"),ye.models=new nh(document.body,"",{top:`${document.getElementById("menubar").offsetHeight}px`,left:e[3]}),ye.models.addBool("face detect",ne.config.face,"enabled",t=>ne.config.face.enabled=t),ye.models.addBool("face mesh",ne.config.face.mesh,"enabled",t=>ne.config.face.mesh.enabled=t),ye.models.addBool("face iris",ne.config.face.iris,"enabled",t=>ne.config.face.iris.enabled=t),ye.models.addBool("face age",ne.config.face.age,"enabled",t=>ne.config.face.age.enabled=t),ye.models.addBool("face gender",ne.config.face.gender,"enabled",t=>ne.config.face.gender.enabled=t),ye.models.addBool("face emotion",ne.config.face.emotion,"enabled",t=>ne.config.face.emotion.enabled=t),ye.models.addHTML('<hr style="border-style: inset; border-color: dimgray">'),ye.models.addBool("body pose",ne.config.body,"enabled",t=>ne.config.body.enabled=t),ye.models.addBool("hand pose",ne.config.hand,"enabled",t=>ne.config.hand.enabled=t),ye.models.addHTML('<hr style="border-style: inset; border-color: dimgray">'),ye.models.addBool("gestures",ne.config.gesture,"enabled",t=>ne.config.gesture.enabled=t),ye.models.addHTML('<hr style="border-style: inset; border-color: dimgray">'),ye.models.addBool("face compare",ne.config.face.embedding,"enabled",t=>{ne.config.face.embedding.enabled=t,Ui=null}),document.getElementById("btnDisplay").addEventListener("click",t=>ye.display.toggle(t)),document.getElementById("btnImage").addEventListener("click",t=>ye.image.toggle(t)),document.getElementById("btnProcess").addEventListener("click",t=>ye.process.toggle(t)),document.getElementById("btnModel").addEventListener("click",t=>ye.models.toggle(t)),document.getElementById("btnStart").addEventListener("click",()=>j4()),document.getElementById("play").addEventListener("click",()=>j4())}async function Ose(e){let t=document.getElementById("canvas");t.width=e.canvas.width,t.height=e.canvas.height,t.getContext("2d").drawImage(e.canvas,0,0,e.canvas.width,e.canvas.height,0,0,t.width,t.height),await ne.draw.all(t,e)}async function zse(){if(qn("Demo starting ..."),Dse(),document.getElementById("log").innerText=`Human: version ${ne.version}`,ce.modelsPreload&&!ce.useWorker){rr("loading"),await ne.load(ls);let e=Object.keys(ne.models).filter(t=>ne.models[t]);qn("Demo loaded models:",e)}if(!ce.useWorker){rr("initializing");let e=await ne.warmup(ls);e&&e.canvas&&ce.drawWarmup&&await Ose(e)}rr("human: ready"),document.getElementById("loader").style.display="none",document.getElementById("play").style.display="block",qn("Demo ready...")}window.onload=zse;window.onresize=Z0;
|
|
/**
|
|
* @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 See the LICENSE file. */
|
|
//# sourceMappingURL=demo-browser-index.js.map
|